Learn about the effect of deforestation and then reforestation on river channel morphology.\n Understand the composite mathematical modelling for continuous simulations of hydro-geomorphological processes.\n Know about the process-response models for estimation of cliff erosion and its quantitative predictions.\n Grow your knowledge about various geomorphometric tools that are available in freely available GIS software.",isbn:"978-953-51-3574-6",printIsbn:"978-953-51-3573-9",pdfIsbn:"978-953-51-4625-4",doi:"10.5772/65532",price:119,priceEur:129,priceUsd:155,slug:"hydro-geomorphology-models-and-trends",numberOfPages:122,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"865bfca98cafeeb9fdcf21c9453845f6",bookSignature:"Dericks P. Shukla",publishedDate:"October 18th 2017",coverURL:"https://cdn.intechopen.com/books/images_new/5805.jpg",numberOfDownloads:9976,numberOfWosCitations:12,numberOfCrossrefCitations:13,numberOfCrossrefCitationsByBook:2,numberOfDimensionsCitations:20,numberOfDimensionsCitationsByBook:3,hasAltmetrics:1,numberOfTotalCitations:45,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"September 28th 2016",dateEndSecondStepPublish:"October 19th 2016",dateEndThirdStepPublish:"January 15th 2017",dateEndFourthStepPublish:"April 15th 2017",dateEndFifthStepPublish:"June 14th 2017",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6,7",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"176921",title:"Dr.",name:"Dericks",middleName:null,surname:"Shukla",slug:"dericks-shukla",fullName:"Dericks Shukla",profilePictureURL:"https://mts.intechopen.com/storage/users/176921/images/6252_n.jpg",biography:"Dr. Dericks P. Shukla, assistant professor in the School of Engineering, Indian Institute of Technology Mandi (IIT Mandi), has more than 7 years of experience in the areas of remote sensing and GIS, natural hazard assessment and mapping, climatic-tectono-geomorphology and hydro-geochemistry. He has published more than 17 research papers in peer-reviewed journals and various conference papers. He has been working in the field of landslide susceptibility/hazard zonation and prediction, groundwater pollution mainly arsenic contamination and fluvial and glacial geomorphologic studies using remote sensing and GIS techniques. He has five ongoing projects as principal investigator funded by DLR (German Aerospace Agency); Space Application Centre, Indian Space Research Organization (SAC-ISRO); and Department of Science and Technology (DST).",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"Indian Institute of Technology Mandi",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"648",title:"Geomorphometry",slug:"geomorphometry"}],chapters:[{id:"57063",title:"Introductory Chapter: Geomorphology",doi:"10.5772/intechopen.70823",slug:"introductory-chapter-geomorphology",totalDownloads:2650,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:1,abstract:null,signatures:"Dericks Praise Shukla",downloadPdfUrl:"/chapter/pdf-download/57063",previewPdfUrl:"/chapter/pdf-preview/57063",authors:[{id:"176921",title:"Dr.",name:"Dericks",surname:"Shukla",slug:"dericks-shukla",fullName:"Dericks Shukla"}],corrections:null},{id:"55152",title:"Computation of Hydro-geomorphologic Changes in Two Basins of Northeastern Greece",doi:"10.5772/intechopen.68655",slug:"computation-of-hydro-geomorphologic-changes-in-two-basins-of-northeastern-greece",totalDownloads:1575,totalCrossrefCites:0,totalDimensionsCites:0,hasAltmetrics:0,abstract:"This chapter presents a composite mathematical model aiming at continuous simulations of hydro-geomorphological processes at the basin scale. Continuous hydrologic simulations, as well as continuous simulations of soil and streambed erosion processes, are performed in two neighbouring basins in northeastern Greece: Kosynthos river basin (district of Xanthi, Thrace, northeastern Greece) and Nestos river basin (Macedonia-Thrace border, northeastern Greece). Both basins are mountainous and covered by forested and bushy areas in their greatest part. Kosynthos river basin extends to an area of 237 km2, whilst Nestos river basin is quite bigger, covering an area of approximately 840 km2. The characteristic of Nestos river basin is the presence of a dam at its northwestern boundary, which largely affects the discharge, as well as the sediment transport in Nestos River. The application of the model results in continuous hydrographs and sediment graphs at the outlets of the two basins. Fine temporal scales are used, providing this way a continuous assessment of water and sediment discharge. The statistic efficiency criteria utilized for the comparison between computed and measured values of water and sediment discharge at the basin outlet provide satisfactory results. Therefore, it is concluded that the continuous hydro-geomorphologic modelling can be successfully applied to Kosynthos and Nestos river basins.",signatures:"Konstantinos Kaffas and Vlassios Hrissanthou",downloadPdfUrl:"/chapter/pdf-download/55152",previewPdfUrl:"/chapter/pdf-preview/55152",authors:[{id:"37707",title:"Prof.",name:"Vlassios",surname:"Hrissanthou",slug:"vlassios-hrissanthou",fullName:"Vlassios Hrissanthou"},{id:"200942",title:"Dr.",name:"Konstantinos",surname:"Kaffas",slug:"konstantinos-kaffas",fullName:"Konstantinos Kaffas"}],corrections:null},{id:"54918",title:"Analysis of the Impacts of Changes in Streamflow and of Restoration on the Morphological Evolution of the Matambin River Channel in the St. Lawrence Lowlands (Quebec, Canada)",doi:"10.5772/intechopen.68444",slug:"analysis-of-the-impacts-of-changes-in-streamflow-and-of-restoration-on-the-morphological-evolution-o",totalDownloads:1411,totalCrossrefCites:1,totalDimensionsCites:1,hasAltmetrics:0,abstract:"Although many plots of land that were once farmed have been reforested in the St Lawrence Lowlands of Quebec since the 1950s, no study has yet looked at the morphological impacts of this land‐use change. To address this, we analyzed the evolution of the Matambin River (99 km2) channel width and sinuosity using diachronic analysis of air photographs taken between 1935 and 2008. Results of this analysis show a roughly 21% decrease in mean channel bankfull width from 1935 to 1964. This time interval was characterized by a low frequency of strong flood flows in the region and a roughly 32% increase in the forested land area, the reforestation having started in the 1950s. After 1964, a trend of increasing mean channel bankfull width is observed. This increase is associated with the increase in frequency of strong flood flows in the region and a decrease in the amount of suspended sediments produced by soil erosion following the increase in forest cover in the watershed. In contrast, channel sinuosity did not change much over the period from 1935 to 2008.",signatures:"Ali Assani, Lisanne Chauvette and Stéphane Campeau",downloadPdfUrl:"/chapter/pdf-download/54918",previewPdfUrl:"/chapter/pdf-preview/54918",authors:[{id:"50312",title:"Prof.",name:"Ali",surname:"Assani",slug:"ali-assani",fullName:"Ali Assani"}],corrections:null},{id:"54919",title:"The Modelling of Coastal Cliffs and Future Trends",doi:"10.5772/intechopen.68445",slug:"the-modelling-of-coastal-cliffs-and-future-trends",totalDownloads:1655,totalCrossrefCites:3,totalDimensionsCites:5,hasAltmetrics:0,abstract:"About 80% of the world’s oceanic shorelines include diverse types of cliffed and rocky coasts: plunging cliffs, bluffs backing beaches and rocky shore platforms. In combination, approximately 60% of the world’s population lives within 60 km of the coast. Rapidly retreating soft cliffs may be found worldwide and are particularly vulnerable to changes in the forcing factors. The study and analysis of the rate of change in shoreline position through time is important or even imperative for coastal management. The development of cliff erosion predictive models is mainly limited to geomorphological data because of the complex interactions between physical‐chemical processes acting simultaneously in time and space that result in large scale variations. Current historical extrapolation models use historical recession data, but different environments with the same historical values can produce identical annual retreat characteristics despite the potential responses to a changing environment being unequal. For that reason, process‐response models (PRMs) are necessary to provide quantitative predictions of the effects of natural and human‐induced changes that cannot be predicted using other models. Several models are explained and discussed, including a process‐response model, based on real data at Holderness Coast (UK).",signatures:"Ricardo Castedo, Carlos Paredes, Rogelio de la Vega‐Panizo and\nAnastasio P. Santos",downloadPdfUrl:"/chapter/pdf-download/54919",previewPdfUrl:"/chapter/pdf-preview/54919",authors:[{id:"196739",title:"Dr.",name:"Ricardo",surname:"Castedo",slug:"ricardo-castedo",fullName:"Ricardo Castedo"},{id:"204921",title:"Dr.",name:"Carlos",surname:"Paredes",slug:"carlos-paredes",fullName:"Carlos Paredes"},{id:"204922",title:"Dr.",name:"Rogelio",surname:"De La Vega-Panizo",slug:"rogelio-de-la-vega-panizo",fullName:"Rogelio De La Vega-Panizo"},{id:"204923",title:"Dr.",name:"Anastasio P.",surname:"Santos",slug:"anastasio-p.-santos",fullName:"Anastasio P. Santos"}],corrections:null},{id:"55617",title:"Digital Elevation Models in Geomorphology",doi:"10.5772/intechopen.68447",slug:"digital-elevation-models-in-geomorphology",totalDownloads:2688,totalCrossrefCites:8,totalDimensionsCites:13,hasAltmetrics:1,abstract:"This chapter presents place of geomorphometry in contemporary geomorphology. The focus is on discussing digital elevation models (DEMs) that are the primary data source for the analysis. One has described the genesis and definition, main types, data sources and available free global DEMs. Then we focus on landform parameters, starting with primary morphometric parameters, then morphometric indices and at last examples of morphometric tools available in geographic information system (GIS) packages. The last section briefly discusses the landform classification systems which have arisen in recent years.",signatures:"Bartłomiej Szypuła",downloadPdfUrl:"/chapter/pdf-download/55617",previewPdfUrl:"/chapter/pdf-preview/55617",authors:[{id:"196721",title:"Ph.D.",name:"Bartłomiej",surname:"Szypuła",slug:"bartlomiej-szypula",fullName:"Bartłomiej Szypuła"}],corrections:null}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},subseries:null,tags:null},relatedBooks:[{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophile",surname:"Theophanides",slug:"theophile-theophanides",fullName:"Theophile Theophanides"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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\r\n\tSimple and complex turbulence is one main issue in tackling applied science and engineering flow troubles. Modified numerical schemes, large-eddy simulations, and powerful computer powers are now accessible for solving the equations and corresponding issues. The applied sciences and modern technologies are always involved in turbulence effects and consistent computational fluid dynamics examination depends progressively more on the performance of the turbulence experimental, numerical models, and large-scale simulation methods.
\r\n
\r\n\tThis book will provide the latest and more predictive research work and discuss new developments in the field of turbulence modeling and investigations, with a special focus on applied-nature issues and their solutions. Eddy simulation book will look at a variety of areas, including but not limited to: Experimental and Numerical Studies, turbulence modeling/ control and applications, direct and large eddy simulations, heat transfer and methods, Vehicle aerodynamics flows, combustion system modeling, and particle image velocimetry, Gyrokinetic Large Eddy Simulations, plasma microturbulence, compressible space plasma turbulence, phase transition and transport phenomena’s.
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1. Introduction
There has been a global trend for populations to increasingly hold governments accountable to open government data (OGD) standards [1]. Because of this, governments have undertaken open data projects, such as providing public access to government data through publicly-accessible dashboards [2, 3]. However, government actors also may have an incentive to hide or obscure data, so there are barriers to accessing data for public dashboards [1]. This chapter focuses on the specific problem where governments attempt to demonstrate compliance with OGD standards through the presentation of a public dashboard, while at the same time, appearing to hide or obscure the data it is supposed to represent through poor dashboard design.
Our motivation to tackle this topic comes from our own disappointing experience trying to use a public dashboard implemented as part of OGD standards established where we live, in Massachusetts in the United States (US). Currently, in general, no standard guidance or recommendations are in place as a process to follow for the development of OGD public dashboards, and no framework or rubric has been proposed to evaluate them. These challenges are barriers to assessing how well public dashboards meet public need, and holding governments accountable for this. The significance of our contribution is that we propose a framework and rubric on which to base the evaluation of how well these public dashboards meet public need. The implication is that the application of this framework and rubric can be further researched in terms of utility in evaluating public dashboards. From this starting point, globally, we can begin to develop scientific consensus on what attributes in evaluate to a good-faith public dashboard implementation, and what the public should rightfully expect from the implementation of an OGD public dashboard.
2. Guidance for the design of public dashboards
The COVID-19 pandemic brought to attention a longstanding need for well-designed dashboards in public health and medicine [4]. It also brought to light that there are no uniform guiding principles behind developing publicly-facing dashboards intended to serve public interests. As a prime example, a recent review of United States (US) government public dashboards for COVID-19 found that “states engaged in dashboard practices that generally aligned with many of the goals set forth by the Centers for Disease Control and Prevention, Essential Public Health Services” (from abstract) [4]. However, the results of this review do not address whether the public was adequately served by any of these dashboards that were funded with the public’s money. Important questions not answered were: Did these dashboards meet the public’s information needs? Did they meet the information needs of public health practitioners? Or more importantly – whose information needs were these dashboards supposed to meet, and what were these needs?
2.1 Philosophies behind public dashboard design
At present, there is no overarching philosophy behind public dashboard design, for public health or other topics [2]. Although individual projects will publish use-cases where they discuss their design philosophy [2, 5, 6], there has not been an overall effort by the professional informatics societies or other academic groups to assemble principles behind the design for dashboards intended to serve the public. This may be because such an effort would be daunting, and would require a relatively narrow scope. The scope should be aimed at addressing high-level requirements focused on ensuring that the public’s needs are met by whatever dashboard solution is developed, regardless of the topic.
This chapter will attempt to summarize the literature into a framework that provides a general, generic rubric by which to evaluate how well a dashboard design for the public ensures that the public’s needs are met through measuring their adherence to high-level requirements. The framework will also put forth a method by which to compare alternative dashboard solutions aimed at meeting similar public needs as to how consistent the solution is with the public’s dashboard requirements.
The framework and rubric are intended to evaluate outcomes. Logically, a design process that adequately includes the public that the dashboard is intended to serve will inevitably produce a dashboard solution that meets these outcomes. Hence, there is no need to invest public funding in bloated efforts such as the Rapid Cycle Quality Improvement (RCQI) model, which is promoted by many health departments and organizations, and is extremely paperwork intensive [7, 8]. Part of what causes the RCQI model to be so effort-intensive is that it measures process outcomes. By contrast, the evaluation framework for public dashboards recommended in this chapter is streamlined, and focused on achieving a design solution, not a process solution.
Nevertheless, an optimal design solution will not be achieved without an adequate design process. Therefore, it is important to consider how the public should be involved in the process of designing public dashboards – especially those that are publicly-funded, and therefore have obligations to respond to the public’s needs.
2.2 Dashboard design process
As stated previously, there is currently no agreed-upon best-practices design process for dashboards in general, and public dashboards specifically [2]. Each time a dashboard is developed, a different design process is used. But a generic, logical process can be summarized in Figure 1.
Figure 1.
Generic logical dashboard design process. This design process produces an alpha prototype for initial testing, and a beta prototype for widespread field testing.
As shown in Figure 1, typically, before the dashboard is designed, some sort of design process is chosen, and this design process is followed to develop an “alpha prototype”. The alpha prototype represents a working mock-up that exists for the purposes of getting feedback and working out an initial design. Next, the alpha prototype undergoes a testing process to inform developers as to modifications that are necessary before widespread testing is done. Once those modifications are made, a beta prototype exists, and can be launched for field testing.
As described in Figure 1, depending upon the project, there can be different components included in the design process for the alpha prototype. First, there will be iterative design processes as part of designing the alpha prototype, as well as the development of design documentation and the actual creation of the prototype. The details behind each of these components will vary by project. Once the alpha prototype exists, the process to convert it to the beta prototype involves some sort of user testing, and some sort of evaluation for adherence to standards. Granted, an alpha prototype may be released into the field without having undergone the beta prototype process, but that means it has not been user-tested or evaluated for adhering to standards.
This logical process can apply to any dashboard development effort. As one example, researchers aimed to design a dashboard for clinicians [9]. They wrote requirements and developed an alpha prototype, then worked with clinicians to gain feedback to guide the development of a beta prototype (which would presumably be developed in the future and field-tested) [9]. This article focused mainly on the feedback process to improving the alpha prototype, but the focus of articles can be on any part of the dashboard design process. Another article focused on the development of a beta prototype aimed at both the public and leaders for real-time decision-making related to traffic flow [2]. While the beta prototype was developed and appeared ready for testing, the article did not report any results, so the current final stage of this project was not evident in the article [2].
Although, this logical design process should theoretically involve the intended users of the dashboard, and prototypes should undergo iterative testing, this is not always the case with public dashboards. Because public dashboards often involve government agencies and leaders at some level, whether as data sources or as intended audiences, these forces can have unintended impacts on the dashboard design and quality.
2.3 Governmental data suppression and misrepresentation
As a general trend, consumers are demanding more data transparency, and calls are being made for governments to make data available for public oversight [1]. Likewise, there is an increasing trend toward using dashboards for empowering the public [2, 3]. Not only do dashboards of public data provide a mechanism for public oversight of leaders, but they also reduce information asymmetry, which refers to the circumstance in which one party (the government) has more information than another party (the public), thus disempowering them [2, 10, 11].
However, governments are not always keen to share the data for various reasons. It has been argued that government agencies will be more likely to comply with open government data (OGD) practices if they see it as an opportunity to showcase their agency’s success [1]. However, if the agency believes the data will cast the agency in a negative light, the agency may be less likely to be inclined toward OGD practices. Ruijer and colleagues recommend that institutional incentives and pressure be created for OGD, because governments have a natural interest in suppressing data they think may be harmful to them in some way if analyzed [1].
However, data suppression is not the only method governments employ to prevent data use and interpretation. One limitation of legal requirements for OGD is that the agency may comply with the requirements in bad faith. During the COVID-19 outbreak in early 2020, a state epidemiologist in Florida said she was fired for refusing to manually falsify data behind a state dashboard [12]. Simply reviewing the limitations of big data can reveal ways to share big data in bad faith in a dashboard, such as visualizing too much data, visualizing incomprehensible or inappropriate data, and not visualizing needed data [13].
For this reason, in addition to holding governments to OGD standards, government efforts need to be evaluated as to whether or not they meet OGD standards in good faith. The framework presented here guides as to how to evaluate good vs. bad faith implementations of a public dashboard.
2.4 Dashboard requirements
The evaluation framework presented has six principles on which to judge the level of good or bad faith in a public dashboard: 1) ease of access to the underlying data, 2) the transparency of the underlying data, 3) approach to data classification, 4) utility of comparison functions, 5) utility of navigation functions, and 6) utility of metrics presented. These principles will be described below.
2.4.1 Access to underlying data
A dashboard is essentially a front-end, with data behind it being visualized [14]. Hence, once a dashboard is published, members of the public may want to access the underlying data for various reasons, including oversight of the dashboard. But governments resistant to data-sharing may use the dashboard in bad faith as a firewall between the public and the underlying data to prevent data access [1]. Hence, good faith OGD principles hold that public dashboards should not serve as barriers, but instead serve as facilitators to access the underlying data being visualized in the dashboard.
2.4.2 Transparency of underlying data
Although raw data are used for the dashboard, in the dashboarding process, they undergo many transformations to be properly visually displayed [9, 14]. The processing of the data can develop calculations that are then displayed in the dashboard. Therefore, to be transparent, the dashboard must not only facilitate access to the underlying raw data, but also to the transformations the data underwent in being displayed. A simple way to accomplish this kind of transparency is to use open source tools and publish the code, along with documentation [14]. This allows citizen data scientists an opportunity to review and evaluate the decisions made in the dashboard display.
2.4.3 Data classification
How data are classified in a dashboard can greatly impact the utility of the dashboard. As an example, developers of an emergency department (ED) dashboard that was in use for five years under beta testing found that after the ED experienced an outbreak of Middle East Respiratory Syndrome (MERS), major structural changes were needed to the dashboard [15]. Another paper about developing a visualization of patient histories for clinicians described in detail how each entity being displayed on the dashboard would be classified [16]. Hence, inappropriate classifications or ones deliberately made in bad faith can negatively impact data interpretation to the point that the dashboard could be incomprehensible to its users.
2.4.4 Comparison functions
Dashboards are used to inform decision-making, and therefore, being able to make needed comparisons is an important factor in a dashboard’s usability [14, 17]. As an example, the public traffic dashboard described earlier presented visualizations of the ten most congested areas of the city, as well as textual feedback on the two most suitable routes between downtown and outlying areas, to provide optimal comparators to allow the public to make the most-informed route decision [2]. While ultimately, optimal design choices could be debated, it is easy to conceive of how agencies looking to maintain opacity could obscure data interpretation in a dashboard in bad faith by deliberately limiting the ability to make useful comparisons.
2.4.5 Navigation functions
Dashboards are typically at least somewhat interactive, providing the user the ability to navigate through the data display, which responds to actions by the user [14, 18, 19]. When operating in good faith, developers often conduct extensive usability testing to ensure that the dashboard is intuitive to use in terms of navigating through the data display, and that any interactivity is useful [15]. But when implemented in bad faith, a dashboard could be designed to deliberately confuse the user as to how to navigate and interpret the data in the dashboard.
2.4.6 Metrics presented
One of the main purposes of dashboards is to present metrics that represent statistics or visualizations meant to summarize a particular state of the data [14, 15]. For example, in the traffic dashboard, the metrics presented are intended to communicate traffic congestion to the users, while the metrics presented in the clinical dashboard are intended for healthcare workers to use in clinical decision-making [2, 16]. In a good-faith effort, developers may conduct extensive user-testing to ensure that the metrics presented are communicative to dashboard users, as is often done with dashboards developed to serve workers in healthcare [9, 20]. However, in a bad faith effort, the metrics presented could be deliberately confusing to the user, and serve merely to hide ugly truths in the underlying data.
3. Use-case: dashboard for hospital-acquired infection rates at Massachusetts hospitals
In the US, the Commonwealth of Massachusetts (MA) Department of Public Health (DPH) posts annual healthcare-associated infection (HAI) reports about MA hospitals on their web page [21]. The purpose of the reports is public data transparency by law [21]. Briefly, HAI, such as catheter-acquired urinary tract infection (CAUTI), central line-associated bloodstream infections (CLABSI), and surgical site infections (SSI), are serious issues because they are the fault of the hospital, and can lead to sepsis, which is a systemic infection that can end in death [22, 23]. Since catheterization happens in the intensive care unit (ICU) setting, typically hospitals track CAUTI and CLABSI as part of healthcare quality activities centered around ICUs [14]. By contrast, SSIs are tracked in association with specific operative procedures (e.g., colon surgery) [24].
In the US compared to other countries, rates of HAI are relatively high, likely because they are not required to be tracked at the federal level [14, 25]. Hospitals can opt into the federal voluntary tracking system called the National Health Safety Network (NHSN), but the NHSN does not have a publicly-facing dashboard, and the data are inaccurate, especially in undercounting severe events [14, 24, 26]. As HAI is a serious public health issue, there has been a call for greater data transparency, so the reports posted on the MA DPH web site represent MA’s attempt to comply with state-level mandates for OGD.
Although summary reports are available for download on the MA DPH web site, it is not possible to access hospital-level reports directly from the web site. To download hospital-level reports, the user must access a dashboard presented on the web page in a link (Figure 2).
Figure 2.
MA HAI public dashboard landing page. Note: “A” labels a menu of tabs that can be used for navigation to view metrics on the various hospital-acquired infections (HAIs). In panel labeled “B”, tabs can be used to toggle between viewing state-level metrics and hospital-level metrics. Hospitals can be selected for display using a map labeled “C”.
As per Figure 2, once inside the dashboard, individual PDF-style reports can be found through navigation to the hospital in question, and the reports appear to present formatted output from a database. One way to navigate to the hospital record is to locate it on the map (“C” in Figure 2) and click on its icon, causing the panel “B” to display hospital-level metrics and a link to the hospital’s PDF report.
Each PDF report has a header displaying attribute data about the hospital (e.g., number of beds), followed by a series of ICU-, procedure-, and infection-level output. This mirrors the structure seen in the dashboard tabs and reports (Figure 2, “A” and “B”). For the ICUs at each hospital, the report displays a set of tables summarizing CAUTI and CLABSI rates, followed by time-series graphs. For a set of high-risk surgical procedures, SSI rates and graphs for the hospital are displayed. Medication-resistant staphylococcus aureus (MRSA) and C. Difficile infections are serious HAIs that can be acquired in any part of the hospital and are diagnosed using laboratory tests [27]. Rates and graphs of MRSA and C. Difficile infections are also displayed on the report.
The underlying data come from the NHSN. This is not stated on the dashboard. Instead, there is a summary report and presentation posted alongside the dashboard on the web site, and the analyses in these files are based on NHSN data [21]. It seems that the DPH is using this NHSN data using as a back-end to the dashboard, and the dashboard is an attempt to comply with OGD laws.
Because the authors are aware of the high rates of HAI in the US, and because we both live in MA and we both are women who are cognizant that sexism in US healthcare adds additional layers of risk to women [28], we identified that we were in a state of information asymmetry. Specifically, we had the information need to compare MA hospitals to choose the least risky or “lethal” one for elective surgery or childbearing (planned procedures), but we felt this need was not met by this OGD implementation.
In this section, we start by evaluating the existing MA DPH HAI dashboard against our good vs. bad faith framework. Next, we propose an alternative dashboard solution that improves the good vs. bad faith features of the implementation.
3.1 Considering existing dashboard: design process and requirements
Figure 3 provides a logical entity-relationship diagram (ERD) for the data behind the dashboard.
Figure 3.
Logical entity-relationship diagram for data behind dashboard. Note: The schema presented assumes four entities: The hospital entity (primary key [PK]: HospRowID), each intensive care unit (ICU) attached to a hospital which contains the frequency of infection and catheter days attributes to allow rate calculation (PK: ICURowID), each procedure type attached to a hospital (to support the analysis of surgical site infection [SSI], with PK: ProcRowID), and each other infection type at the hospital not tracked with ICUs (PK: LabID).
As described earlier, the landing page (Figure 2) provides a map by which users can select a hospital, causing the metrics for the hospital to appear in a panel. The user chooses which measurement to view (e.g., CAUTI) through navigation using the tabs. This suggests the dashboard is aimed at individuals with a working knowledge of MA geography who are intending on comparing and selecting hospitals least likely to cause HAI for an elective procedure (e.g., childbearing), or to establish as their top choice of the local hospital should they ever need to be admitted. This interface makes it difficult to compare HAI at different hospitals, because metrics from more than one hospital cannot be viewed at the same time. Further, metrics about different HAIs at the same hospital are on different panels, so within-hospital comparisons cannot be facilitated. There appears to be no overall metric to use by which to compare hospitals in terms of their HAI rates.
Figure 4 shows an example of the metrics reported by each hospital on the dashboard reporting panel (“B” in Figure 2). The figure also shows one of the two tables and one of the two figures displayed on the CAUTI tab for the selected hospital. In all, two tables and two figures are displayed in portrait style in panel “B” (Figure 2), and Figure 4 shows the top table and figure displayed. In the table displayed (labeled “1” in Figure 4), the metrics presented are the number of infections, predicted infections, standard infection ratios (SIRS), a confidence interval for the SIR, and an interpretation of the level. The figure (labeled “2” in Figure 4) displays a time-series graph of SIRs for the past five years. In the other table on the panel (not shown in Figure 4), ICU-level metrics are provided about catheter-days, predicted catheter-days, Standard Utilization Ratios (SURs) and their confidence interval, and an interpretation, and an analogous time-series graph of five years of SURs is presented (also not shown in Figure 4).
Figure 4.
Dashboard metric display for each hospital. Note: To view hospital-acquired infection (HAI) rates at hospitals, a hospital is selected (Figure 2, panel “C”), then the user selects the tab for the HAI of interest. In Figure 4, a hospital has been identified, and a tab for catheter-associated urinary tract infection (CAUTI) has been selected (see circle). Two tables and two figures are presented in portrait format on the reporting panel for each hospital (Figure 2, panel “B”). Figure 4 shows the first table and figure presented (“1” and “2”); the table reflects stratified metrics for CAUTI at each ICU at the hospital, and the graph reflects a time series of these metrics stratified by hospital vs. state levels, and intensive care unit (ICU) vs. ward (“ward” is not defined in the dashboard). The metrics provided in “1” are a number of infections, predicted infections, standard infection ratios (SIRs), a confidence interval for the SIR, and an interpretation of the level. In “B”, the SIR is graphed.
SIRs and SURs are not metrics used typically by the public to understand rates of HAI in hospitals. Risk communication about rates to the public is typically done in the format of n per 10,000 or 100,000, depending upon the magnitude of the rate [29]. Further, stratifying rates by ICU is confusing, as prospective patients may not know what ICU in which they will be placed. Because the hospital environment confers the strongest risk factors for HAI (e.g., worker burnout), HAI rates will be intra-correlated within each hospital [30]. Therefore, it is confusing to present all these rates and stratify them by ICU. Figure 4 only displays 50% of the information available about CAUTI at one hospital. With each tab displaying similar metrics about SSI and other infections, the experimental unit being used is so small, it obfuscates any summary statistics or comparisons. Also, it is unclear how the “predicted” metrics presented were calculated.
Ultimately, the design process and requirements behind this dashboard are not known. There is no documentation as to how this dashboard was designed, and what it is supposed to do. It appears to be an alpha prototype that was launched without a stated a priori design process, and without any user testing or formal evaluation.
3.2 Alternative design: design process and requirements
We chose to redesign the dashboard into a new alpha prototype that met requirements that we, as members of the public, delineated. Consistent with the good faith principles proposed, our requirements included the following: 1) the dataset we use should be easily downloadable by anyone using the dashboard, 2) the documentation of how the dashboard was developed should be easy to access, 3) hospitals should present summary metrics rather than stratified ones, 4) different HAI metrics for the same hospital should be presented together, and 5) there needs to be a way to easily compare hospitals and choose the least risky hospital. To do this, we first obtained the data underlying the original dashboard. Next, we analyzed it to determine better metrics to present. We also selected open-source software to use to redeploy an alpha prototype of a new dashboard. Finally, we conducted informal user testing on this alpha prototype.
3.2.1 Obtaining the data from the original dashboard
Scraping was done in open-source RStudio and predominantly used packages pdftools, and pdftables [31, 32]. All the PDF reports from each hospital were downloaded and placed in one directory. As a first step, a loop was used with the pdftools package which crawled through each report extracting the data into memory. This was done in conjunction with the pdftables package, which is essentially an online application that applies structure to the unstructured tabular data placed in memory from pdftools. To use this online application, an application programming interface (API) key is issued from the PDF Tables web site, and is used in the RStudio programming to pass the data to the online application [33]. The code resulted in the data being processed into a series of unstructured *.xlsx files and downloaded locally. Then, in a final data cleaning step, data were transformed into the tables in the format specified in Figure 3.
3.2.2 Determining metrics to present
We chose to focus our inquiry on the data from the hospital and ICU tables, as CAUTI and CLABSI are by far the most prevalent and deadly HAIs [23]. Therefore, we scoped our alpha prototype to only display data from the ICU and the hospital tables (although we make all the data we scraped available in the downloadable dataset). This limited us to basing the dashboard on hospital- and ICU-level metrics only.
Next, we intended to present CAUTI and CLABSI frequencies and rates, whereby the numerator would be the number of infections, and the denominator would be the “number of patients catheterized”. We felt that the dashboard’s use of catheter-days as the rate denominator was confusing to the public, and appeared to attenuate the prevalence of patients having experienced a CAUTI or CLABSI. Although, “number of patients catheterized” was not available in the data, “annual admissions” was. Since the proportion of patients admitted annually who are catheterized probably does not vary much from hospital to hospital, we chose to use the number of admissions as the denominator and a proxy measurement.
Third, we needed to develop a way of sorting hospitals as to their likelihood of causing an HAI to allow easy comparisons by public users, so we decided to develop an equation to predict the likelihood of an HAI at the hospital. We did this by developing a linear regression model with hospital-level attributes as independent variables (IVs), and CAUTI rate in 2019 as the dependent variable (DV). We chose CAUTI over CLABSI after observing the two rates were highly correlated, and CAUTI was more prevalent.
Table 1 describes the candidate IVs for the linear regression model. The table also includes the source of external data that were added to the hospital data. We studied our IVs, and found serious collinearity among several variables, so we used principal component analysis (PCA) to help us make informed choices about parsimony [37]. The data predominantly loaded on three factors (not shown). The first factor included all the size and utilization variables for the hospital; these were summed into a Factor 1 score. The second-factor loadings included the proportion of those aged 65 and older and the non-urban flag (Table 1), so those were summed as Factor 2. Proportion non-White was strongly inversely correlated with Factor 2, so it was kept for the model, and county population did not load, so it was removed from the analysis. Factor 3 loadings included teaching status, for-profit status, and Medicare Performance Score (MPS). Rather than create a score, we simply chose to include the variable from Factor 3 that led to the best model fit to represent the factor, which was MPS. Then we finalized our linear regression model, and developed a predicted CAUTI rate (ŷ) using our model that included the following IVs: MPS, Factor 1 score, Factor 2 score, and proportion of non-White residents in hospital county.
Variable
Source
Role
Source
Teaching hospital status
Original dashboard
Exposure
Scraped data from dashboard
Hospital profit status
Original dashboard
Confounder
Scraped data from dashboard
Measurements of hospital size (number of beds)
Original dashboard
Confounder
Scraped data from dashboard
Measurements of hospital utilization (number of admissions, number of patient days)
Calculated as the numerator for rates divided by admissions
Table 1.
Conceptual model specification.
Next, we used the regression equation to calculate ŷ as a “lethality score” for each hospital. Of the 71 hospitals in the dataset, 21 were missing MPS and 8 were missing other data in the model. Therefore, only the 42 with complete data (IVs and DVs) were used to develop the regression model. As a result, the lethality score was non-sensical for some hospitals; where the residual was large, the lethality score was replaced with the 2019 CAUTI rate. If CAUTI data were missing, it was assumed that the hospital had no CAUTI cases, and therefore was scored as 0.
Once the lethality score was calculated, we chose to sort the hospitals by score, and divide them into four categories: least probable (color-coded green), somewhat probable (color-coded yellow), more probable (color-coded red), and most probable (color-coded dark gray). Due to missing CAUTI information and many hospitals having zero CAUTI cases, our data were severely skewed left, so making quartiles of the lethality score to divide the hospitals into four categories was not meaningful. To compensate, we sorted the data by lethality score and placed the first 23 hospitals (32%), which included all the hospitals with zero cases, in the least probable category. We placed the next 16 (23%) in somewhat probable, the next 16 (23%) in more probable, and the final 16 (23%) are most probable. We chose to use this classification in data display on the dashboard to allow for easy comparison between hospitals of risk of a patient contracting HAI.
3.2.3 Choice of software and display
R is an open-source analytics software that allows for user-developed “packages” to be added a la carte to the main application [38]. RStudio was developed to be an integrated development environment (IDE) for R that allows for advanced visualization capabilities that support dashboard development [39]. In RStudio, web applications like dashboards can be placed on a host server and deployed on the internet such that as users interact with the web front-end, it can query and display data from the back-end hosted on the server.
The package Rshiny [40] was developed to support dashboarding in RStudio, and can work with other visualization packages depending upon the design goals of the dashboard. In our newly designed dashboard, the package leaflet was used for a base map on which we placed the hospital icons (like the original dashboard), and add-ons were made to display other items. These add-ons were adapted from other published codes [41]. JavaScript with wrapper DT (data table) was used to display stratified ICU rates, and CSS was used for formatting.
The dashboard we developed was deployed on a server (https://natasha-dukach.shinyapps.io/healthcare-associated-infections-reports/) and code for the dashboard was published (https://github.com/NatashaDukach/HAI-MA-2019). When accessing the link to the dashboard, the user initially sees a map with icons (in the form of dots) on it indicating hospitals. The icons are color-coded according to the lethality score described previously. Clicking on an icon will expand a bubble reporting information about the hospital (Figure 5).
Figure 5.
Alternative dashboard solution. Note: In our new version, two tabs are created (see “A”). The figure shows the first tab titled “ICU Rate Explorer”. The second tab, titled “data collection”, has information about the design of the dashboard and links to the original code. Each of the hospitals is indicated on the map by a color-coded icon that can be clicked on to display a bubble. The legend by “B” displays our color-coding scheme. When clicking on a hospital icon, hospital-level metrics are shown in a bubble, and there is a link that leads to the display of intensive care unit (ICU)-level metrics (see “C”).
As shown in Figure 5, like the original dashboard, this one has a map for navigation. Unlike the original, it only has two tabs: “ICU Rate Explorer” (the one shown in Figure 5), and “Data Collection”, which provides documentation and links to original data and code (see “A” in Figure 5). The hospital icons are placed on the map and coded according to our color scheme (see legend in Figure 5 by “B”). This allows for easy comparison between hospitals. When clicking on an icon for a hospital, a bubble appears that contains the following hospital metrics: Number of admissions, number of ICU beds, overall CAUTI rate, and overall CLABSI rate. There is also a link on the bubble where the user can click to open a new box that provides CAUTI and CLABSI rates stratified by ICU. Future development plans include adding other overall rates (e.g., for SSI), and adding in data from previous years to allow for the evaluation of trends.
3.2.4 User testing
Informally, members of two potential user bases were queried as to their reactions to the differences between the two dashboards: members of the academic public health space, and members of the MA public. When the dashboard redesign was pitched as a project to public health academics, it was dismissed as an unimportant escapade for various reasons. Some reasons cited were lack of agreement on terminology and patient safety priorities, the challenges with undercount of HAIs in NHSN data, and differential reporting accuracy in teaching vs. non-teaching hospitals. Academics also acknowledged that the system for tracking, addressing, and preventing HAIs is hopelessly broken in the US, and therefore it seems a waste of time to prop up such a system when it produces inaccurate data.
A few members of the MA public who are familiar with technology also provided informal feedback about the utility of the dashboard from a patient standpoint. They reported that the alternative solution was more intuitive than the original, and did a better job of representing the highly limited data from the NHSN.
These differences in reactions underscore the challenge of OGD and ensuring that public dashboards are developed and deployed in good faith. Those from the public health field expressed that since the system is broken and the data are inaccurate, they should be dismissed, while those in the public felt that since the data existed, it should be accessible, even if it was not completely accurate. It not only highlights the differing perspectives of those on either side of information asymmetry, it glaringly illustrates how those who are being held accountable by the usage of the data see dashboarding differently than those who are using the data to do oversight and accountability.
4. Application
We wanted to compare the original HAI dashboard with the one we developed based on the good faith principles described earlier. We started by creating the framework presented in Table 2, which guides as to the good faith and bad faith characteristics of public dashboards.
Dashboard function/characteristic
Good faith
Bad faith
Access to underlying data
Easy to download analytic dataset on which dashboard rides in *.csv format (e.g., through report export function)
Easy to access or download component datasets that went into the analytic dataset on which the dashboard rides
Lack of downloading functions, or downloading functions that provide only reports in non-tabular and non-data format
Lack of transparency on how the analytic dataset was developed
Lack of transparency about source datasets
Transparency of underlying data
For each native variable used in the dashboard, its source dataset is specified, and a link is given if available.
For each calculated variable used in the dashboard, clear documentation is available.
It is clear which data reflect real measurements, and which reflect simulations, imputations, or predictions
Source datasets may be specified, but little information about the use of their variables in the dashboard is provided
It is not made clear which dashboard variables are calculated, and how they are calculated is also not made clear
It is not clear which data reflect real measurements, and which data have been simulated, imputed, or otherwise fabricated
Data classification
Data are classified in ways that are intuitive to the consumer, and results are presented according to those classifications
Data are classified in ways that either make the development work easier for the analyst, or serve to mask negative indicators
Data are not grouped into classifications consumers use, making it impossible to obtain summary statistics for these classification levels
Comparison functions
Dashboard allows for comparisons that provide useful consumer decision-support
Dashboard prevents comparisons that would provide consumer decision-support, or makes them very difficult to make using the dashboard functions
Navigation functions
Navigation functions reflect how users conceive of accessing the entities in the dashboard
Specifically, map navigation reflects how users conceive of their geographic locale when searching for information
This allows consumers to intuitively ingest and assimilate information as they interact with the dashboard
Navigation functions reflect how public officials want consumers to navigate the entities in the dashboard
This forces consumers to think differently about the topic, and disrupts their ability to ingest and assimilate information
Map functions force the consumer to conceive of their geographic locale in an unintuitive way, making map navigation confusing
Metrics presented
Metrics are intuitive to consumers
Metrics are presented in such a way that they are intuitive to ingest and assimilate
Metrics that are presented to make comparisons between entities intuitive to support decision-making
Metrics reflect jargon, and are unintuitive to consumers
Metrics require consumers to read documentation to understand
Metrics are presented in such a way as to be confusing, making them impossible to be used for decision-support
Table 2.
Proposed framework for evaluation of good faith and bad faith public dashboards.
Using this framework, we applied a rating system. We chose zero to represent “neither bad faith nor good faith”, −5 to represent “mostly bad faith” and + 5 to represent “mostly good faith”. Then, based on our experience and available information, we rated the original MA HAI dashboard and our alternative dashboard solution to compare the ratings. To experiment with applying our framework to another public dashboard, we used the information published in the article described earlier to rate the traffic dashboard which was in Rio de Janeiro [2]. Our ratings appear in Table 3.
Dashboard function/characteristic
MA Hosp
Alt. MA Hosp
Comment: MA Hosp vs. Alt. MA Hosp
Rio
Comment: MA Hosp vs. Rio
ACCESS TO UNDERLYING DATA
−5
5
The original solution had no access to underlying data (except by way of PDF-style reports). Alternative solution posts data publicly for download.
5
Rio dashboard uses open data from City Hall with user-generated content collected through Waze
Transparency of Underlying Data
−5
3
It was difficult to identify the source of the data in the original solution. The alternative solution uses the same data, which is from NHSN. Because NHSN itself is somewhat opaque, the final solution lacks transparency.
0
Unclear from the article, but it appears that it is possible to audit Rio dashboard design if a member of a certain role (e.g., public data scientist). Not all tools used were open source.
Data Classification
0
3
In informal user testing, public users found the data classifications much more intuitive in the alternative compared to the original solution. However, formal user testing was not conducted.
5
Much effort was made to classify data in Rio dashboard to make it useful for the public to make route decisions.
Comparison Functions
−5
5
In informal user testing, users found the comparison function in the alternative solution useful for decision-making, and could not find a comparison function in the original solution.
5
Rio dashboard was designed to allow the public to make comparisons about potential traffic routes.
Navigation Functions
0
5
In informal user testing, users reported being able to easily navigate the data and dashboard in the alternative solution, but having extreme difficulty in navigating the original solution.
5
Rio dashboard for the public had a very simple, intuitive interface with images and only a few metrics critical to decision-making. This made it possible to easily navigate the dashboard display.
Metrics Presented
−5
5
In informal testing, users indicated that they did not understand the metrics presented on the original solution but found the color-coding of the alternative solution intuitive for decision-making.
3
The few metrics presented on the Rio dashboard were geared specifically to helping the public make route decisions based on traffic metrics. However, no formal user testing is presented.
Total
−20
26
23
Table 3.
Application of rating system.
Note: MA Hosp = original hospital-acquired infection (HAI) dashboard from the Commonwealth of Massachusetts (MA), MA Hosp Alt. = alternative solution, Rio = Rio traffic dashboard [2], and NHSN = National Healthcare Safety Network.
As shown in Table 3, using Table 2 as a rubric and our rating scale, we were able to rate each dashboard and assign a score. We were also able to define in the comments in the table the evidence on which we based our score. Table 3 demonstrates that this framework can be used to compare two different alternatives of a public dashboard displaying the same data, as well as two completely different public dashboards. The total scores show that while our redesigned prototype of the HAI dashboard had a similar level of good faith implementation compared to the Rio traffic dashboard (scores 26 vs. 23, respectively), the original HAI dashboard had a very low level of good faith implementation compared to the other two (score − 20).
5. Discussion
As is consistent with the global trend, the state of MA implemented an OGD requirement to share HAI data with the public through posting a public dashboard on a web page. However, as residents of MA, the authors found that this dashboard did not serve our information needs, and essentially obscured the data it was supposed to present. To address this challenge, we not only redesigned the dashboard into a new prototype, but we also tested our proposed framework for evaluating the level of good faith in public dashboards by applying it. Using our proposed framework and rubric, we evaluated the original HAI dashboard, our redesigned prototype, and a public dashboard on another topic presented in the scientific literature on the level of good faith implementation. Through this exercise, we demonstrated that the proposed framework is reasonable to use when evaluating the level of good faith in a public dashboard.
The next step in the pursuit of holding governments accountable for meeting OGD standards in public dashboards is to improve upon this framework and rubric through rigorous research. As part of this research, entire groups of individuals could be asked to score dashboards on each of these characteristics, and the results could easily be summarized to allow an evidence-based comparison between dashboards. Results can be easily visualized in a dumbbell plot (using packages ggplot2, ggalt, and tidyverse [42, 43, 44]), which we have done with our individual scores, but could be done with summary scores (Figure 6).
Figure 6.
Example of visualization of framework score comparison. Note: MA Hosp = original hospital-acquired infection (HAI) dashboard from the Commonwealth of Massachusetts (MA), MA Hosp Alt. = alternative solution, and Rio = Rio traffic dashboard [2].
As visualized in Figure 5 and summed in Table 3, our scoring system suggested that the alternative HAI dashboard we developed was done in a level of good faith (score = 26) similar to that of the Rio traffic dashboard (score = 23), and that the original HAI dashboard appears to not have been done in good faith (score = −20), and may serve as a governmental attempt to hide or obscure uncomfortable data. This exercise shows that the framework and rubric developed can be used to compare the level of good faith in public dashboards, and to provide evidence-based recommendations on how governments can improve them so they meet both the spirit and the letter of OGD requirements.
6. Conclusion
In conclusion, in this chapter, we describe the challenge of holding governments accountable for developing public dashboards to meet OGD requirements in a way that also serves the public’s information needs. To address this challenge, we propose a framework of six principles of good faith OGD by which public dashboards could be evaluated to ensure data shared by the government under OGD policies and laws are done so in good faith. We also demonstrate applying this framework to the use-case of a public dashboard intended for residents of MA in the US to use to compare and select hospitals based on their HAI rates. As a demonstration, we present our redesign of the dashboard, then use a rubric based on the framework to score and compare the original dashboard and our alternative in terms of levels of good faith OGD. We also demonstrate using the rubric on a published use-case in the literature. As our framework and rubric provide a reasonable starting point as a method for evaluating and comparing the level of good faith in public dashboards, we strongly recommend that future research into this topic consider our framework and rubric, and build upon it through gathering evidence in the field.
\n',keywords:"public reporting of healthcare data, quality of healthcare, cross infection, public health informatics, data visualization",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/80394.pdf",chapterXML:"https://mts.intechopen.com/source/xml/80394.xml",downloadPdfUrl:"/chapter/pdf-download/80394",previewPdfUrl:"/chapter/pdf-preview/80394",totalDownloads:53,totalViews:0,totalCrossrefCites:0,totalDimensionsCites:0,totalAltmetricsMentions:0,impactScore:0,impactScorePercentile:0,impactScoreQuartile:0,hasAltmetrics:0,dateSubmitted:"November 23rd 2021",dateReviewed:"December 9th 2021",datePrePublished:"February 8th 2022",datePublished:"April 13th 2022",dateFinished:"February 8th 2022",readingETA:"0",abstract:"To hold governments accountable to open government data (GD) standards, public dashboards need to be evaluated in terms of how well they meet public needs. To assist with that effort, this chapter presents a framework and rubric by which public dashboards can be evaluated for their level of good faith implementation. It starts by reviewing challenges to governments sharing data in good faith despite increasing open government data (OGD) policies and laws being put in place globally. Next, it presents a use-case in which the authors explain how they examined a public dashboard in their local context that appeared to be following OGD, but not in good faith, and developed an alternative implementation that appeared to increase the level of good faith. The framework and rubric proposed were used to successfully compare and contrast the level of good faith of both implementations, as well as another public dashboard described in the scientific literature, and to generate recommendations to increase the level of good faith. In conclusion, the utility of this framework and rubric for evaluating and comparing good faith in public implementations of dashboards was demonstrated, and researchers are encouraged to build upon this research to quantify the level of good faith in public dashboards as a way of increasing oversight of OGD compliance.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/80394",risUrl:"/chapter/ris/80394",book:{id:"10693",slug:"open-data"},signatures:"Monika M. Wahi and Natasha Dukach",authors:[{id:"190958",title:"Ms.",name:"Monika M.",middleName:null,surname:"Wahi",fullName:"Monika M. Wahi",slug:"monika-m.-wahi",email:"mwahi@vasantahealth.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Labouré College",institutionURL:null,country:{name:"United States of America"}}},{id:"426959",title:"Ms.",name:"Natasha",middleName:null,surname:"Dukach",fullName:"Natasha Dukach",slug:"natasha-dukach",email:"dukach@bu.edu",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Boston University",institutionURL:null,country:{name:"United States of America"}}}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Guidance for the design of public dashboards",level:"1"},{id:"sec_2_2",title:"2.1 Philosophies behind public dashboard design",level:"2"},{id:"sec_3_2",title:"2.2 Dashboard design process",level:"2"},{id:"sec_4_2",title:"2.3 Governmental data suppression and misrepresentation",level:"2"},{id:"sec_5_2",title:"2.4 Dashboard requirements",level:"2"},{id:"sec_5_3",title:"2.4.1 Access to underlying data",level:"3"},{id:"sec_6_3",title:"2.4.2 Transparency of underlying data",level:"3"},{id:"sec_7_3",title:"2.4.3 Data classification",level:"3"},{id:"sec_8_3",title:"2.4.4 Comparison functions",level:"3"},{id:"sec_9_3",title:"2.4.5 Navigation functions",level:"3"},{id:"sec_10_3",title:"2.4.6 Metrics presented",level:"3"},{id:"sec_13",title:"3. Use-case: dashboard for hospital-acquired infection rates at Massachusetts hospitals",level:"1"},{id:"sec_13_2",title:"3.1 Considering existing dashboard: design process and requirements",level:"2"},{id:"sec_14_2",title:"3.2 Alternative design: design process and requirements",level:"2"},{id:"sec_14_3",title:"3.2.1 Obtaining the data from the original dashboard",level:"3"},{id:"sec_15_3",title:"Table 1.",level:"3"},{id:"sec_16_3",title:"3.2.3 Choice of software and display",level:"3"},{id:"sec_17_3",title:"3.2.4 User testing",level:"3"},{id:"sec_20",title:"4. Application",level:"1"},{id:"sec_21",title:"5. Discussion",level:"1"},{id:"sec_22",title:"6. Conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'Ruijer E, Détienne F, Baker M, et al. The politics of open government data: Understanding organizational responses to pressure for more transparency. The American Review of Public Administration. 2020;50:260-274'},{id:"B2",body:'Matheus R, Janssen M, Maheshwari D. 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1. Introduction
In 1959, the celebrated physicist and Nobel laureate Richard Feynman presented an idea of nanotechnology in his talk “There is a plenty of room at the bottom-An invitation to enter a new field of physics” by emphasizing on the fact that the laws of physics allow us to arrange the atoms the way we want. Almost a century ago, Maxwell [1] initiated working on this issue theoretically and unveiled that the particles of size of micrometer and millimeter, if used in traditional fluids can resolve the motive in a more efficient manner. Yet they had few drawbacks like clogging, erosion in micro channel and settling down which were curbed with the evolution of better substitute; nanosized particles (called as nanoparticles). The suspension of nanoparticles in the regular fluids comprised the nanofluids [2]. Nanofluids have also shown many interesting properties, and the distinctive features (refer Table 1) resulting in unprecedented potential for many applications particularly in biological, medical and biomedical applications.
Properties
Microparticles
Nanoparticles
Stability
Not stable
Stable
Surface/Volume ratio
One
One thousand times more than that of microparticles
Conductivity
Less
High
Clogging
More
Negligible
Erosion
Yes
No
Nanoscale phenomenon
No
Yes
Table 1.
Comparison of particles.
The catalytic role of nanoparticles in intensifying the thermal conductivity of nanofluids is analyzed by many researchers: Masuda et al. [3], Eastman et al. [4], Das et al. [5] and others. In 2006, Buongiorno [6] pioneered the formulation of conservation equations of nanofluids by incorporating the impacts of diffusion due to Brownian motion and thermophoresis of nanoparticles. He made an observation that the velocity of nanoparticles can be perceived as a sum of base fluid and relative (slip) velocities. To prosecute his research, he considered seven slip mechanisms; inactivity, magnus effect, Brownian motion, diffusiophoresis, thermophoresis, gravitational settling and fluid drainage. Throughout his investigation, he agreed that from all these seven techniques, Brownian diffusion and thermophoresis have a significant part in the absence of turbulent effects. Choi et al. [7] found that carbon nanotubes provide highest thermal conductivity enhancement of nanofluids. There are ample number of evaluations on thermal conductivity of nanofluids [8, 9, 10, 11] in which they discussed and analyzed the theoretical as well as experimental results. Heat transfer in nanofluids because of convection has been examined and contemplated by Das and Choi [12], Ding et al. [13] and Das et al. [14].
The ballistic character of heat transfer within nanoparticles has been studied by Chen [15]. Abnormal increase in viscosity is generally observed in relation to the base fluid. The presence of nanoparticles has found to enhance thermal conductivity [4, 7, 16, 17, 18, 19]. At very low nanoparticle volume fractions (<0.1%), a heat transfer enhancement up to 40% has been reported [8] and this percentage is found to enhance with temperature [5] and concentration of nanoparticles [16]. The results of Choi et al. [7] established the unexpected non-linear character of measured thermal conductivity with nanotube loadings at low concentration while all theoretical studies concluded a linear relationship. Also, it was discovered that thermal conductivity strongly depends on temperature [5] and particle size [20]. Pak and Cho [21] in their study also reported the heat transfer data for turbulent flow of nanofluids having nanoparticles as aluminum and titanium in circular tubes. They found that Nusselt number is up to 30% more than that of base fluid. Nowadays nanofluids are also used in drug delivery systems [22] and advanced nuclear systems [23] due to enriched thermal properties. The nanofluid technology is still in its early stage and various researchers are using nanofluids as a tool to solve technological riddles of the modern society. Figure 1 establishes big impact of small particles in view of the diverse applications of nanofluids in fields of industrial, residential, biomedical and transportation.
Figure 1.
Applications of nanofluids.
These days, nanoparticles are used in almost every biomedical application. Recent usage of nanotechnology in medicine and cancer therapy has attracted a lot of interest in thermal properties of nanofluid such as blood with nanoparticles suspension. Researchers have made the efforts to construct a mathematical model that shows the physical system or phenomenon nearly exact behaviour [24, 25]. Motivated by their work, we also intended to form an analytical model for the analysis of the convection currents in a horizontal nanofluid layer which is in accordance with the physical laws. Consequently, the onset of convection currents in the nanofluid layer is investigated mathematically with the help of partial differential equations. To begin with, equations are non-dimensionalized to get Rayleigh number in the system. Then small disturbances are added to the initial flow and new set of equations are obtained. Further PDE’s are converted into ordinary differential equations using normal modes and expression for Rayleigh number is obtained. It is found that density and conductivity of nanoparticles are important parameters in deciding the stability of the system.
2. Instability of fluids under small temperature gradient: Rayleigh Bênard convection
The convective motions occur in a fluid layer heated underside in which a small temperature gradient is maintained across its boundaries. The maintained temperature across the boundaries must surpass a certain value before the instability can manifest itself. This Phenomenon was discovered by Bénard [26] in 1900. In most of his experiments, he found that if a fluid layer is heated underside, the layer at the bottom expands due to higher temperature. This makes the fluid density lighter at the bottom than that on the top making the system top heavy. Here viscosity and thermal diffusivity tend to oppose the convective motions but with the application of higher temperature gradient across the fluid layer, the thermal convection process gets initiated showing the pattern of cellular motions (called Bénard convection). Bénard [27] performed an experiment with metallic plate with a thin non-volatile liquid layer of 1 mm depth maintained under constant temperature.
Figure 2.
A view of Rayleigh-Bénard convection.
Keeping the upper layer of fluid exposed to free air, he observed that the fluid layer was decomposed into number of cells (showing cellular motion) called Bénard cells. Thus in the standard Bénard problem, density difference due to variation in temperature across the upper and lower boundaries of the fluid becomes the main reason for the occurrence of instability. Figure 2 shows the schematic representation of Rayleigh-Bénard convection. Rayleigh [28] was the first person who gave an analytical treatment of the problem related to identifying the conditions responsible for breakdown of basic state. As a subsequent work carried out by Rayleigh and Bénard, thermal instability of fluids is known as Rayleigh Bénard convection. The condition for convective motions (depends on temperature gradient) can be represented in dimensionless form by the critical Rayleigh number. He figured out the condition for the instability of free surfaces by showing that the instability would occur on a large temperature gradient β=−dT/dz in such a way that the Rayleigh number; RA=αβgd4/κν, exceeds a certain critical value; where acceleration due to gravity is represented by g, coefficient of thermal expansion by α, the depth of the layer by d, thermal diffusivity by κ and kinematic viscosity is given by ν. For the stabilizing viscous force, RA parameter gives the force of destabilizing buoyancy. Chandra [29] found discrepancy between the theoretical and experimental work for the convective motions in fluids when heated underside. He explained it by conducting an experiment on the layer in air and observed that instability of the fluid layer was dependent on its depth. A simplification in the partial differential equations describing the flow of compressible fluid is done by Spiegel and Veronis [30] by assuming very small depth of the layer as compared to the height. The basic equations of a fluid layer in porous medium (when heated underside) were formulated and derived by Joseph [31] by using Boussinesq approximation. The problem of thermal convection of a fluid layer has been put forward by Chandrasekhar [32] by considering the implications of various aspects of hydrodynamics and hydromagnetics. He depicted the result that addition of rotation and magnetic field increases the stability of the system. Kim et al. [33] considered the same problem of thermal convection for nanofluids. They showed that convective motion directly depends on the two physical properties (heat capacity and density) of nanoparticles and adversely depends on the conductivity of nanoparticles. Buongiorno [6] was the first scientist who formulated the conservation equations of nanofluids by assimilating the effects of diffusion due to Brownian motion and thermophoresis of nanoparticles. During his analysis, he concluded that Brownian and thermophoretic diffusion play a significant role in the absence of turbulent effects as compared to other seven mechanisms. Hwang et al. [34] treated this problem analytically and put forth the result of thermal instability of water based nanofluid with alumina nanoparticles in a rectangular container which is heated from below. They found that stability of the base fluid is enhanced by adding alumina nanoparticles and further it is enhanced by increasing the volume fraction of nanoparticles, the average temperature of the nanofluids and by decreasing the size of nanoparticles. They observed the decrease in heat transfer coefficient of nanofluids with the increase of the size of nanoparticles and decrease in the temperature of nanofluids. Tzou [35, 36] investigated the onset of convective instability of nanofluids using Buongiorno’s model analytically and established that nanofluids exhibit much lower stability than regular fluids. The results depict the inverse relationship of density and heat capacity of nanoparticles with their thermal conductivity and the shape factor. The results also include that the heat transfer coefficient of nanofluid is enhanced relative to volume fraction of nanoparticles. Nield and Kuznetsov [37] reconsidered the instability problem for nanofluids to get the expression for Rayleigh number and found conditions for the existence of oscillatory convection. It was established that the buoyancy coupled with the conservation of nanoparticles lead to higher instability of nanofluids. Alloui et al. [38] considered the shallow cavity to study Rayleigh Bénard instability for nanofluids. They concluded that rate of heat transfer in nanofluids depends on the strength of convection and volume fraction of nanoparticles while the presence of nanoparticles increase the stability of the system. Thermal instability for a horizontal nanofluid layer was considered by Yadav et al. [39]. They found an expression of thermal Rayleigh number and observed that the temperature gradient delays the convective motions while volumetric fraction of nanoparticles and the ratio of the density of nanoparticles to that of base fluid have destabilizing impact on the layer. The joint behaviour of nano-effects (Brownian motion and thermophoresis) creates destabilizing effect and can reduce the values of critical Rayleigh number as compared to that of regular fluids.
3. Conservation equations for a nanofluid layer
We start this section with the description of Boussinesq approximation which is used to write the conservation equations of nanofluids in simplified form.
As is the case of regular fluid [32], equations of nanofluids are difficult to solve because of their non-linear character. Therefore some mathematical approximations are to be used to simplify the basic equations without violating the physical laws. The contribution of Boussinesq [40] in the solution of thermal instability problems is in the form of approximations which is after his name. This approximation has been used by a many researchers for solving different problems of fluids. Boussinesq suggested that inertial effects of density variations can be neglected as compared to its gravitational effects as such situations exist in the domain of meteorology and oceanography. So, density is assumed to be constant everywhere in the equations of motion except in the term with external force. Therefore, we change ρ01+αT0−T by ρ0 everywhere in the equations of motion except the term representing the external body force.
Anoop et al. [41] explained various experimental techniques using which nanoparticles can be suspended in the base fluid and that suspension remain stable for several weeks. Buongiorno [6] adopted the formalism of Bird et al. [42] and Chandrasekhar [32] to write conservation equations for nanofluids by considering nanoscale effects; Brownian diffusion and thermophoresis. A model for convective transport in regular fluids was reformulated for nanofluids to accommodate these nanoscale effects as follows.
The random motion of nanoparticles is called Brownian motion and results into the continuous collisions with the base fluid molecules. The Brownian diffusion coefficient due to Brownian motion is given by
DB=kBT3πμdp,E1
where dp is the nanoparticle’s diameter, kB is the Boltzmann’s constant and μ is the viscosity of the fluid. The nanoparticles mass flux due to Brownian diffusion, jp,B is given as
jp,B=−ρpDB∇ϕ,E2
where ϕ is the nanoparticle volume fraction and ρp is the nanoparticle mass density.
Thermophoresis is the phenomenon in which particles diffuse due to temperature gradient and the effect is similar to one of well-known effects of solute; Soret effect. The thermophoretic velocity is defined as.
VT=−β˜μρ∇TTwhereβ˜=0.26k2k+kp.E3
Here, ρ is the overall density of the nanofluid, k and kp are the thermal conductivities of the fluid and the particle material, respectively. The negative sign in thermophoretic velocity represents movement of particles down the temperature gradient (from hot to cold). The nanoparticle mass flux due to thermophoresis, jp,T is given as.
jp,T=−ρpϕVT=−ρpDT∇TTwithDT=β˜μρϕ,E4
where DT represents the thermophoretic diffusion coefficient.
The nanoparticles mass flux due to Brownian diffusion (Eq. (1)) and thermophoresis (Eq. (4)) are used to develop a two-component model for convective transport in nanofluids with the following assumptions:
The nanofluid flow is incompressible.
There are no chemical reactions in the fluid layer.
The external forces are negligible.
The mixture is dilute with nanoparticle volume fraction less than 1%.
The viscous dissipation is negligible in the fluid.
The radiative heat transfer is negligible.
The nanoparticles and base fluid are locally in thermal equilibrium.
The seven equations based on basic conservation laws with the above mentioned assumptions are given as follows.
Equation of state (one).
Equation of continuity (one).
Equation of nanoparticles (one).
Equations of motion (three).
Equation of energy (one).
3.1 Equation of state
Variables of state depend only upon the state of a system. The physical quantities: p; the pressure, T; the temperature and ρ; the density are the variables of state. We have three thermodynamic variables and a relation between them is given as.
FpρT=0,E5
For substances with which we shall be principally concerned, the equation of state can be written as
ρ=ρ01+αT0−T,E6
where T0 is the temperature at which ρ = ρ0.
3.2 Equation of continuity-conservation of mass
The equation of continuity for nanofluids is
∂ρ∂t+uj∂ρ∂xj=−ρ∂uj∂xj,E7
where uj is the jth component of nanofluid’s velocity.
For an incompressible flow (using equation of state)
and in vector form continuity equation for nanofluid is expressed as
∇.v=0.E10
3.3 Equation of nanoparticles-conservation of mass
The conservation equation for nanoparticles in absence of chemical reactions is
∂ϕ∂t+v.∇ϕ=−1ρp∇.jp,E11
where t is the time, ϕ is the nanoparticles volume fraction and jp is the diffusion mass flux for nanoparticles and as external forces are negligible jp, the sum of two diffusion terms (Brownian diffusion and thermophoresis) using Eqs. (1) and (4) can be written as
jp=jp,B+jp,T=−ρpDB∇ϕ−ρpDT∇TT,E12
Combining Eqs. (11) and (12), nanoparticles conservation equation becomes
∂ϕ∂t+v.∇ϕ=∇.DB∇ϕ+DT∇TT.E13
Eq. (13) reveals that the nanoparticles move consistently with fluid (second term of left-hand side) and possess velocity relative to fluid (right-hand side) due to Brownian diffusion and thermophoresis.
3.4 Equations of motion-conservation of momentum
The equation of motion is derived from Newton’s second law of motion which states that
Rate of change of linear momentum=Total force.
The momentum equation for nanofluid with negligible external forces is
ρ0∂v∂t+v.∇v=−∇p+μ∇2v+ρg,E14
where ρ0 is the nanofluid density at the reference temperature T0 and the overall density of nanofluid; written as
Note that in the absence of nanoparticles, Eq. (16) reduces to momentum equation for regular fluid.
3.5 Equation of energy-conservation of energy
The thermal energy equation for nanofluid with the assumptions (i)–(v) is
ρc∂T∂t+v.∇T=−∇.q+hp∇.jp,E17
where c and hp are the specific heat of fluid (at constant pressure) and the specific enthalpy of nanoparticles, respectively and q is the energy flux, neglecting radiative heat transfer, the sum of heat fluxes due to conduction and nanoparticle diffusion, written as
with assumption of negligible external forces ∇hp=cp∇T. Substituting Eq. (12) in Eq. (19); gives final form of thermal energy equation as
ρc∂T∂t+v.∇T=k∇2T+ρcpDB∇ϕ.∇T+DT∇T.∇TT.E20
Note that if jp is zero, Eq.(19) and hence Eq. (20) reduces to the familiar energy equation for regular fluid and therefore last two terms on right-hand side truly account for contributions of nanoparticle motion relative to fluid. Eq. (20) establishes that the transport of heat in nanofluids is possible by convection (second term on left-hand side), by conduction (first term on right-hand side), and also by virtue of nanoparticle diffusion (second and third terms on right-hand side).
Thus, Eqs. (10), (13), (16), (20) constitute the convective transport model for nanofluids which further can be solved for different parameters once the initial and boundary conditions are known. It is interesting to note that all the equations are strongly coupled meaning thereby that the one parameter depends on various other parameters.
Let us introduce non-dimensional variables to get the expression for thermal Rayleigh number as.
At the initial state, it is assumed that nanoparticle volume fraction is constant and fluid layer is still while temperature and pressure vary in horizontal direction. We get initial solution of Eqs. (22)–(25) using the fact that thermal diffusivity is very large as compared to Brownian diffusion coefficient (refer Buongiorno [1]) as
vi=0,ϕi=1,Ti=1−zE26
Let us add perturbations to initial solution and write
For non-oscillatory motions s=0, this gives the expression for RA from Eq. (39) as
RA=J3α2−DTρp−ρT1−T0gd3DBμαfT0.E40
where DB=kBT3πμdp and DT=β˜μρϕ with β˜=0.26k2k+kp as given by Nield and Kuznetsov [35].
Also
RA=J3α2−ρp−ρ2k+kpA;E41
where A depends on the base fluid properties.
7. Discussions on analytical results using various metallic/non-metallic nanoparticles
Table 2 shows the ratios of density to conductivity of various metallic/non-metallic nanoparticles and density 997.1 and conductivity 0.613 of water is used.
Physical properties
Al
Cu
Ag
Fe
Al2O3
SiO2
CuO
TiO2
ρKg/m3
2700
9000
10,500
7900
3970
2600
6510
4250
kW/mK
237
401
429
80
40
10.4
18
8.9
ρp/kp
11.3
22.4
24.47
98.7
99.25
250
361.6
477.5
Table 2.
Ratios of density to conductivity of metallic and non-metallic nanoparticles.
It is observed that ratio of density to conductivity is accountable for hastening the onset of convection in the system. The ratio is more for non-metals than metals establishes the lesser stability of non-metallic nanoparticles than metals. Alumina is most stable and titanium oxide is least stable among the nanoparticles under consideration. Density is found to be more influential than conductivity towards deciding the onset of convection in the layer.
8. Conclusions
Tremendous applications of nanofluids in pharmaceutical industry with respect to drug invention and cancer imaging motivated the scientists to study convection currents in fluid layer mathematically as well as experimentally. In the present work, the onset of instability in layer is studied under small temperature difference with the help of equations based on conservation laws. The expression of non-dimensional number Rayleigh number is found analytically which decides the instability of the system. Approximations are made whenever needed without violating the necessary physics to get the useful results. Analysis reveals that lesser the ratio of density to conductivity, higher is the stability of the layer. It is found that convection currents majorly depends on density and conductivity and precisely concluding density is more pronounced property than conductivity of nanoparticles. Metallic oxides make the system more stable than metallic nanoparticles in the fluid.
\n',keywords:"nanofluids, natural convection, conservation equations, metallic and non-metallic nanoparticles",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/70066.pdf",chapterXML:"https://mts.intechopen.com/source/xml/70066.xml",downloadPdfUrl:"/chapter/pdf-download/70066",previewPdfUrl:"/chapter/pdf-preview/70066",totalDownloads:740,totalViews:0,totalCrossrefCites:1,dateSubmitted:"May 6th 2019",dateReviewed:"July 29th 2019",datePrePublished:"November 17th 2019",datePublished:"July 8th 2020",dateFinished:"November 17th 2019",readingETA:"0",abstract:"Nanobiotechnology has huge number of applications in medical science thereby improving health care practices. Keeping in mind the applications of nanoparticles and the convection patterns in biological fields, behaviour of nanofluids is explored for small temperature difference in the layer. The flow of nanofluids is usually described by system of differential equations. A mathematical model for the system based on conservation laws of mass, momentum and energy is formed. To get the insight of the problem, complex equations are simplified wherever needed to get interesting results without violating the necessary physics. The influence of physical properties such as density and conductivity of metallic/non-metallic nanoparticles is examined on the onset of convection currents in the fluid layer.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/70066",risUrl:"/chapter/ris/70066",signatures:"Jyoti Sharma and Urvashi Gupta",book:{id:"9012",type:"book",title:"Applications of Nanobiotechnology",subtitle:null,fullTitle:"Applications of Nanobiotechnology",slug:"applications-of-nanobiotechnology",publishedDate:"July 8th 2020",bookSignature:"Margarita Stoytcheva and Roumen Zlatev",coverURL:"https://cdn.intechopen.com/books/images_new/9012.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",isbn:"978-1-78985-978-2",printIsbn:"978-1-78985-977-5",pdfIsbn:"978-1-83880-997-3",isAvailableForWebshopOrdering:!0,editors:[{id:"170080",title:"Dr.",name:"Margarita",middleName:null,surname:"Stoytcheva",slug:"margarita-stoytcheva",fullName:"Margarita Stoytcheva"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Instability of fluids under small temperature gradient: Rayleigh Bênard convection",level:"1"},{id:"sec_3",title:"3. Conservation equations for a nanofluid layer",level:"1"},{id:"sec_3_2",title:"3.1 Equation of state",level:"2"},{id:"sec_4_2",title:"3.2 Equation of continuity-conservation of mass",level:"2"},{id:"sec_5_2",title:"3.3 Equation of nanoparticles-conservation of mass",level:"2"},{id:"sec_6_2",title:"3.4 Equations of motion-conservation of momentum",level:"2"},{id:"sec_7_2",title:"3.5 Equation of energy-conservation of energy",level:"2"},{id:"sec_9",title:"4. Initial and perturbed flow",level:"1"},{id:"sec_10",title:"5. Method of normal modes",level:"1"},{id:"sec_11",title:"6. Results and discussion",level:"1"},{id:"sec_11_2",title:"6.1 Stationary convection",level:"2"},{id:"sec_13",title:"7. Discussions on analytical results using various metallic/non-metallic nanoparticles",level:"1"},{id:"sec_14",title:"8. Conclusions",level:"1"}],chapterReferences:[{id:"B1",body:'Maxwell JC. Electricity and Magnetism. Oxford, UK: Clarendon Press; 1873'},{id:"B2",body:'Choi S. Enhancing thermal conductivity of fluids with nanoparticles. In: Siginer DA, Wang HP, editors. Development and Applications of Non-Newtonian Flows. FED- 231/MD-Vol. 66. New York; The American Society of Mechanical Engineers (ASME); 1995. pp. 99-105'},{id:"B3",body:'Masuda H, Ebata A, Teramae K, Hishinuma N. Alteration of thermal conductivity and viscosity of liquid by dispersing ultra fine particles. Netsu Bussei. 1993;7:227-233'},{id:"B4",body:'Eastman JA, Choi SUS, Li S, Yu W, Thompson LJ. Anomalously increased effective thermal conductivities of ethylene glycol-based nanofluids containing copper nanoparticles. Applied Physics Letters. 2001;78:718-720'},{id:"B5",body:'Das SK, Putra N, Thiesen P, Roetzel W. Temperature dependence of thermal conductivity enhancement for nanofluids. 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International Journal of Heat and Mass Transfer. 2009;52:2189-2195'},{id:"B42",body:'Byron Bird R, Stewart WE, Lightfoot EN. Transport Phenomena. New York: Wiley; 1960'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Jyoti Sharma",address:"jyoti.maths@gmail.com",affiliation:'
Dr. S. S. Bhatnagar University Institute of Chemical Engineering and Technology, Panjab University, India
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The Open Access model is applied to all of our publications and is designed to eliminate subscriptions and pay-per-view fees. This approach ensures free, immediate access to full text versions of your research.
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Open Access Funding
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For Authors who are still unable to obtain funding from their institutions or research funding bodies for individual projects, IntechOpen does offer the possibility of applying for a Waiver to offset some or all processing feed. Details regarding our Waiver Policy can be found here.
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The Open Access Publishing Fee (OAPF) is payable only after your book chapter, monograph or journal article is accepted for publication.
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*These prices do not include Value-Added Tax (VAT). Residents of European Union countries need to add VAT based on the specific rate in their country of residence. Institutions and companies registered as VAT taxable entities in their own EU member state will not pay VAT as long as provision of the VAT registration number is made during the application process. This is made possible by the EU reverse charge method.
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Services included are:
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English language copyediting and proofreading, including the correction of grammatical, spelling, and other common errors
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XML Typesetting and pagination - web (PDF, HTML) and print files preparation
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Permanent and unrestricted online access to your work
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If a manuscript requires Heavy Editing or Language Polishing, this will incur additional fees.
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Your Author Service Manager will inform you of any items not covered by the OAPF and provide exact information regarding those additional costs before proceeding.
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Open Access Funding
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To explore funding opportunities and learn more about how you can finance your IntechOpen publication, go to our Open Access Funding page. IntechOpen offers expert assistance to all of its Authors. We can support you in approaching funding bodies and institutions in relation to publishing fees by providing information about compliance with the Open Access policies of your funder or institution. We can also assist with communicating the benefits of Open Access in order to support and strengthen your funding request and provide personal guidance through your application process. You can contact us at funders@intechopen.com for further details or assistance.
\n\n
For Authors who are still unable to obtain funding from their institutions or research funding bodies for individual projects, IntechOpen does offer the possibility of applying for a Waiver to offset some or all processing feed. Details regarding our Waiver Policy can be found here.
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Added Value of Publishing with IntechOpen
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Choosing to publish with IntechOpen ensures the following benefits:
\n\n
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Indexing and listing across major repositories, see details ...
\n\t
Long-term archiving
\n\t
Visibility on the world's strongest OA platform
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Live Performance Metrics to track readership and the impact of your chapter
\n\t
Dissemination and Promotion
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Benefits of Publishing with IntechOpen
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Proven world leader in Open Access book publishing with over 10 years experience
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+5,700 OA books published
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Most competitive prices in the market
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Fully compliant with OA funding requirements
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Optimized processes that assure your research is made available to the scientific community without delay
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Personal support during every step of the publication process
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+184,650 citations in Web of Science databases
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Currently strongest OA platform with over 175 million downloads
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Kounis",coverURL:"https://cdn.intechopen.com/books/images_new/5486.jpg",editedByType:"Edited by",editors:[{id:"111582",title:"Dr.",name:"Leo",middleName:"Dimitrios",surname:"Kounis",slug:"leo-kounis",fullName:"Leo Kounis"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],booksByTopicTotal:1,seriesByTopicCollection:[],seriesByTopicTotal:0,mostCitedChapters:[{id:"53099",doi:"10.5772/66222",title:"Improving Quality Assurance in Multidisciplinary Engineering Environments with Semantic Technologies",slug:"improving-quality-assurance-in-multidisciplinary-engineering-environments-with-semantic-technologies",totalDownloads:1572,totalCrossrefCites:4,totalDimensionsCites:8,abstract:"In multidisciplinary engineering (MDE) projects, for example, automation systems or manufacturing systems, stakeholders from various disciplines, for example, electrics, mechanics and software, have to collaborate. In industry practice, engineers apply individual and highly specialized tools with strong limitation regarding defect detection in early engineering phases. Experts typically execute reviews with limited tool support which make engineering projects defective and risky. Semantic Web Technologies (SWTs) can help to bridge the gap between heterogeneous sources as foundation for efficient and effective defect detection. Main questions focus on (a) how to bridge gaps between loosely coupled tools and incompatible data models and (b) how SWTs can help to support efficient and effective defect detection in context of engineering process improvement. This chapter describes success-critical requirements for defect detection in MDE and shows how SWTs can provide the foundation for early and efficient defect detection with an adapted review approach. The proposed defect detection framework (DDF) suggests different levels of SWT contributions as a roadmap for engineering process improvement. Two selected industry-related real-life cases show different levels of SWT involvement. Although SWTs have been successfully applied in real-life use cases, SWT applications can be risky if applied without good understanding of success factors and limitations.",book:{id:"5486",slug:"quality-control-and-assurance-an-ancient-greek-term-re-mastered",title:"Quality Control and Assurance",fullTitle:"Quality Control and Assurance - An Ancient Greek Term Re-Mastered"},signatures:"Dietmar Winkler, Marta Sabou and Stefan Biffl",authors:[{id:"95798",title:"Dr.",name:"Dietmar",middleName:null,surname:"Winkler",slug:"dietmar-winkler",fullName:"Dietmar Winkler"},{id:"135962",title:"Prof.",name:"Stefan",middleName:null,surname:"Biffl",slug:"stefan-biffl",fullName:"Stefan Biffl"},{id:"196030",title:"Dr.",name:"Marta",middleName:null,surname:"Sabou",slug:"marta-sabou",fullName:"Marta Sabou"}]},{id:"53946",doi:"10.5772/67211",title:"The Evolution of Quality Concepts and the Related Quality Management",slug:"the-evolution-of-quality-concepts-and-the-related-quality-management",totalDownloads:4438,totalCrossrefCites:5,totalDimensionsCites:6,abstract:"Enterprises usually adopt some quality practices to control the product quality during the manufacturing process in order to assure the delivery of qualitative good products to customers. The quality practices or quality management systems adopted by industries will further evolve due to the changes of quality concepts as time goes by. This chapter discusses the change of quality concepts and the related revolution of quality management systems in the past century. The quality concepts were gradually changed from the achievement of quality standards, satisfaction of customer needs, and expectations to customer delight. Since merely satisfying customers is not enough to ensure customer loyalty, the enterprises gradually focus on customers’ emotional responses and their delight in order to pursue their loyalty. The emotion of “delight” is composed of “joy” and “surprise,” which can be achieved as the customers’ latent requirements are satisfied. Thus, the concept of “customer delight” and the means to provide the innovative quality so as to meet the unsatisfied customers’ latent needs are elaborated on. Finally, a framework of innovation creation is developed that is based on the mining of customer's latent requirements. This outline will manifest the essential elements of the related operation steps.",book:{id:"5486",slug:"quality-control-and-assurance-an-ancient-greek-term-re-mastered",title:"Quality Control and Assurance",fullTitle:"Quality Control and Assurance - An Ancient Greek Term Re-Mastered"},signatures:"Ching-Chow Yang",authors:[{id:"11862",title:"Prof.",name:"Ching-Chow",middleName:null,surname:"Yang",slug:"ching-chow-yang",fullName:"Ching-Chow Yang"}]},{id:"53267",doi:"10.5772/65847",title:"Exploring the Relationship of Supply Chain Risk Management to Quality Management",slug:"exploring-the-relationship-of-supply-chain-risk-management-to-quality-management",totalDownloads:1551,totalCrossrefCites:5,totalDimensionsCites:5,abstract:"This research explores the relationship between an organization's supply chain risk management (SCRM) maturity and quality maturity. SCRM maturity was measured using a survey questionnaire sent to organizations in the USA. Quality maturity was assessed via ISO 9001:2008 certification status as well as through a survey questionnaire of total quality management (TQM) practices for organizations in the USA. The results suggest that ISO 9001:2008 is not related to SCRM maturity, while TQM maturity is related to SCRM maturity. Organizations with more mature TQM programs appear to also have more mature SCRM programs.",book:{id:"5486",slug:"quality-control-and-assurance-an-ancient-greek-term-re-mastered",title:"Quality Control and Assurance",fullTitle:"Quality Control and Assurance - An Ancient Greek Term Re-Mastered"},signatures:"Tyler Florio",authors:[{id:"195084",title:"Mr.",name:"Tyler",middleName:null,surname:"Florio",slug:"tyler-florio",fullName:"Tyler Florio"}]},{id:"53019",doi:"10.5772/66199",title:"A Framework to Manage Quality of Enterprise Content Management Systems",slug:"a-framework-to-manage-quality-of-enterprise-content-management-systems",totalDownloads:1407,totalCrossrefCites:0,totalDimensionsCites:3,abstract:"There is a wide range of enterprise content management (ECM) systems which supports, among other things, document management processes, records management and Web content management. However, each of these systems has many features and some of them can meet organizational needs depending on the scale, sector and workflow of the organization. In addition, it is very common that organizations are unaware of what ECM system best fits their needs, since each company has its particular scope and strategic objectives. This chapter is contextualized within the real project called THOT designed for the Andalusian Public Administration in Spain. The aim of this project is to study in detail ECM systems and propose an objective method to compare them for the specific scope and strategic objective of organizations. Quality evaluation framework (QuEF) has been adapted for this purpose.",book:{id:"5486",slug:"quality-control-and-assurance-an-ancient-greek-term-re-mastered",title:"Quality Control and Assurance",fullTitle:"Quality Control and Assurance - An Ancient Greek Term Re-Mastered"},signatures:"José González Enríquez, Francisco José Domínguez Mayo, Julián\nAlberto García García, María José Escalona Cuaresma and Manuel\nMejías Risoto",authors:[{id:"104846",title:"Dr.",name:"Maria",middleName:"Jose",surname:"Escalona",slug:"maria-escalona",fullName:"Maria Escalona"},{id:"191332",title:"Ph.D.",name:"José",middleName:null,surname:"González",slug:"jose-gonzalez",fullName:"José González"},{id:"191493",title:"Dr.",name:"F.J.",middleName:null,surname:"Domínguez-Mayo",slug:"f.j.-dominguez-mayo",fullName:"F.J. Domínguez-Mayo"},{id:"191494",title:"Dr.",name:"J.A.",middleName:null,surname:"García-García",slug:"j.a.-garcia-garcia",fullName:"J.A. García-García"},{id:"195075",title:"Dr.",name:"M.",middleName:null,surname:"Mejías",slug:"m.-mejias",fullName:"M. Mejías"}]},{id:"53522",doi:"10.5772/66360",title:"The Use of Control Charts in the Study of Bitcoin’s Price Variability",slug:"the-use-of-control-charts-in-the-study-of-bitcoin-s-price-variability",totalDownloads:1648,totalCrossrefCites:0,totalDimensionsCites:2,abstract:"The focus of this research is bitcoin’s variability and its comparison with the variability of the EURO/USD exchange rate. Virtual currencies have been evolving in a dynamic way in the last few years. Under 600 different virtual currencies, the most successful was bitcoin. Its adherents saw in it an alternative to the traditional means of payments allowing the performance of real-time transactions at low costs. The accessibility, where no financial infrastructure is ensured or where either limited or no international agreements exist between financial and banking institutions was also an advantage. The opponents perceived this as a temporary curiosity with no future. Time confirmed that bitcoin has gained on popularity and the exchange rate to the main currencies rose in a dynamic way. The analysts, however, underline that the bitcoin is too volatile and unpredictable, so it cannot compete against the main currencies. The aim of this research is to compare the bitcoin (BTC) to US Dollar (USD) exchange rate and Euro to USD exchange rate volatility using control charts. The results have shown that BTC/USD exchange rate volatility is strongly affected by unexpected price jumps during the period (2010–2016), an act that significantly distinguishes it from more stable and predictable EUR/USD exchange rate variability.",book:{id:"5486",slug:"quality-control-and-assurance-an-ancient-greek-term-re-mastered",title:"Quality Control and Assurance",fullTitle:"Quality Control and Assurance - An Ancient Greek Term Re-Mastered"},signatures:"Beata Szetela",authors:[{id:"190806",title:"Ph.D. Student",name:"Beata",middleName:null,surname:"Szetela",slug:"beata-szetela",fullName:"Beata Szetela"}]}],mostDownloadedChaptersLast30Days:[{id:"53024",title:"Key Aspects for Implementing ISO/IEC 17025 Quality Management Systems at Materials Science Laboratories",slug:"key-aspects-for-implementing-iso-iec-17025-quality-management-systems-at-materials-science-laborator",totalDownloads:2823,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"Implementing a quality management system based on the requirements specified in ISO/IEC 17025 standard at materials science laboratories is challenging, mainly due to two main factors: (i) the high technical complexity degree of some tests used for materials characterization and (ii) the fact that most materials science laboratories provide materials characterization tests and also carry out research and development activities. In this context, this chapter presents key subjects while implementing a quality management system at materials science laboratories and some considerations on strategies for effectively implementing such systems.",book:{id:"5486",slug:"quality-control-and-assurance-an-ancient-greek-term-re-mastered",title:"Quality Control and Assurance",fullTitle:"Quality Control and Assurance - An Ancient Greek Term Re-Mastered"},signatures:"Rodrigo S. Neves, Daniel P. Da Silva, Carlos E. C. Galhardo, Erlon H.\nM. Ferreira, Rafael M. Trommer and Jailton C. Damasceno",authors:[{id:"20571",title:"Prof.",name:"Erlon H.",middleName:null,surname:"Martins Ferreira",slug:"erlon-h.-martins-ferreira",fullName:"Erlon H. Martins Ferreira"},{id:"145815",title:"Dr.",name:"Rodrigo",middleName:null,surname:"De Santis Neves",slug:"rodrigo-de-santis-neves",fullName:"Rodrigo De Santis Neves"},{id:"145816",title:"Dr.",name:"Carlos",middleName:null,surname:"Eduardo Cardoso Galhardo",slug:"carlos-eduardo-cardoso-galhardo",fullName:"Carlos Eduardo Cardoso Galhardo"},{id:"159056",title:"Dr.",name:"Jailton",middleName:null,surname:"Damasceno",slug:"jailton-damasceno",fullName:"Jailton Damasceno"},{id:"191863",title:"Dr.",name:"Daniel",middleName:"Pereira Da Silva",surname:"Fernandes",slug:"daniel-fernandes",fullName:"Daniel Fernandes"},{id:"191865",title:"Dr.",name:"Rafael",middleName:null,surname:"Mello Trommer",slug:"rafael-mello-trommer",fullName:"Rafael Mello Trommer"}]},{id:"53946",title:"The Evolution of Quality Concepts and the Related Quality Management",slug:"the-evolution-of-quality-concepts-and-the-related-quality-management",totalDownloads:4438,totalCrossrefCites:5,totalDimensionsCites:6,abstract:"Enterprises usually adopt some quality practices to control the product quality during the manufacturing process in order to assure the delivery of qualitative good products to customers. The quality practices or quality management systems adopted by industries will further evolve due to the changes of quality concepts as time goes by. This chapter discusses the change of quality concepts and the related revolution of quality management systems in the past century. The quality concepts were gradually changed from the achievement of quality standards, satisfaction of customer needs, and expectations to customer delight. Since merely satisfying customers is not enough to ensure customer loyalty, the enterprises gradually focus on customers’ emotional responses and their delight in order to pursue their loyalty. The emotion of “delight” is composed of “joy” and “surprise,” which can be achieved as the customers’ latent requirements are satisfied. Thus, the concept of “customer delight” and the means to provide the innovative quality so as to meet the unsatisfied customers’ latent needs are elaborated on. Finally, a framework of innovation creation is developed that is based on the mining of customer's latent requirements. This outline will manifest the essential elements of the related operation steps.",book:{id:"5486",slug:"quality-control-and-assurance-an-ancient-greek-term-re-mastered",title:"Quality Control and Assurance",fullTitle:"Quality Control and Assurance - An Ancient Greek Term Re-Mastered"},signatures:"Ching-Chow Yang",authors:[{id:"11862",title:"Prof.",name:"Ching-Chow",middleName:null,surname:"Yang",slug:"ching-chow-yang",fullName:"Ching-Chow Yang"}]},{id:"53144",title:"Youden Two-Sample Method",slug:"youden-two-sample-method",totalDownloads:2418,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"The results obtained when testing materials, equipment and procedures are not generally identical. Factors that influence the magnitude of the results are not fully controllable. As such, the interpretation and analysis of results must take into account the variations caused by numerous and random unavoidable causes. Intercomparison exercises are considered of being of importance, as they do allow the examination of the analytical process and their generated results. Youden plot is particularly aimed at interlaboratory comparisons. The raw results provided by the participating laboratories are treated by a statistical method applied by the centre performing the trial. In order to materialize this, two similar materials with small differences in the concentration of the characteristics are required. The advantage of Youden analysis is its ability to separate the random errors with a minimum effort by participants in the design from the point of view of the analytical requirement. This book chapter illustrates the method that has been applied to elaborate on data covering a diverse scientific field: polyunsaturated fatty acids in fat and oils, total blood cholesterol and aspirin in pharmaceutical preparations. Finally, liquid chromatography with tandem mass spectrometry detector has been applied to the determination of an emerging contaminant, methylparaben (MeP), in surface waters.",book:{id:"5486",slug:"quality-control-and-assurance-an-ancient-greek-term-re-mastered",title:"Quality Control and Assurance",fullTitle:"Quality Control and Assurance - An Ancient Greek Term Re-Mastered"},signatures:"Julia Martín, Nieves Velázquez and Agustin G. Asuero",authors:[{id:"190870",title:"Dr.",name:"Agustín G.",middleName:null,surname:"Asuero",slug:"agustin-g.-asuero",fullName:"Agustín G. 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This chapter presents survey results from 2000 in three sites of Armenia (Gyumri, Gavar and Goris) using LQAS principles (i.e., 44%, 95% CI: ±6% of women had an induced abortion in their lifetime, a total abortion rate (TAR) of 2.0 abortions per woman). Modern contraceptive use was lowest in Goris (16%. 95% CI: ±7%) and highest in Gyumri (43%, 95% CI: ±11%). Only 37% (95% CI: ±9%) of women with an induced abortion received family planning information and 21% (95% CI: ±4%) of mothers were counselled about family planning after delivery. While limited access to family planning information and contraceptives is still an issue in Armenia, recently new reproductive health priorities—such as infertility, sex-selective abortions and abortions due to socio-economic difficulties—have become more common and can be investigated using LQAS in both community surveys and health facility assessments. This study demonstrates that measuring national abortion prevalence and access to services mask underlying variations; the awareness of which is essential for health program planning.",book:{id:"5486",slug:"quality-control-and-assurance-an-ancient-greek-term-re-mastered",title:"Quality Control and Assurance",fullTitle:"Quality Control and Assurance - An Ancient Greek Term Re-Mastered"},signatures:"Joseph J. Valadez and Lusine Mirzoyan",authors:[{id:"191876",title:"Prof.",name:"Joseph",middleName:null,surname:"Valadez",slug:"joseph-valadez",fullName:"Joseph Valadez"},{id:"195035",title:"Dr.",name:"Lusine",middleName:null,surname:"Mirzoyan",slug:"lusine-mirzoyan",fullName:"Lusine Mirzoyan"}]},{id:"53267",title:"Exploring the Relationship of Supply Chain Risk Management to Quality Management",slug:"exploring-the-relationship-of-supply-chain-risk-management-to-quality-management",totalDownloads:1551,totalCrossrefCites:5,totalDimensionsCites:5,abstract:"This research explores the relationship between an organization's supply chain risk management (SCRM) maturity and quality maturity. SCRM maturity was measured using a survey questionnaire sent to organizations in the USA. Quality maturity was assessed via ISO 9001:2008 certification status as well as through a survey questionnaire of total quality management (TQM) practices for organizations in the USA. The results suggest that ISO 9001:2008 is not related to SCRM maturity, while TQM maturity is related to SCRM maturity. Organizations with more mature TQM programs appear to also have more mature SCRM programs.",book:{id:"5486",slug:"quality-control-and-assurance-an-ancient-greek-term-re-mastered",title:"Quality Control and Assurance",fullTitle:"Quality Control and Assurance - An Ancient Greek Term Re-Mastered"},signatures:"Tyler Florio",authors:[{id:"195084",title:"Mr.",name:"Tyler",middleName:null,surname:"Florio",slug:"tyler-florio",fullName:"Tyler Florio"}]}],onlineFirstChaptersFilter:{topicId:"730",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:318,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:106,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:15,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"13",title:"Veterinary Medicine and Science",doi:"10.5772/intechopen.73681",issn:"2632-0517",scope:"Paralleling similar advances in the medical field, astounding advances occurred in Veterinary Medicine and Science in recent decades. These advances have helped foster better support for animal health, more humane animal production, and a better understanding of the physiology of endangered species to improve the assisted reproductive technologies or the pathogenesis of certain diseases, where animals can be used as models for human diseases (like cancer, degenerative diseases or fertility), and even as a guarantee of public health. Bridging Human, Animal, and Environmental health, the holistic and integrative “One Health” concept intimately associates the developments within those fields, projecting its advancements into practice. This book series aims to tackle various animal-related medicine and sciences fields, providing thematic volumes consisting of high-quality significant research directed to researchers and postgraduates. It aims to give us a glimpse into the new accomplishments in the Veterinary Medicine and Science field. By addressing hot topics in veterinary sciences, we aim to gather authoritative texts within each issue of this series, providing in-depth overviews and analysis for graduates, academics, and practitioners and foreseeing a deeper understanding of the subject. Forthcoming texts, written and edited by experienced researchers from both industry and academia, will also discuss scientific challenges faced today in Veterinary Medicine and Science. In brief, we hope that books in this series will provide accessible references for those interested or working in this field and encourage learning in a range of different topics.",coverUrl:"https://cdn.intechopen.com/series/covers/13.jpg",latestPublicationDate:"June 29th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:11,editor:{id:"38652",title:"Prof.",name:"Rita",middleName:null,surname:"Payan-Carreira",slug:"rita-payan-carreira",fullName:"Rita Payan-Carreira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRiFPQA0/Profile_Picture_1614601496313",biography:"Rita Payan Carreira earned her Veterinary Degree from the Faculty of Veterinary Medicine in Lisbon, Portugal, in 1985. She obtained her Ph.D. in Veterinary Sciences from the University of Trás-os-Montes e Alto Douro, Portugal. After almost 32 years of teaching at the University of Trás-os-Montes and Alto Douro, she recently moved to the University of Évora, Department of Veterinary Medicine, where she teaches in the field of Animal Reproduction and Clinics. Her primary research areas include the molecular markers of the endometrial cycle and the embryo–maternal interaction, including oxidative stress and the reproductive physiology and disorders of sexual development, besides the molecular determinants of male and female fertility. She often supervises students preparing their master's or doctoral theses. She is also a frequent referee for various journals.",institutionString:null,institution:{name:"University of Évora",institutionURL:null,country:{name:"Portugal"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:6,paginationItems:[{id:"22",title:"Applied Intelligence",coverUrl:"https://cdn.intechopen.com/series_topics/covers/22.jpg",isOpenForSubmission:!0,editor:{id:"27170",title:"Prof.",name:"Carlos",middleName:"M.",surname:"Travieso-Gonzalez",slug:"carlos-travieso-gonzalez",fullName:"Carlos Travieso-Gonzalez",profilePictureURL:"https://mts.intechopen.com/storage/users/27170/images/system/27170.jpeg",biography:"Carlos M. Travieso-González received his MSc degree in Telecommunication Engineering at Polytechnic University of Catalonia (UPC), Spain in 1997, and his Ph.D. degree in 2002 at the University of Las Palmas de Gran Canaria (ULPGC-Spain). He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. He has been a member of the IASTED Technical Committee on Image Processing from 2007 and a member of the IASTED Technical Committee on Artificial Intelligence and Expert Systems from 2011. \n\nHe has held the general chair position for the following: ACM-APPIS (2020, 2021), IEEE-IWOBI (2019, 2020 and 2020), A PPIS (2018, 2019), IEEE-IWOBI (2014, 2015, 2017, 2018), InnoEducaTIC (2014, 2017), IEEE-INES (2013), NoLISP (2011), JRBP (2012), and IEEE-ICCST (2005)\n\nHe is an associate editor of the Computational Intelligence and Neuroscience Journal (Hindawi – Q2 JCR-ISI). He was vice dean from 2004 to 2010 in the Higher Technical School of Telecommunication Engineers at ULPGC and the vice dean of Graduate and Postgraduate Studies from March 2013 to November 2017. He won the “Catedra Telefonica” Awards in Modality of Knowledge Transfer, 2017, 2018, and 2019 editions, and awards in Modality of COVID Research in 2020.\n\nPublic References:\nResearcher ID http://www.researcherid.com/rid/N-5967-2014\nORCID https://orcid.org/0000-0002-4621-2768 \nScopus Author ID https://www.scopus.com/authid/detail.uri?authorId=6602376272\nScholar Google https://scholar.google.es/citations?user=G1ks9nIAAAAJ&hl=en \nResearchGate https://www.researchgate.net/profile/Carlos_Travieso",institutionString:null,institution:{name:"University of Las Palmas de Gran Canaria",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"23",title:"Computational Neuroscience",coverUrl:"https://cdn.intechopen.com/series_topics/covers/23.jpg",isOpenForSubmission:!0,editor:{id:"14004",title:"Dr.",name:"Magnus",middleName:null,surname:"Johnsson",slug:"magnus-johnsson",fullName:"Magnus Johnsson",profilePictureURL:"https://mts.intechopen.com/storage/users/14004/images/system/14004.png",biography:"Dr Magnus Johnsson is a cross-disciplinary scientist, lecturer, scientific editor and AI/machine learning consultant from Sweden. \n\nHe is currently at Malmö University in Sweden, but also held positions at Lund University in Sweden and at Moscow Engineering Physics Institute. \nHe holds editorial positions at several international scientific journals and has served as a scientific editor for books and special journal issues. \nHis research interests are wide and include, but are not limited to, autonomous systems, computer modeling, artificial neural networks, artificial intelligence, cognitive neuroscience, cognitive robotics, cognitive architectures, cognitive aids and the philosophy of mind. \n\nDr. Johnsson has experience from working in the industry and he has a keen interest in the application of neural networks and artificial intelligence to fields like industry, finance, and medicine. \n\nWeb page: www.magnusjohnsson.se",institutionString:null,institution:{name:"Malmö University",institutionURL:null,country:{name:"Sweden"}}},editorTwo:null,editorThree:null},{id:"24",title:"Computer Vision",coverUrl:"https://cdn.intechopen.com/series_topics/covers/24.jpg",isOpenForSubmission:!0,editor:{id:"294154",title:"Prof.",name:"George",middleName:null,surname:"Papakostas",slug:"george-papakostas",fullName:"George Papakostas",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hYaGbQAK/Profile_Picture_1624519712088",biography:"George A. Papakostas has received a diploma in Electrical and Computer Engineering in 1999 and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering in 2002 and 2007, respectively, from the Democritus University of Thrace (DUTH), Greece. Dr. Papakostas serves as a Tenured Full Professor at the Department of Computer Science, International Hellenic University, Greece. Dr. Papakostas has 10 years of experience in large-scale systems design as a senior software engineer and technical manager, and 20 years of research experience in the field of Artificial Intelligence. Currently, he is the Head of the “Visual Computing” division of HUman-MAchines INteraction Laboratory (HUMAIN-Lab) and the Director of the MPhil program “Advanced Technologies in Informatics and Computers” hosted by the Department of Computer Science, International Hellenic University. He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. Dr Ventura also holds the positions of Affiliated Professor at Virginia Commonwealth University (Richmond, USA) and Distinguished Adjunct Professor at King Abdulaziz University (Jeddah, Saudi Arabia). Additionally, he is deputy director of the Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) and heads the Knowledge Discovery and Intelligent Systems Research Laboratory. He has published more than ten books and over 300 articles in journals and scientific conferences. Currently, his work has received over 18,000 citations according to Google Scholar, including more than 2200 citations in 2020. In the last five years, he has published more than 60 papers in international journals indexed in the JCR (around 70% of them belonging to first quartile journals) and he has edited some Springer books “Supervised Descriptive Pattern Mining” (2018), “Multiple Instance Learning - Foundations and Algorithms” (2016), and “Pattern Mining with Evolutionary Algorithms” (2016). He has also been involved in more than 20 research projects supported by the Spanish and Andalusian governments and the European Union. He currently belongs to the editorial board of PeerJ Computer Science, Information Fusion and Engineering Applications of Artificial Intelligence journals, being also associate editor of Applied Computational Intelligence and Soft Computing and IEEE Transactions on Cybernetics. Finally, he is editor-in-chief of Progress in Artificial Intelligence. He is a Senior Member of the IEEE Computer, the IEEE Computational Intelligence, and the IEEE Systems, Man, and Cybernetics Societies, and the Association of Computing Machinery (ACM). Finally, his main research interests include data science, computational intelligence, and their applications.",institutionString:null,institution:{name:"University of Córdoba",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"26",title:"Machine Learning and Data Mining",coverUrl:"https://cdn.intechopen.com/series_topics/covers/26.jpg",isOpenForSubmission:!0,editor:{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}},editorTwo:null,editorThree:null},{id:"27",title:"Multi-Agent Systems",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",isOpenForSubmission:!0,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:19,paginationItems:[{id:"82196",title:"Multi-Features Assisted Age Invariant Face Recognition and Retrieval Using CNN with Scale Invariant Heat Kernel Signature",doi:"10.5772/intechopen.104944",signatures:"Kamarajugadda Kishore Kumar and Movva Pavani",slug:"multi-features-assisted-age-invariant-face-recognition-and-retrieval-using-cnn-with-scale-invariant-",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"82063",title:"Evaluating Similarities and Differences between Machine Learning and Traditional Statistical Modeling in Healthcare Analytics",doi:"10.5772/intechopen.105116",signatures:"Michele Bennett, Ewa J. Kleczyk, Karin Hayes and Rajesh Mehta",slug:"evaluating-similarities-and-differences-between-machine-learning-and-traditional-statistical-modelin",totalDownloads:6,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Machine Learning and Data Mining - Annual Volume 2022",coverURL:"https://cdn.intechopen.com/books/images_new/11422.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"81791",title:"Self-Supervised Contrastive Representation Learning in Computer Vision",doi:"10.5772/intechopen.104785",signatures:"Yalin Bastanlar and Semih Orhan",slug:"self-supervised-contrastive-representation-learning-in-computer-vision",totalDownloads:28,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Pattern Recognition - New Insights",coverURL:"https://cdn.intechopen.com/books/images_new/11442.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}},{id:"79345",title:"Application of Jump Diffusion Models in Insurance Claim Estimation",doi:"10.5772/intechopen.99853",signatures:"Leonard Mushunje, Chiedza Elvina Mashiri, Edina Chandiwana and Maxwell Mashasha",slug:"application-of-jump-diffusion-models-in-insurance-claim-estimation-1",totalDownloads:8,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Data Clustering",coverURL:"https://cdn.intechopen.com/books/images_new/10820.jpg",subseries:{id:"26",title:"Machine Learning and Data Mining"}}}]},overviewPagePublishedBooks:{paginationCount:9,paginationItems:[{type:"book",id:"7723",title:"Artificial Intelligence",subtitle:"Applications in Medicine and Biology",coverURL:"https://cdn.intechopen.com/books/images_new/7723.jpg",slug:"artificial-intelligence-applications-in-medicine-and-biology",publishedDate:"July 31st 2019",editedByType:"Edited by",bookSignature:"Marco Antonio Aceves-Fernandez",hash:"a3852659e727f95c98c740ed98146011",volumeInSeries:1,fullTitle:"Artificial Intelligence - Applications in Medicine and Biology",editors:[{id:"24555",title:"Dr.",name:"Marco Antonio",middleName:null,surname:"Aceves Fernandez",slug:"marco-antonio-aceves-fernandez",fullName:"Marco Antonio Aceves Fernandez",profilePictureURL:"https://mts.intechopen.com/storage/users/24555/images/system/24555.jpg",biography:"Dr. Marco Antonio Aceves Fernandez obtained his B.Sc. (Eng.) in Telematics from the Universidad de Colima, Mexico. He obtained both his M.Sc. and Ph.D. from the University of Liverpool, England, in the field of Intelligent Systems. He is a full professor at the Universidad Autonoma de Queretaro, Mexico, and a member of the National System of Researchers (SNI) since 2009. Dr. Aceves Fernandez has published more than 80 research papers as well as a number of book chapters and congress papers. He has contributed in more than 20 funded research projects, both academic and industrial, in the area of artificial intelligence, ranging from environmental, biomedical, automotive, aviation, consumer, and robotics to other applications. He is also a honorary president at the National Association of Embedded Systems (AMESE), a senior member of the IEEE, and a board member of many institutions. 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