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These books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\\n\\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\\n\\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
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IntechOpen and Knowledge Unlatched formed a partnership to support researchers working in engineering sciences by enabling an easier approach to publishing Open Access content. Using the Knowledge Unlatched crowdfunding model to raise the publishing costs through libraries around the world, Open Access Publishing Fee (OAPF) was not required from the authors.
\n\nInitially, the partnership supported engineering research, but it soon grew to include physical and life sciences, attracting more researchers to the advantages of Open Access publishing.
\n\n\n\nThese books synthesize perspectives of renowned scientists from the world’s most prestigious institutions - from Fukushima Renewable Energy Institute in Japan to Stanford University in the United States, including Columbia University (US), University of Sidney (AU), University of Miami (USA), Cardiff University (UK), and many others.
\n\nThis collaboration embodied the true essence of Open Access by simplifying the approach to OA publishing for Academic editors and authors who contributed their research and allowed the new research to be made available free and open to anyone anywhere in the world.
\n\nTo celebrate the 50 books published, we have gathered them at one location - just one click away, so that you can easily browse the subjects of your interest, download the content directly, share it or read online.
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His research interests include nonlinear robust/adaptive control and optimization of renewable energy systems, as well as artificial intelligence applications in smart grid.",institutionString:"Kunming University of Science and Technology",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Kunming University of Science and Technology",institutionURL:null,country:{name:"China"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"20",title:"Physics",slug:"physics"}],chapters:[{id:"82228",title:"Nonlinear Intelligent Predictive Control for the Yaw System of Large-Scale Wind Turbines",slug:"nonlinear-intelligent-predictive-control-for-the-yaw-system-of-large-scale-wind-turbines",totalDownloads:9,totalCrossrefCites:0,authors:[null]}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"347258",firstName:"Marica",lastName:"Novakovic",middleName:null,title:"Ms.",imageUrl:"//cdnintech.com/web/frontend/www/assets/author.svg",email:"marica@intechopen.com",biography:null}},relatedBooks:[{type:"book",id:"8356",title:"Metastable, Spintronics Materials and Mechanics of Deformable Bodies",subtitle:"Recent Progress",isOpenForSubmission:!1,hash:"1550f1986ce9bcc0db87d407a8b47078",slug:"solid-state-physics-metastable-spintronics-materials-and-mechanics-of-deformable-bodies-recent-progress",bookSignature:"Subbarayan Sivasankaran, Pramoda Kumar Nayak and Ezgi Günay",coverURL:"https://cdn.intechopen.com/books/images_new/8356.jpg",editedByType:"Edited by",editors:[{id:"190989",title:"Dr.",name:"Subbarayan",surname:"Sivasankaran",slug:"subbarayan-sivasankaran",fullName:"Subbarayan Sivasankaran"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{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"}],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"}],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"}],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. Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"72",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",isOpenForSubmission:!1,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",slug:"ionic-liquids-theory-properties-new-approaches",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"314",title:"Regenerative Medicine and Tissue Engineering",subtitle:"Cells and Biomaterials",isOpenForSubmission:!1,hash:"bb67e80e480c86bb8315458012d65686",slug:"regenerative-medicine-and-tissue-engineering-cells-and-biomaterials",bookSignature:"Daniel Eberli",coverURL:"https://cdn.intechopen.com/books/images_new/314.jpg",editedByType:"Edited by",editors:[{id:"6495",title:"Dr.",name:"Daniel",surname:"Eberli",slug:"daniel-eberli",fullName:"Daniel Eberli"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"57",title:"Physics and Applications of Graphene",subtitle:"Experiments",isOpenForSubmission:!1,hash:"0e6622a71cf4f02f45bfdd5691e1189a",slug:"physics-and-applications-of-graphene-experiments",bookSignature:"Sergey Mikhailov",coverURL:"https://cdn.intechopen.com/books/images_new/57.jpg",editedByType:"Edited by",editors:[{id:"16042",title:"Dr.",name:"Sergey",surname:"Mikhailov",slug:"sergey-mikhailov",fullName:"Sergey Mikhailov"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1373",title:"Ionic Liquids",subtitle:"Applications and Perspectives",isOpenForSubmission:!1,hash:"5e9ae5ae9167cde4b344e499a792c41c",slug:"ionic-liquids-applications-and-perspectives",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/1373.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"2270",title:"Fourier Transform",subtitle:"Materials Analysis",isOpenForSubmission:!1,hash:"5e094b066da527193e878e160b4772af",slug:"fourier-transform-materials-analysis",bookSignature:"Salih Mohammed Salih",coverURL:"https://cdn.intechopen.com/books/images_new/2270.jpg",editedByType:"Edited by",editors:[{id:"111691",title:"Dr.Ing.",name:"Salih",surname:"Salih",slug:"salih-salih",fullName:"Salih Salih"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"75390",title:"Enzymatic Saccharification of Canola Straw and Oat Hull Subjected to Microwave-Assisted Alkali Pretreatment",doi:"10.5772/intechopen.96394",slug:"enzymatic-saccharification-of-canola-straw-and-oat-hull-subjected-to-microwave-assisted-alkali-pretr",body:'Lignocellulosic biomass is widely available, abundant at low cost, and a possible source of energy that is estimated to contribute up to 10% to 14% of the global energy supply [1, 2]. Sustainable biofuel and biomass-based transport fuel produced from cellulosic biomass is an energy-dense fuel characterized by lower carbon emissions compared to fossil-based petroleum [3]. Research reports indicated that global biofuels supply since 2000 has increased by a factor of 8% to equal 4% of the transport fuels in 2015 [4, 5]. Furthermore, technologies aimed at converting agricultural biomass into bioethanol and bioproducts are being developed using different techniques [6].
The production of bioethanol from lignocellulosic biomass utilizes biotechnological techniques to convert carbohydrate polymers in biomass into fermentable sugars, which are subsequently used for the production of ethanol and other bioproducts [7]. According to a review by Sarkar et al. [8], there is a transitional shift of energy source by many countries from fossil fuels to renewable sources due to environmental challenges associated with fossil fuels. Liu et al. [1] reported that bioenergy production has the potential to minimize the emission of greenhouse gases (GHG), and governments have used mandates to encourage biofuel production. The total biomass production in Canada was estimated to be 37.3 million metric tons (MT) and is dominated by agricultural and forestry residues. Research on the use of cellulosic biomass from the Canadian agricultural sector to produce energy, including bioethanol, is on-going [1]. However, the economic and environmental sustainability of bioethanol conversion from biomass may be affected by pretreatment efficiency, cost, and enzyme preparation [9, 10].
The production of biofuels is carried out using various feedstocks through thermochemical and biochemical conversion. Pre-processing and biochemical pretreatment increase the accessibility of cellulase enzymes that convert cellulose into glucose [11]. The extent of glucose production is dependent on the type of feedstock used. Several research groups have already examined pretreatment using microwave heating on various feedstocks and have reported suitable glucose yields [12]. However, there is no information on the use of microwave-assisted alkali pretreatment and enzymatic saccharification of oat hull or canola straw.
Lignocellulosic biomass must be pretreated to increase the accessibility of the carbohydrate fraction and modify or partially remove lignin prior to converting the components into final market products such as bioethanol, biopower, and bioproducts [13]. Pretreatment can be carried out in the form of physical, chemical or physico-chemical processes (mechanical, extrusion, alkali, microwave-assisted, organic solvent, and lime treatments) and biological pretreatment methods. Also, combinations of pretreatments have been reported, and many studies are still on-going [12, 14]. According to Alvira et al. [14], microwave pretreatment technology shows highly increased accessibility of the surface area, cellulose decrystallization, lignin removal, and structural alteration. The method also features low hemicellulose solubilization and minimal production of toxic compounds compared to other pretreatment methods. Microwave-assisted alkali pretreatment penetrates the biomass, thereby causing direct vibration of the molecules and fast heating and break-down of the lignocellulosic cell wall structure [15, 16]. Microwave heating combined with chemical treatment showed high carbohydrate recovery. The yield of carbohydrates upon alkaline pretreatment is dependent on the feedstock used [17, 18]. The study aimed to investigate the effects of microwave-assisted alkali (sodium and potassium hydroxide) pretreatment and alkali treatment alone (no heating) on glucose yield during enzymatic saccharification of canola straw and oat hull. The morphology and structural changes of canola straw and oat hull biomass after pretreatment were analyzed using scanning electron microscopy (SEM).
The experiments were performed in triplicates, and the data reported were expressed in mean values and standard deviation. The lignocellulose composition of the canola straw and oat hull, including their hydrolyzed residues, is expressed on a dry weight basis.
Dried canola straw was collected from the black soil zone in Maymont, SK and oat hull was sourced from Richardson Milling Ltd., Martensville, SK and stored at room temperature. The biomass samples ground using a hammer mill (Glen Mills Inc., Clifton, NJ) with screen sizes of 1.6 and 3.2 mm. The physical properties of canola straw and oat hull were reported in Agu et al. [19].
Samples of ground canola straw or oat hull (20 g) were mixed with 180 g of NaOH or KOH solutions at concentrations of 0, 0.75, and 1.5% (w/v). Each mixed sample was placed in a 600 ml beaker covered with aluminum foil and incubated at room temperature for soaking times of 6, 12, and 18 min. The process was replicated three times. The moisture of the pretreated samples was determined using ASAE S358.2 [20]. The alkali-treated samples were dried and conditioned, as reported in Agu et al. [19], followed by lignocellulose analysis using the National Renewable Energy Laboratory (NREL) standard [21] and subsequent enzymatic saccharification (see below).
Microwave-assisted alkali pretreatment was carried out on the ground canola straw and oat hull using a microwave oven (Model NNC980W 2450 MHz, Panasonic Canada Ltd., Mississauga, ON). Microwave power was set at 713 W based upon previous experiments [19]. Twenty grams of sample (ground canola straw or oat hull) were mixed in 180 g of NaOH or KOH solutions at concentrations of 0, 0.75, and 1.5% (w/v). The mixture was heated in the microwave oven with constant rotation for heating times of 6, 12, and 18 min. The pretreatment process was replicated three times. After the pretreatment, the sample was dried to 12% w.b. using an air oven at 42 °C; after cooling, the sample was stored in a sealed plastic bag as reported in Iroba et al. [22]. The sample was subjected to composition analysis followed by enzymatic saccharification and glucose yield analysis.
Enzymatic saccharification of microwave pretreated and alkali-treated samples was conducted using cellulase (C2730-50 ml, cellulase from
where FPU/ml is the determined cellulase activity; A540 sample is the absorbance at 540 nm observed for a 1 mg glucose standard; 5.55 μmole/mg equates to the number of μmole of glucose in 1 mg, and X ml (0.02 ml) the volume of cellulase used. According to the NREL protocol [25], the reactions were done and included a 2% sodium azide solution to prevent microbial growth during incubation [26]. A 20 μl aliquot of the reaction products was collected and prepared for the DNS assay in a microplate format [23, 24]. Three replicates of each sample were analyzed.
The NREL standard was used to determine the chemical composition of microwave-alkali pretreated and alkali-treated biomass samples [21], and the sample selection was based on canola straw or oat hull pellet quality [19]. The lignin determination process and the calculation of acid-insoluble lignin content of the samples were done using the methods reported in Iroba and Tabil [27] and Sluiter et al. [21]. Briefly, 0.3 g of dried biomass sample was slurried in 72% H2SO4 and 4% H2SO4, autoclaved, and solids separated by filtration. The solid material was then dried in the air over at 105 °C for 24 h. Acetone was evaporated at room temperature for 3–4 h, and the solids left oven-dried at 105 °C for 24 h. The data was used to calculate acid-insoluble lignin content in the samples [21].
Glucose, xylose, galactose, mannose, and fucose were quantified using the Waters Acquity UPLC – MS system (Acquity 2004–2010, Waters Corp., Milford, MA) according to NREL/TP-510-42618 [21]. Carbohydrate standards were prepared at ~1 mg/ml each and evaluated under the same conditions. Integrated peak areas for each of the monosaccharides were used to evaluate the data and quantify the sugar content [21]. Three replicate measurements were conducted for each sample.
In this study, response surface methodology (RSM) was used to design experiments, build models, and evaluate the effect of factors. User-Defined Design (UDD) was used to study the effect of independent variables (microwave heating time or soaking time and alkali concentration) on the response and factor interactions with different combinations of variables (cellulose, hemicellulose and lignin) [19]. The analysis of variance (ANOVA) or quadratic model was applied to the polynomial (
Analysis of the ground and pretreated canola straw and oat hull structure was carried out using a JEOL-6010LVscanning electron microscope (JEOL USA Inc., Peabody, MA) at 5 kV. All samples were sputter-coated with a thin layer of gold before imaging at 250 and 500x magnification.
Lignocellulosic biomass is composed essentially of cellulose and lignin matrix-bound by hemicellulose. The pretreatment process helps to disintegrate the cell wall structure, allowing enzymes to access the carbohydrate polymers for microbial utilization [7, 28]. The chemical compositions of MW-alkali pretreated and alkali-treated canola straw and oat hull are presented in Table 1. MW heating and alkali treatment enhanced the breakdown of the lignin and hemicellulose in alkali solutions [29, 30]. The proportional content of cellulose increased with increasing alkali concentration and microwave pretreatment time, while the lignin content was inversely related to microwave pretreatment time and alkali concentration. Alkali treatment caused an apparent increase in the proportional cellulose content with decreasing alkali concentration and lower soaking times, while the hemicellulose and lignin contents decreased with longer soaking times and decreasing alkali concentrations. The lignocellulosic changes suggest that there is a breakdown in the lignin structure, which enhances surface area accessibility for enzyme utilization [19, 28, 29, 30, 31]. The solubilization of lignin in microwave alkali pretreated canola straw and oat hull samples were lower than the corresponding alkali-treated biomass. The decrease in lignin content suggests that the aqueous alkaline solution solubilized the lignin. The apparent increase in cellulose content is likely explained by the solubilization of other cell wall components in the alkali solution. The microwave alkali pretreatment was more effective in solubilizing hemicellulose and lignin in canola straw compared to oat hull samples. Hence, similar results were observed with alkali treatment. MW-assisted alkali pretreatment of canola straw and oat hull resulted in higher solubilization of cellulose, along with a decrease in lignin and hemicellulose. The MW heating pretreatment results support structure breaking reactions [19]. Singh and Bishnoi [7] observed a similar effect when optimizing MW alkali pretreated wheat straw for ethanol production. Canola straw samples showed higher solubilization with the alkali solutions compared to oat hull in MW-assisted alkali pretreatment and alkali treatment processes. Furthermore, the NaOH solution was more effective in MW-assisted alkali pretreatment and alkali treatment of canola straw and oat hull.
Sample | Treatment method | Alkali concentration (%) | Treatment time (min) | Compositiona (%) | ||
---|---|---|---|---|---|---|
Cellulose | Hemicellulose | Lignin | ||||
Canola straw 1.6 mm | A | 0.75% NaOH | 6 | 79.9 (1.9) | 8.5 (7.5) | 7.9 (1.4) |
A | 0.75% NaOH | 18 | 69.7 (5.1) | 6.0 (5.2) | 6.6 (4.1) | |
A | 1.5% KOH | 12 | 69.2 (1.0) | 9.8 (8.6) | 8.8 (1.2) | |
A | 1.5% KOH | 18 | 61.3 (16.7) | 8.2 (9.0) | 8.3 (1.4) | |
MWA | 1.5% NaOH | 18 | 59.1 (0.5) | 9.4 (8.3) | 4.3 (1.2) | |
MWA | 1.5% NaOH | 6 | 37.8 (3.1) | 7.2 (6.5) | 4.7 (0.6) | |
MWA | 0.75% KOH | 12 | 53.6 (9.2) | 10.6 (9.2) | 5.8 (0.3) | |
MWA | 1.5% KOH | 6 | 56.9 (17.0) | 7.7 (9.0) | 4.6 (0.5) | |
Oat hull 1.6 mm | A | 0.75% NaOH | 18 | 67.9 (23.1) | 14.4 (14.6) | 11.5 (0.8) |
A | 1.5% NaOH | 12 | 62.4 (0.1) | 21.4 (23.6) | 11.2 (2.7) | |
A | 0.75% KOH | 6 | 64.7 (1.4) | 12.0 (11.0) | 10.9 (2.1) | |
A | 0.75% KOH | 12 | 37.0 (18.8) | 10.3 (10.6) | 13.4 (1.8) | |
MWA | 0.75% NaOH | 18 | 42.8 (11.3) | 15.6 (13.8) | 6.3 (1.0) | |
MWA | 1.5% NaOH | 18 | 37.1 (8.5) | 14.3 (12.6) | 4.2 (1.2) | |
MWA | 1.5% KOH | 18 | 56.4 (17.9) | 16.0 (13.8) | 4.8 (0.9) | |
MWA | 1.5% KOH | 6 | 41.8 (14.0) | 12.9 (11.5) | 5.7 (1.6) | |
Canola straw 3.2 mm | A | 1.5% NaOH | 6 | 54.1 (6.7) | 10.4 (11.2) | 9.2 (1.6) |
A | 1.5% NaOH | 18 | 82.2 (3.9) | 7.3 (7.0) | 6.9 (3.0) | |
A | 0.75% KOH | 6 | 68.1 (8.4) | 9.2 (9.1) | 9.1 (0.9) | |
A | 1.5% KOH | 6 | 46.6 (1.5) | 9.7 (8.4) | 8.2 (1.2) | |
MWA | 0.75% NaOH | 12 | 54.2 (2.3) | 6.7 (5.8) | 5.1 (0.6) | |
MWA | 0.75% NaOH | 6 | 38.2 (2.7) | 8.7 (7.5) | 5.3 (0.3) | |
MWA | 0.75% KOH | 12 | 30.8 (2.9) | 13.8 (13.0) | 5.0 (1.6) | |
MWA | 1.5% KOH | 6 | 63.4 (35.0) | 10.3 (9.2) | 4.4 (0.5) | |
Oat hull 3.2 mm | A | 0 | 6 | 41.5 (2.1) | 9.5 (8.4) | 11.7 (1.3) |
A | 1.5% NaOH | 6 | 66.9 (8.3) | 20.1 (17.4) | 9.8 (3.4) | |
A | 1.5% NaOH | 18 | 57.0 (3.5) | 14.1 (13.2) | 11.8 (0.6) | |
A | 0.75% KOH | 12 | 57.2 (17.2) | 24.8 (23.7) | 13.7 (2.3) | |
MWA | 0.75% NaOH | 6 | 22.7 (11.0) | 12.9 (14.4) | 6.8 (2.2) | |
MWA | 1.5% NaOH | 18 | 48.7 (8.3) | 14.4 (13.3) | 5.1 (0.8) | |
MWA | 0.75% KOH | 12 | 47.9 (18.2) | 16.0 (16.0) | 5.4 (0.6) | |
MWA | 1.5% KOH | 18 | 62.6 (2.0) | 10.4 (18.0) | 6.4 (1.3) |
Chemical composition (% dry basis) of alkali treatment and microwave-assisted alkali pretreatment of canola straw and oat hull 1.6 mm screen size.
Mean ± standard deviation of three replicates.
A: Alkali treatment; MWA: Microwave-assisted alkali pretreatment.
Results obtained showed the highest lignocellulosic solubilization from canola straw samples under both treatment conditions. The response variable obtained was expressed as a function of independent variables reported by Agu et al. [19]. The ANOVA
Sample/screen size (mm) | MW-alkali pretreatment | Parameters | C | H | L |
---|---|---|---|---|---|
Canola straw 1.6 mm | NaOH | Model | 0.030 | 0.033 | 0.024 |
Alkali conc. | 0.052 | 0.024 | 0.035 | ||
MW time | 0.021 | 0.039 | 0.041 | ||
R-Square | 0.868 | 0.852 | 0.805 | ||
Oat hull 3.2 mm | NaOH | Model | 0.049 | 0.026 | 0.045 |
Alkali conc. | 0.011 | 0.049 | 0.040 | ||
MW time | 0.033 | 0.048 | 0.042 | ||
R-Square | 0.838 | 0.882 | 0.817 |
ANOVA
C: Cellulose; H: Hemicellulose; L: Lignin; Alkali conc.: Alkali concentration.
Sample/screen size (mm) | MW-alkali pretreatment | Parameters | C | H | L |
---|---|---|---|---|---|
Canola straw 1.6 mm | KOH | Model | 0.016 | 0.018 | 0.014 |
Alkali conc. | 0.025 | 0.028 | 0.023 | ||
Soaking time | 0.059 | 0.051 | 0.053 | ||
R-Square | 0.883 | 0.853 | 0.865 | ||
Canola straw 3.2 mm | KOH | Model | 0.025 | 0.012 | 0.016 |
Alkali conc. | 0.016 | 0.045 | 0.038 | ||
Soaking time | 0.038 | 0.018 | 0.025 | ||
R-Square | 0.899 | 0.883 | 0.856 | ||
Oat hull 3.2 mm | NaOH | Model | 0.039 | 0.038 | 0.039 |
Alkali conc. | 0.047 | 0.043 | 0.046 | ||
Soaking time | 0.012 | 0.013 | 0.013 | ||
R-Square | 0.875 | 0.878 | 0.876 |
ANOVA
C: Cellulose; H: Hemicellulose; L: Lignin; Alkali conc.: Alkali concentration.
Surface plot of the effects of alkali concentration and MW heating time on chemical composition. (a) canola straw (NaOH) and (b) oat hull (KOH).
Surface plot of the effects of alkali concentration and soaking time on chemical composition. (a) canola straw (NaOH) and (b) oat hull (KOH).
The response surface plots in Figure 1a and b show the effect of the interactions between MW heating time and alkali concentration on cellulose, hemicellulose, and lignin of canola straw and oat hull pretreated in NaOH and KOH solutions. The plots show that there were notable interactions among the variables in both samples. Increasing the alkali concentration and MW heating time showed higher solubilization of cellulose, hemicellulose, and lignin contents in canola straw and oat hull. The response surface plots in Figure 2a and b show the effect of the interactions between soaking time and alkali concentration on chemical cellulose, hemicellulose, and lignin of canola straw and oat hull soaked in NaOH and KOH solutions. The 3D response surface plots of the samples show different shapes of interactions when compared with MW pretreated samples. The interaction effect between soaking time and alkali concentration on both samples significantly influenced the response variables. Decreasing the alkali concentration and soaking time increased the proportional content of cellulose. The hemicellulose and lignin contents plots resulted in longer soaking times and decreased alkali concentrations. Generally, the interaction plot curves of canola straw and oat hull samples significantly influenced the hemicellulose and lignin contents regardless of the alkaline concentration, MW heating or soaking time.
Microwave-assisted pretreatment was investigated due to its rapid heating efficiency in disintegrating the ultrastructure of cellulose. Several studies have combined the technique with alkali pretreatment. The results showed an accelerated chemical reaction rate in lignin removal and partial degradation of hemicellulose depending on the type of feedstock used [34]. NaOH and KOH at various concentrations with MW heating of canola straw and oat hull at different heating and soaking times were investigated. The samples pretreated with MW-assisted alkali and alkali were subjected to cellulase hydrolysis to convert cellulose to glucose. The data shown in Figures 3 and 4 indicate that the microwave-assisted alkali pretreated samples yielded a higher level of reducing sugars compared to alkali-treated samples. Figure 3 shows the highest glucose yield (110.05 mg/g for one-gram canola straw) obtained after pretreatment with 1.5% NaOH concentration for 18 min. The glucose yield (96.77 and 110.05 mg/g for one-gram canola straw) increased after 6 and 12 min of pretreatment, respectively. In alkali treatment, the glucose yields recorded similar results after treatments with 0.75% and 1.5% NaOH and KOH concentrations with longer soaking time for canola straw ground using 1.6 mm screen size.
Glucose production from enzymatic saccharification of microwave-assisted alkali pretreated and alkali treated ground canola straw. MW-A: Microwave-assisted alkali pretreated; AT: Alkali treated.
Glucose production from enzymatic saccharification of microwave-assisted alkali pretreated and alkali treated ground oat hull. MW-A: Microwave-assisted alkali pretreated; AT: Alkali treated.
Figure 4 shows the highest glucose yield (99.10 mg/g for one-gram oat hull sample) obtained after pretreatment with 0.75% NaOH concentration for 18 min. Extending the residence time from 6 to 18 min increased the sugar yields in treatments using 0.75% NaOH and in both ground samples. Similar results were reported in Agu et al. [19] using MW-assisted alkali and distilled water pretreated canola straw and oat hull biomass. For alkali-treated samples, a shorter soaking time with 1.5% NaOH concentration resulted in high glucose yield in samples ground with a 3.2 mm screen size. Aguilar-Reynosa et al. [15] studied MW-assisted pretreatment of corn stover and reported the glucose yields achieved at reduced residence time (10–50 min). On the other hand, Rodrigues et al. [34] studied cashew apple bagasse MW-assisted pretreatment, and Hu and We [35] reported on switchgrass pointing out that glucose yield in both studies increased with increasing alkali concentration and with pretreatment time. To further evaluate the pretreatment alkali reagents, total glucose yields and glucose digestion from the enzymatic saccharification of pretreated biomass substrates compared with alkali-treated biomass substrates are given in Figures 5 and 6. Overall glucose yields of microwave pretreated canola straw with NaOH and KOH pretreatments were 210.75 and 207.07 mg/g, and oat hull total glucose yields with NaOH and KOH pretreatments were 175.96 and 300.30 mg/g. These yields are substantially higher than the yield from alkali-treated canola straw and oat hull with NaOH and KOH pretreatments (109.88 and 140.91, and 102.28 and 23.47 mg/g). For both feedstocks, total glucose yield and digestion overall were higher with KOH pretreatments over pretreatment with NaOH. A similar result was obtained with alkali treatments.
Glucose production from enzymatic saccharification of microwave-assisted alkali pretreated and alkali treated canola straw and oat hull. MW-A: Microwave-assisted alkali pretreated; AT: Alkali treated.
Glucose digestion from enzymatic saccharification of microwave-assisted alkali pretreated and alkali treated canola straw and oat hull. MW-A: Microwave-assisted alkali pretreated; AT: Alkali treated.
Figures 7 and 8(a-c) show the SEM images for the cross-sectional area of untreated ground, alkali-treated, and MW-assisted alkali pretreated canola straw and oat hull biomass at 250x and 500x magnifications, respectively. It was observed that both untreated ground canola straw and oat hull samples showed undamaged surfaces, smooth and no cracks (Figures 7a and 8a). Alkali-treated samples in Figures 7(b) and 8(b) show many induced physical changes on the surfaces of the biomass. Soaking of canola straw and oat hull in alkali solution caused breakage and cracks of the cell walls, and slight erosion of micro-fibrils, especially on oat hull samples. MW-assisted alkali pretreated samples in Figure 7(c) shows detached fibres with an altered fibrillar structure of the distorted cell walls for canola straw samples, and Figure 8(c) for the oat hull sample shows porous development on surfaces. Hence, the SEM images revealed the disruptive effects of the MW-assisted alkali pretreatment and alkali treatment (no heating) on the surface of the samples, which subsequently changed the canola straw and oat hull compositions. These observations were concordant with the positive effects of microwave-assisted alkali pretreatment on the improved enzymatic digestibility of canola straw and oat hull [19, 30, 31]. Furthermore, the chemical treatment using alkali solutions (NaOH/KOH) developed deep cracks on the biomass, increasing the surface area to facilitate lignocellulose disruption, a prerequisite to improving enzymatic reactions. Similar observations have been reported in various studies [36, 37].
SEM images of canola straw at magnifications 250 and 500x. (a) untreated sample; (b) alkali pretreated; (c) microwave-assisted alkali pretreated.
SEM images of oat hull at magnifications 250 and 500x. (a) untreated sample; (b) alkali pretreated; (c) microwave-assisted alkali pretreated.
This study showed that microwave-assisted alkali pretreatment of canola straw and oat hull enhanced the enzymatic digestibility of these substrates compared to alkali pretreatment alone. MW-assisted alkali pretreatment and alkali treatment methods were effective in disrupting the lignocellulose structure of the biomass by inducing changes in their chemical compositions. The MW-assisted alkali pretreatment of biomass increased the glucose yields upon enzymatic saccharification. Total glucose yield overall was higher with KOH pre-treatment compared to pre-treatment with NaOH in both feedstocks. Therefore, based on the results presented, the MW-assisted alkali pretreatment was an efficient pretreatment method of canola straw or oat hull substrate for bioethanol production. Subsequently, treatment variables of MW-assisted alkali pretreatment will be optimized to improve glucose digestibility in the future.
The authors acknowledge the financial support received from the Tertiary Education Trust Fund (TETFund) through Enugu State University of Science and Technology (ESUT) Nigeria, BioFuelNet Canada, and Agricultural and Agri-Food Canada – Saskatoon Research and Development Centre (AAFC-SRDC) for allowing to use the laboratories and facilities for chemical composition and saccharification analysis.
The authors declare no conflict of interest.
In the last 10 years, the market for unmanned aerial vehicles (UAVs) in the civil sector has been growing enormously. This was certainly preceded by a period of intensive research that continues to this day, so, an even greater step forward is expected in the future. Technological advances in the design and manufacture of mechatronic system components have enabled many applications from the aspect of automation. The development of control, propulsion, power supply components, and other subsystems has contributed to greater speed of data processing and greater autonomy, which enables the performance of complex flight missions. The development of propulsion components and numerous studies of propulsion configurations have facilitated applications in various sectors, such as precision agriculture [1, 2], surveillance [3], and aerial photography [4]. The application possibilities of UAVs are plentiful in many other sectors, such as transport [5], construction [6], fire protection [7], and more.
The propulsion configuration defines how the aircraft will move in three-dimensional space and it depends on the type of application or mission that the UAV needs to perform. Numerous types of aircraft with various propulsion configurations are used to perform different tasks, activities, and for research and development. In addition to conventional types of UAVs with fixed wings [8, 9] and rotary wings [10, 11, 12], a number of hybrid configurations [13, 14] and bioinspired propulsion configurations [15, 16] are being investigated. Fixed-wing aircraft can achieve high speeds and compared to other types, consume less energy to achieve movement, but on the other hand, unable to perform the stationary flight. Generally, they need a runway or special launchpad to be able to take off. Aircraft with rotary wings do not have this problem because they have the ability to take off and land vertically (VTOL), and thus stationary flight and flight at moderate speed. This makes them suitable for missions that require complex manoeuvres and a higher degree of system autonomy. Within the rotary-wing UAV type, there are numerous subtypes of aircraft. It is important to highlight two typical representatives, aircraft with variable pitch propellers, such as helicopter aircraft [17] and multirotor aircraft (multicopter) [18], consisting of
Multirotor type of UAV has greater agility and manoeuvrability, which allows them to perform missions that involve precise and complex movements. On the other hand, they are characterised by high-energy consumption, so it is extremely important to choose the right components and parameters of the system. The most commonly used configuration utilises four rotors (so-called quadrotor) and to a lesser extent the configuration with six (hexarotor), and eight rotors (octorotor). Generally, conventional configurations are characterised by a planar geometric arrangement of an even number of rotors. In addition to conventional purposes, a variety of propulsion configurations makes the multirotor type of UAV suitable for usage as aerial robotic systems. Since this type of application is expected for specialised tasks, there is a need to design custom aircraft and make small series or customised systems. It is also important to save time in the design and production phase and lower production costs compared to conventional manufacturing technologies. Rapid prototyping technologies, such as additive manufacturing (AM), allow the fabrication of assembly parts of such systems [19, 20, 21]. Numerous studies have shown the possibilities of rapid prototyping technologies and their application [22, 23].
In this chapter, the framework for design and AM of specialised multirotor UAV parts is presented. In the system design phase, it is necessary to select components and design multirotor UAV based on the purpose of the aircraft. The division into modules (subsystems) allows a greater degree of modularity that leads to a wider range of applications (by fitting the aircraft with different equipment). In the prototyping and production phase, the procedure for making parts using three different AM technologies is described. Depending on the mechanical and other requirements, which are defined in the system design phase, FDM, SLS, and SLA technologies are used within this framework. Professional and hobby 3D printers and related software packages were used in the production process. The procedure was validated for two considered case studies, for a small fully-actuated modular aircraft, and a heavy-lift multirotor UAV. The last part of this chapter presents experimental testing in certain phases of the specialised UAV development, which is necessary for this type of aircraft to be safely used.
Multirotor type of UAV is classified as rotary-wing UAV, aircraft that are heavier than air and are powered by motors. The ability to take off and land vertically, hover, and fly at moderate speeds, amongst other flight manoeuvres, allows multirotor UAVs to perform complex movements, making them suitable for a wide range of tasks. From a mechanical point of view, the multirotor type of UAV system is described as a rigid body consisting of
Conventional multirotor UAV configurations in ×-layout.
The design of the aircraft system primarily depends on the purpose, respectively, the mission profile that the aircraft should typically perform. To allow easier analysis of aircraft parameters and design, the aircraft system can be divided into four key subsystems (Figure 2). The equipment and payload to be carried by aircraft dictate the choice of parameters and components of other subsystems. The rotors of the propulsion subsystem are mainly electric propulsion units (EPUs) whose central part is a brushless DC (BLDC) motor with a corresponding electronic speed controller (ESC), and a fixed-pitch propeller mounted on a motor rotor. By their rotation, the propellers create aerodynamic forces and moments and directly affect the flight dynamics, which means that the rotors angular velocities are the input variables of the propulsion subsystem. The characteristic of the multirotor UAVs is high-energy consumption, so an energy subsystem must deliver a large amount of energy. In conventional EPUs, the power subsystem mainly consists of one or more lithium-polymer (LiPo) batteries with associated electronics. The design of the control subsystem or the selection of components primarily depends on the mission or the degree of autonomy that determines the selection of the flight controller, sensors, and other peripheral modules (telemetry, RC, VTx, and others). It follows that the performance of a multirotor type of UAV is determined by the parameters and components of the propulsion and energy subsystems. These two subsystems are interdependent because, for example, as the power of the aircraft increases, the energy demand increases, resulting in a higher mass of the aircraft. The energy requirements of the propulsion subsystem must be taken into account when selecting batteries, which, in turn, depends on the weight and size of the aircraft and the number of EPUs. When designing a system, the ratio of mass and capacity of the battery is one of the key data.
Multirotor UAV main subsystems.
In this chapter, the design of specialised multirotor aircraft is considered, and two case studies are presented through the design, production, and testing phases. Aircraft, such as those used in the case study, cannot be procured in form of commercial aircraft produced in large series. They are produced in small series or even as unique models designed to perform a specialised task. The first case is an experimental modular multirotor (EMMR) UAV with a power of 350–700 W, which has so far been proposed as an engineering educational platform [18]. EMMR can be used as an aerial robotic system since fully-actuated UAV configurations can be assembled. Such a platform represents a suitable engineering educational tool due to the complexity of the system, which requires an interdisciplinary approach in the field of mechanical engineering, electrical engineering, and computing. The second case is a heavy lift aircraft that can be a power of approximately 10–20 kW, depending on the number of rotors. Such an aircraft is considered for use in precision agriculture for smart spraying tasks. In addition to the fact that these aircraft are not commercially available in a form that would allow change of the parameters within open-source software, it is also important to point out that in small series production the cost per unit increases dramatically. For this reason, technologies for rapid prototyping were chosen, mostly AM in which the cost per unit is the same regardless of the number of units produced (Figure 3), which is a known fact described in numerous studies [24, 25]. AM is often appropriate for small to medium-sized production series but there is always an inflexion point at which other manufacturing methods become more cost-effective.
Cost per unit with respect to quantity for conventional and additive manufacturing technologies.
In this chapter, AM technologies are used for the rapid prototyping and development of specialised multirotor UAVs. In addition to the fact that for small batches AM is cheaper compared to conventional processes, it also significantly shortens the development time by rapid iteration and the possibility of early and often testing many different designs or partial designs with critical features, which further reduce the cost of the final product. Conventional production technologies are much more expensive for small batches due to preparation, tool selection, manufacturing of tools, and other costs. AM, on the other hand, allows the production of parts directly from solid CAD models using software packages, so-called slicers. AM is also suitable for the production of spare parts for damaged aircraft.
There are a large number of low-cost 3D printers on the market, so for low-power multirotor aircraft, parts can be produced very cheaply and quickly. 3D printers may vary greatly in price, size, material, and AM technology used. The paper further considers three AM technologies: FDM, SLS, and SLA. 3D printing uses a wide range of materials, the choice of which is related to AM technology and the purpose of the part. In the case of aircraft parts, plastic materials in the raw form of filament, powder, or resin are mainly used. To determine whether certain materials and AM technologies are suitable for the production of a particular part, the desired strength, stiffness, and weight of the part must be taken into account, but the influence of environmental conditions and the expected duration of the part must also be considered. In addition to the choice of material, the mechanical properties of the part can be alternated and adjusted by changing the printing parameters and the orientation of the printed part. Because parts are fabricated gradually, layer by layer, the inevitable result is the anisotropic properties of printed parts. Better mechanical properties are achieved along with the printing layer and worse in a direction normal to the printing layer. There are many ways in which the mechanical properties of materials can be tested [26, 27, 28]. Also, greater precision and greater detailed geometry can be achieved in planes parallel to the print layer where print accuracy is higher. Table 1 shows the main characteristic of the used 3D printers in combination with the associated software.
AM technology | 3D printer | Raw material form | Build volume | Software |
---|---|---|---|---|
FDM | Prusa i3 MK3S+ | Continuous thermoplastic filaments | 250 × 210 × 210 mm | PrusaSlicer |
FDM | Markforged Onyx Pro | Composite base filaments | 320 × 132 × 154 mm | Eiger |
SLS | Sinterit Lisa Pro | Powder | 150 × 200 × 260 mm | Sinterit Studio |
SLA | Formlabs Form 3 | Resin | 145 × 145 × 185 mm | PreForm |
Used 3D printers with associated software.
Fused deposition modelling (FDM) or known as fused filament fabrication (FFF) is a manufacturing technology in which objects are created by extruding polymer filament onto a built platform through a heated nozzle. There are numerous versions of FDM printers with various price ranges. In this research, Prusa i3 MK3 is used as a low-cost FDM printer where the platform moves in the Y-axis and the nozzle in the X- and Z-axes. When one layer is done, the nozzle will move up vertically to allow a new layer to be applied to the previous one. The thickness of the layer (slice) depends on the print parameters, and in the case of the used Prusa printer, the slices are between 0.05 and 0.30 mm thick [29]. Prior to the AM process, the constructed CAD model must be exported in a compatible file format, such as STL. Such a model is then cut into horizontal slices in a software package (so-called slicer). The paths of the platform and the nozzle are calculated by the software according to the parameters set by the user. In addition to the mentioned layer thickness, which significantly affects the accuracy, some of the other variable parameters are the number of layers in the outer wall and the number of layers at the bottom and top of the part, the percentage and structure of the filling, extrusion speed, and others. Because the next printing layer prints on top of the last one, supporting structures are required to print large overhangs or holes. They are printed together with the part and removed after printing is done. In general, overhangs should be avoided by proper orientation of the part or by using angled overhangs where possible. The most common materials used in FDM technology are ABS, PLA, PC, ASA, PPSF/PPSU, ULTEM, PH-HD. PE-LD, PET, TPU, and others. Figure 4 shows a working principle of the FDM technology.
The principle of operation of FDM technology.
In addition to classic FDM technology, devices that can produce parts from composite materials using FDM processes are known as continuous fibre fabrication (CFF). In this paper, Markforged Onyx Pro is used, in which the platform moves in the Z-axis and the nozzle in the X- and Y-axes. Compared to the Prusa printer, it is a much more expensive device but allows 3D printing of composite materials made of plastic matrix and inlaid fibreglass fibres for better mechanical properties and increased lifetime, compared to plastic alone. The strength and stiffness of a fibre-reinforced part can be comparable to aluminium. The software package allows adjustment of the classic print parameters and further adjustment of the composite reinforcements parameters as shown in Figure 5.
Fibre reinforcement layout—CFF technology [
The next AM technology considered in the chapter is selective laser sintering, which with the advent of cheaper 3D printer systems allows the application not only for industrial purposes but also for research. The material used in this technology is available in the form of powder that is laser-sintered to create a designed geometry. The powder delivery mechanism consists of two chambers, in the first, there is construction powder that is delivered to the second chamber through rollers and a piston in form of a powder layer. In the second chamber, a layer is precisely sintered to the desired shape utilising laser beams. This technology does not require a support structure, as the unsintered powder provides support to the object under construction. This allows the production of parts of more complex geometry from different types of materials, and it is possible to produce prefabricated assemblies with movable joints. After the production process, further processing of the part or assembly is required to achieve certain mechanical properties of the finishing quality. In this chapter, the SLS system is discussed, which consists of the SLS 3D printer Sinterit Lisa Pro and the associated equipment for the preparation of powder materials (nylon 11, nylon 12, TPU, TPE, and polypropylene) and processing of parts and assemblies. Figure 6 shows the working principle of the SLS.
The principle of operation of SLS technology.
The principle of operation of SLA technology.
Stereolithography (SLA) is the first commercially available AM technology developed in 1986 by 3D Systems. With this technology, CAD models are created by curing polymer resin using a laser beam system. With SLA technology, the laser is focussed on a mirror scanning system that cures polymer resin with very high precision. When one layer is cured by laser, the built platform moves upwards in the z-direction and the new layer can be treated. The materials for SLA are thermoset photosensitive resin-shaped polymers. SLA technology makes it possible to achieve high accuracy and a smooth surface, making it the most cost-effective AM technology. Compared to the previously considered technologies, SLA parts have poorer mechanical properties; therefore, SLA technology is not recommended for structurally loaded parts. Figure 7 shows the scheme of the SLA procedure.
The design of the multirotor type of UAV propulsion subsystem is considered and the additive manufacturing framework is shown. This framework can also be used for rapid prototyping of parts from carbon fibre plates. The process of making parts is presented for two experimental aircraft that can be used for specialised purposes, such as performing tasks involving complex and precise movements and in tasks involving the transfer of heavy cargo.
The propulsion subsystem is defined by the parameters of the geometric arrangement and characteristics of the EPUs. A suitable fixed-pitch propeller is mounted on the rotor of the outrunner BLDC motor (Figure 8). The basic parameter of a propeller is its diameter. As the diameter of the propeller increases, the angular velocity of the motor rotor decreases. The motor is defined by a motor velocity constant kV. Motors with a lower motor constant are used in combination with larger diameter propellers and are driven at higher voltages. The ESC is responsible for starting the motor and, depending on the control signal, controls the motor speed. The EPUs are connected to one or more LiPo batteries of the appropriate number of cells and capacity.
Electric propulsion unit of multirotor type of UAV [
The motor stator must be connected to the aircraft assembly which consists of a central part and the rotor arms. Propulsion assembly design is the most complex part of the overall design in terms of the mechanical properties that assembly parts should possess. The aircraft can be used in a wide range of powers, from a few tens of watts to several tens of kilowatts. It is necessary to choose materials and technologies concerning the selected propulsion components. Figure 9a shows the stator geometry which is important from the aspect of mounting the motor to the aircraft assembly. Figure 9b shows the characteristics of the propulsion unit considered in the case of a heavy-lift aircraft.
Electric propulsion unit: (a) BLDC motor geometry [
The configuration of the multirotor UAV is defined by the geometric arrangement of the rotors. Mostly conventional configurations with a planar rotor layout are commercially available. It is possible to select configuration parameters that will result in an increased degree of actuation, which potentially allows the performance of complex tasks in the field of aerial robotics. A fully-actuated aircraft with passively tilted rotor arms are considered in this research (Figure 10).
Fully-actuated multirotor configurations with passively tilted rotors: (a) PTX6; (b) PTX8.
A framework for the production of parts for specialised multirotor UAVs using additive manufacturing is presented. It consists of an aircraft design stage in which various software packages can be used for the needs of 3D modelling of parts and assemblies, and also for simulations. In this research, the SOLIDWORKS software package is used in the design stage. After the process of creating a model is done, triangulation of the 3D CAD model is performed and the model is exported into an STL format. In the prototyping stage, it is necessary to adjust the parameters of the 3D print in accordance with the selected AM technology using associated software, the so-called slicer. The next step is the execution of the g-code by which the given parts are produced. After finishing the print, the parts need to be post-processed (Figure 11).
Additive manufacturing procedure.
Manufactured parts of specialised multirotor UAVs are connected together with other components into functional assemblies. Through the prototyping phase, different test phases were conducted for the two aircraft based on propulsion units with the parameters given in Table 2. By assembling and testing individual subsystems, potential design errors can be identified, and improvements offered.
Multirotor configuration | BLDC motor | Propeller | ESC |
---|---|---|---|
PTX6 D = 500 mm | MN1806 1400 Kv | CF7024 d = 7″ | Air 10A 3S |
X4 D = 1500 mm | P80 100 Kv | G32x11 d = 32″ | Flame 80A 12S |
Considered multirotor configuration main parameters.
The control subsystem of the experimental aircraft is based on the open-source Pixhawk FC. To operate a fully-actuated aircraft, custom firmware has been developed. Figure 12 shows the indoor testing phase where attitude control experiments were conducted. Indoor testing provides a safe way to set the basic parameters of the control subsystem and set up and test all safety elements. It is also possible to tune the parameters of the control algorithm. After the indoor phase, the remote control of the aircraft was tested in two cases that differ by control inputs from the RC transmitter. The first case is represented with conventional control inputs (thrust, roll, pitch, and yaw), while in the second, control inputs were three forces and yaw moment with respect to body axes.
Experimental testing of PTX6 configuration in case of attitude control.
For the second experimental aircraft, the propulsion unit was tested in different operating regimes at the full power range. Characteristics were obtained (Figure 9b) and other parameters, such as heating, were monitored (Figure 13a). Given the power of the aircraft, the described framework is used in a wider range of rapid prototyping, which includes cutting carbon plates, which together with printed parts and prefabricated tubes form the rotor arm assembly (Figure 13b). In the coming period, it is planned to assemble the propulsion subsystem into a functional assembly so that tests can be carried out as in the case of the first experimental aircraft.
Heavy-lift aircraft propulsion: (a) EPU testing; (b) EPU assembly.
This chapter demonstrates the application of three different AM technologies for the development of customised parts for the specialised multirotor UAVs—fused deposition modelling (FDM), selective laser sintering (SLS), and stereolithography (SLA). Special purpose multirotor UAVs are often produced in small series, with the option of personalization and modular design. In the case of prototyping or individual production, conventional manufacturing technologies are too expensive and not flexible enough to be able to make parts quickly and put them into exploitation. AM offers new possibilities for rapid development of UAV multirotor reducing costs and time of research, development, and production. To take full advantage of AM, a new design approach for AM is needed to achieve lightweight and durable structures of UAV parts. Preliminary tests have shown that the use of the proposed AM technologies is very promising in terms of designing parts of specialised aircraft, as many factors (i.e., geometry, strength, firmness, and weight) often have to be changed and adjusted during the design process. In future work, it is planned to use AM technologies to make parts of other aircraft subsystems and to integrate them in the overall multirotor UAV system. Furthermore, the oncoming tests of mechanical properties are expected to have a great significance for frame structure optimisation.
This research was funded by European Regional Development Fund, Operational programme competitiveness and cohesion 2014–2020, as part of the call for proposals entitled “Investing in science and innovation—first call,” grant number KK.01.1.1.04.0092.
additive manufacturing
unmanned aerial vehicle
fused deposition modelling
selective laser sintering
stereolithography
vertically take-off and land
degrees of freedom
electric propulsion unit
brushless direct current
electronic speed controller
fused filament fabrication
continuous fibre fabrication
lithium-polymer
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After finishing his P. hD degree in 1992, he served in the Industry as a Scientific Officer and continued his academic career as a visiting scholar for a number of educational institutions. In 1996 he joined National University of Science & Technology Pakistan (NUST) as an Associate Professor; NUST is one of the top few universities in Pakistan. In 1999 he joined an International Company Lineo Inc, Canada as Manager Compiler Group, where he headed the group for developing Compiler Tool Chain and Porting of Operating Systems for the BLACKfin processor. The processor development was a joint venture by Intel and Analog Devices. In 2002 Lineo Inc., was taken over by another company, so he joined Aalborg University Denmark as an Assistant Professor.\nProfessor Akbar has truly a multi-disciplined career and he continued his legacy and making progress in many areas of his interests both in teaching and research. 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In-service vehicles equipped with sensors and GPS systems can act as probes to detect and analyse real-time vehicle vibration. Recently, a compact on-board sensing device has been developed. This chapter describes the track condition monitoring system that uses a compact on-board sensing device and diagnosis software. The diagnosis software provides the function of detecting track faults using the root mean square (RMS) of the car-body acceleration. It also allows analysis in the time-frequency domain using wavelet transform. A monitoring experiment in a local railway line showed that the system is effective for practical application.",book:{id:"4789",slug:"railway-research-selected-topics-on-development-safety-and-technology",title:"Railway Research",fullTitle:"Railway Research - Selected Topics on Development, Safety and Technology"},signatures:"Hitoshi Tsunashima, Hirotaka Mori, Masayuki Ogino and Akira\nAsano",authors:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",slug:"hitoshi-tsunashima",fullName:"Hitoshi Tsunashima"}]},{id:"59302",doi:"10.5772/intechopen.74277",title:"Model-Based Fault Analysis for Railway Traction Systems",slug:"model-based-fault-analysis-for-railway-traction-systems",totalDownloads:1384,totalCrossrefCites:1,totalDimensionsCites:5,abstract:"Fault analysis in industrial equipment has been usually performed using classical techniques such as failure modes and effects analysis (FMEA) and fault tree analysis (FTA). Model-based fault analysis has been used during the last several years in order to overcome the limitations of classical methods when complex industrial equipment has to be analyzed. In railway and automotive sectors, the development and validation of new products are based on hardware-in-the-loop (HIL) platforms. In this chapter, a methodology to enhance classical FMEAs is presented. Based on HIL simulations, the objective is to improve the results of the fault analysis with quantitative information about the effects of each fault mode. In this way, the impact of the fault analysis in the design of the traction system, the development of new diagnostic functionalities and in the maintenance tasks will increase.",book:{id:"6065",slug:"modern-railway-engineering",title:"Modern Railway Engineering",fullTitle:"Modern Railway Engineering"},signatures:"Jon del Olmo, Fernando Garramiola, Javier Poza and Gaizka\nAlmandoz",authors:[{id:"149511",title:"Dr.",name:"Gaizka",middleName:null,surname:"Almandoz",slug:"gaizka-almandoz",fullName:"Gaizka Almandoz"},{id:"149644",title:"Dr.",name:"Javier",middleName:null,surname:"Poza",slug:"javier-poza",fullName:"Javier Poza"},{id:"235660",title:"Dr.",name:"Jon",middleName:null,surname:"Del Olmo",slug:"jon-del-olmo",fullName:"Jon Del Olmo"},{id:"241062",title:"Mr.",name:"Fernando",middleName:null,surname:"Garramiola",slug:"fernando-garramiola",fullName:"Fernando Garramiola"}]},{id:"49375",doi:"10.5772/61517",title:"Experimental and Simulation Study of the Superstructure and Its Components",slug:"experimental-and-simulation-study-of-the-superstructure-and-its-components",totalDownloads:2553,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"The issues discussed in this chapter are of interest of both the manufacturers and the experts responsible for condition of the track superstructure. In general, stress in steel elements may affect the energy state, phase changes, and corrosion. It may reduce fatigue strength and cause damage and cracks of the rails. It is one of the causes of accelerated development of standard railhead defects. Proper selection of, e.g., bending process parameters provides uniform distribution and acceptable level of residual stresses in the bent components. Residual stresses that develop during manufacturing process in the railway turnout steel components can change their strength properties. The first part of this chapter presents ultrasonic measurement method and computer simulation that allowed to develop a method to diagnose state and distribution of residual stresses in steel components of the railway turnout (wing rails and switch blades) in the production process. The second part of this chapter includes experimental and simulation studies of superstructure in operational conditions. A track substructure with a crashed stone composite is a solution of reinforced standard track substructure. The results are used to draw conclusions concerning further development and possible modifications of a proposed solution. A significant number of simulation calculations also allow to determine the duration of guaranteed functionality of a reinforced track substructure.",book:{id:"4789",slug:"railway-research-selected-topics-on-development-safety-and-technology",title:"Railway Research",fullTitle:"Railway Research - Selected Topics on Development, Safety and Technology"},signatures:"Jacek Kukulski",authors:[{id:"175842",title:"Ph.D.",name:"Jacek",middleName:null,surname:"Kukulski",slug:"jacek-kukulski",fullName:"Jacek Kukulski"}]},{id:"49716",doi:"10.5772/62080",title:"A Systems View of Railway Safety and Security",slug:"a-systems-view-of-railway-safety-and-security",totalDownloads:4110,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"This chapter approaches the concerns over safety and security of modern mainline and light railways from a systems perspective. It addresses the two key concerns from the view point of systemic emergence arising from the interaction between all the principal constituents of the railway system, namely infrastructure, rolling stock, energy and human element comprising workers, passengers and the neighbours of the railways.",book:{id:"4789",slug:"railway-research-selected-topics-on-development-safety-and-technology",title:"Railway Research",fullTitle:"Railway Research - Selected Topics on Development, Safety and Technology"},signatures:"Ali G. Hessami",authors:[{id:"108303",title:"Prof.",name:"Ali G.",middleName:null,surname:"Hessami",slug:"ali-g.-hessami",fullName:"Ali G. Hessami"}]},{id:"57840",doi:"10.5772/intechopen.71768",title:"Advanced Train Positioning/Communication System",slug:"advanced-train-positioning-communication-system",totalDownloads:1660,totalCrossrefCites:3,totalDimensionsCites:3,abstract:"In the past, in order to ensure train positioning as well as ground-to-train information exchange, railways have adopted various technologies. Over time, each new generation of equipment enriched the global information exchange but, as a consequence, necessitated higher data rate transfers. For the positioning functionality, the existing localisation systems are still limited, since most of them require an infrastructure installation with constraints such as laying equipment between the rails or having high database maintenance requirements and computational costs. Moreover, some of them accumulate errors (odometers and inertial sensors) or offer limited coverage in shadowed areas (GNSS, etc.). Currently, in railway applications, a widely used localization system is based on proprioceptive sensors embarked in the train. This on-board system is coupled to the use of balises located at ground between the rails. These balises are kilometre markers. They are used to compensate for the drift of the localization information computed using the proprioceptive sensors alone, when the train moves. The balises provide absolute localization information whenever the train passes over them. They can also provide spot communication during the short period of time when trains are passing over them. In the first part of this chapter, techniques for achieving train positioning and data exchanges between trains and infrastructure are introduced. In the second part, a new balise is proposed. Particular attention is paid to the contribution of this new solution in terms of localization error and communication performances.",book:{id:"6065",slug:"modern-railway-engineering",title:"Modern Railway Engineering",fullTitle:"Modern Railway Engineering"},signatures:"Fouzia Elbahhar and Marc Heddebaut",authors:[{id:"140822",title:"Dr.",name:"Fouzia",middleName:null,surname:"Elbahhar",slug:"fouzia-elbahhar",fullName:"Fouzia Elbahhar"}]}],mostDownloadedChaptersLast30Days:[{id:"57056",title:"Transmission-Based Signaling Systems",slug:"transmission-based-signaling-systems",totalDownloads:3049,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"In this chapter, we describe the principal communication systems applied to the transmission-based signaling (TBS) systems for railways. Typical examples are communication-based train control (CBTC), European Rail Traffic Management System (ERTMS), and distance to go (DTG). Moreover, to properly address some of the challenges that need to face these systems, we will provide a deep insight on propagation issues related to all the environments (urban, suburban, rural, tunnel, etc.). We will highlight all the communication-related issues and the operational as well. Finally, a detailed survey on the directions of research on all these topics is provided, in order to properly cover this interesting subject. In this research, hot topics like virtual coupling are explained as well.",book:{id:"6065",slug:"modern-railway-engineering",title:"Modern Railway Engineering",fullTitle:"Modern Railway Engineering"},signatures:"Cesar Briso-Rodríguez, Juan Moreno García-Loygorri and Lei Zhang",authors:[{id:"171013",title:"Dr.",name:"Cesar",middleName:null,surname:"Briso",slug:"cesar-briso",fullName:"Cesar Briso"},{id:"216915",title:"Dr.",name:"Juan",middleName:null,surname:"Moreno Garcia-Loygorri",slug:"juan-moreno-garcia-loygorri",fullName:"Juan Moreno Garcia-Loygorri"},{id:"216916",title:"Dr.",name:"Lei",middleName:null,surname:"Zhang",slug:"lei-zhang",fullName:"Lei Zhang"}]},{id:"49375",title:"Experimental and Simulation Study of the Superstructure and Its Components",slug:"experimental-and-simulation-study-of-the-superstructure-and-its-components",totalDownloads:2553,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"The issues discussed in this chapter are of interest of both the manufacturers and the experts responsible for condition of the track superstructure. In general, stress in steel elements may affect the energy state, phase changes, and corrosion. It may reduce fatigue strength and cause damage and cracks of the rails. It is one of the causes of accelerated development of standard railhead defects. Proper selection of, e.g., bending process parameters provides uniform distribution and acceptable level of residual stresses in the bent components. Residual stresses that develop during manufacturing process in the railway turnout steel components can change their strength properties. The first part of this chapter presents ultrasonic measurement method and computer simulation that allowed to develop a method to diagnose state and distribution of residual stresses in steel components of the railway turnout (wing rails and switch blades) in the production process. The second part of this chapter includes experimental and simulation studies of superstructure in operational conditions. A track substructure with a crashed stone composite is a solution of reinforced standard track substructure. The results are used to draw conclusions concerning further development and possible modifications of a proposed solution. A significant number of simulation calculations also allow to determine the duration of guaranteed functionality of a reinforced track substructure.",book:{id:"4789",slug:"railway-research-selected-topics-on-development-safety-and-technology",title:"Railway Research",fullTitle:"Railway Research - Selected Topics on Development, Safety and Technology"},signatures:"Jacek Kukulski",authors:[{id:"175842",title:"Ph.D.",name:"Jacek",middleName:null,surname:"Kukulski",slug:"jacek-kukulski",fullName:"Jacek Kukulski"}]},{id:"59304",title:"Improving Feasibility of High-Speed Train Project: Creating Added Value",slug:"improving-feasibility-of-high-speed-train-project-creating-added-value",totalDownloads:1471,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"Infrastructure plays a significant role in increasing economic development by providing access of transportation and improving connectivity. High-speed train (HST), one of mega infrastructure projects, has a positive impact on economic development of a nation. However, the project feasibility requires the maximum value for money and an acceptable risk to attract private investors. This study aims to improve the feasibility of the project by producing a conceptual design of Jakarta-Surabaya high-speed train in Indonesia. Value engineering will be used to evaluate both technical and financial aspects of the project. The methodology uses both qualitative and quantitative approaches through a case study, in-depth interviews, and life-cycle cost analysis. The result shows an optimum route sketching for the project and potential added value to the project. It consists of the solar cell, fiber optic, tourism, and transit-oriented development. The output also generates the division of responsibility between the government and business entity during the project lifecycle regarding the project financing. The institutional scheme will regulate the position and roles for each related stakeholder that was involved in the HST project development.",book:{id:"6065",slug:"modern-railway-engineering",title:"Modern Railway Engineering",fullTitle:"Modern Railway Engineering"},signatures:"Mohammed Ali Berawi",authors:[{id:"207251",title:"Dr.",name:"Mohammed Ali",middleName:null,surname:"Berawi",slug:"mohammed-ali-berawi",fullName:"Mohammed Ali Berawi"}]},{id:"57840",title:"Advanced Train Positioning/Communication System",slug:"advanced-train-positioning-communication-system",totalDownloads:1660,totalCrossrefCites:3,totalDimensionsCites:3,abstract:"In the past, in order to ensure train positioning as well as ground-to-train information exchange, railways have adopted various technologies. Over time, each new generation of equipment enriched the global information exchange but, as a consequence, necessitated higher data rate transfers. For the positioning functionality, the existing localisation systems are still limited, since most of them require an infrastructure installation with constraints such as laying equipment between the rails or having high database maintenance requirements and computational costs. Moreover, some of them accumulate errors (odometers and inertial sensors) or offer limited coverage in shadowed areas (GNSS, etc.). Currently, in railway applications, a widely used localization system is based on proprioceptive sensors embarked in the train. This on-board system is coupled to the use of balises located at ground between the rails. These balises are kilometre markers. They are used to compensate for the drift of the localization information computed using the proprioceptive sensors alone, when the train moves. The balises provide absolute localization information whenever the train passes over them. They can also provide spot communication during the short period of time when trains are passing over them. In the first part of this chapter, techniques for achieving train positioning and data exchanges between trains and infrastructure are introduced. In the second part, a new balise is proposed. Particular attention is paid to the contribution of this new solution in terms of localization error and communication performances.",book:{id:"6065",slug:"modern-railway-engineering",title:"Modern Railway Engineering",fullTitle:"Modern Railway Engineering"},signatures:"Fouzia Elbahhar and Marc Heddebaut",authors:[{id:"140822",title:"Dr.",name:"Fouzia",middleName:null,surname:"Elbahhar",slug:"fouzia-elbahhar",fullName:"Fouzia Elbahhar"}]},{id:"49716",title:"A Systems View of Railway Safety and Security",slug:"a-systems-view-of-railway-safety-and-security",totalDownloads:4110,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"This chapter approaches the concerns over safety and security of modern mainline and light railways from a systems perspective. It addresses the two key concerns from the view point of systemic emergence arising from the interaction between all the principal constituents of the railway system, namely infrastructure, rolling stock, energy and human element comprising workers, passengers and the neighbours of the railways.",book:{id:"4789",slug:"railway-research-selected-topics-on-development-safety-and-technology",title:"Railway Research",fullTitle:"Railway Research - Selected Topics on Development, Safety and Technology"},signatures:"Ali G. Hessami",authors:[{id:"108303",title:"Prof.",name:"Ali G.",middleName:null,surname:"Hessami",slug:"ali-g.-hessami",fullName:"Ali G. 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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:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403",scope:"Artificial Intelligence (AI) is a rapidly developing multidisciplinary research area that aims to solve increasingly complex problems. In today's highly integrated world, AI promises to become a robust and powerful means for obtaining solutions to previously unsolvable problems. This Series is intended for researchers and students alike interested in this fascinating field and its many applications.",coverUrl:"https://cdn.intechopen.com/series/covers/14.jpg",latestPublicationDate:"June 11th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:9,editor:{id:"218714",title:"Prof.",name:"Andries",middleName:null,surname:"Engelbrecht",slug:"andries-engelbrecht",fullName:"Andries Engelbrecht",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNR8QAO/Profile_Picture_1622640468300",biography:"Andries Engelbrecht received the Masters and PhD degrees in Computer Science from the University of Stellenbosch, South Africa, in 1994 and 1999 respectively. He is currently appointed as the Voigt Chair in Data Science in the Department of Industrial Engineering, with a joint appointment as Professor in the Computer Science Division, Stellenbosch University. Prior to his appointment at Stellenbosch University, he has been at the University of Pretoria, Department of Computer Science (1998-2018), where he was appointed as South Africa Research Chair in Artifical Intelligence (2007-2018), the head of the Department of Computer Science (2008-2017), and Director of the Institute for Big Data and Data Science (2017-2018). In addition to a number of research articles, he has written two books, Computational Intelligence: An Introduction and Fundamentals of Computational Swarm Intelligence.",institutionString:null,institution:{name:"Stellenbosch University",institutionURL:null,country:{name:"South Africa"}}},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:29,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:9,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. His research interests include intelligent and embedded systems.",institutionString:"Universidad Autonoma de Queretaro",institution:{name:"Autonomous University of Queretaro",institutionURL:null,country:{name:"Mexico"}}}]},{type:"book",id:"7726",title:"Swarm Intelligence",subtitle:"Recent Advances, New Perspectives and Applications",coverURL:"https://cdn.intechopen.com/books/images_new/7726.jpg",slug:"swarm-intelligence-recent-advances-new-perspectives-and-applications",publishedDate:"December 4th 2019",editedByType:"Edited by",bookSignature:"Javier Del Ser, Esther Villar and Eneko Osaba",hash:"e7ea7e74ce7a7a8e5359629e07c68d31",volumeInSeries:2,fullTitle:"Swarm Intelligence - Recent Advances, New Perspectives and Applications",editors:[{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. 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He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. 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He is currently the Director of the Postgraduate Program in Implantology of the Bioface/UCAM/PgO (Montevideo, Uruguay), Director of the Cathedra of Biotechnology of the Catholic University of Murcia (Murcia, Spain), an Extraordinary Full Professor of the Catholic University of Murcia (Murcia, Spain) as well as the Director of the private center of research Biotecnos – Technology and Science (Montevideo, Uruguay). Applied biomaterials, cellular and molecular biology, and dental implants are among his research interests. He has published several original papers in renowned journals. In addition, he is also a Collaborating Professor in several Postgraduate programs at different universities all over the world.",institutionString:null,institution:{name:"Universidad Católica San Antonio de Murcia",country:{name:"Spain"}}},{id:"342152",title:"Dr.",name:"Santo",middleName:null,surname:"Grace Umesh",slug:"santo-grace-umesh",fullName:"Santo Grace Umesh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/342152/images/16311_n.jpg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"333647",title:"Dr.",name:"Shreya",middleName:null,surname:"Kishore",slug:"shreya-kishore",fullName:"Shreya Kishore",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/333647/images/14701_n.jpg",biography:"Dr. Shreya Kishore completed her Bachelor in Dental Surgery in Chettinad Dental College and Research Institute, Chennai, and her Master of Dental Surgery (Orthodontics) in Saveetha Dental College, Chennai. She is also Invisalign certified. She’s working as a Senior Lecturer in the Department of Orthodontics, SRM Dental College since November 2019. She is actively involved in teaching orthodontics to the undergraduates and the postgraduates. Her clinical research topics include new orthodontic brackets, fixed appliances and TADs. She’s published 4 articles in well renowned indexed journals and has a published patency of her own. Her private practice is currently limited to orthodontics and works as a consultant in various clinics.",institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"323731",title:"Prof.",name:"Deepak M.",middleName:"Macchindra",surname:"Vikhe",slug:"deepak-m.-vikhe",fullName:"Deepak M. Vikhe",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/323731/images/13613_n.jpg",biography:"Dr Deepak M.Vikhe .\n\n\t\n\tDr Deepak M.Vikhe , completed his Masters & PhD in Prosthodontics from Rural Dental College, Loni securing third rank in the Pravara Institute of Medical Sciences Deemed University. He was awarded Dr.G.C.DAS Memorial Award for Research on Implants at 39th IPS conference Dubai (U A E).He has two patents under his name. He has received Dr.Saraswati medal award for best research for implant study in 2017.He has received Fully funded scholarship to Spain ,university of Santiago de Compostela. He has completed fellowship in Implantlogy from Noble Biocare. \nHe has attended various conferences and CDE programmes and has national publications to his credit. His field of interest is in Implant supported prosthesis. Presently he is working as a associate professor in the Dept of Prosthodontics, Rural Dental College, Loni and maintains a successful private practice specialising in Implantology at Rahata.\n\nEmail: drdeepak_mvikhe@yahoo.com..................",institutionString:null,institution:{name:"Pravara Institute of Medical Sciences",country:{name:"India"}}},{id:"204110",title:"Dr.",name:"Ahmed A.",middleName:null,surname:"Madfa",slug:"ahmed-a.-madfa",fullName:"Ahmed A. Madfa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204110/images/system/204110.jpg",biography:"Dr. Madfa is currently Associate Professor of Endodontics at Thamar University and a visiting lecturer at Sana'a University and University of Sciences and Technology. He has more than 6 years of experience in teaching. His research interests include root canal morphology, functionally graded concept, dental biomaterials, epidemiology and dental education, biomimetic restoration, finite element analysis and endodontic regeneration. Dr. Madfa has numerous international publications, full articles, two patents, a book and a book chapter. Furthermore, he won 14 international scientific awards. Furthermore, he is involved in many academic activities ranging from editorial board member, reviewer for many international journals and postgraduate students' supervisor. Besides, I deliver many courses and training workshops at various scientific events. Dr. Madfa also regularly attends international conferences and holds administrative positions (Deputy Dean of the Faculty for Students’ & Academic Affairs and Deputy Head of Research Unit).",institutionString:"Thamar University",institution:null},{id:"210472",title:"Dr.",name:"Nermin",middleName:"Mohammed Ahmed",surname:"Yussif",slug:"nermin-yussif",fullName:"Nermin Yussif",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/210472/images/system/210472.jpg",biography:"Dr. Nermin Mohammed Ahmed Yussif is working at the Faculty of dentistry, University for October university for modern sciences and arts (MSA). Her areas of expertise include: periodontology, dental laserology, oral implantology, periodontal plastic surgeries, oral mesotherapy, nutrition, dental pharmacology. She is an editor and reviewer in numerous international journals.",institutionString:"MSA University",institution:null},{id:"204606",title:"Dr.",name:"Serdar",middleName:null,surname:"Gözler",slug:"serdar-gozler",fullName:"Serdar Gözler",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/204606/images/system/204606.jpeg",biography:"Dr. Serdar Gözler has completed his undergraduate studies at the Marmara University Faculty of Dentistry in 1978, followed by an assistantship in the Prosthesis Department of Dicle University Faculty of Dentistry. Starting his PhD work on non-resilient overdentures with Assoc. Prof. Hüsnü Yavuzyılmaz, he continued his studies with Prof. Dr. Gürbüz Öztürk of Istanbul University Faculty of Dentistry Department of Prosthodontics, this time on Gnatology. He attended training programs on occlusion, neurology, neurophysiology, EMG, radiology and biostatistics. In 1982, he presented his PhD thesis \\Gerber and Lauritzen Occlusion Analysis Techniques: Diagnosis Values,\\ at Istanbul University School of Dentistry, Department of Prosthodontics. As he was also working with Prof. Senih Çalıkkocaoğlu on The Physiology of Chewing at the same time, Gözler has written a chapter in Çalıkkocaoğlu\\'s book \\Complete Prostheses\\ entitled \\The Place of Neuromuscular Mechanism in Prosthetic Dentistry.\\ The book was published five times since by the Istanbul University Publications. Having presented in various conferences about occlusion analysis until 1998, Dr. Gözler has also decided to use the T-Scan II occlusion analysis method. Having been personally trained by Dr. Robert Kerstein on this method, Dr. Gözler has been lecturing on the T-Scan Occlusion Analysis Method in conferences both in Turkey and abroad. Dr. Gözler has various articles and presentations on Digital Occlusion Analysis methods. He is now Head of the TMD Clinic at Prosthodontic Department of Faculty of Dentistry , Istanbul Aydın University , Turkey.",institutionString:"Istanbul Aydin University",institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"240870",title:"Ph.D.",name:"Alaa Eddin Omar",middleName:null,surname:"Al Ostwani",slug:"alaa-eddin-omar-al-ostwani",fullName:"Alaa Eddin Omar Al Ostwani",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/240870/images/system/240870.jpeg",biography:"Dr. Al Ostwani Alaa Eddin Omar received his Master in dentistry from Damascus University in 2010, and his Ph.D. in Pediatric Dentistry from Damascus University in 2014. Dr. Al Ostwani is an assistant professor and faculty member at IUST University since 2014. \nDuring his academic experience, he has received several awards including the scientific research award from the Union of Arab Universities, the Syrian gold medal and the international gold medal for invention and creativity. Dr. Al Ostwani is a Member of the International Association of Dental Traumatology and the Syrian Society for Research and Preventive Dentistry since 2017. He is also a Member of the Reviewer Board of International Journal of Dental Medicine (IJDM), and the Indian Journal of Conservative and Endodontics since 2016.",institutionString:"International University for Science and Technology.",institution:{name:"Islamic University of Science and Technology",country:{name:"India"}}},{id:"42847",title:"Dr.",name:"Belma",middleName:null,surname:"Işik Aslan",slug:"belma-isik-aslan",fullName:"Belma Işik Aslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/42847/images/system/42847.jpg",biography:"Dr. Belma IşIk Aslan was born in 1976 in Ankara-TURKEY. After graduating from TED Ankara College in 1994, she attended to Gazi University, Faculty of Dentistry in Ankara. She completed her PhD in orthodontic education at Gazi University between 1999-2005. Dr. Işık Aslan stayed at the Providence Hospital Craniofacial Institude and Reconstructive Surgery in Michigan, USA for three months as an observer. She worked as a specialist doctor at Gazi University, Dentistry Faculty, Department of Orthodontics between 2005-2014. She was appointed as associate professor in January, 2014 and as professor in 2021. Dr. Işık Aslan still works as an instructor at the same faculty. She has published a total of 35 articles, 10 book chapters, 39 conference proceedings both internationally and nationally. Also she was the academic editor of the international book 'Current Advances in Orthodontics'. She is a member of the Turkish Orthodontic Society and Turkish Cleft Lip and Palate Society. She is married and has 2 children. Her knowledge of English is at an advanced level.",institutionString:"Gazi University Dentistry Faculty Department of Orthodontics",institution:null},{id:"178412",title:"Associate Prof.",name:"Guhan",middleName:null,surname:"Dergin",slug:"guhan-dergin",fullName:"Guhan Dergin",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178412/images/6954_n.jpg",biography:"Assoc. Prof. Dr. Gühan Dergin was born in 1973 in Izmit. He graduated from Marmara University Faculty of Dentistry in 1999. He completed his specialty of OMFS surgery in Marmara University Faculty of Dentistry and obtained his PhD degree in 2006. In 2005, he was invited as a visiting doctor in the Oral and Maxillofacial Surgery Department of the University of North Carolina, USA, where he went on a scholarship. Dr. Dergin still continues his academic career as an associate professor in Marmara University Faculty of Dentistry. He has many articles in international and national scientific journals and chapters in books.",institutionString:null,institution:{name:"Marmara University",country:{name:"Turkey"}}},{id:"178414",title:"Prof.",name:"Yusuf",middleName:null,surname:"Emes",slug:"yusuf-emes",fullName:"Yusuf Emes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178414/images/6953_n.jpg",biography:"Born in Istanbul in 1974, Dr. Emes graduated from Istanbul University Faculty of Dentistry in 1997 and completed his PhD degree in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery in 2005. He has papers published in international and national scientific journals, including research articles on implantology, oroantral fistulas, odontogenic cysts, and temporomandibular disorders. Dr. Emes is currently working as a full-time academic staff in Istanbul University faculty of Dentistry Department of Oral and Maxillofacial Surgery.",institutionString:null,institution:{name:"Istanbul University",country:{name:"Turkey"}}},{id:"192229",title:"Ph.D.",name:"Ana Luiza",middleName:null,surname:"De Carvalho Felippini",slug:"ana-luiza-de-carvalho-felippini",fullName:"Ana Luiza De Carvalho Felippini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192229/images/system/192229.jpg",biography:null,institutionString:"University of São Paulo",institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"256851",title:"Prof.",name:"Ayşe",middleName:null,surname:"Gülşen",slug:"ayse-gulsen",fullName:"Ayşe Gülşen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256851/images/9696_n.jpg",biography:"Dr. Ayşe Gülşen graduated in 1990 from Faculty of Dentistry, University of Ankara and did a postgraduate program at University of Gazi. \nShe worked as an observer and research assistant in Craniofacial Surgery Departments in New York, Providence Hospital in Michigan and Chang Gung Memorial Hospital in Taiwan. \nShe works as Craniofacial Orthodontist in Department of Aesthetic, Plastic and Reconstructive Surgery, Faculty of Medicine, University of Gazi, Ankara Turkey since 2004.",institutionString:"Univeristy of Gazi",institution:null},{id:"255366",title:"Prof.",name:"Tosun",middleName:null,surname:"Tosun",slug:"tosun-tosun",fullName:"Tosun Tosun",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255366/images/7347_n.jpg",biography:"Graduated at the Faculty of Dentistry, University of Istanbul, Turkey in 1989;\nVisitor Assistant at the University of Padua, Italy and Branemark Osseointegration Center of Treviso, Italy between 1993-94;\nPhD thesis on oral implantology in University of Istanbul and was awarded the academic title “Dr.med.dent.”, 1997;\nHe was awarded the academic title “Doç.Dr.” (Associated Professor) in 2003;\nProficiency in Botulinum Toxin Applications, Reading-UK in 2009;\nMastership, RWTH Certificate in Laser Therapy in Dentistry, AALZ-Aachen University, Germany 2009-11;\nMaster of Science (MSc) in Laser Dentistry, University of Genoa, Italy 2013-14.\n\nDr.Tosun worked as Research Assistant in the Department of Oral Implantology, Faculty of Dentistry, University of Istanbul between 1990-2002. \nHe worked part-time as Consultant surgeon in Harvard Medical International Hospitals and John Hopkins Medicine, Istanbul between years 2007-09.\u2028He was contract Professor in the Department of Surgical and Diagnostic Sciences (DI.S.C.), Medical School, University of Genova, Italy between years 2011-16. \nSince 2015 he is visiting Professor at Medical School, University of Plovdiv, Bulgaria. \nCurrently he is Associated Prof.Dr. at the Dental School, Oral Surgery Dept., Istanbul Aydin University and since 2003 he works in his own private clinic in Istanbul, Turkey.\u2028\nDr.Tosun is reviewer in journal ‘Laser in Medical Sciences’, reviewer in journal ‘Folia Medica\\', a Fellow of the International Team for Implantology, Clinical Lecturer of DGZI German Association of Oral Implantology, Expert Lecturer of Laser&Health Academy, Country Representative of World Federation for Laser Dentistry, member of European Federation of Periodontology, member of Academy of Laser Dentistry. Dr.Tosun presents papers in international and national congresses and has scientific publications in international and national journals. He speaks english, spanish, italian and french.",institutionString:null,institution:{name:"Istanbul Aydın University",country:{name:"Turkey"}}},{id:"171887",title:"Prof.",name:"Zühre",middleName:null,surname:"Akarslan",slug:"zuhre-akarslan",fullName:"Zühre Akarslan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/171887/images/system/171887.jpg",biography:"Zühre Akarslan was born in 1977 in Cyprus. She graduated from Gazi University Faculty of Dentistry, Ankara, Turkey in 2000. \r\nLater she received her Ph.D. degree from the Oral Diagnosis and Radiology Department; which was recently renamed as Oral and Dentomaxillofacial Radiology, from the same university. \r\nShe is working as a full-time Associate Professor and is a lecturer and an academic researcher. \r\nHer expertise areas are dental caries, cancer, dental fear and anxiety, gag reflex in dentistry, oral medicine, and dentomaxillofacial radiology.",institutionString:"Gazi University",institution:{name:"Gazi University",country:{name:"Turkey"}}},{id:"256417",title:"Associate Prof.",name:"Sanaz",middleName:null,surname:"Sadry",slug:"sanaz-sadry",fullName:"Sanaz Sadry",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/256417/images/8106_n.jpg",biography:null,institutionString:null,institution:null},{id:"272237",title:"Dr.",name:"Pinar",middleName:"Kiymet",surname:"Karataban",slug:"pinar-karataban",fullName:"Pinar Karataban",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/272237/images/8911_n.png",biography:"Assist.Prof.Dr.Pınar Kıymet Karataban, DDS PhD \n\nDr.Pınar Kıymet Karataban was born in Istanbul in 1975. After her graduation from Marmara University Faculty of Dentistry in 1998 she started her PhD in Paediatric Dentistry focused on children with special needs; mainly children with Cerebral Palsy. She finished her pHD thesis entitled \\'Investigation of occlusion via cast analysis and evaluation of dental caries prevalance, periodontal status and muscle dysfunctions in children with cerebral palsy” in 2008. She got her Assist. Proffessor degree in Istanbul Aydın University Paediatric Dentistry Department in 2015-2018. ın 2019 she started her new career in Bahcesehir University, Istanbul as Head of Department of Pediatric Dentistry. In 2020 she was accepted to BAU International University, Batumi as Professor of Pediatric Dentistry. She’s a lecturer in the same university meanwhile working part-time in private practice in Ege Dental Studio (https://www.egedisklinigi.com/) a multidisciplinary dental clinic in Istanbul. Her main interests are paleodontology, ancient and contemporary dentistry, oral microbiology, cerebral palsy and special care dentistry. She has national and international publications, scientific reports and is a member of IAPO (International Association for Paleodontology), IADH (International Association of Disability and Oral Health) and EAPD (European Association of Pediatric Dentistry).",institutionString:null,institution:null},{id:"202198",title:"Dr.",name:"Buket",middleName:null,surname:"Aybar",slug:"buket-aybar",fullName:"Buket Aybar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/202198/images/6955_n.jpg",biography:"Buket Aybar, DDS, PhD, was born in 1971. She graduated from Istanbul University, Faculty of Dentistry, in 1992 and completed her PhD degree on Oral and Maxillofacial Surgery in Istanbul University in 1997.\nDr. Aybar is currently a full-time professor in Istanbul University, Faculty of Dentistry Department of Oral and Maxillofacial Surgery. She has teaching responsibilities in graduate and postgraduate programs. Her clinical practice includes mainly dentoalveolar surgery.\nHer topics of interest are biomaterials science and cell culture studies. She has many articles in international and national scientific journals and chapters in books; she also has participated in several scientific projects supported by Istanbul University Research fund.",institutionString:null,institution:null},{id:"260116",title:"Dr.",name:"Mehmet",middleName:null,surname:"Yaltirik",slug:"mehmet-yaltirik",fullName:"Mehmet Yaltirik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/260116/images/7413_n.jpg",biography:"Birth Date 25.09.1965\r\nBirth Place Adana- Turkey\r\nSex Male\r\nMarrial Status Bachelor\r\nDriving License Acquired\r\nMother Tongue Turkish\r\n\r\nAddress:\r\nWork:University of Istanbul,Faculty of Dentistry, Department of Oral Surgery and Oral Medicine 34093 Capa,Istanbul- TURKIYE",institutionString:null,institution:null},{id:"172009",title:"Dr.",name:"Fatma Deniz",middleName:null,surname:"Uzuner",slug:"fatma-deniz-uzuner",fullName:"Fatma Deniz Uzuner",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/172009/images/7122_n.jpg",biography:"Dr. Deniz Uzuner was born in 1969 in Kocaeli-TURKEY. After graduating from TED Ankara College in 1986, she attended the Hacettepe University, Faculty of Dentistry in Ankara. \nIn 1993 she attended the Gazi University, Faculty of Dentistry, Department of Orthodontics for her PhD education. After finishing the PhD education, she worked as orthodontist in Ankara Dental Hospital under the Turkish Government, Ministry of Health and in a special Orthodontic Clinic till 2011. Between 2011 and 2016, Dr. Deniz Uzuner worked as a specialist in the Department of Orthodontics, Faculty of Dentistry, Gazi University in Ankara/Turkey. In 2016, she was appointed associate professor. Dr. Deniz Uzuner has authored 23 Journal Papers, 3 Book Chapters and has had 39 oral/poster presentations. She is a member of the Turkish Orthodontic Society. Her knowledge of English is at an advanced level.",institutionString:null,institution:null},{id:"332914",title:"Dr.",name:"Muhammad Saad",middleName:null,surname:"Shaikh",slug:"muhammad-saad-shaikh",fullName:"Muhammad Saad Shaikh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Jinnah Sindh Medical University",country:{name:"Pakistan"}}},{id:"315775",title:"Dr.",name:"Feng",middleName:null,surname:"Luo",slug:"feng-luo",fullName:"Feng Luo",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Sichuan University",country:{name:"China"}}},{id:"423519",title:"Dr.",name:"Sizakele",middleName:null,surname:"Ngwenya",slug:"sizakele-ngwenya",fullName:"Sizakele Ngwenya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of the Witwatersrand",country:{name:"South Africa"}}},{id:"419270",title:"Dr.",name:"Ann",middleName:null,surname:"Chianchitlert",slug:"ann-chianchitlert",fullName:"Ann Chianchitlert",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"419271",title:"Dr.",name:"Diane",middleName:null,surname:"Selvido",slug:"diane-selvido",fullName:"Diane Selvido",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"419272",title:"Dr.",name:"Irin",middleName:null,surname:"Sirisoontorn",slug:"irin-sirisoontorn",fullName:"Irin Sirisoontorn",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Walailak University",country:{name:"Thailand"}}},{id:"355660",title:"Dr.",name:"Anitha",middleName:null,surname:"Mani",slug:"anitha-mani",fullName:"Anitha Mani",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"355612",title:"Dr.",name:"Janani",middleName:null,surname:"Karthikeyan",slug:"janani-karthikeyan",fullName:"Janani Karthikeyan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}},{id:"334400",title:"Dr.",name:"Suvetha",middleName:null,surname:"Siva",slug:"suvetha-siva",fullName:"Suvetha Siva",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"SRM Dental College",country:{name:"India"}}}]}},subseries:{item:{id:"38",type:"subseries",title:"Pollution",keywords:"Human activity, Pollutants, Reduced risks, Population growth, Waste disposal, Remediation, Clean environment",scope:"\r\n\tPollution is caused by a wide variety of human activities and occurs in diverse forms, for example biological, chemical, et cetera. In recent years, significant efforts have been made to ensure that the environment is clean, that rigorous rules are implemented, and old laws are updated to reduce the risks towards humans and ecosystems. However, rapid industrialization and the need for more cultivable sources or habitable lands, for an increasing population, as well as fewer alternatives for waste disposal, make the pollution control tasks more challenging. Therefore, this topic will focus on assessing and managing environmental pollution. It will cover various subjects, including risk assessment due to the pollution of ecosystems, transport and fate of pollutants, restoration or remediation of polluted matrices, and efforts towards sustainable solutions to minimize environmental pollution.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/38.jpg",hasOnlineFirst:!1,hasPublishedBooks:!0,annualVolume:11966,editor:{id:"110740",title:"Dr.",name:"Ismail M.M.",middleName:null,surname:"Rahman",slug:"ismail-m.m.-rahman",fullName:"Ismail M.M. Rahman",profilePictureURL:"https://mts.intechopen.com/storage/users/110740/images/2319_n.jpg",biography:"Ismail Md. Mofizur Rahman (Ismail M. M. Rahman) assumed his current responsibilities as an Associate Professor at the Institute of Environmental Radioactivity, Fukushima University, Japan, in Oct 2015. He also has an honorary appointment to serve as a Collaborative Professor at Kanazawa University, Japan, from Mar 2015 to the present. \nFormerly, Dr. Rahman was a faculty member of the University of Chittagong, Bangladesh, affiliated with the Department of Chemistry (Oct 2002 to Mar 2012) and the Department of Applied Chemistry and Chemical Engineering (Mar 2012 to Sep 2015). Dr. Rahman was also adjunctly attached with Kanazawa University, Japan (Visiting Research Professor, Dec 2014 to Mar 2015; JSPS Postdoctoral Research Fellow, Apr 2012 to Mar 2014), and Tokyo Institute of Technology, Japan (TokyoTech-UNESCO Research Fellow, Oct 2004–Sep 2005). \nHe received his Ph.D. degree in Environmental Analytical Chemistry from Kanazawa University, Japan (2011). He also achieved a Diploma in Environment from the Tokyo Institute of Technology, Japan (2005). Besides, he has an M.Sc. degree in Applied Chemistry and a B.Sc. degree in Chemistry, all from the University of Chittagong, Bangladesh. \nDr. Rahman’s research interest includes the study of the fate and behavior of environmental pollutants in the biosphere; design of low energy and low burden environmental improvement (remediation) technology; implementation of sustainable waste management practices for treatment, handling, reuse, and ultimate residual disposition of solid wastes; nature and type of interactions in organic liquid mixtures for process engineering design applications.",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorTwo:{id:"201020",title:"Dr.",name:"Zinnat Ara",middleName:null,surname:"Begum",slug:"zinnat-ara-begum",fullName:"Zinnat Ara Begum",profilePictureURL:"https://mts.intechopen.com/storage/users/201020/images/system/201020.jpeg",biography:"Zinnat A. Begum received her Ph.D. in Environmental Analytical Chemistry from Kanazawa University in 2012. She achieved her Master of Science (M.Sc.) degree with a major in Applied Chemistry and a Bachelor of Science (B.Sc.) in Chemistry, all from the University of Chittagong, Bangladesh. Her work affiliations include Fukushima University, Japan (Visiting Research Fellow, Institute of Environmental Radioactivity: Mar 2016 to present), Southern University Bangladesh (Assistant Professor, Department of Civil Engineering: Jan 2015 to present), and Kanazawa University, Japan (Postdoctoral Fellow, Institute of Science and Engineering: Oct 2012 to Mar 2014; Research fellow, Venture Business Laboratory, Advanced Science and Social Co-Creation Promotion Organization: Apr 2018 to Mar 2021). The research focus of Dr. Zinnat includes the effect of the relative stability of metal-chelator complexes in the environmental remediation process designs and the development of eco-friendly soil washing techniques using biodegradable chelators.",institutionString:null,institution:{name:"Fukushima University",institutionURL:null,country:{name:"Japan"}}},editorThree:null,series:{id:"25",title:"Environmental Sciences",doi:"10.5772/intechopen.100362",issn:"2754-6713"},editorialBoard:[{id:"252368",title:"Dr.",name:"Meng-Chuan",middleName:null,surname:"Ong",slug:"meng-chuan-ong",fullName:"Meng-Chuan Ong",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRVotQAG/Profile_Picture_2022-05-20T12:04:28.jpg",institutionString:null,institution:{name:"Universiti Malaysia Terengganu",institutionURL:null,country:{name:"Malaysia"}}},{id:"63465",title:"Prof.",name:"Mohamed Nageeb",middleName:null,surname:"Rashed",slug:"mohamed-nageeb-rashed",fullName:"Mohamed Nageeb Rashed",profilePictureURL:"https://mts.intechopen.com/storage/users/63465/images/system/63465.gif",institutionString:null,institution:{name:"Aswan University",institutionURL:null,country:{name:"Egypt"}}},{id:"187907",title:"Dr.",name:"Olga",middleName:null,surname:"Anne",slug:"olga-anne",fullName:"Olga Anne",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBE5QAO/Profile_Picture_2022-04-07T09:42:13.png",institutionString:null,institution:{name:"Klaipeda State University of Applied Sciences",institutionURL:null,country:{name:"Lithuania"}}}]},onlineFirstChapters:{paginationCount:20,paginationItems:[{id:"80964",title:"Upper Airway Expansion in Disabled Children",doi:"10.5772/intechopen.102830",signatures:"David Andrade, Joana Andrade, Maria-João Palha, Cristina Areias, Paula Macedo, Ana Norton, Miguel Palha, Lurdes Morais, Dóris Rocha Ruiz and Sônia Groisman",slug:"upper-airway-expansion-in-disabled-children",totalDownloads:35,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Oral Health Care - An Important Issue of the Modern Society",coverURL:"https://cdn.intechopen.com/books/images_new/10827.jpg",subseries:{id:"1",title:"Oral Health"}}},{id:"80839",title:"Herbs and Oral Health",doi:"10.5772/intechopen.103715",signatures:"Zuhair S. 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