Summarized results for flow rates and water level (using high and low flows) [36].
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Belskaya, Irina G. Danilova, Maxim O. Kazakov, Roman M. Mironenko, Alexander V. Lavrenov and Vladimir A. 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Escobar Barrios, José R. Rangel Méndez, Nancy V. Pérez Aguilar, Guillermo Andrade Espinosa and José L. 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Teodor, Georgiana-Ileana Truica, Andreia Tache and Gabriel-Lucian Radu",authors:[{id:"24425",title:"Dr.",name:"Simona Carmen",middleName:null,surname:"Litescu",fullName:"Simona Carmen Litescu",slug:"simona-carmen-litescu"},{id:"24429",title:"Prof.",name:"Gabriel-Lucian",middleName:null,surname:"Radu",fullName:"Gabriel-Lucian Radu",slug:"gabriel-lucian-radu"},{id:"108318",title:"Dr.",name:"Eugenia D.",middleName:null,surname:"Teodor",fullName:"Eugenia D. Teodor",slug:"eugenia-d.-teodor"},{id:"108323",title:"Dr.",name:"Georgiana-Ileana",middleName:null,surname:"Badea",fullName:"Georgiana-Ileana Badea",slug:"georgiana-ileana-badea"},{id:"136337",title:"Ms.",name:"Andreia",middleName:null,surname:"Tache",fullName:"Andreia Tache",slug:"andreia-tache"}]},{id:"36184",title:"Infrared Spectroscopy in the Analysis of Building and Construction Materials",slug:"infrared-spectroscopy-of-cementitious-materials",signatures:"Lucia Fernández-Carrasco, D. Torrens-Martín, L.M. Morales and Sagrario Martínez-Ramírez",authors:[{id:"107401",title:"Dr.",name:"Lucia J",middleName:null,surname:"Fernández",fullName:"Lucia J Fernández",slug:"lucia-j-fernandez"}]},{id:"36185",title:"Infrared Spectroscopy Techniques in the Characterization of SOFC Functional Ceramics",slug:"infrared-spectroscopy-techniques-in-the-characterization-of-sofc-functional-ceramics",signatures:"Daniel A. Macedo, Moisés R. Cesário, Graziele L. Souza, Beatriz Cela, Carlos A. Paskocimas, Antonio E. Martinelli, Dulce M. A. Melo and Rubens M. Nascimento",authors:[{id:"102015",title:"MSc.",name:"Daniel",middleName:null,surname:"Macedo",fullName:"Daniel Macedo",slug:"daniel-macedo"},{id:"112309",title:"MSc",name:"Moisés",middleName:"Romolos",surname:"Cesário",fullName:"Moisés Cesário",slug:"moises-cesario"},{id:"112310",title:"Ms.",name:"Graziele",middleName:null,surname:"Souza",fullName:"Graziele Souza",slug:"graziele-souza"},{id:"112311",title:"MSc.",name:"Beatriz",middleName:null,surname:"Cela",fullName:"Beatriz Cela",slug:"beatriz-cela"},{id:"112312",title:"Prof.",name:"Carlos",middleName:null,surname:"Paskocimas",fullName:"Carlos Paskocimas",slug:"carlos-paskocimas"},{id:"112314",title:"Prof.",name:"Antonio",middleName:null,surname:"Martinelli",fullName:"Antonio Martinelli",slug:"antonio-martinelli"},{id:"112315",title:"Prof.",name:"Dulce",middleName:null,surname:"Melo",fullName:"Dulce Melo",slug:"dulce-melo"},{id:"112316",title:"Dr.",name:"Rubens",middleName:"Maribondo Do",surname:"Nascimento",fullName:"Rubens Nascimento",slug:"rubens-nascimento"}]},{id:"36186",title:"Infrared Spectroscopy of Functionalized Magnetic Nanoparticles",slug:"infrared-spectroscopy-of-functionalized-magnetic-nanoparticles",signatures:"Perla E. García Casillas, Claudia A. Rodriguez Gonzalez and Carlos A. Martínez Pérez",authors:[{id:"104636",title:"Dr.",name:"Perla E.",middleName:null,surname:"García Casillas",fullName:"Perla E. García Casillas",slug:"perla-e.-garcia-casillas"},{id:"112440",title:"Dr.",name:"Carlos A.",middleName:null,surname:"Martínez Pérez",fullName:"Carlos A. Martínez Pérez",slug:"carlos-a.-martinez-perez"},{id:"112441",title:"Dr.",name:"Claudia A.",middleName:null,surname:"Rodriguez Gonzalez",fullName:"Claudia A. Rodriguez Gonzalez",slug:"claudia-a.-rodriguez-gonzalez"}]},{id:"36187",title:"Determination of Adsorption Characteristics of Volatile Organic Compounds Using Gas Phase FTIR Spectroscopy Flow Analysis",slug:"determination-of-adsorption-characteristics-of-volatile-organic-compounds-using-gas-phase-ftir-spect",signatures:"Tarik Chafik",authors:[{id:"107310",title:"Prof.",name:"Tarik",middleName:null,surname:"Chafik",fullName:"Tarik Chafik",slug:"tarik-chafik"}]},{id:"36188",title:"Identification of Rocket Motor Characteristics from Infrared Emission Spectra",slug:"identification-of-rocket-motor-characteristics-from-infrared-emission-spectra",signatures:"N. Hamp, J.H. Knoetze, C. Aldrich and C. Marais",authors:[{id:"112229",title:"Prof.",name:"Chris",middleName:null,surname:"Aldrich",fullName:"Chris Aldrich",slug:"chris-aldrich"},{id:"112232",title:"Prof.",name:"Hansie",middleName:null,surname:"Knoetze",fullName:"Hansie Knoetze",slug:"hansie-knoetze"},{id:"135327",title:"Ms.",name:"Corne",middleName:null,surname:"Marais",fullName:"Corne Marais",slug:"corne-marais"}]},{id:"36189",title:"Optical Technologies for Determination of Pesticide Residue",slug:"optical-technology-for-determination-of-pesticide-residue",signatures:"Yankun Peng, Yongyu Li and Jingjing Chen",authors:[{id:"113343",title:"Prof.",name:"Yankun",middleName:null,surname:"Peng",fullName:"Yankun Peng",slug:"yankun-peng"},{id:"116636",title:"Dr.",name:"Yongyu",middleName:null,surname:"Li",fullName:"Yongyu Li",slug:"yongyu-li"},{id:"116637",title:"Dr.",name:"Jingjing",middleName:null,surname:"Chen",fullName:"Jingjing Chen",slug:"jingjing-chen"}]},{id:"36190",title:"High Resolution Far Infrared Spectra of the Semiconductor Alloys Obtained Using the Synchrotron Radiation as Source",slug:"high-resolution-spectra-of-semiconductor-s-alloys-obtained-using-the-far-infrared-synchrotron-radi",signatures:"E.M. Sheregii",authors:[{id:"102655",title:"Prof.",name:"Eugen",middleName:null,surname:"Sheregii",fullName:"Eugen Sheregii",slug:"eugen-sheregii"}]},{id:"36191",title:"Effective Reaction Monitoring of Intermediates by ATR-IR Spectroscopy Utilizing Fibre Optic Probes",slug:"effective-reaction-monitoring-of-intermediates-by-atr-ir-spectroscopy-utilizing-fibre-optic-probes",signatures:"Daniel Lumpi and Christian Braunshier",authors:[{id:"109019",title:"Dr.",name:"Christian",middleName:null,surname:"Braunshier",fullName:"Christian Braunshier",slug:"christian-braunshier"},{id:"111798",title:"MSc.",name:"Daniel",middleName:null,surname:"Lumpi",fullName:"Daniel Lumpi",slug:"daniel-lumpi"}]}]}],publishedBooks:[{type:"book",id:"1816",title:"The Biosphere",subtitle:null,isOpenForSubmission:!1,hash:"6a38f234b8fd53320d14fb1347954a23",slug:"the-biosphere",bookSignature:"Natarajan Ishwaran",coverURL:"https://cdn.intechopen.com/books/images_new/1816.jpg",editedByType:"Edited by",editors:[{id:"114574",title:"Dr.",name:"Natarajan",surname:"Ishwaran",slug:"natarajan-ishwaran",fullName:"Natarajan Ishwaran"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6062",title:"Advances in Bioremediation and Phytoremediation",subtitle:null,isOpenForSubmission:!1,hash:"7b537906414bbdbbe7a318c5702ef67e",slug:"advances-in-bioremediation-and-phytoremediation",bookSignature:"Naofumi Shiomi",coverURL:"https://cdn.intechopen.com/books/images_new/6062.jpg",editedByType:"Edited by",editors:[{id:"163777",title:"Dr.",name:"Naofumi",surname:"Shiomi",slug:"naofumi-shiomi",fullName:"Naofumi Shiomi"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"6699",title:"Community and Global Ecology of Deserts",subtitle:null,isOpenForSubmission:!1,hash:"3f9477aa1d898626573100c92fa392e7",slug:"community-and-global-ecology-of-deserts",bookSignature:"Levente Hufnagel",coverURL:"https://cdn.intechopen.com/books/images_new/6699.jpg",editedByType:"Edited by",editors:[{id:"10864",title:"Dr.",name:"Levente",surname:"Hufnagel",slug:"levente-hufnagel",fullName:"Levente Hufnagel"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"8058",title:"Natural History and Ecology of Mexico and Central America",subtitle:null,isOpenForSubmission:!1,hash:"604d5be911d1225699383acef2a50dae",slug:"natural-history-and-ecology-of-mexico-and-central-america",bookSignature:"Levente Hufnagel",coverURL:"https://cdn.intechopen.com/books/images_new/8058.jpg",editedByType:"Edited by",editors:[{id:"10864",title:"Dr.",name:"Levente",surname:"Hufnagel",slug:"levente-hufnagel",fullName:"Levente Hufnagel"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}],publishedBooksByAuthor:[{type:"book",id:"1816",title:"The Biosphere",subtitle:null,isOpenForSubmission:!1,hash:"6a38f234b8fd53320d14fb1347954a23",slug:"the-biosphere",bookSignature:"Natarajan Ishwaran",coverURL:"https://cdn.intechopen.com/books/images_new/1816.jpg",editedByType:"Edited by",editors:[{id:"114574",title:"Dr.",name:"Natarajan",surname:"Ishwaran",slug:"natarajan-ishwaran",fullName:"Natarajan Ishwaran"}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},onlineFirst:{chapter:{type:"chapter",id:"80843",title:"Understanding the Role of Constructed Wetlands in Stormwater Management",doi:"10.5772/intechopen.102912",slug:"understanding-the-role-of-constructed-wetlands-in-stormwater-management",body:'Whilst constructed wetlands have been utilized for some time in the treatment of wastewater, they only gained popularity for the treatment of stormwater runoff and flood protection in the last couple of decades [1, 2]. Constructed wetlands are employed to remove sediment and nutrients, primarily phosphorus and nitrogen, from contaminated water [1]. However, with increased urbanization and enhanced climate change, these constructed wetlands need to be managed and their treatment effectiveness monitored and maintained once these are established.
Constructed wetlands remove sediments using large ponds which allow for dissipation of water velocities, making sediment particles drop out of the water column, settling at the bottom of the basin which is then supposed to be cleaned regularly [1]. The removal of nutrients by constructed wetlands is varied and complex and is understood to be primarily undertaken by anoxic microbial degradation processes within the wetland environment [3]. Secondary to this, plants also capture nitrogen and remove it from the system through various methods such as volatilization and phytodegradation [1]. Wetland performance in treating stormwater is generally a function of hydraulic loading rate and detention time and these two parameters are in turn functions of the runoff volume, storm intensity and the wetland size itself [4]. Sizing the wetland is crucial for the health of the wetland treatment system. The hydrodynamic criteria of wetlands such as the inundation depth, wetness gradient, base flow and hydraulic regime are crucial for wetland sizing. If these hydrodynamic characteristics receive inadequate attention, the performance of treating stormwater is likely to be reduced.
Constructed wetlands also provide a retarding function, and therefore can be utilized to assist in flood protection in urban areas. As wetlands are generally controlled by a pit and a piped outlet, they can act under the same principle as a retarding basin by discharging flood flows at a controlled rate. With more wetlands being constructed and restored widely, flood storage capacity is increased, and the flood peak is reduced. Constructed wetlands and the restoration of wetlands have come into wide practice as they have the potential to act as an effective water treatment basin as well as provide essential flood control [5].
In Australia, particularly in metropolitan areas, constructed wetlands have become a common occurrence [3]. There is a multitude of reasons why wetlands have increased in popularity over the years, some reasons include their effectiveness in treating stormwater, their ability to treat large areas, scalability, their cost-effectiveness, ease of maintenance, and because they can act as a feature [6, 7]. Perhaps the main driver for their increase in popularity in Victoria, Australia is the legislation that requires all new developments to treat the additional runoff caused by the newly installed impervious surfaces to acceptable levels so that the concentrations of nutrients in receiving waters are not compromised [8].
The Best Practice Guidelines recommend the removal of 80% TSS (Total suspended solids) [9]. This is generally managed practically by sizing a constructed wetland to treat 100% of rainfall flows up to 1 in 3 months ARI rainfall intensity, which in Victoria represents on average 80% of the total annual rainfall [10]. Depending on the design, i.e., if the wetlands are constructed “online” as opposed to “offline”, constructed wetlands may experience inflows from larger rainfall intensities. However, the best practice guidelines do not consider detention characteristics of the wetlands.
To date, there has been limited research into constructed wetlands treating flows larger than its design intent. Whilst there have been studies which investigate the capabilities of constructed wetlands over long periods, e.g., 2 years, which cover a range of storms [11, 12], there appears to be little research directly focusing on the treatment that occurs from wetlands receiving flows larger than their design capacities.
Urban Stormwater: Best Practice Environmental Management (BPEM) Guidelines [9] outline the principles and objectives behind the use of water treatment devices such as wetlands by referencing SEPPs (State Environmental Protection Policies) of Victoria, Australia. These objectives are clear: to preserve the beneficial uses of local waterways, including:
natural aquatic ecosystems and associated wildlife;
water-based recreation;
agricultural water supply;
potable water supply;
production of mollusks for human consumption;
commercial and recreational use of edible fish and crustacea; and
industrial water use.
As urbanization increases, so too does the anthropogenic environmental impact, which includes pollutants occurring from human lifestyle activities, building and infrastructure, construction activities [9], urban vehicular emissions and increased stormwater runoff volume peaks and nutrient loads due to hard surface runoffs inherent in typical urban development [13]. Constructed wetlands, as part of a SUDS (Sensitive Urban Drainage System) can be used to mitigate these impacts [14], and within Victoria, Australia they are typically installed as part of large-scale urban developments to comply with the BPEM guidelines.
Wetlands are cost-effective treatment systems that can be used to treat urban stormwater runoff. The advantages for installation of constructed wetlands, including “(1) low cost of construction, and, especially, maintenance; (2) low energy requirements; (3) being a ‘low-technology’ system, they can be established and run by relatively untrained personnel; and (4) the systems are usually more flexible and less susceptible to variations in loading rate than conventional treatment systems” [3]. In addition, “the major disadvantages of constructed wetland treatment systems are the increased land area required, compared to conventional systems, and the possible decreased performance during winter in temperate regions” [3]. Under Melbourne Water’s drainage Schemes, landowners and developers are fairly compensated for land use dedicated to wetlands, thus mitigating the disadvantage of the increased land area required [15]. As wetlands are integrated into large-scale urban development design and construction, they are typically designed to receive flows up to the 1 in 3-month ARI rainfall to minimize land take whilst treating to best practice.
To enable efficient operation and maintenance of constructed wetlands, the current practice is to split the treatment processes into separate zones; the sediment pond and macrophyte zone. Figure 1 shows the design layout for constructed wetlands within Melbourne as per the guideline and Figure 2 indicates the sediment storage pond.
Constructed wetland diagram [
Sediment pond storage [
The sediment pond is utilized to remove sediments before the wetland. Current design guidelines require that sediment ponds shall be sized to retain 95% of sand particles (i.e., particles down to 125 μm) during a 1 in 3-month ARI rainfall event [16]. Regular cleanout of retained sediment is required whenever retained sediment levels reach 500 mm below the normal water level (NWL) [17]. There is conjecture as to how well this maintenance is carried out, as many existing constructed wetlands do not receive regular sediment maintenance.
Secondly, the Macrophyte Zone (shallow water-filled ponds planted with aquatic plants) is utilized to contain the remaining sediments not captured by the sediment pond by the velocity reducing and filtering effect of Macrophyte (aquatic plant) stems and root systems [18].
The macrophyte zone removes nitrogen through the Nitrification–denitrification process [19, 20]. Sediment ponds also provide limited nutrient treatment. This includes an attachment of approx. 15% of Total Nitrogen (TN) and Total Phosphorus (TP) to particles larger than 300 um [21], and small amounts via anoxic biochemical processes [3]. Studies on the Prado wetlands in California USA suggest that constructed wetlands have, on average, 50–60% TN removal [22].
Phosphorus removal is primarily through sorption by clay, and typically will reach a saturation point after which phosphorus can leach back into the water it should be treating [23], and upon reaching this point, wetland clay materials should be replaced. Additional sorption can be achieved via decomposed plant matter [23]. Studies on the Prado wetlands in California USA suggest that constructed wetlands have, on average, 40–50% TP removal [22].
Standard wetland designs in Victoria include two typical layouts: online wetlands with the sediment pond receiving unrestricted flows and the macrophyte zone receiving controlled flows, and alternatively, offline wetlands where flows into the wetland can be restricted using a diversion pit [16]. Online flows include the total runoff from a catchment area. Offline flows divert a volume of the flow up to a certain amount, and the remaining flow bypasses the wetland. If a wetland does not include a sediment pond, then the bypass can be managed via a pit arrangement with suitable baffle, invert levels and pipe sizes to suit the urban catchment area.
Wetlands that are receiving an online flow passing through the Macrophyte zone are at risk of having collected sediments and nutrients dislodged and washed downstream during peak flows [16]. Standard wetland design practice includes a bypass channel to prevent this occurrence as shown in Figure 3.
Schematic diagram of a constructed wetland, adapted from [
Severe flood events can be distinguished as a natural disaster as its effect includes damages to properties and agricultural lands and in some cases loss of life. Flooding may be caused by dam failures, snow melts and when a large amount of rainfall occurs, and the natural waterways do not have enough capacity to convey excess water and result in overland flow. Overland flow can result from two hydrological processes: the first process is through a big storm event, where the rainfall intensity is large and it cannot infiltrate into the soil and the other process is when the soil is oversaturated - where there is no more capacity for the soil to hold extra rainwater [5]. Rain that falls onto the surface can either go through the evaporation process, get infiltrated into the soil, run along the impervious surfaces or get captured in hollows surface of the ground or wetlands. In the last 150 years, we have lost almost 70% of the capacity of the soil to hold water due to developments being built and more impervious areas installed [24]. This capacity needs to be restored to reduce the amount of overland flows and the risk of properties and people getting inundated. To minimize the risk of flooding and to protect assets and properties downstream, engineers have manipulated the use of constructed wetlands for flood mitigation and control.
In the past, engineers used structural restraints such as levees, which is not always the optimal solution to prevent flooding. Unfortunately, levees tend to hold up water which can significantly increase the level of the river stage and increase the flood velocity. There are a few flood cases where flood water would surge and overtops levees like the flood event in 1993 along the Mississippi River and Missouri River [24]. The flooding in mid-July 1993 from the Mississippi River and Missouri River exceeded the 100-year average recurrence interval (ARI) and had caused major properties damage cost of between US$ 12 billion–US$ 16 billion and approximately 32 losses of life [25]. As more areas are being inundated by overland flow and more properties are damaged, engineers have re-evaluated the situation and have considered other alternatives for flood mitigation plans and developing effective floodplain management programs. The aftermath of the great flooding of the Mississippi and Missouri River, wetlands have been considered as part of the flood management and flood mitigation process [26]. Wetlands have been installed and restored in many areas by the US federal government and the US Army Corps of Engineers in the United States and flooding at the downstream of the rivers was reported to have been reduced [27].
Constructed wetlands and the restoration of wetlands have come into wide practice as they have the potential to act as an effective water treatment basin as well as providing essential flood control. Wetland can alter flooding in many ways such as reducing the peak flood water level, the timing of flood water can be delayed, or the flows can be reduced by providing flood storage [5]. The location of wetlands is important for implementing flood protection. Wetlands that are located at an upstream location, the wetland will mainly be affected by headwater from rainfall, whereas wetlands that are located at the downstream location will mostly be affected by river flow. Constructed wetland at the downstream locations is often dry before a storm event therefore it has the potential to store more water during a storm event [5].
The sizing of wetlands is also equally important to the location of wetlands where continuous hydrologic modeling must be undertaken to simulate wetland storage during major storm events. Moreover, the time of concentration that a large flood needs to reach the wetlands must be taken into consideration. With the right computed concentration time, it can help reduce flooding at the downstream location just before the flood peaks [26]. Like a retarding basin, flood water that is stored in wetlands helps to delay the peak time of downstream hydrograph by releasing its water slowly and in a controlled manner. According to [26], the drainage of wetlands can influence flood levels where the storage of water attenuates and potentially delay downstream flood peaks.
Constructed wetlands are designed to replicate natural wetlands such as meadows, saltwater marshes, forested wetlands, and bogs. Aquatic or wetlands plants are used in constructed wetlands not only to reduce the amount of pollutants for stormwater quality but also to offer an ecological habitat to a wide range of wildlife species. Moreover, wetlands plants can create great landscape features and recreational amenities for the community [28]. Wetlands not only act as a flood storage but also have the capability to reduce the velocity of flood water with the influence of wetlands plants or vegetation. According to [29], velocities of flood water through wetlands are usually delayed by a friction factor which is influenced either by the slope, depth and/or the vegetation type (density and height of plants). This friction factor also known as the Manning’s roughness coefficient developed by Chow in 1959 is widely applied by engineers to calculate the resistance of flow in open channels.
Velocity rate can be altered depending on the surface roughness where a higher Manning’s value can significantly reduce the velocity of water. This can be seen in Manning’s equation where velocity is respectively proportional to the roughness coefficient [29]. Wetland’s riparian or vegetation have higher Manning’s value (“
Schematic elevation view of a wetland emergent plant (adapted from [
The importance of wetlands for flood mitigation is now recognized and understood widely. [31] performed a hydraulic simulation on evaluating the flood mitigation potential of wetlands for the “Charles River, Neponset River and Ten Mile River in Massachusetts”. From the simulation, the results implied that both upstream and downstream wetland locations altered peak flows and reduced flooding. Another study of wetland’s role for flood mitigation was done for the Red River Valley major flood in 1997 and the damage cost by the flood that year was US$ 3.5 billion. The study concluded that a 5% increase in wetland area would significantly reduce flood volume by 5.6% for the 1997 flood event and also reduce the amount of damage cost [32]. Moreover, the restoration of wetlands within the Devils Lake basin of North Dakota could potentially store 72% for the 2 Year ARI storm event and 41% for the 100 Year ARI storm event of total runoff and the US Corps of Engineers calculated that flood damage cost (Approximately US$ 17 million) can be prevented each year with the use of wetlands for flood mitigation [5]. Wetlands are not only used to treat stormwater but also play an important part in reducing flood peaks and flooding at the downstream locations.
The most crucial part of designing wetlands is the sizing of wetlands. It is recommended that the capacity of a wetland should be at least 3% of its catchment size or can take 1 in 3 months flow to remove pollutants within the guidelines for stormwater quality treatment [17]. Since there is limited research on wetlands receiving flows larger than their design intent, this section will review the following fundamental questions:
The duration and frequency of overland flow (water regime) can be a major influence on the development of wetland plants. In Australia, wet to dry seasonal changes cause different water levels each season which can potentially affect plant growth and responses [33]. Wetlands plants are utilized to prevent erosion, capture fine particles and to trap pollutants from runoff [3, 17].
An experiment was done to determine whether the depth, duration and frequency of flooding influence the development of wetlands plants. The experiment was done with different combinations of depth, duration, and frequency of flooding with different types of wetlands plants collected from (a) wetlands that are rarely dry (near permanent) and (b) poorly drained wetlands (intermittent) in New South Wales [33]. All 17 treatments were placed outdoor in uncovered tanks to allow the plants to be exposed to rainfall and some tanks were filled with water depending on the treatment. According to [33], the experiment was conducted for more than 16 weeks using different combinations to maximize results as plants are well established after this period of time. The results show that the depth of flooding does have a significant impact on the biomass and the different species of wetland plants for both wetland types (near permanent and intermittent) and the results of the durations of inundated plants varied between plants from the two wetlands.
The results indicated that the inundated plants from the near-permanent wetlands show no difference between different durations of flooding (4, 8 and 12 weeks) whereas plants from the intermittent wetlands show there was a decline in some species of plants. As for the flooding frequency, no significant impact on plants establishments for all 17 treatments for plants that are from the near-permanent wetland but for the plants from the intermittent wetlands some decline of plants species are reported. The highest biomass and the vast plant species can be seen from the treatment tank that were never flooded [33]. According to [34] some wetland plants species are sensitive to the change of water level and could cause a distinct loss in its species which are caused by oxygen depletion and the ability to go through the photosynthesis process when it is fully submerged. Therefore, depending on the wetland type (near permanent and intermittent) wetlands plants that are frequently flooded can have an adverse effect on the treatment process.
According to [35], “A distribution of times that parcels of water spend in a constructed wetland is known as a residence time distribution”. The residence time distribution (RTD) is a tool that has been used widely by engineers to measure wetland’s characteristic that could affect its treatment capabilities. Retention or residence time can be calculated as retention time = (area
Twelve experiments were conducted with different sets of water levels and flow rates, over a period of 13 weeks by adding 15 l of dye to the inlet of the constructed wetland. The average depth of water is 166 and 398 mm for low and high-water levels respectively. The results of this study indicated that there was no significant difference for the RTD values between the high and low flow rates (Table 1). There was however a significant difference for the RTD between the high and low water depth, the low water level result in distribution with one clear peak value whereas the higher water level result in a continuous probability with two different peaks. According to [36], the value differences are reflected in Table 1 for the water levels are significant. The mean RTD spread, o2e, values changed significantly when the water level changed from low to high. However, the change for the RTD centroid of the first moment,
Flow rates | Water levels | |||
---|---|---|---|---|
Parameters | High flows | Low flows | High flows | Low flows |
Peak concentration time. | 0.25 | 0.22 | 0.19 | 0.29 |
Min. travel time of tracer dye, | 0.12 | 0.11 | 0.15 | 0.077 |
RTD centroid of first moment, | 0.53 | 0.51 | 0.49 | 0.55 |
Normalized variance of RTD, | 0.65 | 0.55 | 0.73 | 0.47 |
Summarized results for flow rates and water level (using high and low flows) [36].
All values are unitless.
This study concluded that the residence time distribution changed significantly with the change of water levels but not so much with different flow rates. Moreover, a little change in the volume can influence the RTD characteristic in a constructed wetland because the volume is a function of depth. Depth or volume - of water effects the hydraulic efficiency of a constructed wetland and should be considered during the designing of wetlands [36]. Poor designing or sizing of wetland can affect its treatment performance. From this study, it can be stated that with the change of depth and volume in wetlands, the treatment process will be affected therefore the water quality can be assumed to be poor.
The modeling of stormwater pollutants in runoff and the modeling of Stormwater Quality Treatment (SWQT) assets has developed significantly over the years. The first modeling primarily consisted of relatively simple mathematical equations which were considered somewhat crude, now software programs model many of the complex interactions which occur through the stormwater runoff and treatment process, via user-friendly interfaces [37]. Within Australia, the most widely used SWQT modeling program is MUSIC [38]. MUSIC is a stochastic model which utilizes probability to help determine the pollutants in stormwater runoff and the performance of SWQT assets [39]. Consistent with the rest of Australia, in the Melbourne region MUSIC is also the SWQT modeling software of choice. To approve new SWQT assets and to assess whether a new development is meeting best practices, Melbourne Water and Councils throughout Melbourne require a MUSIC model [40].
However, even though MUSIC models are a requirement by Councils and the major water authority within the Melbourne region, some research suggests that MUSIC models are not completely accurate and may over-treat or under-treat depend on the situation [38, 41]. In their paper Modeling stormwater treatment systems using MUSIC: Accuracy [41] undertook a series of comparisons between existing SWQT assets (located in Australia, Sweden, and New Zealand} and MUSIC models which had been created, with modified parameters to represent the actual conditions (e.g., inflows concentrations) and existing assets. They found that depending on the type of treatment asset, the accuracy of the MUSIC model may vary; in some cases, the MUSIC models overestimated treatment whereas in other cases the modeling underestimated the treatment. It should be noted that the study did not investigate MUSIC’s ability to accurately model wetlands, a topic which requires further examination, however, it does call into question MUSIC’s ability to create accurate models and may provide a portion of the answer to the research question.
The uncertainty of the accuracy of MUSIC SWQT modeling could be due to setting up and calibrating the model. Several studies have found that some of the parameters in MUSIC, e.g., soil storage and field capacity, are crucial for obtaining accurate results and require calibrating based on local data [38, 39]. When creating MUSIC models, errors may occur in the modeling when the user uses the default MUSIC parameters, accidently inputs the incorrect parameters, is unaware of the correct parameters to input, or intentionally inputs the wrong values. To mitigate these potential human errors and improve the quality of MUSIC modeling, Melbourne Water produced MUSIC guidelines, which state the parameters to be used when creating a MUSIC model and general information about SWQT modeling elements. Whilst Melbourne Water’s MUSIC Guidelines provide some recommended parameters, [38, 42] recommend further research into assessing the parameters required in MUSIC for catchments with “similar land use, climatic characteristics and hydrological behavior”.
The condition of the wetland could contribute to why modeling results may differ from wetlands. Wetland conditions that may influence the performance of the wetland include bad construction, outlet blockages, modification of the terrain by animals, etc. [6, 37]. Models must make some assumptions and they generally assume that assets will function as in intended. However, this is not always the case as there are many operational factors that affect the functioning of a wetland.
To assess whether a comparison between the modeling and real-life conditions should occur, the first aspect that has to be determined is if the wetland is fully developed. [37] state that it can take more than 2 years for the wetland to develop fully. This is the duration required for the bio-system to mature, which requires amongst many other things the build-up of a layer of plant detritus over the base of the wetland so that congregations of periphyton and bacteria can form. The congregations of periphyton and bacteria are essential as these organisms’ form part of the nutrient removal process [37]. Thus, if sampling is undertaken before the wetland is fully developed, it may not be reflective of the future potential of the wetland as the bio-system has not matured and is not working to full capacity.
Another aspect that is of importance to the timing of the sampling, is the change of seasons. As plants are seasonal and sprout and perish on an annual basis, the natural biological process dictates that there will be fluctuations in concentrations of nutrients due to the cycling, uptake and release of nutrients, by the plants [37]. Spring generally produces higher uptake of nutrients as the plants are growing and absorb more nutrients in this period whereas in autumn plants are generally dyeing-off and their decaying litter releases nutrients in the waterways [37]. As a result, depending on the timing of the sampling, the same fully developed wetland may produce significant results. However, [12] found that in their two-year study covering all seasons, there was no increase in nitrogen concentrations over the autumn and winter period, which raised the question that there may be other nitrogen removing mechanisms at play. Although, to mitigate this potential error, it is suggested that long-term sampling occurs so that a baseline performance can be determined which takes into account seasonal fluctuations [43].
One aspect which plays a crucial role in the condition of the wetland is maintenance. Regular maintenance is vital to the performance of a wetland as it facilitates the correct functioning of the wetland [37]. One maintenance task which enables the proper functioning of a wetland, is the cleaning-out of the sediment pond [16]. If the sediment pond fills up beyond its designed depth, the sediment pond may not have the required depth for sediment to settle and therefore the sediment will remain suspended in the water [37]. This suspended sediment may flow into the macrophyte zone and settle, or it may remain suspended and resist treatment. This has various implications to the effectiveness of the wetland, one being that if sediment settles on the base of the macrophyte zone and builds up, the water velocities in the macrophyte zone may increase due to the smaller flow area, which may cause erosion or impact on detention times [37]. Additionally, the makeup of plants in the macrophyte zone may change due to the lack of habitat, e.g., there may be no deep marsh plants, due to sediment changing the makeup of this zone to the shallow marsh.
Another way in which maintenance can impact the performance of a wetland is through the outlet structure. The outlet structure may become blocked due to litter or the natural decay of plant species. This blockage may result in the water level to rise for extended periods of time which can kill off a number of the plant species that inhabit the wetland [37]. Similarly, without regular maintenance of the wetlands, certain plants such as Typha may grow rampant and effect the hydraulic efficiency of the wetland. In doing so it may cause the water level to rise and kill off several plants [37]. To prevent this, it is suggested that scheduled maintenance of the wetland is to occur.
Another area that may add to the differences between modeling and existing wetlands is in the sampling and testing. There are many aspects that need to be controlled to obtain accurate results. An important factor which must be taken into consideration to obtain an accurate result is frequency of the sampling. In one study it was found that “to sample TSS adequately within a storm event, at least 12 flow-weighted samples were required, and that polluto graphs of seven storm events needed to be sampled within a year to estimate mean annual loads at a reasonable level of accuracy” [43]. Building on this research [43] recommend that to have an error of less than 10% for sediment sampling, sampling must occur every three days or less for TSS–TN and TP will be different.
Differences between the modeling and actual results may result from the contamination of samples. This could occur in a multitude of ways hence the samplers must be vigilant and follow the protocols when proceeding to take samples. The following are some examples of ways that contamination may occur [44]:
Through disturbing the sediment/wetland base when sampling by placing the sample container too deep.
Dirty hands or instruments that take the sample may contaminate the water when sampling;
Sampling equipment is contaminated either through poor cleaning or coming into contact with other media before sampling.
Whilst there are no formal policies requiring wetlands there are policies that promote stormwater quality treatment to meet mandatory sediment and nutrient concentrations defined in statutory policies. The Environmental Protection Agency (EPA) has created the State Environment Protection Policies (SEPP), and of relevance to wetland policy is the SEPP Waters of Victoria [8]. The SEPP Waters of Victoria outline the required concentrations of sediment and nutrients in waterways and larger receiving bodies, such as Port Phillip Bay and Western Port, for waters to be considered healthy. In addition to the main policy, there are various Schedules that provide unique requirements for specific catchments, e.g., SEPP Schedule F6 relates to the water quality requirements of waters for Port Phillip Bay, SEPP Schedule F7 relates specific requirements of the Yarra catchment, etc. These policies are statutory under Section 16 of the Environment Protection Act 1970 [8]. The information provided in the SEPPs indicates what the receiving water’s concentrations of pollutants should be [45]. Whilst this information is useful for providing guidelines for testing it provides little guidance on what stormwater quality treatment is required for new urban developments to maintain these concentrations in the receiving bodies [45]. To try and bridge this gap, the EPA and a panel of stakeholders and experts, which included the Department of Sustainability and Environment, Melbourne Water, Municipal Association of Victoria and local government, were engaged to develop the Best Practice Environmental Management (BPEM) guidelines, which provides a pragmatic methodology for maintaining the concentrations of sediment and nutrients listed in the SEPPs [8, 9].
Rather than produce guidelines that have a focus on concentrations, the BPEM guidelines promote performance objectives that utilize a sediment and nutrient load reduction procedure, and if followed, should maintain the concentrations listed in the SEPPs [9, 45]. Table 2 defines the required load reductions by SWQT assets to meet the BPEM objectives and subsequently meet the SEPP (Waters of Victoria) concentration requirements.
Pollutant | Receiving water objective | Current best practice performance objective |
---|---|---|
Suspended solids (SS) | comply with SEPP (e.g., not exceed the 90th percentile of 80 mg/L)1 | 80% retention of the typical urban annual load |
Total phosphorus (TP) | comply with SEPP (e.g., base flow concentration not to exceed 0.08 mg/L)2 | 45% retention of the typical urban annual load |
Total nitrogen (TN) | comply with SEPP (e.g., bate flow concentration not to exceed 0.9 mg/L)2 | 45% retention of the typical urban annual load |
Litter | comply with SEPP (e g No litter in waterways1 | 70% reduction of typical urban annual load3 |
Flows | Maintain flows at pre-urbanization levels | Maintain discharge for the 1.5-year ARI at pre-development levels |
Suspended solids | comply with SEPP | Effective treatment of 90% of daily run-off events (e.g., <4 months ARI). Effective treatment equates to a 50%ile SS concentration of 50 mg/L |
Litter | comply with SEPP (e.g., No litter in waterways)1 | Prevent litter from entering the stormwater system. |
Other pollutants | comply with SEPP | Limit the application, generation and migration of toxic substances to the maximum extent practicable |
BPEM reduction load targets [9].
An example using SEPP (Waters of Victoria 1988), general surface waters segment.
SEPP Schedule F7—Yarra Catchment—urban waterways for the Yarra River main stream.
Litter is defined as anthropogenic material larger than five millimeters.
The reduction loads were determined by the Cooperative Research Centre for Catchment Hydrology, in their research publication Best Practice Environmental Management Guidelines for Urban Stormwater. This research publication was based on data analysis within the Background Report to the Environment Protection Authority, Melbourne Water Corporation and the Department of Natural Resources and Environment, Victoria [10]. The primary intention was to create performance objectives that helped achieved the SEPP however, [10] believed that the BPEM performance objectives should be:
Simple to use,
Practical and cost-effective
Prescriptive
encouraging innovation
flexible and
justifiable and defensible (based on sound scientific method)
“equitable and applicable to all organisations or communities who discharge to urban stormwater”
With these considerations in mind, one of the influencing factors on the performance objectives was land-take. [10] found that an asset footprint of approximately 1% of the catchment was sufficient to produce reasonable reductions, e.g., TSS (40–80%) and T.P (35–45%). Hence the performance objectives were created in an attempt to satisfy the SEPP and the ideals above and not necessarily to prescribe treatment for certain flow frequencies. SEPP and BPM have an influence on the sizing of SWQT assets however it is indirectly and not through explicit statements. Most wetlands are sized for the 1 in 3 months flow, however, this appears to be more of a rule of thumb, which can be enforced by local authorities such as Melbourne Water, rather than a statutory requirement [17]. The 1 in 3-month flow is nominally sized flow frequency which has generally been utilized to satisfy the BPEM performance objectives (retention of the typical annual load: TSS = 80%, TP = 40%, TN = 45%) [9]. The primary objective of wetland sizing is to meet the BPEM performance objectives, and it just SQ happens that the 1 in 3-month flow meets this objective.
Despite the fact the BPEM performance targets are the primary drivers for sizing wetlands, local authorities such as Melbourne Water may enforce that wetland be sized for 1 in 3-month flows. This may not necessarily be due to treatment meeting the SEPP concentrations but rather for maintenance reasons, e.g., plant protection [17]. The authority with which Melbourne Water may influence the sizing of the wetland is somewhat convoluted as they receive their authority from the Water Act 1989, and the Environment Protection Act 1988 via the SEPP (Waters of Victoria). Through these acts and policies, Melbourne Water has the authority to dictate the design parameters of wetlands and in their most recent wetlands manual they state “All flows ≤ the peak three-month ARI event is transferred into the macrophyte zone when the EDD in the macrophyte zone is at Natural Water Level (NWL) (Figure 2)” [17].
Based on the review of literature it can be concluded that:
Constructed wetlands are cost-effective treatment systems that can be used to treat urban stormwater runoff.
Wetlands plants that are frequently flooded can have an adverse effect on the treatment process.
The change of depth and volume of water in constructed wetlands affects the treatment process.
It can take more than 2 years for the constructed wetland to fully develop, when the bio-system matures, and form part of the nutrient removal process. Thus, sampling and monitoring before the wetland is fully developed should be taken into consideration to reflect the future potential of the wetland.
To have an error of less than 10% for sediment sampling, sampling must occur every three days or less for TSS.
Maintenance is important for the ongoing effectiveness of constructed wetlands in water treatment and in flood mitigation.
Whilst there are no formal policies requiring constructed wetlands, in Victoria, Australia they are typically installed as part of large-scale urban developments to comply with the BPEM guidelines.
Further research into assessing the parameters required in MUSIC for catchments with “similar land use, climatic characteristics and hydrological behavior” is recommended.
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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. 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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. 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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. 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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 has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. 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He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. 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Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. 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Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. 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. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,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. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. Shukla",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356823",title:"MSc.",name:"Seonghee",middleName:null,surname:"Min",slug:"seonghee-min",fullName:"Seonghee Min",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Daegu University",country:{name:"Korea, South"}}},{id:"353307",title:"Prof.",name:"Yoosoo",middleName:null,surname:"Oh",slug:"yoosoo-oh",fullName:"Yoosoo Oh",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:"Yoosoo Oh received his Bachelor's degree in the Department of Electronics and Engineering from Kyungpook National University in 2002. He obtained his Master’s degree in the Department of Information and Communications from Gwangju Institute of Science and Technology (GIST) in 2003. In 2010, he received his Ph.D. degree in the School of Information and Mechatronics from GIST. In the meantime, he was an executed team leader at Culture Technology Institute, GIST, 2010-2012. In 2011, he worked at Lancaster University, the UK as a visiting scholar. In September 2012, he joined Daegu University, where he is currently an associate professor in the School of ICT Conver, Daegu University. Also, he served as the Board of Directors of KSIIS since 2019, and HCI Korea since 2016. From 2017~2019, he worked as a center director of the Mixed Reality Convergence Research Center at Daegu University. From 2015-2017, He worked as a director in the Enterprise Supporting Office of LINC Project Group, Daegu University. His research interests include Activity Fusion & Reasoning, Machine Learning, Context-aware Middleware, Human-Computer Interaction, etc.",institutionString:null,institution:{name:"Daegu Gyeongbuk Institute of Science and Technology",country:{name:"Korea, South"}}},{id:"262719",title:"Dr.",name:"Esma",middleName:null,surname:"Ergüner Özkoç",slug:"esma-erguner-ozkoc",fullName:"Esma Ergüner Özkoç",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Başkent University",country:{name:"Turkey"}}},{id:"346530",title:"Dr.",name:"Ibrahim",middleName:null,surname:"Kaya",slug:"ibrahim-kaya",fullName:"Ibrahim Kaya",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"419199",title:"Dr.",name:"Qun",middleName:null,surname:"Yang",slug:"qun-yang",fullName:"Qun Yang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Auckland",country:{name:"New Zealand"}}}]}},subseries:{item:{id:"19",type:"subseries",title:"Animal Science",keywords:"Animal Science, Animal Biology, Wildlife Species, Domesticated Animals",scope:"The Animal Science topic welcomes research on captive and wildlife species, including domesticated animals. 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A dynamic career research platform which is based on the thematic areas of comparative vertebrate physiology, stress endocrinology, reproductive endocrinology, animal health and welfare, and conservation biology. \nEdward has supervised 40 research students and published over 60 peer reviewed research.",institutionString:null,institution:{name:"University of Queensland",institutionURL:null,country:{name:"Australia"}}},editorTwo:null,editorThree:null,series:{id:"13",title:"Veterinary Medicine and Science",doi:"10.5772/intechopen.73681",issn:"2632-0517"},editorialBoard:[{id:"258334",title:"Dr.",name:"Carlos Eduardo",middleName:null,surname:"Fonseca-Alves",slug:"carlos-eduardo-fonseca-alves",fullName:"Carlos Eduardo Fonseca-Alves",profilePictureURL:"https://mts.intechopen.com/storage/users/258334/images/system/258334.jpg",institutionString:null,institution:{name:"Universidade Paulista",institutionURL:null,country:{name:"Brazil"}}},{id:"191123",title:"Dr.",name:"Juan José",middleName:null,surname:"Valdez-Alarcón",slug:"juan-jose-valdez-alarcon",fullName:"Juan José Valdez-Alarcón",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBfcQAG/Profile_Picture_1631354558068",institutionString:"Universidad Michoacana de San Nicolás de Hidalgo",institution:{name:"Universidad Michoacana de San Nicolás de Hidalgo",institutionURL:null,country:{name:"Mexico"}}},{id:"161556",title:"Dr.",name:"Maria Dos Anjos",middleName:null,surname:"Pires",slug:"maria-dos-anjos-pires",fullName:"Maria Dos Anjos Pires",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS8q2QAC/Profile_Picture_1633432838418",institutionString:null,institution:{name:"University of Trás-os-Montes and Alto Douro",institutionURL:null,country:{name:"Portugal"}}},{id:"209839",title:"Dr.",name:"Marina",middleName:null,surname:"Spinu",slug:"marina-spinu",fullName:"Marina Spinu",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRLXpQAO/Profile_Picture_1630044895475",institutionString:null,institution:{name:"University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca",institutionURL:null,country:{name:"Romania"}}},{id:"92185",title:"Dr.",name:"Sara",middleName:null,surname:"Savic",slug:"sara-savic",fullName:"Sara Savic",profilePictureURL:"https://mts.intechopen.com/storage/users/92185/images/system/92185.jfif",institutionString:'Scientific Veterinary Institute "Novi Sad"',institution:{name:'Scientific Veterinary Institute "Novi Sad"',institutionURL:null,country:{name:"Serbia"}}}]},onlineFirstChapters:{paginationCount:14,paginationItems:[{id:"82457",title:"Canine Hearing Management",doi:"10.5772/intechopen.105515",signatures:"Peter M. 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In recent years, the application of chemistry to biological molecules has gained significant interest in medicinal and pharmacological studies. This topic will be devoted to understanding the interplay between biomolecules and chemical compounds, their structure and function, and their potential applications in related fields. Being a part of the biochemistry discipline, the ideas and concepts that have emerged from Chemical Biology have affected other related areas. This topic will closely deal with all emerging trends in this discipline.",annualVolume:11411,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null,editorialBoard:[{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",fullName:"Abdulsamed Kükürt",profilePictureURL:"https://mts.intechopen.com/storage/users/219081/images/system/219081.png",institutionString:null,institution:{name:"Kafkas University",institutionURL:null,country:{name:"Turkey"}}},{id:"241413",title:"Dr.",name:"Azhar",middleName:null,surname:"Rasul",fullName:"Azhar Rasul",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRT1oQAG/Profile_Picture_1635251978933",institutionString:null,institution:{name:"Government College University, Faisalabad",institutionURL:null,country:{name:"Pakistan"}}},{id:"178316",title:"Ph.D.",name:"Sergey",middleName:null,surname:"Sedykh",fullName:"Sergey Sedykh",profilePictureURL:"https://mts.intechopen.com/storage/users/178316/images/system/178316.jfif",institutionString:null,institution:{name:"Novosibirsk State University",institutionURL:null,country:{name:"Russia"}}}]},{id:"17",title:"Metabolism",keywords:"Biomolecules Metabolism, Energy Metabolism, Metabolic Pathways, Key Metabolic Enzymes, Metabolic Adaptation",scope:"Metabolism is frequently defined in biochemistry textbooks as the overall process that allows living systems to acquire and use the free energy they need for their vital functions or the chemical processes that occur within a living organism to maintain life. Behind these definitions are hidden all the aspects of normal and pathological functioning of all processes that the topic ‘Metabolism’ will cover within the Biochemistry Series. Thus all studies on metabolism will be considered for publication.",annualVolume:11413,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",fullName:"Anca Pantea Stoian",profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",institutionURL:null,country:{name:"Romania"}}},{id:"203824",title:"Dr.",name:"Attilio",middleName:null,surname:"Rigotti",fullName:"Attilio Rigotti",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"Pontifical Catholic University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"300470",title:"Dr.",name:"Yanfei (Jacob)",middleName:null,surname:"Qi",fullName:"Yanfei (Jacob) Qi",profilePictureURL:"https://mts.intechopen.com/storage/users/300470/images/system/300470.jpg",institutionString:null,institution:{name:"Centenary Institute of Cancer Medicine and Cell Biology",institutionURL:null,country:{name:"Australia"}}}]},{id:"18",title:"Proteomics",keywords:"Mono- and Two-Dimensional Gel Electrophoresis (1-and 2-DE), Liquid Chromatography (LC), Mass Spectrometry/Tandem Mass Spectrometry (MS; MS/MS), Proteins",scope:"With the recognition that the human genome cannot provide answers to the etiology of a disorder, changes in the proteins expressed by a genome became a focus in research. Thus proteomics, an area of research that detects all protein forms expressed in an organism, including splice isoforms and post-translational modifications, is more suitable than genomics for a comprehensive understanding of the biochemical processes that govern life. The most common proteomics applications are currently in the clinical field for the identification, in a variety of biological matrices, of biomarkers for diagnosis and therapeutic intervention of disorders. From the comparison of proteomic profiles of control and disease or different physiological states, which may emerge, changes in protein expression can provide new insights into the roles played by some proteins in human pathologies. Understanding how proteins function and interact with each other is another goal of proteomics that makes this approach even more intriguing. Specialized technology and expertise are required to assess the proteome of any biological sample. Currently, proteomics relies mainly on mass spectrometry (MS) combined with electrophoretic (1 or 2-DE-MS) and/or chromatographic techniques (LC-MS/MS). MS is an excellent tool that has gained popularity in proteomics because of its ability to gather a complex body of information such as cataloging protein expression, identifying protein modification sites, and defining protein interactions. The Proteomics topic aims to attract contributions on all aspects of MS-based proteomics that, by pushing the boundaries of MS capabilities, may address biological problems that have not been resolved yet.",annualVolume:11414,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null,editorialBoard:[{id:"72288",title:"Dr.",name:"Arli Aditya",middleName:null,surname:"Parikesit",fullName:"Arli Aditya Parikesit",profilePictureURL:"https://mts.intechopen.com/storage/users/72288/images/system/72288.jpg",institutionString:null,institution:{name:"Indonesia International Institute for Life Sciences",institutionURL:null,country:{name:"Indonesia"}}},{id:"40928",title:"Dr.",name:"Cesar",middleName:null,surname:"Lopez-Camarillo",fullName:"Cesar Lopez-Camarillo",profilePictureURL:"https://mts.intechopen.com/storage/users/40928/images/3884_n.png",institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",institutionURL:null,country:{name:"Mexico"}}},{id:"81926",title:"Dr.",name:"Shymaa",middleName:null,surname:"Enany",fullName:"Shymaa Enany",profilePictureURL:"https://mts.intechopen.com/storage/users/81926/images/system/81926.png",institutionString:"Suez Canal University",institution:{name:"Suez Canal University",institutionURL:null,country:{name:"Egypt"}}}]}]}},libraryRecommendation:{success:null,errors:{},institutions:[]},route:{name:"chapter.detail",path:"/chapters/31350",hash:"",query:{},params:{id:"31350"},fullPath:"/chapters/31350",meta:{},from:{name:null,path:"/",hash:"",query:{},params:{},fullPath:"/",meta:{}}}},function(){var e;(e=document.currentScript||document.scripts[document.scripts.length-1]).parentNode.removeChild(e)}()