Search results for: solid coordination network (SCN)

Authors: Bander Mohayya Alotaibi

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The valuable partnerships between parents and teachers may develop positive and effective interactions between home and school. This will help these stakeholders share information and resources regarding student academics during ongoing interactions. Thus, partnerships will build a solid foundation for both families and schools to help children succeed in school. Parental involvement can be seen as an effective tool that can change homes and communities and not just schools’ systems. Seeking parents and stakeholders’ attitudes toward learning and learners can help schools design a curriculum. Subsequently, this information can be used to find ways to help improve the academic performance of students, especially in low performing schools. There may be some conflicts when designing curriculum. In addition, designing curriculum might bring more educational expectations to all the sides. There is a lack of research that targets the specific attitude of parents toward specific concepts on curriculum contents. More research is needed to study the perspective that parents of children with learning disabilities (LD) have regarding early reading curriculum. Parents and stakeholders’ perspectives on early reading intervention implemented as a curriculum for children with LD was studied through an advanced quantitative research. The purpose of this study seeks to understand stakeholders and parents’ perspectives of key concepts and essential early reading skills that impact the design of curriculum that will serve as an intervention for early struggler readers who have LD. Those concepts or stages include phonics, phonological awareness, and reading fluency as well as strategies used in house by parents. A survey instrument was used to gather the data. Participants were recruited through 29 schools and districts of the metropolitan area of the northern part of Saudi Arabia. Participants were stakeholders including parents of children with learning disability. Data were collected using distribution of paper and pen survey to schools. Psychometric properties of the instrument were evaluated for the validity and reliability of the survey; face validity, content validity, and construct validity including an Exploratory Factor Analysis were used to shape and reevaluate the structure of the instrument. Multivariate analysis of variance (MANOVA) used to find differences between the variables. The study reported the results of the perspectives of stakeholders toward reading strategies, phonics, phonological awareness, and reading fluency. Also, suggestions and limitations are discussed.

Keywords: stakeholders, learning disability, early reading, perspectives, parents, intervention, curriculum

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Authors: Shiri Elisheva Decktor, Sharon Hornstein

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Highway merges and unmarked junctions are key components in any urban road network, which can act as bottlenecks and create traffic disruption. Inefficient highway merges may trigger traffic instabilities such as stop-and-go waves, pose safety conditions and lead to longer journey times. These phenomena occur spontaneously if the average vehicle density exceeds a certain critical value. This study focuses on modeling the traffic using a microscopic traffic flow model. A hybrid traffic model, which combines human-driven and controlled vehicles is assumed. The controlled vehicles obey different driving policies when approaching the merge, or in the vicinity of other vehicles. We developed a co-simulation model in SUMO (Simulation of Urban Mobility), in which the human-driven cars are modeled using the IDM model, and the controlled cars are modeled using a dedicated controller. The scenario chosen for this study is a closed track with one merge and one exit, which could be later implemented using a scaled infrastructure on our lab setup. This will enable us to benchmark the results of this study obtained in simulation, to comparable results in similar conditions in the lab. The metrics chosen for the comparison of the performance of our algorithm on the overall traffic conditions include the average speed, wait time near the merge, and throughput after the merge, measured under different travel demand conditions (low, medium, and heavy traffic).

Keywords: highway merges, traffic modeling, SUMO, driving policy

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Authors: Zohreh Khojasteh-Ghamari, Takashi Irohara

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One of the efficient ways in supply chain risk management is avoiding the interruption in Supply Chain (SC) before it occurs. Although the majority of the organizations focus on their first-tier suppliers to avoid risk in the SC, studies show that in only 60 percent of the disruption cases the reason is first tier suppliers. In the 40 percent of the SC disruptions, the reason is downstream SC, which is the second tier and lower. Due to the increasing complexity and interrelation of modern supply chains, the SC elements have become difficult to trace. Moreover, studies show that there is a vital need to better understand the integration of risk and visibility, especially in the context of multiple objectives. In this study, we propose a multi-objective programming model to avoid disruption in SC. The objective of this study is evaluating the effect of downstream SCV on managing supply chain risk. We propose a multi-objective mathematical programming model with the objective functions of minimizing the total cost and maximizing the downstream supply chain visibility (SCV). The decision variable is supplier selection. We assume there are several manufacturers and several candidate suppliers. For each manufacturer, our model proposes the best suppliers with the lowest cost and maximum visibility in downstream supply chain. We examine the applicability of the model by numerical examples. We also define several scenarios for datasets and observe the tendency. The results show that minimum visibility in downstream SC is needed to have a safe SC network.

Keywords: downstream supply chain, optimization, supply chain risk, supply chain visibility

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Authors: T. Topór, A. Derkowski, P. Ziemiański

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Formation of organic matter (OM)-hosted nanopores upon thermal maturation are one of the key factor controlling methane storage potential in unconventional shale-gas reservoirs. In this study, the subcritical CO₂ and N₂ gas adsorption measurements combined with scanning electron microscopy and supercritical methane adsorption have been used to characterize pore system and methane storage potential in black shales from the Baltic Basin (Poland). The samples were collected from a virtually equivalent Llandovery strata across the basin and represent a complete digenetic sequence, from thermally immature to overmature. The results demonstrate that the thermal maturation is a dominant mechanism controlling the formation of OM micro- and mesopores in the Baltic Basin shales. The formation of micro- and mesopores occurs in the oil window (vitrinite reflectance; leavedVR; ~0.5-0.9%) as a result of oil expulsion from kerogenleft OM highly porous. The generated hydrocarbons then turn into solid bitumen causing pore blocking and substantial decrease in micro- and mesopore volume in late-mature shales (VR ~0.9-1.2%). Both micro- and mesopores are regenerated in a middle of the catagenesis range (VR 1.4-1.9%) due to secondary cracking of OM and gas formation. The micropore volume in investigated shales is almost exclusively controlled by the OM content. The contribution of clay minerals to micropore volume is insignificant and masked by a strong contribution from OM. Methane adsorption capacity in the Baltic Basin shales is predominantly controlled by microporous OM with pores < 1.5 nm. The mesopore volume (2-50 nm) and mesopore surface area have no effect on methane sorption behavior. The adsorbed methane density equivalent, calculated as absolute methane adsorption divided by micropore volume, reviled a decrease of the methane loading potential in micropores with increasing maturity. The highest methane loading potential in micropores is observed for OM before metagenesis (VR < 2%), where the adsorbed methane density equivalent is greater than the density of liquid methane. This implies that, in addition to physical adsorption, absorption of methane in OM may occur before metagenesis. After OM content reduction using NaOCl solution methane adoption capacity substantially decreases, suggesting significantly greater adsorption potential for OM microstructure than for the clay minerals matrix.

Keywords: maturation, methane sorption, organic matter, porosity, shales

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Authors: Tanveer Hussain, Khan Muhammad, Amin Ullah, Mi Young Lee, Sung Wook Baik

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The Big Data generated from distributed vision sensors installed on large scale in smart cities create hurdles in its efficient and beneficial exploration for browsing, retrieval, and indexing. This paper presents a three-folded framework for effective video summarization of such data and provide a compact and representative format of Big Video Data. In the first fold, the paper acquires input video data from the installed cameras and collect clues such as type and count of objects and clarity of the view from a chunk of pre-defined number of frames of each view. The decision of representative view selection for a particular interval is based on fuzzy inference system, acquiring a precise and human resembling decision, reinforced by the known clues as a part of the second fold. In the third fold, the paper forwards the selected view frames to the summary generation mechanism that is supported by a saliency-aware convolution neural network (CNN) model. The new trend of fuzzy rules for view selection followed by CNN architecture for saliency computation makes the multi-view video summarization (MVS) framework a suitable candidate for real-world practice in smart cities.

Keywords: big video data analysis, fuzzy logic, multi-view video summarization, saliency detection

Procedia PDF Downloads 182

Authors: Stephanie Fabris Russo, Daiane Costa Guimarães, Jonas Pedro Fabris, Maria Emilia Camargo, Suzana Leitão Russo, José Augusto Andrade Filho

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Among renewable energy sources, solar energy is the one that has stood out. Solar radiation can be used as a thermal energy source and can also be converted into electricity by means of effects on certain materials, such as thermoelectric and photovoltaic panels. These panels are often used to generate energy in homes, buildings, arenas, etc., and have low pollution emissions. Thus, a technological prospecting was performed to find patents related to the use of photovoltaic plates in urban residences. The patent search was based on ESPACENET, associating the keywords photovoltaic and home, where we found 136 patent documents in the period of 1994-2015 in the fields title and abstract. Note that the years 2009, 2010, 2011, 2012, 2013 and 2014 had the highest number of applicants, with respectively, 11, 13, 23, 29, 15 and 21. Regarding the country that deposited about this technology, it is clear that China leads with 67 patent deposits, followed by Japan with 38 patents applications. It is important to note that most depositors, 50% are companies, 44% are individual inventors and only 6% are universities. On the International Patent classification (IPC) codes, we noted that the most present classification in results was H02J3/38, which represents provisions in parallel to feed a single network by two or more generators, converters or transformers. Among all categories, there is the H session, which means Electricity, with 70% of the patents.

Keywords: photovoltaic, urban residences, technology forecasting, prospecting

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Authors: Felipa de Mello-Sampayo

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The aim of this study is to undertake, from patient’s perspective, the timing and probability of using teledermatology, comparing it with a conventional referral system. The dynamic stochastic model’s main value-added consists of the concrete application to patients waiting for dermatology surgical intervention. Patients with low health level uncertainty must use teledermatology treatment as soon as possible, which is precisely when the teledermatology is least valuable. The results of the model were then tested empirically with the teledermatology network covering the area served by the Hospital Garcia da Horta, Portugal, links the primary care centers of 24 health districts with the hospital’s dermatology department via the corporate intranet of the Portuguese healthcare system. Health level volatility can be understood as the hazard of developing skin cancer and the trend of health level as the bias of developing skin lesions. The results of the survival analysis suggest that the theoretical model can explain the use of teledermatology. It depends negatively on the volatility of patients' health, and positively on the trend of health, i.e., the lower the risk of developing skin cancer and the younger the patients, the more presurgical teledermatology one expects to occur. Presurgical teledermatology also depends positively on out-of-pocket expenses and negatively on the opportunity costs of teledermatology, i.e., the lower the benefit missed by using teledermatology, the more presurgical teledermatology one expects to occur.

Keywords: teledermatology, wait time, uncertainty, opportunity cost, survival analysis

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Authors: Julie A. Carberry, Victor Maddalena

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Animal-Assisted Interventions (AAIs) have existed in various forms for centuries. In the past 30 years, there has been a dramatic increase in popularity. AAIs are now part of the lives of persons of all ages in many types of institutions. Anecdotal evidence of the benefits of AAIs have led to widespread adoption, yet there remains a lack of solid research base for support. The research question was, what are the lived experiences of AAI volunteer handlers are? An interpretive phenomenological methodology was used for this qualitative study. Data were collected from 1 - 2 hour-long semi-structured interviews and 1 observational field visit. All interviews were conducted, transcribed, and coded for themes by the principal investigator. Participants must have been an active St. John Ambulance Therapy Dog Program volunteer for a least one year. In total, 14 volunteer handlers, along with some of their dogs, were included. The St. John Ambulance is a not for profit organization that provides training and community services to Canadians. The Therapy Dog Program is 1 of the 4 nationally recognized core community service programs. The program incorporates dogs in the otherwise traditional therapeutic intervention of friendly visitation with clients. The lack of formal objectives and goals, and a trained therapist defines the program as an Animal-Assisted Activity (AAA), which is a type of AAI. Since the animals incorporated are dogs, the program is specifically a Canine-Assisted Activity (CAA), which is a type of Canine-Assisted Intervention (CAI). Six themes emerged from the analysis of the data: (a) a win-win-win situation for all parties involved – volunteer handlers, clients, and the dogs, (b) being on the other end of the leash: functions of the role of volunteer handler, (c) the importance of socialization: from spreading smiles to creating meaningful connections, (d) the role of the dog: initiating interaction and providing comfort, (e) an opportunity to feel good and destress, and (f) altruism versus personal rewards. Other insights were found regarding the program, clients, and staff. Possible implications from this research include increased organizational recruitment and retention of volunteer handlers and as well as increased support for CAAs and other CAIs that incorporate teams of volunteer handlers and their dogs. This support could, in turn, add overall support for the acceptance and broad implementation of AAIs as an alternative and or complementary non-pharmaceutical therapeutic intervention.

Keywords: animal-assisted activity, animal-assisted intervention, canine-assisted activity, canine-assisted intervention, perspective, qualitative, volunteer handler

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Authors: Chien-kuo Chang, Bo-wei Wu, Yi-yun Tang, Min-chiu Wu

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This paper proposes a power equipment diagnosis system based on partial discharge (PD), which is characterized by increasing the readability of experimental data and the convenience of operation. This system integrates a variety of analysis programs of different data formats and different programming languages and then establishes a set of interfaces that can follow and expand the structure, which is also helpful for subsequent maintenance and innovation. This study shows a case of using the developed Convolutional Neural Networks (CNN) to integrate with this system, using the designed model architecture to simplify the complex training process. It is expected that the simplified training process can be used to establish an adaptive deep learning experimental structure. By selecting different test data for repeated training, the accuracy of the identification system can be enhanced. On this platform, the measurement status and partial discharge pattern of each equipment can be checked in real time, and the function of real-time identification can be set, and various training models can be used to carry out real-time partial discharge insulation defect identification and insulation state diagnosis. When the electric power equipment entering the dangerous period, replace equipment early to avoid unexpected electrical accidents.

Keywords: partial discharge, convolutional neural network, partial discharge analysis platform, adaptive deep learning

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Authors: Pinzón Uribe Luis Felipe, Chávez Porras Álvaro, Ruge Castellanos Liliana Constanza

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According to global data, solid waste management of has low economic investment for its management in underdeveloped countries; being the main factor the advanced technologies acknowledge for proper operation and at the same time the technical development. Has been evidenced that communities have a distorted perception of the role and legalized final destinations for waste or "Landfill" places specific management; influenced primarily by their physical characteristics and the information that the media provide of these, as well as their wrong association with "open dumps". One of the major inconveniences in these landfills is the leachate sludge management from treatment plants; as this exhibit a composition highly contaminating (physical, chemical and biological) for the natural environment due to improper handling and disposal. This is the case Landfill Doña Juana (RSDJ), Bogotá, Colombia, considered among the largest in South America; where management problems have persisted for decades, since its creation being definitive on the concept that society has acquired about this form of waste disposal and improper leachate handling. Within this research process for treating phytoremediation alternatives were determined by using plants that are able to degrade heavy metals contained in these; allowing the resulting sludge to be used as a seal in the final landfill cover; within a restoration process, providing option to solve the landscape contamination problem, as well as in the communities perception and conflicts that generates landfill. For the project chemical assays were performed in sludge leachate that allowed the characterization of metals such as chromium (Cr), lead (Pb), arsenic (As) and mercury (Hg), in order to meet the amount in the biosolids regard to the provisions of the USEPA 40 CFR 503. The evaluations showed concentrations of 102.2 mg / kg of Cr, 0.49 mg / kg Pb, 0.390 mg / kg of As and 0.104 mg / kg of Hg; being lower than of the standards. A literature review on native plant species suitable for an alternative process of phytoremediation, these metals degradation capable was developed. Concluding that among them, Vetiveria zizanioides, Eichhornia crassipes and Limnobium laevigatum, for their hiperacumulativas in their leaves, stems and roots characteristics may allow these toxic elements reduction of in the environment, improving the outlook for disposal.

Keywords: health, filling slurry of leachate, heavy metals, phytoremediation

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Authors: Agnieszka Feliczak-Guzik, Paulina Szczyglewska, Izabela Nowak

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A catalyst-assisted oxidation reaction is one of the key reactions exploited by various industries. Their conductivity yields essential compounds and intermediates, such as alcohols, epoxides, aldehydes, ketones, and organic acids. Researchers are devoting more and more attention to developing active and selective materials that find application in many catalytic reactions, such as cyclohexene epoxidation. This reaction yields 1,2-epoxycyclohexane and 1,2-diols as the main products. These compounds are widely used as intermediates in the perfume industry and synthesizing drugs and lubricants. Hence, our research aimed to use hierarchical zeolites modified with transition metal ions, e.g., Nb, V, and Ta, in the epoxidation reaction of cyclohexene using microwaveheating. Hierarchical zeolites are materials with secondary porosity, mainly in the mesoporous range, compared to microporous zeolites. In the course of the research, materials based on two commercial zeolites, with Faujasite (FAU) and Zeolite Socony Mobil-5 (ZSM-5) structures, were synthesized and characterized by various techniques, such as X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electron microscopy (SEM), and low-temperature nitrogen adsorption/desorption isotherms. The materials obtained were then used in a cyclohexene epoxidation reaction, which was carried out as follows: catalyst (0.02 g), cyclohexene (0.1 cm3), acetonitrile (5 cm3) and dihydrogen peroxide (0.085 cm3) were placed in a suitable glass reaction vessel with a magnetic stirrer inside in a microwave reactor. Reactions were carried out at 45° C for 6 h (samples were taken every 1 h). The reaction mixtures were filtered to separate the liquid products from the solid catalyst and then transferred to 1.5 cm3 vials for chromatographic analysis. The test techniques confirmed the acquisition of additional secondary porosity while preserving the structure of the commercial zeolite (XRD and low-temperature nitrogen adsorption/desorption isotherms). The results of the activity of the hierarchical catalyst modified with niobium in the cyclohexene epoxidation reaction indicate that the conversion of cyclohexene, after 6 h of running the process, is about 70%. As the main product of the reaction, 2-cyclohexanediol was obtained (selectivity > 80%). In addition to the mentioned product, adipic acid, cyclohexanol, cyclohex-2-en-1-one, and 1,2-epoxycyclohexane were also obtained. Furthermore, in a blank test, no cyclohexene conversion was obtained after 6 h of reaction. Acknowledgments The work was carried out within the project “Advanced biocomposites for tomorrow’s economy BIOG-NET,” funded by the Foundation for Polish Science from the European Regional Development Fund (POIR.04.04.00-00-1792/18-00.

Keywords: epoxidation, oxidation reactions, hierarchical zeolites, synthesis

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Authors: S. Neelima, P. S. Subramanyam

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A distribution system is an interface between the bulk power system and the consumers. Among these systems, radial distributions system is popular because of low cost and simple design. In distribution systems, the voltages at buses reduces when moved away from the substation, also the losses are high. The reason for a decrease in voltage and high losses is the insufficient amount of reactive power, which can be provided by the shunt capacitors. But the placement of the capacitor with an appropriate size is always a challenge. Thus, the optimal capacitor placement problem is to determine the location and size of capacitors to be placed in distribution networks in an efficient way to reduce the power losses and improve the voltage profile of the system. For this purpose, in this paper, two stage methodologies are used. In the first stage, the load flow of pre-compensated distribution system is carried out using ‘dimension reducing distribution load flow algorithm (DRDLFA)’. On the basis of this load flow the potential locations of compensation are computed. In the second stage, Genetic Algorithm (GA) technique is used to determine the optimal location and size of the capacitors such that the cost of the energy loss and capacitor cost to be a minimum. The above method is tested on IEEE 9 and 34 bus system and compared with other methods in the literature.

Keywords: dimension reducing distribution load flow algorithm, DRDLFA, genetic algorithm, electrical distribution network, optimal capacitors placement, voltage profile improvement, loss reduction

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Authors: Martha Lilia Del Rio Duque, Michelle Bonatti, Katharina Loehr, Marcos Lana, Tatiana Rodriguez, Stefan Sieber

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Nowadays, most agricultural practices can reduce the ability of ecosystems to provide goods and services. To enhance environmentally friendly food production and to maximize social and economic benefits, sustainable land use systems (SLUS) are one of the most critical strategies increasingly/strongly promoted by donors organizations, international agencies, and policymakers. This process involves the question of how SLUS can be scaled out also large-scale landscapes and not merely isolated experiments. As SLUS are context-specific strategies, diffusion and replication of successful SLUS in Colombia required the identification of main factors that facilitate this scaling out process. We applied a case study approach to investigate the scaling out process of SLUS in cocoa and livestock sector within peacebuilding territories in Colombia, specifically, in Cesar and Caqueta region. These two regions are contrasting, but both have a current trend of increasing land degradation. Presently in Colombia, Caqueta is one of the most deforested departments, and Cesar has some most degraded soils. Following a qualitative research approach, 19 semi-structured interviews and 2 focus groups were conducted with agroforestry experts in both regions to analyze (1) what does it mean a sustainable land use system in Cocoa/Livestock, specifically in Caqueta or Cesar and (2) to identify the key elements at the level of the following dimensions: biophysical, economic and profitability, market, social, policy and institutions that can explain how and why SLUS are replicated and spread among more producers. The Interviews were coded and analyzed using MAXQDA to identify, analyze and report patterns (themes) within data. As the results show, key themes, among which: premium market, solid regional markets and price stability, water availability and management, generational renewal, land use knowledge and diversification, producer organization and certifications are crucial to understand how the SLUS can have an impact across large-scale landscapes and how the scaling out process can be set up best in order to be successful across different contexts. The analysis further reveals which key factors might affect SLUS efficiency.

Keywords: agroforestry, cocoa sector, Colombia, livestock sector, sustainable land use system

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Authors: Bi Zhao

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Neural network technology has greatly improved the output of machine translation in terms of both fluency and accuracy, which greatly increases its appeal for young users. The present exploratory study aims to find out how the Chinese undergraduates perceive and use machine translation in their daily life. A survey is conducted to collect data from 100 undergraduate students from multiple Chinese universities and with varied academic backgrounds, including arts, business, science, engineering, and medicine. The survey questions inquire about their use (including frequency, scenarios, purposes, and preferences) of and attitudes (including trust, quality assessment, justifications, and ethics) toward machine translation. Interviews and tasks of evaluating machine translation output are also employed in combination with the survey on a sample of selected respondents. The results indicate that Chinese undergraduate students use machine translation on a daily basis for a wide range of purposes in academic, communicative, and entertainment scenarios. Most of them have preferred machine translation tools, but the availability of machine translation tools within a certain scenario, such as the embedded machine translation tool on the webpage, is also the determining factor in their choice. The results also reveal that despite the reportedly limited trust in the accuracy of machine translation output, most students lack the ability to critically analyze and evaluate such output. Furthermore, the evidence is revealed of the inadequate awareness of ethical responsibility as machine translation users among Chinese undergraduate students.

Keywords: Chinese undergraduates, machine translation, trust, usage

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Authors: M. Kosacka, I. Kudelska

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Vehicle is one of the most influential and complex product worldwide, which affects people’s life, state of the environment and condition of the economy (all aspects of sustainable development concept) during each stage of lifecycle. With the increase of vehicles’ number, there is growing potential for management of End of Life Vehicle (ELV), which is hazardous waste. From one point of view, the ELV should be managed to ensure risk elimination, but from another point, it should be treated as a source of valuable materials and spare parts. In order to obtain materials and spare parts, there are established recycling networks, which are an example of sustainable policy realization at the national level. The basic object in the polish recycling network is dismantling facility. The output material streams in dismantling stations include waste, which very often generate costs and spare parts, that have the biggest potential for revenues creation. Both outputs are stored into warehouses, according to the law. In accordance to the revenue creation and sustainability potential, it has been placed a strong emphasis on storage process. We present the concept of storage method, which takes into account the specific of the dismantling facility in order to support decision-making process with regard to the principles of sustainable development. The method was developed on the basis of case study of one of the greatest dismantling facility in Poland.

Keywords: dismantling, end of life vehicles, sustainability, storage

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Authors: Zeinab Yazdanfar, Dilan Robert, Daniel Lester, S. Setunge

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Scour has been identified as the most common threat to bridge stability worldwide. Traditionally, scour around bridge piers is calculated using the empirical approaches that have considerable limitations and are difficult to generalize. The multi-physic nature of scouring which involves turbulent flow, soil mechanics and solid-fluid interactions cannot be captured by simple empirical equations developed based on limited laboratory data. These limitations can be overcome by direct numerical modeling of coupled hydro-mechanical scour process that provides a robust prediction of bridge scour and valuable insights into the scour process. Several numerical models have been proposed in the literature for bridge scour estimation including Eulerian flow models and coupled Euler-Lagrange models incorporating an empirical sediment transport description. However, the contact forces between particles and the flow-particle interaction haven’t been taken into consideration. Incorporating collisional and frictional forces between soil particles as well as the effect of flow-driven forces on particles will facilitate accurate modeling of the complex nature of scour. In this study, a coupled Computational Fluid Dynamics and Discrete Element Model (CFD-DEM) has been developed to simulate the scour process that directly models the hydro-mechanical interactions between the sediment particles and the flowing water. This approach obviates the need for an empirical description as the fundamental fluid-particle, and particle-particle interactions are fully resolved. The sediment bed is simulated as a dense pack of particles and the frictional and collisional forces between particles are calculated, whilst the turbulent fluid flow is modeled using a Reynolds Averaged Navier Stocks (RANS) approach. The CFD-DEM model is validated against experimental data in order to assess the reliability of the CFD-DEM model. The modeling results reveal the criticality of particle impact on the assessment of scour depth which, to the authors’ best knowledge, hasn’t been considered in previous studies. The results of this study open new perspectives to the scour depth and time assessment which is the key to manage the failure risk of bridge infrastructures.

Keywords: bridge scour, discrete element method, CFD-DEM model, multi-phase model

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Authors: Zhuohan Li, Jing Yang, Yaoyuan Cui

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The gut-brain axis (GBA), a communication network between gut microbiota and the brain, benefits for investigation of brain diseases. Currently, organ chips are considered one of the potential tools for GBA research. However, most of the available GBA chips have limitations in replicating the three-dimensional (3D) growth environment of cells and lack the required cell types for barrier function. In the present study, a microfluidic chip was developed for GBA interaction. Blood-brain barrier (BBB) module was prepared with HBMEC, HBVP, U87 cells and decellularized matrix (dECM). Intestinal epithelial barrier (IEB) was prepared with Caco-2 and vascular endothelial cells and dECM. GBA microfluidic device was integrated with IEB and BBB modules using 3D printing interconnecting microchannel scaffolds. BBB and IEB interaction on this GBA chip were evaluated with lipopolysaccharide (LPS) exposure. The present GBA chip achieved multicellular three-dimensional cultivation. Compared with the co-culture cell model in the transwell, fluorescein was absorbed more slowly by 5.16-fold (IEB module) and 4.69-fold (BBB module) on the GBA chip. Accumulation of Rhodamine 123 and Hoechst33342 was dramatically decreased. The efflux function of transporters on IEB and BBB was significantly increased on the GBA chip. After lipopolysaccharide (LPS) disrupted the IEB, and then BBB dysfunction was further observed, which confirmed the interaction between IEB and BBB modules. These results demonstrated that this GBA chip may offer a promising tool for gut-brain interaction study.

Keywords: decellularized matrix, gut-brain axis, organ-on-chip, three-dimensional printing.

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Authors: Bircan Demiral

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Cognitive radio (CR) is the promising technology that addresses the spectrum scarcity problem for future wireless communications. Orthogonal Frequency Division Multiplexing (OFDM) technology provides more power band ratios for cognitive radio networks (CRNs). While CR is a solution to the spectrum scarcity, it also brings up the capacity problem. In this paper, a novel power allocation algorithm that aims at maximizing the sum capacity in the OFDM based cognitive radio networks is proposed. Proposed allocation algorithm is based on the previously developed water-filling algorithm. To reduce the computational complexity calculating in water filling algorithm, proposed algorithm allocates the total power according to each subcarrier. The power allocated to the subcarriers increases sum capacity. To see this increase, Matlab program was used, and the proposed power allocation was compared with average power allocation, water filling and general power allocation algorithms. The water filling algorithm performed worse than the proposed algorithm while it performed better than the other two algorithms. The proposed algorithm is better than other algorithms in terms of capacity increase. In addition the effect of the change in the number of subcarriers on capacity was discussed. Simulation results show that the increase in the number of subcarrier increases the capacity.

Keywords: cognitive radio network, OFDM, power allocation, water filling

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Authors: Wen Li, Zhengyu Bai, Qi Zhang

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The demand for smart scheduling platform in agriculture, particularly in the scheduling process of machinery equipment, is high. With the continuous development of agricultural machinery equipment technology, a large number of agricultural machinery equipment and agricultural machinery cooperative service organizations continue to appear in China. The large area of cultivated land and a large number of agricultural activities in the central and western regions of China have made the demand for smart and efficient agricultural machinery equipment scheduling platforms more intense. In this study, we design and implement a platform for agricultural machinery equipment scheduling to allocate agricultural machinery equipment resources reasonably. With agricultural machinery equipment scheduling platform taken as the research object, we discuss its research significance and value, use the service blueprint technology to analyze and characterize the agricultural machinery equipment schedule workflow, the network analytic method to obtain the demand platform function requirements, and divide the platform functions through the platform function division diagram. Simultaneously, based on the case-based reasoning (CBR) algorithm, the equipment scheduling module of the agricultural machinery equipment scheduling platform is realized; finally, a design scheme of the agricultural machinery equipment scheduling platform architecture is provided, and the visualization interface of the platform is established via VB programming language. It provides design ideas and theoretical support for the construction of a modern agricultural equipment information scheduling platform.

Keywords: case-based reasoning, service blueprint, system design, ANP, VB programming language

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Authors: Arth Bohra, Marwa Mahmoud

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In this paper, we utilize computer vision to develop a tool for youth coaches to formulate set-piece tactics for their players. We used the Soccernet database to extract the ResNet features and camera calibration data for over 3000 corner kick across 500 professional matches in the top 6 European leagues (English Premier League, UEFA Champions League, Ligue 1, La Liga, Serie A, Bundesliga). Leveraging the provided homography matrix, we construct a feature vector representing the formation of players on these corner kicks. Additionally, labeling the videos manually, we obtained the pass-trajectory of each of the 3000+ corner kicks by segmenting the field into four zones. Next, after determining the localization of the players and ball, we used event data to give the corner kicks a rating on a 1-4 scale. By employing a Convolutional Neural Network, our model managed to predict the success of a corner kick given the formations of players. This suggests that with the right formations, teams can optimize the way they approach corner kicks. By understanding this, we can help coaches formulate set-piece tactics for their own teams in order to maximize the success of their play. The proposed model can be easily extended; our method could be applied to even more game situations, from free kicks to counterattacks. This research project also gives insight into the myriad of possibilities that artificial intelligence possesses in transforming the domain of sports.

Keywords: soccer, corner kicks, AI, computer vision

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Authors: Abderahim Ahmadou, Alfredo Napoli, Noel Durand, Didier Montet

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Biochar is a microporous and adsorbent solid carbon product obtained from the pyrolysis of various organic materials (biomass, agricultural waste). Biochar is distinguished from vegetable charcoal by its manufacture methods. Biochar is used as the amendment in soils to give them favorable characteristics under certain conditions, i.e., absorption of water and its release at low speed. Cashew nuts shell from Mali is usually discarded on land by local processors or burnt as a mean for waste management. The burning of this biomass poses serious socio-environmental problems including greenhouse gas emission and accumulation of tars and soot on houses closed to factories, leading to neighbor complaints. Some mycotoxins as aflatoxins are carcinogenic compounds resulting from the secondary metabolism of molds that develop on plants in the field and during their conservation. They are found at high level on some seeds and nuts in Africa. Ochratoxin A, member of mycotoxins, is produced by various species of Aspergillus and Penicillium. Human exposure to Ochratoxin A can occur through consumption of contaminated food products, particularly contaminated grain, as well as coffee, wine grapes. We showed that cashew shell biochars produced at 400, 600 and 800°C adsorbed aflatoxins (B1, B2, G1, G2) at 100% by filtration (rapid contact) as well as by stirring (long contact). The average percentage of adsorption of Ochratoxin A was 35% by filtration and 80% by stirring. The duration of the biochar-mycotoxin contact was a significant parameter. The effect of biochar was also tested on two strains of toxigenic molds: Aspergillus parasiticus (producers of Aflatoxins) and Aspergillus carbonarius (producers of Ochratoxins). The growth of the strain Aspergillus carbonarius was inhibited at up to 60% by the biochar at 600°C. An opposite effect to the inhibition was observed on Aspergillus parasiticus using the same biochar. In conclusion, we observed that biochar adsorbs mycotoxins: Aflatoxins and Ochratoxin A to different degrees; 100% adsorption of aflatoxins under all conditions (filtration and stirring) and adsorption of Ochratoxin A varied depending on the type of biochar and the experiment conditions (35% by filtration and 85% by stirring). The effects of biochar at 600 °C on the toxigenic molds: Aspergillus parasiticus and Aspergillus carbonarius, varied according to the experimental conditions and the strains. We observed an opposite effect on the growth with an inhibition of Aspergillus carbonarius up to 60% and a stimulated growth of Aspergillus parasiticus.

Keywords: biochar, cashew nut shell, mycotoxins, toxicogenic molds

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Authors: Ping-Hung Chen, Han-Liang Lin

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Taiwan has formed diverse settlement patterns in different time and space backgrounds. Various socio-network links are created between individuals, families, communities, and societies, and different living cultures are also derived. But rapid urbanization and social structural change have caused the creation of densely-packed assembly housing complexes and made neighborhood community upward developed. This, among others, seemed to have affected neighborhood relationship and also created social problems. To understand the complex relations and socio-spatial structure of the community, it is important to use mixed methods. This research employs the theory of space syntax to analyze the layout and structural indicators of the selected communities in Tainan city. On the other hand, this research does the survey about residents' interactions and the sense of community by questionnaire of the selected communities. Then the mean values of the syntax measures from each community were correlated with the results of the questionnaire using a Pearson correlation to examine how elements in physical design affect the sense of community and neighborhood relationship. In Taiwan, most urban morphology research methods are qualitative study. This paper tries to use space syntax to find out the correlation between the community layout and the neighborhood relationship. The result of this study could be used in future studies or improve the quality of residential communities in Taiwan.

Keywords: community layout, neighborhood relationship, space syntax, mixed-method

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Authors: Parisa Mansour

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The coronavirus disease 2019 (COVID-19) was discovered and rapidly spread to various countries around the world since the end of 2019. Computed tomography (CT) images have been used as an important alternative to the time-consuming RT. PCR test. However, manual segmentation of CT images alone is a major challenge as the number of suspected cases increases. Thus, accurate and automatic segmentation of COVID-19 infections is urgently needed. Because the imaging features of the COVID-19 infection are different and similar to the background, existing medical image segmentation methods cannot achieve satisfactory performance. In this work, we try to build a deep convolutional neural network adapted for the segmentation of chest CT images with COVID-19 infections. First, we maintain a large and novel chest CT image database containing 165,667 annotated chest CT images from 861 patients with confirmed COVID-19. Inspired by the observation that the boundary of an infected lung can be improved by global intensity adjustment, we introduce a feature variable block into the proposed deep CNN, which adjusts the global features of features to segment the COVID-19 infection. The proposed PV array can effectively and adaptively improve the performance of functions in different cases. We combine features of different scales by proposing a progressive atrocious space pyramid fusion scheme to deal with advanced infection regions with various aspects and shapes. We conducted experiments on data collected in China and Germany and showed that the proposed deep CNN can effectively produce impressive performance.

Keywords: chest, COVID-19, chest Image, coronavirus, CT image, chest CT

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Authors: Noel Busch-Armendariz, Caitlin Sulley

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Introduction: This study investigated the development of college experiences, COVID-19 pandemic experiences, alcohol use, and sexual violence. The longitudinal study includes 656 college students living in the same dormitory. Students' alcohol use and social network structure were investigated to better understand the relationship with sexual violence risk. Basic Methodologies: Over two years, students repeated five web-based surveys, including a pre-college survey and surveys during four consecutive semesters. Questions were added in the fourth wave to assess students’ experiences of the COVID-19 pandemic, administered from November-January 2021, including mental and behavioral health. Analyses include the impact of COVID on living arrangements, drinking behaviors, and daily life; experiences of COVID symptoms, testing, and diagnosis, responses to COVID such as social distancing, quarantining, not working, increased health care needs; experience of fear, worry, stigma, emotional well-being, loneliness, and mental health; experiences of financial loss, lack of basic supplies, receiving emotional and financial support, and comparison with academic disengagement. Concluding Statement: Findings and discussion will include strategies to strengthen mental and behavioral health programs and policies.

Keywords: COVID, mental health, substance abuse, college students, sexual misconducts

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Authors: Ana-Carolina Feltrin, Daniel Hedman, Farid Akhtar

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High entropy ceramic (HEC) materials are characterized by their compositional disorder due to different metallic element atoms occupying the cation position and non-metal elements occupying the anion position. Several studies have focused on the processing and characterization of high entropy carbides and high entropy borides, as these HECs present interesting mechanical and chemical properties. A few studies have been published on HECs containing two non-metallic elements in the composition. Dual-phase high entropy (Ti₀.₂₅V₀.₂₅Zr₀.₂₅Hf₀.₂₅)BxCy ceramics with different amounts of x and y, (0.25 HfC + 0.25 ZrC + 0.25 VC + 0.25 TiB₂), (0.25 HfC + 0.25 ZrC + 0.25 VB2 + 0.25 TiB₂) and (0.25 HfC + 0.25 ZrB2 + 0.25 VB2 + 0.25 TiB₂) were sintered from boride and carbide precursor powders using SPS at 2000°C with holding time of 10 min, uniaxial pressure of 50 MPa and under Ar atmosphere. The sintered specimens formed two HEC phases: a Zr-Hf rich FCC phase and a Ti-V HCP phase, and both phases contained all the metallic elements from 5-50 at%. Phase quantification analysis of XRD data revealed that the molar amount of hexagonal phase increased with increased mole fraction of borides in the starting powders, whereas cubic FCC phase increased with increased carbide in the starting powders. SPS consolidated (Ti₀.₂₅V₀.₂₅Zr₀.₂₅Hf₀.₂₅)BC0.5 and (Ti₀.₂₅V₀.₂₅Zr₀.₂₅Hf₀.₂₅)B1.5C0.25 had respectively 94.74% and 88.56% relative density. (Ti₀.₂₅V₀.₂₅Zr₀.₂₅Hf₀.₂₅)B0.5C0.75 presented the highest relative density of 95.99%, with Vickers hardness of 26.58±1.2 GPa for the borides phase and 18.29±0.8 GPa for the carbides phase, which exceeded the reported hardness values reported in the literature for high entropy ceramics. The SPS sintered specimens containing lower boron and higher carbon presented superior properties even though the metallic composition in each phase was similar to other compositions investigated. Dual-phase high entropy (Ti₀.₂₅V₀.₂₅Zr₀.₂₅H₀.₂₅)BxCy ceramics were successfully fabricated in a boride-carbide solid solution and the amount of boron and carbon was shown to influence the phase fraction, hardness of phases, and density of the consolidated HECs. The microstructure and phase formation was highly dependent on the amount of non-metallic elements in the composition and not only the molar ratio between metals when producing high entropy ceramics with more than one anion in the sublattice. These findings show the importance of further studies about the optimization of the ratio between C and B for further improvements in the properties of dual-phase high entropy ceramics.

Keywords: high-entropy ceramics, borides, carbides, dual-phase

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Authors: Robert Joseph M. Licup

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The deployment of the fifth-generation (5G) mobile system through mmWave frequencies is the new solution in the requirement to provide higher bandwidth readily available for all users. The usage pattern of the mobile users has moved towards either the work from home or online classes set-up because of the pandemic. Previous mobile technologies can no longer meet the high speed, and bandwidth requirement needed, given the drastic shift of transactions to the home. The millimeter-wave (mmWave) underutilized frequency is utilized by the fifth-generation (5G) cellular networks that support multi-gigabit-per-second (Gbps) transmission. However, due to its short wavelengths, high path loss, directivity, blockage sensitivity, and narrow beamwidth are some of the technical challenges that need to be addressed. Different tools, technologies, and scenarios are explored to support network design, accurate channel modeling, implementation, and deployment effectively. However, there is a big challenge on how the consumer will adopt this solution and maximize the benefits offered by the 5G Technology. This research proposes to study the intricacies of technology diffusion, individual attitude, behaviors, and how technology adoption will be attained. The agent based simulation model shaped by the actual applications, technology solution, and related literature was used to arrive at a computational model. The research examines the different attributes, factors, and intricacies that can affect each identified agent towards technology adoption.

Keywords: agent-based model, AnyLogic, 5G O21, 5G mmWave solutions, technology adoption

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Authors: Abdul Mannan Akhtar

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In this paper a novel concept of a self learning smart personalized computer assistant (ACPCA) is established which is a context aware system. Based on user habits, moods, and other routines/situational reactions the system will manage various services and suggestions at appropriate times including what schedule to follow, what to watch, what software to be used, what should be deleted etc. This system will utilize a hybrid fuzzyNeural model to predict what the user will do next and support his actions. This will be done by establishing fuzzy sets of user activities, choices, preferences etc. and utilizing their combinations to predict his moods and immediate preferences. Various application of context aware systems exist separately e.g. on certain websites for music or multimedia suggestions but a personalized autonomous system that could adapt to user’s personality does not exist at present. Due to the novelty and massiveness of this concept, this paper will primarily focus on the problem establishment, product features and its functionality; however a small mini case is also implemented on MATLAB to demonstrate some of the aspects of ACPCA. The mini case involves prediction of user moods, activity, routine and food preference using a hybrid fuzzy-Neural soft computing technique.

Keywords: context aware systems, APCPCA, soft computing techniques, artificial intelligence, fuzzy logic, neural network, mood detection, face detection, activity detection

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Authors: Irina A. Gudkova, Yousra Demigha

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Scientific research is moving more and more towards the study of complex systems in several areas of economics, biology physics, and computer science. In this paper, we will work on complex systems in communication networks, Wireless Sensor Networks (WSN) that are considered as stochastic systems composed of interacting entities. The current advancements of the sensing in computing and communication systems is an investment ground for research in several tracks. A detailed presentation was made for the WSN, their use, modeling, different problems that can occur in their application and some solutions. The main goal of this work reintroduces the idea of mean field method since it is a powerful technique to solve this type of models especially systems that evolve according to a Continuous Time Markov Chain (CTMC). Modeling of a CTMC has been focused; we obtained a large system of interacting Continuous Time Markov Chain with population entities. The main idea was to work on one entity and replace the others with an average or effective interaction. In this context to make the solution easier, we consider a wireless sensor network as a multi-body problem and we reduce it to one body problem. The method was applied to a system of WSN modeled as a Markovian queue showing the results of the used technique.

Keywords: Continuous-Time Markov Chain, Hidden Markov Chain, mean field method, Wireless sensor networks

Procedia PDF Downloads 155

Authors: Gabriela V. Angeles Perez, Jose Castillejos Lopez, Araceli L. Reyes Cabello, Emilio Bravo Grajales, Adriana Perez Espinosa, Jose L. Quiroz Fabian

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Road traffic accidents are among the principal causes of traffic congestion, causing human losses, damages to health and the environment, economic losses and material damages. Studies about traditional road traffic accidents in urban zones represents very high inversion of time and money, additionally, the result are not current. However, nowadays in many countries, the crowdsourced GPS based traffic and navigation apps have emerged as an important source of information to low cost to studies of road traffic accidents and urban congestion caused by them. In this article we identified the zones, roads and specific time in the CDMX in which the largest number of road traffic accidents are concentrated during 2016. We built a database compiling information obtained from the social network known as Waze. The methodology employed was Discovery of knowledge in the database (KDD) for the discovery of patterns in the accidents reports. Furthermore, using data mining techniques with the help of Weka. The selected algorithms was the Maximization of Expectations (EM) to obtain the number ideal of clusters for the data and k-means as a grouping method. Finally, the results were visualized with the Geographic Information System QGIS.

Keywords: data mining, k-means, road traffic accidents, Waze, Weka

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Authors: Oseni Taiwo Amoo, Bloodless Dzwairo

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In this paper, we extend the versatility and usefulness of GIS as a methodology for any river basin hydrologic characteristics analysis (HCA). The Gurara River basin located in North-Central Nigeria is presented in this study. It is an on-going research using spatial Digital Elevation Model (DEM) and Arc-Hydro tools to take inventory of the basin characteristics in order to predict water abstraction quantification on streamflow regime. One of the main concerns of hydrological modelling is the quantification of runoff from rainstorm events. In practice, the soil conservation service curve (SCS) method and the Conventional procedure called rational technique are still generally used these traditional hydrological lumped models convert statistical properties of rainfall in river basin to observed runoff and hydrograph. However, the models give little or no information about spatially dispersed information on rainfall and basin physical characteristics. Therefore, this paper synthesizes morphometric parameters in generating runoff. The expected results of the basin characteristics such as size, area, shape, slope of the watershed and stream distribution network analysis could be useful in estimating streamflow discharge. Water resources managers and irrigation farmers could utilize the tool for determining net return from available scarce water resources, where past data records are sparse for the aspect of land and climate.

Keywords: hydrological characteristic, stream flow, runoff discharge, land and climate

Procedia PDF Downloads 331