Search results for: storm water network

Authors: Marcos Silva Tavares, Jamile Raquel Regazzo, Edson José de Souza Sardinha, Murilo Mesquita Baesso

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Common beans are a widely cultivated and consumed legume globally, serving as a staple food for humans, especially in developing countries, due to their nutritional characteristics. Nitrogen (N) is the most limiting nutrient for productivity, and foliar analysis is crucial to ensure balanced nitrogen fertilization. Excessive N applications can cause, either isolated or cumulatively, soil and water contamination, plant toxicity, and increase their susceptibility to diseases and pests. However, the quantification of N using conventional methods is time-consuming and costly, demanding new technologies to optimize the adequate supply of N to plants. Thus, it becomes necessary to establish constant monitoring of the foliar content of this macronutrient in plants, mainly at the V4 stage, aiming at precision management of nitrogen fertilization. In this work, the objective was to evaluate the performance of a deep learning model, Resnet-50, in the classification of foliar nitrogen in common beans using RGB images. The BRS Estilo cultivar was sown in a greenhouse in a completely randomized design with four nitrogen doses (T1 = 0 kg N ha-1, T2 = 25 kg N ha-1, T3 = 75 kg N ha-1, and T4 = 100 kg N ha-1) and 12 replications. Pots with 5L capacity were used with a substrate composed of 43% soil (Neossolo Quartzarênico), 28.5% crushed sugarcane bagasse, and 28.5% cured bovine manure. The water supply of the plants was done with 5mm of water per day. The application of urea (45% N) and the acquisition of images occurred 14 and 32 days after sowing, respectively. A code developed in Matlab© R2022b was used to cut the original images into smaller blocks, originating an image bank composed of 4 folders representing the four classes and labeled as T1, T2, T3, and T4, each containing 500 images of 224x224 pixels obtained from plants cultivated under different N doses. The Matlab© R2022b software was used for the implementation and performance analysis of the model. The evaluation of the efficiency was done by a set of metrics, including accuracy (AC), F1-score (F1), specificity (SP), area under the curve (AUC), and precision (P). The ResNet-50 showed high performance in the classification of foliar N levels in common beans, with AC values of 85.6%. The F1 for classes T1, T2, T3, and T4 was 76, 72, 74, and 77%, respectively. This study revealed that the use of RGB images combined with deep learning can be a promising alternative to slow laboratory analyses, capable of optimizing the estimation of foliar N. This can allow rapid intervention by the producer to achieve higher productivity and less fertilizer waste. Future approaches are encouraged to develop mobile devices capable of handling images using deep learning for the classification of the nutritional status of plants in situ.

Keywords: convolutional neural network, residual network 50, nutritional status, artificial intelligence

Procedia PDF Downloads 19

Authors: Joel Weymouth, Ramesh K. Karne, Alexander L. Wijesinha

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Bare Machine Internet is part of the Bare Machine Computing (BMC) paradigm. It is used in programming application ns to run directly on a device. It is software that runs directly against the hardware using CPU, Memory, and I/O. The software application runs without an Operating System and resident mass storage. An important part of the BMC paradigm is the Bare Machine Internet. It utilizes an Application Development model software that interfaces directly with the hardware on a network server and file server. Because it is “bare,” it is a powerful teaching and research tool that can readily display the internals of the network protocols, software, and hardware of the applications running on the Bare Server. It was also demonstrated that the bare server was accessible by laptop and by smartphone/android. The purpose was to show the further practicality of Bare Internet in Computer Engineering and Computer Science Education and Research. It was also to show that an undergraduate student could take advantage of a bare server with any device and any browser at any release version connected to the internet. This paper presents the Bare Web Server as an educational tool. We will discuss possible applications of this paradigm.

Keywords: bare machine computing, online research, network technology, visualizing network internals

Procedia PDF Downloads 172

Authors: Miled Amel, Ben Maad Hatem, Askri Faouzi, Ben Nasrallah Sassi

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Metal hydride water pumping system uses hydrogen as working fluid to pump water for low head and high discharge. The principal operation of this pump is based on the desorption of hydrogen at high pressure and its absorption at low pressure by a metal hydride. This work is devoted to study a concept of the dynamic behavior of a metal hydride pump using unsteady model and LaNi5 as hydriding alloy. This study shows that with MHP, it is possible to pump 340l/kg-cycle of water in 15 000s using 1 Kg of LaNi5 at a desorption temperature of 360 K, a pumping head equal to 5 m and a desorption gear ratio equal to 33. This study reveals also that the error given by the steady model, using LaNi5 is about 2%.A dimensional mathematical model and the governing equations of the pump were presented to predict the coupled heat and mass transfer within the MHP. Then, a numerical simulation is carried out to present the time evolution of the specific water discharge and to test the effect of different parameters (desorption temperature, absorption temperature, desorption gear ratio) on the performance of the water pumping system (specific water discharge, pumping efficiency and pumping time). In addition, a comparison between results obtained with steady and unsteady model is performed with different hydride mass. Finally, a geometric configuration of the reactor is simulated to optimize the pumping time.

Keywords: dynamic behavior, LaNi5, performance of water pumping system, unsteady model

Procedia PDF Downloads 205

Authors: Chen Jun-Hong, He Pu, Tao Wen-Quan

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Proton exchange membrane fuel cell (PEMFC) is the most promising future energy source owing to its low operating temperature, high energy efficiency, high power density, and environmental friendliness. In this paper, a comprehensive PEMFC system control-oriented model is developed in the Matlab/Simulink environment, which includes the hydrogen supply subsystem, air supply subsystem, and thermal management subsystem. Besides, Improved Artificial Bee Colony (IABC) is used in the parameter identification of PEMFC semi-empirical equations, making the maximum relative error between simulation data and the experimental data less than 0.4%. Operation temperature is essential for PEMFC, both high and low temperatures are disadvantageous. In the thermal management subsystem, water pump and fan are both controlled with the PID controller to maintain the appreciate operation temperature of PEMFC for the requirements of safe and efficient operation. To improve the control effect further, fuzzy control is introduced to optimize the PID controller of the pump, and the Radial Basis Function (RBF) neural network is introduced to optimize the PID controller of the fan. The results demonstrate that Fuzzy-PID and RBF-PID can achieve a better control effect with 22.66% decrease in Integral Absolute Error Criterion (IAE) of T_st (Temperature of PEMFC) and 77.56% decrease in IAE of T_in (Temperature of inlet cooling water) compared with traditional PID. In the end, a novel thermal management structure is proposed, which uses the cooling air passing through the main radiator to continue cooling the secondary radiator. In this thermal management structure, the parasitic power dissipation can be reduced by 69.94%, and the control effect can be improved with a 52.88% decrease in IAE of T_in under the same controller.

Keywords: PEMFC system, parameter identification, temperature control, Fuzzy-PID, RBF-PID, parasitic power

Procedia PDF Downloads 85

Authors: N. Y. H. Konagano

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Riverside population of Brazilian amazon suffers drinking water scarcity, seeking alternative water resources such as well and rivers, ordinary polluted. Although Amazon Region holds high annual river inflow and enough available of underground water, human activities have compromised the conservation of water resources. In addition, decentralized rural households make difficult to access of potable water. Main objective is to analyze quantitatively the potential of rainwater harvesting to human consumption at Marupaúba community, located in northeast of Amazon region, Brazil. Methods such as historical rainfall data series of municipality of Tomé-Açu at Pará state were obtained from Hydrological Information System of National Water Agency (ANA). Besides, Rippl method was used to calculate, mainly, volume of the reservoir based on difference of water demand and volume available through rainwater using as references two houses (CA I and CA II) as model of rainwater catchment and supply. Results presented that, from years 1984 to 2017, average annual precipitation was 2.607 mm, average maximum precipitation peak was 474 mm on March and average minimum peak on September was 44 mm. All months, of a year, surplus volume of water have presented in relation to demand, considering catchment area (CA) I = 134.4m² and demand volume =0.72 m³/month; and, CA II = 81.84 m² and demand volume = 0.48 m³/month. Based on results, it is concluded that it is feasible to use rainwater for the supply of the rural community Marupaúba, since the access of drinking water is a human right and the lack of this resource compromises health and daily life of human beings.

Keywords: Amazon Region, rainwater harvesting, rainwater resource, rural community

Procedia PDF Downloads 150

Authors: P. Karimi, A. H. Khedmati Bazkiaei

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The main goal of this study is to test differential neural network as a controller of smart structure and is to enumerate its advantages and disadvantages in comparison with other controllers. In this study, the smart structure has been considered as a Euler Bernoulli cantilever beam and it has been tried that it be under control with the use of vibration neural network resulting from movement. Also, a linear observer has been considered as a reference controller and has been compared its results. The considered vibration charts and the controlled state have been recounted in the final part of this text. The obtained result show that neural observer has better performance in comparison to the implemented linear observer.

Keywords: smart material, on-line differential artificial neural network, active control, finite element method

Procedia PDF Downloads 210

Authors: Radu Pop, Adrian Bot, Vasile Rednic, Emil Bruj, Oana Raita, Liviu Vaida

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Our research presents a study concerning optimization of water flow capture for micro-hydro power plants in order to increase the energy production. It is known that the fish ladder whole, were the water is capture is fix, and the water flow may vary with the river flow, this means that on the fish ladder we will have different servitude flows, sometimes more than needed. We propose to demonstrate that the ‘winter intake’ from micro-hydro power plant, could be automated with an intelligent system which is capable to read some imposed data and adjust the flow in to the needed value. With this automation concept, we demonstrate that the performance of the micro-hydro power plant could increase, in some flow operating regimes, with approx. 10%.

Keywords: energy, micro-hydro, water intake, fish ladder

Procedia PDF Downloads 234

Authors: B. S. Akhmetov, A. I. Ivanov, T. S. Kartbayev, A. Y. Malygin, K. Mukapil, S. D. Tolybayev

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The article examines the testing of the neural network converter of biometrics code. Determined the main reasons that prevented the use adopted in the works of foreign researchers classical a Binomial Law when describing distribution of measures of Hamming "Alien" codes-responses.

Keywords: biometrics, testing, neural network, converter of biometrics-code, Hamming's measure

Procedia PDF Downloads 1138

Authors: Priyanka Yadav, Rajkumar Ghosh, Alok Saini

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Human civilization cannot exist and thrive in the absence of adequate water. As a result, even in smart cities, water plays an important role in human existence. The key causes of this catastrophic water scarcity crisis are lifestyle changes, over-exploitation of groundwater, water over usage, rapid urbanization, and uncontrolled population growth. Furthermore, salty water seeps into deeper aquifers, causing land subsidence. The purpose of this study on artificial groundwater recharge is to address the water shortage in Gomti Nagar, Lucknow. Submersibles are the most common methods of collecting freshwater from groundwater in Gomti Nagar neighbourhood of Lucknow. Gomti Nagar area has a groundwater depletion rate of 1968 m3/day/km2 and is categorized as Zone-A (very high levels) based on the existing groundwater abstraction pattern - A to D. Harvesting rainwater using roof top rainwater harvesting systems (RTRWHs) is an effective method for reducing aquifer depletion in a sustainable water management system. Rainwater collecting using roof top rainwater harvesting systems (RTRWHs) is an effective method for reducing aquifer depletion in a sustainable water conservation system. Due to a water imbalance of 24519 ML/yr, the Gomti Nagar region is facing severe groundwater depletion. According to the Lucknow Development Authority (LDA), the impact of installed RTRWHs (plot area 300 sq. m.) is 0.04 percent of rainfall collected through RTRWHs in Gomti Nagar region of Lucknow. When RTRWHs are deployed in all buildings, their influence will be greater. Bye-laws in India have mandated the installation of RTRWHs on plots greater than 300 sq.m. A better India without any water problem is a pipe dream that may be realized by installing residential and commercial rooftop rainwater collecting systems in every structure. According to the current study, RTRWHs should be used as an alternate source of water to bridge the gap between groundwater recharge and extraction in smart city viz. Gomti Nagar, Lucknow, India.

Keywords: groundwater recharge, RTRWHs, harvested rainwater, rainfall, water extraction

Procedia PDF Downloads 106

Authors: Aziez Ouahiba, Remini Boualem, Habi Mohamed

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The growth and the development of a pay are strongly related to the existence or the absence of water in this area, the sedentary lifestyle of the population makes that water demand is increasing and the different brandishing (dams, tablecloths or other) are increasingly solicited. In normal time rain and snow of the winter period reloads the slicks and the wadis that fill dams. Over these two decades, Global warming fact that temperature is increasingly high and rainfall is increasingly low, which induces a charge less and less important tablecloths, add to that the strong demand in irrigation. Our study will focus on the variation of rainfall and irrigation, Their effects on the degree of pollution of the groundwater in this area based on statistical analyses by the Xlstat (ACP, correlation...) software for a better explanation of these results and determine the hydrochemistry of different groups or polluted areas pou be able to offer adequate solutions for each area.

Keywords: water in the basement, legislation, over exploitation, pollution, water prices

Procedia PDF Downloads 382

Authors: Panagiotis Karadimos, Leonidas Anthopoulos

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Predicting the actual cost and duration in construction projects concern a continuous and existing problem for the construction sector. This paper addresses this problem with modern methods and data available from past public construction projects. 39 bridge projects, constructed in Greece, with a similar type of available data were examined. Considering each project’s attributes with the actual cost and the actual duration, correlation analysis is performed and the most appropriate predictive project variables are defined. Additionally, the most efficient subgroup of variables is selected with the use of the WEKA application, through its attribute selection function. The selected variables are used as input neurons for neural network models through correlation analysis. For constructing neural network models, the application FANN Tool is used. The optimum neural network model, for predicting the actual cost, produced a mean squared error with a value of 3.84886e-05 and it was based on the budgeted cost and the quantity of deck concrete. The optimum neural network model, for predicting the actual duration, produced a mean squared error with a value of 5.89463e-05 and it also was based on the budgeted cost and the amount of deck concrete.

Keywords: actual cost and duration, attribute selection, bridge construction, neural networks, predicting models, FANN TOOL, WEKA

Procedia PDF Downloads 134

Authors: E. Behmanesh, J. Pannek

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Logistics network design is known as one of the strategic decision problems. As these kinds of problems belong to the category of NP-hard problems, traditional ways are failed to find an optimal solution in short time. In this study, we attempt to involve reverse flow through an integrated design of forward/reverse supply chain network that formulated into a mixed integer linear programming. This Integrated, multi-stages model is enriched by three different delivery path which makes the problem more complex. To tackle with such an NP-hard problem a revised random path direct encoding method based memetic algorithm is considered as the solution methodology. Each algorithm has some parameters that need to be investigate to reveal the best performance. In this regard, Taguchi method is adapted to identify the optimum operating condition of the proposed memetic algorithm to improve the results. In this study, four factors namely, population size, crossover rate, local search iteration and a number of iteration are considered. Analyzing the parameters and improvement in results are the outlook of this research.

Keywords: integrated logistics network, flexible path, memetic algorithm, Taguchi method

Procedia PDF Downloads 187

Authors: Mallikarjun B. Channappagoudar, Pallapa Venkataram

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The dynamic nature of Mobile adhoc network (MANET) due to mobility and disconnection of mobile nodes, leads to various problems in predicting the movement of nodes and their location information updation, for efficient interaction among the application specific nodes. Location management is one of the main challenges to be considered for an efficient service provision to the applications of a MANET. In this paper, we propose a location management protocol, for locating the nodes of a MANET and to maintain uninterrupted high-quality service for distributed applications by intelligently anticipating the change of location of its nodes. The protocol predicts the node movement and application resource scarcity, does the replacement with the chosen nodes nearby which have less mobility and rich in resources, with the help of both static and mobile agents, and maintains the application continuity by providing required network resources. The protocol has been simulated using Java Agent Development Environment (JADE) Framework for agent generation, migration and communication. It consumes much less time (response time), gives better location accuracy, utilize less network resources, and reduce location management overhead.

Keywords: mobile agent, location management, distributed applications, mobile adhoc network

Procedia PDF Downloads 394

Authors: C. N. Okafor, M. Maaza, T. A. E. Mokrani

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A proton exchange membrane has been developed for Direct Methanol Fuel Cell (DMFC). The nanofiber network composite membranes were prepared by interconnected network of Nafion (perfuorosulfonic acid) nanofibers that have been embedded in an uncharged and inert polymer matrix, by electro-spinning. The spinning solution of Nafion with a low concentration (1 wt. % compared to Nafion) of high molecular weight poly(ethylene oxide), as a carrier polymer. The interconnected network of Nafion nanofibers with average fiber diameter in the range of 160-700nm, were used to make the membranes, with the nanofiber occupying up to 85% of the membrane volume. The matrix polymer was cross-linked with Norland Optical Adhesive 63 under UV. The resulting membranes showed proton conductivity of 0.10 S/cm at 25°C and 80% RH; and methanol permeability of 3.6 x 10-6 cm2/s.

Keywords: composite membrane, electrospinning, fuel cell, nanofibers

Procedia PDF Downloads 266

Authors: Opeyemi Atiba-Oyewo, Taile Y. Leswfi, Maurice S. Onyango, Christian Wolkersdorfer

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This paper describes the preparation of surface modified montmorillonite using hexadecyltrimethylammonium bromide (HDTMA-Br) for the removal of vanadium from mine water. The adsorbent before and after adsorption was characterised by Fourier transform infra-red (FT-IR), X-ray diffraction (XRD) and scanning electron microscopy (SEM), while the amount of vanadium adsorbed was determined by ICP-OES. The batch adsorption method was employed using vanadium concentrations in solution ranging from 50 to 320 mg/L and vanadium tailings seepage water from a South African mine. Also, solution pH, temperature and sorbent mass were varied. Results show that the adsorption capacity was affected by solution pH, temperature, sorbent mass and the initial concentration. Electrical conductivity of the mine water before and after adsorption was measured to estimate the total dissolved solids in the mine water. Equilibrium isotherm results revealed that vanadium sorption follows the Freundlich isotherm, indicating that the surface of the sorbent was heterogeneous. The pseudo-second order kinetic model gave the best fit to the kinetic experimental data compared to the first order and Elovich models. The results of this study may be used to predict the uptake efficiency of South Africa montmorillonite in view of its application for the removal of vanadium from mine water. However, the choice of this adsorbent for the uptake of vanadium or other contaminants will depend on the composition of the effluent to be treated.

Keywords: adsorption, vanadium, modified montmorillonite, equilibrium, kinetics, mine water

Procedia PDF Downloads 433

Authors: Elhadji Mamadou Sonko, Ndiogou Sankhare, Jean Birane Gning, Cheikh Diop

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In Senegal, small towns have problems of access to water, hygiene, and sanitation. This study aims to assess the situation in Foundiougne. The methodology includes a literature review, semi-structured interviews with stakeholders, surveys of 100 households, and observation. The results show that 35% of households have unimproved water services, 46% have limited service, and 19% have basic service. Regarding sanitation, 77% of households have basic sanitation services, and 23% have limited sanitation services. Manual emptying alone is practiced by 4% of households, while 17% combine it with mechanical emptying. Household wastewater is disposed of in streets, vacant land, and concession yards. The emptied sludge is discharged into the environment without treatment. Hand washing is practiced by 98% of households. These results show that there is real work to be done at the small towns level to close the water and sanitation gap in order to achieve SDG 6 targets in Senegal.

Keywords: foundiougne, SDG 6, senegal, small towns, water sanitation ang hygiene

Procedia PDF Downloads 128

Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

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The U.S. Federal Emergency Management Agency (FEMA) developed flood maps based on experts’ experience and estimates of the probability of flooding. Current flood-risk models evaluate flood risk with regional and subjective measures without impact from torrential rain and nuisance flooding at the neighborhood level. Nuisance flooding occurs in small areas in the community, where a few streets or blocks are routinely impacted. This type of flooding event occurs when torrential rainstorm combined with high tide and sea level rise temporarily exceeds a given threshold. In South Florida, this threshold is 1.7 ft above Mean Higher High Water (MHHW). The National Weather Service defines torrential rain as rain deposition at a rate greater than 0.3-inches per hour or three inches in a single day. Data from the Florida Climate Center, 1970 to 2020, shows 371 events with more than 3-inches of rain in a day in 612 months. The purpose of this research is to develop a data-driven method to determine comprehensive analytical damage-avoidance criteria that account for nuisance flood events at the single-family home level. The method developed uses the Failure Mode and Effect Analysis (FMEA) method from the American Society of Quality (ASQ) to estimate the Damage Avoidance (DA) preparation for a 1-day 100-year storm. The Consequence of Nuisance Flooding (CoNF) is estimated from community mitigation efforts to prevent nuisance flooding damage. The Probability of Nuisance Flooding (PoNF) is derived from the frequency and duration of torrential rainfall causing delays and community disruptions to daily transportation, human illnesses, and property damage. Urbanization and population changes are related to the U.S. Census Bureau's annual population estimates. Data collected by the United States Department of Agriculture (USDA) Natural Resources Conservation Service’s National Resources Inventory (NRI) and locally by the South Florida Water Management District (SFWMD) track the development and land use/land cover changes with time. The intent is to include temporal trends in population density growth and the impact on land development. Results from this investigation provide the risk of nuisance flooding as a function of CoNF and PoNF for coastal areas of South Florida. The data-based criterion provides awareness to local municipalities on their flood-risk assessment and gives insight into flood management actions and watershed development.

Keywords: flood risk, nuisance flooding, urban flooding, FMEA

Procedia PDF Downloads 98

Authors: Maoxin Ye

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This study examines the relationship between social network sites (SNS) usage and social capital. Because SNS usage can expand the users’ networks, and people who are connected in this networks may become resources to SNS users and lead them to advantage in some situation, it is important to estimate the relationship between SNS usage and ‘who’ is connected or what resources the SNS users can get. Additionally, ‘who’ can be divided in two aspects – people who possess high position and people who are different, hence, it is important to estimate the relationship between SNS usage and high position people and different people. This study adapts Lin’s definition of social capital and the measurement of position generator which tells us who was connected, and can be divided into the same two aspects as well. A national data of America (N = 2,255) collected by Pew Research Center is utilized to do a general regression analysis about SNS usage and social capital. The results indicate that SNS usage is negatively associated with each factor of social capital, and it suggests that, in fact, comparing with non-users, although SNS users can get more connections, the variety and resources of these connections are fewer. For this reason, we could lose benefits through SNS usage.

Keywords: social network sites, social capital, position generator, general regression

Procedia PDF Downloads 262

Authors: Mladen Hraste, Igor Jelaska, Ivan Granic

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The scope of this research is the identification and explanation of differences of three levels of water polo players in some parameters of effectiveness. The sample for this study was 132 matches of the Adriatic Water Polo League in the 2013/14 competition season. Using the Kruskal-Wallis test and multiple comparisons of mean ranks for all groups at the significance level of α=0, 05, the hypothesis that there are significant differences between groups of respondents in ten of the seventeen variables of effectiveness was confirmed. There is a reasonable possibility that the differences are caused by the degree of learned and implemented tactical knowledge, the degree of scoring ability and the best selection for certain roles in the team. The results of this study can be applied to selection of teams and players, for the selection of the appropriate match concept and for organizing training process.

Keywords: scoring abilities, selection, tactical knowledge, water polo effectiveness

Procedia PDF Downloads 501

Authors: Qudratullah Muradi

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Geothermal energy is a renewable energy source that can be found in abundance on our planet. Only a small fraction of it is currently converted to electrical power, though in recent years installed geothermal capacity has increased considerably all over the world. In this paper, we assumed a model for designing of Enhanced Geothermal System, EGS. We used computer modeling group, CMG reservoir simulation software to create the typical Hot Dry Rock, HDR reservoir. In this research two wells, one injection of cold water and one production of hot water are included in the model. There are some hydraulic fractures created by the mentioned software. And cold water is injected in order to produce energy from the reservoir. The result of injecting cold water to the reservoir and extracting geothermal energy is defined by some graphs at the end of this research. The production of energy is quantified in a period of 10 years.

Keywords: geothermal energy, EGS, HDR, hydraulic fracturing

Procedia PDF Downloads 199

Authors: M. Nekri, A. Khelladi

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The world wide web network is a network with a complex topology, the main properties of which are the distribution of degrees in power law, A low clustering coefficient and a weak average distance. Modeling the web as a graph allows locating the information in little time and consequently offering a help in the construction of the research engine. Here, we present a model based on the already existing probabilistic graphs with all the aforesaid characteristics. This work will consist in studying the web in order to know its structuring thus it will enable us to modelize it more easily and propose a possible algorithm for its exploration.

Keywords: clustering coefficient, preferential attachment, small world, web community

Procedia PDF Downloads 272

Authors: Huawei Bai, Jianguo Yao, Fellow, IEEE

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Atrial fibrillation (AF) is the most common form of heart arrhythmia and is closely associated with mortality and morbidity in heart failure, stroke, and coronary artery disease. The development of single spot optical sensors enables widespread photoplethysmography (PPG) screening, especially for AF, since it represents a more convenient and noninvasive approach. To our knowledge, most existing studies based on public and unbalanced datasets can barely handle the multiple noises sources in the real world and, also, lack interpretability. In this paper, we construct a large- scale PPG dataset using measurements collected from PPG wrist- watch devices worn by volunteers and propose an attention-based two-stream heterogeneous neural network (TSHNN). The first stream is a hybrid neural network consisting of a three-layer one-dimensional convolutional neural network (1D-CNN) and two-layer attention- based bidirectional long short-term memory (Bi-LSTM) network to learn representations from temporally sampled signals. The second stream extracts latent representations from the PPG time-frequency spectrogram using a five-layer CNN. The outputs from both streams are fed into a fusion layer for the outcome. Visualization of the attention weights learned demonstrates the effectiveness of the attention mechanism against noise. The experimental results show that the TSHNN outperforms all the competitive baseline approaches and with 98.09% accuracy, achieves state-of-the-art performance.

Keywords: PPG wearables, atrial fibrillation, feature fusion, attention mechanism, hyber network

Procedia PDF Downloads 121

Authors: Davod Ahmadigheidari, Isabel Alvarez, Kate Sinclair, Marnie Davidson, Patrick Cortbaoui, Hugo Melgar-Quiñonez

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The burden of collecting water tends to disproportionately fall on women and girls in low-income countries. Specifically, women spend between one to eight hours per day fetching water for domestic use in Sub-Saharan Africa. While there has been research done on the global time burden for collecting water, it has been mainly focused on water quality parameters; leaving the relationship between water fetching and health outcomes understudied. There is little available evidence regarding the relationship between water fetching and maternal child care practices. The main objective of this study was to help fill the aforementioned gap in the literature. Data from two surveys in Ethiopia and Malawi conducted by CARE Canada in 2016-2017 were used. Descriptive statistics indicate that women were predominantly responsible for collecting water in both Ethiopia (87%) and Malawi (99%) respectively, with the majority spending more than 30 minutes per day on water collection. With regards to child care practices, in both countries, breastfeeding was relatively high (77% and 82%, respectively); and treatment for malnutrition was low (15% and 8%, respectively). However, the same consistency was not found for weighing; in Ethiopia only 16% took their children for weighting in contrast to 94% in Malawi. These three practices were summed to create one variable for regressions analyses. Unadjusted logistic regression findings showed that only in Ethiopia was time fetching water significantly associated with child care practices. Once adjusted for covariates, this relationship was no longer found to be significant. Adjusted logistic regressions also showed that the factors that did influence child care practices differed slightly between the two countries. In Ethiopia, a lack of access to community water supply (OR= 0.668; P=0.010), poor attitudes towards gender equality (OR= 0.608; P=0.001), no access to land and (OR=0.603; P=0.000), significantly decreased a women’s odd of using positive childcare practices. Notably, being young women between 15-24 years (OR=2.308; P=0.017), and 25-29 (OR=2.065; P=0.028) increased probability of using positive childcare practices. Whereas in Malawi, higher maternal age, low decision-making power, significantly decreased a women’s odd of using positive childcare practices. In conclusion, this study found that even though amount of time spent by women fetching water makes a difference for childcare practices, it is not significantly related to women’s child care practices when controlling the covariates. Importantly, women’s age contributes to child care practices in Ethiopia and Malawi.

Keywords: time fetching water, community water supply, women’s child care practices, Ethiopia, Malawi

Procedia PDF Downloads 202

Authors: Shyh-Ming Chern, H. Y. Cheng

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Biomass is renewable and sustainable. As an energy source, it will not release extra carbon dioxide into the atmosphere. Hence, tremendous efforts have been made to develop technologies capable of transforming biomass into suitable forms of bio-fuel. One of the viable technologies is gasifying biomass in supercritical water (SCW), a green medium for reactions. While previous studies overwhelmingly selected glucose as a model compound for biomass, the present study adopted fructose for the sake of comparison. The gasification of fructose in SCW was investigated experimentally to evaluate the applicability of supercritical water processes to biomass gasification. Experiments were conducted with an autoclave reactor. Gaseous product mainly consists of H2, CO, CO2, CH4 and C2H6. The effect of two major operating parameters, the reaction temperature (673-873 K) and the dosage of oxidizing agent (0-0.5 stoichiometric oxygen), on the product gas composition, yield and heating value was also examined, with the reaction pressure fixed at 25 MPa.

Keywords: biomass, fructose, gasification, supercritical water

Procedia PDF Downloads 353

Authors: P. Singh, R. M. Banik

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Artificial neural network (ANN) was employed to optimize assay parameters viz., time, temperature, pH of reaction mixture, enzyme volume and substrate concentration of L-glutaminase from Bacillus cereus MTCC 1305. ANN model showed high value of coefficient of determination (0.9999), low value of root mean square error (0.6697) and low value of absolute average deviation. A multilayer perceptron neural network trained with an error back-propagation algorithm was incorporated for developing a predictive model and its topology was obtained as 5-3-1 after applying Levenberg Marquardt (LM) training algorithm. The predicted activity of L-glutaminase was obtained as 633.7349 U/l by considering optimum assay parameters, viz., pH of reaction mixture (7.5), reaction time (20 minutes), incubation temperature (35˚C), substrate concentration (40mM), and enzyme volume (0.5ml). The predicted data was verified by running experiment at simulated optimum assay condition and activity was obtained as 634.00 U/l. The application of ANN model for optimization of assay conditions improved the activity of L-glutaminase by 1.499 fold.

Keywords: Bacillus cereus, L-glutaminase, assay parameters, artificial neural network

Procedia PDF Downloads 429

Authors: P. Suresh, K. Gunasekaran, R. Thanigaivelan

Abstract:

Radio frequency identification (RFID) technology has been attracting considerable attention with the expectation of improved supply chain visibility for consumer goods, apparel, and pharmaceutical manufacturers, as well as retailers and government procurement agencies. It is also expected to improve the consumer shopping experience by making it more likely that the products they want to purchase are available. Recent announcements from some key retailers have brought interest in RFID to the forefront. A modified K- Means Cluster based Heuristic approach, Hybrid Genetic Algorithm (GA) - Simulated Annealing (SA) approach, Hybrid K-Means Cluster based Heuristic-GA and Hybrid K-Means Cluster based Heuristic-GA-SA for Open Loop Supply Chain Network problem are proposed. The study incorporated uniform crossover operator and combined crossover operator in GAs for solving open loop supply chain distribution network problem. The algorithms are tested on 50 randomly generated data set and compared with each other. The results of the numerical experiments show that the Hybrid K-means cluster based heuristic-GA-SA, when tested on 50 randomly generated data set, shows superior performance to the other methods for solving the open loop supply chain distribution network problem.

Keywords: RFID, supply chain distribution network, open loop supply chain, genetic algorithm, simulated annealing

Procedia PDF Downloads 165

Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

Abstract:

In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss

Procedia PDF Downloads 475

Authors: Edafe Lucky Okotie, Emmanuel Osawaru Omosigho

Abstract:

This paper examines the impacts of the introduction of distributed energy generation (DEG) technology into the Nigerian power system as an alternative means of energy generation at distribution ends using Otovwodo 15 MVA, 33/11kV injection substation as a case study. The overall idea is to increase the generated energy in the system, improve the voltage profile and reduce system losses. A photovoltaic-based distributed energy generator (PV-DEG) was considered and was optimally placed in the network using Genetic Algorithm (GA) in Mat. Lab/Simulink environment. The results of simulation obtained shows that the dynamic performance of the network was optimized with DEG-grid integration.

Keywords: distributed energy generation (DEG), genetic algorithm (GA), power quality, total load demand, voltage profile

Procedia PDF Downloads 84

Authors: Eman Hegazy, Stefan Anderberg, Joakim Krook

Abstract:

Urban water infrastructure systems are central to functioning cities. For securing a continuous and efficient supply of the systems services, continuous investment, maintenance, and renewal are needed. Neglecting maintenance and renewal can lead to recurrent breakdown problems as systems age, which makes it more and more difficult to secure efficient long-term supply. Globally, many cities struggle with aging water infrastructure, often due to competing funding priorities. Investment in maintenance and renewal is not prioritized. The problem primarily stems from the challenge of reaping the benefits of investments promptly. The long-term benefits gained from investing in the renewal of water infrastructure may be achievable in the long run, resulting in the oversight of such investments. This leads to a build-up of "renewal debt" for future generations to inherit. Addressing this issue is difficult due to various contributing factors and the complex nature of the systems. The study aims to contribute to an increased understanding of the long-term management challenges of urban water infrastructure, the development of improved maintenance and renewal strategies through the examination of water infrastructure management, and the assessment of the adequacy of the maintenance and renewal in a case study, the city of Linköping, Sweden. Employing a multi-methods approach, this study utilized both qualitative and quantitative methods, including interviews, workshops, and data analysis. The findings of the study provided insights into the current status of the water and sewerage networks in Linkoping, highlighting the risks to ensuring reliable and sustainable water supply and discussing strategies for improving maintenance and renewal.

Keywords: case study, infrastructure management, renewal needs, Sweden, urban water infrastructure

Procedia PDF Downloads 68

Authors: Walid K. M. Bani Salameh, Hesham Ahmad, Mohammad Al-Shannag

Abstract:

In Jordan having deficit atmospheric precipitation, an increase in water demand during summer months . Jordan can be regarded with a relatively high potential for waste water recycling and reuse. The main purpose of this paper was to investigate the removal of Total suspended solids (TSS) and chemical oxygen demand (COD) for olive mill waste water (OMW) by the electrocoagulation (EC) process. In the combination of electrocoagulation by using coupled iron–aluminum electrodes the optimum working pH was found to be in range 6. The efficiency of the electrocoagulation process allowed removal of TSS and COD about 82.5% and 47.5% respectively at 45 mA/cm2 after 70 minutes by using coupled iron–aluminum electrodes. These results showed that the optimum TSS and COD removal was obtained at the optimum experimental parameters such as current density, pH, and reaction time.

Keywords: olive mill wastewater, electrode, electrocoagulation (EC), TSS, COD

Procedia PDF Downloads 393