Search results for: water consumption prediction

Authors: H. Al-Jabli

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The research on the presence of heavy metals and bromate in drinking water is of immense scientific significance due to the potential risks these substances pose to public health. These contaminants are subject to regulatory limits outlined by the National Primary Drinking Water Regulations. Through a comprehensive analysis involving the compilation of existing data and the collection of new data via water sampling in residential areas of Kuwait, the aim is to create detailed maps illustrating the spatial distribution of these substances. Furthermore, the investigation will utilize GRAPHER software to explore correlations among different chemical parameters. By implementing rigorous scientific methodologies, the research will provide valuable insights for the Ministry of Electricity and Water and the Ministry of Health. These insights can inform evidence-based decision-making, facilitate the implementation of corrective measures, and support strategic planning for future infrastructure activities.

Keywords: heavy metals, bromate, ozonation, GIS

Procedia PDF Downloads 81

Authors: Zeineb Ben Salem, Wissem Frikha, Mounir Bouassida

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Liquefaction has been responsible for tremendous amounts of damage in historical earthquakes around the world. The installation of stone columns is widely adopted to prevent liquefaction. Stone columns provide a drainage path, and due to their high permeability, allow for the quick dissipation of earthquake generated excess pore water pressure. Several excess pore pressure generation models in silty sand have been developed and calibrated based on the results of shaking table and centrifuge tests focusing on the effect of silt content on liquefaction resistance. In this paper, the generation and dissipation of excess pore pressure variation of reinforced silty sand by stone columns during liquefaction are analyzedwith different silt content based on test results. In addition, the installation effect of stone columns is investigated. This effect is described by a decrease in horizontal permeability within a disturbed zone around the column. Obtained results show that reduced soil permeability and a larger disturbed zone around the stone column increases the generation of excess pore pressure during the cyclic loading and decreases the dissipation rate after cyclic loading. On the other hand, beneficial effects of silt content were observed in the form of a decrease in excess pore water pressure.

Keywords: stone column, liquefaction, excess pore pressure, silt content, disturbed zone, reduced permeability

Procedia PDF Downloads 154

Authors: Balgaisha Mukanova, Natalya Glazyrina, Sergey Glazyrin

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The formulated problem of optimization of the technological process of water treatment for thermal power plants is considered in this article. The problem is of multiparametric nature. To optimize the process, namely, reduce the amount of waste water, a new technology was developed to reuse such water. A mathematical model of the technology of wastewater reuse was developed. Optimization parameters were determined. The model consists of a material balance equation, an equation describing the kinetics of ion exchange for the non-equilibrium case and an equation for the ion exchange isotherm. The material balance equation includes a nonlinear term that depends on the kinetics of ion exchange. A direct problem of calculating the impurity concentration at the outlet of the water treatment plant was numerically solved. The direct problem was approximated by an implicit point-to-point computation difference scheme. The inverse problem was formulated as relates to determination of the parameters of the mathematical model of the water treatment plant operating in non-equilibrium conditions. The formulated inverse problem was solved. Following the results of calculation the time of start of the filter regeneration process was determined, as well as the period of regeneration process and the amount of regeneration and wash water. Multi-parameter optimization of water treatment process for thermal power plants allowed decreasing the amount of wastewater by 15%.

Keywords: direct problem, multiparametric optimization, optimization parameters, water treatment

Procedia PDF Downloads 387

Authors: M. N. Azian, A. N. Ilia Anisa, Y. Iwai

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The mechanism for extraction bioactive compounds from plant matrix is essential for optimizing the extraction process. As a benchmark technique, a soxhlet extraction has been utilized for discussing the mechanism and compared with an accelerated water extraction. The trends of both techniques show that the process involves extraction and degradation. The highest yields of 6-, 8-, 10-gingerols and 6-shogaol in soxhlet extraction were 13.948, 7.12, 10.312 and 2.306 mg/g, respectively. The optimum 6-, 8-, 10-gingerols and 6-shogaol extracted by the accelerated water extraction at 140oC were 68.97±3.95 mg/g at 3min, 18.98±3.04 mg/g at 5min, 5.167±2.35 mg/g at 3min and 14.57±6.27 mg/g at 3min, respectively. The effect of temperature at 3mins shows that the concentration of 6-shogaol increased rapidly as decreasing the recovery of 6-gingerol.

Keywords: mechanism, ginger bioactive compounds, soxhlet extraction, accelerated water extraction

Procedia PDF Downloads 434

Authors: Nida Rizvi, Deeksha Katyal, Varun Joshi

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River Hindon is an important river catering the demand of highly populated rural and industrial cluster of western Uttar Pradesh, India. Water quality of river Hindon is deteriorating at an alarming rate due to various industrial, municipal and agricultural activities. The present study aimed at identifying the pollution sources and quantifying the degree to which these sources are responsible for the deteriorating water quality of the river. Various water quality parameters, like pH, temperature, electrical conductivity, total dissolved solids, total hardness, calcium, chloride, nitrate, sulphate, biological oxygen demand, chemical oxygen demand and total alkalinity were assessed. Water quality data obtained from eight study sites for one year has been subjected to the two multivariate techniques, namely, principal component analysis and cluster analysis. Principal component analysis was applied with the aim to find out spatial variability and to identify the sources responsible for the water quality of the river. Three Varifactors were obtained after varimax rotation of initial principal components using principal component analysis. Cluster analysis was carried out to classify sampling stations of certain similarity, which grouped eight different sites into two clusters. The study reveals that the anthropogenic influence (municipal, industrial, waste water and agricultural runoff) was the major source of river water pollution. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and elucidation of multifaceted data sets, recognition of pollution sources/factors and understanding temporal/spatial variations in water quality for effective river water quality management.

Keywords: cluster analysis, multivariate statistical techniques, river Hindon, water quality

Procedia PDF Downloads 467

Authors: Venencia Albert, Arulselvi Subramanian, Hara Prasad Pati, Asok K. Mukhophadhyay

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Acute traumatic coagulopathy in an endogenous dysregulation of the intrinsic coagulation system in response to the injury, associated with three-fold risk of poor outcome, and is more amenable to corrective interventions, subsequent to early identification and management. Multiple definitions for stratification of the patients' risk for early acute coagulopathy have been proposed, with considerable variations in the defining criteria, including several trauma-scoring systems based on prehospital data. We aimed to develop a clinically relevant definition for acute coagulopathy of trauma based on conventional coagulation assays and to assess its efficacy in comparison to recently established prehospital prediction models. Methodology: Retrospective data of all trauma patients (n = 490) presented to our level I trauma center, in 2014, was extracted. Receiver operating characteristic curve analysis was done to establish cut-offs for conventional coagulation assays for identification of patients with acute traumatic coagulopathy was done. Prospectively data of (n = 100) adult trauma patients was collected and cohort was stratified by the established definition and classified as "coagulopathic" or "non-coagulopathic" and correlated with the Prediction of acute coagulopathy of trauma score and Trauma-Induced Coagulopathy Clinical Score for identifying trauma coagulopathy and subsequent risk for mortality. Results: Data of 490 trauma patients (average age 31.85±9.04; 86.7% males) was extracted. 53.3% had head injury, 26.6% had fractures, 7.5% had chest and abdominal injury. Acute traumatic coagulopathy was defined as international normalized ratio ≥ 1.19; prothrombin time ≥ 15.5 s; activated partial thromboplastin time ≥ 29 s. Of the 100 adult trauma patients (average age 36.5±14.2; 94% males), 63% had early coagulopathy based on our conventional coagulation assay definition. Overall prediction of acute coagulopathy of trauma score was 118.7±58.5 and trauma-induced coagulopathy clinical score was 3(0-8). Both the scores were higher in coagulopathic than non-coagulopathic patients (prediction of acute coagulopathy of trauma score 123.2±8.3 vs. 110.9±6.8, p-value = 0.31; trauma-induced coagulopathy clinical score 4(3-8) vs. 3(0-8), p-value = 0.89), but not statistically significant. Overall mortality was 41%. Mortality rate was significantly higher in coagulopathic than non-coagulopathic patients (75.5% vs. 54.2%, p-value = 0.04). High prediction of acute coagulopathy of trauma score also significantly associated with mortality (134.2±9.95 vs. 107.8±6.82, p-value = 0.02), whereas trauma-induced coagulopathy clinical score did not vary be survivors and non-survivors. Conclusion: Early coagulopathy was seen in 63% of trauma patients, which was significantly associated with mortality. Acute traumatic coagulopathy defined by conventional coagulation assays (international normalized ratio ≥ 1.19; prothrombin time ≥ 15.5 s; activated partial thromboplastin time ≥ 29 s) demonstrated good ability to identify coagulopathy and subsequent mortality, in comparison to the prehospital parameter-based scoring systems. Prediction of acute coagulopathy of trauma score may be more suited for predicting mortality rather than early coagulopathy. In emergency trauma situations, where immediate corrective measures need to be taken, complex multivariable scoring algorithms may cause delay, whereas coagulation parameters and conventional coagulation tests will give highly specific results.

Keywords: trauma, coagulopathy, prediction, model

Procedia PDF Downloads 176

Authors: Suk Woo Hong, Chang Sung Seok, Jae Mean Koo

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Recently, the welding is widely used in modern industry for joining the structures. However, the waterworks pipes are exposed to the fatigue load by cars, earthquake and etc because of being buried underground. Moreover, the residual stress exists in weld zone by welding process and it is well known that the fatigue life of welded structures is degraded by residual stress. Due to such reasons, the crack can occur in the weld zone of pipeline. In this case, The ground subsidence or sinkhole can occur, if the soil and sand are washed down by fluid leaked from the crack of water pipe. These problems can lead to property damage and endangering lives. For these reasons, the estimation of fatigue characteristics for water pipeline weld zone is needed. Therefore, in this study, for fatigue characteristics estimation of spiral welded waterworks pipe, ASTM standard specimens and Curved Plate specimens were collected from the spiral welded waterworks pipe and the fatigue tests were performed. The S-N curves of each specimen were estimated, and then the fatigue life of weldment Curved Plate specimen was predicted by theoretical and analytical methods. After that, the weldment Curved Plate specimens were collected from the pipe and verification fatigue tests were performed. Finally, it was verified that the predicted S-N curve of weldment Curved Plate specimen was good agreement with fatigue test data.

Keywords: spiral welded pipe, prediction fatigue life, endurance limit modifying factors, residual stress

Procedia PDF Downloads 299

Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

Procedia PDF Downloads 108

Authors: Shang-Hsin Ou, Yang-Chun Lin, Ke-Hao Cheng

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The year 2021 marked a historic drought in Taiwan, posing unprecedented challenges due to record-low rainfall and inadequate reservoir storage. The central region experienced water scarcity, leading to the implementation of "Groundwater Utilization at Construction Sites" for drought-resilient livelihood water supply. This study focuses on the establishment process of temporary groundwater treatment plants at construction sites in Taichung City, serving as a reference for future emergency response and the utilization of construction site groundwater. To identify suitable sites for groundwater reuse projects, site selection operations were carried out based on relevant water quality regulations and assessment principles. Subsequently, the planning and design of temporary water treatment plants were conducted, considering the water quality, quantity, and on-site conditions of groundwater wells associated with construction projects. The study consolidates the major water treatment facilities at each site and addresses encountered challenges during the establishment process. Practical insights gained from operating temporary groundwater treatment plants are presented, including improvements related to stable water quality, water quantity, equipment operation, and hydraulic control. In light of possible future droughts, this study provides an outlook and recommendations to expedite and improve the setup of groundwater treatment plants at construction sites. This includes considering on-site water abstraction, treatment, and distribution conditions. The study's results aim to offer practical guidelines for effectively establishing and managing such treatment plants, while offering experiences and recommendations for other regions facing similar emergencies, water shortages, and drought situations. These endeavors contribute to ensuring sustainable water supply for drought-resilient livelihoods and maintaining societal stability.

Keywords: drought resilience, groundwater treatment, construction site, water supply

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Authors: Nadezhda Nikolaeva, Tatyana Alexandrova, Alexandr Alexandrov

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Processing of high-silicon bauxite on the base of the traditional clinkering method is related to high power consumption and capital investments, which makes production of alumina from those ores non-competitive in terms of basic economic showings. For these reasons, development of technological solutions enabling to process bauxites with various chemical and mineralogical structures efficiently with low level of thermal power consumption is important. Flow sheet of the studies on washability of ores from the Timanskoe and the Severo-Onezhskoe deposits is on the base of the flotation method.

Keywords: low-quality bauxite, resource-saving technology, optimization, aluminum, conditioning of composition, separation characteristics

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Authors: Rouighi Mustapha, Bouzid Laghaa Souad, Rouighi Tahar

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Due to rain Shortage and the increase of population in the last years, wells excavation and groundwater use for different purposes had been increased without any planning. This is a great challenge for our country. Moreover, this scarcity of water resources in this region is unfortunately combined with rapid fresh water resources quality deterioration, due to salinity and contamination processes. Therefore, it is necessary to conduct the studies about groundwater quality in Algeria. In this work consists in the identification of the factors which influence the water quality parameters in Laghouat region by using statistical analysis Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and geographic information system (GIS) in an attempt to discriminate the sources of the variation of water quality variations. The results of PCA technique indicate that variables responsible for water quality composition are mainly related to soluble salts variables; natural processes and the nature of the rock which modifies significantly the water chemistry. Inferred from the positive correlation between K+ and NO3-, NO3- is believed to be human induced rather than naturally originated. In this study, the multivariate statistical analysis and GIS allows the hydrogeologist to have supplementary tools in the characterization and evaluating of aquifers.

Keywords: cluster, analysis, GIS, groundwater, laghouat, quality

Procedia PDF Downloads 324

Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

Procedia PDF Downloads 39

Authors: Kehinde Damilola Ilesanmi, Dev Datt Tewari

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South Africa is in its post-industrial era moving from the primary and secondary sector to the tertiary sector. The study investigated the impact of the disaggregated energy consumption (coal, oil, and electricity) on the primary, secondary and tertiary sectors of the economy between 1980 and 2012 in South Africa. Using vector error correction model, it was established that South Africa is an energy dependent economy, and that energy (especially electricity and oil) is a limiting factor of growth. This implies that implementation of energy conservation policies may hamper economic growth. Output growth is significantly outpacing energy supply, which has necessitated load shedding. To meet up the excess energy demand, there is a need to increase the generating capacity which will necessitate increased investment in the electricity sector as well as strategic steps to increase oil production. There is also need to explore more renewable energy sources, in order to meet the growing energy demand without compromising growth and environmental sustainability. Policy makers should also pursue energy efficiency policies especially at sectoral level of the economy.

Keywords: causality, economic growth, energy consumption, hypothesis, sectoral output

Procedia PDF Downloads 470

Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

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Understanding the causes of a road accident and predicting their occurrence is key to preventing deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network.

Keywords: accident risks estimation, artificial neural network, deep learning, k-mean, road safety

Procedia PDF Downloads 163

Authors: I. O. Nascimento, J. T. Manzi

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The drying process is an important operation in the chemical industry and it is widely used in the food, grain industry and fertilizer industry. However, for demanding a considerable consumption of energy, such a process requires a deep energetic analysis in order to reduce operating costs. This paper deals with thermodynamic optimization applied to rotary dryers based on the entropy production minimization, aiming at to reduce the energy consumption. To do this, the mass, energy and entropy balance was used for developing a relationship that represents the rate of entropy production. The use of the Second Law of Thermodynamics is essential because it takes into account constraints of nature. Since the entropy production rate is minimized, optimals conditions of operations can be established and the process can obtain a substantial gain in energy saving. The minimization strategy had been led using classical methods such as Lagrange multipliers and implemented in the MATLAB platform. As expected, the preliminary results reveal a significant energy saving by the application of the optimal parameters found by the procedure of the entropy minimization It is important to say that this method has shown easy implementation and low cost.

Keywords: thermodynamic optimization, drying, entropy minimization, modeling dryers

Procedia PDF Downloads 258

Authors: Jagannath Koravadi, Archith Gupta

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In a world with constantly growing energy prices, and growing concerns about the global climate changes caused by increased energy consumption, it is becoming more and more essential to save energy wherever possible. Refrigeration systems are one of the major and bulk energy consuming systems now-a-days in industrial sectors, residential sectors and household environment. Refrigeration systems with considerable cooling requirements consume a large amount of electricity and thereby contribute greatly to the running costs. Therefore, a great deal of attention is being paid towards improvement of the performance of the refrigeration systems in this regard throughout the world. The Coefficient of Performance (COP) of a refrigeration system is used for determining the system's overall efficiency. The operating cost to the consumer and the overall environmental impact of a refrigeration system in turn depends on the COP or efficiency of the system. The COP of a refrigeration system should therefore be as high as possible. Slight modifications in the technical elements of the modern refrigeration systems have the potential to reduce the energy consumption, and improvements in simple operational practices with minimal expenses can have beneficial impact on COP of the system. Thus, the challenge is to determine the changes that can be made in a refrigeration system in order to improve its performance, reduce operating costs and power requirement, improve environmental outcomes, and achieve a higher COP. The opportunity here, and a better solution to this challenge, will be to incorporate modifications in conventional refrigeration systems for saving energy. Energy efficiency, in addition to improvement of COP, can deliver a range of savings such as reduced operation and maintenance costs, improved system reliability, improved safety, increased productivity, better matching of refrigeration load and equipment capacity, reduced resource consumption and greenhouse gas emissions, better working environment, and reduced energy costs. The present work aims at fabricating a working model of a refrigerator that will provide for effective heat recovery from superheated refrigerant with the help of an efficient de-superheater. The temperature of the refrigerant and water in the de-super heater at different intervals of time are measured to determine the quantity of waste heat recovered. It is found that the COP of the system improves by about 6% with the de-superheater and the power input to the compressor decreases by 4 % and also the refrigeration capacity increases by 4%.

Keywords: coefficiency of performance, de-superheater, refrigerant, refrigeration capacity, heat recovery

Procedia PDF Downloads 320

Authors: Yilin Liao, Hewen Li, Paula McConvey

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Speed skaters often face a risk of concussion when they fall on the ice floor and impact crash mats during practices and competitive races. Several variables, including those related to the skater, the crash mat, and the impact position (body side/head/feet impact), are believed to influence the severity of the skater's concussion. While computer simulation modeling can be employed to analyze these accidents, the simulation process is time-consuming and does not provide rapid information for coaches and teams to assess the skater's injury risk in competitive events. This research paper promotes the exploration of the feasibility of using AI techniques for evaluating skater’s potential concussion severity, and to develop a fast concussion prediction tool using artificial neural networks to reduce the risk of treatment delays for injured skaters. The primary data is collected through virtual tests and physical experiments designed to simulate skater-mat impact. It is then analyzed to identify patterns and correlations; finally, it is used to train and fine-tune the artificial neural networks for accurate prediction. The development of the prediction tool by employing machine learning strategies contributes to the application of AI methods in sports science and has theoretical involvements for using AI techniques in predicting and preventing sports-related injuries.

Keywords: artificial neural networks, concussion, machine learning, impact, speed skater

Procedia PDF Downloads 109

Authors: Behrooz Balaei, Suzanne Wilkinson, Regan Potangaroa, Larry Abel, Philip McFarlane

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Water supply system failure has serious direct and indirect effects on people wellbeing. Post-disaster water system serviceability depends on a variety of factors from technical characteristics to social, economic, and organizational attributes of communities. This paper tests the organizational factors affecting water supply resilience to outline how these factors contributed to previous disasters. To do so, a framework is briefly introduced in this study to provide a clear guide to identify the significant relevant organizational factors. Then the factors affecting water serviceability following a disaster are outlines. Next, these factors are measured in the case of Tropical Cyclone Pam, which hit Vanuatu in March 2015. Reviewing the existing literature has also been carried out to obtain a comprehensive understanding of the background A site visit and a series of interviews have also been undertaken following the cyclone to collect site-specific data and information. In the end, the organizational factors were ranked to enable decision makers to identify significance of each factor compared to the others.

Keywords: water supply, resilience, organizational capacity, Vanuatu, Tropical Cyclone Pam

Procedia PDF Downloads 129

Authors: Eleanor L. Kutschera

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This study explores the possible impact that QR codes play in helping individuals make more sustainable choices regarding apparel consumption. Data was collected via an online survey to ascertain individuals’ knowledge, attitudes, and behaviors with regard to QR codes and how this impacts their decisions to purchase apparel. Results from 250 participants provide both qualitative and quantitative data that provide valuable information regarding consumers’ use of QR codes and more sustainable purchases. Specifically, results indicate that QR codes are currently under-utilized in the apparel industry but have the potential to generate more environmentally conscious purchases. Also, results posit that while the cost of the item is the most influential factor in purchasing sustainable garments, other factors such as how, where, and what it is made of are in the middle, along with the company’s story/inspiration for creation have an impact. Moreover, participants posit the use of QR codes could make them more informed and empowered consumers, and they would be more likely to make purchases that are better for the environment. Participants’ qualitative responses provide useful incentives that could increase their future sustainable purchases. Finally, this study touches on the study’s limitations, implications, and future direction of research.

Keywords: digital ID, QR codes, environmental consciousness, sustainability, fashion industry, apparel consumption

Procedia PDF Downloads 103

Authors: Isra Elfatih Salih Edrees, Mehmet Serdar Ufuk Türeli

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In this paper, an energy-aware method is presented, integrating energy-efficient relay-augmented techniques for correlated data routing with the goal of optimizing bottleneck throughput in wireless sensor networks. The system tackles the dual challenge of throughput optimization while considering sensor network energy consumption. A unique routing metric has been developed to enable throughput maximization while minimizing energy consumption by utilizing data correlation patterns. The paper introduces a game theoretic framework to address the NP-complete optimization problem inherent in throughput-maximizing correlation-aware routing with energy limitations. By creating an algorithm that blends energy-aware route selection strategies with the best reaction dynamics, this framework provides a local solution. The suggested technique considerably raises the bottleneck throughput for each source in the network while reducing energy consumption by choosing the best routes that strike a compromise between throughput enhancement and energy efficiency. Extensive numerical analyses verify the efficiency of the method. The outcomes demonstrate the significant decrease in energy consumption attained by the energy-efficient relay-augmented bottleneck throughput maximization technique, in addition to confirming the anticipated throughput benefits.

Keywords: correlated data aggregation, energy efficiency, game theory, relay-augmented routing, throughput maximization, wireless sensor networks

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Authors: Ramanpreet Kaur, Upasana Sharma

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The purpose of this paper is to address the challenges faced by MLDB system at the piston foundry plant due to interruption in supply of water. For the MLDB system to work in Model, two sub-units must be connected to the robotic main unit. The system cannot function without robotics and water supply by the fan (WSF). Insufficient water supply is the cause of system failure. The system operates at top performance using two sub-units. If one sub-unit fails, the system capacity is reduced. Priority of repair is given to the main unit i.e. Robotic and WSF. To solve the problem, semi-Markov process and regenerative point technique are used. Relevant graphs are also included to particular case.

Keywords: MLDB system, robotic, semi-Markov process, regenerative point technique

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Authors: Amit Kumar Verma

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The present study deals with fire prediction model in Terai Arc Landscape, one of the most dramatic ecosystems in Asia where large, wide-ranging species such as tiger, rhinos, and elephant will thrive while bringing economic benefits to the local people. Forest fires cause huge economic and ecological losses and release considerable quantities of carbon into the air and is an important factor inflating the global burden of carbon emissions. Forest fire is an important factor of behavioral cum ecological habit of tiger in wild. Post fire changes i.e. micro and macro habitat directly affect the tiger habitat or land. Vulnerability of fire depicts the changes in microhabitat (humus, soil profile, litter, vegetation, grassland ecosystem). Microorganism like spider, annelids, arthropods and other favorable microorganism directly affect by the forest fire and indirectly these entire microorganisms are responsible for the development of tiger (Panthera tigris) habitat. On the other hand, fire brings depletion in prey species and negative movement of tiger from wild to human- dominated areas, which may leads the conflict i.e. dangerous for both tiger & human beings. Early forest fire prediction through mapping the risk zones can help minimize the fire frequency and manage forest fires thereby minimizing losses. Satellite data plays a vital role in identifying and mapping forest fire and recording the frequency with which different vegetation types are affected. Thematic hazard maps have been generated by using IDW technique. A prediction model for fire occurrence is developed for TAL. The fire occurrence records were collected from state forest department from 2000 to 2014. Disciminant function models was used for developing a prediction model for forest fires in TAL, random points for non-occurrence of fire have been generated. Based on the attributes of points of occurrence and non-occurrence, the model developed predicts the fire occurrence. The map of predicted probabilities classified the study area into five classes very high (12.94%), high (23.63%), moderate (25.87%), low(27.46%) and no fire (10.1%) based upon the intensity of hazard. model is able to classify 78.73 percent of points correctly and hence can be used for the purpose with confidence. Overall, also the model works correctly with almost 69% of points. This study exemplifies the usefulness of prediction model of forest fire and offers a more effective way for management of forest fire. Overall, this study depicts the model for conservation of tiger’s natural habitat and forest conservation which is beneficial for the wild and human beings for future prospective.

Keywords: fire prediction model, forest fire hazard, GIS, landsat, MODIS, TAL

Procedia PDF Downloads 352

Authors: Matheus Fonseca Durães, Bruno da Silva Pereira, Bruna Stewart

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The concept of Brazil’s water governance has been the topic of discussion and has undergone legal and organizational improvements due to the need to promote a more effective and sustainable relationship with natural resources and stemming from conflicts related to shortcomings in decision-making. The Waters Act has enabled Brazil to create interesting mechanisms for integrated management, but, on the other hand, it has created a challenge that involves the implementation of the principles established in this legal framework. This study aims to evaluate some challenges and opportunities for water governance in two watersheds based on data collection and analysis of concessions, the water use register, and flow data. The elements presented demonstrated, via an analysis of legally instituted criteria, that the level of commitment of water resources is high, especially to public supply, and the adoption of the reference flow constituted one of the main barriers to implementing an efficient system, demonstrating the need for a regulatory policy that considers the hydrological behavior of the watersheds. Finally, the current water management model presents challenges to be addressed to achieve the objectives proposed by the water policy, such as ensuring sustainable, rational, and integrated use of water resources.

Keywords: management, hydrology, public policies, Brazil

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Authors: Smita Krishnan, Krittika Chandran, Chandra Mohan Sinnathambi

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Produced water and its treatment and management are growing challenges in all producing regions. This water is generally considered as a nonrevenue product, but it can have significant value in enhanced oil recovery techniques if it meets the required quality standards. There is also an interest in the beneficial uses of produced water for agricultural and industrial applications. Advanced Oxidation Process is a chemical technology that has been growing recently in the wastewater treatment industry, and it is highly recommended for non-easily removal of organic compounds. The efficiency of AOPs is compound specific, therefore, the optimization of each process should be done based on different aspects.

Keywords: advanced oxidation process, photochemical processes, degradation, organic contaminants

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Authors: A. Gulbiniene, V. Jankauskaite

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Textile laminates with breathable membranes are used extensively in protective footwear. Such polymeric membranes act as a barrier to liquid water and soil entry from the environment, but are sufficiently permeable to water vapour to allow significant amounts of sweat to evaporate and affect the comfort of the wearer. In this paper the influence of absorbed humidity amount on the electrical properties of textiles lining laminates with and without polymeric membrane is presented. It was shown that textile laminate structure and its layers have a great influence on the water vapour absorption. Laminates with polyurethane foam layers show lower ability to absorb water vapour. Semi-permeable membrane increases absorbed humidity amount. The increase of water vapour absorption ability decreases textile laminates' electrical resistance. However, the intensity of the decrease in electrical resistance depends on the textile laminate layers' nature. Laminates with polyamide layers show significantly lower electrical resistance values.

Keywords: electrical resistance, humid atmosphere, textiles laminate, water vapour absorption

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Authors: Loubna Hamami, Bouchaib Nassereddine

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Due to the evolution of technologies, the need to observe and manage hostile environments, and reduction in size, wireless sensor networks (WSNs) are becoming essential and implicated in the most fields of life. WSNs enable us to change the style of living, working and interacting with the physical environment. The agricultural sector is one of such sectors where WSNs are successfully used to get various benefits. For successful agricultural production, the irrigation system is one of the most important factors, and it plays a tactical role in the process of agriculture domain. However, it is considered as the largest consumer of freshwater. Besides, the scarcity of water, the drought, the waste of the limited available water resources are among the critical issues that touch the almost sectors, notably agricultural services. These facts are leading all governments around the world to rethink about saving water and reducing the volume of water used; this requires the development of irrigation practices in order to have a complete and independent system that is more efficient in the management of irrigation. Consequently, the selection of WSNs in irrigation system has been a benefit for developing the agriculture sector. In this work, we propose a prototype for a complete and intelligent irrigation system based on wireless sensor networks and we present and discuss the design of this prototype. This latter aims at saving water, energy and time. The proposed prototype controls water system for irrigation by monitoring the soil temperature, soil moisture and weather conditions for estimation of water requirements of each plant.

Keywords: precision irrigation, sensor, wireless sensor networks, water resources

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Authors: Jose Flores, Nadia Gamboa

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A proper water quality management requires the establishment of a monitoring network. Therefore, evaluation of the efficiency of water quality monitoring networks is needed to ensure high-quality data collection of critical quality chemical parameters. Unfortunately, in some Latin American countries water quality monitoring programs are not sustainable in terms of recording historical data or environmentally representative sites wasting time, money and valuable information. In this study, multivariate statistical techniques, such as principal components analysis (PCA) and hierarchical cluster analysis (HCA), are applied for identifying the most significant monitoring sites as well as critical water quality parameters in the monitoring network of the Jequetepeque River basin, in northern Peru. The Jequetepeque River basin, like others in Peru, shows socio-environmental conflicts due to economical activities developed in this area. Water pollution by trace elements in the upper part of the basin is mainly related with mining activity, and agricultural land lost due to salinization is caused by the extensive use of groundwater in the lower part of the basin. Since the 1980s, the water quality in the basin has been non-continuously assessed by public and private organizations, and recently the National Water Authority had established permanent water quality networks in 45 basins in Peru. Despite many countries use multivariate statistical techniques for assessing water quality monitoring networks, those instruments have never been applied for that purpose in Peru. For this reason, the main contribution of this study is to demonstrate that application of the multivariate statistical techniques could serve as an instrument that allows the optimization of monitoring networks using least number of monitoring sites as well as the most significant water quality parameters, which would reduce costs concerns and improve the water quality management in Peru. Main socio-economical activities developed and the principal stakeholders related to the water management in the basin are also identified. Finally, water quality management programs will also be discussed in terms of their efficiency and sustainability.

Keywords: PCA, HCA, Jequetepeque, multivariate statistical

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Authors: Abdullahi Jibrin, Aishetu Abdulkadir

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The development of allometric models is crucial to accurate forest biomass/carbon stock assessment. The aim of this study was to develop a set of biomass prediction models that will enable the determination of total tree aboveground biomass for savannah woodland area in Niger State, Nigeria. Based on the data collected through biometric measurements of 1816 trees and destructive sampling of 36 trees, five species specific and one site specific models were developed. The sample size was distributed equally between the five most dominant species in the study site (Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa, Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the equations were developed for five individual species. Secondly these five species were mixed and were used to develop an allometric equation of mixed species. Overall, there was a strong positive relationship between total tree biomass and the stem diameter. The coefficient of determination (R2 values) ranging from 0.93 to 0.99 P < 0.001 were realised for the models; with considerable low standard error of the estimates (SEE) which confirms that the total tree above ground biomass has a significant relationship with the dbh. The F-test value for the biomass prediction models were also significant at p < 0.001 which indicates that the biomass prediction models are valid. This study recommends that for improved biomass estimates in the study site, the site specific biomass models should preferably be used instead of using generic models.

Keywords: allometriy, biomass, carbon stock , model, regression equation, woodland, inventory

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Authors: Gianne Bianca P. Manalo, Ernesto A. Martin, Vanessa V. Velasco

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The laying performance, egg quality, egg classification, and income over feed cost of Improved Philippine Mallard duck (Itik Pinas) were examined as influenced by garlic powder in drinking water. A total of 48 ducks (42 females and 6 males) were used in the study. The ducks were allocated into two treatments - with garlic powder (GP) and without garlic powder (control) in drinking water. Each treatment had three replicates with eight ducks (7 females and 1 male) per replication. The results showed that there was a significant (P = 0.03) difference in average egg weight where higher values were attained by ducks with GP (77.67 g ± 0.64) than the control (75.64 g ± 0.43). The supplementation of garlic powder in drinking water, however, did not affect the egg production, feed intake, FCR, egg mass, livability, egg quality and egg classification. The Itik Pinas with GP in drinking water had numerically higher income over feed cost than those without. GP in drinking water can be considered in raising Itik Pinas. Further studies on increasing level of GP and long feeding duration also merit consideration to substantiate the findings.

Keywords: phytogenic, garlic powder, Itik-Pinas, egg weight, egg production

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Authors: Houssam Hijazi, Laurent Cantrel, Jean-François Paul

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Periodic DFT calculations were performed to study the chemistry of CsI particles and the possible release of volatile iodine from CsI surfaces for nuclear safety interest. The results show that water adsorbs at low temperature associatively on the (011) surface of CsI, while water desorbs at higher temperatures. On the other hand, removing iodine species from the surface requires oxidizing the surface one time for each removed iodide atom. The activation energy of removing I₂ from the surface in the presence of two OH is 1,2 eV.

Keywords: aerosols, CSI, reactivity, DFT, water adsorption

Procedia PDF Downloads 336