Search results for: optimization problem

Authors: Richa Grover, Rahul Grover, V. Balaji Rao, Kavish Kejriwal

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Selection of suppliers is a crucial problem in the supply chain management. On top of that, sustainable supplier selection is the biggest challenge for the organizations. Environment protection and social problems have been of concern to society in recent years, and the traditional supplier selection does not consider about this factor; therefore, this research work focuses on introducing sustainable criteria into the structure of supplier selection criteria. Sustainable Supply Chain Management (SSCM) is the management and administration of material, information, and money flows, as well as coordination among business along the supply chain. All three dimensions - economic, environmental, and social - of sustainable development needs to be taken care of. Purpose of this research is to maximize supply chain profitability, maximize social wellbeing of supply chain and minimize environmental impacts. Problem statement is selection of suppliers in a sustainable supply chain network by ranking the suppliers against sustainable criteria identified. The aim of this research is twofold: To find out what are the sustainable parameters that can be applied to the supply chain, and to determine how these parameters can effectively be used in supplier selection. Multicriteria decision making tools will be used to rank both criteria and suppliers. AHP Analysis will be used to find out ratings for the criteria identified. It is a technique used for efficient decision making. TOPSIS will be used to find out rating for suppliers and then ranking them. TOPSIS is a MCDM problem solving method which is based on the principle that the chosen option should have the maximum distance from the negative ideal solution (NIS) and the minimum distance from the ideal solution.

Keywords: sustainable supply chain management, sustainable criteria, MCDM tools, AHP analysis, TOPSIS method

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Authors: Yi-Ling Chen, Dung-Ying Lin

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In the manufacturing process, computer numerical control (CNC) machining plays a crucial role. CNC enables precise machinery control through computer programs, achieving automation in the production process and significantly enhancing production efficiency. However, traditional CNC production lines often require manual intervention for loading and unloading operations, which limits the production line's operational efficiency and production capacity. Additionally, existing CNC automation systems frequently lack sufficient intelligence and fail to achieve optimal configuration efficiency, resulting in the need for substantial time to reconfigure production lines when producing different products, thereby impacting overall production efficiency. Using the NSGA-II algorithm, we generate production line layout configurations that consider field constraints and select robotic arm specifications from an arm list. This allows us to calculate loading and unloading times for each job order, perform demand allocation, and assign processing sequences. The NSGA-II algorithm is further employed to determine the optimal processing sequence, with the aim of minimizing demand completion time and maximizing average machine utilization. These objectives are used to evaluate the performance of each layout, ultimately determining the optimal layout configuration. By employing this method, it enhance the configuration efficiency of CNC production lines and establish an adaptive capability that allows the production line to respond promptly to changes in demand. This will minimize production losses caused by the need to reconfigure the layout, ensuring that the CNC production line can maintain optimal efficiency even when adjustments are required due to fluctuating demands.

Keywords: evolutionary algorithms, multi-objective optimization, pareto optimality, layout optimization, operations sequence

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Authors: Zaid Jamal Saeed Almahmoud

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Smart Grid is the vision of the future power system that combines advanced monitoring and communication technologies to provide energy in a smart, efficient, and user-friendly manner. This proposal considers a demand response model in the Smart Grid based on utility maximization. Given a set of consumers with conflicting preferences in terms of consumption and a utility company that aims to minimize the peak demand and match demand to supply, we study the problem of aggregating these preferences while modelling the problem as a game. We also investigate whether an equilibrium can be reached to maximize the social benefit. Based on such equilibrium, we propose a dynamic pricing heuristic that computes the equilibrium and sets the prices accordingly. The developed approach was analysed theoretically and evaluated experimentally using real appliances data. The results show that our proposed approach achieves a substantial reduction in the overall energy consumption.

Keywords: heuristics, smart grid, aggregation, mechanism design, equilibrium

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Authors: Shao Bo Cheng, Yong-Jin Han, Se Young Park, Seong-Bae Park

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Consumer-to-Consumer (C2C) E-commerce has been growing at a very high speed in recent years. Since identical or nearly-same kinds of products compete one another by relying on keyword search in C2C E-commerce, some sellers describe their products with spam keywords that are popular but are not related to their products. Though such products get more chances to be retrieved and selected by consumers than those without spam keywords, the spam keywords mislead the consumers and waste their time. This problem has been reported in many commercial services like e-bay and taobao, but there have been little research to solve this problem. As a solution to this problem, this paper proposes a method to classify whether keywords of a product are spam or not. The proposed method assumes that a keyword for a given product is more reliable if the keyword is observed commonly in specifications of products which are the same or the same kind as the given product. This is because that a hierarchical category of a product in general determined precisely by a seller of the product and so is the specification of the product. Since higher layers of the hierarchical category represent more general kinds of products, a reliable degree is differently determined according to the layers. Hence, reliable degrees from different layers of a hierarchical category become features for keywords and they are used together with features only from specifications for classification of the keywords. Support Vector Machines are adopted as a basic classifier using the features, since it is powerful, and widely used in many classification tasks. In the experiments, the proposed method is evaluated with a golden standard dataset from Yi-han-wang, a Chinese C2C e-commerce, and is compared with a baseline method that does not consider the hierarchical category. The experimental results show that the proposed method outperforms the baseline in F1-measure, which proves that spam keywords are effectively identified by a hierarchical category in C2C e-commerce.

Keywords: spam keyword, e-commerce, keyword features, spam filtering

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Authors: Sunmyeng Kim

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IEEE 802.11a/b/g standards support multiple transmission rates. Even though the use of multiple transmission rates increase the WLAN capacity, this feature leads to the performance anomaly problem. Cooperative communication was introduced to relieve the performance anomaly problem. Data packets are delivered to the destination much faster through a relay node with high rate than through direct transmission to the destination at low rate. In the legacy cooperative protocols, a source node chooses a relay node only based on the transmission rate. Therefore, they are not so feasible in multi-flow environments since they do not consider the effect of other flows. To alleviate the effect, we propose a new relay node selection algorithm based on the transmission rate and channel contention level. Performance evaluation is conducted using simulation, and shows that the proposed protocol significantly outperforms the previous protocol in terms of throughput and delay.

Keywords: cooperative communications, MAC protocol, relay node, WLAN

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Authors: Mahmoud Almasri, Xavier Marjou, Fanny Parzysz

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The demand for services provided by Unmanned Aerial Vehicles (UAVs) is increasing pervasively across several sectors including potential public safety, economic, and delivery services. As the number of applications using UAVs grows rapidly, more and more powerful, quality of service, and power efficient computing units are necessary. Recently, cellular technology draws more attention to connectivity that can ensure reliable and flexible communications services for UAVs. In cellular technology, flying with a high speed and altitude is subject to several key challenges, such as frequent handovers (HOs), high interference levels, connectivity coverage holes, etc. Additional HOs may lead to “ping-pong” between the UAVs and the serving cells resulting in a decrease of the quality of service and energy consumption. In order to optimize the number of HOs, we develop in this paper a Q-learning-based algorithm. While existing works focus on adjusting the number of HOs in a static network topology, we take into account the impact of cells deployment for three different simulation scenarios (Rural, Semi-rural and Urban areas). We also consider the impact of the decision distance, where the drone has the choice to make a switching decision on the number of HOs. Our results show that a Q-learning-based algorithm allows to significantly reduce the average number of HOs compared to a baseline case where the drone always selects the cell with the highest received signal. Moreover, we also propose which hyper-parameters have the largest impact on the number of HOs in the three tested environments, i.e. Rural, Semi-rural, or Urban.

Keywords: drones connectivity, reinforcement learning, handovers optimization, decision distance

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Authors: Gilbert Makanda

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The problem of the teaching of mathematics is studied using differential equations. A mathematical model for knowledge acquisition in mathematics is developed. In this study we adopt the mathematical model that is normally used for disease modelling in the teaching of mathematics. It is assumed that teaching is 'infecting' students with knowledge thereby spreading this knowledge to the students. It is also assumed that students who gain this knowledge spread it to other students making disease model appropriate to adopt for this problem. The results of this study show that increasing recruitment rates, learning contact with teachers and learning materials improves the number of knowledgeable students. High dropout rates and forgetting taught concepts also negatively affect the number of knowledgeable students. The developed model is then solved using Matlab ODE45 and \verb"lsqnonlin" to estimate parameters for the actual data.

Keywords: differential equations, knowledge acquisition, least squares, dynamical systems

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Authors: Dirk Winkler, Leon Koevener, Lamees AlHayary

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This paper contributes to the improvement of the municipal wastewater systems in Jordan. An important goal is increased energy efficiency in wastewater treatment plants and therefore lower expenses due to reduced electricity consumption. The chosen way to achieve this goal is through the implementation of Technical Sustainable Management adapted to the Jordanian context. Three wastewater treatment plants in Jordan have been chosen as a case study for the investigation. These choices were supported by the fact that the three treatment plants are suitable for average performance and size. Beyond that, an energy assessment has been recently conducted in those facilities. The project succeeded in proving the following hypothesis: Energy efficiency in wastewater treatment plants can be improved by implementing principles of Technical Sustainable Management adapted to the Jordanian context. With this case study, a significant increase in energy efficiency can be achieved by optimization of operational performance, identifying and eliminating shortcomings and appropriate plant management. Implementing Technical Sustainable Management as a low-cost tool with a comparable little workload, provides several additional benefits supplementing increased energy efficiency, including compliance with all legal and technical requirements, process optimization, but also increased work safety and convenient working conditions. The research in the chosen field continues because there are indications for possible integration of the adapted tool into other regions and sectors. The concept of Technical Sustainable Management adapted to the Jordanian context could be extended to other wastewater treatment plants in all regions of Jordan but also into other sectors including water treatment, water distribution, wastewater network, desalination, or chemical industry.

Keywords: energy efficiency, quality management system, technical sustainable management, wastewater treatment

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Authors: Choy Sonny Yip Hong

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This abstract presents an exploration into the creation of a sustainable bio-polymer compound for additive manufacturing, specifically 3D printing, with a focus on eggshells and polylactide (PLA) polymer. The project initially conducted experiments using a variety of food by-products to create bio-polymers, and promising results were obtained when combining eggshells with PLA polymer. The research journey involved precise measurements, drying of PLA to remove moisture, and the utilization of a filament-making machine to produce 3D printable filaments. The project began with exploratory research and experiments, testing various combinations of food by-products to create bio-polymers. After careful evaluation, it was discovered that eggshells and PLA polymer produced promising results. The initial mixing of the two materials involved heating them just above the melting point. To make the compound 3D printable, the research focused on finding the optimal formulation and production process. The process started with precise measurements of the PLA and eggshell materials. The PLA was placed in a heating oven to remove any absorbed moisture. Handmade testing samples were created to guide the planning for 3D-printed versions. The scrap PLA was recycled and ground into a powdered state. The drying process involved gradual moisture evaporation, which required several hours. The PLA and eggshell materials were then placed into the hopper of a filament-making machine. The machine's four heating elements controlled the temperature of the melted compound mixture, allowing for optimal filament production with accurate and consistent thickness. The filament-making machine extruded the compound, producing filament that could be wound on a wheel. During the testing phase, trials were conducted with different percentages of eggshell in the PLA mixture, including a high percentage (20%). However, poor extrusion results were observed for high eggshell percentage mixtures. Samples were created, and continuous improvement and optimization were pursued to achieve filaments with good performance. To test the 3D printability of the DIY filament, a 3D printer was utilized, set to print the DIY filament smoothly and consistently. Samples were printed and mechanically tested using a universal testing machine to determine their mechanical properties. This testing process allowed for the evaluation of the filament's performance and suitability for additive manufacturing applications. In conclusion, the project explores the creation of a sustainable bio-polymer compound using eggshells and PLA polymer for 3D printing. The research journey involved precise measurements, drying of PLA, and the utilization of a filament-making machine to produce 3D printable filaments. Continuous improvement and optimization were pursued to achieve filaments with good performance. The project's findings contribute to the advancement of additive manufacturing, offering opportunities for design innovation, carbon footprint reduction, supply chain optimization, and collaborative potential. The utilization of eggshell PLA polymer in additive manufacturing has the potential to revolutionize the manufacturing industry, providing a sustainable alternative and enabling the production of intricate and customized products.

Keywords: additive manufacturing, 3D printing, eggshell PLA polymer, design innovation, carbon footprint reduction, supply chain optimization, collaborative potential

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Authors: Preecha Pongpeng

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This research aims to study the education quality management to solve the problem of teachers shortage by the communities participation. This research is action research by using the tools is questionnaire to collect the data whit, students and community representatives and final will interview to ask the opinions of people in the community to help and support instruction in problems in teaching. Results found that people in the community are aware and working together to solve the lack the of teachers by collaboration between school personnel and community members by finding people who are knowledgeable, organized into local wisdom in the community, compound money to donate and hire someone in the community to teaching between classroom with people in the community. In addition, researcher discovered this research project contributes to cooperation between the school and community and there was a problem including administrative expenses and the school's academic quality management.

Keywords: education quality management, local wisdom, northern part of Thailand, participation of the community

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Authors: Habshah Midi, Mohammed A. Mohammed, Sohel Rana

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Multicollinearity occurs when two or more independent variables in a multiple linear regression model are highly correlated. The ridge regression is the commonly used method to rectify this problem. However, the ridge regression cannot handle the problem of multicollinearity which is caused by high leverage collinearity enhancing observation (HLCEO). Since high leverage points (HLPs) are responsible for inducing multicollinearity, the effect of HLPs needs to be reduced by using Generalized M estimator. The existing GM6 estimator is based on the Minimum Volume Ellipsoid (MVE) which tends to swamp some low leverage points. Hence an improvised GM (MGM) estimator is presented to improve the precision of the GM6 estimator. Numerical example and simulation study are presented to show how HLPs can cause multicollinearity. The numerical results show that our MGM estimator is the most efficient method compared to some existing methods.

Keywords: identification, high leverage points, multicollinearity, GM-estimator, DRGP, DFFITS

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Authors: Tohari Ahmad, Hudan Studiawan, Iwang Aryadinata, Royyana M. Ijtihadie, Waskitho Wibisono

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A manual voting system has been implemented worldwide. It has some weaknesses which may decrease the legitimacy of the voting result. An electronic voting system is introduced to minimize this weakness. It has been able to provide a better result, in terms of the total time taken in the voting process and accuracy. Nevertheless, people may be reluctant to go to the polling location because of some reasons, such as distance and time. In order to solve this problem, mobile voting is implemented by utilizing mobile devices. There are many mobile voting architectures available. Overall, authenticity of the users is the common problem of all voting systems. There must be a mechanism which can verify the users’ authenticity such that only verified users can give their vote once; others cannot vote. In this paper, a challenge response-based authentication is proposed by utilizing properties of the users, for example, something they have and know. In terms of speed, the proposed system provides good result, in addition to other capabilities offered by the system.

Keywords: authentication, data protection, mobile voting, security

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Authors: Slava Kalyuga

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There are two opposing major points of view on the optimal degree of initial instructional guidance that is usually discussed in the literature by the advocates of the corresponding learning approaches. Using unguided or minimally guided problem-solving tasks prior to explicit instruction has been suggested by productive failure and several other instructional theories, whereas an alternative approach - using fully guided worked examples followed by problem solving - has been demonstrated as the most effective strategy within the framework of cognitive load theory. An integrated approach discussed in this paper could combine the above frameworks within a broader theoretical perspective which would allow bringing together their best features and advantages in the design of learning tasks for STEM education. This paper represents a systematic review of the available empirical studies comparing the above alternative sequences of instructional methods to explore effects of several possible moderating factors. The paper concludes that different approaches and instructional sequences should coexist within complex learning environments. Selecting optimal sequences depends on such factors as specific goals of learner activities, types of knowledge to learn, levels of element interactivity (task complexity), and levels of learner prior knowledge. This paper offers an outline of a theoretical framework for the design of complex learning tasks in STEM education that would integrate explicit instruction and inquiry (exploratory, discovery) learning approaches in ways that depend on a set of defined specific factors.

Keywords: cognitive load, explicit instruction, exploratory learning, worked examples

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Authors: Kunthida Kulprateepunya, Napat Boontiam, Bunthita Phuasa, Chatsuda Kankayant, Bantoeng Polsawat, Sumran Poontong

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Frailty is the thin line between good health and illness. The syndrome is more common in the elderly who transition from strong to weak. (Vulnerability). Fragility can prevent and promote healthy recovery before it goes into disability. This research and development aim to analyze the situation analysis of frailty of the elderly, develop a program, and evaluate the effect of a health promotion program to prevent and solve the problem of frailty among the elderly. The research consisted of 3 phases: 1) analysis of the frailty situation, 2) development of a model, 3) evaluation of the effectiveness of the model. Samples were 328, 122 elderlies using the multi-stage random sampling method. The research instrument was a frailty questionnaire use of the five symptoms, the main characteristics were muscle weakness, slow walking, low physical activity. Fatigue and unintentional weight loss, criteria frailty use more than or equal to three or more symptoms are frailty. Data were analyzed by descriptive and t-test dependent test statistics. The findings showed three parts. First, frailty in the elderly was 23.05 percentage and 56.70% pre-frailty. Second, it was development of a health promotion program to prevent and solve the problem of frailty the elderly with a combination of Nine-Square Exercise, Elastic Band Exercise, Elastic Coconut Shell. Third, evaluation of the effectiveness of the model by comparison of the elderly's get up and go test, the average time before using the program was 14.42 and after using the program was 8.57. It was statistically significant at the .05 level. In conclusion, the findings can used to develop guidelines to promote the health of the frailty elderly.

Keywords: elderly, fragile, nine-square exercise, elastic coconut shell

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Authors: Rahul R. Gurpude, Pallvita Yadav, Amrut Mulay

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In recent years, there has been a growing focus on advanced manufacturing processes, and one such emerging process is wire electric discharge machining (WEDM). WEDM is a precision machining process specifically designed for cutting electrically conductive materials with exceptional accuracy. It achieves material removal from the workpiece metal through spark erosion facilitated by electricity. Initially developed as a method for precision machining of hard materials, WEDM has witnessed significant advancements in recent times, with numerous studies and techniques based on electrical discharge phenomena being proposed. These research efforts and methods in the field of ED encompass a wide range of applications, including mirror-like finish machining, surface modification of mold dies, machining of insulating materials, and manufacturing of micro products. WEDM has particularly found extensive usage in the high-precision machining of complex workpieces that possess varying hardness and intricate shapes. During the cutting process, a wire with a diameter ranging from 0.18mm is employed. The evaluation of EDM performance typically revolves around two critical factors: material removal rate (MRR) and surface roughness (SR). To comprehensively assess the impact of machining parameters on the quality characteristics of EDM, an Analysis of Variance (ANOVA) was conducted. This statistical analysis aimed to determine the significance of various machining parameters and their relative contributions in controlling the response of the EDM process. By undertaking this analysis, optimal levels of machining parameters were identified to achieve desirable material removal rates and surface roughness.

Keywords: WEDM, MRR, optimization, surface roughness

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Authors: Amir Abbas Fatemi, Zahra Tabrizian, Kabir Sadeghi

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To find the location and severity of damage that occurs in a structure, characteristics changes in dynamic and static can be used. The non-destructive techniques are more common, economic, and reliable to detect the global or local damages in structures. This paper presents a non-destructive method in structural damage detection and assessment using GA and static data. Thus, a set of static forces is applied to some of degrees of freedom and the static responses (displacements) are measured at another set of DOFs. An analytical model of the truss structure is developed based on the available specification and the properties derived from static data. The damages in structure produce changes to its stiffness so this method used to determine damage based on change in the structural stiffness parameter. Changes in the static response which structural damage caused choose to produce some simultaneous equations. Genetic Algorithms are powerful tools for solving large optimization problems. Optimization is considered to minimize objective function involve difference between the static load vector of damaged and healthy structure. Several scenarios defined for damage detection (single scenario and multiple scenarios). The static damage identification methods have many advantages, but some difficulties still exist. So it is important to achieve the best damage identification and if the best result is obtained it means that the method is Reliable. This strategy is applied to a plane truss. This method is used for a plane truss. Numerical results demonstrate the ability of this method in detecting damage in given structures. Also figures show damage detections in multiple damage scenarios have really efficient answer. Even existence of noise in the measurements doesn’t reduce the accuracy of damage detections method in these structures.

Keywords: damage detection, finite element method, static data, non-destructive, genetic algorithm

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Authors: M. Rodionov, Z. Dedovets

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The article analyses the composition and structure of the motivationally oriented methodological system of teaching mathematics (purpose, content, methods, forms, and means of teaching), viewed through the prism of the student as the subject of the learning process. Particular attention is paid to the problem of methods of teaching mathematics, which are represented in the form of an ordered triad of attributes corresponding to the selected characteristics. A systematic analysis of possible options and their methodological interpretation enriched existing ideas about known methods and technologies of training, and significantly expanded their nomenclature by including previously unstudied combinations of characteristics. In addition, examples outlined in this article illustrate the possibilities of enhancing the motivational capacity of a particular method or technology in the real learning practice of teaching mathematics through more free goal-setting and varying the conditions of the problem situations. The authors recommend the implementation of different strategies according to their characteristics in teaching and learning mathematics in secondary schools.

Keywords: education, methodological system, the teaching of mathematics, students motivation

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Authors: Usarat Thawornchaisit, Kamalasiri Juthaisong, Kasama Parsongjeen, Phonsiri Phoengchan

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In this study, sludge samples that were collected from the wastewater treatment plant of a printed circuit board manufacturing industry in Thailand were subjected to acid extraction using sulfuric acid as the chemical extracting agent. The effects of sulfuric acid concentration (A), the ratio of a volume of acid to a quantity of sludge (B) and extraction time (C) on the efficiency of copper extraction were investigated with the aim of finding the optimal conditions for maximum removal of copper from the wastewater treatment sludge. Factorial experimental design was employed to model the copper extraction process. The results were analyzed statistically using analysis of variance to identify the process variables that were significantly affected the copper extraction efficiency. Results showed that all linear terms and an interaction term between volume of acid to quantity of sludge ratio and extraction time (BC), had statistically significant influence on the efficiency of copper extraction under tested conditions in which the most significant effect was ascribed to volume of acid to quantity of sludge ratio (B), followed by sulfuric acid concentration (A), extraction time (C) and interaction term of BC, respectively. The remaining two-way interaction terms, (AB, AC) and the three-way interaction term (ABC) is not statistically significant at the significance level of 0.05. The model equation was derived for the copper extraction process and the optimization of the process was performed using a multiple response method called desirability (D) function to optimize the extraction parameters by targeting maximum removal. The optimum extraction conditions of 99% of copper were found to be sulfuric acid concentration: 0.9 M, ratio of the volume of acid (mL) to the quantity of sludge (g) at 100:1 with an extraction time of 80 min. Experiments under the optimized conditions have been carried out to validate the accuracy of the Model.

Keywords: acid treatment, chemical extraction, sludge, waste management

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Authors: Ahmed Hossam ElMolla, Mohamed Hatem Saleh, Hamza Mostafa, Lara Mamdouh, Yassin Wael

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Artificial intelligence (AI) is reshaping industries, and its potential to revolutionize renewable energy and data center operations is immense. By harnessing AI's capabilities, we can optimize energy consumption, predict fluctuations in renewable energy generation, and improve the efficiency of data center infrastructure. This convergence of technologies promises a future where energy is managed more intelligently, sustainably, and cost-effectively. The integration of AI into renewable energy systems unlocks a wealth of opportunities. Machine learning algorithms can analyze vast amounts of data to forecast weather patterns, solar irradiance, and wind speeds, enabling more accurate energy production planning. AI-powered systems can optimize energy storage and grid management, ensuring a stable power supply even during intermittent renewable generation. Moreover, AI can identify maintenance needs for renewable energy infrastructure, preventing costly breakdowns and maximizing system lifespan. Data centers, which consume substantial amounts of energy, are prime candidates for AI-driven optimization. AI can analyze energy consumption patterns, identify inefficiencies, and recommend adjustments to cooling systems, server utilization, and power distribution. Predictive maintenance using AI can prevent equipment failures, reducing energy waste and downtime. Additionally, AI can optimize data placement and retrieval, minimizing energy consumption associated with data transfer. As AI transforms renewable energy and data center operations, modified Key Performance Indicators (KPIs) will emerge. Traditional metrics like energy efficiency and cost-per-megawatt-hour will continue to be relevant, but additional KPIs focused on AI's impact will be essential. These might include AI-driven cost savings, predictive accuracy of energy generation and consumption, and the reduction of carbon emissions attributed to AI-optimized operations. By tracking these KPIs, organizations can measure the success of their AI initiatives and identify areas for improvement. Ultimately, the synergy between AI, renewable energy, and data centers holds the potential to create a more sustainable and resilient future. By embracing these technologies, we can build smarter, greener, and more efficient systems that benefit both the environment and the economy.

Keywords: data center, artificial intelligence, renewable energy, energy efficiency, sustainability, optimization, predictive analytics, energy consumption, energy storage, grid management, data center optimization, key performance indicators, carbon emissions, resiliency

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Authors: Wang Zhanquan, Yang Zeping, Gu Chunhua, Zhu Fazhi, Guo Weibin

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Recently, Massive Open Online Courses (MOOCs) are becoming the new trend of education. There are many problems under the environment of Database Principle curriculum teaching process in MOOCs, such as teaching ideas and theories which are out of touch with the reality, how to carry out the technical teaching and interactive practice in the MOOCs environment, thus the methods of database course under the environment of MOOCs are proposed. There are three processes to deal with problem solving in the research, which are problems proposed, problems solved, and inductive analysis. The present research includes the design of teaching contents, teaching methods in classroom, flipped classroom teaching mode under the environment of MOOCs, learning flow method and large practice homework. The database designing ability is systematically improved based on the researching methods.

Keywords: problem solving-driven, MOOCs, teaching art, learning flow;

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Authors: Ainagul Yermekova, Liudmila Goncharenko, Ali Baghirzade, Sergey Sybachin

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In this article, we address the problem of Kazakhstan's transition to the Latin alphabet. The transition process started in 2017 and is scheduled to be completed in 2025. In connection with these events, the problem of recognizing the characters of the new alphabet is raised. Well-known character recognition programs such as ABBYY FineReader, FormReader, MyScript Stylus did not recognize specific Kazakh letters that were used in Cyrillic. The author tries to give an assessment of the well-known method of character recognition that could be in demand as part of the country's transition to the Latin alphabet. Three methods of character recognition: template, structured, and feature-based, are considered through the algorithms of operation. At the end of the article, a general conclusion is made about the possibility of applying a certain method to a particular recognition process: for example, in the process of population census, recognition of typographic text in Latin, or recognition of photos of car numbers, store signs, etc.

Keywords: text detection, template method, recognition algorithm, structured method, feature method

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Authors: Arash Parehkar, S. Jamshid Mousavi, Shoubo Bayazidi, Vahid Karami, Laleh Shahidi, Arash Azaranfar, Ali Moridi, M. Shabakhti, Tayebeh Ariyan, Mitra Tofigh, Kaveh Masoumi, Alireza Motahari

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Water resource systems modelling have constantly been a challenge through history for human being. As the innovative methodological development is evolving alongside computer sciences on one hand, researches are likely to confront more complex and larger water resources systems due to new challenges regarding increased water demands, climate change and human interventions, socio-economic concerns, and environment protection and sustainability. In this research, an automatic calibration scheme has been applied on the Gilan’s large-scale water resource model using mathematical programming. The water resource model’s calibration is developed in order to attune unknown water return flows from demand sites in the complex Sefidroud irrigation network and other related areas. The calibration procedure is validated by comparing several gauged river outflows from the system in the past with model results. The calibration results are pleasantly reasonable presenting a rational insight of the system. Subsequently, the unknown optimized parameters were used in a basin-scale linear optimization model with the ability to evaluate the system’s performance against a reduced inflow scenario in future. Results showed an acceptable match between predicted and observed outflows from the system at selected hydrometric stations. Moreover, an efficient operating policy was determined for Sefidroud dam leading to a minimum water shortage in the reduced inflow scenario.

Keywords: auto-calibration, Gilan, large-scale water resources, simulation

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Authors: Chaimongkol Limpianchob

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This work addresses the problem of production planning that arises in the production of aromatic coconuts from Samudsakhorn province in Thailand. The planning involves the forwarding of aromatic coconuts from the harvest areas to the factory, which is classified into two groups; self-owned areas and contracted areas, the decisions of aromatic coconuts flow in the plant, and addressing a question of which warehouse will be in use. The problem is formulated as a mixed-integer linear programming model within supply chain management framework. The objective function seeks to minimize the total cost including the harvesting, labor and inventory costs. Constraints on the system include the production activities in the company and demand requirements. Numerical results are presented to demonstrate the feasibility of coconuts supply chain model compared with base case.

Keywords: aromatic coconut, supply chain management, production planning, mixed-integer linear programming

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Authors: Sina Moradi, Christopher W. K. Chow, John Van Leeuwen, David Cook, Mary Drikas, Patrick Hayde, Rose Amal

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Chloramine is commonly used as a disinfectant in drinking water distribution systems (DWDSs), particularly in Australia and the USA. Maintaining a chloramine residual throughout the DWDS is important in ensuring microbiologically safe water is supplied at the customer’s tap. In order to simulate how chloramine behaves when it moves through the distribution system, a water quality network model (WQNM) can be applied. In this work, the WQNM was based on mono-chloramine decomposition reactions, which enabled prediction of mono-chloramine residual at different locations through a DWDS in Australia, using the Bentley commercial hydraulic package (Water GEMS). The accuracy of WQNM predictions is influenced by a number of water quality parameters. Optimization of these parameters in order to obtain the closest results in comparison with actual measured data in a real DWDS would result in both cost reduction as well as reduction in consumption of valuable resources such as energy and materials. In this work, the optimum operating conditions of water quality parameters (i.e. temperature, pH, and initial mono-chloramine concentration) to maximize the accuracy of mono-chloramine residual predictions for two water supply scenarios in an entire network were determined using response surface methodology (RSM). To obtain feasible and economical water quality parameters for highest model predictability, Design Expert 8.0 software (Stat-Ease, Inc.) was applied to conduct the optimization of three independent water quality parameters. High and low levels of the water quality parameters were considered, inevitably, as explicit constraints, in order to avoid extrapolation. The independent variables were pH, temperature and initial mono-chloramine concentration. The lower and upper limits of each variable for two water supply scenarios were defined and the experimental levels for each variable were selected based on the actual conditions in studied DWDS. It was found that at pH of 7.75, temperature of 34.16 ºC, and initial mono-chloramine concentration of 3.89 (mg/L) during peak water supply patterns, root mean square error (RMSE) of WQNM for the whole network would be minimized to 0.189, and the optimum conditions for averaged water supply occurred at pH of 7.71, temperature of 18.12 ºC, and initial mono-chloramine concentration of 4.60 (mg/L). The proposed methodology to predict mono-chloramine residual can have a great potential for water treatment plant operators in accurately estimating the mono-chloramine residual through a water distribution network. Additional studies from other water distribution systems are warranted to confirm the applicability of the proposed methodology for other water samples.

Keywords: chloramine decay, modelling, response surface methodology, water quality parameters

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Authors: Sireen Irsheid, Stephanie Keeney Parks, Michael A. Lindsey

Abstract:

The medical and mental health field have been organized as reactive systems to respond to symptoms of mental health problems and disability. This becomes problematic particularly for those harmed by structural violence and racism, typically pushing us in the direction of alleviating symptoms and personalizing structural problems. The current paper examines how we assess, diagnose, and treat mental health and disability challenges in clinical spaces. We provide the readers with some context to think about the problem of racism and mental health/disability, ways to deconstruct the problem through the lens of structural violence, and recommendations to critically engage in clinical assessments, diagnosis, and treatment for young people impacted by structural violence and racism.

Keywords: mental health, disability, race and ethnicity, structural violence, structural racism, young people

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Authors: Prathyusha Samvedam, Hiranmaya Nanda

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Doping refers to the practice of using drugs or practices that enhance an athlete's performance. This is a problem that occurs on a worldwide scale and compromises the fairness of athletic tournaments. There are rules that have been created on both the national and international levels in order to prevent doping. However, these rules sometimes contradict one another, and it is possible that they don't do a very good job of prohibiting people from using PEDs. This study will contend that India's inability to comply with specific Code criteria, as well as its failure to satisfy "best practice" standards established by other countries, demonstrates a lack of uniformity in the implementation of anti-doping regulations and processes among nations. Such challenges have the potential to undermine the validity of the anti-doping system, particularly in developing nations like India. This article on the legislative framework in India governing doping in sports is very important. To begin, doping in sports is a significant problem that affects the spirit of fair play and sportsmanship. Moreover, it has the potential to jeopardize the integrity of the sport itself. In addition, the research has the potential to educate policymakers, sports organizations, and other stakeholders about the current legal framework and how well it discourages doping in athletic competitions. This article is divided into four distinct sections. The first section offers an explanation of what doping is and provides some context about its development throughout time. Followed the role of anti-doping authorities and the responsibilities they perform are investigated. Case studies and the research technique that will be employed for the study are in the third section; finally, the results are presented in the last section. In conclusion, doping is a severe problem that endangers the honest competition that exists within sports.

Keywords: sports law, doping, NADA, WADA, performance enhancing drugs, anti-doping bill 2022

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Authors: H. Nouri, I. E. Achouri, A. Grimes, H. Ait Said, M. Aissou, Y. Zebboudj

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This paper aims to analysis the behaviour of DC corona discharge in wire-to-plate electrostatic precipitators (ESP). Current-voltage curves are particularly analysed. Experimental results show that discharge current is strongly affected by the applied voltage. The proposed method of current identification is to use the method of least squares. Least squares problems that of into two categories: linear or ordinary least squares and non-linear least squares, depending on whether or not the residuals are linear in all unknowns. The linear least-squares problem occurs in statistical regression analysis; it has a closed-form solution. A closed-form solution (or closed form expression) is any formula that can be evaluated in a finite number of standard operations. The non-linear problem has no closed-form solution and is usually solved by iterative.

Keywords: electrostatic precipitator, current-voltage characteristics, least squares method, electric field, magnetic field

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Authors: Razak Rahmat, Azizah Ahmad, Rafidah Razak, Roshidi Din, Azizi Abas

Abstract:

Telecenter is a place where communities can access computers, the Internet, and other digital technologies to enable them to gather information, create, learn, and communicate with others. However, previous studies found that sustainability issues related to economic, political and institutional, social and technology is one of the major problem faced by the telecenter. Based on that problem, this research is planning to design a possible solution on rural telecenters sustainability with the support of business intelligence (BI). The empirical study will be conducted through the qualitative and quantitative method including interviews and observations with a range of stakeholders including ministry officers, telecenters managers and operators. Result from the data collection will be analyze using the causal modeling approach of SEM SmartPLS for the validity. The expected finding from this research is the Business Intelligent Requirement Model as a guild for sustainability of the rural telecenters.

Keywords: Rural ICT Telecenter(RICTT), business intelligence, sustainability, requirement analysis modal

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Authors: Mária Hudáková, Vladimír Míka, Katarína Hollá

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Making decisions is the core of management and a result of conscious activities which is under way in a particular environment and concrete conditions. The managers decide about the goals, procedures and about the methods how to respond to the changes and to the problems which developed. Their decisions affect the effectiveness, quality, economy and the overall successfulness in every organisation. In spite of this fact, they do not pay sufficient attention to the individual steps of the decision-making process. They emphasise more how to cope with the individual methods and techniques of making decisions and forget about the way how to cope with analysing the problem or assessing the individual solution variants. In many cases, the underestimating of the analytical phase can lead to an incorrect assessment of the problem and this can then negatively influence its further solution. Based on our analysis of the theoretical solutions by individual authors who are dealing with this area and the realised research in Slovakia and also abroad we can recognise an insufficient interest of the managers to assess the risks in the decision-making process. The goal of this paper is to assess the risks in the managers´ decision-making process relating to the conditions of the environment, to the subject’s activity (the manager’s personality), to the insufficient assessment of individual variants for solving the problems but also to situations when the arisen problem is not solved. The benefit of this paper is the effort to increase the need of the managers to deal with the risks during the decision-making process. It is important for every manager to assess the risks in his/her decision-making process and to make efforts to take such decisions which reflect the basic conditions, states and development of the environment in the best way and especially for the managers´ decisions to contribute to achieving the determined goals of the organisation as effectively as possible.

Keywords: risk, decision-making, manager, process, analysis, source of risk

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Authors: Akaki Qatamidze

Abstract:

Implementation of the project will be a step forward in terms of reliability in Georgia and the improvement of the construction and the development of construction. Completion of the project is expected to result in a complete knowledge, which is expressed in concrete and stone structures of assessing the technical condition of the processing. This method is based on a detailed examination of the structure, in order to establish the injuries and the elimination of the possibility of changing the structural scheme of the new requirements and architectural preservationists. Reinforced concrete and stone structures research project carried out in a systematic analysis of the important approach is to optimize the process of research and development of new knowledge in the neighboring areas. In addition, the problem of physical and mathematical models of rational consent, the main pillar of the physical (in-situ) data and mathematical calculation models and physical experiments are used only for the calculation model specification and verification. Reinforced concrete and stone construction defects and failures the causes of the proposed research to enhance the effectiveness of their maximum automation capabilities and expenditure of resources to reduce the recommended system analysis of the methodological concept-based approach, as modern science and technology major particularity of one, it will allow all family structures to be identified for the same work stages and procedures, which makes it possible to exclude subjectivity and addresses the problem of the optimal direction. It discussed the methodology of the project and to establish a major step forward in the construction trades and practical assistance to engineers, supervisors, and technical experts in the construction of the settlement of the problem.

Keywords: building, reinforced concrete, expertise, stone structures

Procedia PDF Downloads 331