Search results for: optimization problems

Authors: Taiki Baba, Tomoaki Hashimoto

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The random dither quantization method enables us to achieve much better performance than the simple uniform quantization method for the design of quantized control systems. Motivated by this fact, the stochastic model predictive control method in which a performance index is minimized subject to probabilistic constraints imposed on the state variables of systems has been proposed for linear feedback control systems with random dither quantization. In other words, a method for solving optimal control problems subject to probabilistic state constraints for linear discrete-time control systems with random dither quantization has been already established. To our best knowledge, however, the feasibility of such a kind of optimal control problems has not yet been studied. Our objective in this paper is to investigate the feasibility of stochastic model predictive control problems for linear discrete-time control systems with random dither quantization. To this end, we provide the results of numerical simulations that verify the feasibility of stochastic model predictive control problems for linear discrete-time control systems with random dither quantization.

Keywords: model predictive control, stochastic systems, probabilistic constraints, random dither quantization

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Authors: Khald Anisse, Amina Radgui, Mohammed Rziza

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Tracking objects on video sequences is a very challenging task in many works in computer vision applications. However, there is no article that treats this topic in catadioptric vision. This paper is an attempt that tries to describe a new approach of omnidirectional images processing based on inverse stereographic projection in the half-sphere. We used the spherical model proposed by Gayer and al. For object tracking, our work is based on snake method, with optimization using the Greedy algorithm, by adapting its different operators. The algorithm will respect the deformed geometries of omnidirectional images such as spherical neighborhood, spherical gradient and reformulation of optimization algorithm on the spherical domain. This tracking method that we call "spherical snake" permitted to know the change of the shape and the size of object in different replacements in the spherical image.

Keywords: computer vision, spherical snake, omnidirectional image, object tracking, inverse stereographic projection

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Authors: Leila Torkaman, Nasser Ghassembaglou

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Significant quota of Municipal Electrical Energy consumption is related to Decentralized Air Conditioning which is mostly provided by evaporative coolers. So the aim is to optimize design of air conditioners to increase their efficiencies. To achieve this goal, results of practical standardized tests for 40 evaporative coolers in different types collected and simultaneously results for same coolers based on one of EER (Energy Efficiency Ratio) modeling styles are figured out. By comparing experimental results of different coolers standardized tests with modeling results, preciseness of used model is assessed and after comparing gained preciseness with international standards based on EER for cooling capacity, aeration and also electrical energy consumption, energy label from A (most effective) to G (less effective) is classified. finally needed methods to optimize energy consumption and cooler's classification are provided.

Keywords: cooler, EER, energy label, optimization

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Authors: Rajesh Chakraborty, Dibyendu Das, Rabindra Nath Barman, Uttam Kumar Mandal

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In the present study, the objective is to find out the most effective zone causing soil erosion in the Gumati river basin located in the state of Tripura, a north eastern state of India using analytical hierarchy process (AHP) and multi-objective optimization on the basis of ratio analysis (MOORA).The watershed is segmented into 20 zones based on Area. The watershed is considered by pointing the maximum elevation from sea lever from Google earth. The soil erosion is determined using the universal soil loss equation. The different independent variables of soil loss equation bear different weightage for different soil zones. And therefore, to find the weightage factor for all the variables of soil loss equation like rainfall runoff erosivity index, soil erodibility factor etc, analytical hierarchy process (AHP) is used. And thereafter, multi-objective optimization on the basis of ratio analysis (MOORA) approach is used to select the most effective zone causing soil erosion. The MCDM technique concludes that the maximum soil erosion is occurring in the zone 14.

Keywords: soil erosion, analytic hierarchy process (AHP), multi criteria decision making (MCDM), universal soil loss equation (USLE), multi-objective optimization on the basis of ratio analysis (MOORA)

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Authors: Sanjivrao Katakam, Thanumoorthi I., Antony Gerald, Ratan Kulkarni, Shaju Nair

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With increasing energy costs and its impact on the business, sustainability today has evolved from a social expectation to an economic imperative. Therefore, finding methods to reduce cost has become a critical directive for Industry leaders. Effective energy management is the only way to cut costs. However, Energy Management has been a challenge because it requires a change in old habits and legacy systems followed for decades. Today exorbitant levels of energy and operational data is being captured and stored by Industries, but they are unable to convert these structured and unstructured data sets into meaningful business intelligence. It must be noted that for quick decisions, organizations must learn to cope with large volumes of operational data in different formats. Energy analytics not only helps in extracting inferences from these data sets, but also is instrumental in transformation from old approaches of energy management to new. This in turn assists in effective decision making for implementation. It is the requirement of organizations to have an established corporate strategy for reducing operational costs through visibility and optimization of energy usage. Energy analytics play a key role in optimization of operations. The paper describes how today energy data analytics is extensively used in different scenarios like reducing operational costs, predicting energy demands, optimizing network efficiency, asset maintenance, improving customer insights and device data insights. The paper also highlights how analytics helps transform insights obtained from energy data into sustainable solutions. The paper utilizes data from an array of segments such as retail, transportation, and water sectors.

Keywords: energy analytics, energy management, operational data, business intelligence, optimization

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Authors: Ahmad Yame, Ahad Ali, Badih Jawad, Daw Al-Werfalli Mohamed Nasser, Sabah Abro

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Industries in general have a lot of waste. Wool textile company, Baniwalid, Libya has many complex problems that led to enormous waste generated due to the lack of lean strategies, expertise, technical support and commitment. To successfully address waste at wool textile company, this study will attempt to develop a methodical approach that integrates lean manufacturing tools to optimize performance characteristics such as lead time and delivery. This methodology will utilize Value Stream Mapping (VSM) techniques to identify the process variables that affect production. Once these variables are identified, Design of Experiments (DOE) Methodology will be used to determine the significantly influential process variables, these variables are then controlled and set at their optimal to achieve optimal levels of productivity, quality, agility, efficiency and delivery to analyze the outputs of the simulation model for different lean configurations. The goal of this research is to investigate how the tools of lean manufacturing can be adapted from the discrete to the continuous manufacturing environment and to evaluate their benefits at a specific industrial.

Keywords: lean manufacturing, DOE, value stream mapping, textiles

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Authors: Prateek Singh, Dilshad Ahmad

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Growing demand for high-quality steel products has inspired researchers to investigate the unit operations involved in the manufacturing of these products (slabs, rods, sheets, etc.). One such operation is tundish operation, in which a vessel (tundish) acts as a buffer of molten steel for the solidification operation in mold. It is observed that tundish also plays a crucial role in the quality and cleanliness of the steel produced, besides merely acting as a reservoir for the mold. It facilitates removal of dissolved oxygen (inclusions) from the molten steel thus improving its cleanliness. Inclusion removal can be enhanced by increasing the residence time of molten steel in the tundish by incorporation of flow modifiers like dams, weirs, turbo-pad, etc. These flow modifiers also help in reducing the dead or short circuit zones within the tundish which is significant for maintaining thermal and chemical homogeneity of molten steel. Thus, it becomes important to analyze the flow of molten steel in the tundish for different configuration of flow modifiers. In the present work, effect of varying positions and heights/depths of dam and weir on the dead volume in tundish is studied. Steady state thermal and flow profiles of molten steel within the tundish are obtained using OpenFOAM. Subsequently, Residence Time Distribution analysis is performed to obtain the percentage of dead volume in the tundish. Design of Experiment method is then used to configure different tundish geometries for varying positions and heights/depths of dam and weir, and dead volume for each tundish design is obtained. A second-degree polynomial with two-term interactions of independent variables to predict the dead volume in the tundish with positions and heights/depths of dam and weir as variables are computed using Multiple Linear Regression model. This polynomial is then used in an optimization framework to obtain the optimal tundish geometry for minimizing dead volume using Sequential Quadratic Programming optimization.

Keywords: design of experiments, multiple linear regression, OpenFOAM, residence time distribution, sequential quadratic programming optimization, steel, tundish

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Authors: Soha Saad, Jean Bigeon, Florence Ossart, Etienne Sourdille

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Developing better solutions for train rescheduling problems has been drawing the attention of researchers for decades. Most researches in this field deal with minor incidents that affect a large number of trains due to cascading effects. They focus on timetables, rolling stock and crew duties, but do not take into account infrastructure limits. The present work addresses electric infrastructure incidents that limit the power available for train traction, and hence the transportation capacity of the railway system. Rescheduling is needed in order to optimally share the available power among the different trains. We propose a rescheduling process based on dynamic multiphysics railway simulations that include the mechanical and electrical properties of all the system components and calculate physical quantities such as the train speed profiles, voltage along the catenary lines, temperatures, etc. The optimization problem to solve has a large number of continuous and discrete variables, several output constraints due to physical limitations of the system, and a high computation cost. Our approach includes a phase of sensitivity analysis in order to analyze the behavior of the system and help the decision making process and/or more precise optimization. This approach is a quantitative method based on simulation statistics of the dynamic railway system, considering a predefined range of variation of the input parameters. Three important settings are defined. Factor prioritization detects the input variables that contribute the most to the outputs variation. Then, factor fixing allows calibrating the input variables which do not influence the outputs. Lastly, factor mapping is used to study which ranges of input values lead to model realizations that correspond to feasible solutions according to defined criteria or objectives. Generalized Sobol indexes are used for factor prioritization and factor fixing. The approach is tested in the case of a simple railway system, with a nominal traffic running on a single track line. The considered incident is the loss of a feeding power substation, which limits the power available and the train speed. Rescheduling is needed and the variables to be adjusted are the trains departure times, train speed reduction at a given position and the number of trains (cancellation of some trains if needed). The results show that the spacing between train departure times is the most critical variable, contributing to more than 50% of the variation of the model outputs. In addition, we identify the reduced range of variation of this variable which guarantees that the output constraints are respected. Optimal solutions are extracted, according to different potential objectives: minimizing the traveling time, the train delays, the traction energy, etc. Pareto front is also built.

Keywords: optimization, rescheduling, railway system, sensitivity analysis, train timetable

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Authors: Ganiyat Soliu, Glen Bright, Chiemela Onunka

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Performance optimization plays a key role in controlling the waiting time during manufacturing in an advanced manufacturing environment to improve productivity. Queuing mathematical modeling theory was used to examine the performance of the multi-stage production line. Robotics as a disruptive technology was implemented into a virtual manufacturing scenario during the packaging process to study the effect of waiting time on productivity. The queuing mathematical model was used to determine the optimum service rate required by robots during the packaging stage of manufacturing to yield an optimum production cost. Different rates of production were assumed in a virtual manufacturing environment, cost of packaging was estimated with optimum production cost. An equation was generated using queuing mathematical modeling theory and the theorem adopted for analysis of the scenario is the Newton Raphson theorem. Queuing theory presented here provides an adequate analysis of the number of robots required to regulate waiting time in order to increase the number of output. Arrival rate of the product was fast which shows that queuing mathematical model was effective in minimizing service cost and the waiting time during manufacturing. At a reduced waiting time, there was an improvement in the number of products obtained per hour. The overall productivity was improved based on the assumptions used in the queuing modeling theory implemented in the virtual manufacturing scenario.

Keywords: performance optimization, productivity, queuing theory, robotics

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Authors: B. Medjahed, M. A. Didi, B. Guezzen

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This work concerns with the experimental study of the adsorption of the Ni(II) on bentonite. The effects of various parameters such as contact time, stirring rate, initial concentration of Ni(II), masse of clay, initial pH of aqueous solution and temperature on the adsorption yield, were carried out. The study of the effect of the ionic strength on the yield of adsorption was examined by the identification and the quantification of the present chemical species in the aqueous phase containing the metallic ion Ni(II). The adsorbed species were investigated by a calculation program using CHEAQS V. L20.1 in order to determine the relation between the percentages of the adsorbed species and the adsorption yield. The optimization process was carried out using 2³ factorial designs. The individual and combined effects of three process parameters, i.e. initial Ni(II) concentration in aqueous solution (2.10⁻³ and 5.10⁻³ mol/L), initial pH of the solution (2 and 6.5), and mass of bentonite (0.03 and 0.3 g) on Ni(II) adsorption, were studied.

Keywords: adsorption, bentonite, factorial design, Nickel(II)

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Authors: Mihir Mouchum Hazarika, Maddali Ramgopal, Souvik Bhattacharyya

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The thermodynamic analysis shows that the performance of the R744 based transcritical refrigeration cycle drops drastically for higher ambient temperatures. This is due to the peculiar s-shape of the isotherm in the supercritical region. However, subcooling of the refrigerant at the gas cooler exit enhances the performance of the R744 based system. The present study is carried out to analyze the R744 based transcritical system with dedicated mechanical subcooling cycle. Based on this proposed cycle, the thermodynamic analysis is performed, and optimum operating parameters are determined. The amount of subcooling and the pressure ratio in the subcooling cycle are the parameters which are needed to be optimized to extract the maximum COP from this proposed cycle. It is expected that this study will be helpful in implementing the dedicated subcooling cycle with R744 based transcritical system to improve the performance.

Keywords: optimization, R744, subcooling, transcritical

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Authors: Fernanda M. Assef, Maria Teresinha A. Steiner, David Gabriel F. Barros

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Review researches are useful in terms of analysis of research problems. Between the types of review documents, we commonly find bibliometric studies. This type of application often helps the global visualization of a research problem and helps academics worldwide to understand the context of a research area better. In this document, a bibliometric view surrounding clustering techniques and sustainability problems is presented. The authors aimed at which issues mostly use clustering techniques, and, even which sustainability issue would be more impactful on today’s moment of research. During the bibliometric analysis, we found ten different groups of research in clustering applications for sustainability issues: Energy; Environmental; Non-urban planning; Sustainable Development; Sustainable Supply Chain; Transport; Urban Planning; Water; Waste Disposal; and, Others. And, by analyzing the citations of each group, we discovered that the Environmental group could be classified as the most impactful research cluster in the area mentioned. Now, after the content analysis of each paper classified in the environmental group, we found that the k-means technique is preferred for solving sustainability problems with clustering methods since it appeared the most amongst the documents. The authors finally conclude that a bibliometric assessment could help indicate a gap of researches on waste disposal – which was the group with the least amount of publications – and the most impactful research on environmental problems.

Keywords: bibliometric assessment, clustering, sustainability, territorial partitioning

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Authors: Amal Machtalay

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In this survey, we aim to review the rapidly growing literature on numerical methods to solve different forms of mean field problems, namely mean field games (MFG), mean field controls (MFC), potential MFGs, and master equations, as well as their corresponding recent applications. Here, we distinguish two families of numerical methods: iterative methods based on mesh generation and those called mesh-free, normally related to neural networking and learning frameworks.

Keywords: mean-field games, numerical schemes, partial differential equations, complex systems, machine learning

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Authors: Kinza Qadeer, Muhammad Abdul Qyyum, Moonyong Lee

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Natural gas has become an attractive energy source in comparison with other fossil fuels because of its lower CO₂ and other air pollutant emissions. Therefore, compared to the demand for coal and oil, that for natural gas is increasing rapidly world-wide. The transportation of natural gas over long distances as a liquid (LNG) preferable for several reasons, including economic, technical, political, and safety factors. However, LNG production is an energy-intensive process due to the tremendous amount of power requirements for compression of refrigerants, which provide sufficient cold energy to liquefy natural gas. Therefore, one of the major issues in the LNG industry is to improve the energy efficiency of existing LNG processes through a cost-effective approach that is 'optimization'. In this context, a bio-inspired Krill-herd (KH) step-up approach was examined to enhance the energy efficiency of a single mixed refrigerant (SMR) natural gas liquefaction (LNG) process, which is considered as a most promising candidate for offshore LNG production (FPSO). The optimal design of a natural gas liquefaction processes involves multivariable non-linear thermodynamic interactions, which lead to exergy destruction and contribute to process irreversibility. As key decision variables, the optimal values of mixed refrigerant flow rates and process operating pressures were determined based on the herding behavior of krill individuals corresponding to the minimum energy consumption for LNG production. To perform the rigorous process analysis, the SMR process was simulated in Aspen Hysys® software and the resulting model was connected with the Krill-herd approach coded in MATLAB. The optimal operating conditions found by the proposed approach significantly reduced the overall energy consumption of the SMR process by ≤ 22.5% and also improved the coefficient of performance in comparison with the base case. The proposed approach was also compared with other well-proven optimization algorithms, such as genetic and particle swarm optimization algorithms, and was found to exhibit a superior performance over these existing approaches.

Keywords: energy efficiency, Krill-herd, LNG, optimization, single mixed refrigerant

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Authors: Taner Cindik, Ferya Tas Ciftci

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Mobbing in the public sector and specific issues (i.e., the demand for non-pecuniary damages) regarding mobbing have become very important in the light of the precedents constituted by the Turkish Council of State in 2010. The legal scope of mobbing is not able to be determined since the concept of mobbing is not defined in Turkish law system. This study aims to reveal three major problems caused by the lack of laws related to mobbing in the Turkish legal system. First, the absence of an arrangement for disciplinary penalties leads that general provisions in the disciplinary law are implemented. This situation, therefore, causes difficulties in practice. Second, not being drawn of the lines in the topic concerning mobbing in public sector leads confusions in being direction of hostility. Third, the fact that there is a legal gap on seeking non-pecuniary compensation when employees in public sector are exposed to mobbing might make it difficult to obtain non-pecuniary compensation. Within the context of these major problems, civil servants in Turkey do not have enough protection mechanism. However, some possible legal arrangements will help civil servants to protect against mobbing. This study may be considered important because of the fact that mobbing in the public sector is at a significant level and has not been evaluated in this context before. This research is mainly a study of Turkish legal system and evaluates critically law case to determine legal problems. As a result of this study, three main problems might be identified because there is legal gap regarding mobbing in the public sector. In conclusion, the introduction of the major problems related to mobbing in this study might shed light on making the proper regulations of this subject in Turkish law system. In this respect, the plaintiff will be provided convenience in the point of non-pecuniary damages and this study will guide the assessment of legal liability of those who implement mobbing.

Keywords: human rights violations, mobbing, public sector, direction of hostility, non-pecuniary compensation, disciplinary law

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Authors: Othman Mohamed Altheni, Abdurrahman Abusaada

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This study presents optimization of multiple performance characteristics [material removal rate (MRR), surface roughness (Ra), and overcut (OC)] of hardened AISI D3 tool steel in electrical discharge machining (EDM) using Taguchi method and Grey relational analysis. Machining process parameters selected were pulsed current Ip, pulse-on time Ton, pulse-off time Toff and gap voltage Vg. Based on ANOVA, pulse current is found to be the most significant factor affecting EDM process. Optimized process parameters are simultaneously leading to a higher MRR, lower Ra, and lower OC are then verified through a confirmation experiment. Validation experiment shows an improved MRR, Ra and OC when Taguchi method and grey relational analysis were used

Keywords: edm parameters, grey relational analysis, Taguchi method, ANOVA

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Authors: Michael Zenker, Henrik Prinzhorn, Christian Böning, Tom Strating

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Large-scale products are often assembled according to the job-site principle, meaning that during the assembly the product is located at a fixed position, while the area requirements are constantly changing. On one hand, the product itself is growing with each assembly step, whereas varying areas for storage, machines or working areas are temporarily required. This is an important factor when arranging products to be assembled within the factory. Currently, it is common to reserve a fixed area for each product to avoid overlaps or collisions with the other assemblies. Intending to be large enough to include the product and all adjacent areas, this reserved area corresponds to the superposition of the maximum extents of all required areas of the product. In this procedure, the reserved area is usually poorly utilized over the course of the entire assembly process; instead a large part of it remains unused. If the available area is a limited resource, a systematic arrangement of the products, which complies with the dynamic area requirements, will lead to an increased area utilization and productivity. This paper presents the results of a study on the arrangement of assembly objects assuming dynamic, competing area requirements. First, the problem situation is extensively explained, and existing research on associated topics is described and evaluated on the possibility of an adaptation. Then, a newly developed mathematical optimization model is introduced. This model allows an optimal arrangement of dynamic areas, considering logical and practical constraints. Finally, in order to quantify the potential of the developed method, some test series results are presented, showing the possible increase in area utilization.

Keywords: dynamic area requirements, facility layout problem, optimization model, product assembly

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Authors: Zeynep Tanrıverdi

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The Bosphorus is an international waterway in Istanbul city of Turkey connecting the Sea of Marmara and the Black Sea. The Bosphorus, which has formed an important part of the silhouette of Istanbul throughout history, has also influenced the design of the coastal structures built around it. The waterfront mansions, which are located on both sides of the Bosphorus by the sea, and can be generally of two or three storeys, are called “yalı”. The yalı buildings with their architectural characteristics of the traditional Turkish House are the most grandiose examples of Ottoman residential architecture. However, the classical Ottoman yalı architecture of the 18th century can only be seen in engravings, and today only the modest and smaller yalı examples from the 19th century can be seen because of their disappearance over time. The study aims to reveal the architectural conservation and restoration problems of waterfront mansions and propose solutions for them. Firstly, the development of the waterfront mansion architecture in Bosphorus was evaluated in its historical process. Secondly, the waterfront mansions and their architectural features were explained. Thirdly, the architectural conservation and restoration problems that caused the disappearance of waterfront mansions were discussed. These problems include disruptions in legal regulations and practices about the Bosphorus, dramatic changes in Turkey’s socio-cultural life from the Ottoman Empire to the present, inadequacies in economic resources, negative environmental effects, and errors in restoration works. Finally, solution suggestions were proposed for the problems that threaten the protection of waterfront mansions. In the study, literature on waterfront mansions was reviewed using historical reports, photographs, maps, and drawings in archival documents. It is hoped that this study will contribute the conservation of the “Yalı” waterfront mansions, which occupy a particular role in the cultural heritage of Turkey, and to their transmission with their authentic values to the next generation.

Keywords: bosphorus architecture, conservation, heritage, Istanbul, waterfront mansions (yalı)

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Authors: Arslan Ellahi, Syed Amjad Hussain

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Software Testing is a vital process in software development life cycle. We can attain the quality of software after passing it through software testing phase. We have tried to find out automatic test data generation techniques that are a key research area of software testing to achieve test automation that can eventually decrease testing time. In this paper, we review some of the approaches presented in the literature which use evolutionary search based algorithms like Genetic Algorithm, Particle Swarm Optimization (PSO), etc. to validate the test data generation process. We also look into the quality of test data generation which increases or decreases the efficiency of testing. We have proposed test data generation techniques for model-based testing. We have worked on tuning and fitness function of PSO algorithm.

Keywords: search based, evolutionary algorithm, particle swarm optimization, genetic algorithm, test data generation

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Authors: Asma Rebaya, Imen Amari, Kaouther Gasmi, Salem Hasnaoui

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Over these last years, the number of cores witnessed a spectacular increase in digital signal and general use processors. Concurrently, significant researches are done to get benefit from the high degree of parallelism. Indeed, these researches are focused to provide an efficient scheduling from hardware/software systems to multicores architecture. The scheduling process consists on statically choose one core to execute one task and to specify an execution order for the application tasks. In this paper, we describe an efficient scheduler that calculates the optimal number of cores required to schedule an application, gives a heuristic scheduling solution and evaluates its cost. Our proposal results are evaluated and compared with Preesm scheduler results and we prove that ours allows better scheduling in terms of latency, computation time and number of cores.

Keywords: computation time, hardware/software system, latency, optimization, multi-cores platform, scheduling

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Authors: Soheil Mohtaram, Wu Weidong, Yashar Aryanfar

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This research investigates the points with heat recovery potential in a triple-pressure cogeneration combined cycle power plant and determines the amount of waste heat that can be recovered. A modified cycle arrangement is then adopted for accessing thermal potentials. Modeling the energy system is followed by thermodynamic and energetic evaluation, and then the price of the manufactured products is also determined using the Total Revenue Requirement (TRR) method and term economic analysis. The results of optimization are then presented in a Pareto chart diagram by implementing a new model with dual objective functions, which include power cost and produce heat. This model can be utilized to identify the optimal operating point for such power plants based on electricity and heat prices in different regions.

Keywords: heat loss, recycling, unused energy, efficient production, optimization, triple-pressure cogeneration

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Authors: Ambali Alade Odebowale, Andargachew Mekonnen Berhe, Haroldo T. Hattori, Andrey E. Miroshnichenko

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Solar thermophotovoltaic systems (STPV) have emerged as a promising solution to overcome the Shockley-Queisser limit, a significant impediment in the direct conversion of solar radiation into electricity using conventional solar cells. The STPV system comprises essential components such as an optical concentrator, selective emitter, and a thermophotovoltaic (TPV) cell. The pivotal element in achieving high efficiency in an STPV system lies in the design of a spectrally selective emitter or absorber. Traditional methods for designing and optimizing selective emitters are often time-consuming and may not yield highly selective emitters, posing a challenge to the overall system performance. In recent years, the application of machine learning techniques in various scientific disciplines has demonstrated significant advantages. This paper proposes a novel nanostructure composed of four-layered materials (SiC/W/SiO2/W) to function as a selective emitter in the energy conversion process of an STPV system. Unlike conventional approaches widely adopted by researchers, this study employs a machine learning-based approach for the design and optimization of the selective emitter. Specifically, a random forest algorithm (RFA) is employed for the design of the selective emitter, while the optimization process is executed using genetic algorithms. This innovative methodology holds promise in addressing the challenges posed by traditional methods, offering a more efficient and streamlined approach to selective emitter design. The utilization of a machine learning approach brings several advantages to the design and optimization of a selective emitter within the STPV system. Machine learning algorithms, such as the random forest algorithm, have the capability to analyze complex datasets and identify intricate patterns that may not be apparent through traditional methods. This allows for a more comprehensive exploration of the design space, potentially leading to highly efficient emitter configurations. Moreover, the application of genetic algorithms in the optimization process enhances the adaptability and efficiency of the overall system. Genetic algorithms mimic the principles of natural selection, enabling the exploration of a diverse range of emitter configurations and facilitating the identification of optimal solutions. This not only accelerates the design and optimization process but also increases the likelihood of discovering configurations that exhibit superior performance compared to traditional methods. In conclusion, the integration of machine learning techniques in the design and optimization of a selective emitter for solar thermophotovoltaic systems represents a groundbreaking approach. This innovative methodology not only addresses the limitations of traditional methods but also holds the potential to significantly improve the overall performance of STPV systems, paving the way for enhanced solar energy conversion efficiency.

Keywords: emitter, genetic algorithm, radiation, random forest, thermophotovoltaic

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Authors: Ying Shen, Weihua Zhu

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Medical images are important to help identifying different diseases, for example, Magnetic resonance imaging (MRI) can be used to investigate the brain, spinal cord, bones, joints, breasts, blood vessels, and heart. Image segmentation, in medical image analysis, is usually the first step to find out some characteristics with similar color, intensity or texture so that the diagnosis could be further carried out based on these features. This paper introduces an improved C-means model to segment the MRI images. The model is based on information entropy to evaluate the segmentation results by achieving global optimization. Several contributions are significant. Firstly, Genetic Algorithm (GA) is used for achieving global optimization in this model where fuzzy C-means clustering algorithm (FCMA) is not capable of doing that. Secondly, the information entropy after segmentation is used for measuring the effectiveness of MRI image processing. Experimental results show the outperformance of the proposed model by comparing with traditional approaches.

Keywords: magnetic resonance image (MRI), c-means model, image segmentation, information entropy

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Authors: Sehrish Khan

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The present study investigated the attitude of university students towards semester system and teachers with a specific objective of finding problems faced by students in semester system. 10 focus group discussions were conducted among students in five Universities of Hazara Division of KPK regarding their knowledge and attitudes about semester system and problems they faced due to this system and teacher’s attitude. The key findings were the problems like favoritism, gender biased ness, racial biased ness, biased ness in marking, relative marking, harassment, using students for personal tasks and authoritarian attitude from teachers’ side and the heavy tasks in less time which are causing stress among students. It was recommended that proper training and monitoring system should be maintained for evaluation of teachers to minimize the corruption in this sacred profession and maximize the optimal functioning. The information gathered in this research can be used to develop training modules for University teachers.

Keywords: university teachers, favoritism, biasedness, harassment

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Authors: Ghanima Al-Sharrah, Haitham M. Lababidi, Yusuf I. Ali

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The main objective of the current work is to introduce sustainability factors in optimizing the supply chain model for process industries. The supply chain models are normally based on purely economic considerations related to costs and profits. To account for sustainability, two additional factors have been introduced; environment and risk. A supply chain for an entire petroleum organization has been considered for implementing and testing the proposed optimization models. The environmental and risk factors were introduced as indicators reflecting the anticipated impact of the optimal production scenarios on sustainability. The aggregation method used in extending the single objective function to multi-objective function is proven to be quite effective in balancing the contribution of each objective term. The results indicate that introducing sustainability factor would slightly reduce the economic benefit while improving the environmental and risk reduction performances of the process industries.

Keywords: environmental indicators, optimization, risk, supply chain

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Authors: Aprajeeta Jha, Punyadarshini P. Tripathy

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Drying is one of the most critical unit operations for prolonging the shelf-life of food grains in order to ensure global food security. Photovoltaic integrated solar dryers can be a sustainable solution for replacing energy intensive thermal dryers as it is capable of drying in off-sunshine hours and provide better control over drying conditions. But, performance and reliability of PV based solar dryers depend hugely on climatic conditions thereby, drastically affecting process parameters. Therefore, to ensure quality and prolonged shelf-life of paddy, optimization of process parameters for solar dryers is critical. Proper moisture distribution within the grains is most detrimental factor to enhance the shelf-life of paddy therefore; modeling of mass transport can help in providing a better insight of moisture migration. Hence, present work aims at optimizing the process parameters and to develop a 3D finite element model (FEM) for predicting moisture profile in paddy during solar drying. Optimization of process parameters (power level, air velocity and moisture content) was done using box Behnken model in Design expert software. Furthermore, COMSOL Multiphysics was employed to develop a 3D finite element model for predicting moisture profile. Optimized model for drying paddy was found to be 700W, 2.75 m/s and 13% wb with optimum temperature, milling yield and drying time of 42˚C, 62%, 86 min respectively, having desirability of 0.905. Furthermore, 3D finite element model (FEM) for predicting moisture migration in single kernel for every time step has been developed. The mean absolute error (MAE), mean relative error (MRE) and standard error (SE) were found to be 0.003, 0.0531 and 0.0007, respectively, indicating close agreement of model with experimental results. Above optimized conditions can be successfully used to dry paddy in PV integrated solar dryer in order to attain maximum uniformity, quality and yield of product to achieve global food and energy security

Keywords: finite element modeling, hybrid solar drying, mass transport, paddy, process optimization

Procedia PDF Downloads 124

Authors: Pranav Mohan Parki, C. Mallika Parveen, Tahseen Ahmad Khan, Mihika Shivkumar

Abstract:

Additive manufacturing (AM) is one of the several manufacturing processes in use today. AM comprises of techniques such as ‘Selective Laser Sintering’ and ‘Selective Laser Melting’ etc. along with other equipment and materials has been developed way back in 1980s, although major use of these methods has risen during the last decade. AM seems to be the most efficient way when compared to the traditional machining procedures. Still many problems continue to hinder its progress to becoming the most widely used of all. This paper contributes to the better understanding of AM and also aims at providing viable solutions to these problems, which may further help in enabling AM to become the most flaw free production method.

Keywords: additive manufacturing (AM), 3D printing, prototype, laser sintering

Procedia PDF Downloads 363

Authors: V. S. S. Kumar, B. Vikram, G. C. S. Reddy

Abstract:

Time and cost are the two critical objectives of construction project management and are not independent but intricately related. Trade-off between project duration and cost are extensively discussed during project scheduling because of practical relevance. Generally when the project duration is compressed, the project calls for an increase in labor and more productive equipments, which increases the cost. Thus, the construction time-cost optimization is defined as a process to identify suitable construction activities for speeding up to attain the best possible savings in both time and cost. As there is hidden tradeoff relationship between project time and cost, it might be difficult to predict whether the total cost would increase or decrease as a result of compressing the schedule. Different combinations of duration and cost for the activities associated with the project determine the best set in the time-cost optimization. Therefore, the contractors need to select the best combination of time and cost to perform each activity, all of which will ultimately determine the project duration and cost. In this paper, the fuzzy set theory is used to model the uncertainties in the project environment for time-cost trade off analysis.

Keywords: fuzzy sets, uncertainty, qualitative factors, decision making

Procedia PDF Downloads 634

Authors: Okechukwu Uzoma Nkwocha, Edward Uche Omeire

Abstract:

Information and communication technologies (ICT) undeniably, have expanded the sphere of arts and creativity. It proves to be an important tool for production, preservation, sharing and utilization of arts and cultural heritage. While art and heritage institutions around the globe are increasingly utilizing ICT for the promotion and sharing of their collections, the story seems different in most part of Africa. In this paper, we will examine the prospects and problems of utilizing ICT in promotion, preservation and sharing of arts and cultural heritage.

Keywords: arts, cultural heritage, digitalization, ICT

Procedia PDF Downloads 165

Authors: Usman Jilani, Ibad Khurram, Irshad Hussain

Abstract:

Environmentally sustainable waste management is a challenging task as it involves multiple and diverse economic, environmental, technical and regulatory issues. Municipal Solid Waste Management (MSWM) is more challenging in developing countries like Pakistan due to lack of awareness, technology and human resources, insufficient funding, inefficient collection and transport mechanism resulting in the lack of a comprehensive waste management system. This work presents an overview of current MSWM practices in Peshawar, the provincial capital of Khyber Pakhtunkhwa, Pakistan and proposes a better and sustainable integrated solid waste management system with incineration (Waste to Energy) option. The diverted waste would otherwise generate revenue; minimize land fill requirement and negative impact on the environment. The proposed optimized solution utilizing scientific techniques (like mathematical modeling, optimization algorithms and GIS) as decision support tools enhances the technical & institutional efficiency leading towards a more sustainable waste management system through incorporating: - Improved collection mechanisms through optimized transportation / routing and, - Resource recovery through incineration and selection of most feasible sites for transfer stations, landfills and incineration plant. These proposed methods shift the linear waste management system towards a cyclic system and can also be used as a decision support tool by the WSSP (Water and Sanitation Services Peshawar), agency responsible for the MSWM in Peshawar.

Keywords: municipal solid waste management, incineration, mathematical modeling, optimization, GIS, Peshawar

Procedia PDF Downloads 359