Search results for: reliability optimization

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

Procedia PDF Downloads 342

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)

Procedia PDF Downloads 536

Authors: Patrick Cormier, Cesar Meylan, Matt Jensen, Dana Agar-Newman, Chloe Werle, Ming-Chang Tsai, Marc Klimstra

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Sprint-derived horizontal force-velocity-power (FVP) profiles can be developed with adequate validity and reliability with satellite (GPS/GNSS) systems. However, FVP metrics are sensitive to small nuances in data processing procedures such that minor differences in defining the onset and end of the sprint could result in different FVP metric outcomes. Furthermore, in team-sports, there is a requirement for rapid analysis and feedback of results from multiple athletes, therefore developing standardized and automated methods to improve the speed, efficiency and reliability of this process are warranted. Thus, the purpose of this study was to compare different methods of sprint end detection on the development of FVP profiles from 10Hz GPS/GNSS data through goodness-of-fit and intertrial reliability statistics. Seventeen national team female soccer players participated in the FVP protocol which consisted of 2x40m maximal sprints performed towards the end of a soccer specific warm-up in a training session (1020 hPa, wind = 0, temperature = 30°C) on an open grass field. Each player wore a 10Hz Catapult system unit (Vector S7, Catapult Innovations) inserted in a vest in a pouch between the scapulae. All data were analyzed following common procedures. Variables computed and assessed were the model parameters, estimated maximal sprint speed (MSS) and the acceleration constant τ, in addition to horizontal relative force (F₀), velocity at zero (V₀), and relative mechanical power (Pmax). The onset of the sprints was standardized with an acceleration threshold of 0.1 m/s². The sprint end detection methods were: 1. Time when peak velocity (MSS) was achieved (zero acceleration), 2. Time after peak velocity drops by -0.4 m/s, 3. Time after peak velocity drops by -0.6 m/s, and 4. When the integrated distance from the GPS/GNSS signal achieves 40-m. Goodness-of-fit of each sprint end detection method was determined using the residual sum of squares (RSS) to demonstrate the error of the FVP modeling with the sprint data from the GPS/GNSS system. Inter-trial reliability (from 2 trials) was assessed utilizing intraclass correlation coefficients (ICC). For goodness-of-fit results, the end detection technique that used the time when peak velocity was achieved (zero acceleration) had the lowest RSS values, followed by -0.4 and -0.6 velocity decay, and 40-m end had the highest RSS values. For intertrial reliability, the end of sprint detection techniques that were defined as the time at (method 1) or shortly after (method 2 and 3) when MSS was achieved had very large to near perfect ICC and the time at the 40 m integrated distance (method 4) had large to very large ICCs. Peak velocity was reached at 29.52 ± 4.02-m. Therefore, sport scientists should implement end of sprint detection either when peak velocity is determined or shortly after to improve goodness of fit to achieve reliable between trial FVP profile metrics. Although, more robust processing and modeling procedures should be developed in future research to improve sprint model fitting. This protocol was seamlessly integrated into the usual training which shows promise for sprint monitoring in the field with this technology.

Keywords: automated, biomechanics, team-sports, sprint

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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: 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: Hossein Alimohammadi, Mohsen Amirmojahedi, Mehrdad Rowhani

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Soil properties are used by geotechnical engineers to evaluate and analyze site conditions for designing purposes. Although basic soil classification tests are easy to perform and provide useful information to determine the properties of soils, it may take time to get the result and add some costs to the projects. Standard Penetration Test (SPT) provides an opportunity to evaluate soil parameters without performing laboratory tests. In addition to its simplicity and cheapness, the results become available immediately. This research provides a guideline on the application of the SPT test method, reliability of adapting the SPT test results in evaluating soil physical and mechanical properties such as Atterberg limits, shear strength, and compressive strength compressibility parameters. A total of 70 boreholes were investigated in this study by taking soil samples between depths of 1.2 to 15.25 meters. The project site was located in Morrow County, Ohio. A regression-based formula was proposed based on Tobit regression with a stepwise variable selection analysis conducted between SPT and other typical soil properties obtained from soil tests. The results of the research illustrated that the shear strength and physical properties of the soil affect the SPT number. The proposed correlation can help engineers to use SPT test results in their design with higher accuracy.

Keywords: standard penetration test, soil properties, soil classification, regression method

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Authors: Cemile Kütmeç Yilmaz, Güler Duru Asiret, Gulcan Bagcivan

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The aim of this study was to evaluate the reliability and validity of the Turkish version of the Carer’s Assessment of Satisfaction Index (CASI-TR). The study was conducted between the dates of June 2016 and September 2017 at the Training and Research Hospital of Aksaray University with the caregiving family members of the inpatients with chronic diseases. For this study, the sample size was calculated as at least 10 individuals for each item (item number (30)X10=300). The study sample included 300 caregiving family members, who provided primer care for at least three months for a patient (who had at least one chronic disease and received inpatient treatment in general internal medicine and palliative care units). Data were collected by using a demographic questionnaire and CASI-TR. Descriptive statistics, and psychometric tests were used for the data analysis. Of those caregivers, 76.7% were female, 86.3% were 65 years old and below, 43.7% were primary school graduates, 87% were married, 86% were not working, 66.3% were housewives, and 60.3% defined their income status as having an income covering one’s expenses. Care recipients often had problems in terms of walking, sleep, balance, feeding and urinary incontinence. The Cronbach Alpha value calculated for the CASI-TR (30 items) was 0,949. Internal consistency coefficients calculated for subscales were: 0.922 for the subscale of ‘caregiver satisfaction related to care recipient’, 0.875 for the subscale of ‘caregiver satisfaction related to themselves’, and 0.723 for the subscale of ‘dynamics of interpersonal relations’. Factor analysis revealed that three factors accounted for 57.67% of the total variance, with an eigenvalue of >1. assessed in terms of significance, we saw that the items came together in a significant manner. The factor load of the items were between 0.311 and 0.874. These results show that the CASI-TR is a valid and reliable scale. The adoption of the translated CASI in Turkey is found reliable and valid to assessing the satisfaction of caregivers. CASI-TR can be used easily in clinics or house visits by nurses and other health professionals for assessing caregiver satisfaction from caregiving.

Keywords: carer’s assessment of satisfaction index, caregiver, validity, reliability

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Authors: Malika Ourabia

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A new and efficient method is presented for the analysis of arbitrarily shaped discontinuities. The discontinuities is characterized using a hybrid spectral/numerical technique. This structure presents an arbitrary number of ports, each one with different orientation and dimensions. This article presents a hybrid method based on multimode contour integral and mode matching techniques. The process is based on segmentation and dividing the structure into key building blocks. We use the multimode contour integral method to analyze the blocks including irregular shape discontinuities. Finally, the multimode scattering matrix of the whole structure can be found by cascading the blocks. Therefore, the new method is suitable for analysis of a wide range of waveguide problems. Therefore, the present approach can be applied easily to the analysis of any multiport junctions and cascade blocks. The accuracy of the method is validated comparing with results for several complex problems found in the literature. CPU times are also included to show the efficiency of the new method proposed.

Keywords: segmentation, s parameters, simulation, optimization

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Authors: Harrison Gideon Maghra

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The study was conducted on the challenges in the use of ICT in Agricultural Education and Training in Colleges of Education in Adamawa State. Three objectives guided the study, and the objectives were translated into three research questions and the research questions translated into two null hypotheses. Frequency and percentage were used to answer research question one, mean and standard deviation were used to answer research questions two and three, and t-test statistic was used to test the null hypotheses at 0.05 level of significance. The study was descriptive research and a questionnaire was used to solicit responses from the respondent. The instrument for data collection was subjected to face and content validity by 1 expert in the Department of Vocational Education, Modibbo Adama University, Yola and 3 experts from the Department of Vocational and Technical Education, Adamawa State University, Mubi. Pearson Product Moment Correlation Coefficient was used to test the reliability of the instrument and a reliability coefficient of 0.76 was obtained through the test re-test test method. Results from the study revealed that ICT facilities are not available in state-owned colleges of education. Agricultural Education lecturers have a positive attitude toward the use of ICT in teaching agricultural education and training. Based on the findings of the study, recommendations were made, among which: Colleges of Education in the state should organize training on the use of ICT for all lecturers, including those in the Agricultural Education program.

Keywords: challenges, ICT, agricultural education, colleges of education

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Authors: Mark Kennedy, E. Bantugon, Noruane A. Daileg

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Leaks arising from aircraft fuel tanks is a protracted problem for the aircraft manufacturers, operators, and maintenance crews. It principally arises from stress, structural defects, or degraded sealants as the aircraft age. It can be ignited by different sources, which can result in catastrophic flight and consequences, exhibiting a major drain both on time and budget. In order to mitigate and eliminate this kind of problem, the researcher produced an experimental sealant having a base material of natural tree resin, the Pili Tree Resin. Aside from producing an experimental sealant, the main objective of this research is to analyze its physical, chemical, mechanical, thermal, and rheological properties, which is beneficial and effective for specific aircraft parts, particularly the integral fuel tank. The experimental method of research was utilized in this study since it is a product invention. This study comprises two parts, specifically the Optimization Process and the Characterization Process. In the Optimization Process, the experimental sealant was subjected to the Flammability Test, an important test and consideration according to 14 Code of Federal Regulation Appendix N, Part 25 - Fuel Tank Flammability Exposure and Reliability Analysis, to get the most suitable formulation. Followed by the Characterization Process, where the formulated experimental sealant has undergone thirty-eight (38) different standard testing including Organoleptic, Instrumental Color Measurement Test, Smoothness of Appearance Test, Miscibility Test, Boiling Point Test, Flash Point Test, Curing Time, Adhesive Test, Toxicity Test, Shore A Hardness Test, Compressive Strength, Shear Strength, Static Bending Strength, Tensile Strength, Peel Strength Test, Knife Test, Adhesion by Tape Test, Leakage Test), Drip Test, Thermogravimetry-Differential Thermal Analysis (TG-DTA), Differential Scanning Calorimetry, Calorific Value, Viscosity Test, Creep Test, and Anti-Sag Resistance Test to determine and analyze the five (5) material properties of the sealant. The numerical values of the mentioned tests are determined using product application, testing, and calculation. These values are then used to calculate the efficiency of the experimental sealant. Accordingly, this efficiency is the means of comparison between the experimental and commercial sealant. Based on the results of the different standard testing conducted, the experimental sealant exceeded all the data results of the commercial sealant. This result shows that the physicochemical-mechanical, thermal, and rheological properties of the experimental sealant are far more effective as an aircraft integral fuel tank sealant alternative in comparison to the commercial sealant. Therefore, Pili Tree possesses a new role and function: a source of ingredients in sealant production.

Keywords: Aircraft Integral Fuel Tank, Physicochemi-mechanical, Pili Tree Resin, Properties, Rheological, Sealant, Thermal

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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

Procedia PDF Downloads 152

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: 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: 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: 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: Boris Djartov, Sanaz Mostaghim

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This paper presents a number-based dominance method. The main idea is how to fragment the many attributes of the problem into subsets suitable for the well-established concept of Pareto dominance. Although other similar methods can be found in the literature, they focus on comparing the solutions one objective at a time, while the focus of this method is to compare entire subsets of the objective vector. Given the nature of the method, it is computationally costlier than other methods and thus, it is geared more towards selecting an option from a finite set of alternatives, where each solution is defined by multiple objectives. The need for this method was motivated by dynamic alternate airport selection (DAAS). In DAAS, pilots, while en route to their destination, can find themselves in a situation where they need to select a new landing airport. In such a predicament, they need to consider multiple alternatives with many different characteristics, such as wind conditions, available landing distance, the fuel needed to reach it, etc. Hence, this method is primarily aimed at human decision-makers. Many methods within the field of multi-objective and many-objective decision-making rely on the decision maker to initially provide the algorithm with preference points and weight vectors; however, this method aims to omit this very difficult step, especially when the number of objectives is so large. The proposed method will be compared to Favour (1 − k)-Dom and L-dominance (LD) methods. The test will be conducted using well-established test problems from the literature, such as the DTLZ problems. The proposed method is expected to outperform the currently available methods in the literature and hopefully provide future decision-makers and pilots with support when dealing with many-objective optimization problems.

Keywords: multi-objective decision-making, many-objective decision-making, multi-objective optimization, many-objective optimization

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Authors: Jemely M. Punzalan, Christine B. Bernal, Beatrice B. Canonigo, Maria Rosario F. Cabansag, Dennis S. Flores, Paul Joseph T. Galutira, Remedios D. Chan

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Background: Systemic lupus erythematosus (SLE) is one of the most common autoimmune disorders predominates in women of childbearing age. Simple Measure of Impact of Lupus Erythematosus in Youngsters (SMILEY) is the only health specific quality of life tool for pediatric SLE, which has been translated to different languages except in Filipino. Objective: The primary objective of this study was to develop a Filipino translation of the SMILEY and to examine the validity and reliability of this translation. Methodology: The SMILEY was translated into Filipino by a bilingual individual and back-translated by another bilingual individual blinded from the original English version. The translation was evaluated for content validity by a panel of experts and subjected to pilot testing. The pilot-tested translation was used in the validity and reliability testing proper. The SMILEY, together with the previously validated PEDSQL 4.0 Generic Core Scale was administered to lupus pediatric patients and their parent at two separate occasions: a baseline and a re-test seven to fourteen days apart. Tests for convergent validity, internal consistency, and test-retest reliability were performed. Results: A total of fifty children and their parent were recruited. The mean age was 15.38±2.62 years (range 8-18 years), mean education at high school level. The mean duration of SLE was 28 months (range 1-81 months). Subjects found the questionnaires to be relevant, easy to understand and answer. The validity of the SMILEY was demonstrated in terms of content validity, convergent validity, internal consistency, and test-retest reliability. Age, socioeconomic status and educational attainment did not show a significant effect on the scores. The difference between scores of child and parent report was showed to be significant with SMILEY total (p=0.0214), effect on social life (p=0.0000), and PEDSQL physical function (p=0.0460). Child reports showed higher scores for the following domains compared to their parent. Conclusion: SMILEY is a brief, easy to understand, valid and reliable tool for assessing pediatric SLE specific HRQOL. It will be useful in providing better care, understanding and may offer critical information regarding the effect of SLE in the quality of life of our pediatric lupus patients. It will help physician understands the needs of their patient not only on treatment of the specific disease but as well as the impact of the treatment on their daily lives.

Keywords: systemic lupus erythematosus, pediatrics, quality of life, Simple Measure of Impact of Lupus Erythematosus in Youngsters (SMILEY)

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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

Abstract:

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: Zeinab Haji Abolhasani, Romeo Marian, Lee Luong

Abstract:

This paper and its companions (Part II, Part III) will concentrate on optimizing a class of supply chain problems known as Multi- Commodities Consumer Supply Chain (MCCSC) problem. MCCSC problem belongs to production-distribution (P-D) planning category. It aims to determine facilities location, consumers’ allocation, and facilities configuration to minimize total cost (CT) of the entire network. These facilities can be manufacturer units (MUs), distribution centres (DCs), and retailers/end-users (REs) but not limited to them. To address this problem, three major tasks should be undertaken. At the first place, a mixed integer non-linear programming (MINP) mathematical model is developed. Then, system’s behaviors under different conditions will be observed using a simulation modeling tool. Finally, the most optimum solution (minimum CT) of the system will be obtained using a multi-objective optimization technique. Due to the large size of the problem, and the uncertainties in finding the most optimum solution, integration of modeling and simulation methodologies is proposed followed by developing new approach known as GASG. It is a genetic algorithm on the basis of granular simulation which is the subject of the methodology of this research. In part II, MCCSC is simulated using discrete-event simulation (DES) device within an integrated environment of SimEvents and Simulink of MATLAB® software package followed by a comprehensive case study to examine the given strategy. Also, the effect of genetic operators on the obtained optimal/near optimal solution by the simulation model will be discussed in part III.

Keywords: supply chain, genetic algorithm, optimization, simulation, discrete event system

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

Abstract:

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: Gautier Girard, Marion Martiny, Sebastien Mercier, Mohamad Jrad, Mohamed-Slim Bahi, Laurent Bodin, Francois Lechleiter, David Nevo, Sophie Dareys

Abstract:

Reliability of electronic devices has always been of highest interest for Aero-MIL and space applications. In any electronic device, Printed Circuit Board (PCB), providing interconnection between components, is a key for reliability. During the last decades, PCB technologies evolved to sustain and/or fulfill increased original equipment manufacturers requirements and specifications, higher densities and better performances, faster time to market and longer lifetime, newer material and mixed buildups. From the very beginning of the PCB industry up to recently, qualification, experiments and trials, and errors were the most popular methods to assess system (PCB) reliability. Nowadays OEM, PCB manufacturers and scientists are working together in a close relationship in order to develop predictive models for PCB reliability and lifetime. To achieve that goal, it is fundamental to characterize precisely base materials (laminates, electrolytic copper, …), in order to understand failure mechanisms and simulate PCB aging under environmental constraints by means of finite element method for example. The laminates are woven composites and have thus an orthotropic behaviour. The in-plane properties can be measured by combining classical uniaxial testing and digital image correlation. Nevertheless, the out-of-plane properties cannot be evaluated due to the thickness of the laminate (a few hundred of microns). It has to be noted that the knowledge of the out-of-plane properties is fundamental to investigate the lifetime of high density printed circuit boards. A homogenization method combining analytical and numerical approaches has been developed in order to obtain the complete elastic orthotropic behaviour of a woven composite from its precise 3D internal structure and its experimentally measured in-plane elastic properties. Since the mechanical properties of the resin surrounding the fibres are unknown, an inverse method is proposed to estimate it. The methodology has been applied to one laminate used in hyperfrequency spatial applications in order to get its elastic orthotropic behaviour at different temperatures in the range [-55°C; +125°C]. Next; numerical simulations of a plated through hole in a double sided PCB are performed. Results show the major importance of the out-of-plane properties and the temperature dependency of these properties on the lifetime of a printed circuit board. Acknowledgements—The support of the French ANR agency through the Labcom program ANR-14-LAB7-0003-01, support of CNES, Thales Alenia Space and Cimulec is acknowledged.

Keywords: homogenization, orthotropic behaviour, printed circuit board, woven composites

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

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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

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Authors: Jafar Mortadha, Imran Qureshi

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This research explains and compares the modern techniques used for measuring the flow angles of a flowing fluid with the traditional technique of using multi-hole pressure probes. In particular, the focus of the study is on four-hole probes, which offer great reliability and benefits in several applications where the use of modern measurement techniques is either inconvenient or impractical. Due to modern advancements in manufacturing, small multi-hole pressure probes can be made with high precision, which eliminates the need for calibrating every manufactured probe. This study aims to improve the range of calibration maps for a four-hole probe to allow high flow angles to be measured accurately. The research methodology comprises a literature review of the successful calibration definitions that have been implemented on five-hole probes. These definitions are then adapted and applied on a four-hole probe using a set of raw pressures data. A comparison of the different definitions will be carried out in Matlab and the results will be analyzed to determine the best calibration definition. Taking simplicity of implementation into account as well as the reliability of flow angles estimation, an adapted technique from a research paper written in 2002 offered the most promising outcome. Consequently, the method is seen as a good enhancement for four-hole probes and it can substitute for the existing calibration definitions that offer less accuracy.

Keywords: calibration definitions, calibration maps, flow measurement techniques, four-hole probes, multi-hole pressure probes

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Authors: Adzongo Philomena Ibuh, Aloga O. Austin

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The purpose of the study was to examine lifelong education for teachers as a tool for achieving effective teaching and learning. Lifelong education enhances social inclusion, personal development, citizenship, employability, teaching and learning, community and the nation, and the challenges of lifelong education were also discussed. Descriptive survey design was adopted for the study. A simple random sampling technique was used to select 80 teachers as sample from a population of 105 senior secondary school teachers in Makurdi local government area of Benue state. A 20-item self designed questionnaire subjected to expert validation and reliability was used to collect data. The reliability Alpha coefficient of 0.87 was established using Crombach Alpha technique, mean scores and standard deviation were used to answer the 2 research questions while chi-square was used to analyze data for the 2 hypotheses. The findings of the study revealed that, lifelong education for teachers can be used to achieve as a tool for achieving effective teaching and learning, and the study recommended among others that government, organizations and individuals should in collaboration put lifelong education programmes for teachers on the priority list. The paper concluded that the strategic position of lifelong education for teachers towards enhanced teaching and learning makes it imperative for all hands to be on deck to support the programme financially and otherwise.

Keywords: effective teaching and learning, lifelong education, teachers, tool

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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 374