Search results for: maximum clique problem

Authors: Ahmed Al-Adaileh

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Renewable energy sources, domestic storage systems, controllable loads and machine learning technologies will be key components of future smart homes management systems. An energy management scheme that uses a Deep Learning (DL) approach to support the smart home management systems, which consist of a standalone photovoltaic system, storage unit, heating ventilation air-conditioning system and a set of conventional and smart appliances, is presented. The objective of the proposed scheme is to apply DL-based machine learning to predict various running parameters within a smart home's environment to achieve maximum comfort levels for occupants, reduced electricity bills, and less dependency on the public grid. The problem is using Reinforcement learning, where decisions are taken based on applying the Continuous-time Markov Decision Process. The main contribution of this research is the proposed framework that applies DL to enhance the system's supervised dataset to offer unlimited chances to effectively support smart home systems. A case study involving a set of conventional and smart appliances with dedicated processing units in an inhabited building can demonstrate the validity of the proposed framework. A visualization graph can show "before" and "after" results.

Keywords: smart homes systems, machine learning, deep learning, Markov Decision Process

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Authors: Mohamed E. Abdelrahamn, Mahmoud Aly Hassan, Mohamed Sarhan

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Subacromial impingement syndrome (SIS) is a common shoulder disorder. Patients often complain from a decrease in electromyography (EMG) activity of the rotator cuff muscles especially the supraspinatus muscle during glenohumeral elevation. Objective: The purpose of the study is to assess the effect of applying 50% of maximum voluntary contraction of hand grip strength on the EMG activity of the shoulder muscles in patients with SIS. Methods: Thirty male and female patients participated in this study. Their ages ranged from 25 to 40 years. EMG activity of supraspinatus muscle and middle deltoid muscle was assessed without and with applying 50% of maximum voluntary contraction (MVC). Results: A significant difference was found for both supraspinatus and middle deltoid muscles, indicating that the gripping resulted in increasing muscle activity. Conclusion: Applying 50% MVC of hand grip strength could increase the supraspinatus and middle deltoid muscles activity in patients of SIS. This might be useful in the development and monitoring of shoulder rehabilitation strategies.

Keywords: electromyography, supraspinatus muscle, deltoid muscle, subacromial impingement syndrome

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Authors: Shun Horikoshi, Tohru Kawabe

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This study presents performance analysis results of SMC (Sliding mode control) with changing the chattering functions applied to slip suppression problem of electric vehicles (EVs). In SMC, chattering phenomenon always occurs through high frequency switching of the control inputs. It is undesirable phenomenon and degrade the control performance, since it causes the oscillations of the control inputs. Several studies have been conducted on this problem by introducing some general saturation function. However, study about whether saturation function was really best and the performance analysis when using the other functions, weren’t being done so much. Therefore, in this paper, several candidate functions for SMC are selected and control performance of candidate functions is analyzed. In the analysis, evaluation function based on the trade-off between slip suppression performance and chattering reduction performance is proposed. The analyses are conducted in several numerical simulations of slip suppression problem of EVs. Then, we can see that there is no difference of employed candidate functions in chattering reduction performance. On the other hand, in slip suppression performance, the saturation function is excellent overall. So, we conclude the saturation function is most suitable for slip suppression sliding mode control.

Keywords: sliding mode control, chattering function, electric vehicle, slip suppression, performance analysis

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Authors: Soumyadeep Bhaduri, Rahul Ghosh, Rahul Shukla, Manaswini Behera

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The textile industry consumes a substantial amount of water throughout the processing and production of textile fabrics. The water eventually turns into wastewater, where it acts as an immense damaging nuisance due to its dye content. Wastewater streams contain a percentage ranging from 2.0% to 50.0% of the total weight of dye used, depending on the dye class. The management of dye effluent in textile industries presents a formidable challenge to global sustainability. The current focus is on implementing wastewater treatment technology that enable the recycling of wastewater, reduce energy usage and offset carbon emissions. Microbial fuel cell (MFC) is a device that utilizes microorganisms as a bio-catalyst to effectively treat wastewater while also producing electricity. The MFC harnesses the chemical energy present in wastewater by oxidizing organic compounds in the anodic chamber and reducing an electron acceptor in the cathodic chamber, thereby generating electricity. This research investigates the potential of MFCs to tackle this challenge of azo dye removal with simultaneously generating electricity. Although MFCs are well-established for wastewater treatment, their application in dye decolorization with concurrent electricity generation remains relatively unexplored. This study aims to address this gap by assessing the effectiveness of MFCs as a sustainable solution for treating wastewater containing azo dyes. By harnessing microorganisms as biocatalysts, MFCs offer a promising avenue for environmentally friendly dye effluent management. The performance of MFCs in treating azo dyes and generating electricity was evaluated by optimizing the Chemical Oxygen Demand (COD) and Hydraulic Retention Time (HRT) of influent. COD and HRT values ranged from 1600 mg/L to 2400 mg/L and 5 to 9 days, respectively. Results showed that the maximum open circuit voltage (OCV) reached 648 mV at a COD of 2400 mg/L and HRT of 5 days. Additionally, maximum COD removal of 98% and maximum color removal of 98.91% were achieved at a COD of 1600 mg/L and HRT of 9 days. Furthermore, the study observed a maximum power density of 19.95 W/m3 at a COD of 2400 mg/L and HRT of 5 days. Electrochemical analysis, including linear sweep voltammetry (LSV), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were done to find out the response current and internal resistance of the system. To optimize pH and dye concentration, pH values were varied from 4 to 10, and dye concentrations ranged from 25 mg/L to 175 mg/L. The highest voltage output of 704 mV was recorded at pH 7, while a dye concentration of 100 mg/L yielded the maximum output of 672 mV. This study demonstrates that MFCs offer an efficient and sustainable solution for treating azo dyes in textile industry wastewater, while concurrently generating electricity. These findings suggest the potential of MFCs to contribute to environmental remediation and sustainable development efforts on a global scale.

Keywords: textile wastewater treatment, microbial fuel cell, renewable energy, sustainable wastewater treatment

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Authors: Jesus Hernandez, Zead Elzoeiry, Md. S. Islam, Abel E. Navarro

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The adsorption of bovine serum albumin (BSA) and human hemoglobin (Hb) on naturally-occurring adsorbents was studied to evaluate the potential recovery of proteins from meat industry residues. Spent peppermint tea (PM), powdered purple corn cob (PC), natural clay (NC) and chemically-modified clay (MC) were investigated to elucidate the effects of pH, adsorbent dose, initial protein concentration, presence of salts and heavy metals. Equilibrium data were fitted according to isotherm models, reporting a maximum adsorption capacity at pH 8 of 318 and 344 mg BSA/g of PM and NC, respectively. Moreover, Hb displayed maximum adsorption capacity at pH 5 of 125 and 143 mg/g of PM and PC, respectively. Hofmeister salt effect was only observed for PM/Hb system. Salts tend to decrease protein adsorption, and the presence of Cu(II) ions had negligible impacts on the adsorption onto NC and PC. Desorption experiments confirmed that more than 85% of both proteins can be recovered with diluted acids and bases. SEM, EDX, and TGA analyses demonstrated that the adsorbents have favorable morphological and mechanical properties. The long-term goal of this study aims to recover soluble proteins from industrial wastewaters to produce animal food or any protein-based product.

Keywords: adsorption, albumin, clay, hemoglobin, spent peppermint leaf

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Authors: Rama Bhattacharyya, S. N. Ojha, Umesh K. Singh

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Anthropogenic control on groundwater chemistry has emerged as a critical concern now-a-days, especially in the industrial areas. In view of this, a comprehensive study on the distribution of the heavy metal in the groundwater was conducted to investigate the impact of urbanization in the aquatic media. Water samples either from well or borehole from Fourty different sites in and around, Durgapur, West Bengal were collected for this purpose. The samples were analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) for Calcium (Ca), Cobalt (Co), Chromium (Cr), Copper (Cu), Iron (Fe), Potassium (K), Magnesium (Mg), Manganese (Mn), Sodium (Na), Nickel (Ni), Lead (Pb), Zinc (Zn) content and the levels were compared with WHO specified maximum contaminant level as well as permissible limits given by the Bureau of Indian Standards (BIS). The result obtained from the present study indicates a significant risk to the population of this important emerging ‘smart city’ of eastern India. Because of the toxicity of these metals and the fact that for many tube-wells, dug-wells and bore-wells are the only sources of the water supply for a major fraction of the population in this environment. In this study, an attempt has been made to develop metal contamination risk map.

Keywords: heavy metals, ground water, maximum contamination level, ICP-MS

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Authors: Kalimullah Khan, Samina Roohi, Mohammad Rafi, Rizwana Zahoor

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Labeling of 5-Aminolevulinic acid (5-ALA) with 99 mTc was achieved by using tin chloride dihydrate (Sncl2.2H2O) as reducing agent. Radiochemical purity and labeling efficiency was determined by Whattman paper No.3 and instant thin layer chromatographic strips impregnated with silica gel (ITLC/SG). Labeling efficiency was dependent on many parameters such as amount of ligand, reducing agent, pH, and incubation time. Therefore, optimum conditions for maximum labeling were selected. Stability of 99 mTc- 5-ALA was also checked in fresh human serum. Tissue bio-distribution of 99 mTc-5-ALA was evaluated in Spargue Dawley rats. 5-ALA was 98% labeled with 99 mTc under optimum conditions, i.e. 100µg of 5-ALA, pH: 4, 10µg of Sncl2.2H2O and 30 minutes incubation at room temperature. 99 mTc labelled 5- ALA remained stable for 24 hours in human serum. Bio-distribution study (%ID/gm) in rats revealed that maximum accumulation of 99 mTc-5-ALA was in liver, spleen, stomach and intestine after half hour, 4 hours, and 24 hours. Significant activity in bladder and urine indicated urinary mode of excretion.

Keywords: 99mTc-ALA, aminolevulinic acid, quality control, radiopharmaceuticals

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Authors: Rajesh Singh, Kailash Kale

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In this paper, the Binomial process type occurrence of software failures is considered and failure intensity has been characterized by one parameter Rayleigh class Software Reliability Growth Model (SRGM). The proposed SRGM is mathematical function of parameters namely; total number of failures i.e. η-0 and scale parameter i.e. η-1. It is assumed that very little or no information is available about both these parameters and then considering non-informative priors for both these parameters, the Bayes estimators for the parameters η-0 and η-1 have been obtained under square error loss function. The proposed Bayes estimators are compared with their corresponding maximum likelihood estimators on the basis of risk efficiencies obtained by Monte Carlo simulation technique. It is concluded that both the proposed Bayes estimators of total number of failures and scale parameter perform well for proper choice of execution time.

Keywords: binomial process, non-informative prior, maximum likelihood estimator (MLE), rayleigh class, software reliability growth model (SRGM)

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Authors: Abdulrahman Alenezi

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This research paper investigates the surface heat transfer characteristics using computational fluid dynamics for orthogonal and inclined impinging jet. A jet Reynolds number (Rₑ) of 10,000, jet-to- plate spacing (H/D) of two and eight and two angles of impingement (α) of 45° and 90° (orthogonal) were employed in this study. An unconfined jet impinges steadily a constant temperature flat surface using air as working fluid. The numerical investigation is validated with an experimental study. This numerical study employs grid dependency investigation and four different types of turbulence models including the transition SSD to accurately predict the second local maximum in Nusselt number. A full analysis of the effect of both turbulence models and mesh size is reported. Numerical values showed excellent agreement with the experimental data for the case of orthogonal impingement. For the case of H/D =6 and α=45° a maximum percentage error of approximately 8.8% occurs of local Nusselt number at stagnation point. Experimental and numerical correlations are presented for four different cases

Keywords: turbulence model, inclined jet impingement, single jet impingement, heat transfer, stagnation point

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Authors: Jean Berger, Nassirou Lo, Martin Noel

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Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.

Keywords: search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization

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Authors: Svenja Pieritz, Jakab Pilaszanovich

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Collaborative Problem Solving (CPS) is recognized as being one of the most important skills of the 21st century with having a potential impact on education, job selection, and collaborative systems design. Therefore, CPS has been adopted in several standardized tests, including the Programme for International Student Assessment (PISA) in 2015. A significant challenge of evaluating CPS is the underlying interplay of cognitive and social skills, which requires a more holistic assessment. However, the majority of the existing tests are using a questionnaire-based assessment, which oversimplifies this interplay and undermines ecological validity. Two major difficulties were identified: Firstly, the creation of a controllable, real-time environment allowing natural behaviors and communication between at least two people. Secondly, the development of an appropriate method to collect and synthesize both cognitive and social metrics of collaboration. This paper proposes a more holistic and automated approach to the assessment of CPS. To address these two difficulties, a multiplayer problem-solving game called Sea of Light was developed: An environment allowing students to deploy a variety of measurable collaborative strategies. This controlled environment enables researchers to monitor behavior through the analysis of game actions and chat. The according solution for the statistical model is a combined approach of Natural Language Processing (NLP) and Bayesian network analysis. Social exchanges via the in-game chat are analyzed through NLP and fed into the Bayesian network along with other game actions. This Bayesian network synthesizes evidence to track and update different subdimensions of CPS. Major findings focus on the correlations between the evidences collected through in- game actions, the participants’ chat features and the CPS self- evaluation metrics. These results give an indication of which game mechanics can best describe CPS evaluation. Overall, Sea of Light gives test administrators control over different problem-solving scenarios and difficulties while keeping the student engaged. It enables a more complete assessment based on complex, socio-cognitive information on actions and communication. This tool permits further investigations of the effects of group constellations and personality in collaborative problem-solving.

Keywords: bayesian network, collaborative problem solving, game-based assessment, natural language processing

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Authors: Amin Rezazadeh, Parisa Farahpour, Arezoo Rezazadeh, Morteza Sam Deliri

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In order to investigate the effects of nitrogen and compost different levels on qualitative and quantitative performance of Calendula officinalis L. herb, an experiment was carried out in the research field of Chalous Azad University in 2011-2012. The experiment was done in factorial form as a randomized complete block design, in three replicates. Treatments consisted of nitrogen and compost. Considered nitrogen levels consisted of N0=0, N1=50, N2=100 kg/ha and compost levels were including C0=0, C1=6, C2=12 ton/ha. Investigated characteristics consisted of flower dry weight, number of flowers in plant, flower diameter. The results showed, nitrogen and compost treatments had statistically significant influence (p ≤ 0.01) on studied characteristics. Flower dry weight, flower diameter and number of flower in plant characteristics has been studied in four harvest; as, the performance of these characteristics had increasing procedure from the first harvest up to the forth harvest; and, in the fourth harvest, it has reached to its` maximum level. As, up to the forth harvest, the maximum flower dry weight, flower diameter and number of flower in plant obtained by C1× N2 (C1=6 ton/ha compost and N2=100 kg/ha nitrogen) treatment.

Keywords: calendula, compost, nitrogen, flavonoid

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Authors: Juan Sepúlveda

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Energy is a fundamental component in sustainability, the access and use of this resource is related with economic growth, social improvements, and environmental impacts. In this sense, energy efficiency has been studied as a factor that enhances the positive impacts of energy in communities; however, the implementation of efficiency requires strong policy and strategies that usually rely on individual measures focused in independent dimensions. In this paper, the problem of energy efficiency as a multi-objective problem is studied, using scientometric analysis to discover trends and patterns that allow to identify the main variables and study approximations related with a further development of models to integrate energy efficiency and MCA into policy making for small communities.

Keywords: energy efficiency, MCA, scientometric, trends

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Authors: Luciana Abednego, Cecilia Nugraheni

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There are many approaches proposed for solving Sudoku puzzles. One of them is by modelling the puzzles as block world problems. There have been three model for Sudoku solvers based on this approach. Each model expresses Sudoku solver as a parameterized multi agent systems. In this work, we propose a new model which is an improvement over the existing models. This paper presents the development of a Sudoku solver that implements all the proposed models. Some experiments have been conducted to determine the performance of each model.

Keywords: Sudoku puzzle, Sudoku solver, block world problem, parameterized multi agent systems

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Authors: Zeinab Haji Abolhasani, Romeo Marian, Lee Luong

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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: Kazam Ali, Muhammad Sagheer, Mansoor-Ul- Hasan, Abdul Rashid, Chaudhary Muhammad Shahid Hanif, Fawad Zafar Ahmad Khan, Hafiz Muhammad Aatif

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Natural extracts of two medicinal plants Nicotiana tabacum and Eucalyptus globulus were tested for their toxic and enzyme inhibition effects against three insects species of stored grains Tribolium castaneum, Trogoderma granarium and Sitophilus granarius. Responses of insects varied with exposure periods and dilution levels of acetone extracts of plants. Both plant extracts were lethal to insects but the crude leaf extract of N. tabacum evidenced strong toxic action against three tested insect species. Maximum mortality 36.30% in S. granarius, 25.96% in T. castaneum, and 21.88% in T. granarium were found at 20% dilution level, after 10 days exposure to botanical extract of N. tabacum. The impact of N. tabacum and E. globulus on the activity of esterases; acetylcholinesterase (AChE), α-carboxylesterase (α-CE), β-carboxylesterase (β-CE) and phosphatses; acid phosphatase (AcP), alkaline phosphatase (AlP) of three stored grain insect species were also studied in the survivors of toxicity assay. Whole body homogenates of insects were used for enzyme determination and consumption of high dose rate N. tabacum extract containing diet resulted in maximum 55.33% inhibition of AChE and 26.17% AlP inhibition in T. castaneum, while 44.17% of α-CE and 31.67% inhibition of β-CE activity were noted in S. granarius. Maximum inhibition 23.44% of AcP activity was found in T. granarium exposed to diet treated with the extract of E. globulus. The findings indicate that acetone extracts of N. tabacum and E. globulus are naturally occurring pesticide and facts of the enzyme inhibition relations specify that their effect changes with the insect species.

Keywords: natural extract, medicinal plant, toxic effects, enzyme inhibition, acetone extract

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Authors: A. Y. Mukhtar, J. B. Munyakazi, R. Ouifki

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Over the past few decades, the unprecedented increase in mobility has raised considerable concern about the relationship between mobility and vector-borne diseases and malaria in particular. Thus, one can claim that human mobility is one of the contributing factors to the resurgence of malaria. To assess human mobility on malaria burden among hosts, we formulate a movement-based model on a network of patches. We then extend human multi-group SEIAR deterministic epidemic models into a system of stochastic differential equations (SDEs). Our quantitative stochastic model which is expressed in terms of average rates of movement between compartments is fitted to time-series data (weekly malaria data of 2011 for each patch) using the maximum likelihood approach. Using the metapopulation (multi-group) model, we compute and analyze the basic reproduction number. The result shows that human movement is sufficient to preserve malaria disease firmness in the patches with the low transmission. With these results, we concluded that the sensitivity of malaria to the human mobility is turning to be greatly important over the implications of future malaria control in South Sudan.

Keywords: basic reproduction number, malaria, maximum likelihood, movement, stochastic model

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Authors: Qazi Salman Khalid, Muhammad Khalid, Shahid Maqsood

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This paper presents a solution for optimizing the cycle time in an assembly line with human-robot collaboration and diverse operators. A genetic algorithm with tailored parameters is used to address the assembly line balancing problem in the automobile sector. A mathematical model is developed, depicting the problem. Currently, the firm runs on the largest candidate rule; however, it causes a lag in orders, which ultimately gets penalized. The results of the study show that the proposed GA is effective in providing efficient solutions and that the cycle time has significantly impacted productivity.

Keywords: line balancing, cycle time, genetic algorithm, productivity

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Authors: Sopheak Sorn, Kwok Yip Szeto

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Reliability is one of the important measures of how well the system meets its design objective, and mathematically is the probability that a complex system will perform satisfactorily. When the system is described by a network of N components (nodes) and their L connection (links), the reliability of the system becomes a network design problem that is an NP-hard combinatorial optimization problem. In this paper, we address the network design problem for a random point set’s pattern in two dimensions. We make use of a Voronoi construction with each cell containing exactly one point in the point pattern and compute the reliability of the Voronoi’s dual, i.e. the Delaunay graph. We further investigate the communicability of the Delaunay network. We find that there is a positive correlation and a negative correlation between the homogeneity of a Delaunay's degree distribution with its reliability and its communicability respectively. Based on the correlations, we alter the communicability and the reliability by performing random edge flips, which preserve the number of links and nodes in the network but can increase the communicability in a Delaunay network at the cost of its reliability. This transformation is later used to optimize a Delaunay network with the optimum geometric mean between communicability and reliability. We also discuss the importance of the edge flips in the evolution of real soap froth in two dimensions.

Keywords: Communicability, Delaunay triangulation, Edge Flip, Reliability, Two dimensional network, Voronio

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Authors: Mohammad Alshawaf, Rahmat Poudineh, Nawaf Alhajeri

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The power generated from photovoltaic (PV) modules is non-dispatchable on demand due to the stochastic nature of solar radiation. The random variations in the measured intensity of solar irradiance are due to clouds and, in the case of arid regions, dust storms which decrease the intensity of intensity of solar irradiance. Therefore, modeling PV power output using average, maximum, or minimum solar irradiance values is inefficient to predict power generation reliably. The overall objective of this paper is to predict the power output of PV modules using Monte Carlo approach based the weather and solar conditions measured in Kuwait. Given the 250 Wp PV module used in study, the average daily power output is 1021 Wh/day. The maximum power was generated in April and the minimum power was generated in January 1187 Wh/day and 823 Wh/day respectively. The certainty of the daily predictions varies seasonally and according to the weather conditions. The output predictions were far more certain in the summer months, for example, the 80% certainty range for August is 89 Wh/day, whereas the 80% certainty range for April is 250 Wh/day.

Keywords: Monte Carlo, solar energy, variable renewable energy, Kuwait

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Authors: Tae Gwan Kim, Hyun Kyu Cho, Young Hoon Lee, Young Chul Park

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Foam monitors are devices that are installed on cargo tank decks to suppress cargo area fires in oil tankers or hazardous chemical ship cargo ships. In general, the main design parameter of the foam monitor is the distance of the projection through the foam monitor. In this study, the relationship between flow characteristics and projection distance, depending on the shape was examined. Numerical techniques for fluid analysis of foam monitors have been developed for prediction. The flow pattern of the fluid varies depending on the shape of the flow path of the foam monitor, as the flow losses affecting projection distance were calculated through numerical analysis. The basic shape of the foam monitor was an L shape designed by N Company. The modified model increased the length of the flow path and used the S shape model. The calculation result shows that the L shape, which is the basic shape, has a problem that the force is directed to one side and the vibration and noise are generated there. In order to solve the problem, S-shaped model, which is a change model, was used. As a result, the problem is solved, and the projection distance from the nozzle is improved.

Keywords: CFD, foam monitor, projection distance, moment

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Authors: Mithlesh Chourase

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Health of the transgender is as important as any other population sub-groups. However, little is known about the issues of mental health problems and health seeking behaviour of transgender in India. This paper examines the depression, stigma problem and suicidality (risk of suicide) among the transgender people in Mumbai city. The study used the primary survey data conducted in Mumbai city among the transgender community with a total sample of 120 among the transgender. Both qualitative and quantitative data was collected on demographic and socio-economic characteristic, general health and sexual health problems, mental health and health seeking behaviour among transgender. The quantitative results revealed that among the transgender, the prevalence of depression was very high. In this community 58.3% and 45.8 % of the transgender were suffered from depression and stigma problem respectively. On the other hand 42% and 48% of the transgender attempted suicide and experienced discrimination in the society. The qualitative results also revealed that the transgender were suffered from physical violence especially due to being a transgender, stressed due to being a transgender, experienced discrimination everywhere, experienced sexual health problems especially HIV, partner problem etc. As a result the prevalence of depression, self-harm attempt and suicidal attempt was common among this community.

Keywords: transgender, depression, Mumbai, mental health

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Authors: Javad Sadoghi Yazdi, Robb Eric S. Moss

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This paper utilizes a probabilistic liquefaction triggering method for modeling post-liquefaction ground deformation. This cone penetration test CPT-based liquefaction triggering is employed to estimate the factor of safety against liquefaction (FSL) and compute the maximum cyclic shear strain (γmax). The study identifies a maximum PL value of 90% across various relative densities, which challenges the decrease from 90% to 70% as relative density decreases. It reveals that PL ranges from 5% to 50% for volumetric strain (εvol) less than 1%, while for εvol values between 1% and 3.2%, PL spans from 50% to 90%. The application of the CPT-based simplified liquefaction triggering procedures has been employed in previous researches to estimate liquefaction ground-failure indices, such as the Liquefaction Potential Index (LPI) and Liquefaction Severity Number (LSN). However, several studies have been conducted to highlight the variability in liquefaction probability calculations, suggesting a more accurate depiction of liquefaction likelihood. Consequently, the utilization of these simplified methods may not offer practical efficiency. This paper further investigates the efficacy of various established liquefaction vulnerability parameters, including LPI and LSN, in explaining the observed liquefaction-induced damage within residential zones of Christchurch, New Zealand using results from CPT database.

Keywords: cone penetration test (CPT), liquefaction, postliquefaction, ground failure

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Authors: Neslihan Sahin Celik, Ali Eraslan

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As a result of PISA (Program for International Student Assessments) survey that tests how well students can apply the knowledge and skills they have learned at school to real-life challenges, the new and redesigned mathematics education programs in many countries emphasize the necessity for the students to face complex and multifaceted problem situations and gain experience in this sense allowing them to develop new skills and mathematical thinking to prepare them for their future life after school. At this point, mathematical models and modeling approaches can be utilized in the analysis of complex problems which represent real-life situations in which students can actively participate. In particular, model eliciting activities that bring about situations which allow the students to create solutions to problems and which involve mathematical modeling must be used right from primary school years, allowing them to face such complex, real-life situations from early childhood period. A qualitative study was conducted in a university foundation primary school in the city center of a big province in 2013-2014 academic years. The participants were 4th grade students in a primary school. After a four-week preliminary study applied to a fourth-grade classroom, three students included in the focus group were selected using criterion sampling technique. A focus group of three students was videotaped as they worked on the Crime Problem. The conversation of the group was transcribed, examined with students’ written work and then analyzed through the lens of Blum and Ferri’s modeling processing cycle. The results showed that primary fourth-grade students can successfully work with model eliciting problem while they encounter some difficulties in the modeling processes. In particular, they developed new ideas based on different assumptions, identified the patterns among variables and established a variety of models. On the other hand, they had trouble focusing on problems and occasionally had breaks in the process.

Keywords: primary school, modeling, mathematical modeling, crime problem

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Authors: Tigmanshu Bhatnagar, Petra Badke-Schaub

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Facilitating Design Thinking (DT) and Creative Problem Solving (CPS) in engineering education could benefit students by aiding them to think creatively and meaningfully in their education and future profession. A study in the pseudonym of a ‘popup class’ was conducted for a week at the Indian Institute of Technology, Delhi (IITD) to have an indication for the perceived relevance, benefits and challenges of DT and CPS from the perspective of engineering students in India. 30 third year Bachelor of Technology students from various technical fields participated in the study. They were introduced to the notion of DT and CPS via a mix of theoretical lectures, case discussions and practical workshops. Their reactions were identified on the basis of silent observations made during the course and responses were recorded through a questionnaire, which was filled after the course. All the respondents felt that DT and CPS are relevant to their education. It was perceived by them that there is a subtle improvement in the quality, quantity and approach of solutions to open ended problems. 90% responded positively to the induction of such an exercise in their education and reasoned it by stating that it’s important for engineers to know, how to solve open-ended real world problems in a meaningful and innovative way.

Keywords: creative problem solving, design thinking, India, undergraduate engineering education

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Authors: Kuei-Ling Sun, Emily Chia-Yu Su

Abstract:

Allergy is a hypersensitive overreaction of the immune system to environmental stimuli, and a major health problem. These overreactions include rashes, sneezing, fever, food allergies, anaphylaxis, asthmatic, shock, or other abnormal conditions. Allergies can be caused by food, insect stings, pollen, animal wool, and other allergens. Their development of allergies is due to both genetic and environmental factors. Allergies involve immunoglobulin E antibodies, a part of the body’s immune system. Immunoglobulin E antibodies will bind to an allergen and then transfer to a receptor on mast cells or basophils triggering the release of inflammatory chemicals such as histamine. Based on the increasingly serious problem of environmental change, changes in lifestyle, air pollution problem, and other factors, in this study, we both collect allergens and non-allergens from several databases and use several machine learning methods for classification, including logistic regression (LR), stepwise regression, decision tree (DT) and neural networks (NN) to do the model comparison and determine the permutations of allergen amino acid’s sequence.

Keywords: allergy, classification, decision tree, logistic regression, machine learning

Procedia PDF Downloads 302

Authors: M. Mashiur Rahman, Ulrik Birk Henriksen, Jesper Ahrenfeldt, Maria Puig Arnavat

Abstract:

Using biomass gasification to make producer gas is one of the promising sustainable energy options available for small scale plant and rural applications for power and electricity. Tar content in producer gas is the main problem if it is used directly as a fuel. A low-tar biomass (LTB) gasifier of approximately 30 kW capacity has been developed to solve this. Moving bed gasifier with internal recirculation of pyrolysis gas has been the basic principle of the LTB gasifier. The gasifier focuses on the concept of mixing the pyrolysis gases with gasifying air and burning the mixture in separate combustion chamber. Five tests were carried out with the use of wood pellets and wood chips separately, with moisture content of 9-34%. The LTB gasifier offers excellent opportunities for handling extremely low-tar in the producer gas. The gasifiers producer gas had an extremely low tar content of 21.2 mg/Nm³ (avg.) and an average lower heating value (LHV) of 4.69 MJ/Nm³. Tar content found in different tests in the ranges of 10.6-29.8 mg/Nm³. This low tar content makes the producer gas suitable for direct use in internal combustion engine. Using mass and energy balances, the average gasifier capacity and cold gas efficiency (CGE) observed 23.1 kW and 82.7% for wood chips, and 33.1 kW and 60.5% for wood pellets, respectively. Average heat loss in term of higher heating value (HHV) observed 3.2% of thermal input for wood chips and 1% for wood pellets, where heat loss was found 1% of thermal input in term of enthalpy. Thus, the LTB gasifier performs better compared to typical gasifiers in term of heat loss. Equivalence ratio (ER) in the range of 0.29 to 0.41 gives better performance in terms of heating value and CGE. The specific gas production yields at the above ER range were in the range of 2.1-3.2 Nm³/kg. Heating value and CGE changes proportionally with the producer gas yield. The average gas compositions (H₂-19%, CO-19%, CO₂-10%, CH₄-0.7% and N₂-51%) obtained for wood chips are higher than the typical producer gas composition. Again, the temperature profile of the LTB gasifier observed relatively low temperature compared to typical moving bed gasifier. The average partial oxidation zone temperature of 970°C observed for wood chips. The use of separate combustor in the partial oxidation zone substantially lowers the bed temperature to 750°C. During the test, the engine was started and operated completely with the producer gas. The engine operated well on the produced gas, and no deposits were observed in the engine afterwards. Part of the producer gas flow was used for engine operation, and corresponding electrical power was found to be 1.5 kW continuously, and maximum power of 2.5 kW was also observed, while maximum generator capacity is 3 kW. A thermodynamic equilibrium model is good agreement with the experimental results and correctly predicts the equilibrium bed temperature, gas composition, LHV of the producer gas and ER with the experimental data, when the heat loss of 4% of the energy input is considered.

Keywords: biomass gasification, low-tar biomass gasifier, tar elimination, engine, deposits, condensate

Procedia PDF Downloads 114

Authors: Konstantinos Tolidis

Abstract:

The mountains are amongst the most fragile environments in the world. The world’s mountain areas cover 24% of the Earth’s land surface and are home to 12% of the global population. A further 14% of the global population is estimated to live in the vicinity of their surrounding areas. As urbanization continues to increase in the world, the mountains are also key centers for recreation and tourism; their attraction is often heightened by their remarkably high levels of biodiversity. Due to the fact that the features in mountain areas vary spatially (development degree, human geography, socio-economic reality, relations of dependency and interaction with other areas-regions), the spatial planning on these areas consists of a crucial process for preserving the natural, cultural and human environment and consists of one of the major processes of an integrated spatial policy. This research has been focused on the spatial decision problem of land use allocation optimization which is an ordinary planning problem on the mountain areas. It is a matter of fact that such decisions must be made not only on what to do, how much to do, but also on where to do, adding a whole extra class of decision variables to the problem when combined with the consideration of spatial optimization. The utility of optimization as a normative tool for spatial problem is widely recognized. However, it is very difficult for planners to quantify the weights of the objectives especially when these are related to mountain areas. Furthermore, the land use allocation optimization problems at mountain areas must be addressed not only by taking into account the general development objectives but also the spatial objectives (e.g. compactness, compatibility and accessibility, etc). Therefore, the main research’s objective was to approach the land use allocation problem by utilizing a hybrid meta-heuristic optimization technique tailored to the mountain areas’ spatial characteristics. The results indicates that the proposed methodological approach is very promising and useful for both generating land use alternatives for further consideration in land use allocation decision-making and supporting spatial management plans at mountain areas.

Keywords: multiobjective land use allocation, mountain areas, spatial planning, spatial decision making, meta-heuristic methods

Procedia PDF Downloads 345

Authors: Allen A. Espinosa, Larkins A. Trinidad

Abstract:

The present study investigated collegiate students’ problem solving strategies and misconceptions in solving stoichiometric problems and later on formulate a teaching framework from the result of the study. The study found out that the most prominent strategies among students are the mole method and the proportionality method, which are both algorithmic by nature. Misconception was also noted as some students rely on Avogadro’s number in converting between moles. It is suggested therefore that the teaching of stoichiometry should not be confined to demonstration. Students should be involved in the process of thinking of ways to solve the problem.

Keywords: stoichiometry, Svogadro’s number, mole method, proportionality method

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Authors: Mahnaz Hosseinzadeh, Aliyeh Kazemi

Abstract:

In this paper, a method is proposed for solving Fuzzy Multi-Objective Linear Programming problems (FMOLPP) with fuzzy right hand side and fuzzy decision variables. To illustrate the proposed method, it is applied to the problem of selecting suppliers for an automotive parts producer company in Iran in order to find the number of optimal orders allocated to each supplier considering the conflicting objectives. Finally, the obtained results are discussed.

Keywords: fuzzy multi-objective linear programming problems, triangular fuzzy numbers, fuzzy ranking, supplier selection problem

Procedia PDF Downloads 383