Search results for: discrete group search optimizer (DGSO); Travelling salesman problem (TSP); Variable neighborhood search(VNS)

Authors: Sania Sana, Afnan Nasim, Usman Malik, Maroof Tahir

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The aim of this research is to scrutinize the interdependent relationship between terrorism and behavioral changes in the tourism activities in Pakistan with the moderating impact of a unique variable titled 'Financial Risk Tolerance'. The article looks at the inter-reliant relationship with the alleged political and economic aspects and behavioral changes in the tourists and the consumers by these variables over time. The researchers used many underlying theories like the catastrophe theory by (Svyantek, Deshon and Siler 1991), information integration theory (Anderson 1981, 1982) and prospect theory (Kahneman and Tversky 1979) to shape the study’s framework as per tourist decision making model. A sample of around 110 locals was used for this purpose and the data was gathered by convenience sampling. The responses were analyzed using regression analysis. The results exhibited how terrorism along with the influence of financial risk tolerance had inclined a behavioral shift in the travelling patterns and vacation destination choice of the local tourists. Lastly, the paper proposes a number of suggestive measures for the tourism industry and the legislative bodies to ensure the safety of travelers and to boost the tourist activities in the vacation industry of Pakistan.

Keywords: terrorism, tourism, financial risk tolerance, tourist decision-making, destination choice

Procedia PDF Downloads 219

Authors: Markus Pajones, Theresa Steiner, Matthias Neubauer

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Selecting a logistics location is vital for logistics providers, food retailing and other trading companies since the selection poses an essential factor for economic success. Therefore various location search methods like cost-benefit analysis and others are well known and under usage. The development of a logistics location can be related to considerable negative effects for the eco system such as sealing the surface, wrecking of biodiversity or CO2 and noise emissions generated by freight and commuting traffic. The increasing importance of sustainability demands for taking an informed decision when selecting a logistics location for the future. Sustainability considers economic, ecologic and social aspects which should be equally integrated in the process of location search. Objectives of this paper are to define various methods which support the selection of sustainable logistics locations and to generate knowledge about the suitability, assets and limitations of the methods within the selection process. This paper investigates the role of economical, ecological and social aspects when searching for new logistics locations. Thereby, related work targeted towards location search is analyzed with respect to encoded sustainability aspects. In addition, this research aims to gain knowledge on how to include aspects of sustainability and take an informed decision when searching for a logistics location. As a result, a decomposition of the various location search methods in there components leads to a comparative analysis in form of a matrix. The comparison within a matrix enables a transparent overview about the mentioned assets and limitations of the methods and their suitability for selecting sustainable logistics locations. A further result is to generate knowledge on how to combine the separate methods to a new method for a more efficient selection of logistics locations in the context of sustainability. Future work will especially investigate the above mentioned combination of various location search methods. The objective is to develop an innovative instrument, which supports the search for logistics locations with a focus on a balanced sustainability (economy, ecology, social). Because of an ideal selection of logistics locations, induced traffic should be reduced and a mode shift to rail and public transport should be facilitated.

Keywords: commuting traffic, freight traffic, logistics location search, location search method

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Authors: Ramakrishna Rao Mamidi

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It is essential for Surface Mounted Permanent Magnet (SMPM) generators to determine the performance prediction and analyze the magnet’s air gap flux density wave shape. The flux density wave shape is neither a pure sine wave or square wave nor a combination. This is due to the variation of air gap reluctance between the stator and permanent magnets. The stator slot openings and the number of slots make the wave shape highly complicated. To reduce the complexity of analysis, approximations are made to the wave shape using Fourier analysis. In contrast to the traditional integration method, the Fourier coefficients, an and bn, are obtained by direct search method optimization. The wave shape with optimized coefficients gives a wave shape close to the desired wave shape. Harmonics amplitudes are worked out and compared with initial values. It can be concluded that the direct search method can be used for estimating Fourier coefficients for irregular wave shapes.

Keywords: direct search, flux plot, fourier analysis, permanent magnets

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Authors: Mahdi Salarian, Xi Xu, Rashid Ansari

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Accurate localization of mobile devices based on camera-acquired visual media information usually requires a search over a very large GPS-referenced image database. This paper proposes an efficient method for limiting the search space for image retrieval engine by extracting and leveraging additional media information about Estimated Positional Error (EP E) to address complexity and accuracy issues in the search, especially to be used for compensating GPS location inaccuracy in dense urban areas. The improved performance is achieved by up to a hundred-fold reduction in the search area used in available reference methods while providing improved accuracy. To test our procedure we created a database by acquiring Google Street View (GSV) images for down town of Chicago. Other available databases are not suitable for our approach due to lack of EP E for the query images. We tested the procedure using more than 200 query images along with EP E acquired mostly in the densest areas of Chicago with different phones and in different conditions such as low illumination and from under rail tracks. The effectiveness of our approach and the effect of size and sector angle of the search area are discussed and experimental results demonstrate how our proposed method can improve performance just by utilizing a data that is available for mobile systems such as smart phones.

Keywords: localization, retrieval, GPS uncertainty, bag of word

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Authors: Noor Ismael, Lisa Mische Lawson, Lauren Little, Murad Moqbel

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Background/Significance: Caregivers of children with Autism Spectrum Disorders (ASD) develop coping mechanisms to overcome daily challenges to successfully parent their child. There is variability in coping strategies used among caregivers of children with ASD. Capturing homogeneity among such variable groups may help elucidate targeted intervention approaches for caregivers of children with ASD. Study Purpose: This study aimed to identify groups of caregivers of children with ASD based on coping mechanisms, and to examine whether there are differences among these groups in terms of strain level. Methods: This study utilized a secondary data analysis, and included survey responses of 273 caregivers of children with ASD. Measures consisted of the COPE Inventory and the Caregiver Strain Questionnaire. Data analyses consisted of cluster analysis to group caregiver coping strategies, and analysis of variance to compare the caregiver coping groups on strain level. Results: Cluster analysis results showed four distinct groups with different combinations of coping strategies: Social-Supported/Planning (group one), Spontaneous/Reactive (group two), Self-Supporting/Reappraisal (group three), and Religious/Expressive (group four). Caregivers in group one (Social-Supported/Planning) demonstrated significantly higher levels than the remaining three groups in the use of the following coping strategies: planning, use of instrumental social support, and use of emotional social support, relative to the other three groups. Caregivers in group two (Spontaneous/Reactive) used less restraint relative to the other three groups, and less suppression of competing activities relative to the other three groups as coping strategies. Also, group two showed significantly lower levels of religious coping as compared to the other three groups. In contrast to group one, caregivers in group three (Self-Supporting/Reappraisal) demonstrated significantly lower levels of the use of instrumental social support and the use of emotional social support relative to the other three groups. Additionally, caregivers in group three showed more acceptance, positive reinterpretation and growth coping strategies. Caregivers in group four (Religious/Expressive) demonstrated significantly higher levels of religious coping relative to the other three groups and utilized more venting of emotions strategies. Analysis of Variance results showed no significant differences between the four groups on the strain scores. Conclusions: There are four distinct groups with different combinations of coping strategies: Social-Supported/Planning, Spontaneous/Reactive, Self-Supporting/Reappraisal, and Religious/Expressive. Each caregiver group engaged in a combination of coping strategies to overcome the strain of caregiving.

Keywords: autism, caregivers, cluster analysis, coping strategies

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Authors: Ahmed E. Hodaib, Mohamed A. Hashem

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In engineering applications, a design has to be as fully perfect as possible in some defined case. The designer has to overcome many challenges in order to reach the optimal solution to a specific problem. This process is called optimization. Generally, there is always a function called “objective function” that is required to be maximized or minimized by choosing input parameters called “degrees of freedom” within an allowed domain called “search space” and computing the values of the objective function for these input values. It becomes more complex when we have more than one objective for our design. As an example for Multi-Objective Optimization Problem (MOP): A structural design that aims to minimize weight and maximize strength. In such case, the Pareto Optimal Frontier (POF) is used, which is a curve plotting two objective functions for the best cases. At this point, a designer should make a decision to choose the point on the curve. Engineers use algorithms or iterative methods for optimization. In this paper, we will discuss the Evolutionary Algorithms (EA) which are widely used with Multi-objective Optimization Problems due to their robustness, simplicity, suitability to be coupled and to be parallelized. Evolutionary algorithms are developed to guarantee the convergence to an optimal solution. An EA uses mechanisms inspired by Darwinian evolution principles. Technically, they belong to the family of trial and error problem solvers and can be considered global optimization methods with a stochastic optimization character. The optimization is initialized by picking random solutions from the search space and then the solution progresses towards the optimal point by using operators such as Selection, Combination, Cross-over and/or Mutation. These operators are applied to the old solutions “parents” so that new sets of design variables called “children” appear. The process is repeated until the optimal solution to the problem is reached. Reliable and robust computational fluid dynamics solvers are nowadays commonly utilized in the design and analyses of various engineering systems, such as aircraft, turbo-machinery, and auto-motives. Coupling of Computational Fluid Dynamics “CFD” and Multi-Objective Evolutionary Algorithms “MOEA” has become substantial in aerospace engineering applications, such as in aerodynamic shape optimization and advanced turbo-machinery design.

Keywords: mathematical optimization, multi-objective evolutionary algorithms "MOEA", computational fluid dynamics "CFD", aerodynamic shape optimization

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Authors: Ravneil Nand

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Cooperative coevolution uses problem decomposition methods to solve a larger problem. The problem decomposition deals with breaking down the larger problem into a number of smaller sub-problems depending on their method. Different problem decomposition methods have their own strengths and limitations depending on the neural network used and application problem. In this paper we are introducing a new problem decomposition method known as Hidden-Neuron Level Decomposition (HNL). The HNL method is competing with established problem decomposition method in time series prediction. The results show that the proposed approach has improved the results in some benchmark data sets when compared to the standalone method and has competitive results when compared to methods from literature.

Keywords: cooperative coevaluation, feed forward network, problem decomposition, neuron, synapse

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Authors: Arshad Mehmood Ch, Riaz Ahmad, Imran Ali Ch, Waqas Durrani

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This study deals with the application of Ant Colony Optimization (ACO) approach to solve no-wait flowshop scheduling problem (NW-FSSP). ACO algorithm so developed has been coded on Matlab computer application. The paper covers detailed steps to apply ACO and focuses on judging the strength of ACO in relation to other solution techniques previously applied to solve no-wait flowshop problem. The general purpose approach was able to find reasonably accurate solutions for almost all the problems under consideration and was able to handle a fairly large spectrum of problems with far reduced CPU effort. Careful scrutiny of the results reveals that the algorithm presented results better than other approaches like Genetic algorithm and Tabu Search heuristics etc; earlier applied to solve NW-FSSP data sets.

Keywords: no-wait, flowshop, scheduling, ant colony optimization (ACO), makespan

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Authors: A. Ramalho, L. Romeiro, R. Ventura, A. Suleman

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A real-time path planning framework for Unmanned Air Vehicles, and in particular multi-rotors is proposed. The framework is designed to provide feasible trajectories from the current UAV position to a goal state, taking into account constraints such as obstacle avoidance, problem kinematics, and vehicle limitations such as maximum speed and maximum acceleration. The framework computes feasible paths online, allowing to avoid new, unknown, dynamic obstacles without fully re-computing the trajectory. These features are achieved using an iterative process in which the robot computes and optimizes the trajectory while performing the mission objectives. A first trajectory is computed using a modified Rapidly-Exploring Random Tree (RRT) algorithm, that provides trajectories that respect a maximum curvature constraint. The trajectory optimization is accomplished using the Interior Point Optimizer (IPOPT) as a solver. The framework has proven to be able to compute a trajectory and optimize to a locally optimal with computational efficiency making it feasible for real-time operations.

Keywords: interior point optimization, multi-rotors, online path planning, rapidly exploring random trees, trajectory optimization

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Authors: Ibrahim Umar, S Chindo, A Rajab

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Background: TB remains a disease of public health concern in Nigeria with an estimated incidence rate of 219/100,000. Kano has the second highest TB burden in Nigeria and is the leading state with the highest consistent yearly TB notification. House-to-house (H2H) active case search in the community was found to have major contribution to the total TB notification in the state. Aims and Objective: To showcase the impact of H2H community active TB case search (ACF) to yearly TB notification in Kano State, Northern Nigeria from 2012 to 2022. Methodology: This is a retrospective descriptive study based on the analysis of data collected during the routine quarterly and yearly TB data collected in the state. Data was analyzed using the Power BI with statistical alpha level of significance <0.05. Results: Between 2012 and 2013 there was no House-to-house active TB case search in Nigeria and Kano had zero contribution to TB notification from the community in those years. However, in 2014 with the introduction of H2H Active TB Case Search Kano notified 6,014 TB cases out of which 113 came from the community ACF that translated to 2% contribution to total TB notification. From 2014 to 2022 there was progressive increase in community contribution to TB case notification from 113 out of 6,014 total TB patients notified (2012) to 11,799 out of 26,371 TB patients notified (2022) in Kano State. This translated to 45% increase in community contribution to total TB case notification. Discussion: Remarkable increase in community contribution to total TB case notification in Kano State was achieved in 2022 with 11,799 TB cases notified from the community Active TB case search to the total of 26,731 TB cases notified in Kano State, Nigeria. Conclusion: in research has shown that Community-based H2H Active TB Case Search through Community TB Workers (CTWs) is an excellent strategy in finding the missing TB cases towards Ending TB in the world.

Keywords: tuberculosis(TB), active case search (ACF), house-to-house (H2H), community TB workers (CTWs)

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Authors: Muhammad Mukhtar Aliyu

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This study investigated tutors’ experiences and perceptions of a problem-based learning approach (PBL) in a writing classroom. The study involved two Nigerian lecturers who facilitated an intact class of second-year students in an English composition course for the period of 12 weeks. Semi-structured interviews were employed to collect data of the study. The lecturers were interviewed before and after the implementation of the PBL process. The overall findings of the study show that the lecturers had positive perceptions of the use of PBL in a writing classroom. Specifically, the findings reveal the lecturers’ positive experiences and perception of the group activities. Finally, the paper gives some pedagogical implications which would give insight for better implementation of the PBL approach.

Keywords: experiences and perception, Nigeria, problem-based learning approach, writing classroom

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Authors: Raziyeh Shamsi

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In this paper, we present a multiple objective linear programming (MOLP) problem in full fuzzy case and find Data Envelopment Analysis(DEA) targets. In the presented model, we are seeking the least inputs and the most outputs in the production possibility set (PPS) with the variable return to scale (VRS) assumption, so that the efficiency projection is obtained for all decision making units (DMUs). Then, we provide an algorithm for finding DEA targets interactively in the full fuzzy case, which solves the full fuzzy problem without defuzzification. Owing to the use of interactive methods, the targets obtained by our algorithm are more applicable, more realistic, and they are according to the wish of the decision maker. Finally, an application of the algorithm in 21 educational institutions is provided.

Keywords: DEA, MOLP, full fuzzy, target

Procedia PDF Downloads 287

Authors: Moon-Tak Oh, Kyung-Min Park, Tae-Eun Yoon, Hoon Choi, Chil-Woo Lee

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This paper is about middle-ware which enables group-user applications on mobile devices in physical proximity to interact with other devices without intervention of a central server. Requirements of the middle-ware are identified from service usage scenarios, and the functional architecture of the middle-ware is specified. These requirements include group management, synchronization, and resource management. Group Management needs to provide various capabilities to such applications with respect to managing multiple users (e.g., creation of groups, discovery of group or individual users, member join/leave, election of a group manager and service-group association) using D2D communication technology. We designed the middle-ware for the above requirements on the Android platform.

Keywords: group user, middleware, mobile service, physical proximity

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Authors: Xing Lv, Hui-Qin Xu

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The present study aimed to reveal the mechanism in aggravating STZ induced diabetic nephropathy (DN) by AGEs (advanced glycation end products). At the eighth day, 20 diabetic mice were randomly divided into STZ group and combination (combine AGEs with STZ) group. Simultaneously, AGEs group and normal group were set. Only mice in AGEs group, combination group were fed with high-AGEs diets. Mice diabetic conventional indicators, biochemical analysis were measured. Among the indictors, food consumptions, water intake, urine output, blood glucose, urine protein, urine creatinine, serum urea nitrogen were increased significantly in STZ, combination groups. The AGEs levels in combination group increased significantly when compared with STZ group. Weights and insulin levels in the STZ, combination groups were decreased significantly when compared with normal group, and the difference was significantly between AGEs group and STZ group. As a conclusion, AGEs play an important role in the DN development, inducing kidney damages.

Keywords: AGEs, diabetic nephropathy, serum urea nitrogen, urine protein

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Authors: Zhuoran Li, Guan Qin

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A robust and efficient compositional equilibrium characterization model for hydrate-containing systems is required, especially for time-critical simulations such as subsea pipeline flow assurance analysis, compositional simulation in hydrate reservoirs etc. A multiphase flash calculation framework, which combines Gibbs energy minimization function and cubic plus association (CPA) EoS, is developed to describe the highly non-ideal phase behavior of hydrate-containing systems. A non-iterative eigenvalue problem-solving approach for the trust-region sub-problem is selected to guarantee efficiency. The developed flash model is based on the state-of-the-art objective function proposed by Michelsen to minimize the Gibbs energy of the multiphase system. It is conceivable that a hydrate-containing system always contains polar components (such as water and hydrate inhibitors), introducing hydrogen bonds to influence phase behavior. Thus, the cubic plus associating (CPA) EoS is utilized to compute the thermodynamic parameters. The solid solution theory proposed by van der Waals and Platteeuw is applied to represent hydrate phase parameters. The trust-region method combined with the trust-region sub-problem non-iterative eigenvalue problem-solving approach is utilized to ensure fast convergence. The developed multiphase flash model's accuracy performance is validated by three available models (one published and two commercial models). Hundreds of published hydrate-containing system equilibrium experimental data are collected to act as the standard group for the accuracy test. The accuracy comparing results show that our model has superior performances over two models and comparable calculation accuracy to CSMGem. Efficiency performance test also has been carried out. Because the trust-region method can determine the optimization step's direction and size simultaneously, fast solution progress can be obtained. The comparison results show that less iteration number is needed to optimize the objective function by utilizing trust-region methods than applying line search methods. The non-iterative eigenvalue problem approach also performs faster computation speed than the conventional iterative solving algorithm for the trust-region sub-problem, further improving the calculation efficiency. A new thermodynamic framework of the multiphase flash model for the hydrate-containing system has been constructed in this work. Sensitive analysis and numerical experiments have been carried out to prove the accuracy and efficiency of this model. Furthermore, based on the current thermodynamic model in the oil and gas industry, implementing this model is simple.

Keywords: equation of state, hydrates, multiphase equilibrium, trust-region method

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Authors: Ercan Yilmaz, Ali Murat Sünbül

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The aim of the study is to investigate teachers’ self-efficacy with regards to their emotional intelligence. The relational model was used in the study. The participant of the study included 194 teachers from secondary schools in Konya, Turkey. In order to assess teachers’ emotional intelligence, “Trait Emotional Intelligence Questionnaire-short Form was implemented. For teachers’ self-efficacy, “Teachers’ Sense of Self-Efficacy Scale” was used. As a result of the study, a significant relationship is available between teachers’ sense of self-efficacy and their emotional intelligence. Teachers’ emotional intelligence enucleates approximate eighteen percent of the variable in dimension named teachers’ self-efficacy for the students’ involvement. About nineteen percent of the variable in dimension “self-efficacy for teaching strategies is represented through emotional intelligence. Teachers’ emotional intelligence demonstrates about seventeen percent of variable aimed at classroom management.

Keywords: teachers, self-efficacy, emotional intelligence, education

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Authors: A. Baviskar, C. Sandeep, K. Shankar

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Solving Multi-objective Optimization Problems requires faster convergence and better spread. Though existing Evolutionary Algorithms (EA's) are able to achieve this, the computation effort can further be reduced by hybridizing them with innovative strategies. This study is focuses on converging to the pareto front faster while adapting the advantages of Strength Pareto Evolutionary Algorithm-II (SPEA-II) for a better spread. Two different approaches based on optimizing the objective functions independently are implemented. In the first method, the decision variables corresponding to the optima of individual objective functions are strategically used to guide the search towards the pareto front. In the second method, boundary points of the pareto front are calculated and their decision variables are seeded to the initial population. Both the methods are applied to different constrained and unconstrained multi-objective test functions. It is observed that proposed guided search based algorithm gives better convergence and diversity than several well-known existing algorithms (such as NSGA-II and SPEA-II) in considerably less number of iterations.

Keywords: boundary points, evolutionary algorithms (EA's), guided search, strength pareto evolutionary algorithm-II (SPEA-II)

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Authors: Shubeska Stratrova S., Muca A., Panovska S. Clinic of endocrinology, diabetes, metabolic disorders, Medical Faculty, Skopje, N. Macedonia

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Rationale: Obese subjects have a high energy density diet, low physical activity levels, a sedentary lifestyle, as well as eating disorders, which are considered important risk factors for the development of obesity. Methods: In order to discover the imbalance of energy intake and energy expenditure in obese women (W), two groups of examinees answered questionnaires regarding nutrition and physical activity: 1st group of women with normal body mass index (BMI <25 kg/m²) and 2nd group of obese women with BMI >30 kg/m². Results: 61.11% of obese W from the 2nd group reported good appetite, which was higher than the 1st group (45%). In 55.56% W, frustrations were a provocation for over nutrition. In the 2nd group, 38.89% W ate too much compared to 9.09% W from the 1st group. In the ²ⁿᵈ group, 35.29% W reported consuming food rarely and too much, while 29.41% W reported consuming food often and too much. All examinees from the ²ⁿᵈ group had consumed food in less than 5 hours, compared to only 8.33% W from the ¹ⁿᵈ group and had consumed hyper-caloric food. Consumption of fruits and vegetables was lower in the 2nd group compared to the 1st group. Half of the subjects in the 2nd group were physically inactive, compared to only 8% in the 1st group. All of the examinees in the 2nd group walked for less than 3 hours a day, compared to 54% in the 1st group. In the 2nd group, 67% W reported watching TV very often, 39% reported watching TV longer than 3 hours, which is significantly higher than 8.33% W in the 1st group. Overall, 81.25% of examinees from the 2nd group reported sitting for more than 3 hours a day, which is significantly more compared to the 1st group (45.45%). Conclusions: Obese women are less physically active, have a sedentary lifestyle, good appetite, and consume too much hyper-caloric food very often.

Keywords: (W) obese women, BMI(Body mass Index), nutrition, hyper-caloric food

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Authors: Maxat Bokambayev, Bella Tussupova, Aisha Mamyrova, Erlan Izbasarov

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Optimization of business processes in trading companies is reviewed in the report. There is the presentation of the “Wholesale Customer Order Handling Process” business process model applicable for small and medium businesses. It is proposed to apply the algorithm for automation of the customer order processing which will significantly reduce labor costs and time expenditures and increase the profitability of companies. An optimized business process is an element of the information system of accounting of spare parts trading network activity. The considered algorithm may find application in the trading industry as well.

Keywords: business processes, discrete-event simulation, management, trading industry

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Authors: Mukadder Baran, Mustafa Sözbilir

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The purpose of this paper is to investigate the applicabillity of the Context- and Problem-Based Learning (CPBL) in general chemistry course to the subject of “Thermodynamics” but also the influence of CPBL on students’ achievement, retention of knowledge, their interest, attitudes, motivation and problem-solving skills. The study group included 13 freshman students who were selected with the sampling method appropriate to the purpose among those taking the course of General Chemistry within the Program of Medical Laboratory Techniques at Hakkari University. The application was carried out in the Spring Term of the academic year of 2012-2013. As the data collection tool, Lesson Observation form were used. In the light of the observations held, it was revealed that CPBL increased the students’ intragroup and intergroup communication skills as well as their self-confidence and developed their skills in time management, presentation, reporting, and technology use; and that they were able to relate chemistry to daily life. Depending on these findings, it could be suggested that the area of use of CPBL be widened; that seminars related to constructive methods be organized for teachers. In this way, it is believed that students will not be passive in the group any longer. In addition, it was concluded that in order to avoid the negative effects of the socio-cultural structure on the education system, research should be conducted in places where there is socio-cultural obstacles, and appropriate solutions should be suggested and put into practice.

Keywords: chemistry, education, science, context-based learning

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Authors: Rama Ajineh

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Neighborhoods are defined as local zones within settlements and cities recognized by individuals who live there, with their identities and given boundaries. Neighborhoods mainly structure individual’s lives, the small box which various social groups interact with each other, develop and become one strong entity. Also, it is a platform for more activities, providing many of the social services to enhance the connections between the people, giving a sense of community. However, some of these neighborhoods were unplanned and caused many social, economical and architectural problems to its residents in the first place, and to the city. A great example of such case is in Saudi Arabia, Jeddah, Al-Ruwais neighborhood, where the authority is planning to regenerate the area and make it a landmark for the city. Urban Regeneration of Unplanned Settlements is a process to make people live and work, now and in the future, and meet the various needs of the current and coming inhabitants, with a high-quality life for all. Through research, it was discovered that Urban regeneration plans on Al-Ruwais were planned regardless to the collective agreement of the inhabitants, giving themselves the absolute right to demolish and reconstruct the desired locations with a low compensation. Consequently, a deep research will be done on integrating the residents with the process, by showcasing examples of successful Urban Regenerations of Unplanned settlements in different cities. The research aims to understand the sustainable, and well-planned regeneration strategies used to enhance people’s living without harming them, and give sustainable urban solutions. Moreover, the research explores the definition of Sustainable Communities. The used methods in this paper are secondary research on site analysis and the relationship between the human and the neighborhood. The conclusion reveals the most successful fashion of Urban regeneration of Unplanned settlements and applies it to Al-Ruwais neighborhood considering the human factor as a primary element.

Keywords: architecture, human integration, original residents, site analysis, sustainable communities, urban sustainable solutions, urban regeneration

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Authors: Saud Al Taj

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Employer branding is considered as a useful tool for addressing the global-local problem facing complex organisations that have operations scattered across the globe and face challenges of dealing with the local environment alongside. Despite being an established field of study within the Western developed world, there is little empirical evidence concerning the relevance of employer branding to global companies that operate in the under-developed economies. This paper fills this gap by gaining rich insight into the implementation of employer branding programs in a foreign multinational operating in Pakistan dealing with the global-local problem. The study is qualitative in nature and employs semi-structured and focus group interviews with senior/middle managers and local frontline employees to deeply examine the phenomenon in case organisation. Findings suggest that authenticity is required in employer brands to enable them to respond to the local needs thereby leading to the resolution of the global-local problem. However, the role of signaling theory is key to the development of authentic employer brands as it stresses on the need to establish an efficient and effective signaling environment wherein signals travel in both directions (from signal designers to receivers and backwards) and facilitate firms with the global-local problem. The paper also identifies future avenues of research for the employer branding field.

Keywords: authenticity, counter-signals, employer branding, global-local problem, signaling theory

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Authors: Niharika Verma, Sandeep Santosh

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DOA technique is a localization technique used in the communication field. Various algorithms have been developed for direction of arrival estimation like MUSIC, ROOT MUSIC, etc. These algorithms depend on various parameters like antenna array elements, number of snapshots and various others. Basically the MUSIC spectrum is evaluated and peaks obtained are considered as the angle of arrivals. The angles evaluated using this process depends on the scanning interval chosen. The accuracy of the results obtained depends on the coarseness of the interval chosen. In this paper, golden section search is applied to the MUSIC algorithm and therefore, more accurate results are achieved. Initially the coarse DOA estimations is done using the MUSIC algorithm in the range -90 to 90 degree at the interval of 10 degree. After the peaks obtained then fine DOA estimation is done using golden section search. Also, the partitioning method is applied to estimate the number of signals incident on the antenna array. Dependency of the algorithm on the number of snapshots is also being explained. Hence, the accurate results are being determined using this algorithm.

Keywords: Direction of Arrival (DOA), golden section search, MUSIC, number of snapshots

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Authors: Zhaohan Xie, Yining Yu, Mingliang Chen

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As research has shown a convergent tendency for aversion to AI recommendation, it is imperative to find a way to promote AI usage and better harness the technology. In the context of e-commerce, this study has found evidence that people show less avoidance of algorithms when recommending search products compared to experience products. This is due to people’s different attribution of mind to AI versus humans, as suggested by mind perception theory. While people hold the belief that an algorithm owns sufficient capability to think and calculate, which makes it competent to evaluate search product attributes that can be obtained before actual use, they doubt its capability to sense and feel, which is essential for evaluating experience product attributes that must be assessed after experience in person. The result of the behavioral investigation (Study 1, N=112) validated that consumers show low purchase intention to experience products recommended by AI. Further consumer neuroscience study (Study 2, N=26) using Event-related potential (ERP) showed that consumers have a higher level of cognitive conflict when faced with AI recommended experience product as reflected by larger N2 component, while the effect disappears for search product. This research has implications for the effective employment of AI recommenders, and it extends the literature on e-commerce and marketing communication.

Keywords: algorithm recommendation, consumer behavior, e-commerce, event-related potential, experience product, search product

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Authors: A. Boudjemai, A. Zafrane, R. Hocine

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Honeycomb sandwich panels are increasingly used in the construction of space vehicles because of their outstanding strength, stiffness and light weight properties. However, the use of honeycomb sandwich plates comes with difficulties in the design process as a result of the large number of design variables involved, including composite material design, shape and geometry. Hence, this work deals with the presentation of an optimal design of hexagonal honeycomb sandwich structures subjected to space environment. The optimization process is performed using a set of algorithms including the gravitational search algorithm (GSA). Numerical results are obtained and presented for a set of algorithms. The results obtained by the GSA algorithm are much better compared to other algorithms used in this study.

Keywords: optimization, gravitational search algorithm, genetic algorithm, honeycomb plate

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Authors: Rachel K. Cremona

Abstract:

Forty years ago, Vila Autodromo was a small fishing settlement in southwest Rio de Janeiro. By 2012, Vila Autodromo had established itself into a working class neighborhood – certainly not a slum, but nonetheless designated as a ‘favela’ as a consequence of its history as an illegal settlement that was thus never provided with public services. Vila Autodromo sits on a large lagoon, adjacent to the Olympic Park being constructed for the 2016 Olympic Games to be held in Rio, and looks out over the expensive high rise condominiums that have sprouted across the water. In 2009, when Rio submitted their bid for the Olympic games, there were approximately 900 families that called Vila Autodromo home, and the original plans for the games clearly show their homes remaining in place. Today, only a handful of these homes remain. This paper will utilize the case study of Vila Autodromo to examine the broader issue of Favelas in 21st century Rio de Janeiro. While race and poverty have become synonymous with Brazil’s inegalitarian social order – and personified by the thousands of favelas scattered in and around large cities like Rio and Sao Paulo – much less attention has been given to the political status of the nation’s invisible majority. In particular, this research will examine the question of citizenship and argue that the most fundamental problem of inequality in Brazil is not simply a product of history, race and social order, but more specifically a problem of ‘personhood’. The political marginalization of Brazil’s poor does not simply reinforce their social marginalization, it institutionalizes it in a way that makes it almost impossible to escape. The story of Vila Autodromo captures this problem in a way that not only illustrates the clear (though ambiguous) role of the state in the perpetuation of Brazil’s underclass, but also the human resilience that it has fostered.

Keywords: citizenship, poverty, displacement, favela

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Authors: Mejía M. Paula, Ramírez L. Leonardo, Puerta A. Gabriel

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In telemedicine, the image repository service is important to increase the accuracy of diagnostic support of medical personnel. This study makes comparison between two routing algorithms regarding the quality of service (QoS), to be able to analyze the optimal performance at the time of loading and/or downloading of medical images. This study focused on comparing the performance of Tabu Search with other heuristic and metaheuristic algorithms that improve QoS in telemedicine services in Colombia. For this, Tabu Search and Simulated Annealing heuristic algorithms are chosen for their high usability in this type of applications; the QoS is measured taking into account the following metrics: Delay, Throughput, Jitter and Latency. In addition, routing tests were carried out on ten images in digital image and communication in medicine (DICOM) format of 40 MB. These tests were carried out for ten minutes with different traffic conditions, reaching a total of 25 tests, from a server of Universidad Militar Nueva Granada (UMNG) in Bogotá-Colombia to a remote user in Universidad de Santiago de Chile (USACH) - Chile. The results show that Tabu search presents a better QoS performance compared to Simulated Annealing, managing to optimize the routing of medical images, a basic requirement to offer diagnostic images services in telemedicine.

Keywords: medical image, QoS, simulated annealing, Tabu search, telemedicine

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Authors: Sami Houry

Abstract:

Complex systems exhibit universal characteristics as they near a tipping point. Among them are common generic early warning signals which precede critical transitions. These signals include: critical slowing down in which the rate of recovery from perturbations decreases over time; an increase in the variance of the state variable; an increase in the skewness of the state variable; an increase in the autocorrelations of the state variable; flickering between different states; and an increase in spatial correlations over time. The presence of the signals has management implications, as the identification of the signals near the tipping point could allow management to identify intervention points. Despite the applications of the generic early warning signals in various scientific fields, such as fisheries, ecology and finance, a review of literature did not identify any applications that address the program student withdrawal problem at the undergraduate distance universities. This area could benefit from the application of generic early warning signals as the program withdrawal rate amongst distance students is higher than the program withdrawal rate at face-to-face conventional universities. This research specifically assessed the generic early warning signals through an intensive case study of undergraduate program student withdrawal at a Canadian distance university. The university is non-cohort based due to its system of continuous course enrollment where students can enroll in a course at the beginning of every month. The assessment of the signals was achieved through the comparison of the incidences of generic early warning signals among students who withdrew or simply became inactive in their undergraduate program of study, the true positives, to the incidences of the generic early warning signals among graduates, the false positives. This was achieved through significance testing. Research findings showed support for the signal pertaining to the rise in flickering which is represented in the increase in the student’s non-pass rates prior to withdrawing from a program; moderate support for the signals of critical slowing down as reflected in the increase in the time a student spends in a course; and moderate support for the signals on increase in autocorrelation and increase in variance in the grade variable. The findings did not support the signal on the increase in skewness of the grade variable. The research also proposes a new signal based on the fractal-like characteristic of student behavior. The research also sought to extend knowledge by investigating whether the emergence of a program withdrawal status is self-similar or fractal-like at multiple levels of observation, specifically the program level and the course level. In other words, whether the act of withdrawal at the program level is also present at the course level. The findings moderately supported self-similarity as a potential signal. Overall, the assessment of the signals suggests that the signals, with the exception with the increase of skewness, could be utilized as a predictive management tool and potentially add one more tool, the fractal-like characteristic of withdrawal, as an additional signal in addressing the student program withdrawal problem.

Keywords: critical transitions, fractals, generic early warning signals, program student withdrawal

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Authors: A. M. Sagir

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Discrete linear multistep block method of uniform order for the solution of first order Initial Value Problems (IVPs) in Ordinary Differential Equations (ODEs) is presented in this paper. The approach of interpolation and collocation approximation are adopted in the derivation of the method which is then applied to first order ordinary differential equations with associated initial conditions. The continuous hybrid formulations enable us to differentiate and evaluate at some grids and off – grid points to obtain four discrete schemes, which were used in block form for parallel or sequential solutions of the problems. Furthermore, a stability analysis and efficiency of the block method are tested on ordinary differential equations, and the results obtained compared favorably with the exact solution.

Keywords: block method, first order ordinary differential equations, hybrid, self-starting

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Authors: A. Idawaty, O. Mohamed, A. Z. Zuriati

Abstract:

This paper presents the development of an event based Discrete Event Simulation (DES) for a recovery algorithm known Backward Recovery Global Preemptive Utility Accrual Scheduling (BR_GPUAS). This algorithm implements the Backward Recovery (BR) mechanism as a fault recovery solution under the existing Time/Utility Function/ Utility Accrual (TUF/UA) scheduling domain for multiprocessor environment. The BR mechanism attempts to take the faulty tasks back to its initial safe state and then proceeds to re-execute the affected section of the faulty tasks to enable recovery. Considering that faults may occur in the components of any system; a fault tolerance system that can nullify the erroneous effect is necessary to be developed. Current TUF/UA scheduling algorithm uses the abortion recovery mechanism and it simply aborts the erroneous task as their fault recovery solution. None of the existing algorithm in TUF/UA scheduling domain in multiprocessor scheduling environment have considered the transient fault and implement the BR mechanism as a fault recovery mechanism to nullify the erroneous effect and solve the recovery problem in this domain. The developed BR_GPUAS simulator has derived the set of parameter, events and performance metrics according to a detailed analysis of the base model. Simulation results revealed that BR_GPUAS algorithm can saved almost 20-30% of the accumulated utilities making it reliable and efficient for the real-time application in the multiprocessor scheduling environment.

Keywords: real-time system (RTS), time utility function/ utility accrual (TUF/UA) scheduling, backward recovery mechanism, multiprocessor, discrete event simulation (DES)

Procedia PDF Downloads 289