Search results for: direct problem

Authors: Melake Kuflom

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European power networks involve the use of multiple overhead transmission lines to construct a highly duplicated system that delivers reliable and stable electrical energy to the distribution level. The transmission line protection applied in the existing GB transmission network are normally independent unit differential and time stepped distance protection schemes, referred to as main-1 & main-2 respectively, with overcurrent protection as a backup. The increasing penetration of renewable energy sources, commonly referred as “weak sources,” into the power network resulted in the decline of fault level. Traditionally, the fault level of the GB transmission network has been strong; hence the fault current contribution is more than sufficient to ensure the correct operation of the protection schemes. However, numerous conventional coal and nuclear generators have been or about to shut down due to the societal requirement for CO2 emission reduction, and this has resulted in a reduction in the fault level on some transmission lines, and therefore an adaptive transmission line protection is required. Generally, greater utilization of renewable energy sources generated from wind or direct solar energy results in a reduction of CO2 carbon emission and can increase the system security and reliability but reduces the fault level, which has an adverse effect on protection. Consequently, the effectiveness of conventional protection schemes under low fault levels needs to be reviewed, particularly for future GB transmission network operating scenarios. The proposed paper will evaluate the transmission line challenges under high penetration of renewable energy sources andprovides alternative viable protection solutions based on the problem observed. The paper will consider the assessment ofrenewable energy sources (RES) based on a fully rated converter technology. The DIgSILENT Power Factory software tool will be used to model the network.

Keywords: fault level, protection schemes, relay settings, relay coordination, renewable energy sources

Procedia PDF Downloads 185

Authors: Vildan Kistik, Tuncay Can

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From a business perspective, cost and profit are two key factors for businesses. The intent of most businesses is to minimize the cost to maximize or equalize the profit, so as to provide the greatest benefit to itself. However, the physical system is very complicated because of technological constructions, rapid increase of competitive environments and similar factors. In such a system it is not easy to maximize profits or to minimize costs. Businesses must decide on the competence and competence of the personnel to be recruited, taking into consideration many criteria in selecting personnel. There are many criteria to determine the competence and competence of a staff member. Factors such as the level of education, experience, psychological and sociological position, and human relationships that exist in the field are just some of the important factors in selecting a staff for a firm. Personnel selection is a very important and costly process in terms of businesses in today's competitive market. Although there are many mathematical methods developed for the selection of personnel, unfortunately the use of these mathematical methods is rarely encountered in real life. In this study, unlike other methods, an exponential programming model was established based on the possibilities of failing in case the selected personnel was started to work. With the necessary transformations, the problem has been transformed into unconstrained Geometrical Programming problem and personnel selection problem is approached with geometric programming technique. Personnel selection scenarios for a classroom were established with the help of normal distribution and optimum solutions were obtained. In the most appropriate solutions, the personnel selection process for the classroom has been achieved with minimum cost.

Keywords: geometric programming, personnel selection, non-linear programming, operations research

Procedia PDF Downloads 255

Authors: Hsiang-Wen Tang, Cheng-Ying Lo

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In this study, the static behavior of super elliptical Winkler plate is analyzed by applying the double side approach method. The lack of information about super elliptical Winkler plates is the motivation of this study and we use the double side approach method to solve this problem because of its superior ability on efficiently treating problems with complex boundary shape. The double side approach method has the advantages of high accuracy, easy calculation procedure and less calculation load required. Most important of all, it can give the error bound of the approximate solution. The numerical results not only show that the double side approach method works well on this problem but also provide us the knowledge of static behavior of super elliptical Winkler plate in practical use.

Keywords: super elliptical winkler plate, double side approach method, error bound, mechanic

Procedia PDF Downloads 336

Authors: Avinoam Rabinovich

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CO₂ geological storage is a proven technology for reducing anthropogenic carbon emissions, which is paramount for achieving the ambitious net zero emissions goal. Core flooding experiments are an important step in any CO₂ storage project, allowing us to gain information on the flow of CO₂ and brine in the porous rock extracted from the reservoir. This information is important for understanding basic mechanisms related to CO₂ geological storage as well as for reservoir modeling, which is an integral part of a field project. In this work, a different method for constructing accurate models of CO₂-brine core flooding will be presented. Results for synthetic cases and real experiments will be shown and compared with numerical models to exhibit their predictive capabilities. Furthermore, the various mechanisms which impact the CO₂ distribution and trapping in the rock samples will be discussed, and examples from models and experiments will be provided. The new method entails solving an inverse problem to obtain a three-dimensional permeability distribution which, along with the relative permeability and capillary pressure functions, constitutes a model of the flow experiments. The model is more accurate when data from a number of experiments are combined to solve the inverse problem. This model can then be used to test various other injection flow rates and fluid fractions which have not been tested in experiments. The models can also be used to bridge the gap between small-scale capillary heterogeneity effects (sub-core and core scale) and large-scale (reservoir scale) effects, known as the upscaling problem.

Keywords: CO₂ geological storage, residual trapping, capillary heterogeneity, core flooding, CO₂-brine flow

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Authors: Kyu Chul Lee, Sung Hyun Yoo, Choon Ki Ahn, Myo Taeg Lim

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Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended Kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore, the number of centers will be considered since it affects the performance of approximation.

Keywords: extended Kalman filter, classification problem, radial basis function networks (RBFN), finite impulse response (FIR) filter

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Authors: K. A. Ghazaryan, H. S. Movsesyan, N. P. Ghazaryan

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The present study was aimed in assessing the heavy metal pollution of the soils around Agarak copper-molybdenum mine complex and related environmental risks. This mine complex is located in the south-east part of Armenia, and the present study was conducted in 2013. The soils of the five riskiest sites of this region were studied: surroundings of the open mine, the sites adjacent to processing plant of Agarak copper-molybdenum mine complex, surroundings of Darazam active tailing dump, the recultivated tailing dump of “ravine - 2”, and the recultivated tailing dump of “ravine - 3”. The mountain cambisol was the main soil type in the study sites. The level of soil contamination by heavy metals was assessed by Contamination factors (Cf), Degree of contamination (Cd), Geoaccumulation index (I-geo) and Enrichment factor (EF). The distribution pattern of trace metals in the soil profile according to Cf, Cd, I-geo and EF values shows that the soil is much polluted. Almost in all studied sites, Cu, Mo, Pb, and Cd were the main polluting heavy metals, and this was conditioned by Agarak copper-molybdenum mine complex activity. It is necessary to state that the pollution problem becomes pressing as some parts of these highly polluted region are inhabited by population, and agriculture is highly developed there; therefore, heavy metals can be transferred into human bodies through food chains and have direct influence on public health. Since the induced pollution can pose serious threats to public health, further investigations on soil and vegetation pollution are recommended. Finally, Cf calculating based on distance from the pollution source and the wind direction can provide more reasonable results.

Keywords: Agarak copper-molybdenum mine complex, heavy metals, soil contamination, enrichment factor (EF), Armenia

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Authors: Mohammad Shokoohi-Yekta, Hamid Mirebrahim

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A body of research has been devoted to investigating the preferences of computer programmers. These researches used various questionnaires to find out what programming language is most popular among programmers. The problem with such research is that the programmers are usually familiar with only a few languages; therefore, disregarding a number of other languages which might have characteristics that match their preferences more closely. To overcome such a problem, we decided to investigate the preferences of programmers in regards to the characteristics of languages, which help us to discover the languages that include the most characteristics preferred by the users. We conducted a user study to measure the preferences of programmers on different characteristics of programming languages and then tried to compare existing languages in the areas of application, Web and system programming. Overall, the results of our study indicated that the Ruby programming language has the highest preference score in the two areas of application and Web, and C++ has the highest score in the system area. The results of our study can also help programming language designers know the characteristics they should consider when developing new programming languages in order to attract more programmers.

Keywords: object orientation, programming language design, programmers' preferences, characteristic

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Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

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The utilization of Large Eddy Simulation (LES) has been extensive in turbulence research. LES concentrates on resolving the significant grid-scale motions while representing smaller scales through subfilter-scale (SFS) models. The deconvolution model, among the available SFS models, has proven successful in LES of engineering and geophysical flows. Nevertheless, the thorough investigation of how sub-filter scale dynamics and filter anisotropy affect SFS modeling accuracy remains lacking. The outcomes of LES are significantly influenced by filter selection and grid anisotropy, factors that have not been adequately addressed in earlier studies. This study examines two crucial aspects of LES: Firstly, the accuracy of direct deconvolution models (DDM) is evaluated concerning sub-filter scale (SFS) dynamics across varying filter-to-grid ratios (FGR) in isotropic turbulence. Various invertible filters are employed, including Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The importance of FGR becomes evident as it plays a critical role in controlling errors for precise SFS stress prediction. When FGR is set to 1, the DDM models struggle to faithfully reconstruct SFS stress due to inadequate resolution of SFS dynamics. Notably, prediction accuracy improves when FGR is set to 2, leading to accurate reconstruction of SFS stress, except for cases involving Helmholtz I and II filters. Remarkably high precision, nearly 100%, is achieved at an FGR of 4 for all DDM models. Furthermore, the study extends to filter anisotropy and its impact on SFS dynamics and LES accuracy. By utilizing the dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with anisotropic filters, aspect ratios (AR) ranging from 1 to 16 are examined in LES filters. The results emphasize the DDM’s proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. Notably high correlation coefficients exceeding 90% are observed in the a priori study for the DDM’s reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as filter anisotropy increases. In the a posteriori analysis, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, including velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strainrate tensors, and SFS stress. It is evident that as filter anisotropy intensifies, the results of DSM and DMM deteriorate, while the DDM consistently delivers satisfactory outcomes across all filter-anisotropy scenarios. These findings underscore the potential of the DDM framework as a valuable tool for advancing the development of sophisticated SFS models for LES in turbulence research.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

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Authors: Mustapha Kamel Mihoubi, Reda Madi

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The problem of natural disasters in general and flooding in particular is a topic which marks a memorable action in the world and specifically in cities and large urban areas. Torrential floods and faster flows pose a major problem in urban area. Indeed, a better management of risks of floods becomes a growing necessity that must mobilize technical and scientific means to curb the adverse consequences of this phenomenon, especially in the Saharan cities in arid climate. The aim of this study is to deploy a basic calculation approach based on a hydrologic and hydraulic quantification for locating the black spots in urban areas generated by the flooding and to locate the areas that are vulnerable to flooding. The principle of flooding method is applied to the city of Ghardaia to identify vulnerable areas to inundation and to establish maps management and prevention against the risks of flooding.

Keywords: Alea, Beni Mzab, cartography, HEC-RAS, inundation, torrential, vulnerability, wadi

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Authors: Niken Hartati

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This study provides a description of the problem and sources of social support that given to 90 mothers from poor households. Data were collected using structured interviews with the three main questions: 1) what kind of problem in mothers daily life, 2) to whom mothers ask for help to overcome it and 3) the form of the assistances that provided. Furthermore, the data were analyzed using content analysis techniques were then coded and categorized. The results of the study illustrate the problems experienced by mothers of poor households in the form of: subsistence (37%), child care (27%), management of money and time (20%), housework (5%), bad place of living (5%), the main breadwinner (3%), and extra costs (3%). While the sources of social support that obtained by mothers were; neighbors (10%), extended family (8%), children (8%), husband (7%), parents (7%), and siblings (5%). Unfortunately, more mothers who admitted not getting any social support when having problems (55%). The form of social support that given to mother from poor household were: instrumental support (91%), emotional support (5%) and informational support (2%). Implications for further intervention also discussed in this study.

Keywords: household problems, social support, mothers, poor households

Procedia PDF Downloads 349

Authors: Devinder Singh, Rajneesh Kumar, Arvind Kumar

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The present investigation deals with generalized model of the equations for a homogeneous isotropic microstretch thermoelastic half space with mass diffusion medium. Theories of generalized thermoelasticity Lord-Shulman (LS) Green-Lindsay (GL) and Coupled Theory (CT) theories are applied to investigate the problem. The stresses in the considered medium have been studied due to normal force and tangential force. The normal mode analysis technique is used to calculate the normal stress, shear stress, couple stresses and microstress. A numerical computation has been performed on the resulting quantity. The computed numerical results are shown graphically.

Keywords: microstretch, thermoelastic, normal mode analysis, normal and tangential force, microstress force

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Authors: Pasala Gopi, P. Linga Reddy

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The response of the load frequency control problem in an multi-area interconnected electrical power system is much more complex with increasing size, changing structure and increasing load. This paper deals with Load Frequency Control of three area interconnected Power system incorporating Reheat, Non-reheat and Reheat turbines in all areas respectively. The response of the load frequency control problem in an multi-area interconnected power system is improved by designing PID controller using different tuning techniques and proved that the PID controller which was designed by Simulink Design Optimization (SDO) Software gives the superior performance than other controllers for step perturbations. Finally the robustness of controller was checked against system parameter variations

Keywords: load frequency control, pid controller tuning, step load perturbations, inter connected power system

Procedia PDF Downloads 628

Authors: Grace Rademacher

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Trauma” of the Kingdom of Hungary and the “Lost Cause” of the American Confederacy. Applying Nicole Maurantonio’s articulation of “confederate exceptionalism” and Svetlana Boym’s definition of “restorative nostalgia”, this article argues that, via memorialization and public discourse, both far right bodies flood their constituencies with narratives of nostalgia and martyrdom to sow existential anxieties about past and prophetic victimhood, all under the guise of protecting or restoring heritage. Linking this practice to gamification and conspiracy theorizing and following the work of Patrick Jagoda, this article identifies such industries of nostalgia as means by which the far right in both nations can partake in the “immanent and improvisational process of problem making.” Reified through monuments and references to the Trianon Trauma and the American confederacy, political actors “problem make” by alleging that they are victims of the West or the Left, subject to the cruel whims of liberalism and denial of historical legitimacy. In both nations, relying on their victimhood, pundits and politicians can appeal to white supremacists and distract citizens from legitimate active conflicts, such as wars or democratic rollbacks, redirecting them to fictional, mythical attacks on Hungarian or American society and civilization. This article will examine memorials and monuments as “lieux de memoire” and identify the purposeful similarities between the discourse of public figures and politicians such as María Schmidt, János Lázár, and Viktor Orbán, with that of Donald Trump and pundits such as Tucker Carlson.

Keywords: nationalism, political memory, white supremacy, trianon

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Authors: Qasim M. Kriri

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Few Saudi Arabia production companies face financial profit issues until this moment. This work presents a linear integer programming model that solves a production problem of a Saudi Food Company in Saudi Arabia. An optimal solution to the above-mentioned problem is a Linear Programming solution. In this regard, the main purpose of this project is to maximize profit. Linear Programming Technique has been used to derive the maximum profit from production of natural juice at Saudi Food Co. The operations of production of the company were formulated and optimal results are found out by using Lindo Software that employed Sensitivity Analysis and Parametric linear programming in order develop Linear Programming. In addition, the parameter values are increased, then the values of the objective function will be increased.

Keywords: parameter linear programming, objective function, sensitivity analysis, optimize profit

Procedia PDF Downloads 190

Authors: Gangadhara Rao K.

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In Andhra Pradesh traditionally, the flood problem had been confined to the flooding of smaller rivers. But the drainage problem in the coastal delta zones has worsened, multiplying the destructive potential of cyclones and increasing flood hazards. As a result of floods, the people living around these areas are forced to move out of their traditions in search of higher altitude places. This paper will be discussing about suitability of techniques used in Bangladesh in context of Godavari river basin in Andhra Pradesh. The study considers social, physical and environmental conditions of the region. The methods for achieving this objective includes the study of both cases from Bangladesh and Andhra Pradesh. Comparison with the existing techniques and suit to our requirements and context. If successful, we can adopt those techniques and this might help the people living in riverfront areas to stay safe during the floods without losing their traditional lands.

Keywords: amphibious, bouyancy, floating, architecture, flood resistent

Procedia PDF Downloads 157

Authors: Nyla Anjum, Humaira Bano

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Disability, regardless of its type and nature limits one or two significant life activities. These limitations constitute risk factors for suicide. Rate and intensity of problem upsurges in critical age of adolescence. Researches in the field of mental health over look problem of suicide among persons with disability. Aim of the study was to investigate prevalence and risk factors for suicide among adolescents with disability. The study constitutes purposive sample of 106 elements of both gender with four major categories of disability: hearing impairment, physical impairment, visual impairment and intellectual disabilities. Face to face interview technique was opted for data collection. Other variable are: socio-economic status, social and family support, provision of services for persons with disability, education and employment opportunities. For data analysis independent sample t-test was applied to find out significant differences in gender and One Way Analysis of variance was run to find out differences among four types of disability. Major predictors of suicide were identified with multiple regression analysis. It is concluded that ideation, plans and attempts of suicide among adolescents with disability is a multifaceted and imperative concern in the area of mental health. Urgent research recommendations contains valid measurement of suicide rate and identification of more risk factors for suicide among persons with disability. Study will also guide towards prevention of this pressing problem and will bring message of happy and healthy life not only for persons with disability but also for their families. It will also help to reduce suicide rate in society.

Keywords: suicide, risk factors, adolescent, disability, mental health

Procedia PDF Downloads 369

Authors: Quoc Khanh Dang, Thomas Bourdeaud’huy, Khaled Mesghouni, Armand Toguy´eni

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This paper studies a train routing and scheduling problem for busy railway stations. Our objective is to allow trains to be routed in dense areas that are reaching saturation. Unlike traditional methods that allocate all resources to setup a route for a train and until the route is freed, our work focuses on the use of resources as trains progress through the railway node. This technique allows a larger number of trains to be routed simultaneously in a railway node and thus reduces their current saturation. To deal with this problem, this study proposes an abstract model and a mixed-integer linear programming formulation to solve it. The applicability of our method is illustrated on a didactic example.

Keywords: busy railway stations, mixed-integer linear programming, offline railway station management, train platforming, train routing, train scheduling

Procedia PDF Downloads 240

Authors: Mounira Laabidi, Rafik Zayani, Ridha Bouallegue, Daniel Roviras

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The Filter Bank multicarrier with Offset Quadrature Amplitude Modulation (FBMC-OQAM) has been introduced to overcome the poor spectral characteristics and the waste in both bandwidth and energy caused by the use of the cyclic prefix. However, the FBMC-OQAM signals suffer from the high Peak to Average Power Ratio (PAPR) problem. Due to the overlapping structure of the FBMC-OQAM signals, directly applying the PAPR reduction schemes conceived for the OFDM one turns out to be ineffective. In this paper, we address the problem of PAPR reduction for FBMC-OQAM systems by suggesting a new scheme based on an improved version of Active Constellation Extension scheme (ACE) of OFDM. The proposed scheme, named Rolling Window ACE, takes into consideration the overlapping naturally emanating from the FBMC-OQAM signals.

Keywords: ACE, FBMC, OQAM, OFDM, PAPR, rolling-window

Procedia PDF Downloads 533

Authors: Mayank Raj, V. G. Narendra

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Ever since the DARPA challenge on autonomous vehicles in 2005, there has been a lot of buzz about ‘Autonomous Vehicles’ amongst the major tech giants such as Google, Uber, and Tesla. Numerous approaches have been adopted to solve this problem, which can have a long-lasting impact on mankind. In this paper, we have used Deep Learning techniques and TensorFlow framework with the goal of building a neural network model to predict (speed, acceleration, steering angle, and brake) features needed for navigation of autonomous vehicles. The Deep Neural Network has been trained on images and sensor data obtained from the comma.ai dataset. A heatmap was used to check for correlation among the features, and finally, four important features were selected. This was a multivariate regression problem. The final model had five convolutional layers, followed by five dense layers. Finally, the calculated values were tested against the labeled data, where the mean squared error was used as a performance metric.

Keywords: autonomous vehicles, deep learning, computer vision, artificial intelligence

Procedia PDF Downloads 143

Authors: Thien Van Ngo

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The engineering design process is a systematic approach to solving problems. It involves identifying a problem, brainstorming solutions, prototyping and testing solutions, and evaluating the results. The engineering design process can be used to teach students how to solve problems in a creative and innovative way. The research aim of this study was to investigate the effectiveness of using the engineering design process to enhance student learning outcomes in a physics course. A mixed research method was used in this study. The quantitative data were collected using a pretest-posttest control group design. The qualitative data were collected using semi-structured interviews. The sample was 150 first-year students in the Department of Mechanical Engineering Technology at Cao Thang Technical College in Vietnam in the 2022-2023 school year. The quantitative data were collected using a pretest-posttest control group design. The pretest was administered to both groups at the beginning of the study. The posttest was administered to both groups at the end of the study. The qualitative data were collected using semi-structured interviews with a sample of eight students in the experimental group. The interviews were conducted after the posttest. The quantitative data were analyzed using independent sample T-tests. The qualitative data were analyzed using thematic analysis. The quantitative data showed that students in the experimental group, who were taught using the engineering design process, had significantly higher post-test scores on physics problem-solving than students in the control group, who were taught using the conventional method. The qualitative data showed that students in the experimental group were more motivated and engaged in the learning process than students in the control group. Students in the experimental group also reported that they found the engineering design process to be a more effective way of learning physics. The findings of this study suggest that the engineering design process can be an effective way of enhancing student learning outcomes in physics courses. The engineering design process engages students in the learning process and helps them to develop problem-solving skills.

Keywords: engineering design process, problem-solving, learning outcome of physics, students’ physics competencies, deep learning

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Authors: Tabassum Yasmin, Hamid Pahlevan

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HIV/Hepatitis C co-infection treatments have evolved substantially and they have similar sustained virologic response rates as those of Hepatitis C monoinfected population. There are a few studies on therapy of patients with dual genotypes, especially in HIV/Hepatic C coinfected group. Most studies portrayed case reports of dual genotype chronic Hepatitis C coinfection treatment with Sofosbuvir/Ledipasvir and Ribavirin. A 79-year-old male with a history of HIV on Truvada and Isentress had chronic Hepatitis C with 1a and 2 genotypes. The patient has a history of alcohol intake for 40 years but recently stopped drinking alcohol. He has a history of intravenous drug use in the past and currently is not using any recreational drugs. Patient has Fibro score of 0.7 with Metavir score F2 to F4. AFP is 3.2. The HCV RNA is 493,034 IU/ML. The HBV viral DNA is < 1.30 (not detected). The CD4 is 687CU/MM. The FIB 4 is 3.34 with APRI index 0.717. The HIV viral load is 101 copies/ML. MRI abdomen did not show any liver abnormality. Fixed dose Sofosbuvir/Ledipasvir was used for therapy without Ribavirin. He tolerated medication except for some minor gastrointestinal side effects like abdominal bloating. He demonstrated 100% adherence rate. Patient completed 12 weeks of therapy. HCV RNA was undetectable at 4 and 12 weeks. He achieved SVR at week 12 and subsequently had undetectable RNA for 2 years. Dual genotype prevalence in chronic hepatitis C population is rare, especially in HIV/hepatic coinfection. Our case demonstrates that dual genotypic cases can still be successfully treated with Direct Acting Antiviral agents. The newer agents for therapy for pan genotypes were not available at the time the patient was being treated. We demonstrated that dual agent therapy was still able to maintain SVR in our patient.

Keywords: HIV/Hepatitis C, SVR (sustained virologic response), DAA (direct active antiviral agents, dual genotype

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid distributed algorithm has been suggested for multi-objective dynamic flexible job shop scheduling problem. The proposed algorithm is high level, in which several algorithms search the space on different machines simultaneously also it is a hybrid algorithm that takes advantages of the artificial intelligence, evolutionary and optimization methods. Distribution is done at different levels and new approaches are used for design of the algorithm. Apache spark and Hadoop frameworks have been used for the distribution of the algorithm. The Pareto optimality approach is used for solving the multi-objective benchmarks. The suggested algorithm that is able to solve large-size problems in short times has been compared with the successful algorithms of the literature. The results prove high speed and efficiency of the algorithm.

Keywords: distributed algorithms, apache-spark, Hadoop, flexible dynamic job shop scheduling, multi-objective optimization

Procedia PDF Downloads 339

Authors: Hsiao-Tien Pao, Yi-Ying Li, Hsin-Chia Fu

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This paper addressed the impacts of energy consumption, economic growth, financial development, and population size on environmental degradation using grey relational analysis (GRA) for China, where foreign direct investment (FDI) inflows is the proxy variable for financial development. The more recent historical data during the period 2004–2011 are used, because the use of very old data for data analysis may not be suitable for rapidly developing countries. The results of the GRA indicate that the linkage effects of energy consumption–emissions and GDP–emissions are ranked first and second, respectively. These reveal that energy consumption and economic growth are strongly correlated with emissions. Higher economic growth requires more energy consumption and increasing environmental pollution. Likewise, more efficient energy use needs a higher level of economic development. Therefore, policies to improve energy efficiency and create a low-carbon economy can reduce emissions without hurting economic growth. The finding of FDI–emissions linkage is ranked third. This indicates that China do not apply weak environmental regulations to attract inward FDI. Furthermore, China’s government in attracting inward FDI should strengthen environmental policy. The finding of population–emissions linkage effect is ranked fourth, implying that population size does not directly affect CO₂ emissions, even though China has the world’s largest population, and Chinese people are very economical use of energy-related products. Overall, the energy conservation, improving efficiency, managing demand, and financial development, which aim at curtailing waste of energy, reducing both energy consumption and emissions, and without loss of the country’s competitiveness, can be adopted for developing economies. The GRA is one of the best way to use a lower data to build a dynamic analysis model.

Keywords: China, CO₂ emissions, foreign direct investment, grey relational analysis

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Authors: R. Nagarani

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An intrinsic property of software in a real-world environment is its need to evolve, which is usually accompanied by the increase of software complexity and deterioration of software quality, making software maintenance a tough problem. Refactoring is regarded as an effective way to address this problem. Many refactoring approaches at the method and class level have been proposed. But the extent of research on software refactoring at the package level is less. This work presents a novel approach to refactor the package structures of object oriented software using genetic algorithm based community detection. It uses software networks to represent classes and their dependencies. It uses a constrained community detection algorithm to obtain the optimized community structures in software networks, which also correspond to the optimized package structures. It finally provides a list of classes as refactoring candidates by comparing the optimized package structures with the real package structures.

Keywords: community detection, complex network, genetic algorithm, package, refactoring

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Authors: Petcharat Kerdonfag, Supunnee Thrakul

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School health services through regular screening of school students’ health status have been the main responsibility for community or school health nurses. The purposes of these retrospective study were to assess and compare health problems between government and private primary school students in the central region of Thailand. The data were collected from the school health records in October at the end of the first semester in the academic year 2018. Two thousand and fifty primary school health records from government and private primary schools were gathered to assess health problems regarding anthropometric measurements, physical examination/personal hygiene, and clinical findings for this study. Descriptive statistics and Chi-square were used to be analyzed. The results revealed that health problems of all the school students remained high magnitude. The five top ranks for prevalence rate of health problems were dental caries (36.6%), visual acuity problem (27.7%), over-nutrition (16.8%), head lice (12.8%), and under-nutrition (6.8%), respectively. However, when compared between government and private schools among five health problems; dental caries (55.0% vs 19.9%), visual acuity problem (23.1% vs 31.9%), over-nutrition (20.2% vs 13.8%), head lice (26.5% vs 0.3%), and under-nutrition (10.6% vs 3.4%) with Chi-square analysis, there were significantly different (p < .001). The problem of visual acuity seems to be more serious in private schools while other health problems tend to be more critical in government schools. The findings have suggested that parents who have children in the private primary schools should pay more attention to visual health defects whereas parents with children in the government school should pay more vigilance regards to hygiene and health behavior problems.

Keywords: community health nursing, school health service, health status, primary school children

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Authors: María Dolores Caro, Eugenio M. Fedriani, Ángel F. Tenorio

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When lorries transport dangerous goods, there exist some legal stipulations in the European Union for assuring the security of the rest of road users as well as of those goods being transported. At this respect, lorry drivers cannot park in usual parking areas, because they must use parking areas with special conditions, including permanent supervision of security personnel. Moreover, drivers are compelled to satisfy additional regulations about resting and driving times, which involve in the practical possibility of reaching the suitable parking areas under these time parameters. The “European Agreement concerning the International Carriage of Dangerous Goods by Road” (ADR) is the basic regulation on transportation of dangerous goods imposed under the recommendations of the United Nations Economic Commission for Europe. Indeed, nowadays there are no enough parking areas adapted for dangerous goods and no complete study have suggested the best locations to build new areas or to adapt others already existing to provide the areas being necessary so that lorry drivers can follow all the regulations. The goal of this paper is to show how many additional parking areas should be built in the Iberian Peninsula to allow that lorry drivers may park in such areas under their restrictions in resting and driving time. To do so, we have modeled the problem via graph theory and we have applied a new efficient algorithm which determines an optimal solution for the problem of locating new parking areas to complement those already existing in the ADR for the Iberian Peninsula. The solution can be considered minimal since the number of additional parking areas returned by the algorithm is minimal in quantity. Obviously, graph theory is a natural way to model and solve the problem here proposed because we have considered as nodes: the already-existing parking areas, the loading-and-unloading locations and the bifurcations of roads; while each edge between two nodes represents the existence of a road between both nodes (the distance between nodes is the edge's weight). Except for bifurcations, all the nodes correspond to parking areas already existing and, hence, the problem corresponds to determining the additional nodes in the graph such that there are less up to 100 km between two nodes representing parking areas. (maximal distance allowed by the European regulations).

Keywords: dangerous goods, parking areas, Iberian peninsula, graph-based modeling

Procedia PDF Downloads 570

Authors: Alireza Mirrashid, Mohammad Khoshbin, Ali Atghaei, Hassan Shahbazi

Abstract:

In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is the use of infrared thermal and smoke sensors, which cannot be used in outdoor applications. Therefore, the use of vision-based methods seems necessary. The problem of smoke and fire detection is spatiotemporal and requires spatiotemporal solutions. This paper presents a method that uses spatial features along with temporal-based features to detect smoke and fire in the scene. It consists of three main parts; the task of each part is to reduce the error of the previous part so that the final model has a robust performance. This method also uses transformer modules to increase the accuracy of the model. The results of our model show the proper performance of the proposed approach in solving the problem of smoke and fire detection and can be used to increase workplace safety.

Keywords: attention, fire detection, smoke detection, spatio-temporal

Procedia PDF Downloads 182

Authors: Alireza Monzavi Chaleshtari, Mahnaz Aliakbari Dehkordi, Nazila Esmaeili, Ahmad Alipour, Amin Asadi Hieh

Abstract:

Headache disorders are one of the most common disorders of the nervous system and are associated with suffering, disability, and financial costs for patients. Mindfulness as a lifestyle, in line with human nature, has the ability to affect the emotional system, i.e. thoughts, body sensations, raw emotions and action impulses of people. The aim of this study was to test the fit of structural model of mindfulness and severity of headache mediated by resilience and perfectionism in patients with migraine. Methods: The statistical population of this study included all patients with migraine referred to neurologists in Tehran in the spring and summer of 1401. The inclusion criteria were diagnosis of migraine by a neurologist, not having mental disorders or other physical diseases, and having at least a diploma. According to the number of research variables, 180 people were selected by convenience sampling method, which online answered the Ahvaz perfectionism questionnaire (AMQ), Connor and Davidson resilience questionnaire (CD-RISC), Ahvaz migraine headache questionnaire (APS) and 5-factor mindfulness questionnaire ((MAAS). Data were analyzed using structural equation modeling and Amos software. Results: The results showed that the direct pathways of mindfulness were not significant for severe headache (P <0.05), but other direct pathways - mindfulness to resilience, mindfulness to perfectionism, resilience to severe headache and perfectionism to severe headache), Was significant (P <0.01). After modifying and removing the non-significant paths, the final model fitted. Mediating variables Resilience and perfectionism mediated all paths of predictor variables to the criterion. Conclusion: According to the findings of the present study, mindfulness in migraine patients reduces the severity of headache by promoting resilience and reducing perfectionism.

Keywords: migraine, headache severity, mindfulness, resilience, perfectionism

Procedia PDF Downloads 66

Authors: Sung Ham, Chanho Song, Jiabin Wu

Abstract:

Employees are commonly incentivized on both quantity and quality performance and much of the extant literature focuses on demonstrating that multitasking incentives lead to tradeoffs. Alternatively, we consider potential solutions to the tradeoff problem from both a theoretical and an experimental perspective. Across two field experiments from a call center, we find that tradeoffs can be mitigated when incentives are jointly enhanced across tasks, where previous research has suggested that incentives be reduced instead of enhanced. In addition, we also propose and test, in a laboratory setting, the implications of revising the metric used to assess quality. Our results indicate that metrics can be adjusted to align quality and quantity more efficiently. Thus, this alignment has the potential to thwart the classic tradeoff problem. Finally, we validate our findings with an economic experiment that verifies that effort is largely consistent with our theoretical predictions.

Keywords: incentives, multitasking, field experiment, experimental economics

Procedia PDF Downloads 152

Authors: Bita Payami-Shabestari, Dariush Eslami

Abstract:

The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.

Keywords: economic production quantity, random cost, supply chain management, vendor-managed inventory

Procedia PDF Downloads 113