Search results for: supplier selection problem

Authors: Miroslava Markovic, Snezana Rajkovic, Ljubinko Rakonjac, Aleksandar Lucic

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Oak powdery mildew is a serious problem on seedlings in nurseries as well as on naturally and artificially introduced progeny. The experiments were set on oak seedlings in two nurseries located in Central Serbia, where control of oak powdery mildew Microsphaera alphitoides Griff. et Maubl. had been conducted through alternative protection measures by means of various dosages of AQ-10 biofungicide, with and without added polymer (which has so far never been used in this country for control of oak powdery mildew). Simultaneous testing was conducted on the efficiency of a chemical sulphur-based preparation (used in this area for many years as a measure of suppression of powdery mildews, without the possibility of developing resistance of the pathogen to the active matter). To date, the Republic of Serbia has registered no fungicides for suppression of pathogens in the forest ecosystems. In order to introduce proper use of new disease-fighting agents into a country, certain relevant principles, requirements and criteria prescribed by the Forest Stewardship Council (FSC) must be observed, primarily with respect to measures of assessment and mitigation of risks, the list of dangerous and highly dangerous pesticides with the possibility of alternative protection. One of the main goals of the research was adjustment of the protective measures to the FSC policy through selection of eco-toxicologically favourable fungicides, given the fact that only preparations named on the list of permitted active matters are approved for use in certified forests. The results of the research have demonstrated that AQ-10 biofungicide can be used as a part of integrated disease management programmes as an alternative, through application of several treatments during vegetation and combination with other active matters registered for these purposes, so as to curtail the use of standard fungicides for control of powdery mildews on oak seedlings in nurseries. The best results in suppression of oak powdery mildew were attained through use of AQ-10 biofungicide (dose 50 or 70g/ha) with added polymer Nu Film-17 (dose 1.0 or 1.5 l/ha). If the treatment is applied at the appropriate time, even fewer number of treatments and smaller doses will be just as efficient.

Keywords: oak powdery mildew, biofungicides, polymers, Microsphaera alphitoides

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Authors: Tarathorn Podcharathitikull, Jirarat Teeravaraprug

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Transportation cost is the highest cost in logistics cost of Thailand, and truck transportation is counted as about 90% of the overall transportation cost. The main problem of truck transportation is backhauling. Backhauling has become an attractive cost-saving approach in logistics. To explore such opportunities, this paper investigated the current backhauling systems in Thailand. It was found that the backhauling problem is attracted to both governmental agencies and private sector. They gave attempts to build backhauling systems. This paper investigated two systems built by governmental agencies and one by private sector. Moreover, based on the interviews with the system representatives and users, pros and cons of the systems were found. The obstacles and challenges were obtained. This paper finally proposed a conceptual model of to-be backhauling system in Thailand.

Keywords: backhauling system, backhauls, interview, Thailand

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Authors: P. V. Pramila , V. Mahesh

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Pulmonary Function Tests are important non-invasive diagnostic tests to assess respiratory impairments and provides quantifiable measures of lung function. Spirometry is the most frequently used measure of lung function and plays an essential role in the diagnosis and management of pulmonary diseases. However, the test requires considerable patient effort and cooperation, markedly related to the age of patients esulting in incomplete data sets. This paper presents, a nonlinear model built using Multivariate adaptive regression splines and Random forest regression model to predict the missing spirometric features. Random forest based feature selection is used to enhance both the generalization capability and the model interpretability. In the present study, flow-volume data are recorded for N= 198 subjects. The ranked order of feature importance index calculated by the random forests model shows that the spirometric features FVC, FEF 25, PEF,FEF 25-75, FEF50, and the demographic parameter height are the important descriptors. A comparison of performance assessment of both models prove that, the prediction ability of MARS with the `top two ranked features namely the FVC and FEF 25 is higher, yielding a model fit of R2= 0.96 and R2= 0.99 for normal and abnormal subjects. The Root Mean Square Error analysis of the RF model and the MARS model also shows that the latter is capable of predicting the missing values of FEV1 with a notably lower error value of 0.0191 (normal subjects) and 0.0106 (abnormal subjects). It is concluded that combining feature selection with a prediction model provides a minimum subset of predominant features to train the model, yielding better prediction performance. This analysis can assist clinicians with a intelligence support system in the medical diagnosis and improvement of clinical care.

Keywords: FEV, multivariate adaptive regression splines pulmonary function test, random forest

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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Authors: Obaid Alotaibi

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The geographical location of the State of Kuwait contributed significantly to the suffering of Kuwait in the past, due to the scarcity of natural water resources and the inability of the State's financial resources to provide other water resources to meet the needs of the population. The problem of water scarcity in Kuwait remained until the beginning of the second half of the twentieth century, as the country's economic conditions revived with the emergence and export of oil; which was clearly reflected in the steady growth of the population. To cope with this population, increase, it was necessary to expand the various development programs to include all sectors of the state. The process of development and urbanization could not start without finding solutions to the problem of water shortage in Kuwait. The only option for officials to meet the needs of the population and the different sectors of water development is the desalination of seawater. This process necessitated the establishment of six desalination plants along the coast of Kuwait and extended freshwater arteries to reach everywhere on the land. However, this does not mean that the problem of water shortage has been completely solved. The desalination plants are not meeting the country's future water needs, especially considering the increasing population growth. These stations are nearing completion and they need to be replaced, renovation and maintenance, require significant expenses. Therefore, it was necessary for scientific research to address the issue of water in Kuwait, whether in the field of development of existing resources or in the field of rationalization of consumption and protection of available resources. The study focused on how to address the increasing demand for water resulting from population increase, the impact of water on economic and social development, the prospects of water resources in Kuwait and its ability to meet the needs of the country by 2030.

Keywords: economic, development, Kuwait, social, water resources

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Authors: Richard Tanaka, Ying Zhu

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This paper studies a few randomized algorithms in application-layer peer-to-peer networks. The significant gain in scalability and resilience that peer-to-peer networks provide has made them widely used and adopted in many real-world distributed systems and applications. The unique properties of peer-to-peer networks make them particularly suitable for randomized algorithms such as random walks and gossip algorithms. Instead of simulations of peer-to-peer networks, we leverage the Docker virtual container technology to develop implementations of the peer-to-peer networks and these distributed randomized algorithms running on top of them. We can thus analyze their behaviour and performance in realistic settings. We further consider the problem of identifying high-risk bottleneck links in the network with the objective of improving the resilience and reliability of peer-to-peer networks. We propose a randomized algorithm to solve this problem and evaluate its performance by simulations.

Keywords: distributed randomized algorithms, peer-to-peer networks, virtual container technology, resilient networks

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Authors: Fariborz Ahmadi, Reza Tati

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Genetic algorithm is a soft computing method that works on set of solutions. These solutions are called chromosome and the best one is the absolute solution of the problem. The main problem of this algorithm is that after passing through some generations, it may be produced some chromosomes that had been produced in some generations ago that causes reducing the convergence speed. From another respective, most of the genetic algorithms are implemented in software and less works have been done on hardware implementation. Our work implements genetic algorithm in hardware that doesn’t produce chromosome that have been produced in previous generations. In this work, most of genetic operators are implemented without producing iterative chromosomes and genetic diversity is preserved. Genetic diversity causes that not only do not this algorithm converge to local optimum but also reaching to global optimum. Without any doubts, proposed approach is so faster than software implementations. Evaluation results also show the proposed approach is faster than hardware ones.

Keywords: hardware, genetic algorithm, computer science, engineering

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Authors: Tatiana A. Dolenko, Sergey A. Burikov, Alexander O. Efitorov, Sergey A. Dolenko

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In this study, a comparative analysis of the approaches associated with the use of neural network algorithms for effective solution of a complex inverse problem – the problem of identifying and determining the individual concentrations of inorganic salts in multicomponent aqueous solutions by the spectra of Raman scattering of light – is performed. It is shown that application of artificial neural networks provides the average accuracy of determination of concentration of each salt no worse than 0.025 M. The results of comparative analysis of input data compression methods are presented. It is demonstrated that use of uniform aggregation of input features allows decreasing the error of determination of individual concentrations of components by 16-18% on the average.

Keywords: inverse problems, multi-component solutions, neural networks, Raman spectroscopy

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Authors: Vandana Dave, Neelam Kumari

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India, a fast growing global power, is climbing the ladder of success very swiftly and has been attracting the world’s attention in recent decades. But unfortunately in the modern society, women who constitute half the population of our country have been the victims of violence in different fields of life both physically, socially, mentally and economically. Women face a lot of societal pressure, gender based violence – including rape, domestic violence, dowry death, murder and sexual abuse. But none the less, it is not considered as a problem of serious concern. Among the issues related to women, domestic violence is one of the major issue in our society which is occurring within the safe confines of home at the hands of close family members and cuts across line of race, nationality, language, culture, economics, sexual orientation, physical ability and religion to affect women from all walks of life. It is not to be perceived as a law and order problem alone but it is a socio- cultural problem and it is directly affecting the family life, health of women and life of children. Structural imbalance of power, systematic gender based discrimination; inequality between women and men and other kind of subordination are the context and cause of violence against women. Understanding it as a major problem of our society, the present study was conducted to assess the status of women of Rohtak, district of Haryana. The present study is based on primary and secondary data, adopting feminist research methodology. Case study method was incorporated during the research. It was observed that violence varied according to different age groups of women, marital status, education status, economic status and sociodemography factors. The case studies depicted the inadequate justice system for the victims of domestic violence. The study also revealed that the victims failed to understand the judiciary system and considered themselves helpless and hopeless. The study indicates the need of women friendly justice system for the upliftment of the society.

Keywords: domestic violence, women, victim, justice

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Authors: Samar Swaid

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Today, corporates are moving toward the adoption of Design-Thinking techniques to develop products and services, putting their consumer as the heart of the development process. One of the leading companies in Design-Thinking, IDEO (Innovation, Design, Engineering Organization), defines Design-Thinking as an approach to problem-solving that relies on a set of multi-layered skills, processes, and mindsets that help people generate novel solutions to problems. Design thinking may result in new ideas, narratives, objects or systems. It is about redesigning systems, organizations, infrastructures, processes, and solutions in an innovative fashion based on the users' feedback. Tim Brown, president and CEO of IDEO, sees design thinking as a human-centered approach that draws from the designer's toolkit to integrate people's needs, innovative technologies, and business requirements. The application of design thinking has been witnessed to be the road to developing innovative applications, interactive systems, scientific software, healthcare application, and even to utilizing Design-Thinking to re-think business operations, as in the case of Airbnb. Recently, there has been a movement to apply design thinking to machine learning and artificial intelligence to ensure creating the "wow" effect on consumers. The Association of Computing Machinery task force on Data Science program states that" Data scientists should be able to implement and understand algorithms for data collection and analysis. They should understand the time and space considerations of algorithms. They should follow good design principles developing software, understanding the importance of those principles for testability and maintainability" However, this definition hides the user behind the machine who works on data preparation, algorithm selection and model interpretation. Thus, the Data Science program includes design thinking to ensure meeting the user demands, generating more usable machine learning tools, and developing ways of framing computational thinking. Here, describe the fundamentals of Design-Thinking and teaching modules for data science programs.

Keywords: data science, design thinking, AI, currculum, transformation

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Authors: Sevgi Özlem Bulu, Arif Furkan Mendi, Tolga Erol, İzzet Gökhan Özbilgin

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The rapid progress of technology in today's competitive conditions has also accelerated companies' technology development activities. As a result, companies are paying more attention to R&D studies and are beginning to allocate a larger share to R&D projects. A more systematic, comprehensive, target-oriented implementation of R&D studies is crucial for the company to achieve successful results. As a consequence, Technology Roadmap (TRM) is gaining importance as a management tool. It has critical prospects for achieving medium and long term success as it contains decisions about past business, future plans, technological infrastructure. When studies on TRM are examined, projects to be placed on the roadmap are selected by many different methods. Generally preferred methods are based on multi-criteria decision making methods. Management of selected projects becomes an important point after the selection phase of the projects. At this stage, TRM are used. TRM can be created in many different ways so that each institution can prepare its own Technology Roadmap according to their strategic plan. Depending on the intended use, there can be TRM with different layers at different sizes. In the evaluation phase of the R&D projects and in the creation of the TRM, HAVELSAN, Turkey's largest defense company in the software field, carries out this process with great care and diligence. At the beginning, suggested R&D projects are evaluated by the Technology Management Board (TMB) of HAVELSAN in accordance with the company's resources, objectives, and targets. These projects are presented to the TMB periodically for evaluation within the framework of certain criteria by board members. After the necessary steps have been passed, the approved projects are added to the time-based TRM, which is composed of four layers as market, product, project and technology. The use of a four-layered roadmap provides a clearer understanding and visualization of company strategy and objectives. This study demonstrates the benefits of using TRM, four-layered Technology Roadmapping and the possibilities for the institutions in the defense industry.

Keywords: technology roadmap, research and development project, project selection, research development in defense industry

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Authors: Seyedmirsajad Mokhtarimousavi, Danial Talebi, Hamidreza Asgari

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Assigning aircrafts’ activities to appropriate gates is one the most challenging issues in airport authorities’ multiple criteria decision making. The potential financial loss due to imbalances of demand and supply in congested airports, higher occupation rates of gates, and the existing restrictions to expand facilities provide further evidence for the need for an optimal supply allocation. Passengers walking distance, towing movements, extra fuel consumption (as a result of awaiting longer to taxi when taxi conflicts happen at the apron area), etc. are the major traditional components involved in GAP models. In particular, the total cost associated with gate assignment problem highly depends on the airport terminal layout. The study herein presents a well-elaborated literature review on the topic focusing on major concerns, applicable variables and objectives, as well as proposing a three-objective mathematical model for the gate assignment problem. The model has been tested under different concourse layouts in order to check its performance in different scenarios. Results revealed that terminal layout pattern is a significant parameter in airport and that the proposed model is capable of dealing with key constraints and objectives, which supports its practical usability for future decision making tools. Potential solution techniques were also suggested in this study for future works.

Keywords: airport management, terminal layout, gate assignment problem, mathematical modeling

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Authors: Ibrahim Aydogdu, Alper Akin

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In this study, the development of minimizing the cost and the CO2 emission of the RC retaining wall design has been performed by Biogeography Based Optimization (BBO) algorithm. This has been achieved by developing computer programs utilizing BBO algorithm which minimize the cost and the CO2 emission of the RC retaining walls. Objective functions of the optimization problem are defined as the minimized cost, the CO2 emission and weighted aggregate of the cost and the CO2 functions of the RC retaining walls. In the formulation of the optimum design problem, the height and thickness of the stem, the length of the toe projection, the thickness of the stem at base level, the length and thickness of the base, the depth and thickness of the key, the distance from the toe to the key, the number and diameter of the reinforcement bars are treated as design variables. In the formulation of the optimization problem, flexural and shear strength constraints and minimum/maximum limitations for the reinforcement bar areas are derived from American Concrete Institute (ACI 318-14) design code. Moreover, the development length conditions for suitable detailing of reinforcement are treated as a constraint. The obtained optimum designs must satisfy the factor of safety for failure modes (overturning, sliding and bearing), strength, serviceability and other required limitations to attain practically acceptable shapes. To demonstrate the efficiency and robustness of the presented BBO algorithm, the optimum design example for retaining walls is presented and the results are compared to the previously obtained results available in the literature.

Keywords: bio geography, meta-heuristic search, optimization, retaining wall

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Authors: Maged Assem Soliman Mossallam

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Thermal vacuum testing target is to qualify the space system and ensure its operability under harsh space environment. The functionality of the cubesat was checked at extreme orbit conditions. Test was performed for operational and nonoperational modes. Analysis is done to simulate the cubesat thermal cycling inside thermal vacuum chamber. Comsol Multiphysics finite element is used to solve three dimensional problem for the cubesat inside TVAC. Three dimensional CAD model is done using Autodesk Inventor program. The boundary conditions were applied from the actual shroud temperature. The input heat load variation with time is considered to solve the transient three dimensional problem. Results show that the simulated temperature profiles are within an acceptable range from the real testing data.

Keywords: cubesat, thermal vacuum test, testing simulation, finite element analysis

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Authors: Selin Guney, Andres Riquelme

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Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

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Authors: Dona Grace Jeyaseeli

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Water quality conditions in a pond are controlled by both natural processes and human influences. Natural factors such as the source of the pond water and the types of rock and soil in the pond watershed will influence some water quality characteristics. These factors are difficult to control but usually cause few problems. Instead, most serious water quality problems originate from land uses or other activities near or in the pond. The effects of these activities can often be minimized through proper management and early detection of problems through testing. In the present study a survey of three ponds in Coimbatore city, Tamilnadu, India were analyzed and found that water quality problems in their ponds, ranging from muddy water to fish kills. Unfortunately, most pond owners have never tested their ponds, and water quality problems are usually only detected after they cause a problem. Hence the present study discusses some common water quality parameters that may cause problems in ponds and how to detect through testing for better management of pond.

Keywords: water quality, pond, test, problem

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Authors: Ram Kishor

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The Lyapunov characteristic exponent (LCE) is an important tool to describe behavior of a dynamical system, which measures the average rate of divergence (or convergence) of a trajectory emanating in the vicinity of initial point. To analyze the behavior of nearby trajectory emanating in the neighborhood of an equilibrium point in the restricted three-body problem under the influence of perturbations in the form of radiation pressure and oblateness, we compute LCEs of first order with the help of slandered method which is based on variational equation of the system. It is observed that trajectories are chaotic in nature due positive LCEs. Also, we analyze the effect of radiation pressure and oblateness on the LCEs. Results are applicable to study the behavior of more generalized RTBP in the presence of perturbations such as PR drag, solar wind drag etc.

Keywords: Lyapunov characteristic exponent, RTBP, radiation pressure, oblateness

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Authors: Katalin Bándy

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The European emigration of highly educated immigrants draws attention to the problem of brain drain. Due to the Eastern European countries joining the EU and the opening of the Western European labour market the west-wards migration brisked up. By now another problem has been intensified correlated to migration: the migration of highly skilled workers related to brain waste tendencies. With some exceptions, educated immigrants from Eastern European countries are more likely to end up in unskilled jobs than residents. This paper is about to reveal the above-mentioned problems and this study is supported by the results of secondary pieces of research and the own survey made in the EU-15 among the Hungarian highly skilled (especially economics graduated) migrants, and it also examines the causes and in the focus there are the migrant motivations of the high-skilled young generation after the crisis.

Keywords: brain drain, brain waste, migration of highly-skilled, underemployment

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Authors: Yong-Kian Lim, Khan Cheung, Xin Dang, Steven Roberts, Xiaotong Wang, Vengatesen Thiyagarajan

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Unprecedented rate of increased CO₂ level in the ocean and the subsequent changes in carbonate system including decreased pH, known as ocean acidification (OA), is predicted to disrupt not only the calcification process but also several other physiological and developmental processes in a variety of marine organisms, including edible oysters. Nonetheless, not all species are vulnerable to those OA threats, e.g., some species may be able to cope with OA stress using environmentally induced modifications on gene and protein expressions. For example, external environmental stressors, including OA, can influence the addition and removal of methyl groups through epigenetic modification (e.g., DNA methylation) process to turn gene expression “on or off” as part of a rapid adaptive mechanism to cope with OA. In this study, the above hypothesis was tested through testing the effect of OA, using decreased pH 7.4 as a proxy, on the DNA methylation pattern of an endemic and a commercially important estuary oyster species, Crassostrea hongkongensis, at the time of larval habitat selection and metamorphosis. Larval growth rate did not differ between control pH 8.1 and treatment pH 7.4. The metamorphosis rate of the pediveliger larvae was higher at pH 7.4 than those in control pH 8.1; however, over one-third of the larvae raised at pH 7.4 failed to attach to an optimal substrate as defined by biofilm presence. During larval development, a total of 130 genes were differentially methylated across the two treatments. The differential methylation in the larval genes may have partially accounted for the higher metamorphosis success rate under decreased pH 7.4 but with poor substratum selection ability. Differentially methylated loci were concentrated in the exon regions and appear to be associated with cytoskeletal and signal transduction, oxidative stress, metabolic processes, and larval metamorphosis, which implies the high potential of C. hongkongensis larvae to acclimate and adapt through non-genetic ways to OA threats within a single generation.

Keywords: adaptive plasticity, DNA methylation, larval metamorphosis, ocean acidification

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Authors: Khorief Ouissem, Sassi Boudmagh Souad, Mahimoud Aissa

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The health and safety problem in the construction companies has been a major subject of research in Algeria for many years. The latest statistics of the Algerian National Social Security Fund (CNAS) shows that a third of accidents recorded at the national level are originated from construction activities. It is becoming increasingly essential and urgent to investigate and address its causes in order to find measures to overcome the deficiencies in this area. Thus, this paper takes in investigating this problem through a study conducted in the city of Skikda, Algeria. The study was carried out through questionnaire where twenty construction companies were taking into consideration. First, the study identifies the regulations and the laws related to the health and safety in the construction sector in Algeria. Then it goes on to assess and evaluate the implementation of the identified regulations in the companies selected. The result of the assessment indicates that the majority of the construction companies considered do not meet the health and safety standards and regulations. To extract the main causes of the failure of the system to control this industry, the observations and the evaluation were analyzed using the 5M or Ichikawa diagram method. This method is based on identifying the causes of the problem in terms of purpose, the list of potential causes for families. These families often correspond to 5M (Labor, Material, Methods, Middle, and Management). Finally, having identified the primary motives, the present authors propose a list of actions to move towards a more controlled and effective health and safety system for the construction industry.

Keywords: health and safety, construction industry, performance measurement, Algeria

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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: Theresa Belema Chris-Biriowu

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The change in trends in relation to gender representation in beer brand commercials was the thrust of the study. The study investigated how beer brand commercials reflect societal realities in their portrayals of gender roles within the span of a decade. The major objective of the study was to find out how gender was contextualized in selected beer brand commercials that both air on Nigerian television and stream on YouTube. The study was anchored on the muted group theory. The population of the study was in two streams: the total number of beer beverages that are produced by the eleven breweries in Nigeria and the registered advertising agencies in Lagos, Nigeria. The sample size was also two-pronged: the purposive selection of beer brands that have their commercials on television and YouTube and the purposive selection of an ad agency that has produced running commercials for beer brands within the period between 2010s and 2020s. They adopted visual framing analysis and narrative analysis research techniques. The study qualitatively analyzed the contents of beer brand commercials and conducted an interview with the management of the ad agency for data collection. The data was presented in images and words. The findings showed that females are underrepresented and misrepresented in the beer brand commercials and that the beer brands are not producing commercials that adequately reflect the realities of present times. It was also found that very little has changed in the ad industry between the periods studied, and commercial screenplays are not written with a specific aim to either target the female demographics or give them equal opportunities to thrive in the beer economy. The study concluded that the gender gap in beer commercials subsists and translates to gender discrimination, especially since it is established that females are also stakeholders in the beer economy. The study recommends that beer brands should produce commercials that appeal to their audience irrespective of gender, reflect contemporary realities, and give all genders equal opportunities to thrive in the increasingly competitive industry.

Keywords: beer brands, commercials, gender representation, visuals, television, YouTube

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid distributed algorithm has been suggested for the multi-objective job shop scheduling problem. Many new approaches are used at design steps of the distributed algorithm. Co-evolutionary structure of the algorithm and competition between different communicated hybrid algorithms, which are executed simultaneously, causes to efficient search. Using several machines for distributing the algorithms, at the iteration and solution levels, increases computational speed. The proposed algorithm is able to find the Pareto solutions of the big problems in shorter time than other algorithm in the literature. Apache Spark and Hadoop platforms have been used for the distribution of the algorithm. The suggested algorithm and implementations have been compared with results of the successful algorithms in the literature. Results prove the efficiency and high speed of the algorithm.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, multi-objective optimization

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Authors: Hyun-Woo Cho

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For ensuring the safety of a manufacturing process one should quickly identify an assignable cause of a fault in an on-line basis. To this end, many statistical techniques including linear and nonlinear methods have been frequently utilized. However, such methods possessed a major problem of small sample size, which is mostly attributed to the characteristics of empirical models used for reference models. This work presents a new method to overcome the insufficiency of measurement data in the monitoring and diagnosis tasks. Some quasi-measurement data are generated from existing data based on the two indices of similarity and importance. The performance of the method is demonstrated using a real data set. The results turn out that the presented methods are able to handle the insufficiency problem successfully. In addition, it is shown to be quite efficient in terms of computational speed and memory usage, and thus on-line implementation of the method is straightforward for monitoring and diagnosis purposes.

Keywords: data analysis, diagnosis, monitoring, process data, quality control

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Authors: Hassan M. H. Mustafa

Abstract:

This piece of research addresses an interesting comparative analytical study. Which considers two concepts of diverse algorithmic computational intelligence approaches related tightly with Neural and Non-Neural Systems. The first algorithmic intelligent approach concerned with observed obtained practical results after three neural animal systems’ activities. Namely, they are Pavlov’s, and Thorndike’s experimental work. Besides a mouse’s trial during its movement inside figure of eight (8) maze, to reach an optimal solution for reconstruction problem. Conversely, second algorithmic intelligent approach originated from observed activities’ results for Non-Neural Ant Colony System (ACS). These results obtained after reaching an optimal solution while solving Traveling Sales-man Problem (TSP). Interestingly, the effect of increasing number of agents (either neurons or ants) on learning performance shown to be similar for both introduced systems. Finally, performance of both intelligent learning paradigms shown to be in agreement with learning convergence process searching for least mean square error LMS algorithm. While its application for training some Artificial Neural Network (ANN) models. Accordingly, adopted ANN modeling is a relevant and realistic tool to investigate observations and analyze performance for both selected computational intelligence (biological behavioral learning) systems.

Keywords: artificial neural network modeling, animal learning, ant colony system, traveling salesman problem, computational biology

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Authors: Faiza Hussain, Usman Qamar

Abstract:

Synonym-based searching is recognized to be a complicated problem as text mining from unstructured data of web is challenging. Finding useful information which matches user need from bulk of web pages is a cumbersome task. In this paper, a novel and practical synonym retrieval technique is proposed for addressing this problem. For replacement of semantics, user intent is taken into consideration to realize the technique. Parts-of-Speech tagging is applied for pattern generation of the query and a thesaurus for this experiment was formed and used. Comparison with Non-Context Based Searching, Context Based searching proved to be a more efficient approach while dealing with linguistic semantics. This approach is very beneficial in doing intent based searching. Finally, results and future dimensions are presented.

Keywords: natural language processing, text mining, information retrieval, parts-of-speech tagging, grammar, semantics

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Authors: Haci Mehmet Guzey, Levent Acar

Abstract:

In this paper, a novel decentralized controller is developed for linear systems with nonlinear unknown interconnections. A model linear decoupled system is assigned for each system. By using the difference actual and model state dynamics, the problem is formulated as inverse problem. Then, the interconnected dynamics are approximated by using Galerkin’s expansion method for inverse problems. Two different sets of orthogonal basis functions are utilized to approximate the interconnected dynamics. Approximated interconnections are utilized in the controller to cancel the interconnections and decouple the systems. Subsequently, the interconnected systems behave as a collection of decoupled systems.

Keywords: decentralized control, inverse problems, large scale systems, nonlinear interconnections, basis functions, system identification

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Authors: Jeerasak Wisatphan, Nara Samattapapong

Abstract:

This study's goals were to enhance nitroglycerin manufacturing efficiency through simulation, recover nitroglycerin from the storage facility, and enhance nitroglycerine recovery and purge systems. It was found that the problem was nitroglycerin reflux. Therefore, the researcher created three alternatives to solve the problem. The system of Nitroglycerine Recovery and Purge was then simulated using the FlexSim program, and each alternative was tested. The results demonstrate that the alternative system-led Nitroglycerine Recovery and Nitroglycerine Purge System collaborate to produce Nitroglycerine, which is more efficient than other alternatives and can reduce production time. It can also improve the recovery of nitroglycerin. It also serves as a guideline for developing a real-world system and modeling it for training staff without wasting raw chemical materials or fuel energy.

Keywords: efficiency increase, nitroglycerine recovery and purge system, production improvement, simulation

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Authors: Nurul Liyana Abdul Aziz, Nur Aidya Hanum Aizam

Abstract:

Course timetabling problems occur every semester in a university which includes the allocation of resources (subjects, lecturers and students) to a number of fixed rooms and timeslots. The assignment is carried out in a way such that there are no conflicts within rooms, students and lecturers, as well as fulfilling a range of constraints. The constraints consist of rules and policies set up by the universities as well as lecturers’ and students’ preferences of courses to be allocated in specific timeslots. This paper specifically focuses on the preferences of the course timetabling problem in one of the public universities in Malaysia. The demands will be considered into our existing mathematical model to make it more generalized and can be used widely. We have distributed questionnaires to a number of lecturers and students of the university to investigate their demands and preferences for their desired course timetable. We classify the preferences thus converting them to construct one mathematical model that can produce such timetable.

Keywords: university course timetabling problem, integer programming, preferences, constraints

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Authors: Syeda Mahnaz Hassan

Abstract:

Social work as a specialized field, grounded in scientific knowledge and skills, is more inclined towards problem-solving process rather than charity focused approach. Medical social work, as a primary method, deals with the bio-psychosocial-spiritual elements of an individual with a problem and assesses the pliability and strength of the patients, social support systems, and their families, to assist the patients to resolve their problems independently. The medical social worker, also known as case-worker or care-worker, has to play a substantial role in the rehabilitation and retrieval of an affected person. This paper examines the roles played and responsibilities discharged by the Medical Social Workers internationally and specifically concerning Pakistan. The capacity constraints and challenges confronted by Medical Social Workers in hospitals have also been highlighted, and some policy implications have been suggested to enhance the capabilities of Medical Social Workers for serving the patients in a befitting manner.

Keywords: medical social work, Pakistan, patients, rehabilitation

Procedia PDF Downloads 340