Search results for: Effective Electric Field and Effective Mobility Model.

Authors: Paitoon Kraipornsak

Abstract:

Government spending is categorized into consumption spending and capital spending. Three categories of private consumption are used: food consumption, nonfood consumption, and services consumption. The estimated model indicates substitution effects of government consumption spending on budget shares of private nonfood consumption and of government capital spending on budget share of private food consumption. However, the results do not indicate whether the negative effects of changes in the budget shares of the nonfood and the food consumption equates to reduce total private consumption. The concept of aggregate demand comprising consumption, investment, government spending (consumption spending and capital spending), export, and import are used to estimate their relationship by using the Vector Error Correction Mechanism. The study found no effect of government capital spending on either the private consumption or the growth of GDP while the government consumption spending has negative effect on the growth of GDP.

Keywords: Complementary effect, government capital spending, government consumption spending, private consumption on food, nonfood, and services, substitution effect, vector error correction mechanism.

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Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection.

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Authors: Roman Klas, František Pochylý, Pavel Rudolf

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This paper is focused on the CFD simulation of the radiaxial pump (i.e. mixed flow pump) with the aim to detect the reasons of Y-Q characteristic instability. The main reasons of pressure pulsations were detected by means of the analysis of velocity and pressure fields within the pump combined with the theoretical approach. Consequently, the modifications of spiral case and pump suction area were made based on the knowledge of flow conditions and the shape of dissipation function. The primary design of pump geometry was created as the base model serving for the comparison of individual modification influences. The basic experimental data are available for this geometry. This approach replaced the more complicated and with respect to convergence of all computational tasks more difficult calculation for the compressible liquid flow. The modification of primary pump consisted in inserting the three fins types. Subsequently, the evaluation of pressure pulsations, specific energy curves and visualization of velocity fields were chosen as the criterion for successful design. 

Keywords: CFD, radiaxial pump, spiral case, stability

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Authors: Huei Chu Weng

Abstract:

This paper presents a study on the effect of second-order slip on forced convection through a long isoflux heated or cooled planar microchannel. The fully developed solutions of flow and thermal fields are analytically obtained on the basis of the second-order Maxwell-Burnett slip and local heat flux boundary conditions. Results reveal that when the average flow velocity increases or the wall heat flux amount decreases, the role of thermal creep becomes more insignificant, while the effect of second-order slip becomes larger. The second-order term in the Deissler slip boundary condition is found to contribute a positive velocity slip and then to lead to a lower pressure drop as well as a lower temperature rise for the heated-wall case or to a higher temperature rise for the cooled-wall case. These findings are contrary to predictions made by the Karniadakis slip model.

Keywords: Microfluidics, forced convection, thermal creep, second-order boundary conditions.

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Authors: Moghiman Mohammad, Amiri Maryam, Amiri Amirhosein

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The present paper develops and validates a numerical procedure for the calculation of turbulent combustive flow in converging and diverging ducts and throuh simulation of the heat transfer processes, the amount of production and spread of Nox pollutant has been measured. A marching integration solution procedure employing the TDMA is used to solve the discretized equations. The turbulence model is the Prandtl Mixing Length method. Modeling the combustion process is done by the use of Arrhenius and Eddy Dissipation method. Thermal mechanism has been utilized for modeling the process of forming the nitrogen oxides. Finite difference method and Genmix numerical code are used for numerical solution of equations. Our results indicate the important influence of the limiting diverging angle of diffuser on the coefficient of recovering of pressure. Moreover, due to the intense dependence of Nox pollutant to the maximum temperature in the domain with this feature, the Nox pollutant amount is also in maximum level.

Keywords: Converging and Diverging Duct, Combustion, Diffuser, Diverging Angle, Nox

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Authors: M. Irannezhad, E. H. N. Gashti, U. Moback, B. Kløve

Abstract:

Climate change would cause mean sea level to rise +1 m by 2100. To prevent coastal floods resulting from the sea level rising, different flood control structures have been built, with acceptable protection levels. Gothenburg with the River Göta älv located on the southwest coast of Sweden is a vulnerable city to the accelerated rises in mean sea level. We evaluated using a sea barrage in the River Göta älv to protect Gothenburg during this century. The highest sea level was estimated to 2.95 m above the current mean sea level by 2100. To verify flood protection against such high sea levels, both barriers have to be closed. To prevent high water level in the River Göta älv reservoir, the barriers would be open when the sea level is low. The suggested flood control structures would successfully protect the city from flooding events during this century.

Keywords: Climate change, Flood control structures, Gothenburg, Sea level rising, Water level model.

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Authors: Ahmed G. Mahgoub, Dahlia H. Hafez, Mostafa A. Abu Kiefa

Abstract:

The Cone Penetration Test (CPT) is a common in-situ test which generally investigates a much greater volume of soil more quickly than possible from sampling and laboratory tests. Therefore, it has the potential to realize both cost savings and assessment of soil properties rapidly and continuously. The principle objective of this paper is to demonstrate the feasibility and efficiency of using artificial neural networks (ANNs) to predict the soil angle of internal friction (Φ) and the soil modulus of elasticity (E) from CPT results considering the uncertainties and non-linearities of the soil. In addition, ANNs are used to study the influence of different parameters and recommend which parameters should be included as input parameters to improve the prediction. Neural networks discover relationships in the input data sets through the iterative presentation of the data and intrinsic mapping characteristics of neural topologies. General Regression Neural Network (GRNN) is one of the powerful neural network architectures which is utilized in this study. A large amount of field and experimental data including CPT results, plate load tests, direct shear box, grain size distribution and calculated data of overburden pressure was obtained from a large project in the United Arab Emirates. This data was used for the training and the validation of the neural network. A comparison was made between the obtained results from the ANN's approach, and some common traditional correlations that predict Φ and E from CPT results with respect to the actual results of the collected data. The results show that the ANN is a very powerful tool. Very good agreement was obtained between estimated results from ANN and actual measured results with comparison to other correlations available in the literature. The study recommends some easily available parameters that should be included in the estimation of the soil properties to improve the prediction models. It is shown that the use of friction ration in the estimation of Φ and the use of fines content in the estimation of E considerable improve the prediction models.

Keywords: Angle of internal friction, Cone penetrating test, General regression neural network, Soil modulus of elasticity.

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Authors: Phruksaphanrat B.

Abstract:

This research proposes a Preemptive Possibilistic Linear Programming (PPLP) approach for solving multiobjective Aggregate Production Planning (APP) problem with interval demand and imprecise unit price and related operating costs. The proposed approach attempts to maximize profit and minimize changes of workforce. It transforms the total profit objective that has imprecise information to three crisp objective functions, which are maximizing the most possible value of profit, minimizing the risk of obtaining the lower profit and maximizing the opportunity of obtaining the higher profit. The change of workforce level objective is also converted. Then, the problem is solved according to objective priorities. It is easier than simultaneously solve the multiobjective problem as performed in existing approach. Possible range of interval demand is also used to increase flexibility of obtaining the better production plan. A practical application of an electronic company is illustrated to show the effectiveness of the proposed model.

Keywords: Aggregate production planning, Fuzzy sets theory, Possibilistic linear programming, Preemptive priority

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Authors: C. Ardil

Abstract:

Multidimensional compromise programming evaluation of digital commerce websites is essential not only to have recommendations for improvement, but also to make comparisons with global business competitors. This research provides a multidimensional decision making model that prioritizes the objective criteria weights of various commerce websites using multidimensional compromise solution. Evaluation of digital commerce website quality can be considered as a complex information system structure including qualitative and quantitative factors for a multicriteria decision making problem. The proposed multicriteria decision making approach mainly consists of three sequential steps for the selection problem. In the first step, three major different evaluation criteria are characterized for website ranking problem. In the second step, identified critical criteria are weighted using the standard deviation procedure. In the third step, the multidimensional compromise programming is applied to rank the digital commerce websites.

Keywords: Standard deviation, commerce website, website evaluation, multicriteria decision making, multicriteria compromise programming, website quality, multidimensional decision analysis.

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Authors: Mária Stachová, Lukáš Sobíšek

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Data mining incorporates a group of statistical methods used to analyze a set of information, or a data set. It operates with models and algorithms, which are powerful tools with the great potential. They can help people to understand the patterns in certain chunk of information so it is obvious that the data mining tools have a wide area of applications. For example in the theoretical chemistry data mining tools can be used to predict moleculeproperties or improve computer-assisted drug design. Classification analysis is one of the major data mining methodologies. The aim of thecontribution is to create a classification model, which would be able to deal with a huge data set with high accuracy. For this purpose logistic regression, Bayesian logistic regression and random forest models were built using R software. TheBayesian logistic regression in Latent GOLD software was created as well. These classification methods belong to supervised learning methods. It was necessary to reduce data matrix dimension before construct models and thus the factor analysis (FA) was used. Those models were applied to predict the biological activity of molecules, potential new drug candidates.

Keywords: data mining, classification, drug design, QSAR

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Authors: Provides Ng

Abstract:

Platform economy is a peer-to-peer model of distributing resources facilitated by community-based digital platforms. In recent years, digital platforms are rapidly reconfiguring the public realm using hyper-personalisation techniques. This paper aims at investigating how urban planning can leapfrog into the digital age to help relieve the rising tension of the global issue of labour flow; it discusses the means to transfer techniques of hyper-personalisation into urban planning for plasticity using platform technologies. This research first denotes the limitations of the current system of urban residency, where the system maintains itself on the circulation of documents, which are data on paper. Then, this paper tabulates how some of the institutions around the world, both public and private, digitise data, and streamline communications between a network of systems and citizens using platform technologies. Subsequently, this paper proposes ways in which hyper-personalisation can be utilised to form a digital planning platform. Finally, this paper concludes by reviewing how the proposed strategy may help to open up new ways of thinking about how we affiliate ourselves with cities.

Keywords: Platform urbanism, hyper-personalisation, urban residency, digital data.

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Authors: Guillermo Romero-Jiménez, Víctor Jiménez-Sánchez, Edgardo J. Roldán-Villasana

Abstract:

This paper describes the development of a control system model using a graphical software tool. This control system is part of an operator training simulator developed for the National Training Center for Operators of Ixtapantongo (CNCAOI, acronym according to its name in Spanish language) of the Mexico-s Federal Commission of Electricity, CFE). The Department of Simulation of the Electrical Research Institute (IIE) developed this simulator using as reference the Unit I of the Combined Cycle Power Plant El Sauz, located at the centre of Mexico. The first step in the project was the developing of the Gas Turbine System and its control system simulator. The Turbo Gas simulator was finished and delivered to CNCAOI in March 2007 for commercial operation. This simulator is a high-fidelity real time dynamic simulator built and tested for accurate operation over the entire load range. The simulator was used primarily for operator training although it has been used for procedure development and evaluation of plant transients.

Keywords: Operators training, Power plant simulator, simulation environment.

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Authors: Penghui Zhang, Hua Zhang, Jun-Bo Wang, Cheng Zeng, Zijian Cao

Abstract:

With the development of software-defined networks and programmable data planes, in-band network telemetry (INT) has become an emerging technology in communications because it can get accurate and real-time network information. However, due to the expansion of the network scale, existing telemetry systems, to the best of the authors’ knowledge, have difficulty in meeting the common requirements of low overhead, low latency and full coverage for traffic measurement. This paper proposes a network-wide telemetry system with a low-latency low-overhead path planning (INT-LLPP). This paper builds a mathematical model to analyze the telemetry overhead and latency of INT systems. Then, we adopt a greedy-based path planning algorithm to reduce the overhead and latency of the network telemetry with the full network coverage. The simulation results show that network-wide telemetry is achieved and the telemetry overhead can be reduced significantly compared with existing INT systems. INT-LLPP can control the system latency to get real-time network information.

Keywords: Network telemetry, network monitoring, path planning, low latency.

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Authors: M.Nafar, A.H.Gheisari, A.Alesaadi

Abstract:

Since large power transformers are the most expensive and strategically important components of any power generator and transmission system, their reliability is crucially important for the energy system operation. Also, Circuit breakers are very important elements in the power transmission line so monitoring the events gives a knowledgebase to determine time to the next maintenance. This paper deals with the introduction of the comparative method of the state estimation of transformers and Circuit breakers using continuous monitoring of voltage, current. This paper gives details a new method based on wavelet to apparatus insulation monitoring. In this paper to insulation monitoring of transformer, a new method based on wavelet transformation and neutral point analysis is proposed. Using the EMTP tools, fault in transformer winding and the detailed transformer winding model were simulated. The current of neutral point of winding was analyzed by wavelet transformation. It is shown that the neutral current of the transformer winding has useful information about fault in insulation of the transformer.

Keywords: Wavelet, Power Transformer, EMTP, CircuitBreaker, Monitoring

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Authors: Wei Zhang, Lifen Zhao

Abstract:

The present study aims to translate and validate the Career Motivation Scale among Chinese University and vocational college teachers. Exploratory factor analysis supported a three-factor structure that was consistent with the original structure of career motivation: career insight, career identity, and career resilience. Confirmatory factor analysis showed that a second-order three-factor model with correlated measurement errors best fit the data. Configural, metric, and scalar invariance models were tested, demonstrating that the Chinese version of the Career Motivation Scale did not differ across groups of school type, educational level, and working years in current institutions. The concurrent validity of the Chinese Career Motivation Scale was confirmed by its significant correlations with work engagement, career adaptability, career satisfaction, job crafting, and intention to quit. The results of the study indicated that the Chinese Career Motivation Scale was a valid and reliable measure of career motivation among university and vocational college teachers in China.

Keywords: Career motivation scale, Chinese university and vocational college teachers, measurement invariance, validation.

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Authors: Ming Wen, Nasim Nezamoddini

Abstract:

Sophisticated numerical simulations like finite element analysis (FEA) involve a complicated process from model setup to post-processing tasks that require replication of time-consuming steps. Utilizing FEA automation program simplifies the complexity of the involved steps while minimizing human errors in analysis set up, calculations, and results processing. One of the main challenges in designing FEA automation programs is to identify user requirements and link them to possible design alternatives. This paper presents a decision-making framework to design a Python based FEA automation program for modal analysis, frequency response analysis, and random vibration fatigue (RVF) analysis procedures. Analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are applied to evaluate design alternatives considering the feedback received from experts and program users.

Keywords: FEA, random vibration fatigue, process automation, AHP, TOPSIS, multiple-criteria decision-making, MCDM.

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Authors: Neville Fernandes, Satish Shenoy B., Raghuvir Pai B., Rammohan S. Pai B, Shrikanth Rao.D

Abstract:

This research details a Computational Fluid Dynamics (CFD) approach to model fluid flow in a journal bearing with 8 equispaced semi-circular axial grooves. Water is used as the lubricant and is fed from one end of the bearing to the other, under pressure. The geometry of the bearing is modeled using a commercially available modeling software GAMBIT and the flow analysis is performed using a dedicated CFD analysis software FLUENT. The pressure distribution in the bearing clearance is obtained from FLUENT for various whirl ratios and is used to calculate the hydrodynamic force components in the radial and tangential direction of the bearing. These values along with the various whirl speeds can be used to do a regression analysis to determine the stiffness and damping coefficients. The values obtained are then compared with the stiffness and damping coefficients of a 3 Axial groove water lubricated journal bearing and those obtained from a FORTRAN code for a similar bearing.

Keywords: CFD, multiple axial groove, Water lubricated, Stiffness and Damping Coefficients.

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Authors: K. Govender, M. Sinclair

Abstract:

This paper demonstrates a proof of concept whereby shorter trips and land use densification can be promoted through an alternative approach to planning and implementation of road infrastructure in the South African context. It briefly discusses how the development of the Compact City concept relies on a combination of promoting shorter trips and densification through a change in focus in road infrastructure provision. The methodology developed in this paper uses a traffic model to test the impact of synthesized deterrence functions on congestion locations in the road network through the assignment of traffic on the study network. The results from this study demonstrate that intelligent planning of road infrastructure can indeed promote reduced urban sprawl, increased residential density and mixed-use areas which are supported by an efficient public transport system; and reduced dependence on the freeway network with a fixed road infrastructure budget. The study has resonance for all cities where urban sprawl is seemingly unstoppable.

Keywords: Compact cities, densification, road infrastructure planning, transportation modeling.

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Authors: Jianguo Tang, Kun She, William Zhu

Abstract:

Covering-based rough sets is an extension of rough sets and it is based on a covering instead of a partition of the universe. Therefore it is more powerful in describing some practical problems than rough sets. However, by extending the rough sets, covering-based rough sets can increase the roughness of each model in recognizing objects. How to obtain better approximations from the models of a covering-based rough sets is an important issue. In this paper, two concepts, determinate elements and indeterminate elements in a universe, are proposed and given precise definitions respectively. This research makes a reasonable refinement of the covering-element from a new viewpoint. And the refinement may generate better approximations of covering-based rough sets models. To prove the theory above, it is applied to eight major coveringbased rough sets models which are adapted from other literature. The result is, in all these models, the lower approximation increases effectively. Correspondingly, in all models, the upper approximation decreases with exceptions of two models in some special situations. Therefore, the roughness of recognizing objects is reduced. This research provides a new approach to the study and application of covering-based rough sets.

Keywords: Determinate element, indeterminate element, refinementof covering-element, refinement of covering, covering-basedrough sets.

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Authors: Chang-Uk Kwak, Sun-Joong Kim, Seong-Bae Park, Sang-Jo Lee

Abstract:

This paper proposes a method of learning topics for broadcasting contents. There are two kinds of texts related to broadcasting contents. One is a broadcasting script, which is a series of texts including directions and dialogues. The other is blogposts, which possesses relatively abstracted contents, stories, and diverse information of broadcasting contents. Although two texts range over similar broadcasting contents, words in blogposts and broadcasting script are different. When unseen words appear, it needs a method to reflect to existing topic. In this paper, we introduce a semantic vocabulary expansion method to reflect unseen words. We expand topics of the broadcasting script by incorporating the words in blogposts. Each word in blogposts is added to the most semantically correlated topics. We use word2vec to get the semantic correlation between words in blogposts and topics of scripts. The vocabularies of topics are updated and then posterior inference is performed to rearrange the topics. In experiments, we verified that the proposed method can discover more salient topics for broadcasting contents.

Keywords: Broadcasting script analysis, topic expansion, semantic correlation analysis, word2vec.

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Authors: Essa Abrahim Abdulgader Saleem, Thien-My Dao

Abstract:

The main objective of this paper is to optimize series-parallel system reliability using Genetic Algorithm (GA) and statistical analysis; considering system reliability constraints which involve the redundant numbers of selected components, total cost, and total weight. To perform this work, firstly the mathematical model which maximizes system reliability subject to maximum system cost and maximum system weight constraints is presented; secondly, a statistical analysis is used to optimize GA parameters, and thirdly GA is used to optimize series-parallel systems reliability. The objective is to determine the strategy choosing the redundancy level for each subsystem to maximize the overall system reliability subject to total cost and total weight constraints. Finally, the series-parallel system case study reliability optimization results are showed, and comparisons with the other previous results are presented to demonstrate the performance of our GA.

Keywords: Genetic algorithm, optimization, reliability, statistical analysis.

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Authors: Hassan Ezzaidi, Jean Rouat

Abstract:

Recently many research has been conducted to retrieve pertinent parameters and adequate models for automatic music genre classification. In this paper, two measures based upon information theory concepts are investigated for mapping the features space to decision space. A Gaussian Mixture Model (GMM) is used as a baseline and reference system. Various strategies are proposed for training and testing sessions with matched or mismatched conditions, long training and long testing, long training and short testing. For all experiments, the file sections used for testing are never been used during training. With matched conditions all examined measures yield the best and similar scores (almost 100%). With mismatched conditions, the proposed measures yield better scores than the GMM baseline system, especially for the short testing case. It is also observed that the average discrimination information measure is most appropriate for music category classifications and on the other hand the divergence measure is more suitable for music subcategory classifications.

Keywords: Audio feature, information measures, music genre.

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Authors: P. C. Tewari, Rajiv Kumar, Dinesh Khanduja

Abstract:

This paper discusses the performance modeling and availability analysis of Yarn Dyeing System of a Textile Industry. The Textile Industry is a complex and repairable engineering system. Yarn Dyeing System of Textile Industry consists of five subsystems arranged in series configuration. For performance modeling and analysis of availability, a performance evaluating model has been developed with the help of mathematical formulation based on Markov-Birth-Death Process. The differential equations have been developed on the basis of Probabilistic Approach using a Transition Diagram. These equations have further been solved using normalizing condition in order to develop the steady state availability, a performance measure of the system concerned. The system performance has been further analyzed with the help of decision matrices. These matrices provide various availability levels for different combinations of failure and repair rates for various subsystems. The findings of this paper are therefore, considered to be useful for the analysis of availability and determination of the best possible maintenance strategies which can be implemented in future to enhance the system performance.

Keywords: Availability Analysis, Markov Process, Performance Modeling, Steady State Availability.

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Authors: Mayar A. Omar, Ismail Gomaa, Heba Badawy, Hosam Moubarak

Abstract:

Enterprise resource planning (ERP) is an integrated system that helps companies in managing their resources. There are two types of ERP systems, the traditional ERP systems, and the cloud ERP systems. Cloud ERP systems were introduced after the development of cloud computing technology. This research aims to identify the factors that affect the adoption of cloud ERP in Egyptian companies. Moreover, the aim of our study is to provide guidance to Egyptian companies in the cloud ERP adoption decision and to participate in increasing the number of the cloud ERP studies that are conducted in the Middle East and in developing countries. There are many factors influencing the adoption of cloud ERP in Egyptian organizations which are discussed and explained in the research. Those factors are examined through combining the Diffusion of Innovation theory (DOI) and technology-organization-environment framework (TOE). Data were collected through a survey that was developed using constructs from the existing studies of cloud computing and cloud ERP technologies and was then modified to fit our research. The analysis of the data was based on Structural Equation Modeling (SEM) using Smart PLS software that was used for the empirical analysis of the research model.

Keywords: cloud computing, cloud ERP systems, DOI, Egypt, SEM, TOE

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Authors: Tuqa Abdulrazzaq, Hussein Togun, M. K. A. Ariffin, S. N. Kazi, A. Badarudin, N. M Adam, S. Masuri

Abstract:

Numerical study of heat transfer and fluid flow over vertical double forward facing step were presented. The k-w model with finite volume method was employed to solve continuity, momentum, and energy equations. Different step heights were adopted for range of Reynolds number varied from 10000 to 40000, and range of temperature varied from 310K to 340 K. The straight side of duct is insulated while the side of double forward facing step is heated. The result shows augmentation of heat transfer due to the recirculation region created after and before steps. Effect of step length and Reynolds number observed on increase of local Nusselt number particularly at recirculation regions. Contour of streamline velocity is plotted to show recirculation regions after and before steps. Numerical simulation in this paper done by used ANSYS FLUENT 14.

Keywords: Turbulent flow, Double forward, Heat transfer, Separation flow.

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Authors: Hamed Rahmani, Wim Groot

Abstract:

The term "youth not in employment, education or training (NEET)" refers to a combination of youth unemployment and school dropout. This study investigates the variables that increase the risk of becoming NEET in Iran. A selection bias-adjusted Probit model was employed using machine learning to identify these risk factors. We used cross-sectional data obtained from the Statistical Center of Iran and the Ministry of Cooperatives Labor and Social Welfare that are taken from the labor force survey conducted in the spring of 2021. We look at years of education, work experience, housework, the number of children under the age of 6 years in the home, family education, birthplace, and the amount of land owned by households. Results show that hours spent performing domestic chores enhance the likelihood of youth becoming NEET, and years of education, years of potential work experience decrease the chance of being NEET. The findings also show that female youth born in cities were less likely than those born in rural regions to become NEET.

Keywords: NEET youth, probit, CART, machine learning, unemployment.

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Authors: Aimen Batool Bint-E-Rashid, Syed Muhammad Dawood Ali Shah, Muhammad Usman Farooq, Mahgul Anwar

Abstract:

As the world is progressing, the needs and demands of the consumer market are also changing. Nowadays the trends of consumer purchase decisions are dependent upon multiple factors. This study aims to identify the influential impact of country of origin over the perception and devotion towards daily personal care products specifically in reference to the knowledge and awareness regarding that particular brand in Pakistan. To corroborate this study, a 30-item brand origin questionnaire has been used with 300 purchase decision makers belonging to different age groups. To illustrate this study, a model has been developed based on brand origin, brand awareness and brand loyalty. Correlation and regression analysis have been used to find out the results which conclude the findings on the perspective of Pakistan’s consumer market as that brand origin has a direct relationship with brand loyalty provided that the consumer has a positive brand awareness. Support for the fact that brand origin impacts brand loyalty through brand awareness has been presented in this study.

Keywords: Brand awareness, brand loyalty, brand origin, personal care products, P&G, Unilever.

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Authors: Silvia Santano Guillén, Luigi Lo Iacono, Christian Meder

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One of the main aims of current social robotic research is to improve the robots’ abilities to interact with humans. In order to achieve an interaction similar to that among humans, robots should be able to communicate in an intuitive and natural way and appropriately interpret human affects during social interactions. Similarly to how humans are able to recognize emotions in other humans, machines are capable of extracting information from the various ways humans convey emotions—including facial expression, speech, gesture or text—and using this information for improved human computer interaction. This can be described as Affective Computing, an interdisciplinary field that expands into otherwise unrelated fields like psychology and cognitive science and involves the research and development of systems that can recognize and interpret human affects. To leverage these emotional capabilities by embedding them in humanoid robots is the foundation of the concept Affective Robots, which has the objective of making robots capable of sensing the user’s current mood and personality traits and adapt their behavior in the most appropriate manner based on that. In this paper, the emotion recognition capabilities of the humanoid robot Pepper are experimentally explored, based on the facial expressions for the so-called basic emotions, as well as how it performs in contrast to other state-of-the-art approaches with both expression databases compiled in academic environments and real subjects showing posed expressions as well as spontaneous emotional reactions. The experiments’ results show that the detection accuracy amongst the evaluated approaches differs substantially. The introduced experiments offer a general structure and approach for conducting such experimental evaluations. The paper further suggests that the most meaningful results are obtained by conducting experiments with real subjects expressing the emotions as spontaneous reactions.

Keywords: Affective computing, emotion recognition, humanoid robot, Human-Robot-Interaction (HRI), social robots.

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Authors: Panagiotis Platanitis

Abstract:

Purpose: This research paper seeks to review the empirical studies in the field of expatriate adjustment in East Asia in order to produce a thematic understanding of the current adjustment challenges, thus enabling practitioners to enrich their knowledge. Background: Learning to live, work, and function in a country and culture vastly different from that of one’s upbringing can pose some unique challenges in terms of adaptation and adjustment. This has led to a growing body of research about the adjustment of expatriate workers. Adjustment itself has been posited as a three-dimensional construct; work adjustment, interaction adjustment and general or cultural adjustment. Methodology: This qualitative systematic review has been conducted on all identified peer-reviewed empirical studies related to expatriate adjustment in East Asia. Five electronic databases (PsychInfo, Emerald, Scopus, EBSCO and JSTOR) were searched to December 2015. Out of 625 identified records, thorough evaluation for eligibility resulted in 15 relevant studies being subjected to data analysis. The quality of the identified research was assessed according to the Standard Quality Assessment Criteria for Evaluating Primary Research Papers from a Variety of Fields. The data were analysed by means of thematic synthesis for systematic reviews of qualitative research. Findings: Data analysis revealed five key themes. The themes developed were: (1) personality traits (2) types of adjustment, (3) language, (4) culture and (5) coping strategies. Types of adjustment included subthemes such as: Interaction, general, work, psychological, sociocultural and cross-cultural adjustment. Conclusion: The present review supported previous literature on the different themes of adjustment and it takes the focus from work and general adjustment to the psychological challenges and it introduces the psychological adjustment. It also gives a different perspective about the use of cross-cultural training and the coping strategies expatriates use when they are abroad. This review helps counselling psychologists to understand the importance of a multicultural approach when working with expatriates and also to be aware of what expatriates might face when working and living in East Asia.

Keywords: Expatriates, adjustment, East Asia, counselling psychology.

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Authors: Turki M. Habeebullah, Atef M. F. Mohammed, Essam A. Morsy

Abstract:

In recent decades, particulate matter (PM10) have received much attention due to its potential adverse health impact and the subsequent need to better control or regulate these pollutants. The aim of this paper is focused on study risk assessment of PM10 in four different districts (Shebikah, Masfalah, Aziziyah, Awali) in Makkah, Saudi Arabia during the period from 1 Ramadan 1434 AH - 27 Safar 1435 AH. Samples were collected by using Low Volume Sampler (LVS Low Volume Sampler) device and filtration method for estimating the total concentration of PM10. The study indicated that the mean PM10 concentrations were 254.6 (186.1 - 343.2) μg/m3 in Shebikah, 184.9 (145.6 - 271.4) μg/m3 in Masfalah, 162.4 (92.4-253.8) μg/m3 in Aziziyah, and 56.0 (44.5 - 119.8) μg/m3 in Awali. These values did not exceed the permissible limits in PME (340 μg/m3 as daily average). Furthermore, health assessment is carried out using AirQ2.2.3 model to estimate the number of hospital admissions due to respiratory diseases. The cumulative number of cases per 100,000 were 1534 (18-3050 case), which lower than that recorded in the United States, Malaysia. The concentration response coefficient was 0.49 (95% CI 0.05 - 0.70) per 10 μg/m3 increase of PM10.

Keywords: Air pollution, Respiratory diseases, AirQ2.2.3, Makkah.

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