Search results for: mental tasks

Authors: Mitko Veta, Tomislav Kartalov, Zoran Ivanovski

Abstract:

Organization of video databases is becoming difficult task as the amount of video content increases. Video classification based on the content of videos can significantly increase the speed of tasks such as browsing and searching for a particular video in a database. In this paper, a content-based videos classification system for the classes indoor and outdoor is presented. The system is intended to be used on a mobile platform with modest resources. The algorithm makes use of the temporal redundancy in videos, which allows using an uncomplicated classification model while still achieving reasonable accuracy. The training and evaluation was done on a video database of 443 videos downloaded from a video sharing service. A total accuracy of 87.36% was achieved.

Keywords: Indoor/outdoor, video classification, imageclassification

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Authors: Haiyan Wang

Abstract:

Constructivism, the latest teaching and learning theory in western countries which is based on the premise that cognition (learning) is the result of "mental construction", lays emphasis on the learner's active learning. Guided by constructivism, this thesis discusses the teaching plan and its application in extensive reading course. In extensive reading classroom, emphasis should be laid on the activation of students' prior knowledge, grasping the skills of fast reading and the combination of reading and writing to check extracurricular reading. With three factors supplementing each other, students' English reading ability can be improved effectively.

Keywords: Constructivism, extensive reading, constructivist teaching.

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Authors: Nai-Chieh Wei, I-Ming Chao, Chin-Jung Liuand, Hong Long Chen

Abstract:

This paper combines the branch-and-bound method and the petri net to solve the two-sided assembly line balancing problem, thus facilitating effective branching and pruning of tasks. By integrating features of the petri net, such as reachability graph and incidence matrix, the propose method can support the branch-and-bound to effectively reduce poor branches with systematic graphs. Test results suggest that using petri net in the branching process can effectively guide the system trigger process, and thus, lead to consistent results.

 

Keywords: Branch-and-Bound Method, Petri Net, Two-Sided Assembly Line Balancing Problem.

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Authors: Antonis Sideris, Elias Chlis Kalogeropoulos, Konstantia Moirogiorgou

Abstract:

The present study proposes a methodology for the efficient daily management of fleet vehicles and construction machinery. The application covers the area of remote monitoring of heavy-duty vehicles operation parameters, where specific sensor data are stored and examined in order to provide information about the vehicle’s health. The vehicle diagnostics allow the user to inspect whether maintenance tasks need to be performed before a fault occurs. A properly designed machine learning model is proposed for the detection of two different types of faults through classification. Cross validation is used and the accuracy of the trained model is checked with the confusion matrix.

Keywords: Fault detection, feature selection, machine learning, predictive maintenance.

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Authors: Seyed Mostafa Torabi

Abstract:

A Wireless sensor network (WSN) consists of a set of battery-powered nodes, which collaborate to perform sensing tasks in a given environment. Each node in WSN should be capable to act for long periods of time with scrimpy or no external management. One requirement for this independent is: in the presence of adverse positions, the sensor nodes must be capable to configure themselves. Hence, the nodes for determine the existence of unusual events in their surroundings should make use of position awareness mechanisms. This work approaches the problem by considering the possible unusual events as diseases, thus making it possible to diagnose them through their symptoms, namely, their side effects. Considering these awareness mechanisms as a foundation for highlevel monitoring services, this paper also shows how these mechanisms are included in the primal plan of an intrusion detection system.

Keywords: Awareness Mechanism, Intrusion Detection, Independent, Wireless Sensor Network

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Authors: Norihiro Nishio, Yuki Deguchi, Takahiro Sugiyama, Yoichi Takebayashi

Abstract:

We developed a multi-camera control system that a (one) cameraman can operate several cameras at a compact studio. we analyzed a workflow of a cameraman of some program shootings with two cameras and clarified their heavy tasks. The system based on a dynamic workflow which adapts a program progressing and recommends of cameraman. we perform the automation of multicamera controls by modeling of studio environment and perform automatic camera adjustment for suitable angle of view with face detection. Our experiment at a real program shooting showed that one cameraman can carry out the task of shooting sufficiently.

Keywords: Camera work, compact studio, dynamic workflow, shooting support.

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Authors: Tae Jin Choi, Jong Ok Kim, Sang Min Jin, Gilwon Yoon

Abstract:

Analysis of EEG brainwave provides information on mental or emotional states. One of the particular states that can have various applications in human machine interface (HMI) is concentration. 8-channel EEG signals were measured and analyzed. The concentration index was compared during resting and concentrating periods. Among eight channels, locations the frontal lobe (F_p1 and F_p2) showed a clear increase of the concentration index during concentration regardless of subjects. The rest six channels produced conflicting observations depending on subjects. At this time, it is not clear whether individual difference or how to concentrate made these results for the rest six channels. Nevertheless, it is expected that F_p1 and F_p2 are promising locations for extracting control signal for HMI applications.

Keywords: Concentration, EEG, human machine interface.

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Authors: Veruska C. Dutra, Lucio F. M. Adorno, Mary L. G. S. Senna

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From the start, the importance of having a plan to sustain tourism was acknowledged. The correct methods to monitor that type of tourism have been researched. Thus, we propose in this work to analyze the applicability of a monitoring and assistance method on the understanding of the tourism sustainability in a small size destiny or getaway. In this study, the subject is Lagoa da Confusão, in the state of Tocantins and the analysis was carried out through the efficiency of the local indicators, according to the WOT approach. We concluded that the sustainable tourism key points that were analyzed demonstrated to be important evaluation and quantification tools for the proposed tasks to be developed in the mentioned destiny. This is a study of an interdisciplinary character and the deductive method was chosen as the guiding line.

Keywords: Indicators, Lagoa da Confusão, Tocantins, Brazil, monitoring, sustainability.

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Authors: A. T. Omarova, G. N. Nakipova

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This article discusses the principles of object-oriented human capital development using the technology program. Also the article includes priorities of the strategy of industrial-innovative development of Kazakhstan in conditions of integration activity into the world community. The article shows the tasks of human resource management in the implementation of industrial and innovation development, particularities of Kazakhstan's theory of management staff, as well as due to the specificity of the Kazakhstan authorities. In the article had considered the factors which are affecting to the people in the organization and also had considered mechanisms of HRM within organization in the conditions of innovative development in Kazakhstan.

Keywords: Programming, management of human resources, innovation, investment, innovation process, HRD model, innovative development, integration, management, transformation, economic potential, competitiveness.

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Authors: Michaela Vašková, Jan Hrdlička, Otakar J. Mika, Jiří Barta, Gabriela Clemensová

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The paper is focused on the methods to solutions of the crisis situation in the Czech Republic associated with the mass methanol poisoning. The emphasis is put on tasks of individual state bodies and of Integrated Rescue System during the handling of the crisis. The theoretical part describes poisonings, ways of intoxication, types of intoxicants and cases of mass poisoning by dangerous substances in the world. The practical part describes the development, causes and solutions of extraordinary event, mass methanol poisoning in the Czech Republic. The main emphasis was put on the crisis management of the Czech Republic in solving this situation.

Keywords: Crisis management, poisoning, methanol, hazardous substances, extraordinary event.

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Authors: Essam Al-Daoud

Abstract:

Several combinations of the preprocessing algorithms, feature selection techniques and classifiers can be applied to the data classification tasks. This study introduces a new accurate classifier, the proposed classifier consist from four components: Signal-to- Noise as a feature selection technique, support vector machine, Bayesian neural network and AdaBoost as an ensemble algorithm. To verify the effectiveness of the proposed classifier, seven well known classifiers are applied to four datasets. The experiments show that using the suggested classifier enhances the classification rates for all datasets.

Keywords: AdaBoost, Bayesian neural network, Signal-to-Noise, support vector machine, MCMC.

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Authors: A. Pajaziti, H. Cana

Abstract:

In this paper, the structural genetic algorithm is used to optimize the neural network to control the joint movements of robotic arm. The robotic arm has also been modeled in 3D and simulated in real-time in MATLAB. It is found that Neural Networks provide a simple and effective way to control the robot tasks. Computer simulation examples are given to illustrate the significance of this method. By combining Genetic Algorithm optimization method and Neural Networks for the given robotic arm with 5 D.O.F. the obtained the results shown that the base joint movements overshooting time without controller was about 0.5 seconds, while with Neural Network controller (optimized with Genetic Algorithm) was about 0.2 seconds, and the population size of 150 gave best results.

Keywords: Robotic Arm, Neural Network, Genetic Algorithm, Optimization.

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Authors: Katarzyna Antosz, DorotaStadnicka

Abstract:

Having regard to the necessity of maintaining the technical infrastructure in a proper condition that ensures production continuity, companies decide to implement modern methods of technological machines park management. These methods include TPM, RCM and outsourcing. Large companies, in particular, are ready to invest in the implementation of these methods because of a great number of machines and a wide range of tasks of their technical service. Methodology of implementing these methods is well known. The aim of the studies, of which the results are presented in this publication, was the identification of real actions that are conducted in enterprises within the application of the TPM method. The studies were carried out in large manufacturing companies of different industries located on a certain area. The study’s results point to the actions actually performed within TPM as well as to the effects of those actions achieved by the studied enterprises.

Keywords: Infrastructure management, modern methods, technical infrastructure, TPM.

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Authors: Anastasia Katsamaki, Nikolaos Bilalis, Vassilis Dedoussis

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This work proposes a set of actions to assist redesign procedure in existing products of Electric and Electronic Equipment (EEE). The aim is to improve their environmental behavior after their withdrawal in the End-of-Life (EOL) phase. In the beginning data collection takes place. Then follows selection and implementation of the optimal EOL Treatment Strategy (EOL_TS) and its results- evaluation concerning the environment. In parallel, product design characteristics that can be altered are selected based on their significance for the environment in the EOL stage. All results from the previous stages are combined and possible redesign actions are formulated for further examination and afterwards configuration in the design stage. The applied method to perform these tasks is Lean Thinking (LT). At the end, results concerning the application of the proposed method on a distribution transformer are presented.

Keywords: End-of-life treatment, Lean thinking, WEEE

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Authors: C. Temaneh Nyah

Abstract:

The analysis of electromagnetic environment using deterministic mathematical models is characterized by the impossibility of analyzing a large number of interacting network stations with a priori unknown parameters, and this is characteristic, for example, of mobile wireless communication networks. One of the tasks of the tools used in designing, planning and optimization of mobile wireless network is to carry out simulation of electromagnetic environment based on mathematical modelling methods, including computer experiment, and to estimate its effect on radio communication devices. This paper proposes the development of a statistical model of electromagnetic environment of a mobile wireless communication network by describing the parameters and factors affecting it including the propagation channel and their statistical models.

Keywords: Electromagnetic Environment, Statistical model, Wireless communication network.

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Authors: Gioacchino Lavanco, Cinzia Novara, Floriana Romano, Elisabetta Di Giovanni

Abstract:

Modern culture, based on disinhibition of cultural trends and on heterodirection, is promoting openmindedness attitudes towards ethnic diversity, but on the other hand also new forms of social representations of the foreigner. Social representation is situated between the psychic field and the social one; it is the representation of oneself and of the other one, hanging between social categories and individual inner world. We will produce the results of a research on the representation of the foreigner, built on the type of prejudice prevailing among middle-low or middle-high educational qualification subjects, in which prejudicial attitudes seem to descend from precise mental images of the foreigner.

Keywords: Community, diversity, integration, prejudice, representations.

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Authors: Delowar Hossain, Genci Capi

Abstract:

This paper concerns with the problem of deep learning parameters tuning using a genetic algorithm (GA) in order to improve the performance of deep learning (DL) method. We present a GA based DL method for robot object recognition and grasping. GA is used to optimize the DL parameters in learning procedure in term of the fitness function that is good enough. After finishing the evolution process, we receive the optimal number of DL parameters. To evaluate the performance of our method, we consider the object recognition and robot grasping tasks. Experimental results show that our method is efficient for robot object recognition and grasping.

Keywords: Deep learning, genetic algorithm, object recognition, robot grasping.

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Authors: M. Adamski, J. Cwiklak

Abstract:

The contemporary battlefield creates a demand for more costly and highly advanced munitions. Training personnel responsible for operations as well as immediate execution of combat tasks which engage real asset is unrealistic and economically not feasible. Owing to a wide array of exploited simulators and various types of imitators, it is possible to reduce the costs. One of the effective elements of training, which can be applied in the training of all service branches, is imitator of aerial targets. This research serves as an introduction to the commencement of design analysis over a real aerial target imitator. Within the project, the basic aerodynamic calculations were made, which enabled to determine its geometry, design layout, performance as well as mass balance of individual components. The conducted calculations of the parameters of flight characteristics come closer to the real performance of such Unmanned Aerial Vehicles.

Keywords: Aerial target, aerodynamics, imitator, performance.

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Authors: S. Liepina, A. Jemeljanovs

Abstract:

Tasks of the work were study the possible E.coli contamination in red deer meat, identify pathogenic strains from isolated E.coli, determine their incidence in red deer meat and determine the presence of VT1, VT2 and eaeA genes for the pathogenic E.coli. 8 (10%) samples were randomly selected from 80 analysed isolates of E.coli and PCR reaction was performed on them. PCR was done both on initial materials – samples of red deer meat - and for already isolated liqueurs. Two of analysed venison samples contain verotoxin-producing strains of E. coli. It means that this meat is not safe to consumer. It was proven by the sequestration reaction of E. coli and by comparison of the obtained results with the database of microorganism genome available on the internet that the isolated culture corresponds to region 16S rDNS of E. coli thus presenting correctness of the microbiological methods.

Keywords: Deer meat, pathogenic Escherichia coli

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Authors: Maassoumeh Bemani Naeini

Abstract:

Studies on interlanguage have long been engaged in describing the phenomenon of variation in SLA. Pursuing the same goal and particularly addressing the role of linguistic features, this study describes the use of Persian morphology in the interlanguage of two adult English-speaking learners of Persian L2. Taking the general approach of a combination of contrastive analysis, error analysis and interlanguage analysis, this study focuses on the identification and prediction of some possible instances of transfer from English L1 to Persian L2 across six elicitation tasks aiming to investigate whether any of contextual features may variably influence the learners’ order of morpheme accuracy in the areas of copula, possessives, articles, demonstratives, plural form, personal pronouns, and genitive cases.  Results describe the existence of task variation in the interlanguage system of Persian L2 learners.

Keywords: English L1, Interlanguage Analysis, Persian L2, SLA variation.

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Authors: Samee Ullah Khan, C. Ardil

Abstract:

We model the process of a data center as a multi- objective problem of mapping independent tasks onto a set of data center machines that simultaneously minimizes the energy consump¬tion and response time (makespan) subject to the constraints of deadlines and architectural requirements. A simple technique based on multi-objective goal programming is proposed that guarantees Pareto optimal solution with excellence in convergence process. The proposed technique also is compared with other traditional approach. The simulation results show that the proposed technique achieves superior performance compared to the min-min heuristics, and com¬petitive performance relative to the optimal solution implemented in UNDO for small-scale problems.

Keywords: Energy-efficient computing, distributed systems, multi-objective optimization.

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Authors: Andrzej Śluzek

Abstract:

To illustrate diversity of methods used to extract relevant (where the concept of relevance can be differently defined for different applications) visual data, the paper discusses three groups of such methods. They have been selected from a range of alternatives to highlight how hardware and software tools can be complementarily used in order to achieve various functionalities in case of different specifications of “relevant data". First, principles of gated imaging are presented (where relevance is determined by the range). The second methodology is intended for intelligent intrusion detection, while the last one is used for content-based image matching and retrieval. All methods have been developed within projects supervised by the author.

Keywords: Relevant visual data, gated imaging, intrusion detection, image matching.

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Authors: Dongjoo Kim, Chang-Sik Son, Won-Seok Kang

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Adequate sleep affects various parts of one’s overall physical and mental life. As one of the methods in determining the appropriate amount of sleep, this research presents a heart rate based sleep quality index. In order to evaluate sleep quality using the heart rate, sleep data from 280 subjects taken over one month are used. Their sleep data are categorized by a three-part heart rate range. After categorizing, some features are extracted, and the statistical significances are verified for these features. The results show that some features of this sleep quality index model have statistical significance. Thus, this heart rate based sleep quality index may be a useful discriminator of sleep.

Keywords: Sleep, sleep quality, heart rate, statistical analysis.

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Authors: Kew Lee Ming, Norhashidah Hj. Mohd. Ali

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In a previous work, we presented the numerical solution of the two dimensional second order telegraph partial differential equation discretized by the centred and rotated five-point finite difference discretizations, namely the explicit group (EG) and explicit decoupled group (EDG) iterative methods, respectively. In this paper, we utilize a domain decomposition algorithm on these group schemes to divide the tasks involved in solving the same equation. The objective of this study is to describe the development of the parallel group iterative schemes under OpenMP programming environment as a way to reduce the computational costs of the solution processes using multicore technologies. A detailed performance analysis of the parallel implementations of points and group iterative schemes will be reported and discussed.

Keywords: Telegraph equation, explicit group iterative scheme, domain decomposition algorithm, parallelization.

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Authors: Xingyu Pan, Laure Tougne

Abstract:

For recognizing coins, the graved release date is important information to identify precisely its monetary type. However, reading characters in coins meets much more obstacles than traditional character recognition tasks in the other fields, such as reading scanned documents or license plates. To address this challenging issue in a numismatic context, we propose a training-free approach dedicated to detection and recognition of the release date of the coin. In the first step, the date zone is detected by comparing histogram features; in the second step, a topology-based algorithm is introduced to recognize coin numbers with various font types represented by binary gradient map. Our method obtained a recognition rate of 92% on synthetic data and of 44% on real noised data.

Keywords: Coin, detection, character recognition, topology.

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Authors: M. K. Zholdassova, G. Matthews, A. M. Kustubayeva, S. M. Jakupov

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The aim of this study was to test whether the Attention Networks Test (ANT) showed temporal decrements in performance. Vigilance tasks typically show such decrements, which may reflect impairments in executive control resulting from cognitive fatigue. The ANT assesses executive control, as well as alerting and orienting. Thus, it was hypothesized that ANT executive control would deteriorate over time. Manipulations including task condition (trial composition) and masking were included in the experimental design in an attempt to increase performance decrements. However, results showed that there is no temporal decrement on the ANT. The roles of task demands, cognitive fatigue and participant motivation in producing this result are discussed. The ANT may not be an effective tool for investigating temporal decrement in attention.

Keywords: ANT, executive control, task engagement, vigilancedecrement

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Authors: Roberto Sabatini, Celia Bartel, Anish Kaharkar, Tesheen Shaid, Subramanian Ramasamy

Abstract:

Two multisensor system architectures for navigation and guidance of small Unmanned Aircraft (UA) are presented and compared. The main objective of our research is to design a compact, light and relatively inexpensive system capable of providing the required navigation performance in all phases of flight of small UA, with a special focus on precision approach and landing, where Vision Based Navigation (VBN) techniques can be fully exploited in a multisensor integrated architecture. Various existing techniques for VBN are compared and the Appearance-Based Navigation (ABN) approach is selected for implementation. Feature extraction and optical flow techniques are employed to estimate flight parameters such as roll angle, pitch angle, deviation from the runway centreline and body rates. Additionally, we address the possible synergies of VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU (Micro-Electromechanical System Inertial Measurement Unit) sensors, and the use of Aircraft Dynamics Model (ADM) to provide additional information suitable to compensate for the shortcomings of VBN and MEMS-IMU sensors in high-dynamics attitude determination tasks. An Extended Kalman Filter (EKF) is developed to fuse the information provided by the different sensors and to provide estimates of position, velocity and attitude of the UA platform in real-time. The key mathematical models describing the two architectures i.e., VBN-IMU-GNSS (VIG) system and VIGADM (VIGA) system are introduced. The first architecture uses VBN and GNSS to augment the MEMS-IMU. The second mode also includes the ADM to provide augmentation of the attitude channel. Simulation of these two modes is carried out and the performances of the two schemes are compared in a small UA integration scheme (i.e., AEROSONDE UA platform) exploring a representative cross-section of this UA operational flight envelope, including high dynamics manoeuvres and CAT-I to CAT-III precision approach tasks. Simulation of the first system architecture (i.e., VIG system) shows that the integrated system can reach position, velocity and attitude accuracies compatible with the Required Navigation Performance (RNP) requirements. Simulation of the VIGA system also shows promising results since the achieved attitude accuracy is higher using the VBN-IMU-ADM than using VBN-IMU only. A comparison of VIG and VIGA system is also performed and it shows that the position and attitude accuracy of the proposed VIG and VIGA systems are both compatible with the RNP specified in the various UA flight phases, including precision approach down to CAT-II.

Keywords: Global Navigation Satellite System (GNSS), Lowcost Navigation Sensors, MEMS Inertial Measurement Unit (IMU), Unmanned Aerial Vehicle, Vision Based Navigation.

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Authors: B. Chandra, P. Paul Varghese

Abstract:

Crypto System Identification is one of the challenging tasks in Crypt analysis. The paper discusses the possibility of employing Neural Networks for identification of Cipher Systems from cipher texts. Cascade Correlation Neural Network and Back Propagation Network have been employed for identification of Cipher Systems. Very large collection of cipher texts were generated using a Block Cipher (Enhanced RC6) and a Stream Cipher (SEAL). Promising results were obtained in terms of accuracy using both the Neural Network models but it was observed that the Cascade Correlation Neural Network Model performed better compared to Back Propagation Network.

Keywords: Back Propagation Neural Networks, CascadeCorrelation Neural Network, Crypto systems, Block Cipher, StreamCipher.

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Authors: Ilya Kavalchuk, Hayrettin Arisoy, Alex Stojcevski, Aman Maun Than Oo

Abstract:

Electric vehicles are one of the most complicated electric devices to simulate due to the significant number of different processes involved in electrical structure of it. There are concurrent processes of energy consumption and generation with different onboard systems, which make simulation tasks more complicated to perform. More accurate simulation on energy consumption can provide a better understanding of all energy management for electric transport. As a result of all those processes, electric transport can allow for a more sustainable future and become more convenient in relation to the distance range and recharging time. This paper discusses the problems of energy consumption simulations for electric vehicles using different software packages to provide ideas on how to make this process more precise, which can help engineers create better energy management strategies for electric vehicles.

Keywords: Electric Vehicles, EV, Power Consumption, Power Management, Simulation.

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Authors: Bella Llego

Abstract:

This study aims to investigate the motivating and de-motivating factors that affect the learning ability of students attending the English Learning Center in Thailand. The subjects of this research were 20 students from the Hana Semiconductor Co., Limited. The data were collected by using questionnaire and analyzed using the SPSS program for the percentage, mean and standard deviation. The research results show that the main motivating factor in learning English at Hana Semiconductor Co., Ltd. is that it would help the employees to communicate with foreign customers and managers. Other reasons include the need to read and write e-mails, and reports in English, as well as to increase overall general knowledge. The main de-motivating factor is that there is a lot of vocabulary to remember when learning English. Another de-motivating factor is that when homework is given, the students have no time to complete the tasks required of them at the end of the working day.

Keywords: Motivating, demotivating, English learning center, student communicate.

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