Search results for: enhancing learning experience

Authors: M. Javid, R. Hassan, J. DeSilva

Abstract:

In this exploratory case study, a 37-year-old male patient who previously terminated treatment after four months of therapy with a different therapist begins anew with a 38-year-old female therapist and undergoes a similar cycle of premature termination, with added discourse caused by erotic transference. Process notes and records of the therapy treatment indicate that during the short course of treatment, the patient explored his difficulties navigating personal relationships, both current and past, and his difficulties coping with hypochondriasis. The therapist becomes tasked with not only navigating the patient’s inner conflict but also how she relates to the patient in the countertransference process while maintaining professional boundaries. This includes empathizing with the patient while also experiencing discomfort in the erotic transference from a professional standpoint. When the patient terminates once more, the therapist reflects on the possible reasons for termination. This includes the patient’s difficulties with tolerating interpretations, which cause him to blame himself for past events. These interpretations were also very frequent, contributing to the emotional burden the patient experienced. The therapist reflected on the use of interpretation versus exploration of the patient’s feelings and how exploring his feelings, including his feelings towards her, would have allowed for an opportunity to explore the emotions that troubled him more deeply. This includes exploring the patient’s anger and fear, which stem from unresolved conflicts from his childhood. Moreover, the erotic transference served as an enactment of previous experiences in which the patient feared losing what he loved, leading him to opt for premature termination instead of losing his ability to control the relationship and experience loss.

Keywords: Countertransference, erotic transference, premature termination, therapist-client boundaries, transference.

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Authors: Othoman Elsayah, Naren Gupta, Binsheng Zhang

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The construction sector constitutes one of the most important sectors in the economy of any country. Contractor selection is a critical decision that is undertaken by client organizations and is central to the success of any construction project. Contractor selection (CS) is a process which involves investigating, screening and determining whether candidate contractors have the technical and financial capability to be accepted to formally tender for construction work. The process should be conducted prior to the award of contract, characterized by many factors such as: contactor’s skills, experience on similar projects, track- record in the industry, and financial stability. However, this paper evaluates the current state of knowledge in relation to contractor selection process and demonstrates the findings from the analysis of the data collected from the Delphi questionnaire survey. The survey was conducted with a group of 12 experts working in the Libyan construction industry (LCI). The paper starts by briefly explaining the general outline of the questionnaire including the survey participation rate, the different fields the experts came from, and the business titles of the participants. Then the paper describes the tests used to determine when the experts had reached consensus. The paper is based on research which aims to develop rank contractor selection criteria with specific application to make construction projects in the Libyan context. The findings of this study will be utilized to establish the scope of work that will be used as part of a PhD research.

Keywords: Contractor selection, Libyan construction industry, Decision experts and Delphi technique.

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Authors: Elizabeth B. Varghese, M. Wilscy

Abstract:

A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame. A lot of algorithms have been proposed for face recognition. Vector Quantization (VQ) based face recognition is a novel approach for face recognition. Here a new codebook generation for VQ based face recognition using Integrated Adaptive Fuzzy Clustering (IAFC) is proposed. IAFC is a fuzzy neural network which incorporates a fuzzy learning rule into a competitive neural network. The performance of proposed algorithm is demonstrated by using publicly available AT&T database, Yale database, Indian Face database and a small face database, DCSKU database created in our lab. In all the databases the proposed approach got a higher recognition rate than most of the existing methods. In terms of Equal Error Rate (ERR) also the proposed codebook is better than the existing methods.

Keywords: Face Recognition, Vector Quantization, Integrated Adaptive Fuzzy Clustering, Self Organization Map.

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Authors: Li Ni, Pen ManMan, Li KenLi

Abstract:

Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: Chemical reaction optimization, expectation maximization, initial, objective function clustering.

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Authors: Berna Cantürk-Günhan, Esra Bukova-Güzel

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The purpose of the study is to determine the primary mathematics student teachers- views related to use instructional technology tools in course of the learning process and to reveal how the sample presentations towards different mathematical concepts affect their views. This is a qualitative study involving twelve mathematics students from a public university. The data gathered from two semi-structural interviews. The first one was realized in the beginning of the study. After that the representations prepared by the researchers were showed to the participants. These representations contain animations, Geometer-s Sketchpad activities, video-clips, spreadsheets, and power-point presentations. The last interview was realized at the end of these representations. The data from the interviews and content analyses were transcribed and read and reread to explore the major themes. Findings revealed that the views of the students changed in this process and they believed that the instructional technology tools should be used in their classroom.

Keywords: Integrating Technology, Mathematics Education, Primary Education, Teacher Education.

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Authors: R. Bremananth

Abstract:

Biometric authentication is an essential task for any kind of real-life applications. In this paper, we contribute two primary paradigms to Iris recognition such as Robust Eyelash Detection (RED) using pathway kernels and hair curve fitting synthesized model. Based on these two paradigms, rotation invariant iris recognition is enhanced. In addition, the presented framework is tested with real-life iris data to provide the authentication for LRC (Learning Resource Center) users. Recognition performance is significantly improved based on the contributed schemes by evaluating real-life irises. Furthermore, the framework has been implemented using Java programming language. Experiments are performed based on 1250 diverse subjects in different angles of variations on the authentication process. The results revealed that the methodology can deploy in the process on LRC management system and other security required applications.

Keywords: Authentication, biometric, eye lashes detection, iris scanning, LRC security, secure access.

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Authors: Yunyoung Nam, Junghun Ryu, Yoo-Joo Choi, We-Duke Cho

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This paper presents a novel approach for representing the spatio-temporal topology of the camera network with overlapping and non-overlapping fields of view (FOVs). The topology is determined by tracking moving objects and establishing object correspondence across multiple cameras. To track people successfully in multiple camera views, we used the Merge-Split (MS) approach for object occlusion in a single camera and the grid-based approach for extracting the accurate object feature. In addition, we considered the appearance of people and the transition time between entry and exit zones for tracking objects across blind regions of multiple cameras with non-overlapping FOVs. The main contribution of this paper is to estimate transition times between various entry and exit zones, and to graphically represent the camera topology as an undirected weighted graph using the transition probabilities.

Keywords: Surveillance, multiple camera, people tracking, topology.

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Authors: Kusumaphorn Sompong, Helen Lawton Smith, Barbara Igel

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This paper provides a key driver-based conceptual framework that can be used to improve a firm-s success in commercializing technology and in new product innovation resulting from collaboration with other organizations through strategic alliances. Based on a qualitative study using an interview approach, strategic alliances of entrepreneurs in the food processing industry in Thailand are explored. This paper describes factors affecting decisions to collaborate through alliances. It identifies four issues: maintaining the efficiency of the value chain for production capability, adapting to present and future competition, careful assessment of value of outcomes, and management of innovation. We consider five driving factors: resource orientation, assessment of risk, business opportunity, sharing of benefits and confidence in alliance partners. These factors will be of interest to entrepreneurs and policy makers with regard to further understanding of the direction of business strategies.

Keywords: Managing collaboration, strategic alliance, technology commercialization, innovation.

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Authors: Wondwosen Teshome

Abstract:

It is impossible to think about democracy without elections. The litmus test of any electoral process in any country is the possibility of a one time minority to become a majority at another time and a peaceful transition of power. In many countries in Sub-Saharan Africa though the multi-party elections appeared to be competitive they failed the acid test of democracy: peaceful regime change in a free and fair election. Failure to solve electoral disputes might lead to bloody electoral conflicts as witnessed in many emerging democracies in Africa. The aim of this paper is to investigate electoral conflicts in Africa since the end of the Cold War by using the 2005 post-election violence in Ethiopia as a case study. In Ethiopia, the coming to power of the EPRDF in 1991 marked the fall of the Derg dictatorial military government and the beginning of a multi-party democracy. The country held multi-party parliamentary elections in 1995, 2000, and 2005 where the ruling EPRDF party “won" the elections through violence, involving intimidation, manipulation, detentions of political opponents, torture, and political assassinations. The 2005 electoral violence was the worst electoral violence in the country-s political history that led to the death of 193 protestors and the imprisonment of more than 40, 000 people. It is found out that the major causes of the 2005 Ethiopian election were the defeat of the ruling party in the election and its attempt to reverse the poll results by force; the Opposition-s lack of decisive leadership; the absence of independent courts and independent electoral management body; and the ruling party-s direct control over the army and police.

Keywords: Africa, Ethiopia, Election, Electoral violence, NEBE.

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Authors: A. M. Sultana, Norhirdawati. M. Zahir, Norzalan. H. Yaacob

Abstract:

Recently in Malaysia, women's participation in teaching profession has increased. The increasing trend of women’s participation in the teaching profession poses challenges in families, especially in the developing countries like Malaysia. One of these challenges, concerns in balancing their role between family and job responsibility that faced by many women teachers. The purpose of this study is to discover how women teachers' impact on family happiness and the challenges faced by them in balancing their role between family and job responsibility. The findings presented in this study are based on survey research in a secondary school Dato’ Bijaya Setia in the district of Gugusan Manjoi which is located in Kedah, Malaysia. The study found that employment of women in economic activity has several beneficial impacts of improving the economic condition of the family. The results also revealed that in low income earning families, both husbands and wives’ employment contribute to the family income that less likely to experience of family poverty. The study also showed despite women's teachers’ significant role towards the overall development of the family, the majority of women teachers encountered a number of difficulties in balancing their role between family and job responsibility especially when they need to work more than the normal working time. Therefore, it is common for the majority of women suffering from psychological stress when they are unable to complete the task at a fixed time. The present study also suggests implication of family friendly policy and its appropriate practice to support the women teachers who are significantly contributing to family, community and the country.

Keywords: Emotional exhaustion, Family friendly policy, Work family conflict, Women Teacher.

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Authors: N. M. Nawi, R. S. Ransing, M. R. Ransing

Abstract:

The conjugate gradient optimization algorithm is combined with the modified back propagation algorithm to yield a computationally efficient algorithm for training multilayer perceptron (MLP) networks (CGFR/AG). The computational efficiency is enhanced by adaptively modifying initial search direction as described in the following steps: (1) Modification on standard back propagation algorithm by introducing a gain variation term in the activation function, (2) Calculation of the gradient descent of error with respect to the weights and gains values and (3) the determination of a new search direction by using information calculated in step (2). The performance of the proposed method is demonstrated by comparing accuracy and computation time with the conjugate gradient algorithm used in MATLAB neural network toolbox. The results show that the computational efficiency of the proposed method was better than the standard conjugate gradient algorithm.

Keywords: Adaptive gain variation, back-propagation, activation function, conjugate gradient, search direction.

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Authors: Sung Uk Park, Young Su Kang, Sangmo Kang, Yong Kweon Suh

Abstract:

Mineral product, waste concrete (fine aggregates), waste in the optical field, industry, and construction employ separators to separate solids and classify them according to their size. Various sorting machines are used in the industrial field such as those operating under electrical properties, centrifugal force, wind power, vibration, and magnetic force. Study on separators has been carried out to contribute to the environmental industry. In this study, we perform CFD analysis for understanding the basic mechanism of the separation of waste concrete (fine aggregate) particles from air with a machine built with a rotor with blades. In CFD, we first performed two-dimensional particle tracking for various particle sizes for the model with 1 degree, 1.5 degree, and 2 degree angle between each blade to verify the boundary conditions and the method of rotating domain method to be used in 3D. Then we developed 3D numerical model with ANSYS CFX to calculate the air flow and track the particles. We judged the capability of particle separation for given size by counting the number of particles escaping from the domain toward the exit among 10 particles issued at the inlet. We confirm that particles experience stagnant behavior near the exit of the rotating blades where the centrifugal force acting on the particles is in balance with the air drag force. It was also found that the minimum particle size that can be separated by the machine with the rotor is determined by its capability to stay at the outlet of the rotor channels.

Keywords: Environmental industry, Separator, CFD, Fine aggregate.

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Authors: Ora Geiger

Abstract:

This paper discusses the question whether a person diagnosed with dyslexia will necessarily have difficulty in reading musical notes. The author specifies the characteristics of alphabet reading in comparison to musical notation reading, and concludes that there should be no contra-indication for teaching standard music reading to children with dyslexia if an appropriate process is offered. This conclusion is based on a long term case study and relies on two main characteristics of music reading: (1) musical notation system is a systematic, logical, relative set of symbols written on a staff; and (2) music reading learning connected with playing a musical instrument is a multi-sensory activity that combines sight, hearing, touch, and movement. The paper describes music reading teaching procedures, using soprano recorders, and provides unique teaching methods that have been found to be effective for students who were diagnosed with dyslexia. It provides theoretical explanations in addition to guidelines for music education practices.

Keywords: Alphabet reading, music reading, multisensory teaching method, dyslexia, recorder playing.

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Authors: Teerawach Khamkorn, Laongtip Mathurasa, Savittree Rochanasmita Arnold, Witthaya Mekhum

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This research is aimed at studying the nature of problems and demands of the training for community leaders in the upper northeastern region of Thailand. Population and group samplings are based on 360 community leaders in the region who have experienced prior training from the Udonthani Rajabhat University. Stratified random samplings have been drawn upon 186 participants. The research tools is questionnaires. The frequency, percentage and standard deviation are employed in data analysis. The findings indicate that most of community leaders are males and senior adults. The problems in training are associated with the inconveniences of long-distance travelling to training locations, inadequacy of learning centers and training sites and high training costs. The demand of training is basically motivated by a desire for self-development in modern knowledge in keeping up-to-date with the changing world and the need for technological application and facilitation in shortening the distance to training locations and in limiting expensive training costs.

Keywords: Community leaders, Distance Training, Management, Technology.

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Authors: Frank Emmert-Streib, Matthias Dehmer

Abstract:

Inferring the network structure from time series data is a hard problem, especially if the time series is short and noisy. DNA microarray is a technology allowing to monitor the mRNA concentration of thousands of genes simultaneously that produces data of these characteristics. In this study we try to investigate the influence of the experimental design on the quality of the result. More precisely, we investigate the influence of two different types of random single gene perturbations on the inference of genetic networks from time series data. To obtain an objective quality measure for this influence we simulate gene expression values with a biologically plausible model of a known network structure. Within this framework we study the influence of single gene knock-outs in opposite to linearly controlled expression for single genes on the quality of the infered network structure.

Keywords: Dynamic Bayesian networks, microarray data, structure learning, Markov chain Monte Carlo.

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Authors: M. Anidha, K. Premalatha

Abstract:

Feature Selection is significant in order to perform constructive classification in the area of cancer diagnosis. However, a large number of features compared to the number of samples makes the task of classification computationally very hard and prone to errors in microarray gene expression datasets. In this paper, we present an innovative method for selecting highly informative gene subsets of gene expression data that effectively classifies the cancer data into tumorous and non-tumorous. The hybrid gene selection technique comprises of combined Mutual Information and Fisher score to select informative genes. The gene selection is validated by classification using Support Vector Machine (SVM) which is a supervised learning algorithm capable of solving complex classification problems. The results obtained from improved Mutual Information and F-Score with SVM as a classifier has produced efficient results.

Keywords: Gene selection, mutual information, Fisher score, classification, SVM.

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Authors: Choon Ling Sia, Yani Shi, Jiaqi Yan, Huaping Chen

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With the development of the Internet, E-commerce is growing at an exponential rate, and lots of online stores are built up to sell their goods online. A major factor influencing the successful adoption of E-commerce is consumer-s trust. For new or unknown Internet business, consumers- lack of trust has been cited as a major barrier to its proliferation. As web sites provide key interface for consumer use of E-Commerce, we investigate the design of web site to build trust in E-Commerce from a design science approach. A conceptual model is proposed in this paper to describe the ontology of online transaction and human-computer interaction. Based on this conceptual model, we provide a personalized webpage design approach using Bayesian networks learning method. Experimental evaluation are designed to show the effectiveness of web personalization in improving consumer-s trust in new or unknown online store.

Keywords: Trust, Web site design, Human-ComputerInteraction, E-Commerce, Design science, Bayesian network.

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Authors: K. E. Oyetade, S. D. Eyono Obono

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One of the fundamental characteristics of Information and Communication Technology (ICT) has been the ever-changing nature of continuous release and models of ICTs with its impact on the academic, social, and psychological benefits of its introduction in schools. However, there seems to be a growing concern about its negative impact on students when introduced early in schools for teaching and learning. This study aims to design a model of child development factors affecting the early introduction of ICTs in schools in an attempt to improve the understanding of child development and introduction of ICTs in schools. The proposed model is based on a sound theoretical framework. It was designed following a literature review of child development theories and child development factors. The child development theoretical framework that fitted to the best of all child development factors was then chosen as the basis for the proposed model. This study hence found that the Jean Piaget cognitive developmental theory is the most adequate theoretical frameworks for modeling child development factors for ICT introduction in schools.

Keywords: Child development factors, child development theories, ICTs, theory.

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Authors: P. Acharjee, S. K. Goswami

Abstract:

Particle Swarm Optimization (PSO) with elite PSO parameters has been developed for power flow analysis under practical constrained situations. Multiple solutions of the power flow problem are useful in voltage stability assessment of power system. A method of determination of multiple power flow solutions is presented using a hybrid of Particle Swarm Optimization (PSO) and local search technique. The unique and innovative learning factors of the PSO algorithm are formulated depending upon the node power mismatch values to be highly adaptive with the power flow problems. The local search is applied on the pbest solution obtained by the PSO algorithm in each iteration. The proposed algorithm performs reliably and provides multiple solutions when applied on standard and illconditioned systems. The test results show that the performances of the proposed algorithm under critical conditions are better than the conventional methods.

Keywords: critical conditions, ill-conditioned systems, localsearch technique, multiple power flow solutions, particle swarmoptimization.

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Authors: Li Kewen, Su Zhaoxin, Wang Xingmou, Zhu Jian Bing

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Conventional reservoir prediction methods ar not sufficient to explore the implicit relation between seismic attributes, and thus data utilization is low. In order to improve the predictive classification accuracy of reservoir lithology, this paper proposes a deep learning lithology prediction method based on ResNet (Residual Neural Network) and SENet (Squeeze-and-Excitation Neural Network). The neural network model is built and trained by using seismic attribute data and lithology data of Shengli oilfield, and the nonlinear mapping relationship between seismic attribute and lithology marker is established. The experimental results show that this method can significantly improve the classification effect of reservoir lithology, and the classification accuracy is close to 70%. This study can effectively predict the lithology of undrilled area and provide support for exploration and development.

Keywords: Convolutional neural network, lithology, prediction of reservoir lithology, seismic attributes.

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Authors: R. Sinthavalai, N. Memongkol, N. Patthanaprechawong, J. Viriyanantavong, C. Choosuk

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In Thailand, the practice of pre-hospital Emergency Medical Service (EMS) in each area reveals the different growth rates and effectiveness of the practices. Those can be found as the diverse quality and quantity. To shorten the learning curve prior to speed-up the practices in other areas, story telling and lessons learnt from the effective practices are valued as meaningful knowledge. To this paper, it was to ascertain the factors, lessons learnt and best practices that have impact as contributing to the success of prehospital EMS system. Those were formulized as model prior to speedup the practice in other areas. To develop the model, Malcolm Baldrige National Quality Award (MBNQA), which is widely recognized as a framework for organizational quality assessment and improvement, was chosen as the discussion framework. Remarkably, this study was based on the consideration of knowledge capture; however it was not to complete the loop of knowledge activities. Nevertheless, it was to highlight the recognition of knowledge capture, which is the initiation of knowledge management.

Keywords: Emergency Medical Service, Modeling, MBNQA, Thailand.

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Authors: Tao Zhang, Nan Yan

Abstract:

In recent years, the Chaoshan area, a special place located in the southeast of Guangdong province in China, actively protects religious heritage and is developing religious tourism, which is attracting many expatriate Chinese who are coming back for travel and to worship. This paper discussed three questions. Firstly, what is the current situation about the different social background of tourists’ motivation, satisfaction and behavioral intention? Secondly, is there a relationship between the motivation, satisfaction and behavioral intention and the different social backgrounds of tourists? Thirdly, what is the relationship between religious tourists’ motivation, satisfaction and behavioral intention? The research methods use a combination of qualitative analysis and quantitative analysis. Qualitative analysis uses the method of observation and interviews. Convenient sampling technique was used for quantitative analysis. The study showed that the different social backgrounds of tourists’ forms diverse cognition and experiences about religious tourism, and their motivations, satisfaction and behavioral intention as tourists vary. Tourists’ motivation and satisfaction has a positive phase relation. Tourists’ motivation with satisfaction as the intervening variable also has a positive phase effect on tourists’ behavior intention. The result shows that religious tourists’ motivations include experiencing a religious atmosphere, and having a rest and recreation. The result also shows that religious tourists want to travel with their family members and friends. While traveling, religious tourists like to talk with Buddhist monks or nuns. Compared to other tourism types, religious tourists have higher expectations about temple environment, traveling experience, peripheral service and temple management.

Keywords: Behavioral intension, motivation, religious tourism, satisfaction.

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Authors: Yang Zhang, Jian He

Abstract:

Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper presents sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for CHD prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, coronary heart disease, ECG, electrocardiogram, ResNet, sliding window.

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Authors: V. Nikkhah Rashidabad, M. Manteghian, M. Masoumi, S. Mousavian, D. Ashouri

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In this research, the capability of neural networks in  modeling and learning complicated and nonlinear relations has been  used to develop a model for the prediction of changes in the diameter  of bubbles in pool boiling distilled water. The input parameters used  in the development of this network include element temperature, heat  flux, and retention time of bubbles. The test data obtained from the  experiment of the pool boiling of distilled water, and the  measurement of the bubbles form on the cylindrical element. The  model was developed based on training algorithm, which is  typologically of back-propagation type. Considering the correlation  coefficient obtained from this model is 0.9633. This shows that this  model can be trusted for the simulation and modeling of the size of  bubble and thermal transfer of boiling.

Keywords: Bubble Diameter, Heat Flux, Neural Network, Training Algorithm.

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Authors: Hsin-Yi Lien

Abstract:

The study explored the role of metacognition in foreign language anxiety on a sample of 411 Taiwanese students of English as a Foreign Language. The reading strategy inventory was employed to evaluate the tertiary learners’ level of metacognitive awareness and a semi-structured background questionnaire was also used to examine the learners’ perceptions of their English proficiency and satisfaction of their current English learning. In addition, gender and academic level differences in employment of reading strategies were investigated. The results showed the frequency of reading strategy use increase slightly along with academic years and males and females actually employ different reading strategies. The EFL tertiary learners in the present study utilized cognitive strategies more frequently than metacognitive strategies or support strategies. Male students use metacognitive strategy more often while female students use cognitive and support strategy more frequently.

Keywords: Cognitive strategy, gender differences, metacognitive strategy, support strategy.

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Authors: Okafor UAC, Ibeabuchimn, Omidina JO, Igwesi-Chidobe CN, Akinbo SRA

Abstract:

Purpose: The fear of falling is a major concern among the elderly. Sixty-five percent of individuals older than 60 years of age experience loss of balance often on a daily basis. Therefore, balance assessment in the elderly deserves special attention due to its importance in functional mobility and safety. This study aimed at assessing balance performance and comparing some anthropometric parameters among a Nigerian non-institutionalized elderly population.

Methods: Sixty one elderly subjects (31 males and 30 females) participated in this study. Their ages ranged between 62 and 84 years. Ability to maintain balance was assessed using Functional Reach Test (FRT) and Sharpened Romberg Test (SRT). Anthropometric data including age, weight, height, arm length, leg length, bi-acromial breadth, foot length and trunk length were also collected. Analysis was done using Pearson’s Product Moment Correlation Coefficient and Independent T-test, while level of significance was set as p<0.05.

Results: Age-related significant relationship was observed between balance performance and bi-acromial breadth among the elderly population. Gender and visual input also had a significant influence on balance performance. Other anthropometric variables (age, weight, height, arm length, leg length, foot length and trunk length) showed no significant relationship with balance performance among this elderly sample.

Conclusion: Only specific anthropometric variables may affect balance performances among the healthy elderly. The study further highlights the need for routine assessment of both static and dynamic balance to detect and appropriately manage aging-related diseases which could affect balance in the elderly.

Keywords: Balance Performance, Anthropometry, Non-institutionalized Elderly.

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Authors: Atif Mehmood, Said M. Easa

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This paper develops driver reaction-time models for car-following analysis based on human factors. The reaction time was classified as brake-reaction time (BRT) and acceleration/deceleration reaction time (ADRT). The BRT occurs when the lead vehicle is barking and its brake light is on, while the ADRT occurs when the driver reacts to adjust his/her speed using the gas pedal only. The study evaluates the effect of driver characteristics and traffic kinematic conditions on the driver reaction time in a car-following environment. The kinematic conditions introduced urgency and expectancy based on the braking behaviour of the lead vehicle at different speeds and spacing. The kinematic conditions were used for evaluating the BRT and are classified as normal, surprised, and stationary. Data were collected on a driving simulator integrated into a real car and included the BRT and ADRT (as dependent variables) and driver-s age, gender, driving experience, driving intensity (driving hours per week), vehicle speed, and spacing (as independent variables). The results showed that there was a significant difference in the BRT at normal, surprised, and stationary scenarios and supported the hypothesis that both urgency and expectancy had significant effects on BRT. Driver-s age, gender, speed, and spacing were found to be significant variables for the BRT in all scenarios. The results also showed that driver-s age and gender were significant variables for the ADRT. The research presented in this paper is part of a larger project to develop a driversensitive in-vehicle rear-end collision warning system.

Keywords: Brake reaction time, car-following, human factors, modeling.

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Authors: Syhalath Xaphakdy, Toshio Nagata, Saykham Phommathat, Pavy Souwannavong, Vilayvanh Srithilat, Phoxay Sengdala, Bounaom Phetarnousone, Boualay Siharath, Xaya Chemcheng

Abstract:

The National University of Laos (NUOL) invited a group of volunteers from the Japan International Cooperation Agency (JICA) to revise the physics experiments to utilize the materials that were already available to students. The intension was to review and revise the materials regularly utilized in physics class. The project had access to limited materials and a small budget for the class in the unit; however, by developing experimental textbooks related to mechanics, electricity, and wave and vibration, the group found a way to apply them in the classroom and enhance the students teaching activities. The aim was to introduce a way to incorporate the materials and practices in the classroom to enhance the students learning and teaching skills, particularly when they graduate and begin working as high school teachers.

Keywords: NUOL, JICA, physics experiment materials, small budget, mechanics, electricity.

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Authors: Rumyana Peytcheva-Forsyth, Blagovesna Yovkova

Abstract:

This paper presents the outcomes of a qualitative study which aims to investigate the pedagogical potentials of serious games in the preparation of future teachers. The authors discuss the existing problems and barriers associated with the organization of teaching practices in Bulgaria as part of the pre-service teacher training, as well as the attitudes and perceptions of the interviewed academics, teachers and trainees concerning the integration of serious games in the teaching practicum. The study outcomes strongly confirm the positive attitudes of the respondents to the introduction of virtual learning environments for the development of professional skills of future teachers as a supplement to the traditional forms of education. Through the inclusion of serious games it is expected to improve the quality of practical training of pre-service teachers as they overcome many of the problems identified in the existing teaching practices. The outcomes of the study will inform the design of the educational simulation software which is part of the project SimAula Tomorrow's Teachers Training.

Keywords: pre-service teacher training, serious games, virtual practicum, simulations

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Authors: Chih-Hung Wu, Chih-Chin Lai, Chun-Yen Chen, Yan-He Chen

Abstract:

Interpretation of aerial images is an important task in various applications. Image segmentation can be viewed as the essential step for extracting information from aerial images. Among many developed segmentation methods, the technique of clustering has been extensively investigated and used. However, determining the number of clusters in an image is inherently a difficult problem, especially when a priori information on the aerial image is unavailable. This study proposes a support vector machine approach for clustering aerial images. Three cluster validity indices, distance-based index, Davies-Bouldin index, and Xie-Beni index, are utilized as quantitative measures of the quality of clustering results. Comparisons on the effectiveness of these indices and various parameters settings on the proposed methods are conducted. Experimental results are provided to illustrate the feasibility of the proposed approach.

Keywords: Aerial imaging, image segmentation, machine learning, support vector machine, cluster validity index

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