Search results for: Research Training

Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

Abstract:

In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other.

As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO.

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Authors: Rachel Baruch

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This article describes the implementation of an experimental model for teaching ICT tools and digital environments in teachers training college. In most educational systems in the Western world, new programs were developed in order to bridge the digital gap between teachers and students. In spite of their achievements, these programs are limited due to several factors: The teachers in the schools implement new methods incorporating technological tools into the curriculum, but meanwhile the technology changes and advances. The interface of tools changes frequently, some tools disappear and new ones are invented. These conditions require an experimental model of training the pre-service teachers. The appropriate method for instruction within the domain of ICT tools should be based on exposing the learners to innovations, helping them to gain experience, teaching them how to deal with challenges and difficulties on their own, and training them. This study suggests some principles for this approach and describes step by step the implementation of this model.

Keywords: ICT tools, e-learning, pre-service teachers.

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Authors: Lynn. J. MacFarlane. A

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Within the healthcare system, training and continued professional development although essential, can be effected by cost and logistical restraints due to the nature of healthcare provision e.g employee shift patterns, access to expertise, cost factors in releasing staff to attend training etc. The use of multimedia technology for the development of e-learning applications is also a major cost consideration for healthcare management staff, and this type of media whether optical or on line requires careful planning in order to remain inclusive of all staff with potentially varied access to multimedia computing. This paper discusses a project in which the use of DVD authoring technology has been successfully implemented to meet the needs of distance learning and user considerations, and is based on film production techniques and reduced product turnaround deadlines.

Keywords: DVD, healthcare, distance learning, cost.

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Authors: Mehmet Altınöz

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Today, the working areas put forward the administration of change. In order to provide this; it is required from the organizations to be creative. Professional creativity in offices depends on an environment that enables the development of the organization only after the individual or collective exertions within the organization. By providing this environment, the organization will gain efficiency, productivity, and work pleasure. In order to bring up the workforce appropriate to the related expectations, the professional creativity of the office management and secretarial profession candidates should be evaluated, education programs appropriate to this and related directly with the service quality should be prepared and the future of this profession should be directed. The aim of this study is to ensure the attention to improve the prepared education program as well as the creative thoughts and their applications, when carrying out an office management and secretarial training. 144 students took place in this research and a questionnaire of 48 questions was carried out.

Keywords: Creativity, professional creativity, creativity evaluation, office management, secretarial

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Authors: M. K. Pradhan, C. K. Biswas,

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In the current research, neuro-fuzzy model and regression model was developed to predict Material Removal Rate in Electrical Discharge Machining process for AISI D2 tool steel with copper electrode. Extensive experiments were conducted with various levels of discharge current, pulse duration and duty cycle. The experimental data are split into two sets, one for training and the other for validation of the model. The training data were used to develop the above models and the test data, which was not used earlier to develop these models were used for validation the models. Subsequently, the models are compared. It was found that the predicted and experimental results were in good agreement and the coefficients of correlation were found to be 0.999 and 0.974 for neuro fuzzy and regression model respectively

Keywords: Electrical discharge machining, material removal rate, neuro-fuzzy model, regression model, mountain clustering.

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Authors: K. Busko

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The aim of the study was to follow changes of powervelocity relationship in female volleyball players during an annual training cycle. The study was conducted on eleven female volleyball players: age 21.6±1.7 years, body height 177.9±4.7 cm, body mass 71.3±6.6 kg and training experience 8.6±3.3 years. Power–velocity relationship was determined from five maximal 10-second cycloergometer efforts with external loads equal: 2.5, 5.0, 7.5, 10.0 and 12.5% of body weight (BW) before (I) and after (II) the preparatory period, after the first (III) and second (IV) competitive season. The maximal power output increased from 9.30±0.85 W•kg–1 (I) to 9.50±0.96 W•kg–1 (II), 9.77±0.96 W•kg–1 (III) and 9.95±1.13 W•kg–1 (IV, p<0,05). The power output at the load of 2.5, 5.0, 7.5, 10.0% BW were statistically significant increased after the first and second competitive season. Power output at load of 12.5% BW was insignificant increased.

Keywords: Female, Force-velocity relationship, Power output, Volleyball

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Authors: B. O. Diyaolu, O. O. Oyerinde

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This study examined the effect of sexuality education training programs on the knowledge and practice of sexual risk behavior among secondary school adolescents in Ibadan North Local Government area of Oyo State. A total of 105 students were sampled from two schools in the Local Government area. 70 students constituted the experimental group while 35 constituted the control group. Pretest-Posttest control group quasi-experimental design was adopted. A self-developed questionnaire was used to test participants’ knowledge and practice of sexual risk behavior before and after the training (α = .62, .82 and .74). Analysis indicated a significant effect of sexuality education training on participants’ knowledge and practice of sexual risk behavior, a significant gender difference in knowledge of sexual risk behavior but no significant age and gender difference in the practice of sexual risk behavior. It was thus concluded that sexuality education should be taught in schools and emphasized at homes with no age or gender restrictions.

Keywords: Early adolescent, health risk, sexual risk behavior, sexuality education.

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Authors: Zoja Raud, Valery Vodovozov

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The paper focuses on the distance laboratory organisation for training the electrical engineering staff and students in the fields of electrical drive and power electronics. To support online knowledge acquisition and professional enhancement, new challenges in remote education based on an active learning approach with self-assessment have been emerged by the authors. Following the literature review and explanation of the improved assessment methodology, the concept and technological basis of the labs arrangement are presented. To decrease the gap between the distance study of the up-to-date equipment and other educational activities in electrical engineering, the improvements in the following-up the learners’ progress and feedback composition are introduced. An authoring methodology that helps to personalise knowledge acquisition and enlarge Web-based possibilities is described. Educational management based on self-assessment is discussed.

Keywords: Advanced training, active learning, distance learning, electrical engineering, remote laboratory, self-assessment.

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Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

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This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: Neural network, rule extraction, rule insertion, self-organizing map.

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Authors: B. Ratchaneepun, N.S. Bardell

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It is recognized that people are the main drivers in almost all the processes that affect airworthiness assurance. This is especially true in the area of aircraft maintenance, which is an essential part of continuing airworthiness. This work investigates what impact English language proficiency, the intersection of the military and Thai cultures, and the lack of initial and continuing human factors training have on the work performance of maintenance personnel in the Royal Thai Air Force (RTAF). A quantitative research method based on a cross-sectional survey was used to gather data about these three key aspects of “people” in a military airworthiness environment. 30 questions were developed addressing the crucial topics of English language proficiency, impact of culture, and human factors training. The officers and the non-commissioned officers (NCOs) who work for the Aeronautical Engineering Divisions in the RTAF comprised the survey participants. The survey data were analysed to support various hypotheses by using a t-test method. English competency in the RTAF is very important since all of the service manuals for Thai military aircraft are written in English. Without such competency, it is difficult for maintenance staff to perform tasks and correctly interpret the relevant maintenance manual instructions; any misunderstandings could lead to potential accidents. The survey results showed that the officers appreciated the importance of this more than the NCOs, who are the people actually doing the hands-on maintenance work. Military culture focuses on the success of a given mission, and leverages the power distance between the lower and higher ranks. In Thai society, a power distance also exists between younger and older citizens. In the RTAF, such a combination tends to inhibit a just reporting culture and hence hinders safety. The survey results confirmed this, showing that the older people and higher ranks involved with RTAF aircraft maintenance believe that the workplace has a positive safety culture and climate, whereas the younger people and lower ranks think the opposite. The final area of consideration concerned human factors training and non-technical skills training. The survey revealed that those participants who had previously attended such courses appreciated its value and were aware of its benefits in daily life. However, currently there is no regulation in the RTAF to mandate recurrent training to maintain such knowledge and skills. The findings from this work suggest that the people involved in assuring the continuing airworthiness of the RTAF would benefit from: (i) more rigorous requirements and standards in the recruitment, initial training and continuation training regarding English competence; (ii) the development of a strong safety culture that exploits the uniqueness of both the military culture and the Thai culture; and (iii) providing more initial and recurrent training in human factors and non-technical skills.

Keywords: Aircraft maintenance, continuing airworthiness, military culture, people, Royal Thai Air Force.

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Authors: Ejaz Ashraf, Raheel Babar, Muhammad Yaseen, Hafiz Khurram Shurjeel, Nosheen Fatima

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Main purpose of this study was to assess adoption level of farmers for quinoa cultivation after they had been taught through training and visit extension approach. At this time of the 21^st century, population structure, climate change, food requirements and eating habits of people are changing rapidly. In this scenario, farmers must play their key role in sustainable crop development and production through adoption of new crops that may also be helpful to overcome the issue of food insecurity as well as reducing poverty in rural areas. Its cultivation in Pakistan is at the early stages and there is a need to raise awareness among farmers to grow quinoa crops. In the middle of the 2015, a training and visit extension approach was used to raise awareness and convince farmers to grow quinoa in the area. During training and visit extension program, 80 farmers were randomly selected for the training of quinoa cultivation. Later on, these farmers trained 60 more farmers living into their neighborhood. After six months, a survey was conducted with all 140 farmers to assess the impact of the training and visit program on adoption level of respondents for the quinoa crop. The survey instrument was developed with the help of literature review and other experts of the crop. Validity and reliability of the instrument were checked before complete data collection. The data were analyzed by using SPSS. Multiple regression analysis was used for interpretation of the results from the survey, which indicated that factors like information/ training, change in agronomic and plant protection practices play a key role in the adoption of quinoa cultivation by respondents. In addition, the model explains more than 50% of variation in the adoption level of respondents. It is concluded that farmers need timely information for improved knowledge of agronomic and plant protection practices to adopt cultivation of the quinoa crop in the area.

Keywords: Farmers, quinoa, adoption, contact, training and visit.

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Authors: Nuran Bahar, Mehmet A. Akcayol

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In the aviation industry, many faults may occur frequently during the maintenance processes and assembly operations of complex structured aircrafts because of their high dependencies of components. These faults affect the quality of aircraft parts or developed modules adversely. Technical employee requires long time and high labor force while checking the correctness of each component. In addition, the person must be trained regularly because of the ever-growing and changing technology. Generally, the cost of this training is very high. Augmented Reality (AR) technology reduces the cost of training radically and improves the effectiveness of the training. In this study, the usage of AR technology in the aviation industry has been investigated and the effectiveness of AR with heads-up display glasses has been examined. An application has been developed for comparison of production process with AR and manual one.

Keywords: Aerospace, assembly quality, augmented reality, heads-up display.

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Authors: E. Supriyanto, S. C. Seow

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Early Intervention Program (EIP) is required to improve the overall development of children with Trisomy 21 (Down syndrome). In order to help trainer and parent in the implementation of EIP, a support system has been developed. The support system is able to screen data automatically, store and analyze data, generate individual EIP (curriculum) with optimal training duration and to generate training automatically. The system consists of hardware and software where the software has been implemented using Java language and Linux Fedora. The software has been tested to ensure the functionality and reliability. The prototype has been also tested in Down syndrome centers. Test result shows that the system is reliable to be used for generation of an individual curriculum which includes the training program to improve the motor, cognitive, and combination abilities of Down syndrome children under 6 years.

Keywords: Early intervention program (curriculum), Trisomy21, support system, Java.

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Authors: A. Alrasheed, I. Connerton

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Daily provision of high quality food and hygiene to patients is a challenging goal of the healthcare. In Saudi Arabia, matters related to food safety and hygiene are regulated by the Ministry of Health (MOH) and the Saudi Food and Drugs Authority (SFDA). The purpose of this research is to discuss the food safety management inconsistencies and flaws, in particular the ones related to Hazard Analysis and Critical Control Points (HACCP) in Riyadh’s MOH hospitals. As required by law, written HACCP regulations must be implemented, and food handlers need to receive the training accordingly. However, in Saudi hospitals, this is not a requirement, and the food handlers do not need to hold training certificates in food safety or HACCP. Nowadays, the matter of food safety and hygiene have become increasingly important since the decision makers want to align these regulations with the majority of the world and to implement HACCP fully and for this purpose, the SFDA was established. 

Keywords: Food safety, patients, hospitals, HACCP, Saudi Arabia.

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

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

Keywords: Extended kalmin filter (EKF), classification problem, radial basis function networks (RBFN), finite impulse response (FIR)filter.

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Authors: Saman M. Abdulla, Najla B. Al-Dabagh, Omar Zakaria

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The aim of this article is to explain how features of attacks could be extracted from the packets. It also explains how vectors could be built and then applied to the input of any analysis stage. For analyzing, the work deploys the Feedforward-Back propagation neural network to act as misuse intrusion detection system. It uses ten types if attacks as example for training and testing the neural network. It explains how the packets are analyzed to extract features. The work shows how selecting the right features, building correct vectors and how correct identification of the training methods with nodes- number in hidden layer of any neural network affecting the accuracy of system. In addition, the work shows how to get values of optimal weights and use them to initialize the Artificial Neural Network.

Keywords: Artificial Neural Network, Attack Features, MisuseIntrusion Detection System, Training Parameters.

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Authors: Andreas Theissler, Ian Dear

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The one-class support vector machine “support vector data description” (SVDD) is an ideal approach for anomaly or outlier detection. However, for the applicability of SVDD in real-world applications, the ease of use is crucial. The results of SVDD are massively determined by the choice of the regularisation parameter C and the kernel parameter  of the widely used RBF kernel. While for two-class SVMs the parameters can be tuned using cross-validation based on the confusion matrix, for a one-class SVM this is not possible, because only true positives and false negatives can occur during training. This paper proposes an approach to find the optimal set of parameters for SVDD solely based on a training set from one class and without any user parameterisation. Results on artificial and real data sets are presented, underpinning the usefulness of the approach.

Keywords: Support vector data description, anomaly detection, one-class classification, parameter tuning.

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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: I. Struhár, L. Dovrtělová, M. Kumstát

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Regular exercise promotes reduction in blood pressure, reduction in body weight and it also helps to increase in insulin sensitivity. Participation in physical activity should always be linked to medical screening which can reveal serious medical problems. One of them is high blood pressure. Hypertension is risk factor for one billion people worldwide and the highest prevalence is found in Africa. Another component of hypertension is that people who suffer from hypertension have no symptoms. It is estimated that reduction of 3mm Hg in Systolic Blood Pressure decreases cardiac morbidity at least 5%. The most of the guidelines suggest aerobic exercise in a prevention of cardiovascular diseases. On the other hand, it is important to emphasize the impact of resistance training. Even, it was found higher effect for reduction on the level of systolic blood pressure than aerobic exercise.

Keywords: Coronary artery disease, physical activity, prevention, resistance training.

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Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: Computer vision, deep learning, object detection, semiconductor.

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Authors: Csilla M. Szabó

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In Hungary, the society has changed a lot for the past 25 years, and these changes could be detected in educational situations as well. The number and the intensity of conflicts have been increased in most fields of life, as well as at schools. Teachers have difficulties to be able to handle school conflicts. What is more, the new net generation, generation Z has values and behavioural patterns different from those of the previous one, which might generate more serious conflicts at school, especially with teachers who were mainly socialising in a traditional teacher – student relationship. In Hungary, the bill CCIV of 2011 declared the foundation of Institutes of Teacher Training in higher education institutes. One of the tasks of the Institutes is to survey the competences and needs of teachers working in public education and to provide further trainings and services for them according to their needs and requirements. This job is supported by the Social Renewal Operative Programs 4.1.2.B. The professors of a college carried out a questionnaire and surveyed the needs and the requirements of teachers working in the region. Based on the results, the professors of the Institute of Teacher Training decided to meet the requirements of teachers and to launch short teacher further training courses in spring 2015. One of the courses is going to focus on school conflict management through mediation. The aim of the pilot course is to provide conflict management techniques for teachers and to present different mediation techniques to them. The theoretical part of the course (5 hours) will enable participants to understand the main points and the advantages of mediation, while the practical part (10 hours) will involve teachers in role plays to learn how to cope with conflict situations applying mediation. We hope if conflicts could be reduced, it would influence school atmosphere in a positive way and the teaching – learning process could be more successful and effective.

Keywords: Conflict resolution, generation Z, mediation, teacher training.

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Authors: Andreas Ahrens, Jelena Zascerinska

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Emotions are crucial in online classes in adult education. Despite that, a little attention was devoted to the emotional experience of being an online teacher in the field of andragogy, and the online teacher’s emotional perspectives in ever changing environments have to be analysed. The paper aims at the analysis of teachers’ emotional experience in online classes in adult education in selected European countries. The research tends to propose implications for training of teachers who work in online classes in adult education. The survey was conducted in April 2022. In the selected European countries 78 respondents took part in the study. Among them, 30 respondents represented Germany, 28 respondents Greece, and 20 respondents were from Italy. The theoretical findings allow defining teacher emotional experience. The analysis of the elements of the respondents’ emotional experience allows concluding that teachers’ attitude to online classes has to be developed. The key content for teacher training is presented. Directions of further work are proposed.

Keywords: Adult education, online classes, teacher emotional experience, European countries.

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Authors: Jindong Gu, Matthias Schubert, Volker Tresp

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In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: Outlier detection, generative adversary networks, semi-supervised learning.

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Authors: Malathi Balakrishnan, Gananthan M. Nadarajah, Noraini Abd Rahim, Amy Wong On Mei

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The purpose of the study is to investigate the level of intrinsic motivation of trainers after attending a Continuous Professional Development Course (CPD) organized by Institute of Teacher Training Malaysia titled, “Transformation of Teaching and Learning the Fun Way”. This study employed a survey whereby 96 teacher trainers were given Situational Intrinsic Motivational Scale (SIMS) Instruments. Confirmatory factor analysis was carried out to get the validity of this instrument in local setting. Data were analyzed with SPSS for descriptive statistic. Semi- structured interviews were also administrated to collect qualitative data on participants’ experiences after participating in the two-day fun-filled program. The findings showed that the participants’ level of intrinsic motivation showed higher mean than the amotivation. The results revealed that the intrinsic motivation mean is 19.0 followed by Identified regulation with a mean of 17.4, external regulation 9.7 and amotivation 6.9. The interview data also revealed that the participants were motivated after attending this training program. It can be concluded that this program, which was organized by Institute of Teacher Training Malaysia, was able to enhance participants’ level of motivation. Self-Determination Theory (SDT) as a multidimensional approach to motivation was utilized. Therefore, teacher trainers may have more success using the “The fun way approach” in conducting training program in future.

Keywords: Teaching and Learning, Motivation, Teacher Trainer, SDT.

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Authors: Muntanavadee Maytapattana

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The purposes of the study were to evaluate the effectiveness of the Parent Training Program for Obesity Reduction (PTPOR) on health behaviors of school-age children. An Ecological Systems Theory (EST) was approached the study and a randomized control trial was used in this study. Participants were school-age overweight or obese children and their parents. One hundred and one parent-child dyads were recruited and random assigned into the PTPOR (N=30), Educational Intervention or EI (N=32), and control group (N=39). The parents in the PTPOR group participated in five sessions including an educational session, a cooking session, aerobic exercise training, 2-time group discussion sessions, and 4-time telephoned counseling sessions. Repeated Measure ANCOVA was used to analyze data. The results presented that the outcomes of the PTPOR group were better than the EI and the control groups at 1^st, 8^th, and 32^nd weeks after finishing the program such as child exercise behavior (F_(2,97) = 3.98, p = .02) and child dietary behavior (F_(2,97) = 9.42, p = .00). The results suggest that nurses and health care providers should utilize the PTPOR for child weight reduction and for the health promotion of a lifestyle among overweight and obese children.

Keywords: Parent training program for obesity reduction, child health behaviors, school-age children.

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Authors: M. T. Becerra, F. Martín, P. Gutiérrez, S. Cubo, E. Iglesias, A. A. Sáenz del Castillo, P. Cañamero

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The consolidation of the European Higher Education Area (EHEA) in universities has led to significant changes in student training. This paper, part of a Teaching Innovation Project, starts from new training requirements that are fit within Undergraduate Thesis Project, a subject that culminate student learning. Undergraduate Thesis Project is current assessment system that weigh the student acquired training in university education. Students should develop a range of cross curricular competences such as public presentation of ideas, problems and solutions both orally and writing in Undergraduate Thesis Project. Specifically, we intend with our innovation proposal to provide resources that enable university students from Teacher Degree in Education Faculty of University of Extremadura (Spain) to develop the cross curricular competence of public speaking.

Keywords: Interaction, Public Speaking, Student, University.

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Authors: D. Uma Devi, P. Seetha Ramaiah

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Voting algorithms are extensively used to make decisions in fault tolerant systems where each redundant module gives inconsistent outputs. Popular voting algorithms include majority voting, weighted voting, and inexact majority voters. Each of these techniques suffers from scenarios where agreements do not exist for the given voter inputs. This has been successfully overcome in literature using fuzzy theory. Our previous work concentrated on a neuro-fuzzy algorithm where training using the neuro system substantially improved the prediction result of the voting system. Weight training of Neural Network is sub-optimal. This study proposes to optimize the weights of the Neural Network using Artificial Bee Colony algorithm. Experimental results show the proposed system improves the decision making of the voting algorithms.

Keywords: Voting algorithms, Fault tolerance, Fault masking, Neuro-Fuzzy System (NFS), Artificial Bee Colony (ABC)

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Authors: Asha Hasnimy Mohd Hashim, Lee Ai Choo

Abstract:

We investigated the effects of modified preprogrammed training mode Chase Trainer from Balance Trainer (BT3, HurLab, Tampere, Finland) on athlete who experienced unilateral Patellofemoral Pain Syndrome (PFPS). Twenty-seven athletes with mean age= 14.23 ±1.31 years, height = 164.89 ± 7.85 cm, weight = 56.94 ± 9.28 kg were randomly assigned to two groups: experiment (EG; n = 14) and injured (IG; n = 13). EG performed a series of Chase Trainer program which required them to shift their body weight at different directions, speeds and angle of leaning twice a week for duration of 8 weeks. The static postural control and perceived pain level measures were taken at baseline, after 6 weeks and 8 weeks of training. There was no significant difference in any of tested variables between EG and IG before and after 6-week the intervention period. However, after 8-week of training, the postural control (eyes open) and perceived pain level of EG improved compared to IG (p<0.05). The postural control with eyes closed of EG improved (p<0.05) but the values were not significantly different compared to IG after training. The results suggest that using Chase Trainer exercise program it is possible to improve individual postural control and decreased perceived pain level in athlete with unilateral Patellofemoral Pain Syndrome (PFPS).

Keywords: Patellofemoral Pain Syndrome, perceived pain level, postural control.

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Authors: E. Giovanis

Abstract:

In this paper we present a Feed-Foward Neural Networks Autoregressive (FFNN-AR) model with genetic algorithms training optimization in order to predict the gross domestic product growth of six countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer of the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model. Moreover this technique can be used in Autoregressive-Moving Average models, with and without exogenous inputs, as also the training process with genetics algorithms optimization can be replaced by the error back-propagation algorithm.

Keywords: Autoregressive model, Feed-Forward neuralnetworks, Genetic Algorithms, Gross Domestic Product

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Authors: Goh Yen Nee

Abstract:

This research aimed to find out the determining factors for ISO 14001 EMS implementation among SMEs in Malaysia from the Resource based view. A cross-sectional approach using survey was conducted. A research model been proposed which comprises of ISO 14001 EMS implementation as the criterion variable while physical capital resources (i.e. environmental performance tracking and organizational infrastructures), human capital resources (i.e. top management commitment and support, training and education, employee empowerment and teamwork) and organizational capital resources (i.e. recognition and reward, organizational culture and organizational communication) as the explanatory variables. The research findings show that only environmental performance tracking, top management commitment and support and organizational culture are found to be positively and significantly associated with ISO 14001 EMS implementation. It is expected that this research will shed new knowledge and provide a base for future studies about the role played by firm-s internal resources.

Keywords: ISO 14001 Environmental Management System, Malaysia, Resource based view, SMEs

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