Search results for: Recognition of Prior Learning

Authors: A.A. Amran, S. R. M. Shukri, S. M. Taib

Abstract:

The role of entrepreneurs in generating the economy is very important. Thus, nurturing entrepreneurship skills among society is very crucial and should start from the early age. One of the methods is to teach through game such as board game. Game provides a fun and interactive platform for players to learn and play. Besides that as today-s world is moving towards Islamic approach in terms of finance, banking and entertainment but Islamic based game is still hard to find in the market especially games on entrepreneurship. Therefore, there is a gap in this segment that can be filled by learning entrepreneurship through game. The objective of this paper is to develop an entrepreneurship digital-based game entitled “Catur Bistari" that is based on Islamic business approach. Knowledge and skill of entrepreneurship and Islamic business approach will be learned through the tasks that are incorporated inside the game.

Keywords: Board game, educational game, entrepreneurship, Islamic finance and simulation.

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Authors: Ersen Yazıcı, Erhan Ertekin

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In this study, any possible differences between mathematics beliefs and anxiety of prospective elementary mathematics teachers have been investigated according to their gender. In this purpose, 1st, 2nd, 3rd and 4th grade students from a Government University in Turkey were selected as a sample. Mathematics Teaching Anxiety Scale (MATAS) and Beliefs About Mathematics Survey (BAMS) has been used as data collection tools. As a result of the study, it has been observed that prospective male teachers have more instrumentalist approach in learning mathematics than females according to their mathematical beliefs. On the other hand, females have more mathematics teaching anxiety than males especially, for subject knowledge in mathematics and selfconfidence.

Keywords: Mathematical beliefs, mathematics teaching anxiety, gender, prospective elementary mathematics teachers.

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Authors: Alicia Y. C. Tang, Rukaini Hj. Abdullah, Sharifuddin M. Zain

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This paper discusses the development of a qualitative simulator (abbreviated QRiOM) for predicting the behaviour of organic chemical reactions. The simulation technique is based on the qualitative process theory (QPT) ontology. The modelling constructs of QPT embody notions of causality which can be used to explain the behaviour of a chemical system. The major theme of this work is that, in a qualitative simulation environment, students are able to articulate his/her knowledge through the inspection of explanations generated by software. The implementation languages are Java and Prolog. The software produces explanation in various forms that stresses on the causal theories in the chemical system which can be effectively used to support learning.

Keywords: Chemical reactions, explanation, qualitative processtheory, simulation

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Authors: Mariam Vardiashvili

Abstract:

The economic value of the asset impairment process is quite large. Impairment reflects the reduction of future economic benefits or service potentials itemized in the asset. The assets owned by public sector entities bring economic benefits or are used for delivery of the free-of-charge services. Consequently, they are classified as cash-generating and non-cash-generating assets. IPSAS 21 - Impairment of non-cash-generating assets, and IPSAS 26 - Impairment of cash-generating assets, have been designed considering this specificity.  When measuring impairment of assets, it is important to select the relevant methods. For measurement of the impaired Non-Cash-Generating Assets, IPSAS 21 recommends three methods: Depreciated Replacement Cost Approach, Restoration Cost Approach, and  Service Units Approach. Impairment of Value in Use of Cash-Generating Assets (according to IPSAS 26) is measured by discounted value of the money sources to be received in future. Value in use of the cash-generating asserts (as per IPSAS 26) is measured by the discounted value of the money sources to be received in the future. The article provides classification of the assets in the public sector  as non-cash-generating assets and cash-generating assets and, deals also with the factors which should be considered when evaluating  impairment of assets. An essence of impairment of the non-financial assets and the methods of measurement thereof evaluation are formulated according to IPSAS 21 and IPSAS 26. The main emphasis is put on different methods of measurement of the value in use of the impaired Cash-Generating Assets and Non-Cash-Generation Assets and the methods of their selection. The traditional and the expected cash flow approaches for calculation of the discounted value are reviewed. The article also discusses the issues of recognition of impairment loss and its reflection in the financial reporting. The article concludes that despite a functional purpose of the impaired asset, whichever method is used for measuring the asset, presentation of realistic information regarding the value of the assets should be ensured in the financial reporting. In the theoretical development of the issue, the methods of scientific abstraction, analysis and synthesis were used. The research was carried out with a systemic approach. The research process uses international standards of accounting, theoretical researches and publications of Georgian and foreign scientists.

Keywords: Non-cash-generating assets, cash-generating assets, recoverable value, recoverable service amount, value in use.

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Authors: M. Rodionov, Z. Dedovets

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This article discusses plausible reasoning use for solution to practical problems. Such reasoning is the major driver of motivation and implementation of mathematical, scientific and educational research activity. A general, practical problem solving algorithm is presented which includes an analysis of specific problem content to build, solve and interpret the underlying mathematical model. The author explores the role of practical problems such as the stimulation of students' interest, the development of their world outlook and their orientation in the modern world at the different stages of learning mathematics in secondary school. Particular attention is paid to the characteristics of those problems which were systematized and presented in the conclusions.

Keywords: Mathematics, motivation, secondary school, student, practical problem.

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Authors: H. Sagha, S. Kasaei, E. Enayati, M. Dehghani

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Although Face detection is not a recent activity in the field of image processing, it is still an open area for research. The greatest step in this field is the work reported by Viola and its recent analogous is Huang et al. Both of them use similar features and also similar training process. The former is just for detecting upright faces, but the latter can detect multi-view faces in still grayscale images using new features called 'sparse feature'. Finding these features is very time consuming and inefficient by proposed methods. Here, we propose a new approach for finding sparse features using a genetic algorithm system. This method requires less computational cost and gets more effective features in learning process for face detection that causes more accuracy.

Keywords: Face Detection, Genetic Algorithms, Sparse Feature.

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Authors: Sana Bouzaida, Anis Sakly, Faouzi M'Sahli

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In this paper, a TSK-type Neuro-fuzzy Inference System that combines the features of fuzzy sets and neural networks has been applied for the identification of MIMO systems. The procedure of adapting parameters in TSK model employs a Shuffled Frog Leaping Algorithm (SFLA) which is inspired from the memetic evolution of a group of frogs when seeking for food. To demonstrate the accuracy and effectiveness of the proposed controller, two nonlinear systems have been considered as the MIMO plant, and results have been compared with other learning methods based on Particle Swarm Optimization algorithm (PSO) and Genetic Algorithm (GA).

Keywords: Identification, Shuffled frog Leaping Algorithm (SFLA), TSK-type neuro-fuzzy model.

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Authors: Abdellghani Bellaachia, Edward Jimenez

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Music Information Retrieval (MIR) and modern data mining techniques are applied to identify style markers in midi music for stylometric analysis and author attribution. Over 100 attributes are extracted from a library of 2830 songs then mined using supervised learning data mining techniques. Two attributes are identified that provide high informational gain. These attributes are then used as style markers to predict authorship. Using these style markers the authors are able to correctly distinguish songs written by the Beatles from those that were not with a precision and accuracy of over 98 per cent. The identification of these style markers as well as the architecture for this research provides a foundation for future research in musical stylometry.

Keywords: Music Information Retrieval, Music Data Mining, Stylometry.

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Authors: Aditya K, Dinesh P, Ramesh Bhakthavatchalu

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This paper explains a project based learning method where autonomous mini-robots are developed for research, education and entertainment purposes. In case of remote systems wireless sensors are developed in critical areas, which would collect data at specific time intervals, send the data to the central wireless node based on certain preferred information would make decisions to turn on or off a switch or control unit. Such information transfers hardly sums up to a few bytes and hence low data rates would suffice for such implementations. As a robot is a multidisciplinary platform, the interfacing issues involved are discussed in this paper. The paper is mainly focused on power supply, grounding and decoupling issues.

Keywords: CPLD, power supply, decoupling, grounding.

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Authors: Fadzilah Abdul Rahman

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Emotional development is developed between the parents and their child. Behavioural development is also developed between the parents and their child. Social Development is how parents can help their special needs child to adapt to society and to face challenges. In promoting a lifelong learning mindset, enhancing skill sets and readiness to face challenges, parents would be able to counter balance these challenges during their care giving process and better manage their expectations through understanding the hierarchy of needs modality towards a positive attitude, and in turn, improve their quality of life and participation in society. This paper aims to demonstrate how the hierarchy of needs can be applied in various situations of caregiving for parents with a special needs child.

Keywords: Hierarchy of needs, parents, special needs, care-giving.

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Authors: M. S. Roslina, A. Noraziah

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Malaysia government had been trying hard in order to find the most efficient methods in learning. However, it is hard to actually access and evaluate students whom will then be called an excellent student. It is because in our realties student who excellent is only excel in academic. This evaluation becomes a problem because it not balances in our real life interm of to get an excellent student in whole area in their involvement of curiculum and cocuriculum. To overcome this scenario, we designed a module for Student Idol to evaluate student through three categories which are academic, co-curiculum and leadership. All the categories have their own merit point. Using this method, student will be evaluated more accurate compared to the previously. So, teacher can easily evaluate their student without having any emotion factor, relation factor and others. As conclusion this system module will helps the development of student evaluation more accurate and valid in Student Idol.

Keywords: Evaluation, curiculum, co-curriculum, idol, systemmodule.

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Authors: Manish Jain, Dinesh Gopalani

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Growing dependency of mankind on software technology increases the need for thorough testing of the software applications and automated testing techniques that support testing activities. We have outlined our testing strategy for performing various types of automated testing of Java applications using AspectJ which has become the de-facto standard for Aspect Oriented Programming (AOP). Likewise JUnit, a unit testing framework is the most popular Java testing tool. In this paper, we have evaluated our proposed AOP approach for automated testing and JUnit on various parameters. First we have provided the similarity between the two approaches and then we have done a detailed comparison of the two testing techniques on factors like lines of testing code, learning curve, testing of private members etc. We established that our AOP testing approach using AspectJ has got several advantages and is thus particularly more effective than JUnit.

Keywords: Aspect oriented programming, AspectJ, Aspects, JUnit, software testing.

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Authors: A. V. Varfolomeeva, N. S. Tkachenko, A. G. Tishchenko

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In this study, we addressed the problem of weak validity, implausible results, and inaccurate reporting in psychological research on different species. The theoretical basis of the study was the systems-evolutionary approach (SEA). We assumed that the root of the problem is the values and attitudes of the researchers (in particular anthropomorphism and anthropocentrism). The first aim of the study was the formulation of a research design that avoids this problem. Based on a literature review, we concluded that such design, amongst other things, should include methodics with playful components. The second aim was to conduct a series of studies on the differences in the formation of instrumental skill in rats raised and housed in different environments. As a result, we revealed that there are contradictions between some of the statements of SEA, so that it is not possible to choose one of the alternative hypotheses. We suggested that in order to get out of this problem, it is necessary to modify these provisions by aligning them with the attitude of multicentrism.

Keywords: epistemological attitudes, experimental design, validity, psychological structure, learning

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Authors: M. Sinecen, M. Makinacı

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The purpose of this paper is to assess the value of neural networks for classification of cancer and noncancer prostate cells. Gauss Markov Random Fields, Fourier entropy and wavelet average deviation features are calculated from 80 noncancer and 80 cancer prostate cell nuclei. For classification, artificial neural network techniques which are multilayer perceptron, radial basis function and learning vector quantization are used. Two methods are utilized for multilayer perceptron. First method has single hidden layer and between 3-15 nodes, second method has two hidden layer and each layer has between 3-15 nodes. Overall classification rate of 86.88% is achieved.

Keywords: Artificial neural networks, texture classification, cancer diagnosis.

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Authors: A. Tellaeche, R. Arana

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Injection molding is a very complicated process to monitor and control. With its high complexity and many process parameters, the optimization of these systems is a very challenging problem. To meet the requirements and costs demanded by the market, there has been an intense development and research with the aim to maintain the process under control. This paper outlines the latest advances in necessary algorithms for plastic injection process and monitoring, and also a flexible data acquisition system that allows rapid implementation of complex algorithms to assess their correct performance and can be integrated in the quality control process. This is the main topic of this paper. Finally, to demonstrate the performance achieved by this combination, a real case of use is presented.

Keywords: Plastic injection, machine learning, rapid complex algorithm prototyping.

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Authors: Aspasia Koutsokosta, Stefanos Katsavounis

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This paper reviews the model-based qualitative and quantitative Operations Management research in the context of Construction Supply Chain Management (CSCM). Construction industry has been traditionally blamed for low productivity, cost and time overruns, waste, high fragmentation and adversarial relationships. The construction industry has been slower than other industries to employ the Supply Chain Management (SCM) concept and develop models that support the decision-making and planning. However the last decade there is a distinct shift from a project-based to a supply-based approach of construction management. CSCM comes up as a new promising management tool of construction operations and improves the performance of construction projects in terms of cost, time and quality. Modeling the Construction Supply Chain (CSC) offers the means to reap the benefits of SCM, make informed decisions and gain competitive advantage. Different modeling approaches and methodologies have been applied in the multi-disciplinary and heterogeneous research field of CSCM. The literature review reveals that a considerable percentage of the CSC modeling research accommodates conceptual or process models which present general management frameworks and do not relate to acknowledged soft Operations Research methods. We particularly focus on the model-based quantitative research and categorize the CSCM models depending on their scope, objectives, modeling approach, solution methods and software used. Although over the last few years there has been clearly an increase of research papers on quantitative CSC models, we identify that the relevant literature is very fragmented with limited applications of simulation, mathematical programming and simulation-based optimization. Most applications are project-specific or study only parts of the supply system. Thus, some complex interdependencies within construction are neglected and the implementation of the integrated supply chain management is hindered. We conclude this paper by giving future research directions and emphasizing the need to develop optimization models for integrated CSCM. We stress that CSC modeling needs a multi-dimensional, system-wide and long-term perspective. Finally, prior applications of SCM to other industries have to be taken into account in order to model CSCs, but not without translating the generic concepts to the context of construction industry.

Keywords: Construction supply chain management, modeling, operations research, optimization and simulation.

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Authors: S. M. Amin Hosseini, Oriol Pons, Carmen Mendoza Arroyo, Albert de la Fuente

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In the aftermath of a natural disaster, the major challenge most cities and societies face, regardless of their diverse level of prosperity, is to provide temporary housing (TH) for the displaced population (DP). However, the features of TH, which have been applied in previous recovery programs, greatly varied from case to case. This situation demonstrates that providing temporary accommodation for DP in a short period time and usually in great numbers is complicated in terms of satisfying all the beneficiaries’ needs, regardless of the societies’ welfare levels. Furthermore, when previously used strategies are applied to different areas, the chosen strategies are most likely destined to fail, unless the strategies are context and culturally based. Therefore, as the population of disaster-prone cities are increasing, decision-makers need a platform to help to determine all the factors, which caused the outcomes of the prior programs. To this end, this paper aims to assess the problems, requirements, limitations, potential responses, chosen strategies, and their outcomes, in order to determine the main elements that have influenced the TH process. In this regard, and in order to determine a customizable strategy, this study analyses the TH programs of five different cases as: Marmara earthquake, 1999; Bam earthquake, 2003; Aceh earthquake and tsunami, 2004; Hurricane Katrina, 2005; and, L’Aquila earthquake, 2009. The research results demonstrate that the main vertexes of TH are: (1) local characteristics, including local potential and affected population features, (2) TH properties, which needs to be considered in four phases: planning, provision/construction, operation, and second life, and (3) natural hazards impacts, which embraces intensity and type. Accordingly, this study offers decision-makers the opportunity to discover the main vertexes, their subsets, interactions, and the relation between strategies and outcomes based on the local conditions of each case. Consequently, authorities may acquire the capability to design a customizable method in the face of complicated post-disaster housing in the wake of future natural disasters.

Keywords: Post-disaster temporary accommodation, urban resilience, natural disaster, local characteristic.

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Authors: Subrahmanyam Kodukula, Nurbiya Maimaiti

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There have been many variations of technologies that helped educators in teaching & learning. From the past research it is evident that Information Technology significantly increases student participation and interactivity in the classrooms. This research started with a aim to find whether adoption of Wi-Fi environment by Malaysian Higher Educational Institutions (HEI) can benefit students and staff equally. The study was carried out in HEI-s of Klang Valley, Malaysia and the data is gathered through paper based surveys. A sample size of 237 units were randomly selected from 5 higher educational institutions in the Klang Valley using the Stratified Random sampling method and from the analysis of the data, it was found that the implementation of wireless technologies in HEIs have created lot of opportunities and also challenges.

Keywords: Wired Technologies, Wireless Classroom, HEI, Dense User Environment.

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Authors: Danilo López, Nelson Vera, Luis Pedraza

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This paper analyzes fundamental ideas and concepts related to neural networks, which provide the reader a theoretical explanation of Long Short-Term Memory (LSTM) networks operation classified as Deep Learning Systems, and to explicitly present the mathematical development of Backward Pass equations of the LSTM network model. This mathematical modeling associated with software development will provide the necessary tools to develop an intelligent system capable of predicting the behavior of licensed users in wireless cognitive radio networks.

Keywords: Neural networks, multilayer perceptron, long short-term memory, recurrent neuronal network, mathematical analysis.

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Authors: Daniel I. Morariu, Lucian N. Vintan, Volker Tresp

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Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, we present three feature selection methods: Information Gain, Support Vector Machine feature selection called (SVM_FS) and Genetic Algorithm with SVM (called GA_SVM). We show that the best results were obtained with GA_SVM method for a relatively small dimension of the feature vector.

Keywords: Feature Selection, Learning with Kernels, Support Vector Machine, Genetic Algorithm, and Classification.

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: Network Intrusion Detection, Machine learning, Artificial Neural Network.

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Authors: Daniel Morariu, Lucian N. Vintan, Volker Tresp

Abstract:

Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, three feature selection methods are evaluated: Random Selection, Information Gain (IG) and Support Vector Machine feature selection (called SVM_FS). We show that the best results were obtained with SVM_FS method for a relatively small dimension of the feature vector. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).

Keywords: Feature Selection, Learning with Kernels, SupportVector Machine, and Classification.

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Authors: Gitanjali Devi, Kandarpa Kumar Sarma, Pranayee Datta, Anjana Kakoti Mahanta

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Artificial Neural Network (ANN)s can be modeled for High Energy Particle analysis with special emphasis on shower core location. The work describes the use of an ANN based system which has been configured to predict locations of cores of showers in the range 1010.5 to 1020.5 eV. The system receives density values as inputs and generates coordinates of shower events recorded for values captured by 20 core positions and 80 detectors in an area of 100 meters. Twenty ANNs are trained for the purpose and the positions of shower events optimized by using cooperative ANN learning. The results derived with variations of input upto 50% show success rates in the range of 90s.

Keywords: EAS, Shower, Core, ANN, Location.

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Authors: Boukerch Haroun, Luo Qing Sheng, Li Hua Shi, Boukraa Sebti

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In this paper we present the design and the implementation of a target tracking system where the target is set to be a moving person in a video sequence. The system can be applied easily as a vision system for mobile robot. The system is composed of two major parts the first is the detection of the person in the video frame using the SVM learning machine based on the “HOG” descriptors. The second part is the tracking of a moving person it’s done by using a combination of the Kalman filter and a modified version of the Camshift tracking algorithm by adding the target motion feature to the color feature, the experimental results had shown that the new algorithm had overcame the traditional Camshift algorithm in robustness and in case of occlusion.

Keywords: Camshift Algorithm, Computer Vision, Kalman Filter, Object tracking.

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Authors: C. Cruz, A. Breda

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Emotions are manifestations of everything that happens around us, influencing, consequently, our actions. People experience emotions continuously when socialize with friends, when facing complex situations, and when at school, among many other situations. Although the influence of emotions in the teaching and learning process is nothing new, its study in the academic field has been more popular in recent years, distinguishing between positive (e.g., enjoyment and curiosity) and negative emotions (e.g., boredom and frustration). There is no doubt that emotions play an important role in the students’ learning process since the development of knowledge involves thoughts, actions, and emotions. Nowadays, one of the most significant changes in acquiring knowledge, accessing information, and communicating is the way we do it through technological and digital resources. Faced with an increasingly frequent use of technological or digital means with different purposes, whether in the acquisition of knowledge or in communicating with others, the emotions involved in these processes change naturally. The speed with which the Internet provides information reduces the excitement for searching for the answer, the gratification of discovering something through our own effort, the patience, the capacity for effort, and resilience. Thus, technological and digital devices are bringing changes to the emotional domain. For this reason and others, it is essential to educate children from an early age to understand that it is not possible to have everything with just one click and to deal with negative emotions. Currently, many curriculum guidelines highlight the importance of the development of so-called soft skills, in which the emotional domain is present, in academic contexts. Within the scope of the Portuguese reality, the “Students’ profile by the end of compulsory schooling” and the “Health education reference” also emphasize the importance of emotions in education. There are several resources to stimulate good emotions in articulation with cognitive development. One of the most predictable and not very used resources in the most diverse areas of knowledge after pre-school education is the literature. Due to its characteristics, in the narrative or in the illustrations, literature provides the reader with a journey full of emotions. On the other hand, literature makes it possible to establish bridges between narrative and different areas of knowledge, reconciling the cognitive and emotional domains. This study results from the presentation session of a children's book, entitled “From the Outside to Inside and from the Inside to Outside”, to children attending the 2nd, 3rd, and 4th years of basic education in the Portuguese education system. In this book, rationale and emotion are in constant dialogue, so in this session, based on excerpts from the book dramatized by the authors, some questions were asked to the children in a large group, with an aim to explore their perception regarding certain emotions or events that trigger them. According to the aim of this study, qualitative, descriptive, and interpretative research was carried out based on participant observation and audio records.

Keywords: Emotions, children’s literature, basic education, soft skills.

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Authors: Aji P. Wibawa, Andrew Nafalski, Neil Murray, Wayan F. Mahmudy

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Since the one-to-one word translator does not have the facility to translate pragmatic aspects of Javanese, the parallel text alignment model described uses a phrase pair combination. The algorithm aligns the parallel text automatically from the beginning to the end of each sentence. Even though the results of the phrase pair combination outperform the previous algorithm, it is still inefficient. Recording all possible combinations consume more space in the database and time consuming. The original algorithm is modified by applying the edit distance coefficient to improve the data-storage efficiency. As a result, the data-storage consumption is 90% reduced as well as its learning period (42s).

Keywords: edit distance coefficient, Javanese, parallel text alignment, phrase pair combination

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Authors: S. Pattanapairoj, D. Chetchotsak

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This paper proposed classification models that would be used as a proxy for hard disk drive (HDD) functional test equitant which required approximately more than two weeks to perform the HDD status classification in either “Pass" or “Fail". These models were constructed by using committee network which consisted of a number of single neural networks. This paper also included the method to solve the problem of sparseness data in failed part, which was called “enforce learning method". Our results reveal that the constructed classification models with the proposed method could perform well in the sparse data conditions and thus the models, which used a few seconds for HDD classification, could be used to substitute the HDD functional tests.

Keywords: Sparse data, Classifications, Committee network

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Authors: Nidhi Gadura

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Given the increase in the number of students and administrators asking for online courses the author developed two partially online courses. One was a biology majors at genetics course while the other was a non-majors at biology course. The student body at Queensborough Community College is generally underprepared and has work and family obligations. As an educator, one has to be mindful about changing the pedagogical approach, therefore, special care was taken when designing the course material. Despite the initial concerns, both of these partially online courses were received really well by students. Lessons learnt were that student engagement is the key to success in an online course. Good practices to run a successful online course for underprepared students are discussed in this paper. Also discussed are the lessons learnt for making the eLearning environment better for all the students in the class, overachievers and underachievers alike.

Keywords: Partially online course, pedagogy, student engagement, community college.

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Authors: Carlos Huertas, Reyes Juarez-Ramirez

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Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: Feature selection, mass spectrometry, biomarker discovery, cancer.

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Authors: H. Nakamura

Abstract:

This study analyzes international strategic alliances in the information industry. The purpose of this study is to clarify the strategic intention of an international alliance. Secondly, it investigates the influence of differences in the target markets of partner companies on alliances. Using an international strategy theory approach to analyze the global strategies of global companies, the study compares a database business and an electronic publishing business. In particular, these cases emphasized factors attributable to "people" and "learning", reliability and communication between organizations and the evolution of the IT infrastructure. The theory evolved in this study validates the effectiveness of these strategies.

Keywords: Database business, electronic library, international strategic alliances, partner selection.

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