Search results for: foreign language learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2859

Search results for: foreign language learning

1269 Effect of Personality Traits on Classification of Political Orientation

Authors: Vesile Evrim, Aliyu Awwal

Abstract:

Today, there is a large number of political transcripts available on the Web to be mined and used for statistical analysis, and product recommendations. As the online political resources are used for various purposes, automatically determining the political orientation on these transcripts becomes crucial. The methodologies used by machine learning algorithms to do an automatic classification are based on different features that are classified under categories such as Linguistic, Personality etc. Considering the ideological differences between Liberals and Conservatives, in this paper, the effect of Personality traits on political orientation classification is studied. The experiments in this study were based on the correlation between LIWC features and the BIG Five Personality traits. Several experiments were conducted using Convote U.S. Congressional- Speech dataset with seven benchmark classification algorithms. The different methodologies were applied on several LIWC feature sets that constituted by 8 to 64 varying number of features that are correlated to five personality traits. As results of experiments, Neuroticism trait was obtained to be the most differentiating personality trait for classification of political orientation. At the same time, it was observed that the personality trait based classification methodology gives better and comparable results with the related work.

Keywords: Politics, personality traits, LIWC, machine learning.

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1268 Forecasting US Dollar/Euro Exchange Rate with Genetic Fuzzy Predictor

Authors: R. Mechgoug, A. Titaouine

Abstract:

Fuzzy systems have been successfully used for exchange rate forecasting. However, fuzzy system is very confusing and complex to be designed by an expert, as there is a large set of parameters (fuzzy knowledge base) that must be selected, it is not a simple task to select the appropriate fuzzy knowledge base for an exchange rate forecasting. The researchers often look the effect of fuzzy knowledge base on the performances of fuzzy system forecasting. This paper proposes a genetic fuzzy predictor to forecast the future value of daily US Dollar/Euro exchange rate time’s series. A range of methodologies based on a set of fuzzy predictor’s which allow the forecasting of the same time series, but with a different fuzzy partition. Each fuzzy predictor is built from two stages, where each stage is performed by a real genetic algorithm.

Keywords: Foreign exchange rate, time series forecasting, Fuzzy System, and Genetic Algorithm.

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1267 Managing an Acute Pain Unit Based on the Balanced Scorecard

Authors: Helena Costa Oliveira, Carmem Oliveira, Rita Moutinho

Abstract:

The Balanced Scorecard (BSC) is a continuous strategic monitoring model focused not only on financial issues but also on internal processes, patients/users, and learning and growth. Initially dedicated to business management, it currently serves organizations of other natures - such as hospitals. This paper presents a BSC designed for a Portuguese Acute Pain Unit (APU). This study is qualitative and based on the experience of collaborators at the APU. The management of APU is based on four perspectives – users, internal processes, learning and growth, and financial and legal. For each perspective, there were identified strategic objectives, critical factors, lead indicators and initiatives. The strategic map of the APU outlining sustained strategic relations among strategic objectives. This study contributes to the development of research in the health management area as it explores how organizational insufficiencies and inconsistencies in this particular case can be addressed, through the identification of critical factors, to clearly establish core outcomes and initiatives to set up.

Keywords: Acute pain unit, balanced scorecard, hospital management, organizational performance, Portugal.

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1266 Elaboration and Validation of a Survey about Research on the Characteristics of Mentoring of University Professors’ Lifelong Learning

Authors: Nagore Guerra Bilbao, Clemente Lobato Fraile

Abstract:

This paper outlines the design and development of the MENDEPRO questionnaire, designed to analyze mentoring performance within a professional development process carried out with professors at the University of the Basque Country, Spain. The study took into account the international research carried out over the past two decades into teachers' professional development, and was also based on a thorough review of the most common instruments used to identify and analyze mentoring styles, many of which fail to provide sufficient psychometric guarantees. The present study aimed to gather empirical data in order to verify the metric quality of the questionnaire developed. To this end, the process followed to validate the theoretical construct was as follows: The formulation of the items and indicators in accordance with the study variables; the analysis of the validity and reliability of the initial questionnaire; the review of the second version of the questionnaire and the definitive measurement instrument. Content was validated through the formal agreement and consensus of 12 university professor training experts. A reduced sample of professors who had participated in a lifelong learning program was then selected for a trial evaluation of the instrument developed. After the trial, 18 items were removed from the initial questionnaire. The final version of the instrument, comprising 33 items, was then administered to a sample group of 99 participants. The results revealed a five-dimensional structure matching theoretical expectations. Also, the reliability data for both the instrument as a whole (.98) and its various dimensions (between .91 and .97) were very high. The questionnaire was thus found to have satisfactory psychometric properties and can therefore be considered apt for studying the performance of mentoring in both induction programs for young professors and lifelong learning programs for senior faculty members.

Keywords: Higher education, mentoring, professional development, university teachers.

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1265 Methods of Estimating the Equilibrium Real Effective Exchange Rate (REER)

Authors: Pavla Ruzickova, Petr Teply

Abstract:

There are many debates now regarding undervalued and overvalued currencies currently traded on the world financial market. This paper contributes to these debates from a theoretical point of view. We present the three most commonly used methods of estimating the equilibrium real effective exchange rate (REER): macroeconomic balance approach, external sustainability approach and equilibrium real effective exchange rate approach in the reduced form. Moreover, we discuss key concepts of the calculation of the real exchange rate (RER) based on applied explanatory variables: nominal exchange rates, terms of trade and tradable and non-tradable goods. Last but not least, we discuss the three main driving forces behind real exchange rates movements which include terms of trade, relative productivity growth and the interest rate differential.

Keywords: real exchange rate, real effective exchange rate, foreign exchange, terms of trade

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1264 Classification of Health Risk Factors to Predict the Risk of Falling in Older Adults

Authors: L. Lindsay, S. A. Coleman, D. Kerr, B. J. Taylor, A. Moorhead

Abstract:

Cognitive decline and frailty is apparent in older adults leading to an increased likelihood of the risk of falling. Currently health care professionals have to make professional decisions regarding such risks, and hence make difficult decisions regarding the future welfare of the ageing population. This study uses health data from The Irish Longitudinal Study on Ageing (TILDA), focusing on adults over the age of 50 years, in order to analyse health risk factors and predict the likelihood of falls. This prediction is based on the use of machine learning algorithms whereby health risk factors are used as inputs to predict the likelihood of falling. Initial results show that health risk factors such as long-term health issues contribute to the number of falls. The identification of such health risk factors has the potential to inform health and social care professionals, older people and their family members in order to mitigate daily living risks.

Keywords: Classification, falls, health risk factors, machine learning, older adults.

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1263 On the Factors Influencing the Competitiveness of Chinese Service Trade after Entering WTO

Authors: Ying Wang

Abstract:

Service trade is an important force of influencing economic development. A review on the related literatures is done firstly. Then through the construction of a Diamond Model, the main factors which influence the competitiveness of Chinese service trade are determined. With three competitiveness indexes served as the reference series respectively, the influencing factors served as the comparable series, three grey incidence models are then built up to conduct an empirical analysis on the main factors influencing the competitiveness of service trade after China entering WTO. The result indicates that urbanization level, open degree of service industry and foreign direct investment have larger impacts on Chinese service trade competitiveness, followed in turn by GDP in service industry and human capital, while commodity trade has the minimum impact. Further discussion provides train of thought for the upgrade of Chinese service trade competitiveness.

Keywords: Service Trade, Competitiveness, Diamond Model, Grey Incidence Model.

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1262 SEM Image Classification Using CNN Architectures

Authors: G. Türkmen, Ö. Tekin, K. Kurtuluş, Y. Y. Yurtseven, M. Baran

Abstract:

A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: Convolutional Neural Networks, deep learning, image classification, scanning electron microscope.

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1261 A Practical Model for Managing Beach Safety Focusing on Tourist Drownings in Koh Samui, Thailand

Authors: Siyathorn Khunon, Thanawit Buafai

Abstract:

This paper aims to investigate management of beach safety with a focus on tourist drownings in Samui. The data collected in this investigation will then lead to the proposal of a practical management model suitable for use in Samui. Qualitative research was conducted in the following manner: nine stakeholders from local government organizations and tourism businesses were interviewed in-depth. Additionally, a best practice case study from Phuket was applied to analyze beach safety. Twelve foreign tourists were also interviewed. Then, a focus group comprised of 32 people was used to determine practical solutions for enhancing tourists’ safety on the beach in Samui. A steering committee to coordinate between public and private organizations was proposed to manage and enhance tourists’ safety. A practical model is proposed to increase the safety level of tourists in Samui

Keywords: Beach safety, drowning, tourists, Samui.

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1260 Feature-Based Summarizing and Ranking from Customer Reviews

Authors: Dim En Nyaung, Thin Lai Lai Thein

Abstract:

Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: Opinion Mining, Opinion Summarization, Sentiment Analysis, Text Mining.

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1259 A Second Look at Gesture-Based Passwords: Usability and Vulnerability to Shoulder-Surfing Attacks

Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

Abstract:

For security purposes, it is important to detect passwords entered by unauthorized users. With traditional alphanumeric passwords, if the content of a password is acquired and correctly entered by an intruder, it is impossible to differentiate the password entered by the intruder from those entered by the authorized user because the password entries contain precisely the same character set. However, no two entries for the gesture-based passwords, even those entered by the person who created the password, will be identical. There are always variations between entries, such as the shape and length of each stroke, the location of each stroke, and the speed of drawing. It is possible that passwords entered by the unauthorized user contain higher levels of variations when compared with those entered by the authorized user (the creator). The difference in the levels of variations may provide cues to detect unauthorized entries. To test this hypothesis, we designed an empirical study, collected and analyzed the data with the help of machine-learning algorithms. The results of the study are significant.

Keywords: Authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability.

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1258 The Extension of Monomeric Computational Results to Polymeric Measurable Properties: An Introductory Computational Chemistry Experiment

Authors: Zhao Jing, Bai Yongqing, Shi Qiaofang, Zang Yang, Zhang Huaihao

Abstract:

Advances in software technology enable the computational chemistry to be commonly applied in various research fields, especially in pedagogy. Thus, in order to expand and improve experimental instructions of computational chemistry for undergraduates, we designed an introductory experiment—research on acrylamide molecular structure and physicochemical properties. Initially, students construct molecular models of acrylamide and polyacrylamide in Gaussian and Materials Studio software respectively. Then, the infrared spectral data, atomic charge and molecular orbitals of acrylamide as well as solvation effect of polyacrylamide are calculated to predict their physicochemical performance. At last, rheological experiments are used to validate these predictions. Through the combination of molecular simulation (performed on Gaussian, Materials Studio) with experimental verification (rheology experiment), learners have deeply comprehended the chemical nature of acrylamide and polyacrylamide, achieving good learning outcomes.

Keywords: Upper-division undergraduate, computer-based learning, laboratory instruction, amides, molecular modeling, spectroscopy.

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1257 Finite-Horizon Tracking Control for Repetitive Systems with Uncertain Initial Conditions

Authors: Sung Wook Yun, Yun Jong Choi, Kyong-min Lee, Poogyeon Park*

Abstract:

Repetitive systems stand for a kind of systems that perform a simple task on a fixed pattern repetitively, which are widely spread in industrial fields. Hence, many researchers have been interested in those systems, especially in the field of iterative learning control (ILC). In this paper, we propose a finite-horizon tracking control scheme for linear time-varying repetitive systems with uncertain initial conditions. The scheme is derived both analytically and numerically for state-feedback systems and only numerically for output-feedback systems. Then, it is extended to stable systems with input constraints. All numerical schemes are developed in the forms of linear matrix inequalities (LMIs). A distinguished feature of the proposed scheme from the existing iterative learning control is that the scheme guarantees the tracking performance exactly even under uncertain initial conditions. The simulation results demonstrate the good performance of the proposed scheme.

Keywords: Finite time horizon, linear matrix inequality (LMI), repetitive system, uncertain initial condition.

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1256 The Strategy for Increasing the Competitiveness of Georgia

Authors: G. Erkomaishvili

Abstract:

The paper discusses economic policy of Georgia aiming to increase national competitiveness as well as the tools and means which will help to improve the competitiveness of the country. The sectors of the economy, in which the country can achieve the competitive advantage, are studied. It is noted that the country’s economic policy plays an important role in obtaining and maintaining the competitive advantage - authority should take measures to ensure high level of education; scientific and research activities should be funded by the state; foreign direct investments should be attracted mainly in science-intensive industries; adaptation with the latest scientific achievements of the modern world and deepening of scientific and technical cooperation. Stable business environment and export oriented strategy is the basis for the country’s economic growth. As the outcome of the research, the paper suggests the strategy for improving competitiveness in Georgia; recommendations are provided based on relevant conclusions.

Keywords: Competitive advantage, competitiveness, competitiveness improvement strategy, competitiveness of Georgia.

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1255 Understanding Work Integrated Learning in ICT: A Systems Perspective

Authors: Anneke Harmse, Roelien Goede

Abstract:

Information and communication technology (ICT) is essential to the operation of business, and create many employment opportunities. High volumes of students graduate in ICT however students struggle to find job placement. A discrepancy exists between graduate skills and industry skill requirements. To address the need for ICT skills required, universities must create programs to meet the demands of a changing ICT industry. This requires a partnership between industry, universities and other stakeholders. This situation may be viewed as a critical systems thinking problem situation as there are various role players each with their own needs and requirements. Jackson states a typical critical systems methods has a pluralistic nature. This paper explores the applicability and suitability of Maslow and Dooyeweerd to guide understanding and make recommendations for change in ICT WIL, to foster an all-inclusive understanding of the situation by stakeholders. The above methods provide tools for understanding softer issues beyond the skills required. The study findings suggest that besides skills requirements, a deeper understanding and empowering students from being a student to a professional need to be understood and addressed.

Keywords: Dooyeweerd, Maslow, Work Integrated Learning.

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1254 The Forensic Swing of Things: The Current Legal and Technical Challenges of IoT Forensics

Authors: Pantaleon Lutta, Mohamed Sedky, Mohamed Hassan

Abstract:

The inability of organizations to put in place management control measures for Internet of Things (IoT) complexities persists to be a risk concern. Policy makers have been left to scamper in finding measures to combat these security and privacy concerns. IoT forensics is a cumbersome process as there is no standardization of the IoT products, no or limited historical data are stored on the devices. This paper highlights why IoT forensics is a unique adventure and brought out the legal challenges encountered in the investigation process. A quadrant model is presented to study the conflicting aspects in IoT forensics. The model analyses the effectiveness of forensic investigation process versus the admissibility of the evidence integrity; taking into account the user privacy and the providers’ compliance with the laws and regulations. Our analysis concludes that a semi-automated forensic process using machine learning, could eliminate the human factor from the profiling and surveillance processes, and hence resolves the issues of data protection (privacy and confidentiality).

Keywords: Cloud forensics, data protection laws, GDPR, IoT forensics, machine learning.

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1253 Electromyography Pattern Classification with Laplacian Eigenmaps in Human Running

Authors: Elnaz Lashgari, Emel Demircan

Abstract:

Electromyography (EMG) is one of the most important interfaces between humans and robots for rehabilitation. Decoding this signal helps to recognize muscle activation and converts it into smooth motion for the robots. Detecting each muscle’s pattern during walking and running is vital for improving the quality of a patient’s life. In this study, EMG data from 10 muscles in 10 subjects at 4 different speeds were analyzed. EMG signals are nonlinear with high dimensionality. To deal with this challenge, we extracted some features in time-frequency domain and used manifold learning and Laplacian Eigenmaps algorithm to find the intrinsic features that represent data in low-dimensional space. We then used the Bayesian classifier to identify various patterns of EMG signals for different muscles across a range of running speeds. The best result for vastus medialis muscle corresponds to 97.87±0.69 for sensitivity and 88.37±0.79 for specificity with 97.07±0.29 accuracy using Bayesian classifier. The results of this study provide important insight into human movement and its application for robotics research.

Keywords: Electrocardiogram, manifold learning, Laplacian Eigenmaps, running pattern.

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1252 Students’ Level of Participation, Critical Thinking, Types of Action and Influencing Factors in Online Forum Environment

Authors: N. I. Bazid, I. N. Umar

Abstract:

Due to the advancement of Internet technology, online learning is widely used in higher education institutions. Online learning offers several means of communication, including online forum. Through online forum, students and instructors are able to discuss and share their knowledge and expertise without having a need to attend the face-to-face, ordinary classroom session. The purposes of this study are to analyze the students’ levels of participation and critical thinking, types of action and factors influencing their participation in online forum. A total of 41 postgraduate students undertaking a course in educational technology from a public university in Malaysia were involved in this study. In this course, the students participated in a weekly online forum as part of the course requirement. Based on the log data file extracted from the online forum, the students’ type of actions (view, add, update, delete posts) and their levels of participation (passive, moderate or active) were identified. In addition, the messages posted in the forum were analyzed to gauge their level of critical thinking. Meanwhile, the factors that might influence their online forum participation were measured using a 24-items questionnaire. Based on the log data, a total of 105 posts were sent by the participants. In addition, the findings show that (i) majority of the students are moderate participants, with an average of two to three posts per person, (ii) viewing posts are the most frequent type of action (85.1%), and followed by adding post (9.7%). Furthermore, based on the posts they made, the most frequent type of critical thinking observed was justification (50 input or 19.0%), followed by linking ideas and interpretation (47 input or 18%), and novelty (38 input or 14.4%). The findings indicate that online forum allows for social interaction and can be used to measure the students’ critical thinking skills. In order to achieve this, monitoring students’ activities in the online forum is recommended.

Keywords: Critical thinking, learning management system, level of online participation, online forum.

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1251 The Optimization of an Intelligent Traffic Congestion Level Classification from Motorists- Judgments on Vehicle's Moving Patterns

Authors: Thammasak Thianniwet, Satidchoke Phosaard, Wasan Pattara-Atikom

Abstract:

We proposed a technique to identify road traffic congestion levels from velocity of mobile sensors with high accuracy and consistent with motorists- judgments. The data collection utilized a GPS device, a webcam, and an opinion survey. Human perceptions were used to rate the traffic congestion levels into three levels: light, heavy, and jam. Then the ratings and velocity were fed into a decision tree learning model (J48). We successfully extracted vehicle movement patterns to feed into the learning model using a sliding windows technique. The parameters capturing the vehicle moving patterns and the windows size were heuristically optimized. The model achieved accuracy as high as 99.68%. By implementing the model on the existing traffic report systems, the reports will cover comprehensive areas. The proposed method can be applied to any parts of the world.

Keywords: intelligent transportation system (ITS), traffic congestion level, human judgment, decision tree (J48), geographic positioning system (GPS).

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1250 Effects of Computer–Based Instructional Designs among Pupils of Different Music Intelligence Levels

Authors: Aldalalah, M. Osamah, Soon Fook Fong

Abstract:

The purpose of this study was to investigate the effects of computer–based instructional designs, namely modality and redundancy principles on the attitude and learning of music theory among primary pupils of different Music Intelligence levels. The lesson of music theory was developed in three different modes, audio and image (AI), text with image (TI) and audio with image and text (AIT). The independent variables were the three modes of courseware. The moderator variable was music intelligence. The dependent variables were the post test score. ANOVA was used to determine the significant differences of the pretest scores among the three groups. Analyses of covariance (ANCOVA) and Post hoc were carried out to examine the main effects as well as the interaction effects of the independent variables on the dependent variables. High music intelligence pupils performed significantly better than low music intelligence pupils in all the three treatment modes. The AI mode was found to help pupils with low music intelligence significantly more than the TI and AIT modes.

Keywords: Modality, Redundancy, Music theory, Cognitivetheory of multimedia learning, Cognitive load theory, Musicintelligence.

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1249 The influence of Local Export Externalities and Firm International Experience on Export Performance

Authors: Isabel Díez Vial, Marta Fernández Olmoss

Abstract:

This research tries to analyze the role that knowledge about foreign markets has in increasing firms- exports in clustered spaces. We consider two interrelated sources of knowledge: firms- direct experience and indirect experience from other clustered firms – export externalities. In particular, it is proposed that firms would improve their export performance by accessing to export externalities if they have some previous direct experience that allows them to identify, understand and exploit them. Also, we propose that this positive influence of previous direct experience on export externalities keeps only up to a point, where it becomes negative, creating an inverted “U" shape. Empirical evidence gathered among wine producers located in La Rioja tends to confirm that firms enjoy of export externalities if they have export experience along several years and countries increase their export performance. While this relationship becomes less relevant as they develop a higher experience, we could not confirm the existence of a curvilinear relationship in their influence on export externalities and export performance.

Keywords: Clusters, curvilinear relationship, absorptive capacity

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1248 Customer Segmentation in Foreign Trade based on Clustering Algorithms Case Study: Trade Promotion Organization of Iran

Authors: Samira Malekmohammadi Golsefid, Mehdi Ghazanfari, Somayeh Alizadeh

Abstract:

The goal of this paper is to segment the countries based on the value of export from Iran during 14 years ending at 2005. To measure the dissimilarity among export baskets of different countries, we define Dissimilarity Export Basket (DEB) function and use this distance function in K-means algorithm. The DEB function is defined based on the concepts of the association rules and the value of export group-commodities. In this paper, clustering quality function and clusters intraclass inertia are defined to, respectively, calculate the optimum number of clusters and to compare the functionality of DEB versus Euclidean distance. We have also study the effects of importance weight in DEB function to improve clustering quality. Lastly when segmentation is completed, a designated RFM model is used to analyze the relative profitability of each cluster.

Keywords: Customers segmentation, Customer relationship management, Clustering, Data Mining

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1247 Creativity in Development of Multimedia Presentation

Authors: Mahathir Sarjan, Ramos Radzly, Noor Baiti Jamaluddin, Mohd Hafiz Zakaria, Hisham Suhadi

Abstract:

Creativity is marked by the ability or power, to produce through imaginative skill and create something anew. The University is one of the great places to improve the talent in imaginative skill. The purpose of this study was to identify a creativity of the student in presentation product development. Two hundred seventeen Technical and Vocational Education (TVE) students in Universiti Tun Hussein Onn had chosen as a respondent. This study is to survey the level of creativity which is focused on knowledge, skills, presentation style, and character of creative personnel. The level of creativity was measured based on the scale at low, medium and high followed by mean score level. The data collected by questionnaire, then analyzed using SPSS version 20.0.The result of the study indicated that the students showed a higher of creativity (mean score in Knowledge = 4.12 and Skills= 4.02). In conjunction with the findings, implications and recommendations were suggested forward like to ensconce the research and improve with a more creativity concept in presentation product of development for learning and teaching process.

Keywords: Creativity, technical, vocational education, presentation products and development for learning and teaching process.

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1246 Solvent Extraction and Spectrophotometric Determination of Palladium(II) Using P-Methylphenyl Thiourea as a Complexing Agent

Authors: Shashikant R. Kuchekar, Somnath D. Bhumkar, Haribhau R. Aher, Bhaskar H. Zaware, Ponnadurai Ramasami

Abstract:

A precise, sensitive, rapid and selective method for the solvent extraction, spectrophotometric determination of palladium(II) using para-methylphenyl thiourea (PMPT) as an extractant is developed. Palladium(II) forms yellow colored complex with PMPT which shows an absorption maximum at 300 nm. The colored complex obeys Beer’s law up to 7.0 µg ml-1 of palladium. The molar absorptivity and Sandell’s sensitivity were found to be 8.486 x 103 l mol-1cm-1 and 0.0125 μg cm-2 respectively. The optimum conditions for the extraction and determination of palladium have been established by monitoring the various experimental parameters. The precision of the method has been evaluated and the relative standard deviation has been found to be less than 0.53%. The proposed method is free from interference from large number of foreign ions. The method has been successfully applied for the determination of palladium from alloy, synthetic mixtures corresponding to alloy samples.

Keywords: Para-methylphenyl thiourea, palladium, spectrophotometry.

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1245 On the Efficient Implementation of a Serial and Parallel Decomposition Algorithm for Fast Support Vector Machine Training Including a Multi-Parameter Kernel

Authors: Tatjana Eitrich, Bruno Lang

Abstract:

This work deals with aspects of support vector machine learning for large-scale data mining tasks. Based on a decomposition algorithm for support vector machine training that can be run in serial as well as shared memory parallel mode we introduce a transformation of the training data that allows for the usage of an expensive generalized kernel without additional costs. We present experiments for the Gaussian kernel, but usage of other kernel functions is possible, too. In order to further speed up the decomposition algorithm we analyze the critical problem of working set selection for large training data sets. In addition, we analyze the influence of the working set sizes onto the scalability of the parallel decomposition scheme. Our tests and conclusions led to several modifications of the algorithm and the improvement of overall support vector machine learning performance. Our method allows for using extensive parameter search methods to optimize classification accuracy.

Keywords: Support Vector Machine Training, Multi-ParameterKernels, Shared Memory Parallel Computing, Large Data

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1244 Anomaly Detection using Neuro Fuzzy system

Authors: Fatemeh Amiri, Caro Lucas, Nasser Yazdani

Abstract:

As the network based technologies become omnipresent, demands to secure networks/systems against threat increase. One of the effective ways to achieve higher security is through the use of intrusion detection systems (IDS), which are a software tool to detect anomalous in the computer or network. In this paper, an IDS has been developed using an improved machine learning based algorithm, Locally Linear Neuro Fuzzy Model (LLNF) for classification whereas this model is originally used for system identification. A key technical challenge in IDS and LLNF learning is the curse of high dimensionality. Therefore a feature selection phase is proposed which is applicable to any IDS. While investigating the use of three feature selection algorithms, in this model, it is shown that adding feature selection phase reduces computational complexity of our model. Feature selection algorithms require the use of a feature goodness measure. The use of both a linear and a non-linear measure - linear correlation coefficient and mutual information- is investigated respectively

Keywords: anomaly Detection, feature selection, Locally Linear Neuro Fuzzy (LLNF), Mutual Information (MI), liner correlation coefficient.

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1243 Cross Project Software Fault Prediction at Design Phase

Authors: Pradeep Singh, Shrish Verma

Abstract:

Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. Earlier we predicted the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven datasets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.

Keywords: Software Metrics, Fault prediction, Cross project, Within project.

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1242 Identifying the Traditional Color Scheme in Decorative Patterns Used by the Bahnar Ethnic Group in the Central Highlands of Vietnam

Authors: Nguyen Viet Tan

Abstract:

The Bahnar is one of 11 indigenous groups living in the Central Highlands of Vietnam. It is one among the four most popular groups in this area, including the Mnong who speak the same language of Mon Khmer family, while both groups of the Jrai and the Rhade belong to the Malayo-Polynesian language family. These groups once captured fertile plateaus, left their cultural and artistic heritage which affected the remaining small groups. Despite the difference in ethnic origins, these groups seem to share similar beliefs, customs and related folk arts after a very long time living beside each other. However, through an in-depth study, this paper points out the fact that the decorative patterns used by the Bahnar are different from the other ethnic groups, especially in color. Based on historical materials from the local museums and some studies in 1980s when all of the ethnic groups in this area had still lived in self-sufficient condition, this paper characterizes the traditional color scheme used by the Bahnar and identifies the difference in decorative motifs of this group compared to the others by pointing out they do not use green in their usual decorative patterns. Moreover, combined with some field surveys recently, through comparative analysis, it also discovers stylistic variations of these patterns in the process of cultural exchange with the other ethnic groups, both in and out of the region, in modern living conditions. This study helps to preserve and promote the traditional values and cultural identity of the Bahnar people in the Central Highlands of Vietnam, avoiding the fusion of styles among groups during the cultural exchange.

Keywords: Bahnar ethic group, decorative patterns, the central highland of Vietnam, traditional color scheme.

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1241 Energy Strategy and Economic Growth of Russia

Authors: Young Sik Kim, Tae Kwon Ha

Abstract:

This article considers the problems of economic growth and Russian energy strategy. Also in this paper, the issues related to the economic growth prospects of Russian were discussed. Russian energy strategy without standing Russia`s stature in global energy markets, at the current production and extraction rates, will not be able to sustain its own production as well as fulfil its energy strategy. Indeed, Russia’s energy sector suffers from a chronic lack of investments which are necessary to modernize its energy supply system. In recent years, especially since the international financial crisis, Russia-EU energy cooperation has made substantive progress. Recently the break-through progress has been made, resulting mainly from long-term contributing factors between the countries and recent international economic and political situation changes. Analytical material presented in the article is intended for a more detailed or substantive analysis related to foreign economic relations of the countries and Russia as well.

Keywords: Russia, Energy strategy, Economic growth, Cooperation.

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1240 PRO-Teaching – Sharing Ideas to Develop Capabilities

Authors: Steve J. Drew, Christopher J. Klopper

Abstract:

In this paper, the action research driven design of a context relevant, developmental peer review of teaching model, its implementation strategy and its impact at an Australian university is presented. PRO-Teaching realizes an innovative process that triangulates contemporaneous teaching quality data from a range of stakeholders including students, discipline academics, learning and teaching expert academics, and teacher reflection to create reliable evidence of teaching quality. Data collected over multiple classroom observations allows objective reporting on development differentials in constructive alignment, peer, and student evaluations. Further innovation is realized in the application of this highly structured developmental process to provide summative evidence of sufficient validity to support claims for professional advancement and learning and teaching awards. Design decision points and contextual triggers are described within the operating domain. Academics and developers seeking to introduce structured peer review of teaching into their organization will find this paper a useful reference.

Keywords: Development loop, Multiple data sources, Objective reporting, Peer review of teaching.

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