Search results for: machine learning algorithms
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4007

Search results for: machine learning algorithms

377 Incremental Learning of Independent Topic Analysis

Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

Abstract:

In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: Text mining, topic extraction, independent, incremental, independent component analysis.

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376 An Empirical Investigation of Big Data Analytics: The Financial Performance of Users versus Vendors

Authors: Evisa Mitrou, Nicholas Tsitsianis, Supriya Shinde

Abstract:

In the age of digitisation and globalisation, businesses have shifted online and are investing in big data analytics (BDA) to respond to changing market conditions and sustain their performance. Our study shifts the focus from the adoption of BDA to the impact of BDA on financial performance. We explore the financial performance of both BDA-vendors (business-to-business) and BDA-clients (business-to-customer). We distinguish between the five BDA-technologies (big-data-as-a-service (BDaaS), descriptive, diagnostic, predictive, and prescriptive analytics) and discuss them individually. Further, we use four perspectives (internal business process, learning and growth, customer, and finance) and discuss the significance of how each of the five BDA-technologies affect the performance measures of these four perspectives. We also present the analysis of employee engagement, average turnover, average net income, and average net assets for BDA-clients and BDA-vendors. Our study also explores the effect of the COVID-19 pandemic on business continuity for both BDA-vendors and BDA-clients.

Keywords: BDA-clients, BDA-vendors, big data analytics, financial performance.

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375 Classifier Combination Approach in Motion Imagery Signals Processing for Brain Computer Interface

Authors: Homayoon Zarshenas, Mahdi Bamdad, Hadi Grailu, Akbar A. Shakoori

Abstract:

In this study we focus on improvement performance of a cue based Motor Imagery Brain Computer Interface (BCI). For this purpose, data fusion approach is used on results of different classifiers to make the best decision. At first step Distinction Sensitive Learning Vector Quantization method is used as a feature selection method to determine most informative frequencies in recorded signals and its performance is evaluated by frequency search method. Then informative features are extracted by packet wavelet transform. In next step 5 different types of classification methods are applied. The methodologies are tested on BCI Competition II dataset III, the best obtained accuracy is 85% and the best kappa value is 0.8. At final step ordered weighted averaging (OWA) method is used to provide a proper aggregation classifiers outputs. Using OWA enhanced system accuracy to 95% and kappa value to 0.9. Applying OWA just uses 50 milliseconds for performing calculation.

Keywords: BCI, EEG, Classifier, Fuzzy operator, OWA.

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374 Towards a Model of Support in the Areas of Services of Educational Assistance and Tutoring in Middle Education in Mexico

Authors: Margarita Zavala, Julio Rolón, Gabriel Chavira, José González, Jorge Orozco, Roberto Pichardo

Abstract:

Adolescence is a neuralgic stage in the formation of every human being, generally at this stage is when the middle school level is studied. In 2006 in Mexico incorporated “mentoring" space to assist students in their integration and participation in life. In public middle schools, is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. Whit this they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: Adolescence, mentoring, middle school students, mentoring system support.

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373 Multitasking Trends and Impact on Education: A Literature Review

Authors: Mohammed Alkahtani, Ali Ahmad, Saber Darmoul, Shatha Samman, Ayoub Al-zabidi, Khaled Ba Matraf

Abstract:

Education systems are complex and involve interactions between humans (teachers and students); media based technologies, lectures, classrooms, etc. to provide educational services. The education system performance is characterized by how well students learn, which is measured using student grades on exams and quizzes, achievements on standardized tests, among others. Advances in portable communications technologies, such as mobile phones, tablets, and laptops, created a different type of classroom, where students seem to engage in more than just the intended learning activities. The performance of more than one task in parallel or in rapid transition is commonly known as multitasking. Several operations in educational systems are performed simultaneously, resulting in a multitasking education environment. This paper surveys existing research on multitasking in educational settings, summarizes literature findings, provides a synthesis of the impact of multitasking on performance, and identifies directions of future research.

Keywords: Education systems, GPA, multitasking, performance.

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372 Communicative Competence: Novice versus Professional Engineers' Perceptions

Authors: Ena Bhattacharyya

Abstract:

The notion of communicative competence has been deemed fuzzy in communication studies. This fuzziness has led to tensions among engineers across tenures in interpreting what constitutes communicative competence. The study seeks to investigate novice and professional engineers- understanding of the said notion in terms of two main elements of communicative competence: linguistic and rhetorical competence. Novice engineers are final year engineering students, whilst professional engineers represent engineers who have at least 5 years working experience. Novice and professional engineers were interviewed to gauge their perceptions on linguistic and rhetorical features deemed necessary to enhance communicative competence for the profession. Both groups indicated awareness and differences on the importance of the sub-sets of communicative competence, namely, rhetorical explanatory competence, linguistic oral immediacy competence, technical competence and meta-cognitive competence. Such differences, a possible attribute of the learning theory, inadvertently indicate sublime differences in the way novice and professional engineers perceive communicative competence.

Keywords: Communicative competence, technical oral presentation, linguistic competence, rhetorical competence.

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371 Semi-Supervised Outlier Detection Using a Generative and Adversary Framework

Authors: Jindong Gu, Matthias Schubert, Volker Tresp

Abstract:

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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370 The Framework for Adaptive Games for Mobile Application Using Neural Networks

Authors: Widodo Budiharto, Michael Yoseph Ricky, Ro'fah Nur Rachmawati

Abstract:

The rapid development of the BlackBerry games industry and its development goals were not just for entertainment, but also used for educational of students interactively. Unfortunately the development of adaptive educational games on BlackBerry in Indonesian language that interesting and entertaining for learning process is very limited. This paper shows the research of development of novel adaptive educational games for students who can adjust the difficulty level of games based on the ability of the user, so that it can motivate students to continue to play these games. We propose a method where these games can adjust the level of difficulty, based on the assessment of the results of previous problems using neural networks with three inputs in the form of percentage correct, the speed of answer and interest mode of games (animation / lessons) and 1 output. The experimental results are presented and show the adaptive games are running well on mobile devices based on BlackBerry platform

Keywords: Adaptive games, neural networks, mobile games, BlackBerry

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369 Dynamic Visualization on Student's Performance, Retention and Transfer of Procedural Learning

Authors: Fauzy M. Wan, Reem S.A. Baragash

Abstract:

This study examined the effects of two dynamic visualizations on 60 Malaysian primary school student-s performance (time on task), retention and transference. The independent variables in this study were the two dynamic visualizations, the video and the animated instructions. The dependent variables were the gain score of performance, retention and transference. The results showed that the students in the animation group significantly outperformed the students in the video group in retention. There were no significant differences in terms of gain scores in the performance and transference among the animation and the video groups, although the scores were slightly higher in the animation group compared to the video group. The conclusion of this study is that the animation visualization is superior compared to the video in the retention for a procedural task.

Keywords: Dynamic visualization, Procedural Task, Retention, Transference

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368 Web-Based Instructional Program to Improve Professional Development: Recommendations and Standards for Radioactive Facilities in Brazil

Authors: Denise Levy, Gian M. A. A. Sordi

Abstract:

This web based project focuses on continuing corporate education and improving workers' skills in Brazilian radioactive facilities throughout the country. The potential of Information and Communication Technologies (ICTs) shall contribute to improve the global communication in this very large country, where it is a strong challenge to ensure high quality professional information to as many people as possible. The main objective of this system is to provide Brazilian radioactive facilities a complete web-based repository - in Portuguese - for research, consultation and information, offering conditions for learning and improving professional and personal skills. UNIPRORAD is a web based system to offer unified programs and inter-related information about radiological protection programs. The content includes the best practices for radioactive facilities in order to meet both national standards and international recommendations published by different organizations over the past decades: International Commission on Radiological Protection (ICRP), International Atomic Energy Agency (IAEA) and National Nuclear Energy Commission (CNEN). The website counts on concepts, definitions and theory about optimization and ionizing radiation monitoring procedures. Moreover, the content presents further discussions related to some national and international recommendations, such as potential exposure, which is currently one of the most important research fields in radiological protection. Only two publications of ICRP develop expressively the issue and there is still a lack of knowledge of fail probabilities, for there are still uncertainties to find effective paths to quantify probabilistically the occurrence of potential exposures and the probabilities to reach a certain level of dose. To respond to this challenge, this project discusses and introduces potential exposures in a more quantitative way than national and international recommendations. Articulating ICRP and AIEA valid recommendations and official reports, in addition to scientific papers published in major international congresses, the website discusses and suggests a number of effective actions towards safety which can be incorporated into labor practice. The WEB platform was created according to corporate public needs, taking into account the development of a robust but flexible system, which can be easily adapted to future demands. ICTs provide a vast array of new communication capabilities and allow to spread information to as many people as possible at low costs and high quality communication. This initiative shall provide opportunities for employees to increase professional skills, stimulating development in this large country where it is an enormous challenge to ensure effective and updated information to geographically distant facilities, minimizing costs and optimizing results.

Keywords: Distance learning, information and communication technology, nuclear science, radioactive facilities.

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367 Information Technology Application for Knowledge Management in Medium-Size Businesses

Authors: S. Thongchai

Abstract:

Result of the study on knowledge management systems in businesses was shown that the most of these businesses provide internet accessibility for their employees in order to study new knowledge via internet, corporate website, electronic mail, and electronic learning system. These business organizations use information technology application for knowledge management because of convenience, time saving, ease of use, accuracy of information and knowledge usefulness. The result indicated prominent improvements for corporate knowledge management systems as the following; 1) administrations must support corporate knowledge management system 2) the goal of corporate knowledge management must be clear 3) corporate culture should facilitate the exchange and sharing of knowledge within the organization 4) cooperation of personnel of all levels must be obtained 5) information technology infrastructure must be provided 6) they must develop the system regularly and constantly. 

Keywords: Business organizations, information technology application, knowledge management systems, and prominent improvements.

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366 Impact of Behavioral Aspects of Autism on Cognitive Abilities in Children with Autism Spectrum Disorder

Authors: Rana M. Zeina, Laila AL-Ayadhi, Shahid Bashir

Abstract:

Cognitive symptoms and behavioral symptoms may, in fact, overlap and be related to the level of the general cognitive function. We have measured the behavioral aspects of autism and its correlation to the cognitive ability in 30 children with ASD. We used a neuropsychological Battery CANTAB eclipse to evaluate the ASD children's cognitive ability. Individuals with ASD and challenging behaviors showed significant correlation between some cognitive abilities and Motor aspects. Based on these findings, we can conclude that the motor behavioral problems in autism affect specific cognitive abilities in ASDs such as comprehension, learning, reversal, acquisition, attention set shifting, and speed of reaction to one stimulus. Future researches should also focus on the relationship between motor stereotypes and other subtypes of repetitive behaviors, such as verbal stereotypes, ritual routine adherence, and the use of different types of CANTAB tests.

Keywords: Autism, Cognitive ability, Motor Behavior, and Neuropsychological battery.

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365 Students´ Knowledge, or Random Choice in ESP?

Authors: Ivana Šimonová

Abstract:

As widely accepted, didactic multiple-choice tests are referred as a tool providing feedback easily and quickly. Despite the final test scores are corrected by a special formula and number of high plausibility distractors is taken into consideration, the results may be influenced by the random choice. The survey was held in three academic years at the Faculty of Informatics and Management, University of Hradec Kralove, Czech Republic, where the multiple-choice test scores were compared to the open-answer ones. The research sample included 567 respondents. The collected data were processed by the NCSS2007 statistic software by the method of frequency and multiple regression analysis and presented in the form of figures and tables. The results proved statistically significant differences in test scores in academic years 2 and 3, and were discussed from the point of the credit system and conditions for teaching/learning English in the Czech education system.

Keywords: ESP, higher education, multiple-choice test, open-answer test.

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364 The Impact of Web Based Education on Cancer Patients’ Clinical Outcomes

Authors: F. Arıkan, Z. Karakus

Abstract:

Cancer is a widespread disease in the world and is the third reason of deaths among the chronic diseases. Educating patients and caregivers has a vital role for empowering them in managing disease and treatment's symptoms. Informing of the patients about their disease and treatment process decreases patient's distress and decisional conflicts, improves wellbeing of them, increase success of the treatment and survival. In this era, technological education methods are used for patients that have different chronic disease. Many studies indicated that especially web based patient education such as chronic obstructive lung disease; heart failure is more effective than printed materials. Web based education provide easiness to patients while they are reaching health services. It also has more advantages because of it decreases health cost and requirement of staff. It is thought that web based education may be beneficial method for cancer patient's empowerment in coping with the disease's symptoms. The aim of the study is evaluate the effectiveness of web based education for cancer patients' clinical outcomes.

Keywords: Cancer Patients, E-Learning, Nursing, Web Based Education.

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363 Power and Wear Reduction Using Composite Links of Crank-Rocker Mechanism with Optimum Transmission Angle

Authors: Khaled M. Khader, Mamdouh I. Elimy

Abstract:

Reducing energy consumption became the major concern for all countries of the world during the recent decades. In general, power saving is currently the nominal goal of most industrial countries. It is well known that fossil fuels are the main pillar of development of world countries. Unfortunately, the increased rate of fossil fuel consumption will lead to serious problems caused by an expected depletion of fuels. Moreover, dangerous gases and vapors emission lead to severe environmental problems during fuel burning. Consequently, most engineering sectors especially the mechanical sectors are looking for improving any machine accompanied by reducing its energy consumption. Crank-Rocker planar mechanism is the most applied in mechanical systems. Besides, it is one of the most significant parts of the machines for obtaining the oscillatory motion. The transmission angle of this mechanism can be considered as an optimum value when its extreme values are equally varied around 90°. In addition, the transmission angle plays an important role in decreasing the required driving power and improving the dynamic properties of the mechanism. Hence, appropriate selection of mechanism links lengthens, which assures optimum transmission angle leads to decreasing the driving power. Moreover, mechanism's links manufactured from composite materials afford link's lightweight, which decreases the required driving torque. Furthermore, wear and corrosion problems can be treated through using composite links instead of using metal ones. This paper is dealing with improving the performance of crank-rocker mechanism using composite links due to their flexural elastic modulus values and stiffness in addition to high damping of composite materials.

Keywords: Composite material, crank-rocker mechanism, transmission angle, design techniques, power saving.

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362 The Relation between Proactive Coping and Well-Being: An Example of Middle-Aged and Older Learners from Taiwan

Authors: Ya-Hui Lee, Ching-Yi Lu, Hui-Chuan Wei

Abstract:

The purpose of this research was to explore the relation between proactive coping and well-being of middle-aged adults. We conducted survey research that with t-test, one way ANOVA, Pearson correlation and stepwise multiple regression to analyze. This research drew on a sample of 395 participants from the senior learning centers of Taiwan. The results provided the following findings: 1.The participants from different residence areas associated significant difference with proactive coping, but not with well-being. 2. The participants’ perceived of financial level associated significant difference with both proactive coping and well-being. 3. There was significant difference between participants’ income and well-being. 4. The proactive coping was positively correlated with well-being. 5. From stepwise multiple regression analysis showed that two dimensions of proactive coping had positive predictability. Finally, these results of this study can be provided as references for designing older adult educational programs in Taiwan.

Keywords: Middle-age adults, learners, proactive coping, well-being.

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361 Struggles for Integration of the Technologies into Learning Environment in Turkey

Authors: Hasan Karal, Yasemin Aydin, Ömer Faruk Ursavas

Abstract:

Primary studies are being carried out in Turkey for expanding information and communication technologies (ICT) aided instruction activities. Subject of the present study is to identify whether those studies achieved their goals in the application. Information technologies (IT) formative teachers in the primary schools, and academicians in the faculties of education were interviewed to investigate the process and results of implementing computer-aided instruction methods whose basis is strengthened in theory. Analysis of the results gained from two separate surveys demonstrated that capability of the teachers in elementary education institutions for carrying into effect computer-aided instruction and technical infrastructure has not been established for computer-aided instruction practices yet. Prospective teachers must be well-equipped in ICT to duly fulfill requirements of modern education and also must be self-confident. Finally, scope and intensity of the courses given in connection with teaching of the ICT in faculties of education needs to be revised.

Keywords: Information and Communication Technologies, Teacher, Education

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360 Development of Cross Curricular Competences in University Classrooms - Public Speaking

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

Abstract:

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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359 A New Technique for Solar Activity Forecasting Using Recurrent Elman Networks

Authors: Salvatore Marra, Francesco C. Morabito

Abstract:

In this paper we present an efficient approach for the prediction of two sunspot-related time series, namely the Yearly Sunspot Number and the IR5 Index, that are commonly used for monitoring solar activity. The method is based on exploiting partially recurrent Elman networks and it can be divided into three main steps: the first one consists in a “de-rectification" of the time series under study in order to obtain a new time series whose appearance, similar to a sum of sinusoids, can be modelled by our neural networks much better than the original dataset. After that, we normalize the derectified data so that they have zero mean and unity standard deviation and, finally, train an Elman network with only one input, a recurrent hidden layer and one output using a back-propagation algorithm with variable learning rate and momentum. The achieved results have shown the efficiency of this approach that, although very simple, can perform better than most of the existing solar activity forecasting methods.

Keywords: Elman neural networks, sunspot, solar activity, time series prediction.

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358 Portfolio Management: A Fuzzy Set Based Approach to Monitoring Size to Maximize Return and Minimize Risk

Authors: Margaret F. Shipley

Abstract:

Fuzzy logic can be used when knowledge is incomplete or when ambiguity of data exists. The purpose of this paper is to propose a proactive fuzzy set- based model for reacting to the risk inherent in investment activities relative to a complete view of portfolio management. Fuzzy rules are given where, depending on the antecedents, the portfolio size may be slightly or significantly decreased or increased. The decision maker considers acceptable bounds on the proportion of acceptable risk and return. The Fuzzy Controller model allows learning to be achieved as 1) the firing strength of each rule is measured, 2) fuzzy output allows rules to be updated, and 3) new actions are recommended as the system continues to loop. An extension is given to the fuzzy controller that evaluates potential financial loss before adjusting the portfolio. An application is presented that illustrates the algorithm and extension developed in the paper.

Keywords: Portfolio Management, Financial Market Monitoring, Fuzzy Controller, Fuzzy Logic,

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357 Real-Time Data Stream Partitioning over a Sliding Window in Real-Time Spatial Big Data

Authors: Sana Hamdi, Emna Bouazizi, Sami Faiz

Abstract:

In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: Real-Time Spatial Big Data, Quality Of Service, Vertical partitioning, Horizontal partitioning, Matching algorithm, Hamming distance, Stream query.

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356 Influence of Noise on the Inference of Dynamic Bayesian Networks from Short Time Series

Authors: Frank Emmert Streib, Matthias Dehmer, Gökhan H. Bakır, Max Mühlhauser

Abstract:

In this paper we investigate the influence of external noise on the inference of network structures. The purpose of our simulations is to gain insights in the experimental design of microarray experiments to infer, e.g., transcription regulatory networks from microarray experiments. Here external noise means, that the dynamics of the system under investigation, e.g., temporal changes of mRNA concentration, is affected by measurement errors. Additionally to external noise another problem occurs in the context of microarray experiments. Practically, it is not possible to monitor the mRNA concentration over an arbitrary long time period as demanded by the statistical methods used to learn the underlying network structure. For this reason, we use only short time series to make our simulations more biologically plausible.

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

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355 EFL Learners- Perceptions of Computer-Mediated Communication (CMC) to Facilitate Communication in a Foreign Language

Authors: Lin, Huifen, Fang, Yueh-chiu

Abstract:

This study explores perceptions of English as a Foreign Language (EFL) learners on using computer mediated communication technology in their learner of English. The data consists of observations of both synchronous and asynchronous communication participants engaged in for over a period of 4 months, which included online, and offline communication protocols, open-ended interviews and reflection papers composed by participants. Content analysis of interview data and the written documents listed above, as well as, member check and triangulation techniques are the major data analysis strategies. The findings suggest that participants generally do not benefit from computer-mediated communication in terms of its effect in learning a foreign language. Participants regarded the nature of CMC as artificial, or pseudo communication that did not aid their authentic communicational skills in English. The results of this study sheds lights on insufficient and inconclusive findings, which most quantitative CMC studies previously generated.

Keywords: computer-mediated communication, EFL, writing

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354 Analysis of Initial Entry-Level Technology Course Impacts on STEM Major Selection

Authors: Ethan Shafer, Timothy Graziano, Jay Fisher

Abstract:

This research seeks to answer whether first-year courses at institutions of higher learning can impact STEM major selection. Unlike many universities, an entry-level technology course (often referred to as CS0) is required for all United States Military Academy (USMA) students–regardless of major–in their first year of attendance. Students at the Academy choose their major at the end of their first year of studies. Through student responses to a multi-semester survey, this paper identifies a number of factors that potentially influence STEM major selection. Student demographic data, pre-existing exposure and access to technology, perceptions of STEM subjects, and initial desire for a STEM major are captured before and after taking a CS0 course. An analysis of factors that contribute to student perception of STEM and major selection are presented. This work provides recommendations and suggestions for institutions currently providing or looking to provide CS0-like courses to their students.

Keywords: STEM major, STEM, pedagogy, digital literacy.

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353 Face Detection using Variance based Haar-Like feature and SVM

Authors: Cuong Nguyen Khac, Ju H. Park, Ho-Youl Jung

Abstract:

This paper proposes a new approach to perform the problem of real-time face detection. The proposed method combines primitive Haar-Like feature and variance value to construct a new feature, so-called Variance based Haar-Like feature. Face in image can be represented with a small quantity of features using this new feature. We used SVM instead of AdaBoost for training and classification. We made a database containing 5,000 face samples and 10,000 non-face samples extracted from real images for learning purposed. The 5,000 face samples contain many images which have many differences of light conditions. And experiments showed that face detection system using Variance based Haar-Like feature and SVM can be much more efficient than face detection system using primitive Haar-Like feature and AdaBoost. We tested our method on two Face databases and one Non-Face database. We have obtained 96.17% of correct detection rate on YaleB face database, which is higher 4.21% than that of using primitive Haar-Like feature and AdaBoost.

Keywords: AdaBoost, Haar-Like feature, SVM, variance, Variance based Haar-Like feature.

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352 Comparison of the Effectiveness of Communication between the Traditional Lecture and IELS

Authors: A. Althobaiti, M. Munro

Abstract:

Communication and effective information exchange within technology has become a crucial part of delivering knowledge to students during the learning process. It enables better understanding, builds trust and respect, and increases the sharing of knowledge between students. This paper examines the communication between undergraduate students and their lecturers during the traditional lecture and when using the Interactive Electronic Lecture System (IELS). The IELS is an application that offers a set of components which support the effective communication between students and their peers and between students and their lecturers. Moreover, this paper highlights communication skills such as sender, receiver, channel and feedback. It will show how the IELS creates a rich communication environment between its users and how they communicate effectively. To examine and assess the effectiveness of communication, an experiment was conducted on groups of users; students and lecturers. The first group communicated in the traditional lecture while the second group communicated by means of the IELS application. The results show that there was more effective communication between the second group than the first.

Keywords: Communication, effective information exchange.

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351 The Code-Mixing of Japanese, English and Thai in Line Chat

Authors: Premvadee Na Nakornpanom

Abstract:

Code- mixing in spontaneous speech has been widely discussed, but not in virtual situations; especially in context of the third language learning students. Thus, this study is an attempt to explore the linguistic characteristics of the mixing of Japanese, English and Thai in a mobile Line chat room by students with their background of English as L2, Japanese as L3 and Thai as mother tongue. The result found that insertion of Thai content words is a very common linguistic phenomenon embedded with the other two languages in the sentences. As chatting is to be ‘relational’ or ‘interactional’, it affected the style of lexical choices to be speech-like, more personal and emotionally-related. A personal pronoun in Japanese is often mixed into the sentences. The Japanese sentence-final question particle か “ka” was added to the end of the sentence based on Thai grammar rules. Some unique characteristics were created while chatting.

Keywords: Code-mixing, Japanese, English, Thai, Line chat.

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350 Neuro-Fuzzy Network Based On Extended Kalman Filtering for Financial Time Series

Authors: Chokri Slim

Abstract:

The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.

Keywords: Neuro-fuzzy, Extended Kalman filter, nonlinear systems, financial time series.

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349 Studies on the Characterization and Machinability of Duplex Stainless Steel 2205 during Dry Turning

Authors: Gaurav D. Sonawane, Vikas G. Sargade

Abstract:

The present investigation is a study of the effect of advanced Physical Vapor Deposition (PVD) coatings on cutting temperature residual stresses and surface roughness during Duplex Stainless Steel (DSS) 2205 turning. Austenite stabilizers like nickel, manganese, and molybdenum reduced the cost of DSS. Surface Integrity (SI) plays an important role in determining corrosion resistance and fatigue life. Resistance to various types of corrosion makes DSS suitable for applications with critical environments like Heat exchangers, Desalination plants, Seawater pipes and Marine components. However, lower thermal conductivity, poor chip control and non-uniform tool wear make DSS very difficult to machine. Cemented carbide tools (M grade) were used to turn DSS in a dry environment. AlTiN and AlTiCrN coatings were deposited using advanced PVD High Pulse Impulse Magnetron Sputtering (HiPIMS) technique. Experiments were conducted with cutting speed of 100 m/min, 140 m/min and 180 m/min. A constant feed and depth of cut of 0.18 mm/rev and 0.8 mm were used, respectively. AlTiCrN coated tools followed by AlTiN coated tools outperformed uncoated tools due to properties like lower thermal conductivity, higher adhesion strength and hardness. Residual stresses were found to be compressive for all the tools used for dry turning, increasing the fatigue life of the machined component. Higher cutting temperatures were observed for coated tools due to its lower thermal conductivity, which results in very less tool wear than uncoated tools. Surface roughness with uncoated tools was found to be three times higher than coated tools due to lower coefficient of friction of coating used.

Keywords: Cutting temperatures, DSS2205, dry turning, HiPIMS, surface integrity.

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348 Probabilistic Bayesian Framework for Infrared Face Recognition

Authors: Moulay A. Akhloufi, Abdelhakim Bendada

Abstract:

Face recognition in the infrared spectrum has attracted a lot of interest in recent years. Many of the techniques used in infrared are based on their visible counterpart, especially linear techniques like PCA and LDA. In this work, we introduce a probabilistic Bayesian framework for face recognition in the infrared spectrum. In the infrared spectrum, variations can occur between face images of the same individual due to pose, metabolic, time changes, etc. Bayesian approaches permit to reduce intrapersonal variation, thus making them very interesting for infrared face recognition. This framework is compared with classical linear techniques. Non linear techniques we developed recently for infrared face recognition are also presented and compared to the Bayesian face recognition framework. A new approach for infrared face extraction based on SVM is introduced. Experimental results show that the Bayesian technique is promising and lead to interesting results in the infrared spectrum when a sufficient number of face images is used in an intrapersonal learning process.

Keywords: Face recognition, biometrics, probabilistic imageprocessing, infrared imaging.

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