Search results for: support vector machine (SVM)

Authors: T. Roussopoulos

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At the end of the 17th Century the Greek orthodox Archbishop in Venice -Meletios Typaldos- decided to turn the doctrine of the orthodox Greeks into Catholicism. More than 5.000 Greeks were living in Venice then. Their leadership -the Greek confraternity- fought against Meletios. Participants in this conflict were the Pope, the ecumenical Patriarch in Constantinople and Peter the Great of Russia. All the play according to my opinion -which is followed by evidence and theoretical support is a strong conflict between the two actors -the Archbishop and the Confraternity- and the object of conflict is the change of the Greek orthodox beliefs to Catholicism. Ethnicity especially for Greeks of the era is identified with orthodoxy. So this was a conflict of identity. The results of that conflict were of tremendous importance to the Greeks in Venice and affected them for long.

Keywords: Greek ethnic identity, Meletios Typaldos, Confraternity, Venice Pope, Patriarch Constantinople Peter the Great Russia.

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Authors: N. H. Othman, N. Udin, M. Ishak, L. H. Shah

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This study focuses on the effect of pin taper tool ratio on friction stir welding of magnesium alloy AZ31. Two pieces of AZ31 alloy with thickness of 6 mm were friction stir welded by using the conventional milling machine. The shoulder diameter used in this experiment is fixed at 18 mm. The taper pin ratio used are varied at 6:6, 6:5, 6:4, 6:3, 6:2 and 6:1. The rotational speeds that were used in this study were 500 rpm, 1000 rpm and 1500 rpm, respectively. The welding speeds used are 150 mm/min, 200 mm/min and 250 mm/min. Microstructure observation of welded area was studied by using optical microscope. Equiaxed grains were observed at the TMAZ and stir zone indicating fully plastic deformation. Tool pin diameter ratio 6/1 causes low heat input to the material because of small contact surface between tool surface and stirred materials compared to other tool pin diameter ratio. The grain size of stir zone increased with increasing of ratio of rotational speed to transverse speed due to higher heat input. It is observed that worm hole is produced when excessive heat input is applied. To evaluate the mechanical properties of this specimen, tensile test was used in this study. Welded specimens using taper pin ratio 6:1 shows higher tensile strength compared to other taper pin ratio up to 204 MPa. Moreover, specimens using taper pin ratio 6:1 showed better tensile strength with 500 rpm of rotational speed and 150mm/min welding speed.

Keywords: Friction stir welding, magnesium AZ31, cylindrical taper tool, taper pin ratio.

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Authors: Cory A. Bennett

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Teaching and learning through the use of discourse support students’ conceptual understanding by attending to key concepts and relationships. One discourse structure used in primary classrooms is number talks wherein students mentally calculate, discuss, and reason about the appropriateness and efficiency of their strategies. In the secondary mathematics classroom, the mathematics understudy does not often lend itself to mental calculations yet learning to reason, and articulate reasoning, is central to learning mathematics. This qualitative case study discusses how one secondary school in the Middle East adapted the number talk protocol for secondary mathematics classrooms. Several challenges in implementing ‘reasoning talks’ became apparent including shifting current discourse protocols and practices to a more student-centric model, accurately recording and probing student thinking, and specifically attending to reasoning rather than computations.

Keywords: Discourse, reasoning, secondary mathematics, teacher development.

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Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: Natural language processing, end user development; natural language interfaces, human computer interaction, data recognition, dialog systems, spreadsheet.

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Authors: Katya Milenova, Penko Nikolov, Irina Stambolova, Plamen Nikolov, Vladimir Blaskov

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In this article a comparison was made between Cu and TiO2 supported catalysts on activated carbon for ozone decomposition reaction. The activated carbon support in the case of TiO2/AC sample was prepared by physicochemical pyrolysis and for Cu/AC samples the supports are chemically modified carbons. The prepared catalysts were synthesized by impregnation method. The samples were annealed in two different regimes- in air and under vacuum. To examine adsorption efficiency of the samples BET method was used. All investigated catalysts supported on chemically modified carbons have higher specific surface area compared to the specific surface area of TiO2 supported catalysts, varying in the range 590÷620 m2/g. The method of synthesis of the precursors had influenced catalytic activity.

Keywords: Activated carbon, adsorption, copper, ozone decomposition, TiO2.

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Authors: Elizabeth Simão Carvalho, Marcirio Silveira Chaves

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The information visualization is still a knowledge field that lacks from a solid theory to support it and there is a myriad of existing methodologies and taxonomies that can be combined and adopted as guidelines. In this context, it is necessary to pre-evaluate as much as possible all the assumptions that are considered for its design and development. We present an exploratory study (n = 123) to detect the graphical preferences of travelers using accommodation portals of Web 2.0 (e.g. tripadvisor.com). We took into account some of the most relevant ground rules applied in the field to map visually data and design end-user interaction. Moreover, the evaluation process was completely data visualization oriented. We found out that people tend to refuse more advanced types of visualization and that a hybrid combination between radial graphs and stacked bars should be explored. In sum, this paper introduces new findings about the visual model and the cognitive response of users of accommodation booking websites.

Keywords: Information visualization, Data visualization, Visualization evaluation, Online reviews, Booking portal, Hotel booking.

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Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

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This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: Visual search, deep learning, convolutional neural network, machine learning.

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Authors: Yingyi Zhou, Tohru Kawabe

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With the spread of EVs (electric Vehicles), the ride comfort has been gaining a lot of attention. The influence of the lateral acceleration is important for the improvement of ride comfort of EVs as well as the longitudinal acceleration, especially upon turning of the vehicle. Therefore, this paper proposes a practical optimal speed control method to greatly improve the ride comfort in the vehicle turning situation. For consturcting this method, effective criteria that can appropriately evaluate deterioration of ride comfort is derived. The method can reduce the influence of both the longitudinal and the lateral speed changes for providing a confortable ride. From several simulation results, we can see the fact that the method can prevent aggravation of the ride comfort by suppressing the influence of longitudinal speed change in the turning situation. Hence, the effectiveness of the method is recognized.

Keywords: Electric vehicle, speed control, ride comfort, optimal control theory, driving support system.

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Authors: Paua Ketan, Bhagate Rajkumar, Adiga Ganesh, M. Kiran

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Low gear noise is an important sound quality feature in modern passenger cars. Annoying gear noise from the gearbox is influenced by the gear design, gearbox shaft layout, manufacturing deviations in the components, assembly errors and the mounting arrangement of the complete gearbox. Geometrical deviations in the form of profile and lead errors are often present on the flanks of the inspected gears. Ghost frequencies of a gear are very challenging to identify in standard gear measurement and analysis process due to small wavelengths involved. In this paper, gear whine noise occurring at non-integral multiples of gear mesh frequency of passenger car gearbox is investigated and the root cause is identified using the displacement deviation analysis (DDA) method. DDA method is applied to identify ghost frequency excitations on the flanks of gears arising out of generation grinding. Frequency identified through DDA correlated with the frequency of vibration and noise on the end-of-line machine as well as vehicle level measurements. With the application of DDA method along with standard lead profile measurement, gears with ghost frequency geometry deviations were identified on the production line to eliminate defective parts and thereby eliminate ghost frequency noise from a vehicle. Further, displacement deviation analysis can be used in conjunction with the manufacturing process simulation to arrive at suitable countermeasures for arresting the ghost frequency.

Keywords: Displacement deviation analysis, gear whine, ghost frequency, sound quality.

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Authors: Thomas Behan, Zaiyi Liao, Lian Zhao, Chunting Yang

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In this paper, low end Digital Signal Processors (DSPs) are applied to accelerate integer neural networks. The use of DSPs to accelerate neural networks has been a topic of study for some time, and has demonstrated significant performance improvements. Recently, work has been done on integer only neural networks, which greatly reduces hardware requirements, and thus allows for cheaper hardware implementation. DSPs with Arithmetic Logic Units (ALUs) that support floating or fixed point arithmetic are generally more expensive than their integer only counterparts due to increased circuit complexity. However if the need for floating or fixed point math operation can be removed, then simpler, lower cost DSPs can be used. To achieve this, an integer only neural network is created in this paper, which is then accelerated by using DSP instructions to improve performance.

Keywords: Digital Signal Processor (DSP), Integer Neural Network(INN), Low Cost Neural Network, Integer Neural Network DSPImplementation.

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Authors: Sarp Erturk, Levent Eyigel, Cihat Celik, Muhammet Sahinoglu, Serdar Ay, Yasin Kaya, Hasan Kaya

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This paper presents a quantitative analysis on the need for automotive calibration methods for digital tachographs. Digital tachographs are mandatory for vehicles used in people and goods transport and they are an important aspect for road safety and inspection. Digital tachographs need to be calibrated for workshops in order for the digital tachograph to display and record speed and odometer values correctly. Calibration of digital tachographs can be performed either manual or automatic. It is shown in this paper that manual calibration of digital tachographs is prone to errors and there can be differences between manual and automatic calibration parameters. Therefore automatic calibration methods are imperative for digital tachograph calibration. The presented experimental results and error analysis clearly support the claims of the paper by evaluating and statistically comparing manual and automatic calibration methods.

Keywords: Digital tachograph, road safety, tachograph calibration, tachograph workshops.

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Authors: S. N. F. Mohd Fauzi, N. Yusof, N. Zainul Abidin

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When the Malaysian government announced the implementation of the Build-Then-Sell (BTS) system in 2007, the proponents of the BTS have argued that the implementation of this new system may provide houses with low defects. However, there has been no empirical data to support their argument. Therefore, this study is conducted to measure the level of housing defects in the BTS housing delivery system. A survey was conducted to the occupiers in six BTS residential areas. The BTS residential areas have been identified through the media and because of the small number of population, all households in the BTS residential areas were required to participate in the study to enable the researcher to collect the data concerning defects. Questionnaire had been employed as the data collection instrument and was distributed to the respondents of this study. The result has shown that the level of defects in the BTS houses is low, as the rate of defects for all elements are slight. Such low level of defects has apparently only affected the aesthetic value of the houses.

Keywords: Build-Then-Sell houses, housing defects, residentialareas, occupiers

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Authors: J. Mansvelt, G. Suddaby, D. O'Hara

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This paper focuses on issues of engagement by staff in professional development related to the delivery of e-learning. The paper reports on findings drawn from a New Zealand research project which is producing a sector-wide framework for professional development in tertiary e-learning. The research findings indicate that staff engaged in e-learning in tertiary institutions is not making the most effective use of the professional development opportunities available to them; rather they seem to gain their knowledge and support from a variety of informal means. This is despite an emphasis on the provision of professional development opportunities by both Government Policies and Institutions themselves. The conclusion drawn from the findings is that institutional approaches to professional development for e-learning do not yet fully reflect the demands and constraints that working in a digital context impose.

Keywords: Academic development, e-learning, engagement, professional development, tertiary education.

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Authors: Jiakai Li, Gursel Serpen, Steven Selman, Matt Franchetti, Mike Riesen, Cynthia Schneider

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This paper presents the development of a Bayesian belief network classifier for prediction of graft status and survival period in renal transplantation using the patient profile information prior to the transplantation. The objective was to explore feasibility of developing a decision making tool for identifying the most suitable recipient among the candidate pool members. The dataset was compiled from the University of Toledo Medical Center Hospital patients as reported to the United Network Organ Sharing, and had 1228 patient records for the period covering 1987 through 2009. The Bayes net classifiers were developed using the Weka machine learning software workbench. Two separate classifiers were induced from the data set, one to predict the status of the graft as either failed or living, and a second classifier to predict the graft survival period. The classifier for graft status prediction performed very well with a prediction accuracy of 97.8% and true positive values of 0.967 and 0.988 for the living and failed classes, respectively. The second classifier to predict the graft survival period yielded a prediction accuracy of 68.2% and a true positive rate of 0.85 for the class representing those instances with kidneys failing during the first year following transplantation. Simulation results indicated that it is feasible to develop a successful Bayesian belief network classifier for prediction of graft status, but not the graft survival period, using the information in UNOS database.

Keywords: Bayesian network classifier, renal transplantation, graft survival period, United Network for Organ Sharing

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Authors: Atiqul Islam, Shamim Akhter, Tumnun E. Mursalin

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Least Development Countries (LDC) like Bangladesh, whose 25% revenue earning is achieved from Textile export, requires producing less defective textile for minimizing production cost and time. Inspection processes done on these industries are mostly manual and time consuming. To reduce error on identifying fabric defects requires more automotive and accurate inspection process. Considering this lacking, this research implements a Textile Defect Recognizer which uses computer vision methodology with the combination of multi-layer neural networks to identify four classifications of textile defects. The recognizer, suitable for LDC countries, identifies the fabric defects within economical cost and produces less error prone inspection system in real time. In order to generate input set for the neural network, primarily the recognizer captures digital fabric images by image acquisition device and converts the RGB images into binary images by restoration process and local threshold techniques. Later, the output of the processed image, the area of the faulty portion, the number of objects of the image and the sharp factor of the image, are feed backed as an input layer to the neural network which uses back propagation algorithm to compute the weighted factors and generates the desired classifications of defects as an output.

Keywords: Computer vision, image acquisition device, machine vision, multi-layer neural networks.

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Authors: Abdelaziz Guerrouat, Harald Richter

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In this paper test generation methods and appropriate fault models for testing and analysis of embedded systems described as (extended) finite state machines ((E)FSMs) are presented. Compared to simple FSMs, EFSMs specify not only the control flow but also the data flow. Thus, we define a two-level fault model to cover both aspects. The goal of this paper is to reuse well-known FSM-based test generation methods for automation of embedded system testing. These methods have been widely used in testing and validation of protocols and communicating systems. In particular, (E)FSMs-based specification and testing is more advantageous because (E)FSMs support the formal semantic of already standardised formal description techniques (FDTs) despite of their popularity in the design of hardware and software systems.

Keywords: Formal methods, testing and validation, finite state machines, formal description techniques.

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Authors: Siavash Asadi Ghajarloo

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Nowadays predicting political risk level of country has become a critical issue for investors who intend to achieve accurate information concerning stability of the business environments. Since, most of the times investors are layman and nonprofessional IT personnel; this paper aims to propose a framework named GECR in order to help nonexpert persons to discover political risk stability across time based on the political news and events. To achieve this goal, the Bayesian Networks approach was utilized for 186 political news of Pakistan as sample dataset. Bayesian Networks as an artificial intelligence approach has been employed in presented framework, since this is a powerful technique that can be applied to model uncertain domains. The results showed that our framework along with Bayesian Networks as decision support tool, predicted the political risk level with a high degree of accuracy.

Keywords: Bayesian Networks, Data mining, GECRframework, Predicting political risk.

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Authors: Zhizhong Jiang, Peter Naudé

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Effective evaluation of software development effort is an important aspect of successful project management. Based on a large database with 4106 projects ever developed, this study statistically examines the factors that influence development effort. The factors found to be significant for effort are project size, average number of developers that worked on the project, type of development, development language, development platform, and the use of rapid application development. Among these factors, project size is the most critical cost driver. Unsurprisingly, this study found that the use of CASE tools does not necessarily reduce development effort, which adds support to the claim that the use of tools is subtle. As many of the current estimation models are rarely or unsuccessfully used, this study proposes a parsimonious parametric model for the prediction of effort which is both simple and more accurate than previous models.

Keywords: Development effort, function points, team size, development language, CASE tool, rapid application development.

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Authors: Shireen Panchoo

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The Internet and the ever growing applications enable communities to share and collaborate through common platforms. However, this growing pattern is not witnessed yet even for elearning. This paper is based on a doctoral research which aimed at researching the ways students interact in an online campus and the supports that they look for and require. Content analysis, based on the Panchoo/Jaillet methodology, was done on four synchronous meetings between a tutor and his ten students. The UNIV-Rct ecampus, analogical to a physical campus, was found to be user friendly and the students enrolled in a master-s course faced no difficulties in using it. In addition to the environmental aspects, the pedagogical implementation of the course has driven the students to interact and collaborate significantly and this has contributed to overcome the problems faced by the distance learners. This completely online model was found to be fruitful in helping distant learners fight their loneliness and brave their difficulties in a socioconstructivism approach.

Keywords: Content analysis, e-campus, interaction, online supports, pedagogy.

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Authors: Amel Grissa-Touzi, Minyar Sassi

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Conception is the primordial part in the realization of a computer system. Several tools have been used to help inventors to describe their software. These tools knew a big success in the relational databases domain since they permit to generate SQL script modeling the database from an Entity/Association model. However, with the evolution of the computer domain, the relational databases proved their limits and object-relational model became used more and more. Tools of present conception don't support all new concepts introduced by this model and the syntax of the SQL3 language. We propose in this paper a tool of help to the conception and implementation of object-relational databases called «NAVIGTOOLS" that allows the user to generate script modeling its database in SQL3 language. This tool bases itself on the Entity/Association and navigational model for modeling the object-relational databases.

Keywords: Abstract Data Table, Navigational model, Objectrelational databases, References.

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Authors: Ji Nyong Jang, Min Woo Lee, Eun Kyung Kim, Ki Keun Kim, Jae Sung Lim

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Since DVB-RCS has been successively implemented, the mobile communication on the multi-beam satellite communication is attractive attention. And the DVB-RCS standard sets up to support mobility of a RCST. In the case of the spot-beam satellite system, the received signal strength does not differ largely between the center and the boundary of the beam. Thus, the RSS based handoff detection algorithm is not benefit to the satellite system as a terrestrial system. Therefore we propose an Adaptive handoff detection algorithm based on RCST mobility information. Our handoff detection algorithm not only can be used as centralized handoff detection algorithm but also removes uncertainties of handoff due to the variation of RSS. Performances were compared with RSS based handoff algorithm. Simulation results show that the proposed handoff detection algorithm not only achieved better handoff and link degradation rate, but also achieved better forward link spectral efficiency.

Keywords: DVB-RCS, satellite multi-beam handoff, mobility information, handover.

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Authors: X. Mamaqi, J.Miguel, P. Olave

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The aim of this paper is to provide an empirical evidence about the effects that the management of continuous training have on employability (or employment stability) in the Spanish labour market. With this purpose a binary logit model with interaction effect is been used. The dependent variable includes two situations of the active workers: continuous and discontinuous employability. To distinguish between them an Employability Index Stability (ESI) was calculated taking into account two factors: time worked and job security. Various aspects of the continuous training and personal workers data are used as independent variables. The data obtained from a survey of a sample of 918 employed have revealed a relationship between the likelihood of continuous employability and continuous training received. The empirical results support the positive and significant relationship between various aspects of the training provided by firms and employability likelihood of the workers, postulate alike from a theoretical point of view.

Keywords: training management, employability/employmentstability, binary logit model, interaction effect, Spanish marketlabour.

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Authors: O. F. Elkommos

Abstract:

Teaching and learning EFL speaking modules is one of the most challenging productive modules for both instructors and learners. In a student-centered interactive communicative language teaching approach, learners and instructors should be aware of the fact that the target language must be taught as/for communication. The student must be empowered by tools that will work on more than one level of their communicative competence. Communicative learning will need a teaching and learning methodology that will address the goal. Teaching turn-taking rules, pragmatic principles and speech acts will enhance students' sociolinguistic competence, strategic competence together with discourse competence. Sociolinguistic competence entails the mastering of speech act conventions and illocutionary acts of refusing, agreeing/disagreeing; emotive acts like, thanking, apologizing, inviting, offering; directives like, ordering, requesting, advising, and hinting, among others. Strategic competence includes enlightening students’ consciousness of the various particular turn-taking systemic rules of organizing techniques of opening and closing conversation, adjacency pairs, interrupting, back-channeling, asking for/giving opinion, agreeing/disagreeing, using natural fillers for pauses, gaps, speaker select, self-select, and silence among others. Students will have the tools to manage a conversation. Students are engaged in opportunities of experiencing the natural language not as a mere extra student talking time but rather an empowerment of knowing and using the strategies. They will have the component items they need to use as well as the opportunity to communicate in the target language using topics of their interest and choice. This enhances students' communicative abilities. Available websites and textbooks now use one or more of these tools of turn-taking or pragmatics. These will be students' support in self-study in their independent learning study hours. This will be their reinforcement practice on e-Learning interactive activities. The students' target is to be able to communicate the intended meaning to an addressee that is in turn able to infer that intended meaning. The combination of these tools will be assertive and encouraging to the student to beat the struggle with what to say, how to say it, and when to say it. Teaching the rules, principles and techniques is an act of awareness raising method engaging students in activities that will lead to their pragmatic discourse competence. The aim of the paper is to show how the suggested pragmatic model will empower students with tools and systems that would support their learning. Supporting students with turn taking rules, speech act theory, applying both to texts and practical analysis and using it in speaking classes empowers students’ pragmatic discourse competence and assists them to understand language and its context. They become more spontaneous and ready to learn the discourse pragmatic dimension of the speaking techniques and suitable content. Students showed a better performance and a good motivation to learn. The model is therefore suggested for speaking modules in EFL classes.

Keywords: Communicative competence, EFL, empowering learners, enhance learning, speech acts, teaching speaking, turn-taking, learner centered, pragmatics.

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: Communication signal, feature extraction, holder coefficient, improved cloud model.

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Authors: Hae-Yeoun Lee

Abstract:

Mosaic refers to a technique that makes image by gathering lots of small materials in various colors. This paper presents an automatic algorithm that makes the photo-mosaic image using photos. The algorithm is composed of 4 steps: partition and feature extraction, block matching, redundancy removal and color adjustment. The input image is partitioned in the small block to extract feature. Each block is matched to find similar photo in database by comparing similarity with Euclidean difference between blocks. The intensity of the block is adjusted to enhance the similarity of image by replacing the value of light and darkness with that of relevant block. Further, the quality of image is improved by minimizing the redundancy of tiles in the adjacent blocks. Experimental results support that the proposed algorithm is excellent in quantitative analysis and qualitative analysis.

Keywords: Photo-mosaic, Euclidean distance, Block matching, Intensity adjustment.

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Authors: S. Thongchai

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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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Authors: Michael Grigutsch, Marco Kennemann, Peter Nyhuis

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Due to the recovering global economy, enterprises are increasingly focusing on logistics. Investing in logistic measures for a production generates a large potential for achieving a good starting point within a competitive field. Unlike during the global economic crisis, enterprises are now challenged with investing available capital to maximize profits. In order to be able to create an informed and quantifiably comprehensible basis for a decision, enterprises need an adequate model for logistically and monetarily evaluating measures in production. The Collaborate Research Centre 489 (SFB 489) at the Institute for Production Systems (IFA) developed a Logistic Information System which provides support in making decisions and is designed specifically for the forging industry. The aim of a project that has been applied for is to now transfer this process in order to develop a universal approach to logistically and monetarily evaluate measures in production.

Keywords: Measures in Production, Logistic Operating Curves, Transfer Functions, Production Logistics

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Authors: Christer Ahlstrom, Katja Höglund, Peter Hult, Jens Häggström, Clarence Kvart, Per Ask

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It is sometimes difficult to differentiate between innocent murmurs and pathological murmurs during auscultation. In these difficult cases, an intelligent stethoscope with decision support abilities would be of great value. In this study, using a dog model, phonocardiographic recordings were obtained from 27 boxer dogs with various degrees of aortic stenosis (AS) severity. As a reference for severity assessment, continuous wave Doppler was used. The data were analyzed with recurrence quantification analysis (RQA) with the aim to find features able to distinguish innocent murmurs from murmurs caused by AS. Four out of eight investigated RQA features showed significant differences between innocent murmurs and pathological murmurs. Using a plain linear discriminant analysis classifier, the best pair of features (recurrence rate and entropy) resulted in a sensitivity of 90% and a specificity of 88%. In conclusion, RQA provide valid features which can be used for differentiation between innocent murmurs and murmurs caused by AS.

Keywords: Bioacoustics, murmur, phonocardiographic signal, recurrence quantification analysis.

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Authors: P. O. Umenne, Odhiambo Marcel O.

Abstract:

A simple network model is developed in OPNET to study the performance of the Wi-Fi protocol. The model is simulated in OPNET and performance factors such as load, throughput and delay are analysed from the model. Four applications such as oracle, http, ftp and voice are applied over the Wireless LAN network to determine the throughput. The voice application utilises a considerable amount of bandwidth of up to 5Mbps, as a result the 802.11g standard of the Wi-Fi protocol was chosen which can support a data rate of up to 54Mbps. Results indicate that when the load in the Wi-Fi network is increased the queuing delay on the point-to-point links in the Wi-Fi network significantly reduces until it is comparable to that of WiMAX. In conclusion, the queuing delay of the Wi-Fi protocol for the network model simulated was about 0.00001secs comparable to WiMAX network values.

Keywords: WLAN-Wireless Local Area Network, MIMO-Multiple Input Multiple Output, Queuing delay, Throughput, AP-Access Point, IP-Internet protocol, TOS-Type of Service.

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Authors: Raquel Ramos López, Anissa El-Khattabi, Ana Lucila Sandoval Orozco, Luis Javier García Villalba

Abstract:

An increasing number of mobile devices with integrated cameras has meant that most digital video comes from these devices. These digital videos can be made anytime, anywhere and for different purposes. They can also be shared on the Internet in a short period of time and may sometimes contain recordings of illegal acts. The need to reliably trace the origin becomes evident when these videos are used for forensic purposes. This work proposes an algorithm to identify the brand and model of mobile device which generated the video. Its procedure is as follows: after obtaining the relevant video information, a classification algorithm based on sensor noise and Wavelet Transform performs the aforementioned identification process. We also present experimental results that support the validity of the techniques used and show promising results.

Keywords: Digital video, forensics analysis, key frame, mobile device, PRNU, sensor noise, source identification.

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