Search results for: Text Assignment.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 664

Search results for: Text Assignment.

454 Evolutionary Search Techniques to Solve Set Covering Problems

Authors: Darwin Gouwanda, S. G. Ponnambalam

Abstract:

Set covering problem is a classical problem in computer science and complexity theory. It has many applications, such as airline crew scheduling problem, facilities location problem, vehicle routing, assignment problem, etc. In this paper, three different techniques are applied to solve set covering problem. Firstly, a mathematical model of set covering problem is introduced and solved by using optimization solver, LINGO. Secondly, the Genetic Algorithm Toolbox available in MATLAB is used to solve set covering problem. And lastly, an ant colony optimization method is programmed in MATLAB programming language. Results obtained from these methods are presented in tables. In order to assess the performance of the techniques used in this project, the benchmark problems available in open literature are used.

Keywords: Set covering problem, genetic algorithm, ant colony optimization, LINGO.

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453 A New Classification of Risk-Reduction Options to Improve the Risk-Reduction Readiness of the Railway Industry

Authors: Eberechi Weli, Michael Todinov

Abstract:

The gap between the selection of risk-reduction options in the railway industry and the task of their effective implementation results in compromised safety and substantial losses. An effective risk management must necessarily integrate the evaluation phases with the implementation phase. This paper proposes an essential categorisation of risk reduction measures that best addresses a standard railway industry portfolio. By categorising the risk reduction options into design, operational, procedural and technical options, it is guaranteed that the efforts of the implementation facilitators (people, processes and supporting systems) are systematically harmonised. The classification is based on an integration of fundamental principles of risk reduction in the railway industry with the systems engineering approach.

This paper argues that the use of a similar classification approach is an attribute of organisations possessing a superior level of risk-reduction readiness. The integration of the proposed rational classification structure provides a solid ground for effective risk reduction.

Keywords: Cost effectiveness, organisational readiness, risk reduction, railway, system engineering.

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452 A Methodology for Investigating Public Opinion Using Multilevel Text Analysis

Authors: William Xiu Shun Wong, Myungsu Lim, Yoonjin Hyun, Chen Liu, Seongi Choi, Dasom Kim, Kee-Young Kwahk, Namgyu Kim

Abstract:

Recently, many users have begun to frequently share their opinions on diverse issues using various social media. Therefore, numerous governments have attempted to establish or improve national policies according to the public opinions captured from various social media. In this paper, we indicate several limitations of the traditional approaches to analyze public opinion on science and technology and provide an alternative methodology to overcome these limitations. First, we distinguish between the science and technology analysis phase and the social issue analysis phase to reflect the fact that public opinion can be formed only when a certain science and technology is applied to a specific social issue. Next, we successively apply a start list and a stop list to acquire clarified and interesting results. Finally, to identify the most appropriate documents that fit with a given subject, we develop a new logical filter concept that consists of not only mere keywords but also a logical relationship among the keywords. This study then analyzes the possibilities for the practical use of the proposed methodology thorough its application to discover core issues and public opinions from 1,700,886 documents comprising SNS, blogs, news, and discussions.

Keywords: Big data, social network analysis, text mining, topic modeling.

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451 A Simple Low-Cost 2-D Optical Measurement System for Linear Guideways

Authors: Wen-Yuh Jywe, Bor-Jeng Lin, Jing-Chung Shen, Jeng-Dao Lee, Hsueh-Liang Huang, Tung-Hsien Hsieh

Abstract:

In this study, a simple 2-D measurement system based on optical design was developed to measure the motion errors of the linear guideway. Compared with the transitional methods about the linear guideway for measuring the motion errors, our proposed 2-D optical measurement system can simultaneously measure horizontal and vertical running straightness errors for the linear guideway.

The performance of the 2-D optical measurement system is verified by experimental results. The standard deviation of the 2-D optical measurement system is about 0.4μm in the measurement range of 100 mm. The maximum measuring speed of the proposed automatic measurement instrument is 1 m/sec.

Keywords: 2-D measurement, linear guideway, motion errors, running straightness.

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450 Image Indexing Using a Color Similarity Metric based on the Human Visual System

Authors: Angelo Nodari, Ignazio Gallo

Abstract:

The novelty proposed in this study is twofold and consists in the developing of a new color similarity metric based on the human visual system and a new color indexing based on a textual approach. The new color similarity metric proposed is based on the color perception of the human visual system. Consequently the results returned by the indexing system can fulfill as much as possibile the user expectations. We developed a web application to collect the users judgments about the similarities between colors, whose results are used to estimate the metric proposed in this study. In order to index the image's colors, we used a text indexing engine to facilitate the integration of visual features in a database of text documents. The textual signature is build by weighting the image's colors in according to their occurrence in the image. The use of a textual indexing engine, provide us a simple, fast and robust solution to index images. A typical usage of the system proposed in this study, is the development of applications whose data type is both visual and textual. In order to evaluate the proposed method we chose a price comparison engine as a case of study, collecting a series of commercial offers containing the textual description and the image representing a specific commercial offer.

Keywords: Color Extraction, Content-Based Image Retrieval, Indexing

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449 Grid Based and Random Based Ant Colony Algorithms for Automatic Hose Routing in 3D Space

Authors: Gishantha Thantulage, Tatiana Kalganova, Manissa Wilson

Abstract:

Ant Colony Algorithms have been applied to difficult combinatorial optimization problems such as the travelling salesman problem and the quadratic assignment problem. In this paper gridbased and random-based ant colony algorithms are proposed for automatic 3D hose routing and their pros and cons are discussed. The algorithm uses the tessellated format for the obstacles and the generated hoses in order to detect collisions. The representation of obstacles and hoses in the tessellated format greatly helps the algorithm towards handling free-form objects and speeds up computation. The performance of algorithm has been tested on a number of 3D models.

Keywords: Ant colony algorithm, Automatic hose routing, tessellated format, RAPID.

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448 Learning to Order Terms: Supervised Interestingness Measures in Terminology Extraction

Authors: Jérôme Azé, Mathieu Roche, Yves Kodratoff, Michèle Sebag

Abstract:

Term Extraction, a key data preparation step in Text Mining, extracts the terms, i.e. relevant collocation of words, attached to specific concepts (e.g. genetic-algorithms and decisiontrees are terms associated to the concept “Machine Learning" ). In this paper, the task of extracting interesting collocations is achieved through a supervised learning algorithm, exploiting a few collocations manually labelled as interesting/not interesting. From these examples, the ROGER algorithm learns a numerical function, inducing some ranking on the collocations. This ranking is optimized using genetic algorithms, maximizing the trade-off between the false positive and true positive rates (Area Under the ROC curve). This approach uses a particular representation for the word collocations, namely the vector of values corresponding to the standard statistical interestingness measures attached to this collocation. As this representation is general (over corpora and natural languages), generality tests were performed by experimenting the ranking function learned from an English corpus in Biology, onto a French corpus of Curriculum Vitae, and vice versa, showing a good robustness of the approaches compared to the state-of-the-art Support Vector Machine (SVM).

Keywords: Text-mining, Terminology Extraction, Evolutionary algorithm, ROC Curve.

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447 Structural Parsing of Natural Language Text in Tamil Using Phrase Structure Hybrid Language Model

Authors: Selvam M, Natarajan. A M, Thangarajan R

Abstract:

Parsing is important in Linguistics and Natural Language Processing to understand the syntax and semantics of a natural language grammar. Parsing natural language text is challenging because of the problems like ambiguity and inefficiency. Also the interpretation of natural language text depends on context based techniques. A probabilistic component is essential to resolve ambiguity in both syntax and semantics thereby increasing accuracy and efficiency of the parser. Tamil language has some inherent features which are more challenging. In order to obtain the solutions, lexicalized and statistical approach is to be applied in the parsing with the aid of a language model. Statistical models mainly focus on semantics of the language which are suitable for large vocabulary tasks where as structural methods focus on syntax which models small vocabulary tasks. A statistical language model based on Trigram for Tamil language with medium vocabulary of 5000 words has been built. Though statistical parsing gives better performance through tri-gram probabilities and large vocabulary size, it has some disadvantages like focus on semantics rather than syntax, lack of support in free ordering of words and long term relationship. To overcome the disadvantages a structural component is to be incorporated in statistical language models which leads to the implementation of hybrid language models. This paper has attempted to build phrase structured hybrid language model which resolves above mentioned disadvantages. In the development of hybrid language model, new part of speech tag set for Tamil language has been developed with more than 500 tags which have the wider coverage. A phrase structured Treebank has been developed with 326 Tamil sentences which covers more than 5000 words. A hybrid language model has been trained with the phrase structured Treebank using immediate head parsing technique. Lexicalized and statistical parser which employs this hybrid language model and immediate head parsing technique gives better results than pure grammar and trigram based model.

Keywords: Hybrid Language Model, Immediate Head Parsing, Lexicalized and Statistical Parsing, Natural Language Processing, Parts of Speech, Probabilistic Context Free Grammar, Tamil Language, Tree Bank.

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446 Hybrid Authentication System Using QR Code with OTP

Authors: Salim Istyaq

Abstract:

As we know, number of Internet users are increasing drastically. Now, people are using different online services provided by banks, colleges/schools, hospitals, online utility, bill payment and online shopping sites. To access online services, text-based authentication system is in use. The text-based authentication scheme faces some drawbacks with usability and security issues that bring troubles to users. The core element of computational trust is identity. The aim of the paper is to make the system more compliable for the imposters and more reliable for the users, by using the graphical authentication approach. In this paper, we are using the more powerful tool of encoding the options in graphical QR format and also there will be the acknowledgment which will send to the user’s mobile for final verification. The main methodology depends upon the encryption option and final verification by confirming a set of pass phrase on the legal users, the outcome of the result is very powerful as it only gives the result at once when the process is successfully done. All processes are cross linked serially as the output of the 1st process, is the input of the 2nd and so on. The system is a combination of recognition and pure recall based technique. Presented scheme is useful for devices like PDAs, iPod, phone etc. which are more handy and convenient to use than traditional desktop computer systems.

Keywords: Graphical Password, OTP, QR Codes, Recognition based graphical user authentication, usability and security.

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445 JaCoText: A Pretrained Model for Java Code-Text Generation

Authors: Jessica Lòpez Espejel, Mahaman Sanoussi Yahaya Alassan, Walid Dahhane, El Hassane Ettifouri

Abstract:

Pretrained transformer-based models have shown high performance in natural language generation task. However, a new wave of interest has surged: automatic programming language generation. This task consists of translating natural language instructions to a programming code. Despite the fact that well-known pretrained models on language generation have achieved good performance in learning programming languages, effort is still needed in automatic code generation. In this paper, we introduce JaCoText, a model based on Transformers neural network. It aims to generate java source code from natural language text. JaCoText leverages advantages of both natural language and code generation models. More specifically, we study some findings from the state of the art and use them to (1) initialize our model from powerful pretrained models, (2) explore additional pretraining on our java dataset, (3) carry out experiments combining the unimodal and bimodal data in the training, and (4) scale the input and output length during the fine-tuning of the model. Conducted experiments on CONCODE dataset show that JaCoText achieves new state-of-the-art results.

Keywords: Java code generation, Natural Language Processing, Sequence-to-sequence Models, Transformers Neural Networks.

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444 TOSOM: A Topic-Oriented Self-Organizing Map for Text Organization

Authors: Hsin-Chang Yang, Chung-Hong Lee, Kuo-Lung Ke

Abstract:

The self-organizing map (SOM) model is a well-known neural network model with wide spread of applications. The main characteristics of SOM are two-fold, namely dimension reduction and topology preservation. Using SOM, a high-dimensional data space will be mapped to some low-dimensional space. Meanwhile, the topological relations among data will be preserved. With such characteristics, the SOM was usually applied on data clustering and visualization tasks. However, the SOM has main disadvantage of the need to know the number and structure of neurons prior to training, which are difficult to be determined. Several schemes have been proposed to tackle such deficiency. Examples are growing/expandable SOM, hierarchical SOM, and growing hierarchical SOM. These schemes could dynamically expand the map, even generate hierarchical maps, during training. Encouraging results were reported. Basically, these schemes adapt the size and structure of the map according to the distribution of training data. That is, they are data-driven or dataoriented SOM schemes. In this work, a topic-oriented SOM scheme which is suitable for document clustering and organization will be developed. The proposed SOM will automatically adapt the number as well as the structure of the map according to identified topics. Unlike other data-oriented SOMs, our approach expands the map and generates the hierarchies both according to the topics and their characteristics of the neurons. The preliminary experiments give promising result and demonstrate the plausibility of the method.

Keywords: Self-organizing map, topic identification, learning algorithm, text clustering.

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443 Exploring Social Impact of Emerging Technologies from Futuristic Data

Authors: Heeyeul Kwon, Yongtae Park

Abstract:

Despite the highly touted benefits, emerging technologies have unleashed pervasive concerns regarding unintended and unforeseen social impacts. Thus, those wishing to create safe and socially acceptable products need to identify such side effects and mitigate them prior to the market proliferation. Various methodologies in the field of technology assessment (TA), namely Delphi, impact assessment, and scenario planning, have been widely incorporated in such a circumstance. However, literatures face a major limitation in terms of sole reliance on participatory workshop activities. They unfortunately missed out the availability of a massive untapped data source of futuristic information flooding through the Internet. This research thus seeks to gain insights into utilization of futuristic data, future-oriented documents from the Internet, as a supplementary method to generate social impact scenarios whilst capturing perspectives of experts from a wide variety of disciplines. To this end, network analysis is conducted based on the social keywords extracted from the futuristic documents by text mining, which is then used as a guide to produce a comprehensive set of detailed scenarios. Our proposed approach facilitates harmonized depictions of possible hazardous consequences of emerging technologies and thereby makes decision makers more aware of, and responsive to, broad qualitative uncertainties.

Keywords: Emerging technologies, futuristic data, scenario, text mining.

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442 Maya Semantic Technique: A Mathematical Technique Used to Determine Partial Semantics for Declarative Sentences

Authors: Marcia T. Mitchell

Abstract:

This research uses computational linguistics, an area of study that employs a computer to process natural language, and aims at discerning the patterns that exist in declarative sentences used in technical texts. The approach is mathematical, and the focus is on instructional texts found on web pages. The technique developed by the author and named the MAYA Semantic Technique is used here and organized into four stages. In the first stage, the parts of speech in each sentence are identified. In the second stage, the subject of the sentence is determined. In the third stage, MAYA performs a frequency analysis on the remaining words to determine the verb and its object. In the fourth stage, MAYA does statistical analysis to determine the content of the web page. The advantage of the MAYA Semantic Technique lies in its use of mathematical principles to represent grammatical operations which assist processing and accuracy if performed on unambiguous text. The MAYA Semantic Technique is part of a proposed architecture for an entire web-based intelligent tutoring system. On a sample set of sentences, partial semantics derived using the MAYA Semantic Technique were approximately 80% accurate. The system currently processes technical text in one domain, namely Cµ programming. In this domain all the keywords and programming concepts are known and understood.

Keywords: Natural language understanding, computational linguistics, knowledge representation, linguistic theories.

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441 A Methodology for Automatic Diversification of Document Categories

Authors: Dasom Kim, Chen Liu, Myungsu Lim, Soo-Hyeon Jeon, Byeoung Kug Jeon, Kee-Young Kwahk, Namgyu Kim

Abstract:

Recently, numerous documents including large volumes of unstructured data and text have been created because of the rapid increase in the use of social media and the Internet. Usually, these documents are categorized for the convenience of users. Because the accuracy of manual categorization is not guaranteed, and such categorization requires a large amount of time and incurs huge costs. Many studies on automatic categorization have been conducted to help mitigate the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorize complex documents with multiple topics because they work on the assumption that individual documents can be categorized into single categories only. Therefore, to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, the learning process employed in these studies involves training using a multi-categorized document set. These methods therefore cannot be applied to the multi-categorization of most documents unless multi-categorized training sets using traditional multi-categorization algorithms are provided. To overcome this limitation, in this study, we review our novel methodology for extending the category of a single-categorized document to multiple categorizes, and then introduce a survey-based verification scenario for estimating the accuracy of our automatic categorization methodology.

Keywords: Big Data Analysis, Document Classification, Text Mining, Topic Analysis.

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440 Performance Optimization of Data Mining Application Using Radial Basis Function Classifier

Authors: M. Govindarajan, R. M.Chandrasekaran

Abstract:

Text data mining is a process of exploratory data analysis. Classification maps data into predefined groups or classes. It is often referred to as supervised learning because the classes are determined before examining the data. This paper describes proposed radial basis function Classifier that performs comparative crossvalidation for existing radial basis function Classifier. The feasibility and the benefits of the proposed approach are demonstrated by means of data mining problem: direct Marketing. Direct marketing has become an important application field of data mining. Comparative Cross-validation involves estimation of accuracy by either stratified k-fold cross-validation or equivalent repeated random subsampling. While the proposed method may have high bias; its performance (accuracy estimation in our case) may be poor due to high variance. Thus the accuracy with proposed radial basis function Classifier was less than with the existing radial basis function Classifier. However there is smaller the improvement in runtime and larger improvement in precision and recall. In the proposed method Classification accuracy and prediction accuracy are determined where the prediction accuracy is comparatively high.

Keywords: Text Data Mining, Comparative Cross-validation, Radial Basis Function, runtime, accuracy.

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439 Probiotic Properties of Lactic Acid Bacteria Isolated from Fermented Food

Authors: Wilailak Siripornadulsil, Siriyanapat Tasaku, Jutamas Buahorm, Surasak Siripornadulsil

Abstract:

The objectives of this study were to isolate LAB from various sources, dietary supplement, Thai traditional fermented food, and freshwater fish and to characterize their potential as probiotic cultures. Out of 1,558 isolates, 730 were identified as LAB based on isolation on MRS agar supplemented with a bromocresol purple indicator&CaCO3 and Gram-positive, catalase- and oxidase-negative characteristics. Eight isolates showed the potential probiotic properties including tolerance to acid, bile salt & heat, proteolytic, amylolytic & lipolytic activities and oxalate-degrading capability. They all showed the antimicrobial activity against some Gram-negative and Gram-positive pathogenic bacteria. Based on 16S rDNA sequence analysis, they were identified as Enterococcus faecalis BT2 & MG30, Leconostoc mesenteroides SW64 and Pediococcus pentosaceous BD33, CF32, NP6, PS34 & SW5. The health beneficial effects and food safety will be further investigated and developed as a probiotic or protective culture used in Nile tilapia belly flap meat fermentation.

Keywords: Lactic acid bacteria, pathogen, probiotic, protective culture.

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438 Development of a Model for the Comprehensive Analysis and Evaluation of Service Productivity

Authors: A. Petz, S. Duckwitz, C. Schmalz, S. Meyer, S. Mütze-Niewöhner, C.M. Schlick

Abstract:

Although services play a crucial role in economy, service did not gain as much importance as productivity management in manufacturing. This paper presents key findings from literature and practice. Based on an initial definition of complex services, seven productivity concepts are briefly presented and assessed by relevant, complex service specific criteria. Following the findings a complex service productivity model is proposed. The novel model comprises of all specific dimensions of service provision from both, the provider-s as well as costumer-s perspective. A clear assignment of identified value drivers and relationships between them is presented. In order to verify the conceptual service productivity model a case study from a project engineering department of a chemical plant development and construction company is presented.

Keywords: assessment model, complex services, service productivity model, value driver.

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437 The Organizational Justice-Citizenship Behavior Link in Hotels: Does Customer Orientation Matter?

Authors: Pablo Zoghbi-Manrique-de-Lara, Miguel A. Suárez-Acosta

Abstract:

The goal of the present paper is to model two classic lines of research in which employees starred, organizational justice and citizenship behavior (OCB), but that have never been studied together when targeting customers. The suggestion is made that a hotel’s fair treatment (in terms of distributive, procedural, and interactional justice) toward customers will be appreciated by the employees, who will reciprocate in kind by favoring the hotel with increased customer-oriented behaviors (COBs). Data were collected from 204 employees at eight upscale hotels in the Canary Islands (Spain). Unlike in the case of perceptions of distributive justice, results of structural equation modeling demonstrate that employees substantively react to interactional and procedural justice toward guests by engaging in customer-oriented behaviors (COBs). The findings offer new reasons why employees decide to engage in COBs, and they highlight potentially beneficial effects of fair treatment toward guests bring to hospitality through promoting COBs.

Keywords: Hotel guests’ (mis) treatment, customer-oriented behaviors, employee citizenship, organizational justice, third-party observers, third-party intervention.

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436 A Heuristic Algorithm Approach for Scheduling of Multi-criteria Unrelated Parallel Machines

Authors: Farhad Kolahan, Vahid Kayvanfar

Abstract:

In this paper we address a multi-objective scheduling problem for unrelated parallel machines. In unrelated parallel systems, the processing cost/time of a given job on different machines may vary. The objective of scheduling is to simultaneously determine the job-machine assignment and job sequencing on each machine. In such a way the total cost of the schedule is minimized. The cost function consists of three components, namely; machining cost, earliness/tardiness penalties and makespan related cost. Such scheduling problem is combinatorial in nature. Therefore, a Simulated Annealing approach is employed to provide good solutions within reasonable computational times. Computational results show that the proposed approach can efficiently solve such complicated problems.

Keywords: Makespan, Parallel machines, Scheduling, Simulated Annealing

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435 A Study on Multi-Agent Behavior in a Soccer Game Domain

Authors: S. R. Mohd Shukri, M. K. Mohd Shaukhi

Abstract:

There have been many games developing simulation of soccer games. Many of these games have been designed with highly realistic features to attract more users. Many have also incorporated better artificial intelligent (AI) similar to that in a real soccer game. One of the challenging issues in a soccer game is the cooperation, coordination and negotiation among distributed agents in a multi-agent system. This paper focuses on the incorporation of multi-agent technique in a soccer game domain. The better the cooperation of a multi-agent team, the more intelligent the game will be. Thus, past studies were done on the robotic soccer game because of the better multi-agent system implementation. From this study, a better approach and technique of multi-agent behavior could be select to improve the author-s 2D online soccer game.

Keywords: Multi-Agent, Robotic Intelligent, Role Assignment, Formation.

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434 Myanmar Character Recognition Using Eight Direction Chain Code Frequency Features

Authors: Kyi Pyar Zaw, Zin Mar Kyu

Abstract:

Character recognition is the process of converting a text image file into editable and searchable text file. Feature Extraction is the heart of any character recognition system. The character recognition rate may be low or high depending on the extracted features. In the proposed paper, 25 features for one character are used in character recognition. Basically, there are three steps of character recognition such as character segmentation, feature extraction and classification. In segmentation step, horizontal cropping method is used for line segmentation and vertical cropping method is used for character segmentation. In the Feature extraction step, features are extracted in two ways. The first way is that the 8 features are extracted from the entire input character using eight direction chain code frequency extraction. The second way is that the input character is divided into 16 blocks. For each block, although 8 feature values are obtained through eight-direction chain code frequency extraction method, we define the sum of these 8 feature values as a feature for one block. Therefore, 16 features are extracted from that 16 blocks in the second way. We use the number of holes feature to cluster the similar characters. We can recognize the almost Myanmar common characters with various font sizes by using these features. All these 25 features are used in both training part and testing part. In the classification step, the characters are classified by matching the all features of input character with already trained features of characters.

Keywords: Chain code frequency, character recognition, feature extraction, features matching, segmentation.

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433 Optimization of a New Three-Phase High Voltage Power Supply for Industrial Microwaves Generators with N Magnetrons by Phase (Treated Case N=1)

Authors: M. Bassoui, M. Ferfra, M. Chraygane, M. Ould Ahmedou, N. Elghazal, A. Belhaiba

Abstract:

Currently, the High voltage power supply for microwave generators with one magnetron uses a single-phase transformer with magnetic shunt. To contribute in the development of technological innovation in industry of manufacturing of power supplies of magnetrons for microwaves, ovens for domestic or industrial use, this original work treats the optimization of a new three-phase high voltage power supply for industrial microwaves generators with N magnetrons by phase (Treated case N=1), from its modeling with Matlab-Simulink. The design of this power supply uses three π quadruple models equivalents of new three-phase transformer with magnetic shunt of each phase. Every one supplies at its output a voltage doubler cell composed of a capacitor and a diode that in its output supplies only one magnetron.  In this work we will define a strategy that aims to reduce the volume of the transformer and the weight and cost of the entire system of the high voltage power supply, while respecting the conditions recommended by the manufacturer, concerning the current flowing in each magnetron: (Imax <1.2 A, IAv ≈ 300 mA).

 

Keywords: Optimization, Three-phase transformer, Modeling, power supply, magnetrons, Matlab Simulink, High Voltage

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432 Developing ESL Students' Writing

Authors: Esmaeil Hassannejad

Abstract:

Some of the students' problems in writing skill stem from inadequate preparation for the writing assignment. Students should be taught how to write well when they arrive in language classes. Having selected a topic, the students examine and explore the theme from as large a variety of viewpoints as their background and imagination make possible. Another strategy is that the students prepare an Outline before writing the paper. The comparison between the two mentioned thought provoking techniques was carried out between the two class groups –students of Islamic Azad University of Dezful who were studying “Writing 2" as their main course. Each class group was assigned to write five compositions separately in different periods of time. Then a t-test for each pair of exams between the two class groups showed that the t-observed in each pair was more than the t-critical. Consequently, the first hypothesis which states those who utilize Brainstorming as a thought provoking technique in prewriting phase are more successful than those who outline the papers before writing was verified.

Keywords: Brainstorming, Outlining, Prewriting, Thought provoking techniques

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431 Object Identification with Color, Texture, and Object-Correlation in CBIR System

Authors: Awais Adnan, Muhammad Nawaz, Sajid Anwar, Tamleek Ali, Muhammad Ali

Abstract:

Needs of an efficient information retrieval in recent years in increased more then ever because of the frequent use of digital information in our life. We see a lot of work in the area of textual information but in multimedia information, we cannot find much progress. In text based information, new technology of data mining and data marts are now in working that were started from the basic concept of database some where in 1960. In image search and especially in image identification, computerized system at very initial stages. Even in the area of image search we cannot see much progress as in the case of text based search techniques. One main reason for this is the wide spread roots of image search where many area like artificial intelligence, statistics, image processing, pattern recognition play their role. Even human psychology and perception and cultural diversity also have their share for the design of a good and efficient image recognition and retrieval system. A new object based search technique is presented in this paper where object in the image are identified on the basis of their geometrical shapes and other features like color and texture where object-co-relation augments this search process. To be more focused on objects identification, simple images are selected for the work to reduce the role of segmentation in overall process however same technique can also be applied for other images.

Keywords: Object correlation, Geometrical shape, Color, texture, features, contents.

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430 Persian/Arabic Document Segmentation Based On Pyramidal Image Structure

Authors: Seyyed Yasser Hashemi, Khalil Monfaredi

Abstract:

Automatic transformation of paper documents into electronic documents requires document segmentation at the first stage. However, some parameters restrictions such as variations in character font sizes, different text line spacing, and also not uniform document layout structures altogether have made it difficult to design a general-purpose document layout analysis algorithm for many years. Thus in most previously reported methods it is inevitable to include these parameters. This problem becomes excessively acute and severe, especially in Persian/Arabic documents. Since the Persian/Arabic scripts differ considerably from the English scripts, most of the proposed methods for the English scripts do not render good results for the Persian scripts. In this paper, we present a novel parameter-free method for segmenting the Persian/Arabic document images which also works well for English scripts. This method segments the document image into maximal homogeneous regions and identifies them as texts and non-texts based on a pyramidal image structure. In other words the proposed method is capable of document segmentation without considering the character font sizes, text line spacing, and document layout structures. This algorithm is examined for 150 Arabic/Persian and English documents and document segmentation process are done successfully for 96 percent of documents.

Keywords: Persian/Arabic document, document segmentation, Pyramidal Image Structure, skew detection and correction.

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429 Decode and Forward Cooperative Protocol Enhancement Using Interference Cancellation

Authors: Siddeeq Y. Ameen, Mohammed K. Yousif

Abstract:

Cooperative communication systems are considered to be a promising technology to improve the system capacity, reliability and performances over fading wireless channels. Cooperative relaying system with a single antenna will be able to reach the advantages of multiple antenna communication systems. It is ideally suitable for the distributed communication systems; the relays can cooperate and form virtual MIMO systems. Thus the paper will aim to investigate the possible enhancement of cooperated system using decode and forward protocol. On the decode and forward an attempt to cancel or at least reduce the interference instead of increasing the SNR values is achieved. The latter can be achieved via the use group of relays depending on the channel status from source to relay and relay to destination respectively.

In the proposed system, the transmission time has been divided into two phases to be used by the decode and forward protocol. The first phase has been allocated for the source to transmit its data whereas the relays and destination nodes are in receiving mode. On the other hand, the second phase is allocated for the first and second groups of relay nodes to relay the data to the destination node. Simulations results have shown an improvement in performance is achieved compared to the conventional decode and forward in terms of BER and transmission rate.

Keywords: Cooperative systems, decode and forward, interference cancellation, virtual MIMO.

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428 The Name of Thai Muslim Students: The Reflection of Value and Identity of Thai Muslim

Authors: Apichaya Kaewuthai

Abstract:

To study the meaning of Muslim name in order to analyze the underlining value and identity from first year to forth year Muslim students at Prince of Songkla University, Hatyai Campus. The questionnaires are employed as a main analytical tool to acquire the names from 80 Muslim students in four study years. The meanings of obtained names are subsequently analyzed and summarized base upon related documents to uncover the beneath value. The study reveals that name of male is derived from the name of prophet; Nabi Muhammad, merit, dignity, origins, leadership and the faith in Islam. For female, on the other hand, their names are related to virtue and beauty, cleanliness and peace, hope and flowers which comply with their characteristics. One of the reasons contribute to the principle of naming is the regulation of Ministry of Culture which states that the name should represent one’s nature and characters. The given name reflects value and identity of Muslim which can be classified into three categories including 1) Value related to belief in Islam 2) value related to relationship among families and relatives 3) value about relationship with nature and environment. All the above mentioned reflect Muslim value and identity vividly.    The name of Muslim students allows the researcher to perceive the perspective, belief and value in giving the name of Thai Muslim. Besides, it reveals social condition and their culture. It can also be the fundamental of studying the meaning of name in other races.

Keywords: The naming, Thai Muslim.

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427 Labor Productivity in the Construction Industry -Factors Influencing the Spanish Construction Labor Productivity-

Authors: G. Robles, A. Stifi, José L. Ponz-Tienda, S. Gentes

Abstract:

This research paper aims to identify, analyze and rank factors affecting labor productivity in Spain with respect to their relative importance. Using a selected set of 35 factors, a structured questionnaire survey was utilized as the method to collect data from companies. Target population is comprised by a random representative sample of practitioners related with the Spanish construction industry. Findings reveal the top five ranked factors are as follows: (1) shortage or late supply of materials; (2) clarity of the drawings and project documents; (3) clear and daily task assignment; (4) tools or equipment shortages; (5) level of skill and experience of laborers. Additionally, this research also pretends to provide simple and comprehensive recommendations so that they could be implemented by construction managers for an effective management of construction labor forces.

Keywords: Construction management, Factors, Improvement, Labor productivity, Lean construction.

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426 Project Portfolio Management Phases: A Technique for Strategy Alignment

Authors: Amaral, António, Araújo, Madalena

Abstract:

This paper seeks to give a general idea of the universe of project portfolio management, from its multidisciplinary nature, to the many challenges it raises, passing through the different techniques, models and tools used to solve the multiple problems known. It is intended to contribute to the clarification, with great depth, of the impacts and relationships involved in managing the projects- portfolio. It aims at proposing a technique for the project alignment with the organisational strategy, in order to select projects that later on will be considered in the analysis and selection of the portfolio. We consider the development of a methodology for assessing the project alignment index very relevant in the global market scenario. It can help organisations to gain a greater awareness of market dynamics, speed up the decision process and increase its consistency, thus enabling the strategic alignment and the improvement of the organisational performance.

Keywords: Project Portfolio Management Cycle, Project Portfolio Selection, Resource Assignment, Strategy Alignment technique

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425 Text-independent Speaker Identification Based on MAP Channel Compensation and Pitch-dependent Features

Authors: Jiqing Han, Rongchun Gao

Abstract:

One major source of performance decline in speaker recognition system is channel mismatch between training and testing. This paper focuses on improving channel robustness of speaker recognition system in two aspects of channel compensation technique and channel robust features. The system is text-independent speaker identification system based on two-stage recognition. In the aspect of channel compensation technique, this paper applies MAP (Maximum A Posterior Probability) channel compensation technique, which was used in speech recognition, to speaker recognition system. In the aspect of channel robust features, this paper introduces pitch-dependent features and pitch-dependent speaker model for the second stage recognition. Based on the first stage recognition to testing speech using GMM (Gaussian Mixture Model), the system uses GMM scores to decide if it needs to be recognized again. If it needs to, the system selects a few speakers from all of the speakers who participate in the first stage recognition for the second stage recognition. For each selected speaker, the system obtains 3 pitch-dependent results from his pitch-dependent speaker model, and then uses ANN (Artificial Neural Network) to unite the 3 pitch-dependent results and 1 GMM score for getting a fused result. The system makes the second stage recognition based on these fused results. The experiments show that the correct rate of two-stage recognition system based on MAP channel compensation technique and pitch-dependent features is 41.7% better than the baseline system for closed-set test.

Keywords: Channel Compensation, Channel Robustness, MAP, Speaker Identification

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