Search results for: Document clustering
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 680

Search results for: Document clustering

200 New Proxy Signatures Preserving Privacy and as Secure as ElGamal Signatures

Authors: Song Han, Elizabeth Chang, Jie Wang, Wanquan Liu

Abstract:

Digital signature is a useful primitive to attain the integrity and authenticity in various wire or wireless communications. Proxy signature is one type of the digital signatures. It helps the proxy signer to sign messages on behalf of the original signer. It is very useful when the original signer (e.g. the president of a company) is not available to sign a specific document. If the original signer can not forge valid proxy signatures through impersonating the proxy signer, it will be robust in a virtual environment; thus the original signer can not shift any illegal action initiated by herself to the proxy signer. In this paper, we propose a new proxy signature scheme. The new scheme can prevent the original signer from impersonating the proxy signer to sign messages. The proposed scheme is based on the regular ElGamal signature. In addition, the fair privacy of the proxy signer is maintained. That means, the privacy of the proxy signer is preserved; and the privacy can be revealed when it is necessary.

Keywords: ElGamal signature, proxy signature, security, hash function, fair privacy.

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199 A Study of Gaps in CBMIR Using Different Methods and Prospective

Authors: Pradeep Singh, Sukhwinder Singh, Gurjinder Kaur

Abstract:

In recent years, rapid advances in software and hardware in the field of information technology along with a digital imaging revolution in the medical domain facilitate the generation and storage of large collections of images by hospitals and clinics. To search these large image collections effectively and efficiently poses significant technical challenges, and it raises the necessity of constructing intelligent retrieval systems. Content-based Image Retrieval (CBIR) consists of retrieving the most visually similar images to a given query image from a database of images[5]. Medical CBIR (content-based image retrieval) applications pose unique challenges but at the same time offer many new opportunities. On one hand, while one can easily understand news or sports videos, a medical image is often completely incomprehensible to untrained eyes.

Keywords: Classification, clustering, content-based image retrieval (CBIR), relevance feedback (RF), statistical similarity matching, support vector machine (SVM).

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198 Discovering Complex Regularities by Adaptive Self Organizing Classification

Authors: A. Faro, D. Giordano, F. Maiorana

Abstract:

Data mining uses a variety of techniques each of which is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optmize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is also able to automatically suggest a strategy for number of classes optimization.The tool is used to classify macroeconomic data that report the most developed countries? import and export. It is possible to classify the countries based on their economic behaviour and use an ad hoc tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation.

Keywords: Unsupervised classification, Kohonen networks, macroeconomics, Visual data mining, cluster interpretation.

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197 Ethnobotany and Distribution of Dioscoreahispida Dennst. (Dioscoreaceae) in Besut, Marang and Setiu Districts of Terengganu, Peninsular Malaysia

Authors: M. Nashriyah, T. Salmah, M.Y. NurAtiqah, O. Siti Nor Indah, A.W. MuhamadAzhar, S. Munirah, Y. Nornasuha, A. Abdul Manaf

Abstract:

Dioscorea species or commonly named as yam is reported to be one of the major food sources worldwide. This ethnobotanical study was conducted to document local knowledge and potentials of DioscoreahispidaDennst. and to investigate and record its distribution in three districts of Terengganu. Information was gathered from 23 villagers from three districts of Besut, Marang and Setiu by using semi-structured questionnaire. The villagers were randomly selected and no appointment was made prior to the visits. For distribution, the location of Dioscoreahispida was recorded by using the Global Positioning System (GPS). The villagers identified Dioscoreahispida or locally named ubigadong by looking at the physical characteristics that include its leaf shape, stem and the color of the tuber-s flesh. The villagers used Dioscoreahispida in many ways in their life such as for food, medicinal purposes and fish poison.

Keywords: Dioscoreahispida, ethnobotany, intoxicating yam, ubigadong, Terengganu.

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196 Recognition of Grocery Products in Images Captured by Cellular Phones

Authors: Farshideh Einsele, Hassan Foroosh

Abstract:

In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation, style, illumination, and can suffer from perspective distortion. Pre-processing is performed to make the characters scale and rotation invariant. Since text degradations can not be appropriately defined using well-known geometric transformations such as translation, rotation, affine transformation and shearing, we use the whole character black pixels as our feature vector. Classification is performed with minimum distance classifier using the maximum likelihood criterion, which delivers very promising Character Recognition Rate (CRR) of 89%. We achieve considerably higher Word Recognition Rate (WRR) of 99% when using lower level linguistic knowledge about product words during the recognition process.

Keywords: Camera-based OCR, Feature extraction, Document and image processing.

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195 Neuro-fuzzy Model and Regression Model a Comparison Study of MRR in Electrical Discharge Machining of D2 Tool Steel

Authors: M. K. Pradhan, C. K. Biswas,

Abstract:

In the current research, neuro-fuzzy model and regression model was developed to predict Material Removal Rate in Electrical Discharge Machining process for AISI D2 tool steel with copper electrode. Extensive experiments were conducted with various levels of discharge current, pulse duration and duty cycle. The experimental data are split into two sets, one for training and the other for validation of the model. The training data were used to develop the above models and the test data, which was not used earlier to develop these models were used for validation the models. Subsequently, the models are compared. It was found that the predicted and experimental results were in good agreement and the coefficients of correlation were found to be 0.999 and 0.974 for neuro fuzzy and regression model respectively

Keywords: Electrical discharge machining, material removal rate, neuro-fuzzy model, regression model, mountain clustering.

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194 Performance and Emission Prediction in a Biodiesel Engine Fuelled with Honge Methyl Ester Using RBF Neural Networks

Authors: Shivakumar, G. S. Vijay, P. Srinivas Pai, B. R. Shrinivasa Rao

Abstract:

In the present study, RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tex and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: Radial Basis Function networks, emissions, Performance parameters, Fuzzy c means.

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193 Enhance Power Quality by HVDC System, Comparison Technique between HVDC and HVAC Transmission Systems

Authors: Smko Zangana, Ergun Ercelebi

Abstract:

The alternating current is the main power in all industries and other aspects especially for the short and mid distances, but as far as long a distance which exceeds 500 KMs, using the alternating current technically will face many difficulties and more costs because it's difficult to control the current and also other restrictions. Therefore, recently those reasons led to building transmission lines HVDC to transmit power for long distances. This document presents technical comparison and assessments for power transmission system among distances either ways and studying the stability of the system regarding the proportion of losses in the actual power sent and received between both sides in different systems and also categorizing filters used in the HVDC system and its impact and effect on reducing Harmonic in the power transmission. MATLAB /Simulink simulation software is used to simulate both HVAC & HVDC power transmission system topologies.

Keywords: HVAC power system, HVDC power system, power system simulation (MATLAB), the alternating current, voltage stability.

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192 Registration Management System for the First Access to a Public Moroccan Institution: Case Sultan Moulay Slimane University, Beni Mellal

Authors: Khalid Ghoulam, Belaid Bouikhalene, Zakaria Harmouch, Hicham Mouncif

Abstract:

One of the essential topics in the information systems is the registration management. The objective of this project is to create a web portal designed to help new students on the first access to the Sultan Moulay Slimane University SMSU (Practical Information, Pre-Registration, Placement Test, Terms of use ... etc.) while creating a secure space protecting both data from the institutions of the University and student information. This portal is accessible from any computer connected to the Internet inside and outside the campus. In this work, we present a platform on the first access to the SMSU which is essential for authentication in the digital work space of the university. This platform allows university to make better decisions for students clustering, to avoid traditional manual method, and to reduce the cost in human and material resources.

Keywords: Registration, SMSU, Security, FAUSMS, digital work space, Placement test.

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191 A Heuristics Approach for Fast Detecting Suspicious Money Laundering Cases in an Investment Bank

Authors: Nhien-An Le-Khac, Sammer Markos, M-Tahar Kechadi

Abstract:

Today, money laundering (ML) poses a serious threat not only to financial institutions but also to the nation. This criminal activity is becoming more and more sophisticated and seems to have moved from the cliché of drug trafficking to financing terrorism and surely not forgetting personal gain. Most international financial institutions have been implementing anti-money laundering solutions (AML) to fight investment fraud. However, traditional investigative techniques consume numerous man-hours. Recently, data mining approaches have been developed and are considered as well-suited techniques for detecting ML activities. Within the scope of a collaboration project for the purpose of developing a new solution for the AML Units in an international investment bank, we proposed a data mining-based solution for AML. In this paper, we present a heuristics approach to improve the performance for this solution. We also show some preliminary results associated with this method on analysing transaction datasets.

Keywords: data mining, anti money laundering, clustering, heuristics.

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190 Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries

Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammadhossein Sedaaghi

Abstract:

Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy CMeans (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic CMeans (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.

Keywords: Facial image, segmentation, PCM, FCM, skin error, facial surgery.

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189 Collaborative and Content-based Recommender System for Social Bookmarking Website

Authors: Cheng-Lung Huang, Cheng-Wei Lin

Abstract:

This study proposes a new recommender system based on the collaborative folksonomy. The purpose of the proposed system is to recommend Internet resources (such as books, articles, documents, pictures, audio and video) to users. The proposed method includes four steps: creating the user profile based on the tags, grouping the similar users into clusters using an agglomerative hierarchical clustering, finding similar resources based on the user-s past collections by using content-based filtering, and recommending similar items to the target user. This study examines the system-s performance for the dataset collected from “del.icio.us," which is a famous social bookmarking website. Experimental results show that the proposed tag-based collaborative and content-based filtering hybridized recommender system is promising and effectiveness in the folksonomy-based bookmarking website.

Keywords: Collaborative recommendation, Folksonomy, Social tagging

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188 Signed Approach for Mining Web Content Outliers

Authors: G. Poonkuzhali, K.Thiagarajan, K.Sarukesi, G.V.Uma

Abstract:

The emergence of the Internet has brewed the revolution of information storage and retrieval. As most of the data in the web is unstructured, and contains a mix of text, video, audio etc, there is a need to mine information to cater to the specific needs of the users without loss of important hidden information. Thus developing user friendly and automated tools for providing relevant information quickly becomes a major challenge in web mining research. Most of the existing web mining algorithms have concentrated on finding frequent patterns while neglecting the less frequent ones that are likely to contain outlying data such as noise, irrelevant and redundant data. This paper mainly focuses on Signed approach and full word matching on the organized domain dictionary for mining web content outliers. This Signed approach gives the relevant web documents as well as outlying web documents. As the dictionary is organized based on the number of characters in a word, searching and retrieval of documents takes less time and less space.

Keywords: Outliers, Relevant document, , Signed Approach, Web content mining, Web documents..

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187 A Survey of Business Component Identification Methods and Related Techniques

Authors: Zhongjie Wang, Xiaofei Xu, Dechen Zhan

Abstract:

With deep development of software reuse, componentrelated technologies have been widely applied in the development of large-scale complex applications. Component identification (CI) is one of the primary research problems in software reuse, by analyzing domain business models to get a set of business components with high reuse value and good reuse performance to support effective reuse. Based on the concept and classification of CI, its technical stack is briefly discussed from four views, i.e., form of input business models, identification goals, identification strategies, and identification process. Then various CI methods presented in literatures are classified into four types, i.e., domain analysis based methods, cohesion-coupling based clustering methods, CRUD matrix based methods, and other methods, with the comparisons between these methods for their advantages and disadvantages. Additionally, some insufficiencies of study on CI are discussed, and the causes are explained subsequently. Finally, it is concluded with some significantly promising tendency about research on this problem.

Keywords: Business component, component granularity, component identification, reuse performance.

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186 Thai Arts and Culture the Formation of Thai Identity Letter Font Designed

Authors: Kreetha Thumcharoensathit

Abstract:

The purpose of the analysis of Thai Arts and Culture which concerning the formation of Thai identity letter font designed is to identify The Aumphawa local community identity so as to select the suitable letter font which can applicable to the computer software usage. The populated survey was from the group of local people who live in Aumphawa sub-district. The methodological is cluster sampling from 100 surveyed, those 50 were from people who have household registration done in Aumphawa sub-district and other from people who live outside. In order to analyze and design the Thai identity letter font computer software designed for both Thai and English language version, the analysis had been completed by compiling of document and field survey from local people’s opinion on their Arts and Culture identity. The out-put will be submitted to the experts for evaluation.

Keywords: Thai Arts, Design, Font, Identity.

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185 The Aspect of the Human Bias in Decision Making within Quality Management Systems & LEAN Theory

Authors: Adriana Ávila Zúñiga Nordfjeld

Abstract:

This paper provides a literature review to document the state of the art with respect to handling “human bias” in decision making within the established quality management systems (QMS) and LEAN theory, in the context of shipbuilding. Previous research shows that in shipbuilding there is a huge deviation from the planned man-hours under the project management to the actual man-hours used because of errors in planning and reworks caused by human bias in the information flows, among others. This reduces the efficiency, and increases operational costs. Thus, the research question is how QMS and LEAN handle biases. The findings show the gap in studying the integration of methods to handle human bias in decision making into QMS and lean, not only within shipbuilding, but in general. Theoretical and practical implications are discussed for researchers and practitioners in the areas of decision making, QMS and LEAN, and future research is suggested.

Keywords: Human bias, decision making, LEAN Shipbuilding, quality management systems.

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184 Handling Mobility using Virtual Grid in Static Wireless Sensor Networks

Authors: T.P. Sharma

Abstract:

Querying a data source and routing data towards sink becomes a serious challenge in static wireless sensor networks if sink and/or data source are mobile. Many a times the event to be observed either moves or spreads across wide area making maintenance of continuous path between source and sink a challenge. Also, sink can move while query is being issued or data is on its way towards sink. In this paper, we extend our already proposed Grid Based Data Dissemination (GBDD) scheme which is a virtual grid based topology management scheme restricting impact of movement of sink(s) and event(s) to some specific cells of a grid. This obviates the need for frequent path modifications and hence maintains continuous flow of data while minimizing the network energy consumptions. Simulation experiments show significant improvements in network energy savings and average packet delay for a packet to reach at sink.

Keywords: Mobility in WSNs, virtual grid, GBDD, clustering.

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183 Classification of Earthquake Distribution in the Banda Sea Collision Zone with Point Process Approach

Authors: Henry J. Wattimanela, Udjianna S. Pasaribu, Nanang T. Puspito, Sapto W. Indratno

Abstract:

Banda Sea Collision Zone (BSCZ) is the result of the interaction and convergence of Indo-Australian plate, Eurasian plate and Pacific plate. This location is located in eastern Indonesia. This zone has a very high seismic activity. In this research, we will calculate the rate (λ) and Mean Square Error (MSE). By this result, we will classification earthquakes distribution in the BSCZ with the point process approach. Chi-square is used to determine the type of earthquakes distribution in the sub region of BSCZ. The data used in this research is data of earthquakes with a magnitude ≥ 6 SR for the period 1964-2013 and sourced from BMKG Jakarta. This research is expected to contribute to the Moluccas Province and surrounding local governments in performing spatial plan document related to disaster management.

Keywords: Banda sea collision zone, earthquakes, mean square error, Poisson distribution, chi-square test.

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182 Tablet Computer as a User Interface: Intelligent Solutions for Multifunctional Hardcopy Devices

Authors: Jaakko Parviainen, Keijo Haataja, Antti Väänänen, Pekka Toivanen

Abstract:

Tablet computers and Multifunctional Hardcopy Devices (MHDs) are common devices in daily life. Though, many scientific studies have not been published. The tablet computers are straightforward to use whereas the MHDs are comparatively difficult to use. Thus, to assist different levels of users, we propose combining these two devices to achieve straightforward intelligent user interface (UI) and versatile What You See Is What You Get (WYSIWYG) document management and production. Our approach to this issue is to design an intelligent user dependent UI for a MHD applying a tablet computer. Furthermore, we propose hardware interconnection and versatile intelligent software between these two devices. In this study, we first provide a state-of-the-art survey on MHDs and tablet computers, and their interconnections. Secondly we provide a comparative UI survey on two state-of-the-art MHDs with a proposal of a novel UI for the MHDs using Jakob Nielsen-s Ten Usability Heuristics Evaluation.

Keywords: Computational intelligence, hardcopy device, tablet computer, user interface.

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181 Malaysia under the Purview of the United Nations and Agenda 21

Authors: Maisarah Makmor, Zulhabri Ismail, Rugayah Hashim, Nasyairi Mat Nasir

Abstract:

Developing a nation geared by the principle of sustainable development has been one of the piers in moulding a greater nation for Malaysia since its independence. This is seen by the act of joining the United Nations in 1957, just a month after gaining their independence. The United Nations is an international organization that aims to unite the nations worldwide based on justice, human dignity and human well-being. Malaysia has established a local body called the United Nations Malaysia which collaborates with the government to accomplish the aim of supporting sustainable development in Malaysia. Agenda 21 is an international document produced from the Earth Summit providing guidelines of implementing sustainable development globally, nationally and locally. Initiatives of applying Agenda 21 in Malaysia have been taken by the government and non-profit organizations to expose issues regarding sustainable development and providing environmental education to the community to increase awareness towards environmental protection.

Keywords: Agenda 21, Environmental Protection, Malaysia, Sustainable Development, United Nations.

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180 Usability Evaluation of Online News Websites: A User Perspective Approach

Authors: Qasem A. Al-Radaideh, Emad Abu-Shanab, Shaima Hamam, Hani Abu-Salem

Abstract:

Online news websites are one of the main and wide areas of Mass Media. Since the nineties several Jordanian newspapers were introduced to the World Wide Web to reach various and large numbers of audiances. Examples of these newspapers that have online version are Al-Rai, Ad-Dustor and AlGhad. Other pure online news websites include Ammon and Rum. The main aim of this study is to evaluate online newspaper websites using two assessment measures; usability and web content. This aim is achieved by using a questionnaire based evaluation which is based on the definition of usability and web content in the ISO document as the standard number 9241-part 11. The results are obtained based on 204 audiences- responses. The results of the research showed that the usability factor is relatively good for all Jordanian online newspapers whereas the web content factor is moderate.

Keywords: Communication and mass media, Jordanian online news websites, website content, website usability.

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179 A Study of Dynamic Clustering Method to Extend the Lifetime of Wireless Sensor Network

Authors: Wernhuar Tarng, Kun-Jie Huang, Li-Zhong Deng, Kun-Rong Hsie, Mingteh Chen

Abstract:

In recent years, the research in wireless sensor network has increased steadily, and many studies were focusing on reducing energy consumption of sensor nodes to extend their lifetimes. In this paper, the issue of energy consumption is investigated and two adaptive mechanisms are proposed to extend the network lifetime. This study uses high-energy-first scheme to determine cluster heads for data transmission. Thus, energy consumption in each cluster is balanced and network lifetime can be extended. In addition, this study uses cluster merging and dynamic routing mechanisms to further reduce energy consumption during data transmission. The simulation results show that the proposed method can effectively extend the lifetime of wireless sensor network, and it is suitable for different base station locations.

Keywords: Wireless sensor network, high-energy-first scheme, adaptive mechanisms, network lifetime

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178 Neural Network based Texture Analysis of Liver Tumor from Computed Tomography Images

Authors: K.Mala, V.Sadasivam, S.Alagappan

Abstract:

Advances in clinical medical imaging have brought about the routine production of vast numbers of medical images that need to be analyzed. As a result an enormous amount of computer vision research effort has been targeted at achieving automated medical image analysis. Computed Tomography (CT) is highly accurate for diagnosing liver tumors. This study aimed to evaluate the potential role of the wavelet and the neural network in the differential diagnosis of liver tumors in CT images. The tumors considered in this study are hepatocellular carcinoma, cholangio carcinoma, hemangeoma and hepatoadenoma. Each suspicious tumor region was automatically extracted from the CT abdominal images and the textural information obtained was used to train the Probabilistic Neural Network (PNN) to classify the tumors. Results obtained were evaluated with the help of radiologists. The system differentiates the tumor with relatively high accuracy and is therefore clinically useful.

Keywords: Fuzzy c means clustering, texture analysis, probabilistic neural network, LVQ neural network.

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177 Preparation of Tender for Building Conservation Work: Current Practices in Malaysia

Authors: Q.Y. Lee, Y.M. Lim

Abstract:

Building conservation work generally involves complex and non-standard work different from new building construction processes. In preparing tenders for building conservation projects, therefore, the quantity surveyor must carefully consider the specificity of non-standard items and demarcate the scope of unique conservation work. While the quantity surveyor must appreciate the full range of works to prepare a good tender document, he typically manages many unfamiliar elements, including practical construction methods, restoration techniques and work sequences. Only by fulfilling the demanding requirements of building conservation work can the quantity surveyor enhance his professionalism an area of growing cultural value and economic importance. By discussing several issues crucial to tender preparations for building conservation projects in Malaysia, this paper seeks a deeper understanding of how quantity surveying can better standardize tender preparation work and more successfully manage building conservation processes.

Keywords: Conservation Works, Quantity Surveying Practice, Tender Preparation, Malaysia

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176 An Approach to Concerns and Aspects Mining for Web Applications

Authors: Carlo Bellettini, Alessandro Marchetto, Andrea Trentini

Abstract:

Web applications have become very complex and crucial, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering), the scientific community has focused attention to Web applications design, development, analysis, and testing, by studying and proposing methodologies and tools. This paper proposes an approach to automatic multi-dimensional concern mining for Web Applications, based on concepts analysis, impact analysis, and token-based concern identification. This approach lets the user to analyse and traverse Web software relevant to a particular concern (concept, goal, purpose, etc.) via multi-dimensional separation of concerns, to document, understand and test Web applications. This technique was developed in the context of WAAT (Web Applications Analysis and Testing) project. A semi-automatic tool to support this technique is currently under development.

Keywords: Aspect Mining, Concepts Analysis, Concerns Mining, Multi-Dimensional Separation of Concerns, Impact Analysis.

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175 Kernel Matching versus Inverse Probability Weighting: A Comparative Study

Authors: Andy Handouyahia, Tony Haddad, Frank Eaton

Abstract:

Recent quasi-experimental evaluation of the Canadian Active Labour Market Policies (ALMP) by Human Resources and Skills Development Canada (HRSDC) has provided an opportunity to examine alternative methods to estimating the incremental effects of Employment Benefits and Support Measures (EBSMs) on program participants. The focus of this paper is to assess the efficiency and robustness of inverse probability weighting (IPW) relative to kernel matching (KM) in the estimation of program effects. To accomplish this objective, the authors compare pairs of 1,080 estimates, along with their associated standard errors, to assess which type of estimate is generally more efficient and robust. In the interest of practicality, the authorsalso document the computationaltime it took to produce the IPW and KM estimates, respectively.

Keywords: Treatment effect, causal inference, observational studies, Propensity score based matching, Kernel Matching, Inverse Probability Weighting, Estimation methods for incremental effect.

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174 Dempster-Shafer Evidence Theory for Image Segmentation: Application in Cells Images

Authors: S. Ben Chaabane, M. Sayadi, F. Fnaiech, E. Brassart

Abstract:

In this paper we propose a new knowledge model using the Dempster-Shafer-s evidence theory for image segmentation and fusion. The proposed method is composed essentially of two steps. First, mass distributions in Dempster-Shafer theory are obtained from the membership degrees of each pixel covering the three image components (R, G and B). Each membership-s degree is determined by applying Fuzzy C-Means (FCM) clustering to the gray levels of the three images. Second, the fusion process consists in defining three discernment frames which are associated with the three images to be fused, and then combining them to form a new frame of discernment. The strategy used to define mass distributions in the combined framework is discussed in detail. The proposed fusion method is illustrated in the context of image segmentation. Experimental investigations and comparative studies with the other previous methods are carried out showing thus the robustness and superiority of the proposed method in terms of image segmentation.

Keywords: Fuzzy C-means, Color image, data fusion, Dempster-Shafer's evidence theory

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173 Evaluation of Robust Feature Descriptors for Texture Classification

Authors: Jia-Hong Lee, Mei-Yi Wu, Hsien-Tsung Kuo

Abstract:

Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets - UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers.

Keywords: Texture classification, texture descriptor, SIFT, SURF, ORB.

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172 Multi-Dimensional Concerns Mining for Web Applications via Concept-Analysis

Authors: Carlo Bellettini, Alessandro Marchetto, Andrea Trentini

Abstract:

Web applications have become very complex and crucial, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering), the scientific community has focused attention to Web applications design, development, analysis, and testing, by studying and proposing methodologies and tools. This paper proposes an approach to automatic multi-dimensional concern mining for Web Applications, based on concepts analysis, impact analysis, and token-based concern identification. This approach lets the user to analyse and traverse Web software relevant to a particular concern (concept, goal, purpose, etc.) via multi-dimensional separation of concerns, to document, understand and test Web applications. This technique was developed in the context of WAAT (Web Applications Analysis and Testing) project. A semi-automatic tool to support this technique is currently under development.

Keywords: Concepts Analysis, Concerns Mining, Multi-Dimensional Separation of Concerns, Impact Analysis.

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171 Modelling Medieval Vaults: Digital Simulation of the North Transept Vault of St Mary, Nantwich, England

Authors: N. Webb, A. Buchanan

Abstract:

Digital and virtual heritage is often associated with the recreation of lost artefacts and architecture; however, we can also investigate works that were not completed, using digital tools and techniques. Here we explore physical evidence of a fourteenth-century Gothic vault located in the north transept of St Mary’s church in Nantwich, Cheshire, using existing springer stones that are built into the walls as a starting point. Digital surveying tools are used to document the architecture, followed by an analysis process to hypothesise and simulate possible design solutions, had the vault been completed. A number of options, both two-dimensionally and three-dimensionally, are discussed based on comparison with examples of other contemporary vaults, thus adding another specimen to the corpus of vault designs. Dissemination methods such as digital models and 3D prints are also explored as possible resources for demonstrating what the finished vault might have looked like for heritage interpretation and other purposes.

Keywords: Digital simulation, heritage interpretation, medieval vaults, virtual heritage, 3D scanning.

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