Search results for: specific emitter identification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2647

Search results for: specific emitter identification

1807 Humor Roles of Females in a Product Color Matrix

Authors: Jin-Tsann Yeh, Chyong-Ling Lin

Abstract:

Healthcare providers sometimes use the power of humor as a treatment and therapy for buffering mental health or easing mental disorders because humor can provide relief from distress and conflict. Humor is also very suitable for advertising because of similar benefits. This study carefully examines humor's widespread use in advertising and identifies relationships among humor mechanisms, female depictions, and product types. The purpose is to conceptualize how humor theories can be used not only to successfully define a product as fitting within one of four color categories of the product color matrix, but also to identify compelling contemporary female depictions through humor in ads. The results can offer an idealization for marketing managers and consumers to help them understand how female role depictions can be effectively used with humor in ads. The four propositions developed herein are derived from related literature, through the identification of marketing strategy formulations that achieve product memory enhancement by adopting humor mechanisms properly matched with female role depictions.

Keywords: Humor mechanisms, Female role depiction, Product types.

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1806 Low Dimensional Representation of Dorsal Hand Vein Features Using Principle Component Analysis (PCA)

Authors: M.Heenaye-Mamode Khan, R.K. Subramanian, N. A. Mamode Khan

Abstract:

The quest of providing more secure identification system has led to a rise in developing biometric systems. Dorsal hand vein pattern is an emerging biometric which has attracted the attention of many researchers, of late. Different approaches have been used to extract the vein pattern and match them. In this work, Principle Component Analysis (PCA) which is a method that has been successfully applied on human faces and hand geometry is applied on the dorsal hand vein pattern. PCA has been used to obtain eigenveins which is a low dimensional representation of vein pattern features. Low cost CCD cameras were used to obtain the vein images. The extraction of the vein pattern was obtained by applying morphology. We have applied noise reduction filters to enhance the vein patterns. The system has been successfully tested on a database of 200 images using a threshold value of 0.9. The results obtained are encouraging.

Keywords: Biometric, Dorsal vein pattern, PCA.

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1805 Islamic Finance: What Is the Outlook for Italy?

Authors: Paolo Pietro Biancone

Abstract:

The spread of Islamic financial instruments is an opportunity to offer integration for the immigrant population and to attract, through the specific products, the richness of sovereign funds from the "Arab" countries. However, it is important to consider the possibility of comparing a traditional finance model, which in recent times has given rise to many doubts, with an "alternative" finance model, where the ethical aspect arising from religious principles is very important.

Keywords: Banks, Europe, Islamic Finance, Italy.

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1804 The Impact of the Economic Crises over Management Marketing Strategies of Romanian B2B Companies

Authors: S. C. Căescu, I. Dumitru

Abstract:

The main objective of the paper has been represented by the identification of the changes that occurred in the competitive environment and their impact on the strategic marketing management of companies in B2B market. At Romania-s level there has not yet been done a similar research that studies change management in crises on business to business field. In order to answer to the paper-s objectives, a qualitative marketing research (in-depth structured interview) was conducted, within the top management of 27 companies in Romanian business to business field. The main results of the research highlight the necessity of a management of change, as a result of the crises, as follows: changes in the corporate objectives (from development objectives to maintaining objectives), changes market segmentation and in competitive advantages, changes at the level of market strategies and of the marketing mix.

Keywords: change management, competitive environment, marketing management strategies, strategic marketing.

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1803 Towards a Systematic Evaluation of Web Design

Authors: Ivayla Trifonova, Naoum Jamous, Holger Schrödl

Abstract:

A good web design is a prerequisite for a successful business nowadays, especially since the internet is the most common way for people to inform themselves. Web design includes the optical composition, the structure, and the user guidance of websites. The importance of each website leads to the question if there is a way to measure its usefulness. The aim of this paper is to suggest a methodology for the evaluation of web design. The desired outcome is to have an evaluation that is concentrated on a specific website and its target group.

Keywords: Evaluation methodology, factor analysis, target group, web design.

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1802 Application of Data Envelopment Analysis and Performance Indicators to Irrigation Systems in Thessaloniki Plain (Greece)

Authors: Ntantos P.N, Karpouzos D.K

Abstract:

In this paper, a benchmarking framework is presented for the performance assessment of irrigations systems. Firstly, a data envelopment analysis (DEA) is applied to measure the technical efficiency of irrigation systems. This method, based on linear programming, aims to determine a consistent efficiency ranking of irrigation systems in which known inputs, such as water volume supplied and total irrigated area, and a given output corresponding to the total value of irrigation production are taken into account simultaneously. Secondly, in order to examine the irrigation efficiency in more detail, a cross – system comparison is elaborated using a performance indicators set selected by IWMI. The above methodologies were applied in Thessaloniki plain, located in Northern Greece while the results of the application are presented and discussed. The conjunctive use of DEA and performance indicators seems to be a very useful tool for efficiency assessment and identification of best practices in irrigation systems management.

Keywords: Benchmarking, D.E.A, Performance Indicators, Irrigation systems.

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1801 Identification of Phenolic Contents in Malaysian Variety of Pummelo (Citrus Grandis L. Osbeck) Fruit Juice Using HPLC-DAD

Authors: N. N. A. K. Shah, R. A. Rahman, R. Shamsuddin, N. M. Adzahan

Abstract:

Pummelo is known to be the largest of all citrus fruits, with expected ratio of 2:1 (w/v) of producing juice, is an attractive opportunity for Malaysia to expand pummelo-s influence and marketability over the international market of juices. The purpose of this study is to identify and quantify the phenolic compounds in two Malaysian varieties of pummelo fruit juice: Ledang (PO55) and Tambun (PO52). Identifications of polyphenols composition were done using High Performance Liquid Chromatography Diode Array Detection (HPLC-DAD). The phenolic compounds that were found in both varieties were hydroxycinnamic acids and flavonones. This study proved that Tambun variety has the highest antioxidant and phenolic compounds in comparison to Ledang variety. However, considerations have to be made to suit consumer-s taste bud and the amount of enzyme needed to clarify the juice for its marketability.

Keywords: Antioxidant, HPLC, phenolic contents and pummelo fruit juice

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1800 Correlation-based Feature Selection using Ant Colony Optimization

Authors: M. Sadeghzadeh, M. Teshnehlab

Abstract:

Feature selection has recently been the subject of intensive research in data mining, specially for datasets with a large number of attributes. Recent work has shown that feature selection can have a positive effect on the performance of machine learning algorithms. The success of many learning algorithms in their attempts to construct models of data, hinges on the reliable identification of a small set of highly predictive attributes. The inclusion of irrelevant, redundant and noisy attributes in the model building process phase can result in poor predictive performance and increased computation. In this paper, a novel feature search procedure that utilizes the Ant Colony Optimization (ACO) is presented. The ACO is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by considering both local heuristics and previous knowledge. When applied to two different classification problems, the proposed algorithm achieved very promising results.

Keywords: Ant colony optimization, Classification, Datamining, Feature selection.

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1799 Evaluation of Internet Anxiety in SRBIAU Higher Education Students in Research Process

Authors: Nima Babazadeh Gashti, Nazanin Pilevari

Abstract:

Increase in using internet makes some problems that one of them is "internet anxiety". Internet anxiety is a type of anxious that people may feel during surfing internet or using internet for their educational purpose, blogging or streaming to digital libraries. The goal of this study is evaluating of internet anxiety among the management students. In this research Ealy's internet anxiety questionnaire, consists of positive and negative items, is completed by 310 participants. According to the findings, about 64.7% of them were equal or below to mean anxiety score (50). The distribution of internet anxiety scores was normal and there was no meaningful difference between men-s and women's anxiety level in this sample. Results also showed that there is no meaningful difference of internet anxiety level between different fields of study in Management. This evaluation will help managers to perform gap analysis between the existent level and the desired one. Future work would be providing techniques for abating human anxiety while using internet via human computer interaction techniques.

Keywords: Internet, anxiety, research process, internet identification, human computer interaction.

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1798 Diagnosis on Environmental Impacts of Tourism at Caju Beach in Palmas, Tocantins, Brazil

Authors: Mary L. G. S. Senna, Veruska, C. Dutra, Jr., Keity L. F. Oliveira, Patrícia A. Santos, Alana C. M. Santana

Abstract:

Environmental impacts are the changes in the physical, chemical or biological properties of natural areas that are most often caused by human actions on the environment and which have consequences for human health, society and the elements of nature. The identification of the environmental impacts is important so that they are mitigated, and above all that the mitigating measures are applied in the area. This work aims to identify the environmental impacts generated in the Praia do Caju area in the city of Palmas/Brazil and show that the lack of structure on the beach intensifies the environmental impacts. The present work was carried out having as parameter, the typologies of exploratory and descriptive and quantitative research through a matrix of environmental impacts through direct observation and registration. The study took place during the holidays from August to December 2016 and photographic record of impacts. From the collected data it was possible to verify that Caju beach suffers constant degradation due to irregular deposition.

Keywords: Leisure, tourism, environmental impacts, Brazil.

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1797 Neural Network-Based Control Strategies Applied to a Fed-Batch Crystallization Process

Authors: P. Georgieva, S. Feyo de Azevedo

Abstract:

This paper is focused on issues of process modeling and two model based control strategies of a fed-batch sugar crystallization process applying the concept of artificial neural networks (ANNs). The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. Two control alternatives are considered – model predictive control (MPC) and feedback linearizing control (FLC). Adequate ANN process models are first built as part of the controller structures. MPC algorithm outperforms the FLC approach with respect to satisfactory reference tracking and smooth control action. However, the MPC is computationally much more involved since it requires an online numerical optimization, while for the FLC an analytical control solution was determined.

Keywords: artificial neural networks, nonlinear model control, process identification, crystallization process

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1796 Identification of the Key Sustainability Issues to Develop New Decision Support Tools in the Spanish Furniture Sector

Authors: P.Cordero, R.Poler, R.Sanchis

Abstract:

The environmental impacts caused by the current production and consumption models, together with the impact that the current economic crisis, bring necessary changes in the European industry toward new business models based on sustainability issues that could allow them to innovate and improve their competitiveness. This paper analyzes the key environmental issues and the current and future market trends in one of the most important industrial sectors in Spain, the furniture sector. It also proposes new decision support tools -diagnostic kit, roadmap and guidelines- to guide companies to implement sustainability criteria into their organizations, including eco-design strategies and other economical and social strategies in accordance with the sustainability definition, and other available tools such as eco-labels, environmental management systems, etc., and to use and combine them to obtain the results the company expects to help improve its competitiveness.

Keywords: Furniture sector, eco-design, sustainability, economical crisis, market trends, roadmap

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1795 The Use of Classifiers in Image Analysis of Oil Wells Profiling Process and the Automatic Identification of Events

Authors: Jaqueline M. R. Vieira

Abstract:

Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge dataset configurations.

Keywords: Brazil, classifiers, data-mining, Image Segmentation, oil well visualization, classifiers.

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1794 A Novel Method for Non-Invasive Diagnosis of Hepatitis C Virus Using Electromagnetic Signal Detection: A Multicenter International Study

Authors: Gamal Shiha, Waleed Samir, Zahid Azam, Premashis Kar, Saeed Hamid, Shiv Sarin

Abstract:

A simple, rapid and non-invasive electromagnetic sensor (C-FAST device) was- patented; for diagnosis of HCV RNA. Aim: To test the validity of the device compared to standard HCV PCR. Subjects and Methods: The first phase was done as pilot in Egypt on 79 participants; the second phase was done in five centers: one center from Egypt, two centers from Pakistan and two centers from India (800, 92 and 113 subjects respectively). The third phase was done nationally as multicenter study on (1600) participants for ensuring its representativeness. Results: When compared to PCR technique, C-FAST device revealed sensitivity 95% to 100%, specificity 95.5% to 100%, PPV 89.5% to 100%, NPV 95% to 100% and positive likelihood ratios 21.8% to 38.5%. Conclusion: It is practical evidence that HCV nucleotides emit electromagnetic signals that can be used for its identification. As compared to PCR, C-FAST is an accurate, valid and non-invasive device.

Keywords: C-FAST- a valid and reliable device, Distant cellular interaction, Electromagnetic signal detection, Non-invasive diagnosis of HCV.

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1793 Optimization Study of Adsorption of Nickel(II) on Bentonite

Authors: B. Medjahed, M. A. Didi, B. Guezzen

Abstract:

This work concerns with the experimental study of the adsorption of the Ni(II) on bentonite. The effects of various parameters such as contact time, stirring rate, initial concentration of Ni(II), masse of clay, initial pH of aqueous solution and temperature on the adsorption yield, were carried out. The study of the effect of the ionic strength on the yield of adsorption was examined by the identification and the quantification of the present chemical species in the aqueous phase containing the metallic ion Ni(II). The adsorbed species were investigated by a calculation program using CHEAQS V. L20.1 in order to determine the relation between the percentages of the adsorbed species and the adsorption yield. The optimization process was carried out using 23 factorial designs. The individual and combined effects of three process parameters, i.e. initial Ni(II) concentration in aqueous solution (2.10−3 and 5.10−3 mol/L), initial pH of the solution (2 and 6.5), and mass of bentonite (0.03 and 0.3 g) on Ni(II) adsorption, were studied.

Keywords: Adsorption, bentonite, factorial design, Nickel(II).

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1792 Identification of Key Parameters for Benchmarking of Combined Cycle Power Plants Retrofit

Authors: S. Sabzchi Asl, N. Tahouni, M. H. Panjeshahi

Abstract:

Benchmarking of a process with respect to energy consumption, without accomplishing a full retrofit study, can save both engineering time and money. In order to achieve this goal, the first step is to develop a conceptual-mathematical model that can easily be applied to a group of similar processes. In this research, we have aimed to identify a set of key parameters for the model which is supposed to be used for benchmarking of combined cycle power plants. For this purpose, three similar combined cycle power plants were studied. The results showed that ambient temperature, pressure and relative humidity, number of HRSG evaporator pressure levels and relative power in part load operation are the main key parameters. Also, the relationships between these parameters and produced power (by gas/ steam turbine), gas turbine and plant efficiency, temperature and mass flow rate of the stack flue gas were investigated.

Keywords: Combined cycle power plant, energy benchmarking, modelling, Retrofit.

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1791 A Practical Construction Technique to Enhance the Performance of Rock Bolts in Tunnels

Authors: O. Chaudhari, A. N. Ghafar, G. Zirgulis, M. Mousavi, T. Ellison, S. Pousette, P. Fontana

Abstract:

In Swedish tunnel construction, a critical issue that has been repeatedly acknowledged is corrosion and, consequently, failure of the rock bolts in rock support systems. The defective installation of rock bolts results in the formation of cavities in the cement mortar that is regularly used to fill the area under the dome plates. These voids allow for water-ingress to the rock bolt assembly, which results in corrosion of rock bolt components and eventually failure. In addition, the current installation technique consists of several manual steps with intense labor works that are usually done in uncomfortable and exhausting conditions, e.g., under the roof of the tunnels. Such intense tasks also lead to a considerable waste of materials and execution errors. Moreover, adequate quality control of the execution is hardly possible with the current technique. To overcome these issues, a non-shrinking/expansive cement-based mortar filled in the paper packaging has been developed in this study which properly fills the area under the dome plates without or with the least remaining cavities, ultimately that diminishes the potential of corrosion. This article summarizes the development process and the experimental evaluation of this technique for the installation of rock bolts. In the development process, the cementitious mortar was first developed using specific cement and shrinkage reducing/expansive additives. The mechanical and flow properties of the mortar were then evaluated using compressive strength, density, and slump flow measurement methods. In addition, isothermal calorimetry and shrinkage/expansion measurements were used to elucidate the hydration and durability attributes of the mortar. After obtaining the desired properties in both fresh and hardened conditions, the developed dry mortar was filled in specific permeable paper packaging and then submerged in water bath for specific intervals before the installation. The tests were enhanced progressively by optimizing different parameters such as shape and size of the packaging, characteristics of the paper used, immersion time in water and even some minor characteristics of the mortar. Finally, the developed prototype was tested in a lab-scale rock bolt assembly with various angles to analyze the efficiency of the method in real life scenario. The results showed that the new technique improves the performance of the rock bolts by reducing the material wastage, improving environmental performance, facilitating and accelerating the labor works, and finally enhancing the durability of the whole system. Accordingly, this approach provides an efficient alternative for the traditional way of tunnel bolt installation with considerable advantages for the Swedish tunneling industry.

Keywords: corrosion, durability, mortar, rock bolt

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1790 An Experimental Comparison of Unsupervised Learning Techniques for Face Recognition

Authors: Dinesh Kumar, C.S. Rai, Shakti Kumar

Abstract:

Face Recognition has always been a fascinating research area. It has drawn the attention of many researchers because of its various potential applications such as security systems, entertainment, criminal identification etc. Many supervised and unsupervised learning techniques have been reported so far. Principal Component Analysis (PCA), Self Organizing Maps (SOM) and Independent Component Analysis (ICA) are the three techniques among many others as proposed by different researchers for Face Recognition, known as the unsupervised techniques. This paper proposes integration of the two techniques, SOM and PCA, for dimensionality reduction and feature selection. Simulation results show that, though, the individual techniques SOM and PCA itself give excellent performance but the combination of these two can also be utilized for face recognition. Experimental results also indicate that for the given face database and the classifier used, SOM performs better as compared to other unsupervised learning techniques. A comparison of two proposed methodologies of SOM, Local and Global processing, shows the superiority of the later but at the cost of more computational time.

Keywords: Face Recognition, Principal Component Analysis, Self Organizing Maps, Independent Component Analysis

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1789 Study on the Electrochemical Performance of Graphene Effect on Cadmium Oxide in Lithium Battery

Authors: Atef Y. Shenouda, Anton A. Momchilov

Abstract:

Graphene and CdO with different stoichiometric ratios of Cd(CH₃COO)₂ and graphene samples were prepared by hydrothermal reaction. The crystalline phases of pure CdO and 3CdO:1graphene were identified by X-ray diffraction (XRD). The particle morphology was studied with SEM. Furthermore, impedance measurements were applied. Galvanostatic measurements for the cells were carried out using potential limits between 0.01 and 3 V vs. Li/Li⁺. The current cycling intensity was 10⁻⁴ A. The specific discharge capacity of 3CdO-1G cell was about 450 Ah.Kg⁻¹ up to more than 100 cycles.

Keywords: CdO, graphene, negative electrode, lithium battery.

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1788 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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1787 Regionalism and Regionalization in Central Asia

Authors: L. Delovarova, A. Davar, S. Asanov, F. Kukeyeva

Abstract:

This article is dedicated to the question of regionalism and regionalization in contemporary international relations, with a specific focus on Central Asia. The article addresses the question of whether or not Central Asia can be referred to as a true geopolitical region. In addressing this question, the authors examine particular factors that are essential for the formation of a region, including those tied to the economy, energy, culture, and labor migration.

Keywords: Central Asia, integration, regionalization, regionalism.

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1786 Multi-View Neural Network Based Gait Recognition

Authors: Saeid Fazli, Hadis Askarifar, Maryam Sheikh Shoaie

Abstract:

Human identification at a distance has recently gained growing interest from computer vision researchers. Gait recognition aims essentially to address this problem by identifying people based on the way they walk [1]. Gait recognition has 3 steps. The first step is preprocessing, the second step is feature extraction and the third one is classification. This paper focuses on the classification step that is essential to increase the CCR (Correct Classification Rate). Multilayer Perceptron (MLP) is used in this work. Neural Networks imitate the human brain to perform intelligent tasks [3].They can represent complicated relationships between input and output and acquire knowledge about these relationships directly from the data [2]. In this paper we apply MLP NN for 11 views in our database and compare the CCR values for these views. Experiments are performed with the NLPR databases, and the effectiveness of the proposed method for gait recognition is demonstrated.

Keywords: Human motion analysis, biometrics, gait recognition, principal component analysis, MLP neural network.

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1785 A Temporal QoS Ontology for ERTMS/ETCS

Authors: Marc Sango, Olimpia Hoinaru, Christophe Gransart, Laurence Duchien

Abstract:

Ontologies offer a means for representing and sharing information in many domains, particularly in complex domains. For example, it can be used for representing and sharing information of System Requirement Specification (SRS) of complex systems like the SRS of ERTMS/ETCS written in natural language. Since this system is a real-time and critical system, generic ontologies, such as OWL and generic ERTMS ontologies provide minimal support for modeling temporal information omnipresent in these SRS documents. To support the modeling of temporal information, one of the challenges is to enable representation of dynamic features evolving in time within a generic ontology with a minimal redesign of it. The separation of temporal information from other information can help to predict system runtime operation and to properly design and implement them. In addition, it is helpful to provide a reasoning and querying techniques to reason and query temporal information represented in the ontology in order to detect potential temporal inconsistencies. To address this challenge, we propose a lightweight 3-layer temporal Quality of Service (QoS) ontology for representing, reasoning and querying over temporal and non-temporal information in a complex domain ontology. Representing QoS entities in separated layers can clarify the distinction between the non QoS entities and the QoS entities in an ontology. The upper generic layer of the proposed ontology provides an intuitive knowledge of domain components, specially ERTMS/ETCS components. The separation of the intermediate QoS layer from the lower QoS layer allows us to focus on specific QoS Characteristics, such as temporal or integrity characteristics. In this paper, we focus on temporal information that can be used to predict system runtime operation. To evaluate our approach, an example of the proposed domain ontology for handover operation, as well as a reasoning rule over temporal relations in this domain-specific ontology, are presented.

Keywords: System Requirement Specification, ERTMS/ETCS, Temporal Ontologies, Domain Ontologies.

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1784 Identification of Reusable Software Modules in Function Oriented Software Systems using Neural Network Based Technique

Authors: Sonia Manhas, Parvinder S. Sandhu, Vinay Chopra, Nirvair Neeru

Abstract:

The cost of developing the software from scratch can be saved by identifying and extracting the reusable components from already developed and existing software systems or legacy systems [6]. But the issue of how to identify reusable components from existing systems has remained relatively unexplored. We have used metric based approach for characterizing a software module. In this present work, the metrics McCabe-s Cyclometric Complexity Measure for Complexity measurement, Regularity Metric, Halstead Software Science Indicator for Volume indication, Reuse Frequency metric and Coupling Metric values of the software component are used as input attributes to the different types of Neural Network system and reusability of the software component is calculated. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE).

Keywords: Software reusability, Neural Networks, MAE, RMSE, Accuracy.

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1783 Computer-aided Lenke Classification of Scoliotic Spines

Authors: Neila Mezghani, Philippe Phan, Hubert Labelle, Carl Eric Aubin, Jacques de Guise

Abstract:

The identification and classification of the spine deformity play an important role when considering surgical planning for adolescent patients with idiopathic scoliosis. The subject of this article is the Lenke classification of scoliotic spines using Cobb angle measurements. The purpose is two-fold: (1) design a rulebased diagram to assist clinicians in the classification process and (2) investigate a computer classifier which improves the classification time and accuracy. The rule-based diagram efficiency was evaluated in a series of scoliotic classifications by 10 clinicians. The computer classifier was tested on a radiographic measurement database of 603 patients. Classification accuracy was 93% using the rule-based diagram and 99% for the computer classifier. Both the computer classifier and the rule based diagram can efficiently assist clinicians in their Lenke classification of spine scoliosis.

Keywords: Scoliosis, Lenke model, decision-rules, computer aided classifier.

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1782 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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1781 Magnesium Borate Synthesis by Microwave Method Using MgCl2.6H2O and H3BO3

Authors: A. S. Kipcak, P. Gurses, K. Kunt, E. Moroydor Derun, S. Piskin

Abstract:

There are many kinds of metal borates found not only in nature but also synthesized in the laboratory such as magnesium borates. Due to its excellent properties, as remarkable ceramic materials, they have also application areas in anti-wear and friction reducing additives as well as electro-conductive treating agents. The synthesis of magnesium borate powders can be fulfilled simply with two different methods, hydrothermal and thermal synthesis. Microwave assisted method, also another way of producing magnesium borate, can be classified into thermal synthesis because of using the principles of solid state synthesis. It also contributes producing particles with small size and high purity in nano-size material synthesize. In this study the production of magnesium borates, are aimed using MgCl2.6H2O and H3BO3. The identification of both starting materials and products were made by the equipments of, X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR). After several synthesis steps magnesium borates were synthesized and characterized by XRD and FT-IR, as well.

Keywords: FT-IR, magnesium borates, microwave method, XRD.

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1780 Inverse Problem Methodology for the Measurement of the Electromagnetic Parameters Using MLP Neural Network

Authors: T. Hacib, M. R. Mekideche, N. Ferkha

Abstract:

This paper presents an approach which is based on the use of supervised feed forward neural network, namely multilayer perceptron (MLP) neural network and finite element method (FEM) to solve the inverse problem of parameters identification. The approach is used to identify unknown parameters of ferromagnetic materials. The methodology used in this study consists in the simulation of a large number of parameters in a material under test, using the finite element method (FEM). Both variations in relative magnetic permeability and electrical conductivity of the material under test are considered. Then, the obtained results are used to generate a set of vectors for the training of MLP neural network. Finally, the obtained neural network is used to evaluate a group of new materials, simulated by the FEM, but not belonging to the original dataset. Noisy data, added to the probe measurements is used to enhance the robustness of the method. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.

Keywords: Inverse problem, MLP neural network, parametersidentification, FEM.

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1779 Using Ontology Search in the Design of Class Diagram from Business Process Model

Authors: Wararat Rungworawut, Twittie Senivongse

Abstract:

Business process model describes process flow of a business and can be seen as the requirement for developing a software application. This paper discusses a BPM2CD guideline which complements the Model Driven Architecture concept by suggesting how to create a platform-independent software model in the form of a UML class diagram from a business process model. An important step is the identification of UML classes from the business process model. A technique for object-oriented analysis called domain analysis is borrowed and key concepts in the business process model will be discovered and proposed as candidate classes for the class diagram. The paper enhances this step by using ontology search to help identify important classes for the business domain. As ontology is a source of knowledge for a particular domain which itself can link to ontologies of related domains, the search can give a refined set of candidate classes for the resulting class diagram.

Keywords: Business Process Model, Model DrivenArchitecture, Ontology, UML Class Diagram.

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1778 Extensions to Some AOSE Methodologies

Authors: Louay M. Jeroudaih, Mohamed S. Hajji

Abstract:

This paper looks into areas not covered by prominent Agent-Oriented Software Engineering (AOSE) methodologies. Extensive paper review led to the identification of two issues, first most of these methodologies almost neglect semantic web and ontology. Second, as expected, each one has its strength and weakness and may focus on some phases of the development lifecycle but not all of the phases. The work presented here builds extensions to a highly regarded AOSE methodology (MaSE) in order to cover the areas that this methodology does not concentrate on. The extensions include introducing an ontology stage for semantic representation and integrating early requirement specification from a methodology which mainly focuses on that. The integration involved developing transformation rules (with the necessary handling of nonmatching notions) between the two sets of representations and building the software which automates the transformation. The application of this integration on a case study is also presented in the paper. The main flow of MaSE stages was changed to smoothly accommodate the new additions.

Keywords: Agents, Intelligent Agents, Software Engineering(SE), UML, AUML, and Design Patterns.

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