Search results for: biometric identification.
393 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
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2345392 Correlation-based Feature Selection using Ant Colony Optimization
Authors: M. Sadeghzadeh, M. Teshnehlab
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2411391 Evaluation of Internet Anxiety in SRBIAU Higher Education Students in Research Process
Authors: Nima Babazadeh Gashti, Nazanin Pilevari
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2030390 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 724389 Neural Network-Based Control Strategies Applied to a Fed-Batch Crystallization Process
Authors: P. Georgieva, S. Feyo de Azevedo
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1824388 Identification of the Key Sustainability Issues to Develop New Decision Support Tools in the Spanish Furniture Sector
Authors: P.Cordero, R.Poler, R.Sanchis
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1504387 The Use of Classifiers in Image Analysis of Oil Wells Profiling Process and the Automatic Identification of Events
Authors: Jaqueline M. R. Vieira
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2536386 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18031385 Optimization Study of Adsorption of Nickel(II) on Bentonite
Authors: B. Medjahed, M. A. Didi, B. Guezzen
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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).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 919384 Identification of Key Parameters for Benchmarking of Combined Cycle Power Plants Retrofit
Authors: S. Sabzchi Asl, N. Tahouni, M. H. Panjeshahi
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1690383 An Experimental Comparison of Unsupervised Learning Techniques for Face Recognition
Authors: Dinesh Kumar, C.S. Rai, Shakti Kumar
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1871382 An Approach to Concerns and Aspects Mining for Web Applications
Authors: Carlo Bellettini, Alessandro Marchetto, Andrea Trentini
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1500381 Crude Distillation Process Simulation Using Unisim Design Simulator
Authors: C. Patrascioiu, M. Jamali
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The paper deals with the simulation of the crude distillation process using the Unisim Design simulator. The necessity of simulating this process is argued both by considerations related to the design of the crude distillation column, but also by considerations related to the design of advanced control systems. In order to use the Unisim Design simulator to simulate the crude distillation process, the identification of the simulators used in Romania and an analysis of the PRO/II, HYSYS, and Aspen HYSYS simulators were carried out. Analysis of the simulators for the crude distillation process has allowed the authors to elaborate the conclusions of the success of the crude modelling. A first aspect developed by the authors is the implementation of specific problems of petroleum liquid-vapors equilibrium using Unisim Design simulator. The second major element of the article is the development of the methodology and the elaboration of the simulation program for the crude distillation process, using Unisim Design resources. The obtained results validate the proposed methodology and will allow dynamic simulation of the process.
Keywords: Crude oil, distillation, simulation, Unisim Design, simulators.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2676380 Multi-View Neural Network Based Gait Recognition
Authors: Saeid Fazli, Hadis Askarifar, Maryam Sheikh Shoaie
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2095379 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1860378 Computer-aided Lenke Classification of Scoliotic Spines
Authors: Neila Mezghani, Philippe Phan, Hubert Labelle, Carl Eric Aubin, Jacques de Guise
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1627377 Multi-Dimensional Concerns Mining for Web Applications via Concept-Analysis
Authors: Carlo Bellettini, Alessandro Marchetto, Andrea Trentini
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1461376 Magnesium Borate Synthesis by Microwave Method Using MgCl2.6H2O and H3BO3
Authors: A. S. Kipcak, P. Gurses, K. Kunt, E. Moroydor Derun, S. Piskin
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2545375 Inverse Problem Methodology for the Measurement of the Electromagnetic Parameters Using MLP Neural Network
Authors: T. Hacib, M. R. Mekideche, N. Ferkha
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1749374 Using Ontology Search in the Design of Class Diagram from Business Process Model
Authors: Wararat Rungworawut, Twittie Senivongse
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2461373 Extensions to Some AOSE Methodologies
Authors: Louay M. Jeroudaih, Mohamed S. Hajji
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1878372 Estimation of the External Force for a Co-Manipulation Task Using the Drive Chain Robot
Authors: Sylvain Devie, Pierre-Philippe Robet, Yannick Aoustin, Maxime Gautier
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The aim of this paper is to show that the observation of the external effort and the sensor-less control of a system is limited by the mechanical system. First, the model of a one-joint robot with a prismatic joint is presented. Based on this model, two different procedures were performed in order to identify the mechanical parameters of the system and observe the external effort applied on it. Experiments have proven that the accuracy of the force observer, based on the DC motor current, is limited by the mechanics of the robot. The sensor-less control will be limited by the accuracy in estimation of the mechanical parameters and by the maximum static friction force, that is the minimum force which can be observed in this case. The consequence of this limitation is that industrial robots without specific design are not well adapted to perform sensor-less precision tasks. Finally, an efficient control law is presented for high effort applications.Keywords: Control, Identification, Robot, Co-manipulation, Sensor-less.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 632371 Attachment Styles of Children Raised in Nursery vs. Those Who are Raised in the Family in Iran
Authors: Narges Razeghi
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In studies on psychological health and children-s personality development and in researches on emotional distresses, children-s behavioral disorders associated with mother deprivation, are known as the major cause of mental disorders. Therefore, for identification of children-s attachment styles in nursery-s children are of significant importance. For this purpose, to compare the attachment styles between children of nursery with those provided care by their families, the Separation Anxiety Test (SAT) of Slough and et al was administered on 72 children (36 in nursery and 36 family-cared). The results indicated, almost half of children in both groups have insecure attachment styles. Tendency ratio of both groups of children towards Secure and Ambivalent Insecure styles are almost the same. However the avoidant style of attachment in children of nursery is more than those provided care by their families. The children under family care compared to the children of nursery, in the situations of separation from their mothers in the first day of school and sleeping in their room, have shown more self reliance.
Keywords: Attachment style, Separation Anxiety Test (SAT), Children, Nursery, Emotional and Behavioral Disorders
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1865370 Formation of Civic Identity in the Process of Globalization: The Example of the U.S.A. and Kazakhstan
Authors: Elnura Assyltayeva, Zhanar Aldubasheva, Zhengisbek Tolen
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An attempt has been made several times to identify and discuss the U.S. experience on the formation of political nation in political science. The purpose of this research paper is to identify the main aspects of the formation of civic identity in the United States and Kazakhstan, through the identification of similarities and differences that can get practical application in making decisions of national policy issues in the context of globalization, as well as to answer the questions “What should unite the citizens of Kazakhstan to the nation?" and “What should be the dominant identity: civil or ethnic (national) one?" Can Kazakhstan being multiethnic country like America, adopt its experience in the formation of a civic nation? Since it is believed that the “multi-ethnic state of the population is a characteristic feature of most modern countries in the world," it states that “inter-ethnic integration is one of the most important aspects of the problem of forming a new social community (metaetnic - Kazakh people, Kazakh nation" [1].Keywords: nation, civic identity, nation building, globalization, interethnic relations, patriotism
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2223369 Simulating Discrete Time Model Reference Adaptive Control System with Great Initial Error
Authors: Bubaker M. F. Bushofa, Abdel Hafez A. Azab
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This article is based on the technique which is called Discrete Parameter Tracking (DPT). First introduced by A. A. Azab [8] which is applicable for less order reference model. The order of the reference model is (n-l) and n is the number of the adjustable parameters in the physical plant. The technique utilizes a modified gradient method [9] where the knowledge of the exact order of the nonadaptive system is not required, so, as to eliminate the identification problem. The applicability of the mentioned technique (DPT) was examined through the solution of several problems. This article introduces the solution of a third order system with three adjustable parameters, controlled according to second order reference model. The adjustable parameters have great initial error which represent condition. Computer simulations for the solution and analysis are provided to demonstrate the simplicity and feasibility of the technique.Keywords: Adaptive Control System, Discrete Parameter Tracking, Discrete Time Model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1056368 Preservation of Artistic Heritage: Effect of Modernization on Antiquities and Traditional Murals in Nigeria
Authors: Uchenna Bella Onu
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Traditional art is one of Nigerian cultural heritage. It is an excellent instrument for documentation and identification. Antiquities are priceless and irreplaceable. They are basically preserved for future generations. Sadly, preserving these highly prized cultural heritage is becoming a serious challenge. This paper examines the extent modernization has affected the preservation of traditional art in Nigeria. Particularly hit is the antiquities and traditional murals of eastern part of Nigeria. Participatory visual methods were used for this study. Efforts were made to reach the few surviving and aged mural artists. Oral information was collected from them as well as first hand drawings and some photographs of their works. Findings indicate that modernization has seriously affected the preservation of Nigerian artistic heritage. Further findings show that traditional mural artists are gradually dwindling and dangerously going into extinct. Antiquities are indiscriminately destroyed due to sheer ignorance and the blind quest to fit into the so called modern world.
Keywords: Antiquities, artistic heritage, cultural preservation, drawings, modernization, murals.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1432367 Decision Tree for Competing Risks Survival Probability in Breast Cancer Study
Authors: N. A. Ibrahim, A. Kudus, I. Daud, M. R. Abu Bakar
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Competing risks survival data that comprises of more than one type of event has been used in many applications, and one of these is in clinical study (e.g. in breast cancer study). The decision tree method can be extended to competing risks survival data by modifying the split function so as to accommodate two or more risks which might be dependent on each other. Recently, researchers have constructed some decision trees for recurrent survival time data using frailty and marginal modelling. We further extended the method for the case of competing risks. In this paper, we developed the decision tree method for competing risks survival time data based on proportional hazards for subdistribution of competing risks. In particular, we grow a tree by using deviance statistic. The application of breast cancer data is presented. Finally, to investigate the performance of the proposed method, simulation studies on identification of true group of observations were executed.Keywords: Competing risks, Decision tree, Simulation, Subdistribution Proportional Hazard.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2365366 Quantification of Heart Rate Variability: A Measure based on Unique Heart Rates
Authors: V. I. Thajudin Ahamed, P. Dhanasekaran, A. Naseem, N. G. Karthick, T. K. Abdul Jaleel, Paul K.Joseph
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It is established that the instantaneous heart rate (HR) of healthy humans keeps on changing. Analysis of heart rate variability (HRV) has become a popular non invasive tool for assessing the activities of autonomic nervous system. Depressed HRV has been found in several disorders, like diabetes mellitus (DM) and coronary artery disease, characterised by autonomic nervous dysfunction. A new technique, which searches for pattern repeatability in a time series, is proposed specifically for the analysis of heart rate data. These set of indices, which are termed as pattern repeatability measure and pattern repeatability ratio are compared with approximate entropy and sample entropy. In our analysis, based on the method developed, it is observed that heart rate variability is significantly different for DM patients, particularly for patients with diabetic foot ulcer.
Keywords: Autonomic nervous system, diabetes mellitus, heart rate variability, pattern identification, sample entropy
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1898365 Identification of Healthy and BSR-Infected Oil Palm Trees Using Color Indices
Authors: Siti Khairunniza-Bejo, Yusnida Yusoff, Nik Salwani Nik Yusoff, Idris Abu Seman, Mohamad Izzuddin Anuar
Abstract:
Most of the oil palm plantations have been threatened by Basal Stem Rot (BSR) disease which causes serious economic impact. This study was conducted to identify the healthy and BSRinfected oil palm tree using thirteen color indices. Multispectral and thermal camera was used to capture 216 images of the leaves taken from frond number 1, 9 and 17. Indices of normalized difference vegetation index (NDVI), red (R), green (G), blue (B), near infrared (NIR), green – blue (GB), green/blue (G/B), green – red (GR), green/red (G/R), hue (H), saturation (S), intensity (I) and thermal index (T) were used. From this study, it can be concluded that G index taken from frond number 9 is the best index to differentiate between the healthy and BSR-infected oil palm trees. It not only gave high value of correlation coefficient (R=-0.962), but also high value of separation between healthy and BSR-infected oil palm tree. Furthermore, power and S model developed using G index gave the highest R2 value which is 0.985.Keywords: Oil palm, image processing, disease, leaves.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2950364 A Fast Adaptive Tomlinson-Harashima Precoder for Indoor Wireless Communications
Authors: M. Naresh Kumar, Abhijit Mitra, C. Ardil
Abstract:
A fast adaptive Tomlinson Harashima (T-H) precoder structure is presented for indoor wireless communications, where the channel may vary due to rotation and small movement of the mobile terminal. A frequency-selective slow fading channel which is time-invariant over a frame is assumed. In this adaptive T-H precoder, feedback coefficients are updated at the end of every uplink frame by using system identification technique for channel estimation in contrary with the conventional T-H precoding concept where the channel is estimated during the starting of the uplink frame via Wiener solution. In conventional T-H precoder it is assumed the channel is time-invariant in both uplink and downlink frames. However assuming the channel is time-invariant over only one frame instead of two, the proposed adaptive T-H precoder yields better performance than conventional T-H precoder if the channel is varied in uplink after receiving the training sequence.
Keywords: Tomlinson-Harashima precoder, Adaptive channel estimation, Indoor wireless communication, Bit error rate.
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