Search results for: hybrid database
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1443

Search results for: hybrid database

993 Modeling the Hybrid Battery/Super-Storage System for a Solar Standalone Microgrid

Authors: Astiaj Khoramshahi, Hossein Ahmadi Danesh Ashtiani, Ahmad Khoshgard, Hamidreza Damghani, Leila Damghani

Abstract:

Solar energy systems using various storages are required to be evaluated based on energy requirements and applications. Also, modeling and analysis of storage systems are necessary to increase the effectiveness of combinations of these systems. In this paper, analysis based on the MATLAB software has been analyzed to evaluate the response of the hybrid energy system considering various technologies of renewable energy and energy storage. In the present study, three different simulation scenarios are presented. Simulation output results using software for the first scenario show that the battery is effective in smoothing the overall power demand to the consumer studied during a day, but temporary loads on the grid with high frequencies, effectively cannot be canceled due to the limited response speed of battery control. Simulation outputs for the second scenario using the energy storage system show that sudden changes in demand power are paved by super saving. The majority of these sudden changes in power demand are caused by sewing consumers and receiving variable solar power (due to clouds passing through the solar array). Simulation outputs for the third scenario show the effects of the hybrid system for the same consumer and the output of the solar array, leading to the smallest amount of power demand fed into the grid, as well as demand at peak times. According to the "battery only" scenario, the displacement technique of the peak load has been significantly reduced.

Keywords: Storage system, super storage, standalone, microgrid.

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992 Predictive Clustering Hybrid Regression(pCHR) Approach and Its Application to Sucrose-Based Biohydrogen Production

Authors: Nikhil, Ari Visa, Chin-Chao Chen, Chiu-Yue Lin, Jaakko A. Puhakka, Olli Yli-Harja

Abstract:

A predictive clustering hybrid regression (pCHR) approach was developed and evaluated using dataset from H2- producing sucrose-based bioreactor operated for 15 months. The aim was to model and predict the H2-production rate using information available about envirome and metabolome of the bioprocess. Selforganizing maps (SOM) and Sammon map were used to visualize the dataset and to identify main metabolic patterns and clusters in bioprocess data. Three metabolic clusters: acetate coupled with other metabolites, butyrate only, and transition phases were detected. The developed pCHR model combines principles of k-means clustering, kNN classification and regression techniques. The model performed well in modeling and predicting the H2-production rate with mean square error values of 0.0014 and 0.0032, respectively.

Keywords: Biohydrogen, bioprocess modeling, clusteringhybrid regression.

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991 Hybrid Quasi-Steady Thermal Lattice Boltzmann Model for Studying the Behavior of Oil in Water Emulsions Used in Machining Tool Cooling and Lubrication

Authors: W. Hasan, H. Farhat, A. Alhilo, L. Tamimi

Abstract:

Oil in water (O/W) emulsions are utilized extensively for cooling and lubricating cutting tools during parts machining. A robust Lattice Boltzmann (LBM) thermal-surfactants model, which provides a useful platform for exploring complex emulsions’ characteristics under variety of flow conditions, is used here for the study of the fluid behavior during conventional tools cooling. The transient thermal capabilities of the model are employed for simulating the effects of the flow conditions of O/W emulsions on the cooling of cutting tools. The model results show that the temperature outcome is slightly affected by reversing the direction of upper plate (workpiece). On the other hand, an important increase in effective viscosity is seen which supports better lubrication during the work.

Keywords: Hybrid lattice Boltzmann method, Gunstensen model, thermal, surfactant-covered droplet, Marangoni stress.

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990 New Methods for E-Commerce Databases Designing in Semantic Web Systems (Modern Systems)

Authors: Karim Heidari, Serajodin Katebi, Ali Reza Mahdavi Far

Abstract:

The purpose of this paper is to study Database Models to use them efficiently in E-commerce websites. In this paper we are going to find a method which can save and retrieve information in Ecommerce websites. Thus, semantic web applications can work with, and we are also going to study different technologies of E-commerce databases and we know that one of the most important deficits in semantic web is the shortage of semantic data, since most of the information is still stored in relational databases, we present an approach to map legacy data stored in relational databases into the Semantic Web using virtually any modern RDF query language, as long as it is closed within RDF. To achieve this goal we study XML structures for relational data bases of old websites and eventually we will come up one level over XML and look for a map from relational model (RDM) to RDF. Noting that a large number of semantic webs get advantage of relational model, opening the ways which can be converted to XML and RDF in modern systems (semantic web) is important.

Keywords: E-Commerce, Semantic Web, Database, XML, RDF.

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989 Economic Assessment of Green House for Cultivation of Float Based Seedling Production in India

Authors: Srinath Ramakkrushnan, Aswathaman Vijayan

Abstract:

In conventional seedling production, the seedlings are being grown in the open field under natural conditions. Here they are susceptible to sudden changes in climate were their quality and yield is affected. Quality seedlings are essential for good growth and performance of crops in main field; they serve as a foundation for the economic returns to the farmer. Producing quality seedling demands usage of hybrid seeds as they have the ability to result in better yield, greater uniformity, improved color, disease resistance, and so forth. Hybrid seed production poses major operational challenge and its seed use efficiency plays an important role. Thus in order to overcome the difficulties currently present in conventional seedling production and to efficiently use hybrid seeds, ITC Limited Agri Business Divisions - Sustainability Cell as conceptualized a novel method of seedling production unit for farmers in West Godavari District of Andhra Pradesh. The “Green House based Float Seedling" methodology aims at a protected cultivation technique wherein the micro climate surrounding the plant/seedling body is controlled partially or fully as per the requirement of the species. This paper reports on the techno economic evaluation of green house for cultivation of float based seedling production with experimental results that was attained from the pilot implementation in West Godavari District, Rajahmundry region of India.

Keywords: Economic Assessment, Float Seedling, Green House, ITC Limited, Payback period.

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988 Automatic Classification of Lung Diseases from CT Images

Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

Abstract:

Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life due to the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or COVID-19 induced pneumonia. The early prediction and classification of such lung diseases help reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans are pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publicly available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scans, COVID-19, deep learning, image processing, pneumonia, lung disease.

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987 Field and Petrographic Relationships between the Charnockitic and Associated Granitic Rock, Akure Area, Southwestern Nigeria

Authors: Ademeso, Odunyemi Anthony

Abstract:

The charnockitic and associated granitic rocks of Akure area were studied for their field and petrographic relationship's. The outcrops locations were plotted in Surfer 8. The granitic rock exhibits a porphyritic texture and outcrops in the north-eastern side of the study area while the charnockitics outcrop in the central/western part. An essentially dark coloured and fine grained intrusive exhibiting xenoliths and xenocrysts (plagioclase phenocrysts) of the granite outcrops between the granitic and charnockitic rocks. Mineralogically, the central rock combines the content of the other two indicating that it is most likely a product of their hybridization. The charnockitic magma is believed to have intruded and assimilated the granite substantially thereby contaminating itself and consequently emplacing the hybrid. The presented model of emplacement elucidates the hybridization proposal. Conclusively, the charnockitics are believed to be (a) younger than the granite, (b) of Pan-African age and (c) of igneous origin.

Keywords: Charnockitic rock, Hybrid rock, ImageJ, Xenocryst

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986 A Hybrid Radial-Based Neuro-GA Multiobjective Design of Laminated Composite Plates under Moisture and Thermal Actions

Authors: Mohammad Reza Ghasemi, Ali Ehsani

Abstract:

In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the Tsai-Hill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuro-GA environment, and the procedure will be carried out until a predicted optimum solution is achieved.

Keywords: Composite Laminates, GA, Multi-objectiveOptimization, Neural Networks, RBFNN.

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985 A New Biologically Inspired Pattern Recognition Spproach for Face Recognition

Authors: V. Kabeer, N.K.Narayanan

Abstract:

This paper reports a new pattern recognition approach for face recognition. The biological model of light receptors - cones and rods in human eyes and the way they are associated with pattern vision in human vision forms the basis of this approach. The functional model is simulated using CWD and WPD. The paper also discusses the experiments performed for face recognition using the features extracted from images in the AT & T face database. Artificial Neural Network and k- Nearest Neighbour classifier algorithms are employed for the recognition purpose. A feature vector is formed for each of the face images in the database and recognition accuracies are computed and compared using the classifiers. Simulation results show that the proposed method outperforms traditional way of feature extraction methods prevailing for pattern recognition in terms of recognition accuracy for face images with pose and illumination variations.

Keywords: Face recognition, Image analysis, Wavelet feature extraction, Pattern recognition, Classifier algorithms

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984 Extended “2D-RIB“ for Impression-Based Satisfactory Retrieval and its Evaluation

Authors: T. Takayama, S. Kikuchi, Y. Hashimoto, T. Ikeda, Y. Murata

Abstract:

Recently, lots of researchers are attracted to retrieving multimedia database by using some impression words and their values. Ikezoe-s research is one of the representatives and uses eight pairs of opposite impression words. We had modified its retrieval interface and proposed '2D-RIB' in the previous work. The aim of the present paper is to improve his/her satisfaction level to the retrieval result in the 2D-RIB. Our method is to extend the 2D-RIB. One of our extensions is to define and introduce the following two measures: 'melody goodness' and 'general acceptance'. Another extension is three types of customization menus. The result of evaluation using a pilot system is as follows. Both of these two measures 'melody goodness' and -general acceptance- can contribute to the improvement. Moreover, it is effective if we introduce the customization menu which enables a retrieval person to reduce the strictness level of retrieval condition in an impression pair based on his/her need.

Keywords: Multimedia database, impression-based retrieval, interface, satisfaction level.

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983 Forecasting Fraudulent Financial Statements using Data Mining

Authors: S. Kotsiantis, E. Koumanakos, D. Tzelepis, V. Tampakas

Abstract:

This paper explores the effectiveness of machine learning techniques in detecting firms that issue fraudulent financial statements (FFS) and deals with the identification of factors associated to FFS. To this end, a number of experiments have been conducted using representative learning algorithms, which were trained using a data set of 164 fraud and non-fraud Greek firms in the recent period 2001-2002. The decision of which particular method to choose is a complicated problem. A good alternative to choosing only one method is to create a hybrid forecasting system incorporating a number of possible solution methods as components (an ensemble of classifiers). For this purpose, we have implemented a hybrid decision support system that combines the representative algorithms using a stacking variant methodology and achieves better performance than any examined simple and ensemble method. To sum up, this study indicates that the investigation of financial information can be used in the identification of FFS and underline the importance of financial ratios.

Keywords: Machine learning, stacking, classifier.

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982 An Embedded System for Artificial Intelligence Applications

Authors: Ioannis P. Panagopoulos, Christos C. Pavlatos, George K. Papakonstantinou

Abstract:

Conventional approaches in the implementation of logic programming applications on embedded systems are solely of software nature. As a consequence, a compiler is needed that transforms the initial declarative logic program to its equivalent procedural one, to be programmed to the microprocessor. This approach increases the complexity of the final implementation and reduces the overall system's performance. On the contrary, presenting hardware implementations which are only capable of supporting logic programs prevents their use in applications where logic programs need to be intertwined with traditional procedural ones, for a specific application. We exploit HW/SW codesign methods to present a microprocessor, capable of supporting hybrid applications using both programming approaches. We take advantage of the close relationship between attribute grammar (AG) evaluation and knowledge engineering methods to present a programmable hardware parser that performs logic derivations and combine it with an extension of a conventional RISC microprocessor that performs the unification process to report the success or failure of those derivations. The extended RISC microprocessor is still capable of executing conventional procedural programs, thus hybrid applications can be implemented. The presented implementation is programmable, supports the execution of hybrid applications, increases the performance of logic derivations (experimental analysis yields an approximate 1000% increase in performance) and reduces the complexity of the final implemented code. The proposed hardware design is supported by a proposed extended C-language called C-AG.

Keywords: Attribute Grammars, Logic Programming, RISC microprocessor.

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981 GEP Considering Purchase Prices, Profits of IPPs and Reliability Criteria Using Hybrid GA and PSO

Authors: H. Shayeghi, H. Hosseini, A. Shabani, M. Mahdavi

Abstract:

In this paper, optimal generation expansion planning (GEP) is investigated considering purchase prices, profits of independent power producers (IPPs) and reliability criteria using a new method based on hybrid coded Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). In this approach, optimal purchase price of each IPP is obtained by HCGA and reliability criteria are calculated by PSO technique. It should be noted that reliability criteria and the rate of carbon dioxide (CO2) emission have been considered as constraints of the GEP problem. Finally, the proposed method has been tested on the case study system. The results evaluation show that the proposed method can simply obtain optimal purchase prices of IPPs and is a fast method for calculation of reliability criteria in expansion planning. Also, considering the optimal purchase prices and profits of IPPs in generation expansion planning are caused that the expansion costs are decreased and the problem is solved more exactly.

Keywords: GEP Problem, IPPs, Reliability Criteria, GA, PSO.

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980 Mining and Visual Management of XML-Based Image Collections

Authors: Khalil Shihab, Nida Al-Chalabi

Abstract:

This article describes Uruk, the virtual museum of Iraq that we developed for visual exploration and retrieval of image collections. The system largely exploits the loosely-structured hierarchy of XML documents that provides a useful representation method to store semi-structured or unstructured data, which does not easily fit into existing database. The system offers users the capability to mine and manage the XML-based image collections through a web-based Graphical User Interface (GUI). Typically, at an interactive session with the system, the user can browse a visual structural summary of the XML database in order to select interesting elements. Using this intermediate result, queries combining structure and textual references can be composed and presented to the system. After query evaluation, the full set of answers is presented in a visual and structured way.

Keywords: Data-centric XML, graphical user interfaces, information retrieval, case-based reasoning, fuzzy sets

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979 UB-Tree Indexing for Semantic Query Optimization of Range Queries

Authors: S. Housseno, A. Simonet, M. Simonet

Abstract:

Semantic query optimization consists in restricting the search space in order to reduce the set of objects of interest for a query. This paper presents an indexing method based on UB-trees and a static analysis of the constraints associated to the views of the database and to any constraint expressed on attributes. The result of the static analysis is a partitioning of the object space into disjoint blocks. Through Space Filling Curve (SFC) techniques, each fragment (block) of the partition is assigned a unique identifier, enabling the efficient indexing of fragments by UB-trees. The search space corresponding to a range query is restricted to a subset of the blocks of the partition. This approach has been developed in the context of a KB-DBMS but it can be applied to any relational system.

Keywords: Index, Range query, UB-tree, Space Filling Curve, Query optimization, Views, Database, Integrity Constraint, Classification.

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978 Hybrid Artificial Immune System for Job Shop Scheduling Problem

Authors: Bin Cai, Shilong Wang, Haibo Hu

Abstract:

The job shop scheduling problem (JSSP) is a notoriously difficult problem in combinatorial optimization. This paper presents a hybrid artificial immune system for the JSSP with the objective of minimizing makespan. The proposed approach combines the artificial immune system, which has a powerful global exploration capability, with the local search method, which can exploit the optimal antibody. The antibody coding scheme is based on the operation based representation. The decoding procedure limits the search space to the set of full active schedules. In each generation, a local search heuristic based on the neighborhood structure proposed by Nowicki and Smutnicki is applied to improve the solutions. The approach is tested on 43 benchmark problems taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.

Keywords: Artificial immune system, Job shop scheduling problem, Local search, Metaheuristic algorithm

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977 Mobile to Server Face Recognition: A System Overview

Authors: Nurulhuda Ismail, Mas Idayu Md. Sabri

Abstract:

This paper presents a system overview of Mobile to Server Face Recognition, which is a face recognition application developed specifically for mobile phones. Images taken from mobile phone cameras lack of quality due to the low resolution of the cameras. Thus, a prototype is developed to experiment the chosen method. However, this paper shows a result of system backbone without the face recognition functionality. The result demonstrated in this paper indicates that the interaction between mobile phones and server is successfully working. The result shown before the database is completely ready. The system testing is currently going on using real images and a mock-up database to test the functionality of the face recognition algorithm used in this system. An overview of the whole system including screenshots and system flow-chart are presented in this paper. This paper also presents the inspiration or motivation and the justification in developing this system.

Keywords: Mobile to server, face recognition, system overview.

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976 Big Brain: A Single Database System for a Federated Data Warehouse Architecture

Authors: X. Gumara Rigol, I. Martínez de Apellaniz Anzuola, A. Garcia Serrano, A. Franzi Cros, O. Vidal Calbet, A. Al Maruf

Abstract:

Traditional federated architectures for data warehousing work well when corporations have existing regional data warehouses and there is a need to aggregate data at a global level. Schibsted Media Group has been maturing from a decentralised organisation into a more globalised one and needed to build both some of the regional data warehouses for some brands at the same time as the global one. In this paper, we present the architectural alternatives studied and why a custom federated approach was the notable recommendation to go further with the implementation. Although the data warehouses are logically federated, the implementation uses a single database system which presented many advantages like: cost reduction and improved data access to global users allowing consumers of the data to have a common data model for detailed analysis across different geographies and a flexible layer for local specific needs in the same place.

Keywords: Data integration, data warehousing, federated architecture, online analytical processing.

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975 Hybrid Approach for Memory Analysis in Windows System

Authors: Khairul Akram Zainol Ariffin, Ahmad Kamil Mahmood, Jafreezal Jaafar, Solahuddin Shamsuddin

Abstract:

Random Access Memory (RAM) is an important device in computer system. It can represent the snapshot on how the computer has been used by the user. With the growth of its importance, the computer memory has been an issue that has been discussed in digital forensics. A number of tools have been developed to retrieve the information from the memory. However, most of the tools have their limitation in the ability of retrieving the important information from the computer memory. Hence, this paper is aimed to discuss the limitation and the setback for two main techniques such as process signature search and process enumeration. Then, a new hybrid approach will be presented to minimize the setback in both individual techniques. This new approach combines both techniques with the purpose to retrieve the information from the process block and other objects in the computer memory. Nevertheless, the basic theory in address translation for x86 platforms will be demonstrated in this paper.

Keywords: Algorithms, Digital Forensics, Memory Analysis, Signature Search.

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974 Providing Energy Management of a Fuel Cell-Battery Hybrid Electric Vehicle

Authors: Fatma Keskin Arabul, Ibrahim Senol, Ahmet Yigit Arabul, Ali Rifat Boynuegri

Abstract:

On account of the concern of the fossil fuel is depleting and its negative effects on the environment, interest in alternative energy sources is increasing day by day. However, considering the importance of transportation in human life, instead of oil and its derivatives fueled vehicles with internal combustion engines, electric vehicles which are sensitive to the environment and working with electrical energy has begun to develop. In this study, simulation was carried out for providing energy management and recovering regenerative braking in fuel cell-battery hybrid electric vehicle. The main power supply of the vehicle is fuel cell on the other hand not only instantaneous power is supplied by the battery but also the energy generated due to regenerative breaking is stored in the battery. Obtained results of the simulation is analyzed and discussed.

Keywords: Electric vehicles, fuel cell, battery, regenerative braking, energy management.

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973 Computer Aided Classification of Architectural Distortion in Mammograms Using Texture Features

Authors: Birmohan Singh, V. K. Jain

Abstract:

Computer aided diagnosis systems provide vital opinion to radiologists in the detection of early signs of breast cancer from mammogram images. Architectural distortions, masses and microcalcifications are the major abnormalities. In this paper, a computer aided diagnosis system has been proposed for distinguishing abnormal mammograms with architectural distortion from normal mammogram. Four types of texture features GLCM texture, GLRLM texture, fractal texture and spectral texture features for the regions of suspicion are extracted. Support vector machine has been used as classifier in this study. The proposed system yielded an overall sensitivity of 96.47% and an accuracy of 96% for mammogram images collected from digital database for screening mammography database.

Keywords: Architecture Distortion, GLCM Texture features, GLRLM Texture Features, Mammograms, Support Vector Machine.

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972 An Advanced Hybrid P2p Botnet 2.0

Authors: T. T. Lu, H.Y. Liao, M .F. Chen

Abstract:

Recently, malware attacks have become more serious over the Internet by e-mail, denial of service (DoS) or distributed denial of service (DDoS). The Botnets have become a significant part of the Internet malware attacks. The traditional botnets include three parts – botmaster, command and control (C&C) servers and bots. The C&C servers receive commands from botmaster and control the distributions of computers remotely. Bots use DNS to find the positions of C&C server. In this paper, we propose an advanced hybrid peer-to-peer (P2P) botnet 2.0 (AHP2P botnet 2.0) using web 2.0 technology to hide the instructions from botmaster into social sites, which are regarded as C&C servers. Servent bots are regarded as sub-C&C servers to get the instructions from social sites. The AHP2P botnet 2.0 can evaluate the performance of servent bots, reduce DNS traffics from bots to C&C servers, and achieve harder detection bots actions than IRC-based botnets over the Internet.

Keywords: Peer-to-peer, Botnets, Botnet 2.0, Hybridpeer-to-peer

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971 Global Security Using Human Face Understanding under Vision Ubiquitous Architecture System

Authors: A. Jalal, S. Kim

Abstract:

Different methods containing biometric algorithms are presented for the representation of eigenfaces detection including face recognition, are identification and verification. Our theme of this research is to manage the critical processing stages (accuracy, speed, security and monitoring) of face activities with the flexibility of searching and edit the secure authorized database. In this paper we implement different techniques such as eigenfaces vector reduction by using texture and shape vector phenomenon for complexity removal, while density matching score with Face Boundary Fixation (FBF) extracted the most likelihood characteristics in this media processing contents. We examine the development and performance efficiency of the database by applying our creative algorithms in both recognition and detection phenomenon. Our results show the performance accuracy and security gain with better achievement than a number of previous approaches in all the above processes in an encouraging mode.

Keywords: Ubiquitous architecture, verification, Identification, recognition

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970 Study of Features for Hand-printed Recognition

Authors: Satish Kumar

Abstract:

The feature extraction method(s) used to recognize hand-printed characters play an important role in ICR applications. In order to achieve high recognition rate for a recognition system, the choice of a feature that suits for the given script is certainly an important task. Even if a new feature required to be designed for a given script, it is essential to know the recognition ability of the existing features for that script. Devanagari script is being used in various Indian languages besides Hindi the mother tongue of majority of Indians. This research examines a variety of feature extraction approaches, which have been used in various ICR/OCR applications, in context to Devanagari hand-printed script. The study is conducted theoretically and experimentally on more that 10 feature extraction methods. The various feature extraction methods have been evaluated on Devanagari hand-printed database comprising more than 25000 characters belonging to 43 alphabets. The recognition ability of the features have been evaluated using three classifiers i.e. k-NN, MLP and SVM.

Keywords: Features, Hand-printed, Devanagari, Classifier, Database

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969 2 – Block 3 - Point Modified Numerov Block Methods for Solving Ordinary Differential Equations

Authors: Abdu Masanawa Sagir

Abstract:

In this paper, linear multistep technique using power series as the basis function is used to develop the block methods which are suitable for generating direct solution of the special second order ordinary differential equations of the form y′′ = f(x,y), a < = x < = b with associated initial or boundary conditions. The continuaous hybrid formulations enable us to differentiate and evaluate at some grids and off – grid points to obtain two different three discrete schemes, each of order (4,4,4)T, which were used in block form for parallel or sequential solutions of the problems. The computational burden and computer time wastage involved in the usual reduction of second order problem into system of first order equations are avoided by this approach. Furthermore, a stability analysis and efficiency of the block method are tested on linear and non-linear ordinary differential equations whose solutions are oscillatory or nearly periodic in nature, and the results obtained compared favourably with the exact solution.

Keywords: Block Method, Hybrid, Linear Multistep Method, Self – starting, Special Second Order.

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968 Mamdani Model based Adaptive Neural Fuzzy Inference System and its Application

Authors: Yuanyuan Chai, Limin Jia, Zundong Zhang

Abstract:

Hybrid algorithm is the hot issue in Computational Intelligence (CI) study. From in-depth discussion on Simulation Mechanism Based (SMB) classification method and composite patterns, this paper presents the Mamdani model based Adaptive Neural Fuzzy Inference System (M-ANFIS) and weight updating formula in consideration with qualitative representation of inference consequent parts in fuzzy neural networks. M-ANFIS model adopts Mamdani fuzzy inference system which has advantages in consequent part. Experiment results of applying M-ANFIS to evaluate traffic Level of service show that M-ANFIS, as a new hybrid algorithm in computational intelligence, has great advantages in non-linear modeling, membership functions in consequent parts, scale of training data and amount of adjusted parameters.

Keywords: Fuzzy neural networks, Mamdani fuzzy inference, M-ANFIS

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967 An Extensible Software Infrastructure for Computer Aided Custom Monitoring of Patients in Smart Homes

Authors: Ritwik Dutta, Marilyn Wolf

Abstract:

This paper describes the tradeoffs and the design from scratch of a self-contained, easy-to-use health dashboard software system that provides customizable data tracking for patients in smart homes. The system is made up of different software modules and comprises a front-end and a back-end component. Built with HTML, CSS, and JavaScript, the front-end allows adding users, logging into the system, selecting metrics, and specifying health goals. The backend consists of a NoSQL Mongo database, a Python script, and a SimpleHTTPServer written in Python. The database stores user profiles and health data in JSON format. The Python script makes use of the PyMongo driver library to query the database and displays formatted data as a daily snapshot of user health metrics against target goals. Any number of standard and custom metrics can be added to the system, and corresponding health data can be fed automatically, via sensor APIs or manually, as text or picture data files. A real-time METAR request API permits correlating weather data with patient health, and an advanced query system is implemented to allow trend analysis of selected health metrics over custom time intervals. Available on the GitHub repository system, the project is free to use for academic purposes of learning and experimenting, or practical purposes by building on it.

Keywords: Flask, Java, JavaScript, health monitoring, long term care, Mongo, Python, smart home, software engineering, webserver.

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966 Investigation of Regional Differences in Strong Ground Motions for the Iranian Plateau

Authors: Farhad Sedaghati, Shahram Pezeshk

Abstract:

Regional variations in strong ground motions for the Iranian Plateau have been investigated by using a simple statistical method called Analysis of Variance (ANOVA). In this respect, a large database consisting of 1157 records occurring within the Iranian Plateau with moment magnitudes of greater than or equal to 5 and Joyner-Boore distances up to 200 km has been considered. Geometric averages of horizontal peak ground accelerations (PGA) as well as 5% damped linear elastic response spectral accelerations (SA) at periods of 0.2, 0.5, 1.0, and 2.0 sec are used as strong motion parameters. The initial database is divided into two different datasets, for Northern Iran (NI) and Central and Southern Iran (CSI). The comparison between strong ground motions of these two regions reveals that there is no evidence for significant differences; therefore, data from these two regions may be combined to estimate the unknown coefficients of attenuation relationships.

Keywords: ANOVA, attenuation relationships, Iranian Plateau, PGA, regional variation, SA, strong ground motion.

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965 Comics as Third Space: An Analysis of the Continuous Negotiation of Identities in Postcolonial Philippines

Authors: Anna Camille V. Flores

Abstract:

Comics in the Philippines has taken on many uses for the Filipino people. They have been sources of entertainment, education, and political and social commentaries. History has been witnessed to the rise and fall of Philippine comics but the 21st century is seeing a revival of the medium and the industry. It is within this context that an inquiry about Filipino identity is situated. Employing the analytical framework of postcolonialism, particularly Homi K. Bhabha’s concepts of Hybridity and the Third Space, this study analyzes three contemporary Philippine comics, Trese, Filipino Heroes League, and Dead Balagtas. The study was able to draw three themes that represent how Filipinos inhabit hybrid worlds and hybridized identities. First, the third space emerged through the use of hybrid worlds in the comics. Second, (re)imagined communities are established through the use of intertextual signifiers. Third, (re)negotiated identities are expressed through visual and narrative devices such as the use of Philippine mythology, historical and contemporary contexts, and language. In conclusion, comics can be considered as Third Space where these identities have the agency and opportunity to be expressed and represented.

Keywords: Comics, hybridity and third space, Philippine comics, postcolonialism.

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964 A Hybrid Fuzzy AGC in a Competitive Electricity Environment

Authors: H. Shayeghi, A. Jalili

Abstract:

This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.

Keywords: AGC, Hybrid Fuzzy Controller, Deregulated Power System, Power System Control, GAs.

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