Search results for: Attack Features
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1795

Search results for: Attack Features

1345 A Neural Approach for the Offline Recognition of the Arabic Handwritten Words of the Algerian Departments

Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda

Abstract:

In the context of the handwriting recognition, we propose an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods. The Distribution parameters, the centered moments of the different projections of the different segments, the centered moments of the word image coding according to the directions of Freeman, and the Barr features applied binary image of the word and on its different segments. The classification is achieved by a multi layers perceptron. A detailed experiment is carried and satisfactory recognition results are reported.

Keywords: Handwritten word recognition, neural networks, image processing, pattern recognition, features extraction.

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1344 Assessment of the Number of Damaged Buildings from a Flood Event Using Remote Sensing Technique

Authors: Jaturong Som-ard

Abstract:

The heavy rainfall from 3rd to 22th January 2017 had swamped much area of Ranot district in southern Thailand. Due to heavy rainfall, the district was flooded which had a lot of effects on economy and social loss. The major objective of this study is to detect flooding extent using Sentinel-1A data and identify a number of damaged buildings over there. The data were collected in two stages as pre-flooding and during flood event. Calibration, speckle filtering, geometric correction, and histogram thresholding were performed with the data, based on intensity spectral values to classify thematic maps. The maps were used to identify flooding extent using change detection, along with the buildings digitized and collected on JOSM desktop. The numbers of damaged buildings were counted within the flooding extent with respect to building data. The total flooded areas were observed as 181.45 sq.km. These areas were mostly occurred at Ban khao, Ranot, Takhria, and Phang Yang sub-districts, respectively. The Ban khao sub-district had more occurrence than the others because this area is located at lower altitude and close to Thale Noi and Thale Luang lakes than others. The numbers of damaged buildings were high in Khlong Daen (726 features), Tha Bon (645 features), and Ranot sub-district (604 features), respectively. The final flood extent map might be very useful for the plan, prevention and management of flood occurrence area. The map of building damage can be used for the quick response, recovery and mitigation to the affected areas for different concern organization.

Keywords: Flooding extent, Sentinel-1A data, JOSM desktop, damaged buildings.

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1343 Statistical Feature Extraction Method for Wood Species Recognition System

Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

Abstract:

Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: Classification, fuzzy, inspection system, image analysis.

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1342 Trabecular Bone Radiograph Characterization Using Fractal, Multifractal Analysis and SVM Classifier

Authors: I. Slim, H. Akkari, A. Ben Abdallah, I. Bhouri, M. Hedi Bedoui

Abstract:

Osteoporosis is a common disease characterized by low bone mass and deterioration of micro-architectural bone tissue, which provokes an increased risk of fracture. This work treats the texture characterization of trabecular bone radiographs. The aim was to analyze according to clinical research a group of 174 subjects: 87 osteoporotic patients (OP) with various bone fracture types and 87 control cases (CC). To characterize osteoporosis, Fractal and MultiFractal (MF) methods were applied to images for features (attributes) extraction. In order to improve the results, a new method of MF spectrum based on the q-stucture function calculation was proposed and a combination of Fractal and MF attributes was used. The Support Vector Machines (SVM) was applied as a classifier to distinguish between OP patients and CC subjects. The features fusion (fractal and MF) allowed a good discrimination between the two groups with an accuracy rate of 96.22%.

Keywords: Fractal, micro-architecture analysis, multifractal, SVM, osteoporosis.

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1341 The Integration of Iranian Traditional Architecture in the Contemporary Housing Design: A Case Study

Authors: H. Nejadriahi

Abstract:

Traditional architecture is a valuable source of inspiration, which needs to be studied and integrated in the contemporary designs for achieving an identifiable contemporary architecture. Traditional architecture of Iran is among the distinguished examples of being contextually responsive, not only by considering the environmental conditions of a region, but also in terms of respecting the socio-cultural values of its context. In order to apply these valuable features to the current designs, they need to be adapted to today's condition, needs and desires. In this paper, the main features of the traditional architecture of Iran are explained to interrogate them in the formation of a contemporary house in Tehran, Iran. Also a table is provided to compare the utilization of the traditional design concepts in the traditional houses and the contemporary example of it. It is believed that such study would increase the awareness of contemporary designers by providing them some clues on maintaining the traditional values in the current design layouts particularly in the residential sector that would ultimately improve the quality of space in the contemporary architecture.

Keywords: Contemporary housing design, Iran, Tehran, traditional architecture.

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1340 The Adsorption of SDS on Ferro-Precipitates

Authors: R.Marsalek

Abstract:

This paper present a new way to find the aerodynamic characteristic equation of missile for the numerical trajectories prediction more accurate. The goal is to obtain the polynomial equation based on two missile characteristic parameters, angle of attack (α ) and flight speed (ν ). First, the understudied missile is modeled and used for flow computational model to compute aerodynamic force and moment. Assume that performance range of understudied missile where range -10< α <10 and 0< ν <200. After completely obtained results of all cases, the data are fit by polynomial interpolation to create equation of each case and then combine all equations to form aerodynamic characteristic equation, which will be used for trajectories simulation.

Keywords: ferro-precipitate, adsorption, SDS, zeta potential

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1339 Day/Night Detector for Vehicle Tracking in Traffic Monitoring Systems

Authors: M. Taha, Hala H. Zayed, T. Nazmy, M. Khalifa

Abstract:

Recently, traffic monitoring has attracted the attention of computer vision researchers. Many algorithms have been developed to detect and track moving vehicles. In fact, vehicle tracking in daytime and in nighttime cannot be approached with the same techniques, due to the extreme different illumination conditions. Consequently, traffic-monitoring systems are in need of having a component to differentiate between daytime and nighttime scenes. In this paper, a HSV-based day/night detector is proposed for traffic monitoring scenes. The detector employs the hue-histogram and the value-histogram on the top half of the image frame. Experimental results show that the extraction of the brightness features along with the color features within the top region of the image is effective for classifying traffic scenes. In addition, the detector achieves high precision and recall rates along with it is feasible for real time applications.

Keywords: Day/night detector, daytime/nighttime classification, image classification, vehicle tracking, traffic monitoring.

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1338 Function of Fractals: Application of Non-linear Geometry in Continental Architecture

Authors: Mohammadsadegh Zanganehfar

Abstract:

Since the introduction of fractal geometry in 1970, numerous efforts have been made by architects and researchers to transfer this area of mathematical knowledge in the discipline of architecture and postmodernist discourse. The discourse of complexity and architecture is one of the most significant ongoing discourses in the discipline of architecture from the 70's until today and has generated significant styles such as deconstructivism and parametricism in architecture. During these years, several projects were designed and presented by designers and architects using fractal geometry, but due to the lack of sufficient knowledge and appropriate comprehension of the features and characteristics of this nonlinear geometry, none of the fractal-based designs have been successful and satisfying. Fractal geometry as a geometric technology has a long presence in the history of architecture. The current research attempts to identify and discover the characteristics, features, potentials and functionality of fractals despite their aesthetic aspect by examining case studies of pre-modern architecture in Asia and investigating the function of fractals. 

Keywords: Asian architecture, fractal geometry, fractal technique, geometric properties

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1337 Analysis of Threats in Interoperability of Medical Devices

Authors: M. Sandhya, R. M. Madhumitha, Sharmila Sankar

Abstract:

Interoperable medical devices (IMDs) face threats due to the increased attack surface accessible by interoperability and the corresponding infrastructure. Initiating networking and coordination functionalities primarily modify medical systems' security properties. Understanding the threats is a vital first step in ultimately crafting security solutions for such systems. The key to this problem is coming up with some common types of threats or attacks with those of security and privacy, and providing this information as a roadmap. This paper analyses the security issues in interoperability of devices and presents the main types of threats that have to be considered to build a secured system.

Keywords: Interoperability, threats, attacks, medical devices.

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1336 Mechanical, Thermal and Biodegradable Properties of Bioplast-Spruce Green Wood Polymer Composites

Authors: A. Atli, K. Candelier, J. Alteyrac

Abstract:

Environmental and sustainability concerns push the industries to manufacture alternative materials having less environmental impact. The Wood Plastic Composites (WPCs) produced by blending the biopolymers and natural fillers permit not only to tailor the desired properties of materials but also are the solution to meet the environmental and sustainability requirements. This work presents the elaboration and characterization of the fully green WPCs prepared by blending a biopolymer, BIOPLAST® GS 2189 and spruce sawdust used as filler with different amounts. Since both components are bio-based, the resulting material is entirely environmentally friendly. The mechanical, thermal, structural properties of these WPCs were characterized by different analytical methods like tensile, flexural and impact tests, Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC) and X-ray Diffraction (XRD). Their water absorption properties and resistance to the termite and fungal attacks were determined in relation with different wood filler content. The tensile and flexural moduli of WPCs increased with increasing amount of wood fillers into the biopolymer, but WPCs became more brittle compared to the neat polymer. Incorporation of spruce sawdust modified the thermal properties of polymer: The degradation, cold crystallization, and melting temperatures shifted to higher temperatures when spruce sawdust was added into polymer. The termite, fungal and water absorption resistance of WPCs decreased with increasing wood amount in WPCs, but remained in durability class 1 (durable) concerning fungal resistance and quoted 1 (attempted attack) in visual rating regarding to the termites resistance except that the WPC with the highest wood content (30 wt%) rated 2 (slight attack) indicating a long term durability. All the results showed the possibility to elaborate the easy injectable composite materials with adjustable properties by incorporation of BIOPLAST® GS 2189 and spruce sawdust. Therefore, lightweight WPCs allow both to recycle wood industry byproducts and to produce a full ecologic material.

Keywords: Biodegradability, durability, mechanical properties, melt flow index, spectrophotometry, structural properties, thermal properties, wood-plastic composites.

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1335 Cryptanalysis of Two-Factor Authenticated Key Exchange Protocol in Public Wireless LANs

Authors: Hyunseung Lee, Donghyun Choi, Yunho Lee, Dongho Won, Seungjoo Kim

Abstract:

In Public Wireless LANs(PWLANs), user anonymity is an essential issue. Recently, Juang et al. proposed an anonymous authentication and key exchange protocol using smart cards in PWLANs. They claimed that their proposed scheme provided identity privacy, mutual authentication, and half-forward secrecy. In this paper, we point out that Juang et al.'s protocol is vulnerable to the stolen-verifier attack and does not satisfy user anonymity.

Keywords: PWLANs, user privacy, smart card, authentication, key exchange

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1334 Quantum Dot Cellular Automata Based Effective Design of Combinational and Sequential Logical Structures

Authors: Hema Sandhya Jagarlamudi, Mousumi Saha, Pavan Kumar Jagarlamudi

Abstract:

The use of Quantum dots is a promising emerging Technology for implementing digital system at the nano level. It is effecient for attractive features such as faster speed , smaller size and low power consumption than transistor technology. In this paper, various Combinational and sequential logical structures - HALF ADDER, SR Latch and Flip-Flop, D Flip-Flop preceding NAND, NOR, XOR,XNOR are discussed based on QCA design, with comparatively less number of cells and area. By applying these layouts, the hardware requirements for a QCA design can be reduced. These structures are designed and simulated using QCA Designer Tool. By taking full advantage of the unique features of this technology, we are able to create complete circuits on a single layer of QCA. Such Devices are expected to function with ultra low power Consumption and very high speeds.

Keywords: QCA, QCA Designer, Clock, Majority Gate

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1333 The Impact of Scientific Content of National Geographic Channel on Drawing Style of Kindergarten Children

Authors: Ahmed Amin Mousa, Mona Yacoub

Abstract:

This study depends on tracking children style through what they have drawn after being introduced to 16 visual content through National Geographic Abu Dhabi Channel programs and the study of the changing features in their drawings before applying the visual act with them. The researchers used Goodenough-Harris Test to analyse children drawings and to extract the features which changed in their drawing before and after the visual content. The results showed a positive change especially in the shapes of animals and their properties. Children become more aware of animals’ shapes. The study sample was 220 kindergarten children divided into 130 girls and 90 boys at the Orman Experimental Language School in Dokki, Giza, Egypt. The study results showed an improvement in children drawing with 85% than they were before watching videos.

Keywords: National Geographic, children drawing, kindergarten, Goodenough-Harris Test.

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1332 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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1331 Investigation of New Gait Representations for Improving Gait Recognition

Authors: Chirawat Wattanapanich, Hong Wei

Abstract:

This study presents new gait representations for improving gait recognition accuracy on cross gait appearances, such as normal walking, wearing a coat and carrying a bag. Based on the Gait Energy Image (GEI), two ideas are implemented to generate new gait representations. One is to append lower knee regions to the original GEI, and the other is to apply convolutional operations to the GEI and its variants. A set of new gait representations are created and used for training multi-class Support Vector Machines (SVMs). Tests are conducted on the CASIA dataset B. Various combinations of the gait representations with different convolutional kernel size and different numbers of kernels used in the convolutional processes are examined. Both the entire images as features and reduced dimensional features by Principal Component Analysis (PCA) are tested in gait recognition. Interestingly, both new techniques, appending the lower knee regions to the original GEI and convolutional GEI, can significantly contribute to the performance improvement in the gait recognition. The experimental results have shown that the average recognition rate can be improved from 75.65% to 87.50%.

Keywords: Convolutional image, lower knee, gait.

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1330 Elastic Lateral Features of a New Glass Fiber Reinforced Gypsum Wall

Authors: Zhengyong Liu, Huiqing Ying

Abstract:

GFRG(Glass Fiber Reinforced Gypsum) wall is a green product which can erect a building fast in prefabricated method, but its application to high-rise residential buildings is limited for its poor lateral stiffness. This paper has proposed a modification to GFRG walls structure to increase its lateral stiffness, which aiming to erect small high-rise residential buildings as load-bearing walls. The elastic finite element analysis to it has shown the lateral deformation feature and the distributions of the axial force and the shear force. The analysis results show that the new GFRG reinforced concrete wall can be used for small high-rise residential buildings.

Keywords: GFRG wall, lateral features, elastic analysis, residential building.

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1329 Performance Analysis of Brain Tumor Detection Based On Image Fusion

Authors: S. Anbumozhi, P. S. Manoharan

Abstract:

Medical Image fusion plays a vital role in medical field to diagnose the brain tumors which can be classified as benign or malignant. It is the process of integrating multiple images of the same scene into a single fused image to reduce uncertainty and minimizing redundancy while extracting all the useful information from the source images. Fuzzy logic is used to fuse two brain MRI images with different vision. The fused image will be more informative than the source images. The texture and wavelet features are extracted from the fused image. The multilevel Adaptive Neuro Fuzzy Classifier classifies the brain tumors based on trained and tested features. The proposed method achieved 80.48% sensitivity, 99.9% specificity and 99.69% accuracy. Experimental results obtained from fusion process prove that the use of the proposed image fusion approach shows better performance while compared with conventional fusion methodologies.

Keywords: Image fusion, Fuzzy rules, Neuro-fuzzy classifier.

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1328 Single-Camera Basketball Tracker through Pose and Semantic Feature Fusion

Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro

Abstract:

Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.

Keywords: Basketball, deep learning, feature extraction, single-camera, tracking.

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1327 Texture Characterization Based on a Chandrasekhar Fast Adaptive Filter

Authors: Mounir Sayadi, Farhat Fnaiech

Abstract:

In the framework of adaptive parametric modelling of images, we propose in this paper a new technique based on the Chandrasekhar fast adaptive filter for texture characterization. An Auto-Regressive (AR) linear model of texture is obtained by scanning the image row by row and modelling this data with an adaptive Chandrasekhar linear filter. The characterization efficiency of the obtained model is compared with the model adapted with the Least Mean Square (LMS) 2-D adaptive algorithm and with the cooccurrence method features. The comparison criteria is based on the computation of a characterization degree using the ratio of "betweenclass" variances with respect to "within-class" variances of the estimated coefficients. Extensive experiments show that the coefficients estimated by the use of Chandrasekhar adaptive filter give better results in texture discrimination than those estimated by other algorithms, even in a noisy context.

Keywords: Texture analysis, statistical features, adaptive filters, Chandrasekhar algorithm.

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1326 Comparative Study Using Weka for Red Blood Cells Classification

Authors: Jameela Ali Alkrimi, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

Abstract:

Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithms tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital - Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-Nearest Neighbors, Neural Network, Radial Basis Function, Red blood cells, Support vector machine.

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1325 Automatic Staging and Subtype Determination for Non-Small Cell Lung Carcinoma Using PET Image Texture Analysis

Authors: Seyhan Karaçavuş, Bülent Yılmaz, Ömer Kayaaltı, Semra İçer, Arzu Taşdemir, Oğuzhan Ayyıldız, Kübra Eset, Eser Kaya

Abstract:

In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with k-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype.

Keywords: Cancer stage, cancer cell type, non-small cell lung carcinoma, PET, texture analysis.

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1324 Analysis of Endovascular Graft Features Affecting Endotension Following Endovascular Aneurysm Repair

Authors: Zeinab Hooshyar, Alireza Mehdizadeh

Abstract:

Endovascular aneurysm repair is a new and minimally invasive repair for patients with abdominal aortic aneurysm (AAA). This method has potential advantages that are incomparable with other repair methods. However, the enlargement of aneurysm in the absence of endoleak, which is known as endotension, may occur as one of post-operative compliances of this method. Typically, endotension is mainly as a result of pressure transmitted to aneurysm sac by endovascular installed graft. After installation of graft the aneurysm sac reduces significantly but remains non-zero. There are some factors which affect this pressure transmitted. In this study, the geometry features of installed vascular graft have been considered. It is inferred that graft neck angle and iliac bifurcation angle are two factors which can affect the drag force on graft and consequently the pressure transmitted to aneurysm.

Keywords: Endovascular graft, transmitted pressure, Drag force, Finite Element Modeling, neck angle, iliac bifurcation angle.

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1323 What Have Banks Done Wrong?

Authors: F. May Liou, Y. C. Edwin Tang

Abstract:

This paper aims to provide a conceptual framework to examine competitive disadvantage of banks that suffer from poor performance. Banks generate revenues mainly from the interest rate spread on taking deposits and making loans while collecting fees in the process. To maximize firm value, banks seek loan growth and expense control while managing risk associated with loans with respect to non-performing borrowers or narrowing interest spread between assets and liabilities. Competitive disadvantage refers to the failure to access imitable resources and to build managing capabilities to gain sustainable return given appropriate risk management. This paper proposes a four-quadrant framework of organizational typology is subsequently proposed to examine the features of competitive disadvantage in the banking sector. A resource configuration model, which is extracted from CAMEL indicators to examine the underlying features of bank failures.

Keywords: Bank failure, CAMEL, competitive disadvantage, resource configuration.

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1322 Analysis of Electrocardiograph (ECG) Signal for the Detection of Abnormalities Using MATLAB

Authors: Durgesh Kumar Ojha, Monica Subashini

Abstract:

The proposed method is to study and analyze Electrocardiograph (ECG) waveform to detect abnormalities present with reference to P, Q, R and S peaks. The first phase includes the acquisition of real time ECG data. In the next phase, generation of signals followed by pre-processing. Thirdly, the procured ECG signal is subjected to feature extraction. The extracted features detect abnormal peaks present in the waveform Thus the normal and abnormal ECG signal could be differentiated based on the features extracted. The work is implemented in the most familiar multipurpose tool, MATLAB. This software efficiently uses algorithms and techniques for detection of any abnormalities present in the ECG signal. Proper utilization of MATLAB functions (both built-in and user defined) can lead us to work with ECG signals for processing and analysis in real time applications. The simulation would help in improving the accuracy and the hardware could be built conveniently.

Keywords: ECG Waveform, Peak Detection, Arrhythmia, Matlab.

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1321 Eukaryotic Gene Prediction by an Investigation of Nonlinear Dynamical Modeling Techniques on EIIP Coded Sequences

Authors: Mai S. Mabrouk, Nahed H. Solouma, Abou-Bakr M. Youssef, Yasser M. Kadah

Abstract:

Many digital signal processing, techniques have been used to automatically distinguish protein coding regions (exons) from non-coding regions (introns) in DNA sequences. In this work, we have characterized these sequences according to their nonlinear dynamical features such as moment invariants, correlation dimension, and largest Lyapunov exponent estimates. We have applied our model to a number of real sequences encoded into a time series using EIIP sequence indicators. In order to discriminate between coding and non coding DNA regions, the phase space trajectory was first reconstructed for coding and non-coding regions. Nonlinear dynamical features are extracted from those regions and used to investigate a difference between them. Our results indicate that the nonlinear dynamical characteristics have yielded significant differences between coding (CR) and non-coding regions (NCR) in DNA sequences. Finally, the classifier is tested on real genes where coding and non-coding regions are well known.

Keywords: Gene prediction, nonlinear dynamics, correlation dimension, Lyapunov exponent.

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1320 Principle Knowledge of Integrated Pest Management Adopting Cotton Cultivators in Irrigated and Rainfed Conditions: A Critical Analysis

Authors: B. Sudhakar, K. A. Ponnusamy

Abstract:

In India cotton was the major commercial crop and cultivating all the states. In recent years, area of cotton declined due to pest and disease attack, drought, lower price for the produces etc. The first reason as pest and disease attack will be the challenges and it is of utmost importance that in future the insect problems would have to be tackled through Integrated Pest Management (IPM). The present study deals with principle knowledge of IPM adopting cotton cultivators in irrigated and rainfed conditions. Under irrigated conditions, among cultural practices, all respondents had principle knowledge about growing high yielding and pest resistant hybrids, sowing quality and certified seeds and avoiding cotton ratoon cropping. Regarding mechanical practices all respondents had principle knowledge about collecting and destroying egg, larvae and pupae of pests and removing and destroying pest and disease infected cotton squares, flowers and other shed materials. With regard to biological practices, 93% of them had principle knowledge about spraying neem oil, followed by 82% about tying Trichogramma eggcard. Among chemical practices, more than 90% of the respondents had principle knowledge about of spraying herbicide (96%), identifying ETL (Economic Threshold Level) for cotton pests (94%), and applying safe insecticides (90%). Under rainfed condition, among cultural practices, all respondents had principle knowledge about sowing quality and certified seeds and growing high yielding and pest resistant hybrids seeds. Regarding mechanical practices hundred percentage of the respondents had principle knowledge on the mechanical practices viz., collecting and destroying egg, larvae and pupae of pests and removing and destroying pest and disease infected cotton squares, flowers and other shed materials. With regard to biological practices, 96% of the respondents had correct in principle knowledge about spraying neem oil, followed by 89% about tying Trichogramma eggcard. With regard to chemical practices, more than 90% of the respondents had principle knowledge of applying safe insecticides (95%), avoiding repeated use of the same insecticides (95%), identifying ETL for cotton pests (94%) and applying granular insecticides (90%).

Keywords: Biological practices, chemical practices, cultural practices, mechanical practices, integrated pest management.

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1319 An Efficient Clustering Technique for Copy-Paste Attack Detection

Authors: N. Chaitawittanun, M. Munlin

Abstract:

Due to rapid advancement of powerful image processing software, digital images are easy to manipulate and modify by ordinary people. Lots of digital images are edited for a specific purpose and more difficult to distinguish form their original ones. We propose a clustering method to detect a copy-move image forgery of JPEG, BMP, TIFF, and PNG. The process starts with reducing the color of the photos. Then, we use the clustering technique to divide information of measuring data by Hausdorff Distance. The result shows that the purposed methods is capable of inspecting the image file and correctly identify the forgery.

Keywords: Image detection, forgery image, copy-paste.

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1318 Automatic Intelligent Analysis of Malware Behaviour

Authors: H. Dornhackl, K. Kadletz, R. Luh, P. Tavolato

Abstract:

In this paper, we describe the use of formal methods to model malware behaviour. The modelling of harmful behaviour rests upon syntactic structures that represent malicious procedures inside malware. The malicious activities are modelled by a formal grammar, where API calls’ components are the terminals and the set of API calls used in combination to achieve a goal are designated non-terminals. The combination of different non-terminals in various ways and tiers make up the attack vectors that are used by harmful software. Based on these syntactic structures a parser can be generated which takes execution traces as input for pattern recognition.

Keywords: Malware behaviour, modelling, parsing, search, pattern matching.

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1317 Starting Torque Study of Darrieus Wind Turbine

Authors: M. Douak, Z. Aouachria

Abstract:

The aim of our study is to project an optimized wind turbine of Darrieus type. This type of wind turbine is characterized by a low starting torque in comparison with the Savonius rotor allowing them to operate for a period greater than wind speed. This led us to reconsider the Darrieus rotor to optimize a design which will increase its starting torque. The study of a system of monitoring and control of the angle of attack of blade profile, which allows an auto start to wind speeds as low as possible is presented for the straight blade of Darrieus turbine. The study continues to extend to other configurations namely those of parabolic type.

Keywords: Darrieus turbine, pitch angle, self-stating, wind energy.

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1316 Orthosis and Finite Elements: A Study for Development of New Designs through Additive Manufacturing

Authors: M. Volpini, D. Alves, A. Horta, M. Borges, P. Reis

Abstract:

The gait pattern in people that present motor limitations foment the demand for auxiliary locomotion devices. These artifacts for movement assistance vary according to its shape, size and functional features, following the clinical applications desired. Among the ortheses of lower limbs, the ankle-foot orthesis aims to improve the ability to walk in people with different neuromuscular limitations, although they do not always answer patients' expectations for their aesthetic and functional characteristics. The purpose of this study is to explore the possibility of using new design in additive manufacturer to reproduce the shape and functional features of a ankle-foot orthesis in an efficient and modern way. Therefore, this work presents a study about the performance of the mechanical forces through the analysis of finite elements in an ankle-foot orthesis. It will be demonstrated a study of distribution of the stress on the orthopedic device in orthostatism and during the movement in the course of patient's walk.

Keywords: Additive manufacture, new designs, orthoses, finite elements.

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