Search results for: structural damage detection.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3070

Search results for: structural damage detection.

1150 Intelligent System for Breast Cancer Prognosis using Multiwavelet Packets and Neural Network

Authors: Sepehr M.H.Jamarani, M.H.Moradi, H.Behnam, G.A.Rezai Rad

Abstract:

This paper presents an approach for early breast cancer diagnostic by employing combination of artificial neural networks (ANN) and multiwaveletpacket based subband image decomposition. The microcalcifications correspond to high-frequency components of the image spectrum, detection of microcalcifications is achieved by decomposing the mammograms into different frequency subbands,, reconstructing the mammograms from the subbands containing only high frequencies. For this approach we employed different types of multiwaveletpacket. We used the result as an input of neural network for classification. The proposed methodology is tested using the Nijmegen and the Mammographic Image Analysis Society (MIAS) mammographic databases and images collected from local hospitals. Results are presented as the receiver operating characteristic (ROC) performance and are quantified by the area under the ROC curve.

Keywords: Breast cancer, neural networks, diagnosis, multiwavelet packet, microcalcification.

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1149 A Green Method for Selective Spectrophotometric Determination of Hafnium(IV) with Aqueous Extract of Ficus carica Tree Leaves

Authors: A. Boveiri Monji, H. Yousefnia, M. Haji Hosseini, S. Zolghadri

Abstract:

A clean spectrophotometric method for the determination of hafnium by using a green reagent, acidic extract of Ficus carica tree leaves is developed. In 6-M hydrochloric acid, hafnium reacts with this reagent to form a yellow product. The formed product shows maximum absorbance at 421 nm with a molar absorptivity value of 0.28 × 104 l mol⁻¹ cm⁻¹, and the method was linear in the 2-11 µg ml⁻¹ concentration range. The detection limit value was found to be 0.312 µg ml⁻¹. Except zirconium and iron, the selectivity was good, and most of the ions did not show any significant spectral interference at concentrations up to several hundred times. The proposed method was green, simple, low cost, and selective.

Keywords: Spectrophotometric determination, Ficus carica tree leaves, synthetic reagents, hafnium.

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1148 Active Contours with Prior Corner Detection

Authors: U.A.A. Niroshika, Ravinda G.N. Meegama

Abstract:

Deformable active contours are widely used in computer vision and image processing applications for image segmentation, especially in biomedical image analysis. The active contour or “snake" deforms towards a target object by controlling the internal, image and constraint forces. However, if the contour initialized with a lesser number of control points, there is a high probability of surpassing the sharp corners of the object during deformation of the contour. In this paper, a new technique is proposed to construct the initial contour by incorporating prior knowledge of significant corners of the object detected using the Harris operator. This new reconstructed contour begins to deform, by attracting the snake towards the targeted object, without missing the corners. Experimental results with several synthetic images show the ability of the new technique to deal with sharp corners with a high accuracy than traditional methods.

Keywords: Active Contours, Image Segmentation, Harris Operator, Snakes

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1147 Documents Emotions Classification Model Based on TF-IDF Weighting Measure

Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

Abstract:

Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.

Keywords: Emotion detection, TF-IDF, WEKA tool, classification algorithms.

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1146 High Performance Liquid Chromatographic Method for Determination of Colistin Sulfate and its Application in Medicated Premixand Animal Feed

Authors: S.Choosakoonkriang, S. Supaluknari, P. Puangkaew

Abstract:

The aim of the present study was to develop and validate an inexpensive and simple high performance liquid chromatographic (HPLC) method for the determination of colistin sulfate. Separation of colistin sulfate was achieved on a ZORBAX Eclipse XDB-C18 column using UV detection at λ=215 nm. The mobile phase was 30 mM sulfate buffer (pH 2.5):acetonitrile(76:24). An excellent linearity (r2=0.998) was found in the concentration range of 25 - 400 μg/mL. Intra- day and inter-day precisions of method (%RSD, n=3) were less than 7.9%.The developed and validated method was applied to determination of the content of colistin sulfate in medicated premix and animal feed sample.The recovery of colistin from animal feed was satisfactorily ranged from 90.92 to 93.77%. The results demonstrated that the HPLC method developed in this work is appropriate for direct determination of colistin sulfate in commercial medicated premixes and animal feed.

Keywords: Colistin sulfate, HPLC, medicated premix, animal feed

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1145 ROC Analysis of PVC Detection Algorithm using ECG and Vector-ECG Charateristics

Authors: J. S. Nah, A. Y. Jeon, J. H. Ro, G. R. Jeon

Abstract:

ECG analysis method was developed using ROC analysis of PVC detecting algorithm. ECG signal of MIT-BIH arrhythmia database was analyzed by MATLAB. First of all, the baseline was removed by median filter to preprocess the ECG signal. R peaks were detected for ECG analysis method, and normal VCG was extracted for VCG analysis method. Four PVC detecting algorithm was analyzed by ROC curve, which parameters are maximum amplitude of QRS complex, width of QRS complex, r-r interval and geometric mean of VCG. To set cut-off value of parameters, ROC curve was estimated by true-positive rate (sensitivity) and false-positive rate. sensitivity and false negative rate (specificity) of ROC curve calculated, and ECG was analyzed using cut-off value which was estimated from ROC curve. As a result, PVC detecting algorithm of VCG geometric mean have high availability, and PVC could be detected more accurately with amplitude and width of QRS complex.

Keywords: Vectorcardiogram (VCG), Premature Ventricular contraction (PVC), ROC (receiver operating characteristic) curve, ECG

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1144 Determining the Width and Depths of Cut in Milling on the Basis of a Multi-Dexel Model

Authors: Jens Friedrich, Matthias A. Gebele, Armin Lechler, Alexander Verl

Abstract:

Chatter vibrations and process instabilities are the most important factors limiting the productivity of the milling process. Chatter can leads to damage of the tool, the part or the machine tool. Therefore, the estimation and prediction of the process stability is very important. The process stability depends on the spindle speed, the depth of cut and the width of cut. In milling, the process conditions are defined in the NC-program. While the spindle speed is directly coded in the NC-program, the depth and width of cut are unknown. This paper presents a new simulation based approach for the prediction of the depth and width of cut of a milling process. The prediction is based on a material removal simulation with an analytically represented tool shape and a multi-dexel approach for the workpiece. The new calculation method allows the direct estimation of the depth and width of cut, which are the influencing parameters of the process stability, instead of the removed volume as existing approaches do. The knowledge can be used to predict the stability of new, unknown parts. Moreover with an additional vibration sensor, the stability lobe diagram of a milling process can be estimated and improved based on the estimated depth and width of cut.

Keywords: Dexel, process stability, material removal, milling.

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1143 Segmentation of Korean Words on Korean Road Signs

Authors: Lae-Jeong Park, Kyusoo Chung, Jungho Moon

Abstract:

This paper introduces an effective method of segmenting Korean text (place names in Korean) from a Korean road sign image. A Korean advanced directional road sign is composed of several types of visual information such as arrows, place names in Korean and English, and route numbers. Automatic classification of the visual information and extraction of Korean place names from the road sign images make it possible to avoid a lot of manual inputs to a database system for management of road signs nationwide. We propose a series of problem-specific heuristics that correctly segments Korean place names, which is the most crucial information, from the other information by leaving out non-text information effectively. The experimental results with a dataset of 368 road sign images show 96% of the detection rate per Korean place name and 84% per road sign image.

Keywords: Segmentation, road signs, characters, classification.

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1142 Biomass Gasification and Microcogeneration Unit – EZOB Technology

Authors: Martin Lisý, Marek Baláš, Michal Špiláček, Zdeněk Skála

Abstract:

This paper deals with the issue of biomass and sorted municipal waste gasification and cogeneration using hot-air turbo-set. It brings description of designed pilot plant with electrical output 80 kWe. The generated gas is burned in secondary combustion chamber located beyond the gas generator. Flue gas flows through the heat exchanger where the compressed air is heated and consequently brought to a micro turbine. Except description, this paper brings our basic experiences from operating of pilot plant (operating parameters, contributions, problems during operating, etc.). The principal advantage of the given cycle is the fact that there is no contact between the generated gas and the turbine. So there is no need for costly and complicated gas cleaning which is the main source of operating problems in direct use in combustion engines because the content of impurities in the gas causes operation problems to the units due to clogging and tarring of working surfaces of engines and turbines, which may lead as far as serious damage to the equipment under operation. Another merit is the compact container package making installation of the facility easier or making it relatively more mobile. We imagine, this solution of cogeneration from biomass or waste can be suitable for small industrial or communal applications, for low output cogeneration.

Keywords: Biomass, combustion, gasification, microcogeneration.

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1141 Fragility Assessment for Torsionally Asymmetric Buildings in Plan

Authors: S. Feli, S. Tavousi Tafreshi, A. Ghasemi

Abstract:

The present paper aims at evaluating the response of three-dimensional buildings with in-plan stiffness irregularities that have been subjected to two-way excitation ground motion records simultaneously. This study is broadly-based fragility assessment with greater emphasis on structural response at in-plan flexible and stiff sides. To this end, three type of three-dimensional 5-story steel building structures with stiffness eccentricities, were subjected to extensive nonlinear incremental dynamic analyses (IDA) utilizing Ibarra-Krawinkler deterioration models. Fragility assessment was implemented for different configurations of braces to investigate the losses in buildings with center of resisting (CR) eccentricities.

Keywords: Ibarra Krawinkler, fragility assessment, flexible and stiff side, center of resisting.

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1140 Adaptive Gaussian Mixture Model for Skin Color Segmentation

Authors: Reza Hassanpour, Asadollah Shahbahrami, Stephan Wong

Abstract:

Skin color based tracking techniques often assume a static skin color model obtained either from an offline set of library images or the first few frames of a video stream. These models can show a weak performance in presence of changing lighting or imaging conditions. We propose an adaptive skin color model based on the Gaussian mixture model to handle the changing conditions. Initial estimation of the number and weights of skin color clusters are obtained using a modified form of the general Expectation maximization algorithm, The model adapts to changes in imaging conditions and refines the model parameters dynamically using spatial and temporal constraints. Experimental results show that the method can be used in effectively tracking of hand and face regions.

Keywords: Face detection, Segmentation, Tracking, Gaussian Mixture Model, Adaptation.

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1139 Use of Ecommerce Websites in Developing Countries

Authors: Vera Pujani

Abstract:

The purpose of this study is to investiagte the use of the ecommerce website in Indonesia as a developing country. The ecommerce website has been identified having the significant impact on business activities in particular solving the geographical problem for islanded countries likes Indonesia. Again, website is identified as a crucial marketing tool. This study presents the effect of quality and features on the use and user satisfaction employing ecommerce websites. Survey method for 115 undergraduate students of Management Department in Andalas University who are attending Management Information Systems (SIM) class have been undertaken. The data obtained is analyzed using Structural Equation Modeling (SEM) using SmartPLS program. This result found that quality of system and information, feature as well satisfaction influencing the use ecommerce website in Indonesia contexts.

Keywords: Use, Developing Country, Satisfaction, Website

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1138 Improvement of Ground Truth Data for Eye Location on Infrared Driver Recordings

Authors: Sorin Valcan, Mihail Găianu

Abstract:

Labeling is a very costly and time consuming process which aims to generate datasets for training neural networks in several functionalities and projects. For driver monitoring system projects, the need of labeled images has a significant impact on the budget and distribution of effort. This paper presents the modifications done to a ground truth data generation algorithm for 2D eyes location on infrared images with drivers in order to improve the quality of the data and performance of the trained neural networks. The algorithm restrictions become tougher which makes it more accurate but also less constant. The resulting dataset becomes smaller and shall not be altered by any kind of manual labels adjustment before being used in the neural networks training process. These changes resulted in a much better performance of the trained neural networks.

Keywords: Labeling automation, infrared camera, driver monitoring, eye detection, Convolutional Neural Networks.

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1137 Graphene/ZnO/Polymer Nanocomposite Thin Film for Separation of Oil-Water Mixture

Authors: Suboohi Shervani, Jingjing Ling, Jiabin Liu, Tahir Husain

Abstract:

Offshore oil-spill has become the most emerging problem in the world. In the current paper, a graphene/ZnO/polymer nanocomposite thin film is coated on stainless steel mesh via layer by layer deposition method. The structural characterization of materials is determined by Scanning Electron Microscopy (SEM) and X-ray diffraction (XRD). The total petroleum hydrocarbons (TPHs) and separation efficiency have been measured via gas chromatography – flame ionization detector (GC-FID). TPHs are reduced to 2 ppm and separation efficiency of the nanocomposite coated mesh is reached ≥ 99% for the final sample. The nanocomposite coated mesh acts as a promising candidate for the separation of oil- water mixture.

Keywords: Oil-spill, graphene, oil-water separation, nanocomposite.

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1136 Audio Watermarking Based on Compression-expansion Technique

Authors: Say Wei Foo, Qi Dong

Abstract:

A novel robust audio watermarking scheme is proposed in this paper. In the proposed scheme, the host audio signals are segmented into frames. Two consecutive frames are assessed if they are suitable to represent a watermark bit. If so, frequency transform is performed on these two frames. The compressionexpansion technique is adopted to generate distortion over the two frames. The distortion is used to represent one watermark bit. Psychoacoustic model is applied to calculate local auditory mask to ensure that the distortion is not audible. The watermarking schemes using mono and stereo audio signals are designed differently. The correlation-based detection method is used to detect the distortion and extract embedded watermark bits. The experimental results show that the quality degradation caused by the embedded watermarks is perceptually transparent and the proposed schemes are very robust against different types of attacks.

Keywords: Audio watermarking, Compression-expansion, Stereo signals, Robustness.

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1135 Words Reordering based on Statistical Language Model

Authors: Theologos Athanaselis, Stelios Bakamidis, Ioannis Dologlou

Abstract:

There are multiple reasons to expect that detecting the word order errors in a text will be a difficult problem, and detection rates reported in the literature are in fact low. Although grammatical rules constructed by computer linguists improve the performance of grammar checker in word order diagnosis, the repairing task is still very difficult. This paper presents an approach for repairing word order errors in English text by reordering words in a sentence and choosing the version that maximizes the number of trigram hits according to a language model. The novelty of this method concerns the use of an efficient confusion matrix technique for reordering the words. The comparative advantage of this method is that works with a large set of words, and avoids the laborious and costly process of collecting word order errors for creating error patterns.

Keywords: Permutations filtering, Statistical languagemodel N-grams, Word order errors

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1134 Migration and Unemployment Duration: The Case of the OECD Countries

Authors: Vincent Fromentin

Abstract:

This paper examines whether or not immigration has a positive influence on the duration of unemployment, in a macroeconomic perspective. We analyse also whether the degree of labor market integration can influence migration. The integration of immigrants into the labor market is a recurrence theme in the work on the economic consequences of immigration. However, to our knowledge, no researchers have studied the impact of immigration on unemployment duration, and vice versa. With two methodology of research (panel estimations (OLS and 2SLS) and panel cointegration techniques), we show that migration seems to influence positively the short-term unemployment and negatively long-term unemployment, for 14 OECD destination countries. In addition, immigration seems to be conditioned by the structural and institutional characteristics of the labour market.

Keywords: international migration, unemployment duration, OECD countries, panel data

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1133 A K-Means Based Clustering Approach for Finding Faulty Modules in Open Source Software Systems

Authors: Parvinder S. Sandhu, Jagdeep Singh, Vikas Gupta, Mandeep Kaur, Sonia Manhas, Ramandeep Sidhu

Abstract:

Prediction of fault-prone modules provides one way to support software quality engineering. Clustering is used to determine the intrinsic grouping in a set of unlabeled data. Among various clustering techniques available in literature K-Means clustering approach is most widely being used. This paper introduces K-Means based Clustering approach for software finding the fault proneness of the Object-Oriented systems. The contribution of this paper is that it has used Metric values of JEdit open source software for generation of the rules for the categorization of software modules in the categories of Faulty and non faulty modules and thereafter empirically validation is performed. The results are measured in terms of accuracy of prediction, probability of Detection and Probability of False Alarms.

Keywords: K-Means, Software Fault, Classification, ObjectOriented Metrics.

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1132 Absorbed Dose Measurement in Gonads Menduring Abdominal and Pelvicradiotherapy

Authors: Sadegh Masoudi, Ali Asghar Yousefi, Somayeh Nourollahi, Fatemeh Noughani

Abstract:

Two different testicular tissues have to be distinguished in regard to radiation damage: first the seminiferous tubules, corresponding to the sites of spermatogenesis, which are extremely radiosensitive. Second the testosterone secreting Leydig cells, which are considered to be less radiosensitive. This study aims to estimate testicular dose and the associated risks for infertility and hereditary effects from Abdominal and pelvic irradiation. Radiotherapy was simulated on a humanoid phantom using a 15 MV photon beam. Testicular dose was measured for various field sizes and tissue thicknesses along beam axis using an ionization chamber and TLD. For transmission Factor Also common method of measuring the absorbed dose distribution and electron contamination in the build-up region of high-energy beams for radiation therapy is by means of parallel-plate Ionisation chambers. Gonadal dose was reduced by placing lead cups around the testes supplemented by a field edge block. For a tumor dose of 100 cGy, testicular dose was 2.96-8.12 cGy depending upon the field size and the distance from the inferior field edge. The treatment at parameters, the presence of gonad shield and the somatometric characteristics determine whether testicular dose can exceed 1 Gy which allows a complete recovery of spermatogenesis.

Keywords: Absorbed Dose, Abdominal and pelvic, gonads men, Radiotherapy.

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1131 Nonlinear Conduction in Pure and Doped ZnO Varistors

Authors: A. Sedky, E. El-Suheel

Abstract:

We report here structural, mechanical and I-V characteristics of Zn1-xMxO ceramic samples with various x and M. It is found that the considered dopants does not influence the wellknown peaks related to wurtzite structure of ZnO ceramics, while the shape and size of grains are clearly affected. Average crystalline diameters, deduced from XRD are between 42 nm and 54 nm, which are 70 times lower than those obtained from SEM micrographs. Interestingly, the potential barrier could be formed by adding Cu up to 0.20, and it is completely deformed by 0.025 Ni additions. The breakdown field could be enhanced up to 4138 V/cm by 0.025 Cu additions, followed by a decrease with further increase of Cu . On the other hand a gradual decrease in VHN is reported for both dopants and their values are higher in Ni samples as compared to Cu samples. The electrical conductivity is generally improved by Ni, while addition of Cu improved it only in the over doped region (≥ 0.10). These results are discussed in terms of the difference of valency and ferromagnetic ordering for both dopants as compared to undoped sample.

Keywords: Semiconductors, Chemical Synthesis, Impurities and Electronic Transport

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1130 Machine Learning Methods for Environmental Monitoring and Flood Protection

Authors: Alexander L. Pyayt, Ilya I. Mokhov, Bernhard Lang, Valeria V. Krzhizhanovskaya, Robert J. Meijer

Abstract:

More and more natural disasters are happening every year: floods, earthquakes, volcanic eruptions, etc. In order to reduce the risk of possible damages, governments all around the world are investing into development of Early Warning Systems (EWS) for environmental applications. The most important task of the EWS is identification of the onset of critical situations affecting environment and population, early enough to inform the authorities and general public. This paper describes an approach for monitoring of flood protections systems based on machine learning methods. An Artificial Intelligence (AI) component has been developed for detection of abnormal dike behaviour. The AI module has been integrated into an EWS platform of the UrbanFlood project (EU Seventh Framework Programme) and validated on real-time measurements from the sensors installed in a dike.

Keywords: Early Warning System, intelligent environmentalmonitoring, machine learning, flood protection.

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1129 Multiplayer Game System for Therapeutic Exercise in Which Players with Different Athletic Abilities Can Participate on an Even Competitive Footing

Authors: Kazumoto Tanaka, Takayuki Fujino

Abstract:

Sports games conducted as a group are a form of therapeutic exercise for aged people with decreased strength and for people suffering from permanent damage of stroke and other conditions. However, it is difficult for patients with different athletic abilities to play a game on an equal footing. This study specifically examines a computer video game designed for therapeutic exercise, and a game system with support given depending on athletic ability. Thereby, anyone playing the game can participate equally. This video-game, to be specific, is a popular variant of balloon volleyball, in which players hit a balloon by hand before it falls to the floor. In this game system, each player plays the game watching a monitor on which the system displays tailor-made video-game images adjusted to the person’s athletic ability, providing players with player-adaptive assist support. We have developed a multiplayer game system with an image generation technique for the tailor-made video-game and conducted tests to evaluate it.

Keywords: Therapeutic exercise, computer video game, disability-adaptive assist, tailor-made video-game image.

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1128 Adaptive Dynamic Time Warping for Variable Structure Pattern Recognition

Authors: S. V. Yendiyarov

Abstract:

Pattern discovery from time series is of fundamental importance. Particularly, when information about the structure of a pattern is not complete, an algorithm to discover specific patterns or shapes automatically from the time series data is necessary. The dynamic time warping is a technique that allows local flexibility in aligning time series. Because of this, it is widely used in many fields such as science, medicine, industry, finance and others. However, a major problem of the dynamic time warping is that it is not able to work with structural changes of a pattern. This problem arises when the structure is influenced by noise, which is a common thing in practice for almost every application. This paper addresses this problem by means of developing a novel technique called adaptive dynamic time warping.

Keywords: Pattern recognition, optimal control, quadratic programming, dynamic programming, dynamic time warping, sintering control.

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1127 Fast Facial Feature Extraction and Matching with Artificial Face Models

Authors: Y. H. Tsai, Y. W. Chen

Abstract:

Facial features are frequently used to represent local properties of a human face image in computer vision applications. In this paper, we present a fast algorithm that can extract the facial features online such that they can give a satisfying representation of a face image. It includes one step for a coarse detection of each facial feature by AdaBoost and another one to increase the accuracy of the found points by Active Shape Models (ASM) in the regions of interest. The resulted facial features are evaluated by matching with artificial face models in the applications of physiognomy. The distance measure between the features and those in the fate models from the database is carried out by means of the Hausdorff distance. In the experiment, the proposed method shows the efficient performance in facial feature extractions and online system of physiognomy.

Keywords: Facial feature extraction, AdaBoost, Active shapemodel, Hausdorff distance

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1126 Rapid Study on Feature Extraction and Classification Models in Healthcare Applications

Authors: S. Sowmyayani

Abstract:

The advancement of computer-aided design helps the medical force and security force. Some applications include biometric recognition, elderly fall detection, face recognition, cancer recognition, tumor recognition, etc. This paper deals with different machine learning algorithms that are more generically used for any health care system. The most focused problems are classification and regression. With the rise of big data, machine learning has become particularly important for solving problems. Machine learning uses two types of techniques: supervised learning and unsupervised learning. The former trains a model on known input and output data and predicts future outputs. Classification and regression are supervised learning techniques. Unsupervised learning finds hidden patterns in input data. Clustering is one such unsupervised learning technique. The above-mentioned models are discussed briefly in this paper.

Keywords: Supervised learning, unsupervised learning, regression, neural network.

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1125 Ultrasonic Echo Image Adaptive Watermarking Using the Just-Noticeable Difference Estimation

Authors: Amnach Khawne, Kazuhiko Hamamoto, Orachat Chitsobhuk

Abstract:

Most of the image watermarking methods, using the properties of the human visual system (HVS), have been proposed in literature. The component of the visual threshold is usually related to either the spatial contrast sensitivity function (CSF) or the visual masking. Especially on the contrast masking, most methods have not mention to the effect near to the edge region. Since the HVS is sensitive what happens on the edge area. This paper proposes ultrasound image watermarking using the visual threshold corresponding to the HVS in which the coefficients in a DCT-block have been classified based on the texture, edge, and plain area. This classification method enables not only useful for imperceptibility when the watermark is insert into an image but also achievable a robustness of watermark detection. A comparison of the proposed method with other methods has been carried out which shown that the proposed method robusts to blockwise memoryless manipulations, and also robust against noise addition.

Keywords: Medical image watermarking, Human Visual System, Image Adaptive Watermark

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1124 Vessel Inscribed Trigonometry to Measure the Vessel Progressive Orientations in the Digital Fundus Image

Authors: Pil Un Kim, Yunjung Lee, Gihyoun Lee, Jin Ho Cho, Myoung Nam Kim

Abstract:

In this paper, the vessel inscribed trigonometry (VITM) for the vessel progression orientation (VPO) is proposed in the two-dimensional fundus image. The VPO is a major factor in the optic disc (OD) detection which is a basic process in the retina analysis. To measure the VPO, skeletons of vessel are used. First, the vessels are classified into three classes as vessel end, vessel branch and vessel stem. And the chain code maps of VS are generated. Next, two farthest neighborhoods of each point on VS are searched by the proposed angle restriction. Lastly, a gradient of the straight line between two farthest neighborhoods is estimated to measure the VPO. VITM is validated by comparing with manual results and 2D Gaussian templates. It is confirmed that VPO of the proposed mensuration is correct enough to detect OD from the results of experiment which applied VITM to detect OD in fundus images.

Keywords: Angle measurement, Optic disc, Retina vessel, Vessel progression orientation.

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1123 Energy Efficient Clustering and Data Aggregation in Wireless Sensor Networks

Authors: Surender Kumar Soni

Abstract:

Wireless Sensor Networks (WSNs) are wireless networks consisting of number of tiny, low cost and low power sensor nodes to monitor various physical phenomena like temperature, pressure, vibration, landslide detection, presence of any object, etc. The major limitation in these networks is the use of nonrechargeable battery having limited power supply. The main cause of energy consumption WSN is communication subsystem. This paper presents an efficient grid formation/clustering strategy known as Grid based level Clustering and Aggregation of Data (GCAD). The proposed clustering strategy is simple and scalable that uses low duty cycle approach to keep non-CH nodes into sleep mode thus reducing energy consumption. Simulation results demonstrate that our proposed GCAD protocol performs better in various performance metrics.

Keywords: Ad hoc network, Cluster, Grid base clustering, Wireless sensor network.

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1122 3D Dynamic Representation System for the Human Head

Authors: Laurenţiu Militeanu, Cristina Gena Dascâlu, D. Cristea

Abstract:

The human head representations usually are based on the morphological – structural components of a real model. Over the time became more and more necessary to achieve full virtual models that comply very rigorous with the specifications of the human anatomy. Still, making and using a model perfectly fitted with the real anatomy is a difficult task, because it requires large hardware resources and significant times for processing. That is why it is necessary to choose the best compromise solution, which keeps the right balance between the details perfection and the resources consumption, in order to obtain facial animations with real-time rendering. We will present here the way in which we achieved such a 3D system that we intend to use as a base point in order to create facial animations with real-time rendering, used in medicine to find and to identify different types of pathologies.

Keywords: 3D models, virtual reality.

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1121 Money Laundering and Financing of Terrorism

Authors: C. Mallada Fernández

Abstract:

Economic development and globalization of international markets have created a favourable atmosphere for the emergence of new forms of crime such as money laundering or financing of terrorism, which may contribute to destabilized and damage economic systems. In particular, money laundering have acquired great importance since the 11S attacks, what has caused on the one hand, the establishment and development of preventive measures and, on the other hand, a progressive hardening of penal measures. Since then, the regulations imposed to fight against money laundering have been viewed as key components also in the fight against terrorist financing. Terrorism, at the beginning, was a “national” crime connected with internal problems of the State (for instance the RAF in Germany or ETA in Spain) but in the last 20 years has started to be an international problem that is connected with the defence and security of the States. Therefore, the new strategic concept for the defense and security of NATO has a comprehensive list of security threats to the Alliance, such as terrorism, international instability, money laundering or attacks on cyberspace, among others. With this new concept, money laundering and terrorism has become a priority in the national defense.

In this work we will analyze the methods to combat these new threats to the national security. We will study the preventive legislations to combat money laundering and financing of terrorism, the UIF that exchange information between States, and the hawala-Banking.

Keywords: Control of financial flows, money laundering, terrorism, financing of terrorism.

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