Search results for: Disease detection
638 Review of Surface Electromyogram Signals: Its Analysis and Applications
Authors: Anjana Goen, D. C. Tiwari
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Electromyography (EMG) is the study of muscles function through analysis of electrical activity produced from muscles. This electrical activity which is displayed in the form of signal is the result of neuromuscular activation associated with muscle contraction. The most common techniques of EMG signal recording are by using surface and needle/wire electrode where the latter is usually used for interest in deep muscle. This paper will focus on surface electromyogram (SEMG) signal. During SEMG recording, several problems had to been countered such as noise, motion artifact and signal instability. Thus, various signal processing techniques had been implemented to produce a reliable signal for analysis. SEMG signal finds broad application particularly in biomedical field. It had been analyzed and studied for various interests such as neuromuscular disease, enhancement of muscular function and human-computer interface.
Keywords: Evolvable hardware (EHW), Functional Electrical Simulation (FES), Hidden Markov Model (HMM), Hjorth Time Domain (HTD).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3504637 Secondary School Students- Perceptions about Biological Issues in South Korea
Authors: Jung-Hyun Kim, Kew-Cheol Shim, Shin-Cheol Song, Kyoungho Kim, Nam-Il Kim, Jinho Bae, Keum-Hyun So
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The purpose of present paper was to investigate perceptions of Korean secondary school students about social issues related to biological sciences. Twenty issues were selected based on topics of articles in the newspaper from 2005 to 2010. The issues were categorized into biotechnology, health-disease and environment domains. Subjects were 541 high school students (male 253 and female 288). On the survey, students were asked to answer on 5-point Lickert scales how they thought of the effect of biological phenomena or events related to biological issues on the individual life and the society. They perceived that the biological issues would be more effectible on the society than on the individual life. Female students had a little more perceptions than males.Keywords: biological issue, biological sciences, perception, secondary school
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1782636 Numerical Study of Fiber Bragg Grating Sensor: Longitudinal and Transverse Detection of Temperature and Strain
Authors: K. Khelil, H. Ammar, K. Saouchi
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Fiber Bragg Grating (FBG) structure is an periodically modulated optical fiber. It acts as a selective filter of wavelength whose reflected peak is called Bragg wavelength and it depends on the period of the fiber and the refractive index. The simulation of FBG is based on solving the Coupled Mode Theory equation by using the Transfer Matrix Method which is carried out using MATLAB. It is found that spectral reflectivity is shifted when the change of temperature and strain is uniform. Under non-uniform temperature or strain perturbation, the spectrum is both shifted and destroyed. In case of transverse loading, reflectivity spectrum is split into two peaks, the first is specific to X axis, and the second belongs to Y axis. FBGs are used in civil engineering to detect perturbations applied to buildings.
Keywords: Bragg wavelength, coupled mode theory, optical fiber, temperature measurement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 864635 Indicator of Small Calcification Detection in Ultrasonography using Decorrelation of Forward Scattered Waves
Authors: Hirofumi Taki, Takuya Sakamoto, Makoto Yamakawa, Tsuyoshi Shiina, Toru Sato
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For the improvement of the ability in detecting small calcifications using Ultrasonography (US) we propose a novel indicator of calcifications in an ultrasound B-mode image without decrease in frame rate. Since the waveform of an ultrasound pulse changes at a calcification position, the decorrelation of adjacent scan lines occurs behind a calcification. Therefore, we employ the decorrelation of adjacent scan lines as an indicator of a calcification. The proposed indicator depicted wires 0.05 mm in diameter at 2 cm depth with a sensitivity of 86.7% and a specificity of 100%, which were hardly detected in ultrasound B-mode images. This study shows the potential of the proposed indicator to approximate the detectable calcification size using an US device to that of an X-ray imager, implying the possibility that an US device will become a convenient, safe, and principal clinical tool for the screening of breast cancer.Keywords: Ultrasonography, Calcification, Decorrelation, Forward scattered wave
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1438634 Detection and Analysis of Deficiencies in Groundnut Plant using Geometric Moments
Authors: Sumeet S. Nisale, Chandan J. Bharambe, Vidya N.More
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We propose our genuine research of geometric moments which detects the mineral inadequacy in the frail groundnut plant. This plant is prone to many deficiencies as a result of the variance in the soil nutrients. By analyzing the leaves of the plant, we detect the visual symptoms that are not recognizable to the naked eyes. We have collected about 160 samples of leaves from the nearby fields. The images have been taken by keeping every leaf into a black box to avoid the external interference. For the first time, it has been possible to provide the farmer with the stages of deficiencies. This paper has applied the algorithms successfully to many other plants like Lady-s finger, Green Bean, Lablab Bean, Chilli and Tomato. But we submit the results of the groundnut predominantly. The accuracy of our algorithm and method is almost 93%. This will again pioneer a kind of green revolution in the field of agriculture and will be a boon to that field.Keywords: Component image, geometric moments, average intensity, average affected area, black box
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2117633 Speech Enhancement of Vowels Based on Pitch and Formant Frequency
Authors: R. Rishma Rodrigo, R. Radhika, M. Vanitha Lakshmi
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Numerous signal processing based speech enhancement systems have been proposed to improve intelligibility in the presence of noise. Traditionally, studies of neural vowel encoding have focused on the representation of formants (peaks in vowel spectra) in the discharge patterns of the population of auditory-nerve (AN) fibers. A method is presented for recording high-frequency speech components into a low-frequency region, to increase audibility for hearing loss listeners. The purpose of the paper is to enhance the formant of the speech based on the Kaiser window. The pitch and formant of the signal is based on the auto correlation, zero crossing and magnitude difference function. The formant enhancement stage aims to restore the representation of formants at the level of the midbrain. A MATLAB software’s are used for the implementation of the system with low complexity is developed.
Keywords: Formant estimation, formant enhancement, pitch detection, speech analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1629632 Hybrid Honeypot System for Network Security
Authors: Kyi Lin Lin Kyaw
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Nowadays, we are facing with network threats that cause enormous damage to the Internet community day by day. In this situation, more and more people try to prevent their network security using some traditional mechanisms including firewall, Intrusion Detection System, etc. Among them honeypot is a versatile tool for a security practitioner, of course, they are tools that are meant to be attacked or interacted with to more information about attackers, their motives and tools. In this paper, we will describe usefulness of low-interaction honeypot and high-interaction honeypot and comparison between them. And then we propose hybrid honeypot architecture that combines low and high -interaction honeypot to mitigate the drawback. In this architecture, low-interaction honeypot is used as a traffic filter. Activities like port scanning can be effectively detected by low-interaction honeypot and stop there. Traffic that cannot be handled by low-interaction honeypot is handed over to high-interaction honeypot. In this case, low-interaction honeypot is used as proxy whereas high-interaction honeypot offers the optimal level realism. To prevent the high-interaction honeypot from infections, containment environment (VMware) is used.Keywords: Low-interaction honeypot, High-interactionhoneypot, VMware, Proxy
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2938631 Multidimensional Data Mining by Means of Randomly Travelling Hyper-Ellipsoids
Authors: Pavel Y. Tabakov, Kevin Duffy
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The present study presents a new approach to automatic data clustering and classification problems in large and complex databases and, at the same time, derives specific types of explicit rules describing each cluster. The method works well in both sparse and dense multidimensional data spaces. The members of the data space can be of the same nature or represent different classes. A number of N-dimensional ellipsoids are used for enclosing the data clouds. Due to the geometry of an ellipsoid and its free rotation in space the detection of clusters becomes very efficient. The method is based on genetic algorithms that are used for the optimization of location, orientation and geometric characteristics of the hyper-ellipsoids. The proposed approach can serve as a basis for the development of general knowledge systems for discovering hidden knowledge and unexpected patterns and rules in various large databases.Keywords: Classification, clustering, data minig, genetic algorithms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1761630 Real-time Tracking in Image Sequences based-on Parameters Updating with Temporal and Spatial Neighborhoods Mixture Gaussian Model
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Gaussian mixture background model is widely used in moving target detection of the image sequences. However, traditional Gaussian mixture background model usually considers the time continuity of the pixels, and establishes background through statistical distribution of pixels without taking into account the pixels- spatial similarity, which will cause noise, imperfection and other problems. This paper proposes a new Gaussian mixture modeling approach, which combines the color and gradient of the spatial information, and integrates the spatial information of the pixel sequences to establish Gaussian mixture background. The experimental results show that the movement background can be extracted accurately and efficiently, and the algorithm is more robust, and can work in real time in tracking applications.Keywords: Gaussian mixture model, real-time tracking, sequence image, gradient.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1466629 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1387628 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 726627 Active Contours with Prior Corner Detection
Authors: U.A.A. Niroshika, Ravinda G.N. Meegama
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2261626 Documents Emotions Classification Model Based on TF-IDF Weighting Measure
Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1700625 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
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8139624 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
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2929623 Segmentation of Korean Words on Korean Road Signs
Authors: Lae-Jeong Park, Kyusoo Chung, Jungho Moon
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2731622 Pervasive Computing in Healthcare Systems
Authors: Elham Rastegari, Amirmasood Rahmani, Saeed Setayeshi
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The hospital and the health-care center of a community, as a place for people-s life-care and health-care settings, must provide more and better services for patients or residents. After Establishing Electronic Medical Record (EMR) system -which is a necessity- in the hospital, providing pervasive services is a further step. Our objective in this paper is to use pervasive computing in a case study of healthcare, based on EMR database that coordinates application services over network to form a service environment for medical and health-care. Our method also categorizes the hospital spaces into 3 spaces: Public spaces, Private spaces and Isolated spaces. Although, there are many projects about using pervasive computing in healthcare, but all of them concentrate on the disease recognition, designing smart cloths, or provide services only for patient. The proposed method is implemented in a hospital. The obtained results show that it is suitable for our purpose.Keywords: Pervasive computing, RFID, Health-care.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2993621 Investigation of Genetic Epidemiology of Metabolic Compromises in ß Thalassemia Minor Mutation: Phenotypic Pleiotropy
Authors: Surajit Debnath, Soma Addya
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Human genome is not only the evolutionary summation of all advantageous events, but also houses lesions of deleterious foot prints. A single gene mutation sometimes may express multiple consequences in numerous tissues and a linear relationship of the genotype and the phenotype may often be obscure. ß Thalassemia minor, a transfusion independent mild anaemia, coupled with environment among other factors may articulate into phenotypic pleotropy with Hypocholesterolemia, Vitamin D deficiency, Tissue hypoxia, Hyper-parathyroidism and Psychological alterations. Occurrence of Pancreatic insufficiency, resultant steatorrhoea, Vitamin-D (25-OH) deficiency (13.86 ngm/ml) with Hypocholesterolemia (85mg/dl) in a 30 years old male ß Thal-minor patient (Hemoglobin 11mg/dl with Fetal Hemoglobin 2.10%, Hb A2 4.60% and Hb Adult 84.80% and altered Hemogram) with increased Para thyroid hormone (62 pg/ml) & moderate Serum Ca+2 (9.5mg/ml) indicate towards a cascade of phenotypic pleotropy where the ß Thalassemia mutation ,be it in the 5’ cap site of the mRNA , differential splicing etc in heterozygous state is effecting several metabolic pathways. Compensatory extramedulary hematopoiesis may not coped up well with the stressful life style of the young individual and increased erythropoietic stress with high demand for cholesterol for RBC membrane synthesis may have resulted in Hypocholesterolemia.Oxidative stress and tissue hypoxia may have caused the pancreatic insufficiency, leading to Vitamin D deficiency. This may in turn have caused the secondary hyperparathyroidism to sustain serum Calcium level. Irritability and stress intolerance of the patient was a cumulative effect of the vicious cycle of metabolic compromises. From these findings we propose that the metabolic deficiencies in the ß Thalassemia mutations may be considered as the phenotypic display of the pleotropy to explain the genetic epidemiology. According to the recommendations from the NIH Workshop on Gene-Environment Interplay in Common Complex Diseases: Forging an Integrative Model, study design of observations should be informed by gene-environment hypotheses and results of a study (genetic diseases) should be published to inform future hypotheses. Variety of approaches is needed to capture data on all possible aspects, each of which is likely to contribute to the etiology of disease. Speakers also agreed that there is a need for development of new statistical methods and measurement tools to appraise information that may be missed out by conventional method where large sample size is needed to segregate considerable effect. A meta analytic cohort study in future may bring about significant insight on to the title comment.Keywords: Genetic disease, Genetic epidemiology, Heterozygous, Phenotype, Pleotropy, ß Thalassemia minor, Metabolic compromises.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6548620 Adaptive Gaussian Mixture Model for Skin Color Segmentation
Authors: Reza Hassanpour, Asadollah Shahbahrami, Stephan Wong
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2401619 Improvement of Ground Truth Data for Eye Location on Infrared Driver Recordings
Authors: Sorin Valcan, Mihail Găianu
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 383618 Audio Watermarking Based on Compression-expansion Technique
Authors: Say Wei Foo, Qi Dong
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1631617 Words Reordering based on Statistical Language Model
Authors: Theologos Athanaselis, Stelios Bakamidis, Ioannis Dologlou
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1572616 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2291615 Machine Learning Methods for Environmental Monitoring and Flood Protection
Authors: Alexander L. Pyayt, Ilya I. Mokhov, Bernhard Lang, Valeria V. Krzhizhanovskaya, Robert J. Meijer
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4075614 Fast Facial Feature Extraction and Matching with Artificial Face Models
Authors: Y. H. Tsai, Y. W. Chen
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1796613 Rapid Study on Feature Extraction and Classification Models in Healthcare Applications
Authors: S. Sowmyayani
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 322612 Ultrasonic Echo Image Adaptive Watermarking Using the Just-Noticeable Difference Estimation
Authors: Amnach Khawne, Kazuhiko Hamamoto, Orachat Chitsobhuk
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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
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1589611 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1401610 Energy Efficient Clustering and Data Aggregation in Wireless Sensor Networks
Authors: Surender Kumar Soni
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3123609 Post-Compression Consideration in Video Watermarking for Wireless Communication
Authors: Chuen-Ching Wang, Yao-Tang Chang, Yu-Chang Hsu
Abstract:
A simple but effective digital watermarking scheme utilizing a context adaptive variable length coding (CAVLC) method is presented for wireless communication system. In the proposed approach, the watermark bits are embedded in the final non-zero quantized coefficient of each DCT block, thereby yielding a potential reduction in the length of the coded block. As a result, the watermarking scheme not only provides the means to check the authenticity and integrity of the video stream, but also improves the compression ratio and therefore reduces both the transmission time and the storage space requirements of the coded video sequence. The results confirm that the proposed scheme enables the detection of malicious tampering attacks and reduces the size of the coded H.264 file. Therefore, the current study is feasible to apply in the video applications of wireless communication such as 3G systemKeywords: 3G, wireless communication, CAVLC, digitalwatermarking, motion compensation
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