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The rapid increase in urban population due to the urbanization has led to one of the major problems in urban areas, namely, traffic congestion. With the constraint on road surface in urban areas and limited city budget, it is almost impossible to build additional streets and/or increase the road surface to support such the increase in urban traffic. As a result, a new technology known as Virtual Traffic...
In many application Floating point Arithmetic is basic building blocks such as Scientific, digital signal processing and numeric. In this Floating point Arithmetic, Multiplication is most commonly used method. This multipliers are going to discussing about the double precision multiplier. This double precision operation is performed in the form of IEEE-754 FP (floating point) standard format. The...
Emotion play an important role at several activities in the present world. Human decision making, cognitive process and interaction between human & machine all the activities depends on human emotions. Facial expression, musical activities and several approaches used to find the human emotions. In this paper EEG is used to find the accurate emotion. Emotion classification is the huge task. Classification...
Detection of moving objects is one of the key steps for vision based applications. Many previous works leverage background subtraction using background models and assume that image sequences are captured from a stationary camera. These methods are not directly applied to image sequences from a moving camera because both foreground and background objects move with respect to the camera. One of the...
Cardiovascular disease (CVD) is the leading cause of death throughout the world. Since electrocardiogram-reports (ECG) have a great CVD predicting potential, the demand for their real-time analysis is high. Although algorithms are present to perform analysis, most countries still use analogue acquisition systems that can only output a printed trace. It is necessary to extract the signal from these...
Radiologists are known to suffer from fatigue and drop in diagnostic accuracy due to large number of slices to read and long working hours. A computer aided diagnosis (CAD) system could help lighten the workload. Segmentation is the first step in a CAD system. This study aims to propose an accurate automatic segmentation. This study deals with High Resolution Computed Tomography (HRCT) scans of the...
This paper describes the development of a system that uses off the shelf ranging technology (distance cameras) to acquire a real-time multidimensional respiratory signal from a 3D surface reconstruction of the patient's chest and abdomen without the use of markers. The preliminary measurements are discussed within the context of the use of such a system with an existing CT scanner.
This paper presents an effective re-ranking method that uses learning-to-rank paradigms to improve the accuracy of landmark-based audio fingerprinting (AFP) for audio music retrieval. The re-ranking mechanism is invoked whenever the returned ranking from an AFP system does not have a high enough confidence measure. We propose that use of new features for re-ranking, and employ the popular learning-to-rank...
The paper discusses the development of emotion recognition system which can be applied to a wider range of human population. This is achieved by measuring the unique electromagnetic (EM) signal generated upon invoking certain emotions. A set of audio-visual stimulants is designed to invoke the desired emotions under study that are happy, sad and nervous. A set of questionnaire is developed to verify...
The paper proposes cognitive learning technique for predicting the destination in a video conference being held over an organizational network. The dataset comprised of 22801 connectivity records of video conferences held during the year 2010–2013. Naive Bayes, k-NN and decision tree were trained on the dataset and the performance of the learning algorithms were evaluated. The destination has been...
Whole brain tractography generates a very huge dataset composed by various tracts of different shapes, lengths, positions. Then clustering them into anatomically meaningful bundles is a challenge. Until now, several clustering methods have been proposed such as methods based on similarity measures or methods based on anatomical information, but no optimal clustering criteria were found yet. All methods...
Developing efficient and usable brain-computer interfaces (BCIs) requires well-designed trade-off between accuracy and computational time. This paper presents a very fast and accurate method to classify asynchronous brain signals from a multi-class mental tasks dataset using time-domain features. Five different statistical time-domain features were extracted to characterize various properties of three...
Word level Script and language identification is a process of separating the script and language of each word present in a printed or handwritten multi-script document. It is an essential part of a multi-lingual Optical Character Recognizer (OCR). Most of the OCRs are solely designed for a single script. So it can't convert a document which is written in more than one script. This paper explained...
This paper presents an efficient image exploration scheme for the unshaped object using semantic modelling. The local regions of an image have been classified with respect to the frequency of occurrences. The semantic concept is evaluated using RGB histogram dissimilarity factor, overall dissimilarity factor and regional dissimilarity factor. The dissimilarities determine the local concept with accuracy...
This paper presents an evaluation of characteristic frequency features in healthy and diseased ECG via k-NN classifier. Initially, a total of 264 segment samples are obtained for healthy, bundle branch blocks, dysrhythmia cardiomyopathy conditions from the PTB Diagnostic ECG database. The signal is preprocessed to obtain the power spectral density. The characteristic frequency for each segment sample...
Stress is a mental condition that can effects the brain electrical activity to be different from the normal state. This brain cognitive change can be measured using EEG. The objective of this paper is to classify stress subjects based on EEG signal using SVM. The data which are used to represent stress subjects were taken from the residents of Pusat Darul Wardah; a shelter centre for troubled women...
This paper presents an intelligent system for the classification of ischemic stroke severity. The application of Artificial Neural Network (ANN) is proposed in this study to classify ischemic stroke severity using EEG sub bands Relative Power Ratio (RPR). There were 100 subjects from National Stroke Association of Malaysia NASAM, Petaling Jaya, Selangor, Malaysia divided into Early Group (EG), Intermediate...
This paper investigates the effect of grid cell size on ground flash density (GFD) of distribution powerlines. The study was based on the lightning data provided by local lightning detection systems and the analysis was conducted by overlaying ground flash map to the map of utility distribution network. The study result shows that GFD based on grid cell size with less magnitude has higher correlation...
Recent years have witnessed the explosive growth of recommender systems in various exciting application domains such as electronic commerce, social networking, and location-based services. A great many algorithms have been proposed to improve the accuracy of recommendation, but until recently the long tail problem rising from inadequate recommendation of niche items is recognized as a real challenge...
The paper presents a measure to improve the Tarantula spectral fault localization algorithm and solves the problems that the weight of the statements with a high-frequency coverage is significantly lower than the statements with a low-frequency coverage when Tarantula algorithm calculate the statement suspicious degrees. The improved algorithm has better discrimination when calculating the statement...
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