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Exploiting unique wireless channel characteristics like signal strength for secret key generation has been recently studied by researchers. These schemes are lightweight and suitable for resource constrained wearable devices. However, a major drawback of existing schemes is that the successive channel samples with small sampling interval will have high correlation in time. This reduces the entropy...
Network intrusions may illicitly retrieve data/information, or prevent legitimate access. Reliable detection of network intrusions is an important problem, misclassification of an intrusion is an issue in and of itself reducing overall accuracy of detection. A variety of potential methods exist to develop an improved system to perform classification more accurately. Feature selection is one potential...
Video Summarization acts as an important function in the field of video examination and abstraction. Due to the enormous growth in multimedia techniques, it is becoming increasingly important to be able to navigate the videos efficiently and in shorter time. To address these challenges, we propose a novel Video Summarization technique based on the weighted combination of color and texture features...
Text-frame classification for video is important prior to text detection and recognition to ensure that the text detection and recognition process is being conducted only for frames that consist of text. Otherwise, detecting and recognizing text on non-text frames will lead to false positive where non-text objects may be mistakenly classified as text. In this paper, we investigate the use of texture...
Gait dynamics of human appears to have a self-similar pattern and this self-similarity is studied using various non-linear methods. In this paper we employ three non-linear methods namely Hurst's rescaled range analysis method, Higuchi's fractal dimension method, Approximate entropy method to quantize the gait dynamics of people suffering from Parkinson diseases (PD). Also they are asked to perform...
Diabetic retinopathy (DR) is a complication of retinal related common micro vascular disease occurred in diabetic patients. It is the one of the major causes of adult blindness in the worldwide. DR is indicated by the presence of hard exudates, soft exudates, haemorrhages, the growth of new blood vessels and foveal avascular zone (FAZ) enlargement. The objective of this work is to detect FAZ area...
This paper discusses about a method adopted to develop a computer-aided diagnostic system to achieve automatic detection and classification of liver lesions. The procedure followed consists of first segmenting the CT scan image so as to accurately extract out the lesion region alone from the rest of the abdominal details. This Region Of Interest(ROI) is now used up for extracting out first order and...
Electroencephalographic (EEG) signals are produced in brain due to firing of the neurons. Any anomaly found in the EEG indicates abnormality associated with brain functioning. The efficacy of automated analysis of EEG depends on features chosen to represent the time series, classifier used and quality of training data. In this work, we present automated analysis of EEG time series acquired from two...
Cyclone vortex localization under varying conditions of saturated spiral bands is challenging. This paper presents a unique combination of image processing techniques, viz., Sequential Cross-Correlation (SCC) and Multi-Level Thresholding (MLT) for vortex localization. SCC is used for cyclone detection in a full-disk satellite imagery, and is based on the high degree of correlation in the sequence...
Inflammation of the conjunctiva and pain and discomfort in the inner surface of the eyelids is referred to as Conjunctivitis. It causes severe pain, burning sensation or in extreme cases blindness of the eye. Normally conjunctivitis is detected by eye specialist doctors and their limited number makes it difficult for everyone to reach them and get themselves diagnosed. This paper describes an automatic...
In MCDM problems some criteria (attributes) having different importance are used to determine a best alternative from many. Thus, different weight methods exist in literature to evaluate the importance of each criteria. In this work TOPSIS, multi-criteria decision making (MCDM) method is applied using crisp data set with different techniques of weight proposed in literature. Therefore, intuitionistic...
Envelope models are common in speech and audio processing: for example, linear prediction is used for modeling the spectral envelope of speech, whereas audio coders use scale factor bands for perceptual masking models. In this work we introduce an envelope model called distribution quantizer (DQ), with the objective of combining the accuracy of linear prediction and the flexibility of scale factor...
Canonical correlation analysis (CCA) is an established multivariate statistical method for finding similarities between linear combinations of (normally two) sets of multivariate observations. In this contribution we replace (linear) correlation as the measure of association between the linear combinations with the information theoretical measure mutual information (MI). We term this type of analysis...
This paper presents an efficient encryption technique for image. The designed chaos-based key generator provides a random and complex dynamic behavior and can change it automatically via a random-like switching rule. The proposed encryption scheme is called PDCSS (Parametric Discrete Chaos-based Switching System). The performances of this technique were evaluated in terms of data security. The originality...
Bug fixing is one of the most important activities in software development and maintenance. A software project often employs an issue tracking system such as Bugzilla to store and manage their bugs. In the issue tracking system, many bugs are invalid but take unnecessary efforts to identify them. In this paper, we mainly focus on bug fixing rate, i.e., The proportion of the fixed bugs in the reported...
Incorporation of user feedback in enterprise management products can greatly enhance our understanding of modern technology challenges and amplify the ability for those products to home in to user environments. In this paper we present an entropy-based confidence determination approach to process user feedback data (direct or indirect) to automatically rank and update the beliefs of any recommender...
The Izhikevich spiking neuron model is a relatively new mathematical framework which is able to represent many observed spiking neuron behaviors, excitatory or inhibitory, by simply adjusting a set of four model parameters. This model is deterministic in nature and has achieved wide applications in analytical and numerical analysis of biological neurons due largely to its biological plausibility and...
This work proposes an efficient texture classification strategy performed in the wavelet domain in order to characterize healthy and pathological speech signals from recurrence plots (RP). The two-dimensional wavelet transform is applied to the recurrence plots at one resolution level. Thirteen Haralick texture features are obtained from each approximation and detail subband coefficients. In classification,...
Recently, a variety of new measures of quantum Rényi mutual information and quantum Rényi conditional entropy have been proposed, and some of their mathematical properties explored. Here, we show that the Rényi mutual information attains operational significance in the context of composite hypothesis testing, when the null hypothesis is a fixed bipartite state and the alternate hypothesis consists...
Given low order moment information over the random variables X = (X1, X2, …, Xp) and Y, what distribution minimizes the Hirschfeld-Gebelein-Rényi (HGR) maximal correlation coefficient between X and Y, while remains faithful to the given moments? The answer to this question is important especially in order to fit models over (X, Y) with minimum dependence among the random variables X and Y. In this...
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