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The most critical and difficult problem in speech analysis is reliable discrimination among Silence, Unvoiced and Voiced speech. Several methods have been proposed for making this three levels decision and most of them need Speech Activity Detection (SAD). In this study, we propose the Estimated Degree of Noise (EDON) to adjust the threshold of speech activity. To estimate the degree of noise, a function...
Automated Essay Grading (AEG) is a very important research area in educational technology. Latent Semantic Analysis (LSA) is an information retrieval technique used for automated essay grading. LSA forms a word by document matrix and then the matrix is decomposed using Singular Value Decomposition (SVD) technique. Existing AEG systems based on LSA cannot achieve higher level of performance to be a...
Synchronization is considered an important design issue for the implementation of digital television (DTV) receiver, specially for proper reception of multipath distorted signal at low signal to noise ratio (SNR). This challenge is more pronounced in complex multipath channel scenarios and for high mobility applications in presence of carrier frequency offset (CFO). In this paper, time domain correlation...
Fingerprint detection is one of the most important applications of image processing in a security system. Recent literature deals with fingerprint detection based on pattern recognition, moment based image recognition and discrete wavelet transform (DWT). Among them DWT based analysis requires the least amount of memory space which considers only wavelet coefficient of an image in matching with preserved...
Network traffic has been studied extensively since new findings by Taqqu et. al. (1994), which has shown that network traffic is not memoryless. Such traffic has been called self similar with Long Range Dependence (LRD) and their distribution is commonly known as heavy-tailed. It is very hard to estimate buffer size to protect against overflow in presence of such traffic as packet sizes and their...
Data mining is the process of extracting non-trivial patterns from large volume of data. It generates insight and turns the data into valuable information. A critical yet common flaw when performing data mining is to ignore the geographic locations from where the data is taken. When this geospatial attribute of the data is taken into consideration, the process is known to be geospatial data mining...
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