Titlebook: Computational Intelligence in Digital Forensics: Forensic Investigation and Applications; Azah Kamilah Muda,Yun-Huoy Choo,Sargur N. Srihar

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Cost Optimized Random Sampling in Cellular Automata for Digital Forensic Investigations,osure to distressing and offensive materials are of major concerns. Lack of technological support for processing large amount of offensive data makes the analytical procedure quite time consuming and expensive. Thus, it results in a degradation of mental health of concerned investigators. Backlog in

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Integrating Computational Methods for Forensic Identification of Drugs by TLC, GC and UV Techniques into account the shape of the spectra. The analyzed sample will take the class of the closest pattern. Spectra are previously standardized in order to eliminate the variation of the slope of the curves caused by the dispersion and the variation in the particle size. With this purpose, the standard

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Detecting Counterfeit RFID Tags Using Digital Forensic,od V which uses three way ANOVA test to analyze backscatter power of tag has the most accurate results. This is because Method V has the highest area under curve (AUC) (0.999) and lowest equal error rate (EER) (0.01) values. Besides that, the false acceptance rate (FAR) and false rejection rate (FRR

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Speech Quality Enhancement in Digital Forensic Voice Analysis, of iteratively refining Hidden Markov Model (HMM) speech labels for improved intelligibility is introduced. Third, a simulation of the distortion from a quantised R-bit and computation of the Signal-to-Noise Ratio (SNR) for the signal to quantisation noise is carried out for the purpose of managing