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Titlebook: Intelligent Decision Technologies 2019; Proceedings of the 1 Ireneusz Czarnowski,Robert J. Howlett,Lakhmi C. Ja Conference proceedings 2019

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Recognition of Daily Human Activities Using Accelerometer and sEMG Signalsle. HAR is usually achieved in two steps: acquisition of body signals and classification of performed activities. This paper presents an investigation on the optimal setup for recognizing daily activities using a wearable system designed to acquire surface electromyography (sEMG) and accelerometer s
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Classification of Alzheimer’s Disease from Structural Magnetic Resonance Imaging using Particle-Bern the first stage of dementia condition with an increased risk of eventually developing Alzheimer’s disease (AD). In general, an MRI diagnosis system requires some fundamental activities: MRI processing, features selection, data classification. The aim of this paper is twofold: (i) first, a high-perf
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Genetic Algorithm for Selecting Relevant Regions in Digital Watermarking Scheme for 2D/3D Medical Imks, such as region of interest, patient electronic record, and fragile watermark, require varied quality after extraction from the watermarked image. First, we select the relevant regions in a host image and second, the genetic algorithm is employed to search the best coefficients for embedding usin
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A Transport Coding Gain Estimation in the Conditions of Time Limitation for Maximum Acceptable Messatime that was impossible before. A requirement of low message delay now is a part of many communication standards such as 5G and recommendation papers of future standards such as Tactile Internet proposed by ITU-T. In this research, we perform an efficiency estimation of the transport coding for pac
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Modeling Customers Speed of Movement from POS- and RFID-Datacorded and analyzed to improve the functioning of any area of life is stated. Second, the case of a grocery store is used in order to identify useful dependencies. The data from the store contains information that characterizes consumer behavior. As a result, it becomes possible to evaluate the char
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Discovering and Analyzing Binary Codes Based on Monocyclic Quasi-Orthogonal Matrices quasi-orthogonal matrices, including special Mersenne and Raghavarao matrices with cyclic structure. It has been demonstrated that these new codes exceed Barker codes, which are known to be the only codes with the highest peak side lobe ratio (PSLR). Their autocorrelation functions are compared in
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Training Sample Generation Softwareareas such as human behavior analysis, identifying nonstandard patterns in human behavior, or situations leading to accidents, while driving a vehicle, operating a train, piloting an aircraft, etc. Also, the main requirements for newly developed applications for image annotation are formulated.
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