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In this paper, an prediction speed method of hand open-çlose by using the Artificial Neural Network (ANN) surface electromyography (sEMG) signal is presented. The first step of this method is to analyze sEMG signal detected from the subject's right upper forearm and extract features using the mean absolute value (MAV), the root mean square (RMS), the variance (VAR), the standart deviation (STD), the...
In this study, is aimed to estimated of the region which observed on the screen by the artificial neural network (ANN) trained with using images of laptop user. Study were formed of two phases. In the first stage, an ANN has been developed for determining eye region in the captured image with webcam. In the second stage, the data obtained from the eye region are used for training of another ANN which...
Several muscular-skeletal problems can affect the foot and thus the structural development of a child, causing damage to his or her tone-postural system. Hence, the early detection of any possible postural alteration is essential in avoiding further adult life complications. There are several methods and instruments for feet evaluation; however, they are generally restricted to clinical environments,...
Emergency management systems are Cyber-Physical-Human Systems (CPHS) that use sensing, together with communications and control, to guide humans and physical systems such as vehicles, towards safe desirable outcomes in the shortest possible time. When human health and safety, and lives also, are at stake, it is important to take decisions in real-time with the best possible use of resources, including...
NFV Technology facilitates implementation of network functions as SW packages, called Virtual Network Functions (VNF) running over common IT platforms and simple network switches. NFV could be used to virtualize dispersed functions and devices currently deployed as CPEs in the customer home. This new architecture has a major impact on public and home networks. Not only are HW components virtualised,...
With the huge growth in the volume of data today, there is an enhanced need to extract meaningful information from the data. Data mining contributes towards this and finds its application across various diverse domains such as in information technology, retail, stock markets, banking, and healthcare among others. The increase in population coupled with the growth in diseases has necessitated the inclusion...
Predicting students' performance is very important if not crucial especially in engineering courses. This is to enable strategic intervention to be carried out before the students reach the higher semesters including the final semester before graduation. This paper presents a comparison study between Artificial Neural Network (ANN) and Linear Regression (LR) in predicting the academic performance...
We apply recent developments in clustering theory of asymmetric networks to study the equilibrium configurations of consensus dynamics in trust networks. We show that reciprocal clustering characterizes the equilibrium opinions of mutual trust dynamics. That is, clusters in the reciprocal dendrogram correspond to different equilibrium opinions of mutual trust consensus for varying trust thresholds...
In the past, indoor wireless access systems had been designed mainly from the radio coverage perspective. Recently, fingerprint-based localization has also been proposed as another popular application for such access systems. However, few has been studied in the network design for both coverage and localization at the same time. This paper proposes a novel network design for guaranteeing radio coverage...
Based on preliminary observation of international engineering conference presentations in East Asia and Europe, a comparative, two-stage investigation of the effect of delivery style on audience comprehension was undertaken. The current paper reports on the first stage, which involves measuring presenter's 1) bodily degree of orientation to audience and 2) proportion of spoken words that are additional...
In this work is proposed a writer identification approach based on graphometrical and forensic features. The proposal replies to an off-line system, where the handwriting is provided before to perform the analysis. An Artificial Neural Network is used as classifier and after the decision fusion module, the system reaches up to 94.6% of success rate for a own database composed by 100 users with 10...
Evolutionary Algorithms (EA) are used in many optimization problems such as the Artificial Neural Networks (ANN). But the main challenging issue of using these algorithms is the time taken for computing the function value, implementation and verification of hardware architecture design. In this paper we propose to implement the architecture design of Back Propagation Neural (BPN) networks using Very...
This paper presents a new algorithm based on characteristic equation of solar cells to determine the Maximum Power Point (MPP) of PV modules under partially shaded conditions (PSC). To achieve this goal, an analytic condition is introduced to determine uniform or non-uniform atmospheric conditions quickly. This paper also proposes an effective and quick response technique to find the MPP of PV array...
Load forecasting is a critical necessity in the electricity industry since any unanticipated demand could cause possible grid instability and blackouts. Ideally, the capacity should be kept slightly above the current demand to avoid any undesired outages and suboptimal last minute power purchase. Motivated to develop an intelligent and efficient forecasting approach, we propose investigating in this...
We evaluate the information-theoretic achievable rates of Quantize-Map-and-Forward (QMF) relaying schemes over Gaussian N-relay diamond networks. Focusing on vector Gaussian quantization at the relays, our goal is to understand how close to the cutset upper bound these schemes can achieve in the context of diamond networks, and how much benefit is obtained by optimizing the quantizer distortions at...
In this study, a Common Spatial Pattern (CSP) driven Artificial Neural Network (ANN) Classification strategy is presented to classify the mental tasks, namely, left-hand movement imagination, right-hand movement imagination, and word generation in EEG data. According to this strategy, first, electrode re-referencing and band-pass filtering are used to enhance the EEG signal. Then a multi-class extension...
For a patient diagnosed with epilepsy, a neurological disorder that affects the patient only during a seizure, and the following short duration for some cases, it is important to predict a seizure before it happens. EEG signal processing plays an important role in detection and prediction of epileptic seizures. The aim of this study is to develop a patient specific seizure prediction method based...
This paper presents a comparison between DMPML and three data mining applications (Weka, RapidMiner, and KN-IME) that implement the directed graph approach, concerning the time spent to create and execute the data preparation tasks for two data mining algorithms. The tests were executed using different types of data sets: numerical, categorical, and mixed. We observed that the scheme used by the DMPML...
This study presents a comparative algorithms for oil spill automatic detection from different RADARSAT-1 SAR different mode data and ENVISAT ASAR data. Three algorithms are involved: Entropy, Mahalanobis, and Artificial Neural Network (ANN) algorithms. The study shows that ANN provide automatically oil spill detection with error of standard deviation of 0.12 which is lower than Entropy and the Mahalanobis...
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