Optimizing the Access Point (AP) deployment has a great role in wireless applications due to the need for providing an efficient communication with low deployment costs. Quality of Service (QoS), is a major significant parameter and objective to be considered along with AP placement as well the overall deployment cost. This study proposes and investigates a multi-level optimization algorithm called Wireless Optimization Algorithm for Indoor Placement (WOAIP) based on Binary Particle Swarm Optimization (BPSO). WOAIP aims to obtain the optimum AP multi-floor placement with effective coverage that makes it more capable of supporting QoS and cost-effectiveness. Five pairs (coverage, AP deployment) of weights, signal thresholds and received signal strength (RSS) measurements simulated using Wireless InSite (WI) software were considered in the test case study by comparing the results collected from WI with the present wireless simulated physical AP deployment of the targeted building - Computer Science Department at University of Baghdad. The performance evaluation of WOAIP shows an increase in terms of AP placement and optimization distinguished in order to increase the wireless coverage ratio to 92.93% compared to 58.5% of present AP coverage (or 24.5% coverage enhancement on average).
The present research deals with the study of the symmetries of the design of interior spaces in fast food restaurants in terms of formality as it is an important element and plays a direct role in the spatial configuration, which is designed in both of its performance, aesthetic and expressive aspects. Since the choice of shapes is a complex subject that has many aspects imposed by functional and aesthetic correlations, the problem of the research is represented by the following question: (To what extent can the symmetries of the interior design be used in the spaces of fast food restaurants?)
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As cities across the world grow and the mobility of populations increases, there has also been a corresponding increase in the number of vehicles on roads. The result of this has been a proliferation of challenges for authorities with regard to road traffic management. A consequence of this has been congestion of traffic, more accidents, and pollution. Accidents are a still major cause of death, despite the development of sophisticated systems for traffic management and other technologies linked with vehicles. Hence, it is necessary that a common system for accident management is developed. For instance, traffic congestion in most urban areas can be alleviated by the real-time planning of routes. However, the designing of an efficie
... Show MoreThe control of prostheses and their complexities is one of the greatest challenges limiting wide amputees’ use of upper limb prostheses. The main challenges include the difficulty of extracting signals for controlling the prostheses, limited number of degrees of freedom (DoF), and cost-prohibitive for complex controlling systems. In this study, a real-time hybrid control system, based on electromyography (EMG) and voice commands (VC) is designed to render the prosthesis more dexterous with the ability to accomplish amputee’s daily activities proficiently. The voice and EMG systems were combined in three proposed hybrid strategies, each strategy had different number of movements depending on the combination protocol between voic
... Show MoreResearch,s Summary The purpose of the research was to specify the standerd Levels for results of basketball for Iraqi young sters, Becuse there werenot the standerd Levels which related to the testings abilities of the players based on plying centers specially the physical abilities, This made weakness in arrangement and putting the suitable training studies for different age stadges which suitable with game ,s requirements, besides evaluation the performance of the plyers in common and the levels of the coachs train in special according to the scientific style. The researchers depended on (8) special testings of chossen physical abilities, These testings applied on the teams, young players for sharing clubs among excellent series of basket
... Show MoreA novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh
... Show MoreLED is an ultra-lightweight block cipher that is mainly used in devices with limited resources. Currently, the software and hardware structure of this cipher utilize a complex logic operation to generate a sequence of random numbers called round constant and this causes the algorithm to slow down and record low throughput. To improve the speed and throughput of the original algorithm, the Fast Lightweight Encryption Device (FLED) has been proposed in this paper. The key size of the currently existing LED algorithm is in 64-bit & 128-bit but this article focused mainly on the 64-bit key (block size=64-bit). In the proposed FLED design, complex operations have been replaced by LFSR left feedback technology to make the algorithm perform more e
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
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