High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination by considering the traffic segment status when choosing the next intersection. RTISAR presents a new formula for assessing segment status based on connectivity, density, load segment, and cumulative distance toward the destination. A verity period mechanism is proposed to denote the projected period when a network failure is likely to occur in a particular segment. This mechanism can be calculated for each collector packet to minimize the frequency of RTISAR execution and to control the generation of collector packets. As a result, this mechanism minimizes the communication overhead generated during the segment status computation process. Simulations are performed to evaluate RTISAR, and the results are compared with those of intersection-based connectivity aware routing and traffic flow oriented routing. The evaluation results provided evidence that RTISAR outperforms in terms of packet delivery ratio, packet delivery delay, and communication overhead.
Steganography involves concealing information by embedding data within cover media and it can be categorized into two main domains: spatial and frequency. This paper presents two distinct methods. The first is operating in the spatial domain which utilizes the least significant bits (LSBs) to conceal a secret message. The second method is the functioning in the frequency domain which hides the secret message within the LSBs of the middle-frequency band of the discrete cosine transform (DCT) coefficients. These methods enhance obfuscation by utilizing two layers of randomness: random pixel embedding and random bit embedding within each pixel. Unlike other available methods that embed data in sequential order with a fixed amount.
... Show MoreSolar cells has been assembly with electrolytes including I−/I−3 redox duality employ polyacrylonitrile (PAN), ethylene carbonate (EC), propylene carbonate (PC), with double iodide salts of tetrabutylammonium iodide (TBAI) and Lithium iodide (LiI) and iodine (I2) were thoughtful for enhancing the efficiency of the solar cells. The rendering of the solar cells has been examining by alteration the weight ratio of the salts in the electrolyte. The solar cell with electrolyte comprises (60% wt. TBAI/40% wt. LiI (+I2)) display elevated efficiency of 5.189% under 1000 W/m2 light intensity. While the solar cell with electrolyte comprises (60% wt. LiI/40% wt. TBAI (+I2)) display a lower efficiency of 3.189%. The conductivity raises with the
... Show MoreAgent technology has a widespread usage in most of computerized systems. In this paper agent technology has been applied to monitor wear test for an aluminium silicon alloy which is used in automotive parts and gears of light loads. In addition to wear test monitoring، porosity effect on
wear resistance has been investigated. To get a controlled amount of porosity, the specimens have
been made by powder metallurgy process with various pressures (100, 200 and 600) MPa. The aim of
this investigation is a proactive step to avoid the failure occurrence by the porosity.
A dry wear tests have been achieved by subjecting three reciprocated loads (1000, 1500 and 2000)g
for three periods (10, 45 and 90)min. The weight difference a
Intelligent systems can be used to build systems that simulate human behavior. One such system is lip reading. Hence, lip reading is considered one of the hardest problems in image analysis, and thus machine learning is used to solve this problem, which achieves remarkable results, especially when using a deep neural network, in which it dives deeply into the texture of any input. Microlearning is the new trend in E-learning. It is based on small pieces of information to make the learning process easier and more productive. In this paper, a proposed system for multi-layer lip reading is presented. The proposed system is based on micro content (letters) to achieve the lip reading process using deep learning and auto-correction mo
... Show MoreVoice denoising is the process of removing undesirable voices from the voice signal. Within the environmental noise and after the application of speech recognition system, the discriminative model finds it difficult to recognize the waveform of the voice signal. This is due to the fact that the environmental noise needs to use a suitable filter that does not affect the shaped waveform of the input microphone. This paper plans to build up a procedure for a discriminative model, using infinite impulse response filter (Butterworth filter) and local polynomial approximation (Savitzky-Golay) smoothing filter that is a polynomial regression on the signal values. Signal to noise ratio (SNR) was calculated after filtering to compare the results
... Show MoreBotnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet
... Show MoreThe objective of this research is employ the special cases of function trapezoid in the composition of fuzzy sets to make decision within the framework of the theory of games traditional to determine the best strategy for the mobile phone networks in the province of Baghdad and Basra, has been the adoption of different periods of the functions belonging to see the change happening in the matrix matches and the impact that the strategies and decision-making available to each player and the impact on societ
... Show MoreThe first successful implementation of Artificial Neural Networks (ANNs) was published a little over a decade ago. It is time to review the progress that has been made in this research area. This paper provides taxonomy for classifying Field Programmable Gate Arrays (FPGAs) implementation of ANNs. Different implementation techniques and design issues are discussed, such as obtaining a suitable activation function and numerical truncation technique trade-off, the improvement of the learning algorithm to reduce the cost of neuron and in result the total cost and the total speed of the complete ANN. Finally, the implementation of a complete very fast circuit for the pattern of English Digit Numbers NN has four layers of 70 nodes (neurons) o
... Show MoreThe first successful implementation of Artificial Neural Networks (ANNs) was published a little over a decade ago. It is time to review the progress that has been made in this research area. This paper provides taxonomy for classifying Field Programmable Gate Arrays (FPGAs) implementation of ANNs. Different implementation techniques and design issues are discussed, such as obtaining a suitable activation function and numerical truncation technique trade-off, the improvement of the learning algorithm to reduce the cost of neuron and in result the total cost and the total speed of the complete ANN. Finally, the implementation of a complete very fast circuit for the pattern of English Digit Numbers NN has four layers of 70 nodes (neurons) o
... Show MoreSkin detection is classification the pixels of the image into two types of pixels skin and non-skin. Whereas, skin color affected by many issues like various races of people, various ages of people gender type. Some previous researchers attempted to solve these issues by applying a threshold that depends on certain ranges of skin colors. Despite, it is fast and simple implementation, it does not give a high detection for distinguishing all colors of the skin of people. In this paper suggests improved ID3 (Iterative Dichotomiser) to enhance the performance of skin detection. Three color spaces have been used a dataset of RGB obtained from machine learning repository, the University of California Irvine (UCI), RGB color space, HSV color sp
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