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In today’s technological world, one of the most challenging problems is information security. In the past ten years, many methods were introduced for securing the secret data transmission over the public network (Internet). One of the best choices to solve such issue is to combine AI and steganography methods. In the presented work, the text will be hidden inside an image depending on the ant colony optimization algorithm for generation of secret key for hiding. First an image is chosen as a carrier media of the secret text, then a set of rows are chosen from carrier image and used as an entry point for the ant colony optimization algorithm where the matrix resulting from the algorithm is used as a key to determine the hiding pixels of secret text bits in an image. The secret text will convert to ASCII code then convert to binary bits and hiding these bits on pixels of image depending on generation key using least significant bits techniques. The experimental results were the high-quality stego images as well as its minimal histogram changeability, also validating the efficiency of the suggested method, and it’s hard to determine pixels of hiding and complexity to determine the sequence of hiding bits.

Home Automation System (HAS) has attracted great interest as communication technology advances. A Smart Home (SH) is an Internet of Things (IoT) app that utilizes the Internet to surveillance and control devices through the use of a smart home automation system (SHAS). Current home automation systems (HASs) are limited by a lack of IoT technology, an unfriendly user interface, a limited wireless transmission range, and high costs. This paper describes an affordable, safe and energy-efficient WiFi-based system smart home or intelligent home, which enables home appliances to be monitored by homeowners in local and remote locations via mobile phone/PC. Raspberry Pi 3 Model B+ and Arduino Mega 2560 were used to configuring the server automation framework. Moreover, various sensors that are connected to the Arduino Mega controller have been used to monitor current, voltage, power, energy, frequency, humidity, temperature, motion, flame, smoke, gas, doors, windows and other household conditions, and also to successfully control household appliances (lights, fans, reverse fan, water pump, etc.) either automatically or via relays. The proposed automation system can surveillance and control home conditions via the Blynk app for both Android or IOS.

In this paper the benchmarking functions are used to evaluate and check the particle swarm optimization (PSO) algorithm. However, the functions utilized have two dimension but they selected with different difficulty and with different models. In order to prove capability of PSO, it is compared with genetic algorithm (GA). Hence, the two algorithms are compared in terms of objective functions and the standard deviation. Different runs have been taken to get convincing results and the parameters are chosen properly where the Matlab software is used. Where the suggested algorithm can solve different engineering problems with different dimension and outperform the others in term of accuracy and speed of convergence.

Each project management system aims to complete the project within its identified objectives: budget, time, and quality. It is achieving the project within the defined deadline that required careful scheduling, that be attained early. Due to the nature of unique repetitive construction projects, time contingency and project uncertainty are necessary for accurate scheduling. It should be integrated and flexible to accommodate the changes without adversely affecting the construction project’s total completion time. Repetitive planning and scheduling methods are more effective and essential. However, they need continuous development because of the evolution of execution methods, essentially based on the repetitive construction projects’ composition of identical production units. This study develops a mathematical model to forecast repetitive construction projects using the Support Vector Machine (SVM) technique. The software (WEKA 3.9.1©2016) has been used in the process of developing the mathematical model. The number of factors affecting the planning and scheduling of the repetitive projects has been identified through a questionnaire that analyzed its results using SPSS V22 software. Three accuracy measurements, correlation coefficient (R), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE), were used to check the mathematical model and to compare the actual values with predicted values. The results showed that the SVM technique was more precise than those calculated by the conventional methods and was found the best generalization with R 97 %, MAE 3.6 %, and RMSE 7 %.

Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postponement of delay of interim payments is at the forefront of delay factors caused by the employer’s decision. Even the least one is to leave the job site caused by the contractor’s second part of the contract, the repeated unjustified stopping of the work at the site, without permission or notice from the client’s representatives. The developed model was applied to about 97 projects and used as a prediction model. The decision tree model shows higher accuracy in the prediction.

Attention Deficit Hyperactivity Disorder (ADHD) is a common and heritable disease that has an environmental influence on brain function. The diseases affects multiple aspects of the lives of college students, not only on their study but also on the relationships with other people. The problem with ADHD attention involves short term memory. The purpose of this paper is to investigate the capability of improving short term working memory for ADHD patients by the aid of technology a proper VR environment is built for ADHD, who are isolated from the real circumference. Electroencephalography (EEG) is taken as biofeedback to read the brain signal from the patient. A deep learning approach and an artificial neural network method, are employed to efficiently and accurately process EEG. The findings of the trial indicate that the virtual reality recommended system will play a greater role in improving the attention to the ADHD patient.

The Internet of Things (IoT) is a newly emerging term for the new generation of the Internet which allows understanding between interconnected devices. IoT acts as an assistant in healthcare and plays an extremely important role in wide scopes of medicinal services observing applications. Through determining the pattern of parameters that are observed, the character of the disease can be expected. Health specialists and technicians have developed a great system with low-cost healthcare monitoring for people suffering from many diseases using common techniques such as wearable devices, wireless channels, and other remote devices. Network-related sensors, either worn on the body or in living environments, collect rich information to assess the physical and mental state of the patient. This work focuses on scanning the existing e-health (electronic healthcare) monitoring system using integrated systems. The main goal of the e-health monitoring system is to offer the patient a prescription automatically according to his or her condition. The doctor can check patient health continuously without physical interaction. The study aims to explore the uses of IoT applications in the medical sector, and its role in raising the level of medical care services in health institutions. Also, the study will address the applications of IoT in the medical field and the extent of its use to enrich traditional methods in various health fields and to determine the extent of the ability of IoT to improve the quality of health services provided. The study relies on a descriptive research approach through an analysis of the literature published in this field. The results of the study refer to the application of IoT in the health institutions, it will help to obtain accurate diagnoses for patients, which will reflect on the quality of service provided to the patient. It will also reduce periodic patient reviews to the hospital by relying on IoT applications for remote diagnosis. Also, an application in health institutions will contribute to providing data correct for the diseases that patients suffer from, and hence employing them in preparing scientific research to obtain more accurate results. This paper introduces the review of the Internet-based healthcare monitoring system (HCMS) and the general outlines on opportunities and challenges of the patient’s Internet-based patient health monitoring system.

The paper aims to use throughput accounting as an approach for developing cost accounting systems in the modern manufacturing environment to evaluate the organization performance. The sample consists of (60) persons in organization for examining the hypotheses. The findings show that information provided by throughput accounting helps in measuring costs and evaluate the efficiency and effectiveness of performance in the organization. This approach supports planning and control processes to maximize throughput and reduce inventory levels. The use of Throughput Accounting under the Theory of Constraints leads to finding solutions to bottlenecks that affect the efficiency and effectiveness of performance.

This paper presents a low-cost Brushless DC (BLDC) motor drive system with fewer switches. BLDC motors are widely utilized in variable speed drives and industrial applications due to their high efficiency, high power factor, high torque, low maintenance, and ease of control. The proposed control strategy for robust speed control is dependent on two feedback signals which are speed sensor loop which is regulated by Sliding Mode Controller (SMC) and current sensor loop which is regulated by Proportional-Integral (PI) for boosting the drive system adaptability. In this work, the BLDC motor is driven by a four-switch three-phase inverter emulating a three-phase six switch inverter, to reduce switching losses with a low complex control strategy. In order to reach a robust performance of the proposed control strategy, the Lévy Flight Distribution (LFD) technique is used to tune the gains of PI and SMC parameters. The Integral Time Absolute Error (ITAE) is used as a fitness function. The simulation results show the SMC with LFD technique has superiority over conventional SMC and optimization PI controller in terms of fast-tracking to the desired value, reduction speed error to the zero value, and low overshoot under sudden change conditions.

In recent years, the rapid development in the field of wireless technologies led to the appearance of a new topic, known as the Internet of things (IoT). The IoT applications can be found in various fields of our life, such as smart home, health care, smart building, and etc. In all these applications, the data collected from the real world are transmitted through the Internet; therefore, these data have become a target of many attacks and hackers. Hence, a secure communication must be provided to protect the transmitted data from unauthorized access. This paper focuses on designing a secure IoT system to protect the sensing data. In this system, the security is provided by the use of Lightweight AES encryption algorithm to encrypt the data received from physical environment. The hardware used in this proposal is the Raspberry Pi 3 model B and two types of sensors. The LAES algorithm was embedded inside the Raspberry in order to protect the sensing data, that come from sensors connected to the Raspberry Pi, before sending them through the network. The analysis results show that the proposed IoT security system consumes less time in encryption/decryption and has high throughput when compared with others from related work. Its throughput is higher in about 19.24% than the value reported for one system in the related studies.

Huge data rates have been provided by 5G wireless communication systems using millimeter wave (mmWave) band that have frequencies ranging from 30 to 300 GHz. mmWave provides much wider bandwidth than the existing 4G band. The 5G network deals with massive number of devices. This presents many challenges including capacity, end to end delay, data rate, and very large number of connections. In this paper, the main task is to apply network coding to 5G mmWave communication system to increase the throughput of the communication links. Simple packet-based network coding schemes using butterfly network topology are simulated. The two network coding schemes considered here are Physical Layer Network Coding (PLNC) and Network Layer Network Coding (NLNC). Models of Additive White Gaussian Noise (AWGN) and mmWave indoor fading channels are considered in the work using Quadrature Phase Shift Keying (QPSK) modulation. The results of the tests showed that the use of both NLNC and PLNC improved throughput in comparison to uncoded system. Using PLNC increased the Bit Error Rate (BER) and the Packet Error Rate (PER), while NLNC scheme showed almost identical error performance to uncoded system over mmWave fading channel. The results show that network coding improved throughput when compared.

Steganography art is a technique for hiding information where the unsuspicious cover signal carrying the secret information. Good steganography technique must be includes the important criterions robustness, security, imperceptibility and capacity. The improving each one of these criterions is affects on the others, because of these criterions are overlapped each other. In this work, a good high capacity audio steganography safely method has been proposed based on LSB random replacing of encrypted cover with encrypted message bits at random positions. The research also included a capacity studying for the audio file, speech or music, by safely manner to carrying secret images, so it is difficult for unauthorized persons to suspect presence of hidden image. Measures calculations of SNR, SNR segmental, SNR spectral, MSE and correlation show that, audio music cover file (2channales) is the safest uses as arrier with replace the 9 number of LSB without noticeable noise. Bits of secret message can be hiding capacity reach up to 28 % of the total music cover audio size and the three type's measures of SNR are 32, 28 and 31 dB. For speech cover audio the replacing LSB is safely uses at LSB bits number 6, where the hiding capacity is reach up to 37 % of size speech cover audio at 37, 36 and 39 dB for three type's measures of SNR. Correlation of cover samples was did not effected as a result of hiding secret image, where its value is up to 0.99 for all hiding operations.

In this study, an adaptive data compression scheme (ADCS) is proposed for efficiently controlling the IoT device compression rate and energy consumption in the cloud based IoT network. The ADCS consists of two data compression schemes, the sensor Lempel–Ziv–Welch (S-LZW) scheme and the sequential lossless entropy compression (S-LEC) scheme. In Auto state, the ADCS can select the appropriate energy efficient data compression scheme for each IoT device, while taking into consideration the IoT device’s processing capability, the available energy in each IoT device battery, and the amount of compression power. Our proposed scheme has been developed using mixed integer linear programming. The result verifies that the proposed ADCS scheme saves power by an average of 40% compared to the non-compression scheme (NCS) due to reducing the traffic load and the number of hops in the network, which leads to an ability to handle higher traffic demands and increasing the lifetime of IoT devices by 50% compared to NCS systems.

Adaptive Reduced Path Successive Cancellation List (ARP-SCL) decoding for polar codes is proposed in this paper. The aim here is to reduce the complexity of the conventional Successive Cancellation List (SCL) and a previously proposed Reduced Path SCL (RP-SCL) decoders. The complexity reduction is obtained at low and moderate signal to noise power ratio (SNR) regions. The operation of the proposed ARP-SCL decoder relied on the calculation of different optimum pruning parameters according to the operating SNR, while RP-SCL used single parameters set. Simulation tests are carried out to determine both the complexity and Bit Error Rate (BER) performances of the proposed ARP-SCL decoder in comparison with SCL and RP-SCL decoders. Additive White Gaussian Noise (AWGN) channel and two fading channel models simulating indoor 5G environment using millimeter Wave (mmWave) with carrier frequency of 28GHz and having either 50 or 400 MHz bandwidths are used. The results revealed that the proposed ARP-SCL decoder reduced the average processed paths up to 46.88%. The largest complexity reductions are obtained in the case of fading channel having 400 MHz bandwidth at high SNR regions. In most test conditions, the mentioned reduction in complexity is achieved without greatly sacrificing the required BER.

Image encryption is one of the primary approaches which is used to keep image information secure and safe. Recently, image encryption is turning its attention to combination with the field of DNA computing. In the presented study, a novel method of image encryption is suggested and implemented based on the DNA algorithm and Chaos theory, the most important principle in image encryption is breaking the correlation amongst pixels. This algorithm performs well against chosen cipher-text attacks. Furthermore, the proposed approach was implemented and analyzed for the Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), The performance of the encryption method is analyzed using the histogram, Shannon entropy and key space.

In this paper, an optimal speed controller for dc motor is considered using a PID controller and tuned its parameters of gain to offer an optimal solution by using a modified camel algorithm MCA approach. The proposed MCA scheme was applied to solve the difficulty of getting the optimum gains of PID parameters. The MCA has good evolutionary speed with the simple construction of optimization depend on camel searching performance. The characteristics of the MCA algorithm were confirmed by optimizing the gains parameters of proportional, integral, derivative PID controller. The performance of PID-MCA is comparing with a classic PID controller enhanced with GA genetic algorithm optimization method to tune the gain parameters of the speed controller system. It was shown that the utilize of optimization processes indicated better performance for the MCA procedure in term of speed of execution and the size of memory compared with the GA method by applying computer simulations analysis. The proposed scheme has an efficient feature that includes the ease of implementation, good efficiency of computational performances with stable convergence characteristics. The results indicated that the proposed MCA scheme is a useful tool for search ability, produced efficient outcomes compared with the GA optimized method when applied in the proposed system.

Cloud computing security has received great attention by researchers in the past few years due to the importance of the data used and the increasing use of cloud computing, which has become the pro...

In this article, we presented the concepts of -compact, b -compact, pre -compact, a -compact and -compact) spaces by using -open sets in -space and study their properties in detail. The relationshi...

The oil consumption and CO2 generation were the drives to innovate electric vehicles. At the recent years, there is large evolution in the industry of electric vehicles and in the near future, the normal vehicles may be replaced with electric vehicles. The energy consumption of these vehicles depends on the vehicle body size and weight, passengers' weight, mobility speed, and vehicle communications. In this paper, we focus only on vehicle communications and propose a new concept called Electrical Vehicular Ad Hoc Network (E-VANET). E-VANET is a new trend of vehicular ad hoc networks (VANET) which composes of connecting a group of electric vehicles with each other and with the infrastructure to exchange information. In addition to the challenges of VANET such as mobility, routing, location awareness, etc., the main challenge in E-VANET is energy consumption that needs a great research effort to be reduced. Therefore, it is necessary to highlight E-VANET and new concepts, standards, and technologies that can be used to enhance its performance and reduce energy consumption. The main goal of this paper is to explain the concept of this new network type, its architectures, applications, and challenges as well as the technologies that can be merged with it to increase the network lifetime like software-defined network, fog computing, internet of vehicles (IoV) and cloud computing. This paper can open the door in front of the researchers to contribute in enhancing the work of E-VANET.

The internet has made the world a little community, linking millions of people, organizations, and equipment for different purposes. The great impact of these networks in our lives makes their efficiency a vital matter to take care of, and this needs handling some problems including congestion. In this paper, the fuzzy-PID controller is used to control the nonlinear TCP / AQM model. This controller adjusts congestion of the computer network and commits controlled pressurized signaling features. Many experiments were carried out using different network parameter values, various queue sizes, and additional disturbances to verify the robustness and efficiency of the proposed controller. From all experiments carried out in the NS-2 simulator version (2.35), the results show the superiority of the FPID controller under different network traffic conditions.

Internet of Vehicles (IoV) is a new style of vehicular ad hoc network that is used to connect the sensors of each vehicle with each other and with other vehicles' sensors through the internet. These sensors generate different tasks that should be analyzed and processed in some given period of time. They send the tasks to the cloud servers but these sending operations increase bandwidth consumption and latency. Fog computing is a simple cloud at the network edge that is used to process the jobs in a short period of time instead of sending them to cloud computing facilities. In some situations, fog computing cannot execute some tasks due to lack of resources. Thus, in these situations it transfers them to cloud computing that leads to an increase in latency and bandwidth occupation again. Moreover, several fog servers may be fuelled while other servers are empty. This implies an unfair distribution of jobs. In this research study, we shall merge the software defined network (SDN) with IoV and fog computing and use the parked vehicle as assistant fog computing node. This can improve the capabilities of the fog computing layer and help in decreasing the number of migrated tasks to the cloud servers. This increases the ratio of time sensitive tasks that meet the deadline. In addition, a new load balancing strategy is proposed. It works proactively to balance the load locally and globally by the local fog managers and SDN controller, respectively. The simulation experiments show that the proposed system is more efficient than VANET-Fog-Cloud and IoV-Fog-Cloud frameworks in terms of average response time and percentage of bandwidth consumption, meeting the deadline, and resource utilization.

Polar codes have already been adopted in 5G systems to improve error performance. Successive cancellation list (SCL) decoding is usually used at the decoder and involves lengthy processing. Therefore, different methods have been developed to reduce an SCL decoder’s complexity. In this paper, a reduced path successive cancellation list (RP-SCL) decoder is presented to reduce this complexity, where some decoding paths are pruned. The pruning is achieved by using three different thresholds: two for the path metric and one for the pruning depth in the decoding tree. An optimization procedure is considered to determine the optimum settings for these thresholds. The simulation tests are carried out over models of an additive white Gaussian noise channel and a fading channel by using 5G environments. The results reveal that the proposed RP-SCL decoder provides the complexity reduction in terms of the average number of processed paths at high SNR. Additionally, the computational complexity and the memory requirements decrease.

There have been strong links between chaotic theory and cryptographic theory for the last three decades. The characterization of behaviors of the Chaotic system, such as: highly responsive to initial states, mixing attributes, deterministic existence, and often unable to predict long-term returns, allows researchers improve the security of cryptography systems. As a result, there are growing numbers of experiments that have been proposed using chaotic-based random number generators. Furthermore, These proposed generators suffer from minimal key space and those centered on a 1D chaotic map have limited capacity to produce entropy due to their limited number of exponents of Lyapunov (s). Random binary sequence generator producing sequence of bits has been proposed in this paper. The proposed system model consists of two parts that use mouse device data constructively as the basis for the theory of non-determinism and chaos. The chaos theory includes three forms with the mouse cursor coordinates while moving as the initial seeds in this proposed system (1D logistic chaotic system, 2D Henon system and 3D chaotic system) and combines the values produced in the algorithm. With 1D, 2D Henon, 3D chaotic maps, the mouse cursor coordinates are treated as an initial random number with post processing to increase the randomness and security of the keys. In the suggested research, there is high key space and a very long time. It is also evident that the developed keys have successful statistical features that require purely random binary sequences that are optimal for use in essential cryptography systems provided by evaluating the results of 16 NIST hardness tests (National Institute of Standards and Technology).

A robust video-bitrate adaptive scheme at client-aspect plays a significant role in keeping a good quality of video streaming technology experience. Video quality affects the amount of time the video has turned off playing due to the unfilled buffer state. Therefore to maintain a video streaming continuously with smooth bandwidth fluctuation, a video buffer structure based on adapting the video bitrate is considered in this work. Initially, the video buffer structure is formulated as an optimal control-theoretic problem that combines both video bitrate and video buffer feedback signals. While protecting the video buffer occupancy from exceeding the limited operating level can provide continuous video streaming, it may also cause a video bitrate oscillation. So the video buffer structure is adjusted by adding two thresholds as operating points for overflow and underflow states to filter the impact of throughput fluctuation on video buffer occupancy level. Then a bandwidth prediction algorithm is proposed for enhancing the performance of video bitrate adaptation. This algorithm's work depends on the current video buffer level, video bitrate of the previous segment, and iterative throughput measurements to predict the best video bitrate for the next segment. Simulation results show that reserving a bandwidth margin is better in adapting the video bitrate under bandwidth variation and then reducing the risk of video playback freezing. Simulation results proved that the playback freezing happens two times: firstly, when there is no bandwidth margin used and secondly, when the bandwidth margin is high while smooth video bitrate is obtained with moderate value. The proposed scheme is compared with other two schemes such as smoothed throughput rate (STR) and Buffer Based Rate (BBR) in terms of prediction error, QoE preferences, buffer size, and startup delay time, then the proposed scheme outperforms these schemes in attaining smooth video bitrates and continuous video playback.

The security strengths of block ciphers greatly rely on the confusion components which have the tendency to transform the data nonlinearly into the perplexed form. This paper proposes to put forward a novel scheme of generating cryptographically strong nonlinear confusion components of block ciphers, usually termed as substitution-boxes (S-boxes). The anticipated S-box design scheme is based on a novel five-dimensional (5-D) chaotic system analyzed in this paper. The proposed 5-D dynamical system consists of hyperchaotic phenomenon, KY dimension, conservativity, unstable equilibrium point, and complex phase attractors which are suited for cryptographic applications. The S-box based on hyperchaotic system is made to evolve in order to generate an optimized S-box for high nonlinearity score to make it robust against many linear attacks. The performance analysis of proposed S-box demonstrates that it has bijectivity, high nonlinearity; satisfied strict avalanche criterion and bits independent criterion; low differential and linear probabilities. Moreover, performance appraisal of proposed S-box justifies its better strength and features over many recently investigated S-boxes.

Human crowd analysis has common utilizations from the urban engineering and traffic management to law enforcement. They all need a crowd for first being detected, and is the issue that has been dealt with in the present study. Considering an image, the algorithm that has been proposed in this paper performs a segmentation of that image to crowd and non-crowd areas. The fundamental concept is capturing two main characteristics of the crowd: (a) on a narrower scale, its main elements have to appear like humans (only weakly so, as a result of the low resolution, dressing variations, occlusion, and so on), whereas (b) on the wider scale, the crowd intrinsically includes elements of the redundant appearance. The proposed approach makes use of that through the utilization of underlying statistical framework which has been based on the quantized features of the SURF. The two previously mentioned characteristics of the crowds have been obtained through the resultant statistical model responses’ feature vector, which describe the level of crowd-like appearances around the location of an image with the increase of the spatial level around it.

Fog computing has proved its importance over legacy cloud architectures for computation, storage, and communication where edge devices are used to facilitate the delay-sensitive applications. The inception of fog nodes has brought computing intelligence close to the end-devices. Many fog computing frameworks have been proposed where edge devices are used for computation. In this paper, we proposed a simulation framework for fog devices that can use end devices to handle the peak computation load to provide better Quality of Services (QoS). The regional fog nodes are deployed at network edge locations which are used as an intelligent agent to handle the computation requests by either scheduling them on local servers, cloud data centers, or at the under-utilized end-user devices. The proposed device-to-device resource sharing model relies on Ant Colony Optimization (ACO) and Earliest Deadline First(EDF) Algorithm to provide a better quality of service using device available at multi-layer design. The concept of using IoT devices as fog nodes has improved the performance of legacy fog based systems. The proposed work is benchmarked in terms of system cost, efficiency, energy, and quality of service. Further, the proposed framework is with xFogSim in terms of task efficiency.

Protection of data transmitted over the network from illegal access is one of the major challenges being posed by exponential growth of data in online digital communication. Modern cryptosystems assist in data sanctuary by utilizing substitution-boxes (S-boxes). This paper presents a modest and novel technique to erect dynamic and key dependent S-boxes with the help of a novel linear trigonometric transformation. A new optimization plan is also suggested to improvise the nonlinearity characteristic of the preliminary S-box generated through trigonometric transformation. The proposed technique has the competence to create significant quantity of cryptographic strong S-boxes with the help of projected scheme. A specimen S-box is procreated, and standard performance criteria is applied to appraise the cryptographic strength of the resultant S-box and other known S-boxes available in the literature. Comparative performance analyses validate the noteworthy contribution of the proposed scheme for the generation of dynamic and secure S-boxes. An image privacy preserving scheme based on the proposed S-box is also suggested to validate the fact that it holds strong candidature for modern cryptosystems to protect multimedia data.

The revolution of Cloud Computing increases the opportunities to provide realistic and most sophisticated evaluation modules that reduce the management time and cost of network performance evaluation and failure prediction. In our research, This paper presents a cloud-based software system that utilizing the Amazon Elastic MapReducer (EMR) ensemble clustered instances for evaluating the collected network measurements to quantifies network performance and predicate its degradation in the long run. The extracted outcomes illustrate the efficiency of the proposed system.

Smart city has developed energy, environmental, and healthcare services. It is also continuously providing new services to all citizens. This paper is concerned with the design and implementation of smart meter system as the core for smart grid in smart city. A system is proposed where the electricity supply is monitored by measuring its related parameters (voltage, current, power, energy consumption, and consumption bill) and issuing Short Message Service (SMS) notification of the consumption. The designed system used PZEM-004T, Arduino Mega, Raspberry Pi and Node-Red platforms. The data related to the measured parameters are successfully transmitted to the datacenter using Message Queuing Telemetry Transport (MQTT) protocol, stored in MySQL database using core python program, and displayed on Node-Red platform. The test and verification of the system are performed using different scenarios showing that successful and accurate operation of the system components are achieved. Finally, the designed system can be extended to cover large geographical areas and can be modified to serve for pre-paid arrangement in an effort to assist in reducing the electricity consumption in Iraq with the continuing crises of electricity.

This research presents a method of image encryption that has been designed based on the algorithm of complete shuffling, transformation of substitution box, and predicated image crypto-system. This proposed algorithm presents extra confusion in the first phase because of including an S-box based on using substitution by AES algorithm in encryption and its inverse in Decryption. In the second phase, shifting and rotation were used based on secrete key in each channel depending on the result from the chaotic map, 2D logistic map and the output was processed and used for the encryption algorithm. It is known from earlier studies that simple encryption of images based on the scheme of shuffling is insecure in the face of chosen cipher text attacks. Later, an extended algorithm has been projected. This algorithm performs well against chosen cipher text attacks. In addition, the proposed approach was analyzed for NPCR, UACI (Unified Average Changing Intensity), and Entropy analysis for determining its strength.

E-Learning system gains a great attention in the past years; with advance of the internet and the information exchange techniques the importance to merge the traditional learning means with the internet-based learning methods became a must especially in Iraq, the Iraqi higher education is now coping with the new information and communication technologies and adopting a modern methods for upgrading their education and learning ways. There are great efforts to blend E-Learning systems with the educational process, in order to fulfill this purposes the proposed research is advancing E-Learning systems by suggesting a hybrid method that combines two Artificial Intelligence Techniques (AI) inside the design and the development of an intelligent E-Learning system for computer science department at university of technology. The utilization of Artificial Neural Networks algorithm (ANNs) especially Recurrent Neural Networks (RNN) is a way of implementing deep learning technique to predict the students' final out comes in virtual class room based on their grades and their learning behaviors. RNN is optimized by utilizing ADAM optimizer to lift the accuracy of the proposed algorithm, the dataset are gathered and processed to suite the education purposes and was divided into80% for training the model and 20% for testing the model, the results of the hybrid model are compared with other machine learning methods like Multi-Layer Perceptron (MLP), decision tree, naïve Bayesian, and random forest using WEKA environment, the results of the proposed model showed a promising accuracy when compared with the mentioned machine learning algorithms.

In this work, a grayscale image steganography scheme is proposed using a discrete wavelet transform (DWT) and singular value decomposition (SVD). In this scheme, 2-level DWT is applied to a cover image to obtain the high frequency band HL2 which is utilized to embed a secret grayscale image based on the SVD technique. The robustness and the imperceptibility of the proposed steganography algorithm are controlled by a scaling factor for obtaining an acceptable trade-off between them. Peak signal to noise ratio (PSNR) and Structural Similarity Index Measure (SSIM) are used for assessing the efficiency of the proposed approach. Experimental results demonstrate that the proposed scheme still holds its validity under different known attacks such as noise addition, filtering, cropping and JPEG compression

Many practical applications for analyzing the reliability of complex system by using fault tree analysis, in this study we introduce fault tree analysis to calculate reliability of safety automatic...

The main idea of this research is to consider Fibrewise I-proximity Space as well as, introduce fibrewise ρ-map and a I-proximal neighbourhood , Likewise those p-continuous maps continuous with res...

There was suggested new utilizing of the dispersion principle, based on the Lorenz Map, and chaos theory is known as perfect for using cryptography applications for their properties like unpredictability and sensitive initial states as one of the complex encryption approaches. to disengage the color of pixels (R, G, B). Was created this suggest with mixing all each color pixel to swap horizontally, vertically, or diagonally, finally using XOR operation. only milliseconds to encryption and decryption image, because the behavior of block cipher that leads to the period for the image to be decrypted fairly close as the images. The experiments demonstrate that the information security capabilities will be both safe more efficient, the result of our analysis of picture quality evaluation, differential attacks (NPSR), (UACI), Pixels correlation shows the quality and strength of encryption processing, Entropy show good results and closely to 8.

Box culverts are the monolithic unit build to pass across railway lines, roadways, etc. earthworks are made to balance the discharge water on both sides. Box takes different types of loads created by a cushion, traffic, water, soil, etc. This paper deals with the optimum design of box culvert by using Newton's-Raphson Method and AppDesigner in MATLAB Software R2017a and studies the design parameters such as the influence of depth of earth fill at the top slab of the culvert, earth pressure, factor Dead Load, Live load, effective width, etc. In this paper, the study of the box-culvert with normal and minimum cushion analyzed for different classes of loadings and conclusions made on the basis of Newton's-Raphson Method normal and minimum cushion and normal cushioning cases.

A modified version of the artificial Bee Colony Algorithm (ABC) was suggested namely Adaptive Dimension Limit- Artificial Bee Colony Algorithm (ADL-ABC). To determine the optimum global path for mobile robot that satisfies the chosen criteria for shortest distance and collision–free with circular shaped static obstacles on robot environment. The cubic polynomial connects the start point to the end point through three via points used, so the generated paths are smooth and achievable by the robot. Two case studies (or scenarios) are presented in this task and comparative research (or study) is adopted between two algorithm’s results in order to evaluate the performance of the suggested algorithm. The results of the simulation showed that modified parameter (dynamic control limit) is avoiding static number of limit which excludes unnecessary Iteration, so it can find solution with minimum number of iterations and less computational time. From tables of result if there is an equal distance along the path such as in case A (14.490, 14.459) unit, there will be a reduction in time approximately to halve at percentage 5%.

Prosthetic is an artificial tool that replaces part of the human frame absent because of ailment, damage, or distortion. The current activities in Iraq draw interest to the upper limb discipline because of the growth in variety of amputees and. It is necessary to do extensive researches in this subject to help lessen the struggling of patients. This paper describes the design and development of low-cost prosthesis for people with transradial amputations. The presented design involves a hand with five fingers moving by means of a gear box mechanism. The design of this artificial hand allows five degrees of freedom(5DOF), one degree of freedom for each finger. The artificial hand works by an actuation system (6V) Polou motor with gear ratio equal to 50:1 due to its compactness and cheapness. The designed hand was manufactured by a 3D printing process using polylacticacid material (PLA). Some experimental were accomplished using the designed hand for gripping objects. Initially the EMG signal was recorded when the muscle contracted in one second, two seconds, three seconds. The synthetic hand was able to produce range of gesture and grasping moves separately just like the actual hand by using KNN classification which are complete hand Pinch, fist, and jack chuck. The simulation of the fingers movements was achieved using ANSYS software to analysis the movement (pinch, fist, and jack chuck), obtain bested of stress influencer at each finger, and maximum deformation at each movement.

In this paper, a real-time ASL recognition system was built with a ConvNet algorithm using real colouring images from a PC camera. The model is the first ASL recognition model to categorize a total of 26 letters, including (J & Z), with two new classes for space and delete, which was explored with new datasets. It was built to contain a wide diversity of attributes like different lightings, skin tones, backgrounds, and a wide variety of situations. The experimental results achieved a high accuracy of about 98.53% for the training and 98.84% for the validation. As well, the system displayed a high accuracy for all the datasets when new test data, which had not been used in the training, were introduced.

يتناول هذا البحث تقديم متحكم منطقي ضبابي للسيطرة على قوى التعليق الخاصة بمحرك تيار مستمر ذاتي التعليق مستخدم في مضخات الدم الصغيرة.يتميز المحرك بانه يجمع بين وظيفة الحركة الدورانية ووظيفة المحامل المغناطيسي,مما يجعله يتميز بحجم صغير نسبة للمحركات ذوات المحامل المنفصل.تم تصميم المحرك باستخدام برنامج Matlab وبرمجيات المحاكاة.

A Tonido cloud server provides a private cloud storage solution and synchronizes customers and employees with the required cloud services over the enterprise. Generally, access to any cloud services by users is via the Internet connection, which can face some problems, and then users may encounter in accessing these services due to a weak Internet connection or heavy load sometimes especially with live video streaming applications overcloud. In this work, flexible and inexpensive proposed accessing methods are submitted and implemented concerning real-time applications that enable users to access cloud services locally and regionally. Practically, to simulate our network connection, we proposed to use the Raspberry-pi3 model B+ as a router wireless LAN (WLAN) that enables users to have the cloud services using different access approaches such as wireless and wireline connections. As a case study for a real-time application over the cloud server, it is suggested to do a live video streaming using an IP webcam and IVIDEON cloud where the streaming video can be accessed via the cloud server at any time with different users taking into account the proposed practical connections. Practical experiments showed and proved that accessing real-time applications of cloud services via wireline and wireless connections is improved by using Tonido cloud server's facilities.