Computer
Haider Saeed Wdhayeh; Raghad Abdulaali Azeez; Athraa Jasim Mohammed
Abstract
In this paper, an algorithm to hide information in an image using QR code technology is presented. QR Code “QUICK RESPONSE CODE” is a two-dimensional array that can include different types of data and was first developed in 1993 for the Japanese Toyota Corporation for the purpose of tracking ...
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In this paper, an algorithm to hide information in an image using QR code technology is presented. QR Code “QUICK RESPONSE CODE” is a two-dimensional array that can include different types of data and was first developed in 1993 for the Japanese Toyota Corporation for the purpose of tracking products through production and marketing. The researchers paid great attention to QR code technology especially in the field of information security. The proposed algorithm in this paper hides the secret text in the image in a random way by generating random positions and using the LSB “Least Significant Bit” method. After that, the random positions are saved in the QR code file, and this is the hiding stage. In the extraction stage, the QR code file is read first to extract the positions where the secret text has been hidden. After that, the secret text is read according to the LSB method. The algorithm was implemented using the C-Sharp programming language and Microsoft Visual Studio 2019 development environment. After conducting experiments on a number of images and extracting results based on the PSNR “Peak signal-to-noise ratio “test method, the results were good and the algorithm is very strong against a brute force attack. This algorithm can be used in building authentication systems.
Communication
Zaid Hashim Jaber; Dheyaa Jasim Kadhim; Ahmed Sabah Al-Araji
Abstract
Massive Multiple-Input Multiple-Output (MIMO) is an extension of the conventional MIMO in the wireless systems which improves both of the access density and the spectral efficiency by adding a massive number of antenna array at the base station (BS). Massive MIMO increases the spectral efficiency by ...
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Massive Multiple-Input Multiple-Output (MIMO) is an extension of the conventional MIMO in the wireless systems which improves both of the access density and the spectral efficiency by adding a massive number of antenna array at the base station (BS). Massive MIMO increases the spectral efficiency by using the beamforming. Besides, the beamforming in massive MIMO improves the energy efficiency by focusing the energy in the desired direction instead of the omnidirectional propagation. In this paper, we propose and discuss different beamforming objectives in both the uplink and the downlink channels. These proposed objectives can be either use the beamforming of the desired signal without nulling the interference or use the beamforming with interference nulling. The beamforming with nulling objectives have better performance than those without nulling but this leads to a higher computational complexity as well. The results of this paper show and compare the performance of these objective including the spectral efficiency and energy efficiency as well as the computational complexity.
Computer
Safa S. Abdul-Jabbar; Alaa K. Farhan; Rana F. Ghani
Abstract
Blockchain technology relies on cryptographic techniques that provide various advantages, such as trustworthiness, collaboration, organization, identification, integrity, and transparency. Meanwhile, data analytics refers to the process of utilizing techniques to analyze big data and comprehend the relationships ...
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Blockchain technology relies on cryptographic techniques that provide various advantages, such as trustworthiness, collaboration, organization, identification, integrity, and transparency. Meanwhile, data analytics refers to the process of utilizing techniques to analyze big data and comprehend the relationships between data points to draw meaningful conclusions. The field of data analytics in Blockchain is relatively new, and few studies have been conducted to examine the challenges involved in Blockchain data analytics. This article presents a systematic analysis of how data analytics affects Blockchain performance, with the aim of investigating the current state of Blockchain-based data analytics techniques in research fields and exploring how specific features of this new technology may transform traditional business methods. The primary objectives of this study are to summarize the significant Blockchain techniques used thus far, identify current challenges and barriers in this field, determine the limitations of each paper that could be used for future development, and assess the extent to which Blockchain and data analytics have been effectively used to evaluate performance objectively. Moreover, we aim to identify potential future research paths and suggest new criteria in this burgeoning discipline through our review.
Computer
Afrah Salman Dawood; Zena Mohammed Faris
Abstract
Recently, Deep Learning (DL) has accomplished enormous prosperity in various areas, like natural language processing (NLP), image processing, different medical issues and computer vision. Both Machine Learning (ML) and DL as compared to traditional methods, can learn and make better and enhanced use ...
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Recently, Deep Learning (DL) has accomplished enormous prosperity in various areas, like natural language processing (NLP), image processing, different medical issues and computer vision. Both Machine Learning (ML) and DL as compared to traditional methods, can learn and make better and enhanced use of datasets for feature extraction. This paper is divided into three parts. The first part introduces a detailed information about different characteristics and learning types in terms of learning problems, hybrid learning problems, statistical inference and learning techniques; besides to an exhausted historical background about feature learning and DL. The second part is about the major architectures of DL with mathematical equations and clarified examples. These architectures include Autoencoders (AEs), Generative Adversarial Networks (GANs), Deep Belief Networks (DBNs), Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and Recursive Neural Networks. The third part of this work represents an overview with detailed explanation about different applications and use-cases. Finally, the fourth part is about hardware/ software tools used with DL.
Computer
Asmaa Ibrahim Hussieen; Abeer Tariq MaoLood; Ekhlas Khalaf Gbash
Abstract
Conventional voting activities are often replaced by electronic voting (EV) in light of the quick expansion of the Internet. For a variety of reasons, various nations have lately switched to EV rather than conventional voting. Different EV systems were presented up to this point. In both practical and ...
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Conventional voting activities are often replaced by electronic voting (EV) in light of the quick expansion of the Internet. For a variety of reasons, various nations have lately switched to EV rather than conventional voting. Different EV systems were presented up to this point. In both practical and theoretical fields, on the other hand, there is no perfect solution. To meet such objectives, the researchers strive for preserving cryptographic primitives when developing high-efficiency e-voting schemes. The concept of fog computing was developed to improve network infrastructure to satisfy the demands of large amounts of data the same time as also increasing the efficiency of the processing power. Also, it has been created as well to address concerns with Cloud computing, like the distribution environment complexity, real-time response, mobility, and IoT application location awareness. The concentration of this study was on a complete review regarding the systems of EVs through various scholars as a platform to detect flaws or problems in the deployment of extremely secure EV systems. In addition, nations having a history of EV system adoption were examined. A concept for future work on establishing a safe EV system depends on problems discovered in numerous works.
Control
Nasir Ahmed Alawad; Amjad J Humaidi; Ahmed Sabah Alarejee
Abstract
Exoskeleton robots help users with mechanical forces by recognizing their intentions, and they require a lot of energy efficiency, a lot of load capacity, and a good fit. A basic one degree of freedom (DOF) construction was devised in this work, which was mostly used in the knees of exoskeleton robots. ...
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Exoskeleton robots help users with mechanical forces by recognizing their intentions, and they require a lot of energy efficiency, a lot of load capacity, and a good fit. A basic one degree of freedom (DOF) construction was devised in this work, which was mostly used in the knees of exoskeleton robots. The exoskeleton is a small robotic device used for knee injury training. It is a nonlinear mathematical model with many mechanical factors that might vary and produce uncertainty, as well as external disturbances that can be utilized to monitor control. The transitioning process is frequently organized using tracking differentiator TD to resolve the conflict between system speed and overshoot. An active disturbance rejection control (ADRC) with a modified tracking differentiator is described to tackle these challenges, enhance control accuracy, and reduce settling time for exoskeleton modified trajectory differentiator (MTD).Simulation tests showed that (MTD) reduced the tracking error by 36%, when compared with the improved TD1 and 37.5% for Hans TD2 at uncertainty case . Despite the presence of several model uncertainties, the suggested training knee exoskeleton robot system using the MTD-ADRC was able to achieve the necessary target value. Control design and analysis can be done with Matlab and Simulink
Communication
Khasraw A. Abdulrahman; Jalal J Hamad Ameen
Abstract
The fifth generation (5G) of mobile technology is emerging as a advance communication network, delivering elevated speeds, coverage and reliability, this technology like other technologies not clear from drawbacks and limitations, 5G mobile system like other mobile systems 4G, 3G and 2G affected by interference ...
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The fifth generation (5G) of mobile technology is emerging as a advance communication network, delivering elevated speeds, coverage and reliability, this technology like other technologies not clear from drawbacks and limitations, 5G mobile system like other mobile systems 4G, 3G and 2G affected by interference and signal quality is going to be decreased because of higher number of C-Node-Bs which is because higher frequency and smaller coverage, in this paper, interference effect has been studied with both types cochannel and adjacent channel, best case and worst cases has been presented simulated and calculated the signal to interference ratio vs cluster size for different pathloss exponents , models and techniques of minimizing this effect has been studied starting with 5G cell planning, then a proposed network using optical fiber between C- Node-Bs, the proposed network model will minimize the interference effect to about negligible level, results shown in this paper about total length of fiber optic cables and cluster size, also, an example with best cluster size has been presented.
Communication
Akam Hussein Hasan; Jalal J Hamad Ameen
Abstract
Since the need for larger data rates and wireless system radio networks has increased, several organizations in this industry have started to develop and implement their 5G mobile technology scenarios. Since mobile telecommunications' quick expansion has motivated companies to constantly plan and work ...
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Since the need for larger data rates and wireless system radio networks has increased, several organizations in this industry have started to develop and implement their 5G mobile technology scenarios. Since mobile telecommunications' quick expansion has motivated companies to constantly plan and work from the first generation to the fourth generation of mobile technologies. MIMO systems and beamforming antenna arrays are expected to be very important. In the 5G wireless communication systems to be utilized after 2020, when they are paired with massive MIMO systems. In this paper, the main goal is to determine the benefits of beamforming techniques in massive MIMO systems in order to increase system throughput and reduce interference, thus eliminating and resolving the various technical challenges that are presented by the implementation of massive MIMO system architectures. The goal of this work is to contribute to the development of a 5G mobile system's C-Node-B base station transceiver. The suggested design makes use of a (64 x 64 MIMO) system and optimum the beamforming technology, MIMO parameters, and the primary fundamental parameters in beamforming.
Computer
Muna Khalaf; Ban N. Dhannoon
Abstract
Semantic segmentation refers to labeling each pixel in the scene to its belonging object. It is a critical task for many computer vision applications that requires scene understanding because It attempts to mimic human perceptual grouping. Despite the unremitting efforts in this field, it is still a ...
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Semantic segmentation refers to labeling each pixel in the scene to its belonging object. It is a critical task for many computer vision applications that requires scene understanding because It attempts to mimic human perceptual grouping. Despite the unremitting efforts in this field, it is still a challenge and preoccupies of researchers. Semantic segmentation performance improved using deep learning rather than traditional methods. Semantic segmentation based on deep learning models requires capturing local and global context information, where deep learning models usually can extract one of them but is challenging to integrate between them. Deep learning based on attention mechanisms can gather between the capturing of local and glopal information, so it is increasingly employed in semantic segmentation. This paper gives an introductory survey of the rising topic attention mechanisms in semantic segmentation. At first, it will discuss the concept of attention and its integration with semantic segmentation requirements. Then, it will review deep learning based on attention mechanisms in semantic segmentation.
Control
Mayyasah Ali Salman; Saleem Khalefa Kadhim
Abstract
The lower limb amputees are increasing day by day. This has led to an increase in research in the field of prosthetic knee. In this work, a prosthetic knee was designed and developed to assist human movements and more quality of life for millions of individuals who have lost lower limbs. The dynamic ...
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The lower limb amputees are increasing day by day. This has led to an increase in research in the field of prosthetic knee. In this work, a prosthetic knee was designed and developed to assist human movements and more quality of life for millions of individuals who have lost lower limbs. The dynamic model and parameter identification of a two degree of freedom (2-DOF) joint prosthetic knee is derived according to the Lagrangian dynamic approach. The two controllers Backstepping and Adaptive Backstepping are adopted to control the system. Stability analysis and controller design dependent on Lyapunov theory are assessed to prove a tracking of a desired trajectory. From the results, found that the quantitative comparison between the two controllers, showed significant improvement in results in position tracking. To comparison between Backstepping control and Adaptive Backstepping control, at the control action consumptions. It was found that the position error of the prosthetic knee in Backstepping control is by 9% at link 1 (thigh) and 7.4% at link 2 (shank) compared with desired trajectory, while in Adaptive Backstepping control is by 1.16% at link 1 and 1.65% at link 2 compared with desired trajectory. When comparing between Backstepping control and Adaptive Backstepping control, the improvement rate was 7.84 at link 1 and 5.75 at link 2 , the proposed Adaptive Backstepping control, it may be concluded, is more robust against this perturbation and to deal with uncertainty. Therefore, the controller is built in a MATLAB environment, and its performance and robustness are assessed.
Communication
Baydaa Sh. Z. Abood; Hanan A. R. Akkar; Amean Sh. Al-Safi
Abstract
Compression of images process is a step in the image processing. It is concerned with the transmission and storage of digitally created images. Fractal coding is a potential image and video compression approach with good reconstruction fidelity and relatively large compression ratios, because of its ...
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Compression of images process is a step in the image processing. It is concerned with the transmission and storage of digitally created images. Fractal coding is a potential image and video compression approach with good reconstruction fidelity and relatively large compression ratios, because of its simplicity and great performance; fractal image compression (FIC) is a particularly popular approach in image compression applications. However, it has a significant disadvantage in the form of a long encoding time. This is because encoding any small bit necessitates a massive similarity search in the original data As a result; the FIC search time is reduced while the quality of the reconstructed images is maintained acceptable level in many introduced paper and other still a study topic in progress. Fractal images are images that are self-similar in that each individual part is the same as the total. This paper will discusses many attempts for more author that working on image and video compression using fractal compression technique based on various approach and with each discuss focuses on the main parameter of compression such compression ratio (CR), peak signal to noise ratio (PSNR) and encoding time, as well as the details of data set the used for testing also writing with each technique to creating fractal video and image compression.
Computer
Adnan T. Kareem; Hasanen S. Abdullah; Ahmed T. Sadiq
Abstract
argumentation has become an attraction recently, because it is widely used in decision-making, at 1994 Dung invented a new argumentation model, called Argumentation Framework AF. This system investigates assaults of arguments, and it also works away on attributes, this model is designed to take care ...
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argumentation has become an attraction recently, because it is widely used in decision-making, at 1994 Dung invented a new argumentation model, called Argumentation Framework AF. This system investigates assaults of arguments, and it also works away on attributes, this model is designed to take care of argument attacks among them, without paying attention to how the sentences are formulated or arranged, and identify the supporting and supporting arguments. It is also possible for a group of experts, to evaluate arguments to resolve the debate about the current problem, by determining the extent to which a particular argument affects the other by attacking it, This framework was a comprehensive new system, called the gaming argumentation framework (GAF), It helps make decisions about the current problems, through making Claims and Attack Determinations (CAD) to arguments, and after that, putting the result of those CAD to game theory, with 2 players for the purpose of achieving final results, which are helpful for decision-makers, in making decisions concerning current problems. The present paper gives a proposed system, using the GAF to build the dynamic model based on the gaming argumentation framework (DGAF); it as works as the GAF by adding the feedback to suit all possible conditions, and by making a companion between them, the argumentation and the game theory. Since the foreign exchange market depends on changing conditions, it was a case study.
Communication
Noora Nazar kamal; Qusay F. Al-Doori; Omar Alani
Abstract
Data theory coding is an excellent and well-known branch of study that has produced various crucial solutionsto the insoluble challenges of safe data transfers. Last improvements in detecting error techniques have resulted in a significant increase in the use of low-density parity-check (LDPC) code to ...
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Data theory coding is an excellent and well-known branch of study that has produced various crucial solutionsto the insoluble challenges of safe data transfers. Last improvements in detecting error techniques have resulted in a significant increase in the use of low-density parity-check (LDPC) code to address critical concerns connected to secure data transfer. Until now, decent efforts have been performed on LDPC codes that target low complexity, high performance, and low bit error rate goals. The final aim of this review is to provide a recent literature understanding of modern improvements previously mentioned and in LDPC encoding and decoding (applicative and theoretical) techniques. A comparative scan of many remarkable LDPC decoding algorithms, 5G standard requirements, popular power management methods, and low-energy LDPC design studies is also shown. Lastly, conclusions are presented by outliningkey study results, current concerns, and general thoughts on new research directions possibilities.
Control
Bashar F. Midhat
Abstract
Temperature control system is a widely applied process since temperature plays a major role in our life starting from room temperature conditioning to various industrial and medical applications. In this paper, a control algorithm is proposed for controlling the temperature of a certain process. Analysis ...
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Temperature control system is a widely applied process since temperature plays a major role in our life starting from room temperature conditioning to various industrial and medical applications. In this paper, a control algorithm is proposed for controlling the temperature of a certain process. Analysis is performed to verify the feasibility of the proposed control algorithm. A simulation is performed using MATLAB software to show the performance of the proposed control algorithm and a practical implementation is performed using Arduino to investigate the validity of the analysis. The results show the ability of the proposed controller to achieve the desired results which confirms the validity of the proposed controller and mathematical analysis.
Communication
Ghada K. Emad; Soukaena Hassan Hashiem
Abstract
Recently, the growth of data transmission through various networks has the necessity for an elevated level of security. Encryption is one of the essential technologies for protecting and ensuring the integrity of IoT devices. Secure communication among constrained devices is critical during data transmission ...
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Recently, the growth of data transmission through various networks has the necessity for an elevated level of security. Encryption is one of the essential technologies for protecting and ensuring the integrity of IoT devices. Secure communication among constrained devices is critical during data transmission from the client to the server devices. Lightweight cipher algorithms are defined as a secure solution for devices with limited computational functions and memory. On the other hand, most lightweight algorithms suffer from a trade-off between complexity and speed to produce a robust cipher algorithm. This paper evaluates the effectiveness of an image encryption technique that uses a Lightweight GIFT algorithm and logistic map equation-based dynamic DNA coding to create a secure, lightweight cipher algorithm for IoT devices. When we employed dynamic DNA coding by the binary bit method, we observed that the developed approach is more secure and has a high level of randomness due to the results. Additionally, the correlation between nearby pixels is approximately zero; there is no association between the two images. Therefore, the developed approach achieves a higher encryption efficiency when compared to the original algorithm.
