Computer
Dina M. Abdulhussien; Laith J. Saud
Abstract
Face detection technology is the first and essential step for facial-based analysis algorithms such as face recognition, face feature extraction, face alignment, face enhancement, and face parsing. That is besides serving other applications related to human intention and act analysis such as facial expression ...
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Face detection technology is the first and essential step for facial-based analysis algorithms such as face recognition, face feature extraction, face alignment, face enhancement, and face parsing. That is besides serving other applications related to human intention and act analysis such as facial expression recognition, gender recognition, and age classification. Face detection is used to detect faces in digital images. It is a special case of object detection and can be used in many areas such as biometrics, security, law enforcement, entertainment, and personal safety. There are various methods proposed in the field of face detection, and they all compete to make it more advanced and accurate. These methods belong to two main approaches; feature-based approach and image-based approach. This paper reviews the face detection methods that belong to the feature-based approach. Moreover, their work concepts, strengths, and limitations are mentioned. This paper concentrates on the feature-based approach due to its simplicity and high applicability in real-time detection compared to the image-based approach.
Computer
Esraa Q. Naamha; Matheel E. Abdulmunim
Abstract
The World Wide Web (WWW) is a vast repository of knowledge, including intellectual, social, financial, and security-related data. Online information is typically accessed for instructional purposes. On the internet, information is accessible in a variety of formats and access interfaces. ...
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The World Wide Web (WWW) is a vast repository of knowledge, including intellectual, social, financial, and security-related data. Online information is typically accessed for instructional purposes. On the internet, information is accessible in a variety of formats and access interfaces. Because of this, indexing or semantic processing of the data via websites may be difficult. The method that seeks to resolve this issue is web data scraping. Unstructured web data can be converted into structured data using web data scraping so that it can be stored and examined in a central local database or spreadsheet. This paper offers a metadata scraping using a programmable Customized Search Engine (CSE) system, which can extract metadata from web pages (HTML pages) in the Google database and save it in an XML format for later analysis and retrieval. Documents that contain metadata are a relatively recent phenomenon on the web and increase the likelihood that users will find the information they need.
Computer
Mohanad A. Mohammed; Hala B. Abdul Wahab
Abstract
decentralization within IoT eliminates the need to use distributed networks within IoT to communicate only with servers that may face difficulties related to the internet, vulnerabilities, DDOS, or hijacks, merging blockchain with IoT converted the IoT system into a decentralized with many benefits and ...
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decentralization within IoT eliminates the need to use distributed networks within IoT to communicate only with servers that may face difficulties related to the internet, vulnerabilities, DDOS, or hijacks, merging blockchain with IoT converted the IoT system into a decentralized with many benefits and outcomes from this conversion. An encryption scheme homomorphic technique (HE) is a method that encrypts the cipher data without the need to decrypt it,paillier encryption method is used. This paper aims to propose a system that integrates Paillier cryptosystem homomorphic technology with IoT and lightweight blockchain technology to provide decentralization to the IoT environment and improve security. The proposed system results in improving the IoT device’s work environment by solving the main challenges of security using blockchain, privacy using homomorphism, and data volume using blockchain. The data set used to implement and evaluate the proposed system is industrial internet of things data The dataset used in this paper is generated via machine industry 4.0 Storage System status which represents the system failure and work status. this system is evaluated using standard metrics used to evaluate the blockchain effectiveness and time, resources consumed and shows better results in time and power consumption.
Computer
Haider M. Al-Mashhadi; Hussain Jassim Fahad
Abstract
Electrical energy is one of the most important components of life today where different fields depend on it. The field of electrical energy distribution (electricity network), which transmits electrical energy from sources to consumers, is one of the most important areas that need to be developed and ...
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Electrical energy is one of the most important components of life today where different fields depend on it. The field of electrical energy distribution (electricity network), which transmits electrical energy from sources to consumers, is one of the most important areas that need to be developed and improved. In addition to analyzing electrical energy consumption, it needs to forecast consumption and determine consumer behavior in terms of consumption and how to balance supply and demand. The research aims to analyze weather data and find the relation between the weather factors and energy consumption in order to prepare data to use as a suitable data in machine learning model for future use. This model analyzes the building consumption rate for a particular area and takes into account the weather factors that affect electrical energy consumption, where (temperature, dew point, ultraviolet index) are selects based on the correlation confidence and then divided these factors into a set of categories using the K-Means algorithm to show the effect of each factors on the other.
Control
Aws M Abdullah; Farah F. Alkhalid; Ali Mohsin Kaittan
Abstract
The artificial intelligence techniques such as neural networks and fuzzy systems play an important role to disconnect flexion & expansion of the swing leg, the earth response force of the other foot has been redesigned. Underthat paper, we think the fuzzy controller plan issue for yield following ...
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The artificial intelligence techniques such as neural networks and fuzzy systems play an important role to disconnect flexion & expansion of the swing leg, the earth response force of the other foot has been redesigned. Underthat paper, we think the fuzzy controller plan issue for yield following flawed genuine investigation of nonlinear systems. For examination, an essential fuzzy control plot has been bristly developed dependent on a current methodology delegate under the field.In this paper, the Feedforward Neural Network has been implemented with integer, fixed point and floating point data representations. Additionally, The Fuzzy Logic Controllers in both analog and digital forms has been implemented in hardware. Both designs use less hardware resources and operate with reasonable speed compared to other existing designs. The digital implementation of Fuzzy Logic Controller has been tested for a simulated first order liquid level process and the performance results have been compared with those of the Matlab version of Fuzzy Logic Controller. Here, Fuzzy Logic Controller is used as the controller and is trained adaptively for the changes in process parameters using recursive k-means clustering algorithm for updating the centers of the hidden layer and Recursive Least Square algorithm for updating the weights of the output layer, the result of the settling time about 20ms and takes 20 iterations, and the squared error reaches zero at approximately 20 µs
Computer
Sama Salam Samaan; Hassan Awheed Jeiad
Abstract
Traditional network abilities have a drastic shortage in the current networking world. Software-Defined Networking (SDN) is a revival development in the networking domain that provides separation of control and data planes, enlarges the data plane granularity, and simplifies the network devices. All ...
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Traditional network abilities have a drastic shortage in the current networking world. Software-Defined Networking (SDN) is a revival development in the networking domain that provides separation of control and data planes, enlarges the data plane granularity, and simplifies the network devices. All these factors accelerate and automate the evolution of new services. However, when the SDN network topology becomes large, it poses new challenges in security, traffic management, and scalability due to the vast amounts of traffic data generated and the need for additional controllers to manage the significant number of networking devices. On the other hand, big data has become an attractive trend that can enhance network performance in general, specifically SDN. Both SDN and big data have gained great attraction from industry and academia. Traditionally, these two subjects have been studied separately in most of the preceding works. However, big data can impact the design and implementation of SDN thoroughly. This paper presents how big data can support SDN in various aspects, including intrusion detection, traffic monitoring, and controller scalability and resiliency. We suggest several approaches toward deeper cooperation between big data and SDN.
Computer
Suha Dh. Athab; Kesra Nermend; Abdulamir Abdullah Karim
Abstract
Microsoft Common Objects in Context (COCO) is a huge image dataset that has over 300 k images belonging to more than ninety-one classes. COCO has valuable information in the field of detection, segmentation, classification, and tagging; but the COCO dataset suffers from being unorganized, and classes ...
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Microsoft Common Objects in Context (COCO) is a huge image dataset that has over 300 k images belonging to more than ninety-one classes. COCO has valuable information in the field of detection, segmentation, classification, and tagging; but the COCO dataset suffers from being unorganized, and classes in COCO interfere with each other. Dealing with it gives very low and unsatisfying results whether when calculating accuracy or intersection over the union in classification and segmentation algorithms. A simple method is proposed to create a customized subset from the COCO dataset by determining the class or class numbers. The suggested method is very useful as preprocessing step for any detection or segmentation algorithms such as YOLO, SSPNET, RCNN, etc. The proposed method was validated using the link net architecture for semantic segmentation. The results after applying the preprocessing were presented and compared to the state of art methods. The comparison demonstrates the exceptional effectiveness of transfer learning with our preprocessing model.
Communication
Dina S Akram; Haydar M. AL-Tamimi
Abstract
Linear and non-linear impairments are the major problems that affected the dense wavelength division multiplexing (DWDM) system performance. In this simulation designs, two different compensation techniques have been proposed to eliminate signal impairments. The repeater technique was ...
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Linear and non-linear impairments are the major problems that affected the dense wavelength division multiplexing (DWDM) system performance. In this simulation designs, two different compensation techniques have been proposed to eliminate signal impairments. The repeater technique was proposed to reduce non-linear effects like four-wave mixing (FWM) which cause transfer power from DWDM channels to another new channels. The dispersion compensation fiber (DCF) technique was used to reduce dispersion effects which cause signal pulse broadening over long transmission distances. Also, three different modulation formats and four frequency separations were used to determine which modulation scheme is more compatible with the compensation techniques. The results is calculated in term of quality factor against power and noetic that the carrier suppressed return to zero (CSRZ) format offers the best performance with the DCF technique with 32.1804 Qfactor at 15dBm threshold power then, the differential phase shift keying (DPSK) format is compatible with the repeater technique with 27.7959 quality factor and 14dBm threshold power
Computer
Hind Moutaz Al-Dabbas; Raghad Abdulaali Azeez; Akbas Ezaldeen Ali
Abstract
Iris identification is a well‐ known technology used to detect striking biometric identification techniques for recognizing human beings based on physical behavior. The texture of the iris is essential and its anatomy varies from individual to individual. Humans have distinctive physical characteristics ...
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Iris identification is a well‐ known technology used to detect striking biometric identification techniques for recognizing human beings based on physical behavior. The texture of the iris is essential and its anatomy varies from individual to individual. Humans have distinctive physical characteristics that never change. This has resulted in a considerable advancement in the field of iris identification, which inherits the random variation of the data and is often a dependable technological area. This research proposes three algorithms to examine the classifications in machine learning approaches using feature extraction for the iris image. The applied recognition system used many methods to enhance the input images for iris recognition using the Multimedia University (MMU) database. Linear Discriminant Analysis (LDA) feature extraction method is applied as an input of three algorithms of machine learning approaches that are OneR, J48, and JRip classifiers. The result indicates that the OneR classifier with LDA achieves the highest performance with 94.387 % accuracy, while J48 and JRip reached to 90.151% and 86.885% respectively.
Computer
Sama Salam Samaan; Hassan Awheed Jeiad
Abstract
Modelling computer networks in general, particularly Software Defined Networking (SDN) as a graph, is beneficial in network planning and design, configuration management, traffic analysis, and security. According to the dynamic nature of SDN, it needs a fast response due to the rapid changes in the network ...
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Modelling computer networks in general, particularly Software Defined Networking (SDN) as a graph, is beneficial in network planning and design, configuration management, traffic analysis, and security. According to the dynamic nature of SDN, it needs a fast response due to the rapid changes in the network state. The SDN network topology can be modelled as a graph and stored in a graph database, and the traffic load of each switch is stored in the created graph. Consequently, a graph processing framework can be used to process the stored traffic data, and the results are utilized in traffic engineering to assist the SDN controller in network management. This paper provides a comprehensive literature survey involving graph techniques applied to SDN. Then, a summary of graph algorithms is presented. In addition, an overview of graph databases and graph processing frameworks is displayed. Finally, a model is suggested to integrate the graph database and graph processing framework in SDN traffic analysis.
Computer
Samara Mohammed Radhi; Raheem Ogla
Abstract
Securing information is difficult in the modern internet era, asterabytes of data are generated daily online and online transactions occurvirtually every second. The current world's information security relies heavily oncryptography, which makes the internet a safer environment. Making informationincoherent ...
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Securing information is difficult in the modern internet era, asterabytes of data are generated daily online and online transactions occurvirtually every second. The current world's information security relies heavily oncryptography, which makes the internet a safer environment. Making informationincoherent to an unauthorized person is done through the use of cryptography.Providing legitimate users with confidentiality as a result. There are a widevariety of cryptographic algorithms suitable for this purpose. An idealcryptography method would allow the user to do their job without breaking thebank. Unfortunately, there is no magic formula that can address everyissue.Several algorithms balance cost and performance. A banking applicationneeds robust security at a high cost, while a gaming software that sends userpatterns for analytics cares more about speed and cost. Thus, choosing theappropriate encryption technique for the user. This study offers importantinsights in the process of selecting cryptographic algorithms in terms of eachalgorithm's strengths, weaknesses, cost, and performance . In order todemonstrate an entire performance analysis in this article, as opposed to justtheoretical comparisons, this research developed and thoroughly examined thecost and performance of commonly used cryptographic algorithms, includingDES, 3DES, AES, RSA, and blowfish. According to the findings, blowfishrequires the smallest amount of time to decrypt files of various sizes (25K, 50K,1M, 2M, 3M, and 4M), and it also consumes the smallest amount of memory. Thismakes it approximately three times faster than other cryptographic algorithms.
Communication
Rawia Abdullah Muhammed; Maisa'a Abid Ali Al-Dabbas; Ashwak Mahmood Alabaichi
Abstract
The Internet of things (IoT) is one of those emerging technologies, which aregoing to rule the world in the next few decades. The IoT environment not only enablesHuman to Machine interaction but also fosters Machine to Machine connectivity.Numerous IoT devices have poor security and insufficient computing ...
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The Internet of things (IoT) is one of those emerging technologies, which aregoing to rule the world in the next few decades. The IoT environment not only enablesHuman to Machine interaction but also fosters Machine to Machine connectivity.Numerous IoT devices have poor security and insufficient computing power, making themprime targets for hackers. The IoT environment uses lightweight cryptographic techniquesto address security requirements. Another security method for IoT devices issteganography. In the contemporary Internet era, the ability to secure private informationis crucial, and steganography offers this capability. Due to its great ability to concealsensitive data, video has drawn the attention of numerous academics among all forms ofdigital media. The main goal of this work is to examine several methods for fusing videosteganography and cryptography techniques. Additionally, a thorough investigation andevaluation of a variety of video steganography methods in both compressed and rawdomains are also emphasized. The comprehensive analysis of prior material makes iteasier to have in-depth knowledge while creating approaches that combine cryptographywith steganography.
Computer
Ammar Abdul Ameer Rasheed; Ahmed Sabah Al-Araji; Mohammed Najm Abdullah; Hamed S Al-Raweshidy
Abstract
A client-server network is one of the most important topics in a computer network. In this work, a real-time computer control system is designed based on the Client-Server Model for a Multi-Agent Mobile Robot System (CSM-MAMRS) and is applied to a building that consists of (N) floors and uses one mobile ...
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A client-server network is one of the most important topics in a computer network. In this work, a real-time computer control system is designed based on the Client-Server Model for a Multi-Agent Mobile Robot System (CSM-MAMRS) and is applied to a building that consists of (N) floors and uses one mobile robot on each floor that has specific actions in different types of environments. The new proposed CSM-MAMRS consists of four layers. The first stage manages the network communication for each agent. The second stage solves the major problems of path planning by using a proposed hybrid algorithm that combines the Rapidly Exploring Random Tree Star (RRT*) and the Particle Swarm Optimization (PSO) algorithms in order to provide the shortest and smoothest path with collision avoidance between the starting and the target points in a static and dynamic robot environments are used.. In the third stage, a velocity planner controller is based on an inverse kinematic mobile robot model. In the fourth stage, the Hypertext Transfer Protocol HTTP is used to send velocity values to real mobile robots via the Wireless Network Control Administration. The simulation results and experimental works successfully achieved to significant improvement in real-time when using three missions of three mobile robots on different static map floors in the building. The maximum tracking pose errors for three robots in the static enviormnets are 0.39 cm, 0.02 cm, 0.32 cm respectively, but the maximum tracking pose error in the dynamic environments are 2.94 cm and 2.8 cm only for two mobile robots along the maximum distance of 250 cm.
Control
Imad Zuhair; Hasan M Alwan; Hussain M. Al-Khafaji
Abstract
The expert system and artificial intelligence are still important modern technologies. A structure can modify its behavior under dynamic stresses by using active controls. The term "intelligent" or "smart" structures refers to these self-modifying structures. The structural engineering discipline may ...
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The expert system and artificial intelligence are still important modern technologies. A structure can modify its behavior under dynamic stresses by using active controls. The term "intelligent" or "smart" structures refers to these self-modifying structures. The structural engineering discipline may experience a revolution thanks to smart structure technologies. Particularly for huge structures, It is anticipated to have major effects. Effects with regard to the avoidance of fatalities and damage to the structure and its contents, particularly with regard to huge buildings that have thousands of elements. An efficient control algorithm to establish the magnitude of the actual forces to be applied to the construction is one of the most critical components in the successful use of smart active control technology. An overview of the primary active control approaches for the reduction of vibration in intelligent mechanical and civil structures that are subject to external dynamic loads is provided in this study. Different control algorithms' benefits and drawbacks are examined. Finally, recent advances in the study of control algorithms are highlighted, including the use of multiparadigm strategies, decentralized control, deep learning techniques applied to neural networks design of controls for sustainability, and a merging of the domains of vibration control and structural health monitoring.
Computer
Yasmin A. Hassan; Abdul Monem S. Rahma
Abstract
Since the Internet has been more widely used and more people have access to multimedia content, copyright hacking, and piracy have risen. By the use of watermarking techniques, security, asset protection, and authentication have all been made possible. In this paper, a comparison between fragile and ...
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Since the Internet has been more widely used and more people have access to multimedia content, copyright hacking, and piracy have risen. By the use of watermarking techniques, security, asset protection, and authentication have all been made possible. In this paper, a comparison between fragile and robust watermarking techniques has been presented to benefit them in recent studies to increase the level of security of critical media. A new technique has been suggested when adding an embedded value (129) to each pixel of the cover image and representing it as a key to thwart the attacker, increase security, rise imperceptibility, and make the system faster in detecting the tamper from unauthorized users. Using the two watermarking types in the same system reaches better results and increases the power of the system and makes it robust against any attack and revel the modification if any at the same time. PSNR has been used as a performance metric to evaluate the study. The result of the new proposed watermark is 54. It is preferable to utilize both a fragile and a robust watermark simultaneously.
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