Sana S. Sabry; Thaker M. Nayl
Volume 19, Issue 1 , January 2019, , Page 63-70
Abstract
The network congestion is an essential problem that leads to packetslosing and performance degradation. Thus, preventing congestion in thenetwork is very important to enhance and improve the quality of service. Activequeue management (AQM) is the solution to control congestion in TCP networkmiddle nodes ...
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The network congestion is an essential problem that leads to packetslosing and performance degradation. Thus, preventing congestion in thenetwork is very important to enhance and improve the quality of service. Activequeue management (AQM) is the solution to control congestion in TCP networkmiddle nodes to improve theire performance. We design a linear quadratic(LQ)-servo controller as an AQM applied to TCP network to control congestionand attempt to achieve high quality of service under dynamic networkenvironments. The LQ-servo controller is proposed to provide queue lengthstabilization with a small delay and faster settling time. The designed controllerparameters are tuned by using the particle swarm optimization (PSO) method.The PSO algorithm was fundamentally applied to find the optimal controllerparameters Q and R, such that a good output response could be obtained. The PIcontroller is examined for comparison reasons. The MATLAB simulation resultshows that the controller is more effective than the PI in reaching zero steadystateerror with better congestion avoidance under the dynamic networkenvironment. Moreover, the proposed controller achieves a smaller delay andfaster settling time.
Noor Abdul Khaleq Zghair; Muayad Sadik Croock; Ali Abdul Razzaq Taresh
Volume 19, Issue 2 , April 2019, , Page 69-77
Abstract
Recently, indoor localization has witnessed an increase in interest,due to the potential wide range of using in different applications, such asInternet of Things (IoT). It is also providing a solution for the absence of GlobalPositioning System (GPS) signals inside buildings. Different techniques havebeen ...
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Recently, indoor localization has witnessed an increase in interest,due to the potential wide range of using in different applications, such asInternet of Things (IoT). It is also providing a solution for the absence of GlobalPositioning System (GPS) signals inside buildings. Different techniques havebeen used for performing the indoor localization, such as sensors and wirelesstechnologies. In this paper, an indoor localization and object tracking system isproposed based on WiFi transmission technique. It is done by distributingdifferent WiFi sources around the building to read the data of the trackedobjects. This is to measure the distance between the WiFi receiver and theobject to allocate and track it efficiently. The test results show that the proposedsystem is working in an efficient way with low cost.
Computer
Wid Badee; Muayad Sadik Croock
Abstract
Designing an efficient irrigation system is a crucial issue in agriculture, due to water scarcity problem around the world with the need of increasing agricultural production to satisfy the demands of the enlargement of population. Therefore, to design a smart irrigation system, a real monitoring of ...
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Designing an efficient irrigation system is a crucial issue in agriculture, due to water scarcity problem around the world with the need of increasing agricultural production to satisfy the demands of the enlargement of population. Therefore, to design a smart irrigation system, a real monitoring of field’s information that affects the watering status is required which can be achieved with Wireless Sensor Networks (WSN). In this paper, an irrigation system based WSN is proposed to save water, power, labor, and as a result, saving cost with production and profit increase. Sensor nodes collect field data to be sent to the Raspberry pi, as a main controller, to make optimal decisions about irrigation process. The field data includes the sensor readings of temperature and soil moisture. Crop evapotranspiration is also considered; thus, the required amount of water is estimated with a particular irrigation time to avoid over irrigation that hurts the plants growth and yields quality. The obtained results show the efficiency of the proposed system operation and controlling on the irrigation process. These results are taken for tomato plant as a case study. The monitoring tools are used to verify the suggested algorithm effectiveness in irrigation scheduling.
Mohammed Ali Yaseen; A. K. Abass
Volume 20, Issue 2 , April 2020, , Page 74-78
Abstract
In this paper, a fiber Bragg grating (FBG) strain sensor is simulated utilizing OptiGrating software. Then the proposed sensor is integrated into the wavelength division multiplexing (WDM) communication system via OptiSystem software in order to evaluate its performance as a strain sensor. The proposed ...
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In this paper, a fiber Bragg grating (FBG) strain sensor is simulated utilizing OptiGrating software. Then the proposed sensor is integrated into the wavelength division multiplexing (WDM) communication system via OptiSystem software in order to evaluate its performance as a strain sensor. The proposed WDM system has 4–channels with NRZ modulation format and 100 GHz frequency spacing. According to the results, the degradation in the receiving signal reaching the limitation value (6 for Q–factor and 10E–9 for BER) at applied strain ranging from 170 μ –to– 180 μ.
Computer
Heba Mohammed Fadhil; Mohammed Najm Abdullah; Mohammed Issam Younis
Abstract
Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques ...
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Trees (DT), K- nearest neighbor (KNN), and Logistic Regression (LR), have been used to identify the parameters that allow for effective price estimation. These approaches were tested on a data set of an extensive Indian airline network. When it came to estimating flight prices, the results demonstrate that the Decision tree method is the best conceivable Algorithm for predicting the price of a flight in our particular situation with 89% accuracy. The SGD method had the lowest accuracy, which was 38 %, while the accuracies of the KNN, NB, ADA, and LR algorithms were 69 %, 45 %, and 43 %, respectively. This study's presented methodologies will allow airline firms to predict flight prices more accurately, enhance air travel, and eliminate delay dispersion.
Computer
Ashraf Tahseen Ali; Hasanen Abdullah; Mohammed Natiq Fadhil
Abstract
Biometrics signs are the most important factor in the human recognition field and considered an effective technique for person authentication systems. Voice recognition is a popular method to use due to its ease of implementation and acceptable effectiveness. This research paper will introduce a speaker ...
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Biometrics signs are the most important factor in the human recognition field and considered an effective technique for person authentication systems. Voice recognition is a popular method to use due to its ease of implementation and acceptable effectiveness. This research paper will introduce a speaker recognition system that consists of preprocessing techniques to eliminate noise and make the sound smoother. For the feature extraction stage, the method Mel Frequency Cepstral Coefficient (MFCC) is used, and in the second step, the four features (FF) Mean, Standard Division, Zero-Cross and Amplitude, which added to (MFCC) to improve the results. For data representation, vector quantization has been used. The evaluation method (k-fold cross-validation) has been used. Supervised machine learning (SML) is proposed using Quadratic Discriminant Analysis (QDA) classification algorithms. And the results obtained by the algorithm (QDA) varied between 98 percent and 98.43 percent, depending on the way of features extraction that was used. These results are satisfactory and reliable.
Computer
Ali khalid Hilool; Soukaena H. hashem; Shatha H. Jafer
Abstract
Computer worms execute damaging functions in the network systems, compromising system security. Although researchers use a variety of methods to detect worms and prevent their spread. Detecting worms remains a challenge for the following reasons: First, a huge volume of irrelevant data affects classification ...
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Computer worms execute damaging functions in the network systems, compromising system security. Although researchers use a variety of methods to detect worms and prevent their spread. Detecting worms remains a challenge for the following reasons: First, a huge volume of irrelevant data affects classification accuracy. Second, frequently used individual classifiers in systems are poor at detecting all types of worms, Third, many systems are built on out-of-date information, rendering them useless for new worm species. As a result, providing a network intrusion detection system is vital for ensuring security and reducing the harm caused by worms on networks to information systems. The goal of the study is to discover computer worms in the computer networks and protect the systems from their damages. The proposed method uses the UNSW NB15 dataset to train and test the ensemble Ada boosting and Bagging algorithms with the Support Vector Nachine (SVM) as a contribution rather than a decision tree. Due to Correlation Feature Selection (CFS) identifying relationships between features and classes, and Chi-square (Chi2) determining whether features and classes are independent or not, we combined these two algorithms as a contribution in a method called CFS&Chi2fs to select the relevant features and reduce the time. The system achieved accuracy reaching 0.998 with Bagging(SVM), and 0.989 with Ada boost(SVM).
Rafal Al Yousuf; Jeffrey Uhlmann
Abstract
A recently-derived alternative method for computing the relative gain array (RGA) for singular and/or non-square systems has been proposed, which provably guarantees unit invariance. This property is not offered by the conventional method that uses the Moore-Penrose (MP) pseudoinverse. In this paper, ...
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A recently-derived alternative method for computing the relative gain array (RGA) for singular and/or non-square systems has been proposed, which provably guarantees unit invariance. This property is not offered by the conventional method that uses the Moore-Penrose (MP) pseudoinverse. In this paper, we note that the absence of the scale-invariance property by the conventional MP-RGA does not *necessarily* imply a practical disadvantage in real-world applications. In other words, while it is true that performance of a controller should not depend on the choice of units via its input and output variables, this does not necessarily imply that the resulting MP-RGA measures of component interaction lead to different controller-design input-output pairings. In this paper we consider the application of the MP-RGA to a realistic transfer function relating to a Sakai fractional distillation system. Specifically, for this transfer function we assess whether or not the choice of unit, which in this case relates to temperature, affects the choice of loop pairings implied by the resulting RGA matrix. Our results show that it does, thus confirming that unit-sensitivity of the MP-RGA undermines its rigorous use for MIMO controller design.
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
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
Ekhlas Kadhum Hamza; Marwan Alaa Hussein
Abstract
As the Internet of Things (IoT) is growing in popularity globally, which has resulted in a rise in cyber threats, experts are focusing more on its security. The majority of IoT security research to date has concentrated on huge devices, while small IoT devices have received comparably little attention. ...
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As the Internet of Things (IoT) is growing in popularity globally, which has resulted in a rise in cyber threats, experts are focusing more on its security. The majority of IoT security research to date has concentrated on huge devices, while small IoT devices have received comparably little attention. Our primary purpose is, therefore, to research how to ensure the operation of IoT devices that are small. The security gateway is a Security Settings on the Gateway for RaspberryPi built gateway that may link Internet of Things devices to their private network, safeguarding IoT devices from exposure to external networks. In addition, a variety of Security Settings on the Gateway for RaspberryPi security settings are installed, including fiel2ban and a Security Settings on the Gateway for RaspberryPi firewall, in order to avoid brute force and dictionary attacks. This article also studies the communication between Internet of Things (IoT) devices utilizing various secure communications, including Secure Shell (SSH), and analyzes their performance in a variety of circumstances. The gateway's experimental evaluation reveals that the proposed framework can secure tiny IoT devices.
Control
Mustafa Laith Muhammed; Amjad Jaleel Humaidi; Enass Hassan Flaieh
Abstract
The search algorithms are characterized by their ability to find the optimal path in a short calculation time. In this study, a comparative analysis has been conducted to perform path planning of planar manipulator for static obstacle avoidance based on graph search algorithms. Four methods have been ...
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The search algorithms are characterized by their ability to find the optimal path in a short calculation time. In this study, a comparative analysis has been conducted to perform path planning of planar manipulator for static obstacle avoidance based on graph search algorithms. Four methods have been taken into account to establish a comparison platform; namely, conventional A*, modified A*, Chaos A*, and circulation heuristic search (CHS) algorithms. The performance of comparison is evaluated in terms of length of optimal path and consumption time of calculation. All algorithms have been coded and simulated within the MATLAB software environment. According to computer simulation, the results showed that CHS algorithms outperform the other graph search ones in terms of generated path length, while the Choas A* could give the least calculation time as compared to its counterparts.
Ibrahim Malik ALattar; Abdul Monem S Rahma
Volume 21, Issue 2 , June 2021, , Page 102-114
Abstract
This paper aims to develop a new cryptographic algorithm that isbased on the magic square method of order five with multi message lengths tobe more complex in order to increase the complexity; in addition to comparingthe cipher with the use of the magic square of order five, four and three (allsingle ...
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This paper aims to develop a new cryptographic algorithm that isbased on the magic square method of order five with multi message lengths tobe more complex in order to increase the complexity; in addition to comparingthe cipher with the use of the magic square of order five, four and three (allsingle message length. The proposed work has been done by using two extrarounds and depending on round statuse ( even or odd) , messages are detectedto be used. The key is placed in agreed positions, then the remaining positionsare filled with the message, and then certain sums are calculated to representthe encrypted text. Speed, complexity, histogram calculations for images, andNIST calculations for texts were calculated, and the results were compared,where the complexity of the algorithms was as follows ((P)15 × (256)10)2 × (P)11× (256)14 and ((256)15 × (256)10)2 × (256)11 × (256)14 for GF(P) and GF(28)respectively , From that, it has been discovered that the proposed algorithm(Magic Square of order five with multi message length) is better than the rest ofthe algorithms as it has excellent complexity and a slight difference in thespeed.
Sarah Ammar Rafea; Abdulkareem Abdulrahman Kadhim
Volume 19, Issue 1 , January 2019, , Page 71-81
Abstract
Internet of Things (IoT) enables things to have connectivity throughthe internet. The number of things is growing fast and has to be uniquelyidentified through the Internet to communicate with other things. In WirelessSensor Networks (WSNs) each node can be considered as a thing. WSN noderesources are ...
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Internet of Things (IoT) enables things to have connectivity throughthe internet. The number of things is growing fast and has to be uniquelyidentified through the Internet to communicate with other things. In WirelessSensor Networks (WSNs) each node can be considered as a thing. WSN noderesources are very limited due to the need to communicate using low power andusually through unreliable links. Such limitations need an energy efficientrouting protocol. WSN is considered as a type of Low power and LossyNetwork (LLN). The routing protocol for low power and lossy network (RPL)is being adopted for LLN and has been standardized to enable connectivity ofWSN over IoT. RPL constricted a topology similar to tree topology. Nodes inRPL optimized its path using an objective function (OF). OF depends ondifferent node/link metrics in the optimization process. In this paper, an EnergyThreshold RPL (ETRPL) protocol is proposed. ETRPL depends on a newobjective function to enhance energy consumption of RPL protocol by takinginto account the remaining energy of the preferred parent node. ETRPL isimplemented using Cooja simulator. The results show that ETRPL provides anincrease in the remaining energy of at least 87.4% for a small area with highnumber of nodes. ETRPL also performed better with regards to Time Delay,Packet Reception Ratio, and the number of dead nodes in a small area. For alarge area, the performance is not encouraging. Thus the proposed ETRPLprotocol is useful for IoT networks with relatively small areas.
Ammar T. Namel; Mouayad A. Sahib; Shatha M. Hasan
Volume 19, Issue 2 , April 2019, , Page 78-89
Abstract
monitoring the behavior of computer networks is essential forproblem identification and optimal management. Part of this behavior to bemonitored is the utilization of the network bandwidth. Several techniques areused to model and forecast network traffic such as time series models, moderndata mining ...
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monitoring the behavior of computer networks is essential forproblem identification and optimal management. Part of this behavior to bemonitored is the utilization of the network bandwidth. Several techniques areused to model and forecast network traffic such as time series models, moderndata mining techniques, soft computing approaches, and neural networks areused for network traffic analysis and prediction. Efficient bandwidth utilizationand optimization are very interesting research issues in effective networksbecause bandwidth is one of the most required and expensive Internetcomponents needed today. It is generally known that the higher the bandwidthavailable, the better the network performance, thus an essential aid for networkdesign and bandwidth wastage control and a need for traffic models which cancapture the characteristics is necessary. In this paper, a time series predictionmodels were proposed for LAN office network bandwidth utilization. Theproposed prediction models are tested by using evaluation metrics used in timeseries such as MSE and performance evaluation plot. Testing results show thatthe proposed models can enhance the detection of bandwidth traffic and providean efficient tool for bandwidth utilization.
Computer
sajjad shamkhi jaber; Yossra Ali; Nuha Ibrahim
Abstract
Task scheduling is one of the very crucial facets of cloud computing. The task scheduling method must assign jobs to virtual machines. In cloud computing, task scheduling includes a frontal influence on a system's resource utilization and operational costs. Diverse meta-heuristic algorithms, in addition ...
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Task scheduling is one of the very crucial facets of cloud computing. The task scheduling method must assign jobs to virtual machines. In cloud computing, task scheduling includes a frontal influence on a system's resource utilization and operational costs. Diverse meta-heuristic algorithms, in addition to their modifications, have been developed to improve the efficiency of task executions in the cloud. In this paper, a multiobjective optimization model is applied using the metaheuristics cuckoo search optimization algorithm (MCSO) to enhance the performance of a cloud system with limited computing resources while minimizing the time and cost. Finally, we analyze the performance of the proposed MCSO with the existing methods, such as Bee Life Algorithm (BLA), A Time–Cost aware Scheduling (TCaS) algorithm, Modified Particle Swarm Optimization (MPSO), and Round Robin (RR), for the evaluation metrics makespan and cost. Based on the outcomes of the experiments, it can be inferred that the proposed MCSO provides essential schedule jobs with the shortest makespan and average cost.
Nashwan Alsalam Ali; Abdul Monem S Rahma; Shaimaa h. Shaker
Abstract
The widespread of recent multimedia, including various 3D model applications in different domains of areas, may lead to 3D models being stolen and attacked by hackers. Moreover, 3D models must be protected from unauthorized users and when transmitting over the internet. Nowadays the 3D model protection ...
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The widespread of recent multimedia, including various 3D model applications in different domains of areas, may lead to 3D models being stolen and attacked by hackers. Moreover, 3D models must be protected from unauthorized users and when transmitting over the internet. Nowadays the 3D model protection is a very important issue. This paper proposed a scheme that provides high protection for the textured 3D model by implementing multiple levels of security. The first level of security is achieved by encrypting the texture map based on a key generated by a 2D Logistic chaotic map. The second level of security is implemented by modifying the vertices values of the 3D mesh based on keys generated by the 3D Lorenz chaotic map. The proposed scheme was implemented on various 3D textured models varying in the number of vertices and faces. The experimental results show that the proposed scheme has a good encryption and provides high security by completely deforms the whole texture and 3D mesh of the textured 3D model into the two levels. The encryption scheme has a large key space 10135 making the scheme resists violent attacks. The Hausdorff Distance (HD) and histogram metrics are adopted to calculate the matching degree between the original and extracted model. The results show that the original and extracted model are identical through the values of HD, which are approximate to zero, and the histogram visually is similar.
Computer
Sameeh Abdulghafour Jassim; Alaa K. Farhan
Abstract
Recently, the Internet of Things (IoT) is begin used in many fields such as smart homes, healthcare systems, industrial applications, etc. Therefore, the use of the IoT led to a growth in the number of dangers especially in the areas of privacy and security for applications running on low- resource computers. ...
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Recently, the Internet of Things (IoT) is begin used in many fields such as smart homes, healthcare systems, industrial applications, etc. Therefore, the use of the IoT led to a growth in the number of dangers especially in the areas of privacy and security for applications running on low- resource computers. Consequently, the demand for lightweight encryption methods is growing. To safeguard sensing data, this study introduces a Lightweight Advanced Encryption Standard (LAES) depending on dynamic ShiftRows, initial permutation instead of MixColumns, and a dynamic number of rounds. It was created with the goal of reducing encryption/decryption time. The proposed approach was assessed by using various measurements such as lengths of the key used was 2128 and it is quite enough for security, key sensitivity values were 100%, Also, this study compared the encryption/decryption time, NIST statistical test, and security strength of the proposed architecture to those of XTEA, SIMON, Skinny, SPECK, and PRESENT. The encryption/decryption time of the proposed approach was had the shortest period (0.0169 S) while the SPECK algorithm was had the longest period (4.1249 S) among the comparative algorithms. Whereas, NIST statistical test values of the proposed approach were passed successfully and had higher values than the comparative algorithms. Moreover, the proposed approach utilized 1280, 1024, and 768 GE with 6, 8, or 10 rounds respectively. The average number of GE was approximately 1000 GE. These numbers of GE are considered highly efficient with the IoT environment.
Computer
Thabit Sulaiman Sabbah
Abstract
Feature space high dimensionality is a well-known problem in text classification and web mining domains, it is caused mainly by the large number of vocabularies contained within web documents. Several methods were applied to select the most useful and important features over the years; however, the performance ...
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Feature space high dimensionality is a well-known problem in text classification and web mining domains, it is caused mainly by the large number of vocabularies contained within web documents. Several methods were applied to select the most useful and important features over the years; however, the performance of such methods is still improvable from different aspects such as the computational cost and accuracy. This research presents an enhanced cosine similarity-based hybridization of two efficient feature selection methods for higher classification performance. The reduced feature sets are generated using the Random Projection (RP) and the Principal Component Analysis (PCA) methods, individually, then hybridized based on the cosine similarity values between features’ vectors. The performance of the proposed method in terms of accuracy and F-measure was tested on a dataset of web pages based on several term weighting schemes. As compared to relevant methods, results of the proposed method show significantly higher accuracy and f-measure performance based on less feature set size.
Ashraf Tahseen Ali; Hasanen Abdullah; Mohammed Natiq Fadhil
Abstract
Finger veins are different from other biometric signs; it is a special characteristic of the human body. The challenge for an imposter to explore and comprehend it, since the veins are below the skin, it is impossible to tell which one is, and which one stands out because the person has more than one ...
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Finger veins are different from other biometric signs; it is a special characteristic of the human body. The challenge for an imposter to explore and comprehend it, since the veins are below the skin, it is impossible to tell which one is, and which one stands out because the person has more than one finger to examine. Impostor recognition based on applying three machine-learning methods will be presented in this article, and then there is a discussion at preprocessing, Linear Discriminant Analysis (LDA) for feature extraction, and k fold cross-validation as an evaluation method. These measures were carried out on two different datasets, which are the Shandong University Machine Learning and Applications - Homologous Multi-modal Traits (SDUMLA-HMT) Dataset and the University of Twente Finger Veins (UTFV) dataset. The classifier with the best results was Support Vector Machine (SVM) and Linear Regression (LR) had the lowest classifier accuracy.
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
Raja’a M. Mohammed; Suhad M. Kadhem
Abstract
Sign language (SL) is Non-verbal communication and a way for thedeaf and mute to communicate without words. A deaf and mute person's hands,face, and body shows what they want to say. Since the number of deaf and dumbpeople is increasing, there must be other ways to learn sign language orcommunicate with ...
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Sign language (SL) is Non-verbal communication and a way for thedeaf and mute to communicate without words. A deaf and mute person's hands,face, and body shows what they want to say. Since the number of deaf and dumbpeople is increasing, there must be other ways to learn sign language orcommunicate with deaf and dumb people. One of these ways is using advancedtechnology to produce systems that help the deaf/dumb, such as creatingrecognition and sign language translators. This paper presents an applicationthat works on the computer for machine translation of Iraqi sign language intwo directions from sign language to Arabic language (text/speech) and fromArabic language(text) to Iraqi sign language. The proposed system uses aConvolution Neural Network (CNN) to classify sign language based on itsfeatures to predicate the sign meaning. The sign language to Arabiclanguage(text/speech) part of the proposed system has an accuracy of 99.3% forletters.
Huda Ghazie Abd UL Sahib; Maisa Abid Ali Khodher
Volume 21, Issue 2 , June 2021, , Page 115-131
Abstract
This paper will present a comparison between three proposed methods. All of these methodsinclude hiding a secret message inside a video for the aim of transferring it to another party with highsecurity and a high embedding rate in order to ensure that the secret message is not discovered by theattacker. ...
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This paper will present a comparison between three proposed methods. All of these methodsinclude hiding a secret message inside a video for the aim of transferring it to another party with highsecurity and a high embedding rate in order to ensure that the secret message is not discovered by theattacker. In addition , facilitating deals with video frames as large data for the purpose of analyzing,dividing and controlling frames easily by the programmer, using the MapReduce method. This isdone by dividing the video into a series of frames, and before the hiding process, the message isencrypted using the advance encryption standard (AES) algorithm. These basic processes areimplemented in all three proposed methods, the rest of the details for each method are:The first method: used the pixel value difference (PVD) algorithm to hide the secret message in thevideo. In addition, the stego secret key was also used. This key is used for the purpose of deciding thelocations of the pixels that will be employed to hide the secret message inside it.The second method: the MapReduce principle is used for the purpose of facilitating dealing withvideo frames. The chosen frame will enter the MapReduce stages. This is implemented by dividing theframe into three matrices red, green, blue (RGB). Each matrix represents a map. Moreover, thetechnique that is used for concealment is the least significant bit (LSB) technology which uses thestego secret key (x2) for the purpose of selecting sites that will be hidden by it.The third method: Also, the MapReduce principle is used, but this method is implemented by dividingthe frame into four blocks. Each block represents a map. In one of the stages of the MapReduce, thehiding process will be done by using the (PVD) method which uses the stego secret key (n+15).Finally, the reducer, which is the last stage, will collect the results of each block to generate thestego-frame.The results of the three methods are efficiency, transparency, robustness and powerful in stegovideo. It is noticed that the second method has achieved the lowest capacity, thus achieving highsecurity. As for the third method, it achieved the highest capacity and the highest execution time wasthe first method. Despite this, all the three methods have achieved high security. The attacker orunauthorized person cannot detect any suspicious differences in a stego video. These results areobtained through using many measurements: peak signal-to-noise ratio (PSNR), Mean Squared Error(MSE), Entropy and correlation coefficient.
Farah F. Alkhalid; Bashra Kadhim Oleiwi
Volume 19, Issue 1 , January 2019, , Page 82-87
Abstract
This study focuses on the design of an autonomous wheelchair basedsmart driving features for disabled persons. The movement directions andposition tracking of the wheelchair are controlled and localized by pre-definedvoice commands and global positioning system (GPS), respectively. Arduinomicrocontroller ...
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This study focuses on the design of an autonomous wheelchair basedsmart driving features for disabled persons. The movement directions andposition tracking of the wheelchair are controlled and localized by pre-definedvoice commands and global positioning system (GPS), respectively. Arduinomicrocontroller based on speaker dependent voice recognition module andtracking system based on quad-board SIM808 has been used to help thewheelchair navigation. The experimental tests of the proposed system have beendone and given satisfactory results in controlling the wheelchair and making acall on demand. Hence the proposed system is a simple, easy to use and lowcosthardware for designing.
Inaam I. Ali; Mohanad Sh. Tarad Al-Aasam
Volume 19, Issue 2 , April 2019, , Page 90-99
Abstract
Electrical power systems are different in their sizes because of their amount of generation power stations, substations, transmission lines and loads. Therefore, these factors may impact on short circuit levels values. Capacity of power stations and dummy transmission lines in Extra high voltage grid ...
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Electrical power systems are different in their sizes because of their amount of generation power stations, substations, transmission lines and loads. Therefore, these factors may impact on short circuit levels values. Capacity of power stations and dummy transmission lines in Extra high voltage grid (400kV) of the Iraqi Electrical power grids cause high short circuit levels values such that exceed both rating of the peak and breaking capacity of switchgear equipment's. Reduction of short-circuit levels by using Fast-acting Flexible Alternating Current Transmission Systems (FACTS) types devices in power grids maintain the operation of power grids with acceptable value of short circuit levels for their electrical equipment's and preventing cascading event outages which may lead to blackouts. This paper mainly studies strategies on how to add Short Circuit Current Limiter (SCCL) device by determining its number, value and location of connection in power grids by programing with (PSS™E version 30.3 Package Program). IEEE 25-bus system is used for testing the adding series SCCL at power transmission lines method procedure. The results of adding series SCCL with power transmission lines give significant reducing short circuit levels for the stations have highest short circuit levels in order to prevent the blackouts of overall power grid.
