جامعة بلاد الرافدين - Bilad Alrafidain University - بحوث التقنيات الهندسية

التقنيات الهندسية

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م.د ايمن عبدالمنعم حميد (1 بحث)

Evaluation of DWDM-FSO Environment Based on OFDM Modulation Technique
	2024	Journal of Advanced Research in Applied Sciences and Engineering Technology
Dense wavelength division multiplexing (DWDM) has emerged as a promising technique for meeting rising bandwidth demands in optical networks. It has been used to boost the capacity of long-distance optical transport systems like free space optics (FSO) and optical fibre. FSO communication is an optical communication technology that sends optical data wirelessly from one location to another. Q-Factor and the BER analyser are used to assess the signal strength of the received signal. DWDM over FSO communication system is very effective in providing high data rate transmission with a very low bit error rate (BER). The maximum reach of the proposed system is 100 km without any compensation scheme. By implementing the OFDM Modulation Technique, four channels of DWDM over a FSO communication system were successfully demonstrated and has been analysed for higher data rate and the better quality of BER. The 15 Gb/s data rate with channel spacing at 0.8 nm and input power of 15 dBm, covered the distance up to 100 km. To show the good performance of the proposed system, its BER, and Q factor are shown. A sharp increase in BER occurs if data rate and distance increase up to 21 Gb/s and 100 km. The simulations are carried out using OptiSystem version 17.0 commercial optical system simulator

م.د نور الدين عباس خالد (5 بحث)

Palmprint recognition system using VR-LBP and KAZE features for better recognition accuracy
	2024	Bulletin of Electrical Engineering and Informatics
Harumanis Mango Classification and Grading System Based on Geometric Shape Extraction for Quality Assessment
	2024	Journal of Advanced Research in Applied Sciences and Engineering Technology
"ABSTRACT In agricultural research, a fruit's appearance, which affects its market value, is the first and most crucial sensory evaluation. Based on external criteria like characteristics of shape and size, they can be categorized and rated during the post-harvest management. However, the mango processing industry still faces significant challenges due to the largely manual post-harvest processing of mangos. Manual grading can be inconsistent, erroneous, and labor-intensive. To address this issue, researchers have explored the use of image processing and machine learning techniques to automate the grading and classification process. This paper implements a proposed system that uses fruit shape, uniformity, and size as feature parameters for evaluating Harumanis mango quality. This system was able to identify the irregularity of the mango shape and its estimated mass. A morphological analysis, median filter, and multilevel threshold-based image processing technique were created to assess the geometric shape of the mango image, including its length, width, and area. These attributes are utilized to assess the mass and categorize its size into four classifications: small (S), medium (M), large (L), and extra-large (XL). Fourier descriptors and shape parameters were employed to characterize the mango's morphology. Stepwise discriminant analysis identified variables that effectively"
A Proposed Approach for Object Detection and Recognition by Deep Learning Models Using Data Augmentation
	2024	Online and Biomedical Engineering
"Object detection and recognition play a crucial role in computer vision applications, ranging from security systems to autonomous vehicles. Deep learning algorithms have shown remarkable performance in these tasks, but they often require large, annotated datasets for training. However, collecting such datasets can be time-consuming and costly. Data augmentation techniques provide a solution to this problem by artificially expanding the training dataset. In this study, we propose a deep learning approach for object detection and recognition that leverages data augmentation techniques. We use deep convolutional neural networks (CNNs) as the underlying architecture, specifically focusing on popular models such as You Only Look Once version 3 (YOLOv3). By augmenting the training data with various trans-formations, such as rotation, scaling, and flipping, we can effectively increase the diversity and size of the dataset. Our approach not only improves the robustness and generalization of the models but also reduces the risk of overfitting. By training on augmented data, the models can learn to recognize objects from different viewpoints, scales, and orientations, leading to improved accuracy and performance. We conduct extensive experiments on benchmark datasets and evaluate the performance of our approach using standard metrics such as pre-cision, recall, and mean average precision (mAP). The experimental results demonstrate that our data augmentation-based deep learning approach achieves superior object detection and recognition accuracy compared to traditional training methods without data augmentation. We compare the average accuracy of the YOLOv3-SPP model with two other variants of the YOLOv3 algorithm: one with a feature extraction network consisting of 53 convolutional layers and the other with 13 convolutional layers. The average accuracy of the proposed model (YOLOv3-SPP) is reported as accuracy of 97%, F1-score of 96%, precision of 94%, and average Intersection over Union (IoU) of 78.04%."

م.م غادة عبدالمنعم موسى (0 بحث)

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م.د.مصعب علي حسن (4 بحث)

Detection of arabic sign language by machine learning techniques with PCA and LDA
	2024	Engineering and Technology Journal
"People need a communication channel and a way to communicate with a person or group. Deaf people communicate with others through sign language. The remarkable and rapid development in image and video recognition systems has made researchers use this development to solve many problems, including sign language for the deaf, and reduce their suffering in communicating with ordinary people. This work aims to use and apply machine learning technology to build an automatic recognition system for Arabic Sign Language (ArSL). In this work, images of ArSL characters were recognized using four classification techniques (Naïve Bayes (NB), Decision Trees (DTs), and Adaptive Boosting), and K-Nearest Neighbor (KNN)) with the Python library and using two feature extraction algorithms (PCA & LDA). Data pre-processing steps, including grayscale conversion, Gaussian blur, histogram equalization, and resizing, are applied to enhance the data's suitability for training and testing. The work was tested with five experiments chosen with multiple ratios for training and test data. The first training is 90%, the second training is 80% of the data, the third is 75%, the fourth is 70%, and the last is 60%. The work also played a good role in interpreting ArSL, and the accuracy of the work considers the KNN algorithm more accurate in prediction."
Enhancing communication: Deep learning for Arabic sign language translation
	2024	open engineering
"This study explores the field of sign language recognition through machine learning, focusing on the development and comparative evaluation of various algorithms designed to interpret sign language. With the prevalence of hearing impairment affecting millions globally, efficient sign language recognition systems are increasingly critical for enhancing communication for the deaf and hard-of-hearing community. We review several studies, showcasing algorithms with accuracies ranging from 63.5 to 99.6%. Building on these works, we introduce a novel algorithm that has been rigorously tested and has demonstrated a perfect accuracy of 99.7%. Our proposed algorithm utilizes a sophisticated convolutional neural network architecture that outperforms existing models. This work details the methodology of the proposed system, which includes preprocessing, feature extraction, and a multi-layered CNN approach. The remarkable performance of our algorithm sets a new benchmark in the field and suggests significant potential for real-world application in assistive technologies. We conclude by discussing the impact of these findings and propose directions for future research to further improve the accessibility and effectiveness of sign language recognition systems."
Recent Progress in Arabic Sign Language Recognition: Utilizing Convolutional Neural Networks (CNN)
	2024	BIO Web of Conferences
"The advancement of assistive communication technology for the deaf and hard-ofhearing community is an area of significant research interest. In this study, we present a Convolutional Neural Network (CNN) model tailored for the recognition of Arabic Sign Language (ArSL). Our model incorporates a meticulous preprocessing pipeline that transforms input images through grayscale conversion, Gaussian blur, histogram equalization, and resizing to standardize input data and enhance feature visibility. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are employed for feature extraction to retain critical discriminat ive information while reducing dimensionality. The proposed CNN architecture leverages a blend of one-dimensional convolutional layers, max pooling, Leaky ReLU activation functions, and Long Short-Term Memory (LSTM) layers to efficiently capture both spatial and temporal patterns within the data. Our experiments on two separate datasets—one consisting of images and the other of videos—demonstrate exceptional recognition rates of 99.7% and 99.9%, respectively. These results significantly surpass the performance of existing models referenced in the literature. This paper discusses the methodologies, architectural considerations, and the training approach of the proposed model, alongside a comparative analysis of its performance against previous studies. The research outcomes suggest that our model not only sets a new benchmark in sign language recognition but also offers a promising foundation for the development of real-time, assistive sign language translation tools. The potential applications of such technology could greatly enhance communication accessibility, fostering greater inclusion for individuals who rely on sign language as their primary mode of communication. Future work will aim to expand the model's capabilities to more diverse datasets and investigate its deployment in practical, everyday scenarios to bridge the communication gap for the deaf and hard of hearing community."

ا.د. خالد عواد حمود (1 بحث)

Design Wien Bridge Oscillator for VLF to VHF Using Practical Op – Amp
	2024	International Journal of Electrical and Electronics Research (IJEER) Volume 12, Issue 3
"Abstract An electronic oscillator is generally a major part of electrical, electronic and communications circuits and systems and it is can be divided into linear and nonlinear families. Wien Bridge is a type of RC phase shift oscillators mostly used for around 1MHz and its design adopts positive feedback technology. In this research, novel look the reasons for the inability to achieve high frequencies was understanding and the ambiguity was removing from the determinants of obtaining a high frequency signal for this type of oscillators, also, new results were obtained with a unique presentation. The output formula for the oscillation resonant frequency was deriving based on the oscillator’s theory. The design has beaning successfully achieved by using a practical high-performance op-amp and from the simulation results the frequency bandwidth was 50.7211 MHZ from,VLF (9.83 HZ ) to VHF (50.73 MHZ) and. These unique and interesting scientific findings were encouraging"

م.م نورا شهاب احمد (0 بحث)

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م.د. عمار محمد عبد اللطيف جاسم (2 بحث)

Sustainable Energy Progress via Integration of Thermal Energy Storage and Other Performance Enhancement Strategies in FPCs: A Synergistic Review
	2023	sustainability
Flat plate collectors (FPCs) are the leading solar thermal technology for low-medium range temperature applications. However, their expansion in developing countries is still lacking because of their poor thermal performance. Improving the thermal performance of flat plate collectors (FPCs) is a crucial concern addressed in this review This study comprehensively discussed the performance improvement methods of FPCs, such as design modification, reflectors, working fluid, and energy storage materials, by covering current issues and future recommendations. Design factors such as coating and glass cover thickness, thickness of absorber plate and material, air gap between the glass cover and absorber plate, and riser spacing, along with insulation materials, are examined for their impact on FPC performance. Absorber design changes with selective coatings for improving the heat transmission rate between the working fluid and absorber are critical for enhancing collectors’ thermal output. The nanofluids utilization improved FPC’s thermal performance in terms of energetic and exergetic outcomes in the 20–30% range. Moreover, adding a heat storage unit extends the operating hours and thermal output fluctuations of FPCs. Research suggests that employing turbulators and nanofluids as heat transfer fluids are particularly effective for enhancing heat transfer in FPCs. This comprehensive review serves as a critical tool for evaluating and comparing various heat transfer augmentation techniques, aiding in the selection of the most suitable option.
Fins-nanoparticle combination for phase change material enhancement in a triplex tube heat exchanger: A numerical approach to thermal sustainability
	2024	ICHMT
Many phase change materials exhibit low thermal conductivity, leading to incomplete melting and solidification processes. To address this issue, researchers have numerically explored the integration of alumina nanoparticles (Al ) with paraffin (RT82), a phase change material with a solidification temperature of 65 ◦ C, in a triplextube heat exchanger. The phase change material model with internal longitudinal fins employed the bothsides freezing technique and was conducted using Ansys Fluent software, employing the enthalpy-porosity method within a finite-volume framework to model the phase change material behavior during both melting and solidification phases. This methodology aims to significantly improve the thermal performance of thermal energy storage systems by enhancing heat transfer efficiency within the phase change material (PCM), thereby ensuring more effective utilization of stored thermal energy. The numerical findings show that the pure PCM completely solidified in 780 min. By dispersing 1 %, 4 %, 7 %, and 10 % of Al 2 O 3 in the PCM, thermal conductivity improved by 3 %, 12.5 %, 22.5 %, and 32.5 %, respectively. Additionally, the inclusion of nano-PCM reduced the solidification time. This research also compares the overall energy release in two different situations: PCM with and without nanoparticles. The computer-generated simulation results closely correlated with the practical experimentation results

ا.م.د. عبد الوهاب محمد عبد الله جاسم (2 بحث)

Fatigue life estimation under high temperature and variable loading of AA7001-T6 usting shot peening
	2024	Tikrit journal of engineering sciences
"In this study, the fatigue life of aluminum alloys (7001-T6) was predicted with shot peening at various temperatures. Surface treatment with shot peening steel balls is a mechanism for reducing damage. An experimental investigation was conducted to find the degree of fatigue accumulation for AA7001-T6 under rotational bending loading and stress ratio R = −1. The experiments were conducted at RT (25 ℃), 330 ℃, and SP + 330 ℃ temperatures. A modified damage stress model that considers damage at various load levels was recommended for forecasting the fatigue life under high temperatures. The model and experimental results were compared to determine the most damage (Miner’s rule). The experimental results of the fatigue life indicated that the increased testing temperature reduced the fatigue life. However, using shot peening at high temperatures increased the fatigue life by 8% when loading sequence L-H and 10% when loading sequence H-L. The results showed a satisfactory degree of safety for the present model. Nevertheless, Miner’s model featured two models: one for low– high loading and high-low loading. The results were proper for prolonging fatigue life."
Numerical Analysis of the Aluminium Alloy Structure of the Brackets based on Conceptualization Processes
	2024	Journal of Advanced Research in Applied Mechanics
"In this study, three conceptual designs of bracket constructions made of aluminum alloy underwent numerical investigation. To analyze the von Mises stresses, present throughout the entire structure, the Ansys program was employed in conjunction with the static structure tool. The selection criteria are determined by two primary elements. The first element is the performance of the design, represented by normal stresses and deformation resulting from the applied load. The second criterion is volume, dependent on the volume itself, represented by a certain density of metals. To select an appropriate design for the aluminum brackets, the procedure was carried out utilizing the Analytic Network Process (ANP) technique. Through the conceptualizing approach, it has been demonstrated that the second design is superior to the alternative."

م. د. باسم عبدالله محمد (2 بحث)

Electrical, Magnetic, And Mechanical Properties of Al7075-T6/Al2O3-T6 Composites Processed by Stir Casting Route
	2023	Journal of Engineering Science and Technology
"This study investigates the fabrication characterization ,electrical, magnetic,and mechanical properties of composites ,made from AA 7075-T6 and Al2O3 prepared by stir casting techniques . Three nano composite materials can be durable and strong and are used in engineering applications structures of aircraft, industrial equipment, cars,etc."
Electrical, Magnetic, and Mechanical Properties of AL7075-T6/AL2O3-T6 Composites Processed by Stir Casting Route
	2023	Journal of Engineering Science and Technology
This study investigates the fabrication ,characterization ,electrical,magnetic,and mechanical properties of composites made from AA7075-T6 and AL2O3 prepared by stir casting techniques.Three nanocomposite materials can be durable and strong and are used in engineering applications structures of aircraft, industrial equipment, car,etc.

أ.د.خنساء داود سلمان (5 بحث)

Effect of ZnO wt.% on microstructure and mechanical properties epoxy/ZnO nanocomposite
	2024	AIP Conference Proceedings
In this research, the influence of ZnO wt.% on the microstructure analysis and mechanical properties of epoxy was investigated. The nanocomposites consist of epoxy resin as a matrix combined with different weight ratios of ZnO (0, 1, 2, 3, 4, and 5wt.%) as a reinforcing material. Ultrasonication was used to disperse ZnO nanoparticles in the epoxy resin. The specimenssome of the nanocomposites manufactured by the casting route. The epoxy was carefully mixed with the additive ZnO nanoparticles in a sonication for 30 minutes before being put into silicon molds. Field Emission Scanning Electron Microscopy (FESEM), Fourier-Transform Infrared Radiation (FTIR), and X-ray diffraction spectra were used to investigate the structural and morphological properties of the preparing specimens and the distribution of ZnO nanoparticles into epoxy resin. Three types of mechanical tests (flexural test, hardness shore (D) and tensile test were conducted on the specimens conforms to ASTM specifications, at room temperature. The results of this work demonstrated that 5wt.% of ZnO nanoparticles had the best mechanical properties compared to net epoxy, except for young᾽s modulus, where the highest percentage was obtained at 3wt.% weight of ZnO nanoparticles, due to the agglomeration of ZnO nanoparticles in epoxy resin above 3wt.%.
Microstructure and mechanical properties of a hybrid epoxy/ZnO + Gr nanocomposites
	2024	AIP Conference Proceedings
This work aims to study the microstructure and mechanical properties of epoxy matrix incorporated with different amount of ZnO at (1wt.%, 2wt.%, 3wt.%, 4wt.% and 5wt.%) with constant amount of Gr at 1wt.%. Dispersion of ZnO and Gr in the epoxy resin was conducted by ultrasonication device. (Epoxy/ZnO+Gr) nanocomposites samples were prepared by casting route. Field Emission Scanning Electron Microscopy (FESEM), X-ray diffraction spectra (XRD) and Fourier Transform Infrared Radiation (FTIR) were used to describe the structural and morphological properties of the prepared the distribution and samples of nanomaterials into the epoxy resin. Mechanical tests (tensile, flexural and hardness shore (D)) were conducted according to ASTM standards. The results indicated that reinforcement at 5wt.% of ZnO nanoparticles and constant amount of Gr at 1wt.% increases comparing pure epoxy and nanocomposites’ mechanical propertie. While the flexural strength decreased at 5 wt.%, this is due to agglomeration of the additives Using nanoparticles in epoxy resin 4 wt.%.
Improving the microstructure and mechanical properties of the nanocomposite’s material (Al + ZnO)
	2024	AIP Conference Proceeedings
The aim of this study is to investigate the mechanical characteristics and microstructural characteristics of aluminum matrix with varying concentrations of ZnO (3, 6, 9, 12, 15) wt.%. The Al/ZnO nanocomposite specimens were prepared by powdered metalworking. Due to their high strength, wear resistance, and low weight, aluminum matrix nanocomposites (AMNCs) are crucial alloys for various applications, including automotive, electronics, and aerospace. The specimens used in this study were subjected to a variety of tests, such as X-Ray Diffraction (XRD) analysis and Field Emission Scanning Electron Microscopy (FESEM), to determine the microstructure and phases of the nanocomposites. Additionally, mechanical tests such as compressive, wear, and micro-hardness tests were performed. By using FESEM and XRD analysis, the findings of this study demonstrate that ZnO nanoparticles have been uniformly dispersed in the Al matrix. Although mechanical testing indicate that increasing compressive strength at 15%, the highest microhardness at 15wt.% and also improving wear rate. The aims of this work is evaluation the mechanical properties of nanocomposites materials when they mixing the materials is ZnO and AL matrix. Aluminum matrix composites have shown a wide field of industrial applications. Many advantages offered by aluminum matrix composites involve economic (low energy and low cost), environment (low airbome fallouts) and performance (improving rate of productions). However, the applications of AMCs depend on the characteristics of reinforcement material and the technique of manufacturing. Aluminum matrix composites reinforced by oxides such as Al2O3, carbides such as TiC or B4C, Nitrides such as TiN have been used for thermally applications such as aerospace and rotating bldes of helicopters. Also, used for automotive, cam shafts and arm of automobiles. Aluminum matrix composites used in sporting which involves golf clubs, frames of bicycle and skating shoes. The increment of ceramic concentration in aluminum matrix made it suitable in electrical applications such as microprocessors in electronics [1].

م.م مصطفى جاسم رستم (1 بحث)

Zeta Potential Optimization of Nano Chitason /SrCNgO Suspensior for Electrophoretic Deposition Using Taguchi Method
	2023	مجلة ديالى للعلوم الهندسية
"The stability of Electro Phoretic Deposition (EPD) suspensions containing nanoparticle relies oa the impact of Zeta Poiential (ZP 9. This property enure that the or nanoparticles have a consistent and stable surface charge, resulting in a uniform and have a stable coating. This research has been conducted as an experimental study and used the Taguchi method to design experiment optimization of the Zeta potential values, which were obtained by preparing nine suspensions. The stud aimed to determine the optima ZP value for the EPD suspension create with three materials mixed- nanochitason Chitason/SrC1MgO, and a constant value of hydroxyapatite (HA) with consideratior of the pH effect. After conducting an analysis, it was found that the suspension's Zeta Potential is negatively charged beiow a pHi value of 8.22. Between 8.22 and 9.7. the ZP has a positive charge, The suspension's isoelectric point (IEP) is 8.22, with a high a corelation coeficieint indicating the model's reliabity in predicting responses Th the analysis showed that SICl: has the most significant impact on the suspension's ZE followed by Chitason (CH), with Me0 having the least impact. The resulis demonstrate the effectiveness of this analysis in determining the optimum ZP value for various solutions purepured ftom diferent biomaterdied partidle"

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ا. م. د. نصير قاسم حمودي عباس الباجةجي (2 بحث)

The Impact of Engineering Anxiety on Students: A Comprehensive Study In the fields of SPORT, ENGINEERING AND ECONOMICS
	2023	REVISTA IBEROAMERICANA DE PSICOLOGÍA DEL EJERCICIO Y EL DEPORTE
Socio-Technical Systems (STS) represent a complex interplay between engineering and economics, encompassing the interaction of technological components with social, organizational, and economic factors. This research aims to investigate the dynamics and implications of STS in the context of engineering and economics. By employing an interdisciplinary approach, it seeks to understand the reciprocal influences between engineering and economics within STS and explore the challenges and opportunities arising from this nexus. The research will draw on quantitative and qualitative methods, including data analysis, case studies, and stakeholder interviews, to provide a comprehensive understanding of the role of STS in driving socio-economic outcomes. The findings will inform decision-making processes, policy development, and future research directions in the fields of engineering and economics.
THE IMPACT OF ENGINEERING ANXIETY ON SPORT, ECONOMICS, AND TEACHING METHODS
	2023	REVISTA IBEROAMERICANA DE PSICOLOGÍA DEL EJERCICIO Y EL DEPORTE
Engineering education can be demanding and challenging, leading to increased levels of anxiety among students. This research aims to explore the prevalence, causes, and consequences of engineering anxiety on students. Through a mixed-methods approach, including surveys, interviews, and psychological assessments, this study investigates the factors contributing to engineering anxiety, such as academic pressure, performance expectations, workload, and imposter syndrome. It examines the psychological, academic, and social implications of anxiety on students' well-being, academic performance, and career aspirations. The findings of this research will provide insights into the nature and extent of engineering anxiety, enabling educational institutions and support services to develop effective interventions and strategies to mitigate anxiety and promote students' overall success and well-being.

م.م عبدالعليم فاضل سلمان (2 بحث)

Numerical analysis of a piled embankment under earthquake loading
	2021	AI0
Abstract. Earthquakes produce massive damage in the road embankment especially if the embankment based on soft subsoil, and this damage which in turn causes great economic losses for maintenance and rehabilitation. Last decades Iraq and the surrounding region faced many earthquakes where the most powerful earthquake happened in 2017 near the Iraq-Iran border specifically at “Halabjah” city. Thus engineers have been focusing on their road embankment design to sustain such earthquakes, by using piles as a foundation for the superstructure. In this research a numerical study for the piled embankment subjected to seismic excitation using three dimensional PLAXIS finite element program]. The effect of changing the pile supporting condition and the pile diameter on the embankment stability under “Halabjah” earthquake is investigated. The results shows that using piles reduces the settlement of the embankment’s crest by about 77% if the supporting condition of the piles was floating and in the case of the end bearing and anchored piles the reduction in the crest’s settlement were 88% and 94% respectively. Key words: Piled-Embankment, Earthquake, soft soil, finite element, stability.
Design, simulation and analysis of induction furnace coil cooling system using FEM
	2023	AIP advances
يتضمن البحث تحليل ومحاكاة منظومة تبريد خاصة بالافران الحثية ذات القدرات العالية باستخدام برنامج الانسز

م.م زهراء محمد جعفر (1 بحث)

Extraction of prodigesin from aqueas two phase system
	2021	ieee
استلاخص مادة برودوجازين الدوائيه بااستخدام محلول ثانئي طور

م.م انور عدنان ماشاءالله (1 بحث)

Numerical analysis of a piled embankment under earthquake loading
	2021	AIP
Abstract. Earthquakes produce massive damage in the road embankment especially if the embankment based on soft subsoil, and this damage which in turn causes great economic losses for maintenance and rehabilitation. Last decades Iraq and the surrounding region faced many earthquakes where the most powerful earthquake happened in 2017 near the Iraq-Iran border specifically at “Halabjah” city. Thus engineers have been focusing on their road embankment design to sustain such earthquakes, by using piles as a foundation for the superstructure. In this research a numerical study for the piled embankment subjected to seismic excitation using three dimensional PLAXIS finite element program]. The effect of changing the pile supporting condition and the pile diameter on the embankment stability under “Halabjah” earthquake is investigated. The results shows that using piles reduces the settlement of the embankment’s crest by about 77% if the supporting condition of the piles was floating and in the case of the end bearing and anchored piles the reduction in the crest’s settlement were 88% and 94% respectively.

م. د جمهور محمود اسماعيل (1 بحث)

Design and Simulation DES Algorithm of Encryption for Information Security
	2018	American Journal of Engineering Research (AJER)
"ABSTRACT :The demand for protection increases, if the confidentiality of the information is of very high value. Security is very essential to avoid the unauthorized disclosure or alteration of the information. Due to the great change in technologies nowadays, a number of multimedia data is being generated and transmitted, leaving our own data vulnerable to be edited, modified and duplicated. Digital documents are therefore being faced by innumerable threats as they are very easy to copy and distribute. Cryptography is an art of secret writing, which authenticates data and important messages as well as protects the systems from valid attacks. One of the best existing security algorithms to provide data security is DATA Encryption Standard (DES). It comprises of encryption and decryption process each associated with a key which is supposed to be kept secret. In this paper the software C++ used for the purpose of synthesis and simulation of DES algorithm. The data encryption standard is also known as DES. DES has been the most extensively used encryption algorithm standard in recent times. Encryption and decryption comprise of cryptography. Cryptography terminology is used in the data encryption standard along with standard algorithm to hide the original text. DES applies the cipher algorithm to each data block. Data encryption is being used to hide the true meaning of data so that it is very hard to attack or crack."

م. د. علي محسن عبدالساده الابراهيمي (9 بحث)

Modeling 3-Degree of Freedom Robotics Manipulator with PID and Sliding Mode
	2022	AIP Conference Proceedings
"Abstract. In this paper, 3-Degree of Freedom (DOF) serial links robot manipulator is modeled and controlled using two different types of control techniques. The trajectory and position control is performed by classical PID controller and Sliding Mode Controller (SMC). The controller aim is to keep the rotate angles of all three links at the desired angles and remove the end effector oscillation. The modeling and the controlling are implemented by MATLAB/ Simulink. The comparison between the dynamic response for 3-DOF serial robotics arms under classical PID controller and Sliding Mode Controller is presented and the results are better than results in PID controller. Keywords: 3-DOF, Robot Arm, PID, Sliding Mode Controller "
Fuzzy Techniques in Concrete Powder Mix Designing
	2023	AIP Conference Proceedings
"Abstract: Water cement ratio It is a method consisting of more than one attempt in order to obtain a product that contains a mixture of ideal components involved in the production and formation of high-performance and cohesion concrete. There are many methods for making and designing concrete mixtures in contemporary studies and researches that are approved at the present time, but one of the most important, well-known and most widely used is the methodologies derived from the method of the three equations. Compressive strength is one of the most important characteristics of concrete, as it determines the concrete class. The concrete block represents the expected compressive strength is necessary for the use of concrete structures. primary feature of its durability and safety. Deep learning has recently received a lot of Concentration, the future of modern prospects for this technology is brighter. Machine learning algorithms have advanced to the point that they can recognize patterns that are difficult for humans to recognize. This has sparked interest in data mining on enormous datasets. We want to use Recent developments and achievements in machine learning approaches to formulation of concrete mixes creation in our study. In order to enhance the possibility of the ideal structure designed for an artificial neural network, an integrated database of concrete specifications and features with corresponding destructive laboratory tests was created. The architecture of an artificial neural network has been translated In a mathematical equation consisting of employed in real-world applications”. Keywords: Deep learning, artificial neural network, Fuzzy, concrete mix, concrete compressive strength, uncertainty. "
Motion Tracking for a 3-DOF Robotics System by Using Particles Swarm Optimization
	2023	AIP Conference Proceedings
"Abstract: Robotics is among the much-touted treatment and therapy solutions in modern dentistry. A unique Particle Swarm Optimization PSO is utilized to manage the needle tip location and direction as a function of the knots along the path between the end-effector segments in a dentistry robotics navigation system recently suggested. The innovative ""Numeric Alphabet Flow"" (NAF) method may control any point-to-point surgical motions for a three-link robotic guiding system. The new NAF approach creates a brand-new form known as the NAF-PSO methodology by using flowing values and alphanumeric characters in the fuzzy rules and employing particle swarm optimization techniques. Within that paper, we use the novel NAF-PSO to improve robotic tracking performance. This study introduces a unique route planner that specifies the suggested NAF-PSO function as minimizing space and traveling time while not reaching a maximal preset force and avoiding obstacles. Keywords: Medical Robot, motion planning, Obstacle avoiding, Needle steering. "

م.م. دينا ساطع اكرم (1 بحث)

Design IMI Electronic Elements Based On Nano Plasmonic Waveguides
	2024	3rd International Conference on Engineering and Science to Achieve the Sustainable Development Goals,
A design of plasmonic AND, OR, and XOR gates were discussed and simulated using Insulator Metal Insulator (IMI) structure. The Finite-Element-Method (FEM) with COMSOL software was suggested for implementing the logic gate structure. Square resonators with input, output, and control stripes were used to realize the constrictive and destructive interference when the transmission threshold (Tthreshold) is chosen to be 0.5 W. The gates footprint is 300 × 350 nm at 1550 nm resonant wavelength. The square resonator, one input one output system offers a high selectivity when the Quality factor (Q-factor) is 38.5 and the Full-Width to Half-Maximum (FWHM) is 33. Modulation-Depth (MD), Contrast-Ratio (CR), and Insertion-Loss (IL) suggested to evaluate, and study the three gates. For AND gate the CR, MD, and IL have 12.9, 97.8, and 2.4, then for OR gate the three parameters have 8.7, 94.9, and -1.7, respectively. Finally, for XOR gate the CR has 8.7, the IM has 86.7, and the IL has -1.7.

م م حمودي قاسم حمودي (2 بحث)

A Reliability Study of Photovoltaics Energy Systems in DC Microgrid
	2023	BAUC14 Bilad Alrafidain Journal for Engineering Science and Technology
Due to removing the mechanical brushes in BLDC motors, BLDC motors are widely used in many industrial applications. Therefore, they are maintenance-free and their control is easy to design, especially for high-speed applications. For example, eco-friendly vacuum cleaners prevent atopic dermatitis, allergic rhinitis, and asthma. Other applications are Micro Gas turbines or compressors with small impellers due to miniaturization, BLDC motors must rotate at very high speeds to maintain the compressor's compression ratio. Generally, airfoil bearings should be used instead of ball bearings because of the friction in high-speed motors. Unfortunately, the characteristics of airfoil bearings depend on rotational speed. In this work, a BLDC motor with an airfoil bearing is controlled by a PID controller, this work analyzed the BLDC SYSTEM to determine the PID coefficient using the feedback method. The proposed controller Fuzzy Logic is used for adaptive control. In addition, the controller of BLDC motors combines auto-tuning and self-tuning technology. The results demonstrate that the proposed method gives efficient control by reducing the settling time and maximum peek overshot. The designed controller for the airfoil-bearing BLDC motor has a good performance
Designing Fuzzy Logic Control for the BLDC Motor Based on Airfoil Bearing
	2024	Vol. 3 No. 2 (2024): Bilad Alrafidain Journal for Engineering Science and Technology (BAJEST)
Due to removing the mechanical brushes in BLDC motors, BLDC motors are widely used in many industrial applications. Therefore, they are maintenance-free and their control is easy to design, especially for high-speed applications. For example, eco-friendly vacuum cleaners prevent atopic dermatitis, allergic rhinitis, and asthma. Other applications are Micro Gas turbines or compressors with small impellers due to miniaturization, BLDC motors must rotate at very high speeds to maintain the compressor's compression ratio. Generally, airfoil bearings should be used instead of ball bearings because of the friction in high-speed motors. Unfortunately, the characteristics of airfoil bearings depend on rotational speed. In this work, a BLDC motor with an airfoil bearing is controlled by a PID controller, this work analyzed the BLDC SYSTEM to determine the PID coefficient using the feedback method. The proposed controller Fuzzy Logic is used for adaptive control. In addition, the controller of BLDC motors combines auto-tuning and self-tuning technology. The results demonstrate that the proposed method gives efficient control by reducing the settling time and maximum peek overshot. The designed controller for the airfoil-bearing BLDC motor has a good performance.

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المهندس حيدر منصورخضير (0 بحث)

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م.م اوس الخزرجي (1 بحث)

Random forest for lung cancer analysis using Apache Mahout and Hadoop based on software defined networking
	2023	Indonesian Journal of Electrical Engineering and Computer Science
Random forest is a machine learning algorithm that mainly built as a classification method to make predictions based on decision trees. Many machine learning approaches used random forest to perform deep analysis on different cancer diseases to understand their complex characterstics and behaviour. However, due to massive and complex data generated from such diseases, it has become difficult to run random forest using single machine. Therefore, advanced tools are highly required to run random forest to analyse such massive data. In this paper, random forest algorithm using Apache Mahout and Hadoop based software defined networking (SDN) are used to conduct the prediction and analysis on large lung cancer datasets. Several experiments are conducted to evaluate the proposed system. Experiments are conducted using nine virtual nodes. Experiments show that the implementation of random forest algorithm using the proposed work outperforms its implementation in traditional environment with regard to the execution time. Comparison between the proposed system using Hadoop based SDN and Hadoop only is performed. Results show that random forest using Hadoop based SDN has less execution time than when using Hadoop only. Furthermore, experiments reveal that the performance of implemented system achieved more efficiency regarding execution time, accuracy and reliability.

م.د محمد احمد جياد (3 بحث)

Exploring adversarial deep learning forfusion in multi-color channel skin detectionapplications
	2024	Information Fusion
Deep learning, a robust framework for complex learning, outperforms previous machine learning approaches and finds widespread use. However, security vulnerabilities, especially in fusion in multi-color channel skin detection applications using adversarial machine learning (AML) and generative adversarial networks (GANs), lead to misclassifications. Researchers are actively exploring AML's and GANs' impact on misclassification, focusing on vulnerabilities in lighting conditions, skin-like patches in lesion segmentation, and insufficient data in facial emotion recognition. Yet, these areas only scratch the surface of potential AML vulnerabilities and GANs. To comprehensively address challenges, an in-depth investigation into AML and GANs components is crucial to uncover underlying reasons for misclassifying skin detection. This study addresses challenges of fusion in multi-color channel skin detection by creating a diverse dataset with 17M patches for enhanced feature fusion/training and meeting dataset criteria, investigating misclassifications using various deep learning models belonging to AML and GANs and color spaces (e.g., RGB, YCbCr, HSV, YUV), and exploring binary and multiclass scenarios. Notably, YCbCr outperformed RGB, achieving 98 % for binary skin classification, 84 % and 69 % for multiclass four and five-class scenarios. Binary classification for skin tones and their skin-like counterparts (e.g., black skin tone and black skin-like) yielded 97 %, 81 %, 60 %, and 51 % for black, brown, medium, and fair, respectively. Exploration of darker skin tones showed improved accuracy. Benchmarking with a CNN and RNN hybrid achieved 99 % accuracy, surpassing the initial 91 %, while SAE reached 97 %. The study explores implications of overlapping between skin and skin-tone recognition, offering insights for developing a generalized skin detector. The investigation demonstrates that improper color space selection can make lighting conditions exploitable in AML attacks and GANs, emphasizing the crucial role of color space choice in mitigating vulnerabilities.
Exploring the Industrial Metaverse: Empowering Meta-Operators with Industry 5.0 Principles and XR Technologies
	2024	International Journal on Informatics Visualization
The term "Metaverse" has recently gained significant attention. It refers to a concept aiming to immerse users in real-time 3D virtual worlds using XR devices like AR/MR glasses and VR headsets. When this idea is applied to industrial settings, it's termed the "Industrial Metaverse," where operators leverage cutting-edge technologies. These technologies align closely with those associated with Industry 4.0, evolving towards Industry 5.0 and prioritizing sustainable and human-centric industrial applications. The Industrial Metaverse stands to benefit from Industry 5.0 principles, emphasizing dynamic content and swift human-to-machine interactions. To facilitate these advancements, this article introduces the concept of the "Meta-Operator," essentially an industrial worker guided by Industry 5.0 principles, engaging with Industrial Metaverse applications and surroundings through advanced XR devices. It also delves into the key technologies supporting this concept: Industrial Metaverse components, the latest XR technologies, and Opportunistic Edge Computing (OEC) for interacting with surrounding IoT/IIoT devices. Furthermore, the paper explores strategies for developing the next generation of Industrial Metaverse applications based on Industry 5.0 principles, such as standardization efforts, integrating AR/MR devices with IoT/IIoT solutions, and advancing communication and software architectures. Emphasis is placed on fostering shared experiences and collaborative protocols. Lastly, the article presents a comprehensive list of potential Industry 5.0 applications for the Industrial Metaverse and an analysis of the main challenges and research directions. It offers a holistic perspective and practical guidance for developers and researchers venturing into Industrial Metaverse applications.
Navigating the metaverse: unraveling the impact of artificial intelligence—a comprehensive review and gap analysis
	2024	Artificial Intelligence Review

م.م. حسن ابراهيم خليل (0 بحث)

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أ.د.حسين جاسم محمد محمود العلكاوي (10 بحث)

Numerical Analysis of the Aluminum Alloy Structure of the Brackets based on Conceptualization Processes
	2023	Journal of advanced research in applied mechanics
Comparison between mechanical and fatigue characteristics of two aluminum matrices strengthened with TiO2 nanoparticles
		AIP Conference Proceedings
ELECTRICAL, MAGNETIC, AND MECHANICAL PROPERTIES OF AL 7075- T6/AL203-T6 COMPOSITES PROCESSED BY STIR CASTING ROUTE
		Journal of Engineering Science and Technology