Computer Engineering Commons^™

Survey: A Study On Image Encryption Using Dna In Bioinformatics, Rana M. Zaki, Zaed S. Mahdi, Matheel E. Abdulmunim

Journal of Soft Computing and Computer Applications

One area of study between computer science and biology is bioinformatics, which deals with methods for collecting, processing, storing, and evaluating biological data. Sequences of RiboNucleic Acid (RNA), DeoxyriboNucleic Acid (DNA), and proteins make up biological data, which has a wide range of uses in domains such as feature extraction, data segmentation, data security, and more. In cryptography, DNA sequences are used as data carriers, enhancing the unique properties of biomolecules. This approach involves using DNA sequences to enhance the security of confidential data that must be transmitted over networks or stored securely. Several DNA-based security techniques have been developed, …

New Feature Selection Using Principal Component Analysis, Zaid Mundher Radeef, Soukaena Hassan Hashem, Ekhlas Khalaf Gbashi

Journal of Soft Computing and Computer Applications

Dimensionality reduction techniques streamline machine learning by reducing data complexity, improving model accuracy, and cutting computational costs. They remove noise and irrelevant features, making models faster and more efficient. These techniques also enhance data visualization and interpretation by condensing data into manageable, insightful dimensions. Ultimately, dimensionality reduction leads to simpler, more interpretable models without sacrificing critical information, making it a cornerstone of efficient data analysis and machine learning applications. Theoretically, feature extraction tends to create new features that encapsulate more information by combining multiple existing features, resulting in more concentrated and informative features. In contrast, feature selection involves choosing a …

Development Of A Hybrid Methodology Of Deep Learning And Machine Learning For Lung Nodule Detection In Medical Computed Tomography Images, Zaed S. Mahdi, Rana M. Zaki, Alaa Kadhim Farhan, Negar Majma

Journal of Soft Computing and Computer Applications

Deep learning and machine learning play an important role in the medical field, helping doctors make accurate, fast and effective diagnosis. Despite the progress achieved in the use of modern technologies in detecting cancerous nodes, current studies still suffer from some challenges and limitations that must be addressed to obtain high efficiency in identifying cancerous nodes. These challenges include using image pre-processing, combining deep learning and machine learning techniques, and constantly adapting to clinical changes, in order to address this. A hybrid methodology has been proposed for detecting cancerous nodules in the lung in medical Computed Tomography (CT) images. It …

Enhancing Image Classification Using A Convolutional Neural Network Model, Zena M. Saadi, Ahmed T. Sadiq, Omar Z. Akif, Marwa M. Eid

Journal of Soft Computing and Computer Applications

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as …

Improved Rapidly-Exploring Random Tree Using Firefly Algorithm For Robot Path Planning, Dena Kadhim Muhsen, Firas Abdulrazzaq Raheem, Yuhanis Yusof, Ahmed T. Sadiq, Faiz Al Alawy

Journal of Soft Computing and Computer Applications

In robotics, efficient path planning makes robots work independently and move through changing environments over time. This study combines the Rapidly-exploring Random Tree (RRT) architecture with the Firefly Algorithm (FA) to make robot’s path-planning better. The proposed ERRT-FA, which stands for "Enhanced RRT with Firefly Algorithm", generates better routes using Firefly social habits. Plan routes using Firefly social habits can effectively aid in exploring configuration space. The role of the FA is to enhance the RRT algorithm by providing an optimized exploration of the search space, ultimately leading to optimizing the path found by the RRT algorithm and better paths …

Exploring Student Satisfaction In Learning With Podcast Applications: A Qualitative Study Based On Open-Ended Questions, Indah Permatasari, Peny Meliaty Hutabarat, Erni Adelina

Jurnal Vokasi Indonesia

This study aims to explore student satisfaction with the use of podcasts as a learning medium in the Non-News Radio Production course. A qualitative approach was used, with three open-ended questions posed to students: (1) What different experiences did you have when listening to the course material via podcast?(2) Did listening to the course material through podcasts help you focus on understanding the material? And why? And (3) provide your opinion on the Adapto podcast material shared during the Non-News Radio Production course in the 4th semester. The data obtained was thematically analyzed to identify the main emerging themes. The …

Real-Time Congestion Control And Load Optimization In Cloud-Manets Using Predictive Algorithms, Preeti Rani, Mohammed Hussien Falaah

NJF Intelligent Engineering Journal

Cloud-MANET environments require a system to balance load and control congestion. As a result of integrating real-time network metrics with predictive traffic algorithms, the proposed model optimizes the management of dynamic topologies, network bandwidth constraints, and fluctuating traffic loads. In addition to energy-aware multi-path routing, the framework incorporates adaptive congestion control mechanisms to ensure data transmission is efficient and stable. This algorithm provides higher packet delivery ratios, reduces end-to-end delays, and increases throughput over existing algorithms, according to the evaluation results. Hybrid Cloud-MANET systems can benefit from this approach by optimizing resource utilization and network performance.

A Practical Intrusion Detection Approach For Arp Spoofing And Mitm In Local Area Networks, Hiba Bazzi, Ali Nassar, Mustafa El Bizri, Ali M. Haidar Prof.

BAU Journal - Science and Technology

In modern network environments, the increasing sophistication of cyberattacks poses significant risks, particularly through Address Resolution Protocol (ARP) spoofing and Man-in-the-Middle (MITM) attacks, which exploit vulnerabilities in local area networks. Existing tools often focus on detection or protection at the client side, leaving network-wide detection and response largely unaddressed. This paper presents a novel intrusion detection tool specifically designed to identify ARP spoofing and MITM attacks in real-time within local area networks. The system leverages Python and Scapy for low-level packet analysis and Flask for an intuitive web-based dashboard. Key features include network monitoring, attack detection through ARP table comparisons, …

Online Learning Transition: An Analysis Of Proactive Institutional Assistance In Reducing Difficulties During The Covid-19 Pandemic, Mohammed Yahya Alghamdi

BAU Journal - Science and Technology

The COVID-19 pandemic caused major changes in the education system, with a shift to online learning, and experience has shown that transitioning from face-to-face instruction is difficult. This study involved 80 academic staff members from Al-Baha University in Saudi Arabia to learn about the benefits, limitations, and institutional support of online education in the setting of an epidemic. The study answers two primary questions: The first study question was, What difficulties did instructors face when they switched to online instruction? While the second research question was, How did institutional support influence the transition to online instruction? The study’s research methodology …

Cropsync: Ai-Powered Sustainable Crop Management, Ziad Doughan, Ibrahim Mneimneh, Zouheir Nakouzi, Noor Al Khaib, Samer Damaj, Jamal Chaaban, Hamza Mrad, Sari Itani

BAU Journal - Science and Technology

CropSync is a smart agriculture system that uses AI and IoT technologies to enable sustain- able crop management and precision farming. The system aims to address the challenges faced by the agriculture sector, such as increasing food production to meet global population demands while minimizing environmental impact. CropSync integrates sensors, cameras, and cloud-based analytics to provide farmers with real-time insights and recommendations for optimizing crop cul- tivation. The system upholds engineering professional and ethical standards, considering broader social, environmental, and economic implications. From a social perspective, CropSync improves food security and enhances farmers’ livelihoods through increased productivity and efficient re- …

Quantitative Analysis Of Machine Learning Model Performance And The Need To Consider Explainability, Vishnu S. Pendyala

Open Educational Resources

This presentation, titled "Quantitative analysis of Machine Learning model performance and the need to consider explainability," delves into various metrics used for evaluating machine learning models. It thoroughly examines fundamental classification metrics like accuracy, precision, recall, and F-score, while also discussing more advanced measures such as the Kappa Statistic and Matthews Correlation Coefficient (MCC), particularly highlighting their relevance in scenarios with imbalanced datasets. The presentation underscores the importance of model accuracy in real-world applications and briefly introduces regression metrics like R-squared and F-statistic. Additionally, it addresses challenges related to data imbalance and fairness in ML models, stressing the critical need …

End-To-End Autonomous Quadcopter Using Reinforcement Learning, Mohamed Marwan Chawa

Theses and Dissertations

This thesis investigates the potential of Reinforcement Learning (RL) for achieving robust and adaptable quadcopter control, focusing on trajectory and attitude stabilization. We compare state-of-the-art RL algorithms, specifically Proximal Policy Optimization (PPO), against traditional Proportional-Integral-Derivative (PID) controllers across three tasks: hovering, slow trajectory following, and fast trajectory following. To enhance realism, we employ a modified PyFlyt simulation environment with a high-fidelity Crazyflie 2.x model, accounting for motor dynamics, noise, wind disturbances, and aerodynamic drag.

The challenge of operating a quadcopter can be divided into two distinct parts: planning a flight path and actually following that path. Our focus is on …

Simulation Of Cascade Failure In Urban Rail Transit Hypernetworks Based On Hypergraph Theory, Zijin Han, Mingjun Qian, Xixian Wang, Kaiyue Zhang

Journal of System Simulation

Abstract: In order to enhance the resilience of urban rail transit networks to ensure stable operations and passenger safety in the face of emergencies, hypergraph theory is introduced to construct a hypergraph based urban rail transit hypernetwork model, and a nonlinear load-capacity cascading failure model based on passenger flow weighting is established. In response to the passenger evacuation process at actual transportation network stations, a load redistribution mechanism is proposed, taking into consideration both the network level and the importance of passenger flow. To address scenarios where stations in actual traffic networks can still accommodate loads during shutdowns, a node …

A Fast Federated Learning-Based Crypto-Aggregation Scheme And Its Simulation Analysis, Boshen Lü, Xiao Song

Journal of System Simulation

Abstract: To solve the problem of increased computation and communication costs caused by using homomorphic encryption (HE) to protect all gradients in traditional cryptographic aggregation (cryptoaggregation) schemes, a fast crypto-aggregation scheme called RandomCrypt was proposed. RandomCrypt performed clipping and quantization to fix the range of gradient values and then added two types of noise on the gradient for encryption and differential privacy (DP) protection. It conducted HE on noise keys to revise the precision loss caused by DP protection. RandomCrypt was implemented based on a FATE framework, and a hacking simulation experiment was conducted. The results show that the proposed …

Critical Node Identification Method For Unmanned Aerial Vehicle Cluster Considering Localized Features, Chenglong Shi, Xiang Hua, Dong Wang, Jinjin Zhang, Tianqi Jiang, Yuanzhang Dang

Journal of System Simulation

Abstract: Aiming at the problem that the UAV cluster critical node identification methods focus on the global network and ignore the correlation between nodes and their local features, a critical nodes identification method for unmanned aerial vehicle cluster considering local features is proposed. An unmanned aerial vehicle cluster network model is constructed based on complex network theory. The Laplacian energy is introduced to evaluate the importance of node within two hops, and information entropy is combined to evaluate the importance of node in a specific motif to comprehensive identify the critical nodes. Simulation results demonstrate that this method identifies critical …

Optimization Of Urban Agglomeration Transportation Network Evacuation Paths, Bowei He, Chengbing Li, Shida Nie, Jialin Wang

Journal of System Simulation

Abstract: Given the complexity of the internal transportation network structure within urban agglomerations and the presence of numerous alternative routes, this paper proposes an enhanced ant colony algorithm to address the evacuation path problem of urban agglomeration transportation networks. A comprehensive urban agglomeration transportation network model is constructed, in which the issue of virtual transfer edges within the urban scope is considered and a weighting function is constructed taking into account the travelling time cost and the transferring time cost. Optimizations are applied to the ant colony algorithm, constructing an adaptive adjustment of state transitions and an information pheromone update …

A Threat Assessment Method In Uncertain Dynamic Environments, Mei Yang, Bingkun Wang, Zhongjie Zhang, Yan Zeng, Jian Huang

Journal of System Simulation

Abstract: A threat assessment method based on priori information and dynamic observation results is studied for the existence of dynamic uncertainty in complex war systems. The data mining is applied to obtain prior knowledge on the battlefield situation and construct an equipment-related confidence matrix. The sensor model is constructed to dynamically update the number of blue-side entities under the current situation by using the Bayesian method and considering both intelligence and observation results. The threat evaluation indicators and their weights are determined, and the TOPSIS method is used to finish the threat assessment. This method can well describe the complex …

Research On Adaptive Scheduling Of Single-Arm Cluster Tools For Throughput Ratio Of Multiple Wafer Types With Concurrent Processing, Chunrong Pan, Yu Cui, Wenqing Xiong, Hao Zhou, Jiliang Luo

Journal of System Simulation

Abstract: Concurrent processing makes the wafer fabrication process prone to deadlocks and completion node ambiguity. A Petri net model is established to describe the system operation process by taking for the single-arm cluster tools for fully parallel processing of two wafer types as the research object, and a control strategy is developed to avoid the system deadlock. Based on the Petri net model, the temporal properties of the system is analyzed based on earliest starting strategy, and the action cycle sequence of robot is determined during the monitoring cycle for different scenarios of lot switching in a single production monitoring …

Research On Latent Space-Based Anime Face Style Transfer And Editing Techniques, Haixin Deng, Fengquan Zhang, Nan Wang, Wancai Zhang, Jierui Lei

Journal of System Simulation

Abstract: To address issues such as image distortion and style uniformity in existing anime style transfer networks within the field of image simulation, we propose the TGFE-TrebleStyleGAN (textguided facial editing with TrebleStyleGAN) for anime facial style transfer and editing. This framework leverages vector guidance within the latent space to generate facial imagery and incorporates a detail control module and a feature control module to constrain the aesthetic attributes of the generated images. The images generated by the transfer network serve as style control signals and constraints for fine-grained segmentation. Text-to-image generation technology captures correlations between styletransferred images and semantic information. …

Research On Digital Twin Simulation Method Of Industrial Robot Integrated With Reinforcement Learning, Tianyue Miao, Lu Wang, Jiaxiao He, Nenggang Xie

Journal of System Simulation

Abstract: In response to the lack of comprehensive functionality and limited application scenarios in the current field of industrial robot digital twin systems, which results in low versatility, a method for constructing a digital twin system for industrial robots with high versatility is proposed. A four-dimensional system architecture for the digital twin is designed, and the components and functions of the four-dimensional system are analyzed, based on the system level planning of the four-dimensional system, the concept of integrating reinforcement learning into the virtual replacement of real concept is defined. By constructing a multi-attribute virtual model and using TCP communication …

Research On Multi-Objective Gait Planning Of Biped Robot Based On Virtual Prototype, Yankai Zhang, Xuesong Wang, Yubin Jin, Dongsheng Zhang

Journal of System Simulation

Abstract: A multi-objective gait optimization method based on virtual prototype is proposed to address the difficulty of balancing personalisation and performance in gait planning for bipedal robots. A scale prototype of a planar underactuated biped robot is created according to the body structure of Chinese people, and an identification approach is used to determine the robot's exact inertial parameters. A virtual prototype of the robot is created, and three optimization goals—speed, energy use, and stability are developed. Using the enhanced NSGA-II algorithm, the Pareto optimal solution set for the robot multi-objective gait planning issue is produced. Numerous gaits that conform …

Capacity Of Self Compact Concrete Walls Using Attapulgite As A Partial Replacement Of Cement Under One Way And Two Way Action Restriction, Wissam Kadhim Alsaraj, Luma Abdul Ghani Zghair, Akhlas Hashem Mohammed

Al-Esraa University College Journal for Engineering Sciences

This investigation about the structural performance of sustainable self-compact concrete walls exposed to eccentric axial regularly dispersed loading, including the effect of aspect ratio (AR) and slenderness ratio (λ) by one-way and two-way action. The experimental program includes testing ten wall panels, the eccentricity of the loading system equivalent to one-sixth of depth. These wall panels are separated into four groups, each one consisting of three specimens. first and second groups clarify the aspect ratio (H/L) effect. The results indicated for decreasing AR from (0.75 to 0.625), (0.625 to 0.5), and (0.75 to 0.5), the increase of final load is …

Exploring The Benefits Of Feature Selection Based On Bat Algorithm And Deep Learning In Brain Cancer Diagnosis, Noor Fawzi Shafiq

Al-Esraa University College Journal for Engineering Sciences

Brain cancer is considered one of the most dangerous types that must be treated as soon as possible. Therefore, it is necessary to detect brain cancer in its early stages to enhance the diagnosis of the condition. This study proposes to combine the bat algorithm (BA) with deep learning methods to identify and classify brain tumors in medical images accurately.

In this paper, the bat algorithm was used to select distinctive features from the input brain images. The Bat Algorithm (BA) is a metaheuristic optimization algorithm that mimics the echolocation behavior of bats. It efficiently explores the feature space to …

Unveiling The Hidden Threat: How Wireless Networks Fuel Serious Cyber Attacks, Ibtesam Jomaa Hawi

Al-Esraa University College Journal for Engineering Sciences

The spread of wireless networks has led to an increase in serious cyber attacks due to their weak architecture. This article focuses on reevaluating cybersecurity in wireless network technology by integrating statistical information detection methods and artificial intelligence (AI) algorithms. To construct a wireless networking scenario that accurately reflects real-life conditions, we created a data fabrication that included four pre-existing anomalies as well as four newly introduced anomalies. The synthetic dataset created from these generation processes contains 20 thousand distinguishable values, which are later divided into training and validation sets. Using the strategy described before, we began to analyze the …

A Study On Improving The Accuracy And Effectiveness Of Similarity Detection Processes In Text Files Using Nlp Techniques, Noor Abdulmuttaleb Jaafar

Al-Esraa University College Journal for Engineering Sciences

The rapid expansion of the Internet has revolutionized access to information, especially in the area of unstructured data, most of which consists of textual content. While instant access to information brings many advantages, it has also given rise to a prevalent problem – plagiarism. Copying and reusing materials without proper permission poses a significant threat to academic integrity and integrity. Rates of plagiarism, especially in academic and scientific publications, have risen with the advent of the Internet, reaching alarming levels, such as 60% in student projects. This study examines the proposed model that includes computation of similarity using cosine coefficients, …

Intersection Braking Guidance For Trams Based On Lineside Signs, Wencong Tong, Jing Teng, Junxian Li, Xing Yao, Zhongjie Zhang

Journal of System Simulation

Abstract: Trams need to brake frequently due to signal control and safety speed limits at intersections. Due to the inaccuracy of distance judgment, tram drivers tend to reserve extra braking distance at intersections, resulting in lower braking coefficients and a decrease in speed. An intersection braking guidance method using lineside signs is proposed for trams to reduce braking distance redundancy and improve running speed. Drivers are guided to brake with the shortest possible distance by marking the initial braking position and speed of trams with fixed lineside signs. A tram driving simulation system was developed based on a vehicle dynamics …

A Clustering-Based Location Allocation Method For Delivery Sites Under Epidemic Situations, Yaqiong Zhou, Junqi Chen, Weishi Li, Sihang Qiu, Rusheng Ju

Journal of System Simulation

Abstract: To address the poor performance of commonly used intelligent optimization algorithms in solving location problems—specifically regarding effectiveness, efficiency, and stability—this study proposes a novel location allocation method for the delivery sites to deliver daily necessities during epidemic quarantines. After establishing the optimization objectives and constraints, we developed a relevant mathematical model based on the collected data and utilized traditional intelligent optimization algorithms to obtain Pareto optimal solutions. Building on the characteristics of these Pareto front solutions, we introduced an improved clustering algorithm and conducted simulation experiments using data from Changchun City. The results demonstrate that the proposed algorithm outperforms …

Research On Verification Method Of Motor Startups In Nuclear Power Plants Based On Topology Recognition, Baozhu Li, Weijie Dong, Chao Chen

Journal of System Simulation

Abstract: There are many motors in operation or on standby in nuclear power plants, and the startup of group motors will have a great impact on the voltage of the emergency bus. At present, there is no special or inexpensive software to solve this problem, and the experience of engineers is not accurate enough. Therefore, this paper developed a method and system for the startup calculation of group motors in nuclear power plants and proposed an automatic generation method of circuit topology in nuclear power plants. Each component in the topology was given its unique number, and the component class …

Modeling And Integration Method Of Sysml Model For Complex Business Scenarios, Bing Yu, Baoran An, Shicao Zhao

Journal of System Simulation

Abstract: The development process of complex equipment involves multi-stage business processes, multi-level product architecture, and multi-disciplinary physical processes. The relationship between its system model and various disciplinary models is extremely complicated. In the modeling and integration process, extensive customized development is needed to realize model integration and interoperability in different business scenarios. Meanwhile, the differences in modeling and interaction between different modeling tools make it difficult to support the consistent representation of models in complex scenarios. To improve the efficiency of system modeling and integration in complex business scenarios, a system modeling and integration method was proposed. This method took …

Algorithm And Semi-Physical System Simulation For Command Intent Recognition Of Uav In Low-Resource Environment, Hongfu Liu, Yajing Fu, Wanpeng Zhang, Hu Zhang

Journal of System Simulation

Abstract: When a communication network is partially disabled or disrupted, an UAV is plunged into a "low-resource environment" and must rely on local hardware resources. This situation imposes constraints on computing power, storage capacity, and energy availability. To address the need for command intent recognition in such environments, a semi-physical simulation system for UAV in emergency rescue operations has been designed and implemented. Based on the low resource airborne hardware in the loop, the system simulates UAV command intention recognition and mission planning through GIS+BIM 3D environment modeling task scenarios. A new lightweight algorithm for intent recognition has been proposed, …