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Articles 901 - 930 of 25595

Full-Text Articles in Computer Engineering

Research On Constrained Programming Of Manipulator Using Rrt* Algorithm And Ellipse Prior, Zhen Yang, Li Su, Zhiyu Cheng Oct 2025

Research On Constrained Programming Of Manipulator Using Rrt* Algorithm And Ellipse Prior, Zhen Yang, Li Su, Zhiyu Cheng

Journal of System Simulation

Abstract: There are problems in the traditional RRT* algorithm using a uniform sampling strategy applied in constrained programming problems, such as inaccurate turning guidance of sampling points and unnecessary node cost comparisons, which lead to an increase in additional time costs. To address these issues, an improved RRT* algorithm was proposed. This algorithm leveraged a heuristic function cost of the projected sampling points to make an ellipse prior judgment on the sampling points. Based on the ellipse prior, the sampling points were judged to determine whether they could optimize the path and shorten the programming time. The geodesics were used …

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Robust Identification Of Dual-Rate Sampled Nonlinear Systems Based On Salr Network, Wenbin Jiang, Yuqing Cao, Li Xie, Huizhong Yang Oct 2025

Robust Identification Of Dual-Rate Sampled Nonlinear Systems Based On Salr Network, Wenbin Jiang, Yuqing Cao, Li Xie, Huizhong Yang

Journal of System Simulation

Abstract: A robust identification algorithm based on the self-join adjacent-feedback loop reservoir (SALR) network was proposed for dual-rate sampled nonlinear systems with complex nonlinear characteristics and measurement outputs containing outliers. The SALR network was applied to describe the nonlinear characteristics of the target system, and wavelet neurons were injected into the reservoir to enhance its memory and nonlinear description capabilities. The identification problem of the nonlinear system was transformed into the identification problem of the network's output weight matrix. The Huber loss function was used to construct the criterion function, and an error threshold was introduced to improve the robustness …

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Distributed Dispatch Method For Distribution Network And Microgrid Considering Diverse Regulating Resources, Yanbo Chen, Jiahao Yin, Tuben Qiang, Haoxin Tian, Yuxin Liang, Zhi Zhang Oct 2025

Distributed Dispatch Method For Distribution Network And Microgrid Considering Diverse Regulating Resources, Yanbo Chen, Jiahao Yin, Tuben Qiang, Haoxin Tian, Yuxin Liang, Zhi Zhang

Journal of System Simulation

Abstract: Traditional centralized optimization-based dispatch methods for distribution networks struggle to balance the interests of multiple stakeholders while ensuring economic efficiency and operational reliability of the system. To address this issue, a distributed dispatch method for distribution network and microgrid considering diverse regulating resources was proposed. The operational models of the distribution network and microgrid were established by comprehensively incorporating active management elements and demand response mechanisms. A fuzzy chance-constrained method was employed to model the uncertainty in renewable energy output, thereby constructing a coordinated optimization dispatch model for distribution network and microgrid under renewable generation uncertainty. An improved goal …

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Deep Learning Modeling Of Multi-Scale Characteristics Of Large-Scale Wind Turbine Gearbox, Yang Hu, Zihao Li, Deyi Fu, Ziqiu Song, Fang Fang, Jizhen Liu Oct 2025

Deep Learning Modeling Of Multi-Scale Characteristics Of Large-Scale Wind Turbine Gearbox, Yang Hu, Zihao Li, Deyi Fu, Ziqiu Song, Fang Fang, Jizhen Liu

Journal of System Simulation

Abstract: To address challenges in characterizing high-frequency vibrations of wind turbine gearboxes, the long computation time of rigid-flexible coupled multi-body dynamics models, and the complexity of configuring gearbox models across multiple scenarios, this study proposed a deep learning modeling method for multi-scale operation using full-condition digital testing. The study proposed a cascaded extended simulation scheme based on stream data-driven OpenFAST and Adams and utilized dynamic mode decomposition technology to construct a multi-scale dataset for the flexible multi-body dynamics characteristics of the gearbox under all operating conditions of the wind turbine. Based on this dataset, a digital surrogate model covering multiple …

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Optimization Dispatch Method For High-Proportion Renewable Energy Power Systems Based On Sc-Ppo, Zhongkai Xu, Chenyang Chu, Kai Xie, Ruizhuo Zhao, Wenjun Ke Oct 2025

Optimization Dispatch Method For High-Proportion Renewable Energy Power Systems Based On Sc-Ppo, Zhongkai Xu, Chenyang Chu, Kai Xie, Ruizhuo Zhao, Wenjun Ke

Journal of System Simulation

Abstract: The high proportion of renewable energy integration brings significant challenges of randomness, multi-objective coupling, and security constraints to power systems. Traditional model-driven methods have limitations in modeling accuracy and adaptability. To address these issues, this paper proposed a safety-constrained PPO algorithm (SC-PPO). The method included three improvements. A temporal convolutional network was utilized to construct a dynamic state encoder that integrated historical operation, real-time monitoring, and prediction data to form a causal state representation. A hierarchical reward structure was designed, and an adaptive weighting mechanism based on constraint satisfaction degree was introduced to coordinate multi-objective optimization. Physical constraint projection …

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Microsimulation Of Infectious Disease Transmission Considering Virus Release, Transmission, And Action, Zhiming Fang, Shengdong Yuan, Ge Huang, Jingqian Yang, Zhongyi Huang Oct 2025

Microsimulation Of Infectious Disease Transmission Considering Virus Release, Transmission, And Action, Zhiming Fang, Shengdong Yuan, Ge Huang, Jingqian Yang, Zhongyi Huang

Journal of System Simulation

Abstract: Existing infection risk assessment methods mostly evaluate infection probability through mathematical models or simulation, but they lack analysis of the relationship between air circulation and individual infection probability. This study proposed a risk prediction model for infectious disease transmission based on indoor air circulation. At the microscopic scale, the space was discretized into grid points. By integrating CFD numerical simulation, the entire process of virus droplet release, transmission, and action was fully simulated. The simulation results show that in an obstacle-free room, the error between the total indoor viral load predicted by the model under windless and low wind …

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Path Planning For Mobile Robots Based On Improved Rrt-Connect And Dwa Fusion, Yi Luo, Jia Deng Oct 2025

Path Planning For Mobile Robots Based On Improved Rrt-Connect And Dwa Fusion, Yi Luo, Jia Deng

Journal of System Simulation

Abstract: To improve the efficiency and quality of dynamic path planning for mobile robots in complex environments, this paper proposed a path planning algorithm that combined an improved RRT-connect with the DWA. Two expanding random trees were introduced for alternating expansion, and a dynamically restricted sampling area was set to reduce the randomness of the sampling process while ensuring the probability completeness of the algorithm. A target bias adaptive step size strategy was employed to enhance the target orientation of the random tree expansion process. A greedy strategy was adopted to prune redundant nodes in the path and smooth the …

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Modeling And Simulation Of Traffic Signal Control Based On Mlp With Improved Gcn-Td3, Deqi Huang, Yating Tu, Zhenhua Zhang, Xin Guo Oct 2025

Modeling And Simulation Of Traffic Signal Control Based On Mlp With Improved Gcn-Td3, Deqi Huang, Yating Tu, Zhenhua Zhang, Xin Guo

Journal of System Simulation

Abstract: To address the issues of uneven traffic flow at urban intersections, limited road capacity, and the poor coordination of existing traffic signal control algorithms, a traffic signal control algorithm based on graph convolutional reinforcement learning was proposed. By utilizing a multilayer perceptron, the dynamic features of vehicles and phase information at the controlled intersection and its neighboring intersections were extracted. A graph convolutional neural network was then employed to aggregate these vehicle dynamic features into potential features representing regional traffic. The control strategy was derived through multiple iterations of an improved twin delayed deep deterministic policy gradient (TD3) algorithm. …

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Dynamic Order Scheduling For Pick-And-Pass System Considering Workload Balance And Learning Effects, Weihong Liu, Sixiang Zhao, Dali Zhang, Zhenhui Jiang Oct 2025

Dynamic Order Scheduling For Pick-And-Pass System Considering Workload Balance And Learning Effects, Weihong Liu, Sixiang Zhao, Dali Zhang, Zhenhui Jiang

Journal of System Simulation

Abstract: In e-commerce logistics, the hybrid pick-and-pass systems offer both complexity and flexibility, enabling adaptation to a wider range of order picking scenarios. Therefore, they have been widely used. However, this also complicates the order scheduling problem, particularly when both workload balance and pickers' learning effects need to be considered. Efficiently scheduling orders to reduce picking time under these conditions poses a significant challenge. This study began by constructing a mathematical model for the static scheduling problem with known orders. Based on this model, a simulation model of hybrid pick-and-pass zones was developed, and a scheduling rule incorporating multiple system …

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Simulation And Optimization Of Continuous Motion Control Based On Spiking Reinforcement Learning, Xiaode Liu, Yufei Guo, Yuanpei Chen, Jie Zhou, Yuhan Zhang, Weihang Peng, Zhe Ma Oct 2025

Simulation And Optimization Of Continuous Motion Control Based On Spiking Reinforcement Learning, Xiaode Liu, Yufei Guo, Yuanpei Chen, Jie Zhou, Yuhan Zhang, Weihang Peng, Zhe Ma

Journal of System Simulation

Abstract: To improve the model robustness for multi-degree-of-freedom continuous motion control, an intelligent motion control algorithm was proposed based on the Actor-Critic reinforcement learning framework and spiking neural networks. This algorithm integrateed the Actor network with spiking population coding and enhanced model training performance by introducing feature transformation methods. The Critic network was used to evaluate the effectiveness of the motion control. The results show that, compared to other reinforcement learning algorithms, the average reward value of this method increases by more than 10%. The simulation results validate the effectiveness of the model in improving multi-degree-of-freedom continuous control performance.

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Distributed Heterogeneous Hybrid Flow-Shop Scheduling Considering Combined Buffer, Hua Xuan, Lin Lü, Bing Li Oct 2025

Distributed Heterogeneous Hybrid Flow-Shop Scheduling Considering Combined Buffer, Hua Xuan, Lin Lü, Bing Li

Journal of System Simulation

Abstract: In order to reduce cost losses caused by delivery delays, distributed heterogeneous hybrid flowshop scheduling problems under combined buffer conditions of finite buffer and zero-wait were studied. A hybrid estimation of distribution algorithm based on Q-learning was proposed to minimize total weighted earliness and tardiness. For the combined buffer, dynamic decoding was designed based on the average factory allocation strategy and the shortest path method. The initial job group was optimized by reverse learning. Q-learning was embedded in the probabilistic model for intelligent searching and updating based on the group state. Reconstruction of the job group was completed using …

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Study Of ~-Topological Space By ~-Binary Relation In Cluster System, Mustafa Hasan Hadi, Luay Abd Al Haine Al Swidi Oct 2025

Study Of ~-Topological Space By ~-Binary Relation In Cluster System, Mustafa Hasan Hadi, Luay Abd Al Haine Al Swidi

Iraqi Journal for Computer Science and Mathematics

In this paper, we introduced a new type of operators, which we called ~-operator by cluster system, and studied its properties without conditions and with certain conditions. Through our study of this operator, we defined a new topology, which we called ~-topological space, since it does not, in general, constitute a regular topological space. We also presented ~-interior points, ~-closure, ~-exterior points and reviewed some theories and examples about this concept.

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Penggunaan Microsoft Excel Di Kehidupan Sehari-Hari, Dimas Hafidz Alfarisi, Bilal Al Kindi, Aisya Mardatila, Reni Anggraeni, Desi Wulandari Oct 2025

Penggunaan Microsoft Excel Di Kehidupan Sehari-Hari, Dimas Hafidz Alfarisi, Bilal Al Kindi, Aisya Mardatila, Reni Anggraeni, Desi Wulandari

Bhakti: Jurnal Pengabdian Masyarakat

Community Service Program (KKN) is one of the main parts of the tridharma of higher education, which requires students to play an active role in community empowerment through education, research, and service. This article discusses one of program from the KKN team from Universitas Negeri Semarang (UNNES), which took place in Tlogopucang Village, Kandangan District, Temanggung. In today's digital era, mastery of information technology has become a crucial requirement, including the ability to operate data processing applications such as Microsoft Excel. Unfortunately, many people, especially in rural areas, are still unfamiliar with the benefits of Excel. However, this application has …

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Chplx: The Hpx Solution For Bridging Chapel And C++, Shreyas Swanand Atre Oct 2025

Chplx: The Hpx Solution For Bridging Chapel And C++, Shreyas Swanand Atre

LSU Master's Theses

Historically, domain scientists faced steep learning curves due to low-level programming models and fragmented tooling. Between 2003 and 2008, Cray, now part of HPE, introduced the Chapel language as part of DARPA’s High Productivity Computing Systems (HPCS) program. Today, Chapel remains under active development and is used across research and production projects. In parallel, the STE||AR Group has advanced C++-based parallel programming through HPX, a standards-conforming runtime that provides lightweight tasking, futures, and distributed execution while abstracting much of the algorithmic “heavy lifting.” Yet for many domain scientists, C++ presents a steeper learning curve than Chapel. To close this complexity …

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Sensing The Pulse Of A Data Stream In Real Time, Vishnu S. Pendyala Oct 2025

Sensing The Pulse Of A Data Stream In Real Time, Vishnu S. Pendyala

Open Educational Resources

In an era where data never sleeps, streaming algorithms offer a powerful toolkit for extracting meaningful insights from high-velocity data flows. This talk explores some foundational techniques that enable efficient, real-time analytics with minimal memory requirements. The algorithms covered include a clever bit-based strategy for approximating the count of 1s in a sliding window, ideal for binary streams where space efficiency is paramount. Another algorithm helps estimate statistical moments (mean, variance, skewness) using compact sketches, enabling a deeper understanding of stream distributions without storing the entire dataset. One other algorithm identifies trending items with exponential decay, giving more weight to …

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Synthetically Expressive: Evaluating Gesture And Voice For Emotion And Empathy In Vr And 2d Scenarios, Haoyang Du, Kiran Chhatre, Christopher Peters, Brian Keegan, Rachel Mcdonnell, Cathy Ennis Oct 2025

Synthetically Expressive: Evaluating Gesture And Voice For Emotion And Empathy In Vr And 2d Scenarios, Haoyang Du, Kiran Chhatre, Christopher Peters, Brian Keegan, Rachel Mcdonnell, Cathy Ennis

Conference papers

The creation of virtual humans increasingly leverages automated synthesis of speech and gestures, enabling expressive, adaptable agents that effectively engage users. However, the independent development of voice and gesture generation technologies, alongside the growing popularity of virtual reality (VR), presents significant questions about the integration of these signals and their ability to convey emotional detail in immersive environments. In this paper, we evaluate the influence of real and synthetic gestures and speech, alongside varying levels of immersion (VR vs. 2D displays) and emotional contexts (positive, neutral, negative) on user perceptions. We investigate how immersion affects the perceived match between gestures …

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Enhancing 6g Network Security With Quantum Key Distribution: A Comprehensive Review, Bassma M. Kamil Oct 2025

Enhancing 6g Network Security With Quantum Key Distribution: A Comprehensive Review, Bassma M. Kamil

Al-Esraa University College Journal for Engineering Sciences

With the considerable progress of sixth-generation (6G) networks further on the horizon, security has attracted much attention in the face of increasingly sophisticated threats, especially from quantum computing. Classical cryptographic schemes based on computational hardness are becoming more and more brittle, as they can easily be attacked with a quantum computer. Quantum Key Distribution (QKD) arises as a promising tool for information-theoretic security through quantum mechanics to obtain an unbreakable key by exchanging unknown bit sequences. In this paper, we provide an extensive survey on the integration of QKD both in the envisioned 6G architecture, including current implementations, technical feasibility, …

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Protection The Nfv Net-Work Using The Random Forest Classification, Mustafa H. Taha, Ibtesam Jomaa Hawi, Wafaa Waheeb Abdullah Ali Oct 2025

Protection The Nfv Net-Work Using The Random Forest Classification, Mustafa H. Taha, Ibtesam Jomaa Hawi, Wafaa Waheeb Abdullah Ali

Al-Esraa University College Journal for Engineering Sciences

A misuse attack is the most common and dangerous type of attack that could target NFV (Network Function Virtualization). In a misuse attack, the attacker attempts to consume the NVF environment’s resources by sending a large amount of traffic. To protect the NFV environment, an early and accurate misuse attack detection system has been proposed based on NFV and Random Forest Classifier. The proposed model starts with importing the dataset and analyzing it then pre-processing and feature selection using a PSO (particle swarm optimization) Test algorithm, classification is based on the most common and efficient machine learning technique, which is …

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Design Of A Hybrid System For Powering Wireless Communication Units, Samer Rabih, Ahed Alboody Oct 2025

Design Of A Hybrid System For Powering Wireless Communication Units, Samer Rabih, Ahed Alboody

Al-Esraa University College Journal for Engineering Sciences

Wireless and optical communication units are becoming more widespread nowadays, especially in rural areas. Therefore, feeding electricity has become essential for the continuity of services. As a result of economic and social development, there has been an urgent need to supply electrical power for the basic requirements of wired and wireless telecommunications equipment. This is linked to public safety, long life, and connection to uninterruptible power systems to ensure continuous power supply, whether from renewable energy sources or traditional diesel systems. This research studies and designs a renewable energy (solar) power system to power telecommunications equipment. The proposed power system …

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Dynamic Ris-Enabled Massive Mimo Noma Systems Power Allocation Optimization For 6g Using Machin Learning Approach, Mohamed Hassan, Khalid Hamid, Salah Hagahmoodi, Elmuntaser Hassan Oct 2025

Dynamic Ris-Enabled Massive Mimo Noma Systems Power Allocation Optimization For 6g Using Machin Learning Approach, Mohamed Hassan, Khalid Hamid, Salah Hagahmoodi, Elmuntaser Hassan

Al-Esraa University College Journal for Engineering Sciences

This study examines spectral efficiency (SE) and throughput throughout a spectrum of user densities (from 50 to 1000 users), user mobility speeds (0 to 350 km/h), latency, packet loss, and fairness index, within a wide range of signal-to-noise ratios (SNRs). The analysis includes a number of different situations, such as (i) cooperative non-orthogonal multiple access (NOMA) with massive multiple-input multiple-output (mMIMO), (ii) mMIMO cooperative NOMA integrated with cognitive radio (CR), and (iii) CR-assisted mMIMO cooperative NOMA enhanced with reconfigurable intelligent surfaces (RIS). All of these are part of 6G millimeter-wave (mmWave) networks. The study investigates the enhancement of latency, packet …

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Harnessing Waste Heat From Solar Cells Using Advanced Energy Storage Systems, Hayder Ibrahim Ismael Oct 2025

Harnessing Waste Heat From Solar Cells Using Advanced Energy Storage Systems, Hayder Ibrahim Ismael

Al-Esraa University College Journal for Engineering Sciences

Renewable energy is largely produced by photovoltaic (PV) solar cells, but such a process is greatly impacted with thermal buildup as the solar cells work. Redundant heat not only lowers the level of electrical production, but also hastens deterioration and decreases the life-time of PV modules. In this study, we suggest a hybrid system which combines high-performance energy storage devices, namely, super-capacitors, and PV modules coupled with the use of waste heat as a source of useful energy and which increases efficiency of the system in conjunction. In order to estimate the potential amount of thermal energy recovery, as well …

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Empirical Research Of A Greenhouse Monitoring And Controlling System Using Zigbee Protocol, Mohammed Hijazeh, Salah Hagahmoodi Oct 2025

Empirical Research Of A Greenhouse Monitoring And Controlling System Using Zigbee Protocol, Mohammed Hijazeh, Salah Hagahmoodi

Al-Esraa University College Journal for Engineering Sciences

Greenhouses are of great importance in the agricultural field as they provide the appropriate and important environment for the growth and production of various plants regardless of the surrounding environmental conditions. Monitoring and controlling these houses are considered necessary and important in order to provide the required environment and obtain the best production. Therefore, the aim of this project is to study the monitoring and control of these houses using wireless sensor networks, which are considered modern and simple methods due to the accuracy of work and little effort they provide, and thus better production. The study will be for …

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Designing An Efficient Deduplication Algorithm For Audio Files In Cloud Storage, Ammar Zakzouk, Alaa Al Sebae, Hasan Hasan Oct 2025

Designing An Efficient Deduplication Algorithm For Audio Files In Cloud Storage, Ammar Zakzouk, Alaa Al Sebae, Hasan Hasan

Al-Esraa University College Journal for Engineering Sciences

Data duplication is a significant challenge in large-scale data storage systems, as it consumes storage space and impacts data organization, management, and processing. An optimal storage system effectively utilizes available storage space. To solve this problem, hash algorithms are employed to generate hash keys for files. Matching files have the same hash key. However, the hash key for two different files in the data may match, and this is what we refer to as a collision. The collision issue is related to the length of the hash key. As the length of the hash key increases, the probability of a …

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The Future Of Al-Driven Cybersecurity For Advanced Iot, Estqlal Hammad Dhahi, Sanaa Hammad Dhahi, Ohood Fadil Alwan Oct 2025

The Future Of Al-Driven Cybersecurity For Advanced Iot, Estqlal Hammad Dhahi, Sanaa Hammad Dhahi, Ohood Fadil Alwan

Al-Esraa University College Journal for Engineering Sciences

Internet of Things technologies experience rapid advancement because of 5G networks and upcoming 6G technologies, which resulted in transformational changes to security dynamics. This study examines the functionality of artificial intelligence through platforms developed to secure Internet of Things systems. The demand for improved security capabilities has become essential because IoT devices generate new assault channels, and their market penetration speed is escalating. Machine learning algorithms, together with deep learning and natural language processing methods, are investigated in this paper for enhancing the security protocols of IoT systems through studies found in academic literature. The paper explores upcoming developments and …

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Foundations Of Artificial Intelligence In Healthcare Diagnostics: A Systematic Survey, Raghad Tariq Al-Hassani Oct 2025

Foundations Of Artificial Intelligence In Healthcare Diagnostics: A Systematic Survey, Raghad Tariq Al-Hassani

Al-Esraa University College Journal for Engineering Sciences

Artificial Intelligence (AI) is becoming the cornerstone of the future of healthcare diagnostics, that has to ability to change the healthcare diagnostic landscape in terms of diagnostic accuracy, speed, and availability. This systematic review investigates the basic methods, tools, applications, and challenges involved in the integration of AI in diagnostic medicine. It emphasizes the using of machine learning models, deep learning networks (e.g., CNNs), NLP for clinical documentation, and smart computing infrastructures, such as edge device and IoMT. They are making possible real-time, data-driven decision making that is already at human-expert-level performance or, in some cases, even better (in the …

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Secure Gif Files Based On Zuc Stream Cipher And Present Algorithm, Suhad Fakhri Hussein Oct 2025

Secure Gif Files Based On Zuc Stream Cipher And Present Algorithm, Suhad Fakhri Hussein

Al-Esraa University College Journal for Engineering Sciences

Some important security needs include authentication, confidentiality, integrity, non-repudiation, and user privacy. Many security systems include these required protections for information transmission. The encryption process is one of the most important security measures. Many secure encryption algorithms are based on different keys and key lengths to ensure a high degree of security. GIF file format is common file format that is used in several application, securing these files through transmission is imperative. In this paper, an efficient method for encryption GIF file is proposed based on using modified present algorithm, modified ZUC stream cipher, and an efficient method for key …

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Advanced Strategies And Solutions Towards More Secure And Effective Two-Factor Authentication In Networking, Zahraa Sameer Jawad Oct 2025

Advanced Strategies And Solutions Towards More Secure And Effective Two-Factor Authentication In Networking, Zahraa Sameer Jawad

Al-Esraa University College Journal for Engineering Sciences

With the rapid increase in cybersecurity threats targeting network systems, traditional two-factor authentication (2FA) methods are insufficient to address advanced attacks. Vulnerabilities such as phishing, SIM-swapping, and social engineering exploit the limitations of SMS-based and email-based 2FA. This paper examines advanced strategies and solutions for securing networked environments through robust 2FA mechanisms, focusing on approaches like elliptic curve cryptography (ECC), digital certificates, and biometric verification. This article offers a comparative review of various strategies about their effectiveness in enhancing security, while also highlighting their capacity to optimize user-friendliness and adaptability to emerging threats. Research findings promote an effective countermeasure strategy …

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Advancements In Ultrasound Technology And Iot Security: A Physics-Based Approach To Enhanced Imaging With Lightweight Encryption Algorithms, Noor Fawzi Shafiq Oct 2025

Advancements In Ultrasound Technology And Iot Security: A Physics-Based Approach To Enhanced Imaging With Lightweight Encryption Algorithms, Noor Fawzi Shafiq

Al-Esraa University College Journal for Engineering Sciences

The rapid advancements in ultrasound technology, coupled with the growing significance of IoT security, present a unique opportunity to enhance imaging systems while ensuring data integrity. This study explores the integration of physics-based principles in ultrasound imaging, focusing on how lightweight encryption algorithms can secure data transmitted from IoT devices.Ultrasound technology has evolved significantly, benefiting from improved imaging techniques and the incorporation of IoT devices. As these devices proliferate across various applications, including healthcare and industrial monitoring, the need for secure data transmission becomes paramount. This paper proposes a framework that combines advanced ultrasound imaging with robust lightweight encryption methods …

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Artificial Intelligence Approaches To Mitigating Network Congestion In Iot Systems, Aysar Hadi Oleiwi Oct 2025

Artificial Intelligence Approaches To Mitigating Network Congestion In Iot Systems, Aysar Hadi Oleiwi

Al-Esraa University College Journal for Engineering Sciences

The unprecedented explosion of Internet of Things (IOT) devices has elevated the requirements of the network infrastructures to unprecedented levels, causing severe congestion problems, especially in applications which demand low latency, high throughput, and real-time feedback. Static routing protocols, AQM, and TCP variants are some of the traditional mechanisms for congestion control that are unable to perform efficiently in dynamic and diverse IoT environments as they are reactive-based and inflexible. To this end, in this paper, we explore the promising ability of Artificial Intelligence (AI) methods such as Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), and their combination …

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Groundwater Quality Analyses For Irrigation Purposes In Salah Al-Din, Iraq: A Review, Noor A. Radhi, Dawood E. Sachit, Abdul-Sahib T. Al-Madhhachi Oct 2025

Groundwater Quality Analyses For Irrigation Purposes In Salah Al-Din, Iraq: A Review, Noor A. Radhi, Dawood E. Sachit, Abdul-Sahib T. Al-Madhhachi

Al-Esraa University College Journal for Engineering Sciences

The focus of this study is the effect of the physical and chemical characteristics of groundwaters on plants and agricultural crops, following the last studies on this matter. The results underscore the necessity for groundwater treatment before its utilization in irrigation for sustainable agricultural farming. It is also possible to identify which crop type can be grown in well-watered land, according to the characteristics of irrigation water and the yield of each crop. The study also introduces some ideas about irrigation water quality parameters such as Electrical conductivity (EC), Total Dissolved Solids (TDS), pH, Chloride (Cl–), Sodium (Na …

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