Digital Commons Network^™

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.

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 …

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 …

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 …

A Novel Joint Training Simulation Evaluation Framework And Its Key Techniques, Rusheng Ju, Dongdong Chen, Yunxiu Zeng, Jiyuan Liu, Sihang Qiu, Peng Zhou

Journal of System Simulation

Abstract: To address the challenges of traditional evaluation systems, such as internal module coupling, lack of reusability, and poor adaptability to multi-domain evaluation needs, a three-tier decoupled technical evaluation framework of "data + service + application" was designed. A strategy was proposed for extracting high-value information from massive audio and video data based on key events, resolving the problem of unstructured evaluation data processing. A design method combining general and dedicated evaluation model templates was proposed, improving the general applicability of the evaluation model. An expert knowledge-driven comprehensive integrated discussion and evaluation environment was constructed using qualitative and …

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 …

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.

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 …

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, …

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 …

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 …

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 …

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 …

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 …

Advancing Mobileclip Through Hybrid Quantization: A Cpu-Focused Approach, Atiqur Rahman

2025 Fall Honors Capstones Projects - Archive

MobileCLIP is a compact model that connects images and text, enabling it to perform tasks like image identification and question answering without needing to be retrained for each new task. Although it’s designed to be lightweight, it still runs slowly on regular computers without a powerful graphics card (GPU). This research focuses on making MobileCLIP run faster and smaller by using post-training quantization, which reduces the model’s precision after training without hurting performance. We combined several strategies: analyzing which parts of the model are more sensitive to changes, applying targeted adjustments to its structure, and running everything using CPU-only tools. …

Learn To Fly: Enabling Deep Learning Based Perception And Control In Aerial Robotics, Krishna Muvva

School of Computing: Dissertations, Theses, and Student Research

Uncrewed Aerial Vehicles (UAVs) are increasingly deployed in dynamic, GPS degraded, and cluttered environments, yet their autonomy remains fundamentally constrained by limitations in onboard perception and real-time control. This dissertation addresses these challenges by proposing a unified framework that co-designs deep learning-based perception and model-based control, organized around three core thrusts: Learn to Track, Learn to Localize, and Learn to Evade.

Learn to Track develops dynamic and adaptive perception control mechanisms that optimize CNN inference for target tracking. A control-aware CNN framework dynamically adjusts inference frequency based on UAV motion, reducing latency while maintaining visual lock. An adaptive CNN with …

Csc36000 - Modern Distributed Computing Assignment, Saptarashmi Bandyopadhyay

Open Educational Resources

This assignment covers standard performance metrics for Distributed Systems and the basics of Multiprocessing for CSC36000 - Modern Distributed Computing at the City College of New York CUNY. It is an interactive coding assignment intended to be executed in a Python notebook.

Approximating The Maximum Weighted Independent Set Problem Empirically, Sue Sue

College of Engineering Summer Undergraduate Research Program

In this project we investigate approximation algorithms for the maximum weighted independent set (MWIS) problem in random graphs that approximate real-world graphs, such as social networks. The problem involves finding a large collection of nodes in a network (vertices in a graph) such that no two nodes are directly connected to one another. Applications of the MWIS problem are broad and include clique-finding algorithms as well as the use of large independent sets in distributed algorithms. We build on prior work by the mentor with a SURP 2024 and senior project, in which preliminary findings suggested that a standard greedy …

Machine Unlearning: The Right To Be Forgotten, Colin Ngo

College of Engineering Summer Undergraduate Research Program

The objective of this SURP proposal is to investigate machine unlearning as a viable approach to support the right to be forgotten in artificial intelligence (AI) systems, many of which rely heavily on personal data. The capability to selectively remove user-specific information upon request—without necessitating full model retraining—is critical for safeguarding individual privacy and enhancing computational and energy efficiency. This project will undertake a systematic review of state-of-the-art unlearning techniques, evaluate their performance using standard benchmark datasets, and assess their feasibility in real-world applications. In addition, the project will provide participating students with practical experience in implementing and analyzing machine …

Relational Algebra Interpreter, Sydney Lynch

College of Engineering Summer Undergraduate Research Program

We would like to build a compiler for relational algebra that converts it to SQL. This compiler will be used in database labs to give the students hands-on experience to write relational algebra code. Current relational algebra compilers that are open source are not very good and are hard for the students to use.

Math+Cs Integrated Curriculum For K-12 Computer Science Education, Amogh Arora

College of Engineering Summer Undergraduate Research Program

This is a proposal for an activity to initiate an effort to create a series of X+CS integrated curricula for learning Computer Science (CS) in K-12. As a start, we examine Mathematics and CS standards, to find the cross-cutting concepts between the two fields. By leveraging these concepts, we bring to the foreground the ways CS can be used in the mathematical context. The goal for this research is to create a 15-week teacher training curriculum that will expose teachers to the CS concepts of Abstraction, Data Representation, Problem Comprehension and Decomposition, Control Structures, Functions and Generalization. Historically, Mathematics and …

Use Matters: How Different Ways Of Using Chatgpt Drive Ai Acceptance And Solutionism, Florian Golo Flaßhoff, Fabian Anicker, Frank Marcinkowski

Human-Machine Communication

Artificial intelligence is central to solutionism—the vision of a world where all major problems are solved through technology. This study theorizes about how human–AI communication shapes attitudes toward AI and influences the formation of public opinion, sparking solutionist imaginaries. We empirically examine the attitude formation resulting from the non-simulated use of an unmanipulated conversational model in a controlled laboratory experiment. Using a between-subjects design, participants engaged in three semi-structured 20-minute sessions with ChatGPT, providing a novel perspective on the effects of its use. The findings reveal that mere use of ChatGPT causally increases AI acceptance; however, its impact significantly depends …

Retracted: Adaptive Crossover And Mutation Mechanisms For Enhanced Lpb Algorithm Performance, Abbas M. Ahmed, Tarik A. Rashid

Iraqi Journal for Computer Science and Mathematics

This study proposes a more effective concept of Learner Performance-based Behavior (LPB). It is a new metaheuristic algorithm based on how the university admission process is done for high school students in various departments. The adaptive crossover and mutation methods were incorporated into the LPB algorithm as part of an investigation. The goal is to enhance convergence and significantly improve the quality of the solutions. The aLPB (adaptive-learner performance-based Behaviour) method stands out because it sets the crossover and mutation parameters based on the performance of the parent solutions. Thus, the proposed technique achieves a balance between exploration and exploitation …

Iot-Enabled Machine Learning Framework For Prediction Of Eutrophication, Hocine Dai, Akli Abbas, Houssam Eddine-Othman Lachemat, Aicha Aid

Iraqi Journal for Computer Science and Mathematics

This study presents an innovative predictive monitoring framework that integrates the Internet of Things (IoT) with advanced machine learning (ML) techniques to model the relationship between oxidized nitrate (NOX)—employed as the sole predictor—and chlorophyll a (CHLA), a key proxy for algal biomass. By utilising a single optimally selected parameter, the approach significantly reduces sensor deployment complexity and instrumentation costs, while minimising data acquisition and computational requirements. Logarithmic and Yeo-Johnson transformations were applied to the predictor and target variables, respectively, to address distributional skewness and enhance variance homogeneity. An optimised Random Forest model demonstrated strong predictive performance, achieving a coefficient of …

Multi Features Data Clustering Using Novel Statistical Method With Application To Color Images, Husham Y. A. Alameen, Ali Karah Bash

Iraqi Journal for Computer Science and Mathematics

The efficiency and performance of the color image clustering algorithms are determined by various factors, including accuracy, data size, speed, and reliability (the absence of randomness in the results). Some applications, like microscopes analyzing images of biological objects or telescopes observing planetary motion prioritize accuracy over execution time. In contrast, surveillance cameras and moving object tracking prioritize speed and reliability over accuracy. This study introduces a novel algorithm that balances these four factors by clustering data with multiple features linked through specific relationships. The proposed algorithm has been practically applied to RGB color images. Traditional clustering methods, such as K-means, …

A New Approach For Multiprocessor System-On-Chip Application Scheduling In Multi-Objective Flow Shops, Tahani Jabbar Khraibet, Bayda Atiya Kalaf, Ahmed Abbas Jasim

Iraqi Journal for Computer Science and Mathematics

The flow shop scheduling problem in Multiprocessor-System-on-Chip (MPSoC) architectures presents challenges for traditional optimization algorithms, especially when addressing multiple conflicting objectives. Hence, advanced optimization approaches are required to tackle these objectives simultaneously. Therefore, this research aims to propose and evaluate a new optimization approach based on the integration of the Fire Hawk Optimizer with the Smart Battery Scheduling Algorithm (FHO-SBSA) to address the multi-objective (make span, CPU time, global average delay, network throughput, and total energy consumption) flow shop scheduling problem in MPSoC systems. To evaluate the performance of the FHO-SBSA optimization approach, two benchmark applications were selected, with ten …

Optimization Of Multi-Target Interception Scheme Based On Performance Simulation Modeling, Hanwen Liu, Zhimin Zhuo, Xue Yang

Journal of System Simulation

Abstract: The air attack scenarios faced by air defense weapons and equipment show the trend of saturation, diversification and intelligence. It is very important to establish multi-target interception efficiency model and optimize interception scheme according to simulation. The current intercepting efficiency index mainly considers the whole operation process, and can not guide the optimization of the intercepting scheme of specific intercepting rounds. The generation of interception schemes mainly relies on experience and simple mathematical model, which is difficult to cope with the increasingly complex and changeable battlefield environment. Therefore, an interception scheme advantage index that comprehensively considers interception probability and …

Design And Prediction Of Deep Fuzzy Neural Network, Chengbiao Wei, Taoyan Zhao, Jiangtao Cao, Ping Li

Journal of System Simulation

Abstract: A deep fuzzy neural network (DFNN) is proposed to solve the problem that the deep neural network has poor interpretability and the correction of the model is not targeted when dealing with the big data regression prediction problem. The proposed deep fuzzy neural network adopts an adaptive fuzzy Cmeans (AFCM) clustering algorithm in structural learning. The structure of the model, namely the number of rules and the antecedent parameters of the rules, is determined by calculating the introduced validity function. The identification of consequent parameters uses an improved grey wolf optimization (IGWO) algorithm. By replacing the linear decreasing strategy …

Kill Chain Efficiency Evaluation Model Based On Gray Dematel-Anp, Zejing Zhao, Junliang Shang, Yanpei Qin

Journal of System Simulation

Abstract: In modern conflict scenarios, the kill chain is integral to the comprehensive understanding, orchestration, and execution of military operations. Accurately appraising the efficiency of the kill chain is imperative for gaining insights into battle dynamics and strategically distributing military assets. However, traditional assessments of kill chain efficacy have been hampered by fragmented and isolated indicators that frequently overlook the interplay and influence among various segments of the kill chain. To address these limitations, based on the characteristics of each phase of the kill chain and the OODA loop theory, a new set of performance evaluation indices has been proposed. …

Optimization Method For Multi Agricultural Machinery Collaborative Operation Based On Genetic Algorithm And A* Algorithm, Yiran Yu, Huicheng Lai, Guxue Gao, Guo Zhang, Wangyinan Peng, Longfei Yang, Junhao Huang

Journal of System Simulation

Abstract: To address the uneven task distribution among multiple agricultural machines (referred to as farm machinery) and the high time cost due to numerous turning points at intersections, this paper proposes a task planning method that combines a pre-heat multi grouped genetic algorithm (PHMGA) with the turn A* algorithm (tA*). PHMGA allocates tasks to each piece of farm machinery based on the known environment, ensuring balanced workload through a cost objective function that considers travel, operation, and turning distances. It also designs various operators and strategies to search for nearoptimal solutions. The tA* algorithm is used to select paths …