Digital Commons Network^™

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, …

Uav Swarm Obstacle Avoidance Based On Visual Filed And Adaptive Radius, Gaohang Ai, Chuntao Li

Journal of System Simulation

Abstract: Aiming at the obstacle avoidance problem of large-scale UAV swarm tracking flight route, a swarm obstacle avoidance algorithm based on distributed model predictive control combined with visual field and adaptive obstacle avoidance radius is proposed. In the process of swarm flight, the UAV obtains the reference route information of the current moment according to its own position, and obtains the predicted trajectory of its neighbors through local information interaction. When encountering obstacles, the adaptive obstacle avoidance radius and field of view topology method are combined to effectively solve the problem that the internal safety distance cannot be maintained and …

A Novel Research Pattern For The Simulation Of Complex Systems Sigd, Bin Chen, Runkang Guo, Zhengqiu Zhu, Yong Zhao, Yatai Ji, Aiguo Chen, Guangquan Cheng

Journal of System Simulation

Abstract: The complexity of the system is mainly reflected in the numerous components and extremely complex interactions. Combined with the current trend of artificial intelligence development, this paper analyzes and considers the changes in thinking mode brought by simulation discipline research, and forms an understanding of the connotation and research scope of simulation intelligence. A new pattern for complex system simulation research is proposed: "simulation intelligence based generating decisions (SIGD)". In the SIGD pattern, the similar principles, modeling methods, and decision-guiding modes in simulation disciplines are different from those in traditional simulation. Under the guidance of this concept, a connection-oriented …

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 …

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 …

An Intelligent System Using Deep Learning For Healthcare Monitoring In Light Of The Covid-19 And Future Pandemics Based On Iot, Sara Salman Qasim, Rajaa J. Khanjar, Jamal Nasir Hasoon, Baesher Abdullateff Abad, Ali Hussein Fadil, Shajan.M. Alsowaidi

Al-Esraa University College Journal for Engineering Sciences

Recently, the Internet of Things has become a compelling research field as a new topic of research in various disciplines, particularly in the field of healthcare, because the Internet of Things is rebuilding modern healthcare systems by integrating technology, economics, and social perspectives. The development of healthcare systems from traditional to more personalized systems in which patients can be easily diagnosed, monitored and treated and many people can be helped. People are treated and cared for remotely and this is what some people need in the crisis the world has been through like COVID-19. This epidemic is caused by the …

The Evolution Of The University Of Al-Anbar Urban Planning Based On The Mental Picture's Diversity And The Contemporary Planning Spaces Filling, Ali Abdulsamea Hameed

Al-Esraa University College Journal for Engineering Sciences

This research concentrated on the role of environmental graphic design (EGD) and the place-making idea in the interior environment of Al-Anbar University. To develop an identity being visual for the University of Al-Anbar internal environment (IE) is this goal of project. The search sought to create and enhance the shape of the internal University of Al-Anbar vacuum by reviving the idea of place building. In order to build and filling the internal emptiness of the campus, the identity being visual must also be strengthened. The descriptive analytical approach was chosen since it was best suited to achieve the goal of …

Optimal Operation Scheduling Of Integrated Energy System Considering Energy Priority, Dongli Jia, Keyan Liu, Zhaoying Ren, Zezhou Wang, Dongsheng Tang

Journal of System Simulation

Abstract: Integrated with the actual situation of power grid and the growth of new energy, a multiobjective model for optimal scheduling of the integrated energy system(IES) is established based on the analysis of the energy-flow relationship of the IES and taking into account the priority of energy utilization and the load demand response in terms of the mismatch between the distributed energy sources and the loads, the net benefit of the unit cost of the IES, and the load response degree. Combined with the equipment and the environmental benefits system, a priority constraint for energy utilization has been established for …

Research On Scheduling Strategies Simulation For Building Air-Conditioning Systems Based On Transfer Imitation Learning, Qiaochu Wang, Yan Ding, Chuanzhi Liang, Haozheng Zhang, Chen Huang

Journal of System Simulation

Abstract: To solve the problem of unstable performance and inefficient training process of low-quality data conditions at the initial stage of online deployment of air conditioner scheduling, we propose a migration-imitation learning-based air conditioning scheduling strategy simulation method. Reinforcement learning methods are used to generate building operation strategies. A standard building simulation model serves as the source domain, upon which migration learning is applied. An imitation learning loss function is incorporated into the intelligent loss function to enhance algorithm performance. The results indicate that, compared with the non-use of migration learning, the proposed method can improve the operational efficiency by …

Behavioral Modeling Of Manned-Unmanned Cooperative Air Combat Based On Improved Abc Algorithm, Peng Wang, Haoyu Liu, Ni Li, Zexi Yu, Shangjie Jia

Journal of System Simulation

Abstract: To solve the problem of difficulty in establishing collaborative behavior models and weak adversarial capabilities in typical MAV/UAV air combat scenarios, a mixed decision based MAV/UAV behavior modeling framework is proposed. Using collaborative rule sets, rule subsets, tactical action sets, and other tools, a hierarchical decision collaborative behavior model supporting five types of collaborative tactics, including grinding tactics and unilateral flanking tactics, is constructed in this framework. a behavior model parameter optimization method based on an improved artificial bee colony (ABC) algorithm is proposed. By using the Mason rotation method to initialize the population, a better initial honey source …

Harmonic Impedance Modeling And Oscillation Analysis Of Modular Multilevel Converter, Yuhong Wang, Wensheng Chen, Shilin Gao, Jianquan Liao, Yangfan Cheng

Journal of System Simulation

Abstract: To facilitate rapid analysis of the oscillation stability mechanism in modular multilevel converter-based high voltage direct current (MMC-HVDC) systems and streamline the simulation process for determining MMC impedance characteristics, a simplified mathematical simulation model for MMC closed-loop impedance is developed using the harmonic state space method. This model considers various control strategies and includes both AC-side and DC-side impedance models. By applying a Nyquist criterion-based impedance analysis method, the stability mechanisms on the AC and DC sides of the MMC are examined. In addition, a data-driven oscillation stability analysis method is also proposed, leveraging a global sensitivity algorithm based …

Path Planning Of Desert Robot Based On Deep Reinforcement Learning, Ming Li, Wangzhong Ye, Jiehua Yan

Journal of System Simulation

Abstract: Due to the complexity and variability of the desert environment, the key to the high-efficient of mobile robot is how to avoid obstacles and plan its path. To solve the problems of poor search efficiency and slow convergence of deep reinforcement learning algorithm in complex environment, an improved deep reinforcement learning path planning algorithm is proposed. The exploration factor is improved and dynamically adjusted according to the convergence degree of the algorithm, so that the exploration factor dynamically decreases with the increase of the understanding degree of the agent to the environment, thus speeding up the convergence speed of …

Secure Healthcare Systems And Big Data: A Bibliometrics Analysis, Rasha Talal Hameed, Saad Ahmed Dheyab, Saba Abdulbaqi Salman, Ahmed Hussein Ali, Omar Abdulwahabe Mohamad

Iraqi Journal for Computer Science and Mathematics

This study conducts a bibliometrics analysis of research on secure healthcare systems and big data, aiming to identify trends, key contributors, and thematic areas within the field. By examining a comprehensive database of academic publications, we highlight the evolution of research from foundational concepts to contemporary innovations in data security and privacy management in healthcare. Key metrics such as publication volume, citation impact, and co-authorship networks are analyzed to uncover the most influential authors and institutions. Additionally, we explore the integration of big data analytics in enhancing healthcare delivery while addressing security challenges. The findings provide valuable insights for researchers …

Integrating Image Data Fusion And Resnet Method For Accurate Fish Freshness Classification, Yahya Layth Khaleel, Mustafa Abdulfattah Habeeb, Ghadeer Ghazi Shayea

Iraqi Journal for Computer Science and Mathematics

Fish freshness classification is critical for protecting public health and ensuring efficient economic, regulatory and environmental sustainability. Classifying accurately reduces the risk of foodborne illness, protects product quality, builds consumer trust and supports sustainable resource conservation through waste minimization. However, the traditional methods for determining fish freshness are variable, time consuming and subjective, precluding practical use. This research presents an improved framework that integrates image data fusion and a deep learning ResNet model to differentiate fresh and nonfresh fish. From multiple sources, a comprehensive dataset including 16,640 samples was curated, and data fusion was used to increase the diversity and …

Predicting Chaotic Systems With Quantum Echo-State Networks, Erik Connerty, Ethan N. Evans, Gerasimos Angelatos, Vignesh Narayanan

Publications

Recent advancements in artificial neural networks have enabled impressive tasks on classical computers, but they demand significant computational resources. While quantum computing offers potential beyond classical systems, the advantages of quantum neural networks (QNNs) remain largely unexplored. In this work, we present and examine a quantum circuit (QC) that implements and aims to improve upon the classical echo-state network (ESN), a type of reservoir-based recurrent neural networks (RNNs), using quantum computers. Typically, ESNs consist of an extremely large reservoir that learns high-dimensional embeddings, enabling prediction of complex system trajectories. Quantum echo-state networks (QESNs) aim to reduce this need for prohibitively …

Enhancement Of Ambient Air Quality Index Forecasting Using Optimized Ensemble Model, Vanitha M

Theses and Dissertations

Forecasting ambient air quality is essential for environmental sustainability and public health, especially in heavily populated regions such as China, India, and the United States where air pollution remains a serious concern. Traditional forecasting models often struggle to accurately represent air quality data because of its complex patterns and nonlinear interactions. To address these challenges and improve forecast performance, this research proposes a comprehensive strategy that integrates parallel heterogeneous ensemble modeling with Bayesian optimization.

The study begins with a seasonal machine learning–based imputation technique (SeasonalMLImpute) designed to handle missing data in meteorological and air quality parameters. This method is evaluated …

Develop Secure Software Specifications For Android App Concealing The Information And Safeguarding Data, Huda Abdulaali Abdulbaqi, Ahmmad Mohamad Ghandour, Thekrayat Abbas Jawad

Iraqi Journal for Computer Science and Mathematics

In the current landscape of technological advancement, data holds a pivotal role, shaping societal interactions and daily routines. The rapid escalation in digital data volume, driven by technological strides, has underscored the critical necessity for robust protective measures to safeguard its sensitive nature. This study aims to develop a secure software specification for Android application ensuring effective data protection through a specialized Android application tailored explicitly for data concealment, assuring utmost confidentiality and secure transmission. In this paper we revolve around the integration of multifaceted security and privacy protocols, employing advanced information concealment techniques, encryption mechanisms, secure key management, and …

Unveiling The Shadows: The Influence Of Anonymity And Fake Accounts On Cyberbully Intention In Social Media, Muzdalini Malik, Hapini Awang, Nur Suhaili Mansor, Mohamad Fadli Zolkipli, Khuzairi Mohd Zaini, Abdulrazak F. Shahatha Al-Mashhadani

Iraqi Journal for Computer Science and Mathematics

Cyberbullying has arisen as a prevalent and worrying issue in the digital age, substantially influencing the well-being and mental health of social media users. Previous studies have identified several factors and theories of cyberbullying. Still more in-depth research is required to understand the key factors influencing cyberbullying intention in social media. This study aims to identify the factors influencing cyberbullying intention in social media and examine the moderating effect of fake accounts on cyberbullying intention. An extensive literature review has been conducted to examine the gaps in existing studies on cyberbullying intention. As a result, this study uses the Theory …

Unpacking Bias, Accountability, And Ethical Practices In Ai, Manya Chandra, Micol Hebron

Student Scholar Symposium Abstracts and Posters

This study is based on understanding how text-to-image generative AI platforms perpetuate biases such as racism and sexism and decoding how this bias is programmed within large language models and datasets. In this study, the results of generative AI are analyzed through the lens of affect and affect theory, as they are applied to investigate the machine learning and computer theory behind generative AI algorithms. The purpose of the study is to explain why generative AI is biased and whether this bias is generated due to current trends or to deficits and biases within the database that it draws information …

Energy Optimization In Wireless Sensor Networks: A Review, Zahraa Hammodi, Ahmed Al Hilli, Mohanad Al-Ibadi

Iraqi Journal for Computer Science and Mathematics

The use of wireless sensor networks (WSNs) has become an inevitably necessary for a smart world, such as smart cities and environmental fields. WSN consists of hundreds or even thousands of sensor nodes that have the ability to sense physical conditions from the target field, and also consists of a device that acts as a link between the sensor nodes and the base station (BS) called cluster head (CH). In the recent years, researchers have become interested in optimizing the energy efficiency of the WSNs due to the limited and non-replenish energy sources of their sensor nodes. In this paper, …

The Impact Of Student Engagement Activities On Future Climate Change Adaptation: The Case Of Student Simulation Models, Bassel Mostafa Elkalaf

Future Journal of Social Science

This paper explores the critical role of student engagement in addressing the growing challenges of climate change, with a focus on the Model United Nations (MUN) as a case study. As climate-related security threats increase globally, educational platforms that prepare youth for effective leadership in climate politics are more essential than ever. MUN, a widely practiced student activity simulating global policy-making, provides a valuable opportunity for students to deepen their understanding of the interconnectedness between climate change, peace, and security. By participating in MUN simulations, students engage in debates, develop innovative solutions, and practice diplomatic skills, all while exploring the …

Designing An Advanced Gui For A Laser Harp, Matthew Moran

2024 Fall Honors Capstone Projects - Archive

This project presents the design and development of a laser harp, an innovative digital instrument that combines music and technology to inspire interest in STEM education. The harp uses laser beams and phototransistors to simulate the strings of a traditional harp, producing sound when the beams are interrupted. The primary focus of the honors section of this work is a custom-built software interface developed with a graphical user interface (GUI) that allows users to easily adjust settings like note range, volume, and the central part of the show, looping notes. The GUI is designed to be intuitive, making it easy …

Quantum Visual Feature Encoding Revisited, Xuan-Bac Nguyen, Hoang-Quan Nguyen, Hugh Churchill, Samee U. Khan, Khoa Luu

Computer Science and Computer Engineering Faculty Publications and Presentations

Although quantum machine learning has been introduced for a while, its applications in computer vision are still limited. This paper, therefore, revisits the quantum visual encoding strategies, the initial step in quantum machine learning. Investigating the root cause, we uncover that the existing quantum encoding design fails to ensure information preservation of the visual features after the encoding process, thus complicating the learning process of the quantum machine learning models. In particular, the problem, termed the “Quantum Information Gap” (QIG), leads to an information gap between classical and corresponding quantum features. We provide theoretical proof and practical examples with visualization …

Protocol Transformations Across Osi Network Stack Layers For Attack, Evasion, And Defense, Nathan Tusing

All Dissertations

Network endpoints frequently contend with errors and deviations within protocols. Many factors account for these deviations including noise, tampering, and algorithm implementations. Intermediate nodes are expected to modify instantiated protocols and not guarantee correctness. This ability to modify traffic enables all sides of network security to alter security and performance properties of protocols, and we define this intermediary modification of an instantiated protocol as a transformation. Protocol transformations traverse layers of the OSI reference model and changes a protocol's time series byte sequence. Within this thesis, we show that this framework applies to multiple domains and protocols. Common examples of …

Not All Samples Are Created Equal: Task-Aware Informative Sampling And Adaptive Inference For Efficient Edge Ai, Rebati Gaire

School of Computing: Dissertations, Theses, and Student Research

The rapid proliferation of Internet of Things (IoT) devices has resulted in an unprecedented influx of data generated at the edge by billions of sensors. Traditional approaches relying on cloud-based processing are increasingly inadequate due to constraints in bandwidth, latency, and privacy. Edge computing has emerged as a transformative paradigm, enabling real-time data processing and decision-making by decentralizing computation to the edge. While the integration of deep learning into edge environments—termed edge intelligence—promises autonomous and personalized operations, it is hindered by challenges such as limited computational resources, energy constraints, and data redundancies.

This thesis addresses these challenges by presenting three …

Using Symbolic Execution To Analyze The Hardware Tcp Protocol, Nianhang Hu

School of Computing: Dissertations, Theses, and Student Research

As the demand for high performance and flexible networking capabilities increases, the shift from software to hardware implementations of stateful networking functions (such as TCP) is becoming increasingly important. This transition not only enhances processing efficiency in modern networking environments where data transmission rates are rising, but it also reduces the inherent CPU overhead found in software implementations, allowing hardware devices to handle network traffic more efficiently. However, validating the correctness of these hardware designs poses significant challenges due to the complex timing requirements and the vast input space associated with packet-level properties.

The verification of packet-level properties requires coverage …

Autism Spectrum Disorder, Vidhya Lakshmi Jeevarathinam

Electronic Theses, Projects, and Dissertations

Autism Spectrum Disorder (ASD) diagnosis requires an integrative approach that combines behavioral, biomedical, and computational methodologies for enhanced accuracy. This study introduces a comprehensive framework that employs machine learning (ML) and deep learning (DL) techniques alongside linear regression to model relationships between behavioral traits, biomedical markers, and ASD likelihood. Behavioral inputs, such as social interaction patterns, repetitive behaviors, and communication characteristics, are analyzed using linear regression to identify significant predictors of ASD. Simultaneously, a Convolutional Neural Network (CNN) is trained on image datasets to detect visual cues, such as facial expressions, associated with ASD. Advanced techniques, including transfer learning and …

Basic Safety Message Generation Through A Video-Based Analytics For Potential Safety Application, Abyad Enan

All Theses

With the advancement of modern artificial intelligence techniques, computer vision can play a vital role in enhancing roadway safety by reducing the risk of imminent collisions. To do so, a vision-based safety application is required, where a roadside camera can monitor the roadway traffic and predict potential risks of crashes in real-time. If any risky situation or behavior is observed that may lead to a crash, then a safety application can send warnings to the vehicles at risk. For vision-based safety applications on a roadway section, it is important to accurately monitor each vehicle’s location, speed, acceleration, heading direction, etc. …

Application Of Lossy And Lossless Compression To Dicom Files, Yizhe Yang

All Theses

The Digital Imaging and Communications in Medicine (DICOM) standard is widely utilized for the management, storage, and transfer of medical images. However, the substantial file sizes associated with DICOM data present challenges in terms of storage and data transmission. Data reduction techniques help address these challenges by minimizing the size of the data while preserving its integrity. This thesis examines various compression methods aimed at reducing the size of DICOM files. We evaluate five lossless compressors and four lossy compressors on DICOM data to compare and assess their performance. Through an analysis of each compressor’s compression efficiency and resulting image …