Computer Sciences Commons^™

Ground Robot Relocation Method Based On Uav Point Cloud Map, Hongzhi Huang, Kai Yan, Changfeng Liu, Jianwen Wang, Bin Luo

Journal of System Simulation

Abstract: In response to the challenge of relocalization in air-ground collaborative systems without the support of Global Navigation Satellite System (GNSS), and the associated issues of insufficient accuracy, a coarse-to-fine relocalization algorithm based on a three-dimensional point cloud map is proposed. The algorithm eliminates the influence of invalid point clouds from the sky and ground through index filtering, performs coarse localization by extracting global features from the point cloud and applying truncated least squares estimation, and then employs voxel-based iterative closest point (ICP) for precise optimization to obtain the more accurate localization results. A ground robot localization and autonomous navigation …

Research On Digital Twin Technology Of Coal Mine Tunneling Machine System, Xingwang Cai, Yaoqiang Pei, Jihua Yang, Ruifeng Pang

Journal of System Simulation

Abstract: Aiming at the problems in coal mine tunneling operations, including complex geological structures, harsh on-site conditions, low automation of excavation equipment, and frequent safety incidents, a digital twin solution is proposed. PLC as hardware core, MQTT protocol, and EMQX as foundation, through the integration of IoT, internet, digital twins, and virtual reality technologies, the mapping rules for parameter matrices and a fault cause analysis table are established, which realize the functions such as data collection, processing during excavation, data mapping between equipment and twin models, data storage, process simulation, remote control, intelligent fault detection, and early warning, and significantly …

Research On Application Of Intelligent Indication Signs In Improving Efficiency Of Crowd Evacuation, Heng Niu, Yanbin Han, Liang Li, Weilin Chen, Sijie Niu, Qingtao Hou

Journal of System Simulation

Abstract: Aiming at the low emergency evacuation efficiency of dense crowds in confined spaces, a crowd evacuation guidance model based on intelligent signs is constructed in this paper. A balanced congestion strategy to optimize the signs layout and a social network search-based sign guidance weights optimization method are proposed to improve evacuation efficiency. Simulation experiments show that the optimized intelligent sign layout can effectively alleviate the local congestion during evacuation and reduce the time consumption of pedestrians caused by congestion. The optimized intelligent sign guidance weights can further balance the utilization rate of exits, which is conducive to making full …

Garage Agv Path Planning And Simulation Based On Improved Dwa, Zongfang Ma, Linxuan Zhang, Lin Song, Jia Wang

Journal of System Simulation

Abstract: Aiming at the path planning and real-time obstacle avoidance of AGV in complex path environment of intelligent garage, an improved hybrid algorithm combining ant colony algorithm and dynamic window method is proposed. In the global planning, the adaptive adjustment of pheromone volatilization coefficient and the fusion of angle parameters are introduced to establish the garage direction pheromone matrix to increase the guidance ability of target points, expand the direction selectivity of ants. In the local planning, the improved DWA of the obstacle distance evaluation subfunction based on elliptic equation is designed. By extracting the global path node of the …

Adaptive Tracking Control For Omnidirectional Vehicle Based On Characteristic Modeling, Lei Cheng, Haoyou Wang, Xinjie Chen

Journal of System Simulation

Abstract: Aiming at the stable and high-precision tracking control of omnidirectional mobile vehicles affected by their own characteristics and external disturbances, an adaptive tracking control approach for omnidirectional vehicles based on characteristic modeling is designed. The characteristic model is established by integrating the model properties into the characteristic parameters, and the characteristic parameters are estimated online by using the projected gradient method. A full coefficient adaptive control law based on the characteristic model is designed, and the stability of the proposed control method is analyzed by using Lyapunov theory. The effectiveness and rationality of the proposed adaptive control scheme are …

Modeling Method Of Blue Army Warship Formation Air Defense Command And Control For System-Of-Systems Simulation, Shikang Chen, Zhimin Wang, Biao Liang, Kunren Gu, Keman Song, Yuan Gao

Journal of System Simulation

Abstract: The command and control of warship formation air defense is a key link for the blue army's sea to air combat tasks and the modeling of air defense for warship formation is an important component of simulation modeling of blue army's maritime combat system. Based on the background of system-of-systems simulation, the air defense command and control modeling for blue army is designed. Through a modular modeling method, functional module including asset management and plan, unified situation generation, command decision are designed. According to blue army's command and control logic, these modules are integrated and the air defense command …

Search Technology For Aircraft Debris Integrating Data Augmentation And Deep Learning Algorithm, Zhe Yang, Yinghan Cui, Lingxi Guo, Jiaxin Li, Xusheng Wu

Journal of System Simulation

Abstract: The reliable recovery of aircraft debris is of great significance for the complete acquisition of flight test data and the subsequent research and development of models. To ensure the safety of flight tests,the landing area of aircraft experiments is generally an unmanned area,and the actual landing point of the aircraft often deviates from the theoretical landing point. The characteristics of the debris target are complex and the dispersion area is large, making it difficult to search for aircraft debris solely by manpower. Aiming at the difficult problem of aircraft debris recovery in the landing area, through on UAV platforms …

Two-Level Optimal Dispatch Of Power System Based On Load-Storage Carbon Flow Model, Yang Yu, Yuxing Xia, Wentao Lu, Mai Liu, Shixu Gao, Dongyang Chen

Journal of System Simulation

Abstract: In order to reduce the output of high energy consuming units on the power generation side, increase the absorption capacity of wind power, and consider the flexible resource allocation such as load and energy storage, a two-level economic low-carbon optimal scheduling method for power systems based on a carbon storage and discharge model is proposed. Based on the carbon emission flow theory of power system, a model for load and energy storage equipment is established; A demand response model based on the electricity carbon coupling price is established on the load side, and in view of the limitation on …

Research On Flexible Operational Optimization Of Cchp System Based On Intelligent Fusion Algorithm, Zhe Bao, Xiaofang Zhang, Wei Li, Ye Xu, Xu Wang

Journal of System Simulation

Abstract: To further improve the accuracy of gas turbine simulation models, based on the construction of a gas turbine mechanism simulation model and BP simulation model, through model substitution technology and BP neural network algorithm three intelligent fusion simulation models for gas turbines, and two intelligent fusion simulation models for parallel gas turbines are constructed respectively as well as the combination of, by comparing the simulated results of the above models with the actual operating data, the simulation model with the best performance was selected. Using the intelligent fusion simulation model of the gas turbine as the output constraint, a …

Chaotic-Encode Quantum Pso Algorithm For Flexible Job-Shop Scheduling Problem, Yuanxing Xu, Mengjian Zhang, Deguang Wang

Journal of System Simulation

Abstract: To solve the flexible job-shop scheduling problem (FJSP), a chaotic-encode quantum PSO (CQPSO) algorithm is proposed. Aiming at the premature convergence of particles to local optimum in standard QPSO, the methods for computing the adaptive contraction-expansion coefficient and mean best position using fitness values of associated particles are proposed to improve the global search ability of QPSO. Through chaotic boundary variation strategy, the probability of a large number of particles gathering at the boundary is reduced and the population diversity is increased to enhance the ability of searching the optimal solution. According to the iterative property of QPSO, a …

Multi-Strategy Partheno-Genetic Algorithm Based On Dynamic Reduction Mechanism For Solving Cvrp Problem, Jiajun Chen, Dailun Tan

Journal of System Simulation

Abstract: Aiming at the problems of premature, slow convergence and low accuracy of traditional genetic algorithm in solving capacitated vehicle routing problem,a multi-strategy partheno-genetic algorithm based on dynamic reduction mechanism is proposed. The algorithm divides the optimization space based on similar individuals, and uses simulated annealing criterion to eliminate or update the lowest category subspace, which constitutes the reduction and movement mechanism of the optimization space. Based on parthenogenetic algorithm,a variety of genetic evolution strategies including intra-group, inter-group, global search, disturbance and jump strategy are designed Based on the three penalty factors of individual development, population evolution and overall convergence, …

Unmanned Vehicle Path Planning And Tracking Control Based On Improved Artificial Potential Field Method, Minghao Guo, Peng Ji, Haiwei Huang

Journal of System Simulation

Abstract: A path planning algorithm based on improved artificial potential field method and a tracking control strategy based on model predictive controller are proposed for the unmanned vehicle avoiding dynamic obstacles in the complex scene of lane changing and overtaking. The theory of safety ellipse and the concept of prediction distance are introduced to adjust the influence region of potential field. By adding velocity potential field to change potential field function, the problem of vehicle avoiding dynamic obstacles is solved. Based on the linear three-degree-of-freedom vehicle dynamics model, a model prediction controller including potential field environment is established. The effectiveness …

Path Following Control And Simulation Analysis Of Multi-Articulated Vehicles, Yu Zhao, Caijin Yang, Tanming Wang, Jing Xu, Shuai Zhou

Journal of System Simulation

Abstract: The structure of multi-articulated vehicle body limits the flexibility of the vehicle and causes the deviation of the rear vehicle. Taking the ideal articulation angle as the control target, a feedforward plus feedback path following control method is proposed, which realizes the precise path following of rear vehicle bodies by minimizing the deviation between the ideal articulation angle and the actual articulation angle. According to the geometric position relationship between the vehicle and the desired path, the traditional calculation method of the ideal articulation angle is improved from two perspectives of application range and error accumulation. Based on the …

Improved Foggy Pedestrian And Vehicle Detection Algorithm Based On Yolov5, Tong Su, Ying Wang, Qiyang Deng, Zhaobin Li

Journal of System Simulation

Abstract: Due to the poor environment perception of car in bad weather, the detection ability on dynamic targets is significantly reduced, and thus the problems such as low accuracy and poor robustness of the deep learning-based target detection network will occur when detecting pedestrians and vehicles in foggy days. A YOLOv5-SGE foggy detection network is proposed on the basis of the combination of image dehazing DehazeNet and the improved YOLOv5. The adaptive calculation of anchor frame is realized by canceling the initial anchor frame of YOLOv5, and the anchor frame suitable for the current dataset is generated. A three-dimensional weighted …

Peer-To-Peer Energy-Carbon Management Method Of Multiple Integrated Energy Systems Considering Multi-Agent Interaction Strategy, Yudong Wang, Junjie Hu

Journal of System Simulation

Abstract: To explore a new energy management model of P2P transaction of electricity, heat and carbon among IES with the participation of ESP, a P2P energy-carbon management method of IES considering multi-agent interaction strategy is proposed. A two-layer energy management framework with the multiagent participation of involving ESP and IES is established. A two-layer electricity-heat-carbon energy management model is constructed in which the upper model is constructed based on reinforcement learning framework to optimize the energy management strategy between ESP and IES cooperative alliance and the lower model is based on Nash negotiation game theory to optimize the cooperative operation …

A Method For Battlefield Situation Information Ontology Construction Based On Top-Down And Bottom-Up Integration, Cong Zhou, Sihang Zhou, Jian Huang, Dong Wang

Journal of System Simulation

Abstract: The construction of the unified expression model of battlefield situational information is challenging due to the complexity of data sources and the significant differences in data structures and expression methods. Ontologies, as semantic conceptual models, are often used to describe concepts, relationships, and attributes within knowledge domains. An ontology construction method for the battlefield situational information domain based on a top-down and bottom-top integration is proposed. The top-down method is used to construct the upper ontology, in which a conceptual hierarchy model with a clear top-down structure is designed to establish the hierarchical relationships and semantic associations. A bottom-up …

Ai And Future-Making: Design, Biases, And Human-Plant Interactions, Maliheh Ghajargar

Art Faculty Articles and Research

Design researchers and practitioners are turning to generative AI (genAI) to support activities such as ideation and concept development in pursuit of preferred futures. At the same time, genAI is known to have biases, which prompts questions about how these biases might adversely affect design practices. In the domain of sustainable HCI, with its recent trends in human-nature interactions and more-than-human design, the question can be further refined into whether and how genAI biases might perpetuate anthropocentric biases that these practices are increasingly seeking to confront. In the present research, we conducted three workshops, focusing on genAI for human-plant interactions; …

"The Words We Do Not Yet Have." A Creative Inquiry Into Human-Plant Relationships, Maliheh Ghajargar

Art Faculty Articles and Research

Climate change, loss of plant biodiversity, and ocean pollution signal the drastic changes in our ecology that call us to attend to the needs of more than human forms of life on Earth. Sustainable design and HCI research are responding to this call by offering methods and approaches to design more sustainable products and systems and recently, more than human design is building momentum. This agenda seeks to reform traditional design processes by decentering the creative agency of the dominant socio-economical group of humans and foregrounding those of diverse Others. In this paper, I focus on plants as a nonhuman …

Predictive Residual Neural Networks For Optical Trapping Of Small Particles, Nasim Mohammadi Estrakhri, Ponthea Zahraii, Saman Kashanchi, Nooshin M. Estakhri

Engineering Faculty Articles and Research

Optical tweezers provide a non-contact method to trap, move, and manipulate micro- and nano-sized objects. Using properly designed dielectric and plasmonic nanostructure configurations, optical tweezers have been tailored to create stable and precise trapping for nanoscale objects. Recent advances in numerical optimization techniques allow further enhancement in nanoscale optical traps through inverse optimization of such configurations. One of the main challenges in such optimization approaches is the time-consuming nature of full-wave simulation of nanostructures and postprocessing steps to extract optical forces. To address this challenge, we introduce a surrogate solver based on residual neural networks that can accurately predict the …

Instructional Systems Design: The Diffusion And Adoption Of Technology: (Volume 2), Cassandra Celaya (Author), Pamela J. Downing (Author), Jessica Shifflett (Author), Debbie Gdula (Author), Tracie Barr (Author), Miguel Ramlatchan (Author & Editor)

University Administration Bookshelf

Instructional designers, instructional systems designers, and other educational technologists are, by their nature, innovators. These professionals apply and extend the applied science of learning, systems, communication, and instructional design theory to help students learn. Technology in some capacity is used to make the connections between subject matter experts, teachers, instructors, and their learners. It is common for instructional designers to seek new tools, techniques, and innovations for the improvement of learning, access, quality, and student satisfaction. However, the adoption and diffusion of new educational technology and innovation is a complex process that depends on many variables. Understanding these processes and …

Bi-Directional Transformers Vs. Word2vec: Discovering Vulnerabilities In Lifted Compiled Code, Gary Mccully, John Hastings, Shengjie Xu, Adam Fortier

Research & Publications

Detecting vulnerabilities within compiled binaries is challenging due to lost high-level code structures and other factors such as architectural dependencies, compilers, and optimization options. To address these obstacles, this research explores vulnerability detection using natural language processing (NLP) embedding techniques with word2vec, BERT, and RoBERTa to learn semantics from intermediate representation (LLVM IR) code. Long short-term memory (LSTM) neural networks were trained on embeddings from encoders created using approximately 48k LLVM functions from the Juliet dataset. This study is pioneering in its comparison of word2vec models with multiple bidirectional transformers (BERT, RoBERTa) embeddings built using LLVM code to train neural …

Using Machine Learning To Predict State Compliance With International Legal Obligations For Registration Of Space Objects: Comparative Performance Of Logistic Regression And Dense Neural Network Models, Jonathan K. Sawmiller

Student Publications

Approximately 12% of satellites and other objects launched into outer space have not been registered with the United Nations (UN) as required by international law. To predict whether States will register a launched space object and understand what factors influence a registration decision, data from a UN online index of space objects was used to train and select the best machine learning model. After preparation, the dataset had 1938 datapoints with 11 features, with categorical features simplified and converted to binary.

Multiple variations of classical logistic regression models were compared to multiple variations of dense neural network models. The best …

The Psychological Impacts Of Algorithmic And Ai-Driven Social Media On Teenagers: A Call To Action, Sunil Arora, Sahil Arora, John Hastings

Research & Publications

This study investigates the meta-issues surrounding social media, which, while theoretically designed to enhance social interactions and improve our social lives by facilitating the sharing of personal experiences and life events, often results in adverse psychological impacts. Our investigation reveals a paradoxical outcome: rather than fostering closer relationships and improving social lives, the algorithms and structures that underlie social media platforms inadvertently contribute to a profound psychological impact on individuals, influencing them in unforeseen ways. This phenomenon is particularly pronounced among teenagers, who are disproportionately affected by curated online personas, peer pressure to present a perfect digital image, and the …

Confronting The Reproducibility Crisis: A Case Study Of Challenges In Cybersecurity Ai, Richard H. Moulton, Gary A. Mccully, John D. Hastings

Research & Publications

In the rapidly evolving field of cybersecurity, ensuring the reproducibility of AI-driven research is critical to maintaining the reliability and integrity of security systems. This paper addresses the reproducibility crisis within the domain of adversarial robustness—a key area in AI-based cybersecurity that focuses on defending deep neural networks against malicious perturbations. Through a detailed case study, we attempt to validate results from prior work on certified robustness using the VeriGauge toolkit, revealing significant challenges due to software and hardware incompatibilities, version conflicts, and obsolescence. Our findings underscore the urgent need for standardized methodologies, containerization, and comprehensive documentation to ensure the …

Quantifying Ethics And Trust In Human-Ai Collaboration, Oliver Lane, Kevin Klave

College of Engineering Summer Undergraduate Research Program

As AI Chatbots continue to evolve in both prevalence and capability, their role in education is becoming increasingly prominent. With chatbots like ChatGPT becoming commonplace in higher education, there is an evident need to understand the ethics and trust dynamics of human-AI collaboration. This research contributes to the ongoing discussion on AI in education, highlighting the importance of trust when utilizing AI in academic settings. By conducting an empirical analysis, this research seeks to quantify trust in human-AI collaboration in higher education with the aim of offering actionable items for higher education institutions to follow to promote ethical and responsible …

Fail Fast, Fail Small: Designing Resilient Systems For The Future Of Software Engineering, Jill Willard, James Hutson

Faculty Scholarship

The principles of "fail fast, fail small" have emerged as critical in modern software and system design. By planning for minor, manageable failures instead of catastrophic breakdowns, developers can ensure that systems degrade gracefully, maintaining functionality even when encountering issues. This article delves into strategies for designing resilient systems, beginning with the concept of slow degradation and distributed systems that prioritize core functions while allowing non-critical components to fail without significant user impact. The Netflix recommendation engine serves as a prime example of a system that continues to operate under failure conditions. Chaos engineering, a proactive methodology for stress-testing system …

Bibliography For "Ai: The Next Chapter Display", Arianna Tillman, Isabella Piechota

Library Displays and Bibliographies

A bibliography created to support a display about artificial intelligence at the Leatherby Libraries during Fall 2024 at the Leatherby Libraries at Chapman University.

Hisoma: A Hierarchical Multi-Agent Model Integrating Self-Organizing Neural Networks With Multi-Agent Deep Reinforcement Learning, Minghong Geng, Shubham Pateria, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Multi-agent deep reinforcement learning (MADRL) has shown remarkable advancements in the past decade. However, most current MADRL models focus on task-specific short-horizon problems involving a small number of agents, limiting their applicability to long-horizon planning in complex environments. Hierarchical multi-agent models offer a promising solution by organizing agents into different levels, effectively addressing tasks with varying planning horizons. However, these models often face constraints related to the number of agents or levels of hierarchies. This paper introduces HiSOMA, a novel hierarchical multi-agent model designed to handle long-horizon, multi-agent, multi-task decision-making problems. The top-level controller, FALCON, is modeled as a class …

Generative Ai In Software Engineering Must Be Human-Centered: The Copenhagen Manifesto, D. Russo, S. Van Berkel Baltes, Christoph Treude

Research Collection School Of Computing and Information Systems

The advent of Generative Artificial Intelligence—systems that can produce human-like content such as text, music, visual art, or source code—marks not only a significant leap for Artificial Intelligence (AI) but also a pivotal moment for software practitioners and researchers. The role of software engineering researchers and practitioners in adopting the technologies that shape our world is critical. Historically, the human aspects of developing software have been treated as secondary to more technical innovations. However, the emergence of Generative AI will simultaneously enhance human capabilities while surfacing complex ethical, social, legal, and technical challenges.While primarily aimed at software engineering (SE) researchers …

Retrofitting A Legacy Cutlery Washing Machine Using Computer Vision, Hua Leong Fwa

Research Collection School Of Computing and Information Systems

Industry 4.0, the digitalization of manufacturing promises to lead to lowered cost, efficient processes and even discovery of new business models. However, many of the enterprises have huge investments in legacy machines which are not 'smart'. In this study, we thus designed a cost-efficient solution to retrofit a legacy conveyor belt-based cutlery washing machine with a commodity web camera. We then applied computer vision (using both traditional image processing and deep learning techniques) to infer the speed and utilization of the machine. We detailed the algorithms that we designed for computing both speed andutilization. With the existing operational constraints of …