Computer Engineering Commons^™

V2i-Based Adaptive Collision Avoidance For Safety And Traffic Efficiency, Vaishnavi Balambeed

Dissertations, Master's Theses and Master's Reports

To leverage the growing communication and connectivity among modern vehicles, Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) systems are increasingly being used to implement active safety applications. However, current research often overlooks the impact of algorithms such as collision avoidance on traffic flow efficiency. This work investigates the adaptation of a collision avoidance algorithm implemented in V2I to incorporate a variable time headway and spacing control strategy. The proposed approach aims to maintain higher average speeds among vehicles, lower individual vehicle’s waiting, and travel times in the vicinity of the infrastructural unit while simultaneously avoiding collisions; thereby enhancing both safety and traffic …

Enhancing Privacy While Revealing Vulnerabilities: Strategies For Adaptation, Optimization, And Model Extraction, Madhureeta Das

Dissertations, Master's Theses and Master's Reports

In the evolving landscape of machine learning and artificial intelligence, this dissertation presents a series of innovative contributions spanning several critical areas: embracing semi-supervised domain adaptation for secure knowledge transfer, enhancing the model performance of tiny models, and executing model stealing attacks via diversified prompts. The overarching goal is to enhance the performance, scalability, and security of AI models across various applications.

The first research focus is on semi-supervised domain adaptation within federated learning frameworks. By leveraging semi-supervised learning techniques, this work addresses the challenge of adapting models trained on a source domain to perform effectively on a target domain …

Specification And Implementation Of Arm Isa Using Adl, Jonathan A. Rabideau

Dissertations, Master's Theses and Master's Reports

In this project, we implement a specification of ARM ISA using the ADL system. Current progress includes 79% of planned instructions, 79% of which are complete for our purposes, and also includes components such as a proxy kernel and a temporary preprocessor. Simple programs compiled directly from gcc can already be properly assembled and simulated using the tools generated by ADL. Once the specification is complete, we can integrate it with other components for testing ideas and theories. This report covers our progress and future plans regarding this project, including some background material and problem solutions.

Implementing Associative Learning Using Neuromorphic Robot, Vinay Kumar Pillalamarri

Dissertations, Master's Theses and Master's Reports

Associative learning, a key cognitive process seen across the animal kingdom, enables organisms to form connections between stimuli and adapt their behaviors based on past experiences. A particularly powerful example is fear conditioning, where animals learn to associate a neutral stimulus with an aversive one, allowing them to predict and avoid potential threats. Inspired by this mechanism, this project implements associative learning on an unmanned ground vehicle (UGV) to develop adaptive behavior through neuromorphic principles. Utilizing Nengo for neural modeling, the UGV learns to associate visual (red color) and tactile (vibration) stimuli through Hebbian learning, a biologically inspired synaptic adaptation …

Leveraging Large Language Models For Enhancing Well-Being In The Digital Age, Xiaobo Guo

Dartmouth College Ph.D Dissertations

The 21st century has seen dramatic shifts in human interactions with information, peers, and the environment, primarily driven by the proliferation of online platforms and social media. These advancements offer more access to information and global connectivity, but also present challenges such as information overload, misinformation, online harms, and biased reporting that can negatively impact user well-being. This thesis examines the role of Large Language Models (LLMs) — advanced forms of artificial intelligence that understand and generate human-like text — in enhancing well-being in the digital age. The study begins by exploring the potential of LLMs to detect early signs …

An Fpga-Based Eit System For Deep Space Medical Imaging, Kendall R. Farnham

Dartmouth College Ph.D Dissertations

Dangers associated with high radiation and microgravity exposure in space are critical challenges inhibiting us from exploring deep space and pursuing long-duration missions, as current medical systems are unable to monitor, diagnose, or treat tissue injury within physical spacecraft constraints and communication limits. Ultrasound (US) is the current imaging system used on the International Space Station, but this technology relies on telemedical support (or onboard artificial intelligence/autonomous capabilities) for both operation and diagnosis, posing challenges for crews isolated in deep space. Electrical impedance tomography (EIT) is a non-invasive, non-ionizing technology that produces images of the electrical properties of tissues and …

Arduino-Based High-Frequency Signal Data Acquisition For Learning Media On Antenna And Wave Propagation Practices, Eko Marpanaji, Masduki Zakarijah, Nikko Aji Bayu Nugraha

Elinvo (Electronics, Informatics, and Vocational Education)

This paper discusses the research results on the development of learning media and the results of the feasibility test for the learning process. This study aims to: (1) obtain the design and prototype of Arduino-based high-frequency signal data acquisition learning media; (2) find out the level of feasibility of learning media that has been made for the learning process of Antenna Practice and Wave Propagation courses. The research model uses Research and Development with the ADDIE development method. The research stages in the ADDIE method are Analyze, Design, Develop, Implement, and Evaluate. The research began with the development of learning …

Gen-Acceleration: Pioneering Work For Hardware Accelerator Generation Using Large Language Models, Durga Lakshmi Venkata Deepak Vungarala

Theses

Optimizing computational power is critical in the age of data-intensive applications and Artificial Intelligence (AI)/Machine Learning (ML). While facing challenging bottlenecks, conventional Von-Neumann architecture with implementing such huge tasks looks seemingly impossible. Hardware Accelerators are critical in efficiently deploying these technologies and have been vastly explored in edge devices. This study explores a state-of-the-art hardware accelerator; Gemmini is studied; we leveraged the open-sourced tool. Furthermore, we developed a Hardware Accelerator in the study we compared with the Non-Von-Neumann architecture. Gemmini is renowned for efficient matrix multiplication, but configuring it for specific tasks requires manual effort and expertise. We propose implementing …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Development Of Several Typical Virtual Reality Fusion Technologies, Qiqi Feng, Zhiming Dong, Wencheng Peng, Yi Dai, Bingshan Si

Journal of System Simulation

Abstract: Virtual reality fusion can realize the two-way interaction, mapping and linkage between virtual world and physical world, which attracts the attention of countries in the world. In order to sort out and make statistics on concept connotation, academic status and application of the related new technologies, digital twin, cyber-physical systems, metaverse and live-virtual-constructive simulation are taken as representatives. The comparison on the development process, functional characteristics, target trends, etc. is carried out.

Data Simulation Testing Framework For Complex Process Equipment Software, Jinkun Zhang, Longfei Shi, Chi Hu, Hao Zhang, Yonghui Yang

Journal of System Simulation

Abstract: Due to the complex task, tight coupling, strict timing, and a large amount of interchange data, the technical threshold of automated testing of bus communication equipment software is high, and the implementation is difficult. The ideas of data-driven testing and keyword-driven testing are introduced, and a data simulation testing framework is proposed. Configuration rules are formulated and implemented in the framework. Testers can simulate peripheral data for complex process equipment software and implement automated testing by only focusing on the task analysis, and configuring interchange data and keywords. There is no need to develop test scripts, which reduces the …

Urban Uav Path Planning Based On Improved Beetle Search Algorithm, Qingqing Yang, Minyi Deng, Yi Peng

Journal of System Simulation

Abstract: An improved SABAS is proposed to improve the safety and path smoothing of UAV missions in urban multi-obstacle environments and to obtain the shortest path. The algorithm no longer completely depends on the difference of odor concentration between the left and the right tentacles of beetle when exploring the path for position update. Instead, it makes full use of the strong searching ability of BAS algorithm, and introduces the annealing algorithm to add the neighborhood position solution of the next position, and finally selects the next best position from the neighborhood position solution. Metropolis criterion of annealing algorithm is …

Reliable Emergency Rescue Model Of Uavs Based On Blockchain, Mengyao Du, Kai Xu, Miao Zhang, Xiang Fu, Quanjun Yin

Journal of System Simulation

Abstract: Natural disasters may unpredictably disrupt ground communication infrastructure and transportation systems, and UAVs emergency response can deal with such uncertainties and highly dynamic scenarios. Aiming at the robustness requirements of decentralized rescue systems. UAV emergency rescue chain (UERChain) based on blockchain technology is proposed. By deploying UAV backbone nodes within a layered local network, the smart contracts for managing reputation considering UAV social relationships are designed. The blockchain is employed as a trust mechanism to realize the trustworthy interactions among distributed UAVs. Experimental results show that, UERChain has higher robustness, and within controllable resource constraints, the reputation management and …

Unrelated Parallel Machine Scheduling With Additional Resource And Learning Effect, Youlian Zheng, Deming Lei

Journal of System Simulation

Abstract: To solve unrelated parallel machine scheduling problem(UPMSP) with additional resource and learning effect, a dynamical artificial bee colony(DABC) algorithm is proposed to minimize the makespan. A new representation and decoding process is given and two initial bee swarms are constructed. A swarm evaluation method is applied to dynamically decide employed bee swarms and onlooker bee swarms. Employed bee phase and onlooker bee phase are implemented in different ways to increase exploration ability. The experimental results show that the new strategies of DABC are effective and reasonable, and can obtain results with better convergence, average value and stability, which d …

Research On Network Public Opinion Propagation Model Of Major Epidemics Under Cross-Infection Of Double Emotions, Yaming Zhang, Yanyuan Su, Guiru Zhao, Xiaoyu Guo

Journal of System Simulation

Abstract: Major epidemics provoke a variety of netizens' emotions. To some degree, the interaction of netizens' intense emotions determine the development direction of public opinion. Considering the complexity and dual emotional contagion, the impact of emotional factors in network public opinion is quantified to three dimensions indicators, emotional enhancement, differences and conversion rates. SIPINR public opinion propagation model is constructed. The equilibrium points and the transmission threshold are estimated and the stability is proved. The law of network public opinion propagation during major epidemics is revealed through numerical simulation. The results show that the dual emotional contagion would lead to …

Automatic Target Recognition Of Substation 3d Scene For Digital Twin, Qian Tu, Jun Li, Dongliang Fan, Qi Kong, Jie Shen

Journal of System Simulation

Abstract: In order to improve the accuracy of automatic target recognition and promote the effect on substation operation and maintenance, automatic target recognition of substation 3D scene for digital twin is proposed. The automatic target recognition model for the three dimensional scene of the substation is constructed. The perception module of the model is used to collect the real-time status data of substation, and the communication module is used to transmit the data to digital twin modules. This module, based on the received data information, realizes the deep fusion and panoramic mapping of substation information through the knowledge base constructed …

Research On Digital Twin Data Modeling And Evaluation Method Of Automated Container Terminal, Guoxuan Xu, Daofang Chang, Jiaqi Li, Qiang Ling

Journal of System Simulation

Abstract: To make full use of the massive operation data of automated container terminals and further realize the digital and intelligent transformation of terminals driven by digital twin, a method for digital twin data modeling and effect verification and evaluation of automated container terminals is proposed. The application framework and operation mechanism based on digital twin are studied. Based on the data processing logic of digital twin framework, a method of terminal operation process evolution and dynamic data modeling based on digital twin is proposed. To verify whether the data could meet the effective operation of the digital twin, a …

Modeling And Simulation On Production Logistics Of Intelligent Workshop Manufacturing System Based On Efsm, Liuzhen Li, Chao Jin, Tingyu Lin, Yaoqin Zhu

Journal of System Simulation

Abstract: The production logistics mode of manufacturing industry is developing rapidly, on which the modeling and simulation can provide the decision support for the design, analysis and transformation of manufacturing system. A description of the entity elements in intelligent workshop manufacturing system is given according to the classification of "human machine material environment rule". A production and logistics componentized EFSM model is created on the basis of EFSM and componentized modeling ideas. The modeling process for multi-job production in smart shop and the component model instantiation methodology are elaborated. The simulation running through the automatic conversion of EFSM-DEVS model and …

Research And Development Of Simulation Training Platform For Multi-Agent Collaborative Decision-Making, Cheng Cheng, Zhijie Chen, Ziming Guo, Ni Li

Journal of System Simulation

Abstract: Reinforcement learning simulation platform can be an interactive and training environment for reinforcement learning. In order to make the simulation platform compatible with the multi-agent reinforcement learning algorithms and meet the needs of simulation in military field, the similar processes in multi-agent reinforcement learning algorithms are refined and a unified interface is designed to embed and verify different types of deep reinforcement learning algorithms on the simulation platform and to optimize the back-end service of the simulation platform to accelerate the training process of the algorithm model. The experimental results show that, by unifing the interface, the simulation platform …

Research On 3d Object Detection Method With Cross-Module Attention, Renjie Xu, Xiaoming Zhang, Chen Wang, Peng Wu

Journal of System Simulation

Abstract: To address the issue of feature loss that occurs during the extraction and transmission of target features in 3D object detection tasks using point cloud data, this study proposes an object detection method based on cross-module attention. This method incorporates a channel attention module and a spatial attention module to enhance the crucial feature information. Through feature transformation, the features from different stages of the attention module are connected to mitigate the loss of features during the extraction and transmission process. To tackle the problem of inadequate detection performance in target detection networks for objects of different scales, a …