Computer Engineering Commons^™

Vr Force Feedback Gloves, Mark Wu, Claire Chen

Electrical Engineering

The goal of this project is to produce a manufacturing plan for a consumer VR glove. The total addressable market of VR is over 170 million global users as of 2022 (Kolmar , 2022) with a serviceable available market of 300,000 users on Meta’s own social platform (Heath, 2022). The targeted Quest 2 platform utilizes handheld controllers, which causes a lack of immersivity in social settings and gaming scenarios. One common use of the platform involves social platforms such as “Horizons” where users meet in a virtual world to interact; handheld controllers don’t allow users to shake hands, make finger …

An Interactive Ecosystem Simulator, Tong Zhou

Computer Science and Software Engineering

This project is about an ecosystem simulator game that allows players to manipulate the population size of the selected species and observe these species interact with each other. It focuses on reflecting the consequences of human intervention in the ecosystem and the difficulty of maintaining a balanced ecosystem. I’ve been astonished by how human intervention could easily crash the ecosystem and how difficult it could be to make up for our faults. And many people still hold the thought that we control the world and could determine the death or live of all other creatures as we like. However, the …

In-Situ Mechanical Tester, Andrrew Murach, Gustavo Marquez, Kosimo Tonn, Jake Vormbaum

Mechanical Engineering

Over the course of the 2022-23 Cal Poly SLO school year, a small tensile tester device was developed specifically for Dr. Long Wang to test thin film materials under a microscope and generate accurate force versus displacement graphs. A tensile tester was manufactured using purchased and machined components, electronics were consolidated in a separate box and connected, and a program and user interface were written to control the motion, provide custom inputs, and organize useful data for the researcher. Tests were conducted to compare the performance of the device to universal tensile testers available in the Composites lab. The device …

Wonder World, Liam M. Shaw, Briana Kuo

Computer Engineering

The main motivation for this project stems from a mutual lifelong love for video games, specifically sandbox games. These types of games, such as Mojang's Minecraft, ConcernedApe's Stardew Valley, and many more, have consistently provided us comfort in stressful times throughout our lives. Now, at the culmination of our undergraduate experience, the curriculum we have experienced throughout these past four years has provided us with the knowledge and resources that allows us to provide this same sense of comfort for others. Our game aims to encourage collaboration between two players through solving puzzles and minigames. In addition, our game seeks …

Contextually Dynamic Quest Generation Using In-Session Player Information In Mmorpg, Shangwei Lin

Master's Theses

Massively multiplayer online role-playing games (MMORPGs) are one of the most

popular genres in video games that combine massively multiplayer online genres with

role-playing gameplay. MMORPGs’ featured social interaction and forms of level pro-

gression through quest completion are the core for gaining players’ attention. Varied

and challenging quests play an essential part in retaining that attention. However,

well-crafted content takes much longer to develop with human efforts than it does to

consume, and the dominant procedural content generation models for quests suffer

from the drawback of being incompatible with dynamic world changes and the feeling

of repetition over time. …

Assessing The Resilience Of Mycorrhizal Networks Following Central Tree Removal, Deon Lillo

Master's Theses

Mycorrhizal networks (MNs), or the networks of fungal mycelia that connect plants to each other, are vital in contributing to the well-being of ecosystems. They not only assist in the transport of nutrients across an ecosystem, but also help protect an ecosystem from disease and adverse conditions. However, more research into these networks is needed and modelling these networks as graphs can help us achieve this. By applying centrality analysis and performing k-core partitioning on these networks, we are able to identify the trees that are most important and central to a MN and observe the effects of removing these …

Effects Of Concussion And Visuomotor Metrics On Nhl Performance: An Explainable Ai Approach, Michael T. Moschitto

Master's Theses

Cognitive motor integration (CMI), the simultaneous coordination between cerebral function and motor output, is known to deteriorate following a mild traumatic brain injury (mTBI). This thesis explores the relationship between mTBI, CMI, and the performance of elite athletes in the National Hockey League (NHL). The approach focuses on examining the predictive value of various supervised Machine Learning (ML) models with an emphasis on Explainable Artificial Intelligence (XAI) models. Since the ML solution is intended to complement human scouting decisions, we evaluate the experiments based on both interpretability and accuracy on a limited class imbalanced dataset. The contributions of this research …

Guest Editorial: Special Issue On Green Iot For Future Space–Air–Ground–Ocean-Integrated Networks And Applications, Bo Rong, Mohamed Cheriet, Jon Montalban, Lei Shu, Yi Qian

Department of Electrical and Computer Engineering: Faculty Publications

The Internet of Things (IoT) plays a critical role in enabling the seamless integration of disparate devices. Future IoT will rapidly expand its coverage to offer future worldwide omnipresent applications and services by merging communications in diverse spatial domains to build the space–air–ground–ocean-integrated network (SAGOI-Net). SAGOI-Net will include a significant number of battery-powered network nodes, such as satellites, unmanned vehicles, and underwater devices, due to the extremely vast geographic reach and dynamics in free space. Given the battery limitations, high-energy-efficiency communications and networking will be critical to the future system. Green SAGOI-Net seeks to not only bring ubiquitous connectivity to …

Mixed-Criticality Scheduling Using Reinforcement Learning, Omar Elseadawy

Theses and Dissertations

Mixed-criticality (MC) scheduling is necessary for many safety-critical real-time embedded systems, as a failure of high-criticality jobs could lead to fatal accidents. With the emergence of software technologies in software-defined vehicles in the automotive and avionics industries, studying Mixed-Critically (MC) systems is essential to their safety standards, similar to ISO26262. The real-time operation of MC systems makes it an inherently online problem, such that the scheduler is only aware of the jobs that are currently released at any point in time and has no knowledge of future jobs. Due to the overhead cost of preemption, this study focuses on enforcing …

Mathematical And Machine Learning Approaches For Classification Of Protein Secondary Structure Elements From Cα Coordinates, Ali Sekmen, Kamal Al Nasr, Bahadir Bilgin, Ahmet Bugra Koku, Christopher Jones

Computer Science Faculty Research

Determining Secondary Structure Elements (SSEs) for any protein is crucial as an intermediate step for experimental tertiary structure determination. SSEs are identified using popular tools such as DSSP and STRIDE. These tools use atomic information to locate hydrogen bonds to identify SSEs. When some spatial atomic details are missing, locating SSEs becomes a hinder. To address the problem, when some atomic information is missing, three approaches for classifying SSE types using Ca atoms in protein chains were developed: (1) a mathematical approach, (2) a deep learning approach, and (3) an ensemble of five machine learning models. The proposed methods were …

Using An Embedded System For A Quality Cup Of Coffee, Evan Powers, Joshua Stermer, Tsion Yohannes

2023 Symposium

Many coffee lovers spend up to $5 on a cup of coffee everyday. To save money one could make them at home, but a quality machine with PIDs start at $1000. Using an embedded system one could spend less than $50 and a few hours implement PIDs into an existing $400 machine that will last a lifetime. microcontroller. Learning C language combined with hardware implementation applied to cheap and simple everyday objects can improve everyday quality of life and save money.

This is challenging because we have to incorporate the additional circuitry into a pre established circuit with limited space, …

Sentiment Analysis Of Text And Emoji Data For Twitter Network, Paramita Dey, Soumya Dey

Al-Bahir

Twitter is a social media platform where users can post, read, and interact with 'tweets'. Third party like corporate organization can take advantage of this huge information by collecting data about their customers' opinions. The use of emoticons on social media and the emotions expressed through them are the subjects of this research paper. The purpose of this paper is to present a model for analyzing emotional responses to real-life Twitter data. The proposed model is based on supervised machine learning algorithms and data on has been collected through crawler “TWEEPY” for empirical analysis. Collected data is pre-processed, pruned and …

Classification Of Arabic Social Media Texts Based On A Deep Learning Multi-Tasks Model, Ali A. Jalil, Ahmed H. Aliwy

Al-Bahir

The proliferation of social networking sites and their user base has led to an exponential increase in the amount of data generated on a daily basis. Textual content is one type of data that is commonly found on these platforms, and it has been shown to have a significant impact on decision-making processes at the individual, group, and national levels. One of the most important and largest part of this data are the texts that express human intentions, feelings and condition. Understanding these texts is one of the biggest challenges that facing data analysis. It is the backbone for understanding …

A Study On Image Processing Techniques And Deep Learning Techniques For Insect Identification, Vinita Abhishek Gupta, M.V. Padmavati, Ravi R. Saxena, Pawan Kumar Patnaik, Raunak Kumar Tamrakar

Karbala International Journal of Modern Science

Automatic identification of insects and diseases has attracted researchers for the last few years. Researchers have suggested several algorithms to get around the problems of manually identifying insects and pests. Image processing techniques and deep convolution neural networks can overcome the challenges of manual insect identification and classification. This work focused on optimizing and assessing deep convolutional neural networks for insect identification. AlexNet, MobileNetv2, ResNet-50, ResNet-101, GoogleNet, InceptionV3, SqueezeNet, ShuffleNet, DenseNet201, VGG-16 and VGG-19 are the architectures evaluated on three different datasets. In our experiments, DenseNet 201 performed well with the highest test accuracy. Regarding training time, AlexNet performed well, …

Deep Reinforcement Learning-Based Control Strategy For Boost Converter, Yuxuan Dai, Chenggang Cui

Journal of System Simulation

Abstract: In view of the problems of model uncertainty and nonlinearity in bus voltage stability control of Boost converter, an intelligent control strategy based on model-free deep reinforcement learning(RL) is proposed. RL double DQN(DDQN) algorithm and deep deterministic policy gradient(DDPG) algorithm are used, and the Boost converter controller is designed. The state, action space, reward function, and neural network are also designed to improve the dynamic performance of the controller. The joint simulation of the Boost converter model and RL agent is realized by RL modelica(RLM …

Simulation And Optimization Of Integrated Production Logistics System Of Underground Coal Mining, Dressing, And Backfilling, Xiangqian Wang, Puhao Guo, Xiangrui Meng

Journal of System Simulation

Abstract: In order to study the green mining mode of coal, the bottleneck problem in the integrated production logistics system of underground coal mining, dressing, and backfilling under the goal of achieving the basic production capacity target is explored, so as to promote the coordinated and efficient logistics transportation of underground coal and gangue. A mine in Shanxi is selected as the prototype, and the queuing theory is adopted to analyze the operation process of the integrated coal production logistics system. A discrete event model is established with the help of Anylogic simulation software for related experimental optimization …

Simulation Platform For Optimization And Decision Making Of Flexible Manufacturing Process Of Automatic Production Lines, Chao Fu, Dongyue Wang, Xinxin Li, Min Xue

Journal of System Simulation

Abstract: In order to simulate a flexible manufacturing process to verify the correctness of theoretical computation and analysis and find other important factors for optimization and decision making in the manufacturing process, a simulation platform for the optimization and decision making of the flexible manufacturing process of automatic production lines is designed and developed. The framework of the simulation platform is constructed with four hierarchies, including the enterprise production hierarchy, optimization and decision making hierarchy, data resource hierarchy, and function module hierarchy. On this basis, the functional implementation of the modules of production allocation …

Modeling And Simulation Of Spaceborne, Near-Spaceborne, And Airborne Integrated Collaborative Remote Sensing System Based On Dodaf, Lili An, Tian Xia, Wenbin Yang, Xinbo Wu

Journal of System Simulation

Abstract: Spaceborne, near-spaceborne, and airborne integrated collaborative remote sensing system (SNA-ICRSS) makes comprehensive use of modern information technology to aggregate multiple and heterogeneous data in spaceborne, near-spaceborne, and airborne domains, so as to realize accurate emergency service and command decision-making. SNA-ICRSS is huge and complex, and there is a lack of research on its architecture modeling and simulation. According to the architecture characteristics of the SNA-ICRSS, the minimum prototype of the SNA-ICRSS is constructed; through the department of defense architecture framework (DoDAF) and activity based methodology (ABM) methods, the minimal prototype of the SNA-ICRSS is modeled, and the operational resource …

Simulation Of Real-Time Path Planning And Formation Control For Unmanned Surface Vessel, Dalei Song, Wenhao Gan, Yingzhi Xu, Xiuqing Qu, Jiangli Cao

Journal of System Simulation

Abstract: Safety and collision-free navigation are the basis of normal navigation of an unmanned surface vessel. The high-fidelity virtual ocean is constructed by using Unity3D.On the basis of the vessel modeling, a real-time path planning and formation control method for unknown complex environments is proposed. Firstly, the local environment information is obtained by the laser sensor. Then the real-time local path planning is completed by combining A-star and route-thinning methods under the replanning strategy. In addition, formation control is carried out based on the leader-follower strategy and consistency method, and the artificial potential field …

Partial Task Offloading Strategy Of Cloud Robots Based On Game Theory Under Cloud-Edge Coordination, Chunmao Jiang, Zhenxing Yang

Journal of System Simulation

Abstract: How to rationally utilize the resources of central and edge clouds to reduce energy consumption of system equipment and shorten average task completion time is a fundamental challenge for computational task offloading of cloud robots. In this paper, we transform the computational task offloading problem of multiple cloud robots into a multi-actor game model by using the computational task completion time and energy consumption of cloud robots as cost measurement indicators and setting different cost weights according to actual needs. We also develop a game theory-based partial task offloading algorithm (GT-PTO). With the Nash equilibrium state …

Auxiliary Decision-Making Method For Flight Support Force Allocation Based On Dbn, Junyang Liu, Shisong Zhu

Journal of System Simulation

Abstract: In order to make up for the deficiency of decision-making methods of full deployment and proportional allocation in airport flight support activities, an auxiliary decision-making model for airport flight support force allocation based on a dynamic Bayesian network (DBN) is constructed.On the basis of quantifying the strength of the support force, thehidden Markov model and Hausdorff distance algorithm are introduced to make auxiliary decisions for flight support activities under different conditions and define relevant decision evaluation indexes as the basis for model verification. Simulation tests are carried out on airport flight support activities under two …

Research On No-Wait Flow Shop Scheduling Based On Discrete State Transition Algorithm, Jiaying Yu, Hongli Zhang, Yingchao Dong

Journal of System Simulation

Abstract: In view of the no-wait flow shop problem (NWFSP) widely existing in the manufacturing industry, an improved discrete state transition algorithm (IDSTA) is proposed to solve the problem. The coding mode of the workpiece is designed based on the characteristics of the flow shop scheduling problem (FSSP). The initial solution is constructed by the Nawaz-Enscore-Ham (NEH) method with the standard deviation of the processing time of the workpiece as the priority, and a multi-neighborhood combinatorial search strategy based on insertion and exchange is designed to improve the quality of the initial solution. A discrete state transition algorithm ( …

Two-Stage Distributed Robust Optimal Dispatching For A Combined Heat And Power Virtual Power Plant, Yaqian Fan, Songyuan Yu, Fang Fang

Journal of System Simulation

Abstract: Combined heat and power virtual power plant (CHP-VPP) aggregates various electrical and thermal output units and takes into account the uncertainty of wind and solar output, dynamic electricity prices, thermal comfort of users, and other influences to achieve optimal dispatching of overall output. A two-stage distributed robust optimal dispatching method is proposed. In the first stage, planned dispatching is considered, so as to maximize the benefit of CHP-VPP. In the second stage, a fuzzy set of wind and solar output uncertainties is constructed based on the distributed robust method of moment uncertainty, and …

Research On Optimal Scheduling Of Microgrid Based On Nbbo Algorithm, Lisheng Wei, Benben Yang, Ruixia Sun

Journal of System Simulation

Abstract: In view of the economic and environmental collaborative optimization of a microgrid with a micro gas turbine, power to gas(P2G) system with the ability to abandon wind and light for consumption and capture carbon is introduced, and a microgrid optimal scheduling model with P2G system based on novel biogeography-based optimization(NBBO) algorithm is proposed. The microgrid model with the P2G system is constructed, and the working principle of the main equipment is analyzed. The reserve capacity of a wind turbine is introduced to reduce the influence of the randomness of wind power …

Picking Path Planning Of Container Robots Based On Improved Genetic Algorithm, Yuwen Wu, Zhiyue Niu, Zhenping Li

Journal of System Simulation

Abstract: Under the new "container-to-person" picking mode in intelligent warehouses, a new optimization model and its improved genetic algorithm are proposed to solve the picking path planning problem of multiple container robots. According to the picking mode and characteristics of container robots, the picking path planning problem is transformed into an asymmetric vehicle routing problem, and a mixed integer programming model is established with bi-objectives of the shortest total picking path and the least completion time. A hybrid genetic algorithm is designed to solve this model, and the effectiveness and stability of the algorithm are verified …

Action Recognition Method Based On Projection Subspace Views Under Single Viewing Angle, Benyue Su, Manzhen Sun, Qing Ma, Min Sheng

Journal of System Simulation

Abstract: In view of the self-occlusion problem of joint action tracking by a depth camera under a single viewing angle, a new human action recognition method based on projection subspace views is proposed. Without adding data acquisition equipment, the method projects the three-dimensional(3D) action sequences obtained under a single viewing angle into multiple two-dimensional subspacesand then seeks the maximum distance between classes in the two-dimensional subspaces, so as to increase the distance between 3D actions based on the fusion of multiple subspace views as much as possible. The recognition rate in the self-built AQNU …

Point Cloud Registration Method Based On Improved Covariance Matrix Descriptor, Yuan Zhang, Haoyu Han, Xie Han, Jiaxu Fu

Journal of System Simulation

Abstract: Point cloud registration is a key part of the digital protection of cultural relics. Improving registration accuracy and noise resistance is the main goal of point cloud registration for cultural relics. In order to solve this problem, a three-dimensional (3D) point cloud registration method based on a covariance matrix descriptor is proposed. The tensor voting method is used to eliminate the noise points, and the internal shape signature method is used to extract the key points from the point cloud after removing the noise. Then, the neighborhood information is constructed for the extracted key points, …

Outlier Detection During Thermal Processes Based On Improved Gaussian Mixture Model, Zheng Wu, Yue Zhang, Ze Dong

Journal of System Simulation

Abstract: Abnormal data detection during thermal processes is the basis for performing system modeling, control, and optimization and constitutes an important part of data processing. In this paper, an unsupervised outlier detection algorithm during thermal processes based on an improved Gaussian mixture model is proposed. The algorithm captures a class of data clusters under specific working conditions by using Gaussian components in each dimension, modifies the posterior probability density of the traditional model by adding penalty constraint factors to penalize the false detection and missed detection items, and identifies abnormal data according to the correlation differences with the …

Improved Social Force Model Based On Enhancing Psych Behavioral Heterogeneity, Yandong Liu, Gaoxiang Huang, Wen Chen

Journal of System Simulation

Abstract: Simulating the evacuation behavior of people under anxiety is of great significance for solving the kinematic problems such as escape. At present, most at home and abroad studies consider the anxiety factors as the only medium of population evacuation without considering how external key factors affect anxiety factors in such emergency environments. The improved social force model is proposed, combined with Agent-based stampede risk assessment, the influence of key environmental variables on the anxiety factor is quantified. The psychological force parameters are introduced, and the impact of the anxiety factor on the actual evacuation process is applied to the …

Research On Collaborative Task Allocation Method Of Multiple Uavs Based On Blockchain, Shuangcheng Niu, Yuqiang Jin, Kunhu Kou

Journal of System Simulation

Abstract: The autonomous collaborative control of a multi-unmanned aerial vehicle (UAV) system lacks a unified underlying technology platform and faces single point failure and information security threats. In order to solve these problems, an idea to build collaborative task planning platforms based on blockchain technology is proposed. With thecollaborative task allocation of multiple UAVs as research objects, an online, safe, high-efficiency, and real-time task allocation method is designed. The contract network task allocation algorithm is described as a smart contract, and system consensus is reached based on the blockchain consensus algorithm. In addition, …