Computer Engineering Commons^™

Mac For Machine-Type Communications In Industrial Iot—Part Ii: Scheduling And Numerical Results, Jie Gao, Mushu Li, Weihua Zhuang, Xuemin Shen, Xu Li

Electrical and Computer Engineering Faculty Research and Publications

In the second part of this article, we develop a centralized packet transmission scheduling scheme to pair with the protocol designed in Part I and complete our medium access control (MAC) design for machine-type communications in the industrial Internet of Things. For the networking scenario, fine-grained scheduling that attends to each device becomes necessary, given stringent Quality-of-Service (QoS) requirements and diversified service types, but prohibitively complex for a large number of devices. To address this challenge, we propose a scheduling solution in two steps. First, we develop algorithms for device assignment based on the analytical results from Part I, when …

Seamless Container Migration Between Cloud And Edge, Aditya Mohan, Jonathan Yezalaleul, Angeline Chen, Tamir Enkhjargal

Computer Science and Engineering Senior Theses

Considering the limited resources of edge devices, it is essential to monitor their current resource utilization and device resource allocation strategies that assign containers to edge and cloud nodes based on their priority. Edge containers may need to be migrated to a cloud platform to reduce the load of edge devices and allow for running missions critical applications. In this case, we proposed a prioritization method to exchange containers between the edge and cloud, while trying to assign delay-sensitive containers to edge nodes. We evaluate the performance of running Docker container management systems on resource-constrained machines such as Raspberry Pi, …

Three Degrees Of Freedom Robotic Arm And Its Digital Twin Using Simulink – A Bibliometric Analysis, Bharath Suthar Mr., Arunkumar Bongale Dr, Satish Kumar Dr, Anupkumar Bongale Dr

Library Philosophy and Practice (e-journal)

The 3-degree Digital Twin robotic arm for freedom can diagnose the joints off-board by placing a torque in the robotic arm joint. MATLAB, Simulink®, SimscapeTM, and Simscape Multibody were the basis of this model. Virtual space with a virtual robot arm was connected to a physical space that was a 3D printed replica of the virtual space and robot arm, built using Unity (a modern Game Engine). The arm in the Digital Twin model was created using the hardware prototype’s dimensions, which were then used to simulate a real-world situation. With its revolute joints, the arm has a certain degree …

Personalized Digital Phenotype Score, Healthcare Management And Intervention Strategies Using Knowledge Enabled Digital Health Framework For Pediatric Asthma, Utkarshani Jaimini, Amit Sheth

Publications

Asthma is a personalized, and multi-trigger respiratory condition which requires continuous monitoring and management of symptoms and medication adherence. We developed kHealth: Knowledge-enabled Digital Healthcare Framework to monitor and manage the asthma symptoms, medication adherence, lung function, daily activity, sleep quality, indoor, and outdoor environmental triggers of pediatric asthma patients. The kHealth framework collects up to 1852 data points per patient per day. It is practically impossible for the clinicians, parents, and the patient to analyze this vast amount of multimodal data collected from the kHealth framework. In this chapter, we describe the personalized scores, clinically relevant asthma categorization using …

Drone-Based Wireless Communications For Disaster Recovery, Mark Rizko, Cameron Burdsall

Computer Science and Engineering Senior Theses

This project aims to establish a drone system that can deploy a wireless mesh network over a disaster area, which would aid in the process of finding survivors by using wireless communications to identify where victims are and allow authorities to send out alerts to people in the area. We also seek to add a device detection feature that would allow the drones to passively look for devices through WiFi and Bluetooth Low Energy, giving disaster responders the ability to actively identify specific devices, locate zones where victims lie, and discern a rough population estimate of that area. Those that …

Enhanced Sensing Methods For Uav-Based Disaster Recovery, Connor Azzarello, Chris Gerbino, Ruchir Mehta

Computer Science and Engineering Senior Theses

Natural and human-caused disasters devastate and displace civilian populations. Over the past century, the rate at which these catastrophes occur has increased dramatically. Climate change and unsustainable human behaviors are large contributors to the occurrence of natural disasters, therefore it is likely this upward trend will continue. The region of the world where a disaster takes place often determines how severe the implications are for the affected civilians. The devastation that occurs from a disaster is much greater in low-resourced regions of the world.

Unmanned aerial vehicles (UAVs) are commonly used to assist first responders during disaster response. The existing …

Create: Creative Resources To Express Art Through Engagement, Katherine Sanchez, Ari Soriano

Computer Science and Engineering Senior Theses

To address the current mental health crisis, we propose a platform for co-creative systems that users can utilize as art/music therapy. Art therapy can be an effective way of self-expression that results in psychological benefits and improved mood. We analyze the effectiveness of 8 different systems, 4 musical and 4 art-based. These systems allow the users to create while the computer interacts and responds to their input. The results are evaluated on a before and after emotional assessment that we issue to the user. We targeted college age students and distributed our platform to Santa Clara University students during a …

Rebalancing Shared Mobility Systems By User Incentive Scheme Via Reinforcement Learning, Matthew Brian Schofield

Theses and Dissertations

Shared mobility systems regularly suffer from an imbalance of vehicle supply within the system, leading to users being unable to receive service. If such imbalance problems are not mitigated some users will not be serviced. There is an increasing interest in the use of reinforcement learning (RL) techniques for improving the resource supply balance and service level of systems. The goal of these techniques is to produce an effective user incentivization policy scheme to encourage users of a shared mobility system to slightly alter their travel behavior in exchange for a small monetary incentive. These slight changes in user behavior …

Windows Kernel Hijacking Is Not An Option: Memoryranger Comes To The Rescue Again, Igor Korkin

Journal of Digital Forensics, Security and Law

The security of a computer system depends on OS kernel protection. It is crucial to reveal and inspect new attacks on kernel data, as these are used by hackers. The purpose of this paper is to continue research into attacks on dynamically allocated data in the Windows OS kernel and demonstrate the capacity of MemoryRanger to prevent these attacks. This paper discusses three new hijacking attacks on kernel data, which are based on bypassing OS security mechanisms. The first two hijacking attacks result in illegal access to files open in exclusive access. The third attack escalates process privileges, without applying …

Alzheimer’S Disease Diagnostic Support Tool, Chelsea Fernandes, Shreya Venkatesh, Aiyushi Kumar

Computer Science and Engineering Senior Theses

Alzheimer’s Disease is the 6th leading cause of death overall and the most common cause of dementia in older people in the US. The prevalence of the disease is projected to increase in the next few decades and disproportionately impact low/middle income populations. Unfortunately, specialized doctors, such as neurologists, may not be present in situations where a diagnosis is necessary, resulting in the possibility of AD being overlooked at its early and most treatable stages. Our proposed application is a tool that can aid doctors in determining a probable AD diagnosis using an inputted combination of imaging data, biomarkers, patient …

Improved Hyperparameter Tuning For Graph Learning With Warm-Start Configuration, Drew Ligman

Computer Science and Engineering Senior Theses

With the increasing size and complexity of machine learning datasets, obtaining highly performing prediction models in various tasks has become increasingly difficult. In particular, the processs of hyperparameter optimization (HPO) contributes a significant portion of this cost. This work examines a specific graph-machine learning model, graph convolutional networks (GCN), to derive a hyperparameter configuration with optimal performance across a variety of datasets. We motivate our configuration theoretically and validate it empirically through comprehensive experimentation. We find that for GCN semi-supervised classification tasks, our configuration performs nearly optimally when compared against traditional HPO while only requiring a fraction of the budget. …

Bluetooth Security Of Colocated Apps On Android, Sean Kelker, Omar Garcia

Computer Science and Engineering Senior Theses

The Bluetooth protocol is used millions of times per day, as a means of short-range wireless communication. Many of these connections are between a phone running the Android operating system and an external device. Due to Android’s implementation of Bluetooth, however, unrelated applications that are co-located on the phone have the potential to stealthily send and receive communications from any device that is connected. Our project involves creating malicious applications to investigate the effectiveness of this attack on real-world devices, and we show that the vulnerability above has practical applications. We also create a defense against this attack by modifying …

Machine Learning Based Model For The Detection Of Brain Aneurysms From Mr Angiography, Katherine Becknell, Claire Bushnell, Rachel Fitzsimmons, Emily Sumner

Interdisciplinary Design Senior Theses

A brain aneurysm is a thin or weak spot on a blood vessel wall that expands and fills with blood. Brain aneurysms are very dangerous due to the fact that in most cases, patients do not show any symptoms. Because of this, aneurysms are difficult to diagnose unless it becomes very large or ruptures, resulting in fatal hemorrhage.

Aneurysms can be detected by a number of different brain imaging methods including Magnetic Resonance Imaging (MRI), Magnetic Resonance Angiography (MRA), Computed Tomography Angiography (CTA) and other imaging methods but for the sake of this report we will only be focusing on …

Is Social Diversity Related To Misinformation Resistance? An Empirical Study On Social Communities, I Chang, Orion Sun, Jasper Sang Ahn

Computer Science and Engineering Senior Theses

Misinformation has become a pervasive issue on online social media. Whether it is spread purposefully with ill intent or accidentally through ignorance, misinformation can be dangerous and create confusion in those who are affected by it. The investigation presented in this paper found that no research has been performed that directly examine the correlation between a social community’s misinformation resistance and diversity. This project utilizes CrowdTangle, a tool to gather data from Facebook groups, along with machine learning models to determine if this correlation can be drawn. We were able to find correlations between some diversity metrics with misinformation resistance …

Multi-Objective Optimization Of Multi-Task Parallel Motorcycle Suspension System Parameters, Xiansheng Ran, Yang Jing, Luo Ling, Chen Kai

Journal of System Simulation

Abstract: Aiming at the comprehensive problem of wobble of front suspension system and weave of rear suspension system of large displacement motorcycle at medium and high speed, a multi-objective optimization scheme based on sensitivity analysis and approximate modeling is proposed. The motorcycle model is established and the dynamics simulation is carried out. The lateral acceleration of front wheel's centroid position, the yaw rate and roll rate of whole vehicle's centroid position, which characterize the wobble and weave are the targets. The sensitivity analysis of suspension system parameters and the approximate modeling are carried out. Based on the analysis results, …

Discussing Digital Twin From Of Modeling And Simulation, Zhang Lin, Lu Han

Journal of System Simulation

Abstract: The development and evolution of modeling and simulation technology, and its importance in scientific and technological progress are briefly reviewed. The intrinsic relation between digital twin and modeling and simulation is revealed by analyzing the background and concept of digital twin. The way to build and evaluate a digital twin based on modeling and simulation theoretical methods is discussed. to ensure the credibility.

Development And Prospect Of Simulation Research In China, Xiaogang Qiu, Duan Hong, Xie Xu, Mengna Zhu

Journal of System Simulation

Abstract: It is important to treat modeling and simulation (M&S) as a discipline to advance its development. In China, M&S has been researched and applied over 40 years, and is gradually becoming an independent discipline. Modeling and simulating the complex systems are the challenge, however, this also brings grand opportunity for M&S to widen and improve itself. Since 1980s, the M&S community in China has realized the broad applications of M&S, comprehended M&S from multiple perspectives, conducted extensive research on basic questions, and discussed the composition of the basic simulation theory. By summarizing these achievements, the future works that have …

Multiple Object Tracking And Kinematic Simulation For Short Track Speed Skating, Li Qi, Hanlin Mo, Xiangdong Wang, Li Hua

Journal of System Simulation

Abstract: Aiming at the problem that it is difficult to obtain the motion data of each athlete in the short track speed skating competition, an algorithm flow of multiple object tracking and kinematic simulation is proposed. A local matching metric is proposed to deal with the partial occlusion in monocular video and improve the tracking stability and robustness. The motion simulation method based on homography mapping and derivative of fitted curve is realized to estimate kinematic parameters such as velocity and acceleration. The experiments on Skating Track Multiple ObjectTracking (STMOT) verified the effectiveness and superiority of the proposed methods.

An Artificial Emotion Model For The Mutual Mapping Between Discrete State And Dimensional Space, Zhihang Tian, Xiaming Chen, Dazhi Jiang

Journal of System Simulation

Abstract: Emotional intelligence is an important component and development direction of machine intelligence. The purpose of artificial emotion model is to construct emotion models for machines to develope systematic ability of emotion understanding and expression. However, the existing methods are still insufficient in artificial emotion modeling ability. Aiming at the key factor of personalization in the construction of artificial emotion model, this paper proposes a method of mutual mapping between discrete emotion state and dimension space state, and constructs a machine personalized artificial emotion model based on Big Five personality model and emotion state transfer model. The relevant experimental results …

Decomposition Furnace Outlet Temperature Prediction Based On Elasticnet And Lstm, Guangyu Yu, Xueping Dong, Xiangmin Wang, Gan Min

Journal of System Simulation

Abstract: The outlet temperature of the decomposition furnace is a key indicator in the cement production process. Aiming at the problem that traditional prediction methods only consider the influence of wind, coal, and materials, a temperature prediction model of ElasticNet combined with Long Short-Term Memory (LSTM) neural network is proposed. The ElasticNet-LSTM export temperature prediction model is constructed by using the ElasticNet method to estimate the parameters of different variables, fully considering the influencing factors and realizing the variable screening, and analyzing the influence of the number of hidden layers and nodes on the accuracy of the neural network. Simulation …

A Shared Memory Based Parallel Hierarchical Interest Matching Algorithm, Wenjie Tang, Junwei Cheng, Yiping Yao, Zhu Feng

Journal of System Simulation

Abstract: Interest matching plays an important role in distributed simulation. However, because of huge number of simulation entities and frequent change of regions, interest matching consumes tremendous computation in large scale simulations. The ubiquity of multicore urges us to improve the performance of interest matching by parallelization. A shared memory based parallel hierarchical interest matching algorithm is propose to solve the problem. It maps subscribe regions into a full binary tree, and compares update regions with the tree in parallel. Due to the associative relationship between adjacent nodes, unnecessary comparisons can be eliminated. The experimental results demonstrate that the …

Time-Varying Ocean Channel Modeling Method, Yuehua Pei, Su Wei, Jincheng Tao, Xialin Jiang

Journal of System Simulation

Abstract: For the ocean channel with extremely complicated situation, an underwater acoustic channel modeling algorithm which can reflect the sparsity, time-varying and space-varying characteristics is proposed. Based on the prior information obtained from the sea trials in a specific sea area, the statistical characteristics of the channel impulses response structure with time and space are obtained. According to the obtained channel sparsities and non-zero position vectors’ statistics, a time-varying underwater acoustic channel model match the real environment is generated. Based on the measured data of marine communication in specific sea area, the simulation results show that the proposed …

Time-Delay Estimation For Mimo Delay Systems With Unknown Structures, Xuguang Wang, Mengjie Feng, Su Jie, Jiale Quan

Journal of System Simulation

Abstract: In the unknown-structure delay system modeling, time-delays lead to a mismatch between the system inputs and outputs on the timeline and cause low system modeling accuracy. A time-delay estimation method is proposed for the unknown-structure MIMO (Multiple-Input Multiple-Output) delay systems. A general mathematical description is given from the algebraic point of view, the delay correlation function is defined, and a quantitative constraint between system input-output and time-delay is constructed. A greedy time-delay search algorithm is introduced based on the delay correlation function. Simulation experiments and real data experiments show the availability of the proposed method.

Fault Detection Of Wind Turbine Bearing Based On Bo-Sdae Multi-Source Signal, Dinghui Wu, Zhichao Zhu, Xinhong Han

Journal of System Simulation

Abstract: Due to the discrepancy within signals from sensors of wind turbines caused by environmental interference, the fault detection results of wind turbine bearing will be affected and the multi-source signal fault diagnosis method is proposed to improve the reliability of fault detection. The time-domain and frequency-domain features of bearing vibration signals, noise signals and temperature signals are used for feature extraction,and then the features are transmitted to the stacked denoising autoencoders, which are optimized the hidden layer node structure by the Bayesian optimization algorithm to achieve multi-source signal feature fusion. Softmax function is used for classification. Experiments show that …

Rapid Development Technology Of Virtual Maintenance Training Simulation Model For Aviation Equipment, Rongqiang Li, Aibing Wen, Bin Hua, Jiajun Li, Jiang Bing

Journal of System Simulation

Abstract: Taking the practical application of the aircraft virtual maintenance training as the demand, the basic development process and technical means of the aircraft virtual maintenance training simulation model are analyzed, which solves the technical bottleneck in the popularization and application of the large-scale engineering. Aiming at the crucial problems such as the low efficiency in the development of maintenance training simulation model and the difficulties in updating the model, a rapid development process to support the large-scale engineering applications is proposed. The principles and implementation ways of three key technologies supporting the rapid development of virtual maintenance training simulation …

Explicit Model Predictive Control For Intelligent Vehicle Lateral Trajectory Tracking, Leng Yao, Shuen Zhao

Journal of System Simulation

Abstract: To ensure the accuracy, driving stability and online real-time of intelligent vehicle tracking control, an explicit model predictive tracking control method is designed. The cost functions and constraints for tracking accuracy and driving stability in the prediction time domain are proposed. The tracking control problem is transformed into the optimization of the active steering angle with dynamic disturbances. To improve the real-time performance, the traditional model predictive control system is transformed into an equivalent explicit polyhedral piece-wise affine (PPWA) system, and the active steering angle of front wheel is gained by the explicit law on parameter partition. Carsim and …

Day-Ahead Dispatching Model Of Source-Load Coordination Based On Response Behavior To Real-Time Pricing, Liu Yun, Han Song, Qiuli Huang

Journal of System Simulation

Abstract: In order to give full play to the regulating role of electricity price on the market, considering the difference of consumers' response behavior to real-time pricing, consumers are divided into short-term consumers, mixed consumers and long-term consumers, and the real-time pricing models of three types of consumers are constructed based on the electricity price elasticity matrix. On this basis, a day-ahead dispatching model of source-load coordination based on consumer’s response behavior to real-time pricing is established. With the help of the MOST toolkits in MATPOWER and the Mosek solver, the arithmetic analysis is developed in a modified IEEE 57-buses …

Multi-View Human Action Recognition Based On Deep Neural Network, Zhao Ying, Lu Yao, Zhang Jian, Qidi Liang, Long Wei

Journal of System Simulation

Abstract: A novel deep neural network named CNN+CA(Convolutional Neural Network plus Context Attention) model is constructed and a new recognition algorithm based on sequence matching is presented to improve the recognition accuracy of MVHAR (Multi-view Human Action Recognition). A CNN(Convolutional Neural Network) is designed to automatically learn multi-view fusion features; the CA (Context Attention) module is introduced to selectively focus on the parts of the features that are relevant for the recognition task; the proposed recognition algorithm based on sequence matching is used to realize MVHAR. The experimental results on the IXMAS dataset and the i3DPost dataset …

Design And Simulation For Compensatory Controller Of Aircraft Rudder Electro-Hydraulic Loading System, Xiaolin Liu, Jingyi Wu

Journal of System Simulation

Abstract: The electro-hydraulic loading system of aircraft rudder is a torque servo system which is a special equipment for testing the performance of rudder. In order to reduce the influence of surplus force in loading system, a control method for PID controller tuned in real time by radial basis function neural network based on particle swarm optimization is proposed. The characteristics of global and hyper parameter optimization of particle swarm optimization are used to improve the control effect of the controller. The learning coefficient based on annealing is used to accelerate the network convergence speed. Simulation results show that, compared …

Spatial Knowledge Representation Model Of Simulation Scenario Based On Ontology, Zhu Jie, Hongjun Zhang

Journal of System Simulation

Abstract: Military simulation scenario has abundant spatial knowledge and is closely related to various models of combat simulation. In view of the lack of uniform specification for the description of simulation scenario knowledge, it is necessary to construct a spatial knowledge representation model in line with spatial thinking to effectively analyze the spatial entities and their interrelationships in simulation scenario. The ontology method is used to establish spatial knowledge domain ontology and form the formal description specification of spatial knowledge concept; the spatial knowledge structure is described hierarchically by using the method of concept knowledge tree, clarifying the semantic logic …