Computer Engineering Commons^™

A Quantitative Validation Of Multi-Modal Image Fusion And Segmentation For Object Detection And Tracking, Nicholas Lahaye, Michael J. Garay, Brian D. Bue, Hesham El-Askary, Erik Linstead

Mathematics, Physics, and Computer Science Faculty Articles and Research

In previous works, we have shown the efficacy of using Deep Belief Networks, paired with clustering, to identify distinct classes of objects within remotely sensed data via cluster analysis and qualitative analysis of the output data in comparison with reference data. In this paper, we quantitatively validate the methodology against datasets currently being generated and used within the remote sensing community, as well as show the capabilities and benefits of the data fusion methodologies used. The experiments run take the output of our unsupervised fusion and segmentation methodology and map them to various labeled datasets at different levels of global …

The Revenue Operations (Revops) Framework: A Qualitative Study Of Industry Practitioners., Oliviero Mottola

Dissertations and Theses

In recent years Revenue Operations or RevOps has emerged in professional circles as a new approach to manage Sales, Marketing and Customer Success teams in the context of b2b sales. In practitioner circles, RevOps definitions range from the increased collaboration of the three job functions to an all-out creation of job function within organizations. While the subject of interdepartmental alignment has been covered extensively in academia (albeit not exhaustively), RevOps as a term and set of practices has received no attention and industry practitioners struggle to find a unified set of best practices that isn’t coming from organizations trying to …

Artificial Intelligence (Ai) And Augmented Reality (Ar): Disambiguated In The Telemedicine / Telehealth Sphere, Sharon L. Burton

Publications

The world is navigating through unfamiliar and incomprehensible times – COVID-19, international economic crisis, and crumbling healthcare systems. The United States (US) healthcare industry is grappling with an increased workload and advancing digitization technological concerns. The failure of organizations to offer suitable cybersecurity controls within the critical infrastructure leads to advanced persistent threat (APT) that could have incapacitating effects on organizations. A keen understanding of cybersecurity is vital for leaders and the need is referenced in US policy that advances a national unity of effort to strengthen and maintain secure, functioning, and resilient critical infrastructure. Akin to the Presidential Policy …

Off-Chain Transaction Routing In Payment Channel Networks: A Machine Learning Approach, Heba Kadry

Theses and Dissertations

Blockchain is a foundational technology that has the potential to create new prospects for our economic and social systems. However, the scalability problem limits the capability to deliver a target throughput and latency, compared to the traditional financial systems, with increasing workload. Layer-two is a collective term for solutions designed to help solve the scalability by handling transactions off the main chain, also known as layer one. These solutions have the capability to achieve high throughput, fast settlement, and cost efficiency without sacrificing network security. For example, bidirectional payment channels are utilized to allow the execution of fast transactions between …

Mac For Machine-Type Communications In Industrial Iot—Part I: Protocol Design And Analysis, Jie Gao, Weihua Zhuang, Mushu Li, Xuemin Shen, Xu Li

Electrical and Computer Engineering Faculty Research and Publications

In this two-part paper, we propose a novel medium access control (MAC) protocol for machine-type communications in the Industrial Internet of Things. The considered use case features a limited geographical area and a massive number of devices with sporadic data traffic and different priority types. We target supporting the devices while satisfying their Quality-of-Service (QoS) requirements with a single access point and a single channel, which necessitates a customized design that can significantly improve the MAC performance. In Part I of this paper, we present the MAC protocol that comprises a new slot structure, corresponding channel access procedure, and mechanisms …

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 …

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.

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-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 …

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 …

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 …

Performance Analysis Of Cognitive Cooperative Systems Based On Quadrature Spatial Modulation, Guo Hui, Xuejiao Guo, Ting Qiao, Liu Meng

Journal of System Simulation

Abstract: The cognitive cooperative communication system based on quadrature spatial modulation (QSM) is proposed to solve the problems of inter-channel interference and inter-antenna synchronization. The mean power allocation algorithm is used to analyze performance of the system. In addition, the relay nodes and the destination node decode their received signals with the maximum likelihood detection algorithm. The exact closed expressions of outage probability under random relay selection (RRS), suboptimal relay selection (SRS) and optimal relay selection (ORS) are derived respectively. The approximate outage probabilities in the high signal-to-noise ratio region are derived, and the diversity gains of three relay …

An Improved Differential Evolution Algorithm For Fractional Order System Identification, Yu Wei, Henghui Liang, Luo Ying

Journal of System Simulation

Abstract: In order to build a high-precision fractional-order model, which needs to identify more parameters, an improved differential evolution algorithm is proposed for the identification of fractional-order systems. In the mutation strategy, the basis vector is randomly selected from the optimal individual population, and the scaling factor and cross-probability factor are adaptively adjusted according to the information of the successfully mutated individual during the search process to improve the exploration and mining capabilities of the algorithm. By solving the five test functions, the improved algorithm is proved to have strong solving ability. Taking the fractional-order model of permanent magnet synchronous …