Computer Engineering Commons^™

One Dimensional Neural Time Series Generation, Kaleb Earl Smith

Theses and Dissertations

Time dependent data is a main source of information in today’s data driven world.Generating this type of data though has shown its challenges and made it an interesting research area in the field of generative machine learning. The challenge with this one-dimensional (1D) data has been for applications in machine learning to gain access to a considerable amount of quality data needed for algorithm development and analysis. Modeling synthetic data using a Generative Adversarial Network (GAN) has been at the heart of providing a viable solution. Our work focuses on one dimensional times series and explores the “few shot” generation …

Performance Analysis Of V2v And V2i Communications Using Empirical Path Loss Models Indicators And Embedded Iot Devices, Ibrahim Lateef Oraibi Al Kinoon

Theses and Dissertations

Vehicle management technologies deals with the management of critical vehicle information, including location, idle time, speed, and mileage. Such information can always be transferred through a direct vehicle-to-vehicle communication among cars. However, the limitation of this type of design is that it is based on the assumption that vehicles are always served by cellular bases, which is not always the case. For the effective implementation of the Internet-of-Things (IoT) technology in this sector, it is critical to design vehicles with systems that enable them to transmit essential information in the absence of base stations. IoT technologies can then be used …

Snitch Application: Addressing Cyber Trust In Future Living Spaces, Russell Moore

Cybersecurity Undergraduate Research Showcase

The future of smart homes is filled with excitement and ample opportunity to live in an environment that features extraordinary convenience and energy efficiency. Devices such as Amazon Alexa and Roku Smart TV’s feature voice interaction options that provide the user with enhanced functionality. While voice-activated devices are accommodating, it is imperative to acknowledge how they work on the backend. The problem is that these devices collect and share a large amount of data from users who are oftentimes unaware that it’s even happening. The Snitch App is being developed in order to inform the user of what exactly is …

Investigating Single Precision Floating General Matrix Multiply In Heterogeneous Hardware, Steven Harris

McKelvey School of Engineering Graduate Student Theses & Dissertations

The fundamental operation of matrix multiplication is ubiquitous across a myriad of disciplines. Yet, the identification of new optimizations for matrix multiplication remains relevant for emerging hardware architectures and heterogeneous systems. Frameworks such as OpenCL enable computation orchestration on existing systems, and its availability using the Intel High Level Synthesis compiler allows users to architect new designs for reconfigurable hardware using C/C++. Using the HARPv2 as a vehicle for exploration, we investigate the utility of several of the most notable matrix multiplication optimizations to better understand the performance portability of OpenCL and the implications for such optimizations on this and …

Water Quality Prediction Based On Machine Learning Techniques, Zhao Fu

UNLV Theses, Dissertations, Professional Papers, and Capstones

Water is one of the most important natural resources for all living organisms on earth. The monitoring of treated wastewater discharge quality is vitally important for the stability and protection of the ecosystem. Collecting and analyzing water samples in the laboratory consumes much time and resources. In the last decade, many machine learning techniques, like multivariate linear regression (MLR) and artificial neural network (ANN) model, have been proposed to address the problem. However, simple linear regression analysis cannot accurately forecast water quality because of complicated linear and nonlinear relationships in the water quality dataset. The ANN model also has shortcomings …

Cooperative Target Tracking In Balanced Circular And Elliptical Formations, Lili Ma, Naira Hovakimyan

Publications and Research

This paper extends our earlier results on cooperative target tracking in cyclic pursuit using a group of mobile robots by further prescribing the formation radius and achieving an elliptical formation pattern. Prescribing the formation radius of a balanced circular formation is achieved by adjusting a parameter in the existing control input to each robot. The new elliptical formation pattern is obtained via a transformation matrix. Both single-integrator and double-integrator robot models are considered. The effectiveness of the proposed schemes is demonstrated by simulation examples.

Enhanced Control Algorithms In Permanent Magnet Synchronous Machines, Haibo Li

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Permanent magnet synchronous machines (PMSMs) are gaining increasing popularity in various applications due to their advantages, such as high efficiency, high power density, and superior control performance. A well-designed machine control algorithm is indispensable for a PMSM system to secure its good performance.

In this work, enhanced control algorithms in PMSMs are developed. Online machine current trajectory tracking, source power management, hardware overcurrent regulation, and machine current sensor fault detection and isolation (FDI) are included in the developed algorithms. The online machine current trajectory tracking ensures the maximum torque per ampere (MTPA) or maximum torque per voltage (MTPV) control in …

An End-To-End Trainable Method For Generating And Detecting Fiducial Markers, J. Brennan Peace

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Existing fiducial markers are designed for efficient detection and decoding. The methods are computationally efficient and capable of demonstrating impressive results, however, the markers are not explicitly designed to stand out in natural environments and their robustness is difficult to infer from relatively limited analysis. Worsening performance in challenging image capture scenarios - such as poorly exposed images, motion blur, and off-axis viewing - sheds light on their limitations. The method introduced in this work is an end-to-end trainable method for designing fiducial markers and a complimentary detector. By introducing back-propagatable marker augmentation and superimposition into training, the method learns …

Intelligent Algorithm For Trapezoidal Interval Valued Neutrosophic Network Analysis, Florentin Smarandache, Said Broumi, Deivanayagampillai Nagarajan, Malayalan Lathamaheswari, Mohamed Talea, Assia Bakali

Branch Mathematics and Statistics Faculty and Staff Publications

The shortest path problem has been one of the most fundamental practical problems in network analysis. One of the good algorithms is Bellman-Ford, which has been applied in network, for the last some years. Due to complexity in the decision-making process, the decision makers face complications to express their view and judgment with an exact number for single valued membership degrees under neutrosophic environment. Though the interval number is a special situation of the neutrosophic, it did not solve the shortest path problems in an absolute manner. Hence, in this work, the authors have introduced the score function and accuracy …

The Role Of Information And Communication Technology (Ict) In Securing Books In Irish Academic Libraries., Emmanuel Oguche

Library Philosophy and Practice (e-journal)

This study examined how effective the ICT gadgets are used in securing books in academic libraries and what technological approach the libraries will adopt in the future to ensure books are secured from mutilation and theft. The study was also to understand why students steal or mutilate books. A semi-structured interview was the qualitative research design used to collect data from six librarians. It was discovered that the libraries had adopted the use of ICT security gadgets like Radio-Frequency Identification (RFID) technology, surveillance cameras, self-service machine, magnetic strips. The combined use of these gadgets led to the drastic reduction of …

Secure Mobile Computing By Using Convolutional And Capsule Deep Neural Networks, Rui Ning

Electrical & Computer Engineering Theses & Dissertations

Mobile devices are becoming smarter to satisfy modern user's increasing needs better, which is achieved by equipping divers of sensors and integrating the most cutting-edge Deep Learning (DL) techniques. As a sophisticated system, it is often vulnerable to multiple attacks (side-channel attacks, neural backdoor, etc.). This dissertation proposes solutions to maintain the cyber-hygiene of the DL-Based smartphone system by exploring possible vulnerabilities and developing countermeasures.

First, I actively explore possible vulnerabilities on the DL-Based smartphone system to develop proactive defense mechanisms. I discover a new side-channel attack on smartphones using the unrestricted magnetic sensor data. I demonstrate that attackers can …

Three-Dimensional (3d) Reconstruction Of Computed Tomography (Ct) Abdominal Images Using Visualization Toolkit (Vtk), Mat Saad Afifah Husna

Student Works (2020-2029)

A computerized tomography (CT) or computerized axial tomography (CAT) scan combines data from several X-raysito produce a detailed image of structures inside the body. CT scans produce 2D of a “slice” or section of the abdomen but the data can also be used to construct 3-dimensional images. However, CT scan unable to accurately represent the internal structure of soft tissues and soft-tissue lesions. Therefore, using the program in Visualization Tool Kit (VTK) is needed to construct a much more clearer 3D image. To reconstruct 3D images from 2D images of a “slice” or section of abdomen which will be resulting …

Emergency Department Systems Engineering: Modelling And Event Simulation, O Alharethi Salman Zayed

Student Works (2020-2029)

Emergency department systems are meant to ensure the timely delivery for essential healthcare services through complex systems. (ED) offers various services and have several components in its parts. Examined long previous research on system engineering and quality of healthcare resulting on these are influenced by operational management. Real time data are very helpful for decision making for any systems. Patient output feedback and satisfaction can be ensured with engineered management. EDs have become evident particularly in current scenario when the world is in the grip of the deadly COVID-19. All this implies that analysis is significant for improvement of services …

Social Participation Performance Of Wheelchair Users Using Clustering And Geolocational Sensor's Data, Yukun Yin, Kar Way Tan

Research Collection School Of Computing and Information Systems

For wheelchair users, social participation and physical mobility play a significant part in determining their mental health and quality of life outcomes. However, little is known about how wheelchair users move about and engage in social interactions within their life-spaces. In this project, we investigate the social participation performance of the wheelchair users based on a combination of geolocational and lifestyle survey data collected over a period of three months. This paper adopts a multi-variate approach combining geolocational travel patterns and various factors such as independence, willingness and self-perception to provide multi-faceted analysis to their lifestyles. We provide profiles of …

Learning Transferrable Parameters For Long-Tailed Sequential User Behavior Modeling, Jianwen Yin, Chenghao Liu, Weiqing Wang, Jianling Sun, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Sequential user behavior modeling plays a crucial role in online user-oriented services, such as product purchasing, news feed consumption, and online advertising. The performance of sequential modeling heavily depends on the scale and quality of historical behaviors. However, the number of user behaviors inherently follows a long-tailed distribution, which has been seldom explored. In this work, we argue that focusing on tail users could bring more benefits and address the long tails issue by learning transferrable parameters from both optimization and feature perspectives. Specifically, we propose a gradient alignment optimizer and adopt an adversarial training scheme to facilitate knowledge transfer …

Research On Optimizing Lot Sizing Of Job Shop Based On Em_Plant, Xiaobing Pei, Linlin Tan

Journal of System Simulation

Abstract: Considering maximizing the rate of account and choosing production process time as the optimization objectives to solve the lot sizing optimization problems of job shop, the model about production time under ideal conditions was established, and accordingly the formula of solving theoretical optimal lot sizing was derived. To compensate for the limitations of mathematical modeling and improve the feasibility of the optimal solution, the actual manufacturing operations in job shop was simulated and optimized according to production batch simulation optimization strategy by eM_plant software. By running the simulation model the theoretical optimal solution was amended, to make optimal …

Intelligent Detecting For Infrared Aerial Small Target Based On Non-Subsampled Contourlet Transform, Liu Gang, Xingyuan Xu, Zhou Heng, Xitao Zhang

Journal of System Simulation

Abstract: Aiming at the problem of infrared aerospace small target's detecting under complex background, an intelligent algorithm was proposed based on the non-subsampled contourlet transform and BP neutral network. By using the morphologic top-hat transform which had adaptive structural element, some infrared background was suppressed. By defining the center vector of subband coefficients, the proposed method constructed the synthetical image at high frequency and suppressed the complex background further. Subsequently, taking pixel's gray level, horizontal gradient, vertical gradient, diagonal gradient, neighbour mean and neighbour variance as input character vector, a BP neutral network which had three layers was constructed by …

Performance Analysis Of Netted Radar Data Fusion Systems, Zhijie Chen, Bin Rao, Yongzhen Li, Zhiwei Zong

Journal of System Simulation

Abstract: The performance analysis of netted radar data fusion systems was proposed. The principles of two representative radar netting modes (i.e., centralized fusion and distributed fusion) were introduced and the associated capabilities of anti-jamming, anti-stealth, fusion accuracy, fusion discrimination, and communication requirements were quantitatively analyzed. Simulation results indicate that the netting essence is, centralized fusion by using ‘or' rule to complement information and realize trajectory composition whereas distributed fusion by using ‘and' rule to reduce information redundancy and realize discrimination ability. The research can provide some enlightenment for the newly-developed intellective netted radar data fusion systems.

Parameter Optimization On Coordinated Control System Of Thermal Power Units In High Rate Variable Load Operation Mode, Tian Liang, Liu Fang, Xinping Liu, Jizhen Liu

Journal of System Simulation

Abstract: The frequent fluctuations and rapid change of power grid generating load instruction cause the deterioration of control quality of generating load and throttle pressure in thermal power units. To solve this problem, a trial and error method, the parameters adjustment range of which could be quantified, was proposed. Based on the model of controlled object, the initial value of controller parameters were set conservatively. By calculating the difference between current value and the target value of load change rate, the optimization times were determined, the PID controller parameters optimization method of coordinated control system was studied, and the effectiveness …

Research On Section Optimization Of Water Quality Monitoring Based On Comprehensive Hierarchical Clustering, Xiaofeng Lian, Peng Sen, Xiaoyi Wang, Zaiwen Liu

Journal of System Simulation

Abstract: In order to optimize the layout of water quality monitoring section of river, lake and reservoir effectively, a new method for water quality monitoring section optimization was proposed based on comprehensive hierarchical clustering (CHC). A normalized matrix was constructed according to the original monitoring data of water quality. The method calculated the similarity to obtain the affinity-disaffinity relationship among the monitoring variables by 5 different distance algorithms, and then clustered the data set automatically by 4 different connection algorithms. Moreover, taking the correlation coefficient as the evaluation criteria, optimal hierarchical clustering algorithm was selected. With the generation …