Engineering Commons^™

Research On Live Migration Scheduling Method For Communication Network Simulation System Based On Vmotion, Yanfang Fu, Gao Xiang, Cheng Bing, Xueyao Feng

Journal of System Simulation

Abstract: In order to make the quality of the simulation service not being affected by load dynamic changes, heuristic scheduling algorithm was proposed. Using the VMotion technology, the virtualization simulation platform was created by calling the SDK. Through the research of the simulation platform application overhead and virtual resource scheduling technology, the single communication network simulation model was modified, implementing the distributed network collaborative simulation which adapted to multiple virtual machines, providing new ideas for the mass communication network simulation system.

Research On Scenario-Driven Component-Based Model Composition Method, Jianchun Zhang, Fengju Kang

Journal of System Simulation

Abstract: To fulfil the requirements for fast, easy and integrated modeling under certain operation conditions, a model composition method of scenario-driven was proposed. Starting with corresponding composition framework, traditional component models were extended through corresponding meta-model and normalization description of scenario was given. Furthermore, a full combat simulation system could be constructed quickly by realizing integrated process including three processes: scenario parse, model search and match. By preliminarily performing underwater weapon system modeling and simulation application, the result shows efficiency of this composition method.

Learning Deep Architectures For Power Systems Operation And Analysis, Mahdi Khodayar

Electrical Engineering Theses and Dissertations

With the rapid increase in size and computational complexities of power systems, the need for powerful computational models to capture strong patterns from energy datasets is emerged. In this thesis, we provide a comprehensive review on recent advances in deep neural architectures that lead to significant improvements in classification and regression problems in the area of power engineering. Furthermore, we introduce our novel deep learning methodologies proposed for a large variety of applications in this area. First, we present the interval deep probabilistic modeling for wind speed forecasting. Incorporating the Rough Set Theory into deep neural networks, we create an …

Agents For Smart Power Grids, Salem Al-Agtash, Hossam Abdel Hafez

Computer Science and Engineering

The future of electricity systems will compose of small-scale generation and distribution where end-users will be active participants with localized energy management systems that are able to interact on a free energy market. Software agents will most likely control power assets and interact together to decide the best and safest configuration of the power grid system. This paper presents a design of agents that can be deployed in real-time with capabilities that include optimization of resources, intensive computation, and appropriate decision-making. Jordan 51-bus system has been used for simulation with a total generation capacity of 4050 MW of which 230 …

Software Quality Control Through Formal Method, Jialiang Chang

Dissertations

With the improvement of theories in the software industry, software quality is becoming the most significant part of the procedure of software development. Due to the implicit and explicit vulnerabilities inside the software, software quality control has caught more researchers and engineers’ attention and interest.

Current research on software quality control and verification are involving various manual and automated testing methods, which can be categorized into static analysis and dynamic analysis. However, both of them have their own disadvantages. With static analysis methods, inputs will not be taken into consideration because the software system isn’t executed so we do not …

Need Based Evaluation Of Cloud Services In The Wake Of Covid-19, Samir Souidi, Stanley Mierzwa

Center for Cybersecurity

For many organizations, particularly those that may be considered legacy, or older existing enterprises, the recent COVID-19 pandemic may be pushing them to further progress into the realm of cloud services. With the global population asked to quarantine or shelter-in-place during the pandemic spread of 2020, many businesses that were able to function with their workforce remotely had no choice but to do so. Having information systems available with true remote access capabilities was a must. For those organizations who had already moved to a cloud-based model, they found themselves in a far better situation than those firms who still …

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 …

An Investigation Into Multi-View Error Correcting Output Code Classifiers Applied To Organ Tissue Classification, Daniel Alvarez

UNLV Theses, Dissertations, Professional Papers, and Capstones

Large amounts of data is being generated constantly each day, so much data that it is difficult to find patterns in order to predict outcomes and make decisions for both humans and machines alike. It would be useful if this data could be simplified using machine learning techniques. For example, biological cell identity is dependent on many factors tied to genetic processes. Such factors include proteins, gene transcription, and gene methylation. Each of these factors are highly complex mechanism with immense amounts of data. Simplifying these can then be helpful in finding patterns in them. Error-Correcting Output Codes (ECOC) does …

Traffic Privacy Study On Internet Of Things – Smart Home Applications, Ayan Patel

Master's Theses

Internet of Things (IoT) devices have been widely adopted in many different applications in recent years, such as smart home applications. An adversary can capture the network traffic of IoT devices and analyze it to reveal user activities even if the traffic is encrypted. Therefore, traffic privacy is a major concern, especially in smart home applications. Traffic shaping can be used to obfuscate the traffic so that no meaningful predictions can be drawn through traffic analysis. Current traffic shaping methods have many tunable variables that are difficult to optimize to balance bandwidth overheads and latencies. In this thesis, we study …

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 …

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 …

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 …

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 …

Implementation And Application Of Coordinate Stretched Pml Under Two-Dimensional Cylindrical Coordinate, Anshi Zhu, Zili Chen, Yang Yong, Yunhui Zhen

Journal of System Simulation

Abstract: According to the numerical calculation of electromagnetic field under cylindrical coordinate, the conventional split field absorbing boundary is no longer applicable. The coordinate stretched perfectly matched layers (CS-PML) were applied in the two-dimensional stretched cylindrical coordinate system. The updating equations of Maxwell curl equations in CS-PML were derived by using auxiliary equation method. The simulation results show that theoretical derivation is correct. The reflection coefficient of CS-PML is less than -30 dB, and it is able to meet the precision demand of numerical calculation. Besides, the CS-PML was adopted to investigate the radiation characteristic of the …

Design And Implementation Of Quantum-Inspired Bee Colony Algorithm, Shuyun Yang, Panchi Li

Journal of System Simulation

Abstract: To enhance the performance of artificial bee colony algorithm, a quantum-inspired bee colony algorithm was proposed. In the proposed approach, the bees were encoded with the qubits described on the Bloch sphere. The evolutionary search was achieved by rotating the qubit about the rotation axis on the Bloch sphere. The Bloch coordinates of qubit can be obtained by measuring with the Pauli matrices, and the optimization solutions can be presented through the solution space transformation. The highlight advantages of this method are the ability to simultaneously adjust two parameters of a qubit and automatically achieve the best match between …