Computer Engineering Commons^™

Low Latency Bearing Fault Detection Of Direct-Drive Wind Turbines Using Stator Current, Samrat Nath, Jingxian Wu, Yue Zhao, Wei Qiao

Department of Electrical and Computer Engineering: Faculty Publications

Low latency change detection aims to minimize the detection delay of an abrupt change in probability distributions of a random process, subject to certain performance constraints such as the probability of false alarm (PFA). In this paper, we study the low latency detection of bearing faults of direct-drive wind turbines (WT), by analyzing the statistical behaviors of stator currents generated by the WT in real-time. It is discovered that the presence of fault will affect the statistical distribution of WT stator current amplitude at certain frequencies. Since the signature of a fault can appear in one of the multiple possible …

Super Education For Supercomputers, Ezgi Gursel, Jeremy Evert

Student Research

Supercomputing (1 OOX more powerful than a desktop) allows organizations to solve complex problems that are not easily studied in any other way (ex. Blue Waters to simulate the known universe since the beginning of time for the design of the James Webb telescope). Producing qualified individuals to take advantage of the growing number of supercomputing jobs is a constant struggle. This poster provides an overview of education in supercomputing, explains how training occurs, and describes some of the key players working to educate a taskforce to deal with these highly complex machines.

Handheld Data Analyzer, Nicholas Shade, Jake Herman, Doug Kern, Graham Hazlett, Anita Richardson

ENGS 89/90 Reports

The goal of this project is to design and build a handheld data analyzer prototype paired with an iPad app that our sponsor can further develop into a marketable product. The system should allow technicians to easily collect vibration data from IEPE accelerometers, inspect the data, and upload the reading to our sponsor’s database system for further analysis.

Dashboard-Mounted Driver Monitoring System, Daniel Lein, Prahlad Sarma, William Roussell, Nathan Nuñez, Elvis Manzanares

ENGS 89/90 Reports

The objective of this project is to deliver safe DMS hardware and interfacing/preprocessing software on which Toyota can run its drowsiness detection neural net. The system shall: securely house all necessary imaging, electronic, and computer hardware to output facial recognition data to the car’s computer, without data input from any other car system; obscure less than 10% of the driver’s field of view out of a standard windshield; be able to capture and process images such that the image classification neural net recognize the images, meeting the top-1 benchmark accuracy statistic across static and dynamic car-cabin lighting conditions; and meet …

Innovation In Pedagogy And Technology Symposium, 2019: Selected Conference Proceedings, University Of Nebraska Online, University Of Nebraska Information Technology Services

Zea E-Books Collection

Advancing Technology in Education at the University of Nebraska, May 7, 2019

Welcome Address • Susan Fritz, Ph.D., Executive Vice President and Provost, University of Nebraska 6

Opening Remarks • Mary Niemiec, Associate Vice President for Digital Education, Director of University of Nebraska Online 6

Keynote Presentation: Shaping the Next Generation of Higher Education • Bryan Alexander, Ph.D. 6

Featured Extended Presentation: Redesigning Courses & Determining Effectiveness Through Research • Tanya Joosten, University of Wisconsin-Milwaukee (UWM), Erin Blankenship, Ph.D. (UNL), Ella Burnham (UNL), Nate Eidem, Ph.D. (UNK), Marnie Imhoff (UNMC), Linsey Donner (UNMC), Ellie Miller (UNMC) 7

5 Ways to …

A Blockchain Approach To Social Responsibility, Augusto Bedin, Wander Queiroz, Miriam A M Capretz, London Hydro

Electrical and Computer Engineering Publications

As blockchain technology matures, more sophisticated solutions arise regarding complex problems. Blockchain continues to spread towards various niches such as government, IoT, energy, and environmental industries. One often overlooked opportunity for blockchain is the social responsibility sector. Presented in this paper is a permissioned blockchain model that enables enterprises to come together and cooperate to optimize their environmental and societal impacts. This is made possible through a private or permissioned blockchain. Permissioned blockchains are blockchain networks where all the participants are known and trust relationships among them can be fostered more smoothly. An example of what a permissioned blockchain would …

Deal: Differentially Private Auction For Blockchain Based Microgrids Energy Trading, Muneeb Ul Hassan, Mubashir Husain Rehmani, Jinjun Chen

Publications

Modern smart homes are being equipped with certain renewable energy resources that can produce their own electric energy. From time to time, these smart homes or microgrids are also capable of supplying energy to other houses, buildings, or energy grid in the time of available self-produced renewable energy. Therefore, researches have been carried out to develop optimal trading strategies, and many recent technologies are also being used in combination with microgrids. One such technology is blockchain, which works over decentralized distributed ledger. In this paper, we develop a blockchain based approach for microgrid energy auction. To make this auction more …

Differential Privacy Techniques For Cyber Physical Systems: A Survey, Muneeb Ul Hassan, Mubashir Husain Rehmani, Jinjun Chen

Publications

Modern cyber physical systems (CPSs) has widely being used in our daily lives because of development of information and communication technologies (ICT).With the provision of CPSs, the security and privacy threats associated to these systems are also increasing. Passive attacks are being used by intruders to get access to private information of CPSs. In order to make CPSs data more secure, certain privacy preservation strategies such as encryption, and k-anonymity have been presented in the past. However, with the advances in CPSs architecture, these techniques also need certain modifications. Meanwhile, differential privacy emerged as an efficient technique to protect CPSs …

Decentralized, Noncooperative Multirobot Path Planning With Sample-Basedplanners, William Le

Master's Theses

In this thesis, the viability of decentralized, noncooperative multi-robot path planning algorithms is tested. Three algorithms based on the Batch Informed Trees (BIT*) algorithm are presented. The first of these algorithms combines Optimal Reciprocal Collision Avoidance (ORCA) with BIT*. The second of these algorithms uses BIT* to create a path which the robots then follow using an artificial potential field (APF) method. The final algorithm is a version of BIT* that supports replanning. While none of these algorithms take advantage of sharing information between the robots, the algorithms are able to guide the robots to their desired goals, with the …

Low-Cost Interior Permanent Magnet Machine With Multiple Magnet Types, Qingqing Ma, Ayman M. El-Refaie, Bruno Lequesne

Electrical and Computer Engineering Faculty Research and Publications

This article is a contribution to answer the following question: Is it possible to design a permanent magnet machine with the performance expected from rare-earth magnets but at a lower cost? Performance being understood as torque, size, efficiency, demagnetization, and temperature rise together. The question is addressed with a systematic exploration of different interior permanent magnet machine topologies mixing rare-earth and ferrite permanent magnets. The study starts from a production baseline, the Prius 2010 traction motor, with interior magnets placed in a single V pattern. It investigates various rotor designs, most specifically, single V and double V patterns as well …

Energy-Efficient Uav-Assisted Mobile Edge Computing: Resource Allocation And Trajectory Optimization, Mushu Li, Nan Cheng, Jie Gao, Yinlu Wang, Lian Zhao, Xuemin Shen

Electrical and Computer Engineering Faculty Research and Publications

In this paper, we study unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) with the objective to optimize computation offloading with minimum UAV energy consumption. In the considered scenario, a UAV plays the role of an aerial cloudlet to collect and process the computation tasks offloaded by ground users. Given the service requirements of users, we aim to maximize UAV energy efficiency by jointly optimizing the UAV trajectory, the user transmit power, and computation load allocation. The resulting optimization problem corresponds to nonconvex fractional programming, and the Dinkelbach algorithm and the successive convex approximation (SCA) technique are adopted to …

Integrated Resource Management For Terrestrial-Satellite Systems, Shu Fu, Jie Gao, Lian Zhao

Electrical and Computer Engineering Faculty Research and Publications

As data traffic in terrestrial-satellite systems surges, the integration of power allocation for caching, computing, and communication (3C) has attracted much research attention. However, previous works on 3C power allocation in terrestrial-satellite systems mostly focus on maximizing the overall system throughput. In this paper, we aim to guarantee both throughput fairness and data security in terrestrial-satellite systems. Specifically, we first divide the system implementation into three steps, i.e., data accumulation, blockchain computing, and wireless transmission. Then, we model and analyze the delay and power consumption in each step by proposing several theorems and lemmas regarding 3C power allocation. Based on …

Partially-Coupled D–Q–0 Components Of Magnetically-Isolated Fscw Ipm Machines With Open-End-Winding Drives, Fan Wu, Hao Ge, Ayman M. El-Refaie, Mohammad Farshadnia, Alireza Pouramin, Rukmi Dutta

Electrical and Computer Engineering Faculty Research and Publications

Fractional-slot concentrated winding interior permanent magnet (FSCW-IPM) machines have been designed with very low winding mutual inductance for magnetic isolation features required for improving their fault-tolerant capabilities. These magnetically-isolated FSCW-IPM machines no longer adhere to the preconditions required for a conventional abc-to-dq0 transformation. As a result, it is found in this article that d-, q-axes could couple with 0-axis in magnetically-isolated FSCW-IPM machines. Considering the second-order reluctance component, this phenomenon leads to third-harmonic injection in phase voltages during normal operation, which can be cancelled out in terms of line-to-line voltage for Y-connected three-phase system. However, for open-end-winding machine drives without …

Toward Additively Manufactured Electrical Machines: Opportunities And Challenges, Fan Wu, Ayman M. El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

With the growing interest in electrification and as hybrid and pure electric powertrains are adopted in more applications, electrical machine design is facing challenges in terms of meeting very demanding performance metrics, for example, high specific power, and harsh environments. This provides clear motivation to explore the impact of advanced materials and manufacturing on the performance of electrical machines. This article provides an overview of additive manufacturing (AM) approaches that can be used for constructing electrical machines, with a specific focus on additively manufactured iron core, winding, insulation, and permanent magnet, as well as cooling systems. Since there has only …

Techniques To Solve Decision-Making Problems, Dilnoz Tulkunovna Muhamediyeva, Bekmuratov Fayzievich Tulkun

Chemical Technology, Control and Management

Solving decision-making problems in poorly formalized systems only with the help of deterministic and probabilistic methods is insufficient. To do this, it is necessary to widely apply the methods of hybrid intelligent systems and, especially, the methods of “soft” calculations (SoftCalculation, SoftComputing) and the directions of ComputationalIntelligence — intelligent computing technologies that are emerging on this theoretical and methodological base. An immune - fuzzy algorithm for the synthesis of fuzzy inference systems (FIS) is proposed. A two-stage adaptive FIS synthesis algorithm is described. At the first stage, the initial fuzzy parameters are clustered in order to reduce the number of …

Scalable Universal Space Vector Pulse Width Modulation Scheme For Multilevel Inverters, Wei Qiao, Fa Chen, Liyan Qu

Department of Electrical and Computer Engineering: Faculty Publications

A scalable universal space vector pulse-width modulation (SVPWM) scheme for multilevel inverters is disclosed. In the disclosed SVPWM scheme, the modulation triable is quickly identified based on a coordinate transformation from an α-β coordinate system to a 120^o oblique coordinate system. Then, the duty cycles and switching states of the three vertices of the modulation triangle are determined by simple algebraic computations. In a switching period, any vertex of the modulation triangle can be flexibly selected as the start point to optimize the switching sequence with flexibly adjustable duty cycle(s) for the redundant switching state(s) according to specific applications.

Reliability Analysis Of Power Grids And Its Interdependent Infrastructures: An Interaction Graph-Based Approach, Upama Nakarmi

USF Tampa Graduate Theses and Dissertations

Large blackouts with significant societal and economic impacts result from cascade of failures in the transmission network of power grids. Understanding and mitigating cascading failures in power grids is challenging due to the large number of components and their complex interactions, wherein, in addition to the physical topology of the system, the physics of power flow and functional dependencies among components largely affect the spatial distribution and propagation of failures. In this dissertation, data-driven interaction graphs, which help in capturing the underlying interactions and influences among the components during cascading failures, are used for capturing the non-local nature of propagation …

Sensitivity Calculations Of High-Speed Optical Receivers Based On Electron-Apds, Vladimir Shulyak, Majeed M. Hayat, Jo Shien Ng

Electrical and Computer Engineering Faculty Research and Publications

Sensitivity of high-speed optical receivers is heavily influenced by the performance of the optical detectors used in the receivers, the data rate, and the target bit-error-rate (BER). A simulation model for sensitivity of optical receivers based on electron-avalanche photodiodes (e-APDs) is presented. It allows for the optimization of avalanche width and operating voltage to achieve the optimum receiver sensitivity for given bit rate and target BER. The effects modelled include inter-symbol interference (ISI), various dark current components (tunnelling, diffusion, and generation), current impulse duration, avalanche gain, and amplifier's noise. The model was demonstrated through simulations of Indium Arsenide (InAs) e-APDs. …

Wireless Underground Communications In Sewer And Stormwater Overflow Monitoring: Radio Waves Through Soil And Asphalt Medium, Usman Raza, Abdul Salam

Faculty Publications

Storm drains and sanitary sewers are prone to backups and overflows due to extra amount wastewater entering the pipes. To prevent that, it is imperative to efficiently monitor the urban underground infrastructure. The combination of sensors system and wireless underground communication system can be used to realize urban underground IoT applications, e.g., storm water and wastewater overflow monitoring systems. The aim of this article is to establish a feasibility of the use of wireless underground communications techniques, and wave propagation through the subsurface soil and asphalt layers, in an underground pavement system for storm water and sewer overflow monitoring application. …

A Lightweight Magnetorheological Actuator Using Hybrid Magnetization, Masoud Moghani, Mehrdad Kermani Ph.D., P.Eng.

Electrical and Computer Engineering Publications

Copyright © 2020, IEEE

This paper presents the design and validation of a lightweight Magneto-Rheological (MR) clutch, called Hybrid Magneto-Rheological (HMR) clutch. The clutch utilizes a hybrid magnetization using an electromagnetic coil and a permanent magnet. The electromagnetic coil can adjust the magnetic field
generated by the permanent magnet to a desired value, and fully control the transmitted torque. To achieve the maximum torque to mass ratio, the design of HMR clutch is formulated as a multiobjective optimization problem with three design objectives, namely the transmitted torque, the mass of the clutch, and the
magnetic field strength within the clutch …

Short-Term Electricity Price Forecasting In Deregulated Electricity Market Based On Enhanced Artificial Intelligence Techniques, Pourdaryaei Alireza

Student Works (2020-2029)

Electricity price forecasting is considered as one of prime factors for operation, planning and scheduling of price-setter market participants. However, possessing time variant, non-linear and non-stationary behaviors make the electricity price a complex signal. The main challenge in this area is providing highly accurate and efficient day-ahead price forecasting. A suitable feature selection technique, which is able to model the interacting features and nonlinearities of the forecast processes, is still required although researches have been performed for day-ahead forecasting. In this research, a hybrid electricity price forecasting methodology is proposed using two-stage feature selection method and optimization using adaptive neuro-fuzzy …

Investigating Patterns In Convolution Neural Network Parameters Using Probabilistic Support Vector Machines, Yuqiu Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Artificial neural networks(ANNs) are recognized as high-performance models for classification problems. They have proved to be efficient tools for many of today's applications like automatic driving, image and video recognition and restoration, big-data analysis. However, high performance deep neural networks have millions of parameters, and the iterative training procedure thus involves a very high computational cost. This research attempts to study the relationships between parameters in convolutional neural networks(CNNs). I assume there exists a certain relation between adjacent convolutional layers and proposed a machine learning model(MLM) that can be trained to represent this relation. The MLM's generalization ability is evaluated …

Ai-Assisted Network-Slicing Based Next-Generation Wireless Networks, Xuemin Shen, Jie Gao, Wen Wu, Kangjia Lyu, Mushu Li, Weihua Zhuang, Xu Li, Jaya Rao

Electrical and Computer Engineering Faculty Research and Publications

The integration of communications with different scales, diverse radio access technologies, and various network resources renders next-generation wireless networks (NGWNs) highly heterogeneous and dynamic. Emerging use cases and applications, such as machine to machine communications, autonomous driving, and factory automation, have stringent requirements in terms of reliability, latency, throughput, and so on. Such requirements pose new challenges to architecture design, network management, and resource orchestration in NGWNs. Starting from illustrating these challenges, this paper aims at providing a good understanding of the overall architecture of NGWNs and three specific research problems under this architecture. First, we introduce a network-slicing based …

Dual-Axis Solar Tracker, Bryan Kennedy

All Undergraduate Projects

Renewable energies, and fuels that are not fossil fuel-based, are one of the prolific topics of debate in modern society. With climate change now becoming a primary focus for scientists and innovators of today, one of the areas for the largest amount of potential and growth is that of the capturing and utilization of Solar Energy. This method involves using a mechanical system to track the progression of the sun as it traverses the sky throughout the day. A dual-axis solar tracker such as the one designed and built for this project, can follow the sun both azimuthally and in …

Eyecom: An Innovative Approach For Computer Interaction, Anam Mazhar

Theses, Dissertations and Capstones

The world is innovating rapidly, and there is a need for continuous interaction with the technology. Sadly, there do not exist promising options for paralyzed people to interact with the machines i.e., laptops, smartphones, and tabs. A few commercial solutions such as Google Glasses are costly and cannot be afforded by every paralyzed person for such interaction. Towards this end, the thesis proposes a retina-controlled device called EYECOM. The proposed device is constructed from off-the-shelf cost-effective yet robust IoT devices (i.e., Arduino microcontrollers, Xbee wireless sensors, IR diodes, and accelerometer). The device can easily be mounted on to the glasses; …

Load-Balancing Rendezvous Approach For Mobility-Enabled Adaptive Energy-Efficient Data Collection In Wsns, Jian Zhang, Jian Tang, Zhonghui Wang, Feng Wang, Gang Yu

Faculty and Student Publications

Copyright © 2020 KSII The tradeoff between energy conservation and traffic balancing is a dilemma problem in Wireless Sensor Networks (WSNs). By analyzing the intrinsic relationship between cluster properties and long distance transmission energy consumption, we characterize three node sets of the cluster as a theoretical foundation to enhance high performance of WSNs, and propose optimal solutions by introducing rendezvous and Mobile Elements (MEs) to optimize energy consumption for prolonging the lifetime of WSNs. First, we exploit an approximate method based on the transmission distance from the different node to an ME to select suboptimal Rendezvous Point (RP) on the …

Revisiting Lightweight Encryption For Iot Applications: Error Performance And Throughput In Wireless Fading Channels With And Without Coding, Yazid M. Khattabi, Mustafa M. Matalgah, Mohammed M. Olama

Faculty and Student Publications

© 2013 IEEE. Employing heavy conventional encryption algorithms in communications suffers from added overhead and processing time delay; and in wireless communications, in particular, suffers from severe performance deterioration (avalanche effect) due to fading. Consequently, a tremendous reduction in data throughput and increase in complexity and time delay may occur especially when information traverse resource-limited devices as in Internet-of-Things (IoT) applications. To overcome these drawbacks, efficient lightweight encryption algorithms have been recently proposed in literature. One of those, that is of particular interest, requires using conventional encryption only for the first block of data in a given frame being transmitted. …

Cooperative Relay Selection For Load Balancing With Mobility In Hierarchical Wsns: A Multi-Armed Bandit Approach, Jian Zhang, Jian Tang, Feng Wang

Faculty and Student Publications

© 2013 IEEE. Energy efficiency is the major concern in hierarchical wireless sensor networks(WSNs), where the major energy consumption originates from radios for communication. Due to notable energy expenditure of long-range transmission for cluster members and data aggregation for Cluster Head (CH), saving and balancing energy consumption is a tricky challenge in WSNs. In this paper, we design a CH selection mechanism with a mobile sink (MS) while proposing relay selection algorithms with multi-user multi-armed bandit (UM-MAB) to solve the problem of energy efficiency. According to the definition of node density and residual energy, we propose a conception referred to …

Ensemble Lung Segmentation System Using Deep Neural Networks, Redha A. Ali, Russell C. Hardie, Hussin K. Ragb

Electrical and Computer Engineering Faculty Publications

Lung segmentation is a significant step in developing computer-aided diagnosis (CAD) using Chest Radiographs (CRs). CRs are used for diagnosis of the 2019 novel coronavirus disease (COVID-19), lung cancer, tuberculosis, and pneumonia. Hence, developing a Computer-Aided Detection (CAD) system would provide a second opinion to help radiologists in the reading process, increase objectivity, and reduce the workload. In this paper, we present the implementation of our ensemble deep learning model for lung segmentation. This model is based on the original DeepLabV3+, which is the extended model of DeepLabV3. Our model utilizes various architectures as a backbone of DeepLabV3+, such as …

Recent Developments In The General Atomic And Molecular Electronic Structure System, Guiseppe M.J. Barca, Colleen Bertoni, Laura Carrington, Dipayan Datta, Nuwan De Silva, J. Emillano Deustua, Dmitri G. Fedorov, Jeffrey R. Cour, Anastasia O. Gunina, Emilie Guidez, Taylor Harville, Stephan Irle, Joe Ivanic, Karol Kowalski, Sarom S. Leang, Wei Li, Jesse J. Lutz, Ilias Magoulas, Joani Mato, Vladimir Mironov, Hiroya Nakata, Buu Q. Pham, Piotr Piecuch, David Poole, Spencer R. Pruitt, Alistair P. Rendell, Luke B. Roskop, Klaus Ruedenberg, Tosaporn Sattasathuchana, Michael W. Schmidt, Jun Shen, Lyudmila Slipchenko, Masha Sosonkina, Vaibhav Sundriyal, Ananta Tiwari, Jorge L. Galvez Vallejo, Bryce Westheimer, Marta Włoch, Peng Xu, Federico Zahariev, Mark S. Gordon

Computational Modeling & Simulation Engineering Faculty Publications

A discussion of many of the recently implemented features of GAMESS (General Atomic and Molecular Electronic Structure System) and LibCChem (the C++ CPU/GPU library associated with GAMESS) is presented. These features include fragmentation methods such as the fragment molecular orbital, effective fragment potential and effective fragment molecular orbital methods, hybrid MPI/OpenMP approaches to Hartree-Fock, and resolution of the identity second order perturbation theory. Many new coupled cluster theory methods have been implemented in GAMESS, as have multiple levels of density functional/tight binding theory. The role of accelerators, especially graphical processing units, is discussed in the context of the new features …