Digital Commons Network^™

Quantum Algorithm For Mining Frequent Patterns For Association Rule Mining, Abdirahman Alasow, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

Maximum frequent pattern generation from a large database of transactions and items for association rule mining is an important research topic in data mining. Association rule mining aims to discover interesting correlations, frequent patterns, associations, or causal structures between items hidden in a large database. By exploiting quantum computing, we propose an efficient quantum search algorithm design to discover the maximum frequent patterns. We modified Grover’s search algorithm so that a subspace of arbitrary symmetric states is used instead of the whole search space. We presented a novel quantum oracle design that employs a quantum counter to count the maximum …

Fragility Of The Florida Panhandle's Electrical Transmission Grid To Hurricanes, Zachary D. Schumann

Theses and Dissertations

The increased frequency and intensity of extreme weather events from climate change necessitates understanding impacts on critical infrastructure, particularly electrical transmission grids. One of the foundational concepts of a grid’s resilience is its robustness to extreme weather events, such as hurricanes. Resilience of the electric grid to high wind speeds is predicated upon the location and physical characteristics of the system components. Previous modeling assessments of electric grid failure were done at the systems level with assumptions on location and type of specific components. To facilitate more explicit adaptation metrics, accurate component-level information is needed. In this study, we build …

Suppressing White-Noise Interference For Orbital Angular Momentum Waves Via The Forward-Backward Dynamic Mode Decomposition, Yanming Zhang, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

When the orbital angular momentum (OAM)-carrying beam propagates in a highly boisterous environment, it causes the degradation of the OAM modes' purity, which brings the crosstalk in the demultiplexing process. To address this issue, we extend the dynamic mode decomposition (DMD) method to suppress white-noise interferences of OAM by using the forward-backward DMD (FBDMD) approach. The FBDMD-based scheme retrieves the noise-free DMD mapping matrix corresponding to the actual OAM's topological charges by combining the forward and backward DMD mapping matrix in the noisy environment and consequently reduces the crosstalk, particularly for sorting the superposed OAM modes. Numerical examples are provided …

Model For Calculating The Static Characteristics Of Hydraulic Systems Of Hydro Technical Buildings, Mirkhalil Ismailov, Dong Zhang, Farkhod Kasimov

Chemical Technology, Control and Management

Hydraulic mechanisms that actuate flat gates, widely used in hydraulic structures, are studied as hydraulic actuators of the system. Their static mathematical models are developed using an integrated methodology with a hydraulic pump, inlet and suction pipes, and internal and external resistance factors. Unlike existing mathematical models, the model developed in this paper allows a detailed description of the characteristics of hydraulic drives due to the fact that pressure losses in the throttle, regulator, and power amplifier, as well as local resistances in hydraulic pipelines, are taken into account.

Design Of International Airport Hybrid Renewable Energy System, Aviti Thadei Mushi

Tanzania Journal of Engineering and Technology (TJET)

This paper presents the design and simulation of a hybrid renewable energy system utilizing solar and wind energy sources with a backup generator. The demand for reliable electric energy in support of investments in large social and economic development activities such as airport operations has been an agenda worldwide. In Tanzania, Mwanza International Airport (MIA) expects to consume about 18 MVA of electric power annually to support its operations for the next 25 years. About 78-80% of the world's commercial energy comes from fossil fuels. Non-renewable fuels and other negative effects contribute to global warming through greenhouse gas emissions and …

Factors Influencing Total Productive Maintenance Implementation For Thermal Generation Plants, Ismail W. R. Taifa Dr

Tanzania Journal of Engineering and Technology (TJET)

This study accepts that the technical and administrative factors can amplify effective total productive maintenance (TPM) implementation at thermal generation plants. It is noted that there is a limited number of studies that have attempted to understand the subject of TPM implementation in the energy sector. Noting this shortcoming, the authors thought it crucial to generate empirical evidence on the factors influencing effective TPM implementation for thermal generation plants, with evidence from gas-fired plants. A sample of 88 respondents was selected and consulted. Data were collected through questionnaires and analyzed quantitatively by inferential statistics and qualitatively through thematic analysis using …

Method For Solving The Kinematics Inverse Problem For Moving Along A Trajectory Objects (As An Example Of Assembly Industrial Robots), Oripjon Olimovich Zaripov, Dildora Usmonovna Sevinova

Chemical Technology, Control and Management

The task of performing a technological operation in kinematic calculation of industrial robots and determining various kinematic parameters describing the efficiency of robots is solved. Among them, one of the urgent problems based on the analysis of the entire kinematics of the assembly industrial robot is the problem of solving the inverse problem of the kinematics of the manipulator positions, that is, the problem of determining the relative parameters that change the coordinates of the gripper according to the given position. The article presents a scheme that allows solving the inverse kinematics problem of an industrial robot manipulator moving in …

Algorithms For Multi-Factory Polynomial Modeling Of Technological Processes, Farrukh Do'stmirzayevich Jo'rayev, Murodjon Ashurqulovich Ochilov

Chemical Technology, Control and Management

The article reveals the meaning and essence of the modeling method in the study of complex technological processes based on the problematic aspects of building multifactorial relationships and the principles for their elimination. In the case of non-linearity of multifactorial connections of a complex system, the expediency of approximating such functions by polynomials is substantiated. The authors' ideas about the increasing importance of interpolation methods in practice against the background of the possibility of simplification based on the use of modern mathematical hardware and software for integration into the process of modeling and optimizing technological processes due to the complexity …

Anodic Electrocatalysis Of Glycerol Oxidation For Hybrid Alkali/Acid Electrolytic Hydrogen Generation, Xin Feng, Bo-Wen Liu, Ke-Xin Guo, Lin-Feng Fan, Gen-Xiang Wang, Su-Qin Ci, Zhen-Hai Wen

Journal of Electrochemistry

Electrolytic hydrogen production is heavily restricted by high-energy consumption majorly due to the relatively high potential of anodic oxygen evolution reaction (OER). Development of OER-alternative reaction at the anode has been recently proposed as a promising pathway to address the associated issues. In this work, we report a hybrid acid/alkali dual-electrolyte electrolyzer by coupling acidic hydrogen evolution reaction (HER) using commercial Pt/C cathode with alkaline Electrocatalytic glycerol oxidation (GOR) which is implemented by developing a nickel foam (NF) supporting Co₃O₄ nanosheets anode that shows low overpotential and high selectivity toward GOR for formate production. The hybrid acid/alkali …

A Representation For Many Player Generalized Divide The Dollar Games, Garrison Greenwood, Daniel Ashlock

Electrical and Computer Engineering Faculty Publications and Presentations

Divide the dollar is a simplified version of a two player bargaining problem game devised by John Nash. The generalized divide the dollar game has n > 2 players. Evolutionary algorithms can be used to evolve individual players for this generalized game but representation—i.e., a genome plus a move or search operator(s)—must be carefully chosen since it affects the search process. This paper proposes an entirely new representation called a demand matrix. Each individual in the evolving population now represents a collection of n players rather than just an individual player. Players use previous outcomes to decide their choices (bids) in …

Opal Actigraphy (Activity And Sleep) Measures Compared To Actigraph: A Validation Study, Vrutangkumar Shah, Barbara H. Brumbach, Sean Pearson, Paul Vasilyev, James Mcnames, Multiple Additional Authors

Electrical and Computer Engineering Faculty Publications and Presentations

Physical activity and sleep monitoring in daily life provide vital information to track health status and physical fitness. The aim of this study was to establish concurrent validity for the new Opal Actigraphy solution in relation to the widely used ActiGraph GT9X for measuring physical activity from accelerometry epic counts (sedentary to vigorous levels) and sleep periods in daily life. Twenty participants (age 56 + 22 years) wore two wearable devices on each wrist for 7 days and nights, recording 3-D accelerations at 30 Hz. Bland–Altman plots and intraclass correlation coefficients (ICCs) assessed validity (agreement) and test–retest reliability between ActiGraph …

Semiconductor Devices, Sheila D. Hill Pe

KSU Distinguished Course Repository

3 Class Hours, 0 Laboratory Hours, 3 Credit Hours Prerequisites: CHEM 1211, CHEM 1211L, EE 1000
This course effectively applies the knowledge of chemistry and physics to understand the operating principles of various semiconductor devices. The course covers topics starting from the fundamental concepts of atomic and crystal structure, crystal growth, impurity doping and energy bands to the in-depth device operation and quantitative analysis of p-n junction diode, metal-semiconductor contacts and Schottky diode, BJTs and MOSFETs. Also fundamental operating principles of optoelectronic devices such as, LEDs and photodiodes are discussed. Simple device simulation components reinforces the understanding of various critical …

Session 12: Analysis Of State And Parameter Estimation Techniques Using Dynamic Perturbation Signals, Timothy M. Hansen

SDSU Data Science Symposium

The trend in electric power systems is the displacement of traditional synchronous generation (e.g., coal, natural gas) with renewable energy resources (e.g., wind, solar photovoltaic) and battery energy storage. These energy resources require power electronic converters (PECs) to interconnect to the grid and have different response characteristics and dynamic stability issues compared to conventional synchronous generators. As a result, there is a need for validated models to study and mitigate PEC-based stability issues, especially for converter dominated power systems (e.g., island power systems, remote microgrids).

This presentation will introduce methods related to dynamic state and parameter estimation via the design …

Identification Of Volatile Organic Liquids By Combining An Array Of Fiber-Optic Sensors And Machine Learning, Wassana Naku, Anand K. Nambisan, Muhammad Roman, Chen Zhu, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

In This Paper, We Report an Array of Fiber-Optic Sensors based on the Fabry-Perot Interference Principle and Machine Learning-Based Analyses for Identifying Volatile Organic Liquids (VOLs). Three Optical Fiber Tip Sensors with Different Surfaces Were Included in the Array of Sensors to Improve the Accuracy for Identifying Liquids: An Intrinsic (Unmodified) Flat Cleaved Endface, a Hydrophobic-Coated Endface, and a Hydrophilic-Coated Endface. the Time-Transient Responses of Evaporating Droplets from the Optical Fiber Tip Sensors Were Monitored and Collected Following the Controlled Immersion Tests of 11 Different Organic Liquids. a Continuous Wavelet Transform Was Used to Convert the Time-Transient Response Signal into …

Experimental And Computational Analysis Of Broadband Thz Photoconductive Antennas, Zachary Uttley, Jose Santos Batista, Bilal Pirzada, Magda El-Shenawee

Electrical Engineering Faculty Publications and Presentations

The work presents the fabrication and measurements of four LT-GaAs photoconductive terahertz (THz) antennas with different geometries of metallic electrodes. The goal is to analyze the overall bandwidth of the antennas through a comparison between the spectra of the generated photocurrent in the antenna gap, the radiated electric field THz pulse, and the S₁₁ parameter of the metallic electrodes. The photocurrent density and the S₁₁ parameters are computed using COMSOL multiphysics, while the generated THz pulse was experimentally measured using a time-domain spectroscopy system. The polarizations of the photoconductive antennas are experimentally measured, using x-cut quartz crystal halfwave …

Noise2clean: Cross-Device Side-Channel Traces Denoising With Unsupervised Deep Learning, Honggang Yu, Mei Wang, Xiyu Song, Haoqi Shan, Hongbing Qiu, Junyi Wang, Kaichen Yang

Michigan Tech Publications, Part 1

Deep learning (DL)-based side-channel analysis (SCA) has posed a severe challenge to the security and privacy of embedded devices. During its execution, an attacker exploits physical SCA leakages collected from profiling devices to create a DL model for recovering secret information from victim devices. Despite this success, recent works have demonstrated that certain countermeasures, such as random delay interrupts or clock jitters, would make these attacks more complex and less practical in real-world scenarios. To address this challenge, we present a novel denoising scheme that exploits the U-Net model to pre-process SCA traces for “noises” (i.e., countermeasures) removal. Specifically, we …

Digital Twin Applications In 3d Concrete Printing, Yuxin Wang, Farhad Aslani, Arcady Dyskin, Elena Pasternak

Research outputs 2022 to 2026

The benefits of 3D concrete printing (3DCP) include reducing construction time and costs, providing design freedom, and being environmentally friendly. This technology is expected to be effective in addressing the global house shortage. This review highlights the main 3DCP applications and four critical challenges. It is proposed to combine 3D concrete printing with Digital Twin (DT) technology to meet the challenges the 3DCP faces and improve quality and sustainability. This paper provides a critical review of research into the application of DT technology in 3DCP, categorize the applications and directions proposed according to different lifecycles, and explore the possibility of …

A Computational Offloading Optimization Scheme Based On Deep Reinforcement Learning In Perceptual Network, Yongli Xing, Tao Ye, Sami Ullah, Muhammad Waqas, Hisham Alasmary, Zihui Liu

Research outputs 2022 to 2026

Currently, the deep integration of the Internet of Things (IoT) and edge computing has improved the computing capability of the IoT perception layer. Existing offloading techniques for edge computing suffer from the single problem of solidifying offloading policies. Based on this, combined with the characteristics of deep reinforcement learning, this paper investigates a computation offloading optimization scheme for the perception layer. The algorithm can adaptively adjust the computational task offloading policy of IoT terminals according to the network changes in the perception layer. Experiments show that the algorithm effectively improves the operational efficiency of the IoT perceptual layer and reduces …

A Novel Data-Driven Method For Two-Dimensional Angles Finding Via Uniform Rectangular Array With Automatic Pairing, Yanming Zhang, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

A new hybrid dynamic mode decomposition (HDMD) algorithm is proposed to estimate the azimuth and elevation angles of multiple independent sources for two-dimensional (2D) massive MIMO systems with the uniform rectangular array (URA). To this end, the proposed hybrid scheme integrates the modified DMD with the augmented DMD. By treating the received data as spatial-spatial correlated signals, the modified DMD is first used to decompose these signals into spatial DMD spectrum and corresponding spatial dynamic modes. The obtained spatial DMD spectrum directly yields the electrical angle in the y-direction. Then, the corresponding electrical angle in the x-direction is computed using …

An Epileptic Seizure Detection Method From Eeg Signals Based On A Classifier-Driven Feature Reduction Technique, Raymond N. Kamel

Theses and Dissertations

Epileptic seizure detection can improve the quality of life of epileptic patients, allow for more accurate medication, and minimize the risk of sudden unexpected death in epilepsy (SUDEP). This thesis work aims to develop a robust and stable algorithm for epileptic seizure detection through the classification of EEG signals. To achieve this aim, a methodology is proposed to develop a classifier that can differentiate between the healthy (normal), interictal, and ictal states of EEG signals, while maximizing the classification accuracy and minimizing the computational redundancy. The main pillar upon which this methodology is designed is using a problem-specific classifier-driven feature …

A Novel Approach For Optimal Sizing Of Stand-Alone Solar Pv Systems With Power Quality Considerations, Aakash Hassan, Octavian Bass, Yasir M. Al-Abdeli, Martin Masek, Mohammad A. S. Masoum

Research outputs 2022 to 2026

Designing reliable and cost-effective solar PV systems with compliance to national and international power quality standards is critical for their economical, efficient, and safe operation. The conventional approaches currently being used to optimally size the solar PV systems generally ignore power quality criteria during the initial design phase. This paper fills this gap by presenting a novel Genetic Algorithm (GA) based strategy to design a stand-alone solar PV system featuring optimal system size with conformance to power quality standards. MATLAB/Simulink environment was used to develop a detailed model of solar PV system, including a robust control mechanism for maximum power …

In-Field Solar Panel Assessment And Fault Diagnosis, Muhammad Elgamal

Theses and Dissertations

Photovoltaic energy is a green energy that suit from small houses to high-power stations spanning large areas. In such large areas, monitoring individual panels can be a tedious task, especially if it was required to identify operational faults of these panels. Photovoltaic 4.0 technology depend on collecting data from each station and feeding them to a central processing system that can analyze operation data and hopefully locate when a fault happens. In such method, it is crucial to be accurate as much as possible and for measuring device to be accurate as well to have a clear judgement. In this …

Design Of A Non-Destructive System For Arctic Permafrost Detection Via High Frequency Electromagnetic Induction, Gray Dominic Thurston

Theses and Dissertations

Electromagnetic induction (EMI) sensors have been utilized in the past by the United States Army Corps of Engineers as a method of detecting unexploded ordnance (UXO). Recently, an EMI instrument was constructed that extended the traditional EMI frequency range from 100 kHz to 15 MHz to aid in the detection of nonmetallic ordnance, landmines, and improvised explosive devices. Building on this research, the iFROST mapper project aims to use the same high-frequency (HF) EMI technique to characterize arctic soil and subsurface permafrost deposits. Based on a device used by the US Army for UXO detection, an HF EMI instrument was …

Wavelet-Based Harmonic Magnitude Measurement In The Presence Of Interharmonics, Flavio Costa, Stefan Häselbarth, Sergey Yanchenko, Kai Strunz, Aurenice M. Oliveira

Michigan Tech Publications, Part 1

The increasing proliferation of power electronic converters, nonlinear loads, and distributed generation are leading to increased levels of harmonic and interharmonics in power networks. As a consequence, power quality (PQ) has become a critical performance indicator for power utilities and end-users. This study proposes a novel harmonic estimation method based on the real-time stationary discrete wavelet packet transform (RT-SDWPT). The proposed technique decomposes an input signal into frequency bands with harmonic information at cutoff frequencies and uses a compensation strategy to estimate root mean square (RMS) values of harmonics at every sampling period. The performance and effectiveness of the proposed …

Enhanced Fractional Adaptive Processing Paradigm For Power Signal Estimation, Naveed Ishtiaq Chaudhary, Zeshan Aslam Khan, Muhammad Asif Zahoor Raja, Iqra Ishtiaq Chaudhary

Articles

Fractional calculus tools have been exploited to effectively model variety of engineering, physics and applied sciences problems. The concept of fractional derivative has been incorporated in the optimization process of least mean square (LMS) iterative adaptive method. This study exploits the recently introduced enhanced fractional derivative based LMS (EFDLMS) for parameter estimation of power signal formed by the combination of different sinusoids. The EFDLMS addresses the issue of fractional extreme points and provides faster convergence speed. The performance of EFDLMS is evaluated in detail by taking different levels of noise in the composite sinusoidal signal as well as considering various …

Prediction Of Ka-Band Radar Cross Section With Thz Scale Models With Varying Surface Roughness, Andrew J. Huebner

Browse all Theses and Dissertations

Radar cross section (RCS) of electrically large targets can be challenging and expensive to measure. The use of scale models to predict the RCS of such large targets saves time and reduces facility requirements. This study investigates Ka-band (27 to 29 GHz) RCS prediction from scale model measurements at 500 to 750 GHz. Firstly, the coherent quasi-monostatic turntable RCS measurement system is demonstrated. Secondly, three aluminum 18:1 scale dihedrals with surface roughness up to 218 icroinches are measured to investigate how the roughness affects the Ka-band prediction. The measurements are compared to a parametric scattering model for the specular response, …

A Hybrid Multifunctional Physicochemical Sensor Suite For Continuous Monitoring Of Crop Health, Nafize Ishtiaque Hossain, Shawana Tabassum

Electrical Engineering Faculty Publications and Presentations

This work reports a first-of-its-kind hybrid wearable physicochemical sensor suite that we call PlantFit for simultaneous measurement of two key phytohormones, salicylic acid, and ethylene, along with vapor pressure deficit and radial growth of stem in live plants. The sensors are developed using a low-cost and roll-to-roll screen printing technology. A single integrated flexible patch that contains temperature, humidity, salicylic acid, and ethylene sensors, is installed on the leaves of live plants. The strain sensor with in-built pressure correction capability is wrapped around the plant stem to provide pressure-compensated stem diameter measurements. The sensors provide real-time information on plant health …

Towards Explainable Ai Using Attribution Methods And Image Segmentation, Garrett J. Rocks

Honors Undergraduate Theses

With artificial intelligence (AI) becoming ubiquitous in a broad range of application domains, the opacity of deep learning models remains an obstacle to adaptation within safety-critical systems. Explainable AI (XAI) aims to build trust in AI systems by revealing important inner mechanisms of what has been treated as a black box by human users. This thesis specifically aims to improve the transparency and trustworthiness of deep learning algorithms by combining attribution methods with image segmentation methods. This thesis has the potential to improve the trust and acceptance of AI systems, leading to more responsible and ethical AI applications. An exploratory …

Investigating The Application And Sustained Effects Of Stochastic Resonance On Haptic Feedback Sensitivity In A Laparoscopic Task, Kara Liane Wilcox

Browse all Theses and Dissertations

Stochastic resonance (SR) is a phenomenon that can enhance the detection or transmission of weak signals by adding random noise to a non-linear system. SR introduced into the human motor control system as a subthreshold mechanical vibration has shown promise to improve sensitivity to haptic feedback. SR can be valuable in a laparoscopic surgery application, where haptic feedback is critical. This research sought to find if applying SR to the human motor control system improves performance in a laparoscopic probing task, if the performance differs based on the location of stochastic resonance application, and if there are sustained effects from …

Utilizing Data Analytics On Single-Phase Ac Arc Flash Testing And Model Development, Po-Chen Chen

Electrical Engineering Dissertations - Archive

Arc flash events could result in injuries, fatalities, and lead to severe medical expenses, equipment replacement cost, and even litigation, fines, and loss of business. Such events could also tremendously traumatize the personnel psychosocially and neurologically. Therefore, it is critical to accurately understand the potential arc flash hazards from all the real applications. Yet, due to the random complex nature of arc flash events and great number of uncertain variables involved, there are challenges to provide mathematical models for equipment designers in determining the arc-flash fault current and the incident energy of various types of events. The early arc flash …