Electrical and Computer Engineering Commons^™

Modular Open-Source Design Of Pyrolysis Reactor Monitoring And Control Electronics, Finn K. Hafting, Daniel G. Kulas, Etienne Michels, Sarvada Chipkar, Stefan Wisniewski, David Shonnard, Joshua M. Pearce

Michigan Tech Publications

Industrial pilot projects often rely on proprietary and expensive electronic hardware to control and monitor experiments. This raises costs and retards innovation. Open-source hardware tools exist for implementing these processes individually; however, they are not easily integrated with other designs. The Broadly Reconfigurable and Expandable Automation Device (BREAD) is a framework that provides many open-source devices which can be connected to create more complex data acquisition and control systems. This article explores the feasibility of using BREAD plug-and-play open hardware to quickly design and test monitoring and control electronics for an industrial materials processing prototype pyrolysis reactor. Generally, pilot-scale pyrolysis …

Microwave-Photonic Vernier Effect Enabled High-Sensitivity Fiber Bragg Grating Sensors For Point-Wise And Quasi-Distributed Sensing, Chen Zhu, Osamah Alsalman, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

This paper reports a sensitivity-improved fiber Bragg grating (FBG) sensor system based on microwave-photonic interferometry and the Vernier effect. an incoherent microwave photonics system based on a broadband light source is employed to interrogate the FBG sensor using the wavelength-to-delay mapping technique combined with interferometry. Specifically, the sensing FBG together with a reference FBG is used to construct a microwave photonics Michelson interferometer (MI). Changes in the Bragg wavelength of the sensing FBG subject to external perturbations are encoded into the spectral shifts of the microwave interferogram of the MI. a virtual interferometer is then generated from the sensing MI …

Vertical Free-Swinging Photovoltaic Racking Energy Modeling: A Novel Approach To Agrivoltaics, Koami Soulemane Hayibo, Joshua M. Pearce

Electrical and Computer Engineering Publications

To enable lower-cost building materials, a free-swinging bifacial vertical solar photovoltaic (PV) rack has been proposed, which complies with Canadian building codes and is the lowest capital-cost agrivoltaics rack. The wind force applied to the free-swinging PV, however, causes it to have varying tilt angles depending on the wind speed and direction. No energy performance model accurately describes such a system. To provide a simulation model for the free-swinging PV, where wind speed and direction govern the array tilt angle, this study builds upon the open-source System Advisor Model (SAM) using Python. After the SAM python model is validated, a …

Recycled Polycarbonate And Polycarbonate/Acrylonitrile Butadiene Styrene Feedstocks For Circular Economy Product Applications With Fused Granular Fabrication-Based Additive Manufacturing, Alessia Romani, Marinella Levi, Joshua M. Pearce

Electrical and Computer Engineering Publications

Distributed recycling and additive manufacturing (DRAM) holds enormous promise for enabling a circular economy. Most DRAM studies have focused on single thermoplastic waste stream. This study takes three paths forward from the previous literature: 1) expanding DRAM into high-performance polycarbonate/ acrylonitrile butadiene styrene (PC/ABS) blends, 2) extending PC/ABS blend research into both recycled materials and into direct fused granular fabrication (FGF) 3-D printing and 3) demonstrating the potential of using recycled PC/ABS feedstocks for new applications in circular economy contexts. A commercial open source large-format FGF 3-D printer was modified and used to assess the different printability and accuracy of …

Learning And Control For Complex Multiagent Systems, Vrushabh S. Donge

Electrical Engineering Dissertations - Archive

Complex multiagent systems (MASs) are pervasive in various fields, from power system networks, and autonomous robotics to traffic management, where groups of agents interact to achieve collective objectives. Effective coordination and control of such systems pose significant challenges due to their inherent complexity and the need for adaptive, efficient strategies. This dissertation explores combining data-driven approaches, reinforcement learning (RL), and control theory to address these challenges. We present novel methodologies for learning and controlling complex MASs, emphasizing the development of adaptive algorithms that can autonomously adapt to dynamic environments, collaborate with other agents, and optimize system-wide performance. Our findings offer …

Simulation Modelling Of Silicon Gated Field Emitter Based Electronic Circuits, Robert Hay, Ranajoy Bhattacharya, Winston Chern, Girish Rughoobur, Akintunde I. Akinwande, Jim Browning

Electrical and Computer Engineering Faculty Publications and Presentations

Vacuum transistors (VTs) are promising candidates in electronics due to their fast response and ability to function in harsh environments. In this study, several oscillator and logic gate circuit simulations using VTs are demonstrated. Silicon-gated field emitter arrays (Si-GFEAs) with 1000 × 1000 arrays were used experimentally to create a VT model. First, transfer and output characteristics sweeps were measured, and based on those data, an LTspice vacuum transistor (VT) model was developed. Then, the model was used to develop Wein and Ring oscillator circuits. The circuits were analytically simulated using LTspice, where the collector bias voltage was 200 V …

Applications Of The Guided-Mode Resonance Sensor In Multiparametric, Transmissive, And Picomolar Regimes, Joseph Anthony Buchanan-Vega

Electrical Engineering Dissertations - Archive

Guided-mode resonance (GMR) sensors are developed and implemented for multiparametric label-free sensing, transmission sensing, enhanced reflection sensing, and low analyte concentration sensing; these are the topics presented in this work. The complete biosensor – capable of label-free multiparametric data collection – is designed, fabricated, and implemented. Multiparametric data collection has previously been relegated to one variable on the sensor surface and one bulk media variable. We use a lookup table and the novel application of an inversion algorithm to simultaneously determine two variables on the sensor surface and one bulk media variable. Multiparametric data sets are required to monitor multiple …

Resilient, Sustainable, And Secure Systems Support For Ultra-Low-Power Computational Things, Nicole Tobias

All Dissertations

Wireless battery-free and energy-harvesting devices are expanding the reach and vision of the Internet of Things, where trillions of embedded computational things interconnect ubiquitously around us and inform many different aspects of our everyday lives. Designing these systems without batteries and interconnecting wires lowers maintenance, environmental, and economic costs while also extending device lifetime and deployment opportunities. Over the last decade, research on these ultra-low-power embedded sensors and systems has dramatically increased — enabling new and exciting prospects in many different scientific fields, from smart building and health monitoring applications to animal and activity tracking.

These systems are not without …

Ism-Band Energy Harvesting Wireless Sensor Node, Fnu Naveed

Graduate Theses and Dissertations

In recent years, the interest in remote wireless sensor networks has grown significantly, particularly with the rapid advancements in Internet of Things (IoT) technology. These networks find diverse applications, from inventory tracking to environmental monitoring. In remote areas where grid access is unavailable, wireless sensors are commonly powered by batteries, which imposes a constraint on their lifespan. However, with the emergence of wireless energy harvesting technologies, there is a transformative potential in addressing the power challenges faced by these sensors. By harnessing energy from the surrounding environment, such as solar, thermal, vibrational, or RF sources, these sensors can potentially operate …

Characterization Of Highly Doped N-Type And P-Type Silicon Carbide Ohmic Contacts, Tanner Rice

Graduate Theses and Dissertations

Silicon Carbide (SiC) is a rather new material that possesses unparalleled properties when compared to Silicon. Due to its larger band gap alongside other thermal properties, SiC can survive in hotter, more radiation intensive environments, whether that be within the crust of the earth or in the reaches of space. As a desirable semiconductor for these applications, CMOS is an especially important device due to its low power consumption. However, creating a good contact between the metal and semiconductor optimally requires two different metals for the n -type and the p-type semiconductor. This greatly increases the processing time, as separate …

Towards A Spaceworthy Cots Graphics Processing Unit: Hardware Performance Counter Based Symptomatic Fault Detection, Antonio E. Teijeiro

Open Access Theses & Dissertations

Ionizing radiation remains an obstacle to bringing graphics processing units (GPU) to space. Since radiation-hardened GPU chips are technically infeasible at the moment, an emphasis has been placed on the adaptation of commercial-off-the-shelf (COTS) GPUs to the space domain. At present, GPU error detection methods require redundant computation. This thesis work explores the utilization of hardware performance counters, special registers useful for monitoring internal GPU hardware events, for symptom-based, lightweight error detection. Hardware performance counters are successfully utilized for the detection of anomalous single event upsets in the L0 instruction cache, the load store unit, the arithmetic and logic unit, …

Investigating Combined Extreme Weather Effects On Solar Module Through Hardware And Simulink Performance Evaluation, Amir Botros

Boise State University Theses and Dissertations

Worldwide adoption of photovoltaic (PV) cells, which use the photovoltaic effect to convert solar energy into electricity, has led to their emergence as a significant source of electricity production. As the number of PV installations continues to grow, understanding the impact of environmental factors on solar module performance becomes paramount.

Factors such as intermittency, cloud cover, shading, and nighttime unavailability significantly affect the efficiency and longevity of solar modules. However, there is a shortage of research connecting extreme weather conditions to overall module performance, hindering informed implementation decisions.

This study addresses the need for continuous monitoring of solar systems under …

Diverse Impacts Of Commercial Ev Charging Load Infrastructure On Electric Power Grid, Antonio Avila

Open Access Theses & Dissertations

With the rising prominence of electric vehicles (EVs) in the transportation sector, this thesis delves into the critical nexus between commercial EVs, charging infrastructure, and their consequential impacts on the power grid. As commercial EVs, particularly medium and heavy-duty variants, gain traction as viable alternatives in the commercial transportation landscape, understanding the intricacies of their charging requirements becomes paramount. This thesis critically examines the technological and logistical dimensions of the charging infrastructure for supporting commercial EVs, evaluating the consequential implications on the power grid and proposing strategies for mitigation through the utilization of Distributed Energy Resources (DERs). In tandem with …

Data-Driven Scheme For Joint Estimation Of Direction-Of-Arrival And Frequency With Uniform Linear Array, Yanming Zhang, Lijun Jiang, Hsi Tseng Chou

Electrical and Computer Engineering Faculty Research & Creative Works

This article presents a two-step dynamic mode decomposition (TSDMD) approach to estimate the direction of arrival (DOA) and frequency for multiple narrow-band sources with single uniform linear array (ULA). The proposed algorithm first decomposes the receiving spatial-temporal data into temporal dynamic modes and corresponding spatial spectrum that yields the DOA information. Then the decomposed temporal dynamic modes are analyzed via the augmented DMD to retrieve the frequency information. The estimated DOAs and frequencies are automatically paired without the extra computational cost with such a temporal-spectral correlated decomposition scheme. Also, the obtained spatial spectrum distribution implies the actual number of the …

Space-Time-Frequency Characterization In Electromagnetic Near-Field Scanning: A Data-Driven Approach, Yanming Zhang, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

Near-field scanning has become a widely used tool for diagnosing electromagnetic compatibility and electromagnetic interference issues. However, the transient signal of the device under test often contains multiple frequency bands and exhibits nonstationarity, which poses a challenge for near-field scanning analysis. To address this issue, this article presents a method for analyzing time-resolved near-field radiation based on multiresolution dynamic mode decomposition (MRDMD). The MRDMD approach recursively and hierarchically applies the traditional dynamic mode decomposition (DMD) method. The distribution of DMD eigenvalues determines the slow and fast modes in each level's decomposition, where the slow modes are preserved, and the fast …

Electromagnetic-Thermal Co-Design Of Base Station Antennas With All-Metal Ebg Structures, Huan Huan Zhang, Jun Bo Chao, Yi Wei Wang, Ying Liu, Yun Xue Xu, Heming Yao, Lijun Jiang, Xiang Hua Li

Electrical and Computer Engineering Faculty Research & Creative Works

In order to improve the heat dissipation capability of the 5G base station, the electromagnetic and thermal performances of a base station antenna array are co-designed by adopting all-metal electromagnetic bandgap (EBG) structures. The geometrical dimension of the EBG structure is determined through balancing the electromagnetic and thermal performances of the antenna array. The operating frequency band (voltage standing wave ratio (VSWR) < 1.5) of the proposed antenna array can cover 3.4-3.8 GHz. Its realized gains, isolation, cross-polarized discrimination ratio, and half-power beamwidth are satisfactory compared with other state-of-the-art base station antennas. Most importantly, more than 9 C temperature reduction can be observed when comparing the heat dissipation capability of the proposed antenna array with the reference antenna array.

Cost Minimizing Energy Management Control Scheme For Microgrids Considering Dynamic Electricity Prices, Levi T. Miller

All Graduate Theses and Dissertations, Fall 2023 to Present

As countries develop and technology improves, the world is using more energy than ever before. This fact along with several other political, social, and economic factors has resulted in simultaneous energy and climate crises. A partial solution to both problems is bringing clean energy sources of electricity closer to the customers who use that energy. A microgrid is a smaller version of the national electric grid where smaller electricity generators are networked with local consumers and controlled independently of the main grid. Because control of electricity sources and loads are transferred to local controllers, the flexibility with which they can …

Design And Modeling Of A Hybrid-Electric Drone System For Conversion, Mark Atttaalla

Electrical Engineering

With the increased use of unmanned aerial vehicles (UAVs), the need for long range high capacity (>1kg) drones has also increased. While these drones do exist, they use complicated and complex technology that proportionately increases the price and barrier to entry for these drones. The goal of this paper is to look at different designs for hybrid electric drones, model the series-hybrid design, and create a low-cost alternative drone that uses off the shelf components. A primary purpose for this document is to present the information required to recreate a similar

Electronic Note-String Detector, Gavin Garcia-Rossi, Tommy Smail

Electrical Engineering

As the virtual space has become a dominant part of everyone’s day-to-day lives, many normal face-to-face interactions and services have not yet been facilitated by adapting technology. One of these prevailing areas is music lessons. Over Zoom meetings, or other virtual platforms, it is tremendously challenging to teach students. These challenges include recognizing student mistakes audibly and visually, and being able to give confident feedback on the incorrect notes played by learning musicians. Without having to delve into improving the complex systems that would be required to improve audio, video, and connection quality of these connections, we have another solution …

Systematic Literature Review On Ontology-Based Indonesian Question Answering System, Fadhila Tangguh Admojo, Adidah Lajis, Haidawati Nasir

Knowledge Engineering and Data Science

Question-Answering (QA) systems at the intersection of natural language processing, information retrieval, and knowledge representation aim to provide efficient responses to natural language queries. These systems have seen extensive development in English and languages like Indonesian present unique challenges and opportunities. This literature review paper delves into the state of ontology-based Indonesian QA systems, highlighting critical challenges. The first challenge lies in sentence understanding, variations, and complexity. Most systems rely on syntactic analysis and struggle to grasp sentence semantics. Complex sentences, especially in Indonesian, pose difficulties in parsing, semantic interpretation, and knowledge extraction. Addressing these linguistic intricacies is pivotal for …

Eeg Classification While Listening To Murottal Al-Quran And Classical Music Using Random Forest Method, Heni Sumarti, Fahira Septiani, Agus Sudarmanto, Wahyu Caesarendra, Rizki Edmi Edison

Knowledge Engineering and Data Science

This study is aimed to classify the brain activity of adolescents associated with audio stimuli; murottal Al-Quran and classical music. The raw data were filtered using Independent Component Analisys (ICA) and followed by band-pass filter in Python on the Google Colab Extraction was processed with Power Spectral Density (PSD) and the Random Forest Method in Weka Machine Learning was used for classification. The research results showed the same results between the two types of stimulation, namely the order of brain waves from highest to lowest were delta, alpha, theta and beta. The average brain waves of teenagers when given murottal …

Deep Learning Approaches With Optimum Alpha For Energy Usage Forecasting, Aji Prasetya Wibawa, Agung Bella Putra Utama, Ade Kurnia Ganesh Akbari, Akhmad Fanny Fadhilla, Alfiansyah Putra Pertama Triono, Andien Khansa’A Iffat Paramarta, Faradini Usha Setyaputri, Leonel Hernandez

Knowledge Engineering and Data Science

Energy use is an essential aspect of many human activities, from individual to industrial scale. However, increasing global energy demand and the challenges posed by environmental change make understanding energy use patterns crucial. Accurate predictions of future energy consumption can greatly influence decision-making, supply-demand stability and energy efficiency. Energy use data often exhibits time-series patterns, which creates complexity in forecasting. To address this complexity, this research utilizes Deep Learning (DL), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Gated Recurrent Unit (GRU) models. The main objective is to improve the accuracy of …

The Effect Of The Number Of Hidden Layers On The Performance Of Deep Q-Network For Traveling Salesman Problem, Benzfica Hanif, Aisyah Larasati, Rudi Nurdiansyah, Trung Le

Knowledge Engineering and Data Science

The Traveling Salesman Problem (TSP) effectively represents the complex distribution issues encountered by couriers, who must carefully plan a route that includes all customer addresses while minimizing the distance traveled. As the magnitude of deliveries and the range of destinations expand, the courier's responsibility becomes progressively challenging. In this particular context, the objective of our research is to expand the existing knowledge and explore the complete capabilities of Deep Q-Network (DQN) models in order to achieve the most efficient route determination. This endeavor can potentially bring about significant changes in the courier and delivery service sector. The foundation of our …

Stacked Lstm-Gru Long-Term Forecasting Model For Indonesian Islamic Banks, Yayat Sujatna, Adhitio Satyo Bayangkari Karno, Widi Hastomo, Nia Yuningsih, Dody Arif, Sri Setya Handayani, Aqwam Rosadi Kardian, Ire Puspa Wardhani, L.M Rasdi Rere

Knowledge Engineering and Data Science

The development of the Islamic banking industry in Indonesia has become a significant concern in recent years, with rapid growth in the number of banks operating based on Sharia principles. To face emerging challenges and opportunities, a deep understanding of the long-term financial behavior of Islamic banks is becoming increasingly important. This study aims to predict the share price of PT Bank Syariah Indonesia Tbk, over 28 days using the LSTM-GRU stack. The observation stage includes importing the dataset, data separation, model variations, the training process, output, and evaluation. Observations were conducted using 10 model variations from 4 stacks of …

Comparison Of Machine Learning Algorithms For Species Family Classification Using Dna Barcode, Lala Septem Riza, M Ammar Fadhlur Rahman, Yudi Prasetyo, Muhammad Iqbal Zain, Herbert Siregar, Topik Hidayat, Khyrina Airin Fariza Abu Samah, Miftahurrahma Rosyda

Knowledge Engineering and Data Science

Classifying plant species within the Liliaceae and Amaryllidaceae families presents inherent challenges due to the complex genetic diversity and overlapping morphological traits among species. This study explores the difficulties in accurate classification by comparing 11 supervised learning algorithms applied to DNA barcode data, aiming to enhance the precision of species family classification in these taxonomically intricate plant families. The ribulose-1,5-bisphosphate carboxylase-oxygenase large sub-unit (rbcL) gene, selected as a DNA barcode locus for plants, is used to represent species within the Amaryllidaceae and Liliaceae families. The experimental results demonstrate that nearly all tested models achieve accurate species classification into the appropriate …

Multivariate Analysis Approach To Factor-Affected Tuberculosis Disease, Zuli Agustina Gultom, Farid Akbar Siregar, Mahardika Abdi Prawira Tanjung, Al-Hamidy Hazidar

Knowledge Engineering and Data Science

Tuberculosis is a disease caused by infection with the mycobacterium tuberculosis complex. Tuberculosis attack organ besides the lung, such as the pleura, lining of the brain, lining of the heart, lymph gland, bones, joint, skin, intestines, kidney, urinary tract, and genital. This disease is found in densely populated settlements with poor sanitation, lack of ventilation and sunlight and lack of rest. Moreover, the factors that will be analyzed in this research are Population Density (X1), Number of HIV/AIDS (X2), number of toddlers who experience nutrition (X3), Number of toddlers who experience BCG immunization (X4), number of toddlers who get exclusive …

Evidence Of Students’ Academic Performance At The Federal College Of Education Asaba Nigeria: Mining Education Data, Arnold Adimabua Ojugo, Christopher Chukwufunaya Odiakaose, Frances Emordi, Rita Erhovwo Ako, Winifred Adigwe, Kizito Eluemonor Anazia, Victor Geteloma

Knowledge Engineering and Data Science

One main objective of higher education is to provide quality education to its students. One way to achieve the highest level of quality in the higher education system is by discovering knowledge for prediction regarding enrolment of students in a particular course, alienation of traditional classroom teaching model, detection of unfair means used in online examination, detection of abnormal values in the result sheets of the students, and prediction about students’ performance. The knowledge is hidden among the educational data set and is extractable through data mining techniques. The present paper is designed to justify the capabilities of data mining …

Recurrent Session Approach To Generative Association Rule Based Recommendation, Tubagus Arief Armanda, Ire Puspa Wardhani, Tubagus M. Akhriza, Tubagus M. Adrie Admira

Knowledge Engineering and Data Science

This article introduces a generative association rule (AR)-based recommendation system (RS) using a recurrent neural network approach implemented when a user searches for an item in a browsing session. It is proposed to overcome the limitations of the traditional AR-based RS which implements query-based sessions that are not adaptive to input series, thus failing to generate recommendations. The dataset used is accurate retail transaction data from online stores in Europe. The contribution of the proposed method is a next-item prediction model using LSTM, but what is trained to develop the model is an associative rule string, not a string of …

Controlled Manipulation And Transport By Microswimmers In Stokes Flows, Jake Buzhardt

All Dissertations

Remotely actuated microscale swimming robots have the potential to revolutionize many aspects of biomedicine. However, for the longterm goals of this field of research to be achievable, it is necessary to develop modelling, simulation, and control strategies which effectively and efficiently account for not only the motion of individual swimmers, but also the complex interactions of such swimmers with their environment including other nearby swimmers, boundaries, other cargo and passive particles, and the fluid medium itself. The aim of this thesis is to study these problems in simulation from the perspective of controls and dynamical systems, with a particular focus …

Ensuring Non-Repudiation In Long-Distance Constrained Devices, Ethan Blum

Honors Theses

Satellite communication is essential for the exploration and study of space. Satellites allow communications with many devices and systems residing in space and on the surface of celestial bodies from ground stations on Earth. However, with the rise of Ground Station as a Service (GsaaS), the ability to efficiently send action commands to distant satellites must ensure non-repudiation such that an attacker is unable to send malicious commands to distant satellites. Distant satellites are also constrained devices and rely on limited power, meaning security on these devices is minimal. Therefore, this study attempted to propose a novel algorithm to allow …