ECE Research Publications

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    Feature engineering from meta-data for prediction of differentially expressed genes: An investigation of Mus musculus exposed to space-conditions
    (Elsevier Ltd, 2024-04) Okwori, Michael; Eslami, Ali
    Transcription profiling is a key process that can reveal those biological mechanisms driving the response to various exposure conditions or gene perturbations. In this work, we investigate the prediction of differentially expressed genes (DEGs) when exposed to conditions in space from a set of diverse engineered features. To do this, we collected DEGs and non-differentially expressed genes (NDEGs) of Mus musculus-based experiments on the GeneLab database. We engineered a diverse set of features from factors reported in the literature to affect gene expression. An extreme gradient boosting (XGBoost) model was trained to predict if a given gene would be differentially expressed at various levels of differential expression. The test results on a separate holdout dataset showed an area under the receiver operating characteristics curves (AUCs) of 0.90±0.07, averaged across the five selected percentages of the most and least differentially expressed genes. Subsequently, we investigated the impact of selection of features, both individually with a correlation-based feature-selection procedure and in groups with a combination procedure, on the prediction performance. The feature selection confirmed some known drivers of adaptation to radiation and highlighted some new transcription factors and micro RNAs (miRNAs). Finally, gene ontology (GO) analysis revealed biological processes that tend to have expression patterns most suitable for this approach. This work highlights the potential of detection of differentially expressed genes using a machine learning (ML) approach, and provides some evidence of gene expression changes being captured by a diverse feature set not related to the condition under study.
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    Modeling and Analyzing Wind Velocity at Entrance Doors to Avoid Accidents
    (Institute of Electrical and Electronics Engineers Inc., 2023-09) Asaduzzaman, Abu; Mercer, Luke; Uddin, Md Raihan; Woldeyes, Yoel
    There are safety threats due to unexpected uncontrolled sudden opens and shuts of entrance doors. This work aims to develop a computer-simulated wind velocity model to study the doors' risky behavior by analyzing the relationship between wind velocity and the corresponding door movements. We develop a microcontroller-based system to detect when a door is opened, and record the wind velocity and door open distance when the door is opened and closed. This process is completed using an anemometer to measure the wind velocity, a magnetic door switch to detect when the door opens, using an ultrasonic sensor to measure the door distance, and calculating the time the door was open using the Arduino timer. The experiments are conducted inside a room., where wind speed and maximum door open distance can be controlled. The preliminary results show that the door open speed and distance increases significantly with increased wind speed. The proposed model can be extended as a potential remedy to dangerous threats for buildings and building occupants.
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    Optimal Reconfiguration of Power Distribution Grids to Maintain Line Thermal Efficiency During Progressive Wildfires
    (Institute of Electrical and Electronics Engineers Inc., 2023-12) Rostamzadeh, Mehdi; Kapourchali, Mohammad Heidari; Zhao, Long; Aravinthan, Visvakumar
    The worsening wildfires due to intensified climate variability increases the risk of both unplanned power outages as well as planned power line de-energizations. It is because wildfires cause thermal stress on overhead conductors, which harms the mechanical properties of overhead distribution lines. This article proposes a proactive strategy for improving the operational efficiency and decision-making capabilities of power distribution networks under progressive wildfire conditions. Dynamic heat balance equations are used to characterize the effect of wildfire on the overhead line conductors. The optimal dynamic reconfiguration of the distribution system and the operation of backup generators are considered as tools to minimize the curtailed loads while maintaining the maximum flow of current through the lines within the thermal rating of the line conductors. A mixed-integer conic programming model is adopted to minimize the operation and load curtailment costs. A higher value of lost load is applied to enhance the continuity of the electricity supply to critical loads. The proposed framework is tested under various environmental conditions and wildfire paths using both a modified 33-node network and the practical 83-node Taiwan Power Company's distribution grid. Results show that the proposed approach enhances proactive decision-making for power distribution system operations and increases the resilience of critical loads to wildfire threats.
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    ComPSim: A Community based Smart Grid Testbed for Holistic Resilience Analysis
    (Institute of Electrical and Electronics Engineers Inc., 2023) Sreejith, Amulya; Dhanapala, Prudhviraj; Melagoda, Adithya; Enderami, Seyyed Amin; Aravinthan, Visvakumar; Pahwa, Anil; Natarajan, Balasubramaniam
    This paper presents a novel approach to designing a smart grid testbed, that advances the state of knowledge on power system resilience analysis by including the social aspects of the community in simulation. The proposed Community-based Power Simulation virtual testbed, termed ComPSim herein, integrates non-physical dimensions of the community into the smart grid infrastructure system. The ComPSim test bed can be applied to identify the social impacts of power system disruptions. The testbed takes into account diverse socioeconomic characteristics of the community, enabling targeted analysis and policy formulation. This research highlights the need for integrating community's social and economic facet into future infrastructure planning and decision efforts.
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    Economic and Reliability Impacts of Combined Solar and Battery Energy Storage as a Non-Wire Alternative
    (Institute of Electrical and Electronics Engineers Inc., 2023-10) Peterson, Mary; O'Reilly, Olivia; Manoharan, Arun-Kaarthick; Rajendran, Sarangan; Melagoda, Adithya; Aravinthan, Visvakumar; Liu, Esther; Tamimi, Al; Yokley, Charles R.
    The decreasing cost of solar PVs is making them a viable non-wire alternative for rural areas considering infrastructure improvements. However, the intermittency and non-dispatchability of solar generation limits this possibility. Using real data from a small farming town in Kansas, this work analyzes the use of a combined community-scale solar farm and battery energy storage system as a non-wire alternative. In this work, various battery energy storage system operating strategies - such as fixed time discharging, outage mitigation, peak shaving, and market event mitigation - are considered. These operating strategies are evaluated based on financial viability for the utility, impact on battery life, and reliability of power supplied to the community served. The results and analysis provide useful insight regarding economic and reliability impacts with respect to the functionality and complexity of battery energy storage operating strategies.