Physical Sciences and Mathematics Commons^™

2022 November - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Reports

No abstract provided.

Mgrre_Thinsections_05_A_68, Mgrre

Thin Sections

No abstract provided.

A Quantitative Application Of Diffusion Of Innovations For Modeling The Spread Of Conservation Behaviors, Matt Clark, Jeffrey Andrews, Vicken Hillis

Human-Environment Systems Research Center Faculty Publications and Presentations

The study of community-based conservation is challenged by a large number of important variables and nonlinear dynamics. This complexity has made quantitative and comparative analyses notoriously difficult. Here, we argue that analyzing the emergence and persistence of community-based conservation institutions as an emergent phenomenon of individual decision-making can yield important quantitative insights. We first review diffusion of innovations theory (DOI) and the broader field of cultural evolution. We then simulate data on community adoption of a conservation institution, contingent on feedbacks between individual behavior and environmental processes. We demonstrate that fitting these data to differential models of disease transmission, on …

Machine Learning For Angiography-Based Blood Flow Velocity Prediction, Swati Padhee, Mark Johnson, Hang Yi, Tanvi Banerjee, Zifeng Yang

Computer Science and Engineering Faculty Publications

Computational fluid dynamics (CFD) is widely employed to predict hemodynamic characteristics in arterial models, while not friendly to clinical applications due to the complexity of numerical simulations. Alternatively, this work proposed a framework to estimate hemodynamics in vessels based on angiography images using machine learning (ML) algorithms. First, the iodine contrast perfusion in blood was mimicked by a flow of dye diffusing into water in the experimentally validated CFD modeling. The generated projective images from simulations imitated the counterpart of light passing through the flow field as an analogy of X-ray imaging. Thus, the CFD simulation provides both the ground …

Filling Critical Gaps In The Space-Time Record Of High Lava Plains And Co-Columbia River Basalt Group Rhyolite Volcanism, Vanessa Marie Swenton, Martin J. Streck, Daniel P. Miggins, William C. Mcintosh

Geology Faculty Publications and Presentations

Miocene rhyolitic volcanism of eastern Oregon, USA, can be divided into two main episodes. Mantle plume upwelling is thought to have generated Columbia River Basalt Group (CRBG) lavas and coeval >16.5−15 Ma silicic volcanism trending north−south from northeast Oregon to northern Nevada. Rhyolite volcanism of the 12−0 Ma High Lava Plains province has been ascribed to either buoyancy-driven westward plume spreading or to slab rollback and mantle convection spanning from southeast Oregon to Newberry Volcano to the west. The apparent ca. 15−12 Ma eruptive hiatus suggests that rhyolites of these provinces were a product of separate processes, yet this gap …

An Interactive Simulation And Visualization Tool For Conventional And Aberration-Corrected Transmission Electron Microscopy, Xingzhong Li

Nebraska Center for Materials and Nanoscience: Faculty Publications

Contrast transfer function (CTF) is a vital function in transmission electron microscopy (TEM). It expresses to what extent amplitudes converted from the phase changes of the diffracted waves contribute to the TEM image, including the effects of lens aberrations. Simulation is very helpful to understand the application of the function thoroughly. In this work, we develop the CTFscope as a component in the Landyne software suite, to calculate the CTF with temporal and spatial dumping envelopes for conventional TEM and to extend it to various aberrations (up to fifth order) for aberration-corrected (AC)- TEM. It also includes effects on the …

Advancing The Use Of Fecal Sludge For Timelier And Better-Quality Epidemiological Data In Low- And Middle-Income Countries For Pandemic Prevention., Petros Chigwechokha, Renée Street, Rochelle H. Holm

Faculty and Staff Scholarship

No abstract provided.

Gesture Controlled Collaborative Robot Arm And Lab Kit, Abel A. Reyes, Skylar Reinhardt, Tony Wise, Nathir Rawashdeh, Sidike Paheding

Michigan Tech Publications, Part 1

In this paper, a mechatronics system was designed and implemented to include the subjects of artificial intelligence, control algorithms, robot servo motor control, and human-machine interface (HMI). The goal was to create an inexpensive, multi-functional robotics lab kit to promote students’ interest in STEM fields including computing and mechtronics. Industrial robotic systems have become vastly popular in manufacturing and other industries, and the demand for individuals with related skills is rapidly increasing. Robots can complete jobs that are dangerous, dull, or dirty for humans to perform. Recently, more and more collaborative robotic systems have been developed and implemented in the …

Operation Of A Controllable Force-Sensing Industrial Pneumatic Parallel Gripper System, Brian Piechocki, Chelsey Spitzner, Namratha Karanam, Travis Winter, Aleksandr Sergeyev, Mark Gauthier, Nathir Rawashdeh

Michigan Tech Publications, Part 1

As part of the advanced programmable logic controllers (PLC) course at Michigan Tech, this class project was performed on a mechatronics system gifted by Donald Engineering, a Michigan-based supplier of industrial automation systems and components. This paper explores the functionality and application of a force-programmable and sensing pneumatic parallel gripper system. Force sensing is a critical part of many systems in modern automation systems. Applications such as prosthetics, robotic surgery, or basic manufacturing systems may rely on the ability to properly read and control forces applied to an object. This work evaluates the basic operation of the pneumatic force-sensing gripper …

Synthesis And Characterization Of Unique Pyridazines, William Hobbs

Senior Honors Theses

The field of semiconductive organic chemistry is vast and expanding as numerous applications are being discovered for semiconductors. The research reported in this thesis focuses on the synthesis and characterization of three pyridazines. Pyridazines are organic heterocyclic aromatic semiconductors containing nitrogen and are planar in structure. The three pyridazine compounds were successfully isolated as evidenced by a high percent yield and then characterized by melting point and infrared spectroscopy. The research goal was achieved as a small library of pyridazines was compiled to be further analyzed concerning their potential within various applications in the electronic and industrial world.

Thermal Degradation Of Erythritol, Sudheendra Gamoji

Physics

The Insulated Solar Electric Cooker (ISEC) is a double walled Aluminum pot with a resistive heater directly connected to a solar panel whose goal is to create and disseminate cheap solar cookers in rural areas that primarily rely on biomass for cooking. Phase Change Materials (PCMs) like Erythritol, a sugar substitute, take a tremendous amount of energy to melt, and when they solidify they release the energy. Through the use of PCMs, the ISECs will produce enough heat to cook food even after the sun sets. However, PCMs like Erythritol degrade over repeated heat exposure, so the purpose of this …

Impact Of The Choice Of Acidic Buffers On The Electrochemical Reduction Of Hexavalent Chromium In Water, Devin D. Meche

Honors Capstones

No abstract provided.

College Of Natural Sciences Newsletter, September & October 2022, College Of Natural Sciences

College of Natural Sciences Newsletters and Reports

Volume 3, Issue 6

Page 1 Dean's Message
Page 2 Awards & Recognition
Page 3 Midwest Regional ACS Meeting
Page 4 North Central ASM Meeting
Page 5 Geography Department Travel
Page 6-7 Media Coverage of CNS
Page 7 REMAST Program at SDState receives national spotlight
Page 8 Celebrating the lives of those who touched the College
Page 9 Innovative Learning Spaces
Page 10 Open PRAIRIE Data
Page 11 2022 CNS Scholarship Brunch
Page 12-14 Fall 2022 Outreach Events

Questions To Advance Research On Equitable Coastal Resilience, Wie Yusuf

School of Public Service Faculty Publications

No abstract provided.

Effects Of Position And Gap Orientation Of The Split Ring Resonator Structure Excited By Microstrip Transmission Line On The Transmission Characteristics, Nezi̇he Karacan, Nesli̇han Kader Bulut, Evren Ekmekçi̇

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the effects of the position and the gap orientation of the split ring resonator (SRR) structure, which is applied as a superstrate, on transmission characteristics (i.e. S21 ) are investigated numerically and experimentally. For that purpose, the left edge of the transmission line has been designated as the reference line and the SRR structure is shifted towards both left and right for three different gap orientations. Subsequently, S21 characteristics of the SRR structure having several substrate thicknesses and several substrate dielectric constants are investigated parametrically for three different gap orientations. The results reveal that the position and …

Comparison Review Of The Production, Microbiology, And Sensory Profile Of Lambic And American Coolship Ales, John Carriglio, Drew Budner, Katherine A. Thompson-Witrick

Chemistry

Sour beers have been traditionally brewed with spontaneous fermentation. This has been occurring in Belgium for hundreds of years, and more recently in the United States as the American craft beer industry has boomed. Belgian sour styles include lambics, which are mirrored in a burgeoning style called the American coolship ale (ACA). American beers have much more creative leeway than their Belgian counterparts, as American craft brewing tends to incorporate more contemporary techniques and ingredients than their traditional European forebears. This review paper will summarize the history, production methods, fermentation, microbiological profiles, and sensory profiles of Belgian lambics and American …

Blockchain And Federated Learning-Based Security Solutions For Telesurgery System: A Comprehensive Review, Sachi Chaudjary, Riya Kakkar, Rajesh Gupta, Sudeep Tanwar, Smita Agrawal, Ravi Sharma

Turkish Journal of Electrical Engineering and Computer Sciences

The advent of telemedicine with its remote surgical procedures has effectively transformed the working of healthcare professionals. The evolution of telemedicine facilitates the remote monitoring of patients that lead to the advent of telesurgery systems, i.e. one of the most critical applications in telemedicine systems. Apart from gaining popularity, the telesurgery system may encounter security and trust issues of patients? data while communicating with the surgeon for their remote treatment. Motivated by this, we have presented a comprehensive survey on secure telesurgery systems comprising healthcare, surgical robots, traditional telesurgery systems, and the role of artificial intelligence to deal with the …

Skin Lesion Segmentation By Using Object Detection Networks, Deeplab3+, And Active Contours, Fatemeh Bagheri, Mohammad Jafar Tarokh, Majid Ziaratban

Turkish Journal of Electrical Engineering and Computer Sciences

Developing an automatic system for detection, segmentation, and classification of skin lesions is very useful to aid well-timed diagnosis of skin diseases. Lesion segmentation is a crucial task for automated diagnosis of skin cancers, as it affects significantly the accuracy of the subsequent steps. Varieties in sizes and locations of lesions, and the lesions with low-contrast boundaries make this task very challenging. In this paper, a three-stage CNN-based method is presented for accurate segmentation of lesions from dermoscopic images. At the first step, normalization, approximate locations and sizes of lesions are estimated. Due to the importance of the normalization stage, …

Computationally Efficient Predictive Torque Control Strategies Without Weighting Factors, Emrah Zerdali̇, Mert Altintaş, Ali̇ Bakbak, Erkan Meşe

Turkish Journal of Electrical Engineering and Computer Sciences

Predictive torque control (PTC) is a promising control method for electric machines due to its simplicity, fast dynamics, ability to handle nonlinearities, and easy inclusion of additional control objectives. The main challenge in conventional PTC design is to determine the weighting factors in the cost function. These weighting factors are generally chosen by the trial-and-error method or metaheuristic optimization algorithms, but these methods may not apply the optimum voltage vectors according to changing operating conditions. There are also several studies on the elimination of the weighting factors. This paper proposes two weighting factorless PTC strategies with lower computational complexities than …

Utilizing Motion And Spatial Features For Sign Language Gesture Recognition Using Cascaded Cnn And Lstm Models, Hamzah Luqman, Elsayed Elalfy

Turkish Journal of Electrical Engineering and Computer Sciences

Sign language is a language produced by body parts gestures and facial expressions. The aim of an automatic sign language recognition system is to assign meaning to each sign gesture. Recently, several computer vision systems have been proposed for sign language recognition using a variety of recognition techniques, sign languages, and gesture modalities. However, one of the challenging problems involves image preprocessing, segmentation, extraction and tracking of relevant static and dynamic features related to manual and nonmanual gestures from different images in sequence. In this paper, we studied the efficiency, scalability, and computation time of three cascaded architectures of convolutional …

Mocmin: Convex Inferring Of Modular Low-Rank Contact Networks Over Covid Diffusion Data, Emre Sefer

Turkish Journal of Electrical Engineering and Computer Sciences

SEIR (which consists of susceptible, exposed, infected, and recovered states) is a common diffusion model which could model different disease propagation dynamics across various domains such as influenza and COVID diffusion. As a motivation, across these domains, observing the node states is relatively easier than observing the network edges over which the diffusion is taking place, or it may not even be possible to observe the underlying network. This paper focuses on the problem of predicting modular low-rank human contact network edges only if a SEIR diffusion dynamics spreading among the human on their contact network can be observed. Such …

Compact Dual-Band Rectangular T E10 Mode To Circular Tm01 Mode Converter For Telemetry/Telecommand Applications In Satellite Communication: Design, Equivalent Circuit Modeling, Mode Level Measurement Technique And 3d Printed Manufacturing, Esra Alkin, Ceyhan Türkmen, Mustafa Seçmen

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the design of a dual-band mode converter, which provides transition from rectangular waveguide T E10 mode to circular waveguide TM01 mode and operates simultaneously in telemetry/telecommand (TT&C) frequencies, is presented along with its equivalent circuit and a mode level measurement technique. This dual-band converter is designed to uniformly excite TT&C slot antennas used in satellite communication with symmetric circular TM01 mode. The structure can work as a transceiver due to having one common rectangular waveguide feed. As a Ku-band application, a converter giving high purity TM01 mode at circular waveguide at 11.75 GHz/TX …

Load2load: Day-Ahead Load Forecasting At Aggregated Level, Mustafa Berkay Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

A reliable and accurate short-term load forecasting (STLF) helps utilities and energy providers deal with the challenges posed by supply and demand balance, higher penetration of renewable energies and the development of electricity markets with increasingly complex pricing strategies in future smart grids. Recent advances in deep learning have been successively utilized to STLF. However, there is no certain study that evaluates the performances of different STLF methods at an aggregated level on different datasets with different numbers of daily measurements.In this study, a deep learning STLF architecture called Load2Load is proposed for day-ahead forecasting. Different forecasting methods have been …

Monte-Carlo Method Based Simulations For Photothermal Mucosa Coagulation With Accurate Depth Limits, Merve Türker Burhan, Serhat Tozburun

Turkish Journal of Electrical Engineering and Computer Sciences

The mucosa layer, the innermost layer of the gastrointestinal (GI) system, is of great importance in carcinogenesis since most cancerous tissues occur as superficial lesions. Although various treatment strategies exist, the main difficulty in eradicating lesions is unintentional damage to healthy tissues with the uncontrolled depth of treatment. This study proposes a computer modeling approach for simulating depth-resolved photothermal (laser) mucosal coagulation therapy. Computer modeling mimics the thermal dynamics of mucosal tissue to characterize the total heat energy required for successful superficial coagulation, which can be controlled by the scan rate, scan time, output power, and beam diameter of the …

Identification Of Initial Events Of Cascading Failures Using Graph Theory Methods, Mojtaba Fekri, Javad Nikoukar, Gevork Babamalek Gharehpetian

Turkish Journal of Electrical Engineering and Computer Sciences

In power systems, the unintentional outage of a grid element can lead to overload and outage of other equipment and, through a domino effect, all or a large part of a power system may collapse. The resulting events are called cascading, consecutive, or sequential failures. So far, various methods have been proposed to identify the initial events of cascading failures with different levels of accuracy and computational load. In this paper, an effective approach is employed which, by calculating the maximum flow of independent paths between generators and loads in the network graph, identifies the critical lines and transformers of …

Application Of Hierarchical Clustering On Electricity Demand Of Electric Vehicles For Gep Problems, Seyedkazem Afghah, Hati̇ce Teki̇ner Moğulkoç, Bi̇jan Bi̇bak

Turkish Journal of Electrical Engineering and Computer Sciences

Increasing fossil fuel consumption and consequently the effects of greenhouse gases (GHGs) on the environment and economy are a major concern for all nations and governments. Electric vehicles (EVs) with plug-in capabilities have the potential to ease such problems. However, the extracted power from the grid for charging the EVs' batteries will significantly impact daily power demand. To satisfy the increasing demand and ensure generation capacity adequacy, the generation expansion planning (GEP) problem is solved to determine the investment decisions for electricity generation sources. Even though there are no centralized utilities for generation planning in most markets, there is still …

Detection And Classification Of White Blood Cells With An Improved Deep Learning-Based Approach, Fatma Akalin, Nejat Yumuşak

Turkish Journal of Electrical Engineering and Computer Sciences

The analysis of white blood cells, which defend the body against deadly infections and disease-causing substances, is an important issue in the medical world. The concentrations of these cells in the blood, examined in 5 classes, i.e. monocytes, eosinophils, basophils, lymphocytes, and neutrophils, vary according to the types of diseases in the body. The peripheral blood smear is widely used to analyze blood cells. Manual evaluation of this method is laborious and time-consuming. At the same time, many environmental and humanistic parameters affect the method's performance. Therefore, in the presented study, a real-time detection process is realized. Firstly, YOLOv5s, YOLOv5x, …

Affective States Classification Performance Of Audio-Visual Stimuli From Eeg Signals With Multiple-Instance Learning, Yaşar Daşdemi̇r, Rüstem Özakar

Turkish Journal of Electrical Engineering and Computer Sciences

Throughout various disciplines, emotion recognition continues to be an essential subject of study. With the advancement of machine learning methods, accurate emotion recognition from different data modalities (facial images, brain EEG signals) has become possible. Success of EEG-based emotion recognition systems depends on efficient feature extraction and pre/postprocessing of signals. Main objective of this study is to analyze the efficacy of multiple-instance learning (MIL) on postprocessing features of EEG signals using three different domains (time, frequency, time-frequency) for human emotion classification. Methods and results are presented for single-trial classification of valence (V), arousal (A), and dominance (D) ratings from EEG …

2022 Final Butte Reduction Works (Brw) Smelter Area Mine Waste Remediation And Contaminated Groundwater Hydraulic Control Site Phase Iii Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Recall Distortion In Neural Network Pruning And The Undecayed Pruning Algorithm, Aidan Good, Jiaqi Lin, Hannah Sieg, Mikey Ferguson, Xin Yu, Shandian Zhe, Jerzy Wieczorek, Thiago Serra

Faculty Conference Papers and Presentations

Pruning techniques have been successfully used in neural networks to trade accuracy for sparsity. However, the impact of network pruning is not uniform: prior work has shown that the recall for underrepresented classes in a dataset may be more negatively affected. In this work, we study such relative distortions in recall by hypothesizing an intensification effect that is inherent to the model. Namely, that pruning makes recall relatively worse for a class with recall below accuracy and, conversely, that it makes recall relatively better for a class with recall above accuracy. In addition, we propose a new pruning algorithm aimed …