Engineering Commons^™

A New Approach For Congestive Heart Failure And Arrhythmia Classification Using Downsampling Local Binary Patterns With Lstm, Süleyman Akdağ, Fatma Kuncan, Yilmaz Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

Electrocardiogram (ECG) is a vital diagnosis approach for the rapid explication and detection of various heart diseases, especially cardiac arrest, sinus rhythms, and heart failure. For this purpose, in this study, a different perspective based on downsampling one-dimensional-local binary pattern (1D-DS-LBP) and long short-term memory (LSTM) is presented for the categorization of Electrocardiogram (ECG) signals. A transformation method named 1DDS-LBP has been presented for Electrocardiogram signals. The 1D-DS-LBP method processes the bigness smallness relationship between neighbors. According to the proposed method, by downsampling the signal, the histograms of 1D local binary patterns (1D-LBP) calculated from the obtained signal groups are …

Two-Layered Blockchain-Based Admission Control For Secure Uav Networks, Müge Özçevi̇k

Turkish Journal of Electrical Engineering and Computer Sciences

The frequent replacement requirement of UAVs for recharging outputs an extreme number of messaging for admission control of end-users. There are many studies that try to optimize the network capacity in an energy-efficient manner. However, they do not consider the security of data and control channels, which is the urgent requirement of 5G. Blockchain handles secure systems. However, the high numbered transactions in blockchain may cause bottlenecks while considering computational delay and throughput of end-user. In UAVs, a high percentage of battery is consumed for computational tasks instead of communication tasks. Therefore, to handle security by considering the computational needs, …

Analysis Of Patch And Sample Size Effects For 2d-3d Cnn Models Using Multiplatform Dataset: Hyperspectral Image Classification Of Rosis And Jilin-1 Gp01 Imagery, Taşkin Kavzoğlu, Eli̇f Özlem Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

Modern hyperspectral sensors provide a huge volume of data at spectral and spatial domains with high redundancy, which requires robust methods for analysis. In this study, 2D and 3D CNN models were applied to hyperspectral image datasets (ROSIS and Jilin-1 GP01) using varying patch and sample sizes to determine their combined impacts on the performance of deep learning models. Differences in classification performances in relation to particle and sample sizes were statistically analysed using McNemar?s test. According to the findings, raising the patch and sample size enhances the performance of the 2D/3D CNN model and produces more accurate results in …

Enhancement Of Stability Delay Margins By Virtual Inertia Control For Microgrids With Time Delay, Suud Ademnur Hasen, Şahi̇n Sönmez, Saffet Ayasun

Turkish Journal of Electrical Engineering and Computer Sciences

Large-scale deployment of renewable energy sources (RESs) contributes to fluctuations in the system frequency due to their inherent reduced inertia feature. Time delays have emerged as a major source of concern in microgrids (MGs) as a result of the broad adoption of open communication networks since significant delays inevitably reduce the controller?s performance and even cause instabilities. In this article, a frequency-domain direct method is used to evaluate the impact of the virtual inertia (VI) control on the stability delay margins of MG with communication delays. By avoiding approximation, the approach first removes transcendental terms from characteristic equations and turns …

Noncontact Machinery Operation Status Monitoring System With Gated Recurrent Unit Model, Jason Jing Wei Lim, Boon Yaik Ooi, Wai Kong Lee, Teik Boon Tan, Soung Yue Liew

Turkish Journal of Electrical Engineering and Computer Sciences

In manufacturing industry, assembly line monitoring provides statistical information about overall performance and reliability of the legacy machines, ensuring that the machines give maximum yield output. However, most legacy machines lack internet connectivity and advanced functionality, increasing the difficulty for tracking task. Therefore, this work seeks to introduce a noncontact acoustic method to track machines rather than the mainstream vibrational approach. In order to provide accurate tracking of the daily machine operation for our machine tracking system, we consider scenario of background noises such as environmental sounds from multiple sources as well as neighbouring machine?s sound. Thus, several neural networks …

Diacritics Correction In Turkish With Context-Aware Sequence To Sequence Modeling, Asi̇ye Tuba Özge, Özge Bozal, Umut Özge

Turkish Journal of Electrical Engineering and Computer Sciences

Digital texts in many languages have examples of missing or misused diacritics which makes it hard for natural language processing applications to disambiguate the meaning of words. Therefore, diacritics restoration is a crucial step in natural language processing applications for many languages. In this study we approach this problem as bidirectional transformation of diacritical letters and their ASCII counterparts, rather than unidirectional diacritic restoration. We propose a context-aware character-level sequence to sequence model for this transformation. The model is language independent in the sense that no language-specific feature extraction is necessary other than the utilization of word embeddings and is …

A Carbon-Aware Planning Framework For Production Scheduling In Mining, Nurual Asyikeen Azhar, Aldy Gunawan, Shih-Fen Cheng, Erwin Leonardi

Research Collection School Of Computing and Information Systems

Managing the flow of excavated materials from a mine pit and the subsequent processing steps is the logistical challenge in mining. Mine planning needs to consider various geometric and resource constraints while maximizing the net present value (NPV) of profits over a long horizon. This mine planning problem has been modelled and solved as a precedence constrained production scheduling problem (PCPSP) using heuristics, due to its NP-hardness. However, the recent push for sustainable and carbon-aware mining practices calls for new planning approaches. In this paper, we propose an efficient temporally decomposed greedy Lagrangian relaxation (TDGLR) approach to maximize profits while …

Examining Drivers’ Behaviors To Connected And Automated Vehicles, Hany Hassan, Taniya Sultana

Publications

It is envisioned that Connected and Automated Vehicles (CAVs) are the future of transportation as they can assist in minimizing some inefficiencies with the current transport systems. However, it is not clear how drivers of conventional vehicles would interact with CAVs in a mixed traffic environment containing both CAVs and human driven vehicles (HDVs). Thus, this study aims to investigate drivers’ behaviors towards CAVs through driving simulation experiment and national survey study. Two on-ramp and two off-ramp driving simulation scenarios were designed where drivers were asked to merge with two-lane highway in presence of HDVs and CAVs truck platoon in …

Tuning The Thermodynamic, Optical, And Rheological Properties Of Thermoresponsive Polymer Solutions Via Silica Nanoparticle Shape And Concentration, Christopher A P Neal, Valeria León, Michelle C. Quan, Nondumiso O. Chibambo, Michelle A. Calabrese

Mechanical Engineering Faculty Publications

Hypothesis

The shape and quantity of hydrophilic silica nanoparticles (NPs) can be used to tune the microstructure, rheology, and stability of phase-separating polymer solutions. In thermoresponsive polymer systems, silica nanospheres are well-studied whereas anisotropic NPs have little literature precedent. Here, we hypothesize that NP shape and concentration lower the onset of rheological and turbidimetric separation of aqueous poly(N-isopropyl acrylamide) (PNIPAM) solutions.

Experiments

Differential scanning calorimetry (DSC), Fourier-transform infrared spectroscopy (FTIR), turbidimetry, and oscillatory rheology are utilized to examine interactions between NPs, PNIPAM, and water and to track changes in phase separation and mechanical properties due to NP concentration and shape. …

A New Classification Network For Diagnosing Alzheimer’S Disease In Class-Imbalance Mri Datasets, Ziyang Chen, Zhuowei Wang, Meng Zhao, Qin Zhao, Xuehu Liang, Jiajian Li, Xiaoyu Song

Electrical and Computer Engineering Faculty Publications and Presentations

Automatic identification of Alzheimer’s Disease (AD) through magnetic resonance imaging (MRI) data can eectively assist to doctors diagnose and treat Alzheimer’s. Current methods improve the accuracy of AD recognition, but they are insufficient to address the challenge of small interclass and large intraclass dierences. Some studies attempt to embed patch-level structure in neural networks which enhance pathologic details, but the enormous size and time complexity render these methods unfavorable. Furthermore, several self-attention mechanisms fail to provide contextual information to represent discriminative regions, which limits the performance of these classifiers. In addition, the current loss function is adversely aected by outliers …

A Study Of Pressure Probe Response In Steady And Unsteady Flows, Michael T. Charonnat

Master's Theses

The objective of this thesis is two-fold: to analyze the directional calibration of a 3-hole probe in steady flow and to develop a method for the interpretation of measurements recorded with a novel, fast-response Pitot-type probe in unsteady, turbulent flow. Calibration data for the 3-hole probe’s two side ports was taken in the steady, non-turbulent region of a free jet and was evaluated for symmetry. In addition, data that was recorded using one side port in two independent calibration runs was compared to study repeatability. Misalignment was found between the nominally symmetric data sets, which may be the result of …

Mitigating Cascading Failures In Power Grids Via Markov Decision-Based Load-Shedding With Dc Power Flow Model, Pankaz Das, Rezoan Ahmed Shuvro, Kassie Povinelli, Francesco Sorrentino, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

Despite the reliability of modern power systems, large blackouts due to cascading failures (CFs) do occur in power grids with enormous economic and societal costs. In this article, CFs in power grids are theoretically modeled proposing a Markov decision process (MDP) framework with the aim of developing optimal load-shedding (LS) policies to mitigate CFs. The embedded Markov chain of the MDP, established earlier to capture the dynamics of CFs, features a reduced state-space and state-dependent transition probabilities. We introduce appropriate actions affecting the dynamics of CFs and associated costs. Optimal LS policies are computed that minimize the expected cumulative cost …

Choice-Based Crowdshipping: A Dynamic Task Display Problem, Alp Arslan, Firat Kilci, Shih-Fen Cheng, Archan Misra

Research Collection School Of Computing and Information Systems

This paper studies the integration of the crowd workforce into a generic last-mile delivery setting in which a set of known delivery requests should be fulfilled at a minimum cost. In this setting, the crowd drivers are able to choose to perform a parcel delivery among the available and displayed requests. We specifically investigate the question: what tasks should be displayed to an individual driver, so as to minimize the overall delivery expenses? In contrast to past approaches, where drivers are either (a) given the choice of a single task chosen so as to optimize the platform’s profit, or (b) …

Tactics Ideation Experiment Data, Thomas L. Ashworth, Carl D. Sorensen

ScholarsArchive Data

This data includes the template worksheets, as well as filled worksheets that include ideas written by the participants in a research experiment. This experiment tested the effectiveness of a novel tactics ideation method (i.e., Random Prompts method) to a modified Brainwriting method. Transcribed copies of this data are also included.

Accompanying the data are experiment briefing presentations, Python code for rapid evaluation of the data (the evaluation methods themselves were also developed by the authors), a spreadsheet file with evaluation data (this is a necessary input to the code), and organizational trees (for team idea sets) associated with the evaluation …

A Qualitative Descriptive Study On Re-Assessing The Mental Certification By Faa For Future Pilots, Kaung Z. Min

Student Works

Mental illness becomes one of the main problems that most pilots do not usually address. It is not because pilots do not have the courage or are open enough to talk with someone, but because the Federal Aviation Administration (FAA) forces them to hide from mental depression. Most of the time, the pilots are not willing to declare such illnesses as they fear losing their job; simultaneously, the Federal Aviation Agencies across the world require pilots to be in peat health, including their mental condition, to operate the aircraft. While it can be said that the passengers’ and crews’ safety …

Stick Built Vs. Precut Wall Framing For New Home Construction: A Comparison Of Framing Labor Hours, Waste Hauls, And Purchase Orders, Eric A. Holt, Mark Laliberte, Tristan Grant, Jordan Dentz

The Professional Constructor

Due to many trends in the construction industry (material cost increase, labor shortages, supply chain issues, pandemic, market demand outpacing supply), the homebuilding industry is looking for alternative ways to frame homes. In response to the National Housing Endowment (NHE) Request for Proposal, the researchers reviewed the literature on the housing market’s current state regarding the scale and scope of the skilled construction framers shortage and the current market share of single-family framing method; stick-built vs. precut framing packages. Working with industry partners, the team analyzed time studies for multiple new home builds. It was found that precut wall framing …

Total Cost Of Ownership Of Battery-Powered Vs. Hardwired Sensor Faucets In Commercial And Educational Construction Projects, Marie Patterson, Blake Wentz

The Professional Constructor

Owners who are pursing the construction of a new commercial building are becoming increasingly more interested in the sustainability, energy efficiency and life cycle costs of their proposed project. These owners are asking designers and construction companies to develop innovative strategies to lower their utility use and total cost in their projects. One area of opportunity to meet this owner need is the decision to use sensor lavatory faucets that are either battery-powered or hardwired.Several construction projects of various types and locations were analyzed to determine the total cost of ownership of both types of sensor faucets over a 12-year …

Analysis Of Current And Future Flood Hazard In The Sacramento-San Joaquin Delta, Nicholas L. Mcguire

Master's Theses

The primary motivation of this study is to estimate the current and future flood hazard throughout the Sacramento-San Joaquin Delta in the context of sea-level rise. I also analyzed the effects of storm surge and river flow on extreme events to better understand how these events originate and vary spatially and in time. To address this goal, I combined digital water level records (primarily 1983-present) with archival data collected by the California Department of Water Resources (1929-1983) to reevaluate flood hazard in the Delta and investigate the possible sensitivity of the region different sea-level rise projections. Available archival records from …

Design And Analysis Of A Discrete, Pcb-Level Low-Power, Microwave Cross-Coupled Differential Lc Voltage-Controlled Oscillator, Pavin Singh Virdee

Master's Theses

Radio Frequency (RF) and Microwave devices are typically implemented in Integrated Circuit (IC) form to minimize parasitics, increase precision and tolerances, and minimize size. Although IC fabrication for students and independent engineers is cost-prohibitive, an abundance of low-cost, easily accessible printed circuit board (PCB) and electronic component manufacturers allows affordable PCB fabrication.

While nearly all microwave voltage-controlled oscillator (VCO) designs are IC-based, this study presents a discrete PCB-level cross-coupled, differential LC VCO to demonstrate this more affordable and accessible approach. This thesis presents a 65 mW, discrete component VCO PCB with industry-comparable RF performance. A phase noise of -103.7 dBc/Hz …

Impact Of Operational And Restoration Interdependencies On Cost And Disruptive Effect In Multilayered Infrastructure Networks, Brigham A. Moore, Steven J. Schuldt, Ramana V. Grandhi, David R. Jacques

Faculty Publications

Network-based modeling and simulation of interdependent infrastructure systems has traditionally modeled 1 to 2 interdependency subtypes within a given model. Typically, different interdependency subtypes are modeled with special sets, variables, and parameters rather than integrated into the model as a standard feature. The most thorough current modeling efforts have modeled only four of the nine interdependency subtypes identified throughout academic literature. This paper presents the first model to incorporate all nine of the identified interdependency subtypes in a multiobjective mixed-integer program. The model is tested using a simulated flood event and a modified interdependent infrastructure dataset representing a medium- to …

Evaluation Of Artificial Neural Network Methods To Forecast Short-Term Solar Power Generation: A Case Study In Eastern Mediterranean Region, Heli̇n Bozkurt, Ramazan Maci̇t, Özgür Çeli̇k, Ahmet Teke

Turkish Journal of Electrical Engineering and Computer Sciences

Solar power forecasting is substantial for the utilization, planning, and designing of solar power plants. Global solar irradiation (GSI) and meteorological variables have a crucial role in solar power generation. The ever-changing meteorological variables and imprecise measurement of GSI raise difficulties for forecasting photovoltaic (PV) output power. In this context, a major motivation appears for the accurate forecast of GSI to perform effective forecasting of the short-term output power of a PV plant. The presented study comprises of four artificial neural network (ANN) methods; recurrent neural network (RNN) method, feedforward backpropagation neural network (FFBPNN) method, support vector regression (SVR) method, …

Error Analysis Of Siso And Dual-Branch Communications With Generalized Gaussian Noise Over Ftr Fading Channels, Mehmet Bi̇li̇m

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we present error probability analysis for single-input single-output (SISO) and asymmetric dual-branch networks with additive white generalized Gaussian noise (AWGGN) over millimeter-wave (mmW) fluctuating two-ray (FTR) fading channels. Then, we examine the error probability evaluation of a SISO system with imperfect phase errors over mmW FTR fading channels. The probability density function (PDF) approach is employed for the error probability performance evaluation and the novel PDF of the asymmetric dual-branch system over Nakagami-m/mmW FTR fading channels is obtained. Specifically, closed-form expressions are derived for the error probability of the SISO and asymmetric dual-branch networks. The derived error …

A Quantitative Evaluation Of Explainable Ai Methods Using The Depth Of Decision Tree, Nizar Abdulaziz Mahyoub Ahmed, Adi̇l Alpkoçak

Turkish Journal of Electrical Engineering and Computer Sciences

It is necessary to develop an explainable model to clarify how and why a medical model makes a particular decision. Local posthoc explainable AI (XAI) techniques, such as SHAP and LIME, interpret classification system predictions by displaying the most important features and rules underlying any prediction locally. Therefore, in order to compare two or more XAI methods, they must first be evaluated qualitatively or quantitatively. This paper proposes quantitative XAI evaluation metrics that are not based on biased and subjective human judgment. On the other hand, it is dependent on the depth of the decision tree (DT) to automatically and …

Track Density Imaging Using Diffusion Tensor Imaging Data From 1.5 T Mri Scanner, Fatma Betül Köşker, Kazim Zi̇ya Gümüş, Mahmut Tokmakçi, Ni̇yazi̇ Acer, Serkan Şenol, Mehmet Bi̇lgen

Turkish Journal of Electrical Engineering and Computer Sciences

Superresolution track density imaging (TDI) has recently been developed for achieving high resolution track density maps from low-resolution diffusion images acquired at 3 T. But, the utility of the approach is still unclear when applied to diffusion tensor imaging (DTI) data acquired at lower 1.5 T magnetic field strength and thus its advantages or disadvantages awaits for exploration. We implemented an algorithm to generate track density maps of human white matter using streamline tracking and tested its performance with data acquired from two healthy volunteers at 1.5 Tesla. The effects of number of diffusion directions and seed selections on the …

Comparison Of Ml Algorithms To Distinguish Between Human Or Human-Like Targets Using The Hog Features Of Range-Time And Range-Doppler Images In Through-The-Wall Applications, Yunus Emre Acar, İsmai̇l Saritaş, Ercan Yaldiz

Turkish Journal of Electrical Engineering and Computer Sciences

When detecting the human targets behind walls, false detections occur for many systematic and environmental reasons. Identifying and eliminating these false detections is of great importance for many applications. This study investigates the potential of machine learning (ML) algorithms to distinguish between the human and human-like targets behind walls. For this purpose, a stepped-frequency continuous-wave (SFCW) radar has been set up. Experiments have been carried out with real human targets and moving plates imitating a regular breath of a healthy human. Unlike conventional methods, human and human-like returns are classified using range-Doppler images containing range and Doppler information. Then, the …

Building A Surrogate Model Of A Perfect Electric Conductor Using Polynomial Chaos Expansion And The Characteristic Mode Analysis, Adem Yilmaz, Hulusi̇ Açikgöz, Alaaldeen Barakat Ahmed Elrouby

Turkish Journal of Electrical Engineering and Computer Sciences

A surrogate model for a perfect electric conductor plate is built by using the polynomial chaos expansion method. The plate is excited via four capacitive coupling elements for which the locations are determined by the analysis of the current distribution for each mode provided by the characteristic mode analysis. A numerical model based on the method of moments is then created to generate a database needed to build the surrogate model. Radiation patterns calculated by the surrogate model are compared with those given by the numerical model. The results show that the surrogate model can mimic the numerical model and …

A Compact Pattern Reconfigurable Antenna Employing Shorted Quarterwave Patch Antennas, Feza Turgay Çeli̇k, Lale Alatan, Hati̇ce Özlem Aydin Çi̇vi̇

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a compact pattern reconfigurable antenna structure is proposed. The proposed antenna is a half-wave square microstrip patch antenna divided into two quarter-wave antenna portions by a conducting wall. This wall forces potential zero at the connection point; therefore, it separates the antenna into two independent quarter-wave portions. Pattern reconfiguration is achieved by separate feeding of the quarter-wave portions. Phase difference between excitations of antenna ports result in variation at the maximum beam direction. Hence, pattern reconfiguration is achieved. Within such a compact antenna, beam steering up to 400 is achieved

A New Network-Based Community Detection Algorithm For Disjoint Communities, Peli̇n Çeti̇n, Şahi̇n Emrah Amrahov

Turkish Journal of Electrical Engineering and Computer Sciences

A community is a group of people that shares something in common. The definition of the community can be generalized as things that have common properties. By using this definition, community detection can be used to solve different problems in various areas. In this study, we propose a new network-based community detection algorithm that can work on different types of datasets. The proposed algorithm works on unweighted graphs and determines the weight by using cosine similarity. We apply a bottom-up approach and find the disjoint communities. First, we accept each node as an independent community. Then, the merging process is …

On Approximate Nash Equilibria Of The Two-Source Connection Game, Buğra Çaşkurlu, Utku Umur Açikalin, Fati̇h Erdem Kizilkaya, Özgün Eki̇ci̇

Turkish Journal of Electrical Engineering and Computer Sciences

The arbitrary-sharing connection game is prominent in the network formation game literature [1]. An undirected graph with positive edge weights is given, where the weight of an edge is the cost of building it. An edge is built if agents contribute a sufficient amount for its construction. For agent i, the goal is to contribute the least possible amount while assuring that the source node si is connected to the terminal node ti . In this paper, we study the special case of this game in which there are only two source nodes. In this setting, we prove that there …

Chemical Disease Relation Extraction Through The Combination Of Multiple Mention Levels: Relscan+, Stanley Chika Onye, Nazi̇fe Di̇mi̇li̇ler, Ari̇f Akkeleş

Turkish Journal of Electrical Engineering and Computer Sciences

Chemical-induced disease (CID) relation extraction has been pivotal in the understanding of biological processes. A CID relation between a chemical and disease entity may be extracted either from a single sentence or from two or more adjacent sentences. We use `intrasentence level' to refer to the mention of the desired entities in the same sentence and `intersentence level? to refer to the mention of these entities in two or more adjacent sentences. This study proposes a three-phase architecture for extracting CID relations from biomedical literature by considering both sentence levels and additionally the combination of these two sentence levels which …