Engineering Commons^™

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 …

Inserting Of Heuristic Techniques Into The Stability Regions For Multiarea Load Frequency Control Systems With Time Delays, Mustafa Saka, Şahi̇n Sönmez, İbrahi̇m Eke, Haluk Gözde, Müslüm Cengi̇z Taplamacioğlu, Saffet Ayasun

Turkish Journal of Electrical Engineering and Computer Sciences

The design and optimization of robust controller parameters are required to improve the controller performances and to keep the stability of load frequency control (LFC) system. In addition, reducing the number of iterations and computational time is very important for swiftly tuning of the controller parameters and the system to reach stability rapidly. For this purpose, this study presents the inserting of heuristic optimization techniques into stability regions method identified in proportional-integral (PI) controllers space for multiarea LFC systems with communication time delays (CTDs). This method consists of two steps: determination of stability region for the system and application of …

A Novel Broadband Double-Ring Holed Element Metasurface Absorber To Suppress Emi From Pcb Heatsinks, Bülent Urul, Habi̇b Doğan, İbrahi̇m Bahadir Başyi̇ği̇t, Abdullah Genç

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a new Broadband Double Ring Hole Element (BDHE) meta-surface absorber is studied to suppress EMI from PCB heatsink for 1-12 GHz covering L, S, C, and X bands. The proposed metamaterial-structure consists of resistances and 8 ring resonators, four of which are inner and four are outer that are configured to provide an absorbing effect. For broadband, numerical simulations show that an average of 65% absorption value is obtained between 4-12 GHz. It is determined that this value reached 69.84% by increasing the used resistance values (R = 150?). This value may be significant to reduce the …

Learning To Play An Imperfect Information Card Game Using Reinforcement Learning, Buğra Kaan Demi̇rdöver, Ömer Baykal, Ferdanur Alpaslan

Turkish Journal of Electrical Engineering and Computer Sciences

Artificial intelligence and machine learning are widely popular in many areas. One of the most popular ones is gaming. Games are perfect testbeds for machine learning and artificial intelligence with various scenarios and types. This study aims to develop a self-learning intelligent agent to play the Hearts game. Hearts is one of the most popular trick-taking card games around the world. It is an imperfect information card game. In addition to having a huge state space, Hearts offers many extra challenges due to its nature. In order to ease the development process, the agent developed in the scope of this …

Comparison Of Deep Learning And Regression-Based Mppt Algorithms In Pv Systems, Murat Sali̇m Karabi̇naoğlu, Beki̇r Çakir, Mustafa Engi̇n Başoğlu, Abdülvehhab Kazdaloğlu, Azi̇z Güneroğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Solar energy systems (SES) and photovoltaic (PV) modules should be operated at the maximum power point (MPP) to achieve the highest efficiency in the energy generation processes. Maximum power point tracking (MPPT) applications using conventional methods may not be able to follow the global MPP (GMPP) of the PV system under changing atmospheric conditions and they could oscillate around the local MPP. In this study, a machine learning and deep learning (DL) based long short-term memory (LSTM) model is proposed as an innovative solution for MPPT. Contrary to the traditional MPPT applications using current and voltage sensors, the output resistance …

Presenting A Method To Detect Intrusion In Iot Through Private Blockchain, Rezvan Mahmoudie, Saeed Parsa, Amir Masoud Rahmani

Turkish Journal of Electrical Engineering and Computer Sciences

Blockchain (BC) has been used as a new solution to overcome security and privacy challenges in the Internet of Things (IoT). However, recent studies have indicated that the BC has a limited scalability and is computationally costly. Also, it has significant overhead and delay in the network, which is not suitable to the nature of IoT. This article aims at implementing BC in the IoT context for smart home management, as the integration of these two technologies ensures the IoT's security and privacy. Therefore, we proposed an overlay network in private BC to optimize its compatibility with IoT by increasing …

Improving The Performance Of Industrial Mixers That Are Used In Agricultural Technologies Via Chaotic Systems And Artificial Intelligence Techniques, Onur Kalayci, İhsan Pehli̇van, Selçuk Coşkun

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, it is aimed to show how important to apply chaotic systems and Fuzzy Logic artificial intelligence technique to increase the production performance of industrial mixers used in agriculture in terms of important criteria such as product quality, homogeneity, time, and energy saving by using. A PLC (Programmable Logic Controller) controlled mixer whose all functions can be controlled by the HMI (Human Machine Interface) operator panel is designed and manufactured for experimental studies. Water, leonardite and potassium hydroxide (KOH) mixture components are mixed in a newly designed mixer in three different ways by using traditional, chaos, and artificial …

Rtpltool: A Software Tool For Path Loss Modeling In 5g Outdoor Systems, Ci̇han Bariş Findik, Özlem Özgün

Turkish Journal of Electrical Engineering and Computer Sciences

The increase in the required bandwidth along with the global growth of existing wireless communication systems is one of the major reasons why research and industry communities are exploring 5G and millimeter-wave frequencies. The advantages of millimeter wave frequencies for 5G applications are a wide range of accessible and unlicensed spectrum, the use of small antennas in RF applications with increasing frequency, and low losses due to the interference effects compared to the currently used frequency bands. However, due to some computational challenges especially at millimeter waves (i.e. in FR2 frequency band), it is necessary to develop efficient software tools …

Design And Implementation Of A Low Cost And Portable Tactile Stimulator, Coşkun Kazma, Vecdi̇ Emre Levent, Merve Çardak, Ni̇zametti̇n Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

When central nervous system has a problem, somatic area I and II respond to stimulation differently. Therefore, it is possible to identify some of the central nervous diseases when somatosensory on the fingertip is stimulated and responses are recorded and analyzed. We designed a system to stimulate the mechanoreceptors on fingertips. It is composed of a mechanical system for fingertip stimulation, an embedded controller, a control computer, and a software to control overall operation. During test, mechanoreceptors are stimulated according to the test protocols. Individuals' answers are recorded to be evaluated by the developed software. In this study, several design …

Effects Of Rotor-Airframe Interaction On The Aeromechanics And Wake Of A Quadcopter In Forward Flight, Denis-Gabriel Caprace, Andrew Ning, Philippe Chatelain, Grégoire Winckelmans

Faculty Publications

From small drones to large Urban Air Mobility vehicles, the market of vertical take-off and landing (VTOL) aircraft is currently booming. Modern VTOL designs feature a variety of configurations involving rotors, lifting surfaces and bluff bodies. The resulting aerodynamics are highly impacted by the interactions between those components and their wakes. This has consequences on the aircraft performance and on the downstream wake. Studying the effects of those interactions through CFD can inform the development of cheaper numerical models. In this work, we focus on the interaction between rotors and bluff bodies based on the example of a generic quadcopter …

Renewable And Recyclable Polymeric Materials For Food Packaging: A New Open Special Issue In Materials, Shima Jafarzadeh, Masoumeh Zargar, Mehrdad Forough

Research outputs 2022 to 2026

“Renewable and Recyclable Polymeric Materials for Food Packaging” is a new open Special Issue of Materials that will publish original and review papers on new scientific and applied research, and the articles it contains will make a contribution to the discovery and understanding of biodegradable and recyclable materials, their functional properties, characterization and applications.

Li-Ion Electrode Microstructure Evolution During Drying And Calendering, Mojdeh Nikpour, Baichuan Liu, Paul Minson, Zachary Hillman, Brian A. Mazzeo, Dean R. Wheeler

Faculty Publications

The drying process of electrodes might seem to be a simple operation, but it has profound effects on the microstructure. Some unexpected changes can happen depending on the drying conditions. In prior work, we developed the multiphase-smoothed-particle (MPSP) model, which predicted a relative increase in the carbon additive and binder adjacent to the current collector during drying. This motivated us to undertake the present experimental investigation of the relationship between the drying rate and microstructure and transport properties for a typical anode and cathode. Specifically, the drying rate was controlled by means of temperature for both an NMC532 cathode and …

Damage Detection And Damage Localization In Bridges With Low-Density Instrumentations Using The Wave-Method: Application To A Shake-Table Tested Bridge, Mehran Rahmani, Xintong Ji, Sovann Reach Kiet

Mineta Transportation Institute

This study presents a major development to the wave method, a methodology used for structural identification and monitoring. The research team tested the method for use in structural damage detection and damage localization in bridges, the latter being a challenging task. The main goal was to assess capability of the improved method by applying it to a shake-table-tested prototype bridge with sparse instrumentation. The bridge was a 4-span reinforced concrete structure comprising two columns at each bent (6 columns total) and a flat slab. It was tested to failure using seven biaxial excitations at its base. Availability of a robust …

Identifying Population Hollowing Out Regions And Their Dynamic Characteristics Across Central China, Bin Guo, Yi Bian, Lin Pei, Xiaowei Zhu, Dingming Zhang, Wencai Zhang, Xianan Guo, Qiuji Chen

Mechanical and Materials Engineering Faculty Publications and Presentations

Continuous urbanization and industrialization lead to plenty of rural residents migrating to cities for a living, which seriously accelerated the population hollowing issues. This generated series of social issues, including residential estate idle and numerous vigorous laborers migrating from undeveloped rural areas to wealthy cities and towns. Quantitatively determining the population hollowing characteristic is the priority task of realizing rural revitalization. However, the traditional field investigation methods have obvious deficiencies in describing socio-economic phenomena, especially population hollowing, due to weak efficiency and low accuracy. Here, this paper conceives a novel scheme for representing population hollowing levels and exploring the spatiotemporal …

Bitrdf: Extending Rdf For Bitemporal Data, Di Wu

Dissertations, Theses, and Capstone Projects

The Internet is not only a platform for communication, transactions, and cloud storage, but it is also a large knowledge store where people as well as machines can create, manipulate, infer, and make use of data and knowledge. The Semantic Web was developed for this purpose. It aims to help machines understand the meaning of data and knowledge so that machines can use the data and knowledge in decision making. The Resource Description Framework (RDF) forms the foundation of the Semantic Web which is organized as the Semantic Web Layer Cake. RDF is limited and can only express a binary …

Deception Detection Across Domains, Languages And Modalities, Subhadarshi Panda

Dissertations, Theses, and Capstone Projects

With the increase of deception and misinformation especially in social media, it has become crucial to develop machine learning methods to automatically identify deception. In this dissertation, we identify key challenges underlying text-based deception detection in a cross-domain setting, where we do not have training data in the target domain. We analyze the differences between domains and as a result develop methods to improve cross-domain deception detection. We additionally develop approaches that take advantage of cross-lingual properties to support deception detection across languages. This involves the usage of either multilingual NLP models or translation models. Finally, to better understand multi-modal …

Computation Of Risk Measures In Finance And Parallel Real-Time Scheduling, Yajuan Li

Dissertations

Many application areas employ various risk measures, such as a quantile, to assess risks. For example, in finance, risk managers employ a quantile to help determine appropriate levels of capital needed to be able to absorb (with high probability) large unexpected losses in credit portfolios comprising loans, bonds, and other financial instruments subject to default. This dissertation discusses the computation of risk measures in finance and parallel real-time scheduling.

Firstly, two estimation approaches are compared for one risk measure, a quantile, via randomized quasi-Monte Carlo (RQMC) in an asymptotic setting where the number of randomizations for RQMC grows large, but …

Optimizing Incentives For Systems With Heterogeneous Agents, Chen Chen

Dissertations

This dissertation explores new models and applications based on the game theory of incentives. This exploration starts with controlling an invasive insect problem to address one of the most significant challenges facing our forests, the invasion of the Emerald ash borer (EAB), a non-native, wood-boring insect that threatens to kill most ash trees in North America, through designing two new cost-sharing programs between the landowners and local governments. Ash trees are one of North America’s most widely distributed tree genera and a vital part of the green infrastructure of cities, where they provide residents with numerous social, economic, and ecological …

Performance Analysis Of The Dominant Mode Rejection Beamformer, Enlong Hu

Dissertations

In array signal processing over challenging environments, due to the non-stationarity nature of data, it is difficult to obtain enough number of data snapshots to construct an adaptive beamformer (ABF) for detecting weak signal embedded in strong interferences. One type of adaptive method targeting for such applications is the dominant mode rejection (DMR) method, which uses a reshaped eigen-decomposition of sample covariance matrix (SCM) to define a subspace containing the dominant interferers to be rejected, thereby allowing it to detect weak signal in the presence of strong interferences. The DMR weight vector takes a form similar to the adaptive minimum …

Low-Reynolds-Number Locomotion Via Reinforcement Learning, Yuexin Liu

Dissertations

This dissertation summarizes computational results from applying reinforcement learning and deep neural network to the designs of artificial microswimmers in the inertialess regime, where the viscous dissipation in the surrounding fluid environment dominates and the swimmer’s inertia is completely negligible. In particular, works in this dissertation consist of four interrelated studies of the design of microswimmers for different tasks: (1) a one-dimensional microswimmer in free-space that moves towards the target via translation, (2) a one-dimensional microswimmer in a periodic domain that rotates to reach the target, (3) a two-dimensional microswimmer that switches gaits to navigate to the designated targets in …

Artificial Neural Networks And Their Applications To Intelligent Fault Diagnosis Of Power Transmission Lines, Fatemeh Mohammadi Shakiba

Dissertations

Over the past thirty years, the idea of computing based on models inspired by human brains and biological neural networks emerged. Artificial neural networks play an important role in the field of machine learning and hold the key to the success of performing many intelligent tasks by machines. They are used in various applications such as pattern recognition, data classification, stock market prediction, aerospace, weather forecasting, control systems, intelligent automation, robotics, and healthcare. Their architectures generally consist of an input layer, multiple hidden layers, and one output layer. They can be implemented on software or hardware. Nowadays, various structures with …

Behavior Of Novel Cementitious Composites For Use In Sustainable Construction And Rehabilitation, Noah A. Thibodeaux

Dissertations

Cementitious composites are a class of cement-based materials that incorporate a cement paste and other constituents to form a composite material. Cementitious composites may include coarse and/or fine aggregate, admixtures, supplementary cementitious materials (SCMs), or fibers in order to achieve a desired workability, strength, or durability property.

Recently, material scientists and engineers have developed a variety of novel cementitious composites for the purpose of new construction, rehabilitation, and reconstruction applications. Such materials can be used to improve the sustainability of civil infrastructure through the use of recycled, repurposed, or low-embodied carbon materials. Since many of the qualification standards and tests …

Digital Image Forensics Via Meta-Learning And Few-Shot Learning, Yuxi Shi

Dissertations

Digital images are a substantial portion of the information conveyed by social media, the Internet, and television in our daily life. In recent years, digital images have become not only one of the public information carriers, but also a crucial piece of evidence. The widespread availability of low-cost, user-friendly, and potent image editing software and mobile phone applications facilitates altering images without professional expertise. Consequently, safeguarding the originality and integrity of digital images has become a difficulty. Forgers commonly use digital image manipulation to transmit misleading information. Digital image forensics investigates the irregular patterns that might result from image alteration. …

Effect Of Current Density Ramping On The Anodic Reaction And Morphology Of Aerospace Aluminum Alloys, Peter Totaro Jr.

Dissertations

Aluminum anodizing has been experimented with and studied over the last century because of its ability to form uniform, well ordered cellular coatings on aluminum alloys. Anodizing aerospace alloys has been problematic, due to the alloying elements used to add strength and resistance to stress cracking corrosion. These intermetallic compounds, i.e., copper and zinc, promote oxygen evolution and stress as they accumulate in and on the surface of the forming aluminum oxide. These inclusions lead to increased electrical resistance that forms porous and flawed coating, which can lead to industrial and field failures. The amount of voltage placed on the …

Sensorimotor Content Of Multi-Unit Activity In The Paramedian Lobule Of The Cerebellum, Esma Cetinkaya

Dissertations

Based on Center for Disease Control and Prevention report 2016, around 39.5 million people in the United States suffer from motor disabilities. These disabilities are due to traumatic conditions like traumatic brain injury (TBI), neurological diseases such as amyotrophic lateral sclerosis (ALS), or congenital conditions. One of the approaches for restoring the lost motor function is to extract the volitional information from the central nervous system (CNS) and control a mechanical device that can replace the function of a paralyzed limb through systems called Brain-Computer Interfaces (BCI).

One of the major challenges being faced in BCIs and also in general …

Resource Allocation, User Association And Placement For Uav-Assisted Communications, Shuai Zhang

Dissertations

In the past few years, unmanned aerial vehicle (UAV)-assisted heterogeneous network has attracted significant attention due to its wide range of applications, such as disaster rescue and recovery, ground macro base station (MBS) traffic offloading, communications for temporary events, and data collection for further processing in Internet of Things (IoT). A UAV can act as a flying base station (BS) to quickly recover the communication coverage in the disaster area when the regular terrestrial infrastructure is malfunctioned. The UAV-assisted heterogeneous network can effectively provision line of sight (LoS) communication links and therefore can mitigate potential signal shadowing and blockage. The …

Development And Evaluation Of A Hand Exoskeleton For Neurorehabilitation Post Stroke, Ashley Joyce Mont

Dissertations

Stroke affects approximately 800,000 people in the United States each year, and due to its chronic effects, it is one of the leading causes of disability. Many individuals with stroke suffer the loss of motor function in their paretic upper extremity, and longitudinal studies show that 30 — 66% of individuals with hemiplegia fail to regain arm function six months post stroke. After a stroke, the brain undergoes neuroplasticity which will promote recovery of function. Investigators and clinicians are trying to develop rehabilitation interventions that can be designed to promote neuroplasticity, enhancing the recovery outcomes of therapy.

For individuals with …

Modeling Of Two-Dimensional And Biological Materials Towards Diverse Nano-Systems Applications, Jatin Kashyap

Dissertations

This dissertation studies the demonstration of materials ranging from two-dimensional (2D) materials to small bio-molecules using various atomistic/molecular and sub-atomic particles (electron, hole, excitons) modeling techniques for multi-domain applications. Three categories of materials/systems are investigated as follows: 2D materials, biological materials, and complexes of 2D and biological materials.

The first problem demonstrates wrinkles' ubiquitous presence in two-dimensional materials significantly alters their properties. It is observed that water molecules, sourced from ambient humidity or transfer method, can get diffused in between Graphene and the substrate during the Graphene growth. The water diffusion causes/assists wrinkle formation in Graphene, which influences its properties. …

Towards Ensuring Integrity And Authenticity Of Software Repositories, Sangat Vaidya

Dissertations

The software development process comprises a series of steps known as a software supply chain. These steps include managing the source code, testing, building and packaging it into a final product, and distributing the product to end users. Along this chain, software repositories are used for different purposes such as source code management (Git, SVN, mercurial), software distribution (PyPI, RubyGems, NPM) or for deploying software based on container images (Harbor, DockerHub, Artifact Hub). In the recent past, different types of repositories have increasingly been the target of attacks. As such, there is a need for mechanisms to ensure integrity and …

2022 Fall Engr333 Project Assignment, Matthew K. Heun

ENGR 333

The Fall 2022 ENGR333 project focused on sustainable heating for Calvin University.

I asked the students “What would it take to eliminate Calvin’s natural gas-related net CO2 emissions?”

Matt Kucinski (Calvin PR) wrote a story about the project. President Boer wrote a complementary post about the students’ work on LinkedIn.

Customer

The customer for this project was Dr. Wiebe Boer, President of Calvin University.