Digital Commons Network^™

Synchrotron X-Rays Characterizations Of Metal-Air Batteries, Ya-Jie Song, Xue Sun, Li-Ping Ren, Lei Zhao, Fan-Peng Kong, Jia-Jun Wang

Journal of Electrochemistry

The rapid development of electric vehicles urgently requires high-energy-density batteries. Recently, metal-air batteries have attracted much attention in industry and academia for their ultra-high theoretical energy densities. However, the practical application of metal-air batteries is severely impeded by multiple drawbacks, including severe side reactions, low energy efficiency, and limited cycle life. Understanding the reaction mechanism of the cell and further developing effective strategies are beneficial for the practical application of metal-air batteries. In the past decade, advanced characterization techniques have accelerated the development of metal-air batteries. In particular, synchrotron radiation-based characterization techniques have been widely applied to the mechanistic study …

Detecting Iot Attacks Using An Ensemble Machine Learning Model, Vikas Tomar, Sachin Sharma

Articles

Malicious attacks are becoming more prevalent due to the growing use of Internet of Things (IoT) devices in homes, offices, transportation, healthcare, and other locations. By incorporating fog computing into IoT, attacks can be detected in a short amount of time, as the distance between IoT devices and fog devices is smaller than the distance between IoT devices and the cloud. Machine learning is frequently used for the detection of attacks due to the huge amount of data available from IoT devices. However, the problem is that fog devices may not have enough resources, such as processing power and memory, …

Cascading Verification Initiated By Switching Attacks Through Compromised Digital Relays, Koji Yamashita, Zhiyuan Yang, Chee Wooi Ten, Soummya Kar, Andrew Ginter

Michigan Tech Publications, Part 1

Attackers are able to enumerate all devices and computers within a compromised substation network. Digital relays deployed in the substation are the devices with IP addresses that can be discovered in the process of trial-and-error search. This paper is concerned with studies of cyberattacks manipulating digital relays to disruptively disconnect the associated breakers. The plausible enumeration of such disruptive attack for each relay in a substation is verified with the dynamic simulation studies with the special protection system for frequency, voltage, and rotor angle stability. A pertinent approach with smaller scale contingency analysis results is proposed to reduce the enormous …

A Deep Learning-Based Approach To Extraction Of Filler Morphology In Sem Images With The Application Of Automated Quality Inspection, Md. Fashiar Rahman, Tzu-Liang Bill Tseng, Jianguo Wu, Yuxin Wen, Yirong Lin

Engineering Faculty Articles and Research

Automatic extraction of filler morphology (size, orientation, and spatial distribution) in Scanning Electron Microscopic (SEM) images is essential in many applications such as automatic quality inspection in composite manufacturing. Extraction of filler morphology greatly depends on accurate segmentation of fillers (fibers and particles), which is a challenging task due to the overlap of fibers and particles and their obscure presence in SEM images. Convolution Neural Networks (CNNs) have been shown to be very effective at object recognition in digital images. This paper proposes an automatic filler detection system in SEM images, utilizing a Mask Region-based CNN architecture. The proposed system …

Queueing Theory Model Of Pentose Phosphate Pathway, Sylwester M. Kloska, Krzysztof Pałczyński, Tomasz Marciniak, Tomasz Talaśka, Marissa Miller, Beata J. Wysocki, Paul H. Davis, Tadeusz A. Wysocki

Department of Electrical and Computer Engineering: Faculty Publications

Due to its role in maintaining the proper functioning of the cell, the pentose phosphate pathway (PPP) is one of the most important metabolic pathways. It is responsible for regulating the concentration of simple sugars and provides precursors for the synthesis of amino acids and nucleotides. In addition, it plays a critical role in maintaining an adequate level of NADPH, which is necessary for the cell to fight oxidative stress. These reasons prompted the authors to develop a computational model, based on queueing theory, capable of simulating changes in PPP metabolites’ concentrations. The model has been validated with empirical data …

Considerations For Radio Frequency Fingerprinting Across Multiple Frequency Channels, Jose A. Gutierrez Del Arroyo, Brett J. Borghetti, Michael A. Temple

Faculty Publications

Radio Frequency Fingerprinting (RFF) is often proposed as an authentication mechanism for wireless device security, but application of existing techniques in multi-channel scenarios is limited because prior models were created and evaluated using bursts from a single frequency channel without considering the effects of multi-channel operation. Our research evaluated the multi-channel performance of four single-channel models with increasing complexity, to include a simple discriminant analysis model and three neural networks. Performance characterization using the multi-class Matthews Correlation Coefficient (MCC) revealed that using frequency channels other than those used to train the models can lead to a deterioration in performance from …

Ad-Corre: Adaptive Correlation-Based Loss For Facial Expression Recognition In The Wild, Ali Pourramezan Fard, Mohammad H. Mahoor

Electrical and Computer Engineering: Faculty Scholarship

Automated Facial Expression Recognition (FER) in the wild using deep neural networks is still challenging due to intra-class variations and inter-class similarities in facial images. Deep Metric Learning (DML) is among the widely used methods to deal with these issues by improving the discriminative power of the learned embedded features. This paper proposes an Adaptive Correlation (Ad-Corre) Loss to guide the network towards generating embedded feature vectors with high correlation for within-class samples and less correlation for between-class samples. Ad-Corre consists of 3 components called Feature Discriminator, Mean Discriminator, and Embedding Discriminator. We design the Feature Discriminator component to guide …

Technical Analysis Of Thanos Ransomware, Ikuromor Ogiriki, Christopher Beck, Vahid Heydari

College of Science & Mathematics Departmental Research

Ransomware is a developing menace that encrypts users’ files and holds the decryption key hostage until the victim pays a ransom. This particular class of malware has been in charge of extortion hundreds of millions of dollars every year. Adding to the problem, generating new variations is cheap. Therefore, new malware can detect antivirus and intrusion detection systems and evade them or manifest in ways to make themselves undetectable. We must first understand the characteristics and behavior of various varieties of ransomware to create and construct effective security mechanisms to combat them. This research presents a novel dynamic and behavioral …

Identification And Mitigation Of Non-Line-Of-Sight Path Effect Using Repeater Forhybrid Ultra-Wideband Positioning And Networking System, Gwo Chin Chung, Mohd. Aqmal Syafiq Kamarudin, It Ee Lee, Soo Fun Tan

Turkish Journal of Electrical Engineering and Computer Sciences

At least two decades ago, various applications have been proposed for the implementation of ultra-wideband (UWB) technology, but only a few of them are being realised such as radar detection, home networking, and indoor positioning. Although UWB positioning offers precise locality tracking, the accuracy of the estimation is greatly affected by the non-line-of-sight (NLOS) path effect. In this paper, we propose a hybrid indoor UWB positioning and networking system that utilises the existing repeater of the data network to eliminate the NLOS paths. A switching algorithm is written to identify the existence of NLOS paths based on received signal strength …

A Factor Graph Optimization Mapping Based On Normaldistributions Transform, Kedi Zhong, Yuansheng Liu, Jiansuo Yang, Ming Lu, Jun Zhang

Turkish Journal of Electrical Engineering and Computer Sciences

This paper aims to achieve highly accurate mapping results and real time pose estimation of autonomous vehicle by using the normal distribution transform (NDT) algoritm. A factor graph optimization algorithm (FGO-NDT) is proposed to address the poor real-time performance and pose drift errors of the NDT algorithm. Smooth point cloud data are obtained by multisensor calibration and data preprocessing. NDT registration is then used for lidar odometry and feature matching. The global navigation satellite system (GNSS) data and loop detection results are added to the factor graph framework as the pose constraint factors to optimize the pose trajectory and eliminate …

Clustering With Density Based Initialization And Bhattacharyya Based Merging, Erdem Köse, Ali̇ Köksal Hocaoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Centroid based clustering approaches, such as k-means, are relatively fast but inaccurate for arbitrary shape clusters. Fuzzy c-means with Mahalanobis distance can accurately identify clusters if data set can be modelled by a mixture of Gaussian distributions. However, they require number of clusters apriori and a bad initialization can cause poor results. Density based clustering methods, such as DBSCAN, overcome these disadvantages. However, they may perform poorly when the dataset is imbalanced. This paper proposes a clustering method, named clustering with density initialization and Bhattacharyya based merging based on the fuzzy clustering. The initialization is carried out by density estimation …

Calculating Influence Based On The Fusion Of Interest Similarity And Informationdissemination Ability, Shulin Cheng, Ziming Wang, Meng Qian, Shan Yang, Xin Zheng

Turkish Journal of Electrical Engineering and Computer Sciences

With the popularization, in-depth development and application of the Internet, microblogs have become a mainstream social network platform. Several studies on social networks have conducted researches, and user influence evaluation is an important research hotspot. Most of the existing studies calculate user influence by improving PageRank and have achieved certain results. However, these studies ignored the fusion of users' interest theme similarity and information dissemination ability, and the analysis of interaction behaviors among users is not comprehensive. To address these issues, we propose a new microblog user influence algorithm called microblog user influence based on interest similarity and information dissemination …

Performance Analysis And Feature Selection For Network-Based Intrusion Detectionwith Deep Learning, Serhat Caner, Nesli̇ Erdoğmuş, Yusuf Murat Erten

Turkish Journal of Electrical Engineering and Computer Sciences

An intrusion detection system is an automated monitoring tool that analyzes network traffic and detects malicious activities by looking out either for known patterns of attacks or for an anomaly. In this study, intrusion detection and classification performances of different deep learning based systems are examined. For this purpose, 24 deep neural networks with four different architectures are trained and evaluated on CICIDS2017 dataset. Furthermore, the best performing model is utilized to inspect raw network traffic features and rank them with respect to their contributions to success rates. By selecting features with respect to their ranks, sets of varying size …

Modeling And Evaluation Of Soc-Based Coordinated Ev Charging For Powermanagement In A Distribution System, Murat Akil, Emrah Dokur, Ramazan Bayindir

Turkish Journal of Electrical Engineering and Computer Sciences

The importance of using clean energy in electrical energy generation and transportation network planning has recently increased due to carbon footprint rising. In this direction, the use of electric vehicles (EV), known as ultra-low carbon emission vehicles, has become widespread in addition to renewable energy sources (RES) such as wind and photovoltaic (PV) power generations. The trend of EVs to be preferred the primary means of transport has revealed the effects of charging an additional load on the grid. There is a need to create coordinated charging methods by considering the approaches for real-time charging models of EVs. In this …

Predictive Optimization Of Sliding Mode Control Using Recurrent Neural Paradigmfor Nonlinear Dfig-Wpgs During Distorted Voltage, Omar Busati, Xiangjie Liu

Turkish Journal of Electrical Engineering and Computer Sciences

Dynamic characteristics of the doubly-fed induction generator (DFIG)-based wind power generation (WPGS) are fully nonlinear. Therefore, issues such as stability and achieving high efficiency, especially under harmonics behavior, are challenges that assess the control strategy reliability to find the perfect dynamic solution. This discussion offers a control strategy for the separated stator-port power using a predictive sliding mode strategy with a resonant function (PSMC-R) based on a deep recurrent neural network (DRNN). DRNN is formed as a low-order Taylor series formula. PSMC-R predicts the perfect switching surface path and regulates the distorted nonlinear DFIG with several dynamic aims. This approach …

Reactive Power Sharing And Voltage Restoration In Islanded Ac Microgrids, Khurram Hashmi, Rizwan Ali, Muhammad Hanan, Waseem Aslam, Abubakar Siddique, Muhammad Mansoor Khan

Turkish Journal of Electrical Engineering and Computer Sciences

Microgrids (MG) are a new and innovative concept in modern distribution networks. Several challenges are associated with the operation and control of MG networks. Active and reactive power sharing among energy resources interfaced through power electronic conversion stages is a major challenge. Although active power sharing can be achieved under varying scenarios, sharing of reactive power between distributed generation units is difficult to achieve. This paper presents a novel and innovative control scheme to ensure sharing of reactive power between Distributed generation units within an autonomous, islanded AC microgrid. A framework composed of novel multiagent moving average estimators is proposed …

Design And Manufacture Of Electromagnetic Absorber Composed Of Boricacid-Incorporated Wastepaper Composites, Ali̇ İhsan Kaya, Ahmet Çi̇fci̇, Fi̇li̇z Kirdioğullari, Mesud Kahri̇man, Osman Çerezci̇

Turkish Journal of Electrical Engineering and Computer Sciences

With the effect of technological advances, the use of electrical and electronic devices has increased dramatically in recent years. Wireless technologies and related applications are mostly preferred for the communication of these devices with each other. Thus, people are easily exposed to electromagnetic waves in daily life. The extensive global use of these devices raises the question of their possible biological effects on human health. Also, electromagnetic waves influence the functioning of a nearby device. In this study, an electromagnetic absorber based on boric acid (5, 10, 20, and 30 wt%) added wastepaper was developed. Copper (Cu) and aluminum (Al) …

45-Nm Cds Qds Photoluminescent Filter For Photovoltaic Conversionefficiency Recovery, Victor Juárez-Luna, Daniel Sauceda-Carvajal, Ivett Zavala-Guillen, Enrique Rodarte-Guajardo, Francisco Carranza-Chávez, Carlos Villa Angulo

Turkish Journal of Electrical Engineering and Computer Sciences

Different energy loss mechanisms have restricted the breakthroughs in concentrated photovoltaic/thermal (CPVT) hybrid solar systems that use photoluminescent filters. Re?ected and transmitted light, emission spectrum, nonideal absorption, Stokes shift (proportional to $f_1 f_2$), overlapping absorption, and scattering of light are mechanisms in photoluminescent filters that restrict optical efficiency to below theoretical limits. In addition, increases in temperature by light concentration affect the operation of photovoltaic cells and photoluminescent filters because of an increase in molecular motion and collisions that consequently lead to energy loss. Meanwhile, nanocrystals or quantum dots (QDs) from groups II VI hold electrical, optical, chemical, and physical …

Tara: Temperature Aware Online Dynamic Resource Allocation Scheme For Energyoptimization In Cloud Data Centres, Narayanamoorthi Thilagavathi, Arockiasamy John Prakash, Sridhar Sridevi, Vaidyanathan Rhymend Uthariaraj

Turkish Journal of Electrical Engineering and Computer Sciences

Cloud data centres, which are characteristic of dynamic workloads, if not optimized for energy consumption, may lead to increased heat dissipation and eventually impact the environment adversely. Consequently, optimizing the usage of energy has become a hard requirement in today's cloud data centres wherein the major part of energy consumption is mostly attributed to computing and cooling systems. Motivated by which this paper proposes an online algorithm for dynamic resource allocation, namely, temperature aware online dynamic resource allocation algorithm (TARA). TARA demonstrates a novel algorithm design to adapt dynamic resource allocation based on the temperature of a data centre using …

Visual Interpretability Of Capsule Network For Medical Image Analysis, Mighty Abra Ayidzoe, Yu Yongbin, Patrick Kwabena Mensah, Jingye Cai, Faiza Umar Bawah

Turkish Journal of Electrical Engineering and Computer Sciences

Deep learning (DL) models are currently not widely deployed for critical tasks such as in health. This is attributable to the "black box", making it difficult to gain the trust of practitioners. This paper proposes the use of visualizations to enhance performance verification, improve monitoring, ensure understandability, and improve interpretability needed to gain practitioners' confidence. These are demonstrated through the development of a CapsNet model for the recognition of gastrointestinal tract infection. The gastrointestinal tract comprises several organs joined in a long tube from the mouth to the anus. It is susceptive to diseases that are difficult for medics to …

Applications Of A Lightning Proxy To Generate Synthetic Lightning For Use In Physics-Based Image-Chain Models, Bryan G. Castro

Theses and Dissertations

A method of generating synthetic lightning through the use of a convective available potential energy (CAPE) times precipitation rate (P) proxy is applied over three distinct climatological zones of the world for a single warm season: central and southern AZ of the United States, central Cuba, and North Korea. Global Forecast System (GFS) 0.25° by 0.25° forecast data for June, July, and August of 2019 is used to provide 6-hourly CAPE and precipitation rate, while Global Lightning Dataset (GLD360) data for the period 2016 to 2020 is used to provide observed lightning strokes. A five-year lightning climatology study is conducted …

Monocular Camera Localization Using A Bag Of Visual Words From Virtual World Data, Joshua A. Rinaldi

Theses and Dissertations

The Visual Localization problem is the question of how to use visual information to determine the location of the camera that captured that data. The wide availability and low price of RGB cameras has made this useful in many fields such as SLAM, SAM and AR. This research seeks to determine if a BOVW can adequately overcome repetitious features in indoor environments and be effectively incorporated into a VL pipeline.

Malware Detection Using Electromagnetic Side-Channel Analysis, Matthew A. Bergstedt

Theses and Dissertations

Many physical systems control or monitor important applications without the capacity to monitor for malware using on-device resources. Thus, it becomes valuable to explore malware detection methods for these systems utilizing external or off-device resources. This research investigates the viability of employing EM SCA to determine whether a performed operation is normal or malicious. A Raspberry Pi 3 was set up as a simulated motor controller with code paths for a normal or malicious operation. While the normal path only calculated the motor speed before updating the motor, the malicious path added a line of code to modify the calculated …

Detection And Identification Of Cellphone Emitted Light Detection And Ranging Light In Security Camera Video Footage, Tristan V. Creek

Theses and Dissertations

The prevalence of Light Detection and Ranging (LiDAR) sensors in consumer cellphones has ushered in an era of access to technologies previously inaccessible to the average person. Although LiDAR sensors emit light in the infrared spectrum invisible to the naked eye, many security cameras possess the ability to capture infrared light reflected off surfaces to detect LiDAR light in an environment. Once detected and recorded to video footage, current classification methods fail to identify the LiDAR light. Therefore, this research develops a methodology to detect LiDAR light in security camera video footage and identify it as cellphone LiDAR. A proposed …

Load Slammer Design For Dc-Dc Converter Testing, Jonathan Hidalgo, Quinton Lacomb

Electrical Engineering

In this work, we dive into the detailed design of a test load or load slammer circuit for DC/DC converters to ensure their correct functioning. This is accomplished through quick variations in frequency, amplitude, and duty cycle of the current being drawn by the converter into the load. Computer simulations of the design were performed using LTSpice and the results show that the load current could be varied per design objectives. Hardware implementation of the design was also conducted and then tested. Results were then compared with the design requirements at lower currents to evaluate the validity of the design. …

Verification Of A Digital Microfluidics Platform, Karanpartap Singh

Electrical Engineering

The electrowetting effect describes the change in contact angle between a solid surface and electrolyte in response to an applied electric potential difference. Given a planar array of individually-actuated electrodes, electrowetting can be used to transport, mix, and separate picoliter to microliter-sized droplets of liquid on a dielectric layer. Applications of this phenomenon range from lab-on-a-chip and other microfluidic devices to liquid lenses capable of altering their topology and focus within milliseconds.

This project extends prior work simulating the dependence of droplet velocity on actuation voltage and demonstrates observed physics on a physical platform. The simulation portion of this project …

Smart Motor Syringe System, Connor Wilson

Electrical Engineering

In this document a proof-of-concept design is developed and implementation to showcase the latest development in an ongoing effort to produce a series of automated syringe pumps.

Underground Transmission For Renewable Energy: Design, Modeling, And Analysis, Matthew Suen

Master's Theses

A microgrid is a local energy grid that could be disconnected from the larger grid and operate autonomously. This particular segment of the power industry is growing due to its reliability during times of emergency and crisis. Among these benefits are improved efficiency, lower operating costs, renewable generation sources, and improved resiliency of the regional electric grid. Communities can better prepare for unprecedented weather like wildfires, hurricanes, and other natural disasters. Regions that produce renewable energy can export their surplus through high voltage transmission lines to balance power supply and demand needs.

This Underground High-Voltage Transmission Network project aims to …

Improving Utilization Rate Of Semi-Parallel Successive Cancellation Architecture For Polar Codes Using 2-Bit Decoding, Dinesh Kumar Devadoss, Shantha Selva Kumari Rama Packiam

Turkish Journal of Electrical Engineering and Computer Sciences

Polar codes are the capacity-achieving error-correcting code proved to be a significant invention in coding theory. It can achieve channel capacity at infinite code length N due to its explicit code construction. However, the processing complexity along with the higher latency due to successive cancellation (SC) decoding is being a major design issue, which reduces the utilization rate in the decoder architectures. This paper presents a modified semi-parallel architecture for decoding polar code with a better decoding latency. Precomputation and look-ahead techniques are used to generate two bits in the final stage. Pipelined partial-sum unit with a less critical path …

Developing A Fake News Identification Model With Advanced Deep Languagetransformers For Turkish Covid-19 Misinformation Data, Mehmet Bozuyla, Akin Özçi̇ft

Turkish Journal of Electrical Engineering and Computer Sciences

The massive use of social media causes rapid information dissemination that amplifies harmful messages such as fake news. Fake-news is misleading information presented as factual news that is generally used to manipulate public opinion. In particular, fake news related to COVID-19 is defined as 'infodemic' by World Health Organization. An infodemic is a misleading information that causes confusion which may harm health. There is a high volume of misinformation about COVID-19 that causes panic and high stress. Therefore, the importance of development of COVID-19 related fake news identification model is clear and it is particularly important for Turkish language from …