Engineering Commons^™

Missing Samples Reconstruction Using An Efficient And Robust Instantaneous Frequency Estimation Algorithm, Sadiq Ali, Nabeel Ali Khan

Turkish Journal of Electrical Engineering and Computer Sciences

In order to recover missing samples in a nonstationary signal, this paper employs a time-signal analysis and filtering method. The instantaneous frequency of a multicomponent signal is first estimated by employing a robust and computationally efficient method. Then the time-frequency filtering is performed using a dechirping operation to recover missing samples. These steps are repeated until convergence. The proposed method achieves better performance than the state of art methods both in terms of the accuracy of the recovered signal and computational efficiency.

Dual-Polarized Elliptic-H Slot-Coupled Patch Antenna For 5g Applications, Emre Alp Mi̇ran, Mehmet Çi̇ydem

Turkish Journal of Electrical Engineering and Computer Sciences

A dual-polarized, slot-coupled dielectric patch antenna design is presented in sub-6 GHz for 5G base stations. Proposed antenna is implemented using two dielectric patch layers (main patch and parasitic patch) above a feeding line layer. Excitation is realized by crossed elliptic-H slots in order to create orthogonal ± 45$^{\circ}$ polarizations. Through the use of patches at proper heights together with elliptic-H slots, significant improvement in impedance bandwidth, matching level, isolation and front-to-back ratio is acquired. Prototype antenna has an impedance bandwidth of 18.5\% (3.23--3.85 GHz) for $ S_{11} $, $ S_{22} $ $

Classification And Phenological Staging Of Crops From In Situ Image Sequences By Deep Learning, Uluğ Bayazit, Deni̇z Turgay Altilar, Ni̇lgün Güler Bayazit

Turkish Journal of Electrical Engineering and Computer Sciences

Accurate knowledge of crop type information is not only valuable for verifying the declaration of farmers to obtain subsidy or insurance for the grown crop, but also for generating crop type maps that serve a variety of purposes in land monitoring and policy. On the other hand, accurate knowledge of crop phenological stage can help farm personnel apply fertilization and irrigation regimes on a timely basis. Although deep learning based networks have been applied in the past to classify the type and predict the phenological stage of crops from in situ images of fields, more advanced deep learning based networks, …

Binary Flower Pollination Algorithm Based User Scheduling For Multiuser Mimo Systems, Jyoti Mohanty, Prabina Pattanayak, Arnab Nandi, Krishna Lal Baishnab, Fazal Ahmed Talukdar

Turkish Journal of Electrical Engineering and Computer Sciences

In this article, a multiuser (MU) multiinput multioutput (MIMO) system is considered, which is essential to support a huge number of subscribers without consuming extra bandwidth or power. Dirty paper coding (DPC) for MU MIMO channel achieves the peak sum-rate for the MU multiple antenna system at the cost of high computational complexity. Both user and antenna scheduling with a population based meta-heuristic algorithm, i.e. binary flower pollination algorithm (binary FPA) has been demonstrated in this article to achieve system sum-rate comparable to DPC with very less computational complexity and time complexity. Moreover, binary FPA shows a significant improvement in …

Stochastic Day-Ahead Optimal Scheduling Of Multimicrogrids: An Alternating Direction Method Of Multipliers (Admm) Approach, Amin Safari, Hossein Nasiraghdam

Turkish Journal of Electrical Engineering and Computer Sciences

Multimicrogrid system is a novel notion in modern power systems as a result of developing renewable-based generation units and accordingly microgrids in distribution networks. Their energy management might be challenging due to presence of independent units. Thus, in this paper, a decentralized method for energy management of multimicrogrid systems has been proposed. Decentralized methods can enhance the privacy of users and reduce the burden of calculations. Alternating direction method of multipliers (ADMM) is selected as a decentralized approach which has the capability of breaking problems with complicating constraints in order to facilitate the solving process. Using decentralized approach not only …

A New Effective Denoising Filter For High Density Impulse Noise Reduction, Iman Elawady, Caner Özcan

Turkish Journal of Electrical Engineering and Computer Sciences

Today, thanks to the rapid development of technology, the importance of digital images is increasing. However, sensor errors that may occur during the acquisition, interruptions in the transmission of images and errors in storage cause noise that degrades data quality. Salt and pepper noise, a common impulse noise, is one of the most well-known types of noise in digital images. This noise negatively affects the detailed analysis of the image. It is very important that pixels affected by noise are restored without loss of image fine details, especially at high level of noise density. Although many filtering algorithms have been …

Twitter Account Classification Using Account Metadata: Organizationvs. Individual, Yusuf Mucahi̇t Çeti̇nkaya, Mesut Gürlek, İsmai̇l Hakki Toroslu, Pinar Karagöz

Turkish Journal of Electrical Engineering and Computer Sciences

Organizations present their existence on social media to gain followers and reach out to the crowds. Social media-related tasks and applications, such as social media graph construction, sentiment analysis, and bot detection, are required to identify the entities' account types. Some applications focus on personal accounts, whereas others only need nonpersonal accounts. This paper addresses the account classification problem using only minimum amount of data, which is the metadata of the account's profile. The proposed approach classifies accounts either as organization or individual, in a language-independent manner, without collecting the accounts' tweet content. The model uses a long short term …

Development Of A Control Algorithm And Conditioning Monitoring For Peak Load Balancing In Smart Grids With Battery Energy Storage System, Turhan Atici, Sezai̇ Taşkin, İbrahi̇m Şengör, Maci̇t Tozak, Osman Demi̇rci̇

Turkish Journal of Electrical Engineering and Computer Sciences

As the traditional electricity grid transitions to the smart grid (SG), some emerging issues such as increased renewable energy penetration in the power system that cause load unbalances require new control methods. Storage of energy seems to be the best option to struggle with such issues. In this manner, energy storage technologies ensure the operating flexibility of the distribution system operator in the power system in terms of both sustainability of energy and peak load balancing. In this study, a grid condition monitoring user-interface and control algorithm is developed for the peak load reduction and supply-demand balancing in a SG …

Blmdp: A New Bi-Level Markov Decision Process Approach To Joint Bidding Andtask-Scheduling In Cloud Spot Market, Mona Naghdehforoushha, Mehdi Dehghan Takht Fooladi, Mohammad Hossein Rezvani, Mohammad Mehdi Gilanian Sadeghi

Turkish Journal of Electrical Engineering and Computer Sciences

In the cloud computing market (CCM), computing services are traded between cloud providers and consumers in the form of the computing capacity of virtual machines (VMs). The Amazon spot market is one of the most well-known markets in which the surplus capacity of data centers is auctioned off in the form of VMs at relatively low prices. For each submitted task, the user can offer a price that is higher than the current price. However, uncertainty in the market environment confronts the user with challenges such as the variable price of VMs and the variable number of users. An appropriate …

Priority Enabled Content Based Forwarding In Fog Computing Via Sdn, Yasi̇n İnağ, Metehan Güzel, Feyza Yildirim Okay, Mehmet Demi̇rci̇, Suat Özdemi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

As the number of Internet of Things (IoT) applications increases, an efficient transmitting of the data generated by these applications to a centralized cloud server can be a challenging issue. This paper aims to facilitate transmission by utilizing fog computing (FC) and software defined networking (SDN) technologies. To this end, it proposes two novel content based forwarding (CBF) models for IoT networks. The first model takes advantage of FC to reduce transmission and computational delay. Based on the first model, the second model makes use of the prioritization concept to address the timely delivery of critical data while ensuring the …

Estimation Of Mode Shape In Power Systems Under Ambient Conditions Using Advanced Signal Processing Approach, Rahul S, Sunitha R

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents a dynamic approach for the monitoring and estimation of electromechanical oscillatory modes in the power system in real time with less computational burden. Extensive implementation of phasor measurement units (PMU) and the utilization of advanced signal processing techniques help in identifying the dynamic behaviors of oscillatory modes. Conventional nonstationary analysis techniques are computationally weak to handle a larger quantity of data in real-time. This research utilizes the variational mode decomposition (VMD) for signal decomposition, which is highly tolerant to noise and computationally more robust. The predefined parameters of the VMD process are assigned using FFT analysis of …

A Novel Crimping Technique Approach For High Power White Good Plugs, Ömer Ci̇han Kivanç, Okan Özgönenel, Ömer Bostan, Şahi̇n Güzel, Mert Demi̇rsoy

Turkish Journal of Electrical Engineering and Computer Sciences

The crimping process is essential to human health and the durability of devices, especially in domestic appliances. Moreover, terminal crimping is critical to the safe transmission of electricity; incorrect crimping leads to problems including overheating of the plug, power loss, arc, and failure of the mechanical connection. In recent years, analysis has been performed by the finite element method (FEM) to prevent the incorrect design of crimping and to develop higher performance crimping techniques. A novel crimping technique for domestic appliances requiring high powered plugs is proposed in this study. After defining the crimp parameters and the materials that are …

A Novel Deep Reinforcement Learning Based Stock Price Prediction Using Knowledge Graph And Community Aware Sentiments, Anil Berk Altuner, Zeynep Hi̇lal Ki̇li̇mci̇

Turkish Journal of Electrical Engineering and Computer Sciences

Stock market prediction has been an important topic for investors, researchers, and analysts. Because it is affected by too many factors, stock market prediction is a difficult task to handle. In this study, we propose a novel method that is based on deep reinforcement learning methodologies for the prediction of stock prices using sentiments of community and knowledge graph. For this purpose, we firstly construct a social knowledge graph of users by analyzing relations between connections. After that, time series analysis of related stock and sentiment analysis is blended with deep reinforcement methodology. Turkish version of Bidirectional Encoder Representations from …

Residential Energy Management System Based On Integration Of Fuzzy Logic And Simulated Annealing, Ömer Ci̇han Kivanç, Beki̇r Tevfi̇k Akgün, Semi̇h Bi̇lgen, Sali̇h Bariş Öztürk, Suat Baysan, Ramazan Nejat Tuncay

Turkish Journal of Electrical Engineering and Computer Sciences

With the increase in prosperity level and industrialization, energy need continues to overgrow in many countries. To meet the rapidly increasing energy needs, countries attach great importance to using limited natural resources rationally, diversifying their energy production using novel technologies, improving the efficiency of existing technologies, and implementing policies and strategies toward alternative energy sources. In particular, individual energy prosumers (someone that both produces and consumes energy) head toward smart home energy management systems (SHEMS) that include renewable energy sources in their homes. By integrating PV solar panels into houses, there is a need to optimize home energy production/consumption scenarios …

A New Speed Planning Method Based On Predictive Curvature Calculation For Autonomous Driving, Beki̇r Öztürk, Volkan Sezer

Turkish Journal of Electrical Engineering and Computer Sciences

As the number of vehicles in traffic is increasing day by day, the accident rates and driving effort are significantly raising. For this reason, ensuring safety and driving comfort is becoming more and more important. Driver assistance systems are the most common systems that are adopted for this purpose. With the development of technology, lane tracking support and adaptive cruise control systems are now being sold as standard equipment. More advanced research is being done for fully autonomous driving. One of the most critical parts of autonomous driving is speed profile planning. In this paper, a curvature-based predictive speed planner …

Lightweight Distributed Computing Framework For Orchestrating High Performance Computing And Big Data, Muhammed Numan İnce, Meli̇h Günay, Joseph Ledet

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, the need for the ability to work remotely and subsequently the need for the availability of remote computer-based systems has increased substantially. This trend has seen a dramatic increase with the onset of the 2020 pandemic. Often local data is produced, stored, and processed in the cloud to remedy this flood of computation and storage needs. Historically, HPC (high performance computing) and the concept of big data have been utilized for the storage and processing of large data. However, both HPC and Hadoop can be utilized as solutions for analytical work, though the differences between these may …

Two Person Interaction Recognition Based On A Dual-Coded Modified Metacognitive (Dcmmc) Extreme Learning Machine, Saman Nikzad, Afshin Ebrahimi

Turkish Journal of Electrical Engineering and Computer Sciences

Human action recognition has been an active research area for over three decades. However, state-of-the-art proposed algorithms are still far from developing error-free and fully-generalized systems to perform accurate interaction recognition. This work proposes a new method for two-person interaction recognition from videos, based on well-known cognitive theories. The main idea is to perform classification based on a theory of cognition known as dual coding theory. The theory states that human brain processes and represents two types of information to learn/classify data named analogue and symbolic codes, i.e. (verbal as analogue and visual as symbolic). To implement such a theory …

Offline Tuning Mechanism Of Joint Angular Controller For Lower-Limb Exoskeleton With Adaptive Biogeographical-Based Optimization, Mohammad Soleimani Amiri, Rizauddin Ramli

Turkish Journal of Electrical Engineering and Computer Sciences

Designing an accurate controller to overcome the nonlinearity of dynamic systems is a technical matter in control engineering, particularly for tuning the parameters of the controller precisely. In this paper, a tuning mechanism for a proportional-integral-derivative (PID) controller of lower limb exoskeleton (LLE) joints by adaptive biogeographical based-optimization (ABBO) is presented. The tuning of the controller is defined as an optimization problem and solved by ABBO, which is an iterative algorithm inspired by a blending crossover operator (BLX-?). The parameters of the migration change proportionally to the growth of iteration that conveys the error to rapid convergence by narrowing the …

Analog & Digital Metronome, Andrew Deering, Paul Kim, Gabriel Ogden

Mechatronics Final Projects

The metronome is a tabletop device designed to keep a consistent rhythm for musicians to follow. This specific metronome combines the visuals of a traditional analog metronome with the ease of use and functionality of its digital counterpart. Like a conventional digital metronome, the user can control the beats per minute (BPM) using the control knob on the front of the device and read the current BPM value on the front mounted display. The user can observe

Fixed-Bed Column Study Of Phosphate Adsorption Using Immobilized Phosphate-Binding Protein, Faten B. Hussein, Brooke K. Mayer

Civil and Environmental Engineering Faculty Research and Publications

Bio-adsorption using high-affinity phosphate-binding proteins (PBP) has demonstrated effective phosphorus removal and recovery in batch-scale tests. Subsequent optimization of design and performance of fixed-bed column systems is essential for scaling up and implementation. Here, continuous-flow fixed-bed column tests were used to investigate the adsorption of inorganic phosphate (orthophosphate, Pi) using phosphate-binding proteins immobilized on resin (PBP–NHS) targeting Pi removal to ultra-low levels followed by recovery. Time to breakthrough decreased with higher influent Pi concentration, smaller bed volume, and higher influent flow rates. The Thomas and Yoon-Nelson breakthrough models adequately described PBP-NHS resin performance with a correlation coefficient of R2 > 0.95. …

Machine Learning Based Surrogate Model For Hurricane Storm Surge Forecasting In The Laguna Madre, Cesar E. Davila Hernandez

Theses and Dissertations

Texas coastal communities are at constant risk of hurricane impacts every storm season. It is especially important to model and predict storm surge variations during hurricane and storm events. Traditionally, hurricane storm surge predictions have been the result of numerical hydrodynamics based simulations. This type of simulations often requires high amounts of computational resources and complex ocean modelling efforts. Recently, machine learning techniques are being explored and are gaining popularity in hydrologic and ocean engineering modelling fields based on their performance to model nonlinear relationships and low computational requirements for prediction. Advances in machine learning and artificial intelligence (A.I.) demand …

Behavior Of Narrow Mechanically Stabilized Earth Walls With Secondary Reinforcement, Abraham Alejandro Alvarez Reyna

Theses and Dissertations

Mechanically Stabilized Earth (MSE) walls have been used in past decades as an alternative, cost-effective, and performance solution to replace conventional retaining walls. AASHTO guidelines recommend a reinforcement length-to-height ratio of 0.7. However, this ratio is not applicable where there exist constraint conditions. FHWA guidelines recommend the minimum reinforcement length-to-height ratio of 0.3 for Narrow Mechanically Stabilized Earth (NMSE) walls in these cases. However, published guidelines have not sufficiently accounted for several parameters influencing NMSE performance and efficiency. Using finite element analysis (PLAXIS 2D), this study focuses on finding a relation between the length-to-height ratio and other parameters/components of the …

Monitoring Of Tool Wear And Surface Roughness Using Anfis Method During Cnc Turning Of Cfrp Composite, Md Mofakkirul Islam

Theses and Dissertations

Carbon fiber-reinforced plastic (CFRP) is gaining wide acceptance in areas including sports, aerospace and automobile industry . Because of its superior mechanical qualities and lower weight than metals, it needs effective and efficient machining methods. In this study, the relationship between the cutting parameters (Speed, Feed, Depth of Cut) and response parameters (Vibration, Surface Finish, Cutting Force and Tool Wear) are investigated for CFRP composite. For machining of CFRP, CNC turning operation with coated carbide tool is used. An ANFIS model with two MISO system has been developed to predict the tool wear and surface finish. Speed, feed, depth of …

Adaptation Strategies To Mitigate Impacts Of Sea Level Rise On A Freshwater Aquifer Supply On A Barrier Island, Kaylyn Bellais

Graduate Theses and Dissertations (2019 - present)

Adaptation strategies are used to reduce vulnerability in response to storms and sea-level rise (SLR). An adaptation tipping point for a barrier island is said to exist when an adaptation strategy fails. Previous studies have applied statistics to identify adaptation tipping points and construct adaptation pathways as a function of quantity of SLR. This study is focused on Alligator Lake and Oleander Pond on the barrier island Dauphin Island, AL; a site residents and community leaders identified as vulnerable to saltwater intrusion under future SLR conditions. Therefore, the purposes of this study are to numerically simulate impacts of a storm …

Enter The Battleverse: China's Metaverse War, Josh Baughman

Military Cyber Affairs

No abstract provided.

The Iwar Range + 21 Years: Cyber Defense Education In 2022, Joseph H. Schafer, Chris Morrell, Ray Blaine

Military Cyber Affairs

Twenty-one years ago, The IWAR Range paper published by CCSC described nascent information assurance (now cybersecurity[1]) education programs and the inspiration and details for constructing cyber ranges and facilitating cyber exercises. This paper updates the previously published work by highlighting the dramatic evolution of the cyber curricula, exercise networks and ranges, influences, and environments over the past twenty years.

[1] In 2014, DoD adopted “cybersecurity” instead of “information assurance.” [34:1]

Modeling Leaf Area Index And Canopy Height Using Growing Degree Days, Ellie J. Kuhn

Biological and Agricultural Engineering Undergraduate Honors Theses

As the global population increases and food security is recognized as a critical issue, crop growth prediction models help ensure the sustainability of reliable food sources. Using a prediction model based on temperature and simple, measurable field parameters, e.g., Leaf Area Index (LAI) or Canopy Height (H_can), may allow farmers and others to intervene mid-season with fertilizer, irrigation, or other inputs to obtain a better harvest.

This study aims to create a general model that could predict LAI and H_can values for numerous rice varieties using Growing Degree Days (GDD) as the time scale. The models use …

Climate Change Impacts And Engineering Solutions, Dawson Oakley

Biological and Agricultural Engineering Undergraduate Honors Theses

With climate change entering the forefront of global issues, the need for sustainable practices that can provide for human welfare, social and economic development, and health has become more urgent than ever. Despite the recent increase in climate change impacts around the world, many people are still unaware of the severity of the situation. Changing public perception of these issues is the first step in enacting change and increasing accessibility to this information plays an important role.

Much of the information people consume today comes in the form of video, and it can be an effective tool to change knowledge …

Exploring The Effects Of Varied Land Use On Elemental Concentrations Within Streams, Logan Jennings

Biological and Agricultural Engineering Undergraduate Honors Theses

It is well documented that human activity influences the chemistry of surrounding waters. As such, it is possible that there is a link between land use within a watershed and the chemical composition of the stream. The objectives of this study are to determine if varied land use does affect the concentrations of macronutrients and trace elements present in the streams of Northwest Arkansas, and if so, to determine what extent urban and agricultural development are responsible for these changes. Water samples were collected across 19 streams in the Northwest Arkansas region between January and March of 2022. Water samples …

Potato Processing In The Home: Sustainability And Nutritional Impacts, Aubin Payne

Biological and Agricultural Engineering Undergraduate Honors Theses

Potatoes are the world's fourth most consumed crop. Their versatility and long shelf-life make them a staple food for millions of people worldwide. Still, the increasing consumption of highly processed potato products in developed countries has damaged the public's appreciation of potatoes as a valuable source of essential nutrients. Additionally, as public awareness of environmental sustainability increases, the average consumer is more likely to value processing methods that mitigate environmental damage.

Researchers simulated several home storage and processing conditions to find out how nutrition and environmental impact are affected by the home processing timeline. Then, a nutrient analysis, life cycle …