Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

Computer Sciences

Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 3601 - 3630 of 17329

Full-Text Articles in Engineering

Improving Intelligent Transportation Safety And Reliability Through Lowering Costs, Integrating Machine Learning, And Studying Model Sensitivity, Cavender Holt May 2022

Improving Intelligent Transportation Safety And Reliability Through Lowering Costs, Integrating Machine Learning, And Studying Model Sensitivity, Cavender Holt

All Theses

As intelligent transportation becomes increasingly prevalent in the domain of transportation, it is essential to understand the safety, reliability, and performance of these systems. We investigate two primary areas in the problem domain. The first area concerns increasing the feasibility and reducing the cost of deploying pedestrian detection systems to intersections in order to increase safety. By allowing pedestrian detection to be placed in intersections, the data can be better utilized to create systems to prevent accidents from occurring. By employing a dynamic compression scheme for pedestrian detection, we show the reduction of network bandwidth improved by 2.12× over the …

Go to article

An Efficient End-To-End Deep Neural Network For Interstitial Lung Disease Recognition And Classification, Masum Shah Junayed, Afsana Ahsan Jeny, Md Baharul Islam, Ikhtiar Ahmed, Afm Shahen Shah May 2022

An Efficient End-To-End Deep Neural Network For Interstitial Lung Disease Recognition And Classification, Masum Shah Junayed, Afsana Ahsan Jeny, Md Baharul Islam, Ikhtiar Ahmed, Afm Shahen Shah

Turkish Journal of Electrical Engineering and Computer Sciences

The automated Interstitial Lung Diseases (ILDs) classification technique is essential for assisting clinicians during the diagnosis process. Detecting and classifying ILDs patterns is a challenging problem. This paper introduces an end-to-end deep convolution neural network (CNN) for classifying ILDs patterns. The proposed model comprises four convolutional layers with different kernel sizes and Rectified Linear Unit (ReLU) activation function, followed by batch normalization and max-pooling with a size equal to the final feature map size well as four dense layers. We used the ADAM optimizer to minimize categorical cross-entropy. A dataset consisting of 21328 image patches of 128 CT scans with …

Go to article

Software Security Management In Critical Infrastructures: A Systematic Literature Review, Gülsüm Ece Ekşi̇, Bedi̇r Teki̇nerdoğan, Cagatay Catal May 2022

Software Security Management In Critical Infrastructures: A Systematic Literature Review, Gülsüm Ece Ekşi̇, Bedi̇r Teki̇nerdoğan, Cagatay Catal

Turkish Journal of Electrical Engineering and Computer Sciences

Critical infrastructure (CI) is an integrated set of systems and assets that are essential to ensure the functioning of a nation, including its economy, the public's health and/or safety. Hence, protecting critical infrastructures (CI) is vital because of the potential severe consequences that may emerge at the national level. Many CIs are now controlled by software, and likewise, software is often the major source of many security problems in critical infrastructures. Software security management in CIs has been addressed in the literature and several useful approaches have been provided. Yet, these approaches are fragmented over multiple different studies, often do …

Go to article

A Comprehensive Survey For Non-Intrusive Load Monitoring, Efe İsa Tezde, Eray Yildiz May 2022

A Comprehensive Survey For Non-Intrusive Load Monitoring, Efe İsa Tezde, Eray Yildiz

Turkish Journal of Electrical Engineering and Computer Sciences

Energy-saving and efficiency are as important as benefiting from new energy sources to supply increasing energy demand globally. Energy demand and resources for energy saving should be managed effectively. Therefore, electrical loads need to be monitored and controlled. Demand-side energy management plays a vital role in achieving this objective. Energy management systems schedule an optimal operation program for these loads by obtaining more accurate and precise residential and commercial loads information. Different intellegent measurement applications and machine learning algorithms have been proposed for the measurement and control of electrical devices/loads used in buildings. Of these, nonintrusive load monitoring (NILM) is …

Go to article

A Survey On Organizational Choices For Microservice-Based Software Architectures, Hüseyi̇n Ünlü, Burak Bi̇lgi̇n, Onur Demi̇rörs May 2022

A Survey On Organizational Choices For Microservice-Based Software Architectures, Hüseyi̇n Ünlü, Burak Bi̇lgi̇n, Onur Demi̇rörs

Turkish Journal of Electrical Engineering and Computer Sciences

During the last decade, the demand for more flexible, responsive, and reliable software applications increased exponentially. The availability of internet infrastructure and new software technologies to respond to this demand led to a new generation of applications. As a result, cloud-based, distributed, independently deployable web applications working together in a microservice-based software architecture style have gained popularity. The style has been a common practice in the industry and successfully utilized by companies. Adopting this style demands software organizations to transform their culture. However, there is a lack of research studies that explores common practices for microservices. Thus, we performed a …

Go to article

Interval Observer-Based Supervision Of Nonlinear Networked Control Systems, Afef Najjar, Thach Ngoc Dinh, Messaoud Amairi, Tarek Raissi May 2022

Interval Observer-Based Supervision Of Nonlinear Networked Control Systems, Afef Najjar, Thach Ngoc Dinh, Messaoud Amairi, Tarek Raissi

Turkish Journal of Electrical Engineering and Computer Sciences

Networked control system (NCS) is a multidisciplinary area that attracts increasing attention today. In this paper, we deal with remote supervision of a nonlinear networked control systems class subject to network imperfections. Different from many existing researches that consider only the problem of small and/or constant communication delays, we focus on large and time-varying network delays problem in both measurement and control channels. The proposed method is a set-membership estimation-based predictor approach computing a guaranteed set of admissible state values when the uncertainties (i.e. measurement noises and system disturbances) are considered unknown but bounded with a priori known bounds. The …

Go to article

Evaluation Of Social Bot Detection Models, Muhammet Buğra Torusdağ, Mücahi̇d Kutlu, Ali̇ Aydin Selçuk May 2022

Evaluation Of Social Bot Detection Models, Muhammet Buğra Torusdağ, Mücahi̇d Kutlu, Ali̇ Aydin Selçuk

Turkish Journal of Electrical Engineering and Computer Sciences

Social bots are employed to automatically perform online social network activities; thereby, they can also be utilized in spreading misinformation and malware. Therefore, many researchers have focused on the automatic detection of social bots to reduce their negative impact on society. However, it is challenging to evaluate and compare existing studies due to difficulties and limitations in sharing datasets and models. In this study, we conduct a comparative study and evaluate four different bot detection systems in various settings using 20 different public datasets. We show that high-quality datasets covering various social bots are critical for a reliable evaluation of …

Go to article

Classification And Phenological Staging Of Crops From In Situ Image Sequences By Deep Learning, Uluğ Bayazit, Deni̇z Turgay Altilar, Ni̇lgün Güler Bayazit May 2022

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, …

Go to article

Binary Flower Pollination Algorithm Based User Scheduling For Multiuser Mimo Systems, Jyoti Mohanty, Prabina Pattanayak, Arnab Nandi, Krishna Lal Baishnab, Fazal Ahmed Talukdar May 2022

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 …

Go to article

Dual-Polarized Elliptic-H Slot-Coupled Patch Antenna For 5g Applications, Emre Alp Mi̇ran, Mehmet Çi̇ydem May 2022

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} $ $

Go to article

Learning Target Class Eigen Subspace (Ltc-Es) Via Eigen Knowledge Grid, Sanjay Kumar Sonbhadra, Sonali Agarwal, P. Nagabhushan May 2022

Learning Target Class Eigen Subspace (Ltc-Es) Via Eigen Knowledge Grid, Sanjay Kumar Sonbhadra, Sonali Agarwal, P. Nagabhushan

Turkish Journal of Electrical Engineering and Computer Sciences

In one-class classification (OCC) tasks, only the target class (class-of-interest (CoI)) samples are well defined during training, whereas the other class samples are totally absent. In OCC algorithms, the high dimensional data adds computational overhead apart from its intrinsic property of curse of dimensionality. For target class learning, conventional dimensionality reduction (DR) techniques are not suitable due to negligence of the unique statistical properties of CoI samples. In this context, the present research proposes a novel target class guided DR technique to extract the eigen knowledge grid that contains the most promising eigenvectors of variance-covariance matrix of CoI samples. In …

Go to article

An Adaptive Search Equation-Based Artificial Bee Colony Algorithm For Transportation Energy Demand Forecasting, Durmuş Özdemi̇r, Safa Dörterler May 2022

An Adaptive Search Equation-Based Artificial Bee Colony Algorithm For Transportation Energy Demand Forecasting, Durmuş Özdemi̇r, Safa Dörterler

Turkish Journal of Electrical Engineering and Computer Sciences

This study aimed to develop a new adaptive artificial bee colony (A-ABC) algorithm that can adaptively select an appropriate search equation to more accurately estimate transport energy demand (TED). Also, A-ABC and canonical artificial bee colony (C-ABC) algorithms were compared in terms of efficiency and performance. The input parameters used in the proposed TED model were the official economic indicators of Turkey, including gross domestic product (GDP), population, and total vehicle kilometer per year (TKM). Three mathematical models, linear (A-ABCL), exponential (A-ABCE), and quadratic (A-ABCQ) were developed and tested. Also, economic variables were generated using the "curve fitting" technique to …

Go to article

A New Effective Denoising Filter For High Density Impulse Noise Reduction, Iman Elawady, Caner Özcan May 2022

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 …

Go to article

Twitter Account Classification Using Account Metadata: Organizationvs. Individual, Yusuf Mucahi̇t Çeti̇nkaya, Mesut Gürlek, İsmai̇l Hakki Toroslu, Pinar Karagöz May 2022

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 …

Go to article

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 May 2022

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 …

Go to article

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 May 2022

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 …

Go to article

A Hybrid Acoustic-Rf Communication Framework For Networked Control Of Autonomous Underwater Vehicles: Design And Cosimulation, Saeed Nourizadeh Azar, Oytun Erdemi̇r, Mehrullah Soomro, Özgür Gürbüz Ünlüyurt, Ahmet Onat May 2022

A Hybrid Acoustic-Rf Communication Framework For Networked Control Of Autonomous Underwater Vehicles: Design And Cosimulation, Saeed Nourizadeh Azar, Oytun Erdemi̇r, Mehrullah Soomro, Özgür Gürbüz Ünlüyurt, Ahmet Onat

Turkish Journal of Electrical Engineering and Computer Sciences

Underwater control applications, especially ones using autonomous underwater vehicles (AUVs) have become very popular for industrial and military underwater exploration missions. This has led to the requirement of establishing a high data rate communication link between base stations and AUVs, while underwater systems mostly rely on acoustic communications. However, limited data rate and considerable propagation delay are the major challenges for employing acoustic communication in missions requiring high control gains. In this paper, we propose a hybrid acoustic and RF communication framework for establishing a networked control system, in which, for long distance communication and control the acoustic link is …

Go to article

Evaluating The Role Of Carbon Quantum Dots Covered Silica Nanofillers On The Partial Discharge Performance Of Transformer Insulation, Kasi Viswanathan Palanisamy, Chandrasekar Subramaniam, Balaji Sakthivel May 2022

Evaluating The Role Of Carbon Quantum Dots Covered Silica Nanofillers On The Partial Discharge Performance Of Transformer Insulation, Kasi Viswanathan Palanisamy, Chandrasekar Subramaniam, Balaji Sakthivel

Turkish Journal of Electrical Engineering and Computer Sciences

The article presents the experimental results on the role of carbon quantum dots (CQD) covered silica nanofillers on the partial discharge (PD) properties of transformer oil insulation. The improvement in PD performance of nanofiller blend oil is tested with increased voltage gradient and nanofiller concentration. PD of nanoblend oils for various concentrations of modified silica ranging from 0 to 0.1%wt was measured. PD activity of the test samples is simulated in the laboratory with needle, rod and plane electrode geometry combinations. The facets of PD signals such as PD magnitude, PD inception and time duration of PD extracted from phase-resolved …

Go to article

A Novel Crimping Technique Approach For High Power White Good Plugs, Ömer Ci̇han Kivanç, Okan Özgönenel, Ömer Bostan, Şahi̇n Güzel, Mert Demi̇rsoy May 2022

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 …

Go to article

A Novel Deep Reinforcement Learning Based Stock Price Prediction Using Knowledge Graph And Community Aware Sentiments, Anil Berk Altuner, Zeynep Hi̇lal Ki̇li̇mci̇ May 2022

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 …

Go to article

A New Speed Planning Method Based On Predictive Curvature Calculation For Autonomous Driving, Beki̇r Öztürk, Volkan Sezer May 2022

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 …

Go to article

A Novel Fault Detection Approach Based On Multilinear Sparse Pca: Application Onthe Semiconductor Manufacturing Processes, Riadh Toumi, Yahia Kourd, Dimitri Lefebvre May 2022

A Novel Fault Detection Approach Based On Multilinear Sparse Pca: Application Onthe Semiconductor Manufacturing Processes, Riadh Toumi, Yahia Kourd, Dimitri Lefebvre

Turkish Journal of Electrical Engineering and Computer Sciences

Batch processes are extremely important to researchers since they are widely used in many fields such as biochemistry, pharmacy, and semiconductors. The powerful batch detection method is critical to increase the performance of the overall equipment and to reduce the use of check wafers. Many techniques have been used in batch process monitoring. Among them, the multivariate statistical process control (MSPC) is very useful in batch process monitoring because of the large number of records data. Therefore, batch processes have certain characteristics, such as multimodal batch nonlinearity trajectories, which were challenged by these MSPCs. In this paper, a novel process …

Go to article

Strategic Integration Of Battery Energy Storage And Photovoltaic At Low Voltage Level Considering Multiobjective Cost-Benefit, Samarjit Patnaik, Manas Nayak, Meera Viswavandya May 2022

Strategic Integration Of Battery Energy Storage And Photovoltaic At Low Voltage Level Considering Multiobjective Cost-Benefit, Samarjit Patnaik, Manas Nayak, Meera Viswavandya

Turkish Journal of Electrical Engineering and Computer Sciences

Renewable energy sources, such as solar photovoltaic (PV) systems and battery energy storage systems (BESS), help reduce greenhouse gas emissions while fulfilling the world?s growing energy demand. The inclusion of BESS reduces the peak hour demand, and control of charging and discharging of BESS can be economical for distributors facing time-based energy pricing. This paper discusses a novel multiobjective Horse herd optimisation algorithm (MOHHOA) approach, which is inspired by the social behaviour of horses in herds for PV and BESS optimal allocation in the radial distribution system. The proposed algorithm combines multiple benefits like benefits from economic gain per day, …

Go to article

Two Person Interaction Recognition Based On A Dual-Coded Modified Metacognitive (Dcmmc) Extreme Learning Machine, Saman Nikzad, Afshin Ebrahimi May 2022

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 …

Go to article

Offline Tuning Mechanism Of Joint Angular Controller For Lower-Limb Exoskeleton With Adaptive Biogeographical-Based Optimization, Mohammad Soleimani Amiri, Rizauddin Ramli May 2022

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 …

Go to article

Anomaly Detection In Rotating Machinery Using Autoencoders Based On Bidirectional Lstm And Gru Neural Networks, Krishna Patra, Rabi Narayan Sethi, Dhiren Kkumar Behera May 2022

Anomaly Detection In Rotating Machinery Using Autoencoders Based On Bidirectional Lstm And Gru Neural Networks, Krishna Patra, Rabi Narayan Sethi, Dhiren Kkumar Behera

Turkish Journal of Electrical Engineering and Computer Sciences

A time series anomaly is a form of anomalous subsequence that indicates future faults will occur. The development of novel techniques for detecting this type of anomaly is significant for real-time system monitoring. Several algorithms have been used to classify anomalies successfully. However, the time series anomaly detection algorithm was not studied well. We use a new bidirectional LSTM and GRU neural networks-based hybrid autoencoder to detect if a machine is operating normally in this research. An autoencoder is trained on a set of 12 features taken from healthy operating data gathered promptly after a planned maintenance period using vibration …

Go to article

Machine Learning Classification Of Digitally Modulated Signals, James A. Latshaw May 2022

Machine Learning Classification Of Digitally Modulated Signals, James A. Latshaw

Electrical & Computer Engineering Theses & Dissertations

Automatic classification of digitally modulated signals is a challenging problem that has traditionally been approached using signal processing tools such as log-likelihood algorithms for signal classification or cyclostationary signal analysis. These approaches are computationally intensive and cumbersome in general, and in recent years alternative approaches that use machine learning have been presented in the literature for automatic classification of digitally modulated signals. This thesis studies deep learning approaches for classifying digitally modulated signals that use deep artificial neural networks in conjunction with the canonical representation of digitally modulated signals in terms of in-phase and quadrature components. Specifically, capsule networks are …

Go to article

Development Of Modeling And Simulation Platform For Path-Planning And Control Of Autonomous Underwater Vehicles In Three-Dimensional Spaces, Sai Krishna Abhiram Kondapalli May 2022

Development Of Modeling And Simulation Platform For Path-Planning And Control Of Autonomous Underwater Vehicles In Three-Dimensional Spaces, Sai Krishna Abhiram Kondapalli

Mechanical & Aerospace Engineering Theses & Dissertations

Autonomous underwater vehicles (AUVs) operating in deep sea and littoral environments have diverse applications including marine biology exploration, ocean environment monitoring, search for plane crash sites, inspection of ship-hulls and pipelines, underwater oil rig maintenance, border patrol, etc. Achieving autonomy in underwater vehicles relies on a tight integration between modules of sensing, navigation, decision-making, path-planning, trajectory tracking, and low-level control. This system integration task benefits from testing the related algorithms and techniques in a simulated environment before implementation in a physical test bed. This thesis reports on the development of a modeling and simulation platform that supports the design and …

Go to article

Data-Driven Framework For Understanding & Modeling Ride-Sourcing Transportation Systems, Bishoy Kelleny May 2022

Data-Driven Framework For Understanding & Modeling Ride-Sourcing Transportation Systems, Bishoy Kelleny

Civil & Environmental Engineering Theses & Dissertations

Ride-sourcing transportation services offered by transportation network companies (TNCs) like Uber and Lyft are disrupting the transportation landscape. The growing demand on these services, along with their potential short and long-term impacts on the environment, society, and infrastructure emphasize the need to further understand the ride-sourcing system. There were no sufficient data to fully understand the system and integrate it within regional multimodal transportation frameworks. This can be attributed to commercial and competition reasons, given the technology-enabled and innovative nature of the system. Recently, in 2019, the City of Chicago the released an extensive and complete ride-sourcing trip-level data for …

Go to article

A Novel Data Lineage Model For Critical Infrastructure And A Solution To A Special Case Of The Temporal Graph Reachability Problem, Ian Moncur May 2022

A Novel Data Lineage Model For Critical Infrastructure And A Solution To A Special Case Of The Temporal Graph Reachability Problem, Ian Moncur

Graduate Theses and Dissertations

Rapid and accurate damage assessment is crucial to minimize downtime in critical infrastructure. Dependency on modern technology requires fast and consistent techniques to prevent damage from spreading while also minimizing the impact of damage on system users. One technique to assist in assessment is data lineage, which involves tracing a history of dependencies for data items. The goal of this thesis is to present one novel model and an algorithm that uses data lineage with the goal of being fast and accurate. In function this model operates as a directed graph, with the vertices being data items and edges representing …

Go to article

First Prev Next Last