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Articles 5581 - 5610 of 25753

Full-Text Articles in Computer Engineering

A New Similarity-Based Multicriteria Recommendation Algorithm Based Onautoencoders, Zeynep Batmaz, Ci̇han Kaleli̇ Mar 2022

A New Similarity-Based Multicriteria Recommendation Algorithm Based Onautoencoders, Zeynep Batmaz, Ci̇han Kaleli̇

Turkish Journal of Electrical Engineering and Computer Sciences

Recommender systems provide their users an efficient way to handle information overload problem by offering personalized suggestions. Traditional recommender systems are based on two-dimensional user-item preference matrix constructed depending on the users' overall evaluations over items. However, they have begun to present their preferences under various circumstances. Thus, traditional recommendation techniques fail to process multicriteria ratings during the recommendation process. Multicriteria recommender systems are an extension of traditional recommender systems that utilize multicriteria-based user preferences. Multicriteria recommender systems provide more personalized and accurate predictions compared to traditional recommender systems. However, the increased amount of data dimension causes sparsity to be …

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Smart Charging Of Electric Vehicles To Minimize The Cost Of Chargingand The Rate Of Transformer Aging In A Residential Distribution Network, Arjun Visakh, M P. Selvan Mar 2022

Smart Charging Of Electric Vehicles To Minimize The Cost Of Chargingand The Rate Of Transformer Aging In A Residential Distribution Network, Arjun Visakh, M P. Selvan

Turkish Journal of Electrical Engineering and Computer Sciences

Electric vehicles (EVs) exhibit several benefits over combustion engine vehicles, making them an attractive mode of mobility for the future. However, supplying the electrical energy required to recharge their batteries could adversely affect the power system infrastructure. The most severe impact of EV integration is expected to be on the distribution transformers, which are among the costliest equipment in the distribution network. Sustained overloads on the transformer could lead to accelerated aging and early retirement. As the rate of EV deployment rises, so does the probability of transformer overloads and the subsequent loss of life. There is a need for …

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The Analysis And Optimization Of Cnn Hyperparameters With Fuzzy Tree Modelfor Image Classification, Kübra Uyar, Şaki̇r Taşdemi̇r, İlker Ali̇ Özkan Mar 2022

The Analysis And Optimization Of Cnn Hyperparameters With Fuzzy Tree Modelfor Image Classification, Kübra Uyar, Şaki̇r Taşdemi̇r, İlker Ali̇ Özkan

Turkish Journal of Electrical Engineering and Computer Sciences

The meaningful performance of convolutional neural network (CNN) has enabled the solution of various state-of-the-art problems. Although CNNs achieve satisfactory results in computer-vision problems, they still have some difficulties. As the designed CNN models are deepened to achieve much better accuracy, computational cost and complexity increase. It is significant to train CNNs with suitable topology and training hyperparameters that include initial learning rate, minibatch size, epoch number, filter size, number of filters, etc. because the initialization of hyperparameters affects classification results. On the other hand, it is not possible to make a definite inference for the hyperparameter initialization and there …

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A Novel Instrumentation Amplifier With High Tunable Gain And Cmrr Forbiomedical Applications, Riyaz Ahmad, Amit Joshi, Dharmendar Boolchandani Mar 2022

A Novel Instrumentation Amplifier With High Tunable Gain And Cmrr Forbiomedical Applications, Riyaz Ahmad, Amit Joshi, Dharmendar Boolchandani

Turkish Journal of Electrical Engineering and Computer Sciences

A new design of current mode instrumentation amplifier (CMIA) with tunable gain and low voltage operation capability is proposed in this paper, which is suitable for biomedical signals processing, especially in electrocardiogram (ECG). It consists of a new design of current differencing transconductance amplifier (CDTA) and dual z copy CDTA (DZC-CDTA). The gain of the proposed CMIA is controlled by a MOS-based tunable resistor. The main advantage of the proposed CMIA is its high gain that can be tuned over a significant range with the help of two resistances. The performance of the proposed instrumentation amplifier is evaluated through simulation …

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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 Mar 2022

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 …

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Analyzing Probabilistic Optimal Power Flow Problem By Cubature Rules, Qing Xiao Mar 2022

Analyzing Probabilistic Optimal Power Flow Problem By Cubature Rules, Qing Xiao

Turkish Journal of Electrical Engineering and Computer Sciences

This paper is devoted to revealing some properties of the probabilistic optimal power flow (POPF) problem. In conjunction with Hermite polynomial model, Nataf transformation is introduced to map POPF problem to the independent standard normal space. Firstly, a multivariate polynomial model is employed to represent the function relationship between POPF inputs and outputs. Then, moment matching equations are derived to characterize the uncertainty effects of POPF inputs on outputs; three cubature rules are derived to calculate statistical moments of POPF outputs. Finally, along with Monte Carlo simulation method, the proposed methods are tested on IEEE 57-bus system and IEEE 118-bus …

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A Bi-Level Charging Management Approach For Electric Truck Charging Stationconsidering Power Losses, Tayfur Gökçek, Mehmet Tan Turan, Yavuz Ateş, Ahmet Yi̇ği̇t Arabul Mar 2022

A Bi-Level Charging Management Approach For Electric Truck Charging Stationconsidering Power Losses, Tayfur Gökçek, Mehmet Tan Turan, Yavuz Ateş, Ahmet Yi̇ği̇t Arabul

Turkish Journal of Electrical Engineering and Computer Sciences

This article presents an optimized heavy duty electric truck charging station (ETCS) design based on bi-level mixed integer linear programming. Electric truck parameters are integrated with the grid model and charging sequences are firstly formulated to optimize charging stages. As the second level of the optimization stage, line losses are aimed to be minimized for the charging station. ETCS model is obtained from actual parameters of the Istanbul Muratbey Customs zone which is one of the busiest customs zone in Europe and an ideal location for ETCS application in the future. The ETCS is equipped with roof type photovoltaic (PV) …

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Tara: Temperature Aware Online Dynamic Resource Allocation Scheme For Energyoptimization In Cloud Data Centres, Narayanamoorthi Thilagavathi, Arockiasamy John Prakash, Sridhar Sridevi, Vaidyanathan Rhymend Uthariaraj Mar 2022

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 …

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Visual Interpretability Of Capsule Network For Medical Image Analysis, Mighty Abra Ayidzoe, Yu Yongbin, Patrick Kwabena Mensah, Jingye Cai, Faiza Umar Bawah Mar 2022

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 …

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Biometric Identification Using Panoramic Dental Radiographic Images Withfew-Shot Learning, Musa Ataş, Cüneyt Özdemi̇r, İsa Ataş, Burak Ak, Esma Özeroğlu Mar 2022

Biometric Identification Using Panoramic Dental Radiographic Images Withfew-Shot Learning, Musa Ataş, Cüneyt Özdemi̇r, İsa Ataş, Burak Ak, Esma Özeroğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Determining identity is a crucial task especially in the cases of mass disasters such as tsunamis, earthquakes, fires, epidemics, and in forensics. Although there are various studies in the literature on biometric identification from radiographic dental images, more research is still required. In this study, a panoramic dental radiographic (PDR) imagebased human identification system was developed using a customized deep convolutional neural network model in a few-shot learning scheme. The proposed model (PDR-net) was trained on 600 PDR images obtained from a total of 300 patients. As the PDR images of the patients were very different in terms of pose …

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Improving Utilization Rate Of Semi-Parallel Successive Cancellation Architecture For Polar Codes Using 2-Bit Decoding, Dinesh Kumar Devadoss, Shantha Selva Kumari Rama Packiam Mar 2022

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 …

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Developing A Fake News Identification Model With Advanced Deep Languagetransformers For Turkish Covid-19 Misinformation Data, Mehmet Bozuyla, Akin Özçi̇ft Mar 2022

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 …

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Event-Related Microblog Retrieval In Turkish, Çağri Toraman Mar 2022

Event-Related Microblog Retrieval In Turkish, Çağri Toraman

Turkish Journal of Electrical Engineering and Computer Sciences

Microblogs, such as tweets, are short messages in which users are able to share any opinion and information. Microblogs are mostly related to real-life events reported in news articles. Finding event-related microblogs is important to analyze online social networks and understand public opinion on events. However, finding such microblogs is a challenging task due to the dynamic nature of microblogs and their limited length. In this study, assuming that news articles are given as queries and microblogs as documents, we find event-related microblogs in Turkish. In order to represent news articles and microblogs, we examine encoding methods, namely traditional bag-of-words …

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Identification Of Gain And Phase Margins Based Robust Stability Regions For Atime-Delayed Micro-Grid System Including Fractional-Order Controller In Presenceof Renewable Power Generation, Hakan Gündüz, Şahi̇n Sönmez, Saffet Ayasun Mar 2022

Identification Of Gain And Phase Margins Based Robust Stability Regions For Atime-Delayed Micro-Grid System Including Fractional-Order Controller In Presenceof Renewable Power Generation, Hakan Gündüz, Şahi̇n Sönmez, Saffet Ayasun

Turkish Journal of Electrical Engineering and Computer Sciences

This study examines the gain and phase margins (GPMs) based robust stability margins in the parameter space of fractional order proportional-integral (FOPI) controller for a micro-grid (MG) system with communication time delays. Fluctuations in renewable energy sources (RESs), uncertainties in parameters of system components and communication delays could adversely affect the dynamical analysis and frequency stability of the MG system. Such a MG system has an interval characteristic due to the parametric variations and the interval transfer functions defined by Kharitonov's theorem, which presents a solution for checking of robust stability. Therefore, this study addresses the robust stability regions containing …

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Removing The Veil: Shining Light On The Lack Of Inclusivity In Cybersecurity Education For Students With Disabilities, Felicia Hellems, Sajal Bhatia Mar 2022

Removing The Veil: Shining Light On The Lack Of Inclusivity In Cybersecurity Education For Students With Disabilities, Felicia Hellems, Sajal Bhatia

School of Computer Science & Engineering Faculty Publications

There are currently over one billion people living with some form of disability worldwide. The continuous increase in new technologies in today's society comes with an increased risk in security. A fundamental knowledge of cybersecurity should be a basic right available to all users of technology. A review of literature in the fields of cybersecurity, STEM, and computer science (CS) has revealed existent gaps regarding educational methods for teaching cybersecurity to students with disabilities (SWD's). To date, SWD's are largely left without equitable access to cybersecurity education. Our goal is to identify current educational methods being used to teach SWD's …

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Batchlens: A Visualization Approach For Analyzing Batch Jobs In Cloud Systems, Shaolun Ruan, Yong Wang, Hailong Jiang, Weijia Xu, Qiang. Guan Mar 2022

Batchlens: A Visualization Approach For Analyzing Batch Jobs In Cloud Systems, Shaolun Ruan, Yong Wang, Hailong Jiang, Weijia Xu, Qiang. Guan

Research Collection School Of Computing and Information Systems

Cloud systems are becoming increasingly powerful and complex. It is highly challenging to identify anomalous execution behaviors and pinpoint problems by examining the overwhelming intermediate results/states in complex application workflows. Domain scientists urgently need a friendly and functional interface to understand the quality of the computing services and the performance of their applications in real time. To meet these needs, we explore data generated by job schedulers and investigate general performance metrics (e.g., utilization of CPU, memory and disk I/O). Specifically, we propose an interactive visual analytics approach, BatchLens, to provide both providers and users of cloud service with an …

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Impact Of Teaching Practices And Communication Climates On Participation In Computer Science Education, Jackie Krone Mar 2022

Impact Of Teaching Practices And Communication Climates On Participation In Computer Science Education, Jackie Krone

Master's Theses

One way to understand teaching is to view it as a people process rather than a presentation of knowledge. It follows that the role of an educator often extends beyond the primary subject matter and into the realm of classroom management. With this in mind, our research aimed to capture the various teaching practices, participation patterns, and communication climates that occur in virtual computer science classrooms. We sought to answer the following research questions related to virtual computer science classrooms at our institution: Who participates in virtual computer science classrooms, and is participation proportional to student demographics? Is there any …

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Investigations On Cogging Torque Mitigation Techniques Of Transverse Flux Motorfor Direct Drive Low-Speed Spacecraft Applications, Ravichandran Mh, Venkatakirthiga Murali, Haridas Tr Mar 2022

Investigations On Cogging Torque Mitigation Techniques Of Transverse Flux Motorfor Direct Drive Low-Speed Spacecraft Applications, Ravichandran Mh, Venkatakirthiga Murali, Haridas Tr

Turkish Journal of Electrical Engineering and Computer Sciences

The transverse flux motor (TFM) is an ideal choice for direct drive high torque applications owing to its proven higher torque density compared to the radial flux and axial flux motors. TFM motors have several merits to be used for spacecraft applications, considering the everlasting demand of the industry for reduction in power and mass. This paper investigates the various cogging torque mitigation techniques for transverse flux motor to be effectively used as the drive motor for precise position control spacecraft requirement. The paper discusses the basic design variables of surface mounted TFM (SM-TFM) that are to be considered for …

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Cryptographically Strong Random Number Generation Using Integrated Cmosphotodiodes For Low-Cost Microcontroller Based Applications, Baykal Sarioğlu Mar 2022

Cryptographically Strong Random Number Generation Using Integrated Cmosphotodiodes For Low-Cost Microcontroller Based Applications, Baykal Sarioğlu

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, we propose a method to generate random numbers for low-cost, low-power, resource-limited low data-rate microcontrollers using integrated CMOS photodiodes. The proposed method utilizes an integrated CMOS photodiode in the photovoltaic mode as the entropy source. The method is based on serially capturing analog values derived from the integrated CMOS photodiode. The entropy of these values increased by a custom algorithm. The proposed random number generator is devised using an integrated CMOS photodiode manufactured in 180 nm standard CMOS technology. The wide applicably of the random number generator is demonstrated by realizing it on a lowcost Arduino UNO …

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Long-Term Traffic Flow Estimation: A Hybrid Approach Using Location-Basedtraffic Characteristic, Tuğberk Ayar, Ferhat Atli̇nar, Mehmet Amaç Güvensan, Hafi̇za İrem Türkmen Mar 2022

Long-Term Traffic Flow Estimation: A Hybrid Approach Using Location-Basedtraffic Characteristic, Tuğberk Ayar, Ferhat Atli̇nar, Mehmet Amaç Güvensan, Hafi̇za İrem Türkmen

Turkish Journal of Electrical Engineering and Computer Sciences

Traffic speed estimation plays a key role in various situations, ranging from individual's trip planning to urban traffic management. Despite many studies on short-term prediction, there is only a limited number of studies focusing on long-term prediction and only a couple of them does go beyond 24 h. On the contrary, this study presents a novel hybrid architecture using location-based traffic characteristic for traffic speed estimation up to 7 days. In this architecture, the introduced mean filtering estimation (MFE) model and long short-term memory (LSTM) neural network are jointly utilized for minimizing the error for traffic flow estimation. Both MFE …

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Privacy Preserving Scheme For Document Similarity Detection, Ayad Abdulsada, Salah Al-Darraji, Dhafer Honi Mar 2022

Privacy Preserving Scheme For Document Similarity Detection, Ayad Abdulsada, Salah Al-Darraji, Dhafer Honi

Turkish Journal of Electrical Engineering and Computer Sciences

The problem of detecting similar documents plays an essential role for many real-world applications, such as copyright protection and plagiarism detection. To protect data privacy, the new version of such a problem becomes more challenging, where the matched documents are distributed among two or more parties and their privacy should be preserved. In this paper, we propose new privacy-preserving document similarity detection schemes by utilizing the locality-sensitive hashing technique, which can handle the misspelled mistakes. Furthermore, the keywords' occurrences of a given document are integrated into its underlying representation to support a better ranking for the returned results. We introduced …

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On An Electrostatic Micropump With A Rigorous Mathematical Model, İbrahi̇m Efe, Fati̇h Di̇kmen, Yury Tuchkin Mar 2022

On An Electrostatic Micropump With A Rigorous Mathematical Model, İbrahi̇m Efe, Fati̇h Di̇kmen, Yury Tuchkin

Turkish Journal of Electrical Engineering and Computer Sciences

The novel electrostatic micropump model for applications such as in biomedical drug delivery is presented. The geometrical arrangement of the coupling rigid electrodes lets us exploit our mathematically rigorous boundary integral equation formulation and its solution. Thus, the charge densities involving the fringe effects on the plates are obtained by means of analytical regularization method (ARM) constructed for annular strips earlier. The efficiency of the constructed method is demonstrated with respect to the direct integral equation solvers implemented via the entire domain Galerkin method and point matching. The main physical characteristics of the suggested system and their deviation from that …

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A New Classification Method Using Soft Decision-Making Based On An Aggregation Operator Of Fuzzy Parameterized Fuzzy Soft Matrices, Samet Memi̇ş, Serdar Engi̇noğlu, Uğur Erkan Mar 2022

A New Classification Method Using Soft Decision-Making Based On An Aggregation Operator Of Fuzzy Parameterized Fuzzy Soft Matrices, Samet Memi̇ş, Serdar Engi̇noğlu, Uğur Erkan

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, a precise and stable machine learning algorithm, i.e. eigenvalue classification method (EigenClass), has been developed by using the concept of generalised eigenvalues in contrast to common approaches, such as k-nearest neighbours, support vector machines, and decision trees. In this paper, we offer a new classification algorithm called fuzzy parameterized fuzzy soft aggregation classifier (FPFS-AC) to combine the modelling ability of soft decision-making (SDM) and classification success of generalised eigenvalues. FPFS-AC constructs a decision matrix by employing the similarity measures of fuzzy parameterized fuzzy soft matrices fpfs -matrices) and a generalised eigenvalue-based similarity measure. Then, it applies an SDM method …

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Defect Classification Of Railway Fasteners Using Image Preprocessing And Alightweight Convolutional Neural Network, İlhan Aydin, Mehmet Sevi̇, Mehmet Umut Salur, Erhan Akin Mar 2022

Defect Classification Of Railway Fasteners Using Image Preprocessing And Alightweight Convolutional Neural Network, İlhan Aydin, Mehmet Sevi̇, Mehmet Umut Salur, Erhan Akin

Turkish Journal of Electrical Engineering and Computer Sciences

Railway fasteners are used to securely fix rails to sleeper blocks. Partial wear or complete loss of these components can lead to serious accidents and cause train derailments. To ensure the safety of railway transportation, computer vision and pattern recognition-based methods are increasingly used to inspect railway infrastructure. In particular, it has become an important task to detect defects in railway tracks. This is challenging since rail track images are acquired using a measuring train in varying environmental conditions, at different times of day and in poor lighting conditions, and the resulting images often have low contrast. In this study, …

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A Date With Cheemis: Bullying In The Virtual Space, Nicholas Roger Nolasco Mar 2022

A Date With Cheemis: Bullying In The Virtual Space, Nicholas Roger Nolasco

Liberal Arts and Engineering Studies

A Date With Cheemis is an alternative game mode for the social platform VRChat designed in the Unity real-time 3D development platform. The project is an experience where the player meets many non-playable characters (NPCs) and makes decisions based on different scenarios. The game tells the story of a VRChat user named Cheemis who is bullied for the avatar they use and how they interact with other characters. The player must make choices of how to react to the way the NPCs treat Cheemis, whether that be defending him or being a bystander. This experience is only available through the …

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Analyzing Offline Social Engagements: An Empirical Study Of Meetup Events Related To Software Development, Abhishek Sharma, Gede Artha Azriadi Prana, Anamika Sawhney, Nachiappan Nagappan, David Lo Mar 2022

Analyzing Offline Social Engagements: An Empirical Study Of Meetup Events Related To Software Development, Abhishek Sharma, Gede Artha Azriadi Prana, Anamika Sawhney, Nachiappan Nagappan, David Lo

Research Collection School Of Computing and Information Systems

Software developers use a variety of social mediachannels and tools in order to keep themselves up to date,collaborate with other developers, and find projects to contributeto. Meetup is one of such social media used by softwaredevelopers to organize community gatherings. We in this work,investigate the dynamics of Meetup groups and events relatedto software development. Our work is different from previouswork as we focus on the actual event and group data that wascollected using Meetup API.In this work, we performed an empirical study of eventsand groups present on Meetup which are related to softwaredevelopment. First, we identified 6,327 Meetup groups related …

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Efficient Certificateless Multi-Copy Integrity Auditing Scheme Supporting Data Dynamics, Lei Zhou, Anmin Fu, Guomin Yang, Huaqun Wang, Yuqing Zhang Mar 2022

Efficient Certificateless Multi-Copy Integrity Auditing Scheme Supporting Data Dynamics, Lei Zhou, Anmin Fu, Guomin Yang, Huaqun Wang, Yuqing Zhang

Research Collection School Of Computing and Information Systems

To improve data availability and durability, cloud users would like to store multiple copies of their original files at servers. The multi-copy auditing technique is proposed to provide users with the assurance that multiple copies are actually stored in the cloud. However, most multi-replica solutions rely on Public Key Infrastructure (PKI), which entails massive overhead of certificate computation and management. In this article, we propose an efficient multi-copy dynamic integrity auditing scheme by employing certificateless signatures (named MDSS), which gets rid of expensive certificate management overhead and avoids the key escrow problem in identity-based signatures. Specifically, we improve the classic …

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Implementation And Characterization Of Ahr On A Xilinx Fpga, Andrew J. Dittrich Mar 2022

Implementation And Characterization Of Ahr On A Xilinx Fpga, Andrew J. Dittrich

Theses and Dissertations

A new version of the Adaptive-Hybrid Redundancy (AHR) architecture was developed to be implemented and tested in hardware using Commercial-Off-The-Shelf (COTS) Field-Programmable Gate Arrays (FPGAs). The AHR architecture was developed to mitigate the effects that the Single Event Upset (SEU) and Single Event Transient (SET) radiation effects have on processors and was tested on a Microprocessor without Interlocked Pipeline Stages (MIPS) architecture. The AHR MIPS architecture was implemented in hardware using two Xilinx FPGAs. A Universal Asynchronous Receiver Transmitter (UART) based serial communication network was added to the AHR MIPS design to enable inter-board communication between the two FPGAs. The …

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Evaluating Neural Network Decoder Performance For Quantum Error Correction Using Various Data Generation Models, Brett M. Martin Mar 2022

Evaluating Neural Network Decoder Performance For Quantum Error Correction Using Various Data Generation Models, Brett M. Martin

Theses and Dissertations

Neural networks have been shown in the past to perform quantum error correction (QEC) decoding with greater accuracy and efficiency than algorithmic decoders. Because the qubits in a quantum computer are volatile and only usable on the order of milliseconds before they decohere, a means of fast quantum error correction is necessary in order to correct data qubit errors within the time budget of a quantum algorithm. Algorithmic decoders are good at resolving errors on logical qubits with only a few data qubits, but are less efficient in systems containing more data qubits. With neural network decoders, practical quantum computation …

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Considerations Using Iterative Closest Point In Presence Of Occlusions In Automated Aerial Refueling, Joel M. Miller Mar 2022

Considerations Using Iterative Closest Point In Presence Of Occlusions In Automated Aerial Refueling, Joel M. Miller

Theses and Dissertations

The United States Air Force is researching vision-based AAR and different methods for this actualization. Previous work has established a computer vision based pipeline with ICP. This work focuses on how ICP can become resilient to boom occlusion by minimizing errors and discusses the limitations of ICP in the face of occlusions. Specifically, we look at various filtering techniques to remove non-salient points. To register point clouds while maintaining real time interactivity, this work also presents a method for downsampling high resolution camera calibrations to preserve real-time processing and significantly decrease the vision pipeline latency.

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