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Articles 1951 - 1980 of 7215
Full-Text Articles in Computer Engineering
An Electrothermal Current Prediction Method For Overload Protection Of Miniaturecircuit Breakers, Sen Lyu, Ming Zong
An Electrothermal Current Prediction Method For Overload Protection Of Miniaturecircuit Breakers, Sen Lyu, Ming Zong
Turkish Journal of Electrical Engineering and Computer Sciences
Traditional miniature circuit breakers (MCBs) cannot meet the requirement for the intelligence of distributing apparatuses in a smart grid. The intellectualization of MCBs is restricted due to the lack of appropriate current measurement methods. Thus, an electrothermal current prediction method is proposed based on the derived relationship between root-mean-square (RMS) current and steady-state temperature rise. A fast acquisition algorithm is used to obtain the required temperature rise before thermal equilibrium to highly reduce the total time consumption. The presented prediction method is found immunized against the ambient temperature. The theory is validated with experiments using a thermostat. The tested steady-state …
Reducing Computational Complexity In Fingerprint Matching, Mubeen Sabir, Tariq Mahmood Khan, Munazza Arshad, Sana Munawar
Reducing Computational Complexity In Fingerprint Matching, Mubeen Sabir, Tariq Mahmood Khan, Munazza Arshad, Sana Munawar
Turkish Journal of Electrical Engineering and Computer Sciences
The performance of cross-correlation functions can decrease computational complexity under optimal fingerprint feature selection. In this paper, a technique is proposed to perform alignment of fingerprints followed by their matching in fewer computations. Minutiae points are extracted and alignment is performed on the basis of their spatial locations and orientation fields. Unlike traditional cross-correlation based matching algorithms, ridges are not included in the matching process to avoid redundant computations. However, optimal cross-correlation is chosen by correlating feature vectors accompanying x-y locations of minutiae points and their aligned orientation fields. As a result, matching time is significantly reduced with much improved …
Low-Profile Folded Dipole Uhf Rfid Tag Antenna With Outer Strip Lines Formetal Mounting Application, Fuad Erman, Effariza Hanafi, Eng-Hock Lim, Wan Amirul Wan Mohd Mahyiddin, Sulaiman Wadi Harun, Mohamad Sofian Abu Talip, Rawan Soboh, Hassan Umair
Low-Profile Folded Dipole Uhf Rfid Tag Antenna With Outer Strip Lines Formetal Mounting Application, Fuad Erman, Effariza Hanafi, Eng-Hock Lim, Wan Amirul Wan Mohd Mahyiddin, Sulaiman Wadi Harun, Mohamad Sofian Abu Talip, Rawan Soboh, Hassan Umair
Turkish Journal of Electrical Engineering and Computer Sciences
A metal mountable UHF RFID tag antenna with a low-profile folded dipole structure is proposed. It is fabricated on a single layer of polytetrafluoroethylene (PTFE) dielectric laminate. It is composed of two symmetrical C-shape resonators integrated with the outer strip lines. The IC chip's terminals are connected directly to the center of the C-shaped resonators. The outer strip lines are integrated with the C-shaped resonators, which function to lower the reflection coefficient so as to match the IC chip impedance. In particular, the outer strip lines increase the inductive reactance of the antenna impedance in order to realize IC chip …
Image Subset Communication For Resource-Constrained Applications In Wirelesssensor Networks, Sajid Nazir, Omar Alzubi, Mohammad Kaleem, Hassan Hamdoun
Image Subset Communication For Resource-Constrained Applications In Wirelesssensor Networks, Sajid Nazir, Omar Alzubi, Mohammad Kaleem, Hassan Hamdoun
Turkish Journal of Electrical Engineering and Computer Sciences
JPEG is the most widely used image compression standard for sensing, medical, and security applications. JPEG provides a high degree of compression but field devices relying on battery power must further economize on data transmissions to prolong deployment duration with particular use cases in wireless sensor networks. Transmitting a subset of image data could potentially enhance the battery life of power-constrained devices and also meet the application requirements to identify the objects within an image. Depending on an application's needs, after the first selected subset is received at the base station, further transmissions of the image data for successive refinements …
Mutant Selection By Using Fourier Expansion, Savaş Takan, Tolga Ayav
Mutant Selection By Using Fourier Expansion, Savaş Takan, Tolga Ayav
Turkish Journal of Electrical Engineering and Computer Sciences
Mutation analysis is a widely used technique to evaluate the effectiveness of test cases in both hardware and software testing. The original model is mutated systematically under certain fault assumptions and test cases are checked against the mutants created to see whether the test cases can detect the faults or not. Mutation analysis is usually a computationally intensive task, particularly in finite state machine (FSM) testing due to a possibly huge amount of mutants. Random selection could be a practical reduction method under the assumption that each mutant is identical in terms of the probability of occurrence of its associating …
Combined Morphology And Svm-Based Fault Feature Extraction Technique Fordetection And Classification Of Transmission Line Faults, Revati Godse, Dr. Sunil Bhat
Combined Morphology And Svm-Based Fault Feature Extraction Technique Fordetection And Classification Of Transmission Line Faults, Revati Godse, Dr. Sunil Bhat
Turkish Journal of Electrical Engineering and Computer Sciences
A transmission line is the main commodity of power transmission network through which power is transmitted to the utility. These lines are often swayed by accidental breakdowns owing to different random origins. Hence, researchers try to detect and track down these failures at the earliest to avoid financial prejudice. This paper offers a new realtime mathematical morphology based approach for fault feature extraction. The morphological open-close-median filter is exploited to wrest unique fault features which are then fed as an input to support vector machine to detect and classify the short circuit faults. The acquired graphical and numerical results of …
A Supervised Learning Approach For Detecting Erroneoussamples In Embeddings, Görkem Saygili
A Supervised Learning Approach For Detecting Erroneoussamples In Embeddings, Görkem Saygili
Turkish Journal of Electrical Engineering and Computer Sciences
Visualizing multidimensional data has been a crucial task in recent years regarding the growing amount of data from various sources. To achieve this, dimensionality reduction algorithms have been used to reduce the number of dimensions for visualization of the data on a screen. However, these algorithms may fail to faithfully represent high dimensional data in lower dimensions and eventually lead to erroneous visualizations. In this work, we propose an error detection algorithm for dimensionality reduction algorithms based on recently developed error prediction algorithms for medical image registration. The proposed algorithm matches the neighborhoods of high and low dimensional data with …
Comparative Study Between Measured And Estimated Wind Energy Yield, Ayman Alquraan, Mohammed Al-Mahmodi, Ashraf Radaideh, Hussein Al-Masri
Comparative Study Between Measured And Estimated Wind Energy Yield, Ayman Alquraan, Mohammed Al-Mahmodi, Ashraf Radaideh, Hussein Al-Masri
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a power-speed (P-V) model of the wind turbine by assuming three different functions for the first performance region; cubic, quadratic and uncorrected cubic. These three functions have been compared with the manufacturer models of five different wind turbines which were installed in five different locations in Jordan; Tafila, Hofa, Fujeij, Al Rajef, and Deahan. The wind turbine of these wind farms are considered as large scale HAWT in the range of Mw. The generated P-V models are developed by applying a new method described in this paper which is basically based on generating a multiplier factor x. …
Distribution Network Reconfiguration Based On Artificial Networkreconfiguration For Variable Load Profile, Hesham Hanie Youssef, Hazlie Bin Mokhlis, Mohamad Sofian Abu Talip, Mohammad Alsamman, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor
Distribution Network Reconfiguration Based On Artificial Networkreconfiguration For Variable Load Profile, Hesham Hanie Youssef, Hazlie Bin Mokhlis, Mohamad Sofian Abu Talip, Mohammad Alsamman, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor
Turkish Journal of Electrical Engineering and Computer Sciences
Network reconfiguration is a process to change the open-switches in distribution system for a minimum power loss. In the past, metaheuristic techniques were applied widely for network reconfiguration with consideration of a fixed loading profile. When the loading changes, the current configuration may not be the optimal one. Thus, the technique needs to be executed to find a new optimal configuration based on the latest loading. The process is time-consuming since metaheuristic techniques commonly require high computational times and produces inconsistent results. Therefore, this paper proposes a network reconfiguration technique based on artificial neural network (ANN) for variable loading conditions. …
A Novel Grouping Proof Authentication Protocol For Lightweight Devices:Gpapxr+, Ömer Aydin, Gökhan Dalkiliç, Cem Kösemen
A Novel Grouping Proof Authentication Protocol For Lightweight Devices:Gpapxr+, Ömer Aydin, Gökhan Dalkiliç, Cem Kösemen
Turkish Journal of Electrical Engineering and Computer Sciences
Radio frequency identification (RFID) tags that meet EPC Gen2 standards are used in many fields such as supply chain operations. The number of the RFID tags, smart cards, wireless sensor nodes, and Internet of things devices is increasing day by day and the areas where they are used are expanding. These devices are very limited in terms of the resources they have. For this reason, many security mechanisms developed for existing computer systems cannot be used for these devices. In order to ensure secure communication, it is necessary to provide authentication process between these lightweight devices and the devices they …
Exhaustive Hard Triplet Mining Loss For Person Re-Identification, Chao Xu, Xiang Sun, Ziliang Chen, Shoubiao Tan
Exhaustive Hard Triplet Mining Loss For Person Re-Identification, Chao Xu, Xiang Sun, Ziliang Chen, Shoubiao Tan
Turkish Journal of Electrical Engineering and Computer Sciences
Person reidentification (Re-ID) is an important task in computer vision and has many applications in videobased surveillance. Recently, the triplet loss has been popular in the deep learning framework for person Re-ID. It is particularly important to note that the selection of hard triplets has significant influence on the performance of the learned deep model. However, the existing triplet losses only focus on some specific forms of hard triplets, thus leading to weaker generalization capability. To address this issue, we propose a novel variant of the triplet loss, named exhaustive hard triplet mining loss (EHTM), which is able to deal …
Exploring The Parameter Space Of Human Activity Recognition With Mobile Devices, Berrenur Saylam, Muhammad Shoaib, Özlem Durmaz İncel
Exploring The Parameter Space Of Human Activity Recognition With Mobile Devices, Berrenur Saylam, Muhammad Shoaib, Özlem Durmaz İncel
Turkish Journal of Electrical Engineering and Computer Sciences
Motion sensors available on smart phones make it possible to recognize human activities. Accelerometer, gyroscope, magnetometer, and their various combinations are used to classify, particularly, locomotion activities, ranging from walking to biking. In most of the studies, the focus is on the collection of data and on the analysis of the impact of different parameters on the recognition performance. The parameter space includes the types of sensors used, features, classification algorithms, and position/orientation of the mobile device. In most of the studies, the impact of some of these parameters is partially analyzed; however, in this work, we investigate the parameter …
Optimization Of Real-Time Wireless Sensor Based Big Data With Deep Autoencoder Network: A Tourism Sector Application With Distributed Computing, Beki̇r Aksoy, Utku Kose
Optimization Of Real-Time Wireless Sensor Based Big Data With Deep Autoencoder Network: A Tourism Sector Application With Distributed Computing, Beki̇r Aksoy, Utku Kose
Turkish Journal of Electrical Engineering and Computer Sciences
Internet usage has increased rapidly with the development of information communication technologies. The increase in internet usage led to the growth of data volumes on the internet and the emergence of the big data concept. Therefore, it has become even more important to analyze the data and make it meaningful. In this study, 690 million queries and approximately 5.9 quadrillion data collected daily from different servers were recorded on the Redis servers by using real-time big data analysis method and load balance structure for a company operating in the tourism sector. Here, wireless networks were used as a triggering factor …
Efficient Turkish Tweet Classification System For Crisis Response, Saed Alqaraleh, Merve Işik
Efficient Turkish Tweet Classification System For Crisis Response, Saed Alqaraleh, Merve Işik
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a convolutional neural networks Turkish tweet classification system for crisis response. This system has the ability to classify the present information before or during any crisis. In addition, a preprocessing model was also implemented and integrated as a part of the developed system. This paper presents the first ever Turkish tweet dataset for crisis response, which can be widely used and improve similar studies. This dataset has been carefully preprocessed, annotated, and well organized. It is suitable to be used by all the well-known natural language processing tools. Extensive experimental work, using our produced Turkish tweet dataset …
Adaptive Fast Sliding Neural Control For Robot Manipulator, Bariş Özyer
Adaptive Fast Sliding Neural Control For Robot Manipulator, Bariş Özyer
Turkish Journal of Electrical Engineering and Computer Sciences
Robotic manipulators are open to external disturbances and actuation failures during performing a task such as trajectory tracking. In this paper, we present a modifed controller consisting of a global fast sliding surface combined with an adaptive neural network which is called adaptive fast sliding neural control (AFSNC) for a robotic manipulator to precise stable trajectory tracking performance under the external disturbances. The adaptive term is employedtoreduce uncertainties due to unmodeled dynamics. Trackingerror asymptoticallyconvergesto zero according to the Lyapunov stability theorem. Numerical examples have been carried on a planar two-links manipulator to verify the control approach efficiency. The experimental results …
Design And Application Of Spwm Based 21-Level Hybrid Inverter For Induction Motor Drive, Sheikh Tanzim Meraj, Kamrul Hasan, Ammar Masaoud
Design And Application Of Spwm Based 21-Level Hybrid Inverter For Induction Motor Drive, Sheikh Tanzim Meraj, Kamrul Hasan, Ammar Masaoud
Turkish Journal of Electrical Engineering and Computer Sciences
Thispaperpresentstheapplicationofanewlydeveloped21-levelhybridmultilevelinverter. Ahighfrequency modulation technique known as sinusoidal pulse width modulation (SPWM) is applied to the hybrid inverter. This modulation methodology operates the switching sequences of the multilevel inverter to produce the desired 21-level output voltage. To validate the proper application of this inverter, it is further utilized to maintain the speed of a single phase induction motor. The velocity control of the motor is established on the principle of V/f control technique. The speed control strategy along with the compatibility of the SPWM modulation technique were verified by means of simulation and experimental results.
Influence Of Varying Magnet Pole-Arcs And Step-Skew On Permanent Magnet Ac Synchronous Motor Performance, Meti̇n Aydin, Oğuzhan Ocak, Yücel Demi̇r
Influence Of Varying Magnet Pole-Arcs And Step-Skew On Permanent Magnet Ac Synchronous Motor Performance, Meti̇n Aydin, Oğuzhan Ocak, Yücel Demi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
Minimization or elimination of cogging torque is a significant issue in permanent magnet (PM) motor design process. There are some design techniques to reduce or eliminate this unwanted torque components in PM motors. This paper focuses on two different design techniques, varying magnet pole-arc and step-skew, to reduce cogging torque component in radial flux PM synchronous motors. Different design points which consider pulsating torque components and back-EMF harmonics are obtained via finite element analysis (FEA) for a low power industrial PM motor. A prototype motor is manufactured for one of the desired designs and is tested experimentally. Good agreement is …
Gated Recurrent Unit Based Demand Response For Preventing Voltage Collapse In A Distribution System, Venkateswarlu Gundu, Sishaj Pulikottil Simon, Kinattingal Sundareswaran, Srinivasa Rao Nayak Panugothu
Gated Recurrent Unit Based Demand Response For Preventing Voltage Collapse In A Distribution System, Venkateswarlu Gundu, Sishaj Pulikottil Simon, Kinattingal Sundareswaran, Srinivasa Rao Nayak Panugothu
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents the application of deep learning algorithms towards demand response management. Demand limit violation and voltage stability are the major problems associated with a secondary distribution system. These problems are solved using demand response models by day ahead scheduling loads at every 15 min interval through linear integer programming and based on short term forecasting of load (kW). A new architecture for short term load forecasting is presented namely gated recurrent unit in which statistical analysis is carried out to get the optimal architecture of the neural network model. Reliability indices such as loss of load probability (LOLP) …
A New Smart Networking Architecture For Container Network Functions, Gülsüm Atici, Pinar Bölük
A New Smart Networking Architecture For Container Network Functions, Gülsüm Atici, Pinar Bölük
Turkish Journal of Electrical Engineering and Computer Sciences
5G slices have challenging application demands from a wide variety of fields including high bandwidth, low latency and reliability. The requirements of the container network functions which are used in telecommunications are different from any other cloud native IT applications as they are used for data plane packet processing functions, together with control, signalling and media processing which have critical processing requirements. This study aims to discover high performing container networking solution by considering traffic loads and application types. The behaviour of several container cluster networking solutions -- Flannel, Weave, Libnetwork, Open Virtual Networking for Open vSwitch and Calico -- …
Adaptive Object Detection For Autonomous Vehicles, Christopher Wolfe
Adaptive Object Detection For Autonomous Vehicles, Christopher Wolfe
Graduate Research Theses & Dissertations
Autonomous vehicles are gradually entering our daily lives. The goal of fully autonomous commercially available vehicles is becoming closer to reality each day as the contributions from researchers and various institutions are being added to the overall body of knowledge. Object detection is a critical component of an autonomous or semi-autonomous vehicle and draws extensively on results from many fields such as image processing and statistics. In this thesis, we consider ideas from the study of real-time computing and control systems to present a novel method of real-time adaptive object detection. We present a conceptual framework of the method as …
A Multi-Constraint Predictive Control System With Auxiliary Emergency Controllerfor Autonomous Vehicles, Farhad Partovi Ebrahimpour
A Multi-Constraint Predictive Control System With Auxiliary Emergency Controllerfor Autonomous Vehicles, Farhad Partovi Ebrahimpour
Graduate Research Theses & Dissertations
In the last few years, several research groups and companies have worked on developing autonomous vehicles. Among the first automation layers, the safety layer plays a significant role in this field. However, considering safety should not diminish the importance of the efficiency of the vehicle in terms of path tracking with the desired speed. This thesis introduces a multi-constraint predictive control algorithm along with a safety layer to guarantee object avoidance in emergency situations. First, there is a quick review of autonomous cars and their functionalities. In the following, a controller switching mechanism is proposed and designed. It switches the …
Knowledge-Infused Statistical Learning For Social Good, Kaushik Roy, Manas Gaur
Knowledge-Infused Statistical Learning For Social Good, Kaushik Roy, Manas Gaur
Publications
Humans are able to provide symbolic knowledge in structured form for potential use by an AI system in learning human-desirable concepts. In clinical settings, for instance, prediction of patient outcomes by an AI can be guided by knowledge from patient history. This history contains concepts such as treatment information, observational and drug-related information, mental health conditions, and severity of disease/disorder. Additionally, there is also often a certain graphical structure to the knowledge among the concepts, for example, ”patient symptoms cause certain tests to be taken”, which in turn affects the prescription of medication. This type of structure between human interpretable …
Explainable Ai Using Knowledge Graphs, Manas Gaur, Ankit Desai, Keyur Faldu, Amit Sheth
Explainable Ai Using Knowledge Graphs, Manas Gaur, Ankit Desai, Keyur Faldu, Amit Sheth
Publications
During the last decade, traditional data-driven deep learning (DL) has shown remarkable success in essential natural language processing tasks, such as relation extraction. Yet, challenges remain in developing artificial intelligence (AI) methods in real-world cases that require explainability through human interpretable and traceable outcomes. The scarcity of labeled data for downstream supervised tasks and entangled embeddings produced as an outcome of self-supervised pre-training objectives also hinders interpretability and explainability. Additionally, data labeling in multiple unstructured domains, particularly healthcare and education, is computationally expensive as it requires a pool of human expertise. Consider Education Technology, where AI systems fall along a …
Alone: A Dataset For Toxic Behavior Among Adolescents On Twitter, Thilini Wijesiriwardene, Hale Inan, Ugur Kursuncu, Manas Gaur, Valerie L. Shalin, Krishnaprasad Thirunarayan, Amit P. Sheth, I. Budak Arpinar
Alone: A Dataset For Toxic Behavior Among Adolescents On Twitter, Thilini Wijesiriwardene, Hale Inan, Ugur Kursuncu, Manas Gaur, Valerie L. Shalin, Krishnaprasad Thirunarayan, Amit P. Sheth, I. Budak Arpinar
Publications
The convenience of social media has also enabled its misuse, potentially resulting in toxic behavior. Nearly 66% of internet users have observed online harassment, and 41% claim personal experience, with 18% facing severe forms of online harassment. This toxic communication has a significant impact on the well-being of young individuals, affecting mental health and, in some cases, resulting in suicide. These communications exhibit complex linguistic and contextual characteristics, making recognition of such narratives challenging. In this paper, we provide a multimodal dataset of toxic social media interactions between confirmed high school students, called ALONE (AdoLescents ON twittEr), along with descriptive …
Assessing The Severity Of Health States Based On Social Media Posts, Shweta Yadav, Joy Prakash Sain, Amit P. Sheth, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya
Assessing The Severity Of Health States Based On Social Media Posts, Shweta Yadav, Joy Prakash Sain, Amit P. Sheth, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya
Publications
The unprecedented growth of Internet users has resulted in an abundance of unstructured information on social media including health forums, where patients request healthrelated information or opinions from other users. Previous studies have shown that online peer support has limited effectiveness without expert intervention. Therefore, a system capable of assessing the severity of health state from the patients’ social media posts can help health professionals (HP) in prioritizing the user’s post. In this study, we inspect the efficacy of different aspects of Natural Language Understanding (NLU) to identify the severity of the user’s health state in relation to two perspectives(tasks) …
Real-Time Urban Weather Observations For Urban Air Mobility, Kevin A. Adkins, Mustafa Akbas, Marc Compere
Real-Time Urban Weather Observations For Urban Air Mobility, Kevin A. Adkins, Mustafa Akbas, Marc Compere
International Journal of Aviation, Aeronautics, and Aerospace
Cities of the future will have to overcome congestion, air pollution and increasing infrastructure cost while moving more people and goods smoothly, efficiently and in an eco-friendly manner. Urban air mobility (UAM) is expected to be an integral component of achieving this new type of city. This is a new environment for sustained aviation operations. The heterogeneity of the urban fabric and the roughness elements within it create a unique environment where flight conditions can change frequently across very short distances. UAM vehicles with their lower mass, more limited thrust and slower speeds are especially sensitive to these conditions. Since …
Techno-Economic Analysis Of Diethyl Ether Production Via Catalytic Dehydration Of Ethanol, Boonraksa Chaiapha
Techno-Economic Analysis Of Diethyl Ether Production Via Catalytic Dehydration Of Ethanol, Boonraksa Chaiapha
Chulalongkorn University Theses and Dissertations (Chula ETD)
The major source of energy comes from non-renewable fuels, which have a non-sustainability and negative impact on the environment. Thus, there is change to renewable fuels as bioethanol. Diethyl ether (DEE) is a part of bioethanol. However, the increase of electric vehicles (EV) may decrease ethanol demand for biofuel in the future. Thus, it will be interesting in adding value to ethanol via the catalytic dehydration to produce DEE by conduct techno-economic analysis. Further, there is comparison on different concentrations of ethanol (93% and 95% ethanol) that affect DEE production. For simulation part, the DEE capacity of 3,600 tons/year is …
Implementation Of Traffic Engineering With Segment Routing And Opendaylight Controller On Emulated Virtual Environment Next Generation (Eve-Ng), Htain Lynn Aung
Implementation Of Traffic Engineering With Segment Routing And Opendaylight Controller On Emulated Virtual Environment Next Generation (Eve-Ng), Htain Lynn Aung
Chulalongkorn University Theses and Dissertations (Chula ETD)
Internet service providers and enterprise networks face rapid changes and rapid growth of the internet, and the networks become complex in operations to support the strict Service-level Agreements (SLAs) needed applications. Segment Routing (SR) is a source routing technology that overcomes the conventional Multiprotocol Label Switching (MPLS) networks' drawbacks in scalability, flexibility, and applicability in Software-defined Networking (SDN). SR enables the source device to instruct the path using a segment or list of segments to go through the network. SR can be implemented in IPv6 and MPLS. A segment can be defined as information that instructs SR capable nodes to …
A Morphable Fpga Soft Processor Using Llvm Infrastructure Targeting Low-Power Application-Specific Embedded Systems, Ehsan Ali
Chulalongkorn University Theses and Dissertations (Chula ETD)
The reconfigurable computing (RC) aims to combine the flexibility of General-Purpose Processor (GPP) with performance of Application Specific Integrated Circuits (ASIC). There are several architectures proposed since RC's inception in 1960s, but all have failed to become mainstream. The main factor preventing RC to become common practice is its requirement for implementers of algorithms (programmers) to be familiar with hardware design. In RC, a hardened processor cooperates with a dynamic reconfigurable Hardware Accelerator (HA) which is implemented on Field-Programmable Gate Array (FPGA). The HA implements crucial software kernel on hardware to increase performance and its design demands digital circuit expertise. …
Systematic Model-Based Design Assurance And Property-Based Fault Injection For Safety Critical Digital Systems, Athira Varma Jayakumar
Systematic Model-Based Design Assurance And Property-Based Fault Injection For Safety Critical Digital Systems, Athira Varma Jayakumar
Theses and Dissertations
With advances in sensing, wireless communications, computing, control, and automation technologies, we are witnessing the rapid uptake of Cyber-Physical Systems across many applications including connected vehicles, healthcare, energy, manufacturing, smart homes etc. Many of these applications are safety-critical in nature and they depend on the correct and safe execution of software and hardware that are intrinsically subject to faults. These faults can be design faults (Software Faults, Specification faults, etc.) or physically occurring faults (hardware failures, Single-event-upsets, etc.). Both types of faults must be addressed during the design and development of these critical systems. Several safety-critical industries have widely adopted …