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Full-Text Articles in Engineering

Learning Multiview Deep Features From Skeletal Sign Language Videos Forrecognition, Ashraf Ali Shaik, Venkata Durga Prasad Mareedu, Venkata Vijaya Kishore Polurie Jan 2021

Learning Multiview Deep Features From Skeletal Sign Language Videos Forrecognition, Ashraf Ali Shaik, Venkata Durga Prasad Mareedu, Venkata Vijaya Kishore Polurie

Turkish Journal of Electrical Engineering and Computer Sciences

The most challenging objective in machine translation of sign language has been the machine?s inability tolearn interoccluding finger movements during an action process. This work addresses the problem of teaching a deeplearning model to recognize differently oriented skeletal data. The multi-view 2D skeletal sign language video data isobtained using 3D motion-captured system. A total of 9 signer views were used for training the proposed network andthe 6 for testing and validation. In order to obtain multi-view deep features for recognition, we proposed an end-to-endtrainable multistream convolutional neural network (CNN) with late feature fusion. The fused multiview features arethen inputted to …

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Analytical Modeling And Study On Noise Characteristics Of Rotor Eccentric Spmsmwith Unequal Magnetic Poles Structure, Pengpeng Xia, Shenbo Yu, Rutong Dou, Fengchen Zhai Jan 2021

Analytical Modeling And Study On Noise Characteristics Of Rotor Eccentric Spmsmwith Unequal Magnetic Poles Structure, Pengpeng Xia, Shenbo Yu, Rutong Dou, Fengchen Zhai

Turkish Journal of Electrical Engineering and Computer Sciences

he establishment of the analytical model of the rotor eccentric surface-mounted permanent magnet syn-chronous motor (SPMSM) with unequal magnetic poles structure will be beneficial to calculating the magnetic field andstudying noise characteristics quickly. Based on the equivalent surface current (ESC) method and equivalent boundarymethod, the analytical model of the rotor eccentric SPMSM with unequal magnetic poles structure is proposed. Duringthe modeling process, the magnetic field produced by a permanent magnet (PM) is obtained using the ESC method, andthe effect on the air gap magnetic field, which arised from stator, is replaced with the concentric current sheet (CCS)magnetic field. And, the …

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Pfecc: A Precise Feedback-Based Explicit Congestion Control Algorithm In Nameddata Networking, Hui Li Jan 2021

Pfecc: A Precise Feedback-Based Explicit Congestion Control Algorithm In Nameddata Networking, Hui Li

Turkish Journal of Electrical Engineering and Computer Sciences

Named data networking (NDN), as a future Internet architecture that is a promising alternative to TCP/IPnetworks, has the new features of connectionless, in-network cache, and hop-by-hop forwarding, which makes thecongestion control algorithms of traditional TCP/IP networks unable to be directly applied to NDN. In addition, sincethe optimal size of the sending window cannot be determined, the existing window-based congestion control algorithmsgenerally use the AIMD-like window adjustment algorithm, which cannot achieve the optimal throughput. In thispaper, we propose a precise feedback-based, multipath-aware congestion control algorithm PFECC, which is inspiredby Accel-Brake Control algorithm. PFECC considers the influence of Interest flows, uses a …

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On The Outage Performance Of Swipt-Noma-Crs With Imperfect Sic And Csi, Ferdi̇ Kara Jan 2021

On The Outage Performance Of Swipt-Noma-Crs With Imperfect Sic And Csi, Ferdi̇ Kara

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a nonorthogonal multiple access based cooperative relaying system (NOMA-CRS) is consideredto increase spectral efficiency. Besides, the simultaneous wireless information and power transfer (SWIPT) is proposedfor the relay in NOMA-CRS. In SWIPT-NOMA-CRS, three different energy harvesting (EH) protocols, power sharing(PS), time sharing (TS) and ideal protocols are implemented. The outage performances of the SWIPT-NOMA-CRSare studied for all three EH protocols. In the analysis, to represent practical/reasonable scenarios, imperfect successiveinterference canceler (SIC) and imperfect channel state information (CSI) are taken into consideration. The derivedoutage probability (OP) expressions are validated via computer simulations. Besides, the OP for the benchmark scheme,NOMA-CRS …

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Turkish Sign Language Recognition Based On Multistream Data Fusion, Cemi̇l Gündüz, Hüseyi̇n Polat Jan 2021

Turkish Sign Language Recognition Based On Multistream Data Fusion, Cemi̇l Gündüz, Hüseyi̇n Polat

Turkish Journal of Electrical Engineering and Computer Sciences

Sign languages are nonverbal, visual languages that hearing- or speech-impaired people use for communication.Aside from hands, other communication channels such as body posture and facial expressions are also valuable insign languages. As a result of the fact that the gestures in sign languages vary across countries, the significance ofcommunication channels in each sign language also differs. In this study, representing the communication channels usedin Turkish sign language, a total of 8 different data streams-4 RGB, 3 pose, 1 optical flow-were analyzed. Inception3D was used for RGB and optical flow; and LSTM-RNN was used for pose data streams. Experiments were conductedby …

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An Adaptive Element Division Algorithm For Accurate Evaluation Of Singular Andnear Singular Integrals In 3d, Hakan Bayindir, Besi̇m Baranoğlu, Ali̇ Yazici Jan 2021

An Adaptive Element Division Algorithm For Accurate Evaluation Of Singular Andnear Singular Integrals In 3d, Hakan Bayindir, Besi̇m Baranoğlu, Ali̇ Yazici

Turkish Journal of Electrical Engineering and Computer Sciences

An adaptive algorithm for evaluation of singular and near singular integrals in 3D is presented. The algorithmis based on successive adaptive/selective subdivisions of the element until a prescribed error criteria is met. For evaluatingthe integrals in each subdivision, Gauss quadrature is applied. The method is computationally simple, memory efficientand can be applied for both triangular and quadrilateral elements, including the elements with nonplanar and/or curvedsurfaces. To assess the method, several examples are discussed. It has shown that the algorithm performs well forsingular and near-singular integral examples presented in the paper and evaluates the integrals with very high accuracy.

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Dual Bit Control Low-Power Dynamic Content Addressable Memory Design For Iotapplications, V V Satyanarayana Satti, Sridevi Sriadibhatla Jan 2021

Dual Bit Control Low-Power Dynamic Content Addressable Memory Design For Iotapplications, V V Satyanarayana Satti, Sridevi Sriadibhatla

Turkish Journal of Electrical Engineering and Computer Sciences

The Internet of things (IoT) is an emerging area in the semiconductor industry for low-power and high-speedapplications. Many search engines of IoT applications require low power consumption and high-speed content addressablememory (CAM) devices for the transmission of data packets between servers and end devices. A CAM is a hardwaredevice used for transfer of packets in a network router with high speed at the cost of power consumption. In this paper,a new dual bit control precharge free (PF) dynamic content addressable memory (DCAM) has been introduced. Theproposed design uses a new charge control circuitry, which is used to control the dual …

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Relational-Grid-World: A Novel Relational Reasoning Environment And An Agentmodel For Relational Information Extraction, Faruk Küçüksubaşi, Eli̇f Sürer Jan 2021

Relational-Grid-World: A Novel Relational Reasoning Environment And An Agentmodel For Relational Information Extraction, Faruk Küçüksubaşi, Eli̇f Sürer

Turkish Journal of Electrical Engineering and Computer Sciences

Reinforcement learning (RL) agents are often designed specifically for a particular problem and they generallyhave uninterpretable working processes. Statistical methods-based agent algorithms can be improved in terms ofgeneralizability and interpretability using symbolic artificial intelligence (AI) tools such as logic programming. Inthis study, we present a model-free RL architecture that is supported with explicit relational representations of theenvironmental objects. For the first time, we use the PrediNet network architecture in a dynamic decision-making problemrather than image-based tasks, and multi-head dot-product attention network (MHDPA) as a baseline for performancecomparisons. We tested two networks in two environments -i.e., the baseline box-world environment and …

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A Topological Overview Of Microgrids: From Maturity To The Future, Ayşe Kübra Erenoğlu, Semanur Sancar, Ozan Erdi̇nç, Mustafa Bağriyanik Jan 2021

A Topological Overview Of Microgrids: From Maturity To The Future, Ayşe Kübra Erenoğlu, Semanur Sancar, Ozan Erdi̇nç, Mustafa Bağriyanik

Turkish Journal of Electrical Engineering and Computer Sciences

The concept of microgrid (MG) has attracted great attention from the system operators for increasing operational effectiveness as well as providing more reliable, sustainable and economic power system. In this paper, a comprehensive investigation is presented to shine new light on evaluating changes in MG operation from maturity to the future. A great deal of literature studies consisting of the traditional MG architecture, encountered challenges and proposed solutions for overcoming them are all examined in detail. Also, the impact of highly integrated renewable-based energy sources into the power system is analysed by current studies. Moreover, modern MG architecture is extensively …

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Chaos In Metaheuristic Based Artificial Intelligence Algorithms:A Short Review, Gökhan Atali, İhsan Pehli̇van, Bi̇lal Gürevi̇n, Hali̇l İbrahi̇m Şeker Jan 2021

Chaos In Metaheuristic Based Artificial Intelligence Algorithms:A Short Review, Gökhan Atali, İhsan Pehli̇van, Bi̇lal Gürevi̇n, Hali̇l İbrahi̇m Şeker

Turkish Journal of Electrical Engineering and Computer Sciences

Metaheuristic based artificial intelligence algorithms are commonly used in the solution of optimization problems. Another area -besides engineering systems- where chaos theory is widely employed is optimization problems. Being applied easily and not trapping in local optima, chaos-based search algorithms have attracted great attention. For example, it has been reported that when random number sequences generated from different chaotic systems are replaced with parameter values in bioinspired and swarm intelligence algorithms, an increase in the performance of metaheuristic algorithms is observed. Many scientific studies on developing hybrid algorithms in which metaheuristic algorithms and chaos theory are used together are already …

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Efficient Power Macromodeling Approach For An Ip-Based Soc System Usingdiscrete Water Cycle Algorithm, Faisal Siddiq, Yaseer Arafat Durrani Jan 2021

Efficient Power Macromodeling Approach For An Ip-Based Soc System Usingdiscrete Water Cycle Algorithm, Faisal Siddiq, Yaseer Arafat Durrani

Turkish Journal of Electrical Engineering and Computer Sciences

Low-power consumption is becoming a crucial concern that cannot be neglected in system-on-chip (SoC) designs. Low-power solutions help designers to provide a powerful methodology to analyze, estimate, and optimize today's power concerns. Early estimation of power at a high level reduces the redesign cycle and turn-around time. Power dissipation is a function of input patterns and their characteristics. This paper describes a power estimation technique by using predefined statistical characteristics-based input patterns, which gives the average power dissipation of individual intellectual property (IP) blocks and interconnects/buses in an SoC system design. During the power estimation phase, the discrete water cycle …

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The Effect Of Demand Response Control On Stability Delay Margins Of Loadfrequency Control Systems With Communication Time-Delays, Deni̇z Kati̇poğlu, Şahi̇n Sönmez, Saffet Ayasun, Ausnain Naveed Jan 2021

The Effect Of Demand Response Control On Stability Delay Margins Of Loadfrequency Control Systems With Communication Time-Delays, Deni̇z Kati̇poğlu, Şahi̇n Sönmez, Saffet Ayasun, Ausnain Naveed

Turkish Journal of Electrical Engineering and Computer Sciences

This paper studies the effect of dynamic demand response (DR) control on stability delay margins of load frequency control (LFC) systems including communication time-delays. A DR control loop is included in each control area, called as LFC-DR system and Rekasius substitution is utilized to identify stability margins for various proportionalintegral (PI) gains and participation ratios of the secondary and DR control loops. The purpose of Rekasius substitution technique is to obtain purely complex roots on the imaginary axis of the time-delayed LFC-DR system. This substitution first converts the characteristic equation of the LFC-DR system including delay-dependent exponential terms into an …

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Using Eeg To Detect Driving Fatigue Based On Common Spatial Pattern Andsupport Vector Machine, Li Wang, David Johnson, Yingzi Lin Jan 2021

Using Eeg To Detect Driving Fatigue Based On Common Spatial Pattern Andsupport Vector Machine, Li Wang, David Johnson, Yingzi Lin

Turkish Journal of Electrical Engineering and Computer Sciences

To investigate the correlation between electroencephalogram (EEG) and driving fatigue states, this study used machine learning algorithms to detect driving fatigue based on EEG. 14 channels of EEG data were collected from thirty-four healthy subjects in this research at Northeastern University. Each subject participated in two scenarios (baseline and fatigue scenarios). Subjective ratings of fatigue levels were also obtained from the subjects using the NASA-Task Load Index (TLX). The common spatial pattern (CSP) algorithm was used to extract features from the raw EEG data. The support vector machine (SVM) was used as the classifier in the design of the machine …

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A Meta-Gradient Approach To Learning Cooperative Multi-Agent Communication Topology, Qi Zhang, Dingyang Chen Jan 2021

A Meta-Gradient Approach To Learning Cooperative Multi-Agent Communication Topology, Qi Zhang, Dingyang Chen

Publications

In cooperative multi-agent reinforcement learning (MARL), agents often can only partially observe the environment state, and thus communication is crucial to achieving coordination. Communicating agents must simultaneously learn to whom to communicate (i.e., communication topology) and how to interpret the received message for decision-making. Although agents can efficiently learn communication interpretation by end-to-end backpropagation, learning communication topology is much trickier since the binary decisions of whether to communicate impede end-to-end differentiation. As evidenced in our experiments, existing solutions, such as reparameterization tricks and reformulating topology learning as reinforcement learning, often fall short. This paper introduces a meta-learning framework that aims …

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Parallel Computation, Mahesh Wosti Jan 2021

Parallel Computation, Mahesh Wosti

Student Academic Conference

Parallel computing has always fascinated me since I became aware of it. I think it is the only path forward if we are to build and make a super-fast computer in days to come. For my senior seminar, I want to build a simple framework of the parallel system and dig deeper into potential benefits and drawbacks of using a parallel system compared to the serial computing that is still pervasive in today’s modern technology.

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Energy Considerations In Blockchain-Enabled Applications, Cesar Enrique Castellon Escobar Jan 2021

Energy Considerations In Blockchain-Enabled Applications, Cesar Enrique Castellon Escobar

UNF Graduate Theses and Dissertations

Blockchain-powered smart systems deployed in different industrial applications promise operational efficiencies and improved yields, while mitigating significant cybersecurity risks pertaining to the main application. Associated tradeoffs between availability and security arise at implementation, however, triggered by the additional resources (e.g., memory, computation) required by each blockchain-enabled host. This thesis applies an energy-reducing algorithmic engineering technique for Merkle Tree root and Proof of Work calculations, two principal elements of blockchain computations, as a means to preserve the promised security benefits but with less compromise to system availability. Using pyRAPL, a python library to measure computational energy, we experiment with both the …

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Re-Designing Main Memory Subsystems With Emerging Monolithic 3d (M3d) Integration And Phase Change Memory Technologies, Chao-Hsuan Huang Jan 2021

Re-Designing Main Memory Subsystems With Emerging Monolithic 3d (M3d) Integration And Phase Change Memory Technologies, Chao-Hsuan Huang

Theses and Dissertations--Electrical and Computer Engineering

Over the past two decades, Dynamic Random-Access Memory (DRAM) has emerged as the dominant technology for implementing the main memory subsystems of all types of computing systems. However, inferring from several recent trends, computer architects in both the industry and academia have widely accepted that the density (memory capacity per chip area) and latency of DRAM based main memory subsystems cannot sufficiently scale in the future to meet the requirements of future data-centric workloads related to Artificial Intelligence (AI), Big Data, and Internet-of-Things (IoT). In fact, the achievable density and access latency in main memory subsystems presents a very fundamental …

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Edge Processing Of Image For Uas Sense And Avoidance, Christopher J. Rave Jan 2021

Edge Processing Of Image For Uas Sense And Avoidance, Christopher J. Rave

Browse all Theses and Dissertations

Today there is a large market for Unmanned Aerial Systems. Although most current systems are remotely piloted by operators on the ground, increasingly, many of these systems will use some sort of automatic flight controller to help mitigate new challenges, due to their deployment at growing scale. These challenges include, but are not limited to, shortage of FAA-certified UAS pilots, transmission bandwidth and delay constraints and cyber security threats associated with wireless networking, profitability of operations constrained by energy capacity and efficiency and air dynamics planning, and etc. In order to address these rising challenges, this thesis is a part …

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Arise - Augmented Reality In Surgery And Education, Sadan Suneesh Menon Jan 2021

Arise - Augmented Reality In Surgery And Education, Sadan Suneesh Menon

Browse all Theses and Dissertations

Human errors in healthcare can be fatal. Proper physical assessment of patients to avoid such errors is of paramount importance. Incorrect or insufficient assessment of the patient can cause treatment delays that may lead to negative outcomes. In this dissertation we introduce innovative technology to assist surgeons in patient assessment as well as during the training of nurses in order to enhance learning. Technological advancements have made it possible to visualize overlays of computer-generated 3D models on real-world surfaces. This technology is called augmented reality. Using Steady State Topography (SST) brain imaging to examine the brain activity of people who …

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Leveraging Sequential Nature Of Conversations For Intent Classification, Shree Gotteti Jan 2021

Leveraging Sequential Nature Of Conversations For Intent Classification, Shree Gotteti

Browse all Theses and Dissertations

Conversations are more than just a sequence of text, it is where two or more participants interact in order to achieve their goals. Conversation Understanding (CU) requires all participants to understand each others intent. In the past decade, CU has been extended from automated human-human text processing to build automated conversational agents for human-machine interactions. Despite their popularity, these automated conversational agents (like Siri, Alexa, etc) can't handle more than one or two utterances, and they don't recognize conversations as intents. The development of approaches that extract intents behind an utterance is essential for the advancements of Question Answering (QA) …

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Simulation For Cybersecurity: State Of The Art And Future Directions, Hamdi Kavak, Jose J. Padilla, Daniele Vernon-Bido, Saikou Y. Diallo, Ross Gore, Sachin Shetty Jan 2021

Simulation For Cybersecurity: State Of The Art And Future Directions, Hamdi Kavak, Jose J. Padilla, Daniele Vernon-Bido, Saikou Y. Diallo, Ross Gore, Sachin Shetty

VMASC Publications

In this article, we provide an introduction to simulation for cybersecurity and focus on three themes: (1) an overview of the cybersecurity domain; (2) a summary of notable simulation research efforts for cybersecurity; and (3) a proposed way forward on how simulations could broaden cybersecurity efforts. The overview of cybersecurity provides readers with a foundational perspective of cybersecurity in the light of targets, threats, and preventive measures. The simulation research section details the current role that simulation plays in cybersecurity, which mainly falls on representative environment building; test, evaluate, and explore; training and exercises; risk analysis and assessment; and humans …

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Human Factors, Ergonomics And Industry 4.0 In The Oil & Gas Industry: A Bibliometric Analysis, Francesco Longo, Antonio Padovano, Lucia Gazzaneo, Jessica Frangella, Rafael Diaz Jan 2021

Human Factors, Ergonomics And Industry 4.0 In The Oil & Gas Industry: A Bibliometric Analysis, Francesco Longo, Antonio Padovano, Lucia Gazzaneo, Jessica Frangella, Rafael Diaz

VMASC Publications

Over the last few years, the Human Factors and Ergonomics (HF/E) discipline has significantly benefited from new human-centric engineered digital solutions of the 4.0 industrial age. Technologies are creating new socio-technical interactions between human and machine that minimize the risk of design-induced human errors and have largely contributed to remarkable improvements in terms of process safety, productivity, quality, and workers’ well-being. However, despite the Oil&Gas (O&G) sector is one of the most hazardous environments where human error can have severe consequences, Industry 4.0 aspects are still scarcely integrated with HF/E. This paper calls for a holistic understanding of the changing …

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Developing An Artificial Intelligence Framework To Assess Shipbuilding And Repair Sub-Tier Supply Chains Risk, Rafael Diaz, Katherine Smith, Beatriz Acero, Francesco Longo, Antonio Padovano Jan 2021

Developing An Artificial Intelligence Framework To Assess Shipbuilding And Repair Sub-Tier Supply Chains Risk, Rafael Diaz, Katherine Smith, Beatriz Acero, Francesco Longo, Antonio Padovano

VMASC Publications

The defense shipbuilding and repair industry is a labor-intensive sector that can be characterized by low-product volumes and high investments in which a large number of shared resources, technology, suppliers, and processes asynchronously converge into large construction projects. It is mainly organized by the execution of a complex combination of sequential and overlapping stages. While entities engaged in this large-scale endeavor are often knowledgeable about their first-tier suppliers, they usually do not have insight into the lower tiers suppliers. A sizable part of any supply chain disruption is attributable to instabilities in sub-tier suppliers. This research note conceptually delineates a …

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Hidden Markov Model And Cyber Deception For The Prevention Of Adversarial Lateral Movement, Md Ali Reza Al Amin, Sachin Shetty, Laurent Njilla, Deepak K. Tosh, Charles Kamhoua Jan 2021

Hidden Markov Model And Cyber Deception For The Prevention Of Adversarial Lateral Movement, Md Ali Reza Al Amin, Sachin Shetty, Laurent Njilla, Deepak K. Tosh, Charles Kamhoua

Computational Modeling & Simulation Engineering Faculty Publications

Advanced persistent threats (APTs) have emerged as multi-stage attacks that have targeted nation-states and their associated entities, including private and corporate sectors. Cyber deception has emerged as a defense approach to secure our cyber infrastructure from APTs. Practical deployment of cyber deception relies on defenders' ability to place decoy nodes along the APT path optimally. This paper presents a cyber deception approach focused on predicting the most likely sequence of attack paths and deploying decoy nodes along the predicted path. Our proposed approach combines reactive (graph analysis) and proactive (cyber deception technology) defense to thwart the adversaries' lateral movement. The …

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Modeling And Simulation Of Cascading Failures In Transportation Systems During Hurricane Evacuations, Yuan Zhu, Kaan Ozbay, Hong Yang, Fan Zuo, Di Sha Jan 2021

Modeling And Simulation Of Cascading Failures In Transportation Systems During Hurricane Evacuations, Yuan Zhu, Kaan Ozbay, Hong Yang, Fan Zuo, Di Sha

Computational Modeling & Simulation Engineering Faculty Publications

Effective and timely evacuation is critical in alleviating the impact of hurricanes. As such, evacuation models are often sought to support the preparedness of evacuations. One important task in the modeling process is to evaluate exogenous factors that cause transportation system capacity loss during evacuation. Typical factors include direct damage to the roadway network due to storm surge and cascading impacts because of other facilities failures. For example, power outage can lead to signal failure and subway suspension. This paper aims to develop a macroscopic simulation-based approach to study the capacity loss of the roadway network in evacuation due to …

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Energy-Efficient In-Memory Architectures Leveraging Intrinsic Behaviors Of Embedded Mram Devices, Shadi Sheikhfaal Jan 2021

Energy-Efficient In-Memory Architectures Leveraging Intrinsic Behaviors Of Embedded Mram Devices, Shadi Sheikhfaal

Electronic Theses and Dissertations, 2020-2023

For decades, innovations to surmount the processor versus memory gap and move beyond conventional von Neumann architectures continue to be sought and explored. Recent machine learning models still expend orders of magnitude more time and energy to access data in memory in addition to merely performing the computation itself. This phenomenon referred to as a memory-wall bottleneck, is addressed herein via a completely fresh perspective on logic and memory technology design. The specific solutions developed in this dissertation focus on utilizing intrinsic switching behaviors of embedded MRAM devices to design cross-layer and energy-efficient Compute-in-Memory (CiM) architectures, accelerate the computationally-intensive operations …

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Development Of An Autonomous Navigation System For The Shuttle Car In Underground Room & Pillar Coal Mines, Vasileios Androulakis Jan 2021

Development Of An Autonomous Navigation System For The Shuttle Car In Underground Room & Pillar Coal Mines, Vasileios Androulakis

Theses and Dissertations--Mining Engineering

In recent years, autonomous solutions in the multi-disciplinary field of the mining engineering have been an extremely popular applied research topic. The growing demand for mineral supplies combined with the steady decline in the available surface reserves has driven the mining industry to mine deeper underground deposits. These deposits are difficult to access, and the environment may be hazardous to mine personnel (e.g., increased heat, difficult ventilation conditions, etc.). Moreover, current mining methods expose the miners to numerous occupational hazards such as working in the proximity of heavy mining equipment, possible roof falls, as well as noise and dust. As …

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Cooperative Target Tracking In Concentric Formations, Lili Ma Jan 2021

Cooperative Target Tracking In Concentric Formations, Lili Ma

Publications and Research

This paper considers the problem of coordinating multiple unmanned aerial vehicles (UAVs) in a circular formation around a moving target. The main contribution is allowing for versatile formation patterns on the basis of the following components. Firstly, new uniform spacing control laws are proposed that spread the agents not necessarily over a full circle, but over a circular arc. Uniform spacing formation controllers are proposed, regulating either the separation distances or the separation angles between agents. Secondly, the use of virtual agents is proposed to allow for different radii in agents’ orbits. Thirdly, a hierarchical combination of formation patterns is …

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Fpga-Augmented Secure Crash-Consistent Non-Volatile Memory, Yu Zou Jan 2021

Fpga-Augmented Secure Crash-Consistent Non-Volatile Memory, Yu Zou

Electronic Theses and Dissertations, 2020-2023

Emerging byte-addressable Non-Volatile Memory (NVM) technology, although promising superior memory density and ultra-low energy consumption, poses unique challenges to achieving persistent data privacy and computing security, both of which are critically important to the embedded and IoT applications. Specifically, to successfully restore NVMs to their working states after unexpected system crashes or power failure, maintaining and recovering all the necessary security-related metadata can severely increase memory traffic, degrade runtime performance, exacerbate write endurance problem, and demand costly hardware changes to off-the-shelf processors. In this thesis, we summarize and expand upon two of our innovative works, ARES and HERMES, to design …

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Real-Time Operation Of Microgrids, Salem Al-Agtash, Asma Alkhraibat, Mohamad Al Hashem, Nisrein Al-Mutlaq Jan 2021

Real-Time Operation Of Microgrids, Salem Al-Agtash, Asma Alkhraibat, Mohamad Al Hashem, Nisrein Al-Mutlaq

Computer Science and Engineering

Microgrid (MG) systems effectively integrate a generation mix of solar, wind, and other renewable energy resources. The intermittent nature of renewable resources and the unpredictable weather conditions contribute largely to the unreliability of microgrid real-time operation. This paper investigates the behavior of microgrid for different intermittent scenarios of photovoltaic generation in real-time. Reactive power coordination control and load shedding mechanisms are used for reliable operation and are implemented using OPAL-RT simulator integrated with Matlab. In an islanded MG, load shedding can be an effective mechanism to maintain generation-load balance. The microgrid of the German Jordanian University (GJU) is used for …

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