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Articles 11911 - 11940 of 17350
Full-Text Articles in Engineering
Metaheuristic Linear Modeling Technique For Estimating The Excitation Current Of A Synchronous Motor, Hamdi̇ Tolga Kahraman
Metaheuristic Linear Modeling Technique For Estimating The Excitation Current Of A Synchronous Motor, Hamdi̇ Tolga Kahraman
Turkish Journal of Electrical Engineering and Computer Sciences
The subject of modeling and estimating of synchronous motor (SM) parameters is a challenge mathematically. Although effective solutions have been developed for nonlinear systems in artificial intelligence (AI)-based models, problems are faced with the application of these models in power circuits in real-time. One of these problems is the delay time resulting from a complex calculation process and thus the difficulties faced in the design of real-time motor driving circuits. Another important problem regards the difficulty in the realization of a complex AI-based model in microprocessor-based real-time systems. In this study, a new hybrid technique is developed to solve the …
Frequency-Emulated Uniform Cellular Automata, Hürevren Kiliç
Frequency-Emulated Uniform Cellular Automata, Hürevren Kiliç
Turkish Journal of Electrical Engineering and Computer Sciences
The notion of a frequency-emulated (f-emulated) uniform cellular automata (CA) that enables the behavior emulation of some elementary CA via memory usage is introduced. An algorithm that generates f-emulated uniform CA sets is developed and an upper bound for its output size is given. It is observed that traffic rule 184 together with its 2-emulator version, which generates the behavior of the known majority rule 232, performs the density classification task perfectly. Moreover, it is possible to use a 2-emulated uniform CA for the solution of the parity problem.
Cervical Cancer Histology Image Feature Extraction And Classification, Peng Guo
Cervical Cancer Histology Image Feature Extraction And Classification, Peng Guo
Masters Theses
"Cervical cancer, the second most common cancer affecting women worldwide and the most common in developing countries can be cured if detected early and treated. Expert pathologists routinely visually examine histology slides for cervix tissue abnormality assessment. In previous research, an automated, localized, fusion-based approach was investigated for classifying squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN) based on image analysis of 62 digitized histology images obtained through the National Library of Medicine. In this research, CIN grade assessments from two pathologists are analyzed and are used to facilitate atypical cell concentration feature development …
Streaming Computations With Precise Control, Peng Li, Kunal Agrawal, Jeremy Buhler, Roger Chamberlain
Streaming Computations With Precise Control, Peng Li, Kunal Agrawal, Jeremy Buhler, Roger Chamberlain
All Computer Science and Engineering Research
No abstract provided.
Federated Scheduling For Stochastic Parallel Real-Time Tasks, Jing Li, Kunal Agrawal, Christopher Gill, Chenyang Lu
Federated Scheduling For Stochastic Parallel Real-Time Tasks, Jing Li, Kunal Agrawal, Christopher Gill, Chenyang Lu
All Computer Science and Engineering Research
Federated scheduling is a strategy to schedule parallel real-time tasks: It allocates a dedicated cluster of cores to high-utilization task (utilization >1); It uses a multiprocessor scheduling algorithm to schedule and execute all low-utilization tasks sequentially, on a shared cluster of the remaining cores. Prior work has shown that federated scheduling has the best known capacity augmentation bound of 2 for parallel tasks with implicit deadlines. In this paper, we explore the soft real-time performance of federated scheduling and address the average-case workloads instead of the worst-case values. In particular, we consider stochastic tasks -- tasks for which execution time …
Rt-Openstack: A Real-Time Cloud Management System, Sisu Xi, Chong Li, Chenyang Lu, Christopher D. Gill, Meng Xu, Linh T.X. Phan, Insup Lee, Oleg Sokolsky
Rt-Openstack: A Real-Time Cloud Management System, Sisu Xi, Chong Li, Chenyang Lu, Christopher D. Gill, Meng Xu, Linh T.X. Phan, Insup Lee, Oleg Sokolsky
All Computer Science and Engineering Research
Clouds have become appealing platforms for running not only general-purpose applications but also real-time applications. However, current clouds cannot provide real-time performance for virtual machines (VM) for two reasons: (1) the lack of a real-time virtual machine monitor (VMM) scheduler on a single host, and (2) the lack of a real-time aware VM placement scheme by the cloud manager. While real-time VM schedulers do exist, prior solutions employ either heuristics-based approaches that cannot always achieve predictable latency or apply real-time scheduling theory that may result in low CPU utilization. We observe the demand and advantage for co-hosting real-time (RT) VMs …
Cloudpowercap: Integrating Power Budget And Resource Management Across A Virtualized Server Cluster, Yong Fu, Anne Holler, Chenyang Lu
Cloudpowercap: Integrating Power Budget And Resource Management Across A Virtualized Server Cluster, Yong Fu, Anne Holler, Chenyang Lu
All Computer Science and Engineering Research
In many datacenters, server racks are highly underutilized. Rack slots are left empty to keep the sum of the server nameplate maximum power below the power provisioned to the rack. And the servers that are placed in the rack cannot make full use of available rack power. The root cause of this rack underutilization is that the server nameplate power is often much higher than can be reached in practice. To address rack underutilization, server vendors are shipping support for per-host power caps, which provide a server-enforced limit on the amount of power that the server can draw. Using this …
Performance Modeling Of Virtualized Custom Logic Computations, Michael J. Hall, Roger D. Chamberlain
Performance Modeling Of Virtualized Custom Logic Computations, Michael J. Hall, Roger D. Chamberlain
All Computer Science and Engineering Research
Virtualization of custom logic computations (i.e., by sharing a fixed function across distinct data streams) provides a means of reusing hardware resources, particularly when resources are limited. This is common practice in traditional processors where more than one user can share processor resources. In this paper, we virtualize a custom logic block using C-slow techniques to support fine-grain context-switching. We then develop and present an analytic model for several performance measures (throughput, latency, input queue occupancy) for both fine-grained and coarse-grained context switching (to a secondary memory). Next, we calibrate the analytic performance model with empirical measurements. We then validate …
Inferring Memory Map Instructions, Paul T. Scheid, Ari J. Spilo, Ron K. Cytron
Inferring Memory Map Instructions, Paul T. Scheid, Ari J. Spilo, Ron K. Cytron
All Computer Science and Engineering Research
We describe the problem of inferring a set of memory map instructions from a reference trace, with the goal of minimizing the number of such instructions as well as the number of unreferenced but mapped storage locations. We prove the related decision problem NP-complete. We then present and compare the results of two heuristic approaches on some actual traces.
Event-Triggered Optimal Regulation Of Uncertain Linear Discrete-Time Systems By Using Q-Learning Scheme, Avimanyu Sahoo, S. Jagannathan
Event-Triggered Optimal Regulation Of Uncertain Linear Discrete-Time Systems By Using Q-Learning Scheme, Avimanyu Sahoo, S. Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, an event-triggered optimal adaptive regulation of an uncertain linear discrete time system is proposed. This scheme solves the optimal control in a forward in- time and online manner by using both dynamic programming and Q learning. First, the time varying action dependent value or the Q-function is estimated online by an adaptive value function estimator (VFE) with event-based state vector and a time dependent basis function. The estimated value function parameters are subsequently used to generate the optimal control gain matrix. Further, aperiodic tuning law for the VFE parameters is proposed not only to estimate the parameters …
Near Optimal Boundary Control Of Distributed Parameter Systems Modeled As Parabolic Pdes By Using Finite Difference Neural Network Approximation, Behzad Talaei, Hao Xu, S. Jagannathan
Near Optimal Boundary Control Of Distributed Parameter Systems Modeled As Parabolic Pdes By Using Finite Difference Neural Network Approximation, Behzad Talaei, Hao Xu, S. Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
This paper develops a novel neural network (NN) based near optimal boundary control scheme for distributed parameter systems (DPS) governed by semi linear parabolic partial differential equations (PDE) in the presence of control constraints and unknown system dynamics. First, finite difference method (FDM) is utilized to develop a reduced order system which represents the discretized dynamics of PDE system. Subsequently, a near optimal control scheme is proposed for the discretized system by using NN based approximate dynamic programming (ADP). To relax the requirement of system dynamics, a NN identifier is utilized. Moreover, a second NN is proposed to estimate a …
A Model-Based Fault Detection And Prognostics Scheme For Takagi-Sugeno Fuzzy Systems, Balaje T. Thumati, Miles A. Feinstein, S. Jagannathan
A Model-Based Fault Detection And Prognostics Scheme For Takagi-Sugeno Fuzzy Systems, Balaje T. Thumati, Miles A. Feinstein, S. Jagannathan
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, a novel model-based fault detection (FD) and prediction scheme is developed for a class of Takagi-Sugeno (T-S) fuzzy systems. Unlike other FD schemes, in the proposed design, an FD observer with online fault learning capability is utilized to generate a residual which is obtained by comparing the system output with respect to the observer output. A fault is declared active if the generated residual exceeds an a priori chosen threshold. Subsequently, the fault magnitude is estimated online by using a suitable parameter update law. Upon detection, the online estimate of the fault magnitude is used in a …
Why The Data Train Needs Semantic Rails, Krzysztof Janowicz, Frank Van Harmelen, James A. Hendler, Pascal Hitzler
Why The Data Train Needs Semantic Rails, Krzysztof Janowicz, Frank Van Harmelen, James A. Hendler, Pascal Hitzler
Computer Science and Engineering Faculty Publications
While catchphrases such as big data, smart data, data intensive science, or smart dust highlight different aspects, they share a common theme: Namely, a shift towards a data-centric perspective in which the synthesis and analysis of data at an ever-increasing spatial, temporal, and thematic resolution promises new insights, while, at the same time, reducing the need for strong domain theories as starting points. In terms of the envisioned methodologies, those catchphrases tend to emphasize the role of predictive analytics, i.e., statistical techniques including data mining and machine learning, as well as supercomputing. Interestingly, however, while this perspective takes the availability …
A Hybrid Approach Using Rup And Scrum As A Software Development Strategy, Dalila Castilla
A Hybrid Approach Using Rup And Scrum As A Software Development Strategy, Dalila Castilla
UNF Graduate Theses and Dissertations
According to some researchers, a hybrid approach can help optimize the software development lifecycle by combining two or more methodologies. RUP and Scrum are two methodologies that successfully complement each other to improve the software development process. However, the literature has shown only few case studies on exactly how organizations are successfully applying this hybrid methodology and the benefits and issues found during the process. To help fill this literature gap, the main purpose of this thesis is to describe the development of the Lobbyist Registration and Tracking System for the City of Jacksonville case study where a hybrid approach, …
Capacity Augmentation Bound Of Federated Scheduling For Parallel Dag Tasks, Jing Li, Abusayeed Saifullah, Kunal Agrawal, Christopher Gill
Capacity Augmentation Bound Of Federated Scheduling For Parallel Dag Tasks, Jing Li, Abusayeed Saifullah, Kunal Agrawal, Christopher Gill
All Computer Science and Engineering Research
We present a novel federated scheduling approach for parallel real-time tasks under a general directed acyclic graph (DAG) model. We provide a capacity augmentation bound of 2 for hard real-time scheduling; here we use the worst-case execution time and critical-path length of tasks to determine schedulability. This is the best known capacity augmentation bound for parallel tasks. By constructing example task sets, we further show that the lower bound on capacity augmentation of federated scheduling is also 2 for any m > 2. Hence, the gap is closed and bound 2 is a strict bound for federated scheduling. The federated scheduling …
Placement Of Mode And Wavelength Converters For Throughput Enhancement In Optical Networks, Ruaa Abdulrahman
Placement Of Mode And Wavelength Converters For Throughput Enhancement In Optical Networks, Ruaa Abdulrahman
Electronic Theses and Dissertations
The success of recent experiments to transport data using combined wavelength division multiplexed (WDM) and mode-division multiplexed (MDM) transmission has generated optimism for the attainment of optical networks with unprecedented bandwidth capacity, exceeding the fundamental Shannon capacity limit attained by WDM alone. Optical mode converters and wavelength converters are devices that can be placed in future optical nodes (routers) to prevent or reduce the connection blocking rate and consequently increase network throughput. In this thesis, the specific problem of the placement of mode converters (MC) and mode-wavelength converters (MWC) in combined mode and wavelength division multiplexing (MWDM) networks is investigated. …
Functional Scaffolding For Musical Composition: A New Approach In Computer-Assisted Music Composition, Amy K. Hoover
Functional Scaffolding For Musical Composition: A New Approach In Computer-Assisted Music Composition, Amy K. Hoover
Electronic Theses and Dissertations
While it is important for systems intended to enhance musical creativity to define and explore musical ideas conceived by individual users, many limit musical freedom by focusing on maintaining musical structure, thereby impeding the user's freedom to explore his or her individual style. This dissertation presents a comprehensive body of work that introduces a new musical representation that allows users to explore a space of musical rules that are created from their own melodies. This representation, called functional scaffolding for musical composition (FSMC), exploits a simple yet powerful property of multipart compositions: The pattern of notes and rhythms in different …
Visual Analysis Of Extremely Dense Crowded Scenes, Haroon Idrees
Visual Analysis Of Extremely Dense Crowded Scenes, Haroon Idrees
Electronic Theses and Dissertations
Visual analysis of dense crowds is particularly challenging due to large number of individuals, occlusions, clutter, and fewer pixels per person which rarely occur in ordinary surveillance scenarios. This dissertation aims to address these challenges in images and videos of extremely dense crowds containing hundreds to thousands of humans. The goal is to tackle the fundamental problems of counting, detecting and tracking people in such images and videos using visual and contextual cues that are automatically derived from the crowded scenes. For counting in an image of extremely dense crowd, we propose to leverage multiple sources of information to compute …
Faults Identification In Three-Phase Induction Motors Using Support Vector Machines, Rama Hammo
Faults Identification In Three-Phase Induction Motors Using Support Vector Machines, Rama Hammo
Master of Technology Management Plan II Graduate Projects
Induction motor is one of the most important motors used in industrial applications. The operating conditions may sometime lead the machine into different fault situations. The main types of external faults experienced by these motors are over loading, single phasing, unbalanced supply voltage, locked rotor, phase reversal, ground fault, under voltage and over voltage. The machine should be shut down when a fault is experienced to avoid damage and for the safety of the workers. Computer based relays monitor the machine and disconnect it during the faults. The relay logic used to identify these faults requires sophisticated signal processing techniques …
Sketchart: A Pen-Based Tool For Chart Generation And Interaction., Andres Vargas Gonzalez
Sketchart: A Pen-Based Tool For Chart Generation And Interaction., Andres Vargas Gonzalez
Electronic Theses and Dissertations
It has been shown that representing data with the right visualization increases the understanding of qualitative and quantitative information encoded in documents. However, current tools for generating such visualizations involve the use of traditional WIMP techniques, which perhaps makes free interaction and direct manipulation of the content harder. In this thesis, we present a pen-based prototype for data visualization using 10 different types of bar based charts. The prototype lets users sketch a chart and interact with the information once the drawing is identified. The prototype's user interface consists of an area to sketch and touch based elements that will …
Energy Efficient Routing Towards A Mobile Sink Using Virtual Coordinates In A Wireless Sensor Network, Rouhollah Rahmatizadeh
Energy Efficient Routing Towards A Mobile Sink Using Virtual Coordinates In A Wireless Sensor Network, Rouhollah Rahmatizadeh
Electronic Theses and Dissertations
The existence of a coordinate system can often improve the routing in a wireless sensor network. While most coordinate systems correspond to the geometrical or geographical coordinates, in recent years researchers had proposed the use of virtual coordinates. Virtual coordinates depend only on the topology of the network as defined by the connectivity of the nodes, without requiring geographical information. The work in this thesis extends the use of virtual coordinates to scenarios where the wireless sensor network has a mobile sink. One reason to use a mobile sink is to distribute the energy consumption more evenly among the sensor …
Automatic 3d Human Modeling: An Initial Stage Towards 2-Way Inside Interaction In Mixed Reality, Yiyan Xiong
Automatic 3d Human Modeling: An Initial Stage Towards 2-Way Inside Interaction In Mixed Reality, Yiyan Xiong
Electronic Theses and Dissertations
3D human models play an important role in computer graphics applications from a wide range of domains, including education, entertainment, medical care simulation and military training. In many situations, we want the 3D model to have a visual appearance that matches that of a specific living person and to be able to be controlled by that person in a natural manner. Among other uses, this approach supports the notion of human surrogacy, where the virtual counterpart provides a remote presence for the human who controls the virtual character's behavior. In this dissertation, a human modeling pipeline is proposed for the …
Exploring Sparsity, Self-Similarity, And Low Rank Approximation In Action Recognition, Motion Retrieval, And Action Spotting, Chuan Sun
Electronic Theses and Dissertations
This thesis consists of 4 major parts. In the first part (Chapters 1-2), we introduce the overview, motivation, and contribution of our works, and extensively survey the current literature for 6 related topics. In the second part (Chapters 3-7), we explore the concept of "Self-Similarity" in two challenging scenarios, namely, the Action Recognition and the Motion Retrieval. We build three-dimensional volume representations for both scenarios, and devise effective techniques that can produce compact representations encoding the internal dynamics of data. In the third part (Chapter 8), we explore the challenging action spotting problem, and propose a feature-independent unsupervised framework that …
Measuring Security: A Challenge For The Generation, Janusz Zalewski, Steven Drager, William Mckeever, Andrew J. Kornecki
Measuring Security: A Challenge For The Generation, Janusz Zalewski, Steven Drager, William Mckeever, Andrew J. Kornecki
Department of Electrical Engineering and Computer Science - Daytona Beach
This paper presents an approach to measuring computer security understood as a system property, in the category of similar properties, such as safety, reliability, dependability, resilience, etc. First, a historical discussion of measurements is presented, beginning with views of Hermann von Helmholtz in his 19th century work “Zählen und Messen”. Then, contemporary approaches related to the principles of measuring software properties are discussed, with emphasis on statistical, physical and software models. A distinction between metrics and measures is made to clarify the concepts. A brief overview of inadequacies of methods and techniques to evaluate computer security is presented, followed by …
M-Fdbscan: A Multicore Density-Based Uncertain Data Clustering Algorithm, Atakan Erdem, Taflan İmre Gündem
M-Fdbscan: A Multicore Density-Based Uncertain Data Clustering Algorithm, Atakan Erdem, Taflan İmre Gündem
Turkish Journal of Electrical Engineering and Computer Sciences
In many data mining applications, we use a clustering algorithm on a large amount of uncertain data. In this paper, we adapt an uncertain data clustering algorithm called fast density-based spatial clustering of applications with noise (FDBSCAN) to multicore systems in order to have fast processing. The new algorithm, which we call multicore FDBSCAN (M-FDBSCAN), splits the data domain into c rectangular regions, where c is the number of cores in the system. The FDBSCAN algorithm is then applied to each rectangular region simultaneously. After the clustering operation is completed, semiclusters that occur during splitting are detected and merged to …
Effects Of A Current Transformer's Magnetizing Current On The Driving Voltage In Self-Oscillating Converters, Güngör Bal, Seli̇m Öncü
Effects Of A Current Transformer's Magnetizing Current On The Driving Voltage In Self-Oscillating Converters, Güngör Bal, Seli̇m Öncü
Turkish Journal of Electrical Engineering and Computer Sciences
Magnetizing inductance is one of the parameters that affect the phase and amplitude error of the output current of current transformers (CTs). In this study, the linear circuit model of a CT is developed to be used for driving purposes in power electronics applications. A simulation of the CT and its linear model is achieved. In the model circuit, the effect of the magnetizing inductance on the driving voltage can be examined. The equivalent circuit simulation results and the linear model simulation results along with the calculated results show agreement with each other. These results are compared with experimental results.
Design And Implementation Of An Observer Controller For A Buck Converter, Shenbaga Lakshmi, Sree Renga Raja
Design And Implementation Of An Observer Controller For A Buck Converter, Shenbaga Lakshmi, Sree Renga Raja
Turkish Journal of Electrical Engineering and Computer Sciences
An observer controller for a buck converter is presented. A state feedback gain matrix is derived in order to achieve the stability of the converter and to ensure the robustness of the controller. A load estimator is designed to estimate the unmeasurable variables and to obtain the zero output voltage error. A pulse-width modulation scheme is adopted to obtain the output voltage regulation. In order to improve the transitory response and dynamic constancy of the converter, the controller parameters are designed based on the current mode control. The design is evaluated and verified using MATLAB/Simulink. An experimental set-up is done …
Impact Of Small-World Topology On The Performance Of A Feed-Forward Artificial Neural Network Based On 2 Different Real-Life Problems, Okan Erkaymaz, Mahmut Özer, Nejat Yumuşak
Impact Of Small-World Topology On The Performance Of A Feed-Forward Artificial Neural Network Based On 2 Different Real-Life Problems, Okan Erkaymaz, Mahmut Özer, Nejat Yumuşak
Turkish Journal of Electrical Engineering and Computer Sciences
Since feed-forward artificial neural networks (FFANNs) are the most widely used models to solve real-life problems, many studies have focused on improving their learning performances by changing the network architecture and learning algorithms. On the other hand, recently, small-world network topology has been shown to meet the characteristics of real-life problems. Therefore, in this study, instead of focusing on the performance of the conventional FFANNs, we investigated how real-life problems can be solved by a FFANN with small-world topology. Therefore, we considered 2 real-life problems: estimating the thermal performance of solar air collectors and predicting the modulus of rupture values …
Finding Evidence Of Wordlists Being Deployed Against Ssh Honeypots – Implications And Impacts, Priya Rabadia, Craig Valli
Finding Evidence Of Wordlists Being Deployed Against Ssh Honeypots – Implications And Impacts, Priya Rabadia, Craig Valli
Australian Digital Forensics Conference
This paper is an investigation focusing on activities detected by three SSH honeypots that utilise Kippo honeypot software. The honeypots were located on the same /24 IPv4 network and configured as identically as possible. The honeypots used the same base software and hardware configurations. The data from the honeypots were collected during the period 17th July 2012 and 26th November 2013, a total of 497 active day periods. The analysis in this paper focuses on the techniques used to attempt to gain access to these systems by attacking entities. Although all three honeypots are have the same configuration settings and …
Using Internet Artifacts To Profile A Child Pornography Suspect, Marcus K. Rogers, Kathryn C. Seigfried-Spellar
Using Internet Artifacts To Profile A Child Pornography Suspect, Marcus K. Rogers, Kathryn C. Seigfried-Spellar
Journal of Digital Forensics, Security and Law
Digital evidence plays a crucial role in child pornography investigations. However, in the following case study, the authors argue that the behavioral analysis or “profiling” of digital evidence can also play a vital role in child pornography investigations. The following case study assessed the Internet Browsing History (Internet Explorer Bookmarks, Mozilla Bookmarks, and Mozilla History) from a suspected child pornography user’s computer. The suspect in this case claimed to be conducting an ad hoc law enforcement investigation. After the URLs were classified (Neutral; Adult Porn; Child Porn; Adult Dating sites; Pictures from Social Networking Profiles; Chat Sessions; Bestiality; Data Cleaning; …