Robust Seed Detection For Coronary Arteries Segmentation Using Thresholded Frangi Response,
2017
TÜBİTAK
Robust Seed Detection For Coronary Arteries Segmentation Using Thresholded Frangi Response, Sammer Zai, Muhammad Ahsan Ansari, Soon-Young Song, Young Shik Moon
Turkish Journal of Electrical Engineering and Computer Sciences
Automatic detection of initial seed points has become an essential step towards delineating coronary arteries in coronary computed tomography angiography (CCTA) images due to image inhomogeneity and other factors. Most coronary segmentation algorithms require user interaction for seed point selection, which may lead to erroneous segmentation. In this study, we present an improved technique of seed detection for coronary segmentation using a thresholded Frangi response. Before computing region of interest (ROI), the proposed method first computes the Frangi response of the complete CCTA volume, followed by thresholding with respect to quantile and median values, and then the ROI selection procedure …
A Novel Hybrid Approach Based On A Chaotic Cloud Gravitational Search Algorithm To Complicated Image Template Matching,
2017
TÜBİTAK
A Novel Hybrid Approach Based On A Chaotic Cloud Gravitational Search Algorithm To Complicated Image Template Matching, Weijia Cui, Yuzhu He
Turkish Journal of Electrical Engineering and Computer Sciences
Template matching is the process of accurately extracting the interesting regions in a source image according to reference templates. In this paper, the gravitational search algorithm (GSA) is employed as a novel search strategy for template matching. However, the basic GSA is easily trapped in a local optimum and has a poor exploitation ability. In this paper, to enhance the optimization performance of GSA, a novel cross-search strategy based on chaotic global search (CGS) and cloud local search (CLS) is incorporated into GSA. The new variant is named chaotic cloud GSA (CCGSA). CGS makes full use of the ergodicity of …
A Novel Approach To Solve Transient Stability Constrained Optimal Power Flow Problems,
2017
TÜBİTAK
A Novel Approach To Solve Transient Stability Constrained Optimal Power Flow Problems, Huy Nguyen-Duc, Linh Tran-Hoai, Dieu Vo Ngoc
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes an approach to solve the transient stability constraint optimal power flow (TSC-OPF) problem. The transient stability constraints are expressed as the critical clearing time (CCT) of different contingencies, and are approximated using artificial neural networks (ANNs). The ANNs provide a nonlinear, differentiable mapping between the load flow variables and the CCT. As a result, the TSC-OPF with multiple transient stability constraints can be solved very efficiently with little additional computational burden. The effectiveness of the proposed method is demonstrated with the IEEE 39 bus and the IEEE 300 bus systems.
Low-Power Voltage To A Frequency-Based Smart Temperature Sensor With +0.8/-0.75 $^{\Circ}$C Accuracy For -55 $^{\Circ}$C To 125 $^{\Circ}$C, Mudasir Bashir, Sreehari Rao Patri, Krishna Prasad
Turkish Journal of Electrical Engineering and Computer Sciences
The high power densities in system-on-chips demand accurate, low power, and compact smart temperatures for thermal monitoring. In this paper, a low-power CMOS-based smart temperature sensor, operating in the subthreshold region, for military applications (-55 $^{\circ}$C to 125 $^{\circ}$C) is presented. The sensor exploits the thermal dependency of the threshold voltage of MOS transistors to generate a voltage proportional to absolute temperature ($V_{PTAT})$. A frequency locked loop technique is employed to generate frequency from $V_{PTAT}$. The frequency variation due to temperature is measured by counting the rising edge with an asynchronous 12-bit counter. The large die area and requirement of …
When Machines Decide: Justice.Exe Learning Modules,
2017
University of Utah, Honors College
When Machines Decide: Justice.Exe Learning Modules, Praxis Lab Team
Law School Historical Documents
Learning modules for the Praxis Lab Honors Course
When Machines Decide: Creating Justice.Exe,
2017
University of Utah
When Machines Decide: Creating Justice.Exe, Randy Dryer, Suresh Venkatasubramanian, Austin Anderson, Abigail Busath, Logan Cox, Morgan Cox, Logan Erickson, Zachary Grena, Joseph Hutchins, Skyler Jayson, Andrew Yang
Law School Historical Documents
Our Praxis Lab centered on the increasingly important need for algorithmic literacy, transparency and oversight, particularly in the context of the use of algorithms in the criminal justice system. Accordingly, we (1) designed an educational simulation to illustrate the function of algorithms in the context of criminal sentencing; (2) created several pre-packaged course modules that faculty in a variety of disciplines could integrate into their existing curriculum to educate students about algorithms and their increasing role in modern society; and (3) curated a set of best practices designed to promote the transparency and oversight of algorithmic systems.
Animatronic Kinect Bear,
2017
California Polytechnic State University, San Luis Obispo
Animatronic Kinect Bear, Christopher J. Barth, Luis Manjarrez, Emily Lopez
Computer Engineering
The objective of the project was to build an interactive robotic bear through the application of Computer Engineering related software and hardware concepts. Utilizing the body recognition features of XBos One Kinect, the bera will be able to mimic a user's motions in real time.
Robust Scale-Invariant Normalization And Similarity Measurement For Time Series Data,
2017
Faculty of Engineering
Robust Scale-Invariant Normalization And Similarity Measurement For Time Series Data, Ariyawat Chonbodeechalermroong
Chulalongkorn University Theses and Dissertations (Chula ETD)
Classification is one of the most prevalent tasks in time series mining. Dynamic Time Warping and Longest Common Subsequence are well-known and widely used algorithms to measure similarity between two time series sequences using non-linear alignment. However, these algorithms work best when the time series pair has similar amplitude scaling. Unfortunately, sensor data and most real-world time series data usually contain noise, missing values, outlier, and variability or scaling in both axes, which is not suitable for the widely used Z-normalization. This research introduces the Local Feature Normalization (LFN) and its Local Scaling Feature (LSF), which can be used to …
Emergent Ai, Social Robots And The Law: Security, Privacy And Policy Issues,
2017
Quinnipiac University & Yale Law School
Emergent Ai, Social Robots And The Law: Security, Privacy And Policy Issues, Ramesh Subramanian
Journal of International Technology and Information Management
The rapid growth of AI systems has implications on a wide variety of fields. It can prove to be a boon to disparate fields such as healthcare, education, global logistics and transportation, to name a few. However, these systems will also bring forth far-reaching changes in employment, economy and security. As AI systems gain acceptance and become more commonplace, certain critical questions arise: What are the legal and security ramifications of the use of these new technologies? Who can use them, and under what circumstances? What is the safety of these systems? Should their commercialization be regulated? What are the …
Quantitative Dependability And Interdependency Models For Large-Scale Cyber-Physical Systems,
2017
Missouri University of Science and Technology
Quantitative Dependability And Interdependency Models For Large-Scale Cyber-Physical Systems, Koosha Marashi
Doctoral Dissertations
"Cyber-physical systems link cyber infrastructure with physical processes through an integrated network of physical components, sensors, actuators, and computers that are interconnected by communication links. Modern critical infrastructures such as smart grids, intelligent water distribution networks, and intelligent transportation systems are prominent examples of cyber-physical systems. Developed countries are entirely reliant on these critical infrastructures, hence the need for rigorous assessment of the trustworthiness of these systems. The objective of this research is quantitative modeling of dependability attributes -- including reliability and survivability -- of cyber-physical systems, with domain-specific case studies on smart grids and intelligent water distribution networks. To …
A Dynamic Scaling Methodology For Improving Performance Of Big Data Systems,
2017
South Dakota State University
A Dynamic Scaling Methodology For Improving Performance Of Big Data Systems, Nashmiah Alhamdawi
Electronic Theses and Dissertations
The continuous growth of data volume in various fields such as, healthcare, sciences, economics, and business has caused an overwhelming flow of data in the last decade. The overwhelming flow of data has raised challenges in processing, analyzing, and storing data, which lead many systems to face an issue in performance. Poor performance of systems creates negative impact such as delays, unprocessed data, and increasing response time. Processing huge amounts of data demands a powerful computational infrastructure to ensure that data processing and analysis success [7]. However, the architectures of these systems are not suitable to process that quantity of …
Availability Of Datasets For Digital Forensics–And What Is Missing,
2017
University of New Haven
Availability Of Datasets For Digital Forensics–And What Is Missing, Cinthya Grajeda, Frank Breitinger, Ibrahim Baggili
Electrical & Computer Engineering and Computer Science Faculty Publications
This paper targets two main goals. First, we want to provide an overview of available datasets that can be used by researchers and where to find them. Second, we want to stress the importance of sharing datasets to allow researchers to replicate results and improve the state of the art. To answer the first goal, we analyzed 715 peer-reviewed research articles from 2010 to 2015 with focus and relevance to digital forensics to see what datasets are available and focused on three major aspects: (1) the origin of the dataset (e.g., real world vs. synthetic), (2) if datasets were released …
Can Phishing Education Enable Users To Recognize Phishing Attacks?,
2017
Technological University Dublin
Can Phishing Education Enable Users To Recognize Phishing Attacks?, Hanaa Alghamdi
Dissertations
Phishing attacks have increased rapidly and caused many drastic damages and losses for internet users‟ .The purpose of this research is to investigate on effectiveness of phishing education and training to help users identify different forms of phishing threats. The study has been conducted through developing a phishing quiz mobile application which includes four kinds of phishing threats. It tested the ability of users to recognize spoofed emails, SMS phishing (SMshing), scam phone calls (Vishing), and phishing through social media networks. A comprehensive literature review was discussed to investigate on the research area, understand the research problem, support the proposed …
Evaluating The Effectiveness Of The Gestalt Principles Of Perceptual Observation For Virtual Reality User Interface Design,
2017
Technological University Dublin
Evaluating The Effectiveness Of The Gestalt Principles Of Perceptual Observation For Virtual Reality User Interface Design, William Macnamara
Dissertations
There is a lot of interest and excitement surrounding the areas of Virtual Reality and Head-Mounted Displays with the recent releases of devices such as the Oculus Rift, Sony PSVR and the HTC Vive. While much of the focus for these devices has been related to sectors of the entertainment industries, namely the cinema and video game industries, there are many more practical applications for these technologies, with potential benefits in educational, training/simulation, therapeutic and modelling/design software. Developing a set of reliable guidelines for Virtual Reality User Interface Design could play a crucial role in whether the medium successfully integrates …
Optimized Multilayer Perceptron With Dynamic Learning Rate To Classify Breast Microwave Tomography Image,
2017
South Dakota State University
Optimized Multilayer Perceptron With Dynamic Learning Rate To Classify Breast Microwave Tomography Image, Chulwoo Pack
Electronic Theses and Dissertations
Most recently developed Computer Aided Diagnosis (CAD) systems and their related research is based on medical images that are usually obtained through conventional imaging techniques such as Magnetic Resonance Imaging (MRI), x-ray mammography, and ultrasound. With the development of a new imaging technology called Microwave Tomography Imaging (MTI), it has become inevitable to develop a CAD system that can show promising performance using new format of data. The platform can have a flexibility on its input by adopting Artificial Neural Network (ANN) as a classifier. Among the various phases of CAD system, we have focused on optimizing the classification phase …
The Impact Of Sampling Frequency And Amplitude Modulation Index On Low Order Harmonics In A 3-Phase Sv-Pvm Voltage Source Inverter, Qamil Kabashi, Myzafere Limani, Nebi Caka, Milaim Zabeli
Turkish Journal of Electrical Engineering and Computer Sciences
Nowadays, variable speed AC motors are widely used in industry and there are many speed adjustment techniques available. In the last decade there has been a trend towards the use of space vector PWM--IGBT inverters, due to easier digital realization and better utilization of the DC bus. Every power inverter produces a total harmonic distortion (THD) on its output that causes extra losses in stator of induction motors. By eliminating a number of low order voltage/current harmonics it is possible to reduce harmonic losses (stator losses) and mechanical oscillations in general. This could be achieved by implementing filters in the …
Neville Interpolation-Based Normal Estimation,
2017
TÜBİTAK
Neville Interpolation-Based Normal Estimation, Buse Meli̇s Özyildirim, Ulus Çevi̇k
Turkish Journal of Electrical Engineering and Computer Sciences
Displaying useful and meaningful information from 3D data is known as volume rendering. Ray casting is one of the most frequently used direct volume rendering methods. It consists of data preparation, sampling, classification, compositing, and shading steps. Normal values are needed for efficient shading. However, 3D volumetric data are discrete and cannot be used directly for shading. Hence, the estimation of normal values, at each voxel on the surface, is needed for realistic shading. In normal estimation, the use of small voxel neighborhoods results in the staircase effect. On the other hand, the use of larger voxel neighborhoods causes loss …
A Computer-Based Modification Solution For Old Type Of Electro-Controlled Mechanical Jacquard Looms,
2017
TÜBİTAK
A Computer-Based Modification Solution For Old Type Of Electro-Controlled Mechanical Jacquard Looms, Mahmut Aykaç, Ercan Yildiz, Abdurrahman Oğuz
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, we modified the old type of electro-controlled mechanical Jacquard looms for the carpet weaving industry by substituting a Jacquard controller with a modern computer running software called the "Weaving Control System", which has also been developed in the context of this study. By this modification, the Jacquard controller, which requires expensive electronic components and maintenance, has been discarded, and a contemporary computer-based solution that is easy to control and use, and cheap to install and maintain, has been employed in the place of the Jacquard controller. Even though the proposed solution has been tested on the Schleicher-type …
A 2-D Analytical Model For Cylindrical Gate Tunnel Fet (Cg-Tfet) Based On Center Potential,
2017
TÜBİTAK
A 2-D Analytical Model For Cylindrical Gate Tunnel Fet (Cg-Tfet) Based On Center Potential, Sidhartha Dash, Guru Prasad Mishra
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a 2-D cylindrical gate tunnel FET (CG-TFET) model is developed based on the potential at the center of cylinder. The center potential is obtained by Laplace solution in the cylindrical coordinate system and the accuracy is validated using a 2-D TCAD device simulator. The tunneling of charge carriers in the CG-TFET is analyzed using the center potential and the results are compared to the surface potential-based model. The drain current is formulated using the initial tunneling point and tunneling path, which further helps to obtain the threshold voltage of this model. The effect of gate engineering and …
Full Occlusion Handling For Pedestrian Tracking Via Hybrid System,
2017
TÜBİTAK
Full Occlusion Handling For Pedestrian Tracking Via Hybrid System, Xiaoyu Zhang, Shiqiang Hu, Huanlong Zhang, Xing Hu
Turkish Journal of Electrical Engineering and Computer Sciences
Occlusion and lack of visibility even in sparse crowd scenes make it difficult to track individual pedestrians correctly and consistently, particularly in a single view. We present a novel pedestrian tracking approach that connects tracking with reidentification to locate and maintain the identity of certain people who may be occluded for a long time. First, two models are constructed. One model tracks the pedestrian and trains a classifier, while the other model reidentifies the pedestrian of interest from detection results with the trained classifier. Secondly, we design a set of transition rules for model switching. Finally, the two models work …
