Engineering Commons^™

Fast And De-Noise Support Vector Machine Training Method Based On Fuzzy Clustering Method For Large Real World Datasets, Omid Naghash Almasi, Modjtaba Rouhani

Turkish Journal of Electrical Engineering and Computer Sciences

Classifying large and real-world datasets is a challenging problem in machine learning algorithms. Among the machine learning methods, the support vector machine (SVM) is a well-known approach with high generalization ability. Unfortunately, while the number of training data increases and the data contain noise, the performance of SVM significantly decreases. In this paper, a fast and de-noise two-stage method for training SVMs to deal with large, real-world datasets is proposed. In the first stage, data that contain noises or are suspected to be noisy are identified and eliminated from the genuine training dataset. The process of elimination and identification is …

A New Cmos Zc-Cdta Realization And Its Filter Applications, Ersi̇n Alaybeyoğlu, Hulusi̇ Hakan Kuntman

Turkish Journal of Electrical Engineering and Computer Sciences

The Z copy current differencing transconductance amplifier (ZC-CDTA) is a new current-mode active element that was introduced recently. ZC-CDTA is improved from the current differencing transconductance amplifier (CDTA) and has increased its universality. In the current study, a CMOS implementation of ZC-CDTA is proposed. The first stage of ZC-CDTA consists of a current differencing unit. The output stage consists of a dual output transconductance amplifier. Furthermore, a third-generation current conveyor is used to copy the Z terminal current instead of a classical current mirror. A fourth-order filter application employing ZC-CDTAs is given and simulation results are added. The ZC-CDTA-based filter …

Design And Implementation Of A Man-Overboard Emergency Discovery System Based On Wireless Sensor Networks, Abdullah Sevi̇n, Cüneyt Bayilmiş, İsmai̇l Ertürk, Hüseyi̇n Eki̇z, Ahmet Karaca

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, wireless sensor networks (WSNs) have been widely employed in many different fields such as military, surveillance, health, agricultural, automation, and environmental monitoring. This paper presents a designed and implemented WSN-based man-overboard emergency discovery system, abbreviated as W-MEDS, that discovers the location of a person in emergency circumstances and runs an alarm system on a ship. The developed W-MEDS carries out a fast man-overboard (MOB) discovery and initiates the vital rescue procedure. It mainly consists of a WSN and a control and discovery system. When a MOB accident occurs, this situation is easily detected through the WSN nodes capable of …

Residential Electricity Pricing Using Time-Varying And Non-Time-Varying Scenarios: An Application Of Game Theory, Najme Khaleghifar, Hamid Amadeh, Mohammad Hosein Rezaeian Koochi

Turkish Journal of Electrical Engineering and Computer Sciences

residential consumer and the power network. With the growth of power systems and the advent of new energy sources, such as solar energy, it seems to be more essential to investigate how the network and the consumer can interact with each other to achieve more financial benefits. To do that, a static game is defined considering the fact that there is a direct relationship between the amount of load shifted by the consumer and the incentive offered by the network. It is concluded that the Nash equilibrium of this game is when the consumer decides to cooperate with the network …

A Robust Undervoltage Load Shedding Scheme Against Voltage Instability, Iman Kaffashan, Seyed Mohammad Taghi Mirali Mortezaee, Turaj Amraee

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

Predicting Acute Hypotensive Episode By Using Hybrid Features And A Neuro-Fuzzy Network, Marzieh Abbasinia, Fardad Farokhi, Shahram Javadi

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents an approach for acute hypotensive episode (AHE) time series forecasting based on hybrid feature space and a neuro-fuzzy network. Prediction was accomplished through a combination of time domain and wavelet features by using six vital time series of each patient, obtained from MIMIC-II and available in the context of the Physionet-Computers in Cardiology 2009 Challenge. At first, statistical time domain features were used and then the wavelet coefficient was utilized for extracting time scale features. Further UTA feature selection was applied and 30 effective features were determined and achieved to predict AHE with 96.30 accuracy 1.5 h …

Energy Efficient Multiconstrained Optimization Using Hybrid Aco And Ga In Manet Routing, Nivetha Senthil Kumaran, Asokan Ramasamy

Turkish Journal of Electrical Engineering and Computer Sciences

Nodes in mobile ad hoc networks (MANET) suffer from limited battery power and bandwidth. Particularly for real time multimedia communications through MANET, metrics like residual node energy, bandwidth, and end-to-end delay have major impacts. In MANET, designing a dynamic routing algorithm to satisfy quality of service (QoS) requirements is a challenging task. Additionally, multiconstrained QoS routing aims to optimize multiple QoS metrics while providing required network resources and is an admittedly complex problem. It has been proved to be NP-complete when a combination of additive, concave, and multiplicative metrics are considered. Hence, this problem can be solved using metaheuristic methods …

A Centralized Self-Adaptive Fault Tolerance Approach Based On Feedback Control For Multiagent Systems, Şebnem Bora, Oğuz Di̇kenelli̇

Turkish Journal of Electrical Engineering and Computer Sciences

Our research introduces a self-adaptive fault tolerance approach for multiagent systems that enables the system to avoid crash failures. It is a replication-based approach that exploits a feedback control loop and a proportional (P) controller within a replication infrastructure. Thus, we are able to both observe the agents' behaviors to estimate criticalities and determine the number of replicas in replica groups with respect to the agents' criticalities and the number of available resources. Thus, agents that are to be replicated and the numbers of replicas in replica groups are automatically and adaptively identified in dynamic environments. We implement this approach …

Exploring Deviant Hacker Networks (Dhm) On Social Media Platforms, Samer Al-Khateeb, Kevin J. Conlan, Nitin Agarwal, Ibrahim Baggili, Frank Breitinger

Journal of Digital Forensics, Security and Law

Online Social Networks (OSNs) have grown exponentially over the past decade. The initial use of social media for benign purposes (e.g., to socialize with friends, browse pictures and photographs, and communicate with family members overseas) has now transitioned to include malicious activities (e.g., cybercrime, cyberterrorism, and cyberwarfare). These nefarious uses of OSNs poses a significant threat to society, and thus requires research attention. In this exploratory work, we study activities of one deviant groups: hacker groups on social media, which we term Deviant Hacker Networks (DHN). We investigated the connection between different DHNs on Twitter: how they are connected, identified …

Cardiovascular Dieseases: From Data Generation To Analysis, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

Cardiovascular diseases remain the leading cause of death in Western societies. This presentation will provide insight into the use of expert knowledge and models to derive diagnostic tools that have the potential to aid in the diagnosis of diffuse cardiovascular diseases that tend to be more difficult to detect in CT angiograms. In order to develop these methods more basic research is needed to prove the validity of the approach, including validation of accuracy as well as approach itself. For that, specimens of porcine hearts were prepared and then analyzed followed by a statistical comparison between computed and optical measurements. …

A Semi-Automated Computer Program For Assessment Of Skeletal Maturity In Children, Sara Gharabaghi, Thomas Wischgoll

Computer Science and Engineering Faculty Publications

In pediatric patients, skeletal maturity is an important tool for detection of hormonal, growth or genetic disorders. The Fels method is a well-known visual assessment method in which the skeletal age is estimated by grading 98 skeletal indicators in the hand-wrist radiographic (x-ray) image. These indicators are features that reflect the three-dimensional shape of the bones and change during the maturation process. Generally, the Fels indicators could be categorized into three main groups of the status of ossification, the ratios of bone widths, and epiphysealdiaphyseal fusion.

Personalized And Adaptive Semantic Information Filtering For Social Media, Pavan Kapanipathi

Browse all Theses and Dissertations

Social media has experienced immense growth in recent times. These platforms are becoming increasingly common for information seeking and consumption, and as part of its growing popularity, information overload pose a significant challenge to users. For instance, Twitter alone generates around 500 million tweets per day and it is impractical for users to have to parse through such an enormous stream to find information that are interesting to them. This situation necessitates efficient personalized filtering mechanisms for users to consume relevant, interesting information from social media. Building a personalized filtering system involves understanding users' interests and utilizing these interests to …

Detecting Php-Based Cross-Site Scripting Vulnerabilities Using Static Program Analysis, Steven M. Kelbley

Browse all Theses and Dissertations

With the widespread adoption of dynamic web applications in recent years, a number of threats to the security of these applications have emerged as significant challenges for application developers. The security of developed applications has become a higher priority for both developers and their employers as cyber attacks become increasingly more prevalent and damaging. Some of the most used web application frameworks are written in PHP and have become major targets due to the large number of servers running these applications worldwide. A number of tools exist to evaluate PHP code for issues, however most of these applications are not …

Miniatured Inertial Motion And Position Tracking And Visualization Systems Using Android Wear Platform, Dhruvkumar Navinchandra Patel

Browse all Theses and Dissertations

In this thesis, we have designed and developed a motion tracking and visualization system using the latest motion tracking sensory technologies. It is one of the enabling technologies for our novel visual-inertial odometer and human anatomy based 3D Locating, Mapping and Navigation system for endoscopy and drug delivery capsules used inside GI tract. In particular, we have: i) designed and completed a cloud-based sensory data collecting, processing and storage system to provide the reliable computing and storage platform; ii) explored different data processing methods to obtain improved-quality motion results from extremely noisy raw data, e.g., by using a low pass …

Positioning Commuters And Shoppers Through Sensing And Correlation, Rufeng Meng

Theses and Dissertations

Positioning is a basic and important need in many scenarios of human daily activities. With position information, multifarious services could be vitalized to benefit all kinds of users, from individuals to organizations. Through positioning, people are able to obtain not only geo-location but also time related information. By aggregating position information from individuals, organizations could derive statistical knowledge about group behaviors, such as traffic, business, event, etc.

Although enormous effort has been invested in positioning related academic and industrial work, there are still many holes to be filled. This dissertation proposes solutions to address the need of positioning in people’s …

Revealing Malicious Contents Hidden In The Internet, Muhammad Nazmus Sakib

Theses and Dissertations

In this age of ubiquitous communication in which we can stay constantly connected with the rest of the world, for most of the part, we have to be grateful for one particular invention - the Internet. But as the popularity of Internet connectivity grows, it has become a very dangerous place where objects of malicious content and intent can be hidden in plain sight. In this dissertation, we investigate different ways to detect and capture these malicious contents hidden in the Internet. First, we propose an automated system that mimics high-risk browsing activities such as clicking on suspicious online ads, …

Hydro-Geological Flow Analysis Using Hidden Markov Models, Chandrahas Raj Venkat Gurram

Theses and Dissertations

Hidden Markov Models a class of statistical models used in various disciplines for understanding speech, finding different types of genes responsible for cancer and much more. In this thesis, Hidden Markov Models are used to obtain hidden states that can correlate the flow changes in the Wakulla Spring Cave. Sensors installed in the tunnels of Wakulla Spring Cave have recorded huge correlated changes in the water flows at numerous tunnels. Assuming the correlated flow changes are a consequence of system being in a set of discrete states, a Hidden Markov Model is calculated. This model comprising all the sensors installed …

Regular Expression Synthesis For Blast Two-Hit Filtering, Jordan Bradshaw

Theses and Dissertations

Genomic databases are exhibiting a growth rate that is outpacing Moore's Law, which has made database search algorithms a popular application for use on emerging processor technologies. NCBI BLAST is the standard tool for performing searches against these databases, which operates by transforming each database query into a filter that is subsequently applied to the database. This requires a database scan for every query, fundamentally limiting its performance by I/O bandwidth. In this dissertation we present a functionally-equivalent variation on the NCBI BLAST algorithm that maps more suitably to an FPGA implementation. This variation of the algorithm attempts to reduce …

Computational Doping For Fuel Cell Material Design Based On Genetic Algorithms And Genetic Programming, Emrah Atilgan

Theses and Dissertations

Developing new materials have historically been time-consuming. Computational material discovery can search large design space to identify promising candidates for experimental verification. Recently, Density Functional Theory (DFT) based first principle calculation has been able to calculate many electrical and physical properties of materials, making them suitable for computational doping based material discovery. In material doping, given a base material, one can change its properties by substituting some elements with new ones or adding additional elements. In computational doping, we have a grid of atoms in a supercell, some of which can be substituted with dopant atoms. There are many possible …

Learning Human Poses From Monocular Images, Xiaochuan Fan

Theses and Dissertations

In this research, we mainly focus on the problem of estimating the 2D human pose from a monocular image and reconstructing the 3D human pose based on the 2D human pose. Here a 3D pose is the locations of the human joints in the 3D space and a 2D pose is the projection of a 3D pose on an image. Unlike many previous works that explicitly use hand-crafted physiological models, both our 2D pose estimation and 3D pose reconstruction approaches implicitly learn the structure of human body from human pose data.

This 3D pose reconstruction is an ill-posed problem without …

Ontology-Driven Integration Of Data For Freight Performance Measures, Eduardo J. Torres

Open Access Theses & Dissertations

Transportation performance measures are defined as quantitative and qualitative indicators that rely on data or information to explain mobility, congestion, safety, environmental and other factors. Though performance measures have been used for freeways and other highways, not many have been specified and applied to the freight transportation system. Recently, freight performance measures have been recommended by Federal Highway Administration to quantify the operating efficiency of the freight transportation system on existing infrastructures. This research seeks to expand this concept and to develop a comprehensive freight performance measurement framework. The expanded framework recommended in this Thesis consists of four criteria: safety, …

Emerging Adaptive Architectures For Biomolecular Computation, Matthew Fleetwood

Maseeh Summer Undergraduate Research Experience

The goal of this work is to explore applications of reservoir computing in biomolecular computation. Reservoir computing is a unique model for representing a mapping from one instance in time to a specific output. A neural network of randomly connected neurons is linked with a single output neuron or multiple output neurons. The output neurons are capable of mapping inputs to desired outputs using adaptable algorithms. This framework is investigated by using the Python programming language and object oriented design and programming. Neurons are created in programs by bundling information like input data and attributes of the network, which utilize …

3d Fpga Cell Matrix By Self-Assembly, Jeffrey Udall

Maseeh Summer Undergraduate Research Experience

Physical size limitations in miniaturizing two-dimensional (2D) transistors are becoming more difficult to overcome. In order to continue increasing the processing power of electronic circuits, new design paradigms are needed. Three-dimensional (3D) architectures provide a solution to this issue and are currently being implemented via wafer stacking. However, more significant gains in terms of packing and speed can be achieved by CMOS components with truly integrated 3D cellular architectures. One of these is the Cell Matrix, a self-configurable defect- and fault-tolerant architecture, which is ideally suited for ultra large-scale integration. For this project, we worked to expand the Cell Matrix …

Detecting And Tracing Slow Attacks On Mobile Phone User Service, Brian Cusack, Zhuang Tian

Australian Digital Forensics Conference

The lower bandwidth of mobile devices has until recently filtered the range of attacks on the Internet. However, recent research shows that DOS and DDOS attacks, worms and viruses, and a whole range of social engineering attacks are impacting on broadband smartphone users. In our research we have developed a metric-based system to detect the traditional slow attacks that can be effective using limited resources, and then employed combinations of Internet trace back techniques to identify sources of attacks. Our research question asked: What defence mechanisms are effective? We critically evaluate the available literature to appraise the current state of …

The Proceedings Of 14th Australian Digital Forensics Conference, 5-6 December 2016, Edith Cowan University, Perth, Australia, Craig Valli

Australian Digital Forensics Conference

Conference Foreword

This is the fifth year that the Australian Digital Forensics Conference has been held under the banner of the Security Research Institute, which is in part due to the success of the security conference program at ECU. As with previous years, the conference continues to see a quality papers with a number from local and international authors. 11 papers were submitted and following a double blind peer review process, 8 were accepted for final presentation and publication. Conferences such as these are simply not possible without willing volunteers who follow through with the commitment they have initially made, …

Breast Cancer Classification Of Mammographic Masses Using Circularity Max Metric, A New Method, Tae Keun Heo

Electronic Theses and Dissertations

Breast cancer classification can be divided into two categories. The first category is a benign tumor, and the other is a malignant tumor. The main purpose of breast cancer classification is to classify abnormalities into benign or malignant classes and thus help physicians with further analysis by minimizing potential errors that can be made by fatigued or inexperienced physicians. This paper proposes a new shape metric based on the area ratio of a circle to classify mammographic images into benign and malignant class. Support Vector Machine is used as a machine learning tool for training and classification purposes. The improved …

Hpc Enabled Data Analytics For High-Throughput High-Content Cellular Analysis, Ross A. Smith, Rhonda J. Vickery, Jack Harris, Sara Gharabaghi, Thomas Wischgoll, David Short, Robert Trevino, Steven A. Kawamoto, Thomas J. Lamkin, Kevin Schoen, Eric E. Bardes, Scott C. Tabar, Bruce J. Aronow

Computer Science and Engineering Faculty Publications

Biologists doing high-throughput high-content cellular analysis are generally not computer scientists or high performance computing (HPC) experts, and they want their workflow to support their science without having to be. We describe a new HPC enabled data analytics workflow with a web interface, HPC pipeline for analysis, and both traditional and new analytics tools to help them transition from a single workstation mode of operation to power HPC users. This allows the processing of multiple plates over a short period of time to ensure timely query and analysis to match potential countermeasures to individual responses.

An Efficient Hybrid Eye Detection Method, Mingxin Yu, Yingzi Lin, Xiangzhou Wang

Turkish Journal of Electrical Engineering and Computer Sciences

Eye detection is the most important and critical task of diverse applications such as face detection and recognition. However, most eye detection methods do not fully consider detection robustness to people with glasses, illumination variation, head pose change, and eye occlusions. This paper proposes an efficient hybrid eye detection method based on a gray intensity variance filter (VF) and support vector machines (SVMs). Firstly, the VF is used for eliminating most of noneye region images to keep less candidate eye regions. Then accurate two eye regions are determined easily through the trained SVM classifier. Moreover, this paper provides an assessment …

Distributed Rule-Based Ontology Reasoning, Raghava Mutharaju

Browse all Theses and Dissertations

The vision of the Semantic Web is to provide structure and meaning to the data on the Web. Knowledge representation and reasoning play a crucial role in accomplishing this vision. OWL (Web Ontology Language), a W3C standard, is used for representing knowledge. Reasoning over the ontologies is used to derive logical consequences. A fixed set of rules are run on an ontology iteratively until no new logical consequences can be derived. All existing reasoners run on a single machine, possibly using multiple cores. Ontologies (sometimes loosely referred to as knowledge bases) that are automatically constructed can be very large. Single …

Customizable 3-D Virtual Gi Tract Systems For Locating, Mapping, And Navigation Inside Human Gastrointestinal Tract, Megha Dattatrey Dalvi

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One of the critical challenges of wireless capsule endoscopy examination is to find the exact position of the capsule in the Gastrointestinal Tract (GI) tract so as to correctly and accurately spot the position of the intestinal diseases. Creating a 3D virtual GI tract system could significantly improve the capsule endoscopy operations. The virtual human model, such as the BioDigital Human, has been credited as Google Earth for the human body, which provides us medically accurate virtual body and organ structures. However, it only assembles a “Standard” human body. The problem is: there is only one earth, but billions of …