Engineering Commons^™

An Event-Driven Wsn Mac Protocol Design Based On Active Node And Dynamic Time Slot Allocation, Nükhet Sazak, İsmai̇l Ertürk, Etem Köklükaya, Murat Çakiroğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The unique features of wireless sensor networks (WSNs) make them suitable for a wide range of applications in many different areas. However, with many of the protocols and algorithms used in traditional wireless networks, it is usually neither feasible nor possible to apply them directly to WSNs due to the strict resource constraints of tiny sensor nodes. Moreover, application-specific approaches for communication protocols are usually imposed since WSN applications have distinct requirements. In this study, event-driven WSN applications, where a number of sensor nodes are randomly and densely deployed in remote and difficult to reach locations, are targeted. In such …

On-Line Self-Learning Pid Controller Design Of Sssc Using Self-Recurrent Wavelet Neural Networks, Soheil Ganjefar, Mojtaba Alizadeh

Turkish Journal of Electrical Engineering and Computer Sciences

Conventionally, FACTS devices employ a proportional-integral (PI) controller as a supplementary controller. However, the conventional PI controller has many disadvantages. The present paper aims to propose an on-line self-learning PI-derivative (PID) controller design of a static synchronous series compensator for power system stability enhancement and to overcome the PI controller problems. Unlike the PI controllers, the proposed PID controller has a local nature because of its powerful adaption process, which is based on the back-propagation (BP) algorithm that is carried out through an adaptive self-recurrent wavelet neural network identifier (ASRWNNI). In fact, the PID controller parameters are updated in on-line …

Feature-Based Fault Detection Of Industrial Gas Turbines Using Neural Networks, Abbas Rasaienia, Behzad Moshiri, Mohammadamin Moezzi

Turkish Journal of Electrical Engineering and Computer Sciences

Gas turbine (GT) fault detection plays a vital role in the minimization of power plant operation costs associated with power plant overhaul time intervals. In other words, it is helpful in generating pre-alarms and paves the way for corrective actions in due time before incurring major equipment failures. Hence, finding an efficient fault detection technique that is applicable in the online operation of power plants involved with minor computations is an urgent need in the power generation industry. Such a method is studied in this paper for the V94.2 class of GTs. As the most leading stage for developing a …

Optimized Features Selection For Gender Classification Using Optimization Algorithms, Sajid Ali Khan, Muhammad Nazir, Naveed Riaz

Turkish Journal of Electrical Engineering and Computer Sciences

Optimized feature selection is an important task in gender classification. The optimized features not only reduce the dimensions, but also reduce the error rate. In this paper, we have proposed a technique for the extraction of facial features using both appearance-based and geometric-based feature extraction methods. The extracted features are then optimized using particle swarm optimization (PSO) and the bee algorithm. The geometric-based features are optimized by PSO with ensemble classifier optimization by the genetic algorithm. Using this approach, we have obtained promising results in terms of the classification error rate and computation time minimization. Moreover, our optimized feature-based method …

A New Tool For Qt Interval Analysis During Sleep In Healthy And Obstructive Sleep Apnea Subjects: A Study On Women, Kemal Ali̇can Kaya, Bülent Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

By monitoring the Q wave/T wave (QT) interval computed from electrocardiography (ECG) signals during sleep, it is possible to create a link between the ventricular repolarization and sleep stages. In this study, we aimed to find a robust and simple approach to automatically determine the fiducials on each 30-s sleep epoch, such as the Q, R, and T-end points, on long sleep ECG recordings in order to statistically analyze the effect of obstructive sleep apnea (OSA) and sleep stages on QT intervals. This is a retrospective study in which the ECG data extracted from the polysomnography recordings of 7 healthy …

Gpu-Optimized Code For Long-Term Simulations Of Beam-Beam Effects In Colliders, Y. Roblin, V. Morozov, B. Terzić, M. Aturban, D. Ranjan, M. Zubair

Computer Science Faculty Publications

We report on the development of the new code for long-term simulation of beam-beam effects in particle colliders. The underlying physical model relies on a matrix-based arbitrary-order symplectic particle tracking for beam transport and the Bassetti-Erskine approximation for beam-beam interaction. The computations are accelerated through a parallel implementation on a hybrid GPU/CPU platform. With the new code, a previously computationally prohibitive long-term simulations become tractable. We use the new code to model the proposed medium-energy electron-ion collider (MEIC) at Jefferson Lab.

3d Grain Segmentation In Superalloy Images Using Multichannel Edge-Weighted Centroidal Voronoi Tessellation Based Methods, Yu Cao

Theses and Dissertations

Accurate grain segmentation on 3D superalloy images is very important in materials science and engineering. From grain segmentation, we can derive the underlying superalloy grains' micro-structures, based on which many important physical, mechanical and chemical properties of the superalloy samples can be evaluated. However, grain segmentation is usually a very challenging problem since: 1) even a small 3D superalloy sample may contain hundreds of grains; 2) carbides and noises may degrade the imaging quality; and 3) the intensity within a grain may not be homogeneous. In addition, the same grain may present different appearances, i.e. intensities, under different microscope settings. …

Accelerating Short Read Mapping Using A Dsp Based Coprocessor, Shaun I. Gause

Theses and Dissertations

Advances in next generation sequencing technologies have allowed short reads to be generated at an increasing rate, shifting the bottleneck of the sequencing process to the short read mapping computations. High costs and extended processing times drive researchers to pursue more efficient solutions with an overall goal of a short read mapping architecture capable of processing short reads as they are generated. Digital signal processors have shown high performance capabilities while maintaining low power consumption in a wide field of applications. This thesis explores the use of a DSP accelerated exact match short read mapping algorithm, focusing on a performance …

Plc Code Vulnerabilities Through Scada Systems, Sidney E. Valentine, Jr.

Theses and Dissertations

Supervisory Control and Data Acquisition (SCADA) systems are widely used in automated manufacturing and in all areas of our nation's infrastructure. Applications range from chemical processes and water treatment facilities to oil and gas production and electric power generation and distribution. Current research on SCADA system security focuses on the primary SCADA components and targets network centric attacks. Security risks via attacks against the peripheral devices such as the Programmable Logic Controllers (PLCs) have not been sufficiently addressed.

Our research results address the need to develop PLC applications that are correct, safe and secure. This research provides an analysis of …

Anomalies In Sensor Network Deployments: Analysis, Modeling, And Detection, Giovani Rimon Abuaitah

Browse all Theses and Dissertations

A sensor network serves as a vital source for collecting raw sensory data. Sensor data are later processed, analyzed, visualized, and reasoned over with the help of several decision making tools. A decision making process can be disastrously misled by a small portion of anomalous sensor readings. Therefore, there has been a vast demand for mechanisms that identify and then eliminate such anomalies in order to ensure the quality, integrity, and/or trustworthiness of the raw sensory data before they can even be interpreted.

Prior to identifying anomalies, it is essential to understand the various anomalous behaviors prevalent in a sensor …

Cooperative Interactive Distributed Guidance On Mobile Devices, Gregory Burnett

Browse all Theses and Dissertations

Mobiles device are quickly becoming an indispensable part of our society. Equipped with numerous communication capabilities, they are increasingly being examined as potential tools for civilian and military usage to aide in distributed remote collaboration for dynamic decision making and physical task completion. With an ever growing mobile workforce, the need for remote assistance in aiding field workers who are confronted with situations outside their expertise certainly increases. Enhanced capabilities in using mobile devices could significantly improve numerous components of a task's completion (i.e. accuracy, timing, etc.). This dissertation considers the design of mobile implementation of technology and communication capabilities …

Accelprint:Accelerometers Are Different By Birth, Sanorita Dey

Theses and Dissertations

This paper submits a hypothesis that smartphone accelerometers possess unique fingerprints. We believe that the fingerprints arise from hardware imperfections during the sensor manufacturing process, causing every sensor chip to respond differently to the same motion stimulus. The differences in responses are subtle enough that they do not affect most of the higher level functions computed on them. Nonetheless, upon close inspection, these fingerprints emerge with consistency, and can even be somewhat independent of the stimulus that generates them. Measurements and classification on 80 standalone accelerometer chips, 25 Android phones, and 2 tablets, show precision and recall upward of 96%, …

Multi-Label Segmentation Propagation For Materials Science Images Incorporating Topology And Interactivity, Jarrell Waggoner

Theses and Dissertations

Segmentation propagation is the problem of transferring the segmentation of an image to a neighboring image in a sequence. This problem is of particular importance to materials science, where the accurate segmentation of a series of 2D serial-sectioned images of multiple, contiguous 3D structures has important applications. Such structures may have prior-known shape, appearance, and/or topology among the underlying structures which can be considered to improve segmentation accuracy. For example, some materials images may have structures with a specific shape or appearance in each serial section slice, which only changes minimally from slice to slice; and some materials may exhibit …

Natural Language Document And Event Association Using Stochastic Petri Net Modeling, Michael Thomas Mills

Browse all Theses and Dissertations

The purpose of this research is to design and implement a new methodology that captures the natural language understanding of events from English natural language text and model it using Stochastic Petri Nets. To establish a baseline of recent natural language processing (NLP) and understanding (NLU) research, two surveys are presented. One is a general survey in NLP and NLU methodologies for processing multi-documents. It summarizes and presents methodologies in terms of their features, capabilities, and maturity. The second survey focuses on graph-based methods for NL text processing and understanding and analyzes them in terms of their functional descriptions, capabilities …

A Large Scale Distributed Syntactic, Semantic And Lexical Language Model For Machine Translation, Ming Tan

Browse all Theses and Dissertations

The n-gram model is the most widely used language model (LM) in statistical machine translation system, due to its simplicity and scalability. However, it only encodes the local lexical relation between adjacent words and clearly ignores the rich syntactic and semantic structures of the natural languages. Attempting to increase the order of an n-gram to describe longer range dependencies in natural language immediately runs into the curse of dimensionality. Although previous researches tried to increase the order of n-gram on a large corpus, they did not see obvious improvement beyond 6-gram. Meanwhile, other LMs, such as syntactic language models and …

A Methodology For Extracting Human Bodies From Still Images, Athanasios Tsitsoulis

Browse all Theses and Dissertations

Monitoring and surveillance of humans is one of the most prominent applications of today and it is expected to be part of many future aspects of our life, for safety reasons, assisted living and many others. Many efforts have been made towards automatic and robust solutions, but the general problem is very challenging and remains still open. In this PhD dissertation we examine the problem from many perspectives. First, we study the performance of a hardware architecture designed for large-scale surveillance systems. Then, we focus on the general problem of human activity recognition, present an extensive survey of methodologies that …

Adaptive Semantic Annotation Of Entity And Concept Mentions In Text, Pablo N. Mendes

Browse all Theses and Dissertations

The recent years have seen an increase in interest for knowledge repositories that are useful across applications, in contrast to the creation of ad hoc or application-specific databases.

These knowledge repositories figure as a central provider of unambiguous identifiers and semantic relationships between entities. As such, these shared entity descriptions serve as a common vocabulary to exchange and organize information in different formats and for different purposes. Therefore, there has been remarkable interest in systems that are able to automatically tag textual documents with identifiers from shared knowledge repositories so that the content in those documents is described in a …

Performance Evaluation And Comparison Of Distributed Messaging Using Message Oriented Middleware, Naveen Mupparaju

UNF Graduate Theses and Dissertations

Message Oriented Middleware (MOM) is an enabling technology for modern event- driven applications that are typically based on publish/subscribe communication [Eugster03]. Enterprises typically contain hundreds of applications operating in environments with diverse databases and operating systems. Integration of these applications is required to coordinate the business process. Unfortunately, this is no easy task. Enterprise Integration, according to Brosey et al. (2001), "aims to connect and combines people, processes, systems, and technologies to ensure that the right people and the right processes have the right information and the right resources at the right time"[Brosey01]. Communication between different applications can be achieved …

Decision Support For Assorted Populations In Uncertain And Congested Environments, Pradeep Reddy Varakantham, Asrar Ahmed, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

This research is motivated by large scale problems in urban transportation and labor mobility where there is congestion for resources and uncertainty in movement. In such domains, even though the individual agents do not have an identity of their own and do not explicitly interact with other agents, they effect other agents. While there has been much research in handling such implicit effects, it has primarily assumed deterministic movements of agents. We address the issue of decision support for individual agents that are identical and have involuntary movements in dynamic environments. For instance, in a taxi fleet serving a city, …

Automated Parameter Tuning Framework For Heterogeneous And Large Instances: Case Study In Quadratic Assignment Problem, Linda Lindawati, Zhi Yuan, Hoong Chuin Lau, Feida Zhu

Research Collection School Of Computing and Information Systems

This paper is concerned with automated tuning of parameters of algorithms to handle heterogeneous and large instances. We propose an automated parameter tuning framework with the capability to provide instance-specific parameter configurations. We report preliminary results on the Quadratic Assignment Problem (QAP) and show that our framework provides a significant improvement on solutions qualities with much smaller tuning computational time.

Accelerated Data Delivery Architecture, Michael L. Grecol

Electronic Theses and Dissertations

This paper introduces the Accelerated Data Delivery Architecture (ADDA). ADDA establishes a framework to distribute transactional data and control consistency to achieve fast access to data, distributed scalability and non-blocking concurrency control by using a clean declarative interface. It is designed to be used with web-based business applications. This framework uses a combination of traditional Relational Database Management System (RDBMS) combined with a distributed Not Only SQL (NoSQL) database and a browser-based database. It uses a single physical and conceptual database schema designed for a standard RDBMS driven application. The design allows the architect to assign consistency levels to entities …

Automatic Detection Of Abnormal Behavior In Computing Systems, James Frank Roberts

Theses and Dissertations--Computer Science

I present RAACD, a software suite that detects misbehaving computers in large computing systems and presents information about those machines to the system administrator. I build this system using preexisting anomaly detection techniques. I evaluate my methods using simple synthesized data, real data containing coerced abnormal behavior, and real data containing naturally occurring abnormal behavior. I find that the system adequately detects abnormal behavior and significantly reduces the amount of uninteresting computer health data presented to a system administrator.

A Robust Rgb-D Slam System For 3d Environment With Planar Surfaces, Po-Chang Su

Theses and Dissertations--Electrical and Computer Engineering

Simultaneous localization and mapping is the technique to construct a 3D map of unknown environment. With the increasing popularity of RGB-depth (RGB-D) sensors such as the Microsoft Kinect, there have been much research on capturing and reconstructing 3D environments using a movable RGB-D sensor. The key process behind these kinds of simultaneous location and mapping (SLAM) systems is the iterative closest point or ICP algorithm, which is an iterative algorithm that can estimate the rigid movement of the camera based on the captured 3D point clouds. While ICP is a well-studied algorithm, it is problematic when it is used in …

Decision Diagrams And Dynamic Programming, John Hooker

John Hooker

No abstract provided.

Probabilistic Verification Of Coordinated Multi-Robot Missions, Sagar Chaki, Joseph Giampapa

Sagar J Chaki

Robots are increasingly used to perform a wide variety of tasks, especially those involving dangerous or inaccessible locations. As the complexity of such tasks grow, robots are being deployed in teams, with complex coordination schemes aimed at maximizing the chance of mission success. Such teams operate under inherently uncertain conditions -- the robots themselves fail, and have to continuously adapt to changing environmental conditions. A key challenge facing robotic mission designers is therefore to construct a mission -- i.e., specify number and type of robots, number and size of teams, coordination and planning mechanisms etc. -- so as to maximize …

Mixed Integer Programming Vs Logic-Based Benders Decomposition For Planning And Scheduling, John Hooker, Andre Cire

John Hooker

No abstract provided.

Location And Tracking Of Mobile Devices: Überveillance Stalks The Streets, Katina Michael, Roger Clarke

Professor Katina Michael

During the last decade, location-tracking and monitoring applications have proliferated, in mobile cellular and wireless data networks, and through self-reporting by applications running in smartphones that are equipped with onboard global positioning system (GPS) chipsets. It is now possible to locate a smartphone-user's location not merely to a cell, but to a small area within it. Innovators have been quick to capitalise on these location-based technologies for commercial purposes, and have gained access to a great deal of sensitive personal data in the process. In addition, law enforcement utilise these technologies, can do so inexpensively and hence can track many …

Towards A Conceptual Model Of User Acceptance Of Location-Based Emergency Services, Anas Aloudat, Katina Michael

Professor Katina Michael

This paper investigates the introduction of location-based services by government as part of an all-hazards approach to modern emergency management solutions. Its main contribution is in exploring the determinants of an individual’s acceptance or rejection of location services. The authors put forward a conceptual model to better predict why an individual would accept or reject such services, especially with respect to emergencies. While it may be posited by government agencies that individuals would unanimously wish to accept life-saving and life-sustaining location services for their well-being, this view remains untested. The theorised determinants include: visibility of the service solution, perceived service …

The Future Prospects Of Embedded Microchips In Humans As Unique Identifiers: The Risks Versus The Rewards, Katina Michael, M.G. Michael

Professor Katina Michael

Microchip implants for humans are not new. Placing heart pacemakers in humans for prosthesis is now considered a straightforward procedure. In more recent times we have begun to use brain pacemakers for therapeutic purposes to combat illnesses such as epilepsy, Parkinson’s Disease, and severe depression. Microchips are even being placed inside prosthetic knees and hips during restorative procedures to help in the gathering of post-operative analytics that can aid rehabilitation further. While medical innovations that utilise microchips abound, over the last decade we have begun to see the potential use of microchip implants for non-medical devices in humans, namely for …

Determination Of Kinetic Parameters From The Thermogravimetric Data Set Of Biomass Samples, Karol Postawa, Wojciech M. Budzianowski

Wojciech Budzianowski

This article describes methods of the determination of kinetic parameters from the thermogravimetric data set of biomass samples. It presents the methodology of the research, description of the needed equipment, and the method of analysis of thermogravimetric data. It describes both methodology of obtaining quantitative data such as kinetic parameters as well as of obtaining qualitative data like the composition of biomass. The study is focused mainly on plant biomass because it is easy in harvesting and preparation. Methodology is shown on the sample containing corn stover which is subsequently pyrolysed. The investigated sample show the kinetic of first order …