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Adaptive Control Of A Time-Varying Rotary Servo System Using A Fuzzy Model Reference Learning Controller With Variable Adaptation Gain, Ömer Aydoğdu, Özdemi̇r Alkan

Turkish Journal of Electrical Engineering and Computer Sciences

The constant parameters in a conventional fuzzy controller lead to a poor performance for time-varying systems. In this study, a fuzzy model reference learning controller (FMRLC) with a newly defined variable adaptation gain is designed and implemented in the adaptive fuzzy control of a time-varying rotary servo (TVRS) system. In the design of the FMRLC, a knowledge-base modification algorithm with variable adaptation gain is used instead of a fuzzy relation table. Hence, it is provided that the learning and adaptation mechanism continuously updates the knowledge base of the adaptive fuzzy controller against any parameter variations, such as changing loads. By …

A Video-Based Eye Pupil Detection System For Diagnosing Bipolar Disorder, Gökay Akinci, Edi̇z Polat, Orhan Murat Koçak

Turkish Journal of Electrical Engineering and Computer Sciences

Eye pupil detection systems have become increasingly popular in image processing and computer vision applications in medical systems. In this study, a video-based eye pupil detection system is developed for diagnosing bipolar disorder. Bipolar disorder is a condition in which people experience changes in cognitive processes and abilities, including reduced attentional and executive capabilities and impaired memory. In order to detect these abnormal behaviors, a number of neuropsychological tests are also designed to measure attentional and executive abilities. The system acquires the position and radius information of eye pupils in video sequences using an active contour snake model with an …

A New Digital Image Steganography Algorithm Based On Visible Wavelength, İbrahi̇m Coşkun, Feyzi̇ Akar, Özdemi̇r Çeti̇n

Turkish Journal of Electrical Engineering and Computer Sciences

Stenography is the science that ensures secret communication through multimedia carriers such as image, audio, and video files. The ultimate end of stenography is to hide the secret data in the carrier file so that they are not detected. To that end, stenography applications should have such features as undetectability; robustness; resistance to various images process, sing methods, and compression; and capacity of the hidden data. At the same time, those features distinguish stenography applications from watermarking and cryptography applications. This study is different from other studies in the literature in that the undetectability parameter has been achieved through hiding …

Actor-Critic-Based Ink Drop Spread As An Intelligent Controller, Hesam Sagha, Iman Esmaili Paeen Afrakoti, Saeed Bagherishouraki

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces an innovative adaptive controller based on the actor-critic method. The proposed approach employs the ink drop spread (IDS) method as its main engine. The IDS method is a new trend in soft-computing approaches that is a universal fuzzy modeling technique and has been also used as a supervised controller. Its process is very similar to the processing system of the human brain. The proposed actor-critic method uses an IDS structure as an actor and a 2-dimensional plane, representing control variable states, as a critic that estimates the lifetime goodness of each state. This method is fast, simple, …

Implementation Of An Ac Model For Transmission Expansion Planning Considering Reliability Constraints, Amin Mahmoudabad, Masoud Rashidinejad, Majid Zeinaddini-Meymand, Mohsen Rahmani

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a hybrid heuristic methodology that employs fuzzy logic for solving the AC transmission network expansion planning (AC-TEP) problem is presented. An enhanced constructive heuristic algorithm aimed at obtaining a significant quality solution for such complicated problems considering contingency is proposed. In order to indicate the severity of the contingency, 2 performance indices, namely the line flow performance index and voltage performance index, are calculated. An interior point method is applied as a nonlinear programming solver to handle such nonconvex optimization problems, while the objective function includes the costs of the new transmission lines as well as the …

Shape Control Of Cyclic Networks In Multirobot Formations, Tolga Eren

Turkish Journal of Electrical Engineering and Computer Sciences

The first part of this paper examines cycles at the network level of sensing and control architectures that are needed to maintain the shape of a multiagent formation in 2-dimensional space, while the formation moves as a cohesive whole. The key tools used in the paper are rigidity theory and graph theory. The second part of the paper focuses on the planner level and controller level of the architecture by designing the fuzzy planner and fuzzy controller of individual agents. This permits the decomposition of the complex coordination problem into a series of smaller ones. The fuzzy planner and the …

Mitigation Of Ssr And Lfo With A Tcsc Based-Conventional Damping Controller Optimized By The Pso Algorithm And A Fuzzy Logic Controller, Hasan Gahramani, Akbar Lak, Murtaza Farsadi, Hossein Hosseini

Turkish Journal of Electrical Engineering and Computer Sciences

The subsynchronous resonance (SSR) phenomenon may occur when a steam turbine-generator is connected to a long transmission line with series compensation. Flexible AC transmission systems (FACTS) devices are widely applied to damp the SSR and low-frequency oscillation (LFO). A thyristor-controlled series capacitor (TCSC) is a commercially available FACTS device that was developed for damping the SSR and LFO. In this paper, 2 control methods for damping the SSR and LFO are added to the TCSC main controller in order to demonstrate that the SSR damping capability of the TCSC can be enhanced by proper modulation of the firing angle. The …

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 …

Efficient Feature Integration With Wikipedia-Based Semantic Feature Extraction For Turkish Text Summarization, Aysun Güran, Ni̇lgün Güler Bayazit, Mustafa Zahi̇d Gürbüz

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents a novel hybrid Turkish text summarization system that combines structural and semantic features. The system uses 5 structural features, 1 of which is newly proposed and 3 are semantic features whose values are extracted from Turkish Wikipedia links. The features are combined using the weights calculated by 2 novel approaches. The first approach makes use of an analytical hierarchical process, which depends on a series of expert judgments based on pairwise comparisons of the features. The second approach makes use of the artificial bee colony algorithm for automatically determining the weights of the features. To confirm the …

Review Of Distinctive Phonetic Features And The Arabic Share In Related Modern Research, Yousef Alotaibi, Ali Meftah

Turkish Journal of Electrical Engineering and Computer Sciences

Most research in the field of digital speech technology has traditionally been conducted in only a few languages, such as English, French, Spanish, or Chinese. Numerous studies using distinctive phonetic features (DPFs) with different techniques and algorithms have been carried out during the last 3 decades, mainly in English, Japanese, and other languages of industrialized countries. DPF elements are based on a technique used by linguists and digital speech and language experts to distinguish between different phones by considering the lowest level of actual features during phonation. These studies have investigated the best performances, outcomes, and theories, especially those regarding …

Charlie: A New Robot Prototype For Improving Communication And Social Skills In Children With Autism And A New Single-Point Infrared Sensor Technique For Detecting Bbeathing And Heart Rate Remotely, Laura Boccanfuso

Theses and Dissertations

This research delivers a new, interactive game-playing robot named CHARLIE and a novel technique for remotely detecting breathing and heart rate using a single-point, thermal infrared sensor (IR). The robot is equipped with a head and two arms, each with two degrees of freedom, and a camera. We trained a human hands classifier and used this classifier along with a standard face classifier to create two autonomous interactive games: single-player ("Imitate Me, Imitate You") and two-player ("Pass the Pose"). Further, we developed and implemented a suite of new interactive games in which the robot is teleoperated by remote control. Each …

Correlation Coefficient Of Interval Neutrosophic Set, Said Broumi, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we introduce for the first time the concept of correlation coefficients of interval valued neutrosophic set (INS for short). Respective numerical examples are presented.

Towards A Tight Integration Of Syntactic Parsing With Semantic Disambiguation By Means Of Declarative Programming, Yuliya Lierler, Peter Schüller

Computer Science Faculty Proceedings & Presentations

We propose and advocate the use of an advanced declarative programming paradigm – answer set programming – as a uniform platform for integrated approach towards syntax-semantic processing in natural language. We illustrate that (a) the parsing technology based on answer set programming implementation reaches performance sufficient for being a useful NLP tool, and (b) the proposed method for incorporating semantic information from FRAMENET into syntactic parsing may prove to be useful in allowing semantic-based disambiguation of syntactic structures.

Real-Time Embodied Agent Adaptation, Ryan M. Schuetzler, David W. Wilson

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

This paper reports on initial investigation of two emerging technologies, FaceFX and Smartbody, capable of creating life-like animations for embodied conversational agents (ECAs) such as the AVATAR agent. Real-time rendering and animation generation technologies can enable rapid adaptation of ECAs to changing circumstances. The benefits of each package are discussed.

Improving Usability: Evaluating The Effect Of Changing Environmental Factors On Cognitive Load, Robin J. Deegan

Theses

Mobile devices are now truly ubiquitous. Their pervasiveness in all facets of our lives brings many advantages. Principle to these advantages is the notion that mobile devices can be used “Anytime, Anywhere”. The size, portability, battery life and computational power of mobile devices mean that they can be used for a diverse range of uses in an equally diverse range of environments.

Usability is primarily concerned with “ease of use” and “learnability”. Mobile devices are challenging this notion of Usability as they are used in new ways. Firstly mobile devices arc used in complex distracting environments and these distractions interfere …

Developing A Group Decision Support System (Gdss) For Decision Making Under Uncertainty, Soroush Mokhtari

Electronic Theses and Dissertations

Multi-Criteria Decision Making (MCDM) problems are often associated with tradeoffs between performances of the available alternative solutions under decision making criteria. These problems become more complex when performances are associated with uncertainty. This study proposes a stochastic MCDM procedure that can handle uncertainty in MCDM problems. The proposed method coverts a stochastic MCDM problem into many deterministic ones through a Monte-Carlo (MC) selection. Each deterministic problem is then solved using a range of MCDM methods and the ranking order of the alternatives is established for each deterministic MCDM. The final ranking of the alternatives can be determined based on winning …

Automatically Acquiring A Semantic Network Of Related Concepts, Sean Szumlanski

Electronic Theses and Dissertations

We describe the automatic acquisition of a semantic network in which over 7,500 of the most frequently occurring nouns in the English language are linked to their semantically related concepts in the WordNet noun ontology. Relatedness between nouns is discovered automatically from lexical co-occurrence in Wikipedia texts using a novel adaptation of an information theoretic inspired measure. Our algorithm then capitalizes on salient sense clustering among these semantic associates to automatically disambiguate them to their corresponding WordNet noun senses (i.e., concepts). The resultant concept-to-concept associations, stemming from 7,593 target nouns, with 17,104 distinct senses among them, constitute a large-scale semantic …

Ssr Mitigation With Sssc Thanks To Fuzzy Control, Seyed Mohammad Hassan Hosseini, Hadi Samadzadeh, Javad Olamaei, Murtaza Farsadi

Turkish Journal of Electrical Engineering and Computer Sciences

This paper deals with the capability of a static synchronous series compensator (SSSC) to attenuate the subsynchronous resonance (SSR). Two well-known controllers are designed, namely a conventional damping controller (CDC) and fuzzy logic damping controller (FLDC). These 2 damping controllers are added to a main control loop of a SSSC operating as a SSR damping controller. It should be noted that, to optimize the parameters of the CDC, a versatile optimization technique is implemented, namely particle swarm optimization (PSO). A comprehensive comparison between the 2 control methods is carried out for different operational conditions. To observe the superior performance of …

Computation Of Grade Values Of Sediment-Hosted Barite Deposits In Northeastern Isparta (Western Turkey), Numan Elmas, Uğur Şahi̇n

Turkish Journal of Earth Sciences

Grade value is a crucial parameter for the mineral industry. Investigation of grade value of mineral resources provides the optimum benefit. In this study, an adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) model were applied for the prediction of grade values. The spatial coordinates X, Y, and Z of the study area along with bore hole geochemical data were used as input variables in the model. In order to illustrate the applicability and capability of these methods, the western part of Turkey, between the latitudes 38°01 45 N and 38°09 52 N and between the longitudes 31°23 …

Antifragility Analysis And Measurement Framework For Systems Of Systems, John Johnson, Adrian V. Gheorghe

Engineering Management & Systems Engineering Faculty Publications

The twenty-first century is defined by the social and technical hazards we face. A hazardous situation is a condition, or event, that threatens the well-being of people, organizations, societies, environments, and property. The most extreme of the hazards are considered X-Events and are an exogenous source of extreme stress to a system. X-Events can also be the unintended outputs of a system with both positive (serendipitous) and negative (catastrophic) consequences. Systems can vary in their ability to withstand these stress events. This ability exists on a continuum of fragility that ranges from fragile (degrading with stress), to robust (unchanged by …

How Often Is Employee Anger An Insider Risk Ii? Detecting And Measuring Negative Sentiment Versus Insider Risk In Digital Communications–Comparison Between Human Raters And Psycholinguistic Software, Eric Shaw, Maria Payri, Michael Cohn, Ilene R. Shaw

Journal of Digital Forensics, Security and Law

This research uses two recently introduced observer rating scales, (Shaw et al., 2013) for the identification and measurement of negative sentiment (the Scale for Negativity in Text or SNIT) and insider risk (Scale of Indicators of Risk in Digital Communication or SIRDC) in communications to test the performance of psycholinguistic software designed to detect indicators of these risk factors. The psycholinguistic software program, WarmTouch (WT), previously used for investigations, appeared to be an effective means for locating communications scored High or Medium in negative sentiment by the SNIT or High in insider risk by the SIRDC within a randomly selected …

Cultivating Local: Building A Local Food System In Western North Carolina, Allison S. Perrett

USF Tampa Graduate Theses and Dissertations

This dissertation examines a movement in Western North Carolina to build a local food system, one grounded in the conditions and relationships of place. In 2000, Mountain Family Farms launched the Local Food Campaign to raise public awareness about the region's farms and farming heritage, to educate consumers about the benefits of buying food grown by local farms, and, ultimately, to build markets for locally grown food to sustain the region's farms. The campaign sparked a social movement and over a decade later local farms and locally grown food are a palpable feature of life in the mountains of Western …

A Latent Dirichlet Allocation/N-Gram Composite Language Model, Raymond Daniel Kulhanek

Browse all Theses and Dissertations

I present a composite language model in which an n-gram language model is integrated with the Latent Dirichlet Allocation topic clustering model. I also describe a parallel architecture that allows this model to be trained over large corpora and present experimental results that show how the composite model compares to a standard n-gram model over corpora of varying size.

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 …

Descriptive Statistical Attributes Of Special Education Datasets, Valerie Felder

Wayne State University Dissertations

ABSTRACT

Descriptive Statistical Attributes of Special Education Data Sets

by

VALERIE FELDER

December 2013

Advisor: Dr. Shlomo Sawilowsky

Major: Educational Evaluation and Research

Degree: Doctor of Philosophy

Micceri (1989) examined the distributional characteristics of 440 large-sample achievement and psychometric measures. All the distributions were found to be nonnormal at alpha = .01. Micceri indicated three factors that might contribute to a non-Gaussian error distribution in the population. The first factor is subpopulations within a target population. The second factor is ceiling effects and the third factor is treatment effects that may change the location parameter, variability, or shape of the …

Balancing Human And Machine Contributions In Human Computation Systems, R. Jordan Crouser, Alvitta Ottley, Remco Chang

Computer Science: Faculty Publications

Many interesting and successful human computation systems leverage the complementary computational strengths of both humans and machines to solve these problems. In this chapter, we examine Human Computation as a type of Human-Computer Collaboration—collaboration involving at least one human and at least one computational agent. We discuss recent advances in the open area of function allocation, and explore how to balance the contributions of humans and machines in computational systems. We then explore how human-computer collaborative strategies can be used to solve problems that are difficult or computationally infeasible for computers or humans alone.

Metacognition And Its Effect On Learning High School Calculus, Bonnie Sue Bergstresser

LSU Master's Theses

The following paper discusses the effect of metacognitive training sessions on students’ calculus retention. Students in two high school classes participated. The students in both classes were then given lessons on a chapter without metacognitive training and lessons on a subsequent chapter with training in a set of metacognitive skills. After the latter chapter students scored higher on a post-test and expressed desire to incorporate the skills they learned into their other classes.

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 …

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 …

Semsos : An Architecture For Query, Insertion, And Discovery For Semantic Sensor Networks, Joshua Kenneth Pschorr

Browse all Theses and Dissertations

With sensors, storage, and bandwidth becoming ever cheaper, there has been a drive recently to make sensor data accessible on the Web. However, because of the vast number of sensors collecting data about our environment, finding relevant sensors on the Web and then interpreting their observations is a non-trivial challenge. The Open Geospatial Consortium (OGC) defines a web service specification known as the Sensor Observation Service (SOS) that is designed to standardize the way sensors and sensor data are discovered and accessed on the Web. Though this standard goes a long way in providing interoperability between sensor data producers and …