Digital Commons Network^™

Extended List Of Stop Words: Does It Work For Keyphrase Extraction From Short Texts?, Svetlana Popova, Gabriella Skitalinskaya

Conference Papers

In this paper we study the problem of key phrase extraction from short texts written in Russian. As texts we consider messages posted on Internet car forums related to the purchase or repair of cars. The main assumption made is: the construction of lists of stop words for key phrase extraction can be effective if performed on the basis of a small, expert-marked collection. The results show that even a small number of texts marked by an expert can be enough to build an extended list of stop words. Extracted stop words allow to improve the quality of the key …

A Neuro-Fuzzy Controller For Grid-Connected Heavy-Duty Gas Turbine Power Plants, Mohamed Iqbal Mohamed Mustafa, Joseph Xavier Rayappan, Kanakaraj Jagannathan

Turkish Journal of Electrical Engineering and Computer Sciences

Frequent load fluctuation and set-point variation may affect the stability of grid-connected heavy-duty gas turbine power plants. To overcome such problems, a novel neuro-fuzzy controller is proposed in this paper for single-shaft heavy-duty gas turbines ranging from 18.2 MW to 106.7 MW. A neuro-fuzzy controller was developed using a hybrid learning algorithm and the effectiveness of the controller for all heavy-duty gas turbine plants (5, 6, 7, and 9 series) is demonstrated against load disturbance and set-point variation in a grid-connected environment. Various time domain specifications and performance index criteria of the neuro-fuzzy controller are compared with that of a …

Nonlinear Model Predictive Control Based On Fuzzy Wavelet Neural Network And Chaos Optimization, Mehrnoush Davanipour, Hanieh Asadipooya

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper a combined controller is proposed for nonlinear dynamical systems. The controller is constructed by a fuzzy wavelet network and nonlinear model predictive control. Chaotic optimization, which is fast and robust, is applied to generate optimized controlled input in nonlinear model predictive control. The ability of the fuzzy wavelet neural network and the proposed controller is shown by simulation. It is illustrated that the proposed method is able to increase the speed of tracking in addition to having very little steady state error. Using chaotic optimization makes the controller robust in the presence of noise.

Complexity Theoretic Parallels Among Automata, Formal Languages And Real Variables : Including Multi-Patterns, L-Systems And Cellular Automata, Jingnan Xie

Legacy Theses & Dissertations (2009 - 2024)

In this dissertation, we emphasize productiveness not just undecidability since pro- ductiveness implies constructive incompleteness. Analogues of Rice’s Theorem for different classes of languages are investigated, refined and generalized. In particular, several sufficient but general conditions are presented for predicates to be as hard as some widely discussed predicates such as “= ∅” and “= {0,1}∗”. These conditions provide several general methods for proving complexity/productiveness results and apply to a large number of simple and natural predicates. As the first step in apply- ing these general methods, we investigate the complexity/productiveness of the pred- icates “= ∅”, “= {0,1}∗” and …

A New Word-Based Compression Model Allowing Compressed Pattern Matching, Hali̇l Nusret Buluş, Aydin Carus, Altan Mesut

Turkish Journal of Electrical Engineering and Computer Sciences

In this study a new semistatic data compression model that has a fast coding process and that allows compressed pattern matching is introduced. The name of the proposed model is chosen as tagged word-based compression algorithm (TWBCA) since it has a word-based coding and word-based compressed matching algorithm. The model has two phases. In the first phase a dictionary is constructed by adding a phrase, paying attention to word boundaries, and in the second phase compression is done by using codewords of phrases in this dictionary. The first byte of the codeword determines whether the word is compressed or not. …

Multiverse Optimized Fuzzy-Pid Controller With A Derivative Filter For Load Frequency Control Of Multisource Hydrothermal Power System, Amit Kumar, Sathans Suhag

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a multiverse optimized (MVO) fuzzy PID controller with a derivative filter (fuzzy-PIDF) is proposed for the load frequency control (LFC) of a two-area multisource hydrothermal power system. The superiority of the MVO algorithm is demonstrated by comparing the system LFC performance with integral and fuzzy-PIDF controllers, both optimized using MVO, as well as some of the recent heuristic optimization techniques such as the ant lion optimizer, gray wolf optimizer, differential evolution, bacterial foraging optimization algorithm, and particle swarm optimization. To the best of the knowledge of the authors, the use of the MVO technique has not yet …

Indirect Adaptive Neurofuzzy Hermite Wavelet Based Control Of Pv In A Grid-Connected Hybrid Power System, Sidra Mumtaz, Laiq Khan

Turkish Journal of Electrical Engineering and Computer Sciences

Owing to the evolution of the smart grid, the emergence of hybrid power systems (HPSs), and the proliferation of plug-in-hybrid electric vehicles, the development of efficient and robust maximum power point tracking (MPPT) algorithms for renewable energy sources due to their inherent intermittent nature has overwhelmed the power industry. In this paper, an incremental conductance (IC) based Hermite wavelet incorporated neurofuzzy indirect adaptive MPPT control paradigm for a photovoltaic (PV) system in a grid-connected HPS is proposed. The performance of the proposed adaptive Hermite wavelet incorporated neurofuzzy MPPT control paradigm is validated through a comprehensive grid-connected HPS test-bed developed in …

Turkish Synonym Identification From Multiple Resources: Monolingual Corpus, Mono/Bilingual Online Dictionaries, And Wordnet, Tuğba Yildiz, Banu Di̇ri̇, Savaş Yildirim

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a model is proposed to determine synonymy by incorporating several resources. The model extracts the features from monolingual online dictionaries, a bilingual online dictionary, WordNet, and a monolingual Turkish corpus. Once it has built a candidate list, it determines the synonymy for a given word by means of those features. All these resources and the approaches are evaluated. Taking all features into account and applying machine learning algorithms, the model shows good performance of F-measure with 81.4%. The study contributes to the literature by integrating several resources and attempting the first corpus-driven synonym detection system for Turkish.

A Self-Tuning Neurofuzzy Feedback Linearization-Based Damping Control Strategy For Multiple Hvdc Links, Saghir Ahmad, Laiq Khan

Turkish Journal of Electrical Engineering and Computer Sciences

This research work proposes a multi-input multi-output (MIMO) online adaptive feedback linearization NeuroFuzzy control (AFLNFC) scheme to improve the damping of low frequency oscillations (LFOs) in an AC/DC power system. Optimized NeuroFuzzy identification architecture online captures the oscillatory dynamics of the power system through wide area measurement system (WAMS)-based measured speed signals of machines. Based on the identified power system model, the appropriate control law is derived through feedback linearization control with a self-tuned coefficient vector. The generated control signal modulates the real power flow through a high voltage direct current (HVDC) link during perturbed operating conditions and enhances system …

A Data-Aware Cognitive Engine For Scheduling Data Intensive Applications In A Grid, Vijaya Nagarajan, Maluk Mohamed Mulk Abdul

Turkish Journal of Electrical Engineering and Computer Sciences

Data-intensive applications produce huge amounts of data that need to be stored, analyzed, and interpreted. A data grid serves as a cost-effective infrastructure for solving these data-intensive applications. Existing scheduling strategies are best suited for handling compute-intensive applications, although they lack in performance while handling data-intensive applications. In this work, a novel mechanism of incorporating cognitive science in a data grid is proposed for scheduling data-intensive workflows. A unique model is derived in which a cognitive engine (CE) is built into the middleware of the data grid. The intelligent agents present in the CE handle the request for data sets …

Adslanf: A Negotiation Framework For Cloud Management Systems Using A Bulk Negotiation Behavioral Learning Approach, Rajkumar Rajavel, Mala Thangarathinam

Turkish Journal of Electrical Engineering and Computer Sciences

One of the major challenges in cloud computing is the development of a service-level agreement (SLA) negotiation framework using an intelligent third-party broker negotiation strategy. Current frameworks exploit various negotiation strategies using game theoretic, heuristic, and argumentation-based approaches for obtaining optimal negotiation with a better success rate (negotiation commitment). However, these approaches fail to optimize the negotiation round (NR), total negotiation time (TNT), and communication overhead (CO) involved in the negotiation strategy. To overcome these problems, certain researchers have exploited trade-off, concession, and behavioral learning strategies with varying degrees of sacrifices (reductions) in their concerned proposal generation. Such sacrifices can …

A Hybrid Of Sliding Mode Control And Fuzzy Logic Control Using A Fuzzy Supervisory Switched System For Dc Motor Speed Control, Husain Ahmed, Abha Rajoriya

Turkish Journal of Electrical Engineering and Computer Sciences

In many applications of DC motor speed control systems, PID controllers are mostly used. Such control schemes do not show good performance when input and load torque disturbances are applied. This paper shows that sliding mode (SM) can give better control due to its robust property but it has an unwanted chattering problem associated with it, which is harmful to the plant. To limit this problem a hybrid controller is presented in which a fuzzy controller is combined with the SM controller by a fuzzy supervisory system in such a way that the SM controller works in transient state and …

Android Malware Classification Based On Anfis With Fuzzy C-Means Clustering Using Significant Application Permissions, Altyeb Altaher, Omar Barukab

Turkish Journal of Electrical Engineering and Computer Sciences

Mobile phones have become an essential part of our lives because we depend on them to perform many tasks, and they contain personal and important information. The continuous growth in the number of Android mobile applications resulted in an increase in the number of malware applications, which are real threats and can cause great losses. There is an urgent need for efficient and effective Android malware detection techniques. In this paper, we present an adaptive neuro-fuzzy inference system with fuzzy c-means clustering (FCM-ANFIS) for Android malware classification. The proposed approach utilizes the FCM clustering method to determine the optimum number …

Turkish Entity Discovery With Word Embeddings, Murat Kalender, Emi̇n Erkan Korkmaz

Turkish Journal of Electrical Engineering and Computer Sciences

Entity-linking systems link noun phrase mentions in a text to their corresponding knowledge base entities in order to enrich a text with metadata. Wikipedia is a popular and comprehensive knowledge base that is widely used in entity-linking systems. However, long-tail entities are not popular enough to have their own Wikipedia articles. Therefore, a knowledge base created by using Wikipedia entities would be limited to only popular entities. In order to overcome the knowledge base coverage limitation of Wikipedia-based entity-linking systems, this paper presents an entity-discovery system that can detect semantic types of entities that are not defined in Wikipedia. The …

Evaluation Of Distance Education Websites: A Hybrid Multicriteria Approach, Mehmet Kabak, Eren Özceylan, Meti̇n Dağdevi̇ren, Tolga Genç

Turkish Journal of Electrical Engineering and Computer Sciences

This study provides an evaluation model that prioritizes the relative weights of various distance education websites. The proposed approach consists of four sequential steps. In the first step, 25 different subcriteria under 4 major criteria are gathered from the existing literature. Identified criteria are weighted by stakeholders of distance education websites using the analytic network process outlined in the second step. In the third step, the technique for order preference by similarity to ideal solution method is applied in order to rank the 15 different Turkish distance education website alternatives. Finally, in the fourth step, different scenario analyses are applied …

Hesitant Fuzzy Pairwise Comparison For Software Cost Estimation: A Case Study In Turkey, Ayfer Başar

Turkish Journal of Electrical Engineering and Computer Sciences

Estimating the cost of software is a complex process for almost all engineering companies. Uncertainties about development method, design, estimation process, data, and processing affect the accuracy of estimation. Underestimation results in fewer resources being committed than the project really needs, an unrealistic schedule, and low quality outputs. On the other hand, overestimation wastes resources and causes loss of customer credit. Thus, choosing the appropriate cost estimation method is crucial. Studies in the literature emphasize the importance of empirical, analytical methods and expert judgement. Certain cost estimation techniques have been widely studied in the literature. However, there are limited studies …

Crowdsourcing A Parallel Corpus For Conceptual Analysis Of Natural Language, Jamie C. Macbeth, Sandra Grandic

Computer Science: Faculty Publications

Computer users today are demanding greater performance from systems that understand and respond intelligently to human language as input. In the past, researchers proposed and built conceptual analysis systems that attempted to understand language in depth by decomposing a text into structures representing complex combinations of primitive acts, events, and state changes in the world the way people conceive them. However, these systems have traditionally been time-consuming and costly to build and maintain by hand. This paper presents two studies of crowdsourcing a parallel corpus to build conceptual analysis systems through machine learning. In the first study, we found that …

Research Strategies For Biomedical And Health Informatics: Some Thought-Provoking And Critical Proposals To Encourage Scientific Debate On The Nature Of Good Research In Medical Informatics, Reinhold Haux, Et Al.

Research Collection School Of Computing and Information Systems

Medical informatics, or biomedical and health informatics (BMHI), has become an established scientific discipline. In all such disciplines there is a certain inertia to persist in focusing on well-established research areas and to hold on to well-known research methodologies rather than adopting new ones, which may be more appropriate. To search for answers to the following questions: What are research fields in informatics, which are not being currently adequately addressed, and which methodological approaches might be insufficiently used? Do we know about reasons? What could be consequences of change for research and for education? Outstanding informatics scientists were invited to …

The Trilogy Of Science: Filling The Knowledge Management Gap With Knowledge Science And Theory, Anthony Shawn Bates

Walden Dissertations and Doctoral Studies

The international knowledge management field has different ways of investigating, developing, believing, and studying knowledge management. Knowledge management (KM) is distinguished deductively by know-how, and its intangible nature establishes different approaches to KM concepts, practices, and developments. Exploratory research and theoretical principles have formed functional intelligences from 1896 to 2013, leading to a knowledge management knowledge science (KMKS) concept that derived a grounded theory of knowledge activity (KAT). This study addressed the impact of knowledge production problems on KM practice. The purpose of this qualitative meta-analysis study was to fit KM practice within the framework of knowledge science (KS) study. …

Multi-Way Factorization Machine For Sentiment Analysis, Jingwei Zhang

Wayne State University Theses

Sentiment analysis is a process of learning the relationship between sentiment label

and text. The research value of sentiment analysis is two-fold: first, it has a wide range

of applications in many sectors and industries, e.g., the industry has flourished due to the

proliferation of commercial applications such as using sentiment analysis as an integrated

part of customer experience strategy. Second, it offers an array of new challenging problems

for research community such as word feature embedding and machine learning. Albeit earlier

methods such as Naïve Bayes (NB), Random Forest (RF), k-Nearest-Neighbours (kNN),

Support Vector Machine (SVM) and more recent …

K-8 Pre-Service Teachers’ Algebraic Thinking: Exploring The Habit Of Mind Building Rules To Represent Functions, Marta T. Magiera, John C. Moyer, Leigh A. Van Den Kieboom

Mathematics, Statistics and Computer Science Faculty Research and Publications

In this study, through the lens of the algebraic habit of mind Building Rules to Represent Functions, we examined 18 pre-service middle school teachers' ability to use algebraic thinking to solve problems. The data revealed that pre-service teachers' ability to use different features of the habit of mind Building Rules to Represent Functions varied across the features. Significant correlations existed between 8 pairs of the features. The ability to justify a rule was the weakest of the seven features and it was correlated with the ability to chunk information. Implications for mathematics teacher education are discussed.

A Semantics-Based Measure Of Emoji Similarity, Sanjaya Wijeratne, Lakshika Balasuriya, Amit Sheth, Derek Doran

Kno.e.sis Publications

Emoji have grown to become one of the most important forms of communication on the web. With its widespread use, measuring the similarity of emoji has become an important problem for contemporary text processing since it lies at the heart of sentiment analysis, search, and interface design tasks. This paper presents a comprehensive analysis of the semantic similarity of emoji through embedding models that are learned over machine-readable emoji meanings in the EmojiNet knowledge base. Using emoji descriptions, emoji sense labels and emoji sense definitions, and with different training corpora obtained from Twitter and Google News, we develop and test …

Triple Non-Negative Matrix Factorization Technique For Sentiment Analysis And Topic Modeling, Alexander A. Waggoner

CMC Senior Theses

Topic modeling refers to the process of algorithmically sorting documents into categories based on some common relationship between the documents. This common relationship between the documents is considered the “topic” of the documents. Sentiment analysis refers to the process of algorithmically sorting a document into a positive or negative category depending whether this document expresses a positive or negative opinion on its respective topic. In this paper, I consider the open problem of document classification into a topic category, as well as a sentiment category. This has a direct application to the retail industry where companies may want to scour …

Prediction Of Local Quality Of Protein Structure Models Considering Spatial Neighbors In Graphical Models., Woong Hee Shin, Xuejiao Kang, Jian Zhang, Daisuke Kihara

Department of Biological Sciences Faculty Publications

Protein tertiary structure prediction methods have matured in recent years. However, some proteins defy accurate prediction due to factors such as inadequate template structures. While existing model quality assessment methods predict global model quality relatively well, there is substantial room for improvement in local quality assessment, i.e. assessment of the error at each residue position in a model. Local quality is a very important information for practical applications of structure models such as interpreting/designing site-directed mutagenesis of proteins. We have developed a novel local quality assessment method for protein tertiary structure models. The method, named Graph-based Model Quality assessment method …

Silence, Please!: Interrupting In-Car Phone Conversations, Soledad López Gambino, Casey Kennington, David Schlangen

Computer Science Faculty Publications and Presentations

Holding phone conversations while driving is dangerous not only because it occupies the hands, but also because it requires attention. Where driver and passenger can adapt their conversational behavior to the demands of the situation, and e.g. interrupt themselves when more attention is needed, an interlocutor on the phone cannot adjust as easily. We present a dialogue assistant which acts as 'bystander' in phone conversations between a driver and an interlocutor, interrupting them and temporarily cutting the line during potentially dangerous situations. The assistant also informs both conversation partners when the line has been cut, as well as when it …

A Graphical Digital Personal Assistant That Grounds And Learns Autonomously, Casey Kennington, Aprajita Shukla

Computer Science Faculty Publications and Presentations

We present a speech-driven digital personal assistant that is robust despite little or no training data and autonomously improves as it interacts with users. The system is able to establish and build common ground between itself and users by signaling understanding and by learning a mapping via interaction between the words that users actually speak and the system actions. We evaluated our system with real users and found an overall positive response. We further show through objective measures that autonomous learning improves performance in a simple itinerary filling task.

A Study On User Demographic Inference Via Ratings In Recommender Systems, Changbin Li

LSU Master's Theses

Everyday, millions of people interact with online services that adopt recommender systems, such as personalized movie, news and product recommendation services. Research has shown that the demographic attributes of users such as age and gender can further improve the performance of recommender systems and can be very useful for many other applications such as marketing and social studies. However, users do not always provide those details in their online profiles due to privacy concern. On the other hand, user interactions such as ratings in recommender systems may provide an alternative way to infer demographic information. Most existing approaches can infer …

A Fuzzy Logic-Based Approach For Assessing The Quality Of Business Process Models, Fadwa Yahya, Khouloud Boukadi, Hanêne Ben Abdallah, Zakaria Maamar

All Works

Copyright © 2017 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved. Similar to software products, the quality of a Business Process model is vital to the success of all the phases of its lifecycle. Indeed, a high quality BP model paves the way to the successful implementation, execution and performance of the business process. In the literature, the quality of a BP model has been assessed through either the application of formal verification, or most often the evaluation of quality metrics calculated in the static and/or simulated model. Each of these assessment means addresses different quality characteristics …

Towards A Relative-Pitch Neural Network System For Chorale Composition And Harmonization, Samuel P. Goree

Honors Papers

Computational creativity researchers interested in applying machine learning to computer composition often use the music of J.S. Bach to train their systems. Working with Bach, though, requires grappling with the conventions of tonal music, which can be difficult for computer systems to learn. In this paper, we propose and implement an alternate approach to composition and harmonization of chorales based on pitch-relative note encodings to avoid tonality altogether. We then evaluate our approach using a survey and expert analysis, and find that pitch-relative encodings do not significantly affect human-comparability, likability or creativity. However, an extension of this model that better …

Online Hacker Forum Censorship: Would Banning The Bad Guys Attract Good Guys?, Qiu-Hong Wang, Le-Ting Zhang, Meng-Ke Qiao

Research Collection School Of Computing and Information Systems

To tackle the ubiquitous cybersecurity threats, a few countries have enacted legislation to criminalize the production, distribution and possession of computer misuse tools. Consequently, online hacker forums, which enable the provision and dissemination of malicious cyber-attack techniques among potential hackers or technology-savvy users, are subject to censorship. This project examines the mixed impacts of online hacker forum censorship on users’ contribution to protection discussion through a natural experiment with large-scale content analysis. We find that while the enforcement indeed reduced the discussion on malicious cyber-attacks, the discussion on cybersecurity protection could increase or decrease in different scenarios. The rationale is …