Digital Commons Network^™

Linking Climate Change And Socio-Economic Impact For Long-Term Urban Growth In Three Mega-Cities, Qi Lu

Electronic Theses and Dissertations

Urbanization has become a global trend under the impact of population growth, socio-economic development, and globalization. However, the interactions between climate change and urban growth in the context of economic geography are unclear due to missing links in between the recent planning megacities. This study aims to conduct a multi-temporal change analysis of land use and land cover in New York City, City of London, and Beijing using a cellular automata-based Markov chain model collaborating with fuzzy set theory and multi-criteria evaluation to predict the city's future land use changes for 2030 and 2050 under the background of climate change. …

Using Natural Language Processing And Machine Learning Techniques To Characterize Configuration Bug Reports: A Study, Wei Wen

Theses and Dissertations--Computer Science

In this study, a tool is developed that achieves two purposes: (1) given bug reports, it identifies configuration bug reports from non-configuration bug reports; (2) once a bug report is identified to be a configuration bug report, the tool finds out what specific configuration option the bug report is associated.

This study starts with a review of related works that used machine learning tools to solve software bug and bug report related issues. It then discusses the natural language processing and machine learning techniques. Afterwards, the development process of the proposed tool is described in detail, including the motivation, the …

Modeling Mortgage Assessment With Computational Argumentation Theory And Defeasible Reasoning, Henrik Szucs

Dissertations

In the mortgage lending business of a bank, a key focus area is risk analysis, which supports the mortgage awarding process and the prediction of the risk of defaulting (repayment issues). The standard risk assessment method at most banks is a scorecard calculation. A new way of predicting the defaulting is proposed using Defeasible Reasoning (DR) and computational Argumentation Theory (AT), areas of interdisciplinary research, in the discipline of Articial Intelligence (AI). Argumentation is formalised by reasoning models which are inspired by human reasoning. For a more realistic representation AT employs DR which is a non-monotonic reasoning process, meaning that …

The Evaluation Of Ensemble Sentiment Classification Approach On Airline Services Using Twitter, Zechen Wang

Dissertations

In the field of sentiment classification, much research has been done on reviews of topics such as movies, software and books. Little research has been done in the airline service domain. In the airline industry, the use of social media as a customer service tool has become a growing phenomenon. The research conducted by Wan and Gao (2015) has proposed an ensemble classification approach for airline service sentiment classification using Twitter data. In accordance, the objective of improving the performance of ensemble classification approach is the primary consideration. This research proposed new hybrid classification approach that uses the state-of-art approach …

Semantics-Based Summarization Of Entities In Knowledge Graphs, Kalpa Gunaratna

Browse all Theses and Dissertations

The processing of structured and semi-structured content on the Web has been gaining attention with the rapid progress in the Linking Open Data project and the development of commercial knowledge graphs. Knowledge graphs capture domain-specific or encyclopedic knowledge in the form of a data layer and add rich and explicit semantics on top of the data layer to infer additional knowledge. The data layer of a knowledge graph represents entities and their descriptions. The semantic layer on top of the data layer is called the schema (ontology), where relationships of the entity descriptions, their classes, and the hierarchy of the …

Development Of A Performance Assessment System For Language Learning, Imen Kasrani

Browse all Theses and Dissertations

Recent advances in computer-assisted, language-speaking, learning/training technology have demonstrated its promising potential to improve the outcome of language learning in early education, special education, English as a Second Language (ESL), and foreign language. The growing number of readily available mobile app-based solutions help encourage interest in learning to speak a foreign language, but their effectiveness is limited due to their lack of objective assessment and performance feedback resembling expert judgment. For example, it has been recognized that, in early education, students learn best with one-on-one instructions. Unfortunately, teachers do not have the time, and it is challenging to extend the …

Multi-Class Classification Of Textual Data: Detection And Mitigation Of Cheating In Massively Multiplayer Online Role Playing Games, Naga Sai Nikhil Maguluri

Browse all Theses and Dissertations

The success of any multiplayer game depends on the player’s experience. Cheating/Hacking undermines the player’s experience and thus the success of that game. Cheaters, who use hacks, bots or trainers are ruining the gaming experience of a player and are making him leave the game. As the video game industry is a constantly increasing multibillion dollar economy, it is crucial to assure and maintain a state of security. Players reflect their gaming experience in one of the following places: multiplayer chat, game reviews, and social media. This thesis is an exploratory study where our goal is to experiment and propose …

Harassment Detection On Twitter Using Conversations, Venkatesh Edupuganti

Browse all Theses and Dissertations

Social media has brought people closer than ever before, but the use of social media has also brought with it a risk of online harassment. Such harassment can have a serious impact on a person such as causing low self-esteem and depression. The past research on detecting harassment on social media is primarily based on the content of messages exchanged on social media. The lack of context when relying on a single social media post can result in a high degree of false alarms. In this study, I focus on the reliable detection of harassment on Twitter by better understanding …

Semantic Web Foundations For Representing, Reasoning, And Traversing Contextualized Knowledge Graphs, Vinh Thi Kim Nguyen

Browse all Theses and Dissertations

Semantic Web technologies such as RDF and OWL have become World Wide Web Consortium (W3C) standards for knowledge representation and reasoning. RDF triples about triples, or meta triples, form the basis for a contextualized knowledge graph. They represent the contextual information about individual triples such as the source, the occurring time or place, or the certainty. However, an efficient RDF representation for such meta-knowledge of triples remains a major limitation of the RDF data model. The existing reification approach allows such meta-knowledge of RDF triples to be expressed in RDF by using four triples per reified triple. While reification is …

Robust Adaptive Fuzzy Control Of A Three-Phase Active Power Filter Based On Feedback Linearization, Shixi Hou, Juntao Fei

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a robust adaptive fuzzy control system using feedback linearization is proposed for a three-phase active power filter (APF). The APF system is divided into two separate loops: the current dynamic inner loop and the DC voltage dynamic outer loop. Adaptive fuzzy tracking control using feedback linearization is employed for the current dynamic inner loop to overcome the drawbacks of the conventional method. The proposed controller can ensure proper tracking of the reference current and impose desired dynamic behavior, giving robustness and insensitivity to parameter variations. Adaptive fuzzy proportional-integral control is applied to the DC voltage dynamics outer …

Implementation Of Svc Based On Grey Theory And Fuzzy Logic To Improve Lvrt Capability Of Wind Distributed Generations, Mohammad Mehdi Karami, Akbar Itami

Turkish Journal of Electrical Engineering and Computer Sciences

Due to the great absorption of reactive power after voltage drops caused by faults in network, the low-voltage ride through (LVRT) capability of squirrel cage induction generators (SCIGs) in wind farms is a great challenge. If a static VAR compensator (SVC) is installed at the point of common coupling (PCC) of a wind farm with a main network, it can improve the wind generation's LVRT capability with reactive power compensation. In the voltage control loop of a conventional SVC, the voltage actual value of the PCC is compared with the reference voltage value. This paper presents a method for implementation …

A Combined Approach Based On Fuzzy Ahp And Fuzzy Inference System To Rank Reviewers In Online Communities, Hossein Abbasimehr, Mohammadjafar Tarokh

Turkish Journal of Electrical Engineering and Computer Sciences

Online product review communities allow users to share their ideas and opinions about various products and services. Although online reviews as user-generated content can be considered as an invaluable source of information for both consumers and firms, these reviews tend to be of very different quality. To tackle the problem of low quality reviews, we address reviewer credibility and propose an innovative framework. The framework comprises five critical phases for ranking reviewers in terms of credibility using a fuzzy analytic hierarchy process (AHP) and fuzzy inference system. To determine the weights of the features, a fuzzy AHP method was applied. …

Implementation Of A Web-Based Service For Mobile Application Risk Assessment, Asim Si̇nan Yüksel, Mehmet Erkan Yüksel, Ahmet Sertbaş, Abdül Hali̇m Zai̇m

Turkish Journal of Electrical Engineering and Computer Sciences

The Android operating system has increased in popularity and has been increasing its shares in the smart phone market. Users can carry out their daily work such as paying bills, being social, and sharing photos through mobile applications. These applications have access to sensitive information about the user, such as location, contacts, call logs, and SMS messages. However, the users have no knowledge of the applications or the personal information these applications have access to. Even if an application is not malware or does not have malicious behavior, it can compromise the security and privacy of the user by accessing …

Unsupervised Learning Of Allomorphs In Turkish, Burcu Can

Turkish Journal of Electrical Engineering and Computer Sciences

One morpheme may have several surface forms that correspond to allomorphs. In English, ed and $d$ are surface forms of the past tense morpheme, and $s$, es, and ies are surface forms of the plural or present tense morpheme. Turkish has a large number of allomorphs due to its morphophonemic processes. One morpheme can have tens of different surface forms in Turkish. This leads to a sparsity problem in natural language processing tasks in Turkish. Detection of allomorphs has not been studied much because of its difficulty. For example, tü and di are Turkish allomorphs (i.e. past tense morpheme), but …

Force And Torque Parameter Estimation For A 4-Pole Hybrid Electromagnet By Anfis Hybrid Learning Algorithm, Murat Atlihan, Bariş Can Yalçin, Kadi̇r Erkan

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a force and torque estimation method based on an adaptive neuro-fuzzy inference system (ANFIS) has been developed to get rid of multiple integral calculations of air gap coefficients that cause time delay for magnetic levitation control applications. During magnetic levitation applications that contain a 4-pole hybrid electromagnet, multiple integral calculations have to be done for obtaining air gap permanence parameters, and these parameters are needed to calculate force and torque parameters that are produced by the poles of the hybrid electromagnet, which means, if time delay occurs for calculation of permanence parameters, actual force and actual torque …

Using Latent Semantic Analysis For Automated Keyword Extraction From Large Document Corpora, Tuğba Önal Süzek

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we describe a keyword extraction technique that uses latent semantic analysis (LSA) to identify semantically important single topic words or keywords. We compare our method against two other automated keyword extractors, Tf-idf (term frequency-inverse document frequency) and Metamap, using human-annotated keywords as a reference. Our results suggest that the LSA-based keyword extraction method performs comparably to the other techniques. Therefore, in an incremental update setting, the LSA-based keyword extraction method can be preferably used to extract keywords from text descriptions from big data when compared to existing keyword extraction methods.

Intellimote: A Hybrid Classifier For Classifying Learners' Emotion In A Distributed E-Learning Environment, Lopa Mandal, Rohan Das, Samar Bhattacharya, Pramatha Nath Basu

Turkish Journal of Electrical Engineering and Computer Sciences

A huge collection of textual, graphical, audio, and video contents are readily available on the Internet to be used for the purpose of learning. Sentimental feedbacks of learners posted at the end of many of these contents may be considered as genuine reactions of the learners who have gone through the contents. Such learners' sentiments are important inputs for judging the acceptability of a learning material. Analyzing such feedbacks using sentiment analysis techniques can identify the best reusable learning contents that may be used for developing new courseware. This can significantly reduce the time and effort of authoring, which is …

A Framework For Social Network Sentiment Analysis Using Big Data Analytics, Bharat Sri Harsha Karpurapu

All ETDs from UAB

The primary research of this thesis focused on the development of a Big Data framework for performing sentiment analysis on social networking sites. Over the last decade, social media has been gaining lots of popularity for sharing thoughts and feelings with a user base of over two billion users. Social networking sites such as Twitter, Facebook, and Instagram are increasingly becoming huge repositories of thoughts and opinions on a wide variety of topics. Several public and private organizations, such as Government and companies are attempting to exploit the expressed preferences, opinions, and attitudes regarding politics, commercial products and other matters …

การอ่านทำความเข้าใจด้วยเครื่องเพื่อคำถามที่มีหลายความสัมพันธ์ด้วยวิธีการเรียนรู้เชิงลึก, ณัฐชัย ตรีทศายุธ

Chulalongkorn University Theses and Dissertations (Chula ETD)

การอ่านทำความเข้าใจเพื่อใช้ตอบคำถาม เป็นหนึ่งในเรื่องที่สำคัญและยากที่สุดในงานสายการประมวลผลภาษาธรรมชาติ วิธีการที่ได้รับความนิยมและให้ผลที่ดีที่สุดในปัจจุบัน คือการใช้โมเดลที่นำเอาการเรียนรู้เชิงลึกเข้ามาช่วยตอบ โดยโมเดลจะทำการหาคำที่คล้ายกันระหว่างคำถามและบทความเพื่อนำไปใช้ในการตอบคำถาม แต่โมเดลในรูปแบบนี้จะมีข้อจำกัดที่ไม่สามารถจะตอบคำถามซึ่งคำตอบจะต้องใช้การเชื่อมต่อคำในหลายประโยคเข้าด้วยกัน หรือที่เรียกว่าคำถามที่มีหลายความสัมพันธ์ได้ งานวิจัยชิ้นนี้ต้องการที่จะเสนอแนวทางในการใช้คำอ้างอิงเข้ามาช่วยแก้ปัญหาดังกล่าว รวมถึงยังได้เสนอวิธีการตอบแบบสองทาง และฟังก์ชันต้นทุนจากความยาวของคำตอบเพื่อเพิ่มประสิทธิภาพโดยรวมของระบบ

Respiratory Prediction And Image Quality Improvement Of 4d Cone Beam Ct And Mri For Lung Tumor Treatments, Seonyeong Park

Theses and Dissertations

Identification of accurate tumor location and shape is highly important in lung cancer radiotherapy, to improve the treatment quality by reducing dose delivery errors. Because a lung tumor moves with the patient's respiration, breathing motion should be correctly analyzed and predicted during the treatment for prevention of tumor miss or undesirable treatment toxicity. Besides, in Image-Guided Radiation Therapy (IGRT), the tumor motion causes difficulties not only in delivering accurate dose, but also in assuring superior quality of imaging techniques such as four-dimensional (4D) Cone Beam Computed Tomography (CBCT) and 4D Magnetic Resonance Imaging (MRI). Specifically, 4D CBCT used in CBCT …

A Human Factors Perspective On Learning Programming Languages Using A Second Language Acquisition Approach, Rebecca Rohmeyer, Paula Sanjuan Espejo, Lulu Sun, Christina Frederick

Publications

In this day and age, knowing a programming language is an essential skill to have for those pursuing a career in any of the STEM fields. In most colleges and universities around the world, engineering and computer science students are required to take an introductory course in a programming language. However, many students find these courses intimidating and too challenging. This paper explores a psychological perspective on learning programming languages using Second Language Acquisition (SLA) theories. The paper also describes the basic function of how learning works and how SLA aids in the learning process. This paper also briefly discusses …

Assessment Of Mental Workload: A Comparison Of Machine Learning Methods And Subjective Assessment Techniques, Karim Moustafa, Saturnino Luz, Luca Longo

Articles

Mental workload (MWL) measurement is a complex multidisciplinary research field. In the last 50 years of research endeavour, MWL measurement has mainly produced theory-driven models. Some of the reasons for justifying this trend includes the omnipresent uncertainty about how to define the construct of MWL and the limited use of datadriven research methodologies. This work presents novel research focused on the investigation of the capability of a selection of supervised Machine Learning (ML) classification techniques to produce data-driven computational models of MWL for the prediction of objective performance. These are then compared to two state-of-the-art subjective techniques for the assessment …

Environmental Hazard Identification, Assessment And Control For A Sustainable Maritime Transportation System, Lizzette Marie Pérez Lespier

Doctoral Dissertations

"A demand exists to contribute towards the widening awareness of the need for sustainable maritime development and for coordinated maritime policies worldwide. Maritime shipping is considered the most eco-efficient mean of transportation and yet, is responsible for negative environmental impacts.

This dissertation focuses on developing data-driven decision support tools to evaluate the sustainable performance of MTS by focusing on the elements of the MTS that place stress on the environment. The first research contribution is a System Dynamics simulation model that examines the MTS resiliency after an extreme event and determines the sequence needed to restore the ocean-going port to …

Cognition-Based Approaches For High-Precision Text Mining, George John Shannon

Doctoral Dissertations

"This research improves the precision of information extraction from free-form text via the use of cognitive-based approaches to natural language processing (NLP). Cognitive-based approaches are an important, and relatively new, area of research in NLP and search, as well as linguistics. Cognitive approaches enable significant improvements in both the breadth and depth of knowledge extracted from text. This research has made contributions in the areas of a cognitive approach to automated concept recognition in.

Cognitive approaches to search, also called concept-based search, have been shown to improve search precision. Given the tremendous amount of electronic text generated in our digital …

Assessing The Usefulness Of Different Feature Sets For Predicting The Comprehension Difficulty Of Text, Brian Mac Namee, John D. Kelleher, Noel Fitzpatrick

Conference papers

Within English second language acquisition there is an enthusiasm for using authentic text as learning materials in classroom and online settings. This enthusiasm, however, is tempered by the difficulty in finding authentic texts at suitable levels of comprehension difficulty for specific groups of learners. An automated way to rate the comprehension difficulty of a text would make finding suitable texts a much more manageable task. While readability metrics have been in use for over 50 years now they only capture a small amount of what constitutes comprehension difficulty. In this paper we examine other features of texts that are related …

Get Rid Of Your Student's Fear And Intimidation Of Learning A Programming Language, Christina Frederick, Matt B. Pierce, Andrew Calvin Griggs, Lulu Sun, Li Ding

Publications

Knowledge of computer programming is very beneficial and often required for engineering students. Unfortunately, students frequently experience fear and intimidation regarding introductory programming courses. Second language acquisition (SLA) techniques have shown promise as a means of content delivery in programming courses. Blended learning environments are also becoming increasingly popular in course frameworks. This workshop will discuss the application of second language acquisition in a blended learning environment (SLA-aBLe) and will examine the effectiveness of using SLA techniques to teach introductory programming. The proposed workshop will also share instructor experience(s), provide course materials, and review student outcomes from this two year …

Curriculum Innovation: Incorporating The Kern Engineering Entrepreneurial Network (Keen) Framework Into Online Discussions, Lisa Bosman, Brooke K. Mayer, Patrick J. Mcnamara

Civil and Environmental Engineering Faculty Research and Publications

The purpose of this study was to respond to the following research question: How does the Kern Engineering Entrepreneurial Network (KEEN) framework build interest in technical topic areas, impact student learning outcomes, and develop the entrepreneurial mindset when applied to the engineering classroom? The KEEN framework was developed to combine the entrepreneurial mindset with engineering education to produce a more valuable, strategically prepared engineer, rather than simply an “obedient engineer”. The framework proposes that the entrepreneurial mindset of students is increased by promoting curiosity, encouraging connections, and creating value. The results from this work provide insight into the impact and …

Using Conversation Analysis In Data-Driven Aviation Training With Large-Scale Qualitative Datasets, William A. Tuccio, Maurice Nevile

Journal of Aviation/Aerospace Education & Research

This paper contributes to a growing body of work related to the Conversation Analytic Role-play Method (CARM) by studying the primary flight instruction environment to create training interventions related to radio communications and flight instruction practices. Framed in the context of conversation analysis, an approach to the detailed analysis of naturally occurring interaction, the large-scale, long-duration qualitative audio/video data collection and coding methodology is discussed, followed by trends identified in the ongoing study. The concept of CARM “trainables” are discussed with examples. The study shows that large-scale qualitative datasets may be leveraged to produce valuable data-driven training interventions.

Project Managers' Strategies For Megaproject Success, Nkenamchi Benedict Oputa

Walden Dissertations and Doctoral Studies

In Africa, most oil and gas megaprojects exceed their original budget and time deadlines despite advancement in project management processes and systems. This study explored strategies project managers used for megaprojects' success in the oil and gas industry in Nigeria, from the perspectives of the owner and contractor organizations. Multiple case study design was utilized to collect data by asking open-ended questions in separate interviews with 4 project managers. Archival project data was also reviewed to eliminate information incongruences. The conceptual framework for the study is the contingency theory that there is no universal management structure for every project. The …

Janus Realized: The Use Of Social Media As A Means Of Transparency Nuclear Communication To The Public, Frances Bachstein

International Journal of Nuclear Security

No abstract provided.