Digital Commons Network^™

Trmor: A Finite-State-Based Morphological Analyzer For Turkish, Ayla Kayabaş, Helmut Schmi̇d, Ahmet Ercan Topcu, Özkan Kiliç

Turkish Journal of Electrical Engineering and Computer Sciences

Morphological analysis is an important component of natural language processing systems like spelling correction tools, parsers, machine translation systems, and dictionary tools. In this paper, we present TRMOR, a morphological analyzer for Turkish, which uses the SFST tool (Stuttgart Finite-State Transducer). TRMOR can be freely used for academic research (see http://www.cis.uni-muenchen.de/~schmid/tools/SFST/). It covers a large part of Turkish morphology including inflection, derivation, and some compounding. It uses morphotactic and morphophonological rules and a stem lexicon. We describe the morphological structure of Turkish, explain the phonological and morphological rules implemented in TRMOR, evaluate the system, and test it in special cases. …

Youtube’S Terms Of Service: Posthumanism, Algorithms, And Professional Writing, Sarah Bresnahan

Graduate Research Theses & Dissertations

This thesis aims to examine YouTube’s Terms of Service as it applies to content creators (known as YouTubers) who use the platform as a means of financial gain and how YouTube’s demonetization policy via an algorithm is negatively affecting them. I conducted a case study featuring one creator, Michelle Guido, and attempted to determine why some of her content is demonetized when it fulfills YouTube’s content standards for monetization. This study is meant as an examination through the lens of Dr. N. Katherine Hayles’s theory of posthumanism as stated in her book, How We Became Posthuman, and will offer insight …

Quantum Metalanguage And The New Cognitive Synthesis, Alexey V. Melkikh, Andrei Khrennikov, Roman V. Yampolskiy

Faculty and Staff Scholarship

Problems with mechanisms of thinking and cognition in many ways remain unresolved. Why are a priori inferences possible? Why can a human understand but a computer cannot? It has been shown that when creating new concepts, generalization is contradictory in the sense that to be created concepts must exist a priori, and therefore, they are not new. The process of knowledge acquisition is also contradictory, as it inevitably involves recognition, which can be realized only when there is an a priori standard. Known approaches of the framework of artificial intelligence (in particular, Bayesian) do not determine the origins of knowledge, …

Adaptive Microphone Array Systems With Neural Network Applications, Jazmine Marisol Covarrubias

Open Access Theses & Dissertations

A microphone array integrated with a neural network framework is proposed to enhance and optimize speech signals derived from environments prone to noise and room reflections that cause reverberation. Microphone arrays provide a way to capture spatial acoustic information for extracting voice input from ambient noise. In this study, we utilize and analyze established signal processing methods combined with different neural network architectures to achieve denoised and dereverberated speech signal results that are comparable with their clean, anechoic versions. The first stage of the proposed system involves using datasets containing anechoic speech recordings of speech utterances and convolving them with …

Smart Control Of Automatic Voltage Regulators Using K-Means Clustering, Brook Abegaz, J. Kueber

Engineering Science Faculty Publications

The future cyber physical systems consist of voltage regulators distributed across wide geographical areas. In this paper, a smart control approach of voltage regulators is presented for cyber physical system applications. The approach is implemented using K-means clustering algorithms that use data from voltage and current sensors, compute the correlation of changes across the regulators and generate a proportional feedback. Advanced estimation methods are used in cases where the data from the sensors was not available. The results show that the approach could be used to improve the performance of networked, power dependent systems by 94.5% in terms of overshoot …

Thai Spelling Correction And Word Normalization On Social Text Using A Two-Stage Pipeline With Neural Contextual Attention, Anuruth Lertpiya

Chulalongkorn University Theses and Dissertations (Chula ETD)

Text correction systems (e.g., spell checkers) have been used to improve the quality of computerized text by detecting and correcting errors. However, the task of performing spelling correction and word normalization (text correction) for Thai social media text has remained largely unexplored. In this thesis, we investigated how current text correction systems perform on correcting errors and word variances in Thai social texts and propose a method designed for this task. We have found that currently available Thai text correction systems are insufficiently robust for correcting spelling errors and word variances, while the text correctors designed for English grammatical error …

Utilizing User-Generated Content To Analyze Tours And Activities In Bangkok: A Tripadvisor Case Study, Naina Chugh

Chulalongkorn University Theses and Dissertations (Chula ETD)

The overarching goal of this paper is to gain visibility on tourist preferences and whether or not the needs of tourists are being met. With the Travel and Tourism (T&T) sector being the backbone to the global economy and the sector becoming more saturated and competitive, insights on T&T are vital now, more than ever. The rise of social media and user-generated content has effectuated the opportunity for a systematic analysis of tourist preferences via user-generated content. This paper is focused on gaining insights into tourism in Bangkok, Thailand through user-generated content scraped from TripAdvisor’s online reviews of tours and …

Differential Mobility Classifiers In The Non-Ideal Assembly, Thamir Alsharifi

Theses and Dissertations

The differential mobility classifier (DMC) is one of the core components in electrical mobility particle sizers for sizing sub-micrometer particles. Designing the DMC requires knowledge of the geometrical and constructional imperfection (or tolerance). Studying the effects of geometrical imperfection on the performance of the DMC is necessary to provide manufacturing tolerance and it helps to predict the performance of geometrically imperfect classifiers, as well as providing a calibration curve for the DMC. This thesis was accomplished via studying the cylindrical classifier and the parallel plate classifier. The numerical model was built using the most recent versions of COMSOL Multiphysics^{® …}

Multi-Element Long Distance Dependencies: Using Spk Languages To Explore The Characteristics Of Long-Distance Dependencies, Abhijit Mahalunkar, John Kelleher

Conference papers

In order to successfully model Long Distance Dependencies (LDDs) it is necessary to under-stand the full-range of the characteristics of the LDDs exhibited in a target dataset. In this paper, we use Strictly k-Piecewise languages to generate datasets with various properties. We then compute the characteristics of the LDDs in these datasets using mutual information and analyze the impact of factors such as (i) k, (ii) length of LDDs, (iii) vocabulary size, (iv) forbidden strings, and (v) dataset size. This analysis reveal that the number of interacting elements in a dependency is an important characteristic of LDDs. This leads us …

Music Information Retrieval For Irish Traditional Music Automatic Analysis Of Harmonic, Rhythmic, And Melodic Features For Efficient Key-Invariant Tune Recognition, Pierre Beauguitte

Doctoral

Music making and listening practices increasingly rely on techno logy,and,asaconsequence,techniquesdevelopedinmusicinformation retrieval (MIR) research are more readily available to end users, in par ticular via online tools and smartphone apps. However, the majority of MIRresearchfocusesonWesternpopandclassicalmusic,andthusdoes not address specificities of other musical idioms. Irishtraditionalmusic(ITM)ispopularacrosstheglobe,withregular sessionsorganisedonallcontinents. ITMisadistinctivemusicalidiom, particularly in terms of heterophony and modality, and these character istics can constitute challenges for existing MIR algorithms. The bene fitsofdevelopingMIRmethodsspecificallytailoredtoITMisevidenced by Tunepal, a query-by-playing tool that has become popular among ITM practitioners since its release in 2009. As of today, Tunepal is the state of the art for tune recognition in ITM. The research in …

Eaglebot: A Chatbot Based Multi-Tier Question Answering System For Retrieving Answers From Heterogeneous Sources Using Bert, Muhammad Rana

College of Graduate Studies: Theses & Dissertations

This paper proposes to tackle Question Answering on a specific domain by developing a multi-tier system using three different types of data storage for storing answers. For testing our system on University domain we have used extracted data from Georgia Southern University website. For the task of faster retrieval we have divided our answer data sources into three distinct types and utilized Dialogflow's Natural Language Understanding engine for route selection. We compared different word and sentence embedding techniques for making a semantic question search engine and BERT sentence embedding gave us the best result and for extracting answer from a …

Application Of Computational Intelligence To Explore And Analyze System Architecture And Design Alternatives, Gene Lesinski

Doctoral Dissertations

"Systems Engineering involves the development or improvement of a system or process from effective need to a final value-added solution. Rapid advances in technology have led to development of sophisticated and complex sensor-enabled, remote, and highly networked cyber-technical systems. These complex modern systems present several challenges for systems engineers including: increased complexity associated with integration and emergent behavior, multiple and competing design metrics, and an expansive design parameter solution space. This research extends the existing knowledge base on multi-objective system design through the creation of a framework to explore and analyze system design alternatives employing computational intelligence. The first research …

Intellectual Output 1 (I01): Skillsfocus 2030: A Model Of Skills And Attributes Needed For Engineers To Achieve The Sdgs, Una Beagon, Brian Bowe, Klara Kövesi, Christiane Gillet, Brad Tabas, Bente Nørgaard, Claus Spliid, Riitta Lehtinen

Reports

No abstract provided.

Report On The Future Role Of Engineers In Society And The Skills And Competences Engineering Will Require, Brad Tabas, Una Beagon, Klara Kövesi

Reports

This literature review outlines the current state of the art knowledge in relation to the influence of diversity, attractiveness of the engineering profession and the skills and competencies required of engineers to achieve the SDGs. We aim to answer the overall research question: How do engineering educators develop new learning and teaching approaches (methods) that will attract a diverse group of students (and mature learners) whilst achieving the SDGs in 2030? The main objective of the A-STEP 2030 project is to create an attractive and fascinating learning environment to encourage young people with diverse backgrounds to engage in engineering studies …

Analyzing Twitter Feeds To Facilitate Crises Informatics And Disaster Response During Mass Emergencies, Arshdeep Kaur

Dissertations

It is a common practice these days for general public to use various micro-blogging platforms, predominantly Twitter, to share ideas, opinions and information about things and life. Twitter is also being increasingly used as a popular source of information sharing during natural disasters and mass emergencies to update and communicate the extent of the geographic phenomena, report the affected population and casualties, request or provide volunteering services and to share the status of disaster recovery process initiated by humanitarian-aid and disaster-management organizations. Recent research in this area has affirmed the potential use of such social media data for various disaster …

Experimental Study Of Low Cycle Fatigue Properties For Epoxy Resins With Dibutyl Phthalate (Dbp), Zhi Wang, Jiajia Zhou, Lianjian Song, Long Li

Department of Civil, Environmental, and Geospatial Engineering Publications

In order to improve the toughness of traditional epoxy resin, dibutyl phthalate (DBP) was introduced into the epoxy resin. The static mechanical performance of plasticized and unplasticized epoxy resin was evaluated. The test results showed that the DBP modified epoxy resin can obtain a higher toughness than conventional epoxy resin, but the elastic modulus and the tensile strength were slightly reduced. The low cycle fatigue test results indicated that the stress ratio and the stress level were two critical factors of fatigue life, which was increased with the growth of stress ratio. It was also found that the fatigue life …

Fuzzy-Multiple Tasks Of Multicriterial Optimization In Risk Conditions ., T.F Bekmuratov, D.T Mukhamedieva

Chemical Technology, Control and Management

Approaches to solving the optimization problem and solving a fuzzy multicriteria optimization problem under risk conditions are considered. To assess risks in fuzzy conditions, it is proposed to supplement the system of constraints of a standard decision-making task with a set of restrictions on possible losses, namely, for selected scenarios, to build a model of their consequences (damages) as functions of control parameters and impose expert limitations on an acceptable level of relative damage for each scenario.

Integrated Intelligent Systems For Industrial Automation: The Challenges Of Industry 4.0, Information Granulation And Understanding Agents ., N.R Yusupbekov, V.B Tarassov

Chemical Technology, Control and Management

The objective of the paper consists in considering the challenges of new automation paradigm Industry 4.0 and reviewing the-state-of-the-art in the field of its enabling information and communication technologies, including Cyberphysical Systems, Cloud Computing, Internet of Things and Big Data. Some ways of multi-dimensional, multi-faceted industrial Big Data representation and analysis are suggested. The fundamentals of Big Data processing with using Granular Computing techniques have been developed. The problem of constructing special cognitive tools to build artificial understanding agents for Integrated Intelligent Enterprises has been faced.

Efficient Machine Learning: Models And Accelerations, Zhe Li

Dissertations - ALL

One of the key enablers of the recent unprecedented success of machine learning is the adoption of very large models. Modern machine learning models typically consist of multiple cascaded layers such as deep neural networks, and at least millions to hundreds of millions of parameters (i.e., weights) for the entire model. The larger-scale model tend to enable the extraction of more complex high-level features, and therefore, lead to a significant improvement of the overall accuracy. On the other side, the layered deep structure and large model sizes also demand to increase computational capability and memory requirements. In order to achieve …

2013 - Greater Monterey County Integrated Regional Water Management - Disadvantaged Community And Tribal Needs Assessment

Miscellaneous Monterey and San Luis Obispo County Documents and Reports

A 2013 Disadvantaged Community and Tribal Needs Assessment as they relate to water management in the Greater Monterey County Integrated Regional Water Management process in the planning region thus informing future project development.

A Fuzzy Based Model For Standardized Sustainability Assessment Of Photovoltaic Cells, Muath Bani Salim, Dervis Emre Demirocak, Nael Barakat

Mechanical Engineering Faculty Publications and Presentations

In this paper, a new environmental sustainability indicator (ESI) is proposed to evaluate photovoltaic (PV) cells utilizing Life Cycle Analysis (LCA) principles. The proposed indicator is based on a model that employs a fuzzy logic algorithm to combine multiple factors, usually used in multiple LCAs, and produce results allowing a comprehensive interpretation of LCA phase sub-results leading to standardized comparisons of various PV cells. Such comparisons would be essential for policymakers and PV cell manufacturers and users, as they allow for fair assessment of the environmental sustainability of a particular type of PV with multiple factors. The output of the …

Second Grade Students Learn About Civil Engineers And Erosion, Andrea Earline Anderson, Jessica A. Meier

Journal of STEM Arts, Crafts, and Constructions

The integration of art into curricula focused on teaching science is a new perspective in education designed to reach a broader range of students. The current study examined the process of second-grade students participating in science and art activities through qualitative content analysis. The subjects of science and art were not taught to the students separately, rather, students engaged in both subjects simultaneously, in an integrated manner. Participants were 23 second-grade students (11 female and 12 male; age range 7 to 8 years) who were learning about erosion through sketching and creative construction and the work of civil engineers through …

Modeling Movement Decisions In Networks: A Discrete Choice Model Approach, Larry Lin Junjie

Dissertations and Theses Collection (Open Access)

In this dissertation, we address the subject of modeling and simulation of agents and their movement decision in a network environment. We emphasize the development of high quality agent-based simulation models as a prerequisite before utilization of the model as an evaluation tool for various recommender systems and policies. To achieve this, we propose a methodological framework for development of agent-based models, combining approaches such as discrete choice models and data-driven modeling.

The discrete choice model is widely used in the field of transportation, with a distinct utility function (e.g., demand or revenue-driven). Through discrete choice models, the movement decision …

Supporting Adolescent Metacognition In Engineering Design Through Scripted Prompts From Peer Tutors: A Comparative Case Study, Kristin Marie Strong

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

In 2013, developers of the Next Generation Science Standards implemented national K-12 directives and elevated engineering design to the level of scientific inquiry. Teaching design, however, is challenging to educators due to the complex nature of design problems, which cannot be solved via simple algorithms. Solving design problems requires a more reflective and iterative approach that emphasizes metacognitive skills like planning, monitoring, and taking another person’s perspective. Educators are further challenged by children’s immature metacognitive skills, which may be insufficient to engage in the entire design process.

A qualitative study of paired seventh graders demonstrated a pragmatic learning activity for …

A Comparative Study Of Defeasible Argumentation And Non-Monotonic Fuzzy Reasoning For Elderly Survival Prediction Using Biomarkers, Lucas Rizzo, Ljiljana Majnaric, Luca Longo

Conference papers

Computational argumentation has been gaining momentum as a solid theoretical research discipline for inference under uncertainty with incomplete and contradicting knowledge. However, its practical counterpart is underdeveloped, with a lack of studies focused on the investigation of its impact in real-world settings and with real knowledge. In this study, computational argumentation is compared against non-monotonic fuzzy reasoning and evaluated in the domain of biological markers for the prediction of mortality in an elderly population. Different non-monotonic argument-based models and fuzzy reasoning models have been designed using an extensive knowledge base gathered from an expert in the field. An analysis of …

Web-Based Archaeology And Collaborative Research, Fabrizio Galeazzi, Heather Richards-Rissetto

Department of Anthropology: Faculty Publications

While digital technologies have been part of archaeology for more than fifty years, archaeologists still look for more efficient methodologies to integrate digital practices of fieldwork recording with data management, analysis, and ultimately interpretation.This Special Issue of the Journal of Field Archaeology gathers international scholars affiliated with universities, organizations, and commercial enterprises working in the field of Digital Archaeology. Our goal is to offer a discussion to the international academic community and practitioners. While the approach is interdisciplinary, our primary audience remains readers interested in web technology and collaborative platforms in archaeology

A Multi-Task Approach To Incremental Dialogue State Tracking, Anh Duong Trinh, Robert J. Ross, John D. Kelleher

Conference papers

Incrementality is a fundamental feature of language in real world use. To this point, however, the vast majority of work in automated dialogue processing has focused on language as turn based. In this paper we explore the challenge of incremental dialogue state tracking through the development and analysis of a multi-task approach to incremental dialogue state tracking. We present the design of our incremental dialogue state tracker in detail and provide evaluation against the well known Dialogue State Tracking Challenge 2 (DSTC2) dataset. In addition to a standard evaluation of the tracker, we also provide an analysis of the Incrementality …

Real-Time Facial Expression And Speech Emotion Recognition App Development On Mobile Phones Using Cloud Computing, Humaid Saif Saeed Alasli Alshamsi

Theses and Dissertations

Emotion plays a vital role in humans’ daily lives. Understanding emotions and recognizing how to react to others’ feelings are fundamental to engaging in successful social interactions. Emotion recognition through facial expression and speech play a significant role in human communication. This subject is becoming important in academic research as new techniques such as emotion recognition from speech context inspire us to recognize how emotions are related to the content we are uttering. The demand and importance of emotion recognition have highly increased in many applications in recent years, such as video games, human-computer interactions, cognitive computing, and affective computing. …

An Interpretable Neural Fuzzy Inference System For Predictions Of Underpricing In Initial Public Offerings, Di Wang, Xiaolin Qian, Chai Quek, Ah-Hwee Tan, Chunyan Miao, Xiaofeng Zhang, Geok See Ng, You Zhou

Research Collection School Of Computing and Information Systems

Due to their aptitude in both accurate data processing and human comprehensible reasoning, neural fuzzy inference systems have been widely adopted in various application domains as decision support systems. Especially in real-world scenarios such as decision making in financial transactions, the human experts may be more interested in knowing the comprehensive reasons of certain advices provided by a decision support system in addition to how confident the system is on such advices. In this paper, we apply an integrated autonomous computational model termed genetic algorithm and rough set incorporated neural fuzzy inference system (GARSINFIS) to predict underpricing in initial public …

Have You Heard Of Shpe? | College Of Engineering, Usu College Of Engineering

College of Engineering News

The Society of Hispanic Professional Engineers is quickly becoming one of Utah State University’s most active student organizations.