Digital Commons Network^™

Query Expansion Techniques For Enterprise Search, Eric M. Domke

Masters Theses

Although web search remains an active research area, interest in enterprise search has waned. This is despite the fact that the market for enterprise search applications is expected to triple within the next six years, and that knowledge workers spend an average of 1.6 to 2.5 hours each day searching for information. To improve search relevancy, and hence reduce this time, an enterprise- focused application must be able to handle the unique queries and constraints of the enterprise environment. The goal of this thesis research was to develop, implement, and study query expansion techniques that are most effective at improving …

A Framework For Clustering And Adaptive Topic Tracking On Evolving Text And Social Media Data Streams., Gopi Chand Nutakki

Electronic Theses and Dissertations

Recent advances and widespread usage of online web services and social media platforms, coupled with ubiquitous low cost devices, mobile technologies, and increasing capacity of lower cost storage, has led to a proliferation of Big data, ranging from, news, e-commerce clickstreams, and online business transactions to continuous event logs and social media expressions. These large amounts of online data, often referred to as data streams, because they get generated at extremely high throughputs or velocity, can make conventional and classical data analytics methodologies obsolete. For these reasons, the issues of management and analysis of data streams have been researched extensively …

Identifying Restaurants Proposing Novel Kinds Of Cuisines: Using Yelp Reviews, Haritha Akella

Boise State University Theses and Dissertations

These days with TV-shows and starred chefs, new kinds of cuisines appear in the market. The main cuisines like French, Italian, Japanese, Chinese and Indian are always appreciated but they are no longer the most popular. The new trend is the fusion cuisine, which is obtained by combining different main cuisines. The opening of a new restaurant proposing new kinds of cuisine produces a lot of excitement in people. They feel the need to try it and be part of this new culture. Yelp is a platform which publishes crowd sourced reviews about different businesses, in particular, restaurants. For some …

Coupling K-12 Music Education With Science, Technology, Engineering And Math (Stem) Curricula: Implementation Of A Stemusic Outreach Program, Mallory Maestri

Civil Engineering Undergraduate Honors Theses

Many studies have investigated the effects of music on evoking human emotions and diverse types of brain responses. One study by Juslin and Vastfjall indicates that hearing music can stimulate brain stem reflexes, create emotional contagion, recall episodic memories and provoke visual imagery. Due to the influence music has on human brain waves, researchers have been studying the effect of music on enhancing the spatial abilities of young students. Science, Technology, Engineering and Math (STEM) professions rely heavily on spatial skills. Research on the connection of music with spatial skills proposes that when the brain processes rhythm a “mental rotation” …

Development Of Some Scalable Pattern Recognition Algorithms For Real Life Data Analysis, Partha Garai

Doctoral Theses

A huge amount of data is being generated continuously as a result of recent advancement and wide use of high-throughput technologies. With the rapid increase in size of data distributed worldwide, understanding the data has become critical. In this regard, dimensionality reduction and clustering have become the necessary preprocessing steps of multiple research areas and applications. One of the important problems of real life large data sets is uncertainty. Some of the sources of this uncertainty include imprecision in computation and vagueness in class denitions. The uncertainty may also be present in the denition of class membership function. In this …

Document Clustering, David Anastasiu, Andrea Tagarelli

Faculty Publications

In a world flooded with information, document clustering is an important tool that can help categorize and extract insight from text collections. It works by grouping similar documents, while simultaneously discriminating between groups. In this article, we provide a brief overview of the principal techniques used to cluster documents, and introduce a series of novel deep-learning based methods recently designed for the document clustering task. In our overview, we point the reader to salient works that can provide a deeper understanding of the topics discussed.

Selecting Technological Alternatives For Regulatory Compliance Towards Emissions Reduction From Shipping : An Integrated Fuzzy Multi-Criteria Decision-Making Approach Under Vague Environment, Khanh Quang Bui

World Maritime University Dissertations

No abstract provided.

Hidden Curriculum, Language, And Math: How To Help Emergent Bilinguals To Succeed In Stem, Marialuisa Di Stefano, Idalis Villanueva

Engineering Education Faculty Publications

No abstract provided.

Application Of P300 Event-Related Potential In Brain-Computer Interface, Ali Raider, Reza Fazel-Rezai

Electrical Engineering Faculty Publications

The primary purpose of this chapter is to demonstrate one of the applications of P300 event-related potential (ERP), i.e., brain-computer interface (BCI). Researchers and students will find the chapter appealing with a preliminary description of P300 ERP. This chapter also appreciates the importance and advantages of noninvasive ERP technique. In noninvasive BCI, the P300 ERPs are extracted from brain electrical activities [electroencephalogram (EEG)] as a signature of the underlying electrophysiological mechanism of brain responses to the external or internal changes and events. As the chapter proceeds, topics are covered on more relevant scholarly works about challenges and new directions in …

Sourcevote: Fusing Multi-Valued Data Via Inter-Source Agreements, Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Mahmoud Barhamgi, Lina Yao, Anne H.H. Ngu

Research Collection School Of Computing and Information Systems

Data fusion is a fundamental research problem of identifyingtrue values of data items of interest from conflicting multi-sourceddata. Although considerable research efforts have been conducted on thistopic, existing approaches generally assume every data item has exactlyone true value, which fails to reflect the real world where data items withmultiple true values widely exist. In this paper, we propose a novel approach,SourceVote, to estimate value veracity for multi-valued data items.SourceVote models the endorsement relations among sources by quantifyingtheir two-sided inter-source agreements. In particular, two graphs areconstructed to model inter-source relations. Then two aspects of sourcereliability are derived from these graphs and …

Sourcevote: Fusing Multi-Valued Data Via Inter-Source Agreements, Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Mahmoud Barhamgi, Lina Yao, Anne H.H. Ngu

Research Collection School Of Computing and Information Systems

Data fusion is a fundamental research problem of identifying true values of data items of interest from conflicting multi-sourced data. Although considerable research efforts have been conducted on this topic, existing approaches generally assume every data item has exactly one true value, which fails to reflect the real world where data items with multiple true values widely exist. In this paper, we propose a novel approach,SourceVote, to estimate value veracity for multi-valued data items. SourceVote models the endorsement relations among sources by quantifying their two-sided inter-source agreements. In particular, two graphs are constructed to model inter-source relations. Then two aspects …

State Feedback Of Complex Systems Using Fuzzy Cognitive Maps, Vassiliki Mpelogianni, Ioannis Arvanitakis, Peter P. Groumpos

UBT International Conference

Complex systems have become a research area with increasing interest over the last years. The emergence of new technologies, the increase in computational power with reduced resources and cost, the integration of the physical world with computer based systems has created the possibility of significantly improving the quality of life of humans. While a significant degree of automation within these systems exists and has been provided in the past decade with examples of the smart homes and energy efficient buildings, a paradigm shift towards autonomy has been noted. The need for autonomy requires the extraction of a model; while a …

What Does Explainable Ai Really Mean? A New Conceptualization Of Perspectives, Derek Doran, Sarah Schulz, Tarek R. Besold

Computer Science and Engineering Faculty Publications

We characterize three notions of explainable AI that cut across research fields: opaque systems that offer no insight into its algo- rithmic mechanisms; interpretable systems where users can mathemat- ically analyze its algorithmic mechanisms; and comprehensible systems that emit symbols enabling user-driven explanations of how a conclusion is reached. The paper is motivated by a corpus analysis of NIPS, ACL, COGSCI, and ICCV/ECCV paper titles showing differences in how work on explainable AI is positioned in various fields. We close by introducing a fourth notion: truly explainable systems, where automated reasoning is central to output crafted explanations without requiring human …

An Investigation Of Information Sought By Caregivers Of Alzheimer’S Patients On Online Peer-Support Groups, Emma Scharett, Kapil Chalil Madathil, Snehal Lopes, Hunter Rogers, Sruthy Agnisarman, Shraddhaa Narasimha, Aparna Ashok, Cheryl Dye

Publications

Alzheimer’s caregivers seek social support through online communities to deal with their issues. The research team conducted a content analysis of ALZConnected.org to investigate the characteristics of information searched by caregivers and responses received. Two-hundred fifty posts and related responses were randomly selected and analyzed using a classification tool derived from the analysis of 500 posts and related responses spanning a yearlong period. The Linguistic Inquiry and Word Count (LIW C) generated an average tone rating of 25.94 for the posts and 52.69 for the responses. The findings highlighted the caregiver’s need for emotional support (59.6%), and confusion about Alzheimer’s …

Semantic Reasoning In Zero Example Video Event Retrieval, M. H. T. De Boer, Yi-Jie Lu, Hao Zhang, Klamer Schutte, Chong-Wah Ngo, Wessel Kraaij

Research Collection School Of Computing and Information Systems

Searching in digital video data for high-level events, such as a parade or a car accident, is challenging when the query is textual and lacks visual example images or videos. Current research in deep neural networks is highly beneficial for the retrieval of high-level events using visual examples, but without examples it is still hard to (1) determine which concepts are useful to pre-train (Vocabulary challenge) and (2) which pre-trained concept detectors are relevant for a certain unseen high-level event (Concept Selection challenge). In our article, we present our Semantic Event Retrieval Systemwhich (1) shows the importance of high-level concepts …

Improving Speech Recognition For Interviews With Both Clean And Telephone Speech, Sung Woo Choi

Journal of Undergraduate Research at Minnesota State University, Mankato

High quality automatic speech recognition (ASR) depends on the context of the speech. Cleanly recorded speech has better results than speech recorded over telephone lines. In telephone speech, the signal is band-pass filtered which limits frequencies available for computation. Consequently, the transmitted speech signal may be distorted by noise, causing higher word error rates (WER). The main goal of this research project is to examine approaches to improve recognition of telephone speech while maintaining or improving results for clean speech in mixed telephone-clean speech recordings, by reducing mismatches between the test data and the available models. The test data includes …

Probabilistic Graphical Models Follow Directly From Maximum Entropy, Anh H. Ly, Francisco Zapata, Olac Fuentes, Vladik Kreinovich

Departmental Technical Reports (CS)

Probabilistic graphical models are a very efficient machine learning technique. However, their only known justification is based on heuristic ideas, ideas that do not explain why exactly these models are empirically successful. It is therefore desirable to come up with a theoretical explanation for these models' empirical efficiency. At present, the only such explanation is that these models naturally emerge if we maximize the relative entropy; however, why the relative entropy should be maximized is not clear. In this paper, we show that these models can also be obtained from a more natural -- and well-justified -- idea of maximizing …

Spatial Thinking In The Engineering Curriculum: An Investigation Of The Relationship Between Problem Solving And Spatial Skills Among Engineering Students., Gavin Duffy

Doctoral

Long considered a primary factor of intelligence, spatial ability has been shown to correlate strongly with success in engineering education, yet is rarely included as a learning outcome in engineering programmes. A clearer understanding of how and why spatial ability impacts on performance in science, technology, engineering and mathematics (STEM) subjects would allow educators to determine if spatial skills development merits greater priority in STEM curricula. The aim of this study is to help inform that debate by shedding new light on the role of spatial thinking in STEM learning and allow teaching practice and curriculum design to be informed …

An Unsupervised Multilingual Approach For Online Social Media Topic Identification, Siaw Ling Lo, Raymond Chiong, David Cornforth

Research Collection School Of Computing and Information Systems

Social media data can be valuable in many ways. However, the vast amount of content shared and the linguistic variants of languages used on social media are making it very challenging for high-value topics to be identified. In this paper, we present an unsupervised multilingual approach for identifying highly relevant terms and topics from the mass of social media data. This approach combines term ranking, localised language analysis, unsupervised topic clustering and multilingual sentiment analysis to extract prominent topics through analysis of Twitter’s tweets from a period of time. It is observed that each of the ranking methods tested has …

In Search Of Homo Sociologicus, Yunqi Xue

Dissertations, Theses, and Capstone Projects

The subject of this dissertation is to build an epistemic logic system that is able to show the spreading of knowledge and beliefs in a social network that contains multiple subgroups. Epistemic logic is the study of logical systems that express mathematical properties of knowledge and belief. In recent years, there have been increasing number of new epistemic logic systems that are focused on community properties such as knowledge and belief adoption among friends.

We are interested in revisable and actionable social knowledge/belief that leads to a large group action. Instead of centralized coordination, bottom-up approach is our focus. We …

Improving Instructor Quality Using The Conversation Analytic Role-Play Method (Carm), William A. Tuccio Ph.D.

National Training Aircraft Symposium (NTAS)

The audience will learn about Stokoe’s Conversation Analytic Role-play Method (CARM) (http://www.carmtraining.org) and how it has been used to study and improve talk-in-interaction in professional settings. CARM is a proven, research-based methodology which collects large volumes of recorded audio and/or video particular to a professional setting and then uses detailed transcription and conversation analysis to identify systematic patterns of interaction and problems thereof. Actual excerpts from the dataset are appropriately anonymized and used by facilitators in a workshop setting to create authentic role-play.

The presentation will explain how CARM has been applied to help improve flight instructor teaching …

Intelligent Computation And Dsp-Based Landing Control, Jih-Gau Juang, Hou-Kai Chiou, Chia-Ling Lee

Journal of Marine Science and Technology–Taiwan

This paper presents several digital signal processor (DSP) based intelligent controllers for aircraft automatic landing systems (ALSs). Proportional-Integral-Derivative (PID) control law is adopted in the intelligent controller design. A fuzzy cerebellar model articulation controller (CMAC) is utilized to compensate for the PID control signal. Control gains are selected by evolutionary computation. The controllers' tracking performance of preset landing paths and capability to adaptively respond to different disturbances are demonstrated through hardware simulations. Different evolution methods, namely Adewuya crossover, arithmetical crossover, average crossover, convex crossover and blend crossover are utilized to analyze the controllers’ performances in terms of optimal parameter search. …

Parallel Real-Time Scheduling For Latency-Critical Applications, Jing Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

In order to provide safety guarantees or quality of service guarantees, many of today's systems consist of latency-critical applications, e.g. applications with timing constraints. The problem of scheduling multiple latency-critical jobs on a multiprocessor or multicore machine has been extensively studied for sequential (non-parallizable) jobs and different system models and different objectives have been considered. However, the computational requirement of a single job is still limited by the capacity of a single core. To provide increasingly complex functionalities of applications and to complete their higher computational demands within the same or even more stringent timing constraints, we must exploit the …

Easier Parallel Programming With Provably-Efficient Runtime Schedulers, Robert Utterback

McKelvey School of Engineering Graduate Student Theses & Dissertations

Over the past decade processor manufacturers have pivoted from increasing uniprocessor performance to multicore architectures. However, utilizing this computational power has proved challenging for software developers. Many concurrency platforms and languages have emerged to address parallel programming challenges, yet writing correct and performant parallel code retains a reputation of being one of the hardest tasks a programmer can undertake.

This dissertation will study how runtime scheduling systems can be used to make parallel programming easier. We address the difficulty in writing parallel data structures, automatically finding shared memory bugs, and reproducing non-deterministic synchronization bugs. Each of the systems presented depends …

Combining Forces: Utilizing Expertise From Applied Linguistics And Flight Instruction For Better Atc Communications, Jennifer L. Roberts, Muhammad T. Omar

National Training Aircraft Symposium (NTAS)

ATC communications are a complex mix of FAA phraseology and plain English. The dynamic demands of a pilot’s workload, simultaneously operating the aircraft, managing checklists, and maintaining situational awareness, make this domain of communication particularly challenging for many non-native English speakers. The dramatic growth of aviation in regions of the world in which English is not the native language has increased the need for flight training organizations to address and manage language issues. This paper outlines a new initiative at Embry-Riddle Aeronautical University to support flight students with the English language necessary for successful flight training. Two subject matter experts …

Separation Of Vocal And Non-Vocal Components From Audio Clip Using Correlated Repeated Mask (Crm), Mohan Kumar Kanuri

LSU New Orleans Theses and Dissertations

Extraction of singing voice from music is one of the ongoing research topics in the field of speech recognition and audio analysis. In particular, this topic finds many applications in the music field, such as in determining music structure, lyrics recognition, and singer recognition. Although many studies have been conducted for the separation of voice from the background, there has been less study on singing voice in particular.

In this study, efforts were made to design a new methodology to improve the separation of vocal and non-vocal components in audio clips using REPET [14]. In the newly designed method, we …

Embedding-Based Representation Of Categorical Data By Hierarchical Value Coupling Learning, Songlei Jian, Longbing Cao, Guansong Pang, Kai Lu, Hang Gao

Research Collection School Of Computing and Information Systems

Learning the representation of categorical data with hierarchical value coupling relationships is very challenging but critical for the effective analysis and learning of such data. This paper proposes a novel coupled unsupervised categorical data representation (CURE) framework and its instantiation, i.e., a coupled data embedding (CDE) method, for representing categorical data by hierarchical value-to-value cluster coupling learning. Unlike existing embedding- and similarity-based representation methods which can capture only a part or none of these complex couplings, CDE explicitly incorporates the hierarchical couplings into its embedding representation. CDE first learns two complementary feature value couplings which are then used to cluster …

An Interactive Interface For Nursing Robots., Ankita Sahu

Electronic Theses and Dissertations

Physical Human-Robot Interaction (pHRI) is inevitable for a human user while working with assistive robots. There are various aspects of pHRI, such as choosing the interface, type of control schemes implemented and the modes of interaction. The research work presented in this thesis concentrates on a health-care assistive robot called Adaptive Robot Nursing Assistant (ARNA). An assistive robot in a health-care environment has to be able to perform routine tasks and be aware of the surrounding environment at the same time. In order to operate the robot, a teleoperation based interaction would be tedious for some patients as it would …

Voltage Controller For Simulating Transition Between Boost –Buck -Boost Converter, Aula Jameel Al-Kamil

Masters Theses

In the present work, a voltage tracking controller is developed for DC-DC Buck-Boost converter using software model. The software developed can track the voltage and the mode of operation (Buck or Boost), which depends on the value of the duty cycle ratio (D). The error between ��_{��������}(reference voltage) and output voltage is minimized by using step input as reference. The simulation results show that the designed software controller can successfully track the voltage with low error and with short settling time. The values for the Buck-Boost circuit components, the capacitor and the inductor, are tuned and selected so …

Semantic Visualization For Short Texts With Word Embeddings, Van Minh Tuan Le, Hady W. Lauw

Research Collection School Of Computing and Information Systems

Semantic visualization integrates topic modeling and visualization, such that every document is associated with a topic distribution as well as visualization coordinates on a low-dimensional Euclidean space. We address the problem of semantic visualization for short texts. Such documents are increasingly common, including tweets, search snippets, news headlines, or status updates. Due to their short lengths, it is difficult to model semantics as the word co-occurrences in such a corpus are very sparse. Our approach is to incorporate auxiliary information, such as word embeddings from a larger corpus, to supplement the lack of co-occurrences. This requires the development of a …