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Articles 5101 - 5130 of 6253
Full-Text Articles in Entire DC Network
A Study On Facility Planning Using Discrete Event Simulation: Case Study Of A Grain Delivery Terminal, Sarah M. Asio
A Study On Facility Planning Using Discrete Event Simulation: Case Study Of A Grain Delivery Terminal, Sarah M. Asio
Department of Industrial and Management Systems Engineering: Dissertations, Theses, and Student Research
The application of traditional approaches to the design of efficient facilities can be tedious and time consuming when uncertainty and a number of constraints exist. Queuing models and mathematical programming techniques are not able to capture the complex interaction between resources, the environment and space constraints for dynamic stochastic processes. In the following study discrete event simulation is applied to the facility planning process for a grain delivery terminal. The discrete event simulation approach has been applied to studies such as capacity planning and facility layout for a gasoline station and evaluating the resource requirements for a manufacturing facility. To …
Assessing Secondary And College Students’ Implicit Assumptions About The Particulate Nature Of Matter: Development And Validation Of The Structure And Motion Of Matter Survey, Marilyne Stains, Marta Escriu-Sune, Myrna Lisseth Molina Alvarez De Santizo, Hannah Sevian
Assessing Secondary And College Students’ Implicit Assumptions About The Particulate Nature Of Matter: Development And Validation Of The Structure And Motion Of Matter Survey, Marilyne Stains, Marta Escriu-Sune, Myrna Lisseth Molina Alvarez De Santizo, Hannah Sevian
Department of Chemistry: Faculty Publications
Development of learning progressions has been at the forefront of science education for several years. While understanding students’ conceptual development toward “big ideas” in science is extremely valuable for researchers, science teachers can also benefit from assessment tools that diagnose their students’ trajectories along the learning progressions. In this paper, we describe the development and validation of a teacher-friendly survey, the Structure and Motion of Matter (SAMM) survey, designed to measure students’ trajectories along aspects of a research-based learning progression on the particulate nature of matter. Specifically, the survey assesses students’ implicit assumptions about four concepts: the structure of solute …
Unsupervised Semantic Classification Methods, John Gilmer
Unsupervised Semantic Classification Methods, John Gilmer
Honors Capstones
No abstract provided.
Compassionate Reappraisal And Emotion Suppression As Alternatives To Offense-Focused Rumination: Implications For Forgiveness And Psychophysiological Well-Being, Charlotte Vanoyen-Witvliet, Nathaniel J. Deyoung, Alicia J. Hofelich, Paul Deyoung
Compassionate Reappraisal And Emotion Suppression As Alternatives To Offense-Focused Rumination: Implications For Forgiveness And Psychophysiological Well-Being, Charlotte Vanoyen-Witvliet, Nathaniel J. Deyoung, Alicia J. Hofelich, Paul Deyoung
Faculty Publications
This within subjects experiment (28 females, 26 males) examined three responses to a past interpersonal offender. We contrasted offense-focused rumination with two subsequent, counterbalanced coping strategies: compassionate reappraisal and emotion suppression. Compassionate reappraisal emphasized the offender's human qualities and need for positive change. Emotion suppression inhibited the experience and expression of negative offense-related emotions. Offense rumination was associated with negative emotion, faster heartbeats (i.e., shortened electrocardiogram R-R intervals), and lower heart rate variability (HRV; i.e., the high-frequency component of the R-R power spectrum). By contrast, both compassionate reappraisal and emotion suppression decreased negative emotion in ratings and linguistic analyses, calmed …
Generating Aspect-Oriented Multi-Document Summarization With Event-Aspect Model, Peng Li, Yinglin Wang, Wei Gao, Jing Jiang
Generating Aspect-Oriented Multi-Document Summarization With Event-Aspect Model, Peng Li, Yinglin Wang, Wei Gao, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper, we propose a novel approach to automatic generation of aspect-oriented summaries from multiple documents. We first develop an event-aspect LDA model to cluster sentences into aspects. We then use extended LexRank algorithm to rank the sentences in each cluster. We use Integer Linear Programming for sentence selection. Key features of our method include automatic grouping of semantically related sentences and sentence ranking based on extension of random walk model. Also, we implement a new sentence compression algorithm which use dependency tree instead of parser tree. We compare our method with four baseline methods. Quantitative evaluation based on …
Learning Author’S Writing Pattern System By Automata, Qun Yu
Learning Author’S Writing Pattern System By Automata, Qun Yu
Master's Projects
The purpose of the report is to document our project’s theory, implementation and test results. The project works on an automata-based learning system which models authors’ writing characters with automatons. Since there were pervious works done by Dr. T.Y. Lin and Ms. S.X. Zhang, we continue on ALERGIA algorithm analysis and initial common pattern study in this project. Although every author has his/her own writing style, such as sentence length and word frequency etc, there are always some similarities in writing style. We hypothesize that common strings fogged the expected test result, just like the noise in radio wave. This …
Unsupervised Information Extraction With Distributional Prior Knowledge, Cane Wing-Ki Leung, Jing Jiang, Kian Ming A. Chai, Hai Leong Chieu, Loo-Nin Teow
Unsupervised Information Extraction With Distributional Prior Knowledge, Cane Wing-Ki Leung, Jing Jiang, Kian Ming A. Chai, Hai Leong Chieu, Loo-Nin Teow
Research Collection School Of Computing and Information Systems
We address the task of automatic discovery of information extraction template from a given text collection. Our approach clusters candidate slot fillers to identify meaningful template slots. We propose a generative model that incorporates distributional prior knowledge to help distribute candidates in a document into appropriate slots. Empirical results suggest that the proposed prior can bring substantial improvements to our task as compared to a K-means baseline and a Gaussian mixture model baseline. Specifically, the proposed prior has shown to be effective when coupled with discriminative features of the candidates.
Linking Entities To A Knowledge Base With Query Expansion, Swapna Gottipati, Jing Jiang
Linking Entities To A Knowledge Base With Query Expansion, Swapna Gottipati, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper we present a novel approach to entity linking based on a statistical language model-based information retrieval with query expansion. We use both local contexts and global world knowledge to expand query language models. We place a strong emphasis on named entities in the local contexts and explore a positional language model to weigh them differently based on their distances to the query. Our experiments on the TAC-KBP 2010 data show that incorporating such contextual information indeed aids in disambiguating the named entities and consistently improves the entity linking performance. Compared with the official results from KBP 2010 …
Generating Aspect-Oriented Multi-Document Summarization With Event-Aspect Model, Peng Li, Yinglin Wang, Wei Gao, Jing Jiang
Generating Aspect-Oriented Multi-Document Summarization With Event-Aspect Model, Peng Li, Yinglin Wang, Wei Gao, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper, we propose a novel approach to automatic generation of aspect-oriented summaries from multiple documents. We first develop an event-aspect LDA model to cluster sentences into aspects. We then use extended LexRank algorithm to rank the sentences in each cluster. We use Integer Linear Programming for sentence selection. Key features of our method include automatic grouping of semantically related sentences and sentence ranking based on extension of random walk model. Also, we implement a new sentence compression algorithm which use dependency tree instead of parser tree. We compare our method with four baseline methods. Quantitative evaluation based on …
Unsupervised Discovery Of Discourse Relations For Eliminating Intra-Sentence Polarity Ambiguities, Lanjun Zhou, Binyang Li, Wei Gao, Zhongyu Wei, Kam-Fai Wong
Unsupervised Discovery Of Discourse Relations For Eliminating Intra-Sentence Polarity Ambiguities, Lanjun Zhou, Binyang Li, Wei Gao, Zhongyu Wei, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Polarity classification of opinionated sentences with both positive and negative sentiments1 is a key challenge in sentiment analysis. This paper presents a novel unsupervised method for discovering intra-sentence level discourse relations for eliminating polarity ambiguities. Firstly, a discourse scheme with discourse constraints on polarity was defined empirically based on Rhetorical Structure Theory (RST). Then, a small set of cuephrase-based patterns were utilized to collect a large number of discourse instances which were later converted to semantic sequential representations (SSRs). Finally, an unsupervised method was adopted to generate, weigh and filter new SSRs without cue phrases for recognizing discourse relations. Experimental …
A Fuzzy Logic Stock Trading System Based On Technical Analysis, Sammy Zeigenbein
A Fuzzy Logic Stock Trading System Based On Technical Analysis, Sammy Zeigenbein
Regis University Student Publications (comprehensive collection)
Technical analysis of financial markets involves analyzing past price movements in order to identify favorable trading opportunities. The objective of this research was to demonstrate that a fuzzy logic stock trading system based on technical analysis can assist average traders in becoming successful by optimizing the use of technical indicators and trading rules that experts use to identify when to buy and sell stock. Research of relevant literature explored the current state of knowledge in methodologies for developing and validating trading systems using technical indicators and fuzzy logic trading systems, providing guidelines for the development and evaluation of the system. …
Automatic Domain Model Creation Using Pattern-Based Fact Extraction, Christopher Thomas, Pankaj Mehra, Wenbo Wang, Amit P. Sheth, Gerhard Weikum, Victor Chan
Automatic Domain Model Creation Using Pattern-Based Fact Extraction, Christopher Thomas, Pankaj Mehra, Wenbo Wang, Amit P. Sheth, Gerhard Weikum, Victor Chan
Kno.e.sis Publications
This paper describes a minimally guided approach to automatic domain model creation. The first step is to carve an area of interest out of the Wikipedia hierarchy based on a simple query or other starting point. The second step is to connect the concepts in this domain hierarchy with named relationships. A starting point is provided by Linked Open Data, such as DBPedia. Based on these community-generated facts we train a pattern-based fact-extraction algorithm to augment a domain hierarchy with previously unknown relationship occurrences. Pattern vectors are learned that represent occurrences of relationships between concepts. The process described can be …
The Object Of Platform Studies: Relational Materialities And The Social Platform (The Case Of The Nintendo Wii), Steven E. Jones, George K. Thiruvathukal
The Object Of Platform Studies: Relational Materialities And The Social Platform (The Case Of The Nintendo Wii), Steven E. Jones, George K. Thiruvathukal
Computer Science: Faculty Publications and Other Works
Racing the Beam: The Atari Video Computer System,by Ian Bogost and Nick Montfort, inaugurated thePlatform Studies series at MIT Press in 2009.We’ve coauthored a new book in the series, Codename: Revolution: the Nintendo Wii Video Game Console. Platform studies is a quintessentially Digital Humanities approach, since it’s explicitly focused on the interrelationship of computing and cultural expression. According to the series preface, the goal of platform studies is “to consider the lowest level of computing systems and to understand how these systems relate to culture and creativity.”In practice, this involves paying close attentionto specific hardware and software interactions--to the vertical …
Topical Keyphrase Extraction From Twitter, Xin Zhao, Jing Jiang, Jing He, Yang Song, Palakorn Achananuparp, Ee Peng Lim, Xiaoming Li
Topical Keyphrase Extraction From Twitter, Xin Zhao, Jing Jiang, Jing He, Yang Song, Palakorn Achananuparp, Ee Peng Lim, Xiaoming Li
Research Collection School Of Computing and Information Systems
Summarizing and analyzing Twitter content is an important and challenging task. In this paper, we propose to extract topical keyphrases as one way to summarize Twitter. We propose a context-sensitive topical PageRank method for keyword ranking and a probabilistic scoring function that considers both relevance and interestingness of keyphrases for keyphrase ranking. We evaluate our proposed methods on a large Twitter data set. Experiments show that these methods are very effective for topical keyphrase extraction.
Link Type Based Pre-Cluster Pair Model For Coreference Resolution, Yang Song, Houfeng Wang, Jing Jiang
Link Type Based Pre-Cluster Pair Model For Coreference Resolution, Yang Song, Houfeng Wang, Jing Jiang
Research Collection School Of Computing and Information Systems
This paper presents our participation in the CoNLL-2011 shared task, Modeling Unrestricted Coreference in OntoNotes. Coreference resolution, as a difficult and challenging problem in NLP, has attracted a lot of attention in the research community for a long time. Its objective is to determine whether two mentions in a piece of text refer to the same entity. In our system, we implement mention detection and coreference resolution seperately. For mention detection, a simple classification based method combined with several effective features is developed. For coreference resolution, we propose a link type based pre-cluster pair model. In this model, pre-clustering of …
Query Weighting For Ranking Model Adaptation, Peng Cai, Wei Gao, Aoying Zhou, Kam-Fai Wong
Query Weighting For Ranking Model Adaptation, Peng Cai, Wei Gao, Aoying Zhou, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
We propose to directly measure the importance of queries in the source domain to the target domain where no rank labels of documents are available, which is referred to as query weighting. Query weighting is a key step in ranking model adaptation. As the learning object of ranking algorithms is divided by query instances, we argue that it’s more reasonable to conduct importance weighting at query level than document level. We present two query weighting schemes. The first compresses the query into a query feature vector, which aggregates all document instances in the same query, and then conducts query weighting …
Creating Realistic Corpora For Security And Forensic Education, Kam Woods, Christopher A. Lee, Simson Garfinkel, David Dittrich, Adam Russell, Kris Kearton
Creating Realistic Corpora For Security And Forensic Education, Kam Woods, Christopher A. Lee, Simson Garfinkel, David Dittrich, Adam Russell, Kris Kearton
Annual ADFSL Conference on Digital Forensics, Security and Law
We present work on the design, implementation, distribution, and use of realistic forensic datasets to support digital forensics and security education. We describe in particular the “M57-Patents” scenario, a multi-modal corpus consisting of hard drive images, RAM images, network captures, and images from other devices typically found in forensics investigations such as USB drives and cellphones. Corpus creation has been performed as part of a scripted scenario; subsequently it is less “noisy” than real-world data but retains the complexity necessary to support a wide variety of forensic education activities. Realistic forensic corpora allow direct comparison of approaches and tools across …
Social Capital In Online Communities, Matthew Scott Smith
Social Capital In Online Communities, Matthew Scott Smith
Theses and Dissertations
Social capital is the value of the relationships we create and maintain within our social networks to gain access to and mobilize needed resources (e.g., jobs, moral support). Quantifying, and subsequently leveraging, social capital are challenging problems in the social sciences. Most work so far has focused on analyses from static surveys of limited numbers of participants. The explosion of online social media means that it is now possible to collect rich data about people's connections and interactions, in a completely ubiquitous, non-intrusive manner. Such dynamic social data opens the door to the more accurate measuring and tracking of social …
Development Of A Distributed Print‐Out Monitoring System For Efficient Forensic Investigation, Satoshi Kai, Tetsutaro Uehara
Development Of A Distributed Print‐Out Monitoring System For Efficient Forensic Investigation, Satoshi Kai, Tetsutaro Uehara
Annual ADFSL Conference on Digital Forensics, Security and Law
If information leakage occurs, an investigator is instructed to specify what documents were leaked and who leaked them. In the present work, a distributed print-out monitoring system—which consists of a virtual printer driver and print-out policy/log management servers—was developed. For easily matching the discovered (i.e., leaked) paper document with the print-out log, the virtual printer driver acquires full-text of printed-out documents by DDI hooking technique to check the content, transforms a spool file to a picture file and creates both a thumbnail and text log for forensic investigation afterwards. The log size is as only about 0.04 times bigger than …
Software Piracy Forensics: Impact And Implications Of Post‐Piracy Modifications, Vinod Bhattathiripad, S. Santhosh Baboo
Software Piracy Forensics: Impact And Implications Of Post‐Piracy Modifications, Vinod Bhattathiripad, S. Santhosh Baboo
Annual ADFSL Conference on Digital Forensics, Security and Law
Piracy is potentially possible at any stage of the lifetime of the software. In a post-piracy situation, however, the growth of the respective versions of the software (both the original and pirated) is expected to be in different directions as a result of expectedly different implementation strategies. This paper shows how such post-piracy modifications are of special interest to a cyber crime expert investigating software piracy and suggests that the present software piracy forensic (or software copyright infringement investigation) approaches require amendments to take in such modifications. For this purpose, the paper also presents a format that is jargon-free, so …
Cacao Use And The San Lorenzo Olmec, Terry G. Powis, Ann Cyphers, Nilesh W. Gaikwad, Louis Grivetti, Kong Cheong
Cacao Use And The San Lorenzo Olmec, Terry G. Powis, Ann Cyphers, Nilesh W. Gaikwad, Louis Grivetti, Kong Cheong
Faculty Articles
Mesoamerican peoples had a long history of cacao use—spanning more than 34 centuries—as confirmed by previous identification of cacao residues on archaeological pottery from Paso de la Amada on the Pacific Coast and the Olmec site of El Manatí on the Gulf Coast. Until now, comparable evidence from San Lorenzo, the premier Olmec capital, was lacking. The present study of theobromine residues confirms the continuous presence and use of cacao products at San Lorenzo between 1800 and 1000 BCE, and documents assorted vessels forms used in its preparation and consumption. One elite context reveals cacao use as part of a …
Hardware Acceleration Of Inference Computing: The Numenta Htm Algorithm, Dan Hammerstrom
Hardware Acceleration Of Inference Computing: The Numenta Htm Algorithm, Dan Hammerstrom
Systems Science Friday Noon Seminar Series
In this presentation I will describe the latest version of the Numenta HTM Cortical Learning Algorithm and why it is interesting for doing research into radical new computer architectures. Then I will discuss the hardware acceleration research we are doing, and briefly look at some preliminary applications development.
General Piecewise Growth Mixture Model: Word Recognition Development For Different Learners In Different Phases, Amery D. Wu, Bruno D. Zumbo, Linda S. Siegel
General Piecewise Growth Mixture Model: Word Recognition Development For Different Learners In Different Phases, Amery D. Wu, Bruno D. Zumbo, Linda S. Siegel
Journal of Modern Applied Statistical Methods
The General Piecewise Growth Mixture Model (GPGMM), without losing generality to other fields of study, can answer six crucial research questions regarding children’s word recognition development. Using child word recognition data as an example, this study demonstrates the flexibility and versatility of the GPGMM in investigating growth trajectories that are potentially phasic and heterogeneous. The strengths and limitations of the GPGMM and lessons learned from this hands-on experience are discussed.
Trust Networks: Interpersonal, Social, And Sensor, Krishnaprasad Thirunarayan, Pramod Anantharam
Trust Networks: Interpersonal, Social, And Sensor, Krishnaprasad Thirunarayan, Pramod Anantharam
Kno.e.sis Publications
Trust relationships occur naturally in many diverse contexts such as ecommerce, interpersonal interactions, social networks, sensor web, etc. As agents providing content and services become increasingly removed from the agents that consume them, the issue of robust trust inference and update become critical. Unfortunately, there is neither a universal notion of trust that is applicable to all domains nor a clear explication of its semantics or computation in many situations. In this beginner's level tutorial, we motivate the trust problem, explain the relevant concepts, summarize research in modeling trust and gleaning trustworthiness, and discuss challenges confronting us in this process.
The Geozoic Supereon, M. Kowalewski, J. L. Payne, F. A. Smith, Steve C. Wang, D. W. Mcshea, S. Xiao, P. M. Novack-Gottshall, C. R. Mcclain, R. A. Krause, A. G. Boyer, S. Finnegan, S. K. Lyons, J. A. Stempien, J. Alroy, P. A. Spaeth
The Geozoic Supereon, M. Kowalewski, J. L. Payne, F. A. Smith, Steve C. Wang, D. W. Mcshea, S. Xiao, P. M. Novack-Gottshall, C. R. Mcclain, R. A. Krause, A. G. Boyer, S. Finnegan, S. K. Lyons, J. A. Stempien, J. Alroy, P. A. Spaeth
Mathematics & Statistics Faculty Works
No abstract provided.
Novel Application Of Neutrosophic Logic In Classifiers Evaluated Under Region-Based Image Categorization System, Wen Ju
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
Neutrosophic logic is a relatively new logic that is a generalization of fuzzy logic. In this dissertation, for the first time, neutrosophic logic is applied to the field of classifiers where a support vector machine (SVM) is adopted as the example to validate the feasibility and effectiveness of neutrosophic logic. The proposed neutrosophic set is integrated into a reformulated SVM, and the performance of the achieved classifier N-SVM is evaluated under an image categorization system. Image categorization is an important yet challenging research topic in computer vision. In this dissertation, images are first segmented by a hierarchical two-stage self organizing …
Narrative Analysis And Computational Model To Predict Interestingness Of Narratives, Laxman Thapa
Narrative Analysis And Computational Model To Predict Interestingness Of Narratives, Laxman Thapa
Theses and Dissertations - UTB/UTPA
In this research, I present results demonstrating the classification of the specially generated narratives by a machine agent by listening to human subject describing the same sets of the events. These classifications are based on human ratings of interestingness for many different recountings of the same stories. The classification is performed on various features selected after analyzing the different possible feature that affect on the interestingness of narratives. The features were extracted from the surface text as well as from annotations of how each narration relates to the content of the known story. I present the annotation process and resulting …
Real-Time Fundamental Frequency Estimation Algorithm For Disconnected Speech, Thomas Skjei
Real-Time Fundamental Frequency Estimation Algorithm For Disconnected Speech, Thomas Skjei
Theses and Dissertations
A new algorithm is presented for real-time fundamental frequency estimation of speech signals. This method extends and alters the YIN algorithm, which uses the autocorrelation-based difference function, by adding features to reduce latency, correct predictable errors, and make it structurally appropriate for real-time processing scenarios. The algorithm is shown to reduce the error rate of its predecessor while demonstrating latencies sufficient for real-time processing. The results indicate that the algorithm can be realized as a real-time estimator of spoken pitch and pitch variation, which has applications including diagnosis and biofeedback-based therapy of many speech disorders.
A Bottom-Up Design And Implementation For Ambiguity-Compatible Natural Language Sentence Parsing, Elise Thrasher
A Bottom-Up Design And Implementation For Ambiguity-Compatible Natural Language Sentence Parsing, Elise Thrasher
Computer Science Honors Theses
Although many theory-focused computer science textbooks give a brief outline of a context-free grammar model of natural language, the approach is often vague and, in reality, greatly simplifies the English language’s grammatical complexities. When applied to commonly-seen sentences, these sentence parsing models often fall short. In this paper, I detail my process of creating a programmable natural language context-free grammar that is able to parse (i.e. diagram) many common sentence forms, as well as the research which influenced the design of this project. In order to create a grammar that recognized the intricacies of the English language, I also incorporated …
Impact Of The Proposed Kimberley Lng Precinct On Customary Fishing In The Vicinity Of James Price Point, Department Of Fisheries
Impact Of The Proposed Kimberley Lng Precinct On Customary Fishing In The Vicinity Of James Price Point, Department Of Fisheries
Fisheries Occasional Publications
No abstract provided.