Miracle-dz/UniFAR-FTUs huggingface dataset:
Constructing Semantic Knowledge Base based on Wikipedia automation

We know that Wikipedia is the largest knowledge set in the world, each instance entries can be a semantic entity, and it has richly hyperlinked text. Based on these, we propose a self-training method based on a small number of positive examples to extract the semantic relations and entities from the dynamic construction of semantic knowledge base. At the same time, we use TFIDF in the field of text classification and Feature Engineering in the field of computer linguistics to extract the physical characteristics of each instance and calculate their correlation. These physical features are used to help improve the accuracy and recall rate of the self-training method based on a small number of positive examples. After getting the entity right, it will be stored in the form of XML. Based on the storage structure of the XML document, a new reasoning algorithm is proposed which we called Hierarchical Reasoning. We use Wikipedia XML data in 2007 as the data test set the experimental results show that the filter based on feature selection constraint can obtain high precision and recall rate. In general, the knowledge base is built automatically. This makes it possible to extracting a large amount information from Wikipedia.
Effects of Liberalization on Incumbent Firms’ Marketing-Mix Responses and Performance: Evidence from a Quasi-Experiment

Many markets are liberalizing by opening up their economies to foreign competition, with the expectation that this will increase economic growth. While foreign competitors with superior technology and management practices pose serious threats to incumbent firms, they also provide them an opportunity to gain new marketing knowledge. How do incumbent firms respond to liberalization? Can incumbent firms’ marketing-mix responses affect their performance following liberalization? Addressing these questions, the authors examine incumbent firms’ marketing-mix responses to liberalization and the impact of these responses on performance, using the quasi-experiment of liberalization reforms in India. Estimation results from a panel of 3,927 firms in the period 1989–2000 suggest that while all incumbent firms intensified their product and promotions in response to liberalization, only incumbent firms with greater domestic market knowledge intensified their advertising and distribution responses. Furthermore, incumbent firms’ marketing-mix responses significantly affect their performance outcomes. The research’s findings extend theory and provide practical guidelines on how incumbent firms can design marketing-mix responses to liberalization to improve performance.
Perception of Service Quality among Malaysian University Recreational Fitness Center Users

The purpose of this study was to examine user’s perceptions of service quality and future intention to use campus recreation fitness center in Universiti Putra Malaysia. Data were collected from 200 students and staff of the university (males = 140, females = 60) who frequently used the campus recreation fitness center. The questionnaire consisted of items based on the Likert-scale Service Quality Assessment Scale (SQAS) developed by Lam, Zhang and Jensen (2005). Behavioral intention is based on three questions modified from Cunningham and Kwon (2003). The results showed that recreation fitness center users are satisfied with the overall staff service quality (m=34.14) and fitness facility service quality (m=34.14), but moderately satisfied with overall facility service quality (m=30.77) and overall program service quality (m=24.44). The findings indicated UPM recreation fitness center users have a high intention (m=4.02) to recommend the recreation center to other people and to renew their membership. The result also shows overall staff service quality (s = . 288 p
The Neural Representation of Room Locations in A Virtual Building

In order to navigate through a building, people need to keep track of their real-time location in the space. In this study, we aim to find the neural representation of room locations in the human brain using functional magnetic resonance imaging (fMRI) and multivariate pattern analysis (MVPA). Specifically, we asked participants to navigate through a learned virtual building. Their real-time brain activity in each room was recorded. It was found that the location of the current room could be decoded from the hippocampus. Consistent with previous studies in outdoor spaces, the hippocampus also tracks one’s real-time location in an indoor space during navigation.
Item Position Effects in a Reading Comprehension Test: An IRT Study of Individual Differences and Individual Correlates

Item position (IP) effects typically indicate that items become more difficult towards the end of a test. Such effects are thought to reflect the persistence with which test takers invest effort and work precisely on the test. As such, IP effects may be related to cognitive and motivational variables that are relevant for maintaining a high level of effort and precision. In this article, we analyzed IP effects in a reading comprehension test. We propose an IRT model that includes random IP effects affecting item difficulties and fixed IP effects affecting item discriminations. We found evidence for gradually increasing item difficulties and decreasing discriminations. Variation in IP effects on the item difficulties was systematically related to students’ decoding speed and reading enjoyment. The results demonstrate that the relationship between the overall scores and other variables is affected by respondents’ test-taking behavior, which is reflected in the random IP effect.
An interactive nanomanipulation system with force and visual feedback

This paper presents a method to implement interactive nanomanipulation.With the method we develop an interactive nanomanipulation system with force feedback and visual feedback.Using the system the operator can not only feel the real-time forces acting on the probe of atomic force microscope(AFM) but also observe the real-time changes of nano-environment under the operation of AFM probe.It makes the operation in micro-world intuitive and flexible as moving object in macro-world.The experimental results prove the efficiency and advantages of the system.
Automatic measuring of brinell hardness based on Image processing using Matlab

A method of automatic measuring of brinell hardness based on image processing technology is described in the paper.Problems caused by traditional measurements such as low efficiency and big error can be solved by using this method.Technologies are applied including median filtering,edge detection,morphological processing of image,boundary tracking,fitting circle with least-squares procedure and so on.The accuracy and robustness of the algorithm listed in this paper are validated by experiments.This method can achieve non-contact,intelligent and automated measuring of brinell hardness,with good application prospects.
Acoustic modeling for speech recognition under limited training data conditions

The development of a speech recognition system requires at least three resources: a large labeled speech corpus to build the acoustic model, a pronunciation lexicon to map words to phone sequences, and a large text corpus to build the language model. For many languages such as dialects or minority languages, these resources are limited or even unavailable we label these languages as under-resourced. In this thesis, the focus is to develop reliable acoustic models for under-resourced languages. The following three works have been proposed. In the first work, reliable acoustic models are built by transferring acoustic information from well-resourced languages (source) to under-resourced languages (target). Specifically, the phone models of the source language are reused to form the phone models of the target language. This is motivated by the fact that all human languages share a similar acoustic space, and hence some acoustic units e.g. phones, of two languages may have high correspondence and therefore allows the mapping of phones between languages. Unlike previous studies which examined only context-independent phone mapping, the thesis extends the studies to use context-dependent triphone states as the units to achieve higher acoustic resolution. In addition, linear and nonlinear mapping models with different training algorithms are also investigated. The results show that the nonlinear mapping with discriminative training criterion achieves the best performance in the proposed work. In the second work, rather than increasing the mapping resolution, the focus is to improve the quality of the cross-lingual feature used for mapping. Two approaches based on deep neural networks (DNNs) are examined. First, DNNs are used as the source language acoustic model to generate posterior features for phone mapping. Second, DNNs are used to replace multilayer perceptrons (MLPs) to realize the phone mapping.
Central Bank Reserves and Currency Volatility

We investigate the effects of Central Bank interventions which are designed to smooth exchange rate volatility but are not aimed at a particular trend level. We present a model in which the intervention flow is a non-linear mapping of the market order flow. Simulations show that small daily drifts, Brexit-led in the case of Bank of England and commodity-driven in the Central Bank of Brazil, lead to major impacts on both the stock of foreign reserves and the distribution of currency returns. The likelihood of this increases with the Central Bank's inability to adopt a neutral policy regarding the drifts.
Kernel-based blup with genomic data

Best linear unbiased prediction (BLUP, Henderson 1973) of breeding values based on phenotypic measurements and additive genetic relationships between individuals is a well established methodology in animal breeding (Robinson, 1991). With the availability of highthroughput genotyping facilities, genotypes for massive numbers of single nucleotide polymorphisms (SNPs) are available. Meuwissen et al. (2001) suggested to include SNP information in a statistical model of prediction. In geostatistics, the prediction of a spatial variable in any point of the considered space based on a given limited set of measurements is of interest. A standard approach in this case is “kriging” whose application is naturally limited to two, three or four dimensions. We suggest the application of a high-dimensional kriging-extension to the genomic prediction problem, where one dimension reflects a genotype realization at one SNP. Our model for genomic data combines a polygenic effect and a general function of SNP genotypes. We present two kriging variants using the Matérn covariance function to reflect the functional dependency of the covariances from the distance of genotypes. Finally, we compare their predictive performance to a common genomic BLUP as a reference method in a simulation study.
Human Factors In Alarm Design

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Evaluation of Students Scientific and Medical Literacy After Performing Laboratory Exercises in a Microbiology Laboratory for Non-Majors

Introduction to Microbes and Disease was designed to introduce students to the field of Microbiology, with a focus on medicine and disease. In this course, students develop a comprehensive understanding of the structure of biology of microbes and how the human immune system interacts with them to fight disease. All undergraduate students directed on a health science course path will benefit from this introductory course, but this course does not fulfill requirements for Biology majors. The newly developed course was developed in 2013 and was first offered in the fall semester of 2014. Pre-assessment and post-assessment exams were used in the Microbes and Disease - Biology 2510 (Introduction to Microbes and Disease) for the spring 2017 semester in which the total enrollment was 140 students. In this study, the assessments were used to examine the confidence and competence in biological concepts and lab techniques in the biology lab course for non-majors. The assessments were evaluated quantitatively and qualitatively. Lab experiment reports were used to examine the collaboration and student-learning occurring in lab. Grades for individual assessments and laboratory reports were collected, and analyzed using Microsoft Excel. Scatter plots illustrated the grade distribution of 98 pre and post assessments representing all students enrolled in BIOL 2510 for the 2017 spring semester. Differences between pre and post assessment grades and laboratory report grades are indicated by line charts These graphs also provided comparisons between the different lab sections. This science education project addressed active learning themes, the importance of weekly lab write ups, collaborative group work and confidence and competence of biological concepts and laboratory techniques.
Self-regulated learning strategies and achievement goals among preservice physical education teachers

Self-regulated learning is critical to student academic success as well as healthy lifestyles. Although widely conducted among students from various disciplines, self-regulated learning research seems not to have paid much attention to preservice physical education teachers. Attempting to amend this literature gap as well as inform the current status of self-regulated learning among preservice physical education (PE) teachers, this study focused on two essential components: learning strategies and motivation. Participants included 419 preservice PE teachers from five teacher preparation programmes in the USA. They responded to two questionnaires that assessed self-regulated learning strategies use and achievement goals. Each item on the questionnaires was on a seven-point Likert scale. Results showed that this group of preservice teachers’ use of cognitive and metacognitive strategies was at a medium level. Their mastery-approach goals demonstrated a predominant effect on general cognitive strategies and elaboration. Performance-approach and performance-avoidance goals also had a positive association with general cognitive strategies and critical thinking. Based on these results, we recommend PE teacher educators integrate self-regulated learning into instructions and focus preservice teachers on endorsing mastery-oriented goals for their learning.
Optimal Monetary Policy with Overlapping Generations of Policymakers

In this paper I study the effect of imperfect central bank commitment on inflationary outcomes. I present a model in which the monetary authority is a committee that consists of members who serve overlapping, finite terms. Older and younger generations of Monetary Policy Committee (MPC) members decide on policy by engaging in a bargaining process. I show that this setup gives rise to a continuous measure of the degree of monetary authority's commitment. The model suggests that the lower the churning rate or the longer the tenure time, the closer social welfare will be to that under optimal commitment policy.
Type-based Static Analysis of Web Documents with Embedded Executable Components

WRIGHT, DAVID R. Type-based Static Analysis of Web Documents with Embedded Executable Components. (Under the direction of Associate Professor S. Purushothaman Iyer) Electronic documents have become an important medium for the exchange of information, and nowhere is this more evident than on the World Wide Web. Web-based documents can be dynamic and interactive with the inclusion of executable elements such as scripting languages, interactive multimedia components, and applets. This flexibility also brings the risks of incompatibilities between client applications, security and privacy concerns, and document integrity verification. Traditional document analysis has been restricted to examining the content of the document, as in spelling and grammar checkers, readability analyzers and keyword indexing, but these forms of analysis do not address the potential problems electronic documents may present. This thesis proposes that proven methods for analyzing computer programs may also be applied to documents with embedded executable elements. In particular, it is shown that type-based static analysis may be successfully and effectively employed to analyze a Web-based document to determine a set of browsers that will correctly render the document and provide all of the functionality incorporated into the document. Type-based Static Analysis of Web Documents with Embedded Executable Components
Supplementary Material for ECCV 2014 Paper: Spatio-temporal Event Classication using Time-series Kernel based Structured Sparsity

This document accompanies the paper: "Spatio-temporal Event Classication using Time-series Kernel based Structured Sparsity". We provide implementation details of the Kernel Structured Sparsity (KSS) method for FISTA (fast iterative shrinkage-thresholding algorithm) (2). We also show scaling results on the 6D Motion Gesture Database (3). Note that information given in this document is not necessary to under- stand the content of the main paper.
Hamiltonian Servo: Control and Estimation of a Large Team of Autonomous Robotic Vehicles

This paper proposes a novel Hamiltonian servo system, a combined modeling framework for control and estimation of a large team/fleet of autonomous robotic vehicles. The Hamiltonian servo framework represents high-dimensional, nonlinear and non-Gaussian generalization of the classical Kalman servo system. After defining the Kalman servo as a motivation, we define the affine Hamiltonian neural network for adaptive nonlinear control of a team of UGVs in continuous time. We then define a high-dimensional Bayesian particle filter for estimation of a team of UGVs in discrete time. Finally, we formulate a hybrid Hamiltonian servo system by combining the continuous-time control and the discrete-time estimation into a coherent framework that works like a predictor-corrector system.
Effects of Advertising Campaign on the Salesperson’s Performance: Should a Multilevel Marketing Firm Advertise Its Brand to Customers?

Purpose - The purpose of this study is to explore how advertising for multilevel marketing brands affect the salesperson’s activity including customer-salesperson interactivity, work attitude, and perceived and actual performance after the campaign. Research Design, data, and methodology - This study collects experimental data, survey data, and actual sales data and applies statistical analyses such as factor analysis, t-tests, and a structural equation model. Results - The results show that advertising campaign can enhance a salesperson’s selling activities and provide wide managerial implications to a multilevel marketing firm by filling the gaps for the field of advertising research. Conclusions - Managerial implications include: i) multilevel marketing firms should consider advertising campaigns as a means of changing customer responses because advertising plays a significant role in increasing familiarity with, and knowledge of, attitudes toward the brand, which also helps salespeople interact with customers; ii) multilevel marketing firms should consider brand advertising as a means to support the sales activities of salespeople including sales effectiveness, work attitudes, and perceived performance, and iii) multilevel marketing firms should consider brand advertising as a means to enhance a salesperson’s pride and motivation for selling their brand, which will lead to improved sales performances.
Who is Eligible for Telework? Exploring the Fast-Growing Acceptance of and Ability to Telework in Sweden, 2005–2006 to 2011–2014

The share of Swedish employees eligible for telework, that is, when work tasks and contractual agreement allow, increased from 22% in 2005–2006 to 35% in 2011–2014. This article explores this fast diffusion of telework eligibility. Micro data from representative national surveys are used to examine how increasing opportunities for telework have spread among different groups of employees and different parts of the labour market and to examine the factors that increase or decrease the probability of being eligible for telework. We find significant increases in telework eligibility in almost all categories of workers and all labour market sectors. However, employees are clearly grouped into those achieving rapid gains in telework eligibility and those achieving such gains much more slowly. Telework continues to be primarily available to high-status segments of the labour market. Information and communication technology and technical solutions increasingly appear to be key factors enabling telework.
Portfolio crash testing: making sense of extreme event exposures

The topic of extreme events is becoming ever more important for risk management. Stress testing is a technique that is explicitly designed to deal with extreme shocks; however, its methodology and place in the risk process is often unclear to risk managers. This paper addresses some common misconceptions about stress testing and provides methodology for its incorporation into the risk process as a supplement to risk measures such as value-at-risk and tracking error. Two stress testing models are presented and empirically validated on actual extreme periods. Both are based on multivariate normal distributions conditional on a factor shock, differing only in the way that covariances are estimated. The first model uses temporal weighting commonly used in the risk model construction; the other uses event weighting, which assigns a higher weight to extreme events that are similar to the factor shock specified. The key conclusion is that the time weighted model performs better in moderate or semi-expected shocks, while the event weighted model performs better in more extreme and unexpected shocks like the Long-Term Capital Management crisis, 9/11 terrorist attacks, and the Fall 2008 financials-led meltdown. The event weighted model, which is designed to reflect the rise in correlations and variances during extreme markets, produces a more conservative estimate of return impacts. Our results support the conclusion that stress testing can be a very valuable addition to standard risk measures.
Regional entrepreneurial ecosystems in China

This study focuses on regional entrepreneurial ecosystems in the largest emerging economy in the world. We use a two-stage structural model distinguishing between two sets of factors, those that have direct impact on entrepreneurial activities and those that have indirect impact. Based on an empirical analysis of 263 Chinese prefecture-level municipalities from 2008 to 2015, we find that human capital, knowledge creation, and access to finance are the main factors that drive local entrepreneurial activity. New technology-based startups are significant predictors of the regional stock of human capital and the presence of risk finance suggesting the unique role of technology-based firms in promoting sustainable growth in regional entrepreneurial ecosystems. The presence of research-intensive universities also has a strong positive impact on regional entrepreneurial ecosystems.