snu-aidas/HVMap-dataset huggingface dataset:
A Latent Semantic Indexing-based approach to multilingual document clustering

The creation and deployment of knowledge repositories formanaging, sharing, and reusing tacit knowledgewithin an organization has emerged as a prevalent approach in current knowledge management practices. A knowledge repository typically contains vast amounts of formal knowledge elements, which generally are available as documents. To facilitate users' navigation of documents within a knowledge repository, knowledge maps, often created by document clustering techniques, represent an appealing and promising approach. Various document clustering techniques have been proposed in the literature, but most deal with monolingual documents (i.e., written in the same language). However, as a result of increased globalization and advances in Internet technology, an organization often maintains documents in different languages in its knowledge repositories, which necessitates multilingual document clustering (MLDC) to create organizational knowledge maps. Motivated by the significance of this demand, this study designs a Latent Semantic Indexing (LSI)-based MLDC technique capable of generating knowledge maps (i.e., document clusters) from multilingual documents. The empirical evaluation results show that the proposed LSI-based MLDC technique achieves satisfactory clustering effectiveness, measured by both cluster recall and cluster precision, and is capable of maintaining a good balance between monolingual and cross-lingual clustering effectiveness when clustering a multilingual document corpus. © 2007 Elsevier B.V. All rights reserved.
CHAPTER 12 WORKFLOW ENGINE FOR CLOUDS

A workflow models a process as consisting of a series of steps that simplifies the complexity of execution and management of applications. Scientific workflows in domains such as high-energy physics and life sciences utilize distributed resources in order to access, manage, and process a large amount of data from a higher level. Processing and managing such large amounts of data require the use of a distributed collection of computation and storage facilities. These resources are often limited in supply and are shared among many competing users. The recent progress in virtualization technologies and the rapid growth of cloud computing services have opened a new paradigm in distributed computing for utilizing existing (and often cheaper) resource pools for ondemand and scalable scientific computing. Scientific Workflow Management Systems (WfMS) need to adapt to this new paradigm in order to leverage the benefits of cloud services. Cloud services vary in the levels of abstraction and hence the type of service they present to application users. Infrastructure virtualization enables providers such as Amazon to offer virtual hardware for use in computeand dataintensive workflow applications. Platform-as-a-Service (PaaS) clouds expose a higher-level development and runtime environment for building and deploying workflow applications on cloud infrastructures. Such services may also expose domain-specific concepts for rapid-application development. Further up in the cloud stack are Software-as-a-Service providers who offer end users with
CS224N Project: Let Computers Do Reading Comprehension

In this work, we want to teach the computers to do reading comprehension. More specifically, the task is to let computers read a short passage and then answer some simple questions based on the passage.[1] proposes an end-to-end, RNN-like approach which, according to them, needs significantly less supervision but performs comparatively good to benchmarks for many applications. However, we found that their Q&A result is based on a small synthetic data set defined in [2]. We could see that the dataset is quite small and simple with a vocabulary size of 177. Here is a sample from the dataset.
Performance Management : A model and research agenda

© International Association for Applied Psychology, 2004. Published by Blackwell Publishing, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA. Blackwell Publishing, Ltd. Oxford, UK APPS pplied Psychology: an International Review 0269-994X © Blackwell Publishing 2004 ct ber 2004 53 4 riginal Arti le PERFORMANCE MANAGEMENT D N HARTOG ET AL. Performance Management: A Model and Research Agenda
Insulin detemir versus insulin glargine for type 2 diabetes mellitus.

BACKGROUND
Chronically elevated blood glucose levels are associated with significant morbidity and mortality. Many diabetes patients will eventually require insulin treatment to maintain good glycaemic control. There are still uncertainties about the optimal insulin treatment regimens for type 2 diabetes, but the long-acting insulin analogues seem beneficial. Several reviews have compared either insulin detemir or insulin glargine to NPH insulin, but research directly comparing both insulin analogues is limited.


OBJECTIVES
To assess the effects of insulin detemir and insulin glargine compared with each other in the treatment of type 2 diabetes mellitus.


SEARCH STRATEGY
We searched MEDLINE, EMBASE, The Cochrane Library, online registries of ongoing trials and abstract books. Date of last search was January 2011.


SELECTION CRITERIA
All randomised controlled trials comparing insulin detemir with insulin glargine with a duration of 12 weeks or longer were included.


DATA COLLECTION AND ANALYSIS
Two authors independently selected the studies and extracted the data. Pooling of studies by means of random-effects meta-analysis was performed.


MAIN RESULTS
This review examined four trials lasting 24 to 52 weeks involving 2250 people randomised to either insulin detemir or glargine. Overall, risk of bias of the evaluated studies was high. Insulin glargine was dosed once-daily in the evening. Insulin detemir was initiated once-daily in the evening with the option of an additional dose in the morning in three studies and initiated twice-daily in one study. Of randomised patients 13.6% to 57.2% were injecting insulin detemir twice-daily at the end of trial.Glycaemic control, measured by glycosylated haemoglobin A1c (HbA1c) and HbA1c equal to or less than 7% with or without hypoglycaemia, did not differ statistically significantly between treatment groups.The results showed no significant differences in overall, nocturnal and severe hypoglycaemia between treatment groups.Insulin detemir was associated with less weight gain. Treatment with insulin glargine resulted in a lower daily basal insulin dose and a lower number of injection site reactions.There was no significant difference in the variability of FPG or glucose values in 24-hour profiles between treatment groups. It was not possible to draw conclusions on quality of life, costs or mortality. Only one trial reported results on health-related quality of life and showed no significant differences between treatment groups.


AUTHORS' CONCLUSIONS
Our analyses suggest that there is no clinically relevant difference in efficacy or safety between insulin detemir and insulin glargine for targeting hyperglycaemia. However, to achieve the same glycaemic control insulin detemir was often injected twice-daily in a higher dose but with less weight gain, while insulin glargine was injected once-daily, with somewhat fewer injection site reactions.
Statistical mechanics and phase transitions in clustering.
Understanding of Antecedents to Achieve Customer Trust and Customer Intention to Purchase E-Commerce in Social Media , an Empirical Assessment

Received Dec 9, 2016 Revised Mar 27, 2017 Accepted Apr 11, 2017 This study aims to analyze empirically three factors antecedents of trust they are system quality, information quality, and service quality. Customer trust is used in determining customer intention to purchase of e-commerce in social media (facebook). A number of respondents were 451. The results of this study concluded that three factors antecedents of trust directly had a positive impact to customer trust and indirectly had positive impact on customer intention to purchase in e-commerce transactions on social media. Keyword:
A Metric for Distributions with Applications to Image Databases

Proceedings of the 1998 IEEE International Conference on Computer Vision, Bombay, India We introduce a new distance between two distributions that we call the Earth Mover’s Distance (EMD), which reflects the minimal amount of work that must be performed to transform one distribution into the other by moving “distribution mass” around. This is a special case of the transportation problem from linear optimization, for which efficient algorithms are available. The EMD also allows for partial matching. When used to compare distributions that have the same overall mass, the EMD is a true metric, and has easy-to-compute lower bounds. In this paper we focus on applications to image databases, especially color and texture. We use the EMD to exhibit the structure of color-distribution and texture spaces by means of MultiDimensional Scaling displays. We also propose a novel approach to the problem of navigating through a collection of color images, which leads to a new paradigm for image database search.
Logic Programming for Software-Defined Networks
Motor skill acquisition.

INTRODUCTION ..................................................................................... 213 A GENERAL LAW OF MOTOR LEARNING ................................................. 215 Motor Learning as a Power Law .............................................................. 216 The Power Law--A Special Case of Motor Learning? .................................... 217 WHAT IS LEARNED WITH PRACTICE ....................................................... 219 One-To-One R call-Recognition Processes .................................................. 219 Schema Representation of Action .............................................................. 221 Problems with Prescriptive Accounts of Motor Learning ................................. 223 Motor Skill Acquisition as a Search Strategy ............................................... 224 INFORMATION A D MOTOR SKILL ACQUISITION ..................................... 225 Information as a Prescription .................................................................. 226 Information as Feedback ........................................................................ 227 Information to Channel the Search ............................................................ 231 CONCLUDING REMARKS ........................................................................ 233
Poststroke fatigue: a 2-year follow-up study of stroke patients in Sweden.

BACKGROUND AND PURPOSE
Fatigue is common among stroke patients. This study determined the prevalence of fatigue among long-term survivors after stroke and what impact fatigue had on various aspects of daily life and on survival.


METHODS
This study was based on Riks-Stroke, a hospital-based national register for quality assessment of acute stroke events in Sweden. During the first 6 months of 1997, 8194 patients were registered in Riks-Stroke, and 5189 were still alive 2 years after the stroke. They were followed up by a mail questionnaire, to which 4023 (79%) responded. Patients who reported that they always felt depressed were excluded.


RESULTS
To the question, "Do you feel tired?" 366 (10.0%) of the patients answered that they always felt tired, and an additional 1070 (29.2%) were often tired. Patients who always felt tired were on average older than the rest of the study population (74.5 versus 71.5 years, P<0.001); therefore, all subsequent analyses were age adjusted. Fatigue was an independent predictor for having to move into an institutional setting after stroke. Fatigue was also an independent predictor for being dependent in primary activities of daily living functions. Three years after stroke, patients with fatigue also had a higher case fatality rate.


CONCLUSIONS
Fatigue is frequent and often severe, even late after stroke. It is associated with profound deterioration of several aspects of everyday life and with higher case fatality, but it usually receives little attention by healthcare professionals. Intervention studies are needed.
Aging in Place: Self-Care in Smart Home Environments
Horse Racing Prediction Using Artificial Neural Networks

Artificial Neural Networks (ANNs) have been applied to predict many complex problems. In this paper ANNs are applied to horse racing prediction. We employed Back-Propagation, Back-Propagation with Momentum, QuasiNewton, Levenberg-Marquardt and Conjugate Gradient Descent learning algorithms for real horse racing data and the performances of five supervised NN algorithms were analyzed. Data collected from AQUEDUCT Race Track in NY, include 100 actual races from 1 January to 29 January 2010. The experimental results demonstrate that NNs are appropriate methods in horse racing prediction context. Results show that BP algorithm performs slightly better than other algorithms but it needs a longer training time and more parameter selection. Furthermore, LM algorithm is the fastest. Key-Words: Artificial Neural Networks, Time Series Analysis, Horse Racing Prediction, Learning Algorithms, BackPropagation
CellDesigner: a process diagram editor for gene-regulatory and biochemical networks

Systems biology is characterized by synergistic integration of theory, computational modeling, and experiment. Though software infrastructure is one of the most critical components of systems biology research, there has been no common infrastructure or standard to enable integration of computational resources. To solve this problem, the Systems Biology Markup Language (SBML) [2] and Systems Biology Workbench (SBW) have been developed. A number of simulation and analysis software packages already support SBML and SBW, or are in the process to support it. An identification of logic and dynamics of gene-regulatory and biochemical networks is a major challenge of systems biology. We believe that such network building tools and simulation environments using standardized technologies play an important role in software platform of systems biology. As one of the approaches, we have developed CellDesigner [1], which is a process diagram editor for gene-regulatory and biochemical networks.
VISUAL SENSITIVITY ANALYSIS
Systems Development in Information Systems Research

In this paper, the use of systems development as a methodology in information systems (is) research is described and defended. A framework to explain the nature of systems development as a research methodology in is research is proposed. Use of this methodology in the engineering field in general is compared with its use specifically in computer science and computer engineering. An integrated program for conducting IS research that incorporates theory building, systems development, experimentation, and observation is proposed. Progress in several application domains is reviewed to provide a basis upon which to argue that systems development is a valid research methodology. A systems development research process is presented from a methodological perspective. Software engineering, which is the basic method of applying the systems development research methodology, is then discussed. It is the authors' belief that systems development and other research methodologies are complementary and that an integrated multi-dimensional and multimethodological approach will generate fruitful is research results. The premise is that research contributions can result from systems development, experimentation, observation, and performance testing of the systems under development and that all of these research approaches are needed to investigate different aspects of the research question. An earlier version of Ihis paper was originally published in the Proceedings of ihe Twenty-Third Hawaii International Conference on System Sciences (IEEE Computer Society Press, 1990). Journal of Management Information Systems I Winter 1990-91, Vol. 7, No, 3, pp. 89-106. Copyright © M. E. Sharpe, Inc., 1991. 90 NUNAMAKER, CHEN. AND PURDIN
Greenhouse Temperature and Humidity Intelligent Control System

The article based on embedded database of greenhouse temperature and humidity control system intelligent. Put forward by embedded database system set up in an ideal environment for data greenhouse temperature and humidity control, greenhouse crops in the process of growth under control. To address the growth of greenhouse crops in the process of temperature and humidity controlled environment is not ideal, at the same time improve the efficiency of control and cost-effective system. The article focuses on the structure of the control system, hardware, software design and system control strategy. The control system has a simple hardware structure, cost-effective, easy to use and maintenance, temperature and humidity data, and other advantages of good stability. Key-Words: Embedded database, Temperature and Humidity, Control ; data filtering, Greenhouse,
Effect of transdermal teriparatide administration on bone mineral density in postmenopausal women.

CONTEXT
Treatment of osteoporosis with an anabolic agent, teriparatide [human PTH 1-34 (TPTD)], is effective in reducing incident fractures, but patient resistance to daily sc injections has limited its use. A novel transdermal patch, providing a rapid, pulse delivery of TPTD, may provide a desirable alternative.


OBJECTIVE
The aim of the study was to determine the safety and efficacy of a novel transdermal TPTD patch compared to placebo patch and sc TPTD 20-microg injection in postmenopausal women with osteoporosis.


DESIGN
Our study consisted of 6-month, randomized, placebo-controlled, positive control, multidose daily administration.


PATIENTS
We enrolled 165 postmenopausal women (mean age, 64 yr) with osteoporosis.


INTERVENTIONS
A TPTD patch with a 20-, 30-, or 40-microg dose or a placebo patch was self-administered daily for 30-min wear time, or 20 microg of TPTD was injected daily.


OUTCOMES
The primary efficacy measure was mean percentage change in lumbar spine bone mineral density (BMD) from baseline at 6 months.


RESULTS
TPTD delivered by transdermal patch significantly increased lumbar spine BMD vs. placebo patch in a dose-dependent manner at 6 months (P < 0.001). TPTD 40-microg patch increased total hip BMD compared to both placebo patch and TPTD injection (P < 0.05). Bone turnover markers (procollagen type I N-terminal propeptide and C-terminal cross-linked telopeptide of type I collagen) increased from baseline in a dose-dependent manner in all treatment groups and were all significantly different from placebo patch (P < 0.001). All treatments were well tolerated, and no prolonged hypercalcemia was observed.


CONCLUSION
Transdermal patch delivery of TPTD in postmenopausal women with osteoporosis for 6 months is safe and effective in increasing lumbar spine and total hip BMD.
MedScan, a natural language processing engine for MEDLINE abstracts

MOTIVATION
The importance of extracting biomedical information from scientific publications is well recognized. A number of information extraction systems for the biomedical domain have been reported, but none of them have become widely used in practical applications. Most proposals to date make rather simplistic assumptions about the syntactic aspect of natural language. There is an urgent need for a system that has broad coverage and performs well in real-text applications.


RESULTS
We present a general biomedical domain-oriented NLP engine called MedScan that efficiently processes sentences from MEDLINE abstracts and produces a set of regularized logical structures representing the meaning of each sentence. The engine utilizes a specially developed context-free grammar and lexicon. Preliminary evaluation of the system's performance, accuracy, and coverage exhibited encouraging results. Further approaches for increasing the coverage and reducing parsing ambiguity of the engine, as well as its application for information extraction are discussed.
Predicting good probabilities with supervised learning

We examine the relationship between the predictions made by different learning algorithms and true posterior probabilities. We show that maximum margin methods such as boosted trees and boosted stumps push probability mass away from 0 and 1 yielding a characteristic sigmoid shaped distortion in the predicted probabilities. Models such as Naive Bayes, which make unrealistic independence assumptions, push probabilities toward 0 and 1. Other models such as neural nets and bagged trees do not have these biases and predict well calibrated probabilities. We experiment with two ways of correcting the biased probabilities predicted by some learning methods: Platt Scaling and Isotonic Regression. We qualitatively examine what kinds of distortions these calibration methods are suitable for and quantitatively examine how much data they need to be effective. The empirical results show that after calibration boosted trees, random forests, and SVMs predict the best probabilities.
Utility of MRI after inconclusive ultrasound in pediatric patients with suspected appendicitis: retrospective review of 60 consecutive patients.

OBJECTIVE
The purpose of this study is to examine the utility of appendix MRI in evaluation of pediatric patients with right lower quadrant pain and inconclusive appendix sonography findings.


MATERIALS AND METHODS
A search of the radiology electronic database was performed for all appendix MRI examinations performed of pediatric patients within 24 hours after inconclusive appendix sonography from December 1, 2009, through April 26, 2012. Sixty patients underwent appendix MRI within 24 hours of inconclusive sonography and represented the study cohort. MRI examinations were reviewed independently by two radiologists blinded to the diagnosis and were graded as "positive," "negative," or "indeterminate" for acute appendicitis. The final diagnosis was established by review of the surgical and pathology reports and patients' electronic medical records.


RESULTS
Ten of 60 patients (17%) had acute appendicitis. Both readers graded the same 12 examinations as positive and the same 48 examinations as negative for acute appendicitis, with a kappa value of 1.00 (expected agreement, 0.695). No MRI examination was interpreted as indeterminate. The sensitivity and specificity of MRI for acute appendicitis in children with inconclusive appendix ultrasound findings were 100% (95% CI, 0.72-1.00) and 96% (95% CI, 0.87-0.98), respectively. The positive predictive value for the examination was 83%, the negative predictive value was 100%, and overall test accuracy was 97%.


CONCLUSION
Our study shows that MRI has a sensitivity of 100% and specificity of 96% for appendicitis in pediatric patients after inconclusive appendix sonography. We think that MRI may supplant CT as the secondary modality to follow inconclusive appendix sonography.
Impact Selective Incivility as Modern Discrimination in Organizations : Evidence and