snu-aidas/HVMap-dataset huggingface dataset:
Internet-based peer support for parents: a systematic integrative review.

OBJECTIVES
The Internet and social media provide various possibilities for online peer support. The aim of this review was to explore Internet-based peer-support interventions and their outcomes for parents.


DESIGN
A systematic integrative review.


DATA SOURCES
The systematic search was carried out in March 2014 in PubMed, Cinahl, PsycINFO and Cochrane databases.


REVIEW METHODS
Two reviewers independently screened the titles (n=1793), abstracts and full texts to decide which articles should be chosen. The inclusion criteria were: (1) an Internet-based community as an intervention, or at least as a component of an intervention; (2) the participants in the Internet-based community had to be mothers and/or fathers or pregnant women; (3) the parents had to interact and communicate with each other through the Internet-based community. The data was analysed using content analysis. When analysing peer-support interventions only interventions developed by researchers were included and when analysing the outcomes for the parents, studies that focused on mothers, fathers or both parents were separated.


RESULTS
In total, 38 publications met the inclusion criteria. Most of the studies focused on Internet-based peer support between mothers (n=16) or both parents (n=15) and seven focused on fathers. In 16 studies, the Internet-based interventions had been developed by researchers and 22 studies used already existing Internet peer-support groups, in which any person using the Internet could participate. For mothers, Internet-based peer support provided emotional support, information and membership in a social community. For fathers, it provided support for the transition to fatherhood, information and humorous communication. Mothers were more active users of Internet-based peer-support groups than fathers. In general, parents were satisfied with Internet-based peer support. The evidence of the effectiveness of Internet-based peer support was inconclusive but no harmful effects were reported in these reviewed studies.


CONCLUSIONS
Internet-based peer support provided informational support for parents and was accessible despite geographical distance or time constraints. Internet-based peer support is a unique form of parental support, not replacing but supplementing support offered by professionals. Experimental studies in this area are needed.
Real-time motion planning methods for autonomous on-road driving: State-of-the-art and future research directions

Currently autonomous or self-driving vehicles are at the heart of academia and industry research becauseof itsmulti-faceted advantages that includes improved safety, reduced congestion, lower emissions and greater mobility. Software is the key driving factor underpinning autonomy within which planning algorithms that are responsible for mission-critical decision making hold a significant position. While transporting passengers or goods from a givenorigin to agivendestination,motionplanningmethods incorporate searching for apath to follow, avoiding obstacles and generating the best trajectory that ensures safety, comfort and efficiency. A range of different planning approaches have beenproposed in the literature. Thepurpose of this paper is to reviewexisting approaches and then compare and contrast different methods employed for the motion planning of autonomous on-road driving that consists of (1)findingapath, (2) searching for the safestmanoeuvre and (3)determining themost feasible trajectory. Methods developed by researchers in each of these three levels exhibit varying levels of complexity and performance accuracy. This paper presents a critical evaluation of each of these methods, in terms of their advantages/disadvantages, inherent limitations, feasibility, optimality, handling of obstacles and testing operational environments. Based on a critical review of existingmethods, research challenges to address current limitations are identified and future research directions are suggested so as to enhance the performanceofplanningalgorithmsat all three levels. Somepromising areasof future focushave been identified as the use of vehicular communications (V2V and V2I) and the incorporation of transport engineering aspects in order to improve the look-ahead horizon of current sensing technologies that are essential for planning with the aim of reducing the total cost of driverless vehicles. This critical reviewon planning techniques presented in this paper, along with theassociateddiscussions on their constraints and limitations, seek to assist researchers in accelerating development in the emerging field of autonomous vehicle research. Crown Copyright 2015 Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
ON THE EMERGENCE OF GR 4 AMMAR FROM THE LEXICON
Word Segmentation : The Role of Distributional Cues

One of the infant’s first tasks in language acquisition is to discover the words embedded in a mostly continuous speech stream. This learning problem might be solved by using distributional cues to word boundaries—for example, by computing the transitional probabilities between sounds in the language input and using the relative strengths of these probabilities to hypothesize word boundaries. The learner might be further aided by language-specific prosodic cues correlated with word boundaries. As a first step in testing these hypotheses, we briefly exposed adults to an artificial language in which the only cues available for word segmentation were the transitional probabilities between syllables. Subjects were able to learn the words of this language. Furthermore, the addition of certain prosodic cues served to enhance performance. These results suggest that distributional cues may play an important role in the initial word segmentation of language learners. q 1996 Academic Press, Inc.
Bio-Inspired Robotics Based on Liquid Crystalline Elastomers ( LCEs ) and Flexible Stimulators
Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke.

OBJECTIVE
To compare the effects of robot-assisted movement training with conventional techniques for the rehabilitation of upper-limb motor function after stroke.


DESIGN
Randomized controlled trial, 6-month follow-up.


SETTING
A Department of Veterans Affairs rehabilitation research and development center.


PARTICIPANTS
Consecutive sample of 27 subjects with chronic hemiparesis (>6mo after cerebrovascular accident) randomly allocated to group.


INTERVENTIONS
All subjects received twenty-four 1-hour sessions over 2 months. Subjects in the robot group practiced shoulder and elbow movements while assisted by a robot manipulator. Subjects in the control group received neurodevelopmental therapy (targeting proximal upper limb function) and 5 minutes of exposure to the robot in each session.


MAIN OUTCOME MEASURES
Fugl-Meyer assessment of motor impairment, FIMtrade mark instrument, and biomechanic measures of strength and reaching kinematics. Clinical evaluations were performed by a therapist blinded to group assignments.


RESULTS
Compared with the control group, the robot group had larger improvements in the proximal movement portion of the Fugl-Meyer test after 1 month of treatment (P<.05) and also after 2 months of treatment (P<.05). The robot group had larger gains in strength (P<.02) and larger increases in reach extent (P<.01) after 2 months of treatment. At the 6-month follow-up, the groups no longer differed in terms of the Fugl-Meyer test (P>.30); however, the robot group had larger improvements in the FIM (P<.04).


CONCLUSIONS
Compared with conventional treatment, robot-assisted movements had advantages in terms of clinical and biomechanical measures. Further research into the use of robotic manipulation for motor rehabilitation is justified.
Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
Number : AUTCON-D16-00058 R 1 Title : BIM for Infrastructure : An Overall Review and Constructor Perspective

6 The subject of Building Information Modelling (BIM) has become a central topic to the improvement of the AECOO 7 (Architecture, Engineering, Construction, Owner and Operator) industry around the world, to the point where the 8 concept is being expanded into domains it was not originally conceived to address. Transitioning BIM into the 9 domain of infrastructure projects has provided challenges and emphasized the constructor perspective of BIM. 10 Therefore, this study aims to collect the relevant literature regarding BIM within the Infrastructure domain and its 11 use from the constructor perspective to review and analyse the current industry positioning and research state of 12 the art, with regards to the set criteria. The review highlighted a developing base of BIM for infrastructure. From 13 the analysis, the related research gaps were identified regarding information integration, alignment of BIM 14 processes to constructor business processes & the effective governance and value of information. From this a 15 unique research strategy utilising a framework for information governance coupled with a graph based distributed 16 data environment is outlined to further progress the integration and efficiency of AECOO Infrastructure projects. 17
Laughbot: Detecting Humor in Spoken Language with Language and Audio Cues

We propose detecting and responding to humor in spoken dialogue by extracting language and audio cues and subsequently feeding these features into a combined recurrent neural network (RNN) and logistic regression model. In this paper, we parse Switchboard phone conversations to build a corpus of punchlines and unfunny lines where punchlines precede laughter tokens in Switchboard transcripts. We create a combined RNN and logistic regression model that uses both acoustic and language cues to predict whether a conversational agent should respond to an utterance with laughter. Our model achieves an F1-score of 63.2 and accuracy of 73.9. This model outperforms our logistic language model (F1-score 56.6) and RNN acoustic model (59.4) as well as the final RNN model of D. Bertero, 2016 (52.9). Using our final model, we create a “laughbot” that audibly responds to a user with laughter when their utterance is classified as a punchline. A conversational agent outfitted with a humorrecognition system such as the one we present in this paper would be valuable as these agents gain utility in everyday life. Keywords—Chatbots; spoken natural language processing; deep learning; machine learning
Reconstruction of dorsal and/or caudal nasal septum deformities with septal battens or by septal replacement: an overview and comparison of techniques.

OBJECTIVES
The objectives of this study were to describe and compare two techniques used to correct nasal septum deviations located in the dorsal and/or caudal septum.


STUDY DESIGN
The authors conducted a retrospective clinical chart review.


METHODS
The authors conducted a comparison of functional and technical results between surgery in the L-strut of the septum in 114 patients with septal battens or by septal replacement by subjective self-evaluation and by examination of the position of the septum during follow up.


RESULTS
There was subjective improvement in nasal breathing in 86% of the septal batten group and in 94% of the septal replacement group. This difference was not statistically significant. The technical result was judged by examining the position of the septum during follow up as midline, slightly deviated, or severely deviated. The septum was significantly more often located in the midline during follow up in the septal replacement group than in the septal batten group.


CONCLUSION
Treatment of deformities located in the structurally important L-strut of the septum may be technically challenging and many functional, structural, and esthetic considerations must be taken into account. On the basis of this series, both septal battens and septal replacement techniques may be considered for correction of deviations in this area. The functional improvement rates were not significantly different between the techniques, although during follow up, the septum appeared to be significantly more often located in the midline in the septal replacement group. The techniques are described and their respective advantages and potential drawbacks are discussed.
Performance Analysis of Classification Algorithms on Medical Diagnoses-a Survey

Corresponding Author: Vanaja, S., Research Scholar and Research guide, Research and Development, Bharathiar University, Coimbatore, Tamil Nadu, India Email: vanajasha@yahoo.com Abstract: The aim of this research paper is to study and discuss the various classification algorithms applied on different kinds of medical datasets and compares its performance. The classification algorithms with maximum accuracies on various kinds of medical datasets are taken for performance analysis. The result of the performance analysis shows the most frequently used algorithms on particular medical dataset and best classification algorithm to analyse the specific disease. This study gives the details of different classification algorithms and feature selection methodologies. The study also discusses about the data constraints such as volume and dimensionality problems. This research paper also discusses the new features of C5.0 classification algorithm over C4.5 and performance of classification algorithm on high dimensional datasets. This research paper summarizes various reviews and technical articles which focus on the current research on Medical diagnosis.
Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs Part 1 . Background

Battery management systems (BMS) in hybrid-electric-vehicle (HEV) battery packs must estimate values descriptive of the pack’s present operating condition. These include: battery state of charge, power fade, capacity fade, and instantaneous available power. The estimation mechanism must adapt to changing cell characteristics as cells age and therefore provide accurate estimates over the lifetime of the pack. In a series of three papers, we propose a method, based on extended Kalman filtering (EKF), that is able to accomplish these goals on a lithium-ion polymer battery pack. We expect that it will also work well on other battery chemistries. These papers cover the required mathematical background, cell modeling and system identification requirements, and the final solution, together with results. This first paper investigates the estimation requirements for HEV BMS in some detail, in parallel to the requirements for other battery-powered applications. The comparison leads us to understand that the HEV environment is very challenging on batteries and the BMS, and that precise estimation of some parameters will improve performance and robustness, and will ultimately lengthen the useful lifetime of the pack. This conclusion motivates the use of more complex algorithms than might be used in other applications. Our premise is that EKF then becomes a very attractive approach. This paper introduces the basic method, gives some intuitive feel to the necessary computational steps, and concludes by presenting an illustrative example as to the type of results that may be obtained using EKF. © 2004 Elsevier B.V. All rights reserved.
Consumers ’ Trust in Electronic Commerce Transactions : The Role of Perceived Privacy and Perceived Security 1 Introduction

Acknowledgement I am greatly indebted to Omar El Sawy and Ann Majchrzak for their guidance and suggestion, and I would like to thank Ricky Lim and Raymond for their help with the data analysis. Abstract Consumers' trust in their online transactions is vital for the sustained progress and development of electronic commerce. Our paper proposes that in addition to known factors of trust such a vendor's reputation, consumers' perception of privacy and security influence their trust in online transactions. Our research shows that consumers exhibit variability in their perceptions of privacy, security and trust between online and offline transactions even if it is conducted with the same store. We build upon this finding to develop and validate measures of consumers' perceived privacy and perceived security of their online transactions which are then theorized to influence their trust in EC transactions. We propose that the perceptions of privacy and security are factors that affect the consumers' trust in the institutional governance mechanisms underlying the Internet. We conduct two distinct empirical studies and through successive refinement and analysis using the Partial Least Squares technique, we test our hypothesized relationships while verifying the excellent measurement properties associated with our instrument. Our study finds that the consumers' perceived privacy and perceived security are indeed distinct constructs but the effect of perceived privacy on trust in EC transactions is strongly mediated by perceived security. A major implication of our findings is that while the much studied determinants of trust such as reputation of the transacting firm should not be neglected, vendors should also engage in efforts to positively influence consumer perceptions of privacy and security. We discuss the significance of this observation in the context of increasing importance in acquiring customer information for personalization and other online strategies.
Modeling crowdsourcing systems: design and analysis of incentive mechanism and rating system

Over the past few years, we have seen an increasing popularity of crowdsourcing services [5]. Many companies are now providing such services, e.g., Amazon Mechanical Turk [1], Google Helpouts [3], and Yahoo! Answers [8], etc. Briefly speaking, crowdsourcing is an online, distributed problem solving paradigm and business production platform. It uses the power of today’s Internet to solicit the collective intelligence of large number of users. Relying on the wisdom of the crowd to solve posted tasks (or problems), crowdsourcing has become a promising paradigm to obtain “solutions” which can have higher quality or lower costs than the conventional method of solving problems via specialized employees or contractors in a company. Typically, a crowdsourcing system operates with three basic components: Users, tasks and rewards. Users are classified into requesters and workers. A user can be a requester or a worker, and in some cases, a user can be a requester/worker at the same time. Requesters outsource tasks to workers and associate each task with certain rewards, which will be granted to the workers who solve the task. Workers, on the other hand, solve the assigned tasks and reply to requesters with solutions, and then take the reward, which can be in form of money [1], entertainment [7] or altruism [8], etc. To have a successful crowdsourcing website, it is pertinent to attract high volume of participation of users (requesters and workers), and at the same time, solutions by workers have to be of high quality. In this paper we design a rating system and a mechanism to encourage users to participate, and incentivize workers to high quality solutions. First, we develop a game-theoretic model to characterize workers’ strategic behavior. We then design a class effective incentive mechanisms which consist of a task bundling scheme and a rating system, and pay workers according to solution ratings from requesters. We develop a model to characterize the design space of a class of commonly users rating systems– threshold based rating system. We quantify the impact of such rating systems, and the bundling scheme on reducing requesters’ reward payment in guaranteeing high quality solutions. We find out that a simplest rating system, e.g., two rating points, is an effective system in which requesters only need to provide binary feedbacks to indicate whether they are satisfied or not with a solution.
OCCUPATIONAL THERAPY FOR THE POLY- TRAUMA CASUALTY WITH LIMB LOSS
Information systems in supply chain integration and management

Supply chain management (SCM) is the 21st century global operations strategy for achieving organizational competitiveness. Companies are attempting to find ways to improve their flexibility and responsiveness and in turn competitiveness by changing their operations strategy, methods and technologies that include the implementation of SCM paradigm and information technology (IT). However, a thorough and critical review of literature is yet to be carried out with the objective of bringing out pertinent factors and useful insights into the role and implications of IT in SCM. In this paper, the literature available on IT in SCM have been classified using suitable criteria and then critically reviewed to develop a framework for studying the applications of IT in SCM. Based on this review and analysis, recommendations have been made regarding the application of IT in SCM and some future research directions are indicated. 2003 Elsevier B.V. All rights reserved.
The American Economic Review VOLUME XLV MARCH , 1955 NUMBER ONE ECONOMIC GROWTH AND INCOME INEQUALITY
Designing a Tag-Based Statistical Math Word Problem Solver with Reasoning and Explanation

Background Since Big Data mainly aims to explore the correlation between surface features but not their underlying causality relationship, the Big Mechanism 2 program has been proposed by DARPA to find out “why” behind the “Big Data”. However, the pre-requisite for it is that the machine can read each document and learn its associated knowledge, which is the task of Machine Reading (MR). Since a domain-independent MR system is complicated and difficult to build, the math word problem (MWP) [1] is frequently chosen as the first test case to study MR (as it usually uses less complicated syntax and requires less amount of domain knowledge). According to the framework for making the decision while there are several candidates, previous MWP algebra solvers can be classified into: (1) Rule-based approaches with logic inference [2-7], which apply rules to get the answer (via identifying entities, quantities, operations, etc.) with a logic inference engine. (2) Rule-based approaches without logic inference [8-13], which apply rules to get the answer without a logic inference engine. (3) Statistics-based approaches [14, 15], which use statistical models to identify entities, quantities, operations, and get the answer. To our knowledge, all the statistics-based approaches do not adopt logic inference. The main problem of the rule-based approaches mentioned above is that the coverage rate problem is serious, as rules with wide coverage are difficult and expensive to construct. Also, since they adopt Go/No-Go approach (unlike statistical approaches which can adopt a large Top-N to have high including rates), the error accumulation problem would be severe. On the other hand, the main problem of those approaches without adopting logic inference is that they usually need to implement a new handling procedure for each new type of problems (as the general logic inference mechanism is not adopted). Also, as there is no inference engine to generate the reasoning chain [16], additional effort would be required for