Reviewerly/exHarmony huggingface dataset:
Version-Compatible HL7 Parser Based on Object-Oriented Design

International standards for the exchange of healthcare information, known as Health Level Seven (HL7), were developed for the interoperability of healthcare information systems. Because of HL7’s complex structure and syntax, HL7 messages are processed by computer software. HL7 defines that, when the version is updated, it should be compatible with the previous version. However, most of the HL7 interface software that is currently in development does not consider the version compatibility of HL7 messages. Instead, a separate conversion software module has been used to handle the version compatibility of HL7 messages for the healthcare information system. However, such a method is inefficient, because it requires several hours and incurs a huge cost. Therefore, in this study, an HL7 parser was developed that not only supports backward compatibility with older versions in accordance with the version compatibility definition of the HL7 V2 messages but also guarantees forward compatibility with newer versions to enhance its utilization. The developed parser was used to test conversion between different versions of HL7 V2 messages which were created to transmit information from one healthcare device to another. Through this test, the usefulness of the developed parser was verified.
Empirical Heatmap Decomposition—A Fresh Look on Gaze Behavior

The motivation for analyzing a person’s gaze be- havior stems from the eye-mind-hypothesis that correlates the observation of content by viewing it with its cognitive comprehension. A standard approach to quantitative analysis of gaze behavior is to analyze so called heatmaps generated by an eye tracker. This technical process is subject to noise. In order to compensate it, state-of-the-art eye tracking software smooths raw data using linear filters. In this paper, we present an alternative method based on interpolation. We provide empirical data that our method reproduces the actual gaze behavior more precisely. Furthermore, we introduce Empirical Heatmap Decomposition (EHD) to cluster eye movements into classes of similar frequency and amplitude. For evaluation, we present an analysis of gaze data that illustrates how EHD can uncover details in the observed gaze behavior that state-of-the-art heatmaps do not visualize.
The Effect of Sports Activities toward Emotional Intelligence of Junior High School Students

The purpose of this study was to examine the effect of sports activities on EI. The research method uses experimental research methods with pretest-posttest control group design. Participants in this study were extracurricular studentS SMP NU Kaplongan NU consists of 20 students. The research instrument used an EI questionnaire. Data analysis using independent samples t-test. The results of the study state that the factors that influence behavior change are more advanced among junior high school students, one of which is EI and there is an influence of sports activities on EI.
Underwater Image Restoration Based on Red Channel and Haze-Lines Prior

Due to the scattering and absorption of light while it propagates in the water, underwater images often suffer from low contrast and color distortion. In order to solve this problem, we propose an underwater image restoration algorithm based on red channel and haze-lines prior in this paper. Firstly, the red channel prior is used to estimate veiling-light. Secondly, according to the characteristics of red channel attenuation in water, the attenuation ratio of red-blue channel and red-green channel are introduced to estimate the transmission by using haze-lines prior. Finally, the transmission is corrected by the red channel boundary constraint. In addition, for underwater artificial illumination, we introduce saturation as the low bound of the transmission estimation to reduce the impact of artificial light. The experimental results show that the proposed algorithm can restore image color information, improve image clarity and obtain better visual quality. The quantitative analysis indicates that the proposed algorithm performs well on a wide variety of underwater images and is competitive with other state-of-the-arts.
Deducibility and Axiomatic Extensions

Throughout Part I, we have been discussing sequent systems for particular logics, like classical logic and intuitionistic logic, and logical properties of these logics by proof-theoretic analysis of sequent systems for them. These results are sharp and deep, which are often obtained as consequences of cut elimination. On the other hand, cut elimination holds for only a limited number of sequent systems.
An Automatic Calculation Method for Sentiment Word Polarity in Commodity Reviews

The sentiment polarity of sentiment words often appears inconsistent in different commodity fields, due to the numerous fields involved in online commodity reviews. Traditional methods of manually labeling sentiment polarity are time-consuming and laborious. To solve this problem, this paper proposes a Sentiment Polarity Automatic Calculation Method (SPACM) to calculate the sentiment word polarity in commodity reviews. First, the sentiment words are divided into positive, negative and neutral word sets based on Chinese sentiment word ontology base and the weak tagging information of user’s score. Then, based on the weight of each character in word sets, the sentiment polarity value of sentiment character is obtained by normalization of Gaussian function. The sentiment polarity value of sentiment word composed of characters is obtained by method of cumulative averaging. Finally, the sentiment dictionary with weights is constructed. Based on the characteristic of the distribution of sentiment word polarity values in three word sets, the concept of distinguishing the threshold is proposed as the basis of division to re-divide the polarity of sentiment words. The experimental results demonstrate the effectiveness of the proposed method.
ANALISIS KEMAMPUAN SISWA KELAS IV DALAM MENEMUKAN UNSUR-UNSUR PARAGRAF PADA TEKS BACAAN

&#x0D; The purpose of this study was to describe students' ability to find paragraph elements in the reading text. The research method used was a mix of research methods with explanatory sequential research designs. Data collection techniques consisted of tests, interviews, and documentation. The research object was 34 students. Students' ability to find the main sentence in reading texts; 1, 2, and 3 shows sufficient criteria (60.77%) of a maximum score of 100%. The ability of students to find the main ideas in reading texts 1, 2, and 3 showed very fewer criteria (0%) than a maximum score of 100%. Students' ability to find explanatory sentences in the reading texts 1, 2 and 3 with sufficient criteria (55, 01%) from a maximum score of 100%. In general, the students’ mistakes were because they lack attention to teacher explanations and practice questions in finding elements of the paragraph.
MLV-Viewer: Multi-level Visualization in Decision Support Systems Prototype

Information visualization (InfoVis) is defined as ”the use of visual, interactive and visual representations supported by computer, to increase cognition”. InfoVis tools and methods help us accelerate our understanding of a large amount of data. Datavisualization improves understanding, especially with multidimensional data sets. Visual analysis methods allow decision makers to combine their human flexibility, creativity and knowledgewith the huge storage and processing capabilities of today's computers for information about complex problems. Using advanced visual interfaces, humans can interact directly with the data analysis, adding more to their liking and need. The MLV-Viewer prototype will be described in this article.
Protecting the Values of Consumer Law in the Digital Economy: The Case of 3D-Printing

The law on consumer goods is currently underpinned to a significant degree by the need ethic (prioritising protection of consumers as vulnerable parties, over business self-interest and consumer self-reliance ). This is manifest in strict and quasi-strict liability standards. Notwithstanding 3D-printing innovations, there is a good case for adherence to the need ethic: The risks (of poor quality and unsafe goods) are as high as before (or higher); consumers are as vulnerable (or more so) than before; and there is insufficient evidence that the need ethic undermines innovation. We will argue in this paper that, despite the innovative aspects of 3D-printing, the law can often continue to reflect the need ethic via existing legal principles (current strict and quasi strict liability standards), subject to some extensions (e.g. as to supplier and producer liability for digital content), and through clarifications of existing legal rules and principles (e.g. as to who counts as a professional business supplier). However, to ensure that the need ethic is respected fully in all aspects of this technology, the law may need to go beyond these clarifications and modest extensions. For example, the increasing difficulty of locating the source of a quality or safety problem and the impact this has on a consumer’s ability to discharge the burden of proof, increase the need to impose some ‘network’ liability, involving re-allocation of responsibilities to traders (e.g. internet platforms) who would not be responsible under traditional legal regimes.This analysis is significant in providing specific doctrinal solutions for an important and emerging sector of the consumer economy. More generally, it provides a new theoretical framework for analysing how consumer law should deal with the challenges of innovation.
Call Center Application

We are now ready to make our work more practical. We have seen different approaches in using ORM frameworks, and we have a good understanding of the fundamentals of Aurelius. In this chapter, we work on setting up the building blocks that will allow us to see Aurelius in practice.
Social Studies Learning Using Audio Visual Media in Elementary School

This study aims to describe an increase in student learning outcomes in social studies learning using Audio Visual media in grade IV SDN 04 Bukit Apit Puhun Bukittinggi. The type of research is PTK using qualitative and quantitative approaches. RPP assessment cycle I is 81.5% increased to 94% in cycle II, implementation of teacher action cycle I is 79% increased to 91% in cycle II, implementation of student action cycle I is 79% increased to 91% in cycle II, and Student learning outcomes in cycle I were 68.4%, increasing to 80.7% in cycle II. Thus Audio Visual media can improve student learning outcomes in social studies learning in class IV SDN 04 Bukit Apit Puhun Bukittinggi
Introduction to the Special Issue on the Cross-Media Analysis for Visual Question Answering

editorial Free Access Share on Introduction to the Special Issue on the Cross-Media Analysis for Visual Question Answering Editors: Richang Hong Hefei University of Technology, China Hefei University of Technology, ChinaView Profile , Yahong Han Tianjin University, China Tianjin University, ChinaView Profile , Tat-Seng Chua National University of Singapore, Singapore National University of Singapore, SingaporeView Profile Authors Info & Claims ACM Transactions on Multimedia Computing, Communications, and ApplicationsVolume 15Issue 2sApril 2019 Article No.: 48pp 1–3https://doi.org/10.1145/3337985Published:03 July 2019Publication History 1citation368DownloadsMetricsTotal Citations1Total Downloads368Last 12 Months72Last 6 weeks9 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteView all FormatsPDF
Study and Practice on Skills Competition Help Vocational Education Students Growing up

Abstract In order to research the influence of skill contest on students’ growth, a questionnaire survey was conducted among students of Tianmen Vocational College. Research shows that 100% of students want to be respected. 92% percent of students care about their advantage. This brings good enlightenment to teaching. Competition events should not be single. Only in the way that competition promotes each other can lead promoting learning through competition. The purpose of the competition is not to win the prize. Competition is learning, finding gaps and shaping students. Competition avoids the fictitious elements contrast with E-learning. Through the competition students could endeavour to study, self-respect can be developed, psychological quality can be enhanced and the sense of social responsibility can be enhanced. Skills competition pursues frontier ideas. Only by reform can achieve good results. Teachers play a key role in the course of the competition.
Two Parameter Logistics Model with Lognormal Response Time for Computer-based Testing

In addition to the information on response pattern/accuracy, Computer-Based Testing (CBT) can also generate information on response time. This research contributes to develop two-parameter logistics model with random variables of response time for CBT power test. Based on that model, the probability of the test taker answering the test questions correctly is influenced by the test taker’s ability, the test question’s discriminating power, the question’s level of difficulty, the delay due to the test question’s factors and response time. The development of this model aims to improve the parameter estimation of the logistics model on Item Response Theory (IRT) which does not consider the response time of the model. This model is simultaneously developed using joint distribution concept, by multiplying the conditional distribution of response accuracy (two-parameter logistics model) by response time with marginal distribution of response time. The marginal distribution chosen in this study is lognormal distribution because it has positive value in the form of positive skewed according to the characteristics of the response time. To prove the model is suitable for power test, is tested using CBT data. The study found that the simultaneous model generated from the multiplication between the two-parameter logistics model integrated with response time and the lognormal response time model is an appropriate model for CBT power test.
UniCAVE

This chapter introduces UniCAVE, a free Unity3D plugin, which provides support for these types of distributed virtual reality (VR) rendering systems. The UniCAVE plugin works on immersive display systems driven by either a single machine or a cluster. UniCAVE accomplishes data distribution through a combination of Unity3D networking techniques that allow the sharing of camera transformations, user input, randomization seeds, and time step information. The UniCAVE plugin provides support for different stereo techniques. Techniques such as quad-buffered stereo, side-by-side stereo, or split-screen stereo are configured by way of setting up the correct camera and viewport configurations in the Unity3D editor. Input serves as a challenge when trying to create a distributed rendering system within Unity3D due to limitations in how Unity3D provides access to a project’s input definitions. UniCAVE supports basic input via interfacing with VRPN and furthermore supports basic distribution of the input across a cluster.
IMPROVING ENGLISH SPEAKING ABILITIES OF ESL LEARNERS THROUGH COMMUNICATIVE TASK-BASED INSTRUCTION

Speaking is one of the most exploited skills. However, despite the many endeavors conducted by English teachers, speaking proficiency remains poor among tertiary students. This qualitative-phenomenological study aimed to determine the experiences of the students on the use of communicative task-based instruction in improving their speaking abilities. Using the focus group discussion, the researcher found that gener-ally, the participants believed that the communicative task-based instruction provided them opportunities to enhance their communicative abilities; let them overcome the fear of speaking; gave them a lot of fun; and allowed them to apply the tasks even outside their classrooms. The participants suggested that exposure to real conversa-tion tasks might be done; design individual tasks would be interesting, and that technology might be used in doing the tasks. Thorough discussions and conclusion were provided.
The Studentsâ€™ Ability in Reading Comprehension in Narrative Text

Reading skill plays an important role in English learning process, especially when student have to deal with TOEFL Exam which includes reading and writing skill. The writer observed that the process of comprehending a reading text was still a serious problem for the students. The writer applied a qualitative method in this research with descriptive approach. The subject of the study was the first semester students class E of Universitas Prima Indonesia Medan. The instrument of data collecting was multiple choice test. The mean score of the studentsâ€™ in comprehending narrative text was 77. It shown that their comprehension narrative text was average to good. There was 12 students (48%) was classified as Excellent, 12 students (48%) was classified as Good and there was 1 students (4%) was classified as Average whereas no student (0%) wasÂ classified as poor to comprehending narrative text. Therefore, the writer hopes that the other English lecturer should always try to create an interesting text and media for their teaching.
Meta-Learner with Sparsified Backpropagation

In todays world, Deep Learning is an area of research that has ever increasing applications. It deals with the use of neural networks to bring improvements in areas like speech recognition, computer vision, natural language processing and several automated systems. Training deep neural networks involves careful selection of appropriate training examples, tuning of hyperparameters and scheduling step sizes, finding a proper combination of all these is a tedious and time-consuming task. In the recent times, a few learning-to-learn models have been proposed, that can learn automatically. The time and accuracy of the model are exceedingly important. A technique named meProp was proposed to accelerate Deep Learning with reduced over-fitting. meProp is a method that proposes a sparsified back propagation method which reduces the computational cost. In this paper, we propose an application of meProp to the learning-to-learn models to focus on learning of the most significant parameters which are consciously chosen. We demonstrate improvement in accuracy of the learning-to-learn model with the proposed technique and compare the performance with that of the unmodified learning-to-learn model.
Penerapan model think talk write (ttw) guna meningkatkan keterampilan representasi soal cerita materi bangun datar peserta didik kelas ivc sekolah dasar

The purpose of this research is improve representation skills in the stories matter by applying Think Talk Write (TTW) learning model. The subjects were 25 a taken from all the  students in IVC class at SD Ta’mirul Islam Surakarta in the 2018/ 2019. This research is classroom reseach with three cycles. Data collection technique are using test, observation and documentation with data analysis of technique triangulation, source triangulation and content validity. The initial condition of representation skills in IVC class students showed 4% classically. The first cycle began with the first learning resulting in percentage of 21.7% in classical the second learning was 40.90 % in classical. The study continued with the second cycle with the percentage of achievement at the first learning amounting 61.90 % in classical, the second was 77.30%. The sudy continued with third cycles with the first learning persentage of 84.00% and the second was 87.00%.
Sistem Rekomendasi Produk Menggunakan Model RFM, AHP dan Ranked Clustering

Monstreation is a business engaged in clothing convection, these business products are marketed online such as jackets and shirts for class, shirt and community clothing. The problem that occurs in this convection is the lack of product recommendation services to customers. Another problem is that if there are customers who order products that are not in accordance with their needs, the customer will rarely order products at Monstreation. The solution used is to provide services that match the characteristics of the customer, for example by giving product recommendations. Product recommendations are also needed considering this type of business is a business that has many business rivals. The steps taken in this study begin by collecting customer transaction data, then the data is transformed into RFM criteria data. After being transformed, the data is weighted using AHP, after that the RFM data is weighted then grouped / clustered. The grouping results are validated with DBI. From the experiments conducted it is known that the number of cluster 3 is the optimal number of clusters in product grouping. After it is ranked based on the value of the total weight. From the experiments conducted, it is known that the results of the 3 customer clusters, the customers who have the highest weight value are customers in cluster 1. The results of this study are a product recommendation that is an association of product history of customers who have a cluster similarity and a product recommendation information system.&#x0D;
An Efficient Scheme for Automatic Pill Recognition Using Neural Networks

An efficient scheme, capable of extracting key pill features, for an automatic pill recognition is proposed. The devised system involves a number of processes which starts with the thresholding applied to the input query pill image for extraction of the shape feature vector and generation of mask images. The extracted shape feature vector is used for shape recognition through a trained neural network. Information regarding the color and size of the pill is obtained by using the mask images and shape information. For pill imprint extraction, a modified stroke width transform (MSWT) and two-step sampling is applied. The extracted pill query features are compared with the feature values of the created database for recognition of the pill and its purpose. The proposed method is evaluated on a dataset of 2500 images and achieves an accuracy of 98% which shows the supremacy of the proposed method in comparison to the other similar pill recognition systems.
Conceptions of Library and Information Science (CoLIS)

Conceptions of Library and Information Science (CoLIS) is a series of international conferences aiming to provide a broad forum for the exploration and exchange of ideas in the field of Library and Information Science, Information Studies, and related disciplines. It welcomes diverse contributions offering empirical, theoretical and historical perspectives.The 10th conference in the series was organised in June 16-19 2019 by the Department of Library and Information Science and Book Studies at Faculty of Arts, University of Ljubljana.