Reviewerly/exHarmony huggingface dataset:
CONVERGÊNCIAS E ENTRELACES ENTRE MEDIAÇÃO E GESTÃO DA INFORMAÇÃO: INDÍCIOS E PERSPECTIVAS APRESENTADOS NA LITERATURA DA CIÊNCIA DA INFORMAÇÃO

In this work, information management activities are understood as implicit information mediation actions.This is due to the fact that these activities aim to help users in their own development by means of information appropriation.The information manager should must act in order to meet user demands, attend information needs, as well as support them the development of their information practices.Therefore, they must act from the perspective of information mediation, developing conscious actions.This work aimed to seek convergence between the areas of information management (IM) and information mediation (IM), based on the analysis of scholarly articles dealing with these issues present in the Base de Dados Referenciais de Artigos de Periódicos em Ciência da Informação (BRAPCI).The methodology used was of bibliographic research, with a qualitative approach to data analysis and content analysis technique.The research points out that most researchers treat information mediation and management as elements that maintain some level of approximation, but the majority of these studies focus on these issues separately, without an indication of possible connections.In other cases, these subjects are subliminally presented.Thus, the research points out the need for the development of studies that consider theoretical and practical prepositions in accordance to information mediation.It is an alternative to broaden the information management spectrum and support organizational culture where other professionals are also act as mediators, favoring a dialogical relationship with users that will support the information use and appropriation.
Security Theater, the Beat Goes On

Presents corrections to affiliation information in the above named paper.
Low Power VLSI Architecture for Modular Adder by Reversible Gates

Reversible logic is a computing paradigm that has attracted significant attention in recent years due to its properties that lead to ultra-low power and reliable circuits. Reversible circuits are fundamental, for quantum computing. Since addition is a basic operation, designing efficient adders is a cornerstone in the research of reversible circuits. Residue Number Systems (RNS) has been as a powerful to provide parallel computations where additions and multiplications are dominant. In this paper, for the first time in the literature, we propose the combination of RNS and reversible logic. The parallelism of RNS is leveraged to increase the performance of reversible computational circuits. Being the most fundamental part in any RNS, in this work we propose the implementation of modular adders, namely modulo 2n-1 adders, using reversible logic. Analysis and comparison with traditional logic show that modulo adders can be designed using reversible gates with minimum overhead in comparison to regular adders.
초등학교 한자교육에 필요한 한자의 字數, 字種 선정에 대한 연구 - 초등학교 한자 교과서를 중심으로 -

This study aims to suggest the selection of the optimum numbers(i.e., character quantity) and the species of Chinese characters(i.e., type of Chinese character) for elementary school education, based on the idea that Chinese character education in elementary school is centered on Sino-Korean word education. In our resent study - A Study on the Optimum Number and the Selection Standard of Chinese Character for Elementary School Education, we suggested the selecting strategy of ‘Chinese character for elementary school education’, by newly applying the data of Kim, Han-saem(2009) and Natmal Inc: Research Institute of Korean language information Processing. In the process of discussing the details, we considered elementary school textbook corpus, graded lexicon reflecting vocabulary evaluation, productivity in word-formation, professional judgment, etc. Among them, elementary school textbook corpus that we applied at every stage had been merely applied for measuring the simple frequency in the previous researches. The applications of graded lexicon and productivity in word-formation in this study are first considered in the academic field. Although the existing research has achieved the above results, it still has its own limitation. It is that it does not include the textbooks of elementary schools in the scope of research, so it does not give importance to actual education field. This study intends to supplement and expand the existing research by conducting research on eight current Chinese character textbooks consisting of six volumes. As a result, 548 Chinese characters are selected and the list was presented, and 75 Chinese characters are added that could be used in vocabulary education. We hope that the above 623 characters will be a constant reference in the education of Chinese characters in elementary schools in the future, and that supplementary research by academia will be conducted in the future.
Depth Map Building and Enhancement using a Monocular Camera, Object Shape Priors and Variational Methods

We present a monocular system that uses shape priors for improving the quality of estimated depth maps, specially in the region of an object of interest, when the environment presents complex conditions like changes in light, with low-textured, very reflective and translucent objects. A depth map is built by solving a non-convex optimization problem using the primal-dual algorithm and a coupling term. The energy functional consists of a photometric term for a set of images with common elements in the scene and a regularization term that allows smooth solutions. The camera is moved by hand and tracked using ORB-SLAM2. The resulting depth map is enhanced by integrating, with a novel variational formulation, depth data coming from the 3D model that best fits to observed data, optimized w.r.t. shape, pose and scale (shape prior). We also present an alternative algorithm that simultane ously builds a depth map and integrates a previously estimated shape prior. We quantify the improvements in accuracy and in noise reduction of the final depth map.
PENINGKATAN KETERAMPILAN MENYUSUN TEKS CERITA SEJARAH MENGGUNAKAN STRATEGI GENIUS LEARNING MATA PELAJARAN BAHASA INDONESIA PADA KELAS XII BAHASA 1 DI SMAN 2 MAUMERE

This study aims to improve the skills of composing the history stories of students of class XII Language 1 of SMA Negeri 2 Maumere by implementing a genius learning strategy. Through the genius learning model, improvement can be seen both in processes and products. The research subjects subjected to action were students of XII Language 1 of SMA Negeri 2 Maumere, totaling 29 students. The research model used is Classroom Action Research (CAR). The procedure for implementing the action and implementing the action at the study site is divided into two cycles. Each cycle is done three times. This research is focused on issues related to improving the skills of composing Historical Story Texts by applying genius learning strategies. The data analysis technique was carried out using qualitative and quantitative description techniques. The criteria for success achieved by students in this study is seen from a change in the direction of a better and increased learning and the results in the practice of composing Story Text.The results of the study show the following. First, the use of genius learning strategies can improve the quality of the learning process of composing historical narrative texts. An increase in the process in aspects of the learning situation, student focus and activeness, makes positive changes so that learning makes composing historical narrative texts more interesting and enjoyable. Second, learning to compose Historical Story Texts with a genius learning strategy can improve the results of the skills of composing historical story texts. This can be seen from the average score of the skills to compose the historical story text in cycle I was 64.53 whereas after being given the action of the second cycle the average score was 85.00. This shows an increase of 20.47. Overall, at the end of the second cycle, all aspects and criteria for composing historical narrative texts experienced a significant increase. Based on the results of the research above, it is known that the use of genius learning strategies is successful and can improve the skills of compiling the history story text of students of class XII Language 1 of SMA Negeri 2 Maumere.
An Ensemble Technique for Named Entity Recognition using Conditional Random Fields and L-BFGS Optimization Algorithm

This paper is regarding Named Entity Recognition (NER) for English.It is a computational phonetic under-taking wherein we generally tend to glance to rearrange each word in an exceedingly record, as tending to be categorized principally into 4 classes Person, area, Organization, and name-other (Date, time and so forth).Now, we tend to begin our assessments in building a CRF (Conditional Random Fields) that found along Noun Tagger Trained with a physically labeled information of around 48,000 sentences.This noun tagger has given an associate F-score of 85%.A CRF based NER framework is then developed for English and tried it on some informational indexes.We have got F-scores among 80% to 92% in numerous preliminaries.Named entity recognition could be a crucial task for a number of NLP applications.
PENELUSURAN BANJIR LEWAT PELIMPAH EMBUNG TB. SOSORNIAPOAN DIDESA LOBU TOLONG KECAMATAN PARANGINAN, KABUPATEN HUMBANG HASUNDUTAN PROVINSI SUMATERA UTARA

Lobu Tolong village, Paranginan Subdistrict, is one of the areas in Humbang Hasundutan Regency which is located in thehighlands. In this village area there is a small dam building and is called Embung Tambok Bolon (TB) Sosorniapoan. Byobserving the technical small dam layout, the reservoirs capacity of small dam can still be increased by increasing the heightof the small dam embankment. But socio-economically that is the inhabitants of the small dam management does not acceptthat the small dam embankment is elevated with the reason to avoid flooding and inundation in the yards, buildings andplants around the reservoir. In the downstream area of the TB. Sosorniapoan small dam there are rainfed rice fields and dryfields that are potential enough to be developed into agricultural areas with technical irrigation systems. In connection withthese conditions, studies were carried out so that flood discharge and flood height in the reservoir could be detected.From the results of the study it can be concluded, the calculation of flood discharge in the reservoir is 6.303 m3 / s and is atan elevation of + 1,400.70 m.
Prediction of Factors Influencing Rats Tuberculosis Detection Performance Using Data Mining Techniques

This thesis aimed to predict the factors that influence rats TB detection performance using data mining techniques. A rats TB detection performance dataset was given from APOPO TB training and rese ...
COMPETÊNCIA EM INFORMAÇÃO E O TRABALHADOR DO CONHECIMENTO: COMPREENDENDO AS ABORDAGENS NAS PRODUÇÕES CIENTÍFICAS NA CIÊNCIA DA INFORMAÇÃO

This article seeks to characterize the relationships between information competences and the knowledge worker through: mapping, in scientific journals A1 focused on CI (Information & Society: Studies; TransInformation; Perspectives in Information Science), available on the Sucupira Platform (Quadriênio 2013(Quadriênio -2016)), in the period from 2015 to 2019, the articles that deal, individually, with the terms "information skills" and "knowledge worker", as well as those that express relations between them.To this end, this research report was constructed through an investigative, qualitative and descriptive study based on review, bibliographic analysis and content analysis on the subject in question.The studies conclude that, in the scope of the investigated journals and the research period, publications on information skills are in evidence compared to those aimed at the knowledge worker.The analyzed publications do not refer to the relationship between the knowledge worker and the information skills necessary for the development of their work.They also conclude that publications about the knowledge worker are scarce.
Analyzing Changes in Student Graph Reasoning and Comprehension Regarding Graph Axis Presentation

of Maine and has worked in the mechanical engineering field for 22 years, with approximately 14 years of industrial experience.His industrial experience includes open hole testing in the oil and gas industry; failure analysis consulting; and extensive experience in the plastic processing industry, in which he designed plastic preforms and bottles, designed injection-and blow-molding tooling, designed and optimized polymer processing equipment, and led continuous improvement activities (e.g., Lean Six Sigma, SMED, and Gage R&R).Dr. Ellis's professional interests include stress analysis, solid mechanics, continuous improvement, design, and education.He is a licensed Professional Engineer and a Certified Six Sigma Black Belt.
Zeta Functions with Respect to General Coined Quantum Walk of Periodic Graphs

We define a zeta function of a graph by using the time evolution matrix of a general coined quantum walk on it, and give a determinant expression for the zeta function of a finite graph. Furthermore, we present a determinant expression for the zeta function of an (inifinite) periodic graph.
The need for a school festival as a form of collective creative activity.

The article refers to the influence of scientific and technological progress on the nature of communication between people, changing the style and methods of communication, and putting the use of electronic devices first. It was revealed that modern children are in computer dependence, this affects their behavior. The parameters of a mentally healthy child and teenager and cyber-dependent were noted. Emphasis is placed on the importance of the school festival as a form of collective and creative activity, on the need to hold annual school festivals. It is shown that this will allow developing cooperation and independence of schoolchildren, they will be useful in life for organiz-ing dialogue, for exchanging creative ideas. The question is raised about the need for a school festival as a form of collective and creative activity. The necessity of the festival for the use of its talented and creative youth as a platform for further self-realization and new discoveries is shown. The results of the study can form the basis for the development and conduct of a school festival as a form of collective creative activity. A description of the survey conducted among parents and teachers of MBOU secondary school № 52 p.g.t. Ilsky, as well as a survey of students of the 9th grade and its results is given. The survey was conducted through social media questionnaires.
THE RELEVANCE OF USING THE INFORMATION AND COMMUNICATION TECHNOLOGIES IN THE PROCESS OF FORMING CULTURAL COMPETENCE OF FUTURE PRIMARY SCHOOL TEACHERS

It is claimed that currently the information technologies have a significant didactic potential, which allows to incentivize students to achieve personal goals in education, including in the acquisition of cultural competences. The aims and objectives of higher pedagogical education provided for by current educational standards include the mastering the basic knowledge and skills, including cultural competency, which is particularly relevant to primary school teachers in the framework of the increasing trend towards globalization.
Order Embeddings for Supervised Hypernymy Detection

In this work we present a supervised approach to partially order word embeddings, through a learned order embedding, and we apply it in supervised hypernymy detection. We use neural network as an order embedding to map general purpose word embeddings to a partially ordered vector set. The mapping is trained using positive and negative instances of the relationship. We consider two alternatives to deal with compound terms: a character based embedding of an underscored version of the terms, and a convolutional neural network that consumes the word embedding of each term. We show that this distributional approach presents interesting results in comparison to other distributional and path-based approaches. In addition, we observe still good behavior on different sized portions of the training data. This may suggest an interesting generalization capability.
Library Services: Library Resources & Services for Remote Research: Find Articles

This Guide provides tips for remote access to library resources and services needed for your classes and doing research.
Edge Detction Using Block Processing and Lookup Table

In present generation there is rapid trade on Edge detection in the image processing in extracting images, image segmentation and army applications. To detect edges, it's very strenuous and time devouring process. So here we propose a simple, fast and efficient technique called Block processing technique and also, proposed one more technique called Lookup Table which accomplish and needs less computational time correlate to previous Edge detection technique and Block Processing technique.
SAT for Epistemic Logic Using Belief Bases

In [4] a new epistemic logic $$\textsf {LDA}$$ of explicit and implicit belief was introduced, and in [5] we presented a tableau-based satisfability checking procedure as well as a dynamic extension for it. Based on such procedure, we created a portable software implementation that works for the family of multi-agent epistemic logics, as well as for the proposed dynamic extension. This software implementation runs as a library for the most common operative systems, also runs in popular IoT and robot hardware, as well as cloud environments and in server-less configurations.
Korelasi antara Interaksi Sosial Terhadap Hasil Belajar Afektif Siswa Sekolah Dasar

Social interaction is the relationship between one individual and another individual, one individual can influence other individuals so that there is reciprocity. The better the students' social interactions, the better their learning outcomes will be. Learning outcomes examined in this study are affective learning outcomes. This study aims to reveal whether the better social interaction, the better the affective learning outcomes of fifth-grade students in SDN throughout Kaliwates Jember District. The population of this research is the fifth-grade students of SDN in Kaliwates Jember District. This study is a correlation study with a population of 182 and a sample of 25 students. The main methods of collecting data are questionnaire and observation. To test the research hypothesis using the product-moment correlation formula with the help of SPSS 20 at a significance level of 5%. The results of the research analysis obtained the value of  r_count> r_tabel  (0.748 > 0.266) and the coefficient of determination 56%. This shows that social interaction has a contribution of 56% to affective learning outcomes the remaining 44% is influenced by other factors. It can be concluded that the better social interaction, the better the affective learning outcomes of fifth-grade students of SDN in Kaliwates Jember District . Keywords :  Social interaction, affective learning outcomes, elementary school student
News automation to support journalism practice (thesis abstract)

PhD thesis abstract The phenomenon of news automation, characterized by the process of transformation of structured data into texts in natural ...
Big Data based Adaptive Learning and Scope of Automation in Actionable Knowledge

In general, big data can be treated as a tool to extract knowledge from the larger datasets with different data values. Big-data research is being carried out for a long time to extract the data from larger datasets. Generally, some of the devices, sensors generate a humongous amount of data continuously. Hence performing any computational operation or search operation in that bulk data is remaining as a challenging task. At present, the big data researchers are facing challenges such as duplication of data, and identifying the data from one data set to others and also identifying the multidisciplinary data is also a challenging task. When the data is increasing tremendously day by day as a result the server size, capacity and device storage size, RAM etc., should also be improved for deploying fast and efficient results. In this research work, the Big Data Analytics Problem (BDAP) is proposed for offering many solutions such as data deduplication, security, reliability access control etc., and finally and most important it is used for making analysis and decision making.
Outlier detection in WSN by entropy based machine learning approach

&lt;p&gt;Environmental disasters like flooding, earthquake etc. causes catastrophic effects all over the world. WSN based techniques have become popular in susceptibility modelling of such disaster due to their greater strength and efficiency in the prediction of such threats. This paper demonstrates the machine learning-based approach to predict outlier in sensor data with bagging, boosting, random subspace, SVM and KNN based frameworks for outlier prediction using a WSN data. First of all database is pre processed with 14 sensor motes with presence of outlier due to intrusion. Subsequently segmented database is created from sensor pairs. Finally, the data entropy is calculated and used as a feature to determine the presence of outlier used different approach. Results show that the KNN model has the highest prediction capability for outlier assessment.&lt;/p&gt;
LibGuides: Bibliotherapy: Using Books for Therapy: Useful Videos and Other Resources

This guide is intended to introduce adult patrons to different resources on bibliotherapy, it's uses and effects.
Model-Based Reinforcement Learning for Type 1 Diabetes Blood Glucose Control

In this paper we investigate the use of model-based reinforcement learning to assist people with Type 1 Diabetes with insulin dose decisions. The proposed architecture consists of multiple Echo State Networks to predict blood glucose levels combined with Model Predictive Controller for planning. Echo State Network is a version of recurrent neural networks which allows us to learn long term dependencies in the input of time series data in an online manner. Additionally, we address the quantification of uncertainty for a more robust control. Here, we used ensembles of Echo State Networks to capture model (epistemic) uncertainty. We evaluated the approach with the FDA-approved UVa/Padova Type 1 Diabetes simulator and compared the results against baseline algorithms such as Basal-Bolus controller and Deep Q-learning. The results suggest that the modelbased reinforcement learning algorithm can perform equally or better than the baseline algorithms for the majority of virtual Type 1 Diabetes person profiles tested. Copyright © 2020 for this paper by its authors.