Reviewerly/exHarmony huggingface dataset:
El poder de la inteligencia emocional contra el acoso escolar entre compañeros

When talking about bullying among peers, it refers to the violent treatment and behaviors that students receive in one educational institution by another, in front of this phenomenon, students receive information perceived by their brain as an emotional impact that cannot be changed, but if can modify the way of interpreting that information captured by some of the senses through the regulation of emotions in schoolchildren through the potentialization and development of Emotional Intelligence through emotional education in educational centers. Within this framework, to educate students emotionally, the intervention of the teacher is necessary to be able to apply executive functioning exercises of the frontal cortex, in order for students to acquire the ability to manage their emotions by inhibiting tonsil sequestration. reduce or mitigate bullying at the Nurqui Educational Institution, headquarters of La Milagrosa in Santafe de Antioquia.
Library: Access Services: Books

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Research on Technology of Digital Resource Management and Publishing Platform for Ancient Books Based on Artificial Intelligence

Under the popularization of artificial intelligence and the support of big data storage technology, Chaoxing Company and Hualu Group cooperate with university digital libraries to digitally collect, clean, classify and utilize ancient books. What they do, not only regenerative protect ancient books, but also inherit traditional culture. Through sorting out the technology used by digital resources platform, this article discussed the organization styles of ancient books digitization. Then, an automatic integration system for ancient book sorting was proposed, contributing to the combination involving production, teaching and research, as well as the international cooperation of ancient books digitization in the future.
Intresseavvägningen mellan bevakningsintresse och personlig integritet vid kameraövervakning

In 2018, the permit requirement regarding camera surveillance for many actors was abolished. The abolition was prompted by the newly established Kamerabevakningslag (2018: 1200). The abolition of the permit requirement meant that actors themselves must carry out an assessment regarding whether their camera surveillance is permitted or not. Camera surveillance is largely regulated by the GDPR. The assessment of whether surveillance is permitted is therefore based almost exclusively on the balance of interest between the interests of surveillance and the interests of personal integrity. The essay is based on the thesis that integrity interests are threatened, and risk being underestimated when the party conducting the surveillance are judging the value of the interests. A analysis of existing legislation, preparatory work, government statements and supervisory decisions identifies an area of great uncertainty. These uncertainties are both intentional and unintentional. On the one hand, there is an explicit intention from the legislator that the interpretation of the law should follow the development of society, and on the other hand all studied bodies agree that an assessment of interests only can take place in each unique case. However, there are factors that indicate that the uncertainties also could lead to a reduced willingness to use camera surveillance. The essays conclusion is that at present it is not possible to determine how a balance between surveillance interests and integrity interests should take place. There are guidelines for the main features of such a balance, but the large uncertainty factors mean that even relatively strong interests can be overridden by assessments based on perceptions with limited traceability. In order to create a more accurate picture of the risks to personal integrity, studies of the actual conditions prevailing in society, how actors practically carry out their assessments, how different interests are assessed, the willingness to report incorrect supervision and similar aspects are required. (Less)
Software Defect Prediction Using Atomic Rule Mining and Random Forest

This research aims to improve software defect prediction in terms of accuracy and processing time. The new proposed algorithm is based on the Random Forest Algorithm that classifies and distributes the data based on tree module. It has value either 1 for defective module or 0 for the non-defective module. Random Forest Algorithm selects a feature from a subset of features which has been already classified. Random Forest Algorithm uses a number of trees for the prediction. For this research, datasets were tested with 10 and 15 sets of trees. Results showed an improvement in accuracy and processing time when the proposed system was used compared to the current solution for the software defect model generation and prediction. The proposed solution achieved an accuracy of 90.09% whereas processing time dropped by 54.14%. Processing time decreased from 19.78s to 9.07s during the prediction for over 100 records. Accuracy was improved from 89.97% to 90.09%. The proposed solution uses Atomic Rule Mining with Random Forest Algorithm for software defect prediction. It consists of classification and prediction process by using the Random Forest Algorithm during storing data that is carried out using Atomic Rule Mining.
How to Set the MX Player As Default Player For Audio & Video

The question how to set MX player as default? is raised by many users when they feel that the default settings of their favorite media player are not ...
Context Aware Dialog Management with Unsupervised Ranking

We propose MoveRank, a novel hybrid approach to dialog management that uses a knowledge graph domain structure designed by a domain-expert. The domain encoder converts a symbolic output of the NLU into a vector representation. MoveRank uses an unsupervised similarity measure to obtain the optimal dialog state modifications in a given context. Using a 1K utterance dataset automatically constructed with template expansion from a small set of annotated human-human dialogs, we show that the proposed unsupervised ranking approach produces the correct result on the gold labeled input without spelling variations. Using an encoding method designed to handle spelling variations, MoveRank is correct with $$\mathrm{F}-1=0.86$$ , with the complete set of labels (including intent, entity, and item) and $$\mathrm{F}-1=0.82$$ , with only the intent labels.
A Human-centric Approach to Near-eye Display Engineering

Virtual and augmented reality technologies are now rapidly gaining traction in our society. Yet even as they improve, these devices continue to face major challenges relating to the wide variability of human vision. In their research, Dr Gordon Wetzstein and his colleagues at Stanford University explore innovative new ways to overcome these challenges, through the latest advances in both optics and vision science. In demonstrating ground-breaking innovations to near-eye displays and sensors, the team’s work could soon bring enormous benefits to users spanning a diverse spectrum of visual ability.
The application of interval type 2 fuzzy analytic hierarchy process to solve personnel selection problems / Raja Nur Hafizah Raja Hang Tuah, Nurfaezah Mohd Husin and Mardiana Zaini

Personnel selection is a phase of human resource management which is selecting the best personnel from a pool of candidates suitable for a vacant position in an organization. This paper aims to present a comprehensive multi-criteria decision making (MCDM) method extended by Interval Type-2 Fuzzy Sets (IT2 FSs) which is Interval Type-2 Fuzzy Analytic Hierarchy Process (IT2 F AHP). Then, the weight priority obtained by IT2 F AHP will be compared with the Analytic Hierarchy Process (AHP) method and it illustrated that the weight priority of AHP is higher than IT2 FAHP. This paper also formalizes several important issues on sensitivity analysis and derived some critical theoretical results. Finally, it can be concluded that the final evaluation made by the decision makers has a significant consistency shown by sensitivity analysis results. Fuzzy sets of type-2 can be used to cater the problem of the inability of Interval Type-I Fuzzy Sets (IT I FSs) to deal with membership grade even with an exact number in [0,1]. Six criteria (work experience (C1), education (C2 ), analytical thinking (C3 ), communication and problem solving skills (C4 ), time management (C5) and core ability (C6 )) were identified by the organization on selecting the right personnel among five candidates (Ai, A2, A3, A4 and A5 ). The results show that C6 and A1 is the most preferred criterion and alternative respectively. Thus, the implementation of the proposed methodology is further demonstrated by several illustrative examples.
Pattern recognition of breast tumor based on image dynamic enhancement technique

At present, the diagnosis of breast tumors is affected by many factors, which leads to certain errors in the diagnosis results. Therefore, it is necessary to improve the diagnosis in combination with the actual situation. This study used the whole tumor ADC histogram to identify the heterogeneous features of benign and malignant breast lesions and used the diffusion characteristics of the whole tumor to construct a diagnostic model suitable for breast tumor image feature recognition. Simultaneously, this study combined the actual situation to construct a system framework of image enhancement algorithm based on Retinex theory, and combined image processing algorithms to improve the model. In addition, this study converted the pixel data type of the grayscale image of each color channel into a double type and converted each color channel image into a logarithmic domain. Finally, in order to study the performance of the algorithm, this study designed a comparative test for performance analysis. The research shows that the algorithm has certain clinical effects and can provide theoretical reference for subsequent related research.
Call for Articles for Issue #3 of New Explorations (NExJ), and for the Supplementary Blog at newexplorations.net

Call for Articles for Issue #3 of New Explorations (NExJ), and for the Supplementary Blog at newexplorations.net
SIGNIFICANTI ‘‘INTRADUCIBILI’’ NELLA TRADUZIONE DEL ROMANZO STORICO IL PONTE SULLA DRINA DI IVO ANDRIĆ

This article compares two texts, the original one in Serbian by Ivo Andric (one of the major voices of Serbian literature) and the version of the Italian translation by Bruno Meriggi, a translator who will be remembered for having left a valuable contribution to philological research in the context of overall historiography. The article analyzes the untranslated elements and signs, which appear most significant for the work of an interpreter, through a comparison of signs, meanings, similarities and dissimilarities, interpretation and intentionality in the translation of the historical novel The Brigde on the Drina by Ivo Andric. The analysis which will in any case be connected with the guiding ideas of the concept of untranslatability, (such as obstacles in translation, and partial and absolute losses in translation), will be also developed through a semiotic gaze in order to understand the true importance of words ininterpretation and the study of non-verbal messages.
대학수학능력시험 영어영역 절대평가 도입 이후의 공대 신입생들의 영어실력 추이와 영어교육 상황 분석

This study explores the English scores of freshmen engineering colleges in two universities and the professors'' and instructors'' perceptions on transition of English ability of the students and the situation of English education after the change of English section of College Scholastic Ability Test (CSAT) from a norm-referenced to a criterion-referenced system. For this study, 10 participants took part in in-depth interviews through a focus group, and the data were analyzed through descriptive coding, which reiterated themes or issues that showed consistent or unique patterns. The key findings of this study are as follows. First, engineering students'' English skills have declined after the introduction of absolute evaluation on the English section of the CSAT. Second, engineering students have a tendency to regard English as an insignificant subject. Finally, in regards to the entrance examination policy, rather than going back to using relative evaluation on the English section of the CSAT, it is necessary to absolutely evaluate all subjects and make the CSAT a minimum requirement.
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Correction to ‘Something has to give: scaling combinatorial computing by biological agents exploring physical networks encoding NP-complete problems’

[This corrects the article DOI: 10.1098/rsfs.2018.0034.].
Analisa Faktor Penyebab Stunting Menggunakan Algoritma C4.5

Stunting or dwarf is a condition where a toddler has a length or height that is less when compared to age. There are five main factors causing stunting, namely poverty, social and culture, inceased exposure to infectious diseases, food insecurity and public access to health services. C4.5 algorithm is a data classification algorithm with a decision tree method that has advantages such as being able to process numeric (continuous) and discrete data, rules that are formed based on exiting decision tree, the main factors causing stunting in the Dulupi sub – district, Boalemo Regency, are Health Facilities and exclusive breastfeeding for babies 0 – 6 months.
One Class Text Classification using an Ensemble of Classifiers

Traditional classification algorithms work in a closed-world scenario where the training data contains all existing classes. In contrast, open set classifiers can handle new input that does not belong to any of the classes seen during training. Open set classification has been studied intensively in the computer vision domain, primarily in handwriting recognition, face recognition, object classification and computer forensics. Here we are interested in open set classification in natural language processing in one class document classification. We propose a new system based on autoencoder for one class classification of documents leveraging the full text. Extending further, we propose a novel ensemble based classifier model, a combination of several basic classifiers, to detect if an incoming document belongs to the class known from training or an unknown class. We compare and evaluate our methods on existing one class classification datasets for NLP - 20 Newsgroups, reuters and webkb. We also extract and use a new full-text dataset from arxiv.org. Our methods significantly outperforms the current state-of-the-art approaches for one class document classification.
DEVELOPMENT OF "CAPTAIN LUNGS 3D" AS A LEARNING MEDIA IN RESPIRATORY SYSTEM TOPIC TO ENHANCE STUDENTS CRITICAL THINKING SKILLS

The Development Science and Technology in the 21st century requires four skills, one of them is the ability to think critically. Based on Facione, critical thinking skills are divided into six indicators, such as evaluation, interpretation, analysis, inference, explanation, and self-regulation. This research aims to develop and implement the “Captain Lungs 3D” application as a learning media on respiratory system topics to enhance students' critical thinking skills. This research used Research and Development method, and there is pre-test and post-test also. Sampling used in this research was convenience sampling, which participated in 60 students of 9th-grade students public school in Bandung. Game-based learning is also used in delivering material during teaching learning process. The objective test used as a research instrument for pre-test and post-test design. Test items that are used is based on the Facione indicator of Critical Thinking Skills. Based on the analysis result, the Normalized gain is 0.48. From the result that used the Wilcoxon Signed Rank Test, the hypothesis in this research is accepted. The value of Asymp (2-tailed) is 0.000, with the level of significant value is 0.05. At the end of class, students are asked to giving feedback based on the questionnaire that is already given about game-based learning implemented on “Captain Lungs 3D”. The research shows that there is a significant difference in “Development of “Captain Lungs 3D” as a Learning Media in Respiratory System Topic To Enhance Students Critical Thinking Skills.
독일의 평화 지향 역사교육- 노르트라인베스트팔렌 중등 II 역사 핵심교수계획(2014)의 사례 -

This study examines Germany''s peace-oriented history education, focusing on the state of North Rhine-Westphalia (NRW). In Germany, peace education in history courses was inspired by the social movement for peace in the 1970s and has been integrated into the school curriculum since the 1990s. This study analyzes the Core Curriculum for Secondary School II History, a revised curriculum for history in upper secondary school, presented by NRW in 2014. Among the seven essential fields of contents in this curriculum, which were reconstructed as historically comprehensive, the last field, “Peace treaties and peace regimes in the modern era,” categorized the capacity for peace-building as an inevitable element of history education. The content runs through modern Europe’s peace history-from the Peace of Westphalia, Vienna Settlement, Treaty of Versailles, Cold War, and German unification to European integration.This study analyzes the following: first, the characteristics of the Core Curriculum with regards to structure, goal, and detail; second, the innovations and problems, especially with the last theme “Peace treaties and peace regimes in the modern era,” and finally, its application in school lessons, focused on the teaching model presented by the state. In conclusion, the Core Curriculum systematically introduced “peace” as an essential element of history education. However, this resulted in some challenges, for example, keeping abreast with the latest trends in peace studies and addressing them through the methodology of history education. In this regard, dialogues among historical studies, education of history, and history teachers are ongoing. Thus, cooperation and collaboration between peace practice and history education is an ongoing challenge.
Sesame Workshop’s international response to COVID-19 

Click to increase image sizeClick to decrease image size Additional informationNotes on contributorsTara WrightTara Wright is Professional Development Manager for Sesame Workshop's U.S. Social Impact group, and develops multimedia outreach materials for children and caregivers, as well as learning experiences for the important providers in their lives. She holds a bachelor’s degree in journalism with an emphasis in advertising from the University of Oklahoma.Kama EinhornKama Einhorn is Senior Content Manager for Sesame Workshop's U.S. Social Impact group, and develops multimedia outreach materials for children, parents, and providers. Prior to joining the Workshop, she wrote and edited early childhood teaching resources for Scholastic. She holds a master's degree in education from University of California at Berkeley.Daniel LabinDanny Labin is the Vice President of International Projects at Sesame Workshop. Danny is responsible for developing and distributing content that drives social impact with a vast network of global partners. Danny has worked across the field of educational media in various roles spanning content creation, evaluation and research, project management, and international business development. In his current role, Danny oversees multiple local Sesame initiatives around the world.Sal PerezSal Perez is an Emmy-nominated Producer with over 14 years’ experience in international and domestic production. Sal oversees both studio and location production, live shows and themed entertainment for International Sesame Street Co-Productions as well as production for U.S. Social Impact Projects. With a BFA from NYU’s Tisch School of the Arts, other credits include the adaptations of Gossip Girl and the Got Talent franchises in Mexico.Jessica DiSalvoJessica DiSalvo is the Senior Content Manager at Sesame Workshop. Ms. DiSalvo assists with reviewing and implementing Sesame Street’s whole-child curriculum making sure content across all media platforms is curriculum-driven, educational, and developmentally appropriate.Rosemarie TruglioDr. Rosemarie Truglio is responsible for the development of the interdisciplinary school readiness curriculum on which Sesame Street is based and leads content development across platforms (e.g., digital, publishing, toys, and themed entertainment). She also oversees the curriculum development for all new show production, including Esme & Roy, Ghostwriter, and Helpsters. Dr. Truglio has written numerous articles and her current book is Ready for School! A Parent’s Guide to Playful Learning for Children Ages 2 to 5.
FAST INTERACTIVE REGIONAL PATTERN MERGING FOR GENERIC TISSUE SEGMENTATION IN HISTOPATHOLOGY IMAGES

The image segmentation of histopathological tissue images has always been a challenge due to the overlapping of tissue color distributions, the complexity of extracellular texture and the large image size. In this paper, we introduce a new region-merging algorithm, namely, the Regional Pattern Merging (RPM) for interactive color image segmentation and annotation, by efficiently retrieving and applying the user’s prior knowledge of stroke-based interaction. Low-level color/texture features of each region are used to compose a regional pattern adapted to differentiating a foreground object from the background scene. This iterative region-merging is based on a modified Region Adjacency Graph (RAG) model built from initial segmented results of the mean shift to speed up the merging process. The foreground region of interest (ROI) is segmented by the reduction of the background region and discrimination of uncertain regions. We then compare our method against state-of-the-art interactive image segmentation algorithms in both natural images and histological images. Taking into account the homogeneity of both color and texture, the resulting semi-supervised classification and interactive segmentation capture histological structures more completely than other intensity or color-based methods. Experimental results show that the merging of the RAG model runs in a linear time according to the number of graph edges, which is essentially faster than both traditional graph-based and region-based methods.
Initial Coin Offerings, Information Disclosure, and Fraud

We study the extent of fraud in initial coin offerings (ICOs), and whether information disclosure prior to the issuance predicts fraud. We document different types of fraud, and that fraudulent ICOs are on average much larger than the sample average. Issuers that disclose their code on GitHub are more likely to be targeted by phishing and hacker activities, which suggests that there are risks related to disclosing the code. Generally, we find it extremely difficult to predict fraud with the information available at the time of issuance. This calls for the need to install a third-party that certifies the quality of the issuers, such as specialized platforms, or the engagement of institutional investors and venture capital funds that can perform a due diligence and thus verify the quality of the project.