Reviewerly/exHarmony huggingface dataset:
Design of a Knowledge Representation and Indexing: Background and Future

People are good at getting, thinking and deciphering information. A human knows many things, which is information, and as far as anyone cares, they perform different activities. In any case, how machines do all of those things go under information portrayal and thinking. Thus, we will depict knowledge portrayal and thinking as that piece of artificial insight which worries the AI specialists and the way thinking adds to keen conduct of specialists. It is responsible for communicating with data about this present reality, so that a computer can comprehend and may use this information to solve mindboggling real-life issues, for instance, analyzing an ailment or communicating with people in characteristic language. It’s portrays how we will speak to information in human-made reasoning. Information portrayal is not simply putting away information into some information base, yet it additionally empowers a smart machine to realize from that. The recommendation-extended semantic network is an inventive framework for information representation and ontology construction, which not just induces implications but also searches for sets of relationship between hubs as restricted to the current technique for catchphrase affiliation, and the objective here is to accomplish semi-supervised information representation method with great exactness and minimum human mediation. This is acknowledged by lifting a specialized coactivity among numerical and mind models to reap their aggregate knowledge.
INCREASING THE STUDENTS’VOCABULARY MASTERY THROUGH CONSTRUCTIVISM PRINCIPLE IN THE FIFTH GRADE OF SDN ZAHA PROBOLINGGO

This study focused on finding out whether “Constructivism Principle” approach can be used to improve students’ vocabulary mastery in the fifth grade of SDN ZAHA Probolinggo.This research involved twenty fifve students,thereare ten boys ang fifteen girls.The research instruments of this study consisted of obsevation guide in learning process, test, and given questionnaire. This study was a classroom action research. From the first cycle reflection result, some procedures and activities were revised accordingly.Steps include: (1)The students did the activities in groups made by the teacher which was not previously done in cycle 1; (2) different from cycle 1 which used “constructivism principle”.In cycle 2 used Constructivism principle and some pictures related of tehnique used.The result from the action in cycle 2 was that the average score of students achieve 80,96.It can be concluded that used “Constructivism principle” tehnique can improve the vocabulary mastery in the fifth grade of SDN ZAHA Probolinggo.
Exhibit 8: ADEA Competency Documents

Journal of Dental EducationVolume 84, Issue S1 p. S68-S89 EXHIBITS Exhibit 8: ADEA Competency Documents First published: 26 July 2020 https://doi.org/10.1002/jdd.12279Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Volume84, IssueS1Supplement: ADEA ANNUAL PROCEEDINGSJuly 2020Pages S68-S89 RelatedInformation
Peer review declaration

All conference organisers/editors are required to declare details about their peer review. Therefore, please provide the following information: • Type of peer review: Single-blind / Double-blind / Triple-blind / Open / Other (please describe) All reviews follow a double-blind process. 1-AOPR Editors perform an initial check of the manuscript’s suitability upon receipt, and use a software tool to finish the plagiarism analysis, manuscripts are out of conference topics will be rejected directly, generally, authors will receive the result within 3-5 working days in this round. 2-Only the manuscripts passed the initial checking can be submitted to reviewers, AOPR Editorial Office will then organize the peer-review process performed by independent experts. Papers will be strictly and thoroughly peer-reviewed by experts and reviewers. 3-All regular papers are reviewed by at least two reviewers, but usually by three or more, and rated considering: Relevance, Originality, Technical Quality, Significance and Presentation of the submissions; There are four results: 1, Accept; 2, Accept after Minor Revisions; 3, Reconsider after Major Revisions; 4, Reject. 4-Authors have 2-3 weeks to make minor or major revisions after received the comments from reviewers. Usually, one round of major revisions is allowed. 5-Only the submission passed the peer review and accepted by reviewers will be included in the conference proceeding finally. • Conference submission management system: Online Email System • Number of submissions received: 75 • Number of submissions sent for review: 55 (20 papers out of the conference scope are rejected directly) • Number of submissions accepted: 28 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 37% • Average number of reviews per paper: 2-3 • Total number of reviewers involved: 64 reviewers • Any additional info on review process: • Contact person for queries: Josh Sheng aoprconf@163.com Please submit this form along with the rest of your files on the submission date written in your publishing agreement. The information you provide will be published as part of your proceedings.
Extracting and Clustering of Story Events from a Story Corpus

This article describes how events that make up text stories can be represented and extracted.We also address the results from our simple experiment on extracting and clustering events in terms of emotions, under the assumption that different emotional events can be associated with the classified clusters.Each emotion cluster is based on Plutchik's eight basic emotion model, and the attributes of the NLTK-VADER are used for the classification criterion.While comparisons of the results with human raters show less accuracy for certain emotion types, emotion types such as joy and sadness show relatively high accuracy.The evaluation results with NRC Word Emotion Association Lexicon (aka EmoLex) show high accuracy values (more than 90% accuracy in anger, disgust, fear, and surprise), though precision and recall values are relatively low.
PSYCHOLOGICAL-PEDAGOGICAL ASPECTS OF STUDENTS' ADAPTATION IN RUSSIAN UNIVERSITIES

The article discusses effective ways to improve the quality of psychological preparation of students for pedagogical activity, where an important criterion is the special training of future teachers in psychologically meaningful pedagogical design.The method of teaching is to create conditions for the formation of a certain psychodidactic model of the lesson in the student's consciousness.An educational and professional constructive task intended for pedagogical practice can act as a means of creating these conditions.
Auto-configuration of Programmable Photonic Circuits

Programmable photonic integrated circuits enable their reconfiguration through control electronics. In this paper we describe the key missing part of the ecosystem, the control algorithms that govern the circuit operation, focusing on arbitrary optical filters.
Analysis of Behavioral Image Recognition of Pan-Entertainment of Contemporary College Students’ Network

With the continuous update and iteration of network technology and technological innovation, the handheld smart media of college students will become more and more sensitive. With the advancement of economic globalization, various ideologies and cultures in the world will rapidly invade, and the “pan-entertainment” of online media may intensify. Only through the government’s supervision function and the self-discipline of the internet industry, we can strictly control and screen positive values. In order to better establish the correct employment value orientation of university students and further analyze the importance of the “pan-entertainment” behavior image recognition of college students, this study analyzes the related technology and basic theory of behavior recognition. After introducing several mainstream methods, the traditional dual-stream convolutional network method is improved, and the time information and spatial information extracted by the two channels are discussed for the weighted fusion of feature maps. Finally, using R(2 + 1)D structure and dual-stream network structure design, a deep learning-based spatiotemporal convolution behavior recognition algorithm is proposed. The proposed algorithm is tested and analyzed on the datasets UCF101 and HMDB51. The specific work content is as follows: (1) to summarize the widely used video behavior classification methods proposed so far and discuss the future development. Then, it mainly analyzes the existing technical bottlenecks of some methods based on deep learning methods and summarizes and explores an efficient, stable, and accurate spatiotemporal feature joint extraction and learning method theory. (2) The design of spatiotemporal convolutional network algorithm framework is proposed, the method of segmentation processing of long video is studied, the improvement of the dual-stream network decision-level fusion method is studied, and the R(2 + 1)D network is reorganized. The network algorithm is trained and tested on the UCF-101 dataset and HMDB-51 dataset under the condition of calling the pretrained model. Finally, the accuracy is compared with the existing classic algorithms to obtain better accuracy, which proves the effectiveness of the algorithm for the “pan-entertainment” behavioral image recognition of contemporary college students.
Method of manufacturing hydrocarbons

Image segmentation is a key issue in image processing. New image segmentation algorithms have been proposed in the last years. However, there is no optimal algorithm for every image processing task. The selection of the most suitable algorithm usually occurs by testing every possible algorithm or using knowledge from previous problems. These processes can have a high computational cost. Meta-learning has been successfully used in the machine learning research community for the recommendation of the most suitable machine learning algorithm for a new dataset. We believe that meta-learning can also be useful to select the most suitable image segmentation algorithm. This hypothesis is investigated in this paper. For such, we perform experiments with eight segmentation algorithms from two approaches using a segmentation benchmark of 300 images and 2100 augmented images. The experimental results showed that meta-learning can recommend the most suitable segmentation algorithm with more than 80% of accuracy for one group of algorithms and with 69% for the other group, overcoming the baselines used regarding recommendation and segmentation performance.
INTELLECTUAL POTENTIAL OF STUDENTS OF THE UNIVERSITY: MAIN WAYS OF IMPROVEMENT

At this stage of social development, new requirements are imposed on the intellectual development of university students. An individually developed form of teaching and the development of the dialogical component of the educational process has a strong influence on the improvement of intellectual students. Modern society needs a graduate who thinks independently. An individually creative approach makes it possible to launch the mechanism of general self-development. In this work, the task is to consider ways of implementing intellectual students in universities. Various forms of cooperation between a teacher and students are presented, where self-control and a set of rules of behavior are actively improved. The article also includes the features of teaching dialogical speech, the need for the teacher's creativity, the ability to abstract thinking. The special role of personality culture in the process of becoming a modern specialist is presented. The author proposes to focus on tasks of a creative nature, emphasizing the primary role in the development of intellectual students. In the theory of the educational process, one can single out such pedagogical phenomena as self-expression of students, the ability to think independently, conduct dialogical speech, and operate with hypotheses. The possibility of constructing a monitoring system for the intellectual development of students of higher educational institutions is approved. This will make it possible to simultaneously clarify other components of intellectual development.
Science Education in Egypt—Intelligent Technology in Education Development

Enduring personal achievement throughout one’s life while serving the community’s needs into the future require sustainable changes for the education system based on the Artificial Intelligence and emerging technology. This entails forcing science education as a whole-of-society approach and building an enabling intelligent environment that allow all societal actors to critically act towards cohesive educational and research goals. Once this is done, and research is centralized at the decision-making process, citizens shouldn’t miss any opportunities to explore knowledge of and about science, its culture and values, and put forward future plans that sets scientific thinking as a solid foundation for future success. This chapter describes the current status of education in Egypt and provide the future trends in this field.
Recommendation Generation Justified for Information Access Assistance Service (IAAS) : Study of Architectural Approaches

Recommendation systems only provide more specific recommendations to users. They do not consider giving a justification for the recommendation. However, the justification for the recommendation allows the user to make the decision whether or not to accept the recommendation. It also improves user satisfaction and the relevance of the recommended item. However, the IAAS recommendation system that uses advisories to make recommendations does not provide a justification for the recommendations. That is why in this article, our task consists for helping IAAS users to justify their recommendations. For this, we conducted a related work on architectures and approaches for justifying recommendations in order to identify an architecture and approach suitable for the context of IAAS. From the analysis in this article, we note that neither of these approaches uses the notices (IAAS mechanism) to justify their recommendations. Therefore, existing architectures cannot be used in the context of IAAS. That is why,we have developed a new IAAS architecture that deals separately with item filtration and justification extraction that accompanied the item during recommendation generation (Figure 7). And we haveimproved the reviews by adding users’ reviews on the items. The user’s notices include the Documentary Unit (DU), the user Group (G), the Justification (J) and the weight (a); noted A=(DU,G,J,a).
Planning in the midst of chaos: how a stochastic Blood Bowl model can help to identify key planning features

For several decades now, games have become an important research ground for artificial intelligence. In addition to often present useful and complex problems, they also provide a clear framework thanks to their rules, sometimes numerous. In this article, we explore a very difficult two-players board game named Blood Bowl. This game allows the players to perform many different actions, which depend for a large part on the result of one or more dice rolls. Thus, it can be seen as a multi-action probabilistic problem driven by a Markov decision process. In this article, we present the first stochastic model of the main phase of Blood Bowl to our knowledge and the premise of a dedicated planning framework. Such a framework could offer interesting grounds and insights for modeling high turn-wise branch factor games.
An optimised clustering algorithm with dual tree DS for lossless image compression

The emerging utilisation of web and other electronic applications have expedited much consideration on image compression systems to spare storage room and diminish transmission time by compressing the size of an image by discarding the repetitive data sequences. Most of the techniques are based on lossy compression techniques where the compression ratio would be low. The proposed system based on lossless compression technique achieves best compression ratio, good image quality and less PSNR value by extracting the best features of an image, which is to be compressed and encoded by incorporating firefly algorithm with k means algorithm there by avoids local optima problem. To make the eminent compression of best derived features, quad tree decomposition and Huffman encoding technique are combined, which provide high compression ratio by fetching correct probabilities of occurrence of pixel intensity. This proposed technique is actualised in MATLAB and in this manner the trial results demonstrated the effectiveness of the proposed image compression technique regarding high compression ratio, low noise ratio, and reduced compression and decompression time when compared with existing techniques.
Peer review declaration

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Single-blind / Double-blind / Triple-blind / Open / Other (please describe) • Conference submission management system: • Number of submissions received: 35 • Number of submissions sent for review: 35 • Number of submissions accepted: 34 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 97 • Average number of reviews per paper: 2 • Total number of reviewers involved: 33 • Any additional info on review process: • Contact person for queries: Alexandr Kvon tpeac2021@gmail.com
Post-quantum software for distillation of non-orthogonal quantum states through binary frames

Quantum cryptography is a paradigm for the establishment of secret keys and data confidentiality, which represents an alternative in the quantum era because its security properties are based on the principles of quantum physics. Unfortunately, errors that occur during transmission and detection of quantum states have made it difficult to implement this technology globally. However, a new cryptographic key quantum distribution scheme based on non-orthogonal state pairs has recently been published which considerably outperforms known schemes. This article describes the fundamentals of this protocol which are represented as an algorithm and the pseudo-code of the most relevant functions of the system is shown; The current development of the software for the distillation of non-orthogonal quantum states by means of binary frames is presented, which demonstrates the transmission control, reconciliation and privacy amplification of the shared secret bits. Likewise, we present the results obtained from the computer system and its interpretation in relation to the efficiency of the protocol, which exceeds 50% channel error rates and a quadratic growth of the length of the secret key as a function of the number of double detection events. Objectives: Demonstrate the effectiveness of the non-orthogonal state distillation protocol through binary frames using the software developed. Methodology: For the development of this project, the following methodology has been carried out (see Figure 1). Contribution: The results of this software guide tests for quantum distillation in an experimental communications environment in order to provide a useful solution in the era of quantum information transmission and communication technologies.
Swapping-based Data Sanitization Method for Hiding Sensitive Frequent Itemset in Transaction Database

Sharing a transaction database with other parties for exploring valuable information becomes more recognized by business institutions, i.e., retails and supermarkets.It offers various benefits for the institutions, such as finding customer shopping behavior and frequently bought items, known as frequent itemsets.Due to the importance of such information, some institutions may consider certain frequent itemsets as sensitive information that should be kept private.Therefore, prior to handling a database, the institutions should consider privacy preserving data mining (PPDM) techniques for preventing sensitive information breaches.Presently, several PPDM methods, such as item suppression-based methods and item insertionbased methods have been developed.Unfortunately, the methods result in significant changes to the database and induce some side effects such as hiding failure, significant data dissimilarity, misses cost, and artificial frequent itemset occurrence.In this paper, we propose a swapping-based data sanitization method that can hide the sensitive frequent itemset while at the same time it can minimize the side effects of the data sanitization process.Experimental results indicate that the proposed method outperforms existing methods in terms of minimizing the side effects.
Social Media Moderations, User Ban, and Content Generation: Evidence from Zhihu

Social media platforms have evolved as major outlets for many entities to distribute and consume information.The content on social media sites, however, are often considered inaccurate, misleading, or even harmful.To deal with such challenges, the platforms have developed rules and guidelines to moderate and regulate the content on their sites.In this study, we explore user banning as a moderation strategy that restricts, suspends, or bans a user who the platform deems as violating community rules from further participation on the platform for a predetermined period of time.We examine the impact of such moderation strategy using data from a major Q&A platform.Our analyses indicate that user banning increases a user's contribution after the platform lifts the ban.The magnitude of the impact, however, depends on the user's engagement level with the platform.We find that the increase in contributions is smaller for a more engaged user.Additionally, we find that the quality of the user-generated content (UGC) decreases after the user ban is lifted.Our research is among the first to empirically evaluate the effectiveness of platform moderations.The findings have important implications for platform owners in managing the content on their sites.