Reviewerly/exHarmony huggingface dataset:
Platform to improve the reachability of web based advertisement

Advertisements are the messages that are intended to inform or influence the people who receive them. It is a paid announcement in a newspaper or on a television or on a poster about a product, event, or a job. In olden day advertisement was carried out by printing messages in the bronze plate, and by painting in-wall or rock and by campaigning. After that, it was carried out in the billboards, flyers or pamphlets, television, newspaper, radio, etc. In recent years traditional advertisement is getting changed into a web-based advertisement. It is the type of advertisement that uses the internet to deliver promotional marketing messages to consumers. It is very important to get the attraction of the customer. This project focuses on improving the reachability of that advertisement in a cost-efficient manner. This platform allows the user to post their advertisement on a different website. In turn, it will generate the report through which the user can identify the best place to get a better response from the social media, e-commerce, etc.
STUDENTS OF THE PHYSICAL CULTURE SPORTS PROGRAM OF THE UAC, ANTE Tics

The objective of the research was to determine the relationship between academic activities in the institutional platform (Moodle), and the perception of the teaching-learning process, by students of the Sports and Physical Culture program of the Autonomous University of Caribbean in the year 2018; The focus of this research was Quantitative, with a descriptive study and a descriptive transactional design, the population employed were 40 students of the sixth and seventh semester of the Sports and Physical Culture program of the Autonomous University of the Caribbean in 2018, allowing to know the relationship that exists between the virtual platform and the perception that the students of the Sports and Physical Culture program possess of the teaching - learning process, carrying out the virtual activities established by their teachers. Among the results, it was found that the majority of the students of the Sports and Physical Culture program, agreed that the virtual academic activities established in the Moodle platform called by the Autonomous University of the Caribbean as EXIA, allowed students to generate an active role in its formation process; On the other hand, the students perceived that the activities promoted the elaboration of research projects.
Extended Insertion Functions for Opacity Enforcement

Opacity is a confidentiality property that holds when certain secret strings of a given system cannot be revealed to an outside observer under any system activity. Opacity violations stimulate the study of opacity enforcement strategies. Among other methodologies, opacity has been enforced using insertion mechanisms, i.e., output obfuscation mechanisms that are allowed to insert fictitious output symbols before actual system outputs, in order to preserve opacity. This paper studies and analyzes more powerful extended insertion mechanisms, which can insert symbols before and after an actual system output, thus, providing opacity to a wider class of systems. In order to address practical considerations, the paper also introduces event insertion constraints (i.e., the case when only specific symbols can be inserted before and/or after an actual system output). For each case, we construct an appropriate verifier that can be used to obtain necessary and sufficient conditions for checking opacity enforceability.
Thematic Organization of Conversations in the Voip Application Viber

In a large number of social media and mobile applications, a new hybrid oral-writing formation is emerging, which is called from linguists' written spoken speech with similar features to both written and oral speech, but also has its own distinctive features. This study will illustrate the thematic structure of a conversation using the VoIP application Viber to highlight the most common model of a zig-zag themed organization and its specifics.
Is the idea of 'care robots' an oxymoron?

The idea that technology and the digital revolution will transform our lives and be wholly positive is a familiar trope. Undoubtedly the pace of change is rapid - especially since the arrival of high-speed internet connectivity - and the emergence of interactive and voice-activated devices has progressed from the possible to the common place in very short order. The implications not only for our leisure time and entertainment, but also for practical applications in our lives are seemingly boundless. From apps to control our heating, lighting and home security systems; electric vehicles, to ‘swipe to pay’ or ‘tap to activate’ travel permits, the possibilities are rapidly evolving.
QuASE: Question-Answer Driven Sentence Encoding

Question-answering (QA) data often encodes essential information in many facets. This paper studies a natural question: Can we get supervision from QA data for other tasks (typically, non-QA ones)? For example, {\em can we use QAMR (Michael et al., 2017) to improve named entity recognition?} We suggest that simply further pre-training BERT is often not the best option, and propose the {\em question-answer driven sentence encoding (QuASE)} framework. QuASE learns representations from QA data, using BERT or other state-of-the-art contextual language models. In particular, we observe the need to distinguish between two types of sentence encodings, depending on whether the target task is a single- or multi-sentence input; in both cases, the resulting encoding is shown to be an easy-to-use plugin for many downstream tasks. This work may point out an alternative way to supervise NLP tasks.
A Causal Model of Psychological Well-being based on Social Capital through the Mediating role of Emotional Intelligence in Education Staff

A Causal Model of Psychological Well-being based on Social Capital through the Mediating role of Emotional Intelligence in Education Staff
Technical Report of "Deductive Joint Support for Rational Unrestricted Rebuttal"

In ASPIC-style structured argumentation an argument can rebut another argument by attacking its conclusion. Two ways of formalizing rebuttal have been proposed: In restricted rebuttal, the attacked conclusion must have been arrived at with a defeasible rule, whereas in unrestricted rebuttal, it may have been arrived at with a strict rule, as long as at least one of the antecedents of this strict rule was already defeasible. One systematic way of choosing between various possible definitions of a framework for structured argumentation is to study what rationality postulates are satisfied by which definition, for example whether the closure postulate holds, i.e. whether the accepted conclusions are closed under strict rules. While having some benefits, the proposal to use unrestricted rebuttal faces the problem that the closure postulate only holds for the grounded semantics but fails when other argumentation semantics are applied, whereas with restricted rebuttal the closure postulate always holds. In this paper we propose that ASPIC-style argumentation can benefit from keeping track not only of the attack relation between arguments, but also the relation of deductive joint support that holds between a set of arguments and an argument that was constructed from that set using a strict rule. By taking this deductive joint support relation into account while determining the extensions, the closure postulate holds with unrestricted rebuttal under all admissibility-based semantics. We define the semantics of deductive joint support through the flattening method.
Discrete-to-Deep Supervised Policy Learning

Neural networks are effective function approximators, but hard to train in the reinforcement learning (RL) context mainly because samples are correlated. For years, scholars have got around this by employing experience replay or an asynchronous parallel-agent system. This paper proposes Discrete-to-Deep Supervised Policy Learning (D2D-SPL) for training neural networks in RL. D2D-SPL discretises the continuous state space into discrete states and uses actor-critic to learn a policy. It then selects from each discrete state an input value and the action with the highest numerical preference as an input/target pair. Finally it uses input/target pairs from all discrete states to train a classifier. D2D-SPL uses a single agent, needs no experience replay and learns much faster than state-of-the-art methods. We test our method with two RL environments, the Cartpole and an aircraft manoeuvring simulator.
Assisted Generation of Bone Fracture Patterns

We present a method for the generation of bone fracture patterns assisted by computer. A tool has been designed for the generation of a fracture pattern interactively and guided by the system, based on the study of real cases of fractures. This tool assists the specialist in obtaining fracture patterns according to certain rules taken from the statistical analysis of real cases. This tool can be used for the generation of biological databases of fractures. Another use of the fracture pattern could be the generation of virtual fractures, applying the fracture pattern to 3D osseous models.
전문대학 비교과 프로그램 인식차이를 통한 방향성 탐색

The purpose of this study was to identify the needs of supporting on basic learning ability from the perspectives of learners and instructors of junior colleges, and to seek systematic support measures for extra curricular programs. The results showed that the importance of basic learning competencies was recognized as more important by instructors than by learners. As a result of checking the difference in recognition on extracurricular programs, it was revealed that the instructors perceived that the basic learning support program was more important than the learners in the basic basics, the learning clinic program, and the foreign language support program. In the case of university-sponsored living programs, the instructor also found it more important. Lastly, in the case of employment support programs, instructors perceived 'shoulder tutoring, live mentoring, and majoring majors programs' as more important than leaners did. In all programs, the teacher's perception was higher than the learner's perception. Therefore, first, Measures targeting learners should be sought to improve awareness of basic learning competencies. Second, it is necessary to establish a university system to improve basic learning competencies. In detail, first, incentives should be provided, such as securing a pool of workers and providing incentives to support basic learning. Second, extracurricular programs suitable for university characteristics should be established. Third, extracurricular programs should be organized into processes that suit each major and learner's characteristics. Fourth, it should undergo improvement as learner-oriented extracurricular programs. Fifth, it is necessary to form a virtuous cycle of extracurricular programs.
Challenges of Word Sense Alignment: Portuguese Language Resources

The authors would like to thank the anonymous reviewers for their thoughtful comments towards improving ourmanuscript. Research financed by Portuguese NationalFunding through the FCT – Fundac¸ao para a Ci ˜ encia e Tec- ˆnologia as part of the project Centro de Lingu´istica da Universidade NOVA de Lisboa – UID/LIN/03213/2020, by theEuropean Union’s Horizon 2020 research and innovationprogram under Grant Agreement No. 731015 (ELEXIS),and through the FCT/MCTES as part of the project 2Ai –School of Technology, IPCA – UIDB/05549/2020.
Lipschitz Constrained Parameter Initialization for Deep Transformers

The Transformer translation model employs residual connection and layer normalization to ease the optimization difficulties caused by its multi-layer encoder/decoder structure. Previous research shows that even with residual connection and layer normalization, deep Transformers still have difficulty in training, and particularly Transformer models with more than 12 encoder/decoder layers fail to converge. In this paper, we first empirically demonstrate that a simple modification made in the official implementation, which changes the computation order of residual connection and layer normalization, can significantly ease the optimization of deep Transformers. We then compare the subtle differences in computation order in considerable detail, and present a parameter initialization method that leverages the Lipschitz constraint on the initialization of Transformer parameters that effectively ensures training convergence. In contrast to findings in previous research we further demonstrate that with Lipschitz parameter initialization, deep Transformers with the original computation order can converge, and obtain significant BLEU improvements with up to 24 layers. In contrast to previous research which focuses on deep encoders, our approach additionally enables Transformers to also benefit from deep decoders.
Off-Policy Adversarial Inverse Reinforcement Learning

Adversarial Imitation Learning (AIL) is a class of algorithms in Reinforcement learning (RL), which tries to imitate an expert without taking any reward from the environment and does not provide expert behavior directly to the policy training. Rather, an agent learns a policy distribution that minimizes the difference from expert behavior in an adversarial setting. Adversarial Inverse Reinforcement Learning (AIRL) leverages the idea of AIL, integrates a reward function approximation along with learning the policy, and shows the utility of IRL in the transfer learning setting. But the reward function approximator that enables transfer learning does not perform well in imitation tasks. We propose an Off-Policy Adversarial Inverse Reinforcement Learning (Off-policy-AIRL) algorithm which is sample efficient as well as gives good imitation performance compared to the state-of-the-art AIL algorithm in the continuous control tasks. For the same reward function approximator, we show the utility of learning our algorithm over AIL by using the learned reward function to retrain the policy over a task under significant variation where expert demonstrations are absent.
남북분단 극복을 위한 기독교의 두 시각: 민족주의적 담론과 탈민족주의적 담론

This paper discusses two perspectives of Korean Protestantism on overcoming the division of the Korean peninsula: nationalist versus post-national discourses. By doing so, this paper analyzes the complex relationship between peace and unification in each discourse. The justification of unification has been driven by the nationalist paradigm, and the nationalist perspective has provided for legitimacy. This view argues that the division of the Korean Peninsula into South and North Korea is an abnormal situation because the two states are originally one nation sharing history and using the same language. Therefore, this distorted reality should be overcome through unification. This study analyzes a historic document representing nationalist discourses, “The Declaration by Korean Christian Church on National Unification and Peace,” which was issued by The National Council of Churches in Korea in 1988. In nationalist discourses, peace is seen as a subcategory of unification and does not have its own place; Unification leads peace. Nationalist discourses faced criticism amid historical changes after the 1990s, including the rise of civil society movements through democratization, the gradual predominance of state identity over national identity, the spread of peace discourses since the 2000s, and emergence of multiculturalism and pluralism engendered by globalization. Responding the social changes, post-national discourses on peace and reunification have emerged. Christian post-national discourses on peace and unification include a pacifist perspective, a position emphasizing the value of reconciliation, a discourse centering on evangelization, or a unification perspective reconfigured by multiculturalism. This paper examines contentious relationship between peace and unification, discussing these post-nationalist discourses.
Entropic measurement uncertainty relations for all the infinite components of a spin vector

Abstract The information-theoretic formulation of quantum measurement uncertainty relations (MURs), based on the notion of relative entropy between measurement probabilities, is extended to the set of all the spin components for a generic spin s . For an approximate measurement of a spin vector, which gives approximate joint measurements of the spin components, we define the device information loss as the maximum loss of information per observable occurring in approximating the ideal incompatible components with the joint measurement at hand. By optimizing on the measuring device, we define the notion of minimum information loss. By using these notions, we show how to give a significant formulation of state independent MURs in the case of infinitely many target observables. The same construction works as well for finitely many observables, and we study the related MURs for two and three orthogonal spin components. The minimum information loss plays also the role of measure of incompatibility and in this respect it allows us to compare quantitatively the incompatibility of various sets of spin observables, with different number of involved components and different values of s .
Robot Education for Earlier Grade Students by Active Learning in National Institute of Technology

Since the establishment of the National Institute of Technology, Akita College 53 years ago, it has permitted students to choose one course among four in the Department of Mechanical Engineering, Department of Electrical and Computer Engineering, Department of Applied Chemical, or Department of Civil and Environmental Engineering. However, students have been able to enter a desired course after admission after a large comprehensive entrance system was introduced in fiscal year 2017. During the first year, all students take the Creative Systems Engineering course and finish the same curriculum for one year. Through this sweeping change, during the second year and thereafter, each student will be able to choose a course independently from the Department of Mechanical Engineering, Department of Electrical and Information Engineering, Department of Chemical and Biological Engineering, and Department of Civil Engineering and Architecture. For this reason, we trained all first-year students in robot and 3D CAD education, which is the main theme of the Robotics Course, to choose one course after completing the first year. The contents of the education are industrial robots, mobile trace robots, humanoid robots and 3D CAD. Therefore, we trained students about the methods of operation using the four. At the completion of the training, we compiled reports and administered a questionnaire. The questionnaire results demonstrate that it became clear that students in lower grades thought that learning about robots and 3D CAD was important, and were actively working on classes.
Rohrbach Library Home: Coronavirus emergency - resources for students & faculty: Paying a library fine or fee

This is a guide to help students and faculty navigate the changes created by the coronavirus emergency
An Accurate Model for Predicting the (Graded) Effect of Context in Word Similarity Based on Bert

Natural Language Processing (NLP) has been widely used in the semantic analysis in recent years. Our paper mainly discusses a methodology to analyze the effect that context has on human perception of similar words, which is the third task of SemEval 2020. We apply several methods in calculating the distance between two embedding vector generated by Bidirectional Encoder Representation from Transformer (BERT). Our team will_go won the 1st place in Finnish language track of subtask1, the second place in English track of subtask1.
El Taller de Creatividad: Un modelo para la educación artística

Art education becomes relevant to facilitate human awareness processes in the current context where to find spaces for personal reflection is increasingly complex. The purpose of this text is to present the Creativity Workshop as a model for artistic education, that is, the design of a creative process to promote in the person subjectivity transformations in favor of best satisfactory and free quality of life, through relationship dynamics between artistic experience and self-reflection, across the exploration of different languages of art within a social context. And since it is a previously systematized device the method of analysis used was deductive logic. In this way it has realized how the Creativity Workshop contributes to self-knowledge, self-esteem and assertive emotions management. Since it promotes, among other things, the development of perception and emotional awareness. Therefore, the Creativity Workshop is a space where the expansion of self-awareness becomes posible because it encourages the construction of significant learning.
Simulation Research on Influence of Neural Networks Scale on its Performance

Abstract When using deep learning methods to deal with specific problems, the structure and configuration complexity of neural networks model have a great impact on the performance of the system. This paper constructed a multi-layer perceptual neural networks model basing on classification problem of film and television reviews. The paper also analyzed the forward and back propagation, processing algorithm and key parameter optimization method, and built the simulation environment. By adjusting the network depth and the number of neurons in each layer, the paper analyzed the influence of the complexity of the neural networks model on the network performance. Then the paper gave the analysis results under the condition of different model scale. Finally the paper purported conclusion in the last section that the performance of the neural networks model changes greatly with number of neurons in each layer changed, but the performance changes little with network depth changed. It can provide an important reference for two classification problems in different fields.
Research on College English Teaching Model Based on Wechat Public Platform

This paper analyzes the functions and advantages of WeChat public platform and expounds the feasibility of applying WeChat public platform to college English teaching. Through the smart phone terminal, students conduct personalized learning to promote the reform of teachers’ teaching modes and student’s learning modes so as to build an college English teaching model based on the WeChat public platform, which improves students’ autonomous learning ability and learning efficiency.
Ethicalisation of Engineering in the Age of Digitalisation

The aim of the study is to determine specifics of engineering, which is treated as a sociocultural phenomenon influencing changes in political, economic, social life of the society. It is proven that a change of an engineer’s status throughout scientific history depends on a degree of the technosphere development. The study is novel in that it defines the content of the notion “digital engineer” used to denote a personality type of an engineer, which is characterised by a combination of professional and informational competences, the latter being among the crucial ones in the age of digitalisation. The results have proven that it is necessary to teach the principles of engineering ethicalisation to students for further successful development of the society.