Reviewerly/exHarmony huggingface dataset:
An Evaluation of Automatic Text Summarization of News Articles: The Case of Three Online Arabic Text Summary Generators

Digital news platforms and online newspapers have multiplied at an unprecedented speed, making it difficult for users to read and follow all news articles on important, relevant topics.Numerous automatic text summarization systems have thus been developed to address the increasing needs of users around the world for summaries that reduce reading and processing time.Various automatic summarization systems have been developed and/or adapted in Arabic.The evaluation of automatic summarization performance is as important as the summarization process itself.Despite the importance of assessing summarization systems to identify potential limitations and improve their performance, very little has been done in this respect on systems in Arabic.Therefore, this study evaluated three text summarizers AlSummarizer, LAKHASLY, and RESOOMER using a corpus built of 40 news articles.Only articles written in Modern Standard Arabic (MSA) were selected as this is the formal and working language of Arab newspapers and news networks.Three expert examiners generated manual summaries and examined the linguistic consistency and relevance of the automatic summaries to the original news articles by comparing the automatic summaries to the manual (human) summaries.The scores for the three automatic summarizers were very similar and indicated that their performance was not satisfactory.In particular, the automatic summaries had serious problems with sentence relevance, which has negative implications for the reliability of such systems.The poor performance of Arabic summarizers can mainly be attributed to the unique morphological and syntactic characteristics of Arabic, which differ in many ways from English and other Western languages (the original language/s of automatic summarizers), and are critical in building sentence relevance and coherence in Arabic.Thus, summarization systems should be trained to identify discourse markers within the texts and use these in the generation of automatic summaries.This will have a positive impact on the quality and reliability of text summarization systems.Arabic summarization systems need to incorporate semantic approaches to improve performance and construct more coherent and meaningful summaries.This study was limited to news articles in MSA.However, the findings of the study and their implications can be extended to other genres, including academic articles.
Freedom of expression in turbulent times – comparative approaches to dangerous speech: the ECtHR and the US Supreme Court

The European Court of Human Rights (ECtHR) and the US Supreme Court (USSC) have emphasised the foundational importance of freedom of expression. However, when the exercise of this liberty appears to endanger the democratic institutions or the national security of the state, readiness to uphold limitations of this right increases. Over the years each judicial body has adopted a distinctive approach towards limitations on dangerous speech. The US Constitution envisages free speech as an unconditional freedom; a ‘free market of ideas’ is the key concept, suggesting that the protection availed to speech should be the widest possible. The USSC gradually adopted a viewpoint-neutral approach focusing solely on the secondary effects of the speech, thus protecting even abstract advocacy of violence. On the contrary, the ECtHR may contracted freedom of expression in view of wider societal interests; the key concept is that of a militant democracy capable of protecting itself. The ECtHR adopts a lower threshold of protection that precludes abstract advocacy of violence and applies an intricate balancing exercise. ECtHR’s approach allows more space for indeterminacy and obscurity in its jurisprudence. The USSC’s case-law may serve the ECtHR as a source of inspiration with a view to refining its standards.
Physical modeling of the Bazhenov formation in combination with CSEM and seismic methods

To predict the properties of the Bazhenov formation and to identify the areas in which oil deposits are localized the use of electrical prospecting methods is promising. The main goal of the current research is to evaluate the effectiveness of using Controlled Source Electro Magnetics (CSEM) exploration for the area forecast of the properties of the Bazhenov formation. The main objectives of physical modeling in this research are: Creation of an isotropic physical model corresponding to the electrical and elastic parameters of the section of the studied area, and performing 3D modeling on it with survey parameters that reproduce real seismic and CSEM surveys To convince that the contrast of the elastic properties and the ratio of the resistivity of the target interval of the Bazhenov formation and overlying rocks in the created physical model corresponds to the real petrophysical characteristics of the section of the studied area; Obtaining initial data for testing algorithms for synchronous inversion of seismic + electric and testing various approaches to processing and interpretation of CSEM and 3D seismic data.
Distribution Matching for Rationalization

The task of rationalization aims to extract pieces of input text as rationales to justify neural network predictions on text classification tasks. By definition, rationales represent key text pieces used for prediction and thus should have similar classification feature distribution compared to the original input text. However, previous methods mainly focused on maximizing the mutual information between rationales and labels while neglecting the relationship between rationales and input text. To address this issue, we propose a novel rationalization method that matches the distributions of rationales and input text in both the feature space and output space. Empirically, the proposed distribution matching approach consistently outperforms previous methods by a large margin. Our data and code are available.
GRAPH BASED CLUSTERING WITH CONSTRAINTS AND ACTIVE LEARNING

During the past few years, semi-supervised clustering has emerged as a new interesting direction in machine learning research. In a semi-supervised clustering algorithm, the clustering results can be significantly improved by using side information, which is available or collected from users. There are two main kinds of side information that can be learned in semi-supervised clustering algorithms: the class labels - called seeds or the pairwise constraints. The first semi-supervised clustering was introduced in 2000, and since that, many algorithms have been presented in literature. However, it is not easy to use both types of side information in the same algorithm. To address the problem, this paper proposes a semi-supervised graph based clustering algorithm that tries to use seeds and constraints in the clustering process, called MCSSGC. Moreover, we introduces a simple but efficient active learning method to collect the constraints that can boost the performance of MCSSGC, named KMMFFQS. In order to verify effectiveness of the proposed algorithm, we conducted a series of experiments not only on real data sets from UCI, but also on a document data set applied in an Information Extraction of Vietnamese documents. These obtained results show that the proposed algorithm can significantly improve the clustering process compared to some recent algorithms.
Password authentication scheme based on smart card and QR code

As a hopeful computing paradigm, cloud services are obtainable to end users based on pay-as-you-go service. Security is represented one of the vital issues for the extended adoption of cloud computing, with the object of accessing several cloud service providers, applications, and services by using anonymity features to authenticate the user. We present a good authentication scheme based on quick response (QR) code and smart card. Furthermore, our proposed scheme has several crucial merits such as key management, mutual authentication, one-time password, user anonymity, freely chosen password, secure password changes, and revocation by using QR code. The security of proposed scheme depends on crypto-hash function, QR-code validation, and smart card. Moreover, we view that our proposed scheme can resist numerous malicious attacks and are more appropriate for practical applications than other previous works. The proposed scheme has proved as a strong mutual authentication based on burrows-abadi-needham (BAN) logic and security analysis. Furthermore, our proposed scheme has good results compared with related work.
Perbandingan Metode Klasifikasi Random Forest dan SVM Pada Analisis Sentimen PSBB

COVID-19 in Indonesia, has made the local government not remain silent. Several local governments in Indonesia have enacted regulations to reduce the growth of COVID-19 victims by limiting public meetings with Large-Scale Social Restrictions or LSSR. However, the implementation of this LSSR has received many comments from social media users, especially from Twitter. This research was conducted with the aim of analyzing the sentiment of implementing the LSSR with media tweets on the Twitter social media platform. The data that were successfully extracted were 466 tweet data with training data and test data having a ratio of 7 to 3. Then the data was calculated into 2 different algorithms to be compared, the first algorithm used was the Support Vector Machine (SVM) algorithm and Random Forest with the aim get the most accurate sentiment analysis results.
Analisis Lama Penggunaan Komputer Pada Mahasiswa Universitas ABC Dengan Metode Algoritma C4.5

Nowadays computers are a very important technology and widely used, almost in all sectors of the field, one of which is in the field of education. In ABC University we know that every student must have or even used a computer often. For this reason, the authors make research on the duration of computer use in students and anything that can affect the duration of students in using computers. Using the C4.5 Algorithm the author created a decision tree where the decision tree is made from datasets that have been collected from several students who filled out the questioner. Then the dataset calculation results will provide a rule or scheme where students can be said to have used a computer for a long time or not. For example, students in the last semester or semester 8 can be said to be using a computer for a long time.
Educación superior en tiempos de pandemia: fortalezas y retos

This issue of the Revista de Educación Superior del Sur Global -RESUR- provides us with an approach to higher education institutions and the way in which they have adapted the teaching processes during the health contingency generated as a result of COVID-19 , which has caused a transition from face-to-face to virtual systems, causing a series of disruptive changes for which teachers, students or society in general were not prepared.The current issue of RESUR aims to present an in-depth analysis of the challenges that the closure of higher education institutions has implied, as well as the strengths of this new work modality, considering issues related to the educational innovations implemented to migrate from face-to-face training to virtual classrooms, the challenges of carrying out this process both for students, as well as for teachers and the institutions under which teaching and learning are carried out, the students' perspective regarding the new way of learning, the strategies proposed by professors to maintain the attention and motivation of young people and the potential that this contingency raises for the improvement of educational practices in favor of training for a new normality. (...)
On the Role of Orthographic Variations in Building Multidialectal Arabic Word Embeddings

Dialectal Arabic (DA) is mostly used by over 400 million people across Arab countries as a communication channel on social media platforms, web forums, and daily life.Building Natural Language Processing systems for each DA variant is a challenging issue due to the lack of data and the noisy nature of the available corpora.In this paper, we propose a method to incorporate orthographic features into word embedding mapping methods, inducing a multidialectal embedding space.Our method can be used for both supervised and unsupervised cross-lingual embedding mapping approaches.The core idea of our method is to project the orthographic features into a shared vector space using Canonical Correlation Analysis (CCA).Then, it extends word embedding vectors using the resulting features and learns the multidialectal mapping.The overall obtained results of our proposed method show that our method enhances Bilingual Lexicon Induction of DA by 3.33% and 17.50% compared to state-of-the-art supervised and unsupervised cross-lingual alignment methods, respectively.
Las nuevas tecnologías en la educación superior, una oportunidad

One of the main challenges facing education systems today is related to the development of inclusive schools that welcome and respond to the diversity of students and is probably a key factor in moving towards quality education that is relevant to all people and not just to certain social groups.
PENGEMBANGAN GAME EDUKASI DIGITAL DAN IMPLEMENTASI PADA PEMBELAJARAN BIOLOGI MATERI PLANTAE SISWA SMA KELAS X

Science and Technology in education demand teachers as educators with integrated innovations in technological developments. The media is used to improve understanding of educational game-based material with student characteristics. The research aims to develop and the feasibility of digital educational games on the Plantae SMA class X material. This type of research uses development (R&D). The research model used is ADDIE with five stages: (1) analyze, (2) design, (3) development, (4) implementation, and (5) evaluation. . The instrument used a questionnaire and test (Pretest-Postest). The questionnaire assessment data were analyzed using the quantitative descriptive test, the pre-test and post-test assessment data were analyzed using the N-Gain test. Based on the results of the game assessment analysis by media experts with a total score of 3.40 (very good), then the assessment by the material expert with a total score of 3.48 (very good), then the assessment by the teacher with a total score of 3.23 (very good), and assessment by students with a total score of 3.38 (very good). The implementation of the game "Adventure Of Plant" shows that there is an increase in the average pretest score of 57 and the average post-test score of 77, with the N-Gain analysis result of 0.47 (moderate). Conclusion: digital education game research on Plantae material is suitable for use as a learning medium, but it has a (moderate) influence on student learning outcomes in understanding the concept of learning.Kata kunci: ADDIE, Game Edukasi Digital, Materi Plantae, Media Pembelajaran.
RANCANG BANGUN APLIKASI SISTEM PAKAR DIAGNOSA PENYAKIT PADA TANAMAN KELAPA SAWIT MENGGUNAKAN METODE FORWARD CHAINING BERBASIS WEB

This research aims to develop an expert system application that can facilitate users in diagnosing oil palm plant diseases based on symptoms. The data used in this expert system consists of 7 diseases and 12 symptoms of oil palm plants. Expert system that is built on web-based using a rule with the Forward Chaining method to identify diseases. Testing has been done in two stages. They are internal testing and external testing. Internal testing consists of functional testing and system expertise testing. Functional testing using the Black Box method with the Equivalence Patitioning (EP) technique shows that the developed system functions as expected. Expertise testing is done by comparing the results of the diagnosis by the system and the results of the diagnosis by experts to produce a diagnosis of system expertise as expected. External testing is done by giving questionnaires to 23 respondents who were divided into 2 groups to get an assessment of the system. The questionnaire results of the group I (Experts) obtained a satisfaction value of 81%, while the group II (Students of the Department of Plantation Cultivation) obtained a satisfaction value of 75%.
USING THE METHOD OF COLLABORATIVE LEARNING SCHOOLCHILDREN ON THE EXAMPLE THE TOPIC «VOLUMES OF POLYHEDRA»

One of the most important tasks of training today is the development of the student's creative potential. The teacher needs to create conditions in which the student would seek to get new results of their work and then apply them in practice. The collaborative learning method refers to interactive learning methods and promotes and contributes to the formation of the creative personality of a student capable of self-development and self-education and transition from formal assignments to the active role of the student, able to defend own opinion when performing tasks. Interactive methods of teaching stereometry are not well represented in the methodological literature. The article discusses the theoretical foundations of interactive teaching methods and provides fragments of lessons on the topic «Volume of polyhedral» using the method of teaching in collaborative learning.
AMUSEVR: A Virtual Reality Authoring Environment for Immersive Mulsemedia Applications

To meet the demand for mulsemedia (multiple sensorial media) content production, numerous tools exist, among which many present the currently typical approach providing 2D content organized in timelines. However, when it comes to 360° content where 3D spatial positioning is necessary, neither consensus on authoring methodology nor widely-adopted approaches to design exist. In order to fulfll this gap, we propose AMUSEVR, a virtual-reality environment for mulsemedia application development. In addition to supporting various media and sensory eﬀect types, AMUSEVR allows authors to create and visualize content dynamically using VR technology. We evaluated AMUSEVR with an authoring experiment with users, using UEQ questionnaires, and obtained promising results.
Positive Impact of Balinese Folktale Literacy Learning on Students' Social Attitudes and Reading Ability

This paper reports the effect of Balinese folktale literacy learning on elementary students’ reading ability and social attitudes. The type of research is pseudo-experimental research with a non-equivalent post-test-only control group design. The population in this study was 129 students. The sample was selected by using random sampling techniques. 23 students were treated as an experimental group and 27 students were treated as a control group. The data were obtained by administering multiple-choice tests and distributing questionnaires. The data were analyzed by using descriptive statistical analysis techniques and inferential statistics, i.e., Manova-test. The data of this study were also described through the classification level of each data group by using five conversion guidelines. The results showed that there was a significant difference between the reading ability and the social attitudes of the students taught by using folktale literacy learning and those who were taught by using conventional learning. It can be seen from the Sig.&lt; value of 0.05. Based on these results, it can be concluded that Balinese folktale literacy learning affected reading ability and social attitudes of elementary students.
CYBERSPEDAGOGICS – AN INNOVATIVE BRANCH OF PEDAGOGICAL SCIENCE

The article is devoted to problems of cybermedicine industry as an innovative pedagogical science.Some aspects of the prerequisites for the formation of cyberspedagogics are considered. The authors give a conceptual series of cyberpedagogics. The article substantiates the necessity of using a cyberontological approach in education, which is effective in solving the actual problems of human education and training in the XXI century. Cyberspace is characterized as a new environment of human activity and a factor of social and intrapsychic changes. The key features of a modern person using information and communication technologies are described. Substantiates the importance of developing a culture of cybersocialization of each person, as well as cybermediary – science of the XXI century – as the basis of organization of modern education with regard to the influence of cyberspace on the processes of learning, education and development. The article analyzes a number of concepts on the problem of cyberspedagogics.
Competitive Programming 4: The New Lower Bound of Programming Contests in the 2020s

Seven years have passed since me and my brother Felix Halim released the 3rd edition of our Competitive Programming book (CP3) on 24 May 2013 that had influenced the competitive programming field in the past decade: 2010s. We have just released the 4th edition of our book (CP4) on 19 July 2020 – the original IOI 2020 arrival day where free preview copies should have been given to all invited delegations. In this short report, we address two groups of readers: those who have read/heard about CP3 and those who are new with this book.
Learning in Online Communities: Behavioral Strategies of the Users of Educational Social Networks

The article deals with the results of a study on users’ behavioral strategies in educational social networks as Internet platforms for the communities of students and teachers who collaborate to solve educational problems. According to the analysis of the students and teachers’ activity on the educational social network of the Volgograd State Socio-Pedagogical University, the author has determined the groups of users with similar behavioral strategies, namely: community organizers, activists for communication and document exchange, educational assignment performers, information consumers, and inactive users. The author provides generalized portraits of each group, their numerical composition, as well as comparative characteristics in relation to other groups. The manuscript concludes that the presented groups reveal typical behavioral strategies of the users of educational social networks, which further development of educational platform tools, as well as pedagogical technologies based on their implementation should consider.
Effects of Nonlinear Functions on Knowledge Graph Convolutional Networks for Recommender Systems with Yelp Knowledge Graph

Knowledge Graph (KG) related recommendation method is advanced in dealing with cold start problems and sparse data. Knowledge Graph Convolutional Network (KGCN) is an end-to-end framework that has been proved to have the ability to capture latent item-entity features by mining their associated attributes on the KG. In KGCN, aggregator plays a key role for extracting information from the high-order structure. In this work, we proposed Knowledge Graph Processor (KGP) for pre-processing data and building corresponding knowledge graphs. A knowledge graph for the Yelp Open dataset was constructed with KGP. In addition, we investigated the impacts of various aggregators with three nonlinear functions on KGCN with Yelp Open dataset KG.
Sentiment Analysis with Cognitive Attention Supervision

Neural network-based language models such as BERT (Bidirectional Encoder Representations from Transformers) use attention mechanisms to create contextualized representations of inputs, conceptually analogous to humans reading words in context.For the task of classifying the sentiment of texts, we ask whether BERT's attention can be informed by human cognitive data.During training, we supervise attention with eye-tracking and/or brain imaging data and combine binary sentiment classification loss with these attention losses.We find that attention supervision can be used to manipulate BERT attention to be more similar to the ground truth human data, but that there are no significant differences in sentiment classification accuracy.However, models with cognitive attention supervision more frequently misclassify different samples from the baseline models-they more often make different errors-and the errors from models with supervised attention have a higher ratio of false negatives.