Reviewerly/exHarmony huggingface dataset:
Modeling the parallelism of empirical models of optimal complexity using a Petri net

Many physical processes and phenomena in view of their complexity cannot be described analytically. In these cases, empirical modeling is applied. In this research, the method based on the genetic approach is used to construct empirical models of optimal complexity that have the form of a polynomial of assigned power. Implementation of the developed method requires a multiple solution of the system of linear algebraic equations. Solution of the system of linear algebraic equations is found by reducing the corresponding matrix to the upper diagonal form with unities on the main diagonal. Analysis of the algorithm showed that the procedure of reducing the matrix to the upper diagonal form has internal parallelism. Based on the created model of the computational process in the form of a Petri net, the strategy of construction of the parallel algorithm for solving the system of linear algebraic equations was developed. The essence of the strategy is that computations are performed on some parallel processors. One of them was assigned coordinating functions, and it was named master. Other processors – slaves are subordinated to the master. Division of computation volume is such that the number of rows of the matrix, which master operates is at least by unity more than the corresponding number of rows allocated to the servant. The effectiveness of the parallel algorithm for the proposed strategy was evaluated based of the criterion of the total number of arithmetic operations. The proposed strategy is an integral part of the process of synthesis of the empirical model of optimal complexity based on the genetic algorithms. Distribution of computational load between processors working in parallel (master and slaves) ensures the acceleration of the computational process by five times or more.
Team Howard Beale at SemEval-2019 Task 4: Hyperpartisan News Detection with BERT

This paper describes our system for SemEval-2019 Task 4: Hyperpartisan News Detection (Kiesel et al., 2019).We use pretrained BERT (Devlin et al., 2018) architecture and investigate the effect of different fine tuning regimes on the final classification task.We show that additional pretraining on news domain improves the performance on the Hyperpartisan News Detection task.Our system 1 ranked 8th out of 42 teams with 78.3% accuracy on the held-out test dataset.
MULTIPLICATIVE NEURON MODEL BASED ON SINE COSINE ALGORITHM FOR TIME SERIES PREDICTION

Time series prediction is a method to predict the system behavior in the future based on current given data. Neural Networks (NNs) approach is a well-known technique that is useful for time series prediction. In the literature many NN models such Multilayer Perceptron (MLP), Pi-Sigma NN (PSNN), Recurrent NN etc. are proposed for solving time series prediction. In this paper, we use Multiplicative Neuron Model (MNM) to predict time series. For training this model, we propose use newly developed evolutionary optimization algorithm called Sine Cosine algorithm (SCA), and this algorithm has not been used as far as we know in training the MNM. The proposed SCA-MNM model is employed for the most known time series problems. In this paper, the application of the SCA-MNM on time prediction is illustrated using two mostly used datasets Mackey-Glass time series dataset, Box-Jenkins gas furnace dataset. To investigate the effect of the proposed SCA-MNM model, comparisons were made with some of the results given in the literature.
Pengembangan Penghapus Papan Tulis Putih Menggunakan Metode TRIZ

In Faculty of Industrial Technology Islamic University of Indonesia, whiteboards are used as a medium of learning in the classroom. Generally, instructors use non-permanent markers to make it easy to clean with an eraser. The problem that occurs is if this eraser is often used, the ability will decrease. This is caused by the large amount of ink markers that have been attached to the eraser cloth so that some ink that can not stick in the form of fine grains eventually falls and collects in the dirt container. These fine grains can contaminate clothes, hands, and other body parts. In addition, there are remnants of ink markers on the board that can hinder to write the next material. But to overcome this, there is a contradiction that is if an eraser is often used, the ability will decrease. To eliminate this contradiction, a systematic method of problem solving was used, namely TRIZ method. This method helps to provide solutions through the principle of preliminary action. This principle was realized by adding a spray mechanism that is used just before the erasing process is carried out. Testing the ability of the eraser was done on a whiteboard with ink markers with the size of 50 x 50 cm. The results show that the new eraser that has been developed is able to bind more ink markers and can completely erase so that it can write the next material clearly.
Article 10 ECHR and Expressive Conduct

The European Court of Human Rights has recently delivered a series of judgments finding violations of the right to freedom of expression over convictions for engaging in expressive conduct. The purpose of this article is to discuss the European Court’s recent case law on expressive conduct under Article 10 of the European Convention on Human Rights, and in particular to assess in what circumstances, if any, domestic courts may impose prison sentences, even if suspended, on individuals engaging in peaceful, but provocative and offensive expression.
UTILISATION AND CHALLENGES OF THE LEARNING MANAGEMENT SYSTEMS IN THE HIGHER EDUCATION INSTITUTIONS IN MALDIVES: THE LECTURERS’ AND STUDENTS’ PERSPECTIVES

The purpose of this study is to discover the level of utilisation and challenges in using learning management system (LMS) from the perspective of the lecturers and students in higher education institutions (HEI) in Maldives.This study has examined the utilisation and challenges of LMS in the HEIs in Maldives by conducting a qualitative survey questionnaire with lecturers and students.In this study, three HEIs which are currently using an LMS in Maldives were selected.It was found that the LMSs are utilised for passive communication and they are underutilised for meaningful collaborative teaching and learning.The identified key challenges are the lack of planning and strategies for the LMS implementation, the lack of user participation and training, the need of models to track and forecast the evolution of LMS, and the need to support the decisions regarding LMS implementation.The LMS is at the heart of every successful modern HEI.The failure to implement an effective LMS could affect the success of the HEIs.The HEIs have realised that the failures of the LMS are because of the under-utilisation, lack of planning and strategies, and lack of integration with other information systems.Understanding these issues and challenges is significant for the senior management to take key decisions on implementing LMSs in HEIs to develop a more robust educational ecosystem.
Solving Venn-Diagram Based Comprehension Questions in Set Theory using Natural Language Processing

Natural language problems have gained increased attention in the recent times.There are many special purposes, and carefully constructed evaluations driving the NLP research.Problem solving tests offer an interesting alternative to these evaluations.The primary goal of creating these problem solving tests is to evaluate the reading skills, and there by create bank of training materials and ranking procedures to match the existing measures of human performance.Solving Set Theory problems using NLP exposes once such research problem and helps creating an evaluation method for Natural Language Understanding Systems.This paper describes the possibility to challenge these systems to successively push higher performance levels up to an accuracy of 80% with high speed as an added advantage.
Research on the Revitalization of Talents in the Old Revolutionary Areas of Sichuan Province

The economic development of the old revolutionary areas in Sichuan Province is backward, especially in the rural areas.To solve this problem, it is necessary to implement the rural revitalization strategy.The biggest problem and key issue in implementing the rural revitalization strategy are the talent problem.This study analyzes the reasons for the lack of rural revitalization talents in the old revolutionary areas of Sichuan from the perspective of local talents and talents from other places, and puts forward corresponding countermeasures, which can provide certain ideas for solving the problem of revitalizing talents in the old revolutionary areas of Sichuan.
ecoEd: Cohesive training and skill development for digital ecoscience tools

Digital research infrastructures such as data portals and virtual laboratories enable easier access to data and analytical tools. Such infrastructures are essential to deliver research excellence that drives innovation, but we also need to ensure that we have a skilled workforce that can use these infrastructures. Therefore, training and skill development of students, researchers, government practitioners and industry professionals is key to the long-term success of this investment. In Australia, a suite of digital infrastructures has been developed for environmental sciences to enhance our understanding of the natural world and making forward projections into novel conditions (e.g. Atlas of Living Australia, Biodiversity and Climate Change Virtual Laboratory, ecocloud , Terrestrial Ecosystem Research Network). To provide users with a holistic approach to environmental spatial data discovery and analysis, these infrastructures have joined forces to deliver an exciting and innovative new training program. This program, called ecoEd , provides cohesive training and skill development to university lecturers, researchers and industry professionals enabling them to combine theoretical concepts with real-world applications. In this presentation, I will present how ecoEd was developed and the outcomes of the training sessions in which a group of ecoEd Champions absorbed ready-to-use lecture and workshop modules along with tools and knowledge on how to use the platforms. These resources can immediately be used in undergraduate courses that focus on topics such as ecology, biogeography, conservation biology, environmental management and spatial analysis as well as in stand alone workshops for researchers and practitioners. The training program aims to provide the Champions with the resources and knowledge required so that they can confidently re-deliver the lectures and workshops in their own institutions. As such, ecoEd is increasing the capacity of Australia’s environmental science community to advance science and deliver outcomes that underpin the sustainable use of our ecosystems using the latest advances in digital technologies. Moreover, it is enabling first-rate science education in Australia by supporting and nurturing our future scientists.
An Enhanced Association Rule Mining Method for Processing Network Comments

In order to facilitate the processing and understanding of text by computer, this paper uses a triple tuple containing entity and entity relationship to represent the text's fact in a more formal and concise way.The knowledge base (KBs), which contains a large number of facts, is used in various fields related to natural language processing.KBs usually integrates information from different places, such as manually edited encyclopedia, news articles, and social networks.In this paper, a natural language enhanced association rule mining method (NEARM) combined with KBs is used to deal with network comments.The fragments of fact are found from the pure text, and then the emotion is classified according to the fragments of fact found by the classifiers.Firstly, NEARM clusters the original data containing the pairs of related entities into clusters with different granularity from the data in KBs, and then excavates the rules in each cluster.These rules contain a large number of relational facts, which can reflect the relationship between plain text data, and can be effectively used in emotional classification of text.The experimental results show that the method is feasible.NEARM can deduce the relational triple facts and improve the accuracy of emotional classification.
THE ETHICS OF THE SUBJECT-SUBJECT INTERACTION IN THE MODERN EDUCATIONAL ENVIRONMENT

The article is dedicated to the assessment and evaluation of the particularities of the professional ethics of a modern teacher on the basis of studying the phenomenon of ethics in the organization of human relationships. The authors specify the structure of professional ethics of a modern teacher while taking into account the ethical and psychological knowledge about verbal and nonverbal behavior of a person and professional image of modern business communication. The functional possibilities of the teacher’s moral competence and the protective mechanism of the teacher’s ethical behavior in the conflict pedagogical situations, in particular, are investigated.
Perbedaan Perkembangan Bahasa Anak Pra Sekolah yang Mengikuti dan Tidak Mengikuti PAUD

Background: Delay in language development can affect subsequent development in children. Research comparing language development of pre-school age children who participated and did not participated in PAUD had never been done before. The purpose of this study was to analyze differences in language development of pre-schoolers who attended Early Childhood Education (PAUD) and did not attend Early Childhood Education (PAUD).Methods: This research was a quantitative research with comparative descriptive method. The sampling technique was proportionate random sampling and involved of 82 children in Bulusan Village, Tembalang District, Semarang City. Data analysis used Kolmogorov-Smirnov test.Results: The results showed that the language development of pre-schoolers attending the early childhood was better than the non-attending pre-schoolers with p-value from non-parametric test Kolmogorov Smirnov (0.032) &lt;α (0.005).Conclusion: There are differences of preschool language development who attended and did not attend PAUD. Based on the results of the study, it is advisable for parents of children to provide stimulation appropriate to the stage of language development of children according to their age and to include children in PAUD.
Metode Automatic clustering-fuzzy logical relationships pada Peramalan Jumlah Penduduk di Kota Makassar

Abstrak. Penelitian ini merupakan penerapan metode automatic clustering-fuzzy logical relationships unruk meramalkan jumlah penduduk di Kota Makassar menggunakan data sekunder BPS Kota Makassar yang bertujuan memprediksi jumlah penduduk tahun 2017-2021. Penelitian diawali dengan penentuan panjang interval, nilai tengah panjang interval, membuat relasi logika fuzzy, fuzzifikasi, defuzzifikasi, dan menghitung nilai error hasil ramalan dengan metode Mean Absolute Percentage Error. Hasil penelitian ini menunjukkan bahwa ramalan jumlah penduduk di Kota Makassar dari tahun 2016 ke 2017 meningkat, tahun 2017 sampai tahun 2019 menurun, dan pada tahun 2019-2021 meningkat dengan keakuratan yang sangat bagus.Kata kunci:Automatic clustering-fuzzy logical relationships, Fuzzy Time Series,TeoriFuzzyAbstract.This research is the application of the forecasting method of fuzzy time series which is the method of automatic clustering fuzzy-logical relationships in forecasting the population of Makassar City using secondary data from BPS Makassar city which aims to predicting the population in year 2017-2021. The discussion starting from the determination of the length of the interval, determining the value of the middle length interval, making relations of fuzzy logic, fuzzification, defuzzification, and calculating the error value of the forecasting result by using the method of Mean Absolute Percentage Error. The result of this research shows that the predictions of the population of Makassar City from 2016 to 2017 increased, from 2017 to 2019 decreased, and in 2019-2021 increased with the very good accuracy. Keywords:Automatic Clustering-Fuzzy Logical Relationships, Fuzzy Time Series,Fuzzy Theory
A New Balanced Greedy Snake Algorithm

The existing greedy snake algorithm (GSA) suffers from some problems, such as three forces are unbalance and the extracting contour on concave region is unsatisfactory. This paper presents an algorithm, called balanced greedy snake algorithm (BGSA), for solving objective contour extraction problem. BGSA is compose of continuity force, curvature force and image force, which is similar to the origin GSA. Whereas, BGSA improved the computing rule of GSA to balance the influence of above three forces. Especially, BGSA can process the image with concave region well. The results of experiment show that BGSA is efficient and outperform the existing GSA.
Hybrid distributed application in banking transaction using remote method invocation

Today banks have many branches in big cities of the world. System usually used a central database in a particular city. Increased of database server performance due to number of users accessing this application should not degrade performance of application. To keep database server performance optimally, application must distributed to the network. In distributed applications it takes a remote method call, that is why we are going to used Remote Method Invocation to develop this system. Based on results of analysis conducted, author can draw following conclusion of the application, which is once the client get a reference from the remote object then method of remote object is called like calling method from local object and methods that we have defined and implemented on remote object can we call or use both on desktop and web applications so we do not need to work twice. This approach makes more effective and efficient in application development, allows for better optimization, eliminates the need for processing of type information at run time and makes a light weight communication protocol possible. We have built a hybrid application, which supports both compile time and run time generation of marshallers in desktop and web application.
YUN-HPCC at SemEval-2019 Task 3: Multi-Step Ensemble Neural Network for Sentiment Analysis in Textual Conversation

This paper describes our approach to the emotion detection of Twitter textual conversations based on deep learning.We analyze the syntax, abbreviations, and informal-writing of Twitter; and perform perfect data preprocessing on the data to convert them to normative text.We apply a multi-step ensemble strategy to solve the problem of extremely unbalanced data in the training set.This is achieved by taking the GloVe and ELMo word vectors as input into a combination model with four different deep neural networks.The experimental results from the development dataset demonstrate that the proposed model exhibits a strong generalization ability.For evaluation on the test dataset, we integrated the results using the stacking ensemble learning approach and achieved competitive results.According to the final official review, the results of our model achieved micro-F 1 score of about 0.7588 on the final evaluation.
Maximality on Construction of Ternary Cross Bifix Free Code

The purpose of this research was to show that ternary cross bifix free code CBFS3(2m+1) and CBFS3(2m+2) achieved the maximum for every natural number m. This research was a literature review. A cross bifix free codes was constructed by using Dyck path method which achieved the maximality, that was non-expandable on binary set sequences for appropriate length. This result is obtained by partitioning members of CBFS3(2m+1) and CBFS3(2m+2) and comparing them with the maximality of CBFS2(2m+1) and CBFS2(2m+2). For small length 3, the result also shows that the code CBFS3(3) is optimal.
Axiomatization and computability of a variant of iteration-free PDL with fork

We devote this paper to the axiomatization and the computability of PDL0Δ, a variant of iteration-free PDL with fork. Concerning the axiomatization, our results are based on the following: although the program operation of fork is not modally definable in the ordinary language of PDL, it becomes definable in a modal language strengthened by the introduction of propositional quantifiers. Instead of using axioms to define the program operation of fork in the language of PDL enlarged with propositional quantifiers, we add an unorthodox rule of proof that makes the canonical model standard for the program operation of fork and we use large programs for the proof of the Truth Lemma. Concerning the computability, we prove by a selection procedure that PDL0Δ has a strong finite property, hence is decidable.
Decision-Making at National Level for the Support of Research Infrastructures

The presentation will elaborate on the Dutch decision-making process concerning large-scale research infrastructures at national and European levels. The process involves several stakeholders, from scientists, to funders to Ministries. The Permanent Committee for Scientific Infrastructures (http://www.onderzoeksfaciliteiten.nl/permanente-commissie) plays a high-level decision-making and vision role in this effort. The committee is independent and part of NWO, the Netherland's Research Organisation for Scientific Research, on special request of the Minister of Education, Culture and Science. This level of decision making is necessary to participate at the next level within the vision of the European Roadmap for Research Infrastructures. This Roadmap is set up by the European Strategy Forum for Research Infrastrcutures (ESFRI, https://www.esfri.eu) and is a portfolio of Research Infrastructures regarded as crucial to shape the European Landscape of scientific Research Infrastrcutures. DiSCCo (Distributed System of Scientific Collections), led by Naturalis (Leiden) is a recent and good example of such an infrastructure that gained a place in the European research infrastructure environment connecting 115 Museums, Botanical Gardens and collection-holding Universities in 21 European countries.
FACTORS HINDERING THE ACHIEVEMENT OF ENGLISH COMMUNICATIVE COMPETENCE

English communicative competence is one of the prime preferences for learners in this current century, including tourism academy students. As the consequence, learners are equipped by relevant skills including how to articulate English communicative competence insight effectively. Learners are encouraged to fulfill the of micro and macro components of English communicative competence and minimize the factors hindered to be a competent English speaker. The aims of this research were to analyze the factors hindering communicative competence and disclose the micro and macro component problems of English communicative competence at the fourth semester of hotel department students enrolled in three-year diploma program in Denpasar tourism academy. This was descriptive-quantitative study and involved 30 students and one English lecturer as respondents at this college. Data were collected through in-depth interview, questionnaire, field observation, and students’ English communicative competence document. Then, data were analysed by using software program, Excel Chart Data Series. The result indicates that internal factors were more affecting than external factors and micro components were more complicated than macro components in the students’ English communicative competence.