Reviewerly/exHarmony huggingface dataset:
Pemanfaatan open access Jurnal Borneo Administrator melalui pengukuran kepuasan pembaca di Lembaga Administrasi Negara

Open Access Journal (OAJ) is a journal publication that contains articles in full text and user’s can be accessed and used free of charge. The purpose of this study was to determine the extent to which open access was used in the Borneo Administrator Journal (JBA) by measuring reader satisfaction. The research method used was a descriptive quantitative approach. The data collection used a survey method and a data analysis technique used a simple descriptive statistical method. This research has eight research questions, namely the level of user’s satisfaction with access and download facilities, Kemenristek/Dikti accreditation, language, benefit for the profession and career advancement, number of articles and columns, overall format and content, issued quarterly (3x a year), and services provided by JBA managers. The research data analysis has the three highest indicators were published every quarter (3x a year), the format and content as a whole, and were beneficial for professional and career advancement. The lowest score indicators but still in the satisfied category were download facilities, language, and the number of articles and columns. In conclusion, the overall level of reader satisfaction is in the satisfied category. The implementation of open access in the Borneo Administrator Journal is basically to support the development and dissemination of knowledge.
Investigating the applicability of Software Metrics and Technical Debt on X++ Abstract Syntax Tree in XML format : calculations using XQuery expressions

This thesis investigates how XML representation of X++ abstract syntax trees (AST) residing in an XML database can be subject to static code analysis. Microsoft Dynamics 365 for Finance & Opera ...
A Parallel Evaluation Data Set of Software Documentation with Document Structure Annotation

This paper accompanies the software documentation data set for machine translation, a parallel evaluation data set of data originating from the SAP Help Portal, that we released to the machine translation community for research purposes. It offers the possibility to tune and evaluate machine translation systems in the domain of corporate software documentation and contributes to the availability of a wider range of evaluation scenarios. The data set comprises of the language pairs English to Hindi, Indonesian, Malay and Thai, and thus also increases the test coverage for the many low-resource language pairs. Unlike most evaluation data sets that consist of plain parallel text, the segments in this data set come with additional metadata that describes structural information of the document context. We provide insights into the origin and creation, the particularities and characteristics of the data set as well as machine translation results.
Probabilistic Logic Graph Attention Networks for Reasoning.

Knowledge base completion, which involves the prediction of missing relations between entities in a knowledge graph, has been an active area of research. Markov logic networks, which combine probabilistic graphical models and first order logic, have proven to be effective on knowledge graph tasks like link prediction and question answering. However, their intractable inference limits their scalability and wider applicability across various tasks. In recent times, graph attention neural networks, which capture features of neighbouring entities, have achieved superior results on highly complex graph problems like node classification and link prediction. Combining the best of both worlds, we propose Probabilistic Logic Graph Attention Network (pGAT) for reasoning. In the proposed model, the joint distribution of all possible triplets defined by a Markov logic network is optimized with a variational EM algorithm. This helps us to efficiently combine first-order logic and graph attention networks. With the goal of establishing strong baselines for future research on link prediction, we evaluate our model on various standard link prediction benchmarks, and obtain competitive results.
Technology in conflict: how COVID-19 tracing apps can exacerbate violent conflicts

In this Strategic Update, Jennifer Easterday explores how a human security approach to COVID-19 tech tools would prompt tech companies, governments, and other actors to work with communities in ways that enhance their agency in the face of the pandemic to both reduce the risk of exacerbating conflict while maximizing the benefits of technology.
МОДЕЛЬ ПЕДАГОГИЧЕСКОГО ДИЗАЙНА КАК ТЕХНОЛОГИЯ ИННОВАЦИОННОГО ПОДХОДА К ОБУЧЕНИЮ В ВЫСШЕЙ ШКОЛЕ

In the article under consideration the necessity of the educational system modernization in the course of the realization of new initiatives in the field of professional education learning is grounded. Given the global digit environment, the model of pedagogical design is to be given the lead.&#x0D; The author analyses different aspects of the model, formulates some key tasks that are to be solved, provides some likely characteristics of the streamlined model of professional lifelong learning system.
SSN_NLP at SemEval-2020 Task 7: Detecting Funniness Level Using Traditional Learning with Sentence Embeddings

Assessing the funniness of edited news headlines task deals with estimating the humorness in the headlines edited with micro-edits.This task has two sub-tasks in which one has to calculate the mean predicted score of humor level and other deals with predicting the best funnier sentence among given two sentences.We have calculated the humorness level using microtc and predicted the funnier sentence using microtc, universal sentence encoder classifier, many other traditional classifiers that use the vectors formed with universal sentence encoder embeddings, sentence embeddings and majority algorithm within these approaches.Among these approaches, microtc with 6 folds, 24 processes and 3 folds, 36 processes achieve the least Root Mean Square Error for development and test set respectively for subtask 1.For subtask 2, Universal sentence encoder classifier achieves the highest accuracy for development set and Multi-Layer Perceptron applied on vectors vectorized using universal sentence encoder embeddings for the test set.
Vocabulary Building via Language Apps: A Case Study in Hong Kong

To help students who are learning English as a foreign language (EFL) to gain optimal exposure to authentic English, educators and app designers have developed various digital learning resources, including English vocabulary apps for EFL students, which can, without the barriers of time and space, integrate various media including audio-visual texts, assessment, and/or instant links to online dictionaries and Wikipedia.Nevertheless, English vocabulary learning, as an ongoing process (Schmitt, Schmitt & Clapham, 2001), means much more than just the convenient access of audio-visual materials.According to Gu and Johnson (1996), vocabulary learning strategies cover seven main categories of vocabulary learning strategies, which range from learners' beliefs about vocabulary learning, metacognitive regulation, guessing strategies, dictionary strategies, note-taking strategies, memory strategies (rehearsal), memory strategies (encoding), and activation strategies.To what extent vocabulary learning apps are helping students' vocabulary skills is of paramount concern to EFL teachers and apps designers.In light of this, this paper collected data from questionnaires, vocabulary tests, and interviews with EFL students and teachers at university in Hong Kong.It reveals and discusses the effectiveness of current English language learning apps for Hong Kong university students.
Practical experience in organizing distance learning in secondary schools

The COVID-19 pandemic has re-emphasized distance learning. It became a powerful impetus for the transition from theoretical considerations to the practical implementation of such training in the school system (Strategy New Growth Model - New Social Policy, 2020). This article describes the experience of organizing such training for children in the 4th quarter of the 2019/2020 academic year. It considers all stages of implementation of distance learning, such as solution of legal issues regulating the activities of an educational institution; effective construction of the educational process, considering the important relationship "student-teacher"; the right choice of information technology that meets the capabilities and limited skills of students, and has a user-friendly interface. The experience of distance collaboration between a teacher, a student and his parents is also presented, which made it possible to build effective teaching and achieve a high-quality education.
Prediction of Earthquakes; Considering the Ratio of &lt;i&gt;P-to-S&lt;/i&gt; Wave Velocities

The ratio of P-to-S-wave velocities (Vp/Vs) is considered as one of the important measures of stressed natural rocks.The changes of this ratio were observed in various earthquakes, however the time of occurrence of the earthquakes were not determined, since the predictions were not combined with other prediction methods.This discriminant provides information about formation and evolution of composition for the earth's crust.In addition, the changes in Vp/Vs before and after earthquakes are the possibly reliable direction to realizing the mechanics and probably predicting earthquakes.However, due to lattice orientations of anisotropic minerals, most of earth's rocks are anisotropic and there exist cracks and thin layerings.The changing patterns in Vp/Vs acquired from seismic propagations can be readily analyzed according to the ray path and the polarization of the (P) pressure and (S) shear waves.The variations in their ratios carry information about stress variations of THE crust of the earth.The arising stresses in rocks are the messengers of possible earthquakes.The stations with monitoring devices and Geographical Positioning System (GPS) upgraded WI-FI remote data acquisition system can serve monitoring stress and movements in the earth's crust.In view present technological developments, the system is reasonable cost effective and prediction of earthquakes can be possible in narrowed time interval.The laboratory tests will be also part of the prediction process.
Basic Research on the Influence of Descent Flow From Small Unmanned Aerial Vehicle (Quadcopter) on a Small Floating Body

Abstract Currently, unmanned aerial vehicles (UAV), are playing an active role in various situations. However, because of its size and other limitations, the commonly used UAVs (from now on, just called as drone) do not have the long endurance capabilities of large aircraft. Of course, long flight is not the original intention of its design, but flexibility is its main characteristic. This results in the need for frequent replacement and recharging of battery equipment. It may be easy to replace the batteries on land, but it will be more difficult to do the same offshore. Also, there is always the danger of drone falling into the water due to insufficient power. To overcome this problem, it is imagined to place a floating body such that the drone can be docked as and when necessary while flying over the water for maintenance and battery replacement. Therefore, in this preliminary study, we aim to model the basic physical phenomena mainly on how the drone’s descent flow affects structures such as small floating bodies. The effects of drone descent flow on a small floating body and resulting load distribution was investigated both experimentally and numerically. Further, the mechanism of drone descent flow was examined in detail. The drift simulation of the floating body due to the drone descent flow was performed with high accuracy, and the model of the drone’s descent flow became clear.
Un profano di fronte ai tecnicismi musicali: qualche riflessione linguistica

The article focuses on the degree of transparency of musical technical terms for the lay reader. The sample texts examined show that the vast majority of technical terms, starting from indications of duration and pitch, are untranslatable. Enthusiasts who have not studied music can, however, obtain an overall understanding through context, or even their familiarity with the piece described in a concert program or in a popular, widely accessible book.
ACADEMIC STAFF RESEARCH PERFORMANCE EVALUATION: THE FOREIGN EXPERIENCE

The problem of evaluating the university faculty research performance in the European Higher Education Area and in the European Research Area is enlightened in the paper. It is emphasized that under the transition to open science and open access and increasing digitalization, that has emerged in the higher education system due to the global COVID-19 pandemic, the problem of academic staff research performance evaluation and their career attractiveness needs to be reconsidered. The article analyses the key principles of evaluating researchers and their professional development; they are enlightened in the basic regulations of the European Commission, European University Association and European Research Area, and in the Hong Kong Principles as a part of the Open Science and Open Access Initiative. The issue of using almetrics in evaluating research outputs is actualized; it provides the «visibility» of the researcher not only for the scientific or educational community, but also for society as a whole. This expands the scope of usual indicators of research performance and provides a comprehensive and more objective measurement of researchers’ excellence. The structure of research performance evaluation is given; it should be based on an integrated approach, taking into account the peer-review, quantitative and qualitative measurements, and include all the components of university staff research activity, i.e. the scientific creativity potential and its research outputs, research supervision, young scientists’ mentoring, national and international cooperation, performing administrative duties, research dissemination, and mobility.
Method for measuring differences in the neuronal responses to social stimuli

The following topics are dealt with: mobile robots; neurophysiology; motion control; control system synthesis; electroencephalography; medical signal processing; position control; robot dynamics; cognition; remotely operated vehicles.
Blockchain as Part of Industry 4.0.

Blockchain technology is considered to be the driving force of the industry 4.0. It will enable more agile value chains, faster product innovations, closer customer relationships, and quicker integration with the IoT and cloud technology. This paper introduces relevant aspects of Industry 4.0 that illustrate its impacts on blockchain, some of the benefits and challenges that arise when using blockchain. Also there is an overview on blockchain technology. How such ledger technology as blockchain affects on industry 4.0 and implements some of the technologies.
Exploration and Thoughts on the Teaching Reform of the Course "Animal Nutrition"

People have found that if you want to study animal nutrition well, you can't just confine it to a single field, but you should work together in multiple fields to conduct more in-depth research and discussion on animal nutrition. Therefore, omics technology came into being. This article mainly discusses the teaching methods of the animal nutrition omics course, analyzes some of the problems in the course teaching and the corresponding reform measures, in order to improve the teaching effect of the animal nutrition omics course and improve the professional skills of students.
PELATIHAN PENULISAN SURAT DINAS PADA PERANGKAT DESA KAMPUNG WISATA TAMAN YOGYAKARTA

The aim of training in writing official letters at the village office is to increase the understanding of village officials about writing official letters that are good and correct. This community service program activity lasts for two days, namely on September 26, 27, 2020 at the Tamansari Yogyakarta hall. The total number of village apparatus / staff who attended this official letter writing training was 25 people. Based on the preliminary survey, the spelling scores of the participants in the activity were not good, meaning that there was a need for improvement in understanding Indonesian spelling. During the training, the activity participants and the implementation team conducted a reflection and evaluation of the material presented. Thus, activity participants can compile official letters properly and correctly according to the General Guidelines for Spelling in Indonesian.
SOLVING THE PROBLEM OF OBJECTIVATION OF KNOWLEDGE EVALUATION ON THE BASIS OF WEB-LMS MOODLE DATABASE

Rapid changes in modern society, associated with the modernization of educational content, the introduction of a person-centered approach, the peculiarities of work in the quarantine period, significantly affect all components of modern education and require their reorientation and widespread introduction of distance learning. One of the most important elements in the system of distance education is the control of students' educational work as a means of managing the learning process. The use of testing provides an opportunity to check a significant amount of educational material, implements feedback between the student and the educational content of the discipline, allows individualization of work with students. The theory of knowledge control defines the following didactic principles: effectiveness, systematicity, individuality, differentiation, objectivity and unity of requirements. This work is devoted to the issue of objectification of knowledge control in the testing process. Among the tasks that require solution in the implementation of the test form of knowledge control, perhaps the most important is to determine the level of complexity of test tasks to be offered to the student during testing to adequately determine the level of his knowledge. In addition, it is the complexity of test tasks that underlies the algorithm for building an individual learning trajectory and knowledge control. To assess and dynamically adjust the values of the complexity of test tasks, the authors propose to use heuristic algorithms that take into account the total assessment of the performance of students undergoing testing. The generalized scheme of heuristics is as follows: the more students correctly answered a specific test task, the lower should be the assessment of its complexity. And the amount of correction depends on the assessment of the success of each student who answered the test task and the characteristics of the test task. Under the features of test tasks we understand their variety: problems with one correct answer, problems with one answer, selected from the options of graded answers, problems with many answers, selected from the options of graded answers, problems with numerical answers, problems with answers given interval. To build an effective mechanism for objectification of knowledge assessment, the structure of the LMS Moodle database was analyzed in order to select a subset of tables from which the information needed for calculations will be extracted, provided that the required data is stored in the system. Thus, the authors propose theoretical and practical principles for building an effective mechanism for objectifying knowledge assessment in the environment of the distance learning system Moodle.
STAY : Mindfulness and Space

The state of the art technology has been penetrated every corner of people's life. It is a path to transfer to a new way of life with the artificial intelligence and big data resources. The next ge ...
Automated Teller Machine Security with Image Processing and Machine Learning Techniques

There are many scenarios in society with thefts and crimes involved in Automated Teller Machines (ATM). These events are increasing day-by-day and which is also increasing the complexities on the crime investigation agencies. In order to deal with these situations, we have proposed an automated security method inside ATMs using image processing techniques which can alert the concerned authorities immediately whenever these types of situations arise. Hybrid method with Viola-Jones algorithm has been used for face recognition along with the Haar-cascade features. In the case of objects such as knife, gun etc. inside an ATM, combination of SVM and random forest algorithms are used for object detection. TensorFlow with machines learning algorithms have been used in the hybrid methodology. Android application has been developed to prevent and alert the crimes and send alert messages to the concerned. Speech alert system is developed to assist blind and physically challenged people.
Instagram Picture Series to Improve Students Procedure Text

The research is aimed to know whether the students ability in writing procedure text be improved through the use of Instagram picture series as teaching media. This is a classroom action research (CAR) on the eleventh grade of Madrasah Aliyah NU Sidoarjo in 2018/2019 academic year. The researcher used the CAR model developed by Kemmis and Mc Taggart (1990:14) which includes four steps. They are planning, acting, observing and reflecting. This research used quasi-experimental design. Participants were equally assigned to experiment group and control group. The population is 126 students. The samples are ten students of XI MIPA 1 as the experimental group and ten students of XI MIPA 1 XI MIPA 2 as the control group. The researcher applied two kinds of instrument: writing pre-test and writing post-test. The data was analyzed statistically using T-test. As the result, the percentage growths margin between experimental group and control group is 4.52%. The use of Instagram picture series as teaching media was an appropriate strategy for eleventh grade students of Madrasah Aliyah NU Sidoarjo to improve their ability in writing procedure text. It means that, the use of Instagram picture series as teaching media had the significant positive impact to the improvement of the students ability in writing procedure text.Keywords: instagram picture series, procedure text, improvement, CAR
Menu Package Recommendation Menu Package Recommendation Using Combination of K-Means and FP-Growth Algorithms at Bakery Stores

Bakery shop is a shop that sells variants menu like bread, cakes, and drinks. The main problem with this store's sales is still not knowing which product items are best sellers and the shop still markets a lot of non-selling menus, causing the shop to lose money. So it takes the right strategy to increase the sales of bakery shop menus by making a menu package recommendations from the menus most frequently purchased by customers. The k-means algorithm performs grouping on menus to get menu packages. Furthermore, the fp-growth algorithm looks for linkages between frequently purchased menus to get menu package recommendations. The results of the research that the dominant items often purchased in cluster0 packages are hotdogs, pancakes, milk, garlic breadsticks with a confidence value of 92%, cluster1 packages are garlic breadsticks, hotdogs, chicken sand, pancakes with a confidence value of 92% and the last cluster2 packages are garlic breadstick, pastry, milk with a confidence value of 79%.