Reviewerly/exHarmony huggingface dataset:
No such thing as virtual reality!

Telemedicin is used more and more in health care. To be efficient, several aspects that treatments depend on, such as client – therapist relation, have to be applied in a virtual context. As it appears our brain can be very easily fooled. Step by step basic principles of the brain, such as feedback and feedforward mechanisms, general pattern generators, integration of cortico-lymbic loops and consequences for usefulness of Telemedicin will be discussed. The overall conclusion is that the human brain is very well suited for treatment through Telemedicin.
Implementation of Operational Strategy Planning in Doku Application

Background - Health services are one of the most widely used public services, administered by BPJS Health reaching 222.5 million people as of December 31, 2020. This figure is equivalent to 81.3% of the total population in Indonesia. The Doku application is an application that will help level I Health Facilities and Hospitals to manage BPJS patient services. The Doku application will replace the conventional BPJS patient services at Level I Health Facilities and Hospitals to online. This business opportunity is quite large, even though there are threats from existing applications, with more brands and users, but based on the results of QSPM is product development strategy, Doku will always update features and add according to market needs. Method - Product design operational management approach. Result - This product design helps companies to implement user requirements in the form of user interface. Keywords: Application, Doku, Feature Update, Business opportunity.
Detection of Adjective Compound Word in Malay Language using Enhanced Syntactic Rules

Compound word is defined as combination two or more words and it will produce a new meaning. Generally, compound word is existed in many languages such as English, Mandarin, Arabic and others. Although, there are discussion of existing methods to detect compound word yet some limitations on detecting Malay compound word. Thus, this study is done to improve accuracy towards adjective compound words. Training data is used in this study was Malay story books. Digitization data of Malay story book is used in this study. Then, the pre-processing method involved tokenization, stemming, bi-gram and part-of-speech (POS) tagging has been applied to produce the candidate compound word. Applying the enhanced syntactic rules shown the precision result is 70.3% through this study. Thus, this study will contribute to the academic research in improvise the issues on searching and document summarization application.
Data Visualization of Graph-Based Threat Detection System

The Activity and Event Network Model (AEN) is a new security knowledge graph that leverages large dynamic uncertain graph theory to capture and analyze stealthy and longterm attack patterns. Because the graph is expected to become extremely large over time, it can be very challenging for security analysts to navigate it and identify meaningful information. We present different visualization layers deployed to improve the graph model’s presentation. The main goal is to build an enhanced visualization system that can more simply and effectively overlay different visualization layers, namely edge/node type, node property, node age, node’s probability of being compromised, and the threat horizon layer. Therefore, with the help of the developed layers, the network security analysts can identify suspicious network security events and activities as soon as possible.
Нейролідерство в освіті як компонент професійного розвитку викладачів

International scientific and practical conference «Pedagogy, psychology and teaching methods: international experience» : conference proceedings, July 16–17, 2021. Riga, Latvia : «Baltija Publishing», 2021. 295 pages.
مؤشرات تخطیطیة لمواجهة صعوبات العمل بمرکز دراسات العمل التطوعی بجامعة الإمام محمد بن سعود الإسلامیة: دراسة حالة

ملخص البحث: الدراسة وصفية تحليلية باستخدام المسح الاجتماعي الشامل و منهج دراسة الحالة للعاملين بمرکز دراسات العمل التطوعي بجامعة الإمام محمد بن سعود الإسلامية في الرياض, وتهدف الدراسة إلى إلقاء الضوء على أهداف المرکز ومدى تحقيقها من وجهة نظر العاملين فيه, و تحديد أهم الصعوبات التي تواجهه وتحد من تحقيقه لأهدافه والوصول إلى مؤشرات تخطيطية لدعم المرکز في مواجهة تلک الصعوبات في ضوء رؤية المملکة 2030. وقد توصلت الدراسة إلى أن المرکز قد حقق أهدافه بنسب تراوحت بين 76% - 86% و أن من أبرز الصعوبات التي تواجهه هي نقص الإمکانات و خاصة البشرية المتخصصة حيث جاءت في المرتبة الأولى بينما جاءت الصعوبات الإدارية والتنظيمية في المرتبة الخامسة, و أن نسبة  کبيرة من المبحوثين  يوافقون أو يوافقون بشدة  على المقترحات المتعلقة بتطوير عمل المرکز في ضوء رؤية المملکة 2030 مما يدعم هدف الدراسة المتعلق بالمؤشرات التخطيطية المقترحة لتطوير عمل المرکز و تحويله إلى مرکز وطني لدراسات العمل التطوعي في جانبه الاکاديمي العلمي وفي جانبه التطبيقي بالتنسيق مع مرکز الملک سلمان للإغاثة و الأعمال الإنسانية بما يحقق مستهدفات رؤية المملکة 2030. Abstract: This is a descriptive study conducted with a comprehensive social survey coupled with a case study on all employee working in the CVWS at Imam Muhammed Ibn Saud Islamic University in Riyadh, K.S.A.  The study sheds light on the goals of CVWS and the extent to which they are achieved from the view point of the CVWS staff.  It also intends to delineate the most salient obstacles that face CVWS as well as reaching planning indicators that would help CVWS overcome such obstacles in light of the Kingdom's vision 2030. The study found that 76%-87% of its goals have been achieved, albeit with the following difficulties:  low resources, particularly the specialized human resources, which came at the top of the list of the difficulties, with organizational and administrative difficulties being at the fifth position.  Moreover, most of the participants chose either (strongly agree or agree) to the suggestions regarding the advancement  of CVWS in light of the Kingdom's vision 2030 stipulations. Such findings lend support to the purpose of this study in regard to the need for the suggested planning indicators to enhance the work of the CVWS and its promotion to a national center for voluntary studies in both its academic and applied perspectives in coordination with King Salman Humanitarian Aid and Relief Center in an attempt to achieve the requirement of the Kingdom's vision 2030.
Normalised complexity metric for manoeuvering target tracking

Manoeuvering target tracking is a challenging problem for filter design in a variety of tracking systems. However, how to quantify the complexity of this problem is seldom studied. In this paper, a normalised complexity metric for manoeuvering target tracking called relative difficulty to Kalman filter is defined as the ratio between maximum tolerance error of positional estimation and its requirement precision of positional measurement. It can be employed as an indicator of the difficulty of designing an advanced filter to satisfy the tracking requirement. Analytical expression of RD2KF in three-dimensional space is derived. Two typical tracking examples show that RD2KF is affected by manoeuver intensity, data rate and the required precision of the tracking mission.
THE DIFFERENCES OF CHRONOLOGICAL AGE WITH DENTAL AGE BASED ON THE ALQAHTANI METHODE AGED 6-12 YEARS

The chronological age of a person can not provide sufficient information. We can use the dental age in panoramic radiographs to know the growth process appropriately compared to The London Atlas of the Alqahtani method. Children aged 6-12 years have various factors that can affect the velocity in tooth growth and development, such as male and female. This study aims to determine the chronological patient's age differences with dental age based on the Alqahtani method on a panoramic radiograph at Unjani Dental and Oral Education Hospital. This type of research is Analytical Observational with the Cross-Sectional Study method. Research subjects were obtained from all medical records panoramic radiographs with 72 panoramic radiographs aged 6-12 years, divided into 36 male patients and 36 female patients. Differences in chronological age with dental age were analyzed statistically using the Mann-Whitney test and Wilcoxon test, previously tested for the normality using Kolmogorov- Smirnov. The results showed a significant difference between chronological age and dental age by gender and in all patients at the Unjani Dental and Oral Education Hospital (p&lt;0,05). Based on the analysis of the data obtained, all patients in RSGMP Unjani aged 6-12 years have different dental developmental growth processes, and the dental development growth of female patients was faster than male patients. It can be concluded that the dental age is not always comparable with chronological age because of various factors such as gender, genetics and environment, which can affect the dental age.
Attention Guided Filter for Jointly Extracting Entities and Classifying Relations

Jointly extracting entities and classifying relations aims to detect all possible triples from unstructured text with a single model.Tagging-based method effectively improves the performance of jointly relation extraction.However, some taggingbased approaches ignored that one entity pair may exist multiple relations and others set an empirical threshold value for selecting one or more relevant relations, which becomes the bottlenecks of the model.As a solution, we propose the attention guided filter, namely, AGFRel, which introduces transformer blocks to learn the number of relations for every entity pair to filter out irrelevant relations.Moreover, each module of the model has a multi-head attention guided layer to highlight valuable information.Extensive experimental results show that AGFRel is capable of gaining better performance on various tasks including overlapping triples extraction and multiple triples extraction.On NYT and WebNLG public datasets, our model obtains F1 score 90.8 and 91.9 respectively and achieves a new state-of-the-art performance.
A proposed method for encrypting and sending confidential data using polynomials

With the improvements of cyberspace and communications, an essential problem was raised and that is how to secure the transmitted data and keep it confidential. Many techniques have been used for this purpose, some of them were broken but others were stayed immune against different attacks. Complexity of the used technique is one of the major reasons that kept it secure. To increase complexity, mathematics was used. In this paper, a method for encrypting and sending confidential data was proposed. The method depends on mathematical equations for encrypting data, sending and decrypting it. The method is complex, secure and workable.
Перспективи використання досвіду підготовки майбутніх учителів до надання фасилітативної педагогічної підтримки сімей у Норвегії

International scientific and practical conference «Pedagogy, psychology and teaching methods: international experience» : conference proceedings, July 16–17, 2021. Riga, Latvia : «Baltija Publishing», 2021. 295 pages.
English foreign language teaching anxiety of Indonesian pre-service teachers of undergraduate internship program

Anxiety is a topic mostly investigated in the field of foreign language education. Unfortunately, the main focus of the studies on the aforementioned topic has primarily been provided in relation to anxiety suffered by students not teachers. Anxiety in speaking English while teaching has been proven to be a separate obstacle to the success of the language teaching and learning. This still happens to teachers who even have years of teaching experience. This study aims to investigate the English language teaching anxiety as experienced by the pre-service teacher at the department. The FLTA questionnaire consisting of 27 out of 45 items was adopted to collect data. Since this study was carried out during the COVID-19 pandemic, the questionnaire was distributed to the participants via email. The analysis was then made by implementing the qualitative descriptive approach and simple quantification to support the description. The results show that there were five factors of anxiety occur during the program. They were teaching inexperience, self-perception of language proficiency, fear of negative evaluation, lack of student�s interest, and difficulty with time management. These findings are expected to become a reference for the efforts of developing an internship preparation program.
Comparing Lexicons Diachronically in Italian Literary Corpora

The goal of the article is to provide a comparison between several words from Florentine vernacular language and modern Italian language, using software written by the author. This paper focuses on two corpora: the first one includes a selection of Florentine vernacular literature and the second one a group of literary books written in a modern Italian language from the end of XIX Century up until the present. The article demonstrates the use of some features of the software to compare the two corpora, ranking the lexicographic entries using different strategies. It is possible to analyse the lexicon taking into consideration different types of sorting, using only three parameters: the word frequency, the percentage of frequency according to the number of words in the corpus, and the percentage of texts where the word is found in the corpus. From these parameters a fourth parameter also arises the level of persistence of words in each corpus. The software allows observing the differences in the use of lexicon in various periods of history, comparing the Florentine vernacular language, which was used in the Italian peninsula till the beginning of XIX Century, to the modern Italian language.
Tingkat Formulasi Model Soal dalam Permutasi Acak Menggunakan Algoritma Fisher Yates

The problem model in random permutations results in random randomization of the most commonly used questions in exam practice in education ranging from elementary school to college level and even some agencies that utilize exams to test one's abilities. This Problem Model can produce a high random percentage with more complex processes compared to analogues. Conduct Model Formulations on infinite questions so that they can be easily utilized without complicated calculations. The problems processed in this study are from 50 questions, and 12 students are sourced from the Information System Study Program of STMIK Logika, at Medan Indonesia state. Based on the collection of the question by the head of the study program in charge of the STMIK. Furthermore, the problem is saved into the database. The next stage is to randomize the question based on the number of students taking the exam. The problem has been randomized into a model formulation of the question in a random permutation of the question at the time of the Test practice. The result of the test on this question is a matter of courses. Randomized questions can form a problem model in random permutations based on many questions, the number of questions. All questions are made by lecturers who teach courses and help the study program in the teaching and learning process with the formulation of the problem model.
Two-Dimensional Quantitative Profiling of Cell Morphology with Serous Effusion by Unsupervised Machine Learning Analysis

Cytological evaluation of serous effusion specimens is an important part of cancer diagnosis.In this study we performed two-dimensional (2D) morphometric features and clustering analysis for development of useful techniques for identification and differentiation of malignant and begin cells in serous effusion specimens extracted from ten patients with clinical symptoms of pleural and peritoneal effusion.Our findings show that the two-dimensional (2D) morphometric features and clustering analysis are useful techniques for identification and differentiation of malignant and begin cells in serous effusion specimens, which can lead to development of new methods for rapid cells profiling in clinical application.
PENINGKATAN MOTIVASI DAN HASIL BELAJAR MENGGUNAKAN POWERPOINT INTERAKTIF DI SEKOLAH DASAR

The purpose of this research was to enhance motivation and science learning outcomes of grade IV students at SD Negeri 2 Bolopleret.This research is a classroom action research.The subjects of this research was the students of grade IV SDN 2 Bolopleret.Data collection uses documentation, observation, questionnaire and test techniques.The data validity was using source triangulation technique and method triangulation.The qualitative data analysis technique uses an interactive model, namely data reduction, data presentation, and drawing conclusions.While quantitative data were analyzed descriptively.The results showed the following: (1) The learning motivation of students who are categorized as "high" in the first cycle is 55% or 6 students.In the second cycle to 91% or 10 students.2) Student learning outcomes before the action only reached 28% or 3 students who completed.After the action in the first cycle, as many as 4 students or 36% have not achieved complete learning, 7 students or 64% have completed.Cycle II increased to 1 student or 9% incomplete, 10 students or 91% completed.
Pengaruh Model Concept Sentence dengan Pendekatan CLIL terhadap Pengetahuan dan Keterampilan Krangan Narasi Kelas V

This study aims to determine the effect of the concept sentence model with the CLIL approach to the knowledge and skills of writing narrative essays in class V of the Rejang Lebong V. group This type of research is quantitative research using the Quasi Experimental Research method with One Group Pretest and Posttest Design. The population in this study were all fifth grade students of Rejang Lebong Public Elementary School grade A accredited A, totaling 222 students, namely SDN 110, SDN 111, and SDN 114. The sampling technique was using cluster random sampling. The sample in this study consisted of 1 study group, which was an experimental class consisting of 32 students from 111 Rejang Lebong Elementary Schools. The research instrument was used in the form of a 5W + 1H narrative essay knowledge and writing skill given through the pre-test before the learning took place and the post-test after the learning took place. The research data were analyzed using descriptive analysis, prerequisite tests, and inferential analysis, namely one sample t-test. Data were obtained from the results of the study of the average pretest experimental class knowledge (53) and the average pretest experimental class skills (42). While the research data of posttest average experimental class knowledge (68) and posttest average experimental class skills (69). One sample of the results of the t-test is knowledge of the posttest value indicating sig. (2-tailed) (0.468)&gt; ? (0.05). For this reason Ho was rejected. And for the posttest test sample the narrative essay writing skills show sig. (2-tailed) (0.552)&gt; ? (0.05). For this reason Ho was rejected. Because both hypotheses are Ho which is rejected, which means Ha is accepted. Thus it can be concluded that there is an effect of the application of the concept of sentence learning models with the CLIL approach to the knowledge and skills of writing narrative essays in class V SDN Group V Rejang Lebong. The difference is shown after students follow the narrative text learning by applying the concept of sentence learning models with the CLIL approach.
PENGEMBANGAN SISTEM INFORMASI DIRECT DEBIT DONOR PROGRAMME (DDDP) DENGAN PENDEKATAN INCREMENTAL LIFE CYCLE MODEL (STUDI KASUS LEMBAGA KONSERVASI LINGKUNGAN DI JAKARTA)

Direct Debit Donor Programme (DDDP) is a donation program for individuals who are interested in taking part in social activities by direct debit of donations through bank accounts or credit cards which are commonly referred to as supporters or donors. Management of a structured and integrated information system with a good database concept will support a more effective and efficient performance. This study aims to analyze and develop the DDDP information system as a solution for supporter donation data management in increasing time efficiency. Information system development is carried out in stages starting from the need for basic functions in accordance with the development stages with the Incremental model, namely Requirements, Specifications, Architecture Design, Code and Test. modeling system development using the Unified Modeling Language (UML). Data collection was carried out through observation, direct interviews with related parties, viewing documents that were related to the research being carried out and conducting literature reviews. Functional testing on the system uses the black box testing method with the test results not found any errors in the system. The result of this research is a supporter donation data management information system which is named DDDP Application System.
Improved minimum-minimum roughness algorithm for clustering categorical data

Clustering is a fundamental technique in data mining and machine learning. Recently, many researchers are interested in the problem of clustering categorical data and several new approaches have been proposed. One of the successful and pioneering clustering algorithms is the Minimum-Minimum Roughness algorithm (MMR) which is a top-down hierarchical clustering algorithm and can handle the uncertainty in clustering categorical data. However, MMR tends to choose the category with less value leaf node with more objects, leading to undesirable clustering results. To overcome such shortcomings, this paper proposes an improved version of the MMR algorithm for clustering categorical data, called IMMR (Improved Minimum-Minimum Roughness). Experimental results on actual data sets taken from UCI show that the IMMR algorithm outperforms MMR in clustering categorical data.
Fine-Grained Neural Network Abstraction for Efficient Formal Verification

The advance of deep learning makes it possible to empower safety-critical systems with intelligent capabilities.However, its intelligent component, i.e., deep neural network, is difficult to formally verify due to the large scale and intrinsic complexity of the verification problem.Abstraction has been proved to be an effective way of improving the scalability.A challenging problem in abstraction is that it is difficult to achieve a balance between the size reduced and output overestimation caused by abstraction.In this work, we propose an effective fine-grained approach to abstract neural networks.Our approach is fine-grained in that we identify four cases that should be abstracted independently under a certain neuron prioritization strategy.This allows us to merge more neurons in networks and meanwhile maintain a relatively low output overestimation.Experimental results show that our approach outperforms other existing abstraction approaches by significantly reducing the scale of target deep neural networks with small overestimation.
MRI examination teaching system by using virtual reality (VR)

This study proposes a magnetic resonance imaging (MRI) virtual reality system and uses a pulse oximeter measuring device to reduce patient’s anxiety. The research investigates the radiation of the patient’s heart rate when using the virtual reality system and degree of the individual’s perception of anxiety. In the end, a questionnaire survey is conducted to understand the patient’s views of this system.This study uses Beckett Anxiety Scale to measure the degree of patient’s anxiety. The experimental results show that the patient’s anxiety level decreased from moderate anxiety to mild anxiety and the performance of heartbeat rate is very different between before and after using VR system. According to the results of the questionnaire, how easy the system is will affect the willing of the patient to use the system. Besides, the opinion of others will affect the patient’s feeling of the useful of the system.