Reviewerly/exHarmony huggingface dataset:
Scrutiny on the grammatical error of descriptive text written by the first semester public health students Universitas Faletehan

&lt;p style="text-align: justify;"&gt;In English Competency the students should master four skills namely speaking, reading, writing and listening. On the other hand most of students found many barriers to achieve this competency, particularly in writing due to writing is not simple but writing is long process. This study is intended to analyze, find out the types of errors, and the factors for grammatical error in students composition. The use of articles, verbs, adjectives, adverbs, nouns, preposition, and conjunctions are the focus of the analysis. The errors are analyzed through the procedure of identification, description, categorization, classification, calculation and interpretation. The errors were then classified into four types namely omission, addition, misformation, and misordering then they were counted and interpreted. Altogether they were 1401errors in student’s descriptive text. They covered 495 (35.33%) errors of articles, 280 (19.98%) errors of nouns, 225 (16.05%) errors of preposition, 116 (8.27%) errors of adjectives, 62 (5.42%) errors of verb, 58 (5.07%) errors of conjunction, 44 (3.84%) errors of pronouns, and 110 (7.85%) errors of verbs. Based on the type of errors omission errors got the highest frequency. It happened 475 (33.9%) followed by misformation and misordering, addition errors 190 (13.56%). There were various frequencies of errors found from each type. Omission errors included 200 (35.33%) from 495 errors of articles, Nouns 90 (19.98%) from 280 error of nouns, preposition 70 (16.05%) from 225 errors of prepositions, conjunction 40 (4.99%) from 70 errors of conjunction, pronoun 30 (4.63%) from 65 of pronouns, verb 40 (7.85%) from 40 errors of verbs, adjective 30 (8.27%) from 30 errors of adjectives. Addition errors 50 ( 16.05.33%) from 225 errors of preposition, nouns 35 (19.98 %) from 280 errors of nouns and adjective 30 (2.85%) from 30 adjectives. The misordering errors of articles are clearly seen that they got the highest frequency among others. It took place 200 times (35.33%) from 495 of articles. Great tendency to omit and misform, article, nouns, and preposition is influenced by the skill habit of L1, as well as misordering errors of articles, preposition, nouns, and adjective. It is interpreted hat differences of the structure of L1 and L2 greattly influence the learners to make grammatical errors in writing English composition. Another factor that the causes the errors in incomplete of the target language itself.&lt;/p&gt;
Deployment Topologies

In this chapter, we’ll explore some common cluster deployment topologies. Each will make sense in different circumstances, depending on your environment, latency, and survivability requirements.
Money as a marker of the modern era and a factor of aberration of moral values in the novel by M.Yu. Lermontov "A Hero of Our Time"

The undertaken research is aimed at identifying the determinism of the characters of the heroes of the novel "A Hero of Our Time" not so much by the ideological content of the era of the 30s. XIX century, how much of its economic content, as the era of industrialization, aimed at establishing commodity-money relations. The purpose of the article is to determine the value of the factor of money as a marker of the era of industrialization in the construction of human relations of the heroes of the novel and the degree of aberration of moral values, which causes their expression in commodity-money equivalent. The main research method is the comparative-historical method, aimed at identifying and comparing the contexts in which the situations of bargaining or transactions vary in the chapters of the novel, expressed in certain monetary equivalents. As a result of the study, the degree of devaluation of moral values and aberration of consciousness of the heroes of the novel is determined, the motivation of whose actions is determined by the influence of the "industrial age".
Dimensions of Knowledge Sharing and its Role in Career Path Development an Exploratory Study of the Opinions of a Sample of Employees in Al Salam Teaching Hospital

The research aims to show the role of the dimensions of knowledge sharing in career path development of a sample of employees in Al Salam Teaching Hospital, as (100) questionnaire forms were distributed and the data was analyzed using the (SPSS) program and the research hypotheses were tested, and the research concluded that there is a significant correlation between the dimensions of knowledge Sharing and career path development, and one of the most important conclusions reached by the research, knowledge sharing works to coordinate the various activities of the organization towards achieving its goals, enhancing its ability to maintain the individual's job performance and improving and his career path development based on experience and knowledge and creating value for the organization's work by knowledge sharing among employees.The research presented proposals, including the need to adopt knowledge sharing as a means to the career path development and improve job performance, through the skills and experiences that employees obtained from their knowledge sharing, which contributes to the completion of work and the achievement of the organization's goals.
Effects Of An Online Weight Management Program On Weight And Physical Activity Changes.

PURPOSE: To compare the effectiveness of an online weight management program through only online education(OO) or tailored video feedback with online education (OF) or control(CO). METHODS: This intervention included 60 overweight and obese Korean women aged 19 -39 years old. Participants are randomly allocated to one of three groups: (1) 20 women in OO group (online education video and self-monitoring application), (2) 20 women in OF group (online education video, self-monitoring application, and 1:1 tailored video feedback), and (3) 20 women in CO group (only self-monitoring application). Online education included nutrition, physical activity, psychological factors, and medical knowledge for weight loss, goal-setting, and cognitive/behavioral strategies. Tailored feedback helped to motivate weight loss and give solutions for weight loss through real-time video coaching once a week for 10 minutes per session. Effectiveness was assessed using repeated measure ANOVA to compare outcome changes between groups and Tukey’s post-hoc tests were performed. RESULTS: After 6-weeks, a total of 17(85%) of OO group, 17(85%) of OF group, and 19(95%) of CO group completed the post-measurement at 6 weeks. In the intention-to-treat analysis including all 60 participants, there was a significant difference in weight change at 6 weeks in OO and OF groups with a mean weight change of -0.86 kg (95%CI, -1.72 to -0.1) in OO group and -2.23 kg (95%CI, -2.93 to -1.52) in OF group, while no significant change was observed in CO group with a mean weight change of 0.08 kg (95%CI, -0.65 to 0.8). Changes in waist circumference were -2.29 cm (95% CI, -3.48 to -1.11) in OF group, -1.64 cm (95 CI, -3.14 to -0.09) in OO group, and 0.03 cm (95% CI, -1.05 to 1.11) in CO group. In the post-hoc analysis, there was a significant difference only between OF group and CO group in body weight and waist circumference (P > 0.001, P = 0.039, respectively). However, no significant group × time effects were found for the moderate to vigorous physical activity and sedentary behavior (P = 0.979, P = 0.578, respectively). CONCLUSION: Our online weight management program showed significant weight loss and waist circumference reduction in overweight or obese Korean women. Further research is needed to track the long term effects.
Aligning and extending technologies of parallel corpora for the Kazakh language

The paper presents the two-stage alignment and extending methods of parallel corpora for the Kazakh language. The Kazakh language is agglutinative with rich morphology and related to the Turkic language group. So, the traditional alignment methods for similar languages do not work for the Kazakh language. The alignment is used primarily to ensure that the fragment corresponding to the original is found in the translation. After that, identical fragments of parallel texts are compared with each other. At the initial stage, the question is what needs to be leveled. It is possible to align word by word, but this often becomes almost impossible for several reasons: sets of lexemes and expressions do not match in different languages. Considering the linguistic peculiarities of languages, the developed technologies and ways of universal alignment of parallel text may not work in languages with agglutination. It means that the form of the word is formed by additional affixes and auxiliary words that carry semantic and morphological information. The approach presented in this paper is to use a two-stage alignment, which uses a bilingual dictionary of synonyms. The evaluation with the use of the English-Kazakh corpus verifies that our method shows an average of 89 % correct alignment. The second method is designed to expand the parallel corpus due to the lack of natural parallel corpora of the Kazakh-English language pair with good quality. The developed method uses a combinatorial method taking into account the semantic and grammatical features of the Kazakh language. Different tenses of the Kazakh language are used for sentence generation, and different endings for parts of speech are also considered.
Impact of Science Teachers' Attitude on Academic Achievement of Students at Secondary Level in Lahore

The present study was designed to find out the effect of science teachers' attitudes on the academic performance of secondary graders. This study was quantitative in nature that employed a causal comparative research design. The tools used to measure the attitude of teachers was a questionnaire, while academic achievement was determined from the result of BISE. The data collection tool was validated by experts to check its validation, while the reliability of the tool was ensured by piloting it on 80 students. The final version of the questionnaire has a reliability value 0.83. for data collection, 700 teachers were sampled from the total population by using purposive sampling and a questionnaire was administered to them by the researchers personally. The results of the data show that the attitude of teachers are varied across different factors.
Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing Publishing. • Type of peer review: Double Anonymous • Conference submission management system: Morressier • Number of submissions received: 95 • Number of submissions sent for review: 54 • Number of submissions accepted: 12 • Acceptance Rate (Submissions Accepted / Submissions Received × 100): 12.6 • Average number of reviews per paper: 2 • Total number of reviewers involved: 10 • Contact person for queries: Name: Sidik Permana, Dr.Eng, M.Eng, S.Si(B.Sc) Email: psidik@itb.ac.id Affiliation: Faculty of Mathematics and Natural Sciences Bandung Institute of Technology Jl. Ganesha 10 Bandung 40132, INDONESIA Tel. +62-22-250-0834; Fax. +62-22-250-6452
Application of Distributed Database Technology in Data Center Construction of Oilfield

With the rapid development of traditional database, computer network and digital communication technology, people pay more and more attention to the research and development of distributed database system, which is characterized by distributed data storage and processing. Distributed database has the advantages of decentralized organization, load balancing, high reliability and excellent scalability. There are many datebase problems in oilfield enterprises, such as too many management organizations, complex data types, scattered data storage and difficult data sharing in various fields. These problems lead to the difficulty of data centralized storage and management, which is not conducive to data sharing and application. This paper describes the characteristics of Oracle database system, analyzes the distributed database technology and oilfield database status. It expounds the application of distributed database in the construction of oilfield data center from the aspects of database design, data storage, Oracle database synchronization technology, data synchronization design and implementation.
Review on Digital Currency

Nowadays, more and more banks and other financial service companies are promoting digital currency transfers and other online transactions, which are wire transfers or transfers between parties over long distances.Digital currency contributes to the globalization of the global economy because it is easier to trade by sending and receiving digital currency.[1] The Technology underlying Money continues to evolve, and many scholars and experts are concerned about the development of the digital currency.Through the research of domestic and foreign digital currency literature and related information, this article summarizes the concept, classification, characteristics and benefits, risks and potential problems of digital currency, and finally gives an overview of the development trend of digital currency.In a broad sense, digital currency is any form of money or payment that exists only in spreadsheets.And digital currency could be classified as cryptocurrency, virtual currency and central bank digital currency(CBDC).They are usually decentralized and anonymous.The features enhance the security of users.Digital currencies offer enhanced security, greater convenience and compatibility, making up for the drawbacks of cash.Market risks, security risks, law risks, bank risks and risks for producers are the main risks that digital currency brings.According to much research, CBDCs which can maximum to limit the risks of digital currency might be the main trends of digital currency's future.
Improvement of Body Image Flexibility in Adolescent Female Athletes Undergoing Education about Nutrition and Body Image

Methods: A pre-post study was done measuring body image flexibility in adolescent female athletes. Athletes, aged 14-18, participated in educational sessions about nutrition, body image flexibility, and RED-S (relative energy deficiency in sport). Body image flexibility was measured by the BI-AAQ (Body Image - Acceptance and Action Questionnaire).
Meta Q-network: a combination of reinforcement learning and meta learning

Deep reinforcement learning develops rapidly by using neural network to approximate the learning data of reinforcement learning, which makes the sequential decision in continuous space making achieve preliminary results. However, deep reinforcement learning is over-dependent on huge amount of training and requires accurate reward. For many problems in the real world, such as robot learning, there is generally no good reward and no unlimited training, which requires the ability to learn quickly. In this paper, we propose a deep reinforcement learning model with meta-learning, which we call meta Q-network (MQN). The model uses a LSTM-based meta-learner to update the Q-network. This optimises a series of problems such as the difficulty in stability of Q-network in deep reinforcement learning model, and we have proved this improved performance through experiments. It is not optimal, though, still the combination of meta-learning and reinforcement learning is very desirable.
Identifikasi Pola Penjualan Barang dalam Menjaga Stabilitas Stok Menggunakan Algoritma Fp- Growth

To take advantage of a very large collection of databases, a method or technique is needed that can convert a myriad of data into useful information, one of the data that can be processed is sales data at the Kamang Mart Mini Market. Kamang mart mini market is a mini market that will meet the needs of the community. As an effort to support efficient services, an orderly and thorough work procedure is needed so that it will produce fast, accurate and timely information according to the needs of consumers or the community. To facilitate the mini market in managing data, a system is needed that can produce a decision to find out which products are most in demand and needed by consumers and predict the level of stock availability. So that a lot of data can be used optimally so that later the goods needed by consumers can be fulfilled properly by the mini market and can increase sales at the Kamang Mart minimarket and can also reduce the accumulation of goods that are less desirable by consumers. The transaction data that will be processed in this study are as many as 20 transaction data. The transaction data will be examined using one of the Data Mining techniques by association rule using the Fp-Growth algorithm with a minimum support value of 30% and a confidence value of 70%. So that the pattern of product purchases is obtained which is used as information to predict the level of stock availability of goods. This research is very appropriate to be used by supermarkets in order to convey information more quickly and accurately so that sales levels are increased and well controlled.
TASK-BASED LANGUAGE TEACHING (TBLT) TO INCREASE ENGLISH SPEAKING SKILL OF INDONESIAN SECONDARY HIGH SCHOOL STUDENTS

The aim of this study is to investigate the benefits and challenges of Task-Based Language Teaching (TBLT) in the development of students’ speaking ability in Indonesian Secondary School Context. This study used comprehensive literature review from various sources. From the discussion, it is informed that TBLT is useful to increase English speaking competence of students. Firstly, TBLT is applicable to fosters students’ oral fluency. Secondly, TBLT can improves the speaking accuracy of students. Thirdly, TBLT helps students to enhance their speaking confidence. However, several challenges need to be addressed by the English teachers in order to use TBLT effectively. The finding of this study provides valuable literature for English teachers in Indonesia regarding the use (benefits and challenges) of TBLT to teach speaking skill.
Computer Vision for the Humanities: An Introduction to Deep Learning for Image Classification (Part 2)

This is the second of a two-part lesson introducing deep learning based computer vision methods for humanities research. This lesson digs deeper into the details of training a deep learning based computer vision model. It covers some challenges one may face due to the training data used and the importance of choosing an appropriate metric for your model. It presents some methods for evaluating the performance of a model.
Computer Vision for the Humanities: An Introduction to Deep Learning for Image Classification (Part 1)

This is the first of a two-part lesson introducing deep learning based computer vision methods for humanities research. Using a dataset of historical newspaper advertisements and the fastai Python library, the lesson walks through the pipeline of training a computer vision model to perform image classification.
Accuracy evaluation method of sports bracelet monitoring based on grey comprehensive clustering

In order to improve the accuracy and timeliness of evaluation results, this paper designed an accuracy evaluation method of sports bracelet monitoring based on grey comprehensive clustering. Firstly, the iterative algorithm is used to process the sports bracelet data to avoid the loss or abnormality of data affecting the quality of evaluation results and evaluation time. Then, a fuzzy comprehensive evaluation model is established to reflect the prominent influence of different evaluation indexes, and the relative membership degree of evaluation indexes is calculated. Finally, grey comprehensive clustering algorithm is used to optimise the fuzzy comprehensive evaluation model to complete the evaluation of the monitoring accuracy of the sports bracelet. Experimental results show that the maximum accuracy of this method can reach 83%, the minimum time is only 0.8 s, and the amount of data effectively processed reaches more than 1600 MB, which proves that the design expectation is effectively realised.
Cross Domain Evaluation of Text Detection Models

Text detection is a very common task across a wide range of domains, such as document image analysis, remote identity verification, amongst others. It is also considered an integral component of any text recognition system, where the performance of recognition tasks largely depends on the accuracy of the detection of text components. Various text detection models have been developed in the past decade. However, localizing text characters is still considered as one of the most challenging computer vision tasks within the text recognition task. Typical challenges include illumination, font types and sizes, languages, and many others. Furthermore, detection models are often evaluated using specific datasets without much work on cross-datasets and domain evaluation. In this paper, we present an experimental framework to evaluate the generalization capability of state-of-the-art text detection models across different application domains. Extensive experiments were carried using different established methods: EAST, CRAFT, Tessaract and Ensembles applied to various publicly available datasets. The generalisation performance of the models was evaluated and compared using precision, recall and F1-score. This paper opens a future direction in investigating ensemble models for text detection to improve generalisation.
ALEXNET ARCHITECTURE AND FUZZY ANALYSIS ON TALENT JUDGE DECISION PREDICTION BASED ON FACIAL EXPRESSION

The expression on the human face is a means of non-verbal communication. In the talent search event, the facial expressions shown by the judges when watching the participants' performances became one of the components to see whether the contestant who was performing could qualify for the next round or he would fail. Haar cascade is used to provide the location of the face in the frame and to classify the expressions on the face, a CNN model with modified AlexNet architecture is used which increases the accuracy by 5% from the original alexnet. A fuzzy Algorithm is used to predict the judge's decision based on how many facial expressions appear during the participant's appearance. The decision prediction system for talent search judges based on facial expressions using fuzzy is considered effective in predicting decisions, after being tested the system can predict decisions with an accuracy rate of 83%.
A Characteristic of Spontaneous Motor Tempo and Auditory-Motor Synchronization According to Dance Expertise

The purpose of this study is to examine the characteristics of the spontaneous motor tempo(SMT) of skilled dancers in the Korean traditional dance, who have been exposed and trained for a long time in Korean traditional music, compared to unskilled ones, and the effect of individual SMT when the movement is synchronized with the auditory stimulus. 34 volunteers, classified according to their dance expertise, participated. The experiment consisted of SMT task (Experiment 1) and an auditory-motor synchronization task (Experiment 2). The results are summarized as follows. First, average SMT of the skilled dancers was faster than that of the unskilled, despite having trained for a long time based on Korean traditional music composed mainly of relatively slow tempo. Second, individual SMT was effective in improving timing accuracy and reducing variability while performing auditory-motor synchronization. These results can be used as a basic data for developing and applying a training protocol that can increase the learning efficiency in dance, which requires the ability to accurately and stably synchronize intended body movements to the rhythm of music.