Reviewerly/exHarmony huggingface dataset:
A Comparative Analysis of the Genres in Korean Textbooks Using a Korean Analysis Tool

This study aimed to investigate the characteristics of three different genres, including argumentative, expository, and narrative texts that were selected from high school Korean textbooks revised by the 2015 National Curriculum with Auto-Kohesion, a Korean text analysis tool. The indices used for the current study included basic measures (the number of words, the number of sentences, the average sentence length, the average word length), word frequency (word frequency for contents words and all words), lexical diversity (type-token ratio for content words), personal pronouns (the first person pronouns, the second person pronouns, the third person pronouns, all pronouns), connectives (causal, additive, and all connectives), syntactic complexity (the ratio of modifiers, the ratio of constituents), and reference cohesion measures. The analysis demonstrated that the argumentative and expository texts were not significantly different in all measures. However, the differences between the two genres versus narratives were substantial; a greater use of personal pronouns and lower frequency words as well as more words and sentences was identified in the narrative texts, whereas the argumentative and expository texts included the higher text cohesion and the sentence constituent ratio along with the longer average words and sentences. The argumentative texts have been shown to include more personal pronouns than the other two genres. The current study provides some implications for designing Korean textbooks and analyzing the characteristics of different genres.
PENGUKURAN DEBIT AIR DAN MUATAN SUSPENSI DI SUB DAS BAKARANGAN DESA BAKARANGAN KECAMATAN KUSAN HULU KABUPATEN TANAH BUMBU KALIMANTAN SELATAN

Measurement of Water Debit and Suspension Load In Bakarangan Bakarangan Sub-Basin Sub-District Kusan Hulu District Tanah Bumbu Regency South Kalimantan. Guided by Prof. Dr. Ir. H.Muhammad Ruslan, M.S and Mr. Ir. Karta Sirang, M. O bjective of this research is to know the amount of water debit and the suspension load on Kusan River in Sub Das Bakarangan of Tanah Bumbu and Regency to know the relationship between water discharge and suspension load on Kusan river in Sub Das Bakarangan Tanah Bumbu Regency. The method used by measuring the water debit and the suspension charge of Sub Das Bakarangan, the data is processed and analyzed and then described. The result of this research is the biggest water discharge happened on October 5, 2017 equal to 4,715 m³ / sec with average water level 1.78 m while minimum water discharge happened on October 19, 2017 equal to 2,815 m³ / sec with average height water level 1.53 m. The largest suspended load occurred on October 12, 2017 of 0.255 gr / lt with a suspended charge discharge of 0.0748 tons / day. While the smallest loaded content contents occurred on November 9, 2017 of 0.100 gr / ltr with a discharge charge of 0.0251 ton / day. The regression equation produced between the water level (x) and the suspension charge (y) ie y = 5.8665x-5.7784 has a strong correlation (r) relationship of 0.7817. The regression equation produced between the water level and the suspended charge ie y = 0.0472x-0.0105 has a strong correlation (r) relationship of 0.0588. The regression equation generated between the water discharge (x) and the suspended charge discharge (y) ie y = 0.004x + 0.0733 has a strong correlation (r) relationship of 0.9134. Keywords: watershed; water discharge; suspension charge
Using Neural Networks and Diversifying Differential Evolution for Dynamic Optimisation

Dynamic optimisation occurs in a variety of real- world problems. To tackle these problems, evolutionary algorithms have been extensively used due to their effectiveness and minimum design effort. However, for dynamic problems, extra mechanisms are required on top of standard evolutionary algorithms. Among them, diversity mechanisms have proven to be competitive in handling dynamism, and recently, the use of neural networks have become popular for this purpose. Considering the complexity of using neural networks in the process compared to simple diversity mechanisms, we investigate whether they are competitive and the possibility of integrating them to improve the results. However, for a fair comparison, we need to consider the same time budget for each algorithm. Thus instead of the usual number of fitness evaluations as the measure for the available time between changes, we use wall clock timing. The results show the significance of the improvement when integrating the neural network and diversity mechanisms depends to the type and the frequency of changes. Moreover, we observe that for differential evolution, having a proper diversity in population when using neural network plays a key role in the neural network's ability to improve the results.
Parsing in the absence of related languages: Evaluating low-resource dependency parsers on Tagalog

Cross-lingual and multilingual methods have been widely suggested as options for dependency parsing of low-resource languages; however, these typically require the use of annotated data in related high-resource languages. In this paper, we evaluate the performance of these methods versus monolingual parsing of Tagalog, an Austronesian language which shares little typological similarity with any existing high-resource languages. We show that a monolingual model developed on minimal target language data consistently outperforms all cross-lingual and multilingual models when no closely-related sources exist for a low-resource language.
Linguistic proxies of readability: Comparing easy-to-read and regular newspaper Dutch

The aim of this study is to identify linguistic proxies of readability in Dutch, i.e. those linguistic features that define text as being easy-to-read. To this end, we compare the Wablieft corpus (Vandeghinste et al. 2019) (Flemish easy-to-read newspaper archives) to articles that appeared in the regular Flemish newspaper De Standaard, using a wide range of lexical, syntactic and readability metrics. We test which of these metrics has the highest effect size and which combinations of metrics work best in a classification task predicting whether articles belong to Wablieft or De Standaard. The results indicate that the best linguistic proxy for readability is (not surprisingly) the average number of words per sentence. Traditional reading metrics score well, although the combination of the parameters constituting these metrics score better in logistic regression than the original metrics.
Tangled Up in Books: Using the Lyrics of Bob Dylan to Understand the Changing Times of Collection Development

The lyrics of Bob Dylan can be an interesting way of understanding the changes that have occurred in academic libraries in the past 40 years.
Implementasi Metode Forward Chaining dalam Mengidentifikasi Kepribadian Siswa

Personality is the overall psychological and physical aspects of an individual reacting and interacting with other individuals. Personality is a prominent and often shown thing that exists in an individual. Students have different personalities, and that will affect the quality of learning. To be able to improve the quality of learning, schools need to identify and understand the personality of their students. So that appropriate learning methods can be applied and the selection of appropriate majors in tertiary institutions. To identify student personality can be done with a system called the expert system. The expert system identifies student personalities using the forward chaining method obtained from State High School 1 Candung students (SMAN 1 Candung), Agam Regency. In the forward chaining method, the reasoning process starts from the facts first to test the truth of the hypothesis. The process of finding the data starts from the premises to the final conclusion. Creating an expert system for identifying student personalities using the PHP Programming Language and MySQL Database. The result of testing this method is knowing the personality of students so that appropriate learning methods can be applied, majors recommendations and advice on the type of work according to the personality of the student. Personality expert system has been able to identify the personality of students in determining learning methods and choosing majors as well as suggestions for the type of work. Personality expert systems have been able to identify student personalities in determining learning methods and selection of majors as well as suggestions for types of work. This expert system is already running well and can be recommended to help students, teachers and schools in improving the quality of learning in schools
PENGARUH RATING REVIEW BELANJA DI SHOPEE TERHADAP MINAT BELI (Studi pada Mahasiswa Universitas Islam Negeri Raden Intan Lampung)

This study for find out what the impact of ratings and reviews on online shopping (shopee) by adding new a variable, namely buying interest. In t his study us ing quantitative research method (questionnaire) with 5 5 informant s collected from shopee users at UNIVERSITAS ISLAM NEGERI RADEN INTAN LAMPUNG with data analysis techniques using PLS. The results obtained from this study are that both ratings and reviews are proven to have an influence and some do not have a significant effect, therefore shopees must make ratings and reviews as one of the main marketing tools in order to increase the company ’s income . Keywords: rating, review, buying interest.
CORRELATIONAL STUDY BETWEEN STUDENTS’ HABIT OF LISTENING ENGLISH SONGS AND THEIR VOCABULARY MASTERY

ABSTRACTLestari, Ririn. 2020. 1616500061 : “ Correlational Study Between Students’ Habit of Listening English Songs and Their Vocabulary Mastery (A Study on The Fourth Semester Students of Pancasakti University Tegal in the Academic Year 2019/2020)”.Research Project. Strata I Program, Faculty of Teacher Training and Education, Pancasakti University Tegal, The First Advisor is Drs. H. Rofiudin,M.Hum and The Second Advisor is Dra. Hj. Sri Wardhani,Mpd.Key words : Students Habit of Listening English Songs, Their Vocabulary Mastery.The objective of this research is to know whether there is positive correlation between students habit in listening English songs and their vocabulary mastery. Listening to English songs is one of the way to learn vocabulary in fun way.The research hypothesis, proposed there is positive correlation between students habit in listening to English songs and their vocabulary mastery of the forth semester students of English Department of Pancasakti University in the Academic Year 2019/2020.In this research, the population is all of fourth semester students of English Department, Pancasakti University, which is totally 60 Students. The writer uses cluster random sampling technique in taking the sample of the research. The total of the sample is 30 students. The sample fill out a the questionnaire in google form after the writer has given the link by personal chat through whatsapp.This research can be categorized as Quantitative correlation study which studies the correlation between two or more variables. In this research, the researcher examined the relationship between two variable : independent variable (X) and dependent variable. The writer analysis data by using formula of correlation product moment, score of r-count is 0,710 while score of r-table at 5% level significance is 0,361. Thus, r-count is higher than r-table (0,710 > 0,361). According to result of the data, hypothesis H0 is rejected and hypothesis Ha is accepted. It means there is positive correlation between students habit listening English songs and their vocabulary mastery.
Optimalisasi Klasifikasi Kanker Payudara Menggunakan Forward Selection pada Naive Bayes

Breast cancer is a type of malignant tumor which is still the number one killer where the process of spread or metastasis takes a long time. The number of breast cancer sufferers increases every year so that if detected or caught early, prevention can be done early so as to reduce the number of breast cancer sufferers. To reduce the risk of increasing the number of cancer patients, it is necessary to do early detection, several methods can be used to assist the early detection process such as cancer screening, or computational methods. Several machine learning methods that have been chosen to solve cases of breast cancer prediction, especially the classification algorithm, including Naive Bayes have the advantage of being simple but having high accuracy even though they use little data. Weaknesses in Naive Bayes, namely the prediction of the probability result is not running optimally and the lack of selection of relevant features to the classification so that the accuracy is low. This research is intended to build a classification system for detecting breast cancer using the Naive Bayes method, by adding a forward selection method for feature selection from the many features that exist in breast cancer data, because not all features are features that can be used in the classification process. The result of combining the Naive Bayes method and the forward selection method in feature selection can increase the accuracy value of 96.49% detection of breast cancer patients.Â
Data-aware Low-Rank Compression for Large NLP Models

The representations learned by large-scale NLP models such as BERT have been widely used in various tasks. However, the increasing model size of the pre-trained models also brings the efficiency challenges, including the inference speed and the model size when deploying the model on devices. Specifically, most operations in BERT consist of matrix multiplications. These matrices are not low-rank and thus canonical matrix decomposition could not find an efficient approximation. In this paper, we observe that the learned representation of each layer lies in a low-dimensional space. Based on this observation, we propose DRONE (data-aware low-rank compression), a provably optimal low-rank decomposition of weight matrices, which has a simple closed form solution that can be efficiently computed. DRONE is generic, could be applied to both fully-connected and self-attention layers, and does not require any fine-tuning or distillation steps. Experimental results show that DRONE could improve both model size and inference speed with limited loss of accuracy. Specifically, DRONE alone achieves 1.92x faster on MRPC task with only 1.5%loss of accuracy, and when combined with distillation, DRONE achieves over 12.3x faster on various natural language inference tasks.
The Effect Of Model CRH By Board Reward On Student Learning Outcomes Of Class II In Elementary School

This study applies the model course review horay (CRH) with the help of media board reward on the theme of learning 6 caring for animals and plants in SDN Jatirejo. The method used is an experimental method in Pre-Experimental Design in the form of Intact-Group Comparison. The subjects of the study were of grade II SDN Jatirejo in academic year 2019/2020. Data collection through observation of learning activities and written tests to measure student learning outcomes before and after being given treatment. The results of data analysis using the t-test formula to determine the effect of treatment in the experimental and control groups. The results of the study using the model course review horay helped by the media reward board were more fun and students were actively learning so that the teacher easily delivered teaching material with a very good category namely the experimental group (11,843 ) &gt; the control group (11,655) which means that there is an influence on the use of the model course review horay with the help of media board reward in the experimental group is greater than conventional learning applied to the control group. The results of this study as a source of information input and consideration for institutions involved in learning theme 6 grade II elementary school.
Huffman coding and chains in partition lattices

The Huffman coding algorithm is interpreted in the context of the lattice of partitions of the source alphabet.Maximal chains in the partition lattice correspond to linear extensions of tree orders, and those among the chains that exhibit a simple greedy property correspond precisely to executions of the Huffman algorithm.Observation.There is a binary tree with terminal node set S such that there are two distinct j, k ∈ S with
EFISIENSI PENGEMBANGAN MEDIA PEMBELAJARAN TEMATIK SISWA KELAS II SEKOLAH DASAR DI SAMARINDA

This study aims to determine the results of the analysis of the needs of teachers and students, the results of field trials, and the effectiveness test so that they produce appropriate learning thematic teaching materials. This type of research is development research that refers to the ADDIE development model. The research data were obtained from the results of interviews, observation sheets, validation sheets of thematic learning teaching materials, teacher responses and test study results. The results of the assessment of the development of thematic teaching materials, validated by experts, obtained 90% of the very valid conversion results, the analysis of student learning outcomes after using the results of developing thematic teaching materials obtained 90.04% very effective categories. Thematic teaching materials developed by researchers use the ADDIE model that is feasible, effective and efficient to use in the learning process in elementary schools.
OPEN ELECTRONIC RESOURCES ON THE INTERNET AND THE FORMATION OF INFORMATION COMPETENCIES AMONG STUDENTS IN HIGHER EDUCATION

Currently, many world universities are trying to intensify and complicate the learning process, to enrich the educational environment.This is achieved by various methods: electronic textbooks and lecture courses from electronic libraries are used; teachers and students are connected in social networks and on specialized educational platforms (Moodle and others); tasks are performed on the basis of publications from the Internet.These activities allow to form skills at a higher level, both for educational and professional tasks: critical assessment of the content of information; the ability to isolate the main; to form a structure in information flows; apply data in accordance with the tasks to be solved; other (Korableva E.V., Muzychenko M.Ya., 2018, p. 27).The article discusses the results of an experiment to check the level of formation of some informational and related competencies among students.The second-year students were tested for the following skills: to determine the purpose of the educational task; offer the best source for its implementation; develop an algorithm for completing this task; to do practically work according to the model.The research was carried out in line with a new direction in pedagogical science -the concept of «Pedagogical Competenceology» (Grigoriev A.V., 2019).
Face Recognition Bot Using Deep Learning

Face recognition has remained as an interesting, ever ending and significant research topic due to its ever-increasing application in various fields. Face recognition bots have drastically decreased human intervention in human identity authentication. Face recognition bots are used in biometric authentication in cooperate offices, video surveillance, content-based data retrieval. And in various social media platforms.in face recognition bots using deep learning there is no human intervention due to which there is no unnecessary delays in processing the data.in this paper a simulated robot system is designed which can be used for fraud prevention, reduce shop lifting activities, criminal detection and reporting. This face recognition bot clicks the snaps of the people and checks the snap with its database to match the faces of the criminals thereby strengthening the security. In this paper, we proposed a multi-face structure for the identification that is extended to the embedded GPUScheme for real-time identification of multiple faces. The paradigm was trained by a network design that minimised the network parameter, and a monitoring technique has been applied to a parameter System to decrease the cycle time while preserving the method appropriate acceptance rate of recognition. Final experimental results showed that this proposed system recognized multiple faces up to 6 at the same time with up to 0.19 seconds of processing time.
Region-Based Space Filling Curve for Medical Image Scanning

A region-based space filling curve (RB) scanning method based on image segmentation and gradient vector flow (GVF) is presented. The proposed method extends the context-based space filling curve proposed in [1]. In this paper, the scanning path is guided by a preferred vector field which is constructed from the gradient vector field and enhanced by the GVF technique. The proposed method is compared with relevant scanning techniques. The study is important for image compression, pattern recognition, halftoning, and other applications in image processing.
PROBZI as an Innovative Learning Media in a Disruptive Era

The aim of the research is to develope PROBZI as an innovative learning media in disruptive era. This research was done in MTs Ma’arif Ambulu with the data colleting methode are interview, observation, documentation, test and questioner. And than the development model that used is ADDIE which cover analysis, design, development, implementation and evaluation. Based on the research that was done can be explained that PROBZI has been successfully developed as an alternative learning media in the disruptive era. PROBZI that has been developed can be said to be very feasible with an average percentage given a value of 90.40%. As for the more detailed value is given at 86.43% by the validator which includes material experts and media experts, then a value of 94.37% is given based on user responses that include teachers and students. Keywords: PROBZI, innovative learning media, disruptive
ANALISIS IMPLEMENTASI DATA INFORMASI GEOSPASIAL SEBAGAI UPAYA PENINGKATAN KEBUTUHAN PERLENGKAPAN JALAN DI DINAS PERHUBUNGAN KABUPATEN PROBOLINGGO

The purpose of this study was to find out more about how the human resources in the use of data and Geospatial Information in Probolinggo District Department of Transportation. This study uses descriptive analysis with qualitative approach, data collection techniques using the technique of the interview, observation and documentation study, primary data and secondary that was obtained in this research are collected through qualitative procedures that include reduction, and data verification or conclusion. The conclusion of this study is data about the equipment needs of a given path is not optimal due to the limited human resources and facilities are not optimal, such as the lack of application of the equipment needs of the road is used as a reference design of existing activity in Probolinggo District Department of Transportation. In addition, signs equipment on the road needs should be met as needed road because it is a very important instrument in planning towards road safety. Keywords: quality, data geospatial information
The Perception of Japanese Language Education Students About Microteaching

Microteaching is one of the subject matters to prepare student teachers. Many publications confirm the function and importance of microteaching in improving the student teachers’ teaching skills. However, publication on the perception of Japanese Language Education students about microteaching is still limited, despite its importance in guiding the students for better improvement. This study aimed at analyzing the students’ perception on the implementation of microteaching at the Japanese Language Education in a university in Bali on 2018. This study used qualitative research, and the data collected by questionnaire and interview. The results of the analysis showed that holistically, the students have postive perception and microteaching is perceived as very useful to improve the student teachers’ teaching skills. The instrumens used are not only relevant to assess the progress and the achievement of the student teachers but also can function as guideline for students on what to do in improving the teaching skills.