Reviewerly/exHarmony huggingface dataset:
Japanese-Russian TMU Neural Machine Translation System using Multilingual Model for WAT 2019

We introduce our system that is submitted to the News Commentary task (Japanese↔Russian) of the 6th Workshop on Asian Translation.The goal of this shared task is to study extremely low resource situations for distant language pairs.It is known that using parallel corpora of different language pair as training data is effective for multilingual neural machine translation model in extremely low resource scenarios.Therefore, to improve the translation quality of Japanese↔Russian language pair, our method leverages other in-domain Japanese-English and English-Russian parallel corpora as additional training data for our multilingual NMT model.
PENGEMBANGAN MEDIA SCRAPBOOK PADA KETERAMPILAN MENULIS SISWA KELAS IV SD MUHAMMADIYAH KARANGBENDO

This study aims to determine the procedure for developing scrapbook media on the writing skills of fourth grade elementary school students of fiction story material, as well as knowing the feasibility of scrapbook media on the writing skills of fourth grade elementary school students. This research is included in the research (R&amp;D) by using the ADDIE development model with the following stages 1) Analysis, 2) Design, 3) Development, 4) Implementation, 5) Evaluation. The subject of the trial was conducted by media experts, material experts, learning experts, students and teachers. Data collection is done by questionnaire, interview and documentation. Data analysis uses qualitative data analysis and quantitative data. The results of the study of the validation of 85% of media experts with excellent categories. the results of the validation of the material experts 89.6% with a very good category. The results of validation from learning experts 82.7% with very good category. The results of the teacher's response to the small group trial 95% with a very good category, student responses to the small group trial 94% with a very good category. The results of the teacher's response to the large group trial 95% with a very good category, student responses to the large group trial 96.8% with a very good category. The results showed that (1) the scrapbook learning media was produced in writing skills, (2) the results of the entire product trial were categorized very well with a score of 91.2. These results indicate that the scrapbook media is suitable for use in the learning process and supports students' writing skills.
IMPLEMENTASI BUDAYA LITERASI PADA KEMANDIRIAN PESERTA DIDIK DI SD MUHAMMADIYAH SERUT BANTUL

Literacy culture needs to be instilled early on, because it can foster students' interest in reading. Serut Muhammadiyah Elementary School is one of the schools implementing a literacy culture program. This study aims to explain the planning, implementation, evaluation of literacy culture programs at SD Muhammadiyah Serut, as well as describing the independence of students in literacy culture at SD Muhammadiyah Serut. This type of research uses descriptive research with a qualitative approach. The research subjects were school principals, class III teachers and class IV teachers, librarians, class III and IV students taken randomly. The objects in this study are all matters relating to the independence of students in literacy culture in SD Muhammadiyah Serut. Data collection techniques used include observation, interviews, and documentation. Data were analyzed using the Miles and Huberman models, while to test the validity of the data using source triangulation and technique triangulation. The results showed: that literacy program planning is related to the vision, mission and goals of the library, while the literacy culture has been running smoothly. Literacy cultural activities include reading iqra, reading Juz 'Amma, reading activities 15 minutes before the lesson begins, short story activities and bulletin classes. The next stage is the evaluation at Serut Muhammadiyah Elementary School conducted once a semester, to find out the extent of the literacy culture program. In the independence of students in the culture of literacy at Serut Muhammadiyah Elementary School as students do not read when the teacher does not ask. Then students are not confident when reading the results of their work.
Significant experience: academic writing and collaborative work in master of education

The following text narrates the academic writing experience of the collaboration of an academic team work, composed of Isabel Aristizabal, Mauricio Santa and Claudia Mesa as directed by Mercedes Vallejo, membership researcher in Virtual Environments for Education (VEE) Research Group, about the degree thesis of the “Master in Education, with focus in learning environments mediated by ICT” in Pontifical Bolivarian University of Medellin-Colombia, which is called “Effects on teacher's pedagogical practice that have developed significant experience with digital inclusion after receiving the award “Premio Ciudad de Medellín a la calidad de la Educación 2010-2013.”
Sistem Pendukung Keputusan Untuk Mendiagnosa Gizi Buruk Ibu Hamil Menggunakan Metode AHP

In searching and determining decisions can be done by many methods, one of them using the Analytical Hierarchy Process (AHP) method. Analytical Hierarchy Process (AHP) is a decision model developed to describe a complex multi-factor or multi-criteria problem into a representation of a complex problem in a multi-level structure where the first level is an objective, followed by a level of factors, criteria, sub-criteria and so on down to the last level of alternatives. Health is a state of well-being of the body, soul and social that enables everyone to live productively socially and economically. Health care efforts are by way of prevention and prevention of health problems that include examination, treatment and care including the development of pregnant women.
Combination, Pola, Apriori ANALISIS POLA BELANJA KONSUMEN MENGGUNAKAN ALGORITMA APRIORI PADA RAFFA PHOTOCOPY

Raffa Photocopy is a shop that started its business in 2016. This business not only provides photocopy services, but also provides office stationery and school supplies. Every day there are sales transactions where the recording of goods sold has a relationship between one another, because in recording sometimes consumers do not just buy one item, but two items even more as when buying a book, it is likely that consumers also buy a pen. This recording is only stored as an archive by Raffa Photocopy, even though the number of sales transactions that occur every day can lead to a pile of data. One effort to increase sales at Raffa Photocopy can be done by processing transaction data that overlaps by using data mining association techniques. This association rule technique uses the Apriori algorithm which deals with the study of 'what is with what' or discovers the association pattern of items that are often bought. The results of this study in the form of rules include the first, if you buy an eraser, it is likely that consumers also buy notebooks simultaneously. Second, if you buy Tipex, then consumers also buy a double folio. The results of the Apriori algorithm process are based on a minimum support value of 35% and a minimum confidence value of 80%.
MECHANISMS OF TRANSFER OF KNOWLEDGE AND COMPETENCE IN THE FIELD OF BIOENERGY: THE CASE OF BIO SIMULATOR

The lack of knowledge and competence in the field of bioenergy can create a significant barriers for innovation technology diffusion not only in industry itself, but also in strategy management.Overcoming such a "gap" in knowledge and competences requires the development and use of specialized transfer mechanisms.This paper examines the practice of using the online GIS simulator Bioenergy Simulator, developed by the International Renewable Energy Agency (IRENA).The simulator is included in the Global Atlas platform, which is the result of a larger-scale IRENA project to disseminate knowledge and competencies in the field of renewable energy, and involves the use of crowdsourcing technology for validation and further improvement.The practical oriented research on solving a specific scientific and practical problem using the Bioenergy Simulator has shown that the GIS simulator can be considered as a useful tool for transferring knowledge and competencies, primarily in the professional field.At the same time, in case of good translation of this GIS simulator into Russian and supplying it with the appropriate user guide, we can recommend to use the product by public administration in the processes of developing, adjusting and evaluating the effectiveness of regional and sectoral bioenergy development programs.
SelfieBot: A Robot to Detect, Photograph, and Tweet Smiles

SelfieBot is a robot that searches for a face to take a picture and post to a social media site.It is successfully outfitted with a Raspberry Pi, Camera, and Arduino.Using OpenCV library, SelfieBot recognizes faces.The SelfieBot detects smiling faces, takes photographs, and then uploads these pictures to Twitter.There are myriad things that can be done with an autonomous image-processing robot.We plan to use SelfieBot to recognize the faces of animals and take animal selfies in the future.
Indonesian-English Code-Switching in Gogirl! Magazine: Types and Features

&lt;p&gt;&lt;em&gt;&lt;span&gt;The present study investigates the types and features of Indonesian-English code switching in GoGirl! Magazine of March to May 2016 editions. Content analysis was employed in this study. The results of the analysis revealed that 1.355 cases of Indonesian-English code switching appeared in the magazines. The types of code-switching included alternation, insertion, and congruent lexicalization. The features of code switching in the magazines were several constituents, non-nested a b a, length and complexity, discourse particles and adverbs, peripherality, single constituent, nested a b a, content words, linear and structural equivalence, multi-constituent code-mixing, non-constituent mixing, and triggering. The researchers concluded that the mostly used type was alternation and non-nested a b a is the mostly used feature in GoGirl! Magazine.&lt;/span&gt;&lt;/em&gt;&lt;/p&gt;
Sundanese Speaking Test Model

This research focuses on the quality of speaking testing instruments for junior secondary students in West Bandung District.In general, the study aims at creating a model of Sundanese language speaking skills assessment which can provide information for schools in terms of contents, scope, delivery format and time, and can be effectively use Sundanese language teaching.Research and Development method is adopted to produce a model of classbased Indonesian language and literature learning assessment at the junior secondary level and a guide book of Sundanese language and literature assessment at this level.Statistical calculation of field tryout scores shows that speaking model is relevant to field data, namely, (P-value = 0, 72541 > 0,05; RMSEA = 0,000 < 0,05; GFI = 1,70 > 0,9; AGFI = 1,43 > 0,9; PGFI = 1,37 > 0,9) indicating that EPBI model is fit.The relevance of EPBI model and field data (P-value = 0, 72541 > 0,05; RMSEA = 0,000 < 0,05; GFI = 1,70 > 0,9; AGFI = 1,43 > 0,9; PGFI = 1,37 > 0,9) reveals that the quality of speaking testing model is fit is worth considering as an assessing instrument of junior secondary school speaking instruction as supported by theoretical concepts, expert judgment, and field tryout results., and judgment by experts, users, and practitioners shows that MPPBS model is reliable as a referred implementation model.Finally, school principals, Sundanese language teachers, schools, and District Office are recommended to apply the MPPBS Model in assessing the instructional processes of Sundanese language skills in West Bandung District.
СИСТЕМАТИЧНИЙ ПІДХІД ДО ПЕДАГОГІЧНОЇ ВЗАЄМОДІЇ В ОСВІТНІХ ВІЙСЬКОВИХ УСТАНОВАХ

The existing literature related with the problem has been scrutinized in the paper. The nature of pedagogical interaction has been clarified. The role of pedagogue-cadet relationships in shaping cadets’ and future officers’ personality has been brought to the fore and the systematic approach to pedagogical interactions has been delineated. The existing relationships between the communicative approach and other approaches have been identified.
KLASIFIKASI PENYAKIT PNEUMONIA MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK DENGAN OPTIMASI ADAPTIVE MOMENTUM

Pneumonia is an infection of the bacterium Streptococcus pneumoniae which causes inflammation in the air bag in one or both lungs. Pneumonia is a disease that can spread through the patient's air splashes. Pneumonia can be dangerous because it can cause death, therefore it is necessary to have early detection using chest radiograph images to determine the symptoms of pneumonia. Diagnosis using a chest radiograph image manually by medical personnel or a doctor requires a long time, even difficult to detect pneumonia disase. Convolutional neural network (CNN) is a deep learning method that adopts the performance of human brain neurons called neural network and convolution functions to classify images. CNN can also help classify pneumonia based on chest radiograph images. This study used data from Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images for Classification as many as 5860 images entered into two classes, namely normal and pneumonia, then 2400 data samples were taken using simple random sampling. This study uses adaptive momentum optimization (Adam) which serves to improve the accuracy of the model. Adam optimization is a development of existing optimizations such as Stochastic gradient descent (SGD), AdaGard, and RMSProp. The classification results of the models built were 99.98% for training data with 100 epochs, and accuracy in the test data was 78% which means that the model was able to qualify 78% of the test data into normal classes and pneumonia appropriately.
Measuring the effects of video streaming quality in Virtual Reality experience

In this paper we present a methodology of measuring Virtual Reality (VR) experience while simulating various video streaming conditions.For that, we used four different videos, a VR headset and a video editing software, where specific changes were made to video clips in order to make it feel a believable video streaming experience.Frames per second(fps), resolution and bitrate variables were manipulated to measure the changes in perception of video quality.While streaming videos these variables get affected by the quality of internet connection.Our objective was to simulate such a scenario, where an internet connection quality would vary throughout the duration of the whole video, during which we could measure subjective score of quality perception.
A High-Dimensional and Multi-granularity Feature Selection Method Based on CNN and RF

Feature engineering determines the upper limit of the performance of machine learning algorithm. And feature selection is the most critical step in feature engineering. However, the dimensional disasters are caused by high-dimensional and multi-granularity feature data, which makes effective feature selection very difficult. We propose a feature selection based on the Convolutional Neural Networks and Random Forest (FSCNNRF) for this issue. The model includes two parts, Feature Selection Convolutional Neural Networks (FSCNN) and Random Forest (RF). It can select more effective feature set by using FSCNN for dimensionality reduction and RF for feature selection. Firstly, the high-dimensional and multi-granularity feature data are subjected to dimensionality reduction processing by FSCNN, so that each feature becomes a single granularity feature. Then the RF is used to select valid features. Experiments show that the model has better effect on feature selection on high-dimensional and multi-granularity dataset and improves the performance of machine learning algorithms.
SISTEM INFORMASI DOSEN UNIKS ONLINE

Uniks is one of institute in Indonesia has around one hundred lecturers or educators. The educator is the pioneer in the university to do caturdharma Uniks and become measurement in assessment the performance of Uniks. Certainly, Uniks have to publish caturdharma activities from the lecturers, cause the society still unknown about the caturdharma activities. The aim of this research is to built the informations system of Uniks’ lecturers to publish all of the caturdharma activities.
Memetic Variable Clustering and Its Application

Clustering analysis is an important and difficult task in data mining and big data analysis. Although being a widely used clustering analysis technique, variable clustering did not get enough attention in previous studies. Inspired by the metaheuristic optimization techniques developed for clustering data items, we try to overcome the main shortcoming of k -means-based variable clustering algorithm, which is being sensitive to initial centroids by introducing the metaheuristic optimization. A novel memetic algorithm named MCLPSO (Memetic Comprehensive Learning Particle Swarm Optimization) based on CLPSO (Comprehensive Learning Particle Swarm Optimization) has been studied under the framework of memetic computing in our previous work. In this work, MCLPSO is used as a metaheuristic approach to improve the k -means-based variable clustering algorithm by adjusting the initial centroids iteratively to maximize the homogeneity of the clustering results. In MCLPSO, a chaotic local search operator is used and a simulated annealing- (SA-) based local search strategy is developed by combining the cognition-only PSO model with SA. The adaptive memetic strategy can enable the stagnant particles which cannot be improved by the comprehensive learning strategy to escape from the local optima and enable some elite particles to give fine-grained local search around the promising regions. The experimental result demonstrates a good performance of MCLPSO in optimizing the variable clustering criterion on several datasets compared with the original variable clustering method. Finally, for practical use, we also developed a web-based interactive software platform for the proposed approach and give a practical case study—analyzing the performance of semiconductor manufacturing system to demonstrate the usage.
Implementasi Algoritma Fuzzy C-Means dalam Mengelompokkan Kecamatan di Tana Luwu Berdasarkan Produktifitas Hasil Perkebunan

This study aims to classify sub-districts in Tana Luwu (Kabupaten Luwu, Luwu Timur, Luwu Utara, dan Palopo City ) using Fuzzy C-Means algorithm. The data used are data from BPS on the results of estate crops, namely coconut, oil palm, coffee, pepper, cocoa, clove, and land area. The results obtained from this study are from 45 sub-districts, there are 8 districts that are included into productive categories namely Burau, Sabbang, Mappedeceg, Baebunta, West Malangke, Sukamaju, Bone-Bone, and Tanalili. In addition, this study also found that matrix pseudo-partition selection can affect this algorithm in terms of the number of iterations produced.
A Fast-Efficient parallel processing algorithm for straight line detection

&lt;p&gt;This work presents a novel method for detecting straight lines in an image at a very high speed with optimum number of processors and their functionalities. The method can be used to extract straight lines directly from an image without noise removal and pre-processing. First the square image is converted to a binary edge image using a parallel edge detection mechanism. The parallel edge detection mechanism used in this work is capable of producing edge image within a short time. Then the binary square image is transferred to a system having large number of Processing Elements (PEs). A PE has only limited jobs such as pixel scanning, compare line length with nearby PEs and transmit data to the Main Control Unit (MCU). The MCU collects data from all PEs and evaluates straight lines. Even if the number of PEs is high, it is comparatively very much less than the parallel Hough Transform method and practically implementable using recent ULSI technologies.&lt;/p&gt;
Аналіз методів стиснення зображень на основі дискретно - косинусного перетворення

The article analyzes the methods of compressing dynamic images that have found the most practical application – JPEG, MPEG, DCT. The discrete - cosine transformation is considered as the most effective method for compressing redundant information. Compression in DCT is performed by quantizing the DCT coefficients, which were calculated using the input data. Quantization of DCT coefficients can significantly improve compression, and with a fairly small loss of data. You can also use these values to restore the original data. A primary purpose consists in being of optimal compromise between the high level of compression - quality of image without especially noticeable losses. Advantages and lacks of such methods: rounding of acute angles of image (casual «washing» out of sharp edges of images); a code is a very labour intensive process, only it was lately succeeded to carry out a code process programmatic, but not hardwarily; ДКП needs far less of mathematical operations, namely N of log (N), this property does ДКП a method that is used on the modern math processors of the personal computers.
Image tracking technology for dynamic angle measurement of machine vision

In order to realize high-precision measurement of spatial dynamic angle, a spatial dynamic angle measurement method based on machine vision is proposed. A high-precision two-axis servo system is installed onto the measured target. When the spatial angle of the measured target is changed, the servo system outputs the pitch angle and the azimuth angle by identifying and tracking the cooperative target。According to the spatial coordinate system transformation，the angle change value of the measured target can be obtained. The measurement accuracy of the spatial angle will be influenced by the accuracy of the tracking cooperative target with the servo system. A cross-patterned target board is designed based on the measured distance and the imaging system. Several major algorithms of detection are summarized. Their merits and demerits are analyzed by identifying and locating the center of captured image. The captured images are compared by the servo system controlled with these algorithms. The measurement results are solved by spatial coordinate transformation. According to the experimental results, a fast detection algorithm of target center in the real-time image processing is selected. High accuracy and good real-time performance of this method in processing the target image is demonstrated by calculating and comparing the results of each image processing algorithm, which satisfies the measured requirement of space dynamic angle.
HARDWARE IMPLEMENTATION OF AN ENCRYPTION FOR ENHANCEMENT DGHV

In constructing a secure and reliable cloud computing environment, a fully homomorphic encryption (FHE) scheme is conceived as a major cryptographic tool, as it enables arbitrary arithmetic evaluation of a cipher text without revealing the plaintext. However, due to very high of fully homomorphic encryption systems stays impractical and unfit for real-time applications One way to address this restriction is by using graphics processing unit (GPUs) and field programmable gate arrays (FPGAs) to produce homomorphic encryption schemes. This paper represents the hardware implementation of an encryption for enhancement van Dijk, Gentry, Halevi and Vaikuntanathan’s (DGHV) scheme over the integer (DGHV10) using FPGA technology for high speed computation and real time results. The proposed method was simulated via Vivado system generator tools. Then design systems of fully homomrphic encryption are implemented in an FPGA hardware successfully using NEXYS 4 DDR board with ARTIX 7 XC7A100T FPGA. The Experimental results show that the FPGA- based fully homomorphic encryption system is 63 times faster than the simulation based implementation.