Reviewerly/exHarmony huggingface dataset:
Fine: The Paris Court of Appeal confirms most of the decision whereby the French Competition Authority sanctioned restrictions on online sales of chainsaws and brushcutters, while adopting a somewhat ambiguous positions on the principle of legitimate confidence (Stihl)

It is difficult to clear up the long ruling handed down on 17 October 2019 by the Paris Court of Appeal (also commented on in the 'Proceedings' column, below), which is the culmination of a case…
PENINGKATAN KETERAMPILAN MENULIS PUISI MENGGUNAKAN TEKNIK MIND MAPPING DI KELAS V SD.

Abstrak: Based on preliminary studies conducted in class V SDN 01 Koto Merapak. In indoensian language subjects, especially in writing poetry there are still many difficulties and obstacles faced by students. Students find it difficult to express their ideas in the form of poetry. This happens because the learning media used by educators is still less attractive to student, educators have not utilized the media as an object in writing poetry. This causes the skills of student in poetry to be low. The purpose of this study was to describe the improvement of poetry writing skills using the Mind Mapping technique in class V SDN 01 Koto Merapak. This study uses a qualitative and quantitative approach, with a type of classroom action research. This research was conducted in two cycles, with the stages of planning, implementing , observing and reflecting. This research was carried out inthe second semester of the 2018/2019 school year at SDN 01 Koto Merapak. With the subject of this research is the fifth grade students of SDN 01 Koto Merapak with a total of 32 student. While the research instruments are observation sheets, field note sheet test sheet, and documentation. The results showed that poetry writing skills using Mind Mapping techniques can improve poetry writing skills of students in SDN 01 SDN Koto Merapak. This can be seen from the result of the poetry writing ability in the first ccle of meeting I getting an average of 69.78% with the criterion (C), increasing in the first cycle of the first meeting obtaining an average of 74.12 % with the criteria of good (B), and increasing in the second cycle getting average –average 88.74% with very good criteria (SB). So based on the research above, that intellectual ability in writing poetry can increase using the Mind Mapping technique.
Teknologia berriak eta hizkuntza gutxituak: Ikt-en eragina euskaran

EnglishIT has come into our lives and has transformed it. Immersed in the digital information society of today, new technologies have also spread to minority languages, which have brought about obvious consequences for them. The first objective of this article is to analyse what kind of impact it has had. Likewise, with Basque as the object of study, to be exact, the other main objective of this work is to clarify the effects of IT on our language. To this end, the situation of Basque in several IT fields has been looked into. Finally, in reflecting on the results obtained, two of the aforementioned objectives are answered, and the main contribution of this article is a table entitled Resources influencing the IT development of minority languages. euskaraIKTak gure bizitzara iritsi dira eta hura zeharo eraldatu dute. Informazioaren gizarte digitalean murgilduta, teknologia berriak hizkuntza gutxituera ere hedatu dira, eta ondorio nabariak izan dituzte haiengan. Lan honen lehen helburua eragin hori nolakoa izan den aztertzea da. eta, era berean, zehazki euskara aztergai, lan honen beste helburu nagusia honako hau da: Iktek gure hizkuntzarengan izandako ondorioak argitzea. horretarako, euskararen egoera zenbait Ikt-esparrutan ikertu da. Azkenik, lortutako emaitzen inguruko hausnarketaren bidez, aipatutako bi helburuei erantzuna eman zaie, eta lan honek ekarpen nagusi duen “hizkuntza gutxituen Ikt-garapenean eragina duten baliabideak” deitutako taula proposatzen da
Cursive script identification using Gabor features and SVM classifier

Script identification is one of a challenging segment of optical character recognition system for the bilingual or multilingual document image. Significant research work has been noted on script identification in the last two decades which highly concentrated on natural languages like Latin, Chinese, Hindi, French and so forth. Very little efforts are made on script identification of cursive languages like Arabic, Urdu, Pashto, etc. Most of the Urdu ancient literature which is yet to be digitised includes both Urdu and Arabic text. In this paper, we present a script identification of Urdu and Arabic text at word level using Gabor features with suitable orientation and frequencies. The proposed model is trained using support vector machine (SVM) classifier and the results achieved are very promising.
Rancang Bangun Sistem Informasi Apotek Berbasis Client Server Pada Apotek An Nur Kotabumi

An Nur Kotabumi Pharmacy is one of the pharmacies that sell and have a large stock of medicines. All transactions that occur at the pharmacy are still recorded manually, namely by recording the transaction into a book. Some transactions carried out include drug sales transactions to consumers whether sales of prescriptions or non-prescriptions are still recorded manually in a book. Based on these problems, an application is needed to manage and process drug data so that the transaction process can be carried out properly. Applications that are used must also be computerized well in order to reduce errors in the transaction data collection process and can be used by many computers so that it is more effective when inputting drug data. This is because of the large number of drugs and transactions that occur, a well-integrated database is needed so that it will greatly support the performance of employees who interact directly with the system.
Turbulence Enrichment using Generative Adversarial Networks

Generative Adversarial Networks (GANs) have been widely used for generating photo-realistic images. A variant of GANs called super-resolution GAN (SRGAN) has already been used successfully for image super-resolution where low resolution images can be upsampled to a $4\times$ larger image that is perceptually more realistic. However, when such generative models are used for data describing physical processes, there are additional known constraints that models must satisfy including governing equations and boundary conditions. In general, these constraints may not be obeyed by the generated data. In this work, we develop physics-based methods for generative enrichment of turbulence. We incorporate a physics-informed learning approach by a modification to the loss function to minimize the residuals of the governing equations for the generated data. We have analyzed two trained physics-informed models: a supervised model based on convolutional neural networks (CNN) and a generative model based on SRGAN: Turbulence Enrichment GAN (TEGAN), and show that they both outperform simple bicubic interpolation in turbulence enrichment. We have also shown that using the physics-informed learning can also significantly improve the model's ability in generating data that satisfies the physical governing equations. Finally, we compare the enriched data from TEGAN to show that it is able to recover statistical metrics of the flow field including energy metrics and well as inter-scale energy dynamics and flow morphology.
A hybrid Feature Selection Approach for Arabic Handwritten Text Based on Genetic Algorithm and Support Vector Machine

Reducing features dimensionality in Arabic handwritten text recognition is a crucial issue, due to its impact on the overall recognition performance.In this paper, an Arabic handwritten text recognition model based on a hybrid feature-selection approach and Artificial Neural Network (ANN) classifier is proposed.The proposed feature selection approach mainly based on Genetic Algorithm (GA) and Support Vector Machine (SVM).By doing so, we aim to reduce the dimensionality of Arabic handwritten text features and optimize the recognition overall performances.The proposed based on GA-SVM approach was tested using the IFN/ENIT dataset.The results of the proposed features-selection are promising; since they reduce the number of tested features up to 78% by removing the irrelevant and redundant features.Using the ANN classifier, the proposed model reaches a 96.5% recognition rate, which supports its effectiveness in recognizing Arabic handwritten texts.
Implementasi Keamanan Pesan pada Citra Steganografi Menggunakan Modifikasi Cipher Block Chaining (CBC) Vigenere

Internet of Things (IoT) provides easy transportation of data and information, but on the other hand provides opportunities for cyber-terrorists and attackers to carry out attacks on data and information so that security of data and information is needed. This study aims to combine cryptographic techniques with classical algorithm that is Vigenere Cipher and modern algorithms that Cipher Block Chaining (CBC), which will be integrated with steganographic techniques Least Significant Bit (LSB) to insert the message information on an object image so as to provide data security and information more. It is expected to be able to support services in various fields so that digital watermarks on images can be used. Testing with 25 times the encryption and decryption process was successfully carried out 18 times and failed 7 times, influenced by the size and dimensions of the image. Performance on this algorithm is able to accommodate both symbols, characters and numbers. However, changes in image size affect the process of decryption and encryption. Abstrak: Internet of Things (IoT) menghadirkan kemudahan pertukaran data dan informasi, namun demikian di sisi lain memberikan peluang kepada cyber-terrorist dan penyerang untuk melakukan serangan terhadap data dan informasi sehingga pengamanan data dan informasi diperlukan. Penelitian ini bertujuan mengkombinasikan teknik kriptografi dengan algoritme klasik yaitu Vigenere Ciphe r dan algoritma modern yaitu Cipher Block Chaining (CBC) yang akan diintegrasikan dengan teknik steganografi Least Significant Bit (LSB) untuk menyisipkan pesan informasi di sebuah objek gambar sehingga memberikan keamanan data dan informasi yang lebih tinggi. Diharapkan mampu mendukung layanan berbagai bidang sehingga mampu digunakan digital watermark pada gambar. Hasil penelitian yang telah dilakukan menghasilkan visualisasi tidak adanya perbedaan pesan yang belum dan sudah terenkripsi. Pengujian dengan 25 kali proses enkripsi dan dekripsi berhasil dilakukan sebanyak 18 kali dan gagal sebanyak 7 kali, dipengaruhi oleh ukuran dan dimensi citra. Kinerja pada algoritma ini mampu menampung dengan baik simbol, karakter dan angka. Namun perubahan pada size gambar berpengaruh ketika proses dekripsi dan enkripsi. Normal 0 false false false IN ZH-CN AR-SA /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0cm; line-height:107%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-fareast-language:EN-US;}
HUBUNGAN PENGUASAAN KOSAKATA DAN KEBIASAAN MEMBACA DENGAN KETERAMPILAN MENULIS TEKS EKSPOSISI SISWA

This research is a correlation that aims to know (1) the correlation of vacabukary mastery with exposition text writing skills; (2) the correlation of reading habit with exposition text writing skills; (3) the correlation of vacabukary mastery and reading habit together with exposition text writing skills. The sample of this research are 128 students or 28% from 446 students, the total of population. The sampling technique that used is cluster random sampling. The data were collected using test method ang questionnaire. The rewuirements analysis that used is normality test. Meanwhile the data analysis that used are correlation (simple and double) and regression. The results of this study are: 1) positive and significant relationship of vocabulary mastery with the skills of writing exposition text shown with ry1 correlation coefficient of 0.45; 2) there is a positive and significant correlation of reading habits with expository text writing skills shown with ry2 correlation coefficient of 0.67;  3) there is a positive and significant relationship of mastery of vocabulary and reading habits together with the skills of writing expositional texts on the class students shown by the value of Ry.12 of 0.73 and the coefficient of determination of 0.53. Thus X1 Mastery of Vocabulary and X2 Reading Habits together contributes 53% to the skill of writing exposition texts
Precise Quantum Simulations with Optical Lattices

We present an efficient approach to precisely simulate tight binding models with optical lattices, based on programmable digital-micromirror-device (DMD) techniques. Our approach consists of a subroutine of Wegner-flow enabled precise extraction of a tight-binding model for a given optical potential, and a reverse engineering step of adjusting the potential for a targeting model, for both of which we develop classical algorithms to achieve high precision and high efficiency. With renormalization of Wannier functions and high band effects systematically calibrated in our protocol, we show the tight-binding models with programmable onsite energies and tunnelings can be precisely simulated with optical lattices integrated with the DMD techniques. With numerical simulation, we demonstrate that our approach would facilitate quantum simulation of localization physics with unprecedented programmability and atom-based boson sampling for illustration of quantum computational advantage. We expect this approach would pave a way towards large-scale and precise programmable quantum simulations based on optical lattices.
Document Length Variation in the Vector Space Clustering of News in Arabic: A Comparison of Methods

This article is concerned with addressing the effect of document length variation on measuring the semantic similarity in the text clustering of news in Arabic.Despite the development of different approaches for addressing the issue, there is no one strong conclusion recommending one approach.Furthermore, many of these have not been tested for the clustering of news in Arabic.The problem is that different length normalization methods can yield different analyses of the same data set, and that there is no obvious way of selecting the best one.The choice of an inappropriate method, however, has negative impacts on the accuracy and thus the reliability of clustering performance.Given the lack of agreement and disparity of opinions, we set out to comprehensively evaluate the existing normalization techniques to prove empirically which one is the best for the normalization of text length to improve the text clustering performance of news in Arabic.For this purpose, a corpus of 693 stories representing different categories and of different lengths is designed.Data is analyzed using different document length normalization methods along with vector space clustering (VSC), and then the analysis on which the clustering structure agrees most closely with the bibliographic information of the news stories is selected.The analysis of the data indicates that the clustering structure based on the byte length normalization method is the most accurate one.One main problem, however, with this method is that the lexical variables within the data set are not ranked which makes it difficult for retaining only the most distinctive lexical features for generating clustering structures based on semantic similarity.As thus, the study proposes the integration of TF-IDF for ranking the words within all the documents so that only those with the highest TF-IDF values are retained.It can be finally concluded that the proposed model proved effective in improving the function of the byte normalization method and thus on the performance and reliability of news clustering in Arabic.The findings of the study can also be extended to IR applications in Arabic.The proposed model can be usefully used in supporting the performance of the retrieval systems of Arabic in finding the most relevant documents for a given query based on semantic similarity, not document length.
Efficient Estimation of Interval-Valued Symbolic Data Regression Model

In the last two decades, regression analysis with interval-valued type data has received more and more attention. For the interval-valued symbolic data regression, the Minmax method and the center and range (CR) method are two widely used popular estimating approaches. In this paper, to improve the estimating eciency of these two estimating methods, seemingly unrelated regression approach has been applied to take account of the dependence information of two regression models of the Minmax method or the CR method. Finally, real data sets are analysed to examine the performance of our proposed procedure.
HUBUNGAN MOTIVASI BELAJAR DENGAN KETERAMPILAN MENULIS PUISI SISWA KELAS VIII SMP NEGERI 2 KECAMATAN SULIKI GUNUNG MAS

This research is motivated by several problems, namely (1) student learning motivation VIII SMP Negeri 2 Kecamatan Suliki Gunung Mas, (2) Students consider writing poetry is difficult and students do not pay attention to elements that build poetry, (3) motivation learning relationship with Poetry writing skills. The purpose of this study is, (1) to describe the students 'learning motivation, (2) to describe the students' poetry writing skills from the aspects of diction, image, and (3) to describe the relationship of learning motivation with students poetry writing skill.This research type is quantitative by using correlation method. The population in this study is the students of SMP Negeri 2 Kecamatan Suliki Gunung Mas amounted to 130 people consisting of 5 classes. Determination of the sample is done by cluster random sampling or randomly, then selected class VIII.3 which amounted to 26 students. Variables in this study is the motivation to learn as the variable X and skills of writing poetry as a variable Y. The instrument of this study is to distribute questionnaires and performance tests.Based on the results of the study can be concluded that the average value of learning motivation in general is 85 with good qualifications and the value of poetry writing skills is 80,23 with good qualifications. Furthermore, the correlation test using the moment product formula, obtained rhitung 0.1056, obtained t count 5,488 with degrees of freedom n-2 (26-2 = 24), and a significant level of 0.05. Hypothesis accepted if t count> t table. Thus H1 is accepted because the test results prove that t count is bigger than ttable that is 5,488 > 1,711. It can be concluded that there is a significant relationship between learning motivation and the skill of writing poetry of class VIII SMP Negeri 2 Suliki Gunung Mas. Kata kunci: motivasi belajar, keterampilan menulis, menulis puisi.
The Practice of the Training on Stress Tolerance Increase of Ukrainian Students in the Sphere of Legal Education

The new national curriculum implementation in the sphere of higher education in Ukraine raises the need for using tests as the means of students’ knowledge assessment. The authors have identified the connection both between the level of stress tolerance and between the level of test passing by means of using the correlated analysis, the Kolmogorov-Smirnov test and the T-Wilcoxon test. The level of stress tolerance has a serious impact upon the students’ test result. The students show a higher efficiency level while passing the test after visiting the training on stress tolerance increase. It has been identified that the opportunity value as to how to focus the students’ attention on the test is an important harbinger of the thesis that the education of Ukrainian students should be followed by the assessment of their psychological state. The authors have identified that the students’ psychological architype has an impact upon the education efficiency giving both similar and best results according to the results from other cultures.
Effectiveness of the Application Clonezilla to Clone Image with Ubuntu Server 12.04 and Samba Server

The computers owned by Fasilkom more than 30-45 computers are available in six classes. It is considered to be less effective considering by Fasilkom laboratory staff and must clone around 208 computers. So from the results of the analysis, a method was made to measure the effectiveness of installing a computer using a computer network with the Clonezilla application, Ubuntu 12.04, and the samba server. The standard parameters of ISO 9126 namely time, number of computers, costs, laboratory performance, and utilization. The process of resizing the master clone image still has a disadvantage in terms of the transfer rate were to restore the image clone will take four hours to ten computers, but from the work side during the process carried out the laboratory staff can still do other work without having to wait for the cloning process to finish.
JADU partners with Hyland combining content services, accessible web portal and responsive eforms to improve customer experience

JADU, a web experience management software provider with prominence across Government, Higher Education and Commercial organizations, has partnered with Hyland, a leading content services provider.
Action rules for sentiment analysis using Twitter

Actionable patterns are interesting and usable knowledge mined from large datasets. Action rules are rules that describe the possible transition of objects from one state to another with respect to a decision attribute. In this work, we extract actionable recommendations in the form of action rules, that can be applied to social networking data in a scalable manner to achieve the desired user goals. We propose extraction of actionable patterns based on sentiment analysis of social network data. In sentiment analysis there are two approaches to determine the polarity: Corpus-based, and Lexicon-based. We use corpus-based sentiment analysis approach, where sentiment values are generated based on sentence structure rather than words. Results show actionable patterns in tweet data and provide suggestions on how to change sentiment of the tweet to a more positive one. The experiment is performed with Twitter data in a distributed environment using Hadoop MapReduce for scalability with large data.
블록체인 기술과 빅데이터 기술을 적용한 안전 관리 시스템의 필요성

In this study, the study was conducted to derive the utility of the safety management system applying block chain technology and big data technology to improve the problems of construction sites where concealment and operation of safety accidents occur. If block chain technology and big data technology are applied to construction safety management, transparent data can be collected, and based on the collected data, it is possible to predict accidents that can occur at the construction site and establish countermeasures. It can also be an opportunity to strengthen the safety awareness of construction workers and managers, and can clearly identify the responsibility in the event of a safety accident. This study suggests that the application of the 4th Industrial Revolution technology could be a great opportunity to innovate the construction industry which is less than other industries.