Reviewerly/exHarmony huggingface dataset:
Multi-Granularity Contrasting for Cross-Lingual Pre-Training

Cross-lingual pre-training aims at providing effective prior representations for the inputs from multiple languages.With the modeling of bidirectional contexts, recently prevalent language modeling approaches such as XLM achieve better performance than traditional methods based on embedding alignment, which strives to assign similar vector representations to semantic-equivalent units.However, such approaches like XLM capture cross-lingual information based solely on shared BPE vocabulary, resulting in the absence of fine-grained supervision induced by embedding alignment.Inheriting the advantages of the above two paradigms, this work presents a multi-granularity contrasting framework, namely MGC, to learn languageuniversal representations.While predicting the masked words based on bidirectional contexts, the proposal also encodes semantic equivalents from different languages into similar representations to introduce more finegrained and explicit cross-lingual information.Two effective contrasting strategies are further proposed, which can be built upon semantic units of multiple granularities covering words, span, and sentences.Extensive experiments demonstrate that our approach can achieve significant performance gains in various downstream tasks, including machine translation and cross-lingual language understanding.
Studi Penilaian Kinerja Irigasi dan Angka Kebutuhan Nyata Operasi dan Pemeliharaan (AKNOP) pada Daerah Irigasi Sumber Mujur Kecamatan Candipuro Kabupaten Lumajang

The Sumber Mujur Irrigation Area is located in Candipuro District with the broncaptering as the main building which is located in Sumber Mujur Subdistrict. In fact, in this Irrigation Area, there are many damages and problems to the assets owned. From the results of the inventory carried out, there were 109 problem points. Damage and problems are found at six points in the main building, 30 points on the carrier channel, and 73 points on the building on the carrier channel. The performance index value of Sumber Mujur Irrigation Area got a score of 81.94% which consists of physical infrastructure is 33.9%, plant productivity is 14.5%, operation and management supporting facilities is 8.5%, personnel organization is 11.7%, documentation 4.18%, water user farmer association is 9.15%. The calculation of priority for rehabilitation in the Sumber Mujur Irrigation Area using the AHP and ANP method, the aspect that requires rehabilitation most is the Physical Infrastructure aspect of the Main Building aspect. For Real Cost Value of Maintaining and Operating Irrigation calculation (AKNOP) for the main building in the Sumber Mujur Irrigation Area, it was obtained IDR 574,871,655.00.
Pengembangan Modul Pembelajaran Tema Sistem Tata Surya Pada Siswa Kelas IV SDN Gedongombo 6 Kabupaten Tuban

The primary school learning process in implementing the 2013 curriculum is carried out in an integrated manner with the theme of linking between subjects so that it is expected to provide meaningful learning experiences for students. Teachers determine student success in learning so that superior human resources are created through the educational process. The module is a printed teaching material that teachers can use to present learning material. Therefore it is necessary to develop a learning module. The purpose of this development research was to determine the effectiveness of the module with the theme of the solar system, the sub-theme of the change in the appearance of celestial bodies in SDN Gedongombo 6, Kecamatan Semanding, Kabupaten Tuban in fourth grade students. The research procedure uses the Four-D model according to Thiagarajan. The data collection instrument for this module development research consists of an assessment instrument for the subject matter expert learning module, an assessment instrument for the linguist learning module, an assessment instrument for the learning module for media experts, and a student questionnaire. From the final results of module development that have been validated by experts, it is obtained data that the module in the content criteria has an SPV value of 85.94%. The assessment of the accuracy of the narrative language was 90.83% after a revision was made according to the suggested validation results. Evidence of the final test data using the module shows the achievement of KKM 75 by 21 students out of 25 students.
Hierarchical Negative Binomial Factorization for Recommender Systems on Implicit Feedback

When exposed to an item in a recommender system, a user may consume it (known as success exposure) or neglect it (known as failure exposure). The recently proposed methods that consider both success and failure exposure merely regard failure exposure as a constant prior, thus being capable of neither modeling various user behavior nor adapting to overdispersed data. In this paper, we propose a novel model, hierarchical negative binomial factorization, which models data dispersion via a hierarchical Bayesian structure, thus alleviating the effect of data overdispersion to help with performance gain for recommendation. Moreover, we factorize the dispersion of zero entries approximately into two low-rank matrices, thus reducing the updating time linear to the number of nonzero entries. The experiment shows that the proposed model outperforms state-of-the-art Poisson-based methods merely with a slight loss of inference speed.
A STEP TOWARDS THE MAJORITY-BASED CLUSTERING VALIDATION DECISION FUSION METHOD

A variety of clustering validation indices (CVIs) aimed at validating the results of clustering analysis and determining which clustering algorithm performs best. Different validation indices may be appropriate for different clustering algorithms or partition dissimilarity measures; however, the best suitable index to use in practice remains unknown. A single CVI is generally unable to handle the wide variability and scalability of the data and cope successfully with all the contexts. Therefore, one of the popular approaches is to use a combination of multiple CVIs and fuse their votes into the final decision. The aim of this work is to analyze the majority-based decision fusion method. Thus, the experimental work consisted of designing and implementing the NbClust majority-based decision fusion method and then evaluating the CVIs performance with different clustering algorithms and dissimilarity measures in order to discover the best validation configuration. Moreover, the author proposed to enhance the standard majority-based decision fusion method with straightforward rules for the maximum efficiency of the validation procedure. The result showed that the designed enhanced method with an invasive validation configuration could cope with almost all data sets (99%) with different experimental factors (density, dimensionality, number of clusters, etc.).
Sistem Pemantau Kondisi Lingkungan Pertanian Tanaman Pangan dengan NodeMCU ESP8266 dan Raspberry Pi Berbasis IoT

The increasing need for food is not in line with the clearing of agricultural land for food crops. So that the effort to increase the productivity of agricultural products is by applying precision agriculture. However, in reality, precision agriculture is difficult to apply to conventional processes, where farmers come to the farm, collect data, then carry out maintenance. This method will make production results not optimal because maintenance is not done accurately. This study introduces a monitoring system for environmental conditions based on the Internet of Things (IoT) for agricultural land, where trials are carried out in a greenhouse. The system that has been developed consists of several sensors designed to collect information related to agricultural environmental conditions, including DHT22 sensor (temperature and humidity), DS18B20 sensor (soil temperature), soil moisture sensor (moisture content in the soil), and BH1750 sensor (light intensity). Based on the Message Queuing Telemetry Transport (MQTT) protocol, the data is sent to a gateway (Raspberry Pi) and a local server via a wireless network to be stored in a database. By using the Node-RED Dashboard, the received sensor data is then displayed on the browser every time the sensor sends data. In addition, the local server also publishes sensor data to the public MQTT broker so that sensor data can be accessed through the MQTT Dashboard application on a smartphone. The results of testing for 25 days of the system running obtained an average success of the system in storing data of 99.64%.
Non-Criminalisation of Cyberstalking and Its Impact on Justice for Victims: Some Evidence from Malaysia

In the digital era, some real-world crimes have now transcended into cyberspace.Cybercrime such as cyberstalking is one of them and is considered as an emerging threat in Malaysia.Its prevalence in the reported statistics is merely a tip of an iceberg as many cases may not be reported.Cyberstalking may lead to a chain of psychological trauma and more severe crimes such as identity theft, rape, and even murder.However, despite its serious ramifications, the absence of any specific law to curb such criminality is regrettable and glaring in the Malaysian legal landscape.Hence, this paper aims at examining the technological and social factors contributing to such illegality, the rationales for the non-criminalisation and its implication for the victim's sense of justice.This paper adopts a qualitative methodology, of which the primary data is generated from semi-structured interviews with relevant respondents.The data triangulation is obtained from experts at two relevant ministries.The secondary data are the relevant cyber law, the Penal Code, books, academic journals, online databases and library-based sources.The findings revealed that the catalysts for cyberstalking are varied and that such crime has not been specifically criminalised in the Malaysian cyber laws or traditional legal framework.Such a legal lacuna calls into question not only the adequacy of the current law in dealing with such crime but also the availability of legal protection and nondenial of justice for cyberstalking victims as envisaged by the National Cyber Security Policy 2006 and the Sustainable Development Goals No.16.
Shape-based Feature Engineering for Solar Flare Prediction

Solar flares are caused by magnetic eruptions in active regions (ARs) on the surface of the sun. These events can have significant impacts on human activity, many of which can be mitigated with enough advance warning from good forecasts. To date, machine learning-based flare-prediction methods have employed physics-based attributes of the AR images as features; more recently, there has been some work that uses features deduced automatically by deep learning methods (such as convolutional neural networks). We describe a suite of novel shape-based features extracted from magnetogram images of the Sun using the tools of computational topology and computational geometry. We evaluate these features in the context of a multi-layer perceptron (MLP) neural network and compare their performance against the traditional physics-based attributes. We show that these abstract shape-based features outperform the features chosen by the human experts, and that a combination of the two feature sets improves the forecasting capability even further.
Bulut Tabanlı Bilgisayarlı Görü Kullanılarak Sesli Betimleme Sistem Tasarımı

Developments and changes in multimedia tools are actively used in many areas of life and bring a huge value to them. Nowadays, the concept of artificial intelligence is highly developed and there are hundreds of practices and methods to support the living standards especially for people with disabilities. The system developed in this study enables automatic visualization of the media output scenes such as movies, documentaries, etc., which are visually impaired people by means of computer vision technique, and the results are transferred to the users by voice command. HTML5 and CSS are used for visualizing the system, PHP and JAVASCRIPT are used for programming. MySQL is preferred as the database of the system. Computer vision, translation from text to speech and translation from one language to another are the main instruments used in this study. Cloud-based Microsoft AZURE Computer Vision API is used for computer vision, Javascript Responce.js library is used for text-to-speech translation, Google Cloud Text-To-Speech and Microsoft Azure Text to Speech APIs are used for translation from one language to another one.
On the Value of Penalties in Time-Inconsistent Planning

People tend to behave inconsistently over time due to an inherent present bias. As this may impair performance, social and economic settings need to be adapted accordingly. Common tools to reduce the impact of time-inconsistent behavior are penalties and prohibition. Such tools are called commitment devices. In recent work Kleinberg and Oren [6, 7] connect the design of prohibition-based commitment devices to a combinatorial problem in which edges are removed from a task graph G with n nodes. However, this problem is NP-hard to approximate within a ratio less than √n/3 [2]. To address this issue, we propose a penalty-based commitment device that does not delete edges but raises their cost. The benefits of our approach are twofold. On the conceptual side, we show that penalties are up to 1/β times more efficient than prohibition, where β ϵ (0,1] parameterizes the present bias. On the computational side, we significantly improve approximability by presenting a 2-approximation algorithm for allocating the penalties. To complement this result, we prove that optimal penalties are NP-hard to approximate within a ratio of 1.08192.
Student assessments of the higher education (on the example of the monitoring survey of the MPEI graduates)

The authors make an attempt of solving the task of providing the students with a possibility to assess the quality of the organization and content of the higher education. The authors consider the Russian and Western practices of engaging students in such assessing activities as one of their main actors. The article identifies the most common forms of student participation in ensuring the quality of education, some of its problem areas and unused resources. Thus, the basic form of student participation in evaluation and control activities in the university is to fill out various questionnaires in order to express their assessments and opinions about the courses taken during the training period. The authors considered some relevant practices of foreign and Russian universities, in particular, the experience of the RUDN University, North-Eastern Federal University, Institute of Quality Student Commissioners of the Kemerovo branch of the RSTEU, and the Center for Applied Sociological Research of the MPEI. The article presents the results of the sociological study of opinions and assessments of the MPEI graduates in technical and social-humanitarian areas, which was conducted in 2017-2019 on the issues of basic and professional training. The monitoring study revealed a number of factors that affect the quality of practical training at the university, which allowed the authors to identify the key problems of marketing educational services by the contemporary university and to show the need to study the issues of self-realization of graduates, their demand in the labor market, and to search for new criteria for assessing the quality of higher education. The authors believe that we need a new ideology of quality management in the higher education, and propose some conditions and measures that would ensure the high quality of the higher education in Russia.
Penerapan Model PBL dengan Metode Course Review Horay Berbantuan Media Crossword untuk Meningkatkan Aktivitas dan Hasil Belajar Siswa

Penelitian ini bertujuan untuk mengetahui penerapan model PBL dengan metode CRH berbantuan media crossword terhadap aktivitas dan hasil belajar IPA SMP. Penelitian ini merupakan jenis penelitian kuantitatif dengan metode penelitian, yaitu quasi experiment. Metode penelitian quasi experiment ini dilakukan pada kelas eksperimen dan kelas kontrol. Kelas eksperimen menggunakan penerapan model PBL dengan metode CRH berbantuan media crossword, sedangkan kelas kontrol menggunakan penerapan model PBL dengan metode ceramah. Teknik analisis data yang digunakan di antaranya adalah teknik analisis statistik Mann-Whitney untuk mengetahui aktivitas dan hasil belajar siswa. Berdasarkan hasil analisis data melalui instrumen penelitian berupa lembar pengamatan aktivitas belajar yang diperoleh, menunjukkan bahwa terdapat perbedaan aktivitas belajar siswa melalui penerapan model PBL dengan metode CRH berbantuan media crossword dan siswa melalui model PBL dengan metode ceramah, sedangkan untuk hasil belajar siswa melalui instrumen tes hasil belajar menunjukkan bahwa terdapat perbedaan hasil belajar antara kelas yang menggunakan model PBL dengan metode CRH berbantuan media crossword dan kelas yang menggunakan model PBL dengan metode ceramah.&#x0D; This study aims to determine the application of the PBL model with the CRH method assisted by crossword media to the activities and learning outcomes of junior high school science learning. This research is a type of quantitative research with a research method, namely a quasi-experiment. This quasi-experimental research method was carried out in the experimental class and the control class. The experimental class used the application of the PBL model with the CRH method assisted by crossword media while the control class used the application of the PBL model with the lecture method. The data analysis technique used includes the Mann-Whitney statistical analysis technique to determine student activity and learning outcomes. Based on the results of data analysis through research instruments in the form of observation sheets of learning activities obtained, it shows that there are differences in student learning activities through the application of the PBL model with the CRH method assisted by crossword media and students through the PBL model with the lecture method, while for student learning outcomes through the results test instrument learning shows that there are differences in learning outcomes between classes using the PBL model with the CRH method assisted by crossword media and the class using the PBL model with the lecture method.
PELAKSANAAN PEMBELAJARAN E-LEARNING PRODUK KREATIF DAN KEWIRAUSAHAAN KELAS XI SMK NEGERI 5 SUKOHARJO

E-learning during a pandemic is the best solution to support the learning process, but what about vocational students in implementing e-learning.This study aims to determine: (1) Implementation, (2) Supporting and inhibiting factors, and (3) solutions for inhibiting factors for the e-learning process at SMK N 5 Sukoharjo.This type of research is a descriptive study with a qualitative approach.This study used purposive sampling and snowball sampling techniques with the class XI PKKwu teacher as the key informant.Data collection techniques using interviews, observation, documents, and case studies.The data validity test used source triangulation and method triangulation.Data analysis techniques with data collection, data reduction, data presentation, and drawing conclusions.The results showed that: 1) The implementation of PKKwu e-learning at SMK N 5 Sukoharjo consisted of planning, implementation, and evaluating.Planning using face to face learning lesson plans due to the lack of preparation for online learning.The implementation of PKKwu e-learning learning is carried out through the Google Classroom, Edmodo, Email, Whatsapp application, resulting in less than optimal learning of PKKwu practices, the practice of making handsanitizer and disinfectants.Evaluation is done by assessing the timeliness of collection and the correctness of answering the assignment given.2) Supporting factors, namely the provision of credit subsidies and borrowing HP.Inhibiting factors are teacher lack of understanding of e-learning, unstable internet connection, lack of literature and official school learning media and students different economic levels.3) The solution to these obstacles is continued coordination with parents, the use of text and audio-based learning media to minimize quotas, develop school websites, and provide training on e-learning to teachers
Quality Assurance of Online and Distance Learning Education for SAARC Region during Covid-19 Situation

The outbreak of second wave of COVID-19 pandemic has again halted routine life of normal citizen across the globe. The nature always support the change for better future and covid-19 has provide chance to change challenges into opportunities. This study is sought to examine post Covid-19 effects on ICT infrastructure for e-learning education and its quality assurance mechanism in SAARC countries. This research is descriptive in nature and use comparative analysis of numerous challenges faced by SAARC member countries for implementation of E-learning. Challenges and limitation are also brush-up for further refinement in future in these areas. Future researchers may conduct survey techniques in explanatory research on implementation of ICT infrastructure of SAARC region countries. SAARC member countries may take lead from this study to address challenges and their solutions for development and implementation of E-learning.
Sistem Pakar Mendeteksi Malnutrisi pada Remaja dengan Metode Forward Chaining

Adolescence is a transitional period, where a teenager grows towards adulthood. What is meant by maturity is maturity in terms of emotions, ways of thinking and behaving. Currently, many things affect adolescent adolescence apart from the environment, as well as technological developments that make adolescents more negligent and forget about the tasks that have to be undertaken by adolescents. Technological developments have a very big influence on today's adolescents, apart from making them neglectful in carrying out their duties it also makes them neglectful in maintaining their health, especially physical health, where currently teenagers only focus on laptops and smartphones, while for nutrition they forget, so many teenagers today are experiencing malnutrition. This study aims to design an expert system that can help detect malnutrition in adolescents using the forward chaining method. This research is expected to help parents in tracking malnutrition in their teenagers.
Development of Augmented Reality Based Crawl Swimming Learning Module For Students of The UNU Blitar Sport Education Study Program

Swimming is a compulsory subject in the UNU Blitar Sports Education Study Program curriculum. Has a fairly high Semester Credit Unit (SKS) weight of 4 credits. The crawl style swimming is the basis of all styles so that it needs to be studied more deeply according to the era of the industrial revolution 4.0, namely with a touch of Augmented Reality (AR) technology. This study aims to develop a learning module for swimming crawl style which is integrated with Augmented Reality (AR). The method used by researchers is the Research and Development developed by Dick and Carey which consists of 10 steps. However, due to existing limitations, the researcher only carried out 9 steps. The module was validated by 3 experts, namely: media expert, learning expert, and swimming expert. The input from experts is used to complement the product. Subsequently carried out small group trials totaling 6 students while 30 students as large group trial subjects. The results obtained are: the criteria for product clarity obtained by a percentage of 91.17647% are very valid, the strategic criteria obtained by a percentage of 83.33% are quite valid, the evaluation criteria obtained by a presentation of 75% are quite valid. All criteria have met product eligibility. Product development of the module is declared valid enough and fit for use as a medium to maximize the learning process.