Reviewerly/exHarmony huggingface dataset:
PENINGKATAN SELF CONFIDENCE DAN HASIL BELAJAR TEMA SELAMATKAN MAKHLUK HIDUP DENGAN TEKNIK CALL ON THE NEXT SPEAKER PADA SISWA KELAS VI MI AL-IMAN TAHUN PELAJARAN 2019/2020

This research was conducted with the aim to: 1) Describe how to improve self-confidence and learning outcomes of the 6th graders of MI Al-Iman Magelang City with the technique of Call On the Next Speaker. 2) Increase the confidence of the 6th graders of MI Al-Iman students with the Call On The Next Speaker learning technique. 3) Improve the learning outcomes of the theme Save Sentient Beings to the 6th graders of MI Al-Faith with the learning technique of Call On The Next Speaker. This research uses classroom action research (two action research classes). Each cycle is held three times. Each cycle consists of four steps; planning, implementing actions, observing and reflecting. The participants of this study were the 6th graders of MI AL-Iman Magelang academic year 2019/2020. The data obtained consisted of formative test results, observation sheets of teaching and learning activities. From the results of the analysis obtained, the completeness of student learning increased from pre-cycle, cycle I and cycle II, namely pre cycle with an average value of 68 and students who completed 40%, cycle I with an average value of 78 and students who completed by 73%, and cycle II with an average value of 85 and students who completed 100%. While the assessment results obtained student confidence increased from precycle of 20% from 15 students confident when expressing opinions and in the first cycle increased to 60%. then the cycle II increases to 80%. The conclusion of this research is Call Learning Techniques on Speakers Furthermore can improve self-confidence and learning outcomes in the theme of Save Sentient Beings to the 6th graders of MI Al-Iman acadeic year 2019/2020.
Analysis of the principle and test quality on real-time photoelastic stress monitoring of borosilicate glass cold bending molding

Glass bending is an important process in glass device manufacturing, and real-time stress detection is essential for regulating bending mold pressure. A three-point bending experiment is used to simulate the glass cold bending forming process, and the feasibility of the photoelastic method to detect the real-time bending stress in the pure cold bending state is analyzed. The conventional division-of-amplitude polarimeter is optimized to obtain a smaller spot diameter, fewer system conditions, and a wider stress detection range. The Stokes parameter error of the optimized system is 0.05, and the optical path difference measurement accuracy is 4.284 nm. The test quality of the photoelastic stress detection system during the three-point bending was not affected by the glass size or bending span. However, the various curvatures of the incident surface were found to cause different stress values in unloaded glass and fluctuations in y-values (the distance from the test beam to the neutral surface of the glass) to occur outside the normal range. The less the curvature of the glass is, the closer it is to normal incidence, and the more accurate the stress value is. After the heat treatment of the borosilicate glass, the experimental results show that the isotropic structure of the glass does not change significantly. The exploration of testing quality of bending stress provides an effective reference for practical high-precision bending glass manufacturing.
Pelatihan Pengembangan Sumber Daya Manusia (SDM) Melalui Peran Komunitas Jendela Literasi (Jeli) Dalam Meningkatkan Soft Dan Hard Skill Di Kelurahan Penaraga Kecamatan Raba Kota Bima

Bima City as one of the autonomous regions in its development began to establish a non-formal education center in Bima City. The scope and variety of current activities ranging from Life Skills (Education to Life Skills) and courses, so today's educational activities cannot be underestimated, which for some people is considered only oriented to awarding equality certificates to people who do not have time or are forced to leave formal education bench. The methods for implementing these activities include: varied lectures, demonstrations, and exercises.The results of this training will be useful for community members, the teaching and learning process will be more interesting with the use of more varied learning media. In addition, the existence of community member development training through institutional strengthening will increase the skills of community members in developing creativity so that it will support and create superior members so that they are able to create ideas and innovations in the era of global competition as it is today.
Pengembangan Lembar Kerja Peserta Didik (LKPD) Materi Bentuk Aljabar Berbasis Literasi Dalam Pembelajaran Daring Terhadap Kemandirian Belajar Siswa

In research on the development of literacy-based student worksheets, it aims to find out/see the quality/quality of student worksheets as teaching materials/learning media. The type of research used is the ADDIE development model, namely analysis, design, development, implementation and evaluation. However, this research is limited to the third stage, namely the development stage. This research activity was conducted at MTs Al-Azhar Bulu Cina school. The research instrument used was a validity questionnaire, the practical sheet of the subject teacher's response questionnaire that was given aimed at seeing the results of the developed student worksheets and the questionnaire used to see student responses aimed at seeing student responses to the developed teaching materials. The results of data analysis in product development are 3, namely: The results of the validation of the literacy-based LKPD were assessed by two mathematicians who produced a total score of 163 with a very valid category in product development, The results of the assessment sheet conducted by the teacher obtained a total score of 39 with a very category Practically, the results of the assessment of student responses with the number of participants as many as 25 people to the literacy-based LKPD developed obtained a percentage of 80% with a strong category. Student worksheets/teaching materials designed/developed using this research obtained good quality products and for learning media/teaching materials in schools
Pengaruh Interaksi Sosial Teman Sebaya Terhadap Tingkah Laku Salah Suai Peserta Didik di Kelas XI IPS SMAN 2 Tebo

The purpose of this study is to know the students' learning difficulties by grade VI students. The research approach used is qualitative approach. The subject of this research is the students of grade VI State Elementary School 14 Ulakan Tapakis. Key informant in this research is class VI teacher, while the next informant is grade VI student which is taken based on the suggestion of key informant. Data collection techniques used interviews, and documentation, while to test the validity of data used triangulation technique. Based on the result of the research are students' learning difficulties are caused by internal and external factors. The interent factor is a factor from the students themselves; they are cognitive, effective, psychotic. and external factors, namely those that arise from outside the learner's self, such as the family environment, village/community environment. The efforts that can be use by teachers in overcoming the learning difficulties of class VI students at SDN 14 Ulakan Tapakis are given tasks or instructions in detail, teach the main idea of the lesson, provide physical contact/reword..
PENERAPAN GRAMMAR TRANSLATION METHOD (GTM) DALAM MENINGKATKAN WRITING SKILL (WS) DAN SELF-DEVELOPMENT (SD) SISWA MADRASAH ALIYAH (MA) NW MENGKURU

This study aimed at finding out the improving of writing skill (WS) and self-development (SD) students of MA by applying the Grammar Translation Method (GTM). This research is qualitative research. The research was conducted at Madrasah Aliyah (MA) NW Mengkuru, East Lombok, NTB. The data of this research collected through test and non-test. Based on the results of test and data analysis it can be concluded that the ability of students in improving writing skills using grammar translation method is very effective and needs to be applied and developed. The application of grammar translation method can improve students’ writing skills and self-development.&#x0D;
Adaptive Partitioning for Large-Scale Graph Analytics in Geo-Distributed Data Centers

Graph partitioning is an important problem to the performance and cost optimization of graph analytics in geo-distributed environments. Modern hybrid-cut model is expected to obtain better performance and cost optimizations than traditional partitioning models, but can further complicate geo-distributed graph partitioning which is already a challenging problem due to large graph sizes and network heterogeneities of geo-distributed DCs. Existing studies usually adopt heuristic-based methods to achieve fast partitioning for large graphs, which unfortunately sacrifices optimization effectiveness. Further, graph structures of many applications can change at various frequencies. Dynamic partitioning methods usually focus on achieving low latency to quickly adapt to changes, which may again sacrifice partitioning effectiveness. Also, such methods are not aware of the dynamicity of graphs and can over sacrifice effectiveness for unnecessarily low latency. In this paper, we propose RLCut, which uses Reinforcement Learning (RL) to help taming the complexity of the problem. Specifically, RLCut uses multi-agent learning which is more efficient than single agent RL and incorporates a sampling based optimization to adaptively control the training process to satisfy required trade-off between partitioning effectiveness and efficiency according to graph dynamicity. Experiments using real cloud DCs and real-world graphs show that, compared to state-of-the-art static partitioning methods, RLCut improves the performance of geo-distributed graph analytics by 10%-100% with comparable overhead. When users tolerate longer partitioning overhead, we can further improve the performance by up to 43%. With varying graph changing frequencies, RLCut can improve the performance by up to 60% compared to state-of-the-art dynamic partitioning.
Analysis of words in passwords from three different countries

Previous studies have shown that the passwords set by users in different countries are related to their language and culture. This paper introduces a method of analyzing features of words in passwords based on corpora. The first step is constructing specific corpora, mainly including: collecting raw corpora, converting non-English words in raw corpora into ASCII strings, setting the priority of different corpora, and finally combining them according to the priority to build specific corpora. Based on corpus, the frequency of different sense-group in password can be evaluated by the coverage of corpora or a sense-group. According the above methods, the corpora of General Purpose, English, Russian, Japanese and Vietnamese are collected, and the features of words in passwords from Russia, Japan and Vietnam are analyzed. Recovering these features is of great significance to improve the strength of user password.
Data security sharing and interaction method of regulation system based on blockchain

In this paper, we analyze the business characteristics of regulation data in order to meet the application requirements of safe data storage and sharing interaction in the field of regulation and control. At the same time, we combine the characteristics of blockchain data storage, and propose a data sharing and interaction method based on blockchain regulation business, design the overall storage architecture of on-chain and off-chain data, and the smart contract interface for data interaction. Finally, the interaction process realizes the safe sharing and interaction of regulation data, and the performance of different smart contract interfaces is analyzed statistically and comparatively.
Federated Semi-Supervised Classification of Multimedia Flows for 3D Networks

Automatic traffic classification is increasingly becoming important in traffic engineering, as the current trend of encrypting transport information (e.g., behind HTTP-encrypted tunnels) prevents intermediate nodes from accessing end-to-end packet headers. However, this information is crucial for traffic shaping, network slicing, and Quality of Service (QoS) management, for preventing network intrusion, and for anomaly detection. 3D networks offer multiple routes that can guarantee different levels of QoS. Therefore, service classification and separation are essential to guarantee the required QoS level to each traffic sub-flow through the appropriate network trunk. In this paper, a federated feature selection and feature reduction learning scheme is proposed to classify network traffic in a semi-supervised cooperative manner. The federated gateways of 3D network help to enhance the global knowledge of network traffic to improve the accuracy of anomaly and intrusion detection and service identification of a new traffic flow.
Evaluation of Fully Convolutional One-Stage Object Detection for Drone Detection

In this paper, we present our approach for drone detection which we submitted for the Drone-Vs-Bird Detection Challenge. In our work, we used the Fully Convolutional One-Stage Object Detection (FCOS) approach tuned to detect drones. Throughout our experiments, we opted for a simple data augmentation technique to reduce the amount of False Positives (FPs). Upon observing the results of our early experiments, our technique for data augmentation incorporates adding extra samples to the training sets including the object which generated the most number of FPs, namely other flying objects, leaves and objects with sharp edges. With the newly introduced data to the training set, our results for drone detection on the validation set are as follows: AP scores of 0.16, 0.34 and 0.65 for small-sized, medium-sized and large drones respectively.
Compounding Is Semantics-driven in Chinese

Current studies of semantic word formation of Chinese compounds aim to work out collocational patterns and semantic patterns. In addition to investigating the surface semantic relations among the composing morphemes of compound words, researchers adopt the methods of semantic-syntactic analyses of sentences and study the predicative relation among the composing morphemes. Rather than introducing argument structure, it might be better to make use of qualia structure to analyze the semantic structure of nominal compounds.
SPARQL Generation with an NMT-based Approach

SPARQL is a powerful query language which has been widely used in various natural language question answering (QA) systems. As the advances of deep neural networks, Neural Machine Translation (NMT) models are employed to directly translate natural language questions to SPARQL queries in recent years. In this paper, we propose an NMT-based approach with Transformer model to generate SPARQL queries. Transformer model is chosen due to its relatively high efficiency and effectiveness. We design a format to encode a SPARQL query into a simple sequence with only RDF triples reserved. The main purpose of this step is to shorten the sequences and reduce the complexity of the target language. Moreover, we employ entity type tags to further resolve mistranslated problems. The proposed approach is evaluated against three open-domain question answering datasets (QALD-7, QALD-8, and LC-QuAD) on BLEU score and accuracy, and obtains outstanding results (83.49%, 90.13%, and 76.32% on BLEU score, respectively) which considerably outperform all known studies.
Validitas Modul Pembelajaran Berbasis Instagram Pada Materi Zat Adiktif Kelas VIII di MTsN 16 Tanah Datar

This research is motivated by the incompatibility of teaching materials developed by teachers in schools with the characteristics of students. There are a number of reasons for the discrepancy, for example, environment, geography, culture, and others. For this reason, self-developed teaching materials can be adapted to the characteristics of students as targets. Furthermore, the development of teaching materials must be able to answer or solve problems or difficulties in learning. There are a number of learning materials that are often difficult for students to understand or teachers find it difficult to explain. These difficulties may occur because the material is abstract, complicated, foreign, and so on. In addition, biology learning at MTsN 16 Tanah Datar has not yet fully implemented the 2013 curriculum, namely the student center, most teachers still apply the teacher center method, not only science learning, other subject teachers also still apply the same method. This is also due to the lack of new innovations or creative ideas to implement a learning activity in the classroom. Based on the above background, the author conducted a study to find a solution to this problem, namely by developing a biology learning module assisted by Instagram social media on addictive substances for class VIII at MTsN 16 Tanah Datar. This research is a development research using a 4-D development model. The development stage using the 4-D model has four stages, namely the definition stage, the design stage, the development stage, and the dissemination stage. However, in this study, the authors carried out to the development stage (develop). The instrument used in this study was a validation test sheet. Data analysis used descriptive analysis. Based on the research that has been done, a product is produced in the form of an Instragam-Based Learning Module. The results of the validation of the module obtained an average value of 85.15% which was categorized as very valid from the aspects of content feasibility, language use, presentation components, graphic components, instagram components, instagram information quality, service interaction quality. And the Instragam-Based Learning Module has been used for learning.
Pengembangan Modul Pembelajaran Matematika Berbasis Reading, Mind Mapping and Sharing dalam Meningkatkan Kemampuan Representasi Matematis Peserta Didik Kelas VII MTsN 5 Lima Puluh Kota

This study aims to develop a valid and practical Reading, Mind Mapping and Sharing-based mathematics learning module so that it can be used in online learning. The fact on the ground is that the learning resources used only use the 2013 curriculum package, with an insufficient number of students. To overcome this, it is necessary to have additional learning resources that will guide students in learning so that they can develop students' mathematical abilities, especially representational abilities. This research uses development research method with three stages of development, namely 1) defining stage, 2) designing, and 3) developing. The research instruments used were validation sheets and student response questionnaires. While the data analysis technique used is the percentage of the results of the validation and practicality test. Based on the results of the study showed that the RMS-based module was valid and practical. The results of the validation obtained an assessment of 86% with a very valid category and the assessment of 33 grade VII students of MTsN 5 Lima Puluh Kota on the RMS-based module was categorized as practical with an average of 79.73%.
Developing Interactive Learning Media for Narrative Texts at SMK

The objective of this research is to develop interactive learning media for narrative texts at SMK Telkom Pekanbaru and to know the validity of interactive learning media for narrative at SMK Telkom Pekanbaru. This research used research and development method. This development used type of research is ADDIE model. Data analysis technique in this research used needs analysis questionnaire and expert judgment questionnaire by material expert and media expert. The result of the research shows that the range of mean obtained from the material expert is 4.3 meanwhile from the media expert is 4.4. They fall into the “very good” category. The result indicates that the interactive learning media is appropriate to be used for the 10th Grade Students of SMK TELKOM Pekanbaru. The use of interactive learning media has motivated and helped students in the learning process, especially in reading narrative texts. students can learn independently in a fun way. They no longer feel bored in the process of learning to read.
Blockchain: a new era of technology

Many industries, including finance, medical, manufacturing, and education, utilise blockchain applications to benefit from the technology&apos;s unique set of properties. Trust ability, collaboration, organisation, identification, credibility, and transparency are all advantages of blockchain technology (BT). This chapter presents the fundamentals of BT and its properties and working procedure.
Developing Educational Videos Containing Authentic Interaction Video Clips for Teaching Language Functions

Videos containing authentic interaction-based video clips play an important role in facilitating EFL learners to study the target language. This study aimed to develop video lectures containing authentic interaction-based video clips, which can facilitate students in learning requests and apology speech acts. This study employed Research and Development using the ADDIE model. The analysis phase showed that it is necessary to develop the videos. Experts’ evaluations showed that the videos were acceptable, relevant, usable, and appropriate to a very high extent. The students’ evaluation revealed that the videos were valid and applicable to a high extent. In the implementation of the videos, it was revealed that there was a significant increase in the students’ ability. This means that the content of the videos was significant to increase the students’ ability. This means that the products of this research can be applied as lecture videos or instructional devices in teaching and learning devices for independent study.
Learning Attribute Features Based on Class Labels for SAR Ship Classification

Synthetic aperture radar (SAR) image classification usually relies on sample-based training. Mid-level features are widely used because SAR samples are scarce and objects exhibit complex visual appearances and strong variability. The common mid-level feature model is unsupervised, and the classification results are not robust. In this paper, we introduce mid-level features referred to as attributes. We propose a label-based attributes (L-Attribute) learning model that is based on solving mixed constrained optimization problems. We build discriminative image representations by learning a multi-kernel mapping between the input image features and the attribute space. To solve feature variability, we propose a label-based feature aggregation method to ensure that the attribute representations of the same class are similar and that different classes are far apart. In addition, we enforce that these learned attributes are highly discriminative and easy to predict. The framework is very effective and well generalized in scarce datasets.
The Use of Matching Picture to Enrich Vocabulary Mastery of the Kindergarten Students

This study aimed to know how using matching picture game as a strategy in learning vocabulary for young learners can increase students' vocabulary mastery at TK Kristen Petra 12 Sidoarjo in the academic year 2020/2021. The study took four weeks. During the Covid-19 pandemic, an online class met twice a week for 30 minutes each. Between April 3rd and April 28th, 2021, 8 sessions were held to investigate. The research subjects were TK Kristen Petra 12 Sidoarjo of the class B2 consisting 22 children. The researcher and the field note were the instruments. The tests were used to collect data before the study and after the picture game implemented. Before the Picture Game treatment, the students’ performance was below average. 2.71 was the mean. The children’ language mastery vocabulary was limited. The implementation of Picture Game increased the mean score to 3.62. The students used effective approach to obtain accurate results and logical reasoning to achieve their conclusion.