Reviewerly/exHarmony huggingface dataset:
THE IMPLEMENTATION OF COLLABORATIVE WRITING TECHNIQUE IN TEACHING WRITING

The purpose of this study is to describe the implementation of collaborative writing technique in writing text, especially in recount text. Writing is one the English skills that should be mastered by high school students. However, students thought that writing is not easy to do. They have some difficulties while doing writing. They do not know what they have to write while writing, and also they are confused in expressing their ideas into written form. Therefore, the researcher wants to describe the implementation of collaborative writing in teaching writing by the teacher. According to Fernandez Dobao & Blum (2013), collaborative writing is a technique which students work together, share authorship, and share responsibility for all writing processes to produce final product. Students are expected to be helped in developing and gathering the ideas while writing a text by using collaborative writing technique. Moreover, this study uses qualitative approach. The subjects of this study are students of tenth graders in senior high school. The result of this study indicates that collaborative writing technique helps students to develop and gather ideas in writing a text. Collaborative writing technique also is an appropriate technique that can be used in teaching writing for high school students.
LUDIC GAMES: PLAYFUL FORMS OF INSIGHT

The name Ludics, is derived from the term ludus, meaning “play,” a term that is useful in connection with games and rules of play. As a concept for artistic research, the Ludic method is introduced here as it combines both games and rules of play. Conceptual ludic art explores rules of play, systems of investigation and knowledge acquisition through game mechanics, as well as the fundamentals of perception, experience and cognition. The theory and practice of artistic research are concerned with ludic methods of approaching art and science and epistemic things (Erkenntnisgegenstände), insights achieved through research. Their goals are written fictitiously, presented participatively and made public processually. The methods of artistic research comprise contradictions, and are found in feedback between peers in conference contributions and in exhibitions, between radical artistic uniqueness and the claim of universal validity (which is required for the validation of artistic research). We need to clarify the scientific understanding of epistemic things, and as a consequence, introduce a new concept of a ludic artistic research epistemé. Ludic objects are artefacts that trigger discourse and the application of certain rules of research. They constitute an interplay of art and knowledge. Teaching this understanding is equally tied to a certain playful approach toward serious, rule-driven research. Following a ludic method, we introduce a new trope to artistic research, the idea of a playful movement in thinking that dissolves the established trope of art as a field with no further connections than aesthetics per se. The ludic objective thus stems from technologies and cultural techniques of insight, as well as theories, experiments and philosophical conceptions that are connected to the perceived, conceived and lived world.
TEACHING READING COMPREHENSION OF NARRATIVE TEXT USING STUDENT TEAM ACHIEVEMENT DIVISION (STAD)

Reading is an activity to obtain information from a text. Reading a text is not easy, it requires an understanding to get a meaning. The objective of the research was to identify the implementation of the scenario in teaching reading comprehension of narrative text using the Student Team Achievement Division and to find out students’ responses. The researcher used a descriptive qualitative method. The subject of this research was tenth-grade students of Vocational High School in Cimahi. The data were collected by using observation, questionnaires, and documents. The results of the research were the implementation of STAD in teaching reading comprehension was appropriated with the learning scenario. In the implementation of STAD in teaching reading comprehension of narrative text got a good response from students. By using STAD on English study could increase students' reading comprehension, students were motivated and involved in the active learning process. In addition, students felt learning was fun and not boring. STAD (Student Team Achievement Division) was suitable in teaching reading comprehension of narrative text at the tenth-grade students. The students understood better in reading comprehension using STAD. Keywords :  Reading Comprehension, Narrative Text, STAD
Enhancing Jet Taggers with Mass Unspecific Supervised Tagging (MUST)

We introduce a new approach for training jet taggers based on multivariate methods, where the mass and transverse momentum are input variables, along with jet substructure observables, varying over wide ranges.Known as Mass Unspecific Supervised Tagging (MUST), this strategy allows the development of taggers that are sensitive to different types of signal and efficient across large kinematical regions.Additionally, it provides an optimal solution to the mass correlation problem that affects other supervised taggers.We build MUST-inspired generic taggers using neural networks which, when tested with various multi-pronged signals, perform much better than variables commonly used in experiments to discriminate signal from background.These taggers can also spot signals not used in training with a good efficiency.Taggers built upon MUST can be designed to identify the prongness of a jet, which could be extremely useful in a scenario where a new phisics signal is discovered.
Learning Task Agnostic Skills with Data-driven Guidance

To increase autonomy in reinforcement learning, agents need to learn useful behaviours without reliance on manually designed reward functions. To that end, skill discovery methods have been used to learn the intrinsic options available to an agent using task-agnostic objectives. However, without the guidance of task-specific rewards, emergent behaviours are generally useless due to the under-constrained problem of skill discovery in complex and high-dimensional spaces. This paper proposes a framework for guiding the skill discovery towards the subset of expert-visited states using a learned state projection. We apply our method in various reinforcement learning (RL) tasks and show that such a projection results in more useful behaviours.
LibGuides: LibGuide Best Practices: Introduction

TCC Library's best practices, standards, and guidelines to follow when creating and updating LibGuides.
A Study on the Development of Neologism Education Content for Chinese Learners Using SNS

This study aims to design and implement content for Neologism education using SNS as a research on Neologism education methods for Chinese learners. First of all, the educational characteristics of SNS and the teaching and learning models using it were divided into SNS, learners, teachers/managers, and contents as educational factors, and each presented factors to consider. In addition, systematic education list was extracted by selecting and classifying educational contents based on the ‘2019 National Institute of Korean Language’ Neologism data’. Finally, Chinese learners were surveyed by properly implementing Neologism education contents using WeChat according to the educational environment and characteristics. As a result, we were able to identify the need for Korean Neologism education and learners’ desire to learn Neologism using SNS. I could see that it was an effective way of teaching Neologism. (Korea University)
Two Phase Optimization Method Based on Meta heuristic Algorithms, Big Bang-Big Crunch and Black Hole

This research proposes a two-phase algorithm whose main idea is based on meta heuristic algorithms, Big Bang and Black Hole. In the first phase of this algorithm, the artificial ants scan the reticulated rectangular region in parallel directions. The best points in the ant’s navigations are used as starting points for the second stage of this algorithm. Big Bang and Black Hole algorithms, as an exploitation phase, try to investigate more accurate answers in the neighborhood of the starting points by reducing the neighborhood radius. Numerical examples confirm that this algorithm is capable to achieve an optimal solution with the desired accuracy and low computational costs.
Pelatihan Aplikasi Berbasis Web Pada SMK Teladan Pematangsiantar Sebagai Upaya Meningkatkan Kemampuan Vokasi

Internet is the media that has the most up to date information. Now as time grows many web-based applications that can be used as needed. The increasing development of technology is the growing number of human resource needs that are reliable and creative that can provide the latest innovations that can help to suit the needs. The young generation is a very competent generation to be a reliable human resource for example is students. To improve the quality of students to technological developments need to be held special vocational training program. This training Program provides a good impact on students. From pre test results and post test can be seen before training until after training. The results after the training increased rapidly so that it can be concluded through this training the ability of students in the field of vocational get good results
PERANCANGAN SISTEM INFORMASI KOHORT IBU HAMIL MENGGUNAKAN MICROSOFT VISUAL STUDIO 2010

The target data for the 2020 MCH program at the Ahmad Yani Health Center in Bandung City are 472 pregnant women. Every pregnant woman is obliged to check her pregnancy 4 times in 9 months, in which documentation of the development of pregnant women needs to be reported in order to support the health of mothers and children. The recording and reporting system for the cohort registration of pregnant women at the Ahmad Yani Health Center in Bandung City is still manual, so that data incompleteness often occurs due to the many components that must be filled manually in the cohort register, which results in delays in submitting reports to the Head of the Puskesmas and the Bandung City Health Office. This study aims to design a cohort information system for pregnant women at the Ahmad Yani Health Center in Bandung City which can facilitate midwives in recording, processing and reporting data quickly and accurately. The development method used is Waterfall with DFD modeling (Data Flow Diagram) which is implemented using Microsoft Visual Studio 2010 and programming language Microsoft Access 2016 as the database. Data collection techniques used are observation, interviews and literature study. With this information system, it is hoped that it will facilitate data collection on patients, data on routine visits for pregnant women, data collection on midwives, and presentation of reports periodically, by region, visits, detection of risk factors, referrals and computerized quarterly visit charts.
BLOCKCHAIN TECHNOLOGY: THE NEW TRUST PARADIGM AND AN OBJECT VIEW FOR INDIA

This document provides a high-level technical overview of blockchain technology. Decentralized has become this year’s trending concept in the financial. In this article we tend to present an abstract framework to help software system architects, developers, and decision manufacturers to adopt the blockchain technology. In 2008, the idea of blockchain was combined with various computing technologies and concepts to create modern cryptocurrencies: cryptocurrencies protected by cryptographic mechanisms, rather than a vault, archive or central authority. The first blockchain-based cryptocurrency was Bitcoin. The representation of a cryptocurrency is tied to a digital address. Bitcoin users can digitally sign and transfer rights to this information to other users, and the Bitcoin blockchain publicly records this transfer, allowing all network participants to independently verify the accuracy of the information transactions. The Bitcoin blockchain is stored, maintained and managed by a jointly distributed group of participants, which, together with certain cryptographic mechanisms, makes it resistant to attempts to modify the ledger later (changing blocks or tampering with transactions).
THE PHENOMENON OF NETWORK WARS: TO THE PROBLEM OF THE PHILOSOPHICAL THINKING

The article substantiates that the modern social system, the dynamism and specificity of which are due to the intensive development of information technology and network communications, has dramatically changed the nature of conflict resolution and warfare. It is shown that, in essence, network warfare is reduced to a special form of conflict, when their participants use network forms of organization, doctrine, strategy and technology that are best adapted to the current stage of development of the information society. It turns out that one of the goals of the impact of network wars on society is the destruction of the meaning unity of the world and man, in connection with which the basic values ​​of the people and the state, national, religious and cultural identity are destroyed. The dialectical interrelation of network wars with information and information-psychological wars is shown.
Oculomotor strategies do not vary under increasing levels of cognitive demand

Eye movements can be used as a predictor for various ocular and cognitive conditions. In this study, we propose a new paradigm that can be used to analyze the impact of cognitive load on oculomotor behavior. Participants (N=30) viewed a sequence of 100 scenes freely for 10 seconds. After each scene, they identified a target object from a previous scene among 3 similar distractors from unviewed scenes in a 4 alternative forced choice task. A staircase 2 down 1 up controlled N-back - the number of images back in the sequence from which the target was selected. Our paradigm was successful in actively engaging working memory, as subjects demonstrated more difficulty in recalling correct responses as N-back increased (r(2998)=0.292, p<.001). When comparing the maximum N-back achieved between subjects, there were no significant differences between the number of fixations (F(8,21)=0.848, p=0.572), duration of fixations (F(8,21)=0.693, p=0.694), number of saccades (F(8,21)=0.709, p=0.681), or duration of saccades (F(8,21)=0.279, p=0.966). Similarly, oculomotor behavior did not act as a predictor of correct/incorrect responses with increasing demand from the N-back task. There was no significant interaction between N-back and response accuracy for the number of fixations (F(9)=0.128, p=0.999), the duration of fixations (F(9)=0.385, p=0.943), the number of saccades (F(9)=0.309, p=0.972), or the duration of saccades (F(9)=1.350, p=0.205). When analyzing the total area of each scene viewed, we found no significant differences across groups of maximum N-back reached (F(8)=0.448, p=.878), and proportion of image viewed was not a significant predictor of accuracy (F(9)=0.803, p=0.613). These results suggest that oculomotor strategies generally do not change as a result of higher cognitive demand.
A Learning-rate Optimization Technique for Object Detection Accuracy Enhancement

Recently, Deep Learning [1] models are used primarily in Object Detection algorithms because of their specific capability for Image Recognition. These models identify items present in input images and videos [2] by extracting features from them. These models have a variety of applications, which include Image Processing, Video analysis, Speech Recognition, Biomedical Image Analysis, Biometric Recognition, Iris Recognition, National Security applications, Cyber Security, Natural Language Processing [3], Weather Forecasting applications, Renewable Energy Generation Scheduling etc. The Convolution Neural Network (CNN) [3], which comprises many artificial neuron layers, is employed for these models. The accuracy of Deep Learning models is determined by a number of factors, including the learning rate, the training batch size, the validation batch size, the activation function, and the drop-out rate. Hyper-Parameters are the name for these parameters. The accuracy of Object Detection depends on the choice of Hyper-Parameters. It is therefore a difficult task to find the best values for these parameters. Fine-Tuning is a method for selecting an effective Hyper-Parameter for improving Object Detection precision. Selecting an inaccurate Hyper-Parameter value, leads to Over-Fitting or Under-Fitting of data. Over-Fitting is a problem, when training data is greater than the necessary, leading to learning noise and inaccurate Object Detection [4]. Under-Fitting occurs when a model is unable to capture the data's trend, resulting in more erroneous testing or training outcomes. By changing the ‘Learning rate' of various Deep Learning Models, a balance between Over-Fitting and Under-Fitting is reached in this article. For experimentation purpose, this paper considers four Deep Learning Models such as VGG-16, VGG-19, InceptionV3 and Xception. In terms of maximal Object Detection accuracy, the best zone of Learning-rate for each model is analyzed. &nbsp;The prediction accuracy of a dataset of 70 object classes is investigated in this study by adjusting the ‘Learning-Rate' while keeping the rest of the Hyper-Parameters fixed.This article focuses on the impact of ‘Learning-Rate' on accuracy in Object Detection and identifies an ideal accuracy zone. &nbsp;This analysis helps in reduction of computational effort in calculation of Objection Detection Accuracy.
PROJECT PENETASAN TELUR AYAM TERHADAP HASIL BELAJAR IPA PADA SISWA TUNAGRAHITA RINGAN

The ability of mentally retardation children in mastering learning the material of animal breeding was still difficult so that it influenced the learning result value which was less satisfied with the average value 50 or under KKM value. This research had purpose to know the influence of the project of hatching chicken eggs toward learning science result to mild mentally retardation students. This research used quantitative approach, pre-experiment kind with One group pre test – post test design. The average value of pre test result indicated score 37.5 and the average value of post test result got 76.2. The treatment was done 8 times meeting. Student ADT got the highest value and student SI got the lowest value. The research result obtained stated that there was influence of the project of hatching chicken eggs toward learning science result to mild mentally retardation students significantly with the result: Z counted = 2,52 was greater than Z table = 1,64, critic value 5%. In this way, the project of hatching chicken eggs could be effective to be applied to support the learning result of mild mentally retardation students. Keywords: learning science result, the project of hatching chicken eggs, mild mentally retardation
AN ANALYSIS OF CODE SWITCHING AND CODE MIXING USED BY GITA SAVITRI IN HER VIDEO ENTITLED “EVERYTHING WRONG WITH HUSTLE CULTURE”

There are many languages in this world which used as a tool of communication. For that reason many people are bilingual or even multilingual. The ability to speak in more than one language is causing the sociolinguistic phenomenon called code switching. Code switching is the situation when someone switches his language from one into another. This is commonly happening everywhere includes in Indonesia. There are many Indonesian people who have bilingual or multilingual competence who often do code switching. One of them is Gita Savitry, a famous young Youtuber. For that reason this research is trying to find out the code switching that Gita’s used, classify it and explain the reason behind it. Furthermore this is a descriptive qualitative research, and the data was taken from Youtube website. The finding showed that to most dominant type occurring in the speech video was intra sentential switching, it occurred 40 times or 80, 10% of total code switching occurred. Mainly, the reason for using code switching is related to particular topic which is talked. Furthermore the other reasons are lexical needed, interjunction, emphasizing or clarifying statement and showing solidarity. Keywords :  Code Switching, Code Switching Types, Code Switching Reason
Neurophysiologically-inspired model for social interactions recognition from abstract and naturalistic stimuli

INTRODUCTION: Humans can perceive social interactions from natural as well as from schematic stimuli, as shown by the classical experiments by Heider and Simmel (1944). We present a simple neural model that is consistent with the basic facts known about neurons in the visual pathway that recognizes social interaction from naturalistic as well as from abstract stimuli. In addition, we present an algorithm for the generation of highly-controlled stimulus classes of naturalistic and abstract social interactions. Such stimuli are critical for electrophysiological and psychophysics experiments that clarify the underlying mechanisms. METHODS: The model consists of a hierarchical shape-recognition pathway with partial position invariance that is modeled using a deep neural network (VGG16), followed by an estimation of the relative instantaneous positions and orientations of moving agents, which are then robustly tracked and encoded by a population code in a Dynamic Neural Field. The relative positions, velocities and accelerations of moving agents are computed in a top level module, employing gain-field mechanism which is followed by the classifier of the interactive behaviors. The stimulus synthesis algorithm is derived from dynamic models of human navigation (Warren, 2006) which are combined with methods for computer animation of quadrupedal animals. RESULTS: The model successfully reproduces results of Tremoulet and Feldman (2000) on the dependence of perceived animacy of moving agents on their motion parameters and the body axis. We demonstrate how the proposed architecture can recognize interactions from real movies showing interacting animals. The most distinctive three behavioral classes scored better than 71% in terms of the true positive rate. The model makes predictions about the behavior of a variety of different neuron classes, which guide the analysis in physiological experiments. CONCLUSION: Simple neural circuits combined with learning are sufficient to account for simple forms of social interaction perception in real and abstracted stimuli.
DIGITAL TECHNOLOGY AND IDEOLOGICAL IMMUNITY IN YOUNG PEOPLE

The article analyzes the specificity of information and psychological security in our time from a socio-philosophical point of view. The article also discusses issues related to the protection of the constitutional order, sovereignty, territorial integrity of the Republic of Uzbekistan, information security and information protection, timely and adequate response to threats in the field of information, strengthening civil, interethnic and interfaith peace and harmony. explained.