Reviewerly/exHarmony huggingface dataset:
EFEKTIVITAS PENERAPAN MEDIA PEMBELAJARAN POWTOON TERHADAP HASIL BELAJAR PESERTA DIDIK PADA MATA PELAJARAN IPS

This study aimed to determine the effectiveness of the Powtoon application on the learning outcomes of class VIII social studies. This study used a quantitative approach in the form of a quasi-experimental study. The sample of this study comprises 8th-grade B and 8th-grade C students, up to 22 students per class. The data collection techniques used were assessment techniques and documentary study, as well as data collection tools in the form of post-tests and research documents. The results showed that the mean scores from the post-test for the experimental group was 73.81, and the control class was 59.54, with a difference of 14.27. As a result, there are significant differences in learning outcomes. In the normality test, the significance value of the experimental group was 168&gt;0.05, while the significance value of the control group was 143&gt;0.05. Therefore, the data is in a normal distribution. In the hypothesis test, the sig. value (2-tailed) is 0.000&lt;0.05, with an effect size of 1.07&gt;0.08, which is in the high category. The results showed that the Powtoon application is effective and efficient for eighth-grade social studies learning outcomes.
Saving face-wants in casual talks: A discourse analysis

This politeness study aimed to investigate the different politeness strategies or face-saving acts of teachers as they engaged in casual conversations.This study utilized discourse analysis as research method in identifying the face-savings acts exhibited from the samples of teachers' conversations.The researcher analysed the linguistic corpora using Brown and Levinson's Politeness Theory.Data showed that teachers as interactants observed the use of positive politeness strategies such as: By intensifying interest to the Hearer, By joking, By seeking agreement, By giving offers and promises, By asserting a common ground, By concerning a Hearer's wants, By attending to the Hearer, By including both speaker and hearer in the activity and, By using honorifics "Sir and Ma'am.The negative politeness strategies used by teachers in their actual conversations are: By questioning, By stating FTA as a general rule and By minimizing impositions.Teachers, as they engage in their casual talks, used various politeness strategies to mitigate the threatening acts that may cause damages to the hearers' positive and negative face wants.Discourse, as it is, necessitates both hearer and speaker to contribute evenly and observe politeness to successfully convey the message may it be formal or informal setting.
A Study for the Effective Application of the Concept Analysis Learning Model in the Moral Subject: Focused on J. Wilson’s Method of Concept Analysis and the Socratic Method

도덕과는 학생들에게 올바른 도덕적 개념 형성이 이루어지도록 도와야 한다. 개념 분석 수업모형은 교사가 학생들에게 도덕적 개념에 대해 깊이 있게 탐구하도록 이끌 수 있다. 본 논문은 개념 분석 수업모형을 도덕과 수업에 효과적으로 적용하기 위해서 윌슨의 개념 분석 기술과 소크라테스적 방법을 탐구하는 데 목적이 있다. 도덕 교사용 지도서 총론에 제시된 개념 분석 수업모형의 토대라고 할 수 있는 윌슨의 개념 분석 기술들은 방법적 측면에서 학생의 개념 분석 작업을 지도하는 데 있어서 유용하다. 그리고 대화에서 아이러니(Eironeia), 엘렌쿠스(Elenchus), 아포리아(Aporia)를 경험할 수 있는 소크라테스적 방법(Socratic method)은 개념 분석 수업모형을 적용하는 도덕 교사에게 일종의 교육 방법으로서, 다른 한편으로는 교육 윤리로서 가르침을 제공한다.The moral subject should help students form correct moral concepts. The concept analysis learning model can lead teachers to in-depth exploration of moral concepts for students. The purpose of this paper is to explore Wilson’s method of concept analysis and Socratic method in order to effectively apply the concept analysis learning model to the moral subject class. The techniques of concept analysis introduced by him, which can be said to be the foundation of the concept analysis learning model presented in the moral subject teacher’s guidebook, are useful in guiding students’ concept analysis work in terms of methods. And the Socratic method that can experience Eironeia, Elenchus and Aporia in dialogue is a kind of educational method for moral subject teachers who apply the concept analysis learning model. On the other hand, it provides teaching as an ethics in education.
Civil Law Review on NFT

최근 대체 불가능한 토큰(NFT) 시장이 빠르게 성장하고 있다. NFT는 예술 작품의 디지털 등가물, 희소성에 가치가 있는 디지털 콘텐츠 등과 같은 자산의 유동성을 증가시켜 시장에서 가치를 만들어내고 있다. 그러나 NFT는 현실 세계의 재화와 달리 제한적이며, 배타적이며, 고유한 속성을 가지고 있지 않다. 이처럼 디지털 파일에 불과한 NFT가 시장에서 가치를 가진 재화로 거래되는 현실을 고려하면, NFT가 장래에 시장에서 어떤 역할을 할 것인지, 또한 법적으로 어떤 문제를 제기할 것인지가 자못 흥미롭다. NFT는 블록체인상에서 연결 대상 자산을 특정인에게 할당할 수 있다. 그 결과 NFT는 유무형의 자산에 대해서 제한된 수량의 토큰을 발행하여 시장에서 거래를 할 수 있게 되었다. 또한 NFT 발행자가 스스로 NFT에 대한 처분 권한을 포기하고 제3자에게 재판매도 할 수 있게 되었다. 특히 NFT는 디지털 원본의 부재에 따라 저작권법적 사용수익과 민법상의 물권적 사용수익의 분리에 대한 법리의 수정을 요구하고 있다. 따라서 민사법은 이러한 범위에서 거래에 관한 법적 논리를 마련할 의무를 부담한다. 하지만 현행 민사법의 법리를 NFT에 적용할 수 있는지, NFT에 민사법의 법리를 적용하는 경우에 어떠한 법적 문제가 발생할 것인지는 아직 명확하지 않다. NFT는 지금도 계속 진화하고 있는 분야이어서 섣불리 명징한 연구결과를 도출하기가 쉽지 않다. 하지만 새로운 기술의 발전에 따른 법적 환경의 변화에 대한 탐구는 필요하다고 본다. 따라서 이 연구에서는 NFT는 무엇인지, NFT는 어떤 법적 성격을 가지는지, 그리고 NFT에는 어떤 법률문제가 있는지를 살펴보았다.Recently, the non-fungible token (NFT) market is growing rapidly. NFTs are creating a rise in value in the market by increasing the liquidity of assets such as digital equivalents of rare works of art, digital content of value for rarity, etc. However, unlike real-world goods, NFTs do not limited, exclusive, and inherent characteristics. Considering the reality that NFTs, which are merely digital files, are traded as goods with value in the market, it is very interesting to see what role NFTs will play in the market in the future and what legal issues they will raise. NFTs can allocate the assets to be linked to a specific person on the blockchain. As a result, NFTs can trade in the market by issuing a limited number of tokens for tangible and intangible assets. In addition, the issuer of the NFT can voluntarily give up the right to dispose of the NFT and resell it to a third party. In particular, the NFT is demanding a revision of the jurisprudence on the separation of revenue from use of copyright law and revenue from use of real rights under civil law due to the absence of digital originals. Accordingly, civil law is obliged to formulate a legal logic for transactions within this scope. However, it is not yet clear whether the jurisprudence of the current civil law can be applied to the NFT, and what legal problems will arise when the jurisprudence of the civil law is applied to the NFT. Since NFT is a field that is still evolving, it is not easy to draw clear research results hastily. However, it is necessary to investigate changes in the legal environment according to the development of new technologies. Therefore, in this study, what NFT is, what kind of legal characteristics NFT has, and what kind of legal problems there are were examined.
PENGEMBANGAN APLIKASI LATIHAN SOAL UNTUK MENGHADAPI UJIAN SEKOLAH

Tujuan utama dari penelitian ini adalah menciptakan sebuah aplikasi berbasis web yang dapat digunakan oleh siswa-siswi SMP untuk latihan soal atau melakukan simulasi sebagai persiapan Ujian Akhir. Aplikasi latihan sengaja dibuat berbasis web agar lebih fleksibel karena bisa dioperasikan menggunakan Laptop ataupun menggunakan Smartphone. Aplikasi ini secara umum diperuntukkan bagi siswa SMP namun dikhususkan untuk siswa-siswi SMP Negeri 1 Tinondo karena peserta uji coba aplikasi diambil dari sekolah tersebut. Perangkat lunak yang digunakan untuk membuat aplikasi adalah Ispring Suite versi 9. Instrumen yang digunakan untuk mengumpulkan data adalah lembar validasi materi, lembar validasi media dan prototipe yang dibuat. Model yang digunakan dalam pengembangan soal merupakan modifikasi dari beberapa model pengembangan seperti 4D, Plomp dan ADDIE. Dilaksanakan dalam delapan tahapan yaitu: analisis kebutuhan, tahap desain, realisasi, verifikasi, produksi prototipe, analisis butir soal, revisi dan finalisasi. Dari hasil pengembangan yang dilakukan diperoleh sebuah aplikasi bank soal yang dinyatakan layak digunakan sebagai instrumen latihan persiapan menghadapi ujian matematika tahap akhir tingkat SMP. Instrumen ini memudahkan siswa dalam belajar melalui latihan soal karena dapat diakses melali smartphone. Instrumen ini juga merupakan sarana pembiasaan dalam menjawab soal berbasis web. This research aims to create a web-based application that can be used by junior high school students to practice questions or perform simulations in preparation for the Final Exam. The training application is deliberately made web-based to be more flexible because it can be operated using a laptop or using a smartphone. This application is generally intended for junior high school students but is specifically for students of SMP Negeri 1 Tinondo because the participants in the application trial are taken from the school. The software used to create the application is Ispring Suite version 9. The instruments used to collect data are material validation sheets, media validation sheets, and prototypes made. The model used in the problem development is a modification of several development models such as 4D, Plomp, and ADDIE. It is carried out in eight stages, namely: needs analysis, design stage, realization, verification, prototype production, item analysis, revision, and finalization. The results of the development carried out obtained a question bank application that was declared suitable to be used as a preparatory exercise instrument for the final stage of the junior high school mathematics exam. This instrument makes it easier for students to learn through practice questions because it could be accessed via smartphones. This instrument is also a means of habituation in answering web-based questions.
Design of Finger Sign Language Classification using Convolutional Neural Networks

In the post-COVID-19 era, remote education and discussion using video conferencing applications are spreading, but hearing-impaired people have difficulties in interactive. In this paper, we design a finger sign language recognition system using convolutional neural networks to solve the difficulties experienced by the hearing impaired. The hand area is detected from the image acquired by a camera using the Google MediaPipe Hands solution, and the detected hand area is classified by finger sign language classification model based on LeNet-5. In order to evaluate the performance of the finger sign language classification, the American finger sign language dataset (AFSL dataset) consisting of Alphabet sign language and numeric sign language is constructed from open dataset and the feasibility of real-time finger sign language recognition system is confirmed by implementing a prototype.
The Key to an Open, Functional, and Interoperable Metaverse

The term 'Metaverse' has taken on a new sparkle recently, appearing prominently in the marketing materials of several large technology companies.Indeed, many have attempted, or are attempting, to co-opt it for their own purposes, which has resulted in a great deal of confusion among producers and consumers in the marketplace.Is the metaverse a single walled garden, shared game, or social environment?Or will the metaverse be an open unified space suitable for education, ecommerce, entertainment, and industry applications?How will we move ourselves and our content seamlessly between real, virtual, and augmented worlds?How will we ensure security and provide for user-control of personally identifiable information (PII) or health data?The metaverse may well find itself at the intersection of social interaction, industry applications and virtual expressions, the essence of the global apparel and wearable industries.With this in mind, we must ask ourselves, what the metaverse might mean for the apparel industry and its current outlook and its future.With this short position paper, the Web3D Consortium seeks to address this confusion by exploring the history of 3D visualization and its formats, that has led us to our current state, providing a workable definition of the term 'Metaverse', and providing a vision for its sustainable, cooperative construction into the future.We believe that all the technologies are in place to fulfill the vision of an open, equitable, and ubiquitous information space.What remains are the key issues that have kept the Metaverse from manifesting the last two decades: user experience.
Colorful Image Colorization with Classification and Asymmetric Feature Fusion

An automatic colorization algorithm can convert a grayscale image to a colorful image using regression loss functions or classification loss functions. However, the regression loss function leads to brown results, while the classification loss function leads to the problem of color overflow and the computation of the color categories and balance weights of the ground truth required for the weighted classification loss is too large. In this paper, we propose a new method to compute color categories and balance the weights of color images. In this paper, we propose a new method to compute color categories and balance weights of color images. Furthermore, we propose a U-Net-based colorization network. First, we propose a category conversion module and a category balance module to obtain the color categories and to balance weights, which dramatically reduces the training time. Second, we construct a classification subnetwork to constrain the colorization network with category loss, which improves the colorization accuracy and saturation. Finally, we introduce an asymmetric feature fusion (AFF) module to fuse the multiscale features, which effectively prevents color overflow and improves the colorization effect. The experiments show that our colorization network has peak signal-to-noise ratio (PSNR) and structure similarity index measure (SSIM) metrics of 25.8803 and 0.9368, respectively, for the ImageNet dataset. As compared with existing algorithms, our algorithm produces colorful images with vivid colors, no significant color overflow, and higher saturation.
Bibliometric Analysis of Publication on Protein Nanoparticle Using VOSviewer

Background: A Study to determine the development of research can be done by bibliometric analysis technique. There are many studies that have been carried out on bibliometric analysis. However, research on bibliometric analysis of published data in the field of protein nanoparticles that has been carried out specifically to determine research development has not been carried out.&#x0D; Objective: This study aims to examine the development of protein nanoparticle research through a bibliometric approach. &#x0D; Methods: The article data was obtained from the Google Scholar database using the publish or perish reference manager software. The keyword "Protein Nanoparticles" is used with a publication time span from 2012 to 2022. Data processing uses Microsoft Excel. Computational mapping using VOSviewer.&#x0D; Results: The article data obtained and considered relevant were 390 articles. The results of the analysis of the development of protein nanoparticle publications in the last 10 years show quite frequent fluctuations. Research fluctuations occurred in 2012 to 2020. There was a decline in 2020-2022 from 35 in 2020 to 19 in 2022. In 2012 and 2014 research on protein nanoparticles became popular, with 47 studies each.&#x0D; Conclusion: Based on the results of mapping the collected article data, it can be seen that the keyword protein nanoparticles is still rarely used in research. It can be concluded that the field of protein nanoparticles is still very likely to be researched and associated with other terms, this will have a higher impact on the novelty of the research.
TRAVERSAL OF AMAZON WEB SERVICES- A REVIEW

Cloud computing is the very vast technology in the field of information technology as well as in computer science.Cloud computing is not only important in business but also important in day to day activities.Basically, cloud computing we can say that when we use the someone else server to storing, managing, processing the data.It is totally based on the pay per use model.Most business have opted to cloud computing because it is considered safer and more reliable and it is flexible and scalable also.In cloud computing there are many cloud service providers Amazon Web Services (AWS) is one the largest cloud service providers globally.It allow customer to store data on platform.Amazon web service provides 200+ services to the users.The most common services are amazon EC2, S3, Elastic Bean Stalk.This review paper basically contains the feature and advantages of AWS as compared to other cloud service provider.
Situational Leadership Role in Enhancing Organizational Performance during Covid 19 Pandemic among a Sample of Kuwaiti SMEs

COVID 19 hit the world during the end of 2019 and beginnings of 2020, the virus was deadly and fast to spread which had caused a lot of disturbance among country in terms how to avoid such crisis and make sure to get out of it with the least losses possible. The current research sought to examine the impact of situational leadership theory and its dimensions (directive, supportive and delegative) in enhancing organizational performance during COVID 19 pandemic, and how this type of leadership managed to preserve the best performance of many organizations. Depending on quantitative approach and utilizing an electronic questionnaire, researcher adopted a sample of (344) managers and leaders within Kuwaiti SMEs during the fiscal year 2021-2022. SPSS was used to analyze collected primary data, and outcomes of analysis indicated that situational leadership helped a lot during COVID 19 breakout as it saved and preserved an acceptable level of performance among SMEs, in addition to that, it was seen that the directive leadership style of situational leadership theory was the most influential in running a good and acceptable level of performance during the pandemic. Based on such results, current research recommended the need to increase attention to the fact that one of the defects of situational leadership is its failure to identify the leadership skills required for certain situations, and thus it is necessary to identify these skills and work on developing them among individuals.
Improved Sketch-to-Photo Generation Using Filter Aided Generative Adversarial Network

Generating a photographic face image from given input sketch is most challenging task in computer vision. Mainly the sketches drawn by sketch artist used in human identification. Sketch to photo synthesis is very important applications in law enforcement as well as character design, educational training. In recent years Generative Adversarial Network (GAN) shows excellent performance on sketch to photo synthesis problem. Quality of hand drawn sketches affects the quality generated photo. It might be possible that while handling the hand drawn sketches, accidently by touching the user hand on pencil sketch or similar activities causes noise in given sketch. Likewise different styles like shading, darkness of pencil used by sketch artist may cause unnecessary noise in sketches. In recent year many sketches to photo synthesis methods are proposed, but they are mainly focused on network architecture to get better performance. In this paper we proposed Filter-aided GAN framework to remove such noise while synthesizing photo images from hand drawn sketches. Here we implement and compare different filtering methods with GAN. Quantitative and qualitative result shows that proposed Filter-aided GAN generate the photo images which are visually pleasant and closer to ground truth image.
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity

Reinforcement learning provides an automated framework for learning behaviors from high-level reward specifications, but in practice the choice of reward function can be crucial for good results -- while in principle the reward only needs to specify what the task is, in reality practitioners often need to design more detailed rewards that provide the agent with some hints about how the task should be completed. The idea of this type of ``reward-shaping'' has been often discussed in the literature, and is often a critical part of practical applications, but there is relatively little formal characterization of how the choice of reward shaping can yield benefits in sample complexity. In this work, we build on the framework of novelty-based exploration to provide a simple scheme for incorporating shaped rewards into RL along with an analysis tool to show that particular choices of reward shaping provably improve sample efficiency. We characterize the class of problems where these gains are expected to be significant and show how this can be connected to practical algorithms in the literature. We confirm that these results hold in practice in an experimental evaluation, providing an insight into the mechanisms through which reward shaping can significantly improve the complexity of reinforcement learning while retaining asymptotic performance.
Free Dynamics of Feature Learning Processes

Regression models usually tend to recover a noisy signal in the form of a combination of regressors, also called features in machine learning, themselves being the result of a learning process.The alignment of the prior covariance feature matrix with the signal is known to play a key role in the generalization properties of the model, i.e. its ability to make predictions on unseen data during training. We present a statistical physics picture of the learning process. First we revisit the ridge regression to obtain compact asymptotic expressions for train and test errors, rendering manifest the conditions under which efficient generalization occurs. It is established thanks to an exact test-train sample error ratio combined with random matrix properties. Along the way in the form of a self-energy emerges an effective ridge penalty \textemdash\ precisely the train to test error ratio \textemdash\ which offer a very simple parameterization of the problem. This formulation appears convenient to tackle the learning process of the feature matrix itself. We derive an autonomous dynamical system in terms of elementary degrees of freedom of the problem determining the evolution of the relative alignment between the population matrix and the signal. A macroscopic counterpart of these equations is also obtained and various dynamical mechanisms are unveiled, allowing one to interpret the dynamics of simulated learning processes and reproduce trajectories of single experimental run with high precision.
Whole Page Unbiased Learning to Rank

The page presentation biases in the information retrieval system, especially on the click behavior, is a well-known challenge that hinders improving ranking models' performance with implicit user feedback. Unbiased Learning to Rank~(ULTR) algorithms are then proposed to learn an unbiased ranking model with biased click data. However, most existing algorithms are specifically designed to mitigate position-related bias, e.g., trust bias, without considering biases induced by other features in search result page presentation(SERP). For example, the multimedia type may generate attractive bias. Unfortunately, those biases widely exist in industrial systems and may lead to an unsatisfactory search experience. Therefore, we introduce a new problem, i.e., whole-page Unbiased Learning to Rank(WP-ULTR), aiming to handle biases induced by whole-page SERP features simultaneously. It presents tremendous challenges. For example, a suitable user behavior model (user behavior hypothesis) can be hard to find; and complex biases cannot be handled by existing algorithms. To address the above challenges, we propose a Bias Agnostic whole-page unbiased Learning to rank algorithm, BAL, to automatically discover and mitigate the biases from multiple SERP features with no specific design. Experimental results on a real-world dataset verify the effectiveness of the BAL.