Reviewerly/exHarmony huggingface dataset:
Readiness for the Implementation of Ubiquitous Learning in Programming Course in Higher Education

&lt;p class="0abstract"&gt;&lt;span lang="EN-US"&gt;The use of information technology in education is inevitable by the increasing utilization of gadgets and the internet. The emergence of generation Z has driven the need for transformation in learning process, including in Higher Education area. Learning programming is important and fundamental for informatics students. Numerous endeavors have been executed to achieve satisfactory results that is absorption of graduates within the society and industry. However, there are still many efforts that must be done to meet the high need for informatics graduates who are experts in programming. Ubiquitous learning (u-learning) is a mean for learning anywhere, anytime and through anything that aims to provide the right information at the right time and place to accommodate a lifestyle by utilizing technology. In order to harmonize the current generation Z learning styles, u-learning is considered suitable to comply with their style. This research is a descriptive study design to describe the current situation as a basis for finding facts. The results showed that the students' perceptions showed that the support of the u-learning environment could support them in improving programming learning outcomes and u-learning could be applied in programming learning.&lt;/span&gt;&lt;/p&gt;
Super Resolution Reconstruction Algorithm of UAV Image Based on Residual Neural Network

With the development of convolutional neural network, video super-resolution algorithm has achieved remarkable success. Because the dependence between frames is complex, traditional methods lack the ability to model the complex dependence, and it is difficult to estimate and compensate the motion accurately in the process of video super-resolution reconstruction. Therefore, a reconstruction network based on optical flow residuals is proposed. In low resolution space, the dense residual network is used to obtain the complementary information of adjacent video frames, and then the optical flow of high-resolution video frames is predicted through the pyramid structure, and then the low resolution video frames are transformed into high-resolution video frames through the sub-pixel convolution layer, The high-resolution video frame is compensated with the predicted high-resolution optical flow. Finally, it is input into the super-resolution fusion network to get better effect. A new loss function training network is proposed to better constrain the network. Experimental results on public data sets show that the reconstruction effect is improved in PSNR, structural similarity and subjective visual effect.
Perancangan dan Pembuatan Aplikasi Media Pembelajaran Berbasis Android pada Mata Pelajaran Produk Kreatif dan Kewirausahaan

This study aims to determine the validity, practicality and effectiveness of designing and making Android-based learning media applications in the subject of Creative Products and Entrepreneurship for Class XII TKJ 2 at SMK Negeri 8 Padang Odd Semester, Academic Year 2020/2021. This study uses a research development method (research &amp; Development). The research subjects were 35 people. The research model used is the development research model (ADDIE model), with the design of the development steps as follows. (1) Analyze, (2) Design, (3) Development, (4) Implementation and (5) Evaluate. The results of the validity test by the experts as a whole validator test assessment of Android-Based Learning Media Applications in the subject of Creative Products and Entrepreneurship Class XII TKJ 2 SMKN 8 Padang amounting to Odd Semester 82.20%, so that the level of validity can be interpreted as valid to use. The results of the overall practicality test assessment of the practicality of Android-Based Learning Media Applications in the subject of Creative Products and Entrepreneurship Class XII TKJ 2 SMKN 8 Padang Odd Semester is 90.79%, so that the level of practicality can be interpreted as Very Practical to use. The results of the overall effectiveness test assessment of the effectiveness of the Android-Based Learning Media Application in the subject of Creative Products and Entrepreneurship Class XII TKJ 2 SMKN 8 Padang Odd Semester is 84.91%, so that the level of effectivenesscan be interpreted Effectively used. In conclusion, based on the assessment and expert input and the results of the field trial of the Android-Based Learning Media Application as a learning medium, it has been tested for feasibility, excellence, and can be used in the learning process in Creative Products and Entrepreneurship subjects in class XII TKJ 2 SMKN 8 Padang.
How to Exploit a DeFi Project

The growing adoption of decentralized finance poses new security risks, as designing increasingly complex financial models is error-prone. We have witnessed numerous DeFi projects hacked (for tens of millions of dollars) because of unsound liquidation conditions, asset pricing, or position management, etc. To address these issues, we present a systematic way of finding vulnerabilities in DeFi projects based on automatically extracting financial models from smart contracts and reasoning about them symbolically using either a model checker or an interactive theorem prover. Specifically, we (i) formalized the concept of soundness in the financial model of a DeFi project which captures an interesting class of exploits (flash-loan attacks), and (ii) built a domain-specific language to automatically extract models from smart contracts and search possible exploits or prove their soundness. To demonstrate the capability of our approach, we model variants of most DeFi projects with a TVL (total value locked) larger than 20M USD (totaling about 8B USD TVL) and check their soundness. The result showed that we can automatically find both previous exploits and potential new flaws in DeFi.
Tilt Brush. The New Perspective of Art

Interpenetration of ideas, culture, economics, raw materials and etc. are causing globalization in our society. This trend is also assisted by the growing technological innovations. Society is increasingly turning to digital tools to provide fast communications, access to information and goods through the global network, especially needed during the pandemic. In terms of art, these factors contribute to shifting the range from classical means of expression to contemporary art forms focused on digital media. Historically, the discovery of photography in the 19th century radically changed art. Painting frees itself from the function of reflecting objective reality and seeks new means of expression and meaning. In the early 20th century, new trends in the avant-garde art seek to depict intangible things away from visible reality such as the inner world of the artist, emotions, symbols, music, time and more. One of the brightest trends - Cubism is a typical example. It seeks a way to show objects rationally from several sides simultaneously - three-dimensional, but unfortunately it is limited by the means of expression - the two-dimensional surface of the canvas. Digital technologies today have a solution to this problem. They provide digital tools that completely change painting. The canvas no longer exists in the familiar way in which the artist works. It is becoming history. With the invention of VR glasses, the boundaries of visible reality and imagination in art have been removed to enter a new virtual world. Tilt Brush technology goes one step further, giving the opportunity to the artist to create 3D images with a brush in hand while moving in the virtual world he creates. Canvas doesn’t exist, it is a virtual digital world three-dimensional arising from the imagination of the artist and existing only through the eyes of the pink VR glasses. Here comes the question, will technology displace the artist's hand? Keywords: Digital Art, Art, Virtual Reality (VR), Tilt Brush, Technological Innovations, Net Art, Non-Fungible Tokens (NFT), Artificial Intelligence
BLOGS AS NEW MEANS IN MODERN COMMUNICATION

The information scope of the last decade has been realized in the integration of various ways of communication into interactive information networks. Combining texts, images, symbols and sounds in one system in a global network and providing accessible and inexpensive access, dramatically changes the nature of social communication.&#x0D; The history of journalism has its stages of development: from ancient to modern forms, from signs to modern information technologies. If the previous centuries are properly described and analyzed by the researchers, the new means of communication require more study.&#x0D; The proposed study attempts to analyze blogs as new means in modern communication.&#x0D; Blogging is somewhat different from journalism in its predominant communicative function, which in traditional media is only available live on radio and television, but information is often censored by a moderator, an editor, who determines who to broadcast and when to do it.&#x0D; The study focuses on whether a blog is a form of new journalism or a new journalistic genre that has entered mass communication.&#x0D; The article as an applied aspect considers ten most popular Ukrainian bloggers on Instagram based on the results of the analysis of online publications.&#x0D; It is concluded that the blogs are powerful producers of information and, as a consequence, correlators of network information flows.&#x0D; Blogging and journalism are two types of mass information and communication activities, between which there are common and different, but both types have a moral responsibility for the content.&#x0D; The websites and social networks systematically provide rankings of the most popular blogs. In such cases, the authors, their age, number of subscribers, topics and a short history of the author are shown, and details of the private life of bloggers are usually displayed. It attracts the attention of the consumer of information.
On-chip photonic convolutional accelerator for image processing

We demonstrate an on-chip photonic convolutional accelerator, which can perform configurable optical convolution operations to achieve specific image processing. It indicates great potential for on-chip image processing in AI hardware acceleration.
Can contactless volunteer activities be an alternative during the COVID-19 pandemic?

The purpose of this study is to provide a viable alternative for volunteer services which became inactive due to the COVID-19 pandemic. Accordingly, cases of contactless volunteer work involving children using the M Social Welfare Center located in the city of Paju in Gyeonggi-do Province were studied using reputational case selection. The aforementioned children are children whose parents have hearing disabilities (CODAs: child of deaf adults). In all of the examined cases, six sessions of online volunteer work have been carried out with these children. In-depth interviews were conducted with four participants, two non-participants, two of the twelve youth volunteers, and one social worker. The results of the study were as follows: firstly, there are several advantages to online volunteer work such as providing an alternative to the conventional volunteering method during the COVID-19 pandemic, no restrictions of location or place, recipients having their own private space, and the volunteers and recipients being able to open up to each other and being able to grow together through this process. Secondly, issues to be noted during the process are the characteristics of the recipients, the role of social workers, the education of volunteers and the attitude of the volunteers. Finally, aspects that need to be improved are the recognition of online volunteer hours and paralleling online volunteer work with other volunteer methods when the COVID-19 situation improves in the future. Through these findings, this study suggested practical and policy implications.
BERT-Beta: A Proactive Probabilistic Approach to Text Moderation

Text moderation for user generated content, which helps to promote healthy interaction among users, has been widely studied and many machine learning models have been proposed.In this work, we explore an alternative perspective by augmenting reactive reviews with proactive forecasting.Specifically, we propose a new concept text toxicity propensity to characterize the extent to which a text tends to attract toxic comments.Beta regression is then introduced to do the probabilistic modeling, which is demonstrated to function well in comprehensive experiments.We also propose an explanation method to communicate the model decision clearly.Both propensity scoring and interpretation benefit text moderation in a novel manner.Finally, the proposed scaling mechanism for the linear model offers useful insights beyond this work.
The Effectiveness of Using Kahoot! Application as An Evaluation Tool in Arabic Vocabulary Learning at Madrasah Ibtidaiyah

Kahoot application in learning can also help teachers to collect feedback from students, assess students’ learning understanding, and make surveys about problems that can be identified during learning. This research aimed to describe the effectiveness of using Kahoot! application as an evaluation tool in Arabic vocabulary learning for fifth-grade students at MI Al-Ma’arif 01 Margomulyo, Blitar. This research was qualitative with a One Group Pretest Posttest design – an experiment carried out in one group only without comparison. The samples of this research were the fifth-grade 25 students of MI Al-Ma'arif 01 Margomulyo Blitar. The results showed that the average evaluation score of the students after using Kahoot! application as a learning media increased by 75.2, much higher than before, it was 37.6. The use of Kahoot! application as an evaluation tool in Arabic vocabulary learning contributed 32% to the learning outcomes of the fifth-grade students at MI Al-Ma'arif 01 Margomulyo.
Automatic Invigilation Using Computer Vision

Educational institutions determine students' strengths and weaknesses through exams.Students find numerous ways to cheat in physical exams like exchanging their sheets, using hidden notes, getting good grades, fulfilling their parents' expectations, and whatnot.Due to the physical limitations of human supervisors, typical invigilation methods cannot conduct successful exams while maintaining their integrity.An automated method based on computer vision to detect anomalous activities during exams is proposed in this study.This study centers around invigilating students' suspicious behaviour during physical exams through closed-circuit television (CCTV) cameras.The proposed method uses You Only Look Once (YOLOv3) with residual networks as the backbone architecture to inspect cheating in exams.The obtained results show the credibility and efficiency of the proposed method.The experimental results are promising and demonstrate the invigilation of the students in the examination.In this work, achieve 88.03% accuracy for the detection of cheating in the classroom environment
Face Tracking Performance in Head Gesture Recognition System

This paper describes the comparative analysis of different face tracking methods in the head gesture recognition system. The major constraints of head gesture recognition system, i.e. face detection, feature extraction, tracking, and recognition are explained. We used adaboost algorithm for detection, and Camshift algorithm for tracking with different feature extraction methods. We performed extensive experimentations and presented a comparative analysis of tracking performance of head gesture recognition system under cluttered backgrounds, shadow and sunshine conditions. Experimental results show the robustness in face detection, tracking and direction recognition of the proposed method.
Discovery of Pairwise Ordinal Edit Rules

Edit rules are simple tuple-level constraints that concisely model which tuples are not permitted in a consistent relation.Previously, developed algorithms mostly assumed nominal data.This implies that ordinal data either had to be discarded or discretized according to expert knowledge.We can omit this by working with the ordinal data directly.In this paper we explore the discovery of low lift pairwise ordinal edit rules and propose an efficient algorithm employing several pruning strategies derived from the lift measure.Our experiments show that we can obtain a similar precision as nominal algorithms, while having an acceptable computational cost.
New Discoveries of Petroglyphs in Vangchhia: A Preliminary Study

Vangchhia is a small village in Mizoram, lying on the Indo-Myanmar border. Many engraved menhirs were discovered at Vangchhia during the course of exploration. Also, petroglyphs were found in four localities of this particular village. Though their number is very limited, they are very significant for study as they will reflect the cultural life of the people who carved these petroglyphs before the current inhabitants of the area arrived. In terms of subject matter, they are similar in style and theme to their engraved counterparts on the menhirs found in this village. These petroglyphs are made by applying the simple methods of engraving and carving on the exposed rock outcrops situated on the hill slopes overlooking the Tiau River, which flows about a kilometer to the east of the petroglyph sites. It is worth studying these petroglyphs to reconstruct the cultural history of Mizoram mainly before the introduction of Christianity in Mizoram, as the Mizos stopped the practice of engraving petroglyphs onthe rock surfaces after their conversion to Christianity in the 19th century. So this work has been taken up for discussion. This paper will discuss the form, subject matter and distribution of the rock art sites in this village and the probable purpose of these petroglyphs.
Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes

We study the problem of robotic stacking with objects of complex geometry. We propose a challenging and diverse set of such objects that was carefully designed to require strategies beyond a simple pick-and-place solution. Our method is a reinforcement learning (RL) approach combined with vision-based interactive policy distillation and simulation-to-reality transfer. Our learned policies can efficiently handle multiple object combinations in the real world and exhibit a large variety of stacking skills. In a large experimental study, we investigate what choices matter for learning such general vision-based agents in simulation, and what affects optimal transfer to the real robot. We then leverage data collected by such policies and improve upon them with offline RL. A video and a blog post of our work are provided as supplementary material.
Calculation of centroid of high dimensional fuzzy number and application

In this paper, the conception of centroid of $n$-dimensional fuzzy number is introduced viaregarding its membership function as the density function on its support set, and some properties of it are obtained. Compared with the mean of the multi dimensional fuzzy number, the centroid takes into account the overall relationship between the edge membership functions of the membership function of the multi dimensional fuzzy number. Therefore, it can approximate (characterize) the fuzzy number more objectively and reasonably than using the mean of the multi dimensional fuzzy number. The most important work of this paper is that for two special kinds of multi dimensional fuzzy numbers (fuzzy $n$-cell numbers and fuzzy $n$-ellipsoid numbers), we respectively give calculation formulas, which can be used conveniently in application since the formulas are based on a definite integral of the level set functions of the multi dimensional fuzzy number on the unit interval $[0,1]$, rather than the multiple integral of the membership function of the multi dimensional fuzzy number itself on its support set. Then, by using the calculation formulas, we obtain another special property of the centroid for fuzzy $n$-cell number and fuzzy $n$-ellipsoid number. Finally, as an example of application, by using the centroid of multi dimensional fuzzy number, we define a fuzzy order on $n$-dimensional fuzzy number space, which can be used to rank uncertain or imprecise multichannel digital information.
The Acoustical and Language Modeling Issues on Uyghur Speech Recognition

Automatic speech recognition(ASR) is an important application that enables interaction of human beings with machines. Neural network based frameworks have been making some breakthroughs in low-source data processing so that the minority languages meet the great chance, in some cases. Thereupon, low-source languages, such as Uyghur, also get promising results in both speech recognition and natural language processing, as a result, a lot of papers have reported, one after another. In this paper, to begin with, several primary Uyghur speech recognition approaches are listed, then, their pros and cons are discussed respectively. we also attempt to discuss acoustic unit selecting for Uyghur speech recognition system, simultaneously n-gram and RNN language models are compared, in the end.
A New Approach to Modelling Students’ Socio-Emotional Attributes to Predict Their Performance in Intelligent Tutoring Systems

Intelligent Tutoring Systems (ITS) are computer-based learning environments that aim to imitate to the greatest possible extent the behavior of a human tutor in their capacity as a pedagogical and subject expert. One of the major challenges of these systems is to know how to adapt the training both to changing requirements of all kinds and to student knowledge and reactions. The activities recommended by these systems mainly involve active student performance prediction that, nowadays, becomes problematic in the face of the expectations of the present world. In the associated literature, several approaches, using various attributes, have been proposed to solve the problem of performance prediction. However, these approaches have failed to take advantage of the synergistic effect of students' social and emotional factors as better prediction attributes. This paper proposes an approach to predict student performance called SoEmo-WMRMF that exploits not only cognitive abilities, but also group work relationships between students and the impact of their emotions. More precisely, this approach models five types of domain relations through a Weighted Multi-Relational Matrix Factorization (WMRMF) model. An evaluation carried out on a data sample extracted from a survey carried out in a general secondary school showed that the proposed approach gives better performance in terms of reduction of the Root Mean Squared Error (RMSE) compared to other models simulated in this paper.
Putting Edmodo Into Classroom: Portraying Learning Management System (LMS) Manifestation

An array of teaching tools have been developed enormously today sparking interest for educators in their instruction. Edmodo, which is also one of the CALL applications that can be accessed online both from computer and mobile telephone is one option for teachers and students and can be operated to post various things related to EFL teaching-learning process. However, many educators are reluctant to embed with them pedagogical function which coming along in the use of Edmodo. This research employed open-ended questionnaire which is spread to English Language Education ULM students who are taking Extensive Reading course. This research contributes to picture out perception in implementing Edmodo as Web-Quest as well Learning Management System (LMS) in online classroom instructional activities. The result of this study shows that the involvement of Edmodo to material delivery still does not encounter the predicted expectation. The limited storing material in the application and lack of feedback of the task through the media are the reasons of the barrier. In conclusion, the use of Edmodo needs to be developed along with the mindset of students centered activities.