Reviewerly/exHarmony huggingface dataset:
SMARTPHONE APPLICATIONS FOR CONTACT TRACING IN COVID-19 EPIDEMIC: A SYSTEMATIC REVIEW

The great spread of the COVID-19 Pandemic and its effect on lifestyle around the world has led countries and organizations to accelerate the design or use of mobile health systems and applications to tackle and monitor the outbreak. Digital contact tracing applications have been proposed to automatically warning individuals at risk of infection and exposure. This systematic analysis discusses the various types of mechanisms and systems used in applications for digital contact tracing including Centralized, Decentralized, or Hybrid, in addition to, the used communication technologies such as Bluetooth, GPS, WiFi, and others, with a focus on user privacy and the efficiency of dealing with the extracted data. Four databases were scanned (IEEE Xplore, ScienceDirect, Web of Science, and PubMed) between 2015 and 2020. To review the collected 636 papers, precise exclusion criteria and selection strategies were applied. Only seven papers have been thoroughly analyzed and included in this study. The results in all papers have been presented to identify gaps and issues to supply an overview of the main aspects that need to be included and resolved in mobile applications that will be built to effectively restrict the spread of this pandemic and preserve full user privacy.
On Recurrent Neural Network Based Theorem Prover For First Order Minimal Logic

There are three main problems for theorem proving with a standard cut-free system for the first order minimal logic. The first problem is the possibility of looping. Secondly, it might generate proofs which are permutations of each other. Finally, during the proof some choice should be made to decide which rules to apply and where to use them. New systems with history mechanisms were introduced for solving the looping problems of automated theorem provers in the first order minimal logic. In order to solve the rule selection problem, recurrent neural networks are deployed and they are used to determine which formula from the context should be used on further steps. As a result, it yields to the reduction of time during theorem proving.
DIGITAL TRANSFORMATION IN TEACHERS’ EDUCATION

The Covid-19 crisis of the coronavirus has led to a change in business patterns in many areas. Educational institutions were able to quickly reorient and provide work remotely using digital technologies. Remote work is just one of the forms of work created by digitalisation. Digital solutions should not be seen as a one-off, COVID-19 crisis management tool, but as a systematic approach to digitization, as a solution to long-term competitiveness.Digital tools offer a wide range of opportunities to improve teaching and learning processes. To do this, teachers need to understand and accept digital innovations, as well as develop pedagogical digital competence. This points to the need for digital transformation in teacher education. The main challenge of digital transformation is to change the way teachers think and do. Digital transformation in education is an important process of change, which is based on the change of study content, methods, forms of work organization, teaching aids for work in the digital educational environment.The article analyzes the scientific literature and planning documents on digital transformation in teacher education and discusses recommendations for the development of teachers' pedagogical digital competence.
Building Goal-Oriented Dialogue Systems with Situated Visual Context

Goal-oriented dialogue agents can comfortably utilize the conversational context and understand its users' goals. However, in visually driven user experiences, these conversational agents are also required to make sense of the screen context in order to provide a proper interactive experience. In this paper, we propose a novel multimodal conversational framework where the dialogue agent's next action and their arguments are derived jointly conditioned both on the conversational and the visual context. We demonstrate the proposed approach via a prototypical furniture shopping experience for a multimodal virtual assistant.
도덕과교육에서 윤리학의 역할 고찰

This study explains that moral education through studies has distinctive characters and advantages from other methods of moral education and then tries to clarify the role and contribution of ethics in moral education through subjects. There are contradictions of developmental queries alternative accounts for discontinuities of development, in which very few people reach to the highest level of development. Moreover, in many empirical studies, regular schooling has been identified as a variable leading to high levels of moral development. It is because comprehensive social experience itself can sometimes interfere with moral development, and the specific impact of education has lead to high levels of moral development that lies in fostering the “moral reasoning ability” to adequately understand, explain, and judge moral issues. In addition, at ethical discourse levels, moral development means a shift from natural justification of moral judgment to a principled justification, so students should learn contents of moral thinking of high-quality. Thus, ethics in moral education through subjects plays a central role in raising abilities of moral reasoning in terms of how to study morality. Also it would constructs learning contents and provides reasons of principled justification of moral judgment and decision making. Moral education through subjects based on cognition or social cognition has distinctive features from other moral educations, and the effectiveness of education should be evaluated in consideration of these differences.
Theory and Method of Phase-Separation Analysis of Remote Sensing Information Field of Metallogenetic Environment and Nonmodel Ore-Deposit Prediction*

In this paper, the author proposes a new theory and method: the phase-separation analysis of remote sensing information field of metallogenetic environment and nonmodel ore-deposit prediction. By means of the theory and method, through decomposing and feature extracting of multisource information field of geological, geochemical and geophysical data based on RS, GIS and GPS techniques, a natural source model of ore-deposit can be established in order to predict the related deposits accurately. The theory and method have been practically applied in many tested areas and the effects are remarkable.
Typomorphism of сhromespinelides from the Holocene psephites of the Kyvvozhskoye gold-placer field (Volsko-Vymskaya ridge, Middle Timan)

The results of the study of accessory chrome spinels from heavy mineral concentrates of gold-bearing psephites of the Kyvvozhsky gold-placer field (Volsko-Vymskaya ridge, Middle Timan) are presented. As a result of the study of the typochemistry of chromspinelides, their genetic relationship with rocks of mainly alkaline-ultrabasic composition — analogues of Timanian Late-Riphean-Vendian ultramafites and Early-Middle Devonian alnoites is substantiated. The formation of magmatic sources of chrome spinels occurred in a wide range of geotectonic settings — from passive (platform) to active (island-arc subduction zones), which are more characteristic of the bulk of chrome spinels. The crystallization of chrome spinels, found as microinclusions in lherzolite pyropes in the same shlich samples of the Kyvvozhskaya gold-bearing area, is associated with the conditions of rift zones (spreading of the seabed). We made a conclusion about probable local (intra-valley) position of main magmatic sources of chrome spinels. The revealed chrome spinels, containing microinclusions of nickel and copper sulfides, are considered by the authors as indicators of igneous rocks containing platinum group minerals.
The issue of decisiveness in the COVID-19 outbreak in Korea

Based on five stakeholders (the central government, local governments, hospitals, businesses and local communities), the Republic of Korea must shift from its current indecisive approach to a decisive approach to the COVID-19 outbreak. Other nations should also consider the issue of decisiveness before it is too late.
CZECH UNIVERSITY TEACHERS’ PERSPECTIVES ON THE 2020 PANDEMIC

Following WHO’s declaration of a global pandemic in March 2020, the Czech Republic applied social distancing and a lockdown, which has had serious impacts on students, parents, and educators alike. Although distance and blended learning are modes well established and commonly used in the country, is can be assumed that the unforeseen and hasty shift online caught university teachers off guard and confronted them with a number of difficult challenges on the one hand, but also opportunities for professional development on the other. We investigated covid-related changes as perceived by university teachers who work at Czech departments of education in one of the nine subject fields. The online questionnaire survey was conducted over April 2021, i.e. one year after the introduction of the country-wide safety measures, allowing thus respondents to reflect on the whole year and verbalize their overall experience. Apart from a more general Preferences section, the questionnaire comprised 34 Likert-scale items that covered three key areas: Course, Lesson, and Support. Prior to interpreting the data, the reliability of the questionnaire was determined (r = 0.73), with none of its items fundamentally reducing its overall reliability. Using Kruskal-Wallis ANOVA and U test, responses of a representative sample of 364 teachers were analyzed with respect to their subject specification, university affiliation, sex, and years of teaching experience. Each area of interest showed statistically significant differences and similarities among groups of respondents. The findings complement a broader body of research that has been conducted across the globe to address the impacts of the pandemic on both teachers and learners.
Understanding Training-Data Leakage from Gradients in Neural Networks for Image Classification

Federated learning of deep learning models for supervised tasks, e.g. image classification and segmentation, has found many applications: for example in human-in-the-loop tasks such as film post-production where it enables sharing of domain expertise of human artists in an efficient and effective fashion. In many such applications, we need to protect the training data from being leaked when gradients are shared in the training process due to IP or privacy concerns. Recent works have demonstrated that it is possible to reconstruct the training data from gradients for an image-classification model when its architecture is known. However, there is still an incomplete theoretical understanding of the efficacy and failure of such attacks. In this paper, we analyse the source of training-data leakage from gradients. We formulate the problem of training data reconstruction as solving an optimisation problem iteratively for each layer. The layer-wise objective function is primarily defined by weights and gradients from the current layer as well as the output from the reconstruction of the subsequent layer, but it might also involve a 'pull-back' constraint from the preceding layer. Training data can be reconstructed when we solve the problem backward from the output of the network through each layer. Based on this formulation, we are able to attribute the potential leakage of the training data in a deep network to its architecture. We also propose a metric to measure the level of security of a deep learning model against gradient-based attacks on the training data.
Chaos Driven Evolutionary Algorithm: a Novel Approach for Optimization

This research deals with the initial investigations on the concept of a chaos-driven evolutionary algorithm Differential evolution. This paper is aimed at the embedding of simple two-dimensional chaotic system, which is Lozi map, in the form of chaos pseudo random number generator for Differential Evolution. The chaotic system of interest is the discrete dissipative system. Repeated simulations were performed on standard benchmark Schwefel’s test function in higher dimensions. Finally, the obtained results are compared with canonical Differential Evolution.
PREDIKSI TINGKAT KEKERUHAN (TURBIDITAS) MENGGUNAKAN CITRA SATELIT SENTINEL-2A DI WADUK JATILUHUR, JAWA BARAT

Turbidity is one of the remote sensing indicators on theÂ reservoir physical characteristics that can reduce its brightness level. Measuring reservoir physical characteristics traditionally are expensive and time consuming as well. Therefore, remote sensing is used as an alternative for turbidity measurement because it can provide data and products spatially, temporally as well as synoptically with low cost. This study aims to obtain an algorithm using a combination of in-situ turbidity data measurement and Sentinel-2A satellite imagery data. The resulting algorithm can be used to predict and map turbidity in Jatiluhur Reservoir. Based on the multiregression between B3 (green band) and B4 (red band) with in-situ turbidity data measurement, it is obtainted that the regression coefficients are a = 76.77, b = 63.22 and c = -34.31 respectively, with the equation of Y = 76, 77+63.22 X1-34.31X2 (Y=predicted turbidity, X1=lnB3, X2=lnB4). The correlation value between in situ and turbidity prediction is quite strong with a coefficient of determination (R2) of 0.60, and Root Mean Square Error (RMSE) of 1.95 NTU. Based on Mean Absolute Percentage Error (MAPE) analysis, the deviation is 31.1%. High levels of turbidity can reduce the main productivity of water and its organisms, especially in respiratory and visual problems. Sedimentation caused by high turbidity levels can make siltation which results in reservoir capacity loss.Keywords: Turbidity, remote sensing, Sentinel-2A satellite imagery data, Jatiluhur Reservoir, siltation
Praktek Requirement Engineering: Persiapan Implementasi Teknologi QR Code Pada Kegiatan Bimbingan Tugas Akhir

Abstrak: Maraknya penggunaan Smartphone sebagai sebuah teknologi yang saat ini dapat digunakan untuk melakukan verifikasi dan validasi pada proses pengesahan data transaksi, hal ini juga telah mendorong perkembangan teknologi agar dapat mendukung proses tersebut. Saat ini, teknologi QR Code telah dimanfaatkan untuk memudahkan penggunanya dalam melakukan proses pengesahan data transaksi (contoh: transaksi jual-beli, kehadiran suatu acara, registrasi pada suatu komunitas, dll.). Penelitian ini bertujuan untuk menunjukkan peluang bahwa teknologi QR Code dapat digunakan untuk verifikasi dan validasi pada proses pencatatan berita acara bimbingan Tugas Akhir (TA) yang terjadi antara Peserta TA dengan Pembimbing TA. Penelitian dilakukan dengan metode Requirement Engineering (RE) untuk memperoleh gambaran tentang kondisi sistem saat ini serta menganalisis data, proses, dan infrastruktur yang diperlukan. Penelitian ini menghasilkan hal-hal yang diperlukan untuk melakukan implementasi teknologi QR Code berupa spesifikasi sistem target yang dapat digunakan untuk menyiapkan organisasi dalam mengimplementasikan teknologi QR Code pada proses pencatatan kehadiran bimbingan TA.&#x0D; &#x0D; Kata kunci: requirement engineering, tugas akhir, teknologi QR code, verifikasi, validasi.&#x0D; &#x0D; Abstract: The rise of the use of smartphones as a technology that can currently be used to verify and validate the transaction data has encouraged the development of technology to support that process. At present, QR Code technology has been utilized to facilitate its users in the process of validating transaction data (for example: buying and selling transactions, the presence of an event, registration in a community, etc.). This study aims to show the opportunity that QR Code technology can be used for verification and validation in the process of recording the progress of final thesis activity that occurs between students and advisors. The study was conducted using the Requirement Engineering method to obtain an overview of the current state of the system and analyze the data, processes and infrastructure required. This research produced the system requirements to implement QR Code technology in the form of a system target specification that can be used to prepare organizations to implement QR Code technology in the process of recording the progress of final thesis activity. &#x0D; &#x0D; Keywords: final thesis, QR code technology, requirement engineering, verification, validation.
Pengembangan Kompetensi Literasi Digital bagi Widyaiswara pada Pembelajaran Dalam Jaringan

This paper discusses the competency development of Widyaiswara in implementing e-learning (online learning). E-Learning becomes a Distance Learning model that is implemented in the Era of the Technological Revolution and the COVID-19 pandemic. E-Learning methods are important in training as an effort to develop apparatus competence towards Smart ASN. By Online Learning and or Blended Learning, all aspects of training must be prepared. One of the keys is Widyaiswara who must have a new competency, namely digital literacy. This research is a qualitative research using literature study or reference tracing related to digital literacy competencies, and E- learning. It is also adjusted to various regulations regarding the development of ASN competencies, especially Widyaiswara. Data sources were also obtained through empirical studies, namely direct observation as participants in various Community of Practices (CoP) of Widyaiswara on WhatsApp Group, Telegram, Youtube Channel, and Google Class Room. The results show that digital literacy as part of digital intelligence must be a Widyaiswara competence in facing the Industrial and Technological Revolution in education and training. The ability to manage knowledge through Knowledge Management must coincide with competence in digital technology.
Video based human smoking event detection method

The paper proposes a method for recognizing smoking event detection from visual data. The method uses a three-dimensional convolutional neural network ResNet, which provides work with video based spatio-temporal features.
Development of Digital-Based Learning Media in Sociolinguistics Courses in the Pandemic Era

The rise of the Covid-19 virus affects all activities especially activities that need face-to-face.For this reason, the usage of digital is growing rapidly, including in teaching and learning process.Digital-based learning media need to be developed to increase the quality of learning especially in educational institutions during the pandemic.Prezi is a digital-based learning media that can develop various ideas in a narrative visual form.One of the courses in the Indonesian Language and Literature Education Study Program is Sociolinguistics which allows it to be presented using digital-based learning media, in this case Prezi.The purpose of this study was to describe the effectiveness of Prezi-based learning media in sociolinguistics courses at the Indonesian Language and Literature Education Study Program, Medan State University.The population in this study were all students of the 2019 Indonesian Language Education Study Program and the sample is 30 students.This study uses quantitative research methods in the form of experiments and descriptive research with the one group pre-test-post-test type.Student learning outcomes before using Prezi-based learning media in sociolinguistics courses get an average value of 70.2 with a standard deviation of 16.30 and a standard error of 2.9.After using Prezi-based learning media, the average score was 85.4 with a standard deviation of 9.32 and a standard error of 1.8.For this reason, the use of Prezi-based learning media is effectively used in sociolinguistic courses in the Indonesian Language and Literature Education Study Program.
Development of Digital Module on Early Childhood Health and Nutrition

The purpose of this study was to develop a digital module on early childhood health and nutrition.The development was carried out using the research and development research method by borg & gall, the test results from the small group showed an average score of 3.67 (good category), and the average score in the large group was 3.76 (good category).the final product is a module that can be accessed via smartphones, tablets, laptops, etc. via download from the playstore.The advantages of the digital module on early childhood health and nutrition are the many references used from the latest books and, this book is also designed with attractive illustrations and colors to increase reader motivation and increase the brain's ability to store information in the form of words, color and pictures, this book also arouses the reader's desire to think critically and conduct further analysis.
Weakly-supervised Generative Adversarial Networks for medical image classification

Weakly-supervised learning has become a popular technology in recent years. In this paper, we propose a novel medical image classification algorithm, called Weakly-Supervised Generative Adversarial Networks (WSGAN), which only uses a small number of real images without labels to generate fake images or mask images to enlarge the sample size of the training set. First, we combine with MixMatch to generate pseudo labels for the fake images and unlabeled images to do the classification. Second, contrastive learning and self-attention mechanism are introduced into the proposed problem to enhance the classification accuracy. Third, the problem of mode collapse is well addressed by cyclic consistency loss. Finally, we design global and local classifiers to complement each other with the key information needed for classification. The experimental results on four medical image datasets show that WSGAN can obtain relatively high learning performance by using few labeled and unlabeled data. For example, the classification accuracy of WSGAN is 11% higher than that of the second-ranked MIXMATCH with 100 labeled images and 1000 unlabeled images on the OCT dataset. In addition, we also conduct ablation experiments to verify the effectiveness of our algorithm.
Development and Investigation of Adaptive Micro-Service Architecture for Messaging Software Systems

Messaging Software systems (MSS) are one of the most popular tools used by huge amount of people. They could be used for personal communication and for business purposes. Building an own MSS system requires analysis of the quality attributes and considering adaptation to the changing environment. In this paper an overview of existing MSS architecture was done. Data model was developed to support historical and real time data storage and processing. An own approach to build Adaptive Microservice MSS based on the messaging middleware and NoSQL database was proposed.
Cross Account Infrastructure Migration

Cloud computing has been identified as one of the most promising technology which provides highly secured, scalable and optimal Information Technology (IT) infrastructure solutions that too at very low costs. Due to usage of cloud at such a large scale, it gives rise to a wide range of use cases. One use case which has become quite popular in recent times is the migration of the cloud resources between two Amazon Web Services (AWS) accounts. To migrate the infrastructure from one account to another account, the organizations using AWS cloud have either explicit teams, trained to take care of the cloud services or employees from other teams are responsible for the same-which are responsible for migration of the resources. The transfer is done manually and it is a cumbersome and time taking task for the teams. This paper proposes a method to automate the process of migration It gets the resources onboard to a level such that they can directly deliver the results in a very less time and less human effort and hence help in improving customers’ experience.