Reviewerly/exHarmony huggingface dataset:
자연언어처리에서 훈련데이터 확장을 위한 연구 동향

Deeplearning is applied to the field of natural language processing, and the learning model by encoder-decoder model is used. Neural network-based natural language processing techniques mostly use sequence-to-sequence models and train the model with supervised learning. The success of such end-to-end deep neural network depends on securing a large amount of learning data to train the model. It takes a lot of time and money to build a large I / O dataset. Recent studies are looking into ways to secure performance by expanding scarce datasets. In this paper, we describe the data set expansion methods, such as the denoising training method, transfer learning, and pre-learning BERT. We discuss the recent application of data set expansion to. the machine translation system
Transaction Fraud Detection using Invisible Keyboard and Face Detection

With the popularization of on-line trying, dealings fraud is growing seriously. Therefore, the study on fraud detection is attention-grabbing and vital. a big manner of police work fraud is to extract the behavior profiles (BPs) of users supported their historical dealings records, thus to verify if associate incoming dealings is additionally a fraud or not ocular of their bits per second. Markov process models unit widespread to represent bits per second of users, that's effective for those users whose dealings behaviors unit stable relatively. However, with the event and popularization of on-line trying, it's a heap of convenient for users to consume via Infobahn that diversifies the dealings behaviors of users. Therefore, Markov process models unit unsuitable for the illustration of those behaviors. Throughout this paper, we've an inclination to propose logical graph of BP (LGBP) which will be an entire order-based model to represent the relation of attributes of dealings records. Supported LGBP and users dealings records, we tend to square measure ready to cipher a path-based transition likelihood from associate attribute to a definite one. Here we tend to square measure ready to realize Face by pattern viola jones and LBP acknowledge formula for face detection as we tend to use invisible keyword sequence for authentication of OTP. The keyword sequence modification once. At constant time, we've an inclination to stipulate associate knowledge entropy-based diversity constant thus on characterizes the variability of dealings behaviors of a user. we've an inclination to additionally track fraud user with location by mackintosh address of the user laptop pc transportable or computer that have last dealings successfully. additionally , we've an inclination to stipulate a state transition likelihood matrix to capture temporal choices of transactions of a user. Consequently, we tend to square measure ready to construct a BP for every user thus use it to verify if associate incoming dealings is additionally a fraud or not. Our experiments over a true data set illustrate that our methodology is healthier than three progressive ones
Adaptive Digital Image Watermarking for Color Images using Wavelet

Internet and social media have become an inseparable part of the human life which has led to extensive sharing of all kinds of digital information including but not limited to photos and videos. The risk of plagiarism and counterfeiting follows with the technology of information sharing. Digital watermarking deals in encrypting useful information within various forms of media for copyright protection and authentication. In this paper, an algorithm is used to embed a colored watermark image within colored cover image in a robust fashion. In the proposed technique, principal component analysis (PCA) is applied to get compressed watermark image. By using Bhattacharyya distance and kurtosis, the embedding and scaling factors are computed to create an adaptive digital watermarking mechanism. The embedding and extraction algorithms are developed by considering image segmentation in RGB space. Performance of the proposed method was tested using PSNR and NCC parameters on multiple cover and watermark images and also by considering common image processing attacks like salt and pepper, cropping, rotation.
일반 수업과 IC-PBL 적용 수업의 비교를 통한 패션복식사의 교육 효과 연구

The purpose of this study was to present the case of class operation by paralleling a general instructor''s lecture class and a IC-PBL class in a fashion design major course and comparing the educational effects. The teaching model of this study was designed to improve the ability to use the knowledge gained in accordance with the needs of the industrial field and to develop an independent learning ability. It will provide meaningful data. This study measured and considered the qualitative items of self-efficacy and changes in class perception through interviews and questionnaires completed by the learners after experiencing each general class and IC-PBL class. The results of this study are, first, that in the History of Fashion and Costume class, the general teaching method and the IC-PBL teaching method were applied in parallel to design a class, and a method case was presented. Second, as a result of comparing the educational effects of the two teaching methods through a student questionnaire, IC-PBL was more effective in improving learning attitude, learning achievement and self-efficacy. In addition, after the IC-PBL class on History of Fashion and Costume, the students'' negative perception of team activities improved, and the students'' cooperative ability and creativity improved.
Inferring a shallow degassing model for Villarrica Volcano from seismic explosion signals and SO2 flux

&amp;lt;p&amp;gt;Villarrica is a basaltic volcano with an active lava lake in South Central Chile. The lava lake displays a variety of degassing styles from gentle seething to more violent Strombolian explosions. This activity is accompanied by sequences of transient seismic waveforms suggesting the presence of discrete gas bubbles in the upper magma column. Gas bubbles flow through liquid-filled pipes according to distinct patterns depending on viscosity of the liquid and volumetric gas flow rate. Laboratory experiments indicate that these regimes are characterized by distinct frequency distributions of bubble sizes and spacings. By assuming that these parameters are reflected by the magnitude of the transients and the time between them, we compared their statistical distributions to infer a flow regime for the shallow conduit of Villarrica. The approximately log-normal distributions indicate a sustained slug flow regime in which the gas ascends in trains of conduit-wide gas slugs. The event catalog for our analysis contained about 20,000 events and was generated from 12 days of seismic data from March 2012 acquired by a dense local network. A well-known problem in earthquake statistics is the incompleteness of event catalogs towards low magnitudes due to decreasing detectability in the ambient noise. We estimated the actual distribution of magnitudes by using a Monte Carlo simulation of the event detection based on the statistical properties of the observed seismic noise. The unknown source depth and mechanism introduce further ambiguity regarding the distributions. Nevertheless, we hope to refine the degassing model by taking into account degassing rates, magma properties and more detailed analysis of the nature of the seismic events.&amp;lt;/p&amp;gt;
PUSAT KEGIATAN GAME ONLINE DENGAN KONSEP ARSITEKTUR HIGH TECH DI JAKARTA

ABSTRACT The Online Game Activity Center is a place that provides various needs and accommodates various activities for online game lovers and online game developers. In Indonesia, especially Jakarta, many people play online games, some use computers/PCs, smartphones/cellphones, consoles/consoles, and Virtual Reality/VR, and some hold and implement online game tournaments, but there are no good places and facilities and adequate which can cover all activities in online games.At this Online Game Activity Center all needs are provided in one place which is expected to be a place that can accommodate all activities related to online games. The concept of High Tech Architecture is applied by using functional and aesthetic building materials in buildings that can emphasize and accentuate the structure and technology of the building.
Development of an Information Technology-Enabled Learning Environment for Bataan Peninsula State University

The research Information Technology-Enabled Learning Environment for Bataan Peninsula State University was developed to provide an easier and faster process of submission of class requirements and ratings of student works which will help the faculty members to manage their classes efficiently via intranet and an internet-based connection.  It is capable of allowing the students to submit soft copies of their requirements such as major course output, laboratory exercises, case studies, and other projects.  Faculty members are allowed to validate currently enrolled students, create classes, accept students in listed classes, post announcements through the content feeds, and maintain grading system per course and its rubrics of assessment. Finally, the application allows students to check announcements, requirements, and projects posted by the faculty member through the content feeds.  The system was developed using PHP as the programming language, Apache for the webserver, MySQL as the Database Engine.  It passes the user’s acceptability evaluation based on ISO 2510102011 with sub-criteria such as effectiveness, efficiency, satisfaction, freedom from risk, and context coverage.
Nested Mixture of Experts: Cooperative and Competitive Learning of Hybrid Dynamical System

Model-based reinforcement learning (MBRL) algorithms can attain significant sample efficiency but require an appropriate network structure to represent system dynamics. Current approaches include white-box modeling using analytic parameterizations and black-box modeling using deep neural networks. However, both can suffer from a bias-variance trade-off in the learning process, and neither provides a structured method for injecting domain knowledge into the network. As an alternative, gray-box modeling leverages prior knowledge in neural network training but only for simple systems. In this paper, we devise a nested mixture of experts (NMOE) for representing and learning hybrid dynamical systems. An NMOE combines both white-box and black-box models while optimizing bias-variance trade-off. Moreover, an NMOE provides a structured method for incorporating various types of prior knowledge by training the associative experts cooperatively or competitively. The prior knowledge includes information on robots' physical contacts with the environments as well as their kinematic and dynamic properties. In this paper, we demonstrate how to incorporate prior knowledge into our NMOE in various continuous control domains, including hybrid dynamical systems. We also show the effectiveness of our method in terms of data-efficiency, generalization to unseen data, and bias-variance trade-off. Finally, we evaluate our NMOE using an MBRL setup, where the model is integrated with a model-based controller and trained online.
Construction of a Mathematical Model to Describe the Dynamics of Marine Technical Systems With Elastic Links in Order to Improve the Process of Their Design

A mathematical model (MM) has been developed to describe the dynamics of the MTS EL element using an underwater towed system (UTS) as an example, as well as the MM of MTS with EL.The MM of the EL element dynamics makes it possible to take into consideration:1) the movement of a carrier vessel (CV);2) features of the EL design, which affect the functional characteristics MTS; 3) the movement of an underwater vehicle (UV); 4) the impact of obstacles along the path of UV and EL;5) large movements of EL as part of MTS.The mathematical model of MTS with EL makes it possible to solve the following tasks:1) to determine a change in the shape of EL and the forces of its tension in the process of maneuvering of CV and UV taking into consideration sea waves, wind loads on CV, the sea depth and its change in the assigned water area, the mass and elastic properties of EL; 2) to determine the relative position of CV and UV in the process of their maneuvering;3) to determine the maximum loads on EL necessary to assess its strength during the maneuvering of CV and UV.Analysis of design tasks in the construction of marine tethered systems (MTdS) as a variety of MTS reveals that the calculation of MtdS EL is associated with significant theoretical complexity and is science-intensive. The proposed procedure for improving the design of MTS with EL, based on the MM that describes the dynamics of MTS EL (as well as MTS with EL), makes it possible to investigate the different modes of operation of almost all classes of MTdS. Using it could improve existing methods of calculating and designing MTdSs with EL thereby bringing them to the level of an engineering application
사회지지적 인식이 미용전공 대학생의 전공만족도와 진로방향에 미치는 영향

This study investigated the effects of social support perception on satisfaction with academic major and career direction among college students majoring in cosmetology. For this, a questionnaire survey was conducted among college students from cosmetology-related departments in Busan. A frequency analysis was performed to analyze subjects’ general characteristics. To determine the influence of the perception of social support on their satisfaction with academic major and career direction, a correlation analysis and regression analysis were carried out using SPSS 18.0. The results found the following: Social support perception revealed a statistical significance in relationship with academic major satisfaction and career direction. It seems reasonable to say that efforts to enhance such social support perception are a critical factor affecting students’ satisfaction with their academic major and career direction. In addition, since academic major satisfaction plays a mediating role in social support perception and career direction, colleges’ efforts to improve such academic major satisfaction and upgrade the quality of education have a statistically significant effect on decisions regarding career path despite low social support perception. Therefore, it making efforts to enhance students’ satisfaction with their academic major seems to be of critical urgency.
Fuzzy Bayesian Context-Aware System to Reduce Electricity Consumption

Context-awareness develops smart, intelligent IoT devices that can adapt to changing needs and act autonomously on behalf of the user. The main challenge of context-aware internet of things is to interpret the context effectively. There is an abundance of CAIOT in literature. Understanding of the meaning of the context is, however, almost ignored. Misinterpretation of context can lead to an incorrect decision that motivates to develop a system that emphasis context reasoning and decision making using the fuzzy Bayesian approach. The current investigation aims to build a context-aware IoT system using occupancy detection for energy management. The performance evaluation for the proposed system uses data collected in the tutorial room to detect occupancy. Extensive experiments highlight the utility of the proposed approach, which significantly reduces energy than the traditional ON/OFF usage pattern through customer access via mobile phone or personal computer.
A Probabilistic Model For Co-Occurrence Analysis in Bibliometrics

Abstract The co-occurrence analysis of Medical Subject Heading (MeSH) terms in the bibliographic database is popularly used in bibliometrics. Practically for making the result interpretable, it is necessary to apply a certain filter procedure of co-occurrence matrix for removing the low-frequency items that should not appear in the final result due to their low representativeness for co-occurrence analysis. Unfortunately, there is rare research referring to determine a critical threshold to remove noise of data for co-occurrence analysis. Here, we propose a probabilistic model for co-occurrence analysis that can calculate statistical significance (p-values) of co-occurred items. With help of this model, the dimensionality of co-occurrence network could be conveniently reduced according to selection of different levels of p-value thresholds. The conceptual model framework, simulation and practical applications are illustrated in the manuscript. Further details (including all reproducible codes) can be downloaded from the project website: https://github.com/Miao-zhou/Co-occurrence-analysis.git.
Relevance of Neighbouring Rights in India in the Context of the 2019 European Union Directive

Neighbouring rights, which form a subset of copyrights, are those subsidiary, yet parallel, rights that are accrued to a specific class of people that comprises not the actual authors but the neighbours to the authors. The class includes performers, broadcasters, producers and organizers, etc., and in some countries, makers of databases. Of late, as per European Union (EU) Directive No. 2019/790 dated 17th April 2019, the press publishers have also been included in the class. The primary objective of this paper is to revisit neighbouring rights in India in the context of the impugned provisions of the EU Directive on the neighbouring rights of press publishers. The paper tries to know whether it is a ripe time to extend such neighbouring rights to press publishers in India. To reach a logical conclusion, the paper reviews the existing literature on neighbouring rights jurisprudence in India in reference to the Copyright Act, 1957. It also assesses the international instruments governing neighbouring rights, especially the Rome Convention. Last but not the least, it critically reviews the impugned provisions of the 2019 Directive. The paper employs analytical and descriptive methods to testify facts and theoretical frameworks governing the subject.
Tsallis-INF: Improved Robustness to Adversarial Corruptions in Stochastic Multi-armed Bandits and Beyond

We derive improved regret bounds for the Tsallis-INF algorithm of \citet{zimmert2020}. We show that in adversarial regimes with a $(\Delta,C,T)$ self-bounding constraint the algorithm achieves $\Ocal\lr{\lr{\sum_{i\neq i^*} \frac{1}{\Delta_i}}\log_+\lr{\frac{(K-1)T}{\lr{\sum_{i\neq i^*} \frac{1}{\Delta_i}}^2}}+\sqrt{C\lr{\sum_{i\neq i^*}\frac{1}{\Delta_i}}\log_+\lr{\frac{(K-1)T}{C\sum_{i\neq i^*}\frac{1}{\Delta_i}}}}}$ regret bound, where $T$ is the time horizon, $K$ is the number of arms, $\Delta_i$ are the suboptimality gaps, $i^*$ is the best arm, $C$ is the corruption magnitude, and $\log_+(x) = \max\lr{1,\log x}$. The regime includes stochastic bandits, stochastically constrained adversarial bandits, and stochastic bandits with adversarial corruptions as special cases. Additionally, we provide a general analysis, which allows to achieve the same kind of improvement for generalizations of Tsallis-INF to other settings beyond multiarmed bandits.
Resource Evaluation of Valuable and Toxic Tailing Components by Electrotomography Data and Geochemical Sampling

Summary Mining activity entails the accumulation of sulfide-bearing mill wastes with high concentrations of ore and toxic elements. This paper reports on the results of the complex geophysical and geochemical investigation of mine tailing in the Kemerovo region, Russia. The aim of the work was to build a three-dimensional geoelectric model of the tailing, to assess the volumes of man-made bodies, the resources of valuable and toxic components. According to the most conservative estimates, the total volume of dump is about 711,000 m3, water-soluble Arsenicum 827 kg, and the gold content was calculated, which is 331 kg. Besides the numerical relationship between the pH value and the resistivity have been establishedю
Media and Moral Education: A Philosophy of Critical Engagement

Educational TheoryVolume 70, Issue 6 p. 807-816 BOOK REVIEW Media and Moral Education: A Philosophy of Critical Engagement Drew Chambers, Drew Chambers Harvard UniversitySearch for more papers by this author Drew Chambers, Drew Chambers Harvard UniversitySearch for more papers by this author First published: 21 June 2021 https://doi.org/10.1111/edth.12455Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Volume70, Issue6Special Issue: Symposium: Democracy in Crisis and Education: Educating for Citizenship in the Age of PopulismDecember 2020Pages 807-816 RelatedInformation
A novel approach for the geospatial modelling and resource assessment of tailings storage facilities

&amp;lt;p&amp;gt;Tailings are the fine-grained residues of ore processing operations, typically stored in dedicated tailings storage facilities (TSFs). Despite being viewed as &amp;amp;#8216;waste&amp;amp;#8217; materials, tailings can contain significant amounts of valuable metals which were not recovered by original processing techniques or were previously not of economic interest. Re-processing of tailings deposits for the recovery of remaining metals has the additional benefits of mitigation of environmental hazards posed by the TSFs, such as Acid Mine Drainage (AMD). The estimation of mineral resources requires the construction of accurate and reproducible geospatial models. However, the sedimentary-style deposition and subsequent weathering of tailings results in a complex internal structure which is challenging to model, with a laterally and vertically heterogeneous distribution of the minerals comprising the residues. The present study investigates a novel approach for the geospatial modelling of a TSF case study. The surface of the tailings deposit was densely sampled in order to assess the intrinsic horizontal variability. Drill core samples were taken from a depth of 1-3 m, on a 30 m grid and nested grids of 15 m and 7.5 m, with additional random and twin holes. The entire depth of the TSF was sampled in 2 m intervals with a total of 10 drill holes to assess vertical variability. All drill core samples were analysed with x-ray fluorescence spectrometry and inductively coupled plasma mass spectrometry. The compositional data was log-ratio-transformed and variography and subsequent ordinary kriging and co-kriging were performed on the surface samples. The variogram models obtained for the surface samples were then applied for kriging of the deeper layers. Historical photographs of the surface of the TSF were used to improve estimates with co-kriging for the corresponding layers. The entire data set will be used to determine the most efficient sampling approach for the resource estimation of TSFs.&amp;lt;/p&amp;gt;