Reviewerly/exHarmony huggingface dataset:
AUGMENTED REALITY AND EDUCATION SCIENCES

The present paper reviews the field of Augmented Reality, starting from the current research and publications of this specialization, starting from the premise that augmenting reality implies an extension of virtual reality. Thus, types of implementations of augmented reality will be presented, emphasizing the HMD type, referring to an application of this kind, made by the author. Based on the application, the observations from a public presentation of it and, taking into account the way in which RA flirts with education, the educational perspectives of and how they can be implemented in the educational system will be presented. Also, in this paper will be presented the limitations of this technology, given that not every educational subject can be presented and taught in an immersive environment.For the implementation of the application under discussion, the technology was used Microsoft HoloLens 1 that combines an untethered device with apps and solutions that help people across your business learn, communicate, and collaborate more effectively.
PENERAPAN MODEL NUMBER HEAD TOGETHER DALAM MOTIVASI DAN HASIL BELAJAR MATA KULIAH BAHASA INGGRIS UNTUK MEMPERSIAPKAN SDM UNGGUL

The objective is to know the increase of students learning motivation and students outcome through implementation of cooperative learning with Numbered Heads Together method of the English subject.&#x0D; This experimental research is using designing Classroom Action Recearch by applying qualitative approach as well as it is conducted in two cycles in which it involves planning, action, observation, and reflection. &#x0D; The result that the comparison result of students between the first and second cycles is significant and rise sharply, meaning that, second cycles is quite good seen from students’ motivation consisting of Interest (57.33%; 88) %, concentration (62.67%; 92%), attention (56%; 85,33%), perseverance (61,33%; 87,33%). The average increase is 26% from the first to 2nd cycles.
Are All the References Mentioned in Academic Papers? A Quantitative Analysis of the Nonmentioned Phenomenon

The nonmentioned phenomenon is when citations or references are missing from the body of the paper, and the phenomenon may be abnormal citing behavior that results from the negligence of the author or editor. Therefore, this study selected 40 journals in five different disciplines and carried out a comparative study. The research methods employed in this study were multivariate statistical analysis and similarity calculations. The results show that 3.45% of papers included the nonmentioned phenomenon and that the similarity between nonmentioned references and the cited paper are so low as to disqualify part of the nonmentioned references. Further, since the nonmentioned phenomenon did not appear in 96.55% of papers, it can be concluded that although most of the papers are consistent with citation normativeness, the nonmentioned phenomenon does exist in scientific papers. This study provides evidence to suggest that the nonmentioned phenomenon should receive more attention in the academic world.
Opportunities for determining factors affecting the development of intelligent security systems models

Contemporary security challenges require the creation of a continuous and manageable process that guarantees the survival and sustainability of the organization's core activities before, during and after a devastating event. This means that it is necessary to manage the organization's activities, resources, personnel, impact on its functioning and countless risks. Significant contribution in this direction provides intelligent security systems.Thanks to rapid technological progress it is possible to be developed sophisticated security systems able to integrate heterogeneous sources that can monitor, control and manage the security environment of the organization, which is potentially at risk. But the combination of different technologies is not sufficient to significantly increase the level of security and the approach to the integrity of system elements, and compatibility with other systems management organization are basic factors for success in this direction.
Estimating COVID-19 Under-Reporting Across 86 Nations: Implications for Projections and Control

Abstract Based on detailed stratigraphy, petrology and geochemistry, the initial arc magmatism of the Oman Ophiolite consisting of tholeiitic lavas followed by boninite flows and tephras is studied in the Wadi Bidi area, northern Oman Mountains. An 1110-m-thick V2 sequence is divided into the lower 970 m (LV2) and upper 140 m (UV2) thick subsequences by a 1.0-m-thick sedimentary layer. Pahoehoe flows dominate in the lower part of the LV2, while the upper part consists mainly of sheet flows with sparse interbedded pelagic sediments and a cylindrical plug. In addition to the presence of a feeder conduit, the flow-dominant lithofacies with a few thin sedimentary interbeds in the LV2 indicates that the study area was the centre of a volcano grown in a short period. The UV2 is composed of boninite sheet flows overlain by a 2.0-m-thick pyroclastic fall deposit. A small amount of boninite lavas at the end of the V2 sequence overlain by thick pelagic sediments suggests that the subduction-related arc volcanism was short lived and terminated long before the ophiolite obduction. Supplementary material: Locations, mode of occurrence, phenocryst assemblages and bulk-rock major and trace element compositions of lavas in the Wadi Bidi area are available at http://www.geolsoc.org.uk/SUP18684.
Bocconotto, fruttone e pasticciotto in Terra d’Otranto tra storia, onomasiologia e semasiologia

The paper analyses the geographical, lexical and semantic variation of three words belonging to the language of gastronomy: bocconotto , pasticciotto and fruttone . These three gastronymes are widespread (at least, the first two) mainly in the central-southern area where, in many of the variants, they can be considered geosynonyms (and, sometimes, geohomonyms). However, they develop a singular lexical and semantic evolution in Puglia, in the Salento micro-area, which is the privileged object of investigation of this study. The geolinguistic variation leads to a situation of pseudo-geosynonymy that in this work we will try to examine by following the diachronic evolution of the three words characterized by lexical, onomasiological and semasiological variants. The lexical investigation, while not excluding other aspects considered important for the purposes of the survey (that is popular legends, newspaper articles, blogs, specialized websites), concerns above all the attestations that can be taken from ancient culinary literature and from lexicographic repertoires. Furthermore, a clarification is required: when we speak about the language of gastronomy, the reconstruction of the origin and diffusion of the entries is always a difficult task.
The Digital Layer: How Innovative Firms Relate on the Web

In this paper, we introduce the concept of a Digital Layer to empirically investigate inter-firm relations at any geographical scale of analysis. The Digital Layer is created from large-scale, structured web scraping of firm websites, their textual content and the hyperlinks among them. Using text-based machine learning models, we show that this Digital Layer can be used to derive meaningful characteristics for the over seven million firm-to-firm relations, which we analyze in this case study of 500,000 firms based in Germany. Among others, we explore three dimensions of relational proximity: (1) Cognitive proximity is measured by the similarity between firms’ website texts. (2) Organizational proximity is measured by classifying the nature of the firms’ relationships (business vs. non-business) using a text-based machine learning classification model. (3) Geographical proximity is calculated using the exact geographic location of the firms. Finally, we use these variables to explore the differences between innovative and non-innovative firms with regard to their location and relations within the Digital Layer. The firm-level innovation indicators in this study come from traditional sources (survey and patent data) and from a novel deep learning-based approach that harnesses firm website texts. We find that, after controlling for a range of firm-level characteristics, innovative firms compared to non-innovative firms maintain more numerous relationships and that their partners are more innovative than partners of non-innovative firms. Innovative firms are located in dense areas and still maintain relationships that are geographically farther away. Their partners share a common knowledge base and their relationships are business-focused. We conclude that the Digital Layer is a suitable and highly cost-efficient method to conduct large-scale analyses of firm networks that are not constrained to specific sectors, regions, or a particular geographical level of analysis. As such, our approach complements other relational datasets like patents or survey data nicely.
ADAPTIVE WATERMARKING BASED ON DWT/ DCT/ SVD

Many different watermarking methods have been developed since its appearance, most of them are based on mathematical transformations. In this paper, we used a hybrid watermarking algorithm by combining the discrete cosine domain (DCT coefficients, singular value decomposition) and the wavelet domain. By exploiting the results obtained, we were able to increase the size of the mark to be inserted and improve the reconstruction of the mark after an attack.
The Relationship Between Peer Acceptance and Online Game Addiction in Adolescents

At the stage of adolescent development, the existence of peers is an important factor in a teenager's friendship. Adolescents have a strong need to be accepted by peers or groups. Adolescents will feel happy when accepted in their peer environment, and on the other hand, adolescents will feel very distracted and anxious if they are excluded and belittled by their peers. The goal of teenagers who participate in online game play is not only looking for winners but also as a medium for making friends. Currently the types of online games that are popular among teenagers are Mobile Legends: Bang Bang, PUBG (PlayerUnknown's Battlegrounds) Mobile, Garena Free Fire which is a type of online game that can be played together or called a multiplayer online game. This encouraged the researcher to observe the relationship between peer acceptance and online game addiction in adolescents. The purpose of this study is to see the relationship between peer acceptance and online game addiction in adolescents. This research used quantitative methods. Participants in this study were 121 adolescents in one of the public high schools in Medan. Measuring instrument being used was the peer acceptance scale and the online game addiction scale made by the researcher. Results of this study found a correlation value (R) of .371 and the coefficient of determinant (R) Square of .138 and Sig .000. This means that peer acceptance has a positive and significant relationship with online game addiction. The effect contribution of peer acceptance on the online game addiction is 13.8%, while the remaining 86.2% shows other factors that were not examined in this study.
Visual object tracking based on Siamese network and online patch filters

Visual object tracking is one of the popular research topics in computer vision. It has a wide range of application scenarios. Although recent approaches based on siamese network have achieved good performance, similar interference and non-real-time speed are still very challenging problems. In this paper, an online Patch Filter Network (OPFNet) is proposed, the online patch filters learned from the target can introduce the local detailed features and avoid the interference of similar objects. In addition, in order to enhance the generalization ability of the tracker trained with small scale dataset, an image mix-up method for augmentation is proposed during offline training process. These improvements are proved to be effective by experiments and can be applied to existed siamese tracking methods
Catalyst boosts prospects for fuel-cell vehicles

A record-breaking catalyst could help a new generation of fuel-cell electric vehicles draw their hydrogen supplies from liquid fuels such as methanol. By purifying the hydrogen stream that feeds the fuel cell, the catalyst may improve the prospects for a climate-friendly technology that has struggled to gain a commercial foothold. The catalyst is made from particles of molybdenum carbide studded with platinum (Pt/MoC) and converts carbon monoxide and water into carbon dioxide and hydrogen—an industrially important reaction known as the water-gas shift (WGS) reaction. The new catalyst is at least 10 times as active as previously reported WGS catalysts and works at relatively low temperatures ( Nature 2021, DOI: 10.1038/s41586-020-03130-6 ). “It’s a very active system which outperforms current systems,” says Bert M. Weckhuysen of Utrecht University, who designs and studies solid catalysts and was not involved in the work. Hydrogen fuel cells generate electricity by combining hydrogen and oxygen.
Image Classification Using Reinforcement Learning

Recently, such a direction of machine learning as reinforcement learning has been actively developing. As a consequence, attempts are being made to use reinforcement learning for solving computer vision problems, in particular for solving the problem of image classification. The tasks of computer vision are currently one of the most urgent tasks of artificial intelligence.&#x0D; The article proposes a method for image classification in the form of a deep neural network using reinforcement learning. The idea of ​​the developed method comes down to solving the problem of a contextual multi-armed bandit using various strategies for achieving a compromise between exploitation and research and reinforcement learning algorithms. Strategies such as -greedy, -softmax, -decay-softmax, and the UCB1 method, and reinforcement learning algorithms such as DQN, REINFORCE, and A2C are considered. The analysis of the influence of various parameters on the efficiency of the method is carried out, and options for further development of the method are proposed.
An Overview of Analytical Learning: Explanation Based Learning

Learning methods such as neural network and decision tree need a certain number of training samples to achieve a certain level of generalization accuracy. Analytic learning uses prior knowledge and deductive reasoning to expand the information provided by ...
Estimation of Water Quality Parameters in the Sepidrood River by ANFIS, GEP and LS-SVM Models

Rivers are the most important water supply resource for the drinkable, agricultural and industrial demands. Therefore, estimation of water quality parameters in rivers is an essential and necessary task. This research applies the Adaptive Neuro-Fuzzy Inference System (ANFIS), the Least Squares-Support Vector Machines (LS-SVM) and the Gene Expression Programming (GEP) for estimation of Total Dissolved Solids (TDS), Electrical Conductivity (EC) and Total Hardness (TH) in the Sepidrood River and a 40 year period. The applied performance criteria are the correlation coefficient (R), the Nash-Sutcliffe model Efficiency coefficient (NSE), the Normalized Mean Squared Error (NMSE) and the Mean Absolute Error (MAE). These methods have high ability for estimation of water quality parameters. The best method is LS-SVM method for estimation of TDS (RTrain=0.95 RTest=0.96). The best method is GEP method for estimation of EC (RTrain=0.94 RTest=0.95). The best method is ANFIS method for estimation of TH (RTrain=0.92 RTest=0.94). This research shows that intelligence methods can estimate unmeasured concentration of qualitative parameters by concentration of other qualitative parameters.
PENGGUNAAN STRUKTUR DAN UNSUR KEBAHASAAN DALAM TEKS DESKRIPSI SISWA KELAS VII SMP NEGERI 23 PADANG

ABSTRACTThis type of research is qualitative with descriptive methods. The data of this research are in the form of structure and linguistic elements from students' descriptions. The data source of this research is the description text of Grade VII students of SMP Negeri 23 Padang. The research instrument is the researcher himself. Data collection techniques through documentation study. The data collection technique in this research is the triangulation technique (Cross-Check). Data were analyzed by steps, (1) identifying common elements contained in the description text, (2) analyzing the text based on the aspects studied, namely the structure and linguistic elements of the description text, (3) the results of the analysis from the researcher were re-examined by the informant triangulation, (4) make conclusions. Based on the results of the study, the following three things were concluded. First, the structure of the text consists of the identification and description of parts. Identification / General description In the text description of the eighth grade students of SMP Negeri 23 Padang as a whole have been identified. Of the 35 data that have identification, there are 11 data that combine identification with the Description section. Next, the general description of the student's writing section is detailed. Evident from 35 texts that have a section description structure there are 14 texts whose description section consists of one paragraph and 1 text whose description of the section joins with identification. Second, in terms of language. The basic pattern of sentences that students use most often is SPK, while the sentence that is used most rarely is SPOPel. Third, the pattern of student reasoning that is most widely used is deductive reasoning. Of the 87 paragraphs there are 70 paragraphs using deductive reasoning, 2 paragraphs using inductive reasoning, and 15 paragraphs of incorrect reasoning patterns. Kata kunci:Struktur, Kalimat, Pola Penalaran Teks Deskripsi
Cryptocurrencies: Applications and Investment Opportunities

Purpose – This study investigates the role of cryptocurrencies in enhancing the performance of portfolios constructed from traditional asset classes. Using a long sample period covering not only the large value increases but also the dramatic declines during the beginning of 2018, the study aims to provide a more complete analysis of the dynamic nature of cryptocurrencies as individual investment opportunities, and as components of optimal portfolios.Design/methodology/approach – The mean-variance optimization technique of Merton (1990) is applied to develop the risk and return characteristics of the efficient portfolios, along with the optimal weights of the asset class components in the portfolios.Findings – We provide evidence that as a single investment, the best cryptocurrency is Ripple, followed by Bitcoin and Litecoin. Furthermore, cryptocurrencies have a useful role in the optimal portfolio construction and in investments, in addition to their original purposes for which they were created. Bitcoin is the best cryptocurrency enhancing the characteristics of the optimal portfolio. Ripple and Litecoin follow in terms of their usefulness in an optimal portfolio as single cryptocurrencies. Including all these cryptocurrencies in a portfolio generates the best (most optimal) results. Contributions of the cryptocurrencies to the optimal portfolio evolve over time. Therefore, the results and conclusions of this study have no guarantee for continuation in an exact manner in the future. However, the increasing popularity and the unique characteristics of cryptocurrencies will assist their future presence in investment portfolios.Originality/value – This is one of the first studies that examine the role of popular cryptocurrencies in enhancing a portfolio composed of traditional asset classes. The sample period is the largest that has been used in this strand of the literature, and allows comparing optimal portfolios in early/recent subsamples, and during the pre-/post-cryptocurrency crisis periods.
Context-Awareness: A Survey on Internet of Things

As we progress into the Internet of Things (IoT), the amount of sensors installed across the planet is rising at a fast rate. Market research has shown a substantial rise in sensor installations during the last decade and has expected a significant increase in the growth rate in the future. These sensors constantly produce massive quantities of data. However, we need to consider this in order to add meaning to the raw sensor results. Collection, modelling, logic and dissemination of meaning in relation to sensor data play a critical role in this task. Context-aware computation has proved to be effective in the interpretation of sensor data. In this article, we're looking at background understanding from an IoT viewpoint. Introducing the IoT framework and context-conscious basics at the outset, we provide the requisite history. Then we have an in-depth study of the life cycle of the background. We assess a subset of ventures (50) that constitute the plurality of research and commercial solutions proposed in the field of context-conscious computing during the last decade (2001–2011) centered on our own taxonomy. Finally, based on our appraisal, we illustrate the lessons to be gained from the past and some potential paths for future study. The survey covers a wide variety of approaches, processes, templates, functionalities, structures, implementations and middleware technologies relevant to context and IoT understanding. Our aim is not only to evaluate, compare and consolidate past research work, but also to appreciate their conclusions and to address their applicability to IoT.
Konsep Evaluasi dalam Pembelajaran Bahasa Indonesia di SDN Sangiang III Kabupaten Tangerang

This study aims to determine the basic concepts of evaluation and their implications in evaluating Indonesian learning. Type of qualitative research. Research site at SDN Sangiang 3. Subjects of teachers and fourth grade students at SDN Sangiang 3. Interview data collection techniques. Research Subjects are teachers who teach Indonesian subjects. Data collection is done through interviews. The steps of data analysis are recording and collecting, reducing, presenting, and verifying. The results of this study indicate that the evaluation is carried out to determine the effectiveness and efficiency of learning conducted, its function is to determine the capacity of educators and students, so that improvements can be made if indeed there are found factors that are not optimal in the learning process.
Research on Information Trend Analysis in the Field of Corporate Security: Application of Topic Modeling Technique

In rapidly changing economic environment, firms make numerous decisions to compete with other players and maximize profit in the turbulent market. Given the demands to process such decisions repeatedly, firms often seek an architecture that can handle large-scale unstructured data. Furthermore practitioners are seeking higher accessibility and computational efficiency by placing data on remote servers or clouds rather than local storages. Following these recent changes, firms recognize corporate security as a very important issue. The purpose of this study is to use text mining analysis techniques with the “security”-related keywords to identify the most recent trends in the real business world. For this purpose, we present a framework for Corporate Information Trend Analysis (CITA). News data were collected from BIGKinds database for 20 years, and topic modeling analysis was used on three different periods. The results clearly show how our framework can identify the changes in security-related topics and keywords over time. These attempts will also be applicable to future research of corporate information trends using other sets of keywords.
COVID-19 Medicines and Personal Protective Equipment for Sale on Underground Illicit Cryptomarkets

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