Reviewerly/exHarmony huggingface dataset:
Features of the Use of the Internet by Russian Teenagers: The Regional Aspect

In the last two decades, adolescent behaviour has significantly modified by new factors in the form of information technologies embedded in the education and leisure.There is knowledge that the worse of socio-economic conditions of life determine the increase of gaming activity and communication in social networks of teens.The assumption of our study is that different living conditions in metropolis and industrial city in central Russia determinate the teenagers' actions changes in Internet.The paper used a questionnaire to assess the preferences of gaming and internet activities by students of schools in Moscow and Lipetsk of Russia.Methodical features of the questionnaire in the form of the need to select a single choose from a set of possible answers to the questions determine the specific distribution of teenagers with different kinds of internet activity compared to teenagers in other country.The survey of 144 students of schools in Moscow and Lipetsk online showed both similarities in the use of video games and time on social networks with the well-known features of the younger generation of other countries and the specific features of Russian schoolchildren.Most teenagers of Russia used social media communications compared to gaming, with a sufficient degree of competence, higher in the industrial city, Lipetsk, than Moscow.The time of total interaction with gadgets roughly corresponds to the results of cited works in the sample of teenagers of Lipetsk in Moscow this value is higher.Thus, we have proved the impact of regional conditions on adolescent behaviour in cyberspace with Lipetsk teens' normative characteristic in corresponding Moscow students.
A study on the vocabulary in Korean-Japanese Middle School textbooks currently in use in 2020 - Focusing on national language textbooks for grades 1 through 3 -

This paper aims to illuminate the socio-cultural characteristics of the national language textbooks, which Korea and Japan intend to make their students influenced by, through drawing on the significant differences between categories that appear in lexical distributions by areas of the meaning of vocabulary in the current national language textbooks for middle school students in Korea and Japan.<BR> For a qualitative change, the lexical distributions were compared according to the five major categories of Bunruigoihyou (1964, 2004). In the case of Korean textbooks, there are significant differences in the order of <1.2>, <1.4>, and <1.3> based on the total number of words. In the case of Japanese textbooks, significant differences are in the order of <1.5> and <1.1>. It was also compared with Lee(2020) that analyzed the vocabulary of a first-year textbook, which revealed the significant difference in <1.2> and <1.3>, <1.5> is shrinking. Therefore the characteristics of first-year textbooks are now slightly ambiguous.<BR> These tendencies were also found in the medium categories. In the case of Korean textbooks, significant differences were found in ＜human＞，<race·people>, <family>, <members·position> <duty>, <mind>, <economy>, <dwelling>, <clothing>, <foodstuff>, <body> and <life>. On the other hand, Japanese textbooks are different from Korean ones in terms of <instruction>, <quantity>, <time>, <space>, <living organism>, <nature·object>, <animal>, <creation·writing>, and <machinery>.<BR> In particular, Korean textbooks have more vocabulary associated with humans and families than Japanese ones, while Japanese textbooks have more words related to information literacy which is the same tendency shown in the previous textbooks. In addition, the revision of Japanese textbooks has resulted in a decrease in literature-related vocabulary and an emphasis on environmental and ecological themes.
SCELC: How a Library Consortium Empowers Libraries

This is part two of a two-part series on the SCELC library consortium which focuses on current programs and initiatives including financials, licensing, business models, and future directions. Part one, which appeared in the previous JLA consortia column focused on the history, governance, staffing, and the early evolution of services in the organization.
Perancangan Model Knowledge Management System Pengelolaan Proyek Dengan 10-Step Roadmap Knowledge Management System pada PT. Aegis Ultima Teknologi

In the current era of globalization, knowledge is a very valuable asset for companies to increase their effectiveness. Therefore, awareness is needed for companies to foster a culture of sharing knowledge because this will be a valuable asset for the company compared to other assets. To foster a knowledge-sharing culture at PT. Aegis Ultima Teknologi, a knowledge management system is needed, especially in this study using at PT. Aegis Ultima Teknologi the 10-Step Knowledge Management System methodology.
A Federated Interoperability Approach for Data Driven Logistic Support in SMEs.

Small and Medium-sized Enterprises (SMEs) in logistics experience practical barriers when trying to use, exchange, share, and exploit real-time data in their operational processes. Such barriers include the abundance of proprietary data formats and schemes, the cost of implementing standards, the lack of trust among partners, the lack of IT expertise, and the uncertainty about benefits and return on investments. This position paper introduces the goal and proposed approach of a recently started research project that aims at lowering these barriers. The core proposition revolves around the application of a federated approach based on the concepts of the International Data Space (IDS). In this paper we present a high level architecture underlying this goal and approach. Two main components of the architecture are discussed in more detail: (1) a connector store, offering connectors to realize data exchange between heterogeneous ICT environments, and (2) an interoperability simulator, to explore collaboration opportunities prior to implementation.
Classifying Word Association Test (WAT) Response in Song Study at Students Senior High School 1 Sungai Aur

Vocabulary development is a significant purpose in any language teaching.The term that manages vocabularies in the person is named 'mental lexicon'.The mental lexicon describes a dictionary that upgrades every word, meaning, and associate them with another word in the mind.Word Association Test is one measurement to know how depth vocabularies understanding are.It also called Word Affiliation Test and a greatly-renowned research technique in linguistic and psychology research by using word stimulus to acquire the lexical relation amid words.In senior High school, song study is taught at the end of the syllabus.The researcher connected the song with the vocabularies of students and tried to examine the word types of association they are used so they feel easy and enjoyed learning English and have a significant result in their study.The classification of word association composition concentrated on the two central fundamentals of language: syntagmatic; It should be connected with a phrase or syntactic framework and paradigmatic; involve another words or syllable that might switch connection.This research aims to explore the students' dept understanding of the word in the mind and to apply it in the English study.This is a qualitative study and analyzes the response of the students based on syntagmatic and paradigmatic types.The source of this research is got from a preliminary student's senior high school at Sungai Aur.Then, the data are analyzed and classified into syntagmatic and paradigmatic.
Proposal for the Expansion of Research on the South Korean Marina Development Project

Kim, J.-S. and Jang, S.-H., 2021. Proposal for the expansion of research on the South Korean Marina Development Project. In: Lee, J.L.; Suh, K.-S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 345–349. Coconut Creek (Florida), ISSN 0749-0208. The South Korean Marina Development Project includes a long-term plan to construct an industrial cluster and a marina business model by developing marinas nationwide since 2010. This plan aims to develop coastal/fishing regions across the country into leisure hotspots. Building on active support from the government, this led to the establishment of the Second Marina Basic Plan in 2020, making this the largest marine leisure project in the country to date. Unfortunately, many marinas across the country face severe difficulties owing to various causes. In this study, we aimed to suggest new directions for research on the Marina Development Project as part of a series of academic efforts to resolve problems with the project. To this end, we conducted a literature review to explore (1) the current project and the directions of previous research by inspecting “the current state of the Marina Development Project and related research trends” and (2) “the expansion of research on the Marina Development Project.” More specifically, we claim that there is a need for “critical research examining the nature of the problems that have caused failure to date” and for a “cultural approach to participants.” Finally, we also emphasize the need for “community governance research” as a practical and long-term solution. This expansion of research can guide recovery from the various difficulties faced by the current Korean Marina Development Project.
Newtonian, Lagrangian and Hamiltonian Mechanics

Newtonian Mechanics [2, 3] is the branch of Physics which studies the way in which bodies are changing their position in space and time. Space where the objects are at rest or in motion is the Euclidean 3-dimensional space \(E^3\). Time is represented by the real axis \(\mathbb {R}\). It is absolute and the same for any observer.
Analysis of Question Levels Design through Vertex-Edge and Graph Chapter for Prekindergarten-Grade 2

This paper focuses on vertex-edge and graph topics in Prekindergarten to Grade 2, including an overview of the design level of the question and student's strategy in solving problems related to the topic. It discusses how the topic should be introduced in Prekindergarten to Grade 2 and the efforts to facilitate and support the level-question adoption of vertex-edge and graph topics for those graders. Fourteen students participated in this study from different schools in South Sumatra, Indonesia. This research was a development study using design research implementation with quantitative data analysis by testing, and qualitative by face-to-face interview. The results showed that students assessed a question categorized into easy, medium, and hard levels according to the questions' complexity. This study can be used as a guidance to teach vertex-edge and graph topics more interestingly.
LibGuides: Library Helpful Hints for Off-Campus Use: Recording with ZOOM

A guide to help students access library resources to complete assignments when they are not on campus Step by step directions for recording with Zoom and sharing with others
A Comparison of Different Embedding Methods on Session Based Recommendation with Graph Neural Networks

Predicting users&apos; next behavior based on their previous actions is one of the most valuable but also difficult task in the e-commerce and e-marketing fields. Recommendation systems that build upon session-based data try to bring a solution to that desire. The ultimate goal of this type of recommendation system is trying to make the best predictions about the succeeding item. Sequential order of the items within a session is also kept in mind in such systems. Recently proposed SR-GNN (Session Based Recommendation with Graph Neural Networks) has benefited from graph theory and proven its adequacy about being the state-of-art session-based recommendation model. Furthermore, there are some parts exist that can improve the overall performance. The current model uses primitive embedding type which is the simplest way of representing the items, attributes, and their relationships between each other. This study brings the SR-GNN recommendation model with di erent types of graph embedding techniques which are widely used in a variety of research areas. Aim of this research is investigating the the e ect of the embedding types to the SR-GNN. The proposed variety of embedding techniques that applied to SR-GNN show similar but slightly worse results compared to the original SR-GNN embedding. The experimental results obtained on two real datasets show that the performance of the SR-GNN model is not a ected by the embedding models and the power of the model comes from the gated graph neural network model.
An Insight of Opinion Mining on Hotel Reviews

The web has altered the way the humans express opinions on various products or services. We can also share our experience about various services used. Internet era has changed the way of thinking , various platforms on the web are the convenient way of sharing thoughts and knowledge. Opinion mining is a method that classifies human emotions into positive, negative and neutral sentiments. Mining of opinions can be done on the basis of document, sentence and aspects. This paper reviews the various algorithms and techniques used for opinion mining. Here we have focused on opinion mining based on features of hotels like food, transportation, room amenities etc. which enables us to determine the polarity of features of the various reviews of hotel. The recognition of polarity of opinions helps the hotels to promote their services and can plan marketing strategies accordingly.
Penerapan Algoritma K-Means pada Ketersediaan Lapangan Olahraga Setiap Kelurahan Di Indonesia

Sports facilities are the basis of sports activities such as athletic events such as volleyball, ball, tennis, and others. Each type of sports field requires advice and infrastructure to continue activities. The method used is Data Mining using the K-Means algorithm. This method of data is grouped into 2 clusters. The author uses data obtained from government sites that address http://bps.go.id. Based on recap result data from 2014 to 2018, The final results announced are based on sports fields, which are grouped into the lowest highest cluster based on the type of sport in each Kelurahan according to Indonesia's provinces. By using the K-Means method provides a grouping of an area in the Kelurahan, according to the Province in Indonesia. In this study, the government assisted in the sports field and improved facilities and infrastructure in sports for the athletic community.
User Curiosity Factor in Determining Serendipity of Recommender System

Recommender rystem (RS) is created to solve the problem by recommending some items among a huge selection of items that will be useful for the e-commerce users. RS prevents the users from being flooded by information that is irrelevant for them.Unlike information retrieval (IR) systems, the RS system's goal is to present information to the users that is accurate and preferably useful to them. Too much focus on accuracy in RS may lead to an overspecialization problem, which will decrease its effectiveness. Therefore, the trend in RS research is focusing beyond accuracy methods, such as serendipity. Serendipity can be described as an unexpected discovery that is useful. Since the concept of a recommendation system is still evolving today, formalizing the definition of serendipity in a recommendation system is very challenging.One known subjective factor of serendipity is curiosity. While some researchers already addressed curiosity factor, it is found that the relationships between various serendipity component as perceived by the users and their curiosity levels is still yet to be researched. In this paper, the method to determine user curiosity model by considering the variation of rated items was presented, then relation to serendipity components using existing user feedback data was validated. The finding showed that the curiosity model was related to some user-perceived values of serendipity, but not all. Moreover, it also had positive effect on broadening the user preference.
HeadGAN: One-Shot Neural Head Synthesis and Editing

Recent attempts to solve the problem of head reenactment using a single reference image have shown promising results. However, most of them either perform poorly in terms of photo-realism, or fail to meet the identity preservation problem, or do not fully transfer the driving pose and expression. We propose HeadGAN, a novel system that conditions synthesis on 3D face representations, which can be extracted from any driving video and adapted to the facial geometry of any reference image, disentangling identity from expression. We further improve mouth movements, by utilising audio features as a complementary input. The 3D face representation enables HeadGAN to be further used as an efficient method for compression and reconstruction and a tool for expression and pose editing.
CHATTING TO LEARN IN SYNCHRONOUS WHATSAPP GROUP DISCUSSION

Group discussion is a key feature in education. Despite its importance, however, its potential in higher education is under-researched. With the advent of technology in education and the vision for 21 st century learning, innovative use of mobile-based technologies has become a necessity in teaching and learning. Having to get on the bandwagon, the present study examines WhatsApp as a tool for synchronous group discussion in class and how it could promote communication and learning among undergraduates. The app is used in a blended delivery design to teach a content course called Discourse Analysis in an undergraduate program for Applied Linguistics. The research is qualitative in nature and employs pragmatics as the approach to discourse analysis. The study showed that WhatsApp group discussion helped student understanding of content knowledge, facilitated group learning, and promoted learner autonomy and learner cooperation. The students used one another as resources and made sense of the course content together based on their subject matter knowledge and life experiences. They pooled their knowledge and experiences and helped each other figure out the concepts, theories and issues through a negotiation of meaning that involved active participation in the form of questions and responses that justify, explain and clarify meanings. In this new age of digital literacy, the study shows how WhatsApp synchronous group discussion can encourage cumulative learning as a way to learn content knowledge,  stimulate exploratory talk as a relevant communication skill for academia and work, and promote among learners, a sense for autonomy and cooperation.
Keys to Creating, Executing a Campaign Plan

The Major Gifts ReportVolume 23, Issue 11 p. 7-7 Campaign Planning Keys to Creating, Executing a Campaign Plan Kim Pawlak, Kim PawlakSearch for more papers by this author Kim Pawlak, Kim PawlakSearch for more papers by this author First published: 30 September 2021 https://doi.org/10.1002/mgr.31815Read 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 onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume23, Issue11November 2021Pages 7-7 RelatedInformation
Danger-aware Adaptive Composition of DRL Agents for Self-navigation

Self-navigation, referred as the capability of automatically reaching the goal while avoiding collisions with obstacles, is a fundamental skill required for mobile robots. Recently, deep reinforcement learning (DRL) has shown great potential in the development of robot navigation algorithms. However, it is still difficult to train the robot to learn goal-reaching and obstacle-avoidance skills simultaneously. On the other hand, although many DRL-based obstacle-avoidance algorithms are proposed, few of them are reused for more complex navigation tasks. In this paper, a novel danger-aware adaptive composition (DAAC) framework is proposed to combine two individually DRL-trained agents, obstacle-avoidance and goal-reaching, to construct a navigation agent without any redesigning and retraining. The key to this adaptive composition approach is that the value function outputted by the obstacle-avoidance agent serves as an indicator for evaluating the risk level of the current situation, which in turn determines the contribution of these two agents for the next move. Simulation and real-world testing results show that the composed Navigation network can control the robot to accomplish difficult navigation tasks, e.g., reaching a series of successive goals in an unknown and complex environment safely and quickly.
AUTOMATIC CREDIT CARD FRAUD DETECTION SYSTEM USING DBSCAN OUTLIER DETECTION

Penipuan kartu kredit dapat didefinisikan sebagai penggunaan akun kartu kredit orang lain yang menipu atau tidak sah dalam upaya mencuri uang, barang, atau layanan. Penipuan kartu kredit adalah masalah utama, terutama di negara-negara berkembang dan menyebabkan kerugian jutaan dolar setiap tahun. Sistem deteksi penipuan kartu kredit akan sangat membantu dalam memerangi ancaman ini dan mengurangi kerusakan yang ditimbulkannya. Penelitian ini berfokus pada penggunaan DBSCAN untuk melakukan deteksi outlier pada dataset untuk tujuan mendeteksi penipuan. Sistem ini diujicobakan dengan berbagai parameter dan transformasi data, dan kemudian dibandingkan dengan algoritma pengelompokan terkenal lainnya, K-means untuk menentukan efektivitas kinerjanya. Hasil penelitian menunjukkan bahwa DBSCAN mampu lebih akurat menentukan transaksi penipuan daripada K-means. Selain itu, penelitian menunjukkan bahwa memanfaatkan transformasi PCA pada dataset terlebih dahulu meningkatkan akurasi clustering dan deteksi outlier.Credit card fraud can be defined as deceptive or unauthorized use of another person's credit card account in an attempt to steal money, goods, or services. Credit card fraud is a major problem, especially in developing countries and causes millions of dollars in losses annually. A credit card fraud detection system would help greatly in combatting this threat and reducing the damage it causes. This research focuses on the use of DBSCAN is order to perform outlier detection on a dataset for the purposes of detecting fraud. The system was experimented on with various parameters in addition with data transformations, and then compared with another well-known clustering algorithm, K-means in order to determine the effectiveness of its performance. The results of the research showed that DBSCAN was able to more accurately determine fraudulent transactions than K-means. In addition, the research showed that utilizing PCA transformation on the dataset first improves accuracy of the clustering and thus of outlier detection.