Reviewerly/exHarmony huggingface dataset:
A Novel Secured Euclidean Space Points Algorithm for Blind Spatial Image Watermarking

Abstract Digital raw images obtained from the data set of various organizations require authentication, copyright protection, and security with simple processing. New Euclidean space point’s algorithm is proposed to authenticate the images by embedding binary logos in the digital images in the spatial domain. Diffie–Hellman key exchange protocol is implemented along with the Euclidean space axioms to maintain security for the proposed work. The proposed watermarking methodology is tested on the standard set of raw grayscale and RGB color images. The watermarked images are sent in the email, WhatsApp, and Facebook and analyzed. Standard watermarking attacks are also applied to the watermarked images and analyzed. The finding shows that there are no image distortions in the communication medium of email and WhatsApp. But in the Facebook platform, raw images experience compression and observed exponential noise on the digital images. The authentication and copyright protection is tested from the processed Facebook images, it is found that the embedded logo could be recovered and seen with added noise distortions. So the proposed method offers authentication and security with compression attacks. Similarly, it is found that the proposed methodology is robust to JPEG compression, image tampering attacks like collage attack, image cropping, rotation, salt, and pepper noise, sharpening filter, semi-robust to Gaussian filtering, and image resizing, and fragile to other geometrical attacks. The receiver operating characteristics (ROC) curve is drawn and found that the area under the curve is approximately equal to unity and restoration accuracy of [67 to 100]% for various attacks.
Research Guides: Student Curated Digital Exhibits: Metadata Tips

This guide includes information for students curating digital exhibits using Special Collections materials
개인정보유출 사고 방지를 위한 중소기업의 사이버 위험관리

Purpose: Most of cybersecurity breaches occur in SMEs. As the existing cybersecurity framework and certification system are mainly focused on financial and large companies, it is difficult for SMEs to utilize it due to lack of cybersecurity budget and manpower. So it is necessary to come up with measures to allow SMEs to voluntarily manage cyber risks. Method: After reviewing Cybersecurity market, cybersecurity items of financial institutions, cybersecurity framework comparison and cybersecurity incidents reported in the media, the criticality of cybersecurity items was analyzed through AHP analysis. And cybersecurity items of non-life insurers were also investigated and made a comparison between them. Result: Cyber risk management methods for SMEs were proposed for 20 major causes of cyber accidents. Conclusion: We hope that the cybersecurity risk assessment measures of SMEs in Korea will help them assess their risks when they sign up for cyber insurance, and that cyber risk assessment also needs to be linked to ERM standardization .
Moth Flame Optimization and Deep Learning Based Digital Review Sentiment Mining

Organization providing service or product depends on its customer reviews. Collection of such review through online platform provides digital raw data. Extracting information about product review depends on sentiment analysis from the user text review. Language processing is an complex task in case of review analysis as user words and sentiment relation is different for various context. This work has proposed a sentiment analysis hybrid model that combines genetic algorithm and deep neural network techniques.  Genetic algorithm reduces the dimension of input data by clustering terms into two class first is positive sentiment oriented class and other is negative sentiment oriented class. Clustering is done by moth flame optimization algorithm. Learning model linear regression take input of sentiment orient class terms and apply deep feature extraction operators convolution, max-pooling for getting more effective results. Experimental work was done on real dataset of amazon reviews with different testing size. Evaluation parameter values show that proposed model has increased accuracy of work by filtering data.
Research Guides: Profiles in Teaching and Learning with Student Media Projects: Communicating Scientific Concepts Through Engaging Student Videos

This online gallery highlights a diversity of student created projects that Library Media Services has supported over the years. More in-depth description of each project can be found on secondary pages.
GSPL: A Succinct Kernel Model for Group-Sparse Projections Learning of Multiview Data

This paper explores a succinct kernel model for Group-Sparse Projections Learning (GSPL), to handle multiview feature selection task completely. Compared to previous works, our model has the following useful properties: 1) Strictness: GSPL innovatively learns group-sparse projections strictly on multiview data via ‘2;0-norm constraint, which is different with previous works that encourage group-sparse projections softly. 2) Adaptivity: In GSPL model, when the total number of selected features is given, the numbers of selected features of different views can be determined adaptively, which avoids artificial settings. Besides, GSPL can capture the differences among multiple views adaptively, which handles the inconsistent problem among different views. 3) Succinctness: Except for the intrinsic parameters of projection-based feature selection task, GSPL does not bring extra parameters, which guarantees the applicability in practice. To solve the optimization problem involved in GSPL, a novel iterative algorithm is proposed with rigorously theoretical guarantees. Experimental results demonstrate the superb performance of GSPL on synthetic and real datasets.
Comparison of Naive Bayes and SVM Classifiers for Detection of Spam SMS using Natural Language Processing

Day today’s innovative world observers an extraordinary possibility in the communication sector. Individuals will in general utilize various approaches to speak with individuals around the world. The regular methods for sharing short data in an exceptionally simple manner and is cases recorded now a days. This desires a need to recognize Spam SMS to stay away from digital wrongdoing robbery and extortion exercises. A labeled dataset is utilized for recognition reason and two classifiers to be specific Support Vector Machine and Naive Bayes are utilized to make a correlative examination for the location of spam accomplished by utilizing of Short Message Service. SMS doesn’t require any web charges yet, it is unsurpassed utilized methods for remote correspondence. Each versatile client has this office of course. It has an incredible monetary effect on the clients just as the specialist co-ops. Then again SMS spam is one of the major digital wrong doing SMS and the exhibition of classifiers are thought about.
METHODOLOGICAL ASPECTS OF MODELING NETWORK PROCESSES IN GENERAL EDUCATION

The article considers three aspects of modeling network processes in general education - subject, quasi-organizational and institutional. since they define a finite set of properties and relationships in the processes of organizing network interactions, the following processes are presented in a meaningful way: production, organizational and regulatory.
K-means algorithm for clustering system of plant seeds specialization areas in east Aceh

The number of regions and types of plants in East Aceh Regency requires a data clustering process in order to easily find out which areas are most in-demand based on the type of plants. This study applies the k-means algorithm to classify the data. The data used in this study were obtained from the Department of Agriculture, Food Crops and Horticulture, East Aceh Regency. Based on the test results with k-means, the average number of iterations in the 2015-2019 data is 8,7,6,4,3 iterations for each commodity. The test results can show areas of interest for plant seeds with clusters of high demand, attractive, and less desirable. The system in this study was built based on the web using the PHP programming language.
Transforming University Education: A Manifesto

Ashwin, P. 2020. Transforming University Education: A Manifesto. London: Bloomsbury.ISBN 978-1-3501-5724-8
Changes in Attitude, Knowledge, and Use of ICTs During the Progression of an Online Research Master's Program

The objective of the research was to observe the evolution of attitude, knowledge, and use of ICT resources in students during the progression of the Research Master’s degree in Teacher Training and ICTs in the Faculty of Education at the University of Extremadura. A total of 21 students from the Master's program participated. A concurrent triangulation mixed method was used, combining descriptive and inferential data analysis with content analysis, developing the quantitative and qualitative designs in parallel. Among the main conclusions obtained, it is noted that no statistically significant differences were observed in the attitude, knowledge, and use of ICT resources of the students between the beginning and the end of the Master's program. However, a positive correlation was found between knowledge and the use of ICT resources, both at the beginning and at the end of the Master's program. Moreover, it was found that not only do the students have a positive attitude and a medium knowledge with the use of ICT resources but also that the main problems in the teaching/learning process in the online Master's program are related to the teaching staff and organization.
Learning Implicitly with Noisy Data in Linear Arithmetic

Robustly learning in expressive languages with real-world data continues to be a challenging task. Numerous conventional methods appeal to heuristics without any assurances of robustness. While PAC-Semantics offers strong guarantees, learning explicit representations is not tractable even in a propositional setting. However, recent work on so-called learning has shown tremendous promise in terms of obtaining polynomial-time results for fragments of first-order logic. In this work, we extend implicit learning in PAC-Semantics to handle noisy data in the form of intervals and threshold uncertainty in the language of linear arithmetic. We prove that our extended framework keeps the existing polynomial-time complexity guarantees. Furthermore, we provide the first empirical investigation of this hitherto purely theoretical framework. Using benchmark problems, we show that our implicit approach to learning optimal linear programming objective constraints significantly outperforms an explicit approach in practice.
日本語ニュースサイトの韓国語翻訳の誤謬様相に関する考察 －共同通信(KYODO NEWS)韓国語翻訳版を中心に－

Newspaper articles are everyday learning tools used by both practitioners and learners of translation and interpretation. Korea has been providing Japanese or Chinese translations of Korean news shows on the Internet for a long time for the learners to employ them as readily available tools. Furthermore, translated articles of Kyodo news have recently become meaningful tools in Japanese-Korean translation and interpretation learning. As the native speaker of the Korean language, the author of this paper carries out proofreading of Japanese news translated into Korean and figures out, analyzes and systemizes errors from the viewpoint of translation and interpretation. The errors are classified into four types and corrective measures are also presented. The four types of errors include errors in spelling, errors for lack of knowledge in terminology, errors resulting from insufficient knowledge of Korean vocabulary and sentences and errors involved in literal translation of vocabulary and sentences.
CARA GURU DALAM MENGEMBANGKAN BUTIR TES PILIHAN GANDA SEBAGAI INSTRUMEN EVALUASI HASIL BELAJAR

The low quality of teacher-made tests makes the information provided by the measurement results of these tests doubtful as a basis for educational decision making. In order to clearly identify the cause of the low quality of the test, it is important to conduct research that aims to look deeper into the methods that teachers take in the process of developing tests in the field. The sample was taken purposively, limited to 4 teachers at six grade, who were involved in the UTS and UAS question preparation team in Lubuk Alung District. The triangulation technique was chosen for data collection, the four samples were observed several times until the question writing process was completed. Interviews were conducted on matters that were not clear to the researcher during the process. Photos, videos and the form of test instruments made required was collected as documentations. The research findings show that basically the teacher has followed a part of the flow, although not all of the steps were followed correctly during the test item writing process. The findings of the study indicate the process of writing the items by the teacher, namely 1) the design of the lattice table, 2) the writing of the items was found: a) the choice of the operational words only measured aspects of knowledge and understanding, b) there were many negative types of questions such as the use of the word 'except' , c) the distractor is made very predictable, d) there is an ambiguous question language 3) the test review is carried out by a special team who edits all tests before they are printed and distributed, 4) testing and analysis of grain quality is not carried out at all, due to limitations funds, time and effort.
Improving the neural network model in combination with a big semantic-enriched corpus for building an English - Vietnamese semantic-oriented machine translation system

Although the machine translation (MT) quality has been significantly improved, it still fails to meet the practical use requirements, especially in the narrow fields of expertise and under-resource languages. To solve this problem, most studies have been focusing on improving algorithms, translation models and corpora. However, very few studies could address a very important aspect that greatly affects the translation quality, which is semantic-oriented translation. In this article, we propose a solution of building a context-based semantic-oriented MT system by improving the neural network translation model in combination with a big semantic-enriched corpus. The neural network translation approach allows understanding the semantics of the whole sentence based on context vector and phrase translation memory. Moreover, automatic translation results are pre-processed by enriching well-defined meanings to entities for creating the final translated text showing to users. This solution has been used to build an English-Vietnamese semantic-oriented machine translation system dedicated in the tourism field. The result shows that this solution gives good translations that are very helpful and useful to users.
The diffusion of National Domain Name Dispute Resolution Policies: A Network Approach

This paper investigates the adoption of national domain name dispute resolution policies (NDRPs) by country code Top Level Domains (ccTLD). We examine the textual similarity between different NDRPs (35 documents) using Exponential Random Graph Modeling (ERGM). First, we measure similarity between the texts (i.e., cosine similarity) and use it to construct a 35*35 adjacency matrix for a directed network early to late adopters. Using EGRM, we predict which nodal attributes and dyadic attributes predict the observed network. We conclude by discussing what the findings imply about the emergence of a global policy regime for the Internet.
Macdonald-Kelce Library: Journalism: Video & Streaming

The purpose of this guide is to assist students in locating quality resources for their Journalism writing and research.
The possibilities of art therapy as one of integrative methods in therapeutic pedagogy

Taking into account the integrative nature of therapeutic pedagogy, the question of using, choosing and systematizing its methods is still debatable. The methodological toolkit of the therapeutic pedagogy and its classification began to take shape in the twentieth century thanks to the integrative system of V.P. Kashchenko's methods, which includes a set of therapeutic, rehabilitation, psychoanalytical techniques. The results and scientific novelty of the research are that the social significance and expediency of attracting and using varieties of art therapeutic techniques in medical pedagogy for the purpose of harmonious development, recovery and rehabilitation of children were determined. The essence and therapeutic and pedagogical resources of the variety of art therapy methods aimed at integrating and reintegrating a child's personality, developing his or her emotional and moral potential, designing the expected changes in his or her own identity, and predicting humane behavioral patterns with respect to the surrounding authenticity were considered.
A Study on the Impacts of the Coupling Effect and Volatility Spillover Effect of Won-Dollar Exchange Rate on the Rate of Terms of Trade(TOT)

Purpose : The main purpose of this paper is to analyse the impacts of the coupling effect and volatility spillover effect on the rate of terms of trade(TOT). Research design, data, methodology : This study focuses on investigating both the volatility of exchange rate and the coupling effect & volatility spillover effect from Won-Dollar exchange rate to commodity terms of trade(CTOT) & income terms of trade(ITOT) with monthly data(2001.1~2021.2) by using GARCH type models. Results : Firstly, the median lag(ML) of Won-Dollar exchange rate which was estimated relatively small means an indirect evidence of the efficiency of foreign exchange market. Secondary, no evidence was found in detecting the asymmetry effect of volatility of Won-Dollar exchange rate. Thirdly, the positive coupling effect was found from Won-Dollar to CTOT. Fourthly, the positive volatility spillover effect was detected from Won-Dollar to CTOT. Fifthly, in terms of conditional covariance, the positive coupling effect was found from Won-Dollar to ITOT. Conclusions : This paper suggested the efficient risk management of exchange rate by strengthening the trade insurance system, and composing the efficient portfolio of trade settlement currencies in order to enhance the competitiveness of Korean export.
텍스트마이닝을 활용한 북한 지도자의 신년사 및 연설문 트렌드 연구

The goal of this paper is to investigate changes in North Korea’s domestic and foreign policies through automated text analysis over North Korean new year addresses, one of most important and authoritative document publicly announced by North Korean government. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. We propose a procedure to find meaningful tendencies based on a combination of text mining, cluster analysis, and co-occurrence networks. To demonstrate applicability and effectiveness of the proposed procedure, we analyzed the inaugural addresses of Kim Jung Un of the North Korea from 2017 to 2019. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. We found that uncovered semantic structures of North Korean new year addresses closely follow major changes in North Korean government’s positions toward their own people as well as outside audience such as USA and South Korea.
Experimental Evaluation of Similarity Measures for Educational Items

Measuring similarity of educational items has several applications in the development of adaptive learning systems, and previous research has already proposed a wide range of similarity measures. In this work, we provide an experimental evaluation of selected similarity measures using a large dataset. The used items are alternate-choice questions for the practice of English grammar for second language learners; the dataset contains thousands of items and over 10 million student answers. Our results provide warnings about the generalizability of results presented in EDM works: 1) the results vary significantly between knowledge components and 2) the size of available data is an important factor.
Escândalo da dedução e informação semântica de uma perspectiva inferencial-pragmática

The purpose of this article is to the information problem generated in a deduction demands a new perspective for semantic information. First, it is necessary to change the philosophical presuppositions in the analysis of the deduction's problems, evaluating it fromthe Robert Brandom's philosophy of language, where professor Anderson Beraldo Araujo proposed an information theory that solves part of the question. The other part is solved with the expansion of the information measurement framework, in order to calculate the informational contribution of the very constitutive rules of the deduction activity. This conclusion is suggested when we articulate the work of Araujo and the formalizationproposed by Richard Evans, also based on Robert Brandom, combined with the AGM paradigm of operations on beliefs in the form of Horn clauses. The exhibition is divided into three parts. In the first one, I began with an introduction to the concept of information, delimit the type of theory that will be object of investigation and evaluate three theories of this domain: Carnap and Bar-Hillel; Hintikka and D'Agostinho and Floridi. In the second part, I produce an overview of the main philosophical categories that make up Bradom's philosophy of language. Finally, I present Evan's formalization that models the scenario of the debate among several subjects followed by the information theory of Araujo, where the deduction produces measurable information, from a set of beliefs manipulated in a given structure representing a subject. In view of this, I present the AGM paradigm to express the instance that operates rules, enabling us to follow the structural processes and changes on subjects and rules while the debate occurs.
Color Matching Ondel-Ondel Gamification as Culture Edutainment for Children

Gamification can be one-approach children for playing while learning. Researchers proposed one gamification that using ondel-ondel; the giant Betawi dolls that famous, as Betawi icon that can be enjoyed in all Jakarta’s corners will be one of the media for children to learn how to color. Color Matching Ondel-Ondel is an offered coloring multimedia gamification, which inserted information on form elements of ondel-ondel’s attributes. This research used a merging method of gamification implementation in education and user-centered approach. To analyze the form elements of the ondel-ondel’s attribute, semiotic of William Morris had been used, that focus on form, content, context. Several children with positive responds have tried this gamification, they were not just excited and happy but also gave feedback to make this game more interesting and useful. It is expected to be more gamification using ondel-ondel as a main character and coloring gamification of other Betawi’s art and culture.
Factors and trends in the formation of interest in examples of fiction through reading in primary school students

In this article, the factors and directions of the formation of interest in the samples of literary literature through reading in primary school students are expressed. Also, the article gives an idea of the reasons that lead to a decrease in the interest in reading, the main components of reading activity, the printsips that determine the range of reading to be formed in readers.