Reviewerly/exHarmony huggingface dataset:
민주시민교육과 새로운 지역사 교육

If education is defined as value or identity education in a narrow sense, there is a big possibility that it will not be compatible with civic education. It is because the goal of civic education is to help students cultivate their independent thinking competence, critical analysis, and judgment capability. It is thus needed to explore the possibilities of education that can be combined with civic education while keeping its original characteristics.This study examined the possibilities of new history as part of education to practice civic education. It pointed out limitations with traditional education focused on the of state and center, structure and politics, and the ruling class and provided specific problematic consciousness and research in In new history, local areas are perceived anew as historical established through various exchanges and practices. Hybrid characteristics found in the past of areas are also incorporated into historical narratives. This approach allows students to look at places where I live as specific historical and realize that their families and communities as well as they themselves are the subjects of (local) history. They can thus have vivid experiences of plural understanding of and its real examples connected to education for democratic citizenship.One of the prominent methods for education is oral education based on the collaboration work of students, teachers, and interviewees. Students can find familiar as they participate in oral education about familiar and near past. They can also check historical interpretations that change according to the positions and perspectives of interviewees and relativist viewpoints intervening in them. In this process of oral education, they are able to understand in plural ways and further cultivate autonomous and critical thinking and criticism, communication skills, and problem-solving capabilities sought after in education for democratic citizenship. Despite such educational effects expected from oral education, however, one should be careful about the risk of misleading students or leading them to extreme relativism.
Pierre Bourdieu: Contributions to the reading wheels in the university library

This article praises the reading wheel as a category of central analysis of research and collective transformation of reality. Several
Moderating Effect of Organizational Ambidexterity on the Relationship between Dynamic Capabilities and Performance of Food and Beverages Companies in Kenya

The main objective of the study was to assess the moderating effect of organizational ambidexterity on the relationship between dynamic capabilities and performance of Food and Beverages Companies in Kenya. The specific objectives of the study were to assess the effect of sensing, seizing and reconfiguration capabilities on performance and also the moderating effect of organizational ambidexterity on the relationship between dynamic capabilities and performance of Food and Beverages firms. The study adopted positivist philosophy and utilized descriptive and explanatory research design. Primary data was gathered by a census strategy on target population of 98 Food and Beverages Firms registered under Kenya Association of Manufacturers. Structured questionnaires were utilized in collecting data whereas inferential as well as descriptive statistics were employed in analyzing data. To test the linear variables’ association, Pearson correlation was employed whereas to analyze data so as to test the study hypothesis, multiple regression model was utilized. The findings showed that sensing capabilities (β=.392, p=.000), seizing capabilities (β=.194, p=.000) and reconfiguration capabilities (β=.174, p=.001) positively and significantly affect performance of food and beverages firms in Kenya. There was moderation of organizational ambidexterity on the relationship between dynamic capabilities and performance of food and beverages firms in Kenya (CI=.00, .05; p=.00; R2=.33).
ANALISIS HUBUNGAN MINAT DAN MOTIVASI DENGAN KECEMASAN SISWA SD PADA KEGIATAN MARKET DAY

Abstract Factors in students, some of which are anxiety, motivation and interest. These are the students’ internal factors that influence each of their activities in school, one of which is “Market Day” activities. This study aims to determine the relationship between motivation and interest both singly and in combination with students' anxiety in participating in “Market Day” activities. This study uses causal correlation techniques with motivatio (x1) and interest (x2) as free variables and the bounded variables namely anxiety (y). Data was taken using a questionnaire with a Likert scale. The data was taken from two elementary schools in Pacitan with the amount of respondents as many as 116 students from grades 4, 5 and 6. The data analysis was carried out using simple and multiple linear regression analysis methods. The results of data analysis concluded that: 1) Motivation is not related to students' anxiety in participating in “Market Day” activities. 2) Interest has a negative relationship with students' anxiety in participating in “Market Day” activities. The negative relationship was at the strong level with an effective contribution of 62.1%. And 3) Motivation and interest jointly have a strong relationship with students' anxiety in participating in “Market Day” activities. The relationship has an effective contribution of 63.3%, where 2% comes from motivational factors and 61.3% comes from interest factors. Keywords: Motivation, Anxiety, Interest, Market Day
The Impact of Learning Software on Improving Reading Comprehension Skills

One of the challenges of an intelligent tutoring system (ITS) is adapting the difficulty level of the questions posed to the student to suit the student’s academic level. Our study examines the task of adjusting the system’s level of challenges to the level of the learner and addresses the questions of how best to do so and whether there is any benefit from such adjustment. To answer these questions, we developed reading comprehension courseware that includes three adaptive algorithms for adjusting the level of the questions presented to the students: the random selection algorithm, the Q-learning based algorithm, and the Bayesian inference algorithm. We conduct a real-world experiment in which real high school students used the courseware to improve their reading comprehension skills. In order to compare and evaluate the performance of the algorithms, the courseware used by each student utilized one of the three adaptive algorithm alternatives. Our results demonstrate that when considering all of the students, there was significant improvement (learning gain) using each of the methods.
Unsupervised Data Mining Technique for Clustering Library in Indonesia

Organizing school libraries not only keeps library materials, but helps students and teachers in completing tasks in the teaching process so that national development goals are in order to improve community welfare by producing quality and competitive human resources. The purpose of this study is to analyze the Unsupervised Learning technique in conducting cluster mapping of the number of libraries at education levels in Indonesia. The data source was obtained from the Ministry of Education and Culture which was processed by the Central Statistics Agency (abbreviated as BPS) with url: bps.go.id/. The data consisted of 34 records where the attribute used was the number of libraries at each level of education starting from Elementary School, Junior High School, Senior High School and Vocational High School. The Unsupervised Learning Technique used is the k-medoids method which is part of data mining. The mapping label used is the high cluster (K1) for the number of libraries and the low cluster (K2) for the number of libraries at each level of education. The analysis process uses the help of Rapid Miner software. The results of the study indicated that 3 provinces in the high cluster (K1) and 31 provinces in the low cluster (K2) were for elementary schools; 4 provinces in the high cluster (K1) and 30 provinces in the low cluster (K2) for Junior High Schools; 13 provinces in the high cluster (K1) and 21 provinces in the low cluster (K2) for Senior High Schools; 8 provinces in the high cluster (K1) and 26 provinces in the low cluster (K2) for Vocational High Schools. The cluster formed is the optimal school cluster tested with the parameters of the Davies Bouldin Index (DBI) with results of 0.176 (Elementary School), 0.284 (Junior High School), 0.780 (Senior High School) and 0.662 (Vocational High School). The results of the research are expected to provide information in increasing the number of libraries at each level of education so that students and teachers can take advantage of existing library learning resources at school
Assessing Thesis Conclusions by their Goal Connectedness, Judgment and Speculation

Writing a thesis involves complying with certain requirements and rules established by institutional guides of universities. Students have guidelines to follow when developing their first draft, being insufficient to obtain a good document. This study seeks to help the students improve their first writings, based on natural language processing techniques. We focus primarily on the conclusions section of a thesis, a central element when finishing the research. In this paper, we present a conclusion analyzer that includes three models: goal connectedness, judgment and speculation. Such subsystems try to take care of main expected features in conclusions, specifically the connectedness with the general objective, the evidence of value judgments, and the presence of future work as a result of the student reflection. The study provides initial models, internal exploration of conclusions, and evaluations of our approach. We found in the three features evaluated that graduate level student’s texts outperformed those of undergraduate level. This behavior provides evidence that students with more practice writing a scientific paper or thesis (graduate level), possess better writing skills.
Multiple vehicles tracking in the aerial video based on fast incremental discriminative appearance learning

Multiple vehicles tracking in the aerial video have a strong effect on the intelligent transportation system. Therefore, a fast multiple vehicles tracking method is required to meet the demand of a higher energy conversion efficiency. However, frequent and long-term occlusions in complex traffic scenes make it more difficult, and identity switches of vehicles with a similar appearance also bring challenges. Currently, vehicles tracking methods based on detection shows satisfactory performance. In the tracking-after-detection methods, data association plays the key role, and it includes two types, namely, frame-by-frame association and multi-frame association. Frame-by-frame association refers to the association between detections in the two consecutive frames, but tracking drift or failure is likely to occur when vehicles are blocked or not detected. The multi-frame association establishes a relational model by using object detection information of multiple frames instead of the previous two frames, which can effectively reduce the vehicle error association and deal with occlusions. However, the tracking will also be interrupted if the occlusion time is too long to associate the detection points before and after. Therefore, online multiple vehicles tracking in the aerial video based on fast incremental discriminative appearance learning is put forward. A fast incremental discriminative appearance learning (FIDAL) is introduced to discriminate the appearances of vehicles and adaptively update the vehicle appearance models based on the difference value between the new sample and the mean of vehicle samples to address the problem of identity switches. Experimental results on video sequences from different data sets demonstrate an average 25 percent performance improvement when using fast incremental discriminative appearance learning.
An Delineate of Super Fuzzy Matrix and their Inverse: A Review

Fuzzy matrix is one the leading and developing concept in day today life. Specially, super fuzzy matrix is essential of every fuzzy concept if need for error free. In this paper an impression anchored in the various types of fuzzy, super fuzzy and inverse of super fuzzy related concept.
Object detection with a model trained in Google Cloud AutoML

Deep learning applications for computer vision do not end at image classification, a task we applied in Chapter 4. Back then, our goal was to create an app that identifies a digit drawn by the user. For instance, the digit in Figure 7-1 is a 3.
Requirement of New, Effective Educational Programs – Necessity for Future Development of Society

The article analyses demands of new concepts of student education on the level of secondary schools with technical focus. It urges the necessity to create new educational programs that prepare new future technical operators towards requirements of the labour market in future years in harmony with specifications of Industry 4.0. Many of job specializations is possible, at present time, to estimate only as a frame, but considering a length of study it is necessary to realize predictions at sphere of education needs consistently, expertly and continuously to introduce their results into innovations of existing educational programs or to introduce completely new, perspective educational programs by needs rising at production sector.
LibGuides: Primary Sources: Search Tools

This is a research guide to finding primary sources that are accessible through the MSU Duane G. Meyer Library or through the open web.
Discussion of ‘Prior-based Bayesian information criterion (PBIC)’

The authors should be congratulated on a stimulating piece of work. There is definitely a great need to understand information-based criteria such as BIC better. I especially especially enjoyed the...
A Compromise-Tolerant Key Management Framework for Private Blockchain

Onemajor threat for enterprise private blockchains is the compromise of the trust-enabling Public Key Infrastructure (PKI).While the invention of private blockchains has addressed the trust problem in inter-organisational information sharing, the confidentiality, integrity, and availability of information within one organisation is still reliant on traditional, centralised key management like PKI. This design has introduced a number of risks including: a) trust reliance on a few people creating an insider threat vulnerability; b) potential loss of assets, reputation, and privacy; c) single-point-of-failure; and d) defeating the distributed trust introduced by the invention of public blockchains. To mitigate these risks, this work proposes a compromise-tolerant key management approach that combines decentralised blockchain-based trusted PKI with the enforcement of multi-signature and smart contract features. Using a multi-signature feature allows the combination of decentralised blockchains and centralised PKIs, whereas smart contract enables key management transparency among all network participants to establish the distributed trust and mitigate insider and outsider threats.Keywords: blockchain-based key management, process transparency, enterprise key managementCite AsM. Becherer, T. Bui-Nguyen, M. Zipperle and F. Gottwalt, “A Compromise-Tolerant Key Management Framework for Private Blockchain”,  Engineering Intelligent Systems, vol. 28 no. 2, pp. 185-191, 2020.
UPAYA KEPALA SEKOLAH DALAM MENINGKATKAN KINERJA GURU DI MADRASAH ALIYAH ANWARUL ULUM DESA LINTAS UTARA KECAMATAN KERITANG KABUPATEN INDRAGIRI HILIR

This study aims to determine the extent of the principal's efforts in improving teacher performance, obstacles encountered and solutions developed for the obstacles encountered. This study uses a qualitative approach, with data collection methods of observation, interviews and documentation. The results of this study are the principal has made several efforts to improve teacher performance optimally. But there are still a number of obstacles namely there are still teachers who do not have the discipline and limitations of teachers in mastering IT. The solution to this problem, the headmaster gave computer training to teachers who were known to not yet have the skills to operate a computer, gave rewords to high achievers and gave the opportunity for all teachers to attend religious tours to visit the trustees' meals.
Data Trusts: More Data than Trust? The Perspective of the Data Subject in the Face of a Growing Problem

In the recent report, Growing the Artificial Intelligence Industry in the UK, Hall and Pesenti suggest the use of a ‘data trust’ to facilitate data sharing. Whilst government and corporations are focusing on their need to facilitate data sharing, the perspective of many individuals is that too much data is being shared. The issue is not only about data, but about power. The individual does not often have a voice when issues relating to data sharing are tackled. Regulators can cite the ‘public interest’ when data governance is discussed, but the individual’s interests may diverge from that of the public. This paper considers the data subject’s position with respect to data collection leading to considerations about surveillance and datafication. Proposals for data trusts will be considered applying principles of English trust law to possibly mitigate the imbalance of power between large data users and individual data subjects. Finally, the possibility of a workable remedy in the form of a class action lawsuit which could give the data subjects some collective power in the event of a data breach will be explored. Despite regulatory efforts to protect personal data, there is a lack of public trust in the current data sharing system.
Digitisation, Financial Development and Economic Growth in Emerging Economies.

The belief that digitisation directly contributes to promoting financial development and economic growth has occupied much of development policy discourse of most governments and international development organisations over the past decades. It was therefore necessary to: examine the effect of digitisation on financial development; examine the sensitivity of the indicators of digitisation to financial development; and explore the effect of digitisation and financial development on economic growth. Secondary data on 30 emerging economies and between the period of 2004 to 2017 from World Bank’s World Development Indicators (WDI) database and the International Telecommunications Union were used in the estimations. The Generalised Method of Moments (GMM) estimations were used to analyse the data. On the determinants of financial development, digitisation was found to have a statistically significant effect. Results on the sensitivity of digitisation indicators to financial development show that fixed broadband subscriptions per 100 people and mobile cellular telephone subscribers per 100 inhabitants, as key proxies of digitisation, are very sensitive to financial development. With regards to the effect of digitisation and financial development on economic growth, the study found a significant positive result. There is evidence of a strong mediating role of financial development in a digitisation-economic growth nexus. The study recommends that emerging economies need to increase their investment in technology development, formulate effective policies on Information Communication Technology (ICT) that will encourage the use of ICT.
Readiness for Professional and Pedagogical Self-Development: Results Dynamics Among Students of Master's Programs in Pedagogy

Purpose of the study: The purpose of this study is to determine the dynamics of readiness for professional self-development among students of pedagogical Masters programs during their training. It is due to the fact that professional self-development is considered as one of the goals of preparing a pedagogical magistracy graduate for subsequent pedagogical activity.Methodology: As an empirical method, the authors used the diagnosis of partial readiness for professional and pedagogical self-development. It represents a self-assessment map of readiness for self-education activities. This technique allows to conduct a self-assessment of self-development skills formation according to the following components: motivational, cognitive, moral-volitional, gnostic, organizational, communicative, and the ability to self-government. A special feature of this diagnostic technique is the inverse correlation between a number of respondents self-assessment points and his/her readiness for professional self-development. The data obtained were processed using methods of mathematical statistics. Significance of differences was evaluated by Student's t-test (P≥0.95).Results: The study indicates that the readiness for professional self-development among students of pedagogical Masters programs increases during training. These changes occur in the motivational, moral-volitional and intellectual spheres of the graduate students and depend on the presence of teaching experience and teacher education.Applications of this study: The dynamics of students readiness for professional and pedagogical self-development can be taken into account when updating educational Master's programs in pedagogy. Programs improvement can be done on the basis of expanding the possibilities of learning process individualization and identifying optimal conditions for the educational environment which ensure the formation of students' attitudes toward constant self-development.Novelty/Originality of this study: The scientific novelty of this research lies in establishing the correlation between professional self-development of students during their obtaining pedagogical Masters programs and presence/absence of their teaching experience.
One-stage object detection with graph convolutional networks

The task of Object Detection is to find all the objects of interest in the image and determine their categories and locations. The dominant deep learning-based object detection methods usually regard objects as isolated individuals and ignore the relationship between the objects, which limits the accuracy of the object detection model. There is some work that attaches relationships between categories to candidate proposal regions and proves that the relationship improves the accuracy of object detection, but these methods are all operations of the feature map. In this paper, we propose a correlation complement (CC) module that combines the class representation vector with the relationships between categories in the dataset. Experimental results on multiple object detection datasets prove the effectiveness of our module. In addition, this model is extensible and can be added to other one-stage object detection methods. The task of Object Detection is to find all the objects of interest in the image and determine their categories and locations. The dominant deep learning-based object detection methods usually regard objects as isolated individuals and ignore the relationship between the objects, which limits the accuracy of the object detection model. There is some work that attaches relationships between categories to candidate proposal regions and proves that the relationship improves the accuracy of object detection, but these methods are all operations of the feature map. In this paper, we propose a correlation complement (CC) module that combines the class representation vector with the relationships between categories in the dataset. Experimental results on multiple object detection datasets prove the effectiveness of our module. In addition, this model is extensible and can be added to other one-stage object detection methods.
LibGuides: COM 101 - Public Speaking: Sources & the Information Cycle

Instruction in preparation and delivery of speeches to an audience. The student is graded on the choice and phrasing of thesubject, the selection and arrangement of the material, the adaptation to the audience and the delivery. Usually each studentgiv