Reviewerly/exHarmony huggingface dataset:
Gravity

This advanced undergraduate physics textbook presents an accessible treatment of classical mechanics using plain language and clear examples. While comprehensive, the book can be tailored to a one-semester course. An early introduction of the Lagrangian and Hamiltonian formalisms gives students an opportunity to utilize these important techniques in the easily visualized context of classical mechanics. The inclusion of 321 simple in-chapter exercises, 82 worked examples, 550 more challenging end-of-chapter problems, and 65 computational projects reinforce students' understanding of key physical concepts and give instructors freedom to choose from a wide variety of assessment and support materials. This new edition has been reorganized. Numerous sections were rewritten. New problems, a chapter on fluid dynamics, and brief optional studies of advanced topics such as general relativity and orbital mechanics have been incorporated. Online resources include a solutions manual for instructors, lecture slides, and a set of student-oriented video lectures.
Special Topics

This advanced undergraduate physics textbook presents an accessible treatment of classical mechanics using plain language and clear examples. While comprehensive, the book can be tailored to a one-semester course. An early introduction of the Lagrangian and Hamiltonian formalisms gives students an opportunity to utilize these important techniques in the easily visualized context of classical mechanics. The inclusion of 321 simple in-chapter exercises, 82 worked examples, 550 more challenging end-of-chapter problems, and 65 computational projects reinforce students' understanding of key physical concepts and give instructors freedom to choose from a wide variety of assessment and support materials. This new edition has been reorganized. Numerous sections were rewritten. New problems, a chapter on fluid dynamics, and brief optional studies of advanced topics such as general relativity and orbital mechanics have been incorporated. Online resources include a solutions manual for instructors, lecture slides, and a set of student-oriented video lectures.
Digital Media in Indigenous Language Education

Education has started a transformation by including digital media technologies to enhance the learning process. This transformation was accelerated by the COVID-19 pandemic, which paralyzed face-to-face classes and switched to distance education modalities through various platforms. Animation and storytelling have been the most influential digital tools to transmit knowledge; also, augmented reality has gained popularity in education. Indigenous languages are a cultural wealth and provide great philosophical and cultural value associated with linguistic diversity. This chapter describes different digital tools developed to teach Cuicateco, Mazateco, and Nahuatl, three indigenous languages spoken in Mexico; then, a usability study is described to evaluate the effectiveness of digital tools; finally, a case study is presented to evaluate the proposed methodology.
Distributed JPEG Compression and Decompression for Big Image Data Using Map-Reduce Paradigm

Digital data is primarily created and delivered in the form of images and videos in today’s world. Storing and transmitting such a large number of images necessitates a lot of computer resources, such as storage and bandwidth. So, rather than keeping the image data as is, the data could be compressed and then stored, which saves a lot of space. Image compression is the process of removing as much redundant data from an image as feasible while retaining only the non-redundant data. In this paper, the traditional JPEG compression technique is executed in the distributed environment with map-reduce paradigm on big image data. This technique is carried out in serial as well as in parallel fashion with different number of workers in order to show the time comparisons between these setups with the self-created large image dataset. In this, more than one Lakh (121,856) images are compressed and decompressed and the execution times are compared with three different setups: single system, Map-Reduce (MR) with 2 workers and MR with 4 workers. Compression on more than one Million (1,096,704) images using single system and MR with 4 workers is also done. To evaluate the efficiency of JPEG technique, two performance measures such as Compression Ratio (CR) and Peak Signal to Noise Ratio (PSNR) are used.
Betrayed by the Bibliographic Record: How Catalogs Construct Authorship and Constrain Their Own Authority

This cautionary tale outlines how a librarian with an understanding of and respect for cataloging processes was the perfect candidate to be duped by a false attribution in a bibliographic record. In the process of compiling a list of compositions attributed to Alma Mahler for my dissertation, I encountered a handful of works not yet addressed in the scholarship on her compositional work. Despite numerous red flags, and much to my detriment, I invested a great deal in one of these unqualified and unsubstantiated attributions that turned out to be false. In the wake of this false attribution, I have had to come to terms with how my professional identity as librarian has worked to my advantage and detriment as a researcher. I leverage the ACRL frames "Authority is Constructed and Contextual" and "Scholarship as Conversation" to explore this tension.
Exploring the Type of Reading Behavior, Following Changes in Reading Motivation of Middle School Students: A Grounded Theoretical Approach

This study aims to explore the changes in reading behavior according to the reading motivation of middle school students. For this purpose, in-depth interviews were conducted with 26 middle school students and analyzed using the grounded theory approach suggested by Strauss and Corbin(1990). As a result of the study, 17 categories (41 sub-categories) were derived, and the central phenomenon was found to be ‘reading motivation weakened, as it slides down in priority’. Based on this, there were five types of change in reading behavior according to reading motivation. The five types are ‘the avoidance‘, ‘the persistence, ‘the restoration’, ‘the deferment,’ and ‘the leap forward’. This study is expected to provide useful information for the development of educational programs to improve reading motivation in middle school students.
An Analysis on the Implications of Changes in the Financial Resources and Scale of Local Education Subsidy for the Restructure of Subsidy System

This study explored the background of the introduction of the local education subsidy system, examined the change in the size of local education finance according to changes in local education financial resources, and analyzed the impact of the revised Local Education Subsidy Act at the end of 2004.&#x0D; The results of the analysis are as follows. Until 2016, there was a significant erosion of operating and facility costs due to the salaries of teachers. The abolition of the extra grant was a result of the abolition of the policy measures to preserve financial resources, and when there was a deficit in the internal tax grant, it had to be resolved by issuing local education bonds. In addition, since 2005, the education tax has not contributed much to the expansion of educational resources.&#x0D; The implication of the reorganization of the grant system is that the simplification of grant resources caused problems in securing the stability of the grant, therefore, it is necessary to diversify financial resources through the revival of salary grant and additional grant, and it is necessary to reorganize the role and function of education tax grant. The suggestions for reorganizing the grant system are as follows. First, it is necessary to diversify the financial resources of local education financial grants. Second, the national education policy should, in principle, be implemented with state subsidies. Third, a structure for issuing and repaying local education bonds should be established only in accordance with the needs of metropolitan/provincial offices of education. Fourth, the Education Tax Act should be replaced with the Higher Education Tax Act. Fifth, grants excluding labor costs should be converted from the internal tax-linked method to the method of the standard education cost per class.
Numerical Approximations of Log Gaussian Cox Process (Student Abstract)

This paper considers a multi-state Log Gaussian Cox Process (`"LGCP'') on a graph, where transmissions amongst states are calibrated using a non-parametric approach. We thus consider multi-output LGCPs and introduce numerical approximations to compute posterior distributions extremely quickly and in a completely transparent and reproducible fashion. The model is tested on historical data and shows very good performance.
The Implication of Jeongokri Lithic Assemblage in the CNU Museum: examining the results of the earliest excavation campaigns

This article is a substitute for an official report of the lithic assemblage stored at Chungnam National University Museum (CNUM). The assemblage was originally acquired by previous museum personnel through several field trips at Jeongokri in 1979. Taking advantage of introducing the Jeongokri assemblage at CNUM, we also reviewed and examined the result of the past Jeongokri Excavation sessions during the earliest phase from 1979 to 1981 in order to suggest some future issues about the archaeological research of the Jeongokri site. A total of 196 lithic specimens were observed and re-classified according to a more refined typological scheme; their quantitative attributes were compiled and analyzed with the same method as adapted on the previously excavated Jeongok ACF assemblage. The result is that: 1) even though the CNUM Jeongokri assemblage is of very cursory and fragmentary surface collection, the assemblage characteristics are quite similar to those of other previously excavated Jeongokri assemblages, 2) and that more clearly defined lithic categories can be established and a new tool type—the pestle—can be suggested to successfully replace the previous ambiguous type—the handplane. In addition, we closely evaluated the context of discovered handaxes within sediments and approached the fundamental reason why the age of the Jeongokri handaxe was wrongfully understood and miscalculated so far. Taking an example of the recently discovered new Jeongokri 85-12 locality, we summoned a caution that the age estimation of the Jeongokri assemblage need to be clearly based on more rigorous designation of typologically genuine handaxes, as well as on the sound explanation of artifact horizon and relevant formation processes lest any more previous trial-and-error should emerge again.
Research Trend Analysis on Core-competency in Higher Education

본 연구는 2010년 이후의 핵심역량 기반 교육 관련 연구, 특히 대학에서 이루어지고 있는 역량 기반 교육의 연구동향에 관하여 분석함으로써 한국에서의 역량 기반 교육이 주로 어떠한 방향으로 이루어지고 있는지 알아보고자 하였다. 역량 및 핵심역량에 대한 개념이 충분히 정립되었고 K-CESA로 대표되는 핵심역량 진단도구가 보편화된 2010년 이후의 연구를 분석함으로써 핵심역량에 대한 개념정립과 이론화 이후 대학에서 학생들의 핵심역량을 진단하고 해당 결과를 어떤 방식으로 활용하여 학생들의 역량을 강화하고 있는지에 대하여 알아보기 위하여 313건의 국내 등재(후보)지 게재 논문을 토대로 연구 제목 및 핵심어, 연구 자료 및 연구 방법, 연구 결과를 분석하였다. 연구의 주요 결론은 다음과 같다. 먼저, 토픽모델링을 바탕으로 대상 논문을 분석한 결과 대학에서의 핵심역량 관련 연구는 대부분 3가지의 주제로 요약될 수 있다. 첫 번째 주제는 대학의 특징을 살린 자체적 핵심역량진단도구 개발이다. 두 번째 주제는 K-CESA 등 대규모 데이터를 활용한 특정 학교 학생, 혹은 대학생 전반의 역량분석과 이를 통한 사례연구가 이루어지고 있었다. 대학에서의 핵심역량 관련 세 번째 연구 주제는 핵심역량 진단을 통한 교육과정 개발과 해당 교육과정의 성과 분석으로, 한국 대학에서의 핵심역량 관련 연구가 점차 역량기반 교육을 지향하고 있음을 알 수 있다.This study aims to explore the research trend on core-competency in higher education, specifically in Korea. Most of the studies had focused on the meaning of competency and core competencies, literature review on the competencies from business field, and the framework for competencies before early 2010s. Korean Collegiate Essential Skills Assessment(K-CESA) has been established from 2010, and now most of the colleges and universities have participated in the assessment. A large scale of dataset has been accumulated for analysis and discussion on the next stage of competency in higher education. Therefore, this study set 2010 as the starting point of analysis. 313 articles were analyzed to see the research trend on core-competency in higher education, and the articles can be categorized in three topics: 1) development of the competency assessment tool, 2) case study based on the core-competency assessment result(e.g. K-CESA), and 3) development and implementation of educational programs based on the assessment result. This result shows that the research on core-competency in higher education has been rapidly increased in terms of quantity, but restricted in a few topics.
Analysis of the moderating effect of class size on student's educational performance: Focused on the changes in teaching methods and relationship with teachers

This study analyzed the moderating effect of the class size on the student's educational performance from the perspective that that class size is closely related to the quality of learning. 4,979 middle school students were analyzed using the data of the Korean Educational Longitudinal Data(KELS) provided by the Korea Educational Development Institute(KEDI), and a two-way fixed effect model was used.&#x0D; The main research results are as follows. First, there were differences in student and school characteristics depending on the class size, mainly students with excellent grades in the middle and upper classes were distributed in large class sizes. In addition, there were statistical differences in teaching methods and relationships with teachers according to class size, when the class size was small, students perceived the teaching method more individual, interactive, and relationships with teachers more positively. Second, there was the moderating effect of class size on class understanding and class concentration. The smaller the class size, the greater the impact of the individualized·interactive class methods and the relationship with the teachers on the class understanding, and the smaller the class size, the greater the impact of the individualized class method on the class concentration. Third, there was no moderating effect of the class size on the academic achievement. However, as a result of analyzing only students who have experienced small classes for three years, clear moderating effects were found.&#x0D; Through the analysis of the moderating effect of class size on educational performance, this study confirmed that the effect of learning quality on educational performance varies depending on the class size. Based on this discussed the importance of class size and education finance, and suggested policy implications and follow-up studies.
The Changes and Issues of Securing Finance in the Local Education Finance Grant Act at the Central Government Level

The study analyzed the whole changes and issues of the Local Education Finance Grant Act in terms of sufficiency and stability of Local Education Financial Grant which was secured by the central government. The study collected and analyzed the minutes of the National Assembly meetings, government data, and related prior research related to the enactment and revision of the Local Education Finance Grant Act.&#x0D; The findings were as follows: first, the Local Education Financial Grant Act tried to secure the sufficiency and stability of education finance in terms of securing financial resources to complete compulsory middle school education and introduce free education for early childhood education and upper secondary education. However, since the measures to secure financial resources for early childhood education and free high school education are both temporary, it is necessary to ensure the sufficiency and stability by stipulating a method for securing finance in the Grant Act. Second, it is highly recommended to estimate the appropriate size of Local Education Finance Grants through analysis of the demand for local education finance. The Local Education Financial Grant Act is subject to controversy over environmental changes due to a sharp drop in the number of students and the appropriateness of the subsidy size. Third, it is also necessary to design methods of securing financial resources such as Grant for teachers’ salaries and allowances in the future.
The Best Smartphone Brand using The Preference Selection Index Method

The existence of the Covid-19 pandemic has had a tremendous impact in all aspects, including the educational aspect. Before the pandemic, education generally is done by face-to-face learning, but after the pandemic hit, it changed to online learning. Several problems often occur during online learning education, especially for college students, such as a mobile phone that does less support for online learning activities. Hence, the author wants to build an application that has the function of helping users to choose a mobile phone which supports online learning activities. The selection decision used by the author is the Preference Selection Index method since it can determine the value for each attribute and continue with a ranking that is able to select each attribute from the best alternative from several existing alternatives, with the help of a decision support system and application of the PSI (Preference Selection Index) method. The result indicates that the highest value obtained from smartphone selection with an average price under 3 million rupiah is infinix by 90.88%. The application's output meets the purpose because it is able to provide recommendations to buyers in determining which smartphone to buy and can simplify the decision-making process to become more accurate, effective, and efficient in generating information.
Sociolinguistic repositories as asset: challenges and difficulties in Brazil

Purpose This paper aims to provide a context for Brazilian Portuguese language documentation and its data collection to establish linguistic repositories from a sociolinguistic overview. Design/methodology/approach The main sociolinguistic projects that have generated collections of Brazilian Portuguese language data are presented. Findings The comparison with another situation of repositories (seed vaults) and with the accounting concept of assets is evocated to map the challenges to be overcome in proposing a standardized and professional language repository to host the collections of linguistic data arising from the reported projects and others, in the accordance with the principles of the open science movement. Originality/value Thinking about the sustainability of projects to build linguistic documentation repositories, partnerships with the information technology area, or even with private companies, could minimize problems of obsolescence and safeguarding of data, by promoting the circulation and automation of analysis through natural language processing algorithms. These planning actions may help to promote the longevity of the linguistic documentation repositories of Brazilian sociolinguistic research.
Towards Explainable Action Recognition by Salient Qualitative Spatial Object Relation Chains

In order to be trusted by humans, Artificial Intelligence agents should be able to describe rationales behind their decisions. One such application is human action recognition in critical or sensitive scenarios, where trustworthy and explainable action recognizers are expected. For example, reliable pedestrian action recognition is essential for self-driving cars and explanations for real-time decision making are critical for investigations if an accident happens. In this regard, learning-based approaches, despite their popularity and accuracy, are disadvantageous due to their limited interpretability. This paper presents a novel neuro-symbolic approach that recognizes actions from videos with human-understandable explanations. Specifically, we first propose to represent videos symbolically by qualitative spatial relations between objects called qualitative spatial object relation chains. We further develop a neural saliency estimator to capture the correlation between such object relation chains and the occurrence of actions. Given an unseen video, this neural saliency estimator is able to tell which object relation chains are more important for the action recognized. We evaluate our approach on two real-life video datasets, with respect to recognition accuracy and the quality of generated action explanations. Experiments show that our approach achieves superior performance on both aspects to previous symbolic approaches, thus facilitating trustworthy intelligent decision making. Our approach can be used to augment state-of-the-art learning approaches with explainabilities.
Frequent Itemsets: Fuzzy Data from Multiple Datasets

The application of association rule mining plays crucial role in the operations of data warehousing and data mining. To support this argument, the paper proposes a model having fuzzy taxonomic structure at the backend while retrieving frequent itemsets from the database which are organized in the form of star schema tabular database structures. The objective of the study generate new algorithm from the existing algorithm which deploy fuzzy association rule based mining operations in the databases having ER models. The focal point of the paper is centered on the extraction of rules pertaining to linguistic algorithm at multi level structures from several databases in the form tables so as to understand the performance of these extracted data item sets. An example at the end outlines the working of the proposed data mining algorithm which can be used to arrive at the multi level fuzzy rules which pertains to association mining algorithms in an easy and an effective manner.
Deep Fusing Pre-trained Models into Neural Machine Translation

Pre-training and fine-tuning have become the de facto paradigm in many natural language processing (NLP) tasks. However, compared to other NLP tasks, neural machine translation (NMT) aims to generate target language sentences through the contextual representation from the source language counterparts. This characteristic means the optimization objective of NMT is far from that of the universal pre-trained models (PTMs), leading to the standard procedure of pre-training and fine-tuning does not work well in NMT. In this paper, we propose a novel framework to deep fuse the pre-trained representation into NMT, fully exploring the potential of PTMs in NMT. Specifically, we directly replace the randomly initialized Transformer encoder with a pre-trained encoder and propose a layer-wise coordination structure to coordinate PTM and NMT decoder learning. Then, we introduce a partitioned multi-task learning method to fine-tune the pre-trained parameter, reducing the gap between PTM and NMT by progressively learning the task-specific representation. Experimental results show that our approach achieves considerable improvements on WMT14 En2De, WMT14 En2Fr, and WMT16 Ro2En translation benchmarks and outperforms previous work in both autoregressive and non-autoregressive NMT models.
Intelligent personal assistant for personal computers using long short-term memory-based verbalizer

Purpose An intelligent personal assistant for personal computers (PCs) is a vital application for the current generation. The current computer personal assistant services checking frameworks are not proficient at removing significant data from PCs and long-range informal communication information. Design/methodology/approach The proposed verbalizers use long short-term memory to classify the user task and give proper guidelines to the users. The outcomes show that the proposed method determinedly handles heterogeneous information and improves precision. The main advantage of long short-term memory is that handle the long-term dependencies in the input data. Findings The proposed model gives the 22% mean absolute error. The proposed method reduces mean square error than support vector machine (SVM), convolutional neural network (CNN), multilayer perceptron (MLP) and K-nearest neighbors (KNN). Originality/value This paper fulfills the necessity of intelligent personal assistant for PCs using verbalizer.