Reviewerly/exHarmony huggingface dataset:
The Effect of Freshmen's Perception of Liberal Arts Classes on Their Dropout Intention

The purpose of this study is to find out whether freshmen's perception of liberal arts classes has a significant effect on their dropout intention. To this end, it was analyzed freshmen's perceptions of experience and satisfaction with liberal arts classes compared to other grades, and confirmed whether that affect their intention to drop out. As a result, first freshmen's perception of experience and satisfaction in liberal arts classes were more positive compared to other grades, and in particular, it was significantly higher than that of second graders. Second, unlike other grades, only in the case of freshmen, the perception of 'teaching-learning activities' among the liberal arts class experience affected to the dropout intention. This can be attributed to not only the ratio of freshmen taking liberal arts classes being higher than in other grades but also the teaching-learning activities of liberal arts classes, which they experience for the first time as university students, representing the experience of higher education. Third, it was found that satisfaction with liberal arts classes did not affect dropout in all grades. This seems to be because, even for freshmen, college satisfaction is greatly affected by factors outside of class, such as interpersonal experience and social experience, as well as class.
Art &amp; Culture Education Instructor as a Lifelong Education Instructor : Exploring Roles through Systematic Literature Review

The purpose of this study is to analyze research trends on the art and culture education instructor system through systematic literature review and to explore the role of art and culture education instructor as lifelong education instructor. To this end, researchers summarized and analyzed the discussions on the system of art and culture education instructors and discussed the role of culture and arts education history from a lifelong education perspective, and find implications for the development of the culture and arts education history system. Researchers selected 59 papers out of 131 research papers from 2012, a year before the system was implemented, to 2022 and analyzed focusing on the research methods, topics, research purposes and discussed the role of culture and arts education teachers as lifelong education instructors.
Spanish Coaching Educative and Spanish Digital Platform for a Smart Education Environment System

Today, innovative strategies and concrete examples are being introduced that have been applied to artificial intelligence in education, which is at the core of the 4th industrial revolution. A personalized system for the student that uses artificial intelligence is an ideal way to solve the problems facing education today and accelerate the progress of education. However, the application of information and communication technologies in education is not easy and carries many difficulties and risks. Therefore, it is necessary to discuss methods appropriate to the educational situation. To this end, we are going to present a new educational system called ‘Work by field’ in Spain. This system refers to the fact that the teacher must design and develop specialized digital content so that students can solve problems through artificial intelligence projects. In Spain, an educational environment has already been offered in which information and communication technologies and educational services such as gamification and augmented reality(AR) are used. However, in the case of ‘Work by field', it can be seen as an innovative educational system that requires the improvement of the digital competence of teachers and a change of roles of teachers. In this study, it has the objective of discussing which teaching method is suitable for Korean students of Spanish so that the use of artificial intelligence and education can coexist.
Wiley Digital Archives Royal College of Physicians

The Wiley Digital Archives Royal College of Physicians is a rich collection of primary sources for those interested in history of science or history of medicine. The Royal College of Physicians (RCP) was founded in 1518 and is the oldest medical college in England. Items in the collection date from the fourteenth to twentieth centuries and include such sources as monographs on health research, public health reports, and doctors’ case books. Particularly useful and unique features of this product include the ability to download tabulated data from collection items as Excel and CSV files and maps as TIFFs or GeoTIFFs, which can then be imported into GIS software. Documents are transcribed via ATR/OCR technology and can be downloaded in their original languages or translated into several others. The major weaknesses of the product are a glitchy interface and confusing terminology/categories for the different document types. The search filters are also somewhat confusing. For those who are willing to deal with an interface and search engine that are less than ideal, the collection’s range and diversity may make it a good acquisition.
Investment Incentives and Corporate Social Responsibilities: Does Managerial Long-Termism Matter?

We investigate the effect of the accelerated depreciation Policy (ADP) on the corporate social responsibility (CSR) of Chinese A-share firms from 2010 to 2016. The results of difference-in-differences estimation reveal that the ADP has a considerable effect on CSR performance, particularly in employee responsibility, environmental management, and social value contribution. The ADP helps to improve CSR performance by relaxing financial constraints and mitigating managerial myopia. This effect is driven by the value relevance of corporate reputation and is more pronounced in firms with higher visibility and superior corporate governance quality. Our research reveals that tax policy is influential in value-relevant corporate decision-making.
A Study on the lyrics of the ROK Army unit songs

This study aims to analyze the structure and modes of expression of Army core values by scrutinizing the lyrics of the ROK Army unit songs. For that purpose, this study delves into the rhetorical structure and core values expressed in the song lyrics of 117 brigade level and above commands. The in-depth analysis of the song lyrics confirmed the followings. ① The Army unit songs correspond to the linguistic form of military symbolic culture, and a unit’s identity, core-values, history, and mission are implicitly represented in the lyrics. ② The lyrics of different unit songs conform to a structural pattern which consists of beginning, middle, and end(refrain). ③ The core values of the ROK Army are found to have sub-values such as “loyalty,” “courage,” “responsibility,” “respect,” “creativity,” and etc, and these values are expressed in different lexis associated with each value. ④ Among the values found in units songs, “unity,” “loyalty,” “devotion” are the most frequently expressed values.
Responsible AI

Packed with real-world examples, industry insights and practical activities, this textbook is designed to teach machine learning in a way that is easy to understand and apply. It assumes only a basic knowledge of technology, making it an ideal resource for students and professionals, including those who are new to computer science. All the necessary topics are covered, including supervised and unsupervised learning, neural networks, reinforcement learning, cloud-based services, and the ethical issues still posing problems within the industry. While Python is used as the primary language, many exercises will also have the solutions provided in R for greater versatility. A suite of online resources is available to support teaching across a range of different courses, including example syllabi, a solutions manual, and lecture slides. Datasets and code are also available online for students, giving them everything they need to practice the examples and problems in the book.
Regression

Packed with real-world examples, industry insights and practical activities, this textbook is designed to teach machine learning in a way that is easy to understand and apply. It assumes only a basic knowledge of technology, making it an ideal resource for students and professionals, including those who are new to computer science. All the necessary topics are covered, including supervised and unsupervised learning, neural networks, reinforcement learning, cloud-based services, and the ethical issues still posing problems within the industry. While Python is used as the primary language, many exercises will also have the solutions provided in R for greater versatility. A suite of online resources is available to support teaching across a range of different courses, including example syllabi, a solutions manual, and lecture slides. Datasets and code are also available online for students, giving them everything they need to practice the examples and problems in the book.
Classification 1

Packed with real-world examples, industry insights and practical activities, this textbook is designed to teach machine learning in a way that is easy to understand and apply. It assumes only a basic knowledge of technology, making it an ideal resource for students and professionals, including those who are new to computer science. All the necessary topics are covered, including supervised and unsupervised learning, neural networks, reinforcement learning, cloud-based services, and the ethical issues still posing problems within the industry. While Python is used as the primary language, many exercises will also have the solutions provided in R for greater versatility. A suite of online resources is available to support teaching across a range of different courses, including example syllabi, a solutions manual, and lecture slides. Datasets and code are also available online for students, giving them everything they need to practice the examples and problems in the book.
Word-Order of Clause and NP Objects in Korean: A Corpus Study

This study aims to identify the canonical word-orders when Korean verbs take two objects: a clause and an NP. To pursue this goal, with over 7,000 tokens of 27 Korean utterance verbs which reportedly possess a ‘hearer-theme’ construction (Cho 2009; Lee 2016), it observes how many objects (zero, one, or two objects) are realized in a token sentence, analyzes in what type of syntactic categories the objects appear, and finally examines which word-order is preferred in case of the two objects in a token. Besides, it attempts to classify the 27 utterance verbs in terms of their object realization, i.e., the number and the syntactic types of objects in the tokens, using K-means clustering algorithm and Heirarchical Clustering. The findings are (i) the most of the data fell into zero or one object cases while only 5% of the data occurred with two objects, (ii) the canonical word-order differed depending on the syntactic type of an NP object so that an Accusative NP mostly followed a clausal object while a Dative NP preferably preceded an object clause, and (iii) the verbs given were best categorized into three groups when they took only one complement: hearer-dominant group, theme-dominant group, and hearer/theme group.
In Search of the Limits of Music: What Is the Invariant of Musical Art?

The article discusses the methods of constructing an invariant in musical art. The problem of the invariant in its final form is formulated as the problem of the limits of music. The answer to the question “what is music?” requires the formulation of its invariable properties, which are preserved in any form of acoustic realization of a musical concept. The comparison of three influential models of the invariant of music presented in the works of E. Kurt, G. Schenker and Yu.N. Kholopov allows us to draw a conclusion about a unified method for constructing the invariant of music. It is based on the idea of primary energy, which reveals itself in the course of the embodiment of an artistic conception and appears to us through the acoustic realization of a piece of music. Invariant properties permeate the structure of the musical fabric and then ascend to the most important principles of musical expressiveness, which allow the very possibility of perceiving music as a meaningful sound, in contrast to acoustic phenomena of a different origin. Therefore, the construction of the invariant of musical art requires taking into account its features at hierarchically correlated large-scale levels of organization of musical creativity, perception and thinking. This requirement remains the most general and conventional, uniting strategies for finding an invariant even in those cases when they try to search for the area of limiting invariant properties in various existential and conceptual spheres.
El uso de la videocámara en enseñanza remota y la percepción de los estudiantes sobre la privacidad

This study inquired about the use of cameras in the remote teaching video conference and the students’ perceptions of privacy. Participants were students studying for a bachelor’s degree in the English Language at the Universidad Veracruzana who were exposed to remote teaching with the use of videoconferencing platforms. The research had a mixed-method approach. A semi-structured interview was conducted to collect qualitative data and the survey collected ordinal data using the non-parametric method. Tendency graphics showed the ranks for each topic and students’ perceptions, and participants' quotations derived from the interview. Results showed privacy was not the students’ concern, but the ISP, which affected the appropriate image transference. Findings described that improving social interaction is essential when cameras are turned on, but students preferred saving wideband for audioconference. No perception of abuse or invasion of privacy using cameras was shown, but most preferred cameras to be turned off.
Flexible Estimation Framework for Quality of Service in Smart Grid

In order to establish a complete and unified service quality evaluation system for smart grid, a flexible framework came up to dynamically test and evaluate the timeliness and accuracy of services in scheduling tasks. Based on information fusion theory and time scale marking technology, the framework aggregates the information of all sensing devices in smart grid. The information fusion results are approximated to true values, and the accuracy of measurement data and decision information is evaluated by using the bit-level or semantic-level differences between the observed information and the fusion results. According to the delay sensitivity of information acquisition, the timeliness of service is described and modeled in three scenarios, and quantified by the time of the information acquisition metrics. The way of sliding window and incremental calculation method are used to update the evaluation results dynamically. The achieved service timeliness of our proposed framework is verified by simulations in three target monitoring application scenarios and the service accuracy evaluations in two environmental monitoring application scenarios are also conducted. The simulation results are consistent with the service quality baseline, which shows that the framework can flexibly evaluate the accuracy and timeliness of service in different smart grid tasks.
Hybrid Leapfrog Algorithm in Feature Selection Optimization of Text Classification

The research of hybrid leapfrog algorithm has always been a hot spot.The performance of the classifier model can be improved by improving and optimizing the model.This paper proposes a fusion text semantic structure pattern recognition system based on hybrid leapfrog and support vector machine.The leapfrog algorithm is studied to improve the speed and accuracy of text classification feature selection.This paper mainly uses experimental design and data comparison to illustrate the performance of different algorithms in text classification.The experimental results show that MSFLA-FCM algorithm has great advantages in terms of average fitness value, the maximum fitness reaches 1.518, and the effect of text classification is significantly improved.
The Novel Method for Data Preprocessing CLI

Data preprocessing is the first step in machine learning to ensure data quality and extract useful information from datasets. Derived data after data processing is used for model training and has a direct impact on model efficiency. If there is no relevant and dispensable information in the dataset, it will be removed from the dataset to ensure data quality. Data pre-processing includes description of data, null value handling, categorical value coding, normalization, transformation, extraction and selection of various features.
Sistem Keamanan Sepeda Motor dengan Teknologi Biometrik Sidik Jari Menggunakan Sensor Fingerprint R305

Motorcycles are comm only and widely used vehicles in Indonesia. This vehicle is highly popular because of several advantages they have . Some advantages motorcycles have , among others, ease ness of operation and a slim shape that makes them easier to park . But at the same time, it increas es interest in committing crimes of motorcycle theft. Worse, t he standard security system which is factory default is easier to break into. In this research, a tool is designed to resolve the problem by making double protection on a motorcycle using a fingerprint sensor. The fingerprint sensor acts as double protection in the motorcycle starting process. The fingerprint sensor is a component widely used these days because of its accuracy. T he result of the fingerprint registration test shows the average value of fingerprint registration delay is 7.46 seconds and 8.18 seconds for the two objects. T he results of testing the alarm system if the readings do not match 3 times will be locked for one minute. After being locked for one minute, the system will reset again from the beginning. From the results of the fingerprint test as a starter, it is found that 20 trials a re able to read fingerprints well with the status of registered and unregistered fingerprints. Then i t can be concluded that the accuracy of the fingerprint sensor is 100% accurate. The last test of the four different hand conditions shows almost the same delay value, with the dry hand fingerprint response faster than the others.
KONCEPT DUALNOG OBRAZOVANjA U VISOKOM OBRAZOVANjU U REPUBLICI SRBIJI

The paper discusses the concept of a dual study model in the higher education of the Republic of Serbia. This innovative approach in our country is aimed precisely at creating more efficient and successful responses of our educational system to the needs of the market economy and increasing the available knowledge and available skills in our society. The paper is devoted to a critical analysis of the existing positive legal regulation in order to determine whether it contributes to increasing the relevance of higher education, the employability of graduates, the modernization of the teaching process through cooperation with the economy and contact with modern technological achievements.
Multiscale style transfer based on a Laplacian pyramid for traditional Chinese painting

&lt;abstract&gt;&lt;p&gt;Style transfer is adopted to synthesize appealing stylized images that preserve the structure of a content image but carry the pattern of a style image. Many recently proposed style transfer methods use only western oil paintings as style images to achieve image stylization. As a result, unnatural messy artistic effects are produced in stylized images when using these methods to directly transfer the patterns of traditional Chinese paintings, which are composed of plain colors and abstract objects. Moreover, most of them work only at the original image scale and thus ignore multiscale image information during training. In this paper, we present a novel effective multiscale style transfer method based on Laplacian pyramid decomposition and reconstruction, which can transfer unique patterns of Chinese paintings by learning different image features at different scales. In the first stage, the holistic patterns are transferred at low resolution by adopting a Style Transfer Base Network. Then, the details of the content and style are gradually enhanced at higher resolutions by a Detail Enhancement Network with an edge information selection (EIS) module in the second stage. The effectiveness of our method is demonstrated through the generation of appealing high-quality stylization results and a comparison with some state-of-the-art style transfer methods. Datasets and codes are available at &lt;a href="https://github.com/toby-katakuri/LP_StyleTransferNet" target="_blank"&gt;https://github.com/toby-katakuri/LP_StyleTransferNet&lt;/a&gt;.&lt;/p&gt;&lt;/abstract&gt;
An Overview of Blockchain Technology and Its Adoption in Industry

The development of a cryptocurrency cannot occur without the use of a vital piece of technology known as blockchain. It is a distributed ledger that has progressed to the point where they are now even more applicable and beneficial. This is due to the passage of time and the development of many sectors. These days, blockchain technology is being employed in certain ways throughout all the industries. In this study, each and every significant attribute and weakness is discussed and analyzed. We have also conducted a literature analysis on blockchain-related topics and highlighted some of the most current sectors in which blockchain technology has found the greatest utility.
A Memetic Approach for Classic Minimum Dominating Set Problem

Solving the minimum dominating set problem is an NP-hard problem, which cannot be solved in a polynomial time. In this paper, a memetic algorithm is proposed to solve the minimum dominating set problem. We transform the original problem into a sequence of decision problems, i.e., the k-dominating set problem. The algorithm tackling the k-dominating set problem consists of a local search process embedded in a genetic optimization framework. As an optimization algorithm with a parallel structure, the memetic algorithm speeds up the convergence speed and improves the solution efficiency. The results from the memetic algorithm are compared with those of other algorithms, showing that the memetic algorithm is better.
An Extensive Application of Model Predictive Control Combined with Policy Search to Multi-agent Agile UAV Flight

Reinforcement Learning (RL) methods can automatically learn complex policies with minimum prior knowledge about the task. Meanwhile, Model Predictive Control (MPC) can achieve excellent control performance with convincing safety and interpretation. Thus, there is a growing amount of research combining the advantages of both RL methods and MPC so that high accuracy and adaptability to highly dynamic environments, or in a word agility, can be achieved during various unmanned aerial vehicles (UAVs) flight tasks. However, current studies mostly solve the control problem for a single UAV. This paper extends such a framework to the problem of controlling a multi-agent system with an MPC controller whose decision variables represented as high-level policies are chosen by policy search. We validate the improved method by flying two drones through a moving gate simultaneously. Experiments in simulation demonstrate that the improved controller can preserve robust, in-time control performance and further avoid collision when there are multiple UAVs, showing a promising aspect for realizing multi-agent agile UAV flight.