Reviewerly/exHarmony huggingface dataset:
The Harm of Cryptocurrency Mining to the Environment: How Serious is It

Blockchain technology is a significant part of the fourth industrial revolution (Industry 4.0). However, the mining of cryptocurrency is often accused of harming nature, but the situation is changing. Ecomining is distinguished using renewable energy sources. These can be hydroelectric power plants or energy derived from the sun or wind. The energy consumption for the needs of farms will only grow, which means that people will need more diverse energy sources. But the cost of producing solar panels, wind turbines, hydroelectric dams, etc., is an irretrievable environmental cost in mining, manufacturing and construction. This is usually less expensive, but not the best option. In addition, the production of “green” energy for mining does not work as a separate power system. The use of clean energy sources still means drawing electricity from the system, which is also used to supply electricity to homes, which increases consumption and, thereby, stimulates the creation of new energy projects, including those using coal, oil and gas. The research methods in this study contain a synthesis of theoretical and empirical analysis. In the framework of the theoretical part, a comprehensive and multifaceted study of the literature was carried out in relation to the issues of cryptocurrency mining, its environmental friendliness and harm to the environment. In the framework of the empirical part, a survey was conducted on the dangers of cryptocurrency mining for the environment and the possibilities of more environmentally friendly production.
Conditional Proxy Re-Encryption with Equality Test for Ehr Sharing

The combination of the electronic health record (EHR) and cloud computing has overcome many shortcomings of traditional paper health records in storage and sharing. But the confidentiality and integrity of records require that EHRs should be encrypted before uploading, which hinders searching and sharing. Motivated by the issue, some proxy re-encryption with equality test (PRE-ET) schemes are proposed. However, these schemes have some defects such as excessive proxy power and lack of privacy for keywords. In this paper, we focus on these defects and formally define PRE-ET. According to the definition and based on the proxy re-encryption (PRE) scheme proposed by Libert and Vergnaud in PKC 2008, we present a new PRE-ET scheme. It is proven secure against replayable chosen-ciphertext attacks (RCCA) in the standard model. And to limit the range of ciphertext that can be converted, its re-encryption algorithm is conditional.
Working with Bipolar-Valued Digraphs

The chapter introduces bipolar-valued digraphs, the fundamental root type of all the specialised digraphs implemented in the Digraph3 modules. With the help of a randomly valued digraph, we illustrate some basic digraph manipulation methods, like drawing the digraph, dividing the digraph into its asymmetric and symmetric parts, separating the border from the inner part, computing associated dual, converse and codual digraphs, and operating symmetric and transitive closures.
Overview of Narrative Identity Themes from the Initial Analyses

In Chapter 8, we provide frequencies of narrative identity themes concerning negative and positive consequences of mental illness as well as sources of well-being. We find that costs to relationships, self, and identity are widespread themes and that many participants story their illness as an obstacle to educational and vocational success. Furthermore, about half of our participants narrate negative aspects of treatment into their identity. Some participants evidence positive themes when they interpreted their mental illness as leading to helpful changes in terms of heightened insight, showing strength, and increased care for others. In terms of narrative identity as a source of well-being, relationship themes rank high as do themes concerning self and identity. In addition, participants narrate well-being into their identities through the themes revolving around education, vocation, and leisure activities. Finally, some experiences from psychiatric treatment and care were storied with well-being when constructing identity.
Ways Forward for the Data Science of Human-Environment Systems

Data science plays an increasingly prominent role in examining and addressing human–environment dynamics. The growing role of data-intensive inquiry is apparent to many researchers, policymakers, and others. At the same time, however, there is mounting awareness of the interplay between the perils and promise of big data for human-environment systems in particular. Despite all the research and interest, there are few straightforward ways to reconcile the pros and cons of data science. This difficulty stems partly from the many unknowns about data science because its story is still being written. There are exciting developments in data science theory, conversations around democracy and decision-making, and promising developments in data science infrastructure.
God, Golem, and Gadget Worshippers: Meaning of Life in the Digital Age

Meaning of life and technology are not normally theorized together. But once we realize that all human activity is always technologically mediated, we see that any acts in pursuit of personal significance, too, are so mediated. However, this point then opens the possibility that technology enters the quest for meaning the wrong way. This chapter explores what that possibility means and how to respond to it. I use as my starting point Nozick’s proposal for how to think about the meaning of life. Nozick’s account makes central the idea of “limited transcendence,” essentially folding the kind of transcendence normally involved in interaction with divinity into a finite life. Nozick’s high-altitude view does not make sufficiently clear how technology enters. But once we bring in additional ideas from Ihde and Arendt, we can see clearly how it does. Next, we turn to Wiener’s classic God & Golem. Wiener is concerned with “gadget worshippers,” people who surrender control over their lives to machines in ways that are not appropriate to what these machines can do. Working with this notion, we can throw light on how technology can enter into the quest for meaning the wrong way and offer advice for how to counterbalance this challenge.
Inter-Korean Industrial Cooperation Using Smart Green Industrial Complex

By the halted inter-Korean relationship and worsened international relationship including U.S-Sino conflict, the resume of inter-Korean economic cooperation and exchange is hardly expected. Moreover, Covid-19 pandemic reshapes the global economic environment. Above all, climate change and the reconstruction of global supply chain brought paradigm shift. Therefore, we have to contrive new inter-Korean economic cooperation model to response the changed global situation. The aim of this research is to suggest new direction for the inter-Korean economic cooperation. In addition, it hopes to provide new economic momentum for Korean firms.&#x0D; Regarding the changed external condition, this study suggest new inter-Korean industrial cooperation by utilizing smart green industrial complex. To fulfill this goal this research explores the lesson from the previous industrial cooperation, recent response toward climate change and global norms, the necessity of participation into global supply chain. Besides, it handles global trends including carbon emission reduction and eco-friendly products. Namely, smart green industrial complex seeks high level of industrial cooperation by corresponding with climate change and global trade trends. If the aforementioned goals are achieved then we might obtain the new economic momentum.&#x0D; The successful eco-friendly inter-Korean industrial cooperation will provide economic opportunities to the two Koreas. By the establishing eco-friendly products production base, South Korea can expand its role within the global supply chain. As for North Korea, they will have a chance to consume high-quality products. It can also access the global supply chain. Eventually, these policies would increase the overall industrial capacity of North Korea. Last but not least, South Korea’s brand image will arise as the frontier of eco-friendly industry and a good donor state.
A study on the siting of a comprehensive domestic waste treatment center based on an immune algorithm

The problem of waste disposal is gradually becoming the focus of attention in several fields, and the optimal siting plan is derived by taking the siting of a comprehensive domestic waste treatment center as the research object. The characteristics of domestic waste are obtained, the daily per capita domestic waste production in the region is calculated, a production prediction model is constructed using an immune algorithm, and the regional space is regarded as a limited resource to improve the siting model of the integrated treatment center. The analysis results: Under the same daily domestic waste production conditions, the average values of waste collection distance of the four candidate addresses are 12.448 km, 13.112 km, 9.600 km, and 13.131 km, respectively, and candidate address C has the shortest collection distance, so candidate address C is taken as the best site selection option.
Features and Capabilities of a Blockchain-Based Ridesharing Enhanced with Semantics

The integration of blockchain platforms with Artificial Intelligence (AI) technologies is increasingly frequent in research and industry. Semantic Web technologies provide peculiar opportunities, since they have been devised for information interoperability at Web scale and enable intelligent software agents for knowledge-driven task automation and decision support. The paper presents a blockchain platform extending Hyperledger Sawtooth with Knowledge Representation and Reasoning features. Semantic Smart Contracts allow annotated resource registration, discovery –leveraging non-standard inference services for semantic matchmaking–, explanation –exploiting logic-based justification provided by the adopted inferences– and selection. A prototypical semantic-enhanced ridesharing service has been built to validate the proposed framework and a time-series data collection infrastructure has been deployed for performance analysis.
Statistical analyses on the correlation of corruption perception index and some other indices in Nigeria

This study investigated the statistical analysis of Corruption Perception Index (CPI) in Nigeria considering some other indices which are, Human Development Index (HDI), Global Peace Index (GPI) and Global Hunger Index (GHI). Data set was standardized using two different methods due to the different units and scales used in measuring the indices. Analyses were carried out on the two standardized data sets resulting in different covariance matrices but same correlation matrices, multiple and partial correlation coefficients. Hypothesis testing was carried out on both multiple and partial correlation coefficient at 5% level of significance. Result shows that a slight positive correlation exists between CPI and HDI, CPI and GHI (which implies that as CPI is increasing, HDI is also increasing, same for CPI and GHI) while a slight negative correlation exists between CPI and GPI (which implies a reverse). The partial correlation analysis carried out on the standardized data set indicates that a slight positive relationship exists between CPI and HDI holding GHI and GPI constant, a fair positive relationship exists between CPI and GHI holding HDI and GPI constant (which implies that without considering the effect of GPI, as CPI is decreasing, GHI and HDI are also decreasing) , a fair negative relationship exists between CPI and GPI holding HDI and GHI constant (without considering the effect of HDI and GHI, as CPI is decreasing, GPI is also decreasing) holding CPI constant a fair positive relationship exist between HDI and GHI(without considering the effect of CPI, as HDI is increasing, GHI is also increasing, a moderate positive relationship exists between HDI and GPI and a substantial positive correlation exists between GHI and GPI. Multiple correlation analyses were also carried out on the standardized data set which indicates a moderate positive relationship. Generally, CPI and HDI have dominant effect on the national economy.
Construction of Multi-dimensional Dynamic Evaluation System for College English MOOC Autonomous Learning Based on Data Analysis Technology

With data analysis technology as the core, under Sakai platform, aiming at the shortcomings of the current evaluation system of college students' autonomous learning effect in college English massive open online course(MOOC), we have built an online multidimensional dynamic evaluation platform, which can meet the needs of contemporary college students for management, regulation and evaluation in the process of college English learning. By virtue of the efficient and convenient technical features of Web technology and the comprehensiveness, scientificity and intelligence of data analysis technology, the platform evaluates students' knowledge, skills, attitudes, emotions and other dimensions by means of quantitative data analysis, helps students to comprehensively improve their comprehensive application ability of college English, and strengthens the role played by MOOC teaching in current college English teaching, thus promoting the development process of current college teaching informationization.
Research on chinese numerical words teaching based on CiteSpace scientific knowledge map analysis

The teaching of Chinese Numerical Words is an important part of international Chinese teaching. Based on the analysis of the structure, semantics and grammatical functions of 116 numerical words in the Chinese Vocabulary Levels and Chinese Character Ranks Outline, this paper analyzes the errors combined with HSK dynamic composition corpus. The results show that learners have five kinds of errors: writing errors, structural errors, semantic errors, grammatical errors and pragmatic errors. This paper argues that the use of visual metrological analysis software in the process of teaching and learning is helpful to improve the teaching effect of Chinese numerical words. In addition, combined with CiteSpace software, this paper makes a scientific knowledge map analysis on the chronological distribution of the number of papers published and research hotspots of Chinese Numerical Words.
A Hybrid Speed and Radial Distance Feature Descriptor Using Optical Flow Approach in HAR

Video surveillance is ubiquitous in the public area of the world now. Human activity recognition based on video surveillance automatically identifies and analyses the human activity of continuous frame or video sequence data from various sensors. Human activity such as walking, standing, running, sitting, jogging, interaction and so on is a good representation. The human activity contains such inter-class differences, intra-class similarities and so forth challenges to tackle. In this paper, recognizing human actions based on the Optical Flow approach in video sequences has been addressed. The descriptor with Optical Flow vector of boundaries of activity performance includes silhouette speed on several frames, different areas and the eight different angle’s radial distance. The proposed descriptor with a multi-class Support Vector Machine classifier has achieved good accuracy for each action of the Weizmann datasets.
Research on the Construction of Chinese Painting Network Training Platform Based on Web Technology

Based on Web technology and streaming media technology under RTMP protocol, we can complete the construction of online training platform for Chinese painting in colleges and universities. Aiming at the problems of lack of teaching resources, lack of teachers’ special guidance and lack of supervision and evaluation in the current teaching process of Chinese painting major in colleges and universities, the Chinese painting online training platform has realized the reform of traditional Chinese painting teaching mode with the functions of online resource learning, online live streaming training and exchange evaluation, which has become a good supplement to traditional classroom teaching. With the help of the network training platform, the interactive teaching mode of live streaming can enhance the communication between teachers and students, facilitate students to get professional advice from teachers, stimulate students’ interest in learning and improve the teaching quality of Chinese painting. At the same time, it also provides a new idea for the current educational informatization reform in colleges and universities.
Deep Convolutional Generative Adversarial Network for Metastatic Tissue Diagnosis in Lymph Node Section

In this chapter, we proposed a deep convolutional generative adversarial network (DCGAN) for producing augmented images on the PatchCamelyon (PCam) dataset to improve the metastatic tissue detection performance in the lymph node section using scanned images. Training of the DCGAN is performed on graphics processing unit (GPU) up to 300 training epochs. The DCGAN model increased the training images from 262,144 to 300,000 images. Frechet Inception Distance (FID) method is used to evaluate the fidelity and diversity of the DCGAN model. The augmented images which are generated from the most DCGAN are added to the training data of the metastatic tissue detection model. A VGG19 and InceptionV3 networks were used to build the classification models. The classification accuracy of the VGG19 and InceptionV3 models on the test data are 97.73 and 99.26 percentages, respectively. The classification performance of the model which is trained on the augmented dataset is much higher than the model trained on the original dataset. These extensive results show the significance of the DCGAN in data augmentation.
The Educational Effect of Machine Learning-Based Teacher Education Program on the Classifying State of Matter

Objectives In this study, a machine learning-based teacher education program for classifying the state of matter was developed and implemented for elementary and secondary science teachers and machine learning model for state classification of matter was established. And by analyzing the model evaluation and the experience of science teachers qualitatively, it was attempted to confirm the effectiveness of the program and the perception of science teachers about the application of machine learning to science classes.&#x0D; Methods For 31 elementary and middle school science teachers enrolled in the Graduate School of Education at the College of Education located in the central region, a total of three matter classification activities were performed and a decision tree algorithm was applied to the machine learning model. And the effectiveness of the program was confirmed through model performance evaluation such as accuracy and F1-score. In addition, we qualitatively analyzed the thoughts of science teachers on the application of machine learning.&#x0D; Results TAs a result of evaluating the performance of the built model during a total of 3 state of matter classification activities, it was determined that the accuracy and F1-score values increased statically, resulting in the educational effect of the Machine Learning-Based Teacher Education Program on the Classifying State of Matter. And as a result of analyzing the data of the study participants, it was revealed that there are cases in which the states of matter are classified through a deductive thinking process based on knowledge. As a result of comparing evaluation indicators of the machine learning models, the macroscopic classification criteria had a greater effect than the microscopic classification criteria. And when the classification results between the machine learning model and the research participants for various examples were compared, in the case of mixtures, the degree of inconsistency increased. In addition, through qualitative research analysis, the thoughts of science teachers on the application of machine learning were derived into nine topics, including ‘experience the process of creating science concepts’, ‘cognitive conflict’, and ‘communication’.&#x0D; Conclusions Machine learning should be actively introduced into teacher education as an inquiry-learning method of science education. And educational materials such as textbooks that can properly reflect scientific reasoning processes such as inductive thinking should be developed based on machine learning-based education programs. And it is necessary to discuss from a scientific point of view whether mixtures should be included in the learning of Classifying State of Matter.
Exploring the Core Competencies Required for University Education in the With COVID-19 Era

Objectives This study is to recognize the changes in university education after COVID-19 and to explore core competencies that should be emphasized especially in such changes.&#x0D; Methods For this purpose, the literature review and the FGI and Delphi surveys of 18 university education experts were conducted.&#x0D; Results The main results of this study are as follows: First, non-face-to-face education will continue and expand in the situation of COVID-19 prolonged, and ‘self-educational competence, empathic communication, cooperative attitude, media literacy’ competence is especially important. Second, it is expected that the class using smart technology and edutech will be expanded. In this environmental change, ‘4-IR smart technology utilization, media literacy, creative problem solving ability, challenge practice ability, ethical critical thinking ability’ is required. Third, it is expected that social needs and meanings of the role of university education will be restructured, and the importance of ‘citizen consciousness, creative problem solving ability, career creation competence, and convergence ability’ is highlighted. Fourth, the development and operation of joint curriculum between universities are expected, and in this environment, ‘convergence ability, cooperative attitude, and career creation competence’ are emphasized.&#x0D; Conclusions It is expected to be used as useful basic data for resetting core competencies in future by presenting core competencies that are still important regardless of COVID-19, core competencies that should be emphasized more after COVID-19, and newly highlighted core competencies.