Reviewerly/exHarmony huggingface dataset:
The significance of Incheon Culture Forum and its future direction

인천문화포럼(이하 ‘포럼’)은 2017년 ‘시민의 문화적 권리 실현’이라는 목표 아래 ‘시민이 참여하는 협력형 문화정책 네트워크 구축’이라는 과제를 실현하기 위해 출범한 인천시 조례상의 조직이다. 인천시의 문화정책에서 문화예술인, 학계 등 전문가만이 민관협치의 대상이었으나, 처음으로 시민까지 포함했다는 점에서 그리고 시민의 문화권 실현이라는 비전하에서 이뤄졌다는 점에서 주목을 끈다. 이러한 중요성에도 불구하고 지금까지 포럼은 제대로 관심을 받지 못했다. 이 연구는 포럼의 출범 배경에서부터 그 운영과정을 살펴본 후, 포럼의 문제가 무엇인지 분석하고 새롭게 도약하기 위한 방향이 어떤 것인지 제시하려고 한다. 사실상 포럼의 가장 큰 문제는 장기적인 과제를 실현하기 위한 현실적인 추진방향을 제대로 설정하지 못한 것이다. 운영상의 문제 상당 부분도 여기에서 기인했다. 추진방향의 수준이 너무 높거나, 관성적이거나, 적절했지만 과제의 일부분에 불과했다. 게다가 추진방향이 적절하더라도 운영상의 문제들은 발생했다. 향후 포럼을 제대로 운영하기 위해서 우선 추진방향을 현실적으로 설정해야 한다. 조직구성에 있어 과제에 맞는 분과를 만들고 인천문화재단이 포럼의 사무국으로서, 그리고 포럼이라는 네트워크의 관리자로서 그 역할을 명확히 해야 한다. 운영원칙은 세심하게 준비해야 하며, 무엇보다 포럼위원의 인선, 교육, 상호신뢰의 축적 방안을 마련해야 한다. 최초로 포럼의 의미를 밝히고 포럼의 발전 방향성을 제시함으로서 포럼의 지속을 위한 토론 자료를 제공했다는 점에서 이 연구의 의의를 찾을 수 있다. Incheon Culture Forum (henceforth ‘forum’) was created through an Incheon-city ordinance in order to “enshrine its citizens’ cultural rights” through the creation of a ‘collaborative network on cultural policy open to citizens participation’. The Forum was the first attempt at a form of cultural governance which included not just artists, academics, and more generally specialists in arts and cultural matters, but also citizens. Despite its significance, the Forum hasn’t received much attention. This paper examines 1) the background which led to the creation of this Forum and how this institution has been run since then 2) identifies problems in them and 3) suggests which direction it should take in the future in order to reform itself. In fact, the fundamental issue with the Forum is its inability to set itself concrete and short-term goals in order to realize its long-term ones. A lot of the operational issues it faced can be understood to stem from this more fundamental issues. Its goals were either too ambitious, uninspiring, or even adequate but insufficient. And sometimes, even if its goals were adequate, operational issues emerged. For its future functional operation, the Forum must first set its directional goals realistically. In terms of structure, it should create divisions adequate to its tasks; and this initiative should come from its bureau and manager of its network, i.e. the Incheon Cultural Foundation. It should also set detailed operational principles, while also creating measures for the selection, education of, and the creation of mutual trust within the Forum committee. The value of this paper lies in the fact that it is the first to articulate the significance of the Forum, while also recommending the direction that it should take for its future development.
Blockchain-Based Certificate Verification

Academic certificates are essential to acknowledge one’s academic achievement. With the credentials, it can be used to develop a career in a desired industry based on the qualifications. However, nowadays, fake academic certificates are used by irresponsible individuals to apply for a job. Therefore, it is crucial for the employer to validate one’s academic certificate before offering them the job position. To validate, a certificate may be too troublesome and require a long time for the verification process. In addition, the employer must check with the certificate’s issuer, which can involve a lot of processes. Thus, to solve this problem, blockchain-based certificate verification is introduced where the issuer can store the certificates details inside a blockchain network with the help of a smart contract feature that is immutable and anti-counterfeit. Smart contract is written in Solidity programming language and executed in Remix IDE. In terms of security for this smart contract, only the certificate’s issuer is able to add, edit, modify, and delete the details stored. Not only that, the contract’s owner also unable to add data into the blockchain due to the decentralized feature of a blockchain network. The average execution time for the smart contract is 8.3 s. All changes made to the certificate’s details can be tracked; thus, changes to the previous recording are impossible. This system will benefit the university because the students' data can be stored in a system and can be retrieved anytime. For a third-party user such as the employer, it can save time to check the validity of the academic certificates they received because the system generates the confirmation of transaction in less than five seconds.
Eigenvalue-Invariant Transformation of Ising Problem for Anti-Crossing Mitigation in Quantum Annealing

We have proposed the energy landscape transformation of Ising problems (ELTIP), which changes the combination of the state and eigenvalue without changing all the original eigenvalues [arXiv:2202.05927]. We study how the ELTIP affects the anti-crossing between two levels of the ground and first excited states during quantum annealing. We use a 5-spin maximum-weighted independent set for the problem to numerically investigate the anti-crossing. For comparison, we introduce a non-stoquastic Hamiltonian that adds antiferromagnetic interaction to the normal transverse magnetic field. Annealing with the non-stoquastic Hamiltonian is effective for difficult problems. The non-stoquastic Hamiltonian mitigates the anti-crossing when only the energy gap between the ground state and the first excited state of the final state is small. When the ELTIP is used, the anti-crossing disappears. For the problems investigated in this paper, the ELTIP shortens the annealing time to guarantee adiabatic change more than the non-stoquastic Hamiltonian.
Decision support for multicloud deployment of a modeling environment

Nowadays, many companies are moving their activities to the cloud. They are using advantages such as collaboration, disaster recovery, and cost savings as the drive for this change. Nonetheless, many cloud providers have different offerings, some more appealing than others. This article describes decisive factors for the deployment of modeling environments using a multicloud deployment platform. This is conceived for users who are specialists in modeling, but not in cloud computing, but who intend to take advantage of cloud environments’ capabilities. The automate decisions are made by leveraging the decision trees and providing a decisional algorithm that helps one decide the deployment details. Furthermore, the paper evaluates the algorithm from the perspective of the most valuable outcome of it.
Keynote Lecture Towards Neuro-Symbolic AI

A central goal of artificial intelligence is to design algorithms that are both generalisable and interpretable. We combine brain-inspired neural computation principles and scalable deep learning architectures to design compact neural controllers for task-specific compartments of a full-stack autonomous vehicle control system. We show that a single algorithm with 19 control neurons, connecting 32 encapsulated input features to outputs by 253 synapses, learns to map high-dimensional inputs into steering commands. This system shows superior generalisability, interpretability and robustness compared with orders-of-magnitude larger black-box learning systems. The obtained neural agents enable high-fidelity autonomy for task-specific parts of a complex autonomous system.
A Sensitive Data Protection Framework Based on TrustZone

The development of the Internet has made mobile devices become an indispensable part of work for people to store and process sensitive data. Protecting data through encryption algorithms is one of the best ways to solve data security problems at the current stage. However, traditional solutions only focus on the security of encrypted data, and cannot guarantee the security of data during the encryption process. Therefore, in view of the security problems of traditional data encryption, A sensitive data protection framework is proposed in this paper. The encryption process is security enhanced by implementing the data encryption process in the Trusted Execution Environment (TEE). The uniqueness and security of the keys are guaranteed by generating the keys related to the device and the application. The prototype system is implemented based on Qemu. Finally, experiments show that this framework has good security and feasibility with little increase in overhead.
Performance, Technologies, Ontologies

In this chapter, Machalik Gratch discusses an internet-based project created for online audiences only. The project is an extension of oral interpretation, remix practices, and devised performance. The author offers a practical, yet well theorized approach to understanding the process of making digital performance.
Fake news published during the pre-election period and free speech theory

In this essay, I raise the question of whether fake news—which I understand as false statements that are presented in the form of real news in order to mislead a target audience and are likely to be believed by the latter—should be subject to legal regulation. In particular, I am interested in political fake news published during the pre-election period. According to a strong U.S. judicial tradition, the regulation of mendacious political speech is unconstitutional, since it involves the imposition of content-based restrictions on a protected category of free expression. I discuss certain arguments in favour of this approach, which I do not find convincing in the case at hand. This conclusion combined with the threat fake news constitutes to conducting free and fair elections, provides us with strong prima facie reasons for making its publication and deliberate dissemination punishable by law, although more discussion and deliberation are needed before a final legislative decision is made.
Sexist hate speech against women

Hate speech online is an ongoing and continuously evolving phenomenon: every second enormous quantity of hatred is being spilled on social networks, published on webpages, tweeted among friends and colleagues and searched for on search engines. Not all this hatred is legally relevant and yet it worries civil society as well as public institutions, because it constantly shows us that narrow-mindedness, prejudice and intolerance are so accessible, so common and so close to us, to our children, to vulnerable social groups—such as ethnic, racial, religious and other minorities, people with disabilities and so on—all of whom more often than not become not only passive observers but also targets for haters. However, technological advancements not only (to a certain extent) guarantee the anonymity of haters and permit to share and disseminate this abominate speech but can be also used to fight it: this contribution focuses on artificial intelligence (AI)-based techniques and algorithms that are being used for that purpose. On the one hand, AI tries to identify the hate speech and stop it from spreading, but on the other hand, AI is also used to identify the groups of people against whom the hate speech is being directed so as to prevent and get ahead of any possible mobilisations of haters who could decide to leave the online world and move to the real one and translate their hatred into criminal behaviour. This chapter analyses different ways in which AI is used for this purpose and looks at how and whether AI could stop the spreading of hate speech. The chapter also addresses the main hurdles that could hamper AI in being successful, such as difficulties in natural language processing and contextualisation of the speech, and the possibility that the AI (bots) were used by haters themselves to generate hate speech-based audio and video content. Gender-based hate speech against women is a form of gender-based violence. Its roots are cultural and deep in society. Gender-based hate speech against women is often invisible and imperceptible given that hate expressions are deeply internalised in daily language. In reality, they are expressions that denote a deep contempt and in some cases hatred which often is translated into violence against women. What does the law do in relation to this issue? This chapter intends to analyse, from a comparative perspective, the approach developed towards hate speech against women for gender reasons from a normative and judicial point of view.
Exploring Cryptocurrencies: The History, the Hype, and the Future

We attempt to explain cryptocurrencies, their evolution and variety, and their potential place in portfolios. For many, cryptocurrency has become synonymous with Bitcoin, but there is a great variety of cryptocurrencies, all unified by distributed ledger technology—typically blockchain—whose mechanism, theoretical strengths, and practical weaknesses we describe. We also explore where blockchain can have applications beyond cryptocurrencies. In our view, cryptocurrencies are not intended to function only as private digital currencies. We explore them as investable assets that may be fit into portfolios, and evaluate several attempts at valuing them. We also analyze the correlation of cryptos with other asset classes, concluding that their severe drawdowns make cryptos far riskier than equities, and observing that as their market capitalization increases, major cryptos are expected to behave more in line with traditional risk assets. We distinguish cryptocurrencies from the technology that enables them and highlight the potentially transformative implications of so-called atomic settlement (the simultaneous, instantaneous transfer of assets) and how it may translate to assets more generally. Cryptos’ uncertain and rapidly evolving future includes the likelihood of central bank digital currencies (CBDCs) issued by central banks as legal tender. We conclude by discussing exposure methods to cryptocurrencies and (in our view) their highly promising blockchain technology, from direct ownership to broader market approaches.
Large-Scale Identification and Analysis of Factors Impacting Simple Bug Resolution Times in Open Source Software Repositories

One of the most prominent issues the ever-growing open-source software community faces is the abundance of buggy code. Well-established version control systems and repository hosting services such as GitHub and Maven provide a checks-and-balances structure to minimize the amount of buggy code introduced. Although these platforms are effective in mitigating the problem, it still remains. To further the efforts toward a more effective and quicker response to bugs, we must understand the factors that affect the time it takes to fix one. We apply a custom traversal algorithm to commits made for open source repositories to determine when “simple stupid bugs” were first introduced to projects and explore the factors that drive the time it takes to fix them. Using the commit history from the main development branch, we are able to identify the commit that first introduced 13 different types of simple stupid bugs in 617 of the top Java projects on GitHub. Leveraging a statistical survival model and other non-parametric statistical tests, we found that there were two main categories of categorical variables that affect a bug’s life; Time Factors and Author Factors. We find that bugs are fixed quicker if they are introduced and resolved by the same developer. Further, we discuss how the day of the week and time of day a buggy code was written and fixed affects its resolution time. These findings will provide vital insight to help the open-source community mitigate the abundance of code and can be used in future research to aid in bug-finding programs.
Metaverse academic library: would it be patronized?

Purpose This study aims to examine if students would patronize metaverse academic library (MAL) if it becomes available in Nigeria. Design/methodology/approach This study used a descriptive survey research design. The population was made up of 1,037 undergraduate in Adeleke University. Descriptive statistic was used to analyse data. Findings Findings indicated most students have never used virtual reality (VR) equipment, they are eager to use MAL for virtual academic research, library user education, accessing circulation services, reading serials and contacting reference librarians. The study concluded that MAL would be patronised by students if it is made available and therefore recommends that greater effort be made to make VR gear accessible and cheap for developing nations such as Nigeria. Originality/value The study is novel as it contributes to scarce research on MAL.
Teacher-Guided Learning for Blind Image Quality Assessment

The performance of deep learning models for blind image quality assessment (BIQA) suffers from annotated data insufficiency. However, image restoration, as a closely-related task with BIQA, can easily acquire training data without annotation. Moreover, both image semantic and distortion information are vital knowledge for the two tasks to predict and improve image quality. Inspired by these, this paper proposes a novel BIQA framework, which builds an image restoration model as a teacher network (TN) to learn the two aspects of knowledge and then guides the student network (SN) for BIQA. In TN, multi-branch convolutions are leveraged for performing adaptive restoration from diversely distorted images to strengthen the knowledge learning. Then the knowledge is transferred to the SN and progressively aggregated by computing long-distance responses to improve BIQA on small annotated data. Experimental results show that our method outperforms many state-of-the-arts on both synthetic and authentic datasets. Besides, the generalization, robustness and effectiveness of our method are fully validated. The code is available in https://github.com/chencn2020/TeacherIQA .
Multi-granularity Transformer for Image Super-Resolution

Recently, transformers have made great success in computer vision. Thus far, most of those works focus on high-level tasks, e.g., image classification and object detection, and fewer attempts were made to solve low-level problems. In this work, we tackle image super-resolution. Specifically, transformer architectures with multi-granularity transformer groups are explored for complementary information interaction, to improve the accuracy of super-resolution. We exploit three transformer patterns, i.e., the window transformers, dilated transformers and global transformers. We further investigate the combination of them and propose a Multi-granularity Transformer (MugFormer). Specifically, the window transformer layer is aggregated with other transformer layers to compose three transformer groups, namely, Local Transformer Group, Dilated Transformer Group and Global Transformer Group, which efficiently aggregate both local and global information for accurate reconstruction. Extensive experiments on five benchmark datasets demonstrate that our MugFormer performs favorably against state-of-the-art methods in terms of both quantitative and qualitative results.
Cluster analysis by group between learning motivation and academic adaptation to smart media utilization of beauty major Adolescents

Objectives This study clustered the perceived benefits, perceived sacrifices, perceived values, and academic adjustment of smart media based on academic motivation, growth mindset, academic expectations, and value-based acceptance model of beauty majoring youth. and identified significant differences in academic adaptation.&#x0D; Methods The sample for this study was 581 middle school and high school male and female students majoring in beauty in Seoul were sampled. Individuals of similar types among research factors were grouped into categories, and cluster analysis of the overall approach for various attributes was performed, and F-test of difference analysis on academic adaptation between clusters was performed. Cluster analysis was conducted based on the collected research data.&#x0D; Results First, the classification of group types was examined. As a result, the groups were classified into 4 types, and cluster 1 was classified into high multiple groups, cluster 2 high sacrifice, cluster 3 high, intrinsic cluster 4, and multiple bottom groups. Second, the average value of ANOVA for each cluster was. Significant differences between groups were confirmed according to perceived value and academic adjustment.&#x0D; Conclusions This study confirmed the difference between clustering for academic adaptation through cluster analysis of learners' learning motivation and smart media in order to improve the academic adaptation of beauty major youth. Additionally, it was confirmed that the improvement of the learning environment had a positive effect on academic adaptation, and it was confirmed that a strategic approach according to the difference between groups was necessary. In future studies, it is suggested that a two-way longitudinal study of differences between groups and between individuals be conducted.
The Effects of fatigue, depression, and quality of life on leisure satisfaction of college students due to prolonged COVID-19

Objectives This study attempted to understand the relationship between fatigue, depression, quality of life, and leisure satisfaction of college students due to the prolonged COVID-19, and to understand the factors affecting leisure satisfaction.&#x0D; Methods The convenience was extracted from college students who experienced more than one semester of non- face-to-face online lectures among 130 college students enrolled in 4-year colleges in C province. Data collection was conducted from June 1st to June 14th, 2021 and the non-face-to-face URL questionnaire was used for the collection. The collected data was analyzed using SPSS 19.0 program for the mean and standard deviation, Pearson correlation coefficient, and stepwise multiple regression.&#x0D; Results The leisure satisfaction of college students due to the prolonged COVID-19 has a positive(+)correlation with depression, negative correlation, and quality of life, and the higher the leisure satisfaction, the lower the depression and the higher the quality of life. In addition, as a result of analyzing the factors influencing college students' fatigue, depression, and quality of life on leisure satisfaction, fatigue and depression had no significant effect, and quality of life had a significant effect on leisure satisfaction, and the explanatory power of the model was 46%.&#x0D; Conclusions The purposes of this study were to identify the degree of fatigue, depression, and quality of life of college students, and to identify leisure satisfaction according to the variation of the subjects, and to provide basic data for college students to lead their daily and leisure lives and improve mental health in a pandemic situation.