Reviewerly/exHarmony huggingface dataset:
Importance-Performance Analysis of Core Future Competencies needed by Social Welfare Students in the era of the 4th Industrial Revolution

본 연구는 미래사회에서 중요해질 것으로 예견되는 기초 역량 즉 핵심 미래역량의 교육에 현재 대학 교육이 충실히 임하고 있는지를 교육 서비스 수요 당사자인 사회복지학과 재학생의 인식을 통해 파악하고, 이를 바탕으로 향후 사회복지 교육 개선의 방향성을 제시하는 것을 목적으로 하였다. 이를 위해 강원도 내 소재 대학의 사회복지학과에 재학 중인 대학생 207명을 대상으로 수집된 데이터를 분석하였다. 총 14개의 핵심역량을 바탕으로 중요도와 실행도의 차이를 IPA(Importance-Performance Analysis) 기법을 활용하여 분석하였다. 주요 연구결과는 다음과 같다. 첫째, 모든 역량의 중요도 인식 수준이 실행도 인식 수준보다 높아 전반적으로 미충족 욕구가 존재하는 것으로 확인되었다. 둘째, 변화대응역량, 복합문제해결역량, 융합적 사고력, 창의력을 신장시킬 수 있는 교육의 필요성이 가장 시급한 것으로 밝혀졌다. 셋째, ICT기반 최신기술역량, 인간-기계협업역량, 글로벌시민역량 등에 대한 중요성과 사회복지학과의 접점에 대한 이해도를 증진시키기 위한 교육의 필요성이 제시되었다. 이상의 연구 결과를 바탕으로 4차 산업혁명시대가 요구하는 사회복지사의 역량을 함양하기 위해 대학의 사회복지학 교육이 나아가야 할 방향에 대한 정책적, 실천적 방안을 제시하였다.This study identified whether university education is currently faithfully engaged in the education of basic competencies, that is, core future competencies, through the perception of social welfare students who are in demand for educational services. The purpose of this study was to find out through perception, and based on this, to present a direction for improving social welfare education in the future. To this end, data collected from 207 students enrolled in the Department of Social Welfare at a university located in Gangwon-do were analyzed. Based on a total of 14 core competencies, the difference in importance and performance was analyzed using the IPA (Importance-Performance Analysis). The main research findings are as follows. First, it was confirmed that the level of perception of the importance of all competencies was higher than the level of perception of the level of execution, so that there were overall unmet needs. Second, it was found that the need for education that can enhance change response capability, complex problem solving capability, convergence thinking ability, and creativity is the most important. Third, the importance of ICT-based latest technology competency, human-machine collaboration competency, global citizen competency, etc., and the need for education to enhance perception of the interface with the Department of Social Welfare was suggested. Based on the above research results, policy and practical plans for the direction in which social welfare education in universities should go in order to cultivate the capabilities of social workers required in the era of the 4th industrial revolution were presented.
Towards Analyzing Psychomotor Group Activity for Collaborative Teaching Using Neural Networks

Collaborative teaching in psychomotor skills requires the ability to detect and analyze the movements and postures of multiple participants simultaneously. In this paper we explore the feasibility of analyzing group activity in psychomotor contexts using neural networks. We apply our approach to kihon kumite, a training exercise in karate where two participants perform predetermined techniques. The overall activity is measured as the sum of individual performances, with the support of computer vision techniques to label individuals and classify postures. Furthermore, interactions between participants are also analyzed, which allows for a more comprehensive understanding of the group activity. Our approach shows promising results for improving collaborative teaching in psychomotor skills and can be extended to other physical activities.
Using Large Language Models to Develop Readability Formulas for Educational Settings

Readability formulas can be used to better match readers and texts. Current state-of-the-art readability formulas rely on large language models like transformer models (e.g., BERT) that model language semantics. However, the size and runtimes make them impractical in educational settings. This study examines the effectiveness of new readability formulas developed on the CommonLit Ease of Readability (CLEAR) corpus using more efficient sentence-embedding models including doc2vec, Universal Sentence Encoder, and Sentence BERT. This study compares sentence-embedding models to traditional readability formulas, newer NLP-informed linguistic feature formulas, and newer BERT-based models. The results indicate that sentence-embedding readability formulas perform well and are practical for use in various educational settings. The study also introduces an open-source NLP website to readily assess the readability of texts along with an application programming interface (API) that can be integrated into online educational learning systems to better match texts to readers.
How Can ChatGPT Help in Automated Building Code Compliance Checking?

How Can ChatGPT Help in Automated Building Code Compliance Checking? Jiansong Zhang Pages 63-70 (2023 Proceedings of the 40th ISARC, Chennai, India, ISBN 978-0-6458322-0-4, ISSN 2413-5844) Abstract: One main challenge in the full automation of building code compliance checking is in the extraction and transformation of building code requirements into computable representations. Semantic rule-based approach has been taken mainly due to its expected better performance than machine learning-based approach on this particular task. With the recent advancement in deep learning AI, particularly the launch of ChatGPT by OpenAI, there is a potential for this landscape to be shifted given the highly regarded capabilities of ChatGPT in processing (i.e., understanding and generating) natural language texts and computer codes. In this paper, the author preliminarily explored the use of ChatGPT in converting (i.e., extracting and transforming) building code requirements into computer codes, and compared it with the results from cutting-edge semantic rule-based approach. It was found that comparing to the semantic rule-based approach, the conversion results from ChatGPT still has limitations, but there is a great potential for it to help speed up the implementation and scale-up of automated building code compliance checking systems. Keywords: Automated building code compliance checking, AI, ChatGPT, SNACC, Natural language processing DOI: https://doi.org/10.22260/ISARC2023/0011 Download fulltext Download BibTex Download Endnote (RIS) TeX Import to Mendeley Presentation Video: https://youtu.be/cLXvIm9s2R0
Beyond the tool vs. teammate debate: Exploring the sidekick metaphor in human-AI dyads

From symbiosis to copilot, a wide range of metaphors have been employed to characterize cooperative and collaborative relationships between human and non-human agents (be they software, robots, algorithms, or automated agents of any kind) in support of designing such advanced technologies. Recently, the emergence and rapid commoditization of artificial intelligence (AI) and machine learning (ML) algorithms have driven a highly bimodal debate on what metaphor is best to account for AI’s and ML’s new capabilities, particularly when those closely mimic humans’: Is AI a tool or a teammate for humans using the technology? This debate, however, occludes critical elements necessary to practitioners in the fields of human system design. To move past the “tool vs. teammate debate,” we propose an orthogonal metaphor, that of a sidekick, inspired by popular and literary culture, which can both accomplish and facilitate work (i.e., they do, and they help do). The sidekick metaphor was applied to a variety of efforts where it yielded novel design considerations which would have otherwise been unattainable by previous approaches. In this contribution, we report on the debate, describe the sidekick metaphor, and exemplify its application to real-world use cases, in domains such as intelligence analysis, aircraft maintenance, and missile defense.
What Matters in Hiring Professionals for Global Software Development? A SLR and NLP Criteria Clustering

Globalization stimulated a new era of Global Software Development (GSD), followed by the gig economy (GE) phenomenon, which jointly caused considerable transformations in software development markets, mainly after the recent supply chain disruptions. The cultural and geographic barriers have compelled numerous organizations to devise comprehensive digital technologies to overcome this situation. Likewise, the rising unemployment rates led the workforce into short-term contracts or to the on-demand market known as the gig economy. Together with the enhancement in global software development, the organizations found a direction to restore their activities. However, when organizations are immersed in fast-paced environments, selecting skilled professionals is difficult and risky, especially with a lack of qualified professionals. This article identifies the criteria for hiring professionals in the GSD or GE context and proposes a novel approach to clustering them. To do so, we collected the criteria from a broad subject through a systematic literature review, then applied natural language processing with the SBERT algorithm to get the sentence embeddings. Further, we cluster the criteria by applying the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> -means algorithm. After that, we innovatively and responsively grouped the clusters formed by repeating the SBERT and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> -means algorithms and created its mind map. Our findings disclosed 319 criteria and 6 cluster groups comprising a mind map hierarchical structure. Consequently, these outcomes have pedagogical implications to assist specialists from education institutions in designing new course domains. Such as, it can be helpful to practitioners to assist in hiring professional processes in the GSD or GE context.
Supervised learning and model analysis with compositional data

Supervised learning, such as regression and classification, is an essential tool for analyzing modern high-throughput sequencing data, for example in microbiome research. However, due to the compositionality and sparsity, existing techniques are often inadequate. Either they rely on extensions of the linear log-contrast model (which adjust for compositionality but cannot account for complex signals or sparsity) or they are based on black-box machine learning methods (which may capture useful signals, but lack interpretability due to the compositionality). We propose KernelBiome, a kernel-based nonparametric regression and classification framework for compositional data. It is tailored to sparse compositional data and is able to incorporate prior knowledge, such as phylogenetic structure. KernelBiome captures complex signals, including in the zero-structure, while automatically adapting model complexity. We demonstrate on par or improved predictive performance compared with state-of-the-art machine learning methods on 33 publicly available microbiome datasets. Additionally, our framework provides two key advantages: (i) We propose two novel quantities to interpret contributions of individual components and prove that they consistently estimate average perturbation effects of the conditional mean, extending the interpretability of linear log-contrast coefficients to nonparametric models. (ii) We show that the connection between kernels and distances aids interpretability and provides a data-driven embedding that can augment further analysis. KernelBiome is available as an open-source Python package on PyPI and at https://github.com/shimenghuang/KernelBiome.
Event-Based Control in Industry Practice: Paving the Way Toward Resource-Efficient Industrial Internet of Things

Event-based control represents a paradigm shift in the development of theory and practice of digital control systems. Due to the integration of continuous-time dynamics with digital computing, the event-based control frameworks are aligned with the idea of cyber-physical systems (CPSs) and become natural strategies for the development of resource-efficient industrial Internet-of-Things (IIoT). This article summarizes fundamental concepts with a discussion of recent advancements in the use of event-based paradigms from a broad technical perspective. Finally, we analyze the most recent publications in the relevant area and highlight open problems together with future research trends.
A Neutrosophic Model for Identifying and Analyzing the Effect of Relational Leadership on Information Security Policy Compliance: A Case Study of the Hotel Industry

Leaders at hotels are keen to learn how to improve staff adherence to their newly implemented information security rules in the wake of a spate of events involving the compromise of sensitive customer data. In this research, we analyze the relationship between workers' compliance intentions and their perceptions of deterrence, and the leadership styles of their bosses. Gender, education, role, tenure based on ethical leadership, and information security policy compliance intention were some of the particular leadership aspects connected to the information security policy that were evaluated in our research. The overall relevance of the standards may be calculated using the average method, which is used in decision-making. The suggested novel version of the MULTIMOORA (Multi-objective Optimization by Ratio Analysis Plus Full Multiplicative Form) approach uses a single-valued neutrosophic set to handle directly with the uncertainty of the starting point. Developing a decision-support system that takes into account the new conceptual composite framework we offer for selecting criteria, alternatives, and other aspects of leadership and information security policy in hotels is a feasible next step.
How to Provide Feedback? The Role of Robot’s Language and Feedback Framework

AbstractAbstractApproximately half of the world's population are bilingual or multilingual. The foreign language effect has been a part of the academic study of people's decision-making. The Computers are Social Actors (CASA) paradigm posited that people will respond differently when the robot used different social cues. The robot's language might be an important social cue that makes people have different behavior and experience in the interaction. A limited amount of work has examined the effect of the robot's language. Thus, this study investigated the effects of the robot's language (native, foreign) and feedback framework (positive, neutral, negative) on users' interaction with robots in cognitive tasks. This study further used fNIRS to investigate the effects of these factors on users' brain activations. The results indicated that: (i) participants had marginally significantly higher performance, and felt significantly higher social presence when the robot used a foreign language; (ii) participants had significantly lower performance when the robot used a neutral feedback framework; (iii) participants had worse experience when the robot used a negative feedback framework; (iv) the use of a foreign language could reduce the effects of the robot's feedback framework on participants' performance and brain activations. These findings enrich the research on the foreign language effect, CASA paradigm and the feedback intervention. The findings also have implications for the design and development of robots and conversational agents. Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis research was supported by the National Natural Science Foundation of China (No. 71942005) and the Natural Science Foundation of Fujian Province, China (No. 2022J05018).Notes on contributorsHanjing HuangHanjing Huang is an associate professor in the School of Economics and Management, Fuzhou University. She received her Ph.D. in Management Science and Engineering from Tsinghua University. Her research interests include human factors engineering, human–robot interaction, cross-cultural research, design for older people.Pei-Luen Patrick RauPei-Luen Patrick Rau is a professor in the Department of Industrial Engineering, Tsinghua University. He received his Ph.D. in Industrial Engineering from Purdue University. His research areas include human factors engineering, human–computer interaction, cross-cultural design, design for older people, human–robot interaction, and service design and evaluation.Correction StatementThis article has been republished with minor changes. These changes do not impact the academic content of the article.
Uncertainty relations for metric adjusted skew information and Cauchy–Schwarz inequality

Skew information is a pivotal concept in quantum information, quantum measurement, and quantum metrology. Further studies have lead to the uncertainty relations grounded in metric-adjusted skew information. In this work, we present an in-depth investigation using the methodologies of sampling coordinates of observables and convex functions to refine the uncertainty relations in both the product form of two observables and summation form of multiple observables.
Creating an Educational Framework for Project Managers at a Software Company: A Sample Approach

Digital innovations and new technologies are transforming our lives, forcing all organisations, especially software engineering companies, to change their business processes.This rapid innovation and technology advancement positively affects project managers' and software engineers' learning and development, encouraging a new corporate, educational approach.In this study, the authors recognised how to keep up with this challenge and ensure the continuous improvement of employees' competencies, giving the company incredible opportunities to increase its performance and efficiency.The authors of this paper follow the research questions of improving project management education and developing digital skills needed for a sustainable and competitive business environment using e-learning platforms and digital communication channels.This paper presents an approach for designing and implementing a corporate, educational system that trains project managers and software engineers to collect and share acquired knowledge on client projects.Also, this system should reduce the onboarding of newly employed engineers to the company and project managers to new positions.
An infinite family of 0-APN monomials with two parameters

Abstract We consider an infinite family of exponents e ( l , k ) with two parameters, l and k , and derive sufficient conditions for e ( l , k ) to be 0-APN over $${\mathbb F}_{2^n}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>F</mml:mi> <mml:msup> <mml:mn>2</mml:mn> <mml:mi>n</mml:mi> </mml:msup> </mml:msub> </mml:math> . These conditions allow us to generate, for each choice of l and k , an infinite list of dimensions n where $$x^{e(l,k)}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mi>x</mml:mi> <mml:mrow> <mml:mi>e</mml:mi> <mml:mo>(</mml:mo> <mml:mi>l</mml:mi> <mml:mo>,</mml:mo> <mml:mi>k</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:msup> </mml:math> is 0-APN much more efficiently than in general. We observe that the Gold and Inverse exponents, as well as the inverses of the Gold exponents can be expressed in the form e ( l , k ) for suitable l and k . We characterize all cases in which e ( l , k ) can be cyclotomic equivalent to a representative from the Gold, Kasami, Welch, Niho, and Inverse families of exponents. We characterize when e ( l , k ) can lie in the same cyclotomic coset as the Dobbertin exponent (without considering inverses) and provide computational data showing that the Dobbertin inverse is never equivalent to e ( l , k ). We computationally test the APN-ness of e ( l , k ) for small values of l and k over $${\mathbb F}_{2^n}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>F</mml:mi> <mml:msup> <mml:mn>2</mml:mn> <mml:mi>n</mml:mi> </mml:msup> </mml:msub> </mml:math> for $$n \le 100$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>n</mml:mi> <mml:mo>≤</mml:mo> <mml:mn>100</mml:mn> </mml:mrow> </mml:math> , and sketch the limits to which such tests can be performed using currently available technology. We conclude that there are no APN monomials among the tested functions, outside of the known classes.
Spelling-to-sound translation for English disyllables: Use of long and short vowels before single medial consonants.

The English writing system is often seen as having rules that govern the choice between alternative pronunciations of letters but as having many exceptions to the rules. One postulated rule, the V̄|CV rule, is that a vowel is pronounced as long rather than short when it is followed by a single consonant letter plus a vowel letter. We find, in an analysis of English disyllabic words, that exceptions to the V̄|CV rule are not randomly scattered throughout the vocabulary. The use of long versus short vowels is systematically influenced by the identity of the vowel letter itself, the characteristics of the following consonant, and the identity of the word ending. In four studies with a total of 283 participants, we asked university students to pronounce disyllabic nonwords with medial vowel-consonant-vowel sequences and choose the better pronunciation of the first vowel, long or short. Participants were generally sensitive to the effects found in the vocabulary. However, participants used fewer long vowels than expected on the basis of the vocabulary statistics calculated for disyllabic words. We consider possible reasons for this difference and implications for statistical-learning views of reading. Given that the V̄|CV rule is sometimes taught as a part of phonics programs, we also consider implications for reading instruction. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Distribution of a bipartite entanglement in a mixed spin-(1/2,1) Heisenberg tetramer

The distribution of bipartite entanglement in a mixed spin-(1/2,1) Heisenberg tetramer composed from two spin-1/2 and two spin-1 entities is investigated in detail in presence of an external magnetic field. Four different negativities measuring a strength of bipartite entanglement are analyzed at zero and non-zero temperatures. Derived rigorous analytic results and respective numerical results are discussed with the particular emphasis laid on the significance of a strength of the pair spin-spin interactions and spin diversity in the entanglement description. Based on both aforementioned driving forces the regions of parametric space, where the bipartite entanglement can exist solely for one type of spin pair or all four spin pairs, were identified.