Reviewerly/exHarmony huggingface dataset:
Analysis of the Dissemination Characteristics of Papers on <scp>WeChat</scp> Official Accounts of Chinese Academic Journals

ABSTRACT New media platforms have enhanced the efficiency and diversity of information dissemination, providing new possibilities for the dissemination and promotion of academic papers. Currently, a large number of Chinese academic journals from different disciplines have established WeChat official accounts to promote their papers. This study examines WeChat official accounts from three disciplines: social sciences, natural sciences, and medicine. We analyze the existing paper promotion methods employed by these academic journal official accounts from four dimensions: content presentation format, number of papers promoted in a single post, interactive forms, and publishing time. The findings reveal that the current promotion methods for academic papers on WeChat official accounts are relatively limited, with low utilization of multimedia content. Therefore, there is a need for further improvement in new media promotion for academic papers.
Using Playful Metaphors to Conceptualize Practical Use of <scp>ChatGPT</scp>: An Autoethnography

ABSTRACT In this short paper, we employ a month‐long autoethnography to investigate the utilization of ChatGPT through metaphor analysis. We conceptualize three metaphors—unreliable narrator, court jester, and sounding board—that possess the most explanatory capabilities in describing what ChatGPT is, when it can be used, and how it can be helpful. We posit that grounding the use of ChatGPT in metaphors could facilitate discussions and streamline the intricate mechanism of Large Language Models (LLMs). Our study indicates that by proffering playful metaphors as substitutes to apocalyptic and arcane ones, we can enhance the accessibility and comprehensibility of ChatGPT for non‐experts and policymakers, thereby potentially contributing to more informed and productive dialogues about the role and potential of LLMs in everyday life.
Document Conflation of a Large Scholarly Full‐text Dataset

ABSTRACT The availability of large scholarly full‐text datasets with in‐text citations annotated opens the opportunity to investigate how articles have been cited in scientific literature at scale. However, duplicate documents may exist in a dataset, and these duplicates may impact downstream analysis such as calculating citation counts. Document conflation is the task of identifying documents that are nearly identical to each other. This study evaluates document conflation in the Semantic Scholar Open Research Corpus (S2ORC), a dataset containing over 12 million scholarly articles. The evaluation was based on 6,099,232 full‐text S2ORC documents with PubMed IDs (PMIDs) or PubMed Central IDs (PMCIDs). Our findings showed that a portion of S2ORC might contain duplicates. Of the 6,099,232 full‐text documents, 1,280,196 (20.99%) had the same PMIDs or PMCIDs as at least one other document. Pairwise comparisons of their full text found that at least 9.44% of the documents in S2ORC had duplicates.
The Zonal Theory of Musical Time and the Trans-Disciplinary Approach to the Study of Musical Phenomena

The study of the factors of uncertainty in the system of musical thought has become a subject of fixed attention on the part of music researchers, partially being in advance of certain analogous results in the spheres of the exact sciences. The synergetic approach, stipulated by processes of development of contemporary science, is determined by the substantiation of its application towards their studies, not only in the natural sciences, but also in the humanitarian disciplines and becomes an important instrument of cognition and interpretation of the semantic structures of all the temporal arts, including the art of music. the article examines a number of endeavors to study the probabilistic-statistic natural laws of music presented in Ludwik Bielawski’s book The Zonal Theory of Time and its Meanings for Musical Anthropology: The Endeavor of Definition of the Place and the Role in the History of Theoretic Musicology (Krakow, 1976), in which the natural laws of the functioning of musical levels on various levels and in the various forms of its manifestation. The authors of the article give attention to the use in scholarly research works devoted to this problem range of music computer technologies which has served as a basis for the possibility of creating new theoretic and experimental-practical means of studying music, including the factors of indeterminacy in music applied to the sphere of musical education researched with the means of music computer technologies. In this connection, the article elucidates a number of new educational directions and programs developed by the members of the learning and teaching laboratory “Music Computer Technologies” of the Herzen State Pedagogical University of Russia called to provide the preparation of specialists who possessed various forms and means of the transdisciplinary approach to studies of musical phenomena and processes.
Creative Thinking and Creative Technologies as a Modern Component of Instruction of Music Professions

The article is focused on elucidating the necessity of implementation of methods of development of creative thinking into the system of music education. The predominance of logical methods of analysis in the process of music education negates heuristic thinking and transfers the accentuation from the creatively active production of new ideas to mere reproduction of already existing and known models of professional behavior. According to the theory of psychologist Joy Paul Guilford, who initially brought in the term “creativity” into scholarly use, its didactic directedness is initially highlighted, particularly, the formation of its basis the capabilities of solving problems swiftly and non-standardly, the complexity of which is continuously growing in the speedily changing modern society. The presence of this skill within the framework of creative professions is especially crucial, because in art the process of evolution is in many ways connected with the violation of the existent norms. The success of conservatory graduates, who work, among other places, in concert organizations, may be guaranteed not only by their performance opportunities of technical and interpretation varieties, but also by the search for new formats of presenting their music to the audience. This is demonstrated in the article on the example of collaborative artistic projects. While expounding the thesis of a goal-oriented upbringing of creative thinking, the authors propose the structure of a special educational course within the frameworks of which on the basis of theory and practical tasks this skill may be developed. The training part of the course presumes the use of various directions of methods for developing creative skills elaborated by various scholars, such as, for instance, Sigmund Freud’s method of free associations, Tony Buzan’s mindmapping, Mark Levy’s freewriting, etc. The summarizing conclusion of the article is that the formation of the skill of creative thinking is the key to successful personal and professional growth of specialists in the sphere of the art of music.
The Possibilities and Prospects for the Use of Music Computer Technologies in Therapy Dealing with Psychogenic Disorders

The beneficial effect of music on the human body has been known since ancient times and has been actively used in the methods of music therapy. The article analyzes in the manner of a survey the advantages, possibilities and limitations of the traditional methods of music therapy, wherein the patient is presented with a set of musical compositions empirically selected. A radically different and innovative method of music therapy is based on musical or music-like stimulation that is generated by a computer on the basis of feedback signals from the patient’s own physiological characteristic features. The advantages and prospects of this innovative method are examined here and an evaluation is given of the effectiveness of computer-aided transformations of the patient’s brain biopotentials into musical or music-like effects, which are used in the adaptive neuro-stimulation technology developed by the authors with feedback from the current electroencephalogram (EEG) parameters. By means of the examples from our own research with the use of EEG-guided adaptive neurostimulation, we have outlined the prospects for the development of music computer technologies in the treatment of psychogenic disorders and the cognitive rehabilitation of human beings.
Technologies and Music: The Department of Computerization of Musical Activities at the Novosibirsk Conservatory

A new wave of historical development, which defined itself in the second half of the previous century with the advent of computer technology, has brought a number of experimental initiatives to the art of music, education and scholarship. Some of them remained in the history of music as bright artistic projects that have not received any continuation subsequently. Others have become firmly established in the daily practice of performing musicians, teachers, and researchers. One of the largest regional methodological centers for the study of computer technologies in the musical sphere has been the Novosibirsk Conservatory, which opened first a computer laboratory, and then the first department of computerization of musical activities in Russia. The issues of the history of the department at the Novosibirsk Conservatory have been insufficiently brought up in musicological literature. In some sources, the chronology of the history of the department is limited merely to the phenomena of the turn of the centuries. The aim of this article is to actualize the data on the Department of Computerization. The main directions of its activities are outlined, and information is provided about the people who have influenced the formation of this new research center for music scholarship. The role is determined of cooperation between different conservatory departments in the formation of the concept of the work of the Department of Computerization and the search for the vectors of the future development of technological processes.
Praktek Pendekatan Self Regulation Learning pada Peserta Latsar CPNS BPSDM Provinsi Bali Tahun 2021

&#x0D; &#x0D; &#x0D; &#x0D; The purpose of this study is to describe the practice of the Self Regulation Learning (SRL) approach in forming latsar participants to become independent learners and to describe an increase in learning outcomes and motivation after SLR was practiced in the basic training for civil servant candidates (Latsar CPNS) at BPSDM Bali Province in 2021. This study involved 40 participants class XVI In 2021 at BPSDM Bali Province with 30 participants of teacher and 10 non-teacher at the Bali Provincial Government. The approach used in this study is a mixed method with an embedded experimental design. Data analysis techniques with qualitative analysis and quantitative descriptive analysis. The qualitative analysis will describe the process of implementing the SLR practice. While the quantitative analysis will analyze the increase in learning outcomes and achievement of learning motivation after the practice of SRL. The results showed that the practice was implemented in the four SLR approaches, namely: linking goal-oriented learning; facilitate learning and thinking strategies; diversification of learning opportunities that enable hope of success; and socialize learning in the caring community that is created. These four practices have been described through 15 core practices of evidence-based learning. The second result is that there is an increase in learning outcomes after the implementation of the self-regulation learning approach, namely from the initial score of 70.25, it increases to the final score of 80.69. As for the overall learning motivation, it reached an average of 4,295 with a high category after implementing self-regulation learning in the Latsar CPNS Class XVI latsar at BPSDM Bali Province in 2021. The results of this study are expected to be practiced in learning because it has been proven to have a direct impact on increasing the motivation and learning outcomes of training participants&#x0D; &#x0D; &#x0D; &#x0D;
The Management of Facilities and Infrastructures in Educational Institution

Educational institutions own equipment and resources called facilities and infrastructure that facilitate the delivery of educational services. Infrastructure management is required for successful infrastructure. Inventory is one of the key components of infrastructure management. It involves several steps, including management, implementation, organization, recording, and registration of inventory items. The study employs a qualitative paradigm and literary analysis methods. Primary books and scholarly publications comprising 40 references are used as research sources. The findings indicated that maintaining infrastructure quality and quantity is a goal of the invention focus. Activities involving inventory are fundamentally a continuous process. Additionally, the inventory of educational institutions provides data on the number, quality, wealth, planning, acquisition, and removal of facilities and infrastructure, as well as data on data accountability. Activities related to inventory include tracking purchases and creating reports.
Australia’s geoscience paradox threatens its prosperity and sustainability

Unprecedented climatic, environmental, energy, and resource crises threaten our world due to a growing, unsustainable human footprint on our planet. But while Australia awaits national strategies to address climate change amidst the COVID-induced recession, deep staffing cuts and closures of tertiary geoscience programmes across the country compromise our collective ability to respond to these challenges.
Deep Learning Isovist

Understanding the qualitative aspect of space is essential in architectural design.However, the development of computational design tools has lacked features to comprehend architectural quality that involves perceptual and phenomenological aspects of space.The advancement in machine learning opens up a new opportunity to understand spatial qualities as a data-driven approach and utilize the gained information to infer or derive the qualitative aspect of architectural space.This paper presents an experimental unsupervised encoding framework to learn the qualitative features of architectural space by using isovist and deep learning techniques.It combines stochastic isovist sampling with Variational Autoencoder (VAE) model and clustering method to learn and extract spatial patterns from thousands of floor plan data.The developed framework will enable the encoding of architectural spatial qualities into quantifiable features to improve the computability of spatial qualities in architectural design.
User Drafts for the Design of an mHealth Application for Equestrians

A study was conducted to find out user ideas for the design and workflow of an mHealth application supporting triage of horses by equestrians. Results focus on information input elements and also include some requirements for information.
Preserving Decentralized EHR-s Integrity

A blockchain and decentralized storage technology-based architecture is proposed to support the integrity of Electronic Health Records (EHRs).
Autopsy Discoveries in Severe Malaria

Severe malaria is a disease caused by Plasmodium falciparum as the main cause of death in malaria. As autopsy examinations on malaria are rare in Indonesia, we report a nineteen-year-old male from Dumai, Indonesia, who died of severe malaria on November 10th 2018, at Dumai Regional General Hospital of Riau Province. The diagnosis was concluded from autopsy, histopathology and toxicology. This case report aimed to explain autopsy findings in severe malaria. As the result of external examination, we found some bruises on the right earlobe, lip mucosa and lower leg; excoriations on the neck, both arms and right lower leg; excoriations on the right lower leg and blood infiltration in the connective tissue on the right intercostal space. The autopsy and histopathology examination showed signs of congestion and hemozoin pigment in the brain, small intestine, liver, lung, heart, kidney, stomach and spleen. On toxicology examination, there was no narcotic substance found. Based on autopsy findings, histopathology and toxicological findings, we conclude that the cause of death, in this case, was severe malaria. Blunt violence to the ears, lips, neck, arms, and legs did not significantly cause death.
Design Factors in Evaluating and Formulating IT Governance Systems in Public Organizations

The application of information technology (IT) by central and regional governments to public services is intended to efficiently and effectively improve performance and public services. However, many studies have shown the ineffective application of IT. In Gorontalo province, this can be seen in the e-readiness value of Gorontalo province as a prerequisite for successful IT implementation, which is still at 58.15 points, which means that it is at a moderate level of readiness. This shows that implementing IT governance in the local government of Gorontalo province is still not optimal in terms of performance or public services. This study aims to identify the design factors that need to be considered when implementing IT Governance to achieve better public service performance. This study uses a quantitative approach based on a survey method. The results showed six models at Level 3: BAI06, BAI07, DSS01, DSS03, DSS04, and DSS05. In addition, four models were at level 4: APO12, APO13, BAI10, and DSS02. Levels 3 and 4 show that the IT governance capability of the Gorontalo provincial government in each model is not yet optimal. This study recommends that the Gorontalo provincial government evaluate and formulate an effective IT Governance system by focusing on each model's IT Governance design factors to improve public service performance.&#x0D;
The Effectiveness of Using Comic Strips Toward Students' Reading Comprehension on Narrative Text

The objective of this study was to examine the potential impact of Comic Strips on the reading comprehension skills of eighth-grade students at Mulia Insani Junior High School in Loa, Bandung-West Java. This study employed a pre-experimental research design, specifically utilizing a pre-test and post-test design. The sample methodology employed in this study was purposive sampling. The research was conducted on the VIII B class at Mulia Insani Junior High School during the academic year 2022/2023. The data was collected by the administration of a reading exam in a multiple-choice format. Next, the obtained data was subjected to analysis using the paired sample t-test. There were a total of four meetings, with two meetings dedicated to therapy and the remaining two meetings allocated for pretest and posttest purposes. The findings of the study indicate a notable impact of using comic strips as a post-treatment intervention, as seen by the observed increase in post-test scores. According to the findings, the average score of the posttest was 87.41, whereas the average score of the pretest was 39.67. Additionally, according to the results of the paired sample t-test, the two-tailed significance value (sig) was found to be 0.000, which is below the conventional threshold of 0.05. The study of the paired sample t-test yielded statistically significant results. Hence, this study provides evidence that the utilization of comic strips has a notable impact on the reading comprehension of students, particularly in relation to narrative material. The research was conducted in the VIII B class at Mulia Insani Islamic Junior High School in Loa, Bandung-West Java.
Hyperparameter Optimization of CNN Classifier for Music Genre Classification

Playing music through a digital platform that has a large database of songs requires automated classification of music genres, highlighting the need to develop a model for music genre classification that is more efficient and accurate. This study evaluated the hyperparameters in the music genre classification process using CNN in the GTZAN dataset with 30-second duration data optimized using MFCC feature extraction. The model that is formed with a time of 3 (three) seconds classifies music genres in the first 3 seconds of music. This model has a high potential for error because the first 3 seconds of initial music are varied and cannot be used as a benchmark in determining music genres. This study performed hyperparameters on batch size, epoch, and split data set variables with various scenarios. The highest precision result was obtained at 72% with a data split of 85%:15%, 32 batch sizes, and 500 epochs.
Scaling Model Checking for Neural Network Analysis via State-Space Reduction and Input Segmentation

Owing to their remarkable learning capabilities and performance in real-world applica- tions, the use of machine learning systems based on Deep Neural Networks (DNNs) has been continuously increasing. However, various case studies and empirical findings in the literature suggest that slight variations to DNN inputs can lead to erroneous and undesir- able DNN behavior. This has led to considerable interest in their formal analysis, aiming to provide guarantees regarding a given DNN’s behavior. Existing frameworks provide robust- ness and/or safety guarantees for the trained DNNs, using satisfiability solving and linear programming. We proposed FANNet, the first model checking-based framework for analyz- ing a broader range of DNN properties. However, the state-space explosion associated with model checking entails a scalability problem, making the FANNet applicable only to small DNNs. This work develops state-space reduction and input segmentation approaches, to improve the scalability and timing efficiency of formal DNN analysis. Compared to the state-of-the-art FANNet, this enables our new model checking-based framework to reduce the verification’s timing overhead by a factor of up to 8000, making the framework ap- plicable to DNNs even with approximately 80 times more network parameters. This in turn allows the analysis of DNN safety properties using the new framework, in addition to all the DNN properties already included with FANNet. The framework is shown to be efficiently able to analyze properties of DNNs trained on healthcare datasets as well as the well-acknowledged ACAS Xu networks.
Prediction and Control of Stochastic Agents Using Formal Methods

In this paper, we propose an innovative approach that incorporates formal verification methods into the training process of stochastic Reinforcement Learning (RL) agents. Our method allows for the analysis and improvement of the learning process of these agents. Specifically, we demonstrate the capability to evaluate RL policies (prediction) and opti- mize them (control) using different model checkers. The integration of formal verification tools with stochastic RL agents strengthens the applicability and potential of our approach, paving the way for more robust and reliable learning systems.