Reviewerly/exHarmony huggingface dataset:
The Impacts of Changes in Journal Data Policies: A Cross‐disciplinary Survey

ABSTRACT Journal policies play a crucial role in facilitating the sharing of research data. This study examined the Data Sharing Policies (DSP) and Supplemental Materials Policies (SMP) of ten journals from 22 disciplines in 2023, comparing the findings to those of previous surveys conducted in 2014 and 2019. Among the 220 journals analyzed, 91.4% implemented DSP, whereas 95.0% adopted SMP. Compared with the surveys conducted in 2014 and 2019, a greater number of journals exhibited more stringent requirements for DSP, particularly in the fields of Engineering, Economics &amp; Business, and Computer Science. Although the percentage of journals that accepted supplemental materials increased, only 12.7% strongly required their submission. Furthermore, this study compared the changes in Journal Impact Factors (JIF) between journals that adopted DSP (either requiring or recommending it) and those that did not have DSP in 2019. These findings suggest that DSP has a significant effect on JIF in the Economics &amp; Business and Psychiatry/Psychology fields.
Building lexicon-based sentiment analysis model for low-resource languages

Natural Language Processing (NLP) has transformed machine translation, sentiment analysis, information retrieval, and conversation systems. NLP applications rely on complete linguistic resources, which might be difficult for low-resource languages. NLP solutions for every language require a language-specific dataset. Dataset in a language is essential for NLP solution creation. Over 7000 languages are spoken worldwide. Only around 20 languages have text corpora for NLP applications. English has the most datasets, then Chinese and Spanish. Japanese has several Western European language datasets. For an accurate NLP system, most Asian and African languages lack training datasets. To address this challenge, we propose a methodology for building a lexicon-based sentiment analysis model for languages with limited resources. The Hausa language was used as training and evaluation language. The methodology combines lexicon creation; augmentation, annotation, and fine-tuning model, and has been tested on a corpus of Hausa tweets achieving an accuracy of 98 %. The results suggest that our proposed model is a promising tool for sentiment analysis in a variety of applications, such as social media monitoring, customer service, and market research. Our methodology can be used for any low-resource language. The outline of the work done in this paper can be shown as follows:•We propose a methodology for building a lexicon-based sentiment analysis model for languages with limited resources, using the Hausa language as a case study.•The methodology combines lexicon creation, augmentation, annotation, and fine-tuning model, and achieves an accuracy of 98 % on a corpus of Hausa tweets.•The results suggest that the proposed model is a promising tool for sentiment analysis in a variety of applications for low-resource languages.
Advancing <scp>LIS</scp> in <scp>iSchools</scp>: Building a Coalition To Ensure a Vibrant Future

ABSTRACT The LIS Forward initiative is addressing the urgent question: As LIS evolves within the context of iSchools, how do we best position our research and education programs to lead the field and the future of libraries? The initiative stems from the recognition that the evolution of iSchools presents opportunities and challenges for LIS and that there is great value in iSchools working together on charting directions forward. The growing coalition of iSchools is working to support LIS in taking full advantage of the multidisciplinary knowledge and expertise within iSchools, foster future leaders who will champion LIS within iSchools, and confront the dynamic tensions in research intensive iSchools. This session aims to engage international, professional, and academic stakeholders to guide activities and coalition building that can continue to strengthen LIS in iSchools. A panel will present highlights from a recent position paper to catalyze interactive, facilitated dialogue within the ASIS&amp;T community on critical issues in LIS research and education. Breakout sessions will generate responses and recommendations to advance collaborative planning and strategy of value to LIS academic programs and the profession.
Automated Metadata Enhancement for Physical Sample Record Aggregation in the <scp>iSamples</scp> Project

ABSTRACT Large amounts of samples have been collected and stored by different institutions and collections across the world. However, even the most carefully curated collections can appear incomplete when aggregated. To solve this problem and support the increasing multidisciplinary science conducted on these samples, we propose a method to support the FAIRness of the aggregation by augmenting the metadata of source records. Using a pipeline that is a combination of rule‐based and machine learning‐based procedures, we predict the missing values of the metadata fields of 4,388,514 samples. We use these inferred fields in our user interface to improve the reusability.
I am neither Clark Kent nor Superman: A Case Study of Experience in Virtual Activity in the Metaverse

The metaverse has gained attention as an important aspect of virtual word, but little is known about user experiences. This study aims to determine university students' experiences, thoughts, and feelings regarding the metaverse event experience from a virtual reality perspective. A qualitative research method including in-depth interview was utilized to collect data from 34 university students, using purposive sampling method. The interviews were applied after the participants experienced the Roller Coaster metaverse game, which lasted for about 5 minutes. In the qualitative research conducted to explore the participants' experiences with the Roller Coaster metaverse activity, six main themes emerged: Superman, Pleasure Journey, Fearless Coward, Flow, Emotion Zone, and Fear of Missing Out (FoMO). As a result, it was concluded that the students thoroughly enjoyed this experience. Moreover, they couldn't believe how quickly time passed, that this experience was a step toward overcoming their fears. They also added that the experience transitioned them to different worlds and emotions. Additionally, they had FoMO when someone else had this experience before them. Finally, it was revealed that they experienced the feeling of freedom by removing all real-world restrictions. This study might enable to the advancement of virtual reality environments, Metaverse, and leisure-based activities in particular and may reveal many potential research opportunities.
The <scp>Spatial‐Temporal</scp> Trajectories of the Poets and the Sociocultural Environment of the Age

ABSTRACT This research in progress presents a deep learning‐based approach to identifying named entities, including geographical locations and poetic imagery in ancient Chinese poetry. By leveraging association rule mining, this study establishes a connection between historical events, spatial‐temporal trajectories of poets, and sociocultural phenomena of the age. From the perspective of digital humanities, this study hopes to be able to provide new evidence for socioeconomic status, cultural openness, or historical events at different ages and to picture a better view of the development of classical Chinese.
From Digitization and Images to Text and Content: Transkribus as a Case Study

ABSTRACT This poster explores the potential of using technological tools, specifically the Transkribus platform, for the transcription of Hebrew manuscripts. The digitization of historical resources has made them accessible, but the textual content of the scanned images remains inaccessible. Transkribus, an AI‐powered platform, offers tools for text recognition, transcription, and search of historical documents. The poster discusses the process of automatic text recognition (ATR) and the challenges it faces, particularly in handling handwritten texts and Hebrew letters. It provides an overview of the Transkribus platform, its functionalities, and the training process for creating transcription models. The author presents a case study of transcribing a 15th‐century Sephardic semi‐cursive Hebrew manuscript using the Transkribus platform and evaluates the performance of different models. The poster concludes by discussing the implications and possibilities of using Transkribus for automatic transcription of historical Hebrew manuscripts. While the results show promising improvements in accuracy, further challenges and solutions are also discussed. Overall, Transkribus offers significant potential for the study and transcription of Hebrew manuscripts, revolutionizing the field of Jewish studies and historical research.
Conceptualizing Data Behavior: Bridging Data‐centric and User‐centric Approaches

ABSTRACT With the development of technologies in big data and AI, data has become more and more central to users for various tasks in different contexts. Yet the concept of data behavior, an emerging concept that captures the actions and interactions of individuals with data in various contexts and situations is not explicitly defined and framed. Data behavior focuses on the observable actions and reactions of users when they encounter, discover, seek, use, or create data for individual or collaborative tasks, while data practice encompasses the entire spectrum of how people work with data, from creating and managing to sharing and reusing data, as well as the intentional and strategic decisions and actions involved in these processes. This panel proposes a conversation and discussion about the concepts of data practice and data behavior by drawing on literature in data practice, data curation, and information behavior. This panel aims to discuss, compare, and bridge data‐centric and user‐centric approaches to conceptualizing data behavior. It will also present some examples of data behavior research in different domains and scenarios. The panel will highlight the challenges and opportunities of data behavior research for information science and practice.
Transfer Learning Framework for Semantic Segmentation of High-Resolution UAV-based images in Urban Area

Transfer Learning Framework for Semantic Segmentation of High-Resolution UAV-based images in Urban Area
Personalization of a tourism recommender system based on users similarity and the use of deep belief network

Personalization of a tourism recommender system based on users similarity and the use of deep belief network
The Composer-Philosopher as a Key Figure of Musical Aesthetics (by the Example of Tchaikovsky’s Spiritual Endeavor)

The focus of the authors’ scholarly interest is turned to composers-philosophers and philosophers-composers as the crucial figures of musical aesthetics realized in the space of phenomenology. The attention bestowed on such artists makes it possible to approach the understanding of music as an endeavor of transcending, which forms by itself the highest value. Neglecting the latter in the process of mastery of the art of music leads people to “one-dimensionality,” making them admittedly on the decline. When immersing in the inner world of the composer-philosopher or the philosopher-composer, the recipient, essentially, studies the depths of his or her own self, actualizing the dialogue of the artist and the valuator. The criteria for the genuine character of such a dialogue is formed particularly by the process of transcending, under the sign of which music appears in the guise of a meta-philosophical genre. When mastering the dialectics of being realized by musical means of expression, the human being acquires a unity of essence and existence. The authors turn to the personality of Piotr Ilyich Tchaikovsky, considering it appropriate to examine him as a composer-philosopher. Constructing a system of argumentation, they turn their attention towards the great musician’s reading circle, his cultural preferences and antipathies, his students, who manifested themselves in the sphere of philosophical knowledge and in the sphere of the art of music, as well as the musical compositions which have reflected the master’s philosophical ideas. In conclusion, it is emphasized that the study of the musical legacy of the composers-philosophers and the philosophers-composers would help overcome the discontinuity between life and art, when music, remaining aside from the everyday realities experienced by the human being, turn out to be incapable of inspiring him to spiritual wakefulness. As a result, its mission is narrowed down to adornment of everyday life, which inevitably leads to the primitivization of music itself and of the individuals consuming it. Turning to the experience of being of the composers-philosophers would make it possible to overcome this vicious circle.
Sequence prediction with different dimensions based on two novel deep echo state network models

The echo state network (ESN) is a typical reservoir computation model, which was first proposed by Jaeger et al. It was widely used in various fields and achieved excellent results for a long time, especially in time series prediction. In recent years, there are few improvements to the ESN structure, and the more famous is the deep echo state network (DESN) model. However, a DESN will cause the loss of input data. How to effectively optimize the structure of ESN and how to scientifically add input data to deep echo are urgent problems to be solved. In this paper, we propose multi-reservoir ESN models based on how the input data participate in the system. Then, we use complex nonlinear chaotic systems with different dimensions to test our model. Finally, we compare it with the traditional model and the recently proposed model, and then find that our models have better predictive performance.
Data Waltz

This paper explores the impacts of the Internet of Things (IoT) on the fi eld of interactive architecture and the ways this novel technology enables realignments toward inclusive and critical practices in the design of computational systems across different scales.Specifi cally, it examines how the integration of IoT in the design of architectural surfaces can encourage interaction between local and remote users and increase accessibility amongst contributors.Beginning with a survey of media facades and the superimposition of architectural surfaces with projected images, the paper outlines a historical relationship between buildings and the public realm through advancements in technology.The paper next reveals ways in which IoT can transform the fi eld of interactive architecture through the documentation and analysis of a project that stages an encounter between local and remote Wikipedia contributors.The installation creates a feedback loop for engaging Wikipedia in real-time, allowing visitors to follow and produce content from their interactions with the gallery's physical environment.Light, sound, and fabric contextualize the direction and volume of real-time user-generated event data in relation to the gallery's location, creating an interface that allows participants to dance with dynamic bodies of knowledge.By incorporating IoT with the fi eld of interactive architecture, this project creates a framework for designing computational systems responsive to multiple scales and expanding our understanding of computational publics. 1 1 The installation connects local and remote users through their real-time interactions with Wikipedia.
Factors of professional socialization of students (on the example of Altai State University)

Currently, Russian society is faced with a number of political, social and economic challenges and difficulties, which in one way or another has changed all spheres of people's life. Students, student socialization and self-determination аre no exception. The formation of new vectors of the development of modern education and the exit from the Bologna process changed the habitual life of the student, shifted their professional socialization. As a result, a new image of student is formed, which has a qualitatively different way of developing both general cultural and professional competencies. One of the clearest examples of such changes is the mass secondary employment of students literally from the 1st year of study at the university. Moreover, studying at a university is directly related to the further self-determination of an individual, the search for his own life path, but the crisis realities complicate such a search, as a result, the old motivational components of studying at a university turn out to be ineffective. A graduate of a modern university will have to face contradictions between the demands of the labor market and the market of educational services. It is quite possible that a person cannot get a job in his specialty, but this state of affairs is not considered something new and surprising, therefore, modern professional socialization of a student should work on this aspect. Thus, the young specialist is ready for almost any challenges of the labor market, social reality in general.
Evaluating the Value of Exploratory Tools in Digital Humanities Collections and Scholarly Projects: Discussions from Researchers, Developers, and Users’ Perspectives

ABSTRACT Digital content management systems have enabled cultural heritage institutions and humanities researchers to create interactive, public‐facing, and open‐access scholarly work, including digital libraries, databases, archives, manuscripts, and collections. Exploratory tools have become a widely deployed feature of such digital projects that support in‐depth, creative interaction with digital materials. However, producing and managing a digital project with such tools can be complex, time‐consuming, and expensive, requiring significant financial investment, institutional support, and human capital. This has led to a critical need to evaluate the effectiveness of such embedded exploratory infrastructures across different stages of digital projects. This 90‐minute panel discussion aims to explore the questions of how to evaluate the use and effect of such exploratory infrastructures, from diverse perspectives of researchers, developers, and downstream users. The panelists will draw from case studies to address questions such as: (1) the perceived value and impact of embedded exploratory tools, (2) the involvement of communities and stakeholders in the evaluation process, and when to conduct such evaluations, (3) the methods and approaches to evaluation, and (4) the interpretation of evaluation outcomes. The discussion will also delve into the challenges and opportunities associated with evaluating embedded exploratory tools in digital projects and scholarship.
An Exploration of Restructuring the Statistical Estimation Unit in High School &lt;Probability and Statistics&gt;

This study aimed to improve statistical estimation teaching practices in school mathematics, support the development of textbooks according to the 2022 revised mathematics curriculum, and the implementation of the curriculum in the schools. Apropos this, the directions of restructuring the statistical estimation unit were derived by synthesizing the results of previous studies related to statistical estimation. Based on these, specific restructuring suggestions for the statistical estimation unit are proposed as follows. First, in relation to the meaning of the sample and sampling method, it is necessary to focus on the bias in the sampling process to promote conceptual understanding in terms of sample representativeness and to promote the recognition of sampling variability using technologies. Second, in relation to sampling distribution, it is necessary to construct contents that promote conceptual understanding of sampling distribution and the relationship between sample size and sampling variability using simulation. Third, in relation to the confidence interval, it is necessary to construct contents that promote the recognition of the confidence levels as probabilistic confidence and provide interpretation and evaluation opportunities of estimation results using sampling errors. In addition, some examples from foreign mathematics textbooks, that can be referred to when implementing each restructuring suggestion, are explored and presented.
Surface and Contextual Linguistic Cues in Dialog Act Classification: A Cognitive Science View

What role do linguistic cues on a surface and contextual level have in identifying the intention behind an utterance? Drawing on the wealth of studies and corpora from the computational task of dialog act classification, we studied this question from a cognitive science perspective. We first reviewed the role of linguistic cues in dialog act classification studies that evaluated model performance on three of the most commonly used English dialog act corpora. Findings show that frequency-based, machine learning, and deep learning methods all yield similar performance. Classification accuracies, moreover, generally do not explain which specific cues yield high performance. Using a cognitive science approach, in two analyses, we systematically investigated the role of cues in the surface structure of the utterance and cues of the surrounding context individually and combined. By comparing the explained variance, rather than the prediction accuracy of these cues in a logistic regression model, we found that (1) while surface and contextual linguistic cues can complement each other, surface linguistic cues form the backbone in human dialog act identification, (2) with word frequency statistics being particularly important for the dialog act, and (3) the similar trends across corpora, despite differences in the type of dialog, corpus setup, and dialog act tagset. The importance of surface linguistic cues in dialog act classification sheds light on how both computers and humans take advantage of these cues in speech act recognition.
Inferring Causality Is Preference-Sensitive: We Need a Book of Who as Well as Why

In multiple publications over 3 decades, most recently in The Book of Why, Judea Pearl has led what he regards as the ‘causal revolution’. His central contention is that, prior to it, no discipline had produced a rigorous ‘scientific’ way of making the causal inferences from observational data necessary for policy and decision making. The concentration on the statistical processing of data, outputting frequencies or probabilities, had proceeded without adequately acknowledging that this statistical processing is operating, not only on a particular set of data, but on a set of causal assumptions about that data, often unarticulated and unanalysed. He argues that the arrival of the directed acyclic graph (DAG), a ‘language of causation’ has enabled this fundamental weakness to be remedied. We outline the DAG approach to the extent necessary to make the key point, captured in this paper’s title regarding DAG’s potential contribution to improved decision or policy making.
Review on Image Inpainting using Intelligence Mining Techniques

Objective: Inpainting is a technique for fixing or removing undesired areas of an image. Methods:In present scenario, image plays a vital role in every aspect such as business images, satellite images, and medical images and so on. Results and Conclusion:This paper presents a comprehensive review of past traditional image inpainting methods and the present state-of-the-art deep learning methods and also detailed the strengths and weaknesses of each to provide new insights in the field.
Study of Audience Emotions in Epic Cinema

The purpose of epic films is not only to tell a good story, but also to let the audience have more and deeper feelings while being entertained. The audience's emotions go deeper and deeper in the process of watching the film, from pleasing the eyes to understanding the characters to triggering empathy, which also fits the three parts of Freud's theory of the structure of consciousness, and in fact is the process of the audience's consciousness going deeper and deeper into the film step by step.