Reviewerly/exHarmony huggingface dataset:
A Study on Developing a Chinese Textbook Based on Consumer Demand Surveys: Focusing on the Revision of “Saenaegi Chinese” from “K” University

Understanding the demands of consumers is the foremost element in the textbook development process, and sufficient reflection of consumer demands can lead to successful learning outcomes. In this context, this paper investigated and analyzed the demands of learners and instructors for “Saenaegi Chinese”, a liberal arts Chinese textbook at “K” University, as a preliminary stage for developing a university liberal arts Chinese textbook, and discussed future textbook development and improvement directions based on this analysis.The survey of learner demands showed high satisfaction with the overall content of the textbook, including its topics, practicality, difficulty level, grammar explanation, and practice questions. However, there was a high demand for revisions of certain outdated topics and textbook design, as well as a high demand for supplementary materials such as cultural items and workbooks. In the instructors’ demand survey, instructors also responded positively to the textbook’s topics and content. They recognized the need for revisions on certain topics and the addition of cultural items. However, there was a discrepancy in perception of the learning volume between students and instructors. While many students perceived the learning volume and difficulty level of the current textbook as relatively appropriate, many instructors perceived the vocabulary volume and grammar segment difficulty as inappropriate. In addition, there were differences in demand for supplementary materials, textbook format, and design. While students showed a very high demand for workbooks, textbook format, and design, instructors showed a relatively high demand for PPT materials, and their sensitivity for textbook format and design was not as high as that of the students.
Data Management Plan Tools: Overview and Evaluation

Data Management Plans (DMPs) are crucial for a structured research data management and often a mandatory part of research proposals. DMP tools support the development of DMPs. Among the variety of tools available, it can be difficult for researchers, data stewards and institutions to choose the one that is most appropriate for their specific needs and context. We evaluated 18 DMP tools according to 31 requirement parameters covering aspects relating to basic functions, DMP contents, technical aspects and user friendliness. The highest total evaluation scores were reached by Data Stewardship Wizard (703.5), DMPTool (615.5) and RDMO NFDI4Ing (549.5). The tools evaluated satisfied between 10 % and 87 % of the requirement parameters. 11 tools cover at least half of the parameters. In terms of correlation among the tools, which indicates to which degree their scores in the different requirement parameters are alike, we found the highest correlation for ezDMP and GFBio DMPT. Regarding the relatedness between the tools, 85 % of the DMP tools were positively and 16 % negatively correlated. Accounting for the recent developments in the area of DMP tools, this study provides an up-to-date evaluation that can support tool developers in identifying potential improvements, and hosting institutions to select a tool suited to their specific needs.
Digital Literacy and Digital Competence of Selected Filipino Teachers: Basis for a Post-Pandemic Pedagogy

Objective: The study seeks to provide a thorough description of the teachers' digital literacy (DL) and digital competence (DC) and shine a light on the variables that influence the development of their digital literacies and competence. Method: Comprehensive data collection and analysis from 274 participants were completed. Descriptive and inferential statistics were conducted to accomplish the objectives of this study. Results: It came to light that teachers with less than ten years of experience have higher levels of digital literacy. Pre-service education, having access to ICT resources, and a favorable attitude about using ICT were all strongly associated with DL and DC. The research's essential contribution is its findings affirming the value of DL and DC, which can be utilized to approach new technologies critically and use them as a part of digital pedagogy. Novelty: The critical contribution of the research is the result claiming the positive status of DL and DC, which can be used to approach new tools from a critical pedagogical perspective and apply them as part of digital pedagogy.
Modelling Scientific Processes With the m4i Ontology

We present an approach to document research data in a human and machine readable way by creating JSON-LD metadata files based on the m4i ontology. m4i is based on top level ontologies and reuses concepts of widely accepted ontologies to embed information modelled in m4i in larger contexts like a knowledge graph connecting research data with projects, actors, methods, tools and publications. We use a real-life research example from the engineering domain to show how to describe a research process with its object of research, the different steps with input and output data, the actors, and the used methods and tools. The resulting metadata files can serve as low-threshold documentation in a file system, as an exchange format between tools, as an input for data repositories and as a source of information to be used by scripts and tools.
Monitoring the State of Open and FAIR Data in Helmholtz

In this contribution we present an integrated approach to monitoring and assessing the state of open and FAIR data in the Helmholtz Association. The project is part of a multi-method approach by Hub Matter in the Helmholtz Metadata Collaboration (HMC).&#x0D; In a harvesting-approach, data published by Helmholtz researchers is found starting from literature metadata, harvested from the research centers. Data publications linked to that literature are identified using the SCHOLIX API. In a first approach to automated FAIR assessment, we adopted the F-UJI framework, as developed by the FAIRsFAIR consortium.&#x0D; The information collected is presented in an interactive dashboard. It allows to explore in which repositories Helmholtz researchers make their data publicly available, to engage Helmholtz communities, and to identify gaps towards improving the FAIRness of Helmholtz data.&#x0D; The dashboard is publicly available on https://fairdashboard.helmholtz-metadaten.de. The general approach as well as all program code are reusable by all research communities.
Optimizing the Use of Simulation Technology in Digital Learning Content Development

Education in the era of globalization that allows no limits to find all information is very easy and effective to do anywhere. By utilizing simulation technology in learning so that you can prepare even better. Of course there are stages that must be followed, such as knowing what positive effects are applied using simulation technology for the development of digital learning content, you have to know the methods with people who are experienced and knowledgeable in the field. By utilizing this technology in the form of digital learning content that is able to create effective and quality learning, so that it can make the next generation superior and competitive. Increasingly sophisticated technology can facilitate human work in all fields, especially in the field of education. Many people are competing to create interactive media, so they can earn from the media they create. This should also receive attention from parties related to the world of education. The method used in this study is a quantitative method by distributing a questionnaire containing 15 statements about this simulation technology for digital learning. The purpose of this research is to optimize the use of simulation technology to enhance digital learning for students so they are able to master the skills to use maximally, creatively and innovatively against this limitless technological development. The conclusion from this study is that technology greatly influences student learning development, one of which is by optimizing the use of simulation technology in digital learning. Students and teachers really get a big positive impact with the presence of this sophisticated tool. The limitation of this research is that researchers only conduct research at the school or madradah level, which in fact they need learning media like this in learning in class, so that the class atmosphere is more conducive and attracts students' attention to learning with focus.
Side-channel attacks on CRYSTALS-KYBER, countermeasures and comparison with SKELYA (DSTU 8961-2019)

Although the mathematical problems used in post-quantum cryptography algorithms appear to be mathematically secure, a class of attacks known as side-channel attacks may prove to be a threat to the security of such algorithms. Side-channel attacks affect the hardware on which the cryptographic algorithm runs, they are not attacks on the algorithm itself.&#x0D; The good news is that side-channel analysis on new post-quantum cryptographic algorithms started early, even before the algorithms were standardized, given that older algorithms still face side-channel problems.&#x0D; Kyber is a lattice-based post-quantum algorithm based on the complexity of the M-LWE problem. Kyber offers a secure public key encryption (PKE) scheme against a chosen plaintext attack (CPA) and a secure key encapsulation mechanism against a chosen ciphertext attack (CCA).&#x0D; This paper provides a study of side-channel and fault-injection attacks on lattice-based schemes, with focus on the Kyber (KEM).&#x0D; Considering the wide range of known attacks, the protection of the algorithm requires the implementation of individual countermeasures. The paper presents and tests a number of countermeasures capable of providing/improving protection against existing SCA/FIA for Kyber KEM.&#x0D; The obtained results show that the presented countermeasures incur a reasonable performance cost. Therefore, the use of special countermeasures in real implementations of lattice-based schemes, either alone or as an augmentation of general countermeasures, is necessary.
Dependency between digital competence and professional competence of students

The report aims to find out the existence of a dependency between the digital and specialized professional competence of students. The acquisition of certain competences is the basis of the effective exercise of a given profession. The role of information and communication technologies in the formation of the necessary abilities for effective professional career of the graduating specialists is analyzed. The primary data for the empirical study has been collected through the use of the survey method. The results show a statistically significant influence of digital competence on subjective assessments of professional competence, language competence and the contribution of university education to professionalisation. It can be concluded that directing learning in higher education to increase digital competence would have a positive effect on increasing the professional competence of future specialists.
WebGL 3D Virtual Exhibition as a Media to Increase the Visibility of Digital Artwork

The ongoing digital transformation continues to shape various domains, including the realm of art, which adopts social media to digitally promote artworks. Nonetheless, physical art exhibitions maintain their allure as they provide a direct experiential interaction for visitors. Consequently, the development of exhibition platforms that amalgamate user experience with accessibility becomes imperative. One emerging solution involves leveraging information technology and multimedia for virtualization, such as utilizing WebGL for creating a 3D Virtual Exhibition (3DVE). Employing the ADDIE methodology and evaluating it through the Technology Acceptance Model (TAM), the assessments affirm the robust performance and positive responses of 30 participants towards WebGL 3DVE. This development yields practical benefits, particularly for artists seeking to enhance the visibility of their creations. Furthermore, the inherent ease of use and broad accessibility can expand the potential audience for enjoying artworks. The percentage acceptance rates according to TAM validate favorable responses across usability (88%), ease of use (74%), satisfaction (90.6%), and technological acceptance (84.6%). Thus, the deployment of WebGL 3DVE in art exhibition development showcases strong potential in delivering a deeper and more inclusive experiential journey.
THE CULTURAL VALUES OF TENGKO SITURU’ IN ENGLISH LANGUAGE TEACHING AT SMK NEGERI 1 TORAJA UTARA

The purpose of this study was to determine the cultural value of tengko situru' (togetherness) in learning English. It is described in previous research that there is a close relationship between character education, values and culture, where value education cannot be separated from character education as well as culture which is one aspect formation of character education. This research uses descriptive qualitative method. The subjects in this study were four English teachers at SMK Negeri 1 Toraja Utara. The results of the research show that in the process of learning English the teachers introduce and apply the cultural values of tengko situru' in learning English. This can be seen from the interaction of students during the learning process.
Urdu Sentiment Analysis Using Deep Attention-based Technique

Sentiment analysis (SA) is a process that aims to classify text into positive, negative, or neutral categories. It has recently gained the research community's attention because of the abundance of opinion data to be processed for better understanding and decision-making. Deep learning techniques have recently shown tremendous performance, with a high tendency to reveal the underlying semantic meaning of text inputs. Since deep learning techniques are seen as black boxes, their effectiveness comes in the form of interpretability. The major goal of this article is to create an Urdu SA model that can comprehend review semantics without the need for language resources. The proposed model is tested on reviews to extract significant words using various scenarios and architectures. By emphasizing the most informative terms to the class label, the results demonstrated the suggested model's capacity to interpret a given review. Furthermore, the suggested models provide a visualization option for an intelligible explanation of the result. The impact of using transfer learning on the problem of Urdu SA is also investigated in this article.
IMPLEMENTASI METODE MEL-FREQUENCY CEPSTRAL COEFFICIENT DAN DTW PADA APLIKASI PENGENALAN SUARA TEMBANG SEKAR ALIT

The province of Bali has various types of songs that have different structures and functions, one of which is the Sekar Alit song. Seeing current technological advances, conservation efforts should follow the development of existing technology. This study recognizes the singer's voice with the MeliFrequency iCepstrum Coefficients (MFCC) method used to perform feature extraction, i.e. to obtain a parameter and information regarding the characteristics of a person's voice and the training of voice pattern matching against the voice of the DTW Singer Alit (Dinamic) and the Time Warping Alit method. . So that the final result of this research is an android-based tembang sekar alit learning application that can be used by students to learn more easily and effectively which is called the SekARAI application. The results of usability testing on the application found that the average value was above 3, which means that the SekARAI software that has been implemented has met the Usability element and besides that the software is easy to use and understand by users. The Sekar Alit Song Voice Recognition application has been evaluated using the confusion matrix method, it is found that the MFCC algorithm test results in an accuracy of 76.6%.
SPA-UNet: A liver tumor segmentation network based on fused multi-scale features

Liver tumor segmentation is a critical part in the diagnosis and treatment of liver cancer. While U-shaped convolutional neural networks (UNets) have made significant strides in medical image segmentation, challenges remain in accurately segmenting tumor boundaries and detecting small tumors, resulting in low segmentation accuracy. To improve the segmentation accuracy of liver tumors, this work proposes space pyramid attention (SPA)-UNet, a novel image segmentation network with an encoder-decoder architecture. SPA-UNet consists of four modules: (1) Spatial pyramid convolution block (SPCB), extracting multi-scale features by fusing three sets of dilated convolutions with different rates. (2) Spatial pyramid pooling block (SPPB), performing downsampling to reduce image size. (3) Upsample module, integrating dense positional and semantic information. (4) Residual attention block (RA-Block), enabling precise tumor localization. The encoder incorporates 5 SPCBs and 4 SPPBs to capture contextual information. The decoder consists of the Upsample module and RA-Block, and finally a segmentation head outputs segmented images of liver and liver tumor. Experiments using the liver tumor segmentation dataset demonstrate that SPA-UNet surpasses the traditional UNet model, achieving a 1.0 and 2.0% improvement in intersection over union indicators for liver and tumors, respectively, along with increased recall rates by 1.2 and 1.8%. These advancements provide a dependable foundation for liver cancer diagnosis and treatment.
Application of nonlinear regression theory based on edge computing to mathematical modeling in universities

Abstract Mathematical modeling is the link between mathematics and practical problems and is the medium through which mathematics is widely used in related fields. This paper introduces the definitions of mathematical models in different disciplines and for different practical problems and gives the specific steps of mathematical modeling and the key problems to be solved in each step, the most important of which is nonlinear regression theory. The parameter estimation of the error variance of the nonlinear regression model is performed by the least squares method, and for the problem of poor numerical stability and computational complexity due to the pathological matrix in solving the least squares method, the least squares method is proposed based on adding the edge computing framework. The results show that the system efficiency of the nonlinear regression model based on edge computing is 92%, and the resource utilization is between 80% and 90% on average, which is higher than the two algorithms of RPP and RPA. The nonlinear regression model based on edge computing proposed in this paper organically combines mathematical modeling, which can make mathematical modeling play a greater role in the practical application process and solve more practical problems.
Teaching reform and innovation of vocational development and employment guidance courses in colleges and universities based on random forest model

Abstract The current employment situation of graduates is serious and complicated, and employment work is very difficult. Furthermore, the employment quality of college graduates is an important reflection of the quality of education teaching and talent cultivation in higher education. Using big data to provide all-round and multi-perspective feedback on employment quality can find the direction of efforts to improve employment quality further, provide an important reference basis for schools to adjust the layout of majors, make development plans, reform education teaching, optimize career guidance courses and optimize enrollment policies and measures, and effectively promote universities to fulfill better their historical mission of serving the society. This paper extracts features for a series of school behavior data of students and carries out feature selection through appropriate methods. Specifically, the construction problem of the traditional random forest model is analyzed, and a new model is proposed by combining it with a decision tree algorithm; then, the model is constructed and adjusted by grid parameters to ensure the accuracy of the model, and finally, the model is compared and analyzed. The research shows that the accuracy of the RF prediction model using standard features is 0.702, and the LSTM prediction model using only temporal features is only 0.683. In contrast, the prediction accuracy of the model in this paper reaches 0.805. Therefore, the prediction accuracy of the model based on the decision tree algorithm is much higher than the other two, which is effective for optimizing the teaching of career development and employment guidance courses in colleges and universities, thus can improve the education and management-related to career planning and career guidance in schools.
Use of Video Streaming and Video Hosting by US University Libraries to Support Educational and Research Activities

The purpose of the article is to reveal the peculiarities and identify the current problems of using video streaming and video hosting within the framework of the American university libraries aimed to support the educational and scientific activities of students and faculty at the modern stage. The research methodology is based on the application of general scientific and special methods of cognition, in particular, terminological, systematic approach, analysis, synthesis, and logical method. The theory of active systems and theoretical approaches to the formation and functioning of the information and educational environment of the university are also used. The scientific novelty of the article lies in expanding the concept of the university library as a technological system and its contribution to the formation of the information and educational environment of a higher educational institution through such web tools as video streaming and video hosting. Conclusions. In the twenty-first century, university libraries are becoming catalysts of innovation and key structural units of higher educational institutions and “active systems” that increase the efficiency of educational and research activities of faculty and students by creating physical and virtual centres for the consumption and production of knowledge. Based on the analysis of the activities of American universities and colleges at the present stage, it is found that they are actively mastering video streaming and video hosting to support research, teaching and sharing their video collections. The American experience has revealed many progressive steps in the use of video streaming and video hosting by university libraries, as well as current problems related to copyright protection, licensing terms and costs, availability of streaming formats, and image quality. Video streaming and video hosting will continue to play an increasingly important role in the development of video collections of university libraries.&#x0D; Key words: the USA, university library, video streaming, video hosting, library services, video content.