Reviewerly/exHarmony huggingface dataset:
Adaptive Ontologies for Multimedia Maps

The paper illustrates a web-based framework linking geographic elements with geo and temporal-referenced multimedia contents.Among the key features, -multimedia content integration, time management and self-adaptivity to different application contexts are the most relevant ones.A hybrid approach to classify stored contents combines a Machine Learning (ML) technique for text classification with the intervention of human experts.A dynamically configured ontology-based navigation is proposed based on the adaptivity of the tool to dynamic classification of contents.Adaptive navigation is supported by a general world and by a domain-specific ontology.The approach is presented in a framework and prototype named Multimedia Adaptive Geographic Information System (MAGIS), an extension to Geographic Information Systems (GIS) devised as a common foundation to be adapted to different domainspecific implementations.A demonstration of the web-based MAGIS prototype is provided for Cultural Heritage (CH) events.
Design of Formative-Summative Evaluation Model Based on Tri Pramana-Weighted Product

Quality in the implementation of e-learning in health universities can be measured both during the learning process and after the learning ends. Measurement can be performed through evaluation activities. The evaluation model needed was an innovative evaluation model that can look for the dominant aspects that determined the quality of e-learning implementation. One breakthrough evaluation model produced in this research to answer this need was the Formative-Summative evaluation model based on the Tri Pramana-Weighted Product. The main objective of this research was to show the quality of the Formative-Summative evaluation model design based on the Tri Pramana-Weighted Product. This research approach was based on the Borg &amp; Gall development model, which focused on the design development stage. The subjects involved in conducting trials of the evaluation model design were 34 respondents. The technique for determining the subject was carried out using a purposive sampling technique. In addition, the tool used to conduct the trial was a questionnaire. The location for filling out the questionnaire was in health universities and colleges in the province of Bali. The technique used to analyze the data from the test results was descriptive quantitative by comparing the average percentage of the quality of the test results with the percentage of quality that refers to the five-scale categorization. The results showed that the percentage of the design quality of the Formative-Summative evaluation model based on the Tri Pramana-Weighted Productof 88.02%. This means that the quality of the evaluation model design was included in the good category. The impact of the results of this research on the field of education was to present an innovation in evaluation activities that made it easier for educational evaluators to measure the quality of e-learning, especially in health universities and colleges. Doi: 10.28991/ESJ-2022-06-06-016 Full Text: PDF
Geoprivacy protection of agricultural data

A major challenge of sharing spatially explicit agricultural and agri-environmental data is to identify the trade-off between field parcel confidentiality and spatial pattern preservation. in this study, the main drawback of point-based obfuscation was identified and the polygon-based obfuscation methods were designed and developed to overcome these issues.
COVID-19, HIV, and Syphilis Contact Tracing: What Have We Learned and Where Are We Headed?

Abstract Contact tracing is a core public health intervention for a range of communicable diseases, in which the primary goal is to interrupt disease transmission and decrease morbidity. In this article, we present lessons learned from COVID-19, HIV, and syphilis in San Francisco to illustrate factors that shape the effectiveness of contact tracing programs and to highlight the value of investing in a robust disease intervention workforce with capacity to pivot rapidly in response to a range of emerging disease trends and outbreak response needs.
From Metaverse to the Real World: The Role of Avatar Identification in Consumer’s Virtual Purchasing Behavior

Metaverse has drawn much attention in both industrial and academic fields. Based on “extended theory”, this study explores whether consumer behavior in the Metaverse can influence that of the real world and the role of avatar identification in this process. As a quantitative study, 164 samples were collected, and PLS-SEM was used in the analysis. This study found that appearance similarity has a significant positive influence on avatar identification, and avatar identification significantly influenced virtual product purchase intention. In addition, we also found avatar identification fully mediates the relationship between appearance similarity with avatar and virtual product purchase intention. Lastly, this study also found the significant effect of virtual product purchase intention on real product purchasing intention.
Chemistry students’ digital literacy skills on thermochemistry context “hydrogen fuel issue”

Living in the era of the Internet of things makes students familiar with the use of digital platforms in their daily life. However, several studies show that familiarity with digital platforms does not merely indicate that students are digitally literate. Students are still vulnerable to unreliable news, only mastering digital social platforms, and are unfamiliar with specific digital applications of expertise. This study aims to examine chemistry students’ digital skills related to thermochemical content integrated with the global dilemma of ​​using hydrogen fuel. This research utilized a mixed-methods design, a sequential explanatory type. Quantitative data was obtained through surveys and structured interviews to obtain qualitative data. Research participants included 74 chemistry students from seven state universities in Indonesia. The research instrument was a two-tier digital literacy questionnaire (r=0.947) consisting of 13 items, with self-assessment as the first tier and knowledge-based assessment (verification questions) as the second tier. Digital literacy profiles from surveys and interviews show that most students’ skills are at the foundation and intermediate levels. The research implication is that students’ digital literacy skills need to be improved, especially explicitly teaching several competencies related to digital literacy.
Using QKD-exchanged keys for encryption of VPN

The paper aims to highlight how symmetric cryptographic key generation via Quantum Key Distribution-based technology can be used to secure protected communications within a private network. Within a testbed of the 5G network installed in the campus of the Technical University of Ostrava, the quantum key distribution (QKD) technology and encryptors are implemented to demonstrate secure 5G network concepts such as network function virtualization (NFV) and network management software-defined networking (SDN). Specifically, two APIs are programmed with all the necessary steps for two Secure Application Entities to secure a new symmetric key that is in turn generated by two Key Manager Entities via a protocol called "Coherent One-Way".
Efficacy of innovative instructional strategies: effect of learning games strategy on students' learning outcome in social studies classroom

In this study, it was examined whether the innovative instructional strategy of learning games would significantly increase students' learning outcome in the experimental groups and control groups. The study is a quasi-experimental research, which examined the effect of learning games instructional strategy on students' learning outcomes in eight upper basic classroom settings. The study sample comprised of 192 students randomly assigned to the intervention and control groups. The instrument employed for the study was a learning outcome test instrument which comprised of 50 multiple-choice questions. Hypotheses were tested using ANCOVA. After experimentation, the results showed that students instructed using learning games had improved learning outcomes in comparison to those instructed with the lecture strategy (control group). There is no statistically significant influence of gender on students' learning outcomes. This study provides empirical evidence of the efficacy of using learning games instructional strategy in boosting students' learning outcomes.
Multi-party semi-quantum private comparison based on the maximally entangled GHZ-type states

The goal of semi-quantum privacy comparison (SQPC) is to use a small amount of quantum capabilities to compare private information for equality. In recent years, research on semi-quantum privacy comparison protocol has made some achievements. However, most of SQPC protocols can merely compare the private information of two parties, and the research of multi-party SQPC protocols are still scarce. If the number of participants is more than two, the protocol needs to be executed multiple times. Therefore, we proposed a multi-party semi-quantum private comparison protocol based on the maximally entangled GHZ-type state, which has the capability to compare the equality of n parties by executing the protocol once. What is more, the transmission of participant’s encrypted information is not through the classical channel, which improves the security of the protocol. Finally, the security analysis shows that outsider attacks, dishonest participants attacks and semi-honest TP attacks are all invalid for this protocol.
Influencing Factors of Students’ Learning Gains in Tourism Education: An Empirical Study on 28 Tourism Colleges in China

The rapid development of tourism has put forward new requirements for the training of tourism talents. This study conducted a cross-regional questionnaire survey on tourism management undergraduate students from 28 tourism colleges in seven regions of China. PLS method was used to explore the relevant influencing factors of students’ learning gain. The study concluded that: (1) Students’ gain in professional knowledge reserve, learning ability, innovation ability, teamwork ability and social ethics have a significantly positive impact on students’ employment situation. (2) Internship and employment guidance plays an important role in the influence of college investment on students’ learning gain. (3) Student engagement plays an important mediating role in the relationship between teaching factors (such as learning curriculum and teachers’ teaching quality) and students’ learning gain. (4) The college’s learning guidance and advice collection can effectively improve students’ learning gain, but the impact of the college’s environmental facilities on the sense of acquisition of tourism management students is not significant. This paper provides important implications for the improvement of talent mechanism of tourism education.
mmWave Networking and Edge Computing for Scalable 360° Video Multi-User Virtual Reality

We investigate a novel multi-user mobile Virtual Reality (VR) arcade system for streaming scalable 8K 360° video with low interactive latency, while providing high remote scene immersion fidelity and application reliability. This is achieved through the integration of embedded multi-layer 360° tiling, edge computing, and wireless multi-connectivity that comprises sub-6 GHz and mmWave (millimeter wave) links. The sub-6 GHz band is used for broadcast of the base layer of the entire 360° panorama to all users, while the directed mmWave links are used for high-rate transmission of VR-enhancement layers that are specific to the viewports of the individual users. The viewport-specific enhancements can comprise compressed and raw 360° tiles, decoded first at the edge server. We aim to maximize the smallest immersion fidelity for the delivered 360 content across all VR users, given rate, latency and computing constraints. We characterize analytically the rate-distortion trade-offs across the spatiotemporal 360° panorama and the computing power required to decompress 360° tiles. The proposed solution consists of geometric programming algorithms and an intermediate step of graph-theoretic VR user to mmWave access point assignment. The results reveal a significant improvement (8–10 dB) in delivered VR user immersion fidelity and spatial resolution (8K vs. 4K) compared to a state-of-the-art method based on sub-6 GHz transmission only. We also show that an increasing number of raw 360° tiles are sent, as the mmWave network link data rate or the edge server/user computing power increase. Finally, we demonstrate that in order to hypothetically deliver the same immersion fidelity, the reference method would incur a much higher (2.5-4.5x) system latency.
Uniform Rules for Digital Trade Transactions (URDTT): Novelty or Necessity

Uniform Rules for Digital Trade Transactions (URDTT) do not offer solutions to all issues in this area, but by striving to achieve uniformity, by providing a collective understanding of terms and definitions, as well as by promoting and supporting the usage of electronic records, they contribute to easier, faster, cheaper, and environmentally sustainable business. While their formulation and publication are an important step towards a digital future, acceptance and effective implementation are an even greater challenge. The prerequisites for this are a thorough understanding, but also solving a number of technical issues, which can be very complex. To this end, the paper, after determining the area of application, discusses the roles of participants in a digital trade transaction, as well as issues that are key to its proceeding, the payment obligation, the financial services provider (fsp) payment undertaking and the use of electronic records.
The impact of business intelligence in crisis management: the strategic vigilance as an intermediary variable in Jordanian insurance companies

This study aimed to identify the role of strategic vigilance as an intermediary variable in the impact of business intelligence in crisis management in Jordanian insurance companies. This study used the design of quantitative research, where 275 questionnaires were collected from the observers working in Jordanian insurance companies to obtain the necessary data to test the hypotheses of the study. Path analysis was used to test the hypotheses of the study. The findings of the present study revealed that there is a significant impact of business intelligence on crisis management, as well as the impact of business intelligence on strategic vigilance, the presence of strategic vigilance in crisis management, and the impact of business intelligence on strategic vigilance with strategic vigilance as an intermediary variable.
Information needs on research data creation

Researchers’ data related information needs are growing. This paper reports the findings of a study with archaeologists and cultural heritage professionals focussing on data reuse related meta-information needs.Methods. Interviews with (N=)10 archaeologists and cultural heritage professionals. Qualitative coding and content analysis. Four types of paradata needs (data on processes, e.g. data creation) are identified, including 1) scope, 2) provenance, 3) methods and 4) knowledge organisation and representation paradata. Knowledge organisation and representation paradata has been least explored both in research and practises so far. The findings point to a need to develop the understanding of the needs and means of documentation of knowledge organisation and representation. The findings contribute to the data literacy of researchers producing and using data descriptions, and to the study of how paradata can be created and used. Further, the findings indicate that distance-to-data is a significant parameter in determining whether information needs are continuous or discrete. Further, the most likely type of reuse should guide the level and type of paradata. Finally, the findings underline that in spite of the comprehensiveness of available meta-information, it will be incomplete. Complementary means — including collaboration with data creators and meta-information extraction approaches — are needed to increase information reusability.
Research on the Construction of College English Development Courses Based on the Theory of Demand Analysis

Curriculum construction is the core element of talent fostering.College English development course is an important part of college English curriculum system.Through questionnaire survey and semi-structured interview method, this paper analyzes the College students' learning needs in English, needs of teachers' qualification, course types and teaching forms.According to the analysis results, this paper proposed ways of construction of College English development courses from the dimensions of curriculum, teachers, teaching methods, teaching materials and teaching assessment.To build the development courses, construction of the diversified, modular, hierarchical and distinguishing curriculum should be strengthened; highly qualified teachers on development courses can be optimized by teaching team and team teaching, as well as course progression and degree study.Improve teaching effectiveness by use of information technology to create three-dimensional teaching space; develop campus adaption teaching materials and build a teaching resource database for students personalized English learning; and promote diversified and developmental curriculum evaluation to stimulate students' learning interest and involvement.Finally, to meet the needs of development of excellent English talents.
Design Challenges on Machine-Learning Enabled Resource Optimization

Nowadays, service providers’ (SPs) need for efficient resource utilization solutions is more demanding than ever. The optimal use of the physical and virtual infrastructures guarantees that the waste of resources due to overdesign is minimized while the provided services enjoy the required quality of service levels. However, the prediction of the exact amount of the required resources per service at any time of its lifecycle is not an easy process. For this purpose, we propose a solution that handles the infrastructure in a holistic manner introducing a novel architecture that exploits the monitoring data from three layers (hardware, virtualization, and application) and uses them to train machine learning models, which can accurately predict the exact amount of the required resources per service. Its implementation using open-source tools and its performance are also presented.
Advanced Algorithms for Compression of Videos with Ultra High Resolution

In this paper, attention is devoted to advanced video codecs (HEVC, VVC, VP9 and AV1) and their utilization for compression of videos with Ultra High Resolution (UHD), also marked as 4K and 8K.A Python-based program employing FFmpeg multimedia framework is created to explore compression performances of such video codecs.It allows to automate encoding process and record all important information during the video compression (e.g. the required CPU time, time consumption, RAM usage).The performance of the video compression algorithms is evaluated in terms of objective quality metrics.First experimental results show that video codecs VVC and AV1 could replace HEVC and VP9 for 4K and 8K videos in the future.
Visualization of Syntax and Semantics for Simple Functional Language of Natural Numbers and Boolean Values

Building an abstract syntax tree is an integral part of compilers. We analyze a few of the popular techniques providing such analysis in the web environment. Based on the analysis of these solutions, we deal with the implementation of our parser solution, which also provides a graphical representation of abstract syntax trees as well as proof trees. This solution is then used in our application designed to interpret the expressions of the simple teaching functional language of natural numbers and boolean values. In addition, the application supports the evaluation (semantics) of expressions (step by step), and also their individual properties: the depth of the syntax tree, syntax tree nodes count, and the constants used in the expression.
An Improved-PoA Consensus Algorithm for Blockchain-empowered Data Sharing System

In a traditional data sharing system, each participant has carried out the construction of the corresponding database. However, due to the different research objects and data completeness of each participant, it is difficult to form effective interconnection and data sharing among databases, the phenomenon of data silos is still serious. Blockchain has the advantages of high trustworthiness, data immutability, and has a high fit with data sharing systems. While data sharing has brought a lot of benefits, a series of problems caused by bogus data have also emerged. Trust issues becomes a prerequisite for the implementation of the data sharing platform. To address these problems, this paper proposes an improved data sharing method based on the consensus algorithm of Proof of Authority (PoA), implements a distributed data transaction authentication system using a consortium blockchain. To improve the throughput and reduce the latency of the consensus mechanism, temporary grouping of PoA validation nodes is performed and different blocks of data transactions are validated in parallel between each group of validation nodes. After the experimental results in this paper, it is shown that the proposed Improved PoA consensus mechanism improves the throughput by 27.65% and reduces the latency by 21.66% than the traditional PoA consensus algorithm.
BIPS: Bi-modal Indoor Panorama Synthesis via Residual Depth-Aided Adversarial Learning

Providing omnidirectional depth along with RGB information is important for numerous applications. However, as omnidirectional RGB-D data is not always available, synthesizing RGB-D panorama data from limited information of a scene can be useful. Therefore, some prior works tried to synthesize RGB panorama images from perspective RGB images; however, they suffer from limited image quality and can not be directly extended for RGB-D panorama synthesis. In this paper, we study a new problem: RGB-D panorama synthesis under the various configurations of cameras and depth sensors. Accordingly, we propose a novel bi-modal (RGB-D) panorama synthesis (BIPS) framework. Especially, we focus on indoor environments where the RGB-D panorama can provide a complete 3D model for many applications. We design a generator that fuses the bi-modal information and train it via residual depth-aided adversarial learning (RDAL). RDAL allows to synthesize realistic indoor layout structures and interiors by jointly inferring RGB panorama, layout depth, and residual depth. In addition, as there is no tailored evaluation metric for RGB-D panorama synthesis, we propose a novel metric (FAED) to effectively evaluate its perceptual quality. Extensive experiments show that our method synthesizes high-quality indoor RGB-D panoramas and provides more realistic 3D indoor models than prior methods. Code is available at https://github.com/chang9711/BIPS .