Reviewerly/exHarmony huggingface dataset:
VSAS: Decision Transformer-Based On-Demand Volumetric Video Streaming With Passive Frame Dropping

Volumetric video is becoming a popular application among various multimedia services, which is envisioned as a fundamental technology for VR, AR, and the emerging Metaverse. The commodity RGB-D cameras provide an affordable solution for volumetric video capture, and the VR headset allows immersive and interactive display. From the networking perspective, the primary challenge lies in the smooth and high-quality transmission over the Internet, given the enormous data volume and limited bandwidth. MPEG V-PCC standard has stood out recently as a promising compression and streaming solution that can effectively reduce video size while maintaining high visual quality. Since MPEG V-PCC is largely backward compatible with the 2D video compression standard like H.264/AVC, it is natural to use DASH, the most widely used 2D streaming framework, to stream it. We first propose an integrated framework based on DASH to support MPEG V-PCC Internet streaming. During this, we faced three challenges. First, the lack of a rate-distortion model for MPEG V-PCC encoding parameters. Second, the need for a new bitrate adaptation controller that not only considers the rate of the chunks but also chooses the chunks with proper frame rate. We align the decision transformer to this problem, which expands the success of transformer-based models in natural language processing to the decision problems. Finally, to solve the stalling time issue inherited from DASH, we use a frame-dropping mechanism to eliminate the stalling in DASH playback. Our evaluations show that VSAS achieves an average QoE improvement of 1.67x over a range of network conditions.
Multi-step Ahead prediction for Anomaly Detection of Geomagnetic Observation in HVDC transmission

This paper presents an intelligent model for the recognition of high-voltage direct current interference in geomagnetic observation stations. Firstly, it introduces the history and current status of geomagnetic observation in China, highlighting the issue of station interference from HVDC. Next, it discusses the application of traditional methods and deep learning techniques in the identification of geomagnetic data interference, along with related research. To address these issues, the paper emphasizes the proposed model framework, which includes four main components: data preprocessing, model training, interference recognition, and visualization. Data preprocessing is carried out to eliminate dimensional differences between data by using standardization and data augmentation techniques, increasing the diversity and robustness of training data. Model training involves the use of an LSTM network, which learns temporal patterns and relevant features in the input data, implicitly performing feature extraction and representation learning. In the interference recognition stage, the concept of anomaly scores is introduced, and the anomaly score for each data point is calculated using mean and covariance to determine if the point is an anomaly. Finally, the results of interference recognition are presented through visualization. In the experimental section, the paper conducts a comprehensive evaluation of four different models (LSTM, RNN_TANH, RNN_RELU, and GRU) when used as the training network for the proposed model. The evaluation focuses on three aspects: model performance, computational cost, and Friedman’s test. The experimental results demonstrate that selecting LSTM as the training network with a time step of 3 achieves optimal performance in all three aspects, showcasing strong generalization capabilities.
Blockchain: A Crypto-Intensive Technology - A Comprehensive Review

Blockchain has shifted the paradigm of computer-based commercial applications during the last decade. Initially developed as a public ledger for Bitcoin transactions, it has already shown that it has the potential to revolutionize the world, where trust, security, privacy, and anonymity are the assurances. The data stored within the blockchain remains unchangeable, resistant to tampering, and distributed across multiple locations within a decentralized network. The existence and reliability of blockchain rely heavily on robust cryptographic primitives, as these are fundamental to its operation. While blockchain faces significant challenges in the ever-evolving landscape of hardware and software technologies, it has retained its reputation for being secure due to its underlying cryptographic primitives. The architecture of blockchain, various consensus protocols, and the impacts of quantum computing are also discussed here. This study reviews the existing academic literature on cryptographic primitives used in blockchain and endeavours to bridge the gaps and provide a detailed understanding of their role in blockchain security. An exploratory qualitative research methodology is used in this study and is based on the latest literature on the topics. The findings of this study provide a valuable reference to the knowledge body and enhance the comprehension of blockchain, cryptography, and cryptographic primitives in blockchain for both new and experienced researchers, enabling them to identify new opportunities and challenges in the domain.
Edge Caching with Federated Unlearning for Low-latency V2X Communications

Vehicular-to-everything (V2X) communications have gained popularity as a cutting-edge technology in the Internet of Vehicles (IoV), ensuring low-latency communication for emerging transportation features. Federated learning (FL), a widely-used distributed collaborative AI approach, is transforming edge caching in V2X communications due to its exceptional privacy protection. However, current FL-based edge caching methods can negatively impact communication performance when nonindependent and identically distributed (non-IID) data or invalid data, such as poisoned data, are introduced during the training process. In this article, we present FedFilter, an FL-based edge caching solution designed to address these challenges. FedFilter employs a personalized FL method based on model decomposition and hierarchical aggregation, caching content tailored to the diverse preferences of individual users. This enhances the cache hit rate, reducing backhaul load and service latency. Moreover, FedFilter detects and mitigates the adverse effects of invalid data on the global model, ensuring the Quality of Service (QoS) of V2X communications. A case study is introduced to demonstrate the effectiveness of FedFilter, showing that it not only reduces latency but also effectively removes invalid data while maintaining a high cache hit rate.
Preparing Children for an Unpredictable World in the Middle of a Crisis: La Aldea's Approach

No one was prepared when COVID-19 hit. While education systems all over the world turned to distance learning, countries like Colombia faced a significant challenge: only 75 percent of Colombian teachers had received training in online teaching, 64 percent of school principals considered the technology available to schools to be insufficient, and only 67 percent of 15-year-old students had internet access (OECD 2019). And what about the families living in at-risk contexts and facing additional economic and health pressures? The time was ripe to scale up La Aldea—a flexible, learner-centered strategy whose content and methods are designed to meet the needs of the child at the end of the proverbial "last mile." La Aldea is a strategy created by ClickArte, a Colombian organization that specializes in designing and implementing educational projects. Using its print books, radio shows, digital content, songs, and games, La Aldea was disseminated throughout the country via UNICEF Colombia's education in emergencies strategy. It also provided online training sessions to 4,220 teachers. It ultimately reached 87,667 families and children. This immediate, comprehensive, multimedia, multistakeholder plan was adapted to reach every child in Colombia's formal and nonformal education settings in migrant and conflict-affected communities. La Aldea education strategy is composed of carefully crafted stories whose main characters are animals found in Colombia (such as macaws, tapirs, owls, anteaters, among others). The stories and activities that make up La Aldea are metaphors of society: children, families, and teachers can self-identify with the situations being portrayed, hence giving schools material to integrate playfully into the teaching curricula, while at the same time nudging children's cognitive, citizenship, and social-emotional skills—and, of course, COVID-19 awareness.
INTERRELATION SPECIFICITY OF LIFE-PURPOSE AND VALUE ORIENTATIONS OF THE STUDENTS WITH DIFFERENT FEATURES OF SELF-ATTITUDE

The paper presents the results of the empirical research directed to definition of the interrelation specificity of value and life-purpose orientations of the students according to their self-attitude features. The research is based on the idea of self-attitude as an inner factor of the values personal system development at the juvenile socialization stage. Specificity of the life-purpose, terminal and instrumental interrelations for the first, third and fifth course students with different structure of self-attitude has been revealed.Key words: life-purpose orientations, value orientations, terminal orientations, instrumental orientations, self-attitude, students.
ABOUT THE PROBLEMS OF THE SCHEDULE THEORY IN EDUCATION

In the article, a number of statements of the problems of the theory of schedules with accentuation are considered and emphasized for those that reflect the peculiarities of the modern enterprising education of persons who are interested in teachers (mentors), which does not require the presence and analysis of groups and audiences. A classification of such tasks was carried out and a new task of composing schedules from the sphere of education was proposed, it uses such basic parameters as the coefficient of similarity between the mentor and the student, as well as the importance of the subject area for the mentor. The methods of solving the optimization problems of the theory of decompositions are considered. Since the considered problem of scheduling training sessions is NP-complicated, an overview of existing applied methods and task statements is necessary to determine the relevance of this task statement. Further research should be aimed at formalizing and solving similar scheduling tasks using information technology.Keywords: education, online education, theory of schedules, mentor, student, NP-complex.
Pengaruh Promosi, Harga, dan Kualitas Produk terhadap Keputusan Mahasiswa Mendaftar di Stie Gici Business School

This study aims to analyze the effect of promotion, price, and product quality on students' decisions in choosing STIE GICI. The research sample consisted of 80 students. The data analysis method used is multiple linear regression. The results showed that the results of the simultaneous hypothesis testing of all variables consisting of promotion, price and product quality had a significant influence on the student's decision to choose STIE GICI. In addition, partial hypothesis testing also shows that all variables, namely promotion, price, and product quality, have a significant effect on the decision to choose STIE GICI. The findings of this study can assist STIE GICI in planning a more effective marketing strategy to increase the number of new student applicants. By paying attention to the aspects of promotion, price, and product quality, STIE GICI can attract more prospective students and increase their decision to choose the institution.
PELATIHAN PENYUSUNAN PENELITIAN TINDAKAN KELAS BAGI GURU SMPN 1 MARABAHAN

The results of the 2018 study showed that the critical literacy competence of junior high school students in the two schools was low. These symptoms certainly must be overcome. If this is not done, students will continue to experience difficulties in adapting and taking advantage of developments in information technology in their lives. There are various things that can be done, including providing counseling in the form of training in the preparation of classroom action research to teachers. With this training, teachers are expected to be able to design PTK to improve students' critical literacy competencies.
An ICT based collection development model for engineering college’s libraries: Challenges and problems

The paper highlights the current issues in acquisition and procurement of printed and digital resources in order to find out challenges and problems in Collection development in the ICT Environment in Engineering College Libraries. Collection Development in the ICT environment is still more challenges are increased due to the extensive information generated in print and digital form in engineering and technology area. There is need to integrate both print and electronic resources and also making changes in collection development practices in Engineering College Libraries. The main key issues are identified for redefining a collection development policy (CDP) include issues like balancing Ownership verses Access and Cooperative efforts and Evaluation. The main aim of the collection development is to acquire and procurement of print and digital resources in order to provide integrated access to print and e-resources to the users in single window.
An Exploratory Sequential Mixed Methods Design to Identify Criteria for Continuous Performance Evaluation

An alternative to the ubiquitous annual performance evaluation is continuous performance evaluation that is posed to give more objective, frequent and constructive feedbacks. Despite researchers recommending following a continuous performance evaluation for employees, there are hardly any progress in this regard. One of the hindrances is in identifying the evaluation criteria. Identifying the relevant criteria – both from employers and employee’s perspective – is important for the success of a continuous performance evaluation process. Given its novelty, it calls for an exploration to understand a holistic set of criteria. For this purpose, an exploratory sequential mixed method was adopted in the Information Technology Industry in India. In the first phase, an unstructured interview was conducted among 11 software engineers (employees). Based on the responses, a semi-structured interview was conducted among 52 software engineers. A qualitative content analysis of the interview transcripts resulted in 33 criteria. Criteria that were similar, synonymous and complementary were combined. An acceptable interrater reliability was obtained in the content coding and categorization process (Krippendorff’s α = 0.822). This was followed by a focus group discussion among employers (represented by 15 project managers) and 11 criteria were eliminated and seven were added. In the second phase, the importance of 28 criteria were sought using a questionnaire based survey. A simple random sampling was adopted and 498 responses were received. (Cronbach’s α = 0.786). After elimination for incompleteness and erratic information, responses from 443 participants were considered for quantitative analysis. An exploratory factor analysis was conducted on the responses with 28 criteria subjected to exploratory factor analysis. Two criteria were not included for analysis due to a low mean sampling error value. The 26 most relevant criteria were categorized into six factors based on their factor loading. The main criteria factors were titled: Diagnostic, Dynamic, Proactive, Prompt, Resourceful and Responsible. These factors and the criteria within these factors can be used for continuously evaluating the performance of employees.
Likert scales and questions: uses and abuses

when conducting business and management research, the most common strategy employed for collecting primary data is either interviews or questionnaires (or both). When questionnaires are used to collect primary data a very common approach used is to construct questions which can be called Likert-type questions or Likert scales. Numbers are allocated to the question responses of each question.. Often, this is followed by performing arithmetic or statistical operations on the allocated numbers. In many cases encountered by the author, the analysis has even included techniques such as parametric statistics and factor analysis. This paper explains why such simplistic approaches are completely invalid and should never be used. It goes on to explain how analysis can be done whilst avoiding typical hazards. Often, the writers of such papers do not understand or explain levels of measurement. Of course, Likert scales are at an ordinal level of measurement which would normally preclude the use of arithmetic, statistical, factor analysis techniques there is an additional problem of reliability because different people will interpret terms such as strongly disagree and disagree, differently. Likert was aware of these problems when writing the original paper in 1932 although at that time the term “levels of measurement” was not in use. This paper provides approaches and suggestions for avoiding the problems of data analysis when using Likert-type questions. This paper should be of assistance to those who intend to use Likert-type questions in the questionnaire.
Navigating the Intersection of Innovation and Cybersecurity: A Framework

Reliance on digital technologies for innovation management is unavoidable in current contexts. While digital processes and business models have been prioritised as key factors to drive innovation and value creation within firms, cybersecurity concerns are still rife. Increased levels and severity of cybersecurity breaches (CSBs) have had adverse effects on trust, caused significant revenue losses, and inflicted reputational damage on many firms. Further exacerbating these concerns is an observation made in the Global Risks Report of 2022, the World Economic Forum: cybersecurity measures taken by businesses are becoming increasingly obsolete. Many firms face severe consequences without implementing strategic objectives to limit the threats posed by CSBs. Cybersecurity breaches (CSBs) have a significant long-term impact on firm-level innovation and investment decisions. However, many firms are reluctant to examine or enhance their existing cybersecurity practices because of concerns that they may limit their innovation ability. Determining a method to limit CSBs and retain capabilities to perform necessary innovative processes is a delicate balance, with trade-offs to be considered within each process.&#x0D; This paper aims to address the delicate balance between limiting CSBs and preserving the ability to undertake necessary innovative processes. Building upon the Cyber Security Maturity and Innovation matrix introduced by Nelson and Madnick (2017), this paper expands the framework by providing specific suggestions for each quadrant. The matrix classifies firms into different quadrants based on their reliance on innovation and their assessment of cyber risk. We then detail measures to improve cybersecurity maturity for firms in each quadrant, incorporating the National Institute of Standards and Technology (NIST) Cybersecurity Framework Version 1.1 (CSF) as a reference. By making well-informed decisions and implementing appropriate measures, firms can effectively mitigate CSB risks while continuing to drive innovation and create value. This expanded framework serves as a valuable tool for firms seeking to align their cybersecurity practices with their innovation objectives, in accordance with the NIST CSF.
Introduction of Metaverse to Our Lives and Unlimited Services in the World of Metaverse

Metaverse is a universe that combines our physical reality with the digital virtual world and goes beyond reality with multiple users with a permanent and lasting effect. The virtual world is based on digital people and objects and technologies that enable multi-sensory communication with people, such as virtual reality (VR) and augmented reality (AR). It provides highly professional communication in dynamic interactions between digital structures and real time. First, we encountered virtual worlds where avatars could teleport between them. Metaverse’s resurgence has come with social, immersive VR platforms compatible with multiplayer online video games, open game worlds, and AR co-working spaces. Metaverse is a concept that offers opportunities to create virtual communities in the commercial or beyond entertainment world; It is seen that it is a new generation platform that includes the three-dimensional sandbox where metaverse enthusiasts can interact through their avatars and is expressed as the “digital big bang” in cyberspace.
More Secure Outsourcing CP-ABE Scheme Under the Situation of Untrusted PKG

The scheme of CP-ABE is widely used in data security protection in cloud outsourcing service. The architecture based on CP-ABE involves user, SP, PKG and CSP. Under this situation, PKG is trusted by default. However, in the real situation, except the default situation, there exists another scenario, where there is no SP and user communicates with PKG and CSP directly. In the above environment PKG may be untrusted. Once PKG is colluded with CSP or PKG is compromised, the adversary can get the decryption keys from PKG easily and the data preserved on CSP will be decrypted and leaked. In this paper, we first innovatively propose a scheme that can resist the attack from the aforementioned situations. The idea of the scheme is that a factor generated by the user is added to the secret key and the cipher text. The secret key is added the factor, which results that even PKG is compromised or untrusted, the secret key cannot be obtained. We apply the idea on the Li’s scheme and make it be suitable for the cloud outsourcing environment with an untrusted PKG. Finally, we prove the security of our scheme.
Analysis of International Regulations on Artificial Intelligence(AI) Ethics – a Comparative Approach

AI 기술의 급속한 발전으로 국가별 규제가 너무 제한적이거나 비효율적이어서 전 세계적 파급력이 있는 AI 위험을 관리하기에는 한계가 있다는 지적이 제기되면서, AI에 대한 윤리적 문제가 부각되고 있다. 본 논문에서는 먼저 글로벌, 국제, 국내 AI 윤리 규범으로 각각 분류되는 이른바 "다층적 규범 제정 틀(multi-level framework)"을 통해 현존하는 주요 AI 규제를 분석을 시도한다. 또한 국제적 AI 윤리 규범의 사례로 특히 유네스코(UNESCO), 경제협력개발기구(OECD), 유럽연합(EU)의 문헌을 세부적으로 비교 분석한다. 마지막으로 "인류의 공익을 위한 AI 기술 규제"라는 윤리 규범의 정책 목표를 중심으로 한국의 AI 윤리 규정 제정에 대한 국내외적 정책적 시사점을 도출한다. 합니다. 문헌 분석에 따르면 다층적 구조로 형성되는 AI 규범들은 총 8가지 원칙들이 중첩되어 있고, 분석 대상인 3개의 국제적 AI 윤리 규범들 모두 이러한 공통 원칙들을 이행하기 위한 정책적 조치까지 담고 있다. 특히 가이드라인(guideline) 형식을 지닌 유럽연합(EU)의 규범이 보다 더 구체화된 규범이고, 유네스코(UNESCO)의 규범은 유일하게 "다중 이해관계자"를 언급하는 원칙을 갖추고 있다. 따라서 한국은 대외적으로는 다른 국가는 물론 국제기구와 협력하여 AI 윤리 규범의 글로벌 통합을 위해 노력할 필요가 있으며, 대내적으로는 다양한 디지털 통상 이해관계자와의 소통을 통해 공감대를 형성하고 국제적 규범과 국내법과 조화시킬 수 있도록 노력해야 한다. With the rapid development of AI technology, ethical issues on AI have emerged as national regulation may be too limited or ineffective to manage globally shared risks of AI within each state. This paper first analyzes the major existing AI regulations from ‘a multi-level framework, having three-layered rule-making such as global, international, and domestic. It then analyzes international AI ethics regulations under the UNESCO, the OECD, and the EU. Finally, it derives policy implications for Korea"s AI ethics rule-making at both international and domestic levels, particularly concerned with policy goals of regulating AI technology with public interest for humanity. Previous literature shows that there are eight core principles overlapped while all three AI ethics regulations by the UNESCO, the OECD, and the EU contain their own policy actions to implement their principles proposed. In particular, the EU"s regulation, which are in the form of guidelines, are much more advanced, while the UNESCO regulation is the one that suggested a principle related to governance framework of AI ethics which mentions "multi-stakeholder". Internationally, Korea needs to work together with other countries as well as IOs toward global convergence of AI ethics regulations. Domestically, Korea is recommended to take multi-stakeholder approach to build consensus as well as to make the international regulations harmonized with domestic laws.