Reviewerly/exHarmony huggingface dataset:
A study on the development and apply a measuring tool for the measurement of the performance of medical equipment management system

According to the results of a recent study, hospitals can potentially minimize the number of medical equipment breakdowns or failures if they use effective, carefully planned and monitored maintenance management methods. The medical equipment needed can range from highly sophisticated life support systems in tertiary hospitals to the simplest devices needed to accurately diagnose and safely treat patients in primary care. For hospitals to achieve these goals, they must develop and implement an initiative known as a Medical Equipment Management Program (MEMP), which outlines the actions that must be taken to mitigate the risks associated with specific medical devices. Gear. Inspection and preventive maintenance are essential parts of that plan and must be regularly reviewed and updated to keep up with the rapid technological advances in medical devices and the growing expectations of healthcare organizations. According to the latest information gathered on the subject, Indian public hospitals currently do not have a comprehensive metric or "framework to assess the performance of MEMS. This study is carried out with the aim of developing a model or framework for MEMS that can serve as an integrated tool, using key performance indicators (KPIs) as the unit of measurement".
Nadiem Makarim’s Speech in the Freedom of Learning Series: Critical Discourse Analysis of Social Situations and Ideology

This research aims to (1) Explain the transitivity system in Nadiem Makarim speech, (2) Explains the ideology reflected in the speech text. The main character's speech at this time is frequent used as topic study in study Language. A number of study cross disciplinary appear along development role And definition The proposed transitivity system Halliday is an analytical tool for analyzing linguistic data that has been used by Fairclough in his theoretical framework of critical discourse analysis. Based on the purpose of describing the transitivity system and Nadiem Makarim's speech ideology, this research can be categorized as descriptive research. Research result shows the six processes used by Nadiem Makarim in representing his experience, viz material processes, mental processes, relational processes, verbal processes, behavioral processes (behavioral), existential processes. The process that is often used by Nadiema Makarim is the material process followed by the relational process and mental processes. In expressing his ideas, Nadiem Makarim uses a lot of material processes as well show in principle that more Good Act than only just speak. Nadeim Makarim delivered his speech on National Teacher's Day in 2019. And then continued with Nadiem Makarim's speech at the 2020 HGN in the midst of the pandemic.
Role of Text Mining in Extracting Valuable Information from Text Data

Text mining has become a popular field with the rapid development of information technology and the extensive amounts of unstructured text data such as web pages, social network sites and technical documentations. This data contains a lot of information, which is extremely difficult to deal with the huge number and various forms. Extracting and analysing important information from massive data for example in automotive industries has become our major problem. The main aim of text mining is to extract important information from massive text data that are difficult to be handled manually with error-free. In this paper, the fundamental concept is based on Euclidean distance in finding the similarity between words. Finally, a set of data is used to describe the similarities, distances and frequencies between several words. Word cloud, bar plot, dendrogram and co-occurrence network are also presented to illustrate the behaviour of the text data.
Utilization of the Kinemaster Application as a Learning Media

This pandemic has had a considerable impact, disrupting education. However, the implementation of learning must continue. So, for that, teachers are required to be able to make learning videos that are used as practical, exciting learning media so that they are easy to understand. This is so that students can learn as effectively and efficiently as possible in their homes. The purpose of this is so that teachers can improve their ability to make learning media in the form of learning videos using the Kinemaster learning application. Since April 2020, there have been 100,000,000 students ranging from elementary school to tertiary levels have experienced this pandemic, which caused them to be unable to carry out face-to-face learning. Teachers and students are required to adapt to online or online learning. Moreover, of course, teachers are demanded to be more creative, active and innovative in providing materials or teaching materials later; therefore, the ability of teachers to process IT is very much needed in supporting this online learning. Good IT skills and utilization in online learning are required at all levels of education. Still, in online or online learning, videos or creative teaching materials are very much needed, which will take advantage of the sophistication of IT.
Some games via semi-generalized regular spaces

In this research, a new application has been developed for games by using the generalization of the separation axioms in topology, in particular regular, Sg-regular and SSg- regular spaces. The games under study consist of two players and the victory of the second player depends on the strategy and choice of the first player. Many regularity, Sg, SSg regularity theorems have been proven using this type of game, and many results and illustrative examples have been presented.
A Novel Group Signature Scheme with Time-Bound Keys for Blockchain

With the development of blockchain technology, there is an increasing call for privacy protection and supervision of blockchain transactions. We propose a novel privacy protection scheme for group signature. Firstly, we design a revocation algorithm based on hierarchical time tree, that can shorten the size of validity period and support the discontinuity of member time period. Secondly, we provide an anonymous certificate to protect the privacy of group members' identity. Thanks to the combination of signature scheme and blockchain, our scheme can guarantee that the identity of any user will not be revealed during the whole process. Moreover, with the features of group signature, we can also enable the tracking and revocation of risky transactions and provide security for on-chain data. Finally, our experimental evaluation of elliptic curves based on BN-382 bit prime proves that our scheme is feasible and efficient.
Sequential stochastic blackbox optimization with zeroth-order gradient estimators

&lt;abstract&gt;&lt;p&gt;This work considers stochastic optimization problems in which the objective function values can only be computed by a blackbox corrupted by some random noise following an unknown distribution. The proposed method is based on sequential stochastic optimization (SSO), i.e., the original problem is decomposed into a sequence of subproblems. Each subproblem is solved by using a zeroth-order version of a sign stochastic gradient descent with momentum algorithm (i.e., ZO-signum) and with increasingly fine precision. This decomposition allows a good exploration of the space while maintaining the efficiency of the algorithm once it gets close to the solution. Under the Lipschitz continuity assumption on the blackbox, a convergence rate in mean is derived for the ZO-signum algorithm. Moreover, if the blackbox is smooth and convex or locally convex around its minima, the rate of convergence to an $ \epsilon $-optimal point of the problem may be obtained for the SSO algorithm. Numerical experiments are conducted to compare the SSO algorithm with other state-of-the-art algorithms and to demonstrate its competitiveness.&lt;/p&gt;&lt;/abstract&gt;
Exploiting Item Relationships with Dual-Channel Attention Networks for Session-Based Recommendation

Session-based recommendation (SBR) is the task of recommending the next item for users based on their short-term behavior sequences. Most of the current SBR methods model the transition patterns of items based on graph neural networks (GNNs) because of their ability to capture complex transition patterns. However, GNN-based SBR models neglect the global co-occurrence relationship among items and lack the ability to accurately model user intent due to limited evidence in sessions. In this paper, we propose a new SBR model based on Dual-channel Graph Representation Learning (called DCGRL), which well models user intent by capturing item relationships within and beyond sessions respectively. Specifically, we design a local-level hypergraph attention network to model multi-grained item transition relationships within a session by using sliding windows of different sizes. The experiments demonstrate the effectiveness and the efficiency of our proposed method compared with several state-of-the-art methods in terms of HR@20 and MRR@20.
Lazy Machine Unlearning Strategy for Random Forests

Removing the impact of some revoked training data from the machine learning models, i.e., machine unlearning, is a non-trivial task, which plays a pivotal role in fortifying the privacy and security of ML-based applications. This paper focuses on the problem of machine unlearning for random forests efficiently, with the streaming setting of revocation requests. The existing works are all devoted to speeding up the unlearning process of a single revocation request, none of works target at the streaming scenario. A straightforward solution is to carry out the unlearning technique tailored for a single request immediately when a new revocation request arrives. Undoubtedly, that is time-inefficient, since the time cost is proportional to the number of requests involved in the streaming. To solve this problem, this paper proposes a lazy unlearning strategy to carry out the unlearning operations involved in different revocation requests in a single batch, so as to avoid redundant computations and implement computation sharing. In particular, we adopt a node level unlearning policy, which carries out the unlearning operations on demand of the testing request by checking whether the revocation requests on this node can affect the inference of the testing request. Experiments on several real datasets show that compared to the baseline, lazy unlearning strategy can improve the unlearning efficiency by 1.1X-4X on different datasets and the number of retraining times is reduced to 1/4 on average.
Leveraging the OPT Large Language Model for Sentiment Analysis of Game Reviews

Automatically extracting players' sentiments about games can help game developers to better understand the aspects of their games that players like or dislike. Our prior work showed that traditional sentiment analysis techniques do not perform well on game reviews. However, the Natural Language Processing (NLP) field has seen a steep progress in recent years. In this letter, we follow up on our prior work and investigate how a state-of-the-art large language model (OPT-175B) performs on the sentiment classification of game reviews. We manually analyze the game reviews wrongly classified by OPT-175B to better understand the issues that affect the performance of that model and how those issues compare to the challenges faced by traditional classifiers. We found that OPT-175B achieves (far) better performance than traditional sentiment classifiers, with a 72%-increased F-measure and a 30%-increased AUC compared to the best traditional classifier studied in our prior work. We also found that common challenges of traditional classifiers, such as reviews with game comparisons and negative terminology, have been mostly solved by the OPT-175B model.
ENHANCING DATA PRIVACY IN GOVERNMENT ORGANIZATIONS: A COMPARATIVE ANALYSIS AND IMPLEMENTATION OF OPTIMAL CERTIFICATELESS SCHEMES

The rapid expansion in Technology has transformed our everyday objects into interconnected entities, globally changing connectivity through the Internet and reshaping human interactions with their surroundings. This paradigm shift has occasioned the need for various networked infrastructures to facilitate and improve innovative services as well as enhance the flexibility and efficiency in this human- environment interactivity. However, this digitalization drive has also brought forth a range of security concerns that cannot be neglected. This paper emphasizes on the role of certificateless systems in addressing security challenges posed by the digital realm on government organizations based on four fundamental security measures. These measures include confidentiality, integrity, authentication, and non-repudiation. The paper aimed at safeguarding data from unauthorized access, ensuring data integrity during transit, validating user identity and providing data integrity. To enhance these security aspects, the study advocates the adoption of certificateless encryption techniques to uphold data confidentiality and employs digital signature techniques to guarantee integrity, accuracy, and non-repudiation. And the assurance that the sender of information is provided with proof of delivery and the recipient is provided with proof of the sender's identity. The study’s main achievement a comparative analysis of four certificateless schemes to ensure data privacy from malicious attacks, Implementation of the best scheme using an elliptic curve digital signature and data-at-rest encryption. This ensured secure data privacy in transit and at retention to enhance confidentiality, integrity, and authenticity.
Creativity in Art Education as Environment for Realisation of Professional and Creative Potential of the Individual

The purpose of the article is to consider the issue of creativity in modern art education, which forms a holistic environment within which the realisation of the professional and creative potential of the individual becomes possible. The research methodology is based on systemic and value-based approaches, as well as on the application of analytical, synthetic, and cultural methods, which will allow a comprehensive consideration of the above issues and obtaining relevant research results. The scientific novelty lies in the theoretical understanding of issues of formation and development of creativity and creative environment of artistic educational institutions, which contributes to the realisation of the creative potential of the individual and the acquisition of professional competences. Conclusions. The study has revealed an increase in the role of the creativity component in the formation of a holistic space of art education, as well as the transformation of the paradigm in the field of education based on the general principles of humanisation and culturalisation, based on a comprehensive understanding of human existence in the world, their relationship with the environment and the value dimensions of personal development. It is proven that the development of the creative potential of the individual is carried out under the influence of a creative environment, which, in turn, becomes both a condition and a result of the activity of a creative individual. The basis of creativity is the inner potential of the individual, their professional self-realisation and the ability to generate new knowledge, which is largely formed in the environment of art education. Accordingly, art education institutions have the potential to form and/or transform into creative hubs for learning and creating an open creative environment in the process of creative activity, where an innovative product is created and space becomes creative.&#x0D; Key words: creativity, art education, creative space, creative personality, creative environment, art education institutions.
Blockchain‐assisted twin migration for vehicular metaverses: A game theory approach

Abstract As the fusion of automotive industry and metaverse, vehicular metaverses establish a bridge between the physical space and virtual space, providing intelligent transportation services through the integration of various technologies, such as extended reality and real‐time rendering technologies, to offer immersive metaverse services for vehicular metaverse users (VMUs). In vehicular metaverses, VMUs update vehicle twins (VTs) deployed in RoadSide Units (RSUs) to obtain metaverse services. However, due to the mobility of vehicles and the limited service coverage of RSUs, VT migration is necessary to ensure continuous immersive experiences for VMUs. This process requires RSUs to contribute resources for enabling efficient migration, which leads to a resource‐trading problem between RSUs and VMUs. Moreover, a single RSU cannot support large‐scale VT migration. To this end, we propose a blockchain‐assisted game approach framework for reliable VT migration in vehicular metaverses. Based on the subject logic model, we first calculate the reputation values of RSUs considering the freshness of interaction between RSUs and VMUs. Then, a coalition game based on the reputation values of RSUs is formulated, and RSU coalitions are formed to jointly provide bandwidth resources for reliable and large‐scale VT migration. Subsequently, the RSU coalition with the highest utility is selected. Finally, to incentivize VMUs to participate in VT migration, we propose a Stackelberg model between the selected coalition and VMUs. Numerical results demonstrate the reliability and effectiveness of the proposed schemes.
Gender, Age, and Levels of Physical Exercise Related Risk Factors effecting Sleep among Young Adult Varsity Student-Athletes

This study aimed to examine risk factor of sleep problems related with gender, age, levels of physical exercise among varsity student-athletes. Sample included 195 varsity student-athletes from six universities. Data gathering included personal and demographic information, physical exercise level, and sleep health using cross-sectional design. The descriptive analysis showed that over 50 percent of the entire sample was sleeping less than 7 hours per night. In addition, one-fourth of the participants were classified as poor sleepers. Mann-Whitney test indicated that female gender compared with male, lower age compared with greater age, low to moderate levels of physical exercise relative to high level of exercise were more vulnerable to experience sleep problems. These factors should be taken into account to counter sleep issues in varsity student-athletes.
EvoS&amp;R: Evolving Multiple Seeds and Radii For Varying Density Data Clustering

Density clustering has shown advantages over other types of clustering methods for processing arbitrarily shaped datasets. In recent years, extensive research efforts has been made on the improvements of DBSCAN or the algorithms incorporating the concept of density peaks. However, these previous studies remain the problems of being sensitive to the parameter settings, and some of them will stuck in weak results when encountering the situations of varying-density distributions. To overcome these issues, we propose an evolution framework named EvoS&R that evolves multiple seeds and the corresponding radii for varying-density data clustering. Compared with the traditional methods, EvoS&R handles the parameter tuning and multi-density fitting problems in an integrated and straightforward manner. Note that, however, the underlying task in EvoS&R is a mixed-variable optimization problem that is challenging in nature. We specifically design a hybrid encoding differential evolution algorithm with novel encoding, mutation, etc., to solve the optimization problem efficiently. Extensive experiments on density-based datasets shows that our algorithm outperforms the other state-of-the-arts in most cases, which validates the effectiveness of the proposed method.
Urgensi Mindset Tumbuh (Growth Mindset) Dalam Meningkatkan Motivasi Belajar Peserta Didik

The urgency of the growth mindset on students' learning motivation is something that needs to be studied, because motivation is influenced by mindset. This study aims to determine the extent to which the urgency of the growth mindset affects students' learning motivation. This study used a qualitative research method with a library research approach (literary study). Literature studies in this paper are written works that have been published, in this case in the form of books and articles that have been published in a journal. To draw conclusions or results, this literature study goes through several stages, namely: ensuring the sources reviewed are in line with the research title. Furthermore, the contents in the literature are adjusted to the research title. Then finally, the contents of the source in accordance with the research title, a summary is made so as to produce a new idea. The results of this study indicate that the growth mindset possessed by each student has the power to bring out student behavior. The strength of the growth mindset possessed by students will make students have positive learning concepts and behaviors. In the sense that students go through the learning process with the belief that intelligence can be developed through serious learning and experiences
The number of codes over rings of order $ 4 $ containing a hull of given type

We study the hull, that is the intersection of a code with its orthogonal, of both linear and additive codes over the rings with unity of order $ 4, $ where the orthogonal is the Euclidean orthogonal for linear codes and for additive codes it is determined using characters. We relate the hull of the code with the hull of its image under the corresponding Gray map and use this to count the number of codes with a given hull for additive codes for the rings with characteristic $ 2 $. We investigate the codes over these rings which have a hull of given type which gives the cardinality of the hull.
Relationship between Physical Activity and WhatsApp Addiction among Athletes and Non Athletes of University Level Early Adults

This university-level study examined into the connection between physical activity and WhatsApp addiction in young individuals. 100 university student-athletes and 100 university student-non-athletes from three universities participated in a cross-sectional survey. Data was collected using the demographic factors, Bergen's Social Media Addiction Scale, and short version of (Ipaq) International Physical Activity Questionnaire. Mean WhatsApp addiction score for non-athletes was substantially greater than that of their peers who were athletes, according to an examination of independent samples T-test results. The findings suggested that physical activity can aid in reducing university students' addiction to WhatsApp. It is also likely to imply that interventions aimed at promoting physical activity may work as a deterrent to addictive social media behavior in young adults enrolled in universities, such as WhatsApp addiction.
Anomaly Detection of Quenches in Superconducting Magnets Acoustic Data

and small cryostat thickness drove the design to challenging technical solutions, suggesting that Lorentz forces due to transport currents and eddy currents during quench and various failure scenarios are analyzed. The paper covers the magnet system quench analysis using the OPERA3d Quench code.