Reviewerly/exHarmony huggingface dataset:
PENGEMBANGAN LEMBAR KERJA SISWA BERBASIS PENDEKATAN OPEN ENDED PADA MATERI RELASI DAN FUNGSI SISWA KELAS VIII SMP

This study aims to develop worksheets on relations and functions for class VIII students of SMPN 2 Lubuklinggau and to produce valid and practical student worksheets on relations and functions for class VIII students at SMPN 2 Lubuklinggau. This research is a development research with a 4-D (Four-D) development model. This model consists of 3 stages of development, namely the Define stage, Design stage, and Develop stage. The Define stage includes: a) initial analysis, b) student analysis, c) task analysis d) concept design, and e) formulate objectives. The process at the Design stage includes: a) format selection, and b) initial design. The process at the Develop stage includes: a) validation by experts followed by revisions, b) product trials. The product of this research is in the form of student worksheets on Relations and Functions with an open ended approach. The results showed that: (1) Validity showed that the developed student worksheets received a very valid category in the language feasibility component with an average score of 4.16, in the material feasibility component received a very valid category with an average score of 4, 00, while the media feasibility component gets a very valid predicate with an average score of 4.44. (2) the quality of student worksheets seen from the practicality aspect is included in the criteria of "very practical" with an average score of 3.52 which is determined based on the results of the student and teacher practicality questionnaire sheets.
Economic aspects of the search for new energy sources,caused by the transformation of atomic electronic configurations

Energy sources are considered in connection with fundamental electromagnetic interactions. The hypothesis of the possibility of obtaining a fundamentally new energy source by converting atomic electronic configurations, first formulated in the early XX century by the discoverer of the electron J.J. Thomson, is analyzed. It is predicted that research and development related to electromagnetic interaction can lead to the emergence of new highly efficient and economical energy sources.
Defensive Countermeasures Towards Addressing Cloud Security Attacks

&lt;p&gt;The multi-tenant resource-sharing environment of cloud computing among multiple users and vulnerabilities of virtual machines (VM)s and physical machines prompt unauthorized access to users' confidential data and excess power consumption and resource wastage. This paper presents a comparative survey study of securing cloud resource strategies to address this critical issue. Specifically, this study focuses on Defensive Strategies associated with cloud resource allocation with their pandect comparative summary.&lt;/p&gt;
COVID-19 Pandemic Fuels Rise in Cybercrime

Since the declaration of COVID-19 as a pandemic by the World Health Organization, economies and daily life in many countries have been significantly affected. To mitigate the spread of the virus, various measures such as travel restrictions, lockdowns, and stay-at-home orders have been implemented worldwide. Consequently, there has been an increased reliance on internet-based methods to ensure public safety and continue essential activities. However, this increased online presence has also provided cybercriminals with opportunities to engage in malicious activities, exploiting the pandemic for financial gain. This study aims to provide a brief review of the cyber activities associated with the COVID-19 outbreak and investigate the extent of cybercrime during this period. A cross-sectional survey was conducted online, involving 400 internet users, to assess the occurrence of cybercrime during the pandemic. The findings indicate that victims of cybercrime encompass not only individuals who use online directories but also those engaging in routine internet searches and email communications. The study reveals that cybercrime has a detrimental impact on users' online experiences, potentially leading them to limit their online activities and resort to offline alternatives. The objective of this research is to comprehensively study cyber-attacks, analyzing the concept and variations of cyber-attacks before and during the COVID-19 pandemic era, in order to identify patterns, trends, and the overall impact of cybercrime on individuals.
Multi-Party Cross-Chain Asset Transfers

&lt;p&gt;With the growing interest in blockchain technology, researchers and developers in different industries are shifting their attention to creating interoperability mechanisms. Existing mechanisms usually encompass asset exchanges, asset transfers, and general data transfers. However, most of the solutions based on these mechanisms only work for two permissionless blockchains falling short in use cases requiring more complex business relationships. Also, contrary to existing legacy systems, there is little standardization for cross-chain communication. Here we present MP-SATP, a resilient multi-party asset transfer protocol built on top of the Secure Asset Transfer Protocol (SATP). Furthermore, we enhance SATP's crash recovery mechanism that directly influences the reliability and performance of our solution. Using MP-SATP, we show how to perform N-to-N resilient asset transfers in permissioned environments by decoupling them into multiple 1-to-1 asset transfers. Our results demonstrate that the latency of the protocol is driven by the latency of the slowest 1-to-1 session; and how the usage of backup gateways avoid the overhead caused by rollbacks. Enterprise-grade environments such as supply-chain management systems can immediately leverage our solution to perform atomic multi-party asset transfers as shown by our use case.&lt;/p&gt;
Model of project-oriented management of scientific activity of higher education institutions within innovative programs

It is proved that there is an effective socioeconomic development driver of the state considering carrying out the innovative activity.It is the implementation of the research project products into practice with the commercialization of the scientific results.The reasons for the negative trends in the commercialization of the results of research projects in Ukraine are the lack of funding and the organizational reason.It is impossible to achieve results in the field of scientific research and their introduction into production without changing the management system of research activities of higher education based on the use of a scientifically based methodology of project-oriented management.The purpose of the article is to develop a model of projectoriented management of scientific activities of higher education in the implementation of innovative programs.The subject of the research is the methods and models of managing research projects within the framework of innovative programs for the development of higher education.The following research tasks will be set: analysis of the world and national experience in the implementation of innovative activities with the identification of the scientific component, determination of the role of higher education institutions in the implementation of research projects, identification of participants involved in innovative activities, development of a conceptual model of project-oriented management of higher education in the framework of the innovative programs.Resultsbased on the analysis of global and national trends in the development of innovative activities, it was found that the application of the methodology of project management of scientific activities will increase the efficiency of the commercialization of products of research projects.In the work, based on the methodology of project and program management, the concepts of research, innovative project, an innovative program and a portfolio of research projects are clarified.It is proposed to use the triple helix model in the implementation of innovative programs through the complex interaction of the university, business structures and government bodies, considering the strategic goals of each stakeholder.It is proposed to consider the scientific activity of higher education as the implementation of a portfolio of research projects, which made it possible to develop a conceptual model of project-oriented management of the scientific activity of the university within innovative programs.
Why open science is primarily a labour issue

Reforming research assessment and culture is a hot topic in higher education, particularly how these issues relate to research funding. I discussed the HELIOS initiative in my last post, which is a funder-led approach to incentivising open science practices in North American tenure and promotion guidelines. Now, in the past week, EU science ministers have agreed on a plan to facilitate coordinated reform of research assessment processes.
Quantification of Training in Human Thought using Chaos Theory: Degree of Decreasing Entropy as an Indicator

Many analytical methods used to quantify the technical training of human resources have been reported, but they are poor at assessing the training of human thought. Chaos theory and the degree of decreasing entropy have not yet been used in such analytics, although all phenomena—except for those in a completely fixed state (e.g., mathematics, historical facts, and true natural laws) or a random state (e.g., dialing a random digit)—are based on chaos theory. Chaos theory must therefore be considered in the quantification of the technical and intellectual training of human resources because human thinking is involved. This report compares a method for chaos theoretical quantification of human resource training to methods that do not involve chaos theory. The development of the ability to change to a fixed state from a chaotic state beyond the Feigenbaum point is the goal for the training in thinking; this process, which involves a decrease in entropy, is the most difficult, and important process in such training. In a chaotic state with an infinite number of solutions, humans can never show their own state using any method. In many reports, each goal in a fixed state is considered after thinking has been rearranged; however, a chaotic state in human thinking can never be expressed using indices such as productivity, efficiency, or job satisfaction. Indeed, many reported results are merely a part of human resource training, but the change of entropy in the fixed state is small (this corresponds to the “creativity” of artificial intelligence). By contrast, the change in entropy from a chaotic state to a fixed state is large, and this corresponds to human intuitive. Considered in terms of chaos theory, goal achievement for thinking must therefore be quantified in terms of the degree of decreasing entropy (i.e., the problem-solving speed, and degree of problem difficulty). This type of problem-solving speed is not about achieving ta goal but about creating a new idea. The concrete methods considered are the Schedule for the Evaluation of Individual Quality of Life-Direct Weighting method, the Kawakida Jiro method, and the Mandala chart. Based on the findings presented here, considering entropy change in the chaotic state should become an index for evaluating the creation of a new idea instead of the repetition of an existing idea, as this type of thinking is beyond the scope of artificial intelligence. Given that almost all natural phenomena, including human thinking, are based on chaos theory, using this theory can promote scientific development in all academic fields.
Long- and Short-Term Sequential Recommendation Model Based on Transformer and Mixture of Experts

Sequential recommendation is the important topic of current recommendation system research. Deep learning methods such as recurrent neural networks and attention mechanisms are used to extract users interests from their historical behaviors, which have realized the satisfying recommendation results. However, the successive trace of historical behaviors brings the burden of the model input. The simplify of historical behaviors cannot extract the characteristics comprehensively. This paper proposes a long-term and short-term sequential recommendation model based on Transformer and Mixture of Experts (LSSR-TM). Firstly, in the short-term interest layer, LSSR-TM combines Transformer for model training and considers timestamps to effectively capture the users short-term preferences. Secondly, the long-term interest layer involves the Mixture of Experts model via multiple behavioral sequence samples of the same user. Finally, an adaptive gating unit is used to adjust the ratio of long-term and short-term interests to complete the final recommendation. We conduct extensive experiments on four realistic datasets and the results show that our proposed approach outperforms state-of-the-art baselines in capturing users long-term and short-term preferences.
How to shed light on in-house publication review processes?

&lt;em&gt;This post makes a case for universities investing in people and processes for reviewing research in house before publication. This idea has no doubt been proposed before and is probably already a feature of some academic institutions, but I wanted to clarify here why I think it would benefit academic research. &lt;/em&gt; High-energy physics research is often held up as the archetypal open science discipline.
Novel low-pass two-dimensional Mittag-Leffler filter and its application in image processing

&lt;p&gt;This express brief presents an innovative Mittag-Leffler two-dimensional filter and its application in the image processing. The proposed filter leverages the utilization of a Mittag-Leffler function within the probability density function. It introduces three adjustable parameters that enable the manipulation of the curve shape and the filter's forgetting factor. Moreover, a two-dimensional Mittag-Leffler distribution was defined and used for the first time in an image filter. By conducting a comparative analysis against conventional filtering techniques, the paper showcases the distinct advantages of the proposed filter through illustrative examples. Additionally, the paper provides detailed implementation explanations and presents the Matlab function corresponding to the proposed two-dimensional filter.&lt;/p&gt;
Leaking Secrets in Homomorphic Encryption with Side-Channel Attacks

Abstract Homomorphic encryption (HE) allows computing encrypted data in the ciphertext domain without knowing the encryption key. It is possible, however, to break fully homomorphic encryption (FHE) algorithms by using side channels. This article demonstrates side-channel leakages of the Microsoft SEAL HE library. The proposed attack can steal encryption keys during the key generation phase by abusing the leakage of ternary value assignments that occurs during the number theoretic transform (NTT) algorithm. We propose two attacks, one for -O0 flag non-optimized code implementation which targets addition and subtraction operations, and one for -O3 flag compiler optimization which targets guard and mul root operations. In particular, the attacks can steal the secret key coefficients from a single power/electromagnetic measurement trace of SEAL’s NTT implementation. To achieve high accuracy with a single-trace, we develop novel machine-learning side-channel profilers. On an ARM Cortex-M4F processor, our attacks are able to extract secret key coefficients with an accuracy of 98.3% when compiler optimization is disabled, and 98.6% when compiler optimization is enabled. We finally demonstrate that our attack can evade an application of the random delay insertion defense.
Online Intelligent Display Platform for English Teaching Communicative Awareness in Vocational Colleges Based on Multi-Dimensional Cross-Cultural Data Information Mapping Algorithm

Aiming at the problems of low mining accuracy, slow running speed, and large memory footprint when mining complex and large-scale data sets in biological information networks, a multi-dimensional data mining algorithm for biological information networks based on association rule mapping is proposed.At the same time, it analyzes the current situation of English teaching in higher vocational colleges and the problems existing in cultural teaching, which leads to how to cultivate students' cultural communication awareness and improve students' cross-cultural communication ability in English teaching activities in higher vocational colleges., The online and offline college English blended teaching mode of the network platform, and the online and offline college English blended teaching strategy of the network platform is proposed.
Parents' Perception of Digital Media Usage as Home- Based Learning Platform towards Students' Learning Comprehension During Covid-19 Pandemic

During the Covid-19 pandemic, many sectors have experienced redundancy including the education sector.The lockdown phase that was forced by the government influenced the school institution and university to be closed to minimize the physical contact between students and teachers due to transmission of diseases.The children across the country are given alternate resources, some online, to study outside of the classroom.They are unable to attend the real classroom as before which led to a digital media platform as a tool in continuing the learning process.It makes the traditional teaching and learning methods no longer options of learning methods.This study aimed to examine parents' perception of media usage as a home-based learning platform, their involvements with primary school students and satisfaction level with the effectiveness of digital media usage as a homebased learning platform towards students' learning comprehension.This study used a quantitative method and a purposive sampling technique.There were 1161 respondents who have been selected among Kuala Selangor's citizens via an online survey.The findings reported that there are positive responses and significant relationship between digital media usage as a home-based learning platform and learning comprehension levels among parents and their primary school students during the COVID-19 pandemic.
An Insight into Mall-Integrated Language Learning Strategies of Good Language Learners

The dominance of English language around the world is enormous, and to become a competent and proficient student, it is essential to master all four language skills, particularly listening and speaking.English as a Second Language (ESL) learners can effectively acquire the language through Language Learning Strategies with technological advances.Good Language Learners could identify suitable Language Learning Strategies and utilize different learning strategies to master language skills successfully.This study, therefore, aimed to investigate the highly employed Language Learning Strategies by Year 6 ESL good language learners to enhance their listening and speaking abilities using Mobile-Assisted Language Learning (MALL).This quantitative research collected data from 50 Primary advanced ESL learners from selected schools located in Melaka, Malaysia through the administration of a survey questionnaire consisting of 3 parts with 5 Likert scales.The data collected was then analysed using SPSS version 26 and descriptive statistics.The study's findings revealed that the highly preferred MALL-integrated Language Learning Strategies by the Good Language Learners in the clustered schools to enhance their listening skills are the memory-related and social strategies.They used social and metacognitive skills primarily as they engaged in and developed self-direction in their learning through the integration of MALL to improve their speaking capabilities.These outcomes could provide educators with helpful insights for assisting students' language skills development and encourage the adoption of MALL in ESL classrooms.
A Universal Fairness Evaluation Framework for Resource Allocation in Cloud Computing

Abstract: Machine learning is nowadays ubiquitous, providing mechanisms for supporting decision making that leverages big data analytics. However, this recent rise in importance of machine learning also raises societal concerns about the dependability and trustworthiness of systems which depend on such automated predictions. In cloud computing, fairness is one of the most significant indicators to evaluate resource allocation algorithms, which reveals whether each user is allocated as much as that of all other users having the same bottleneck. However, how fair an allocation algorithm is remains an urgent issue. In this paper, we propose Dynamic Evaluation Framework for Fairness (DEFF), a framework to evaluate the fairness of an resource allocation algorithm. In our framework, two sub-models, Dynamic Demand Model (DDM) and Dynamic Node Model (DNM), are proposed to describe the dynamic characteristics of resource demand and the computing node number under cloud computing environment. Combining Fairness on Dominant Shares and the two sub-models above, we finally obtain DEFF. In our experiment, we adopt several typical resource allocation algorithms to prove the effectiveness on fairness evaluation by using the DEFF framework.
A Virtual Machine Placement Algorithm for Resource Allocation in Cloud-Based Environments

This research paper presents a Virtual Machine Placement algorithm designed to optimize the service allocation process, which is one of the most significant challenges in resource allocation and management. Our solution employs a ranking strategy based on global resource scarcity, where we consider all the information contained in datacenter hosts during the allocation process. We compare our approach with two different literature-based methods regarding task allocation time and the number of allocated resources. To evaluate our proposal, we consider scenarios in which requisitions arrive at different times or simultaneously. The first scenario represents a realistic situation where no knowledge is available regarding task arrival. Meanwhile, the second scenario represents a dense situation where many tasks arrive together. Our evaluations show that our solution yields better results in both cases, especially when requisitions arrive simultaneously. Our solution reduced the allocation time by around 25% on average and achieved better load distribution among hosts.
Enabling Self-Driving Networks with Machine Learning

This work aims to enable self-driving networks by addressing the lack of trust that network operators have in Machine Learning (ML) models for networking problems. To achieve this, we propose a natural-language conversational interface (LUMI) and a new ML pipeline that uses techniques from the emerging field of eXplainable Artificial Intelligence (XAI) to scrutinize models. We also propose a new XAI method called TRUSTEE to extract explanations from any given black-box ML model in the form of decision trees of manageable sizes. Our results indicate that ML models used in networking problems need to be put under proper scrutiny and corrected to fulfill their tasks properly.
Software Engineering Education in the DevOps Era: Experiences and Recommendations

DevOps has reached the mainstream, in part, because it proposed a way to solve the last mile of the software delivery process. It brought to the industry concrete solutions to some concerns that software engineering and academia have traditionally ignored. The popularity and success of DevOps got the attention of the academia and some universities have started to include DevOps related content in their programs. After doing our own experience, we found out that introducing DevOps is not as simple as adding a new course. In fact, it requires a major redesign of the Software Engineering curriculum. In this article we share some key ideas and recommendations to include DevOps in Software Engineering programs.