Reviewerly/exHarmony huggingface dataset:
Single Point Integration a Monolithic Application for Versatile Multifunctionality

In today's digitally interconnected world, the management of multiple social media accounts has become increasingly complex. The need for a unified solution that simplifies access to diverse platforms and centralizes notifications has led to the development of a groundbreaking application. This application offers a seamless and user-friendly experience, enabling individuals and businesses to effortlessly consolidate their social media presence in one place. With the capability to access and switch between various social media accounts at the click of a button, users can streamline their online interactions, saving time and improving overall efficiency. This paper introduces the concept and features of this innovative application, highlighting its potential to revolutionize the way we engage with our digital networks while enhancing convenience and productivity. Keywords: Social Media Management, Unified Solution, Centralized Notifications, User-Friendly Interface, Consolidation of Accounts, Diverse Platforms, Efficiency Optimization, Digital Networks, Time-Saving, Online Interactions, Digital Presence, Seamless Access, Switching Between Accounts, Streamlining, Multifunctional Application, Interconnected World, Convenience Enhancem ent, Productivity Improvement, Ground breaking Technology, Social Media Engagement.
Isomorphic Graph Embedding for Progressive Maximal Frequent Subgraph Mining

Maximal frequent subgraph mining (MFSM) is the task of mining only maximal frequent subgraphs, i.e., subgraphs that are not a part of other frequent subgraphs. Although many intelligent systems require MFSM, MFSM is challenging compared to frequent subgraph mining (FSM), as maximal frequent subgraphs lie in the middle of graph lattice, and FSM algorithms must explore an exponential space and an NP-hard subroutine of frequency counting. Different from prior research, which primarily focused on optimal solutions, we introduce pmMine, a progressive graph neural framework designed for MFSM in a single large graph to attain an approximate solution. The framework combines isomorphic graph embedding, non-parametric partitioning, and an efficiently top-down pattern searching strategy. The critical insight that makes pmMine work is to define the concepts of rooted subgraph and isomorphic graph embedding, in which the costly isomorphism subroutine can be efficiently performed using similarity estimation in embedding space. In addition, pmMine returns the patterns identified during the mining process in a progressive manner. We validate the efficiency and effectiveness of our technique through extensive experiments on a variety of datasets spanning various domains.
The Implementation of Digital Multilingual Thematic Dictionary towards The Fourth Grade Students’ Literacy Skill: An Experimental Study

The study aims to investigate whether there is a significant impact on utilizing a digital multilingual dictionary for fourth grade students’ literacy skills. The method of this study is a quasi-experimental and quantitative research approach. The samples were taken using statistical matching techniques by Fraenkel et al., (2012). The samples are the fourth grade students of SDN 2 Pacung as the control group and SDN 1 Banjar as the experimental group. The two groups received three treatments with three themes including: Greeting &amp; Introduction, Family, and Things in the Classroom. The instrument of this study was a students’ literacy test which consisted of a pre-test, treatment, and post-test. To analyze the data quantitatively, researchers used descriptive statistical analysis, inferential statistics, and the N-Gain score test. The results from the N-Gain score of the controlled group were 50.5% and 62,71% for the experimental group. It revealed that the use of a digital multilingual thematic dictionary was categorized as moderately effective compared to the printed version in improving fourth grade students’ literacy skills compared to the controlled group who were treated by the printed version. Therefore, the digital multilingual thematic dictionary significantly affects fourth grade students’ literacy skills.
Examining Coherence Markers Use on the Abstracts of English Graduate Students’ Final Academic Writing

This research aimed to describe the use of Coherence in the thesis abstracts of the graduate program of the English Education Department of UIN Syarif Hidayatullah Jakarta. The descriptive qualitative analysis was used as the methodological design of this research that attempted to describe the phenomenon of discourse analysis, especially about coherence in the abstracts of the graduate program of the English Education Department of UIN Syarif Hidayatullah Jakarta. Some steps were conducted to collect the data, in which ten chosen abstracts were collected from the repository of UIN Syarif Hidayatullah Jakarta and analyzed to examine the types of Coherence proposed by Kehler (2002), the topical subject and the topical progression to see how they build coherence in the abstracts. This research shows that four out of eleven types of Coherence proposed by Kehler (2002) are used in twenty abstracts, including Parallel, Contrast, Generalization, and Explanation. Meanwhile, the topical subject shows mood as the dominant topical subject with a 91.74% percentage. In Addition, Sequential progression is a dominant Type of Topical Progression. Furthermore, Discourse Topic is hard to analyze because the abstracts only have one paragraph, so the discourse topic is analyzed based on the terms that frequently emerge to interpret the discourse topic. Finally, this study is expected to contribute to the development of language study, especially for Discourse Analysis, and it is also hoped to contribute to the education field, especially for university students, to improve the quality of English writing in abstracts of their research papers.
Central Bank Digital Currencies: the Effect on the Banking System

The long-standing autonomy of commercial banks has been challenged in recent decades by various new concepts, such as open banking and decentralised finance, while the potentially wide adoption of cryptocurrencies, as well as the introduction of central bank digital currencies (CBDC), threatens to disrupt core areas of banking business: deposit collection, loan provision and payment execution, and in turn to create much more fragmentation in the sector. Likewise, CBDCs are in the nascent stage, with the first steps being laid out in the financial system, so the understanding of the drawbacks arising and the expected challenges from CBDC is quite limited. In this research, the scientific literature about CBDCs is analysed, using the extensive and systematic study of available research publications, their categorisation, and summaries. This paper provides a review of CBDCs and an assessment from a theoretical point of view of what kind of impact it could potentially generate for a solid and grounded banking system. In the end, depending on the public demand for CBDCs, and the swift reaction by regulators of the finance sector, the results for the banking sector could be a tense experience.
Education – a essential premise for a sustainable development

Education is a fundamental social phenomenon for individual and collective well-being and prosperity. The evolution of this concept over the centuries allowed its transformation into a noble world movement. Today, education is at the center of attention of multiple organizations, unions and summits. Educational policies have become a priority for the European Union, which is working towards the creation of a European Area of education, with the aim of harnessing citizens' knowledge for Europe's prosperity. The continuity of education is one of its most important aspects through which we can create a universal culture of learning. The lifelong education has become an integrative principle for the transformation of any society into an educational fortress, a concept that consists in everyone’s involvement in a continuous educational process.
Students’ Difficulties in English Writing at Tenth Grade in Senior High School

This research discussed about students’ difficulties in writing recount text at tenth grade SMAN 1 Selesai Kab. Langkat. The problem of this research were the students’ difficulties in writing recount text and factors that cause students’ difficulties in writing recount. The objective of this research was to find out the students’ difficulties in writing recount text and to describe the factors that make students have difficulties writing recount text. This research was qualitative descriptive. The source of the data of this research was tenth grade SMAN 1 Selesai Kab. Langkat. Total of the were 24 students. The researcher used test and gave a questionnaire as the instruments. The researcher analysed the data by editing the data, reducing the data, tabulating the data and the last taking conclusion. The researcher found some facts in the field. First, it was found that the answer that students’ difficulties in writing recount text were difficulties in developing the content, organization, vocabulary, language, and mechanics. The data were got from students’ test that had been analysed. Beside that, the causes of the students’ difficulties in writing recount text were grammatical weakness, knowledge and understanding, less practice, and educational background
CHAIN: Exploring Global-Local Spatio-Temporal Information for Improved Self-Supervised Video Hashing

Compressing videos into binary codes can improve retrieval speed and reduce storage overhead. However, learning accurate hash codes for video retrieval can be challenging due to high local redundancy and complex global dependencies between video frames, especially in the absence of labels. Existing self-supervised video hashing methods have been effective in designing expressive temporal encoders, but have not fully utilized the temporal dynamics and spatial appearance of videos due to less challenging and unreliable learning tasks. To address these challenges, we begin by utilizing the contrastive learning task to capture global spatio-temporal information of videos for hashing. With the aid of our designed augmentation strategies, which focus on spatial and temporal variations to create positive pairs, the learning framework can generate hash codes that are invariant to motion, scale, and viewpoint. Furthermore, we incorporate two collaborative learning tasks, i.e., frame order verification and scene change regularization, to capture local spatio-temporal details within video frames, thereby enhancing the perception of temporal structure and the modeling of spatio-temporal relationships. Our proposed Contrastive Hashing with Global-Local Spatio-temporal Ibnformation (CHAIN) outperforms state-of-the-art self-supervised video hashing methods on four video benchmark datasets. Our codes will be released.
A Chaotic Hierarchical Encryption / Watermark Embedding Scheme for Multi-Medical Images Based on Row-Column Confusion and Closed-Loop Bi-Directional Diffusion

Abstract Security during remote transmission has been an important concern for researchers in recent years. In this paper, a hierarchical encryption multi-image encryption scheme for people with different security levels is designed, and a multi-image encryption (MIE) algorithm with row and column confusion and closed-loop bi-directional diffusion is adopted in the paper. While ensuring secure communication of medical image information, people with different security levels have different levels of decryption keys, and differentiated visual effects can be obtained by using the strong sensitivity of chaotic keys. The highest security level can obtain decrypted images without watermarks, and at the same time, patient information and copyright attribution can be verified by obtaining watermark images. The experimental results show that the scheme is sufficiently secure as a MIE scheme with visualized differences and the encryption and decryption efficiency is significantly improved compared to other works.
Introducing Culture in EFL Class: The Junior High School Teachers’ Awareness

The integration of culture into language teaching, particularly in the English as a Foreign Language (EFL) class, is widely regarded as an essential aspect of English teaching. The objective of this study is to explore the 7th-grade teachers’ awareness of Junior High school on introducing culture in EFL class. The research employed a quantitative survey in 26 junior high schools located in Palembang, South Sumatra. The data were collected from 115 English teachers who responded to a set of questionnaire items. Subsequently, the data underwent analysis by the use of descriptive statistics. The findings revealed that English teachers at the seventh-grade level are aware of incorporating cultural components within the context of English language teaching. To begin with, it is evident that the teachers possess a comprehensive understanding of the significance of culture and context in interpreting meaning. Furthermore, the teachers have a fundamental experience of the significance of being able to analyze and contrast cultures concerning their shared characteristics and distinctions. Thirdly, the teachers widely acknowledge that cultural learning has a predominantly positive influence within the English classroom. In the realm of English teaching, the teachers have a consensus regarding the significance of incorporating cultural learning activities into the classroom setting. Ultimately, junior high school English teachers exhibit a predominantly favorable disposition towards the significance of including cultural learning activities inside the English instructional setting
Paragraph Hamburgers Strategy in Writing a Report Text

The purpose of this study was to determine whether employing the paragraph hamburger strategy on the students’ writing report text at SMK Immanuel Medan in the academic year 2022-2023. The writers used the quantitative method when carrying out this research. After doing this research, the writers got several findings. Significant changes are made to students writing abilities after they are trained by using the paragraph hamburger strategy to learn writing skills. The results of this study allow it to be said that applying the paragraph hamburger strategy could have a significant effect on the student’s writing skills. Using the paragraph hamburger Strategy gave a more effective result than using a conventional strategy. The average scores from intensive classes were higher than the average from regular classes. From this pretest, the average test result from the regular class was 63.86, and after doing that post-test, the mean scores were 73.18. Meanwhile, the pretest was completed by the intensive class, and the mean result was 66.00, and upon completion of the post-test, these mean scores were 82.80. The writers used the t- test to obtain the findings of this study. We might therefore say that the value was 5.64. After analyzing this data, the t-table was smaller than the t-t-test (1.67 &gt; 5.64). That author displays a p-value of 0.05. The DF was 47. By seeing the data, the writers could conclude that the paragraph hamburger strategy could have a significant effect on the students’ report text in SMK Immanuel Medan. From this study, it might be said that Paragraph Hamburger had a big impact on the text written for a student report at SMK Immanuel Medan.
Measuring Individuals Cybersecurity Awareness Based on Demographic Features

Cybersecurity awareness has a huge impact on individuals and an even bigger impact on firms, universities, and institutes to those individuals belong. Consequently, it is essential to explore and asses the factors affecting the awareness level of cybersecurity. More specifically this research study examines the impact of demographic features of individuals on cybersecurity awareness. The Studied literature’s limitations have been addressed and overcome in our research from the variability, and ambiguity aspects. A questionnaire was developed and responses were collected from 613 participants. Reliability and validity tests as well as correlations have been applied for the instruments and data employed in this study. Coefficients were calculated via multiple linear regression for the weights of each of the cybersecurity components. Data reliability test showed that Cronbach's Alpha value of 0.707 for the used data which is acceptable for research purposes. Results analysis showed r-value for each of the questions is greater than the r table which was 0.07992. Examining the proposed hypotheses showed that there is a difference as the null hypothesis is rejected for one of the demographic features being tested namely, gender. While there is no significant difference when it comes to the other two factors, education level, and age. Using the weight for each of the components, password security, technical behavior, and social influence could provide a solid base for decision-makers to focus on and implement the available resources for gender-specific developments to raise the cybersecurity awareness level.
Structuring Educational Material When Mastering Quantities in Elementary School

The article discusses one of the ways to achieve subject and meta-subject results in teaching mathematics to junior schoolchildren – structuring educational material. The results of diagnosing the knowledge and skills of third and fourth grade students on the topic “Quantities” are presented and analyzed; Some approaches to developing schoolchildren’s ability to structure knowledge on this topic are outlined. Examples of graphic models that a primary school teacher can use when teaching mathematics are given
Load Balancing Algorithms in Cloud Computing: A Mirror Review

Cloud computing has always been a boon to the end-users by providing access for the storage and retrieval of data on demand rather than using their own devices. However, as count of users using cloud is increasing, and the resources count is finite, the challenges and issues are also getting more. One of the main challenges is balancing the load in the data centre. The dynamically changing requirements of the users need to be considered and should be executed on heterogeneous nodes rather than homogeneous nodes to minimize the response time and maximize resource utilization. Often there arises a need to cater to the load when the number of users multiplies exponentially. Thus, load balancing plays a great role in improving performance by maximizing resource utilization. As task scheduling which is a part of load balancing is an NP-hard problem, Swarm Intelligence techniques are best in designing efficient and effective load balancing algorithms. These algorithms are designed keeping in mind the collective behavior of different insects and how they search for food. Algorithms based on this approach have significantly shown much improvement. This manuscript has presented a comparison of various load balancing algorithms based on the different performance metrics in cloud computing.
Blockchain Based Decentralized Learning and Resource Sharing

Blockchain is an ever-growing ledger that keeps a permanent record of all transactions that took place on the network in a secure and chronological order and cannot be changed or tampered with. Many researchers from library and information science community have undergone to study and explain the ways for utilizing this new technology at their workplaces. Resource sharing amongst multiple learning ecosystems comes with several challenges as multiple access, transactional records, authorization, trust issues and security of learning environment. This paper is an attempt to explain the methods to share learning resources using blockchain technology. It includes the study of current functioning models in resource sharing and their setbacks. Current access and authorization systems are designed for centralized server and distributed databases. A tentative design is proposed to develop a library resource circulation system in which blockchain is used as a platform to manage access control on resources as well.
Optimizing explainability of Breast Cancer Recurrence using FuzzyGenetic

Breast cancer is the most common cancer diagnosed in the world, being the cause of death of 685,000 people worldwide in 2020. Due to the aggressiveness of the disease, early-stage identification, treatment, and remission detection are important to ensure longevity to those who may have cancer. In this paper, we propose a fuzzy-genetic approach for breast cancer recurrence classification. To this end, we use a Genetic Algorithm to design automatically the fuzzy inference system with the objective of balancing between accuracy and explainability. The proposed system achieved an accuracy of 91.30%, finding eleven rules with a maximum of three antecedents per rule, which provided a competitive result compared to other Machine Learning approaches.
SAGE3 for Interactive Collaborative Visualization, Analysis, and Storytelling

SAGE3, the newest and most advanced generation of the Smart Amplified Group Environment, is an open-source software designed to facilitate collaboration among scientists, researchers, students, and professionals across various fields. This tutorial aims to introduce attendees to the capabilities of SAGE3, demonstrating its ability to enhance collaboration and productivity in diverse settings, from co-located office collaboration to remote collaboration to both at once, with diverse displays, from personal laptops to large-scale display walls. Participants will learn how to effectively use SAGE3 for brainstorming, data analysis, and presentation purposes, as well as installation of private collaboration servers and development of custom applications.
Optimizing Instant Herbal Drink Production with IoT-Based Sachet Forming Machines to Increase Productivity and Quality

MSMEs Syarimpon and Melos (Melati Losari) are Micro, Small and Medium Enterprises that focus on the production of herbal drinks in Malang Regency. However, during its development, these MSME players experienced several problems, one of which was the packaging process which was carried out manually. This makes the production process take longer and reduces work efficiency. Apart from that, the process of cutting packaging manually also causes a decrease in the quality of the packaging and its contents. To overcome this problem, one solution is to use a counter machine with an automatic counter. By using this machine, MSMEs can speed up the packaging process, produce precise and neat packaging, and provide the freedom to innovate in determining the size of the packaging to be produced. In the process of using this IoT-based Sachet Forming Machine, it has succeeded in increasing the productivity and quality of the packaging process by taking 3 -5 seconds for one herbal drink sachet so that each day it can increase production to 900 sachets per day. Where the packaging process is still done manually so it takes 4-5 minutes so the packaging process per day is only 50 to 100 PCS of herbal drinks.&#x0D; Keywords: Sachet Forming Machine, IoT, MSMEs Syarimpon and Melos
A Hexagon Tile Map Algorithm for Displaying Spatial Data

Spatial distributions have been presented on alternative representations of geography, such as cartograms, for many years. In modern times, interactivity and animation have allowed alternative displays to play a larger role. Alternative representations have been popularised by online news sites, and digital atlases with a focus on public consumption. Applications are increasingly widespread, especially in the areas of disease mapping, and election results. The algorithm presented here creates a display that uses tessellated hexagons to represent a set of spatial polygons, and is implemented in the R package called sugarbag. It allocates these hexagons in a manner that preserves the spatial relationship of the geographic units, in light of their positions to points of interest. The display showcases spatial distributions, by emphasising the small geographical regions that are often difficult to locate on geographic maps.