Reviewerly/exHarmony huggingface dataset:
The Dual Mediating Effects of Search for Meaning and Presence of Meaning in the Relationship between Motivation to Participate in Learning and Subjective Well-Being in the Middle-Aged Female Later Learners

Objectives The purpose of this study was to identify the relationship between motivation to participate in learning on subjective well-being among middle-aged female later learners entering a college degree program and to investigate the dual mediating effects of search for meaning and presence of meaning in the relationship.&#x0D; Methods A total of 245 middle-aged female later learners aged 40 to 65 years who were enrolled in colleges in Busan. completed the questionnaires to measure motivation to participate in learning, subjective well-being, search for meaning and presence of meaning. Pearson correlation analysis and Process Macro model 6 were used to analyze the relationship between subjective well-being and motivation to participate and dual mediation effect of search for meaning and presence of meaning in the relationship, respectively. Additionally, bootstrapping was conducted to verify the significance of the mediation effect.&#x0D; Results First, motivation to participate in learning was positively related to search for meaning, presence of meaning and subjective well-being. Second, there was no medication effect of search for meaning in the relationship between motivation to participate in learning and subjective well-being. Third, there was a mediating effect in presence of meaning the relationship between motivation to participate in learning and subjective well-being. Fourth, there was a dual mediation of search for meaning and presence of meaning in the relationship between motivation to participate in learning and subjective well-being.&#x0D; Conclusions This study could provide empirical support for possible specific interventions to enhance subjective well-being in among middle-aged female later learners.
PENGEMBANGAN MEDIA KOMIK PINTAR (KOMPA) PADA TEMA 3 PEDULI TERHADAP MAKHLUK HIDUP UNTUK MENINGKATKAN MOTIVASI BELAJAR SISWA KELAS IV SD NEGERI 104211 MARINDAL

This study aims to find out how the development of smart comic book-based learning media (Kompa) in thematic learning theme 3 cares for living things sub-theme 1 animals and plants in my home environment, determines the level of validity of the media and increases the learning motivation of class IV students at SD Negeri 104211 Marindal . This research is a type of Research and Development (R&amp;D) research. The model used in this development is the ADDIE model. The ADDIE model is a development model that has five stages, namely analysis, design, development, implementation, and evaluation. Research limits only to 3 stages, namely the development stage. The subjects in this study were the validation of material experts, media experts, learning experts (teachers) and fourth grade elementary school students, totaling 22 students, while the object of this study was the development of smart comic media (Kompa) on theme 3 caring for living things, fourth grade students at school base. Based on the results of the calculations for the learning media above, the results of the assessment from material experts obtained 87.24% with very valid and feasible criteria for use in learning while the assessment results from media experts obtained 84% with very valid criteria and suitable for use in learning. The results of the practicality of learning media for the teacher's response obtained a value of 96%, and for student responses it obtained 97.04%, meaning that the media criteria were very practical. Based on the data obtained, it can be concluded that smart comic media (Kompa) is stated to be very valid and very practical and can increase students' learning motivation at SD Negeri 104211 Marindal.
The Preschools in Marawi City: Status, Problems and Prospects

This study, conducted during the 2010-2011 school year, explores the status, issues, and potential improvements of preschools in Marawi City. Employing a descriptive survey method, the research addresses several key aspects, including teacher, parent, and pupil profiles; preschool facilities; teacher practices; parenting approaches; encountered problems; and reading comprehension performance.The study encompasses twenty-nine preschools in MSU and Marawi City, with a sample size consisting of ninety-seven teachers, one hundred parents, and two hundred eighty-four pupils. A survey questionnaire, structured by the researcher, covers diverse categories such as teacher and parent profiles, preschool status, classroom practices, upbringing methods, encountered problems, reading comprehension performance, and prospects.Statistical tools like frequency distribution, percentage distribution, weighted mean, and the 5-point Likert scale were used for data analysis. Key findings include: a majority of teachers are female, aged 26-30, with a college degree and training in Early Childhood Education; parents are predominantly government-employed, aged 25-30, with 1-3 children; pupils are mostly 6-7 years old, Muslim, and in their senior level; preschool facilities are generally adequate, with classrooms rated moderately adequate; effective teacher practices contrast with moderately effective parenting approaches; serious problems are reported by teachers; and reading comprehension performance varies, with a need for enhanced social learning.Recommendations arising from the study include a preference for preschool teachers with a degree in Early Childhood Education, supplemented by ongoing training; emphasis on English and Filipino as instructional mediums; improved parent-teacher conferences; expanded preschool resources; careful planning and implementation of teacher practices; focus on developing reading skills; fostering rich social learning; and suggesting follow-up studies addressing specific concerns from teachers, pupils, and parents. In conclusion, this research provides valuable insights into the current state of preschool education in Marawi City and offers practical recommendations to enhance the overall quality of early childhood education in the locality.
Blockchain and Cryptocurrency: Disruptive Forces or Economic Enablers?

In this article the author analyses the complex realm of blockchain and cryptocurrencies, highlighting their transformative impact on today’s financial and regulatory landscape. Beginning with the foundational elements and potential applications of the technology, the paper elucidates the disruptive nature of cryptocurrencies, revealing both the opportunities they offer and the inherent challenges they pose. Key concerns include extreme market volatility, potential for misuse in illegal activities, and their profound macroeconomic implications. Also, the author explores the complexities of the evolving regulatory environment, emphasizing the need for a harmonized, dynamic, and transparent regulatory framework that fosters innovation while safeguarding public interest. The study is based on recent research, statistics, and policy developments, aiming to provide readers with a holistic understanding of the complexities and potential trajectories of cryptocurrency and blockchain technologies.
Resolving Anonymous Nodes Based on “Watermelon Patterns” Towards Constructing Router-Level Topology in Mesh Network

Router-level topology, portraying the connection relationship between network devices, is important for discovering key devices in network. In actual networks, there are some anonymous routers, which do not respond traceroute due to network congestion, firewall security settings, router response rate limitations, and other factors. As these anonymous routers are difficult to eliminate, it makes the constructed router-level topology huge in size. Currently, the time cost of finding key nodes is high. Resolving anonymous nodes for reducing the topology size is necessary to improve the efficiency in finding key node. Although anonymous route resolving methods have been available, they are difficult to handle two-hop anonymous route structures in mesh topologies. To this end, based on the four structures summarized in Graph Based Induction (GBI) method, we propose a method to resolve anonymous nodes based on “watermelon patterns”. Combining with Kapar, an alias IP merging method, to build router-level topologies in mesh networks. We have conducted experiments in 8 cities, such as New York, Tokyo, Seoul and so on. The experimental results show that, our method can handle the local topology containing two-hop anonymous nodes. And using our method to further reduce the size of the router-level topology built using GBI and Kapar, which is conducive to improving the efficiency of discovering key nodes in the topology.
Rhythm: Time and Geometry

The rationale behind RTG, a Haskell library in early development, is presented. RTG aims to provide a tool for the generation and manipulation of rhythmic patterns in music using the concept of geometric structure as a core abstraction of its API.
Qubit entanglement generated by classical light driving an optical cavity

We study the generation of entanglement between two qubits which communicate through a single cavity mode of quantum light but have no direct interaction. We show that such entanglement can be generated simply by exchanging quanta with a third party, which is in our case the cavity mode. Exchanging only a single quantum creates maximal entanglement. A single quantum can be provided by an external quantum light source. However, we use a classical light source to pump quanta which are used for the exchange, and investigate the degree of two-qubit entanglement. We first identify a characteristic timescale of the interaction between the cavity mode and each qubit. We investigate two regimes of the driving pulse length: one is short and the other is long compared to the characteristic timescale of the interaction. In the first regime, it is known that the pulse can pump the system by generating a displacement of the cavity mode. We show that, by using a specific pulse shape, one can make the displacement essentially vanish after the pulse finishes interaction with the cavity mode. In this case, a rotation of the qubits can be invoked. In addition, higher-order effects of the pulse including a nonlocal operation on the joint system of the cavity mode and the qubits are found, and we present a formalism to compute each term up to a given order. An explicit condition on the pulse shape for each term to be nonzero or suppressed is derived to enable an experimental design for verifying the entanglement generation using a classical light source. In the opposite regime where the driving is sufficiently long, we utilize a squeezed state which may be obtained adiabatically. We study how the squeezing and the accompanied rotation of qubits affect the generated two-qubit entanglement.
Scientific Publication Article Development Training for SMK Teachers

The purpose of implementing this community service is to provide information, knowledge, and equip teachers in arrange article ready scientific for published in journal scientific, grow atmosphere academic environment school so that could repair quality education and learning with to do activity study. The methods used in this activity include: (a) lectures or material delivery or information presentation for materials related to making scientific articles for publication, (b) questions and answers that provide opportunities for teachers to explore as much knowledge as possible about writing scientific articles, and (c) simulations to provide opportunities to practice the acquired training materials. The results of the implementation of community service can be felt by the community service team and participants. The training that has been carried out has gone well, smoothly in accordance with the goals to be achieved in this activity, and is very satisfying. The YPPD Vocational School teachers gain knowledge and experience sharing about techniques for writing scientific articles and publications to journals and also expect there will be assistance from FE UNJ lecturers in making articles so that they can be published in scientific journals. This is a good response from the training participants with training in the preparation of scientific article publications for SMK teachers.
Efforts by the Homeroom Teacher to Address Reading Challenges Among Class III Students at SDN Bantar Kemang 06

Background: The research delves into the efforts made by the class teacher to address reading challenges among third-grade students at SDN Bantar Kemang 06. While most class III students typically read proficiently, there are some in SDN Bantar Kemang 06 who require additional support in reading.&#x0D; Purpose: This study aims to identify the specific reading difficulties these students face and explore the teacher's strategies to overcome these challenges.&#x0D; Design and methods: Employing a qualitative approach, the research adopts a case study method. Data collection involves observation, interviews, and documentation techniques. The Miles Huberman Analysis Model guides data analysis through components of data reduction, presentation, and conclusion verification. To ensure data validity, triangulation methods involving source, method, and time are employed.&#x0D; Results: The findings reveal five key efforts by the homeroom teacher to address students' reading difficulties. Firstly, the teacher emphasizes classroom literacy. Secondly, a dedicated reading corner is established within the classroom. Thirdly, additional reading sessions of about 20 minutes are provided after regular learning activities for struggling students. Fourthly, proactive communication with parents and conducting tutoring or individual guidance sessions for students in need are implemented. The identified factors contributing to students' reading difficulties encompass intellectual, environmental, and psychological aspects. These difficulties manifest in hesitancy while reading, inadequate attention to punctuation in lengthy sentences, and a need for assistance in comprehension.
A First Dive into OFAC in DeFi Space

51% of Ethereum Blocks are OFAC Censored was one of the annual headlines in the year 2022. Short for Office of Foreign Assets Control, OFAC, as a division of the U.S. Treasury Department, made itself go on the stage of decentralized finance (DeFi). OFAC was originally established to impose economic sanctions on threats to the United States national security. The jurisdiction of OFAC today, however, seems to be stretching further and further. In this work, we provide the first dive into OFAC in the DeFi space. We describe how OFAC specifically implements its sanctions, namely, on chains (in particular, Ethereum 2.0 as an example), on cryptocurrencies, and on decentralized applications. We discuss the impacts of the presence of OFAC intervention and identify future directions for DeFi products based on this fact.
Unsupervised Fraud Detection on Sparse Rating Networks

Network fraud detection, specifically identifying abnormal users on rating platforms, has attracted considerable interests of researchers due to its wide applicability. However, the performance of existing detection systems suffer from several challenging problems such as class imbalance, lack of annotated data and network sparsity. To address above challenges, in this paper, we propose a novel unsupervised fraud detection algorithm FD-SpaN based on network structure exploration, to effectively rank users based on computed probabilities of being fraudulent and identify abnormal users on sparse networks. Firstly, we model ratings networks as graphs in mathematical manner with introduced metrics. Then, we add variable smoothing terms accordingly when inferring the quality and trustworthiness of each item and rating respectively, to tackle network sparsity on entity level. Meanwhile, for active users, we integrate their rating patterns into our developed formulations as a critical term to avoid overfitting. In addition, our proposed FD-SpaN is scalable to large-scale rating networks in real world due to its linear time complexity with respect to the size of network. Extensive experiments on two real-world datasets show the effectiveness of FD-SpaN under extreme class imbalance and network sparsity, as it outperforms other state-of-the-art baselines in terms of all evaluation metrics.
Sumber Daya Teknologi Terhadap Pelaksanaan Kurikulum di Era Digital

The purpose of writing this work is to analyze technological resources for curriculum implementation in the digital era. The literature review includes scientific journals, books and literature related to education, technology and digital curriculum to gain in-depth insight into the use of technological resources in implementing curriculum in the digital era. Data collection methods involve analysis of official documents, such as government policies, and interviews with education and technology experts to understand the challenges and potential of implementing technology in curriculum contexts. The results of this work are a) Technology has a crucial role in increasing interactivity and personalization of learning, ensuring its effectiveness and providing unlimited access through resources such as digital libraries. Effective use of technology in the digital era has a significant positive impact, creating an adaptive learning environment and improving the overall quality of education. b) The integration of technology in education faces infrastructure barriers, insufficient educator training, limited policy support, and curriculum incompatibility. Solutions require holistic efforts, including infrastructure provision, comprehensive training, policy support, and external collaboration to create an innovative learning environment. c) The use of technology in education provides a positive impact and enriches the learning experience, with challenges such as gaps in access and educator training that can be overcome through a holistic approach and external collaboration, emphasizing awareness of the key role of policy, ongoing training and maintenance of technology as a vital foundation for the future an innovative and responsive educational future.
The Effectiveness of Listen-Read-Discuss (LRD) on Students’ Reading Comprehension

This study aimed to assess the effectiveness of the Listen-Read-Discuss (LRD) strategy in improving students' reading comprehension at SMAN 2 Majene. A quasi-experimental design was used with a population of 277 tenth-grade students. The sample, consisting of 60 students, was selected using convenience sampling. The assessment instrument comprised 20 multiple-choice questions administered to both the experiment and control groups before and after the treatment. The results revealed that the students' average pre-test scores in the experimental group were categorized as poor, with a mean score of 44.33. However, their post-test scores significantly improved to a good level, with a mean of 73.83. Similarly, the control group showed poor pre-test scores with a mean of 44.67, but their post-test scores improved to a good level, averaging 71.83. In conclusion, the students demonstrated enhancement in reading comprehension. The significant value of the pre-test and post-test results for both groups was 0.000, which is less than 0.05. Therefore, the t-test value was smaller than 0.05, confirming that the Alternative Hypothesis (Ha) was accepted, and the Null Hypothesis (H0) was rejected, indicating a significant effect of the LRD strategy on the reading comprehension of tenth-grade students at SMAN 2 Majene.
DNS Flow Analyser (DFA): A DNS-Based Correlation System to Classify CDN Domains and OTT-Applications

Understanding how traffic from the applications is delivered to end-users has been a daunting task of network players for decades. Historically, only DPI (Deep Packet Inspection) has been the dominant technology to provide such insight, but this faces growing challenges with encryption and scaling. In this demonstration, we present an implementation of a DNS-based correlation framework, called DNS Flow Analyser (DFA), to annotate and classify the traffic flows with information about OTT-Applications (e.g., TikTok, Disney+, AmazonPrime, DAZN) and CDN domains (e.g., fastly.net, akamai.net, cloudfront.net). This novel solution allows network providers to expand their traditional network-oriented view with an application-oriented view.
An Improved Product Recommender System Using Collaborative Filtering and a Comparative Study of ML Algorithms

Abstract One of the methods most frequently used to recommend films is collaborative filtering. We examine the potential of collaborative filtering in our paper’s discussion of product suggestions. In addition to utilizing collaborative filtering in a new application, the proposed system will present a better technique that focuses especially on resolving the cold start issue. The suggested system will compute similarity using the Pearson Correlation Coefficient (PCC). Collaborative filtering that uses PCC suffers from the cold start problem or a lack of information on new users to generate useful recommendations. The proposed system solves the issue of cold start by gauging each new user by certain arbitrary parameters and recommending based on the choices of other users in that demographic. The proposed system also solves the issue of users’ reluctance to provide ratings by implementing a keyword-based perception system that will aid users in finding the right product for them.
Fault Tolerance of Cloud Infrastructure with Machine Learning

Abstract Enhancing the fault tolerance of cloud systems and accurately forecasting cloud performance are pivotal concerns in cloud computing research. This research addresses critical concerns in cloud computing by enhancing fault tolerance and forecasting cloud performance using machine learning models. Leveraging the Google trace dataset with 10000 cloud environment records encompassing diverse metrics, we systematically have employed machine learning algorithms, including linear regression, decision trees, and gradient boosting, to construct predictive models. These models have outperformed baseline methods, with C5.0 and XGBoost showing exceptional accuracy, precision, and reliability in forecasting cloud behavior. Feature importance analysis has identified the ten most influential factors affecting cloud system performance. This work significantly advances cloud optimization and reliability, enabling proactive monitoring, early performance issue detection, and improved fault tolerance. Future research can further refine these predictive models, enhancing cloud resource management and ultimately improving service delivery in cloud computing.
Hybridized Cryptographic Encryption and Decryption Using Advanced Encryption Standard and Data Encryption Standard

Abstract This research proposes an efficient hybridized approach for symmetrical encryption of image files in bitmap formats. Due to the heavy use of lightweight encryption in fields such as military and corporate workplaces, intruders try to intercept communication through illegal means and gain access to classified information. This can result in heavy losses if the leaked image data is misused. The proposed enhances the security and efficiency of one of the most used standard symmetric algorithms, Advanced Encryption Standard (AES). In the proposed method, the AES architecture has been modified using a less intensive algorithm, Data Encryption Standard (DES). DES carries a sub-process of permuting data columns rather than the AES’s mixing feature. The proposed algorithm is analyzed using a set of 16 bitmap images of varying memory sizes and resolutions. The effectiveness of the algorithm is evaluated solely in terms of perceptual invisibility as per the main objective of the research.