Reviewerly/exHarmony huggingface dataset:
The Effectiveness of E-Learning Management Through Online Learning Information Systems : An Integrative Approach Model

This study aims to analyze the effectiveness of e-learning management through online learning information systems called sibering at the Faculty of Economics, Jakarta State University. The research used a qualitative approach using the case study. Determination of informants in this study using purposive and snowball techniques. Informants in the research were lecturers, students, and e-learning administrators. Data collection techniques in qualitative research were carried out in natural conditions, using primary sources (directly providing data) and observation, interview, documentation, and triangulation methods. The data analysis technique in this study was the data analysis of the Miles and Huberman models, including data collection, data reduction, data display, and conclusion/verification. The results of the data analysis concluded that sibering had a positive and effective impact on the implementation of e-learning. The results of the system approach model analysis concluded that the learning objectives and the preparation of learning plans were by university standards. The QAIT approach model includes learning system governance that refers to quality operational standards, and the Kirkpatrick approach model includes program evaluations taken from learning outcomes and student satisfaction, which has shown changes in student graduation rates in each course.
Relationship of Parents' Socio-Economic Status to Student Achievement

The economic well-being of parents can affect all aspects of life in the family, including by affecting the learning process of a child or student. This study aims to determine the condition of the socioeconomic status of students' parents, the learning achievement of high-class students and to determine the relationship between parents' socioeconomic status and student learning achievement. The method used in this study is descriptive qualitative. The subjects in this study were students who were ranked from 1 to 5 in high grades, namely class IV and V MI Al Washliyah perbutulan Cirebon. Data collection techniques that researchers use are by using observation and direct interviews. The data analysis technique used in this study is a qualitative descriptive method that is by looking for, collect, and organize systematically. Based on the results of research on the relationship between parents' socioeconomic status and learning achievement in high-class students at MI Al Washliyah, it can be concluded that there is a positive relationship between parents' socioeconomic status and learning achievement. From the explanation above, it can be seen that the socioeconomic status of parents has a significant positive relationship with student learning achievement. This shows that the higher the socioeconomic status of the parents, the higher the learning achievement of the learners. vice versa, the lower the socioeconomic status of parents, the lower the impact on student learning achievement
Dynamic and Private Recommendation System

The amount of data that we retrieve and use every day is increasing rapidly. As data naturally exist in different data domains, the number of data domains that we retrieve and use every day has also increased as a result. As different recommendation systems are needed for different data domains, more and more recommendation systems will need to be built. Furthermore, users will lose their privacy as many recommendation systems collect information about their users. This paper aims to solve the aforementioned issues by creating a recommendation system that will work with any data domain and upholds the privacy of its users. The Dynamic Implementation Of Privacy Based Recommendation System Application is created in this paper. The objective of this thesis is achieved as the Dynamic Implementation Of Privacy Based Recommendation System Application developed in this paper upholds the privacy of its users as it only stores users’ data in their device’s local database and the application has the ability to adapt to different data domains.
Don’t Cross Me! Cross-layer System Security

The computing landscape has undergone significant transformations in recent decades. Modern computation systems involve multiple layers across software and hardware architecture, exposing various security vulnerabilities that can be exploited by attackers. In this paper, we review security threats in these systems and provide insights into future directions in the topic of cross-layer security.
Kalman Filter for tracking a noisy cosinusoidal signal with constant amplitude

This paper presents a Kalman filter based approach in order to solve the problem of tracking a noisy cosinusoidal signal with constant amplitude in the presence of noise. The objective is to estimate the state of the signal accurately, considering the inherent challenges posed by noise corruption. The Kalman filter is utilized as the core algorithm for state estimation, leveraging its ability to combine noisy measurements and a dynamic model to provide optimal estimates. The filter is initialized with zero states and covariance, and the state and covariance estimates are iteratively updated using time updates and measurement update equations. Through extensive simulations, the performance of the proposed Kalman filter-based algorithm is evaluated. The results demonstrate its effectiveness in accurately tracking cosinusoidal signals and mitigating the impact of noise. the Kalman Filter algorithm in this system produces low MSE at about 0.021 and MAE at about 0.111. The metrics results signify the algorithm’s ability to filter noise and estimate the actual state of the system, reflecting its robust tracking performance. The simulation results validate the effectiveness of the proposed approach and highlight its potential to enhance signal tracking accuracy in the presence of noise. Further research can explore the algorithm’s performance in various scenarios and investigate additional modifications to increase its robustness in challenging environments.
A Multi-Scale Denoising Method for Forward-Looking Sonar Image

Underwater object detection and recognition rely heavily on the quality of sonar images, which can be significantly impacted by noise. This paper proposes a multi-scale denoising method for forward-looking sonar images. The proposed method firstly decomposes sonar image into three layers containing edge, texture and content information by the Laplacian pyramid model. Next, the adaptive median filter is applied to the edge layer while the modified adaptive local filter is applied to the texture layer and the content layer is completely retained. Finally, all processed layers are synthesized by Laplacian pyramid inverse transform. Experimental and comparative results on real and simulated sonar images demonstrate that the proposed method effectively reduces speckle noise and improves image quality.
Research on the Application of Blockchain in the Safe and Trusted Sharing of Government Data

To avoid the security vulnerabilities and privacy leakage risks in the process of government data sharing, a data sharing scheme for government data based on blockchain is proposed in this paper. As one of the basic protocols for the next generation of global credit authentication and value Internet, blockchain technology has been paid more and more attention. The blockchain is used to realize data tamper-proof, distributed storage, privacy protection, traceability, and access control. Data sharing and exchange agreements between government public services have adopted blockchain technology, providing identity authentication and message permission management. Using the blockchain to record the sharing behavior and provide traceability, the smart contract is used to share and manage the data and ensure the data’s consistency on-chain and off-chain. Due to shortcomings of government data sharing, the paper designs a data-sharing scheme and technical framework based on blockchain technology. From its perspective, it takes housing provident fund data sharing, for example, to establish a provident fund chain in the industry. This blockchain application scenario has been applied to the housing provident fund industry, forming a new model of industry data sharing.
Improve the level of governance system and accelerate the implementation of strategic transformation - Application analysis of blockchain technology

With the continuous development of the Chinese economy, China’s digital economy has entered the fast lane. We need to promote the deep integration of digital and real economies. The integrated application of blockchain technology is essential in new technological innovation and industrial change. Blockchain technology is developing rapidly in our country and profoundly integrating with many industries. It promotes trust between upstream and downstream sectors, enables efficient data sharing, and enhances risk prevention capabilities. Therefore, by analyzing the strategic requirements of “Five businesses of China Communications Construction Co., Ltd. “ and the governance system of building a “living community,” this paper explores blockchain technology’s essence and application scenarios. It proposes to build a governance system and implementation path of “trust the Internet” with the help of the application of blockchain technology in China Communications Construction Co., Ltd. Group to improve the overall governance level. Finally, we conducted a risk analysis of the CCCC governance system based on blockchain technology to ensure the smooth implementation of the scheme.
КОГНІТИВНЕ МОДЕЛЮВАННЯ В ІГРОВИХ МЕТОДАХ НАВЧАННЯ

The article describes one of the ways to solve the problem of higher and secondary education integration through the use of cognitive modelling of a new approach to the study of disciplines in the game interactive form, namely in the form of a quiz. The quiz is based on educational material on the example of discipline "Geography" with using the combination of well-known models of knowledge representation. Three levels of generalization are introduced in the cognitive model of knowledge in the quiz. The examples of knowledge representation at each level of generalization are shown.
International Journal of Information Security: A Bibliometric Study, 2007-2023

Abstract This study employs various bibliometric analysis techniques to examine the intellectual structure of the International Journal of Information Security from 2007 to 2023. The aim is to identify the most cited journals, underlying research themes within the article corpus, and gradual changes in the research themes over time. “Lecture Notes on Computer Science” is the most referenced knowledge source. In addition, articles on the theme of encryption techniques received the highest average citations, followed by key management and authentication protocols. Moreover, machine learning, blockchain, and the Internet of Things are emerging topics of interest among published authors in the International Journal of Information Security. Qualitative and quantitative comparisons between open-access and regular articles suggested a few notable differences in author keywords but no differences in the number of citations received. Furthermore, regression analysis found a negative correlation between citation counts with the length of the article abstract and article title and a positive correlation with page count, being published in a special issue, and if at least the affiliation of one of the authors is different from others. Finally, we also identified prominent authors, articles, institutions, and countries published in this journal.
Federated Learning in Heterogeneous Networks with Unreliable Communication

In federated learning (FL), local workers learn a global model collaboratively using their local data by communicating trained models to a central server for privacy concerns. Due to its local nature, FL is typically subject to various heterogeneities, including system and statistical heterogeneity. To address these concerns, Federated Proximal (FedProx) has been considered a promising FL paradigm to provide more stable learning convergence in the presence of computation stragglers and statistical heterogeneity. However, in wireless networks with unreliable communication channels, the errors of packet transmissions should be considered, introducing additional heterogeneity. For the first time, we rigorously prove the convergence of FedProx in the presence of transmission packet errors in heterogeneous networks. In addition, we propose a joint client selection and resource allocation strategy that maximizes the number of effective participating users for convergence acceleration. The method is combined with a random weight mechanism to reduce the statistical bias caused by the client selection strategy. An efficient low-complexity algorithm for solving the optimization problem is developed. The proposed method achieves faster convergence and requires fewer communication rounds to attain accuracy than existing state-of-the-art client selection methods.
Structural Design and Experimental Verification of Wave Adaptive Rescue Boat

Existing rescue boats are prone to capsize and poor wind and wave resistance in the rescue process. To solve this problem, this paper proposed a catamaran wave adaptive rescue boat based on automobile suspension technology capable of resisting wind and waves under class 4 sea state. Combined with the design requirement of the rescue boat, the buoyancy required by the rescue boat is calculated using 3D modeling software. The drag force experienced by the rescue boat during its voyage is calculated by computational fluid dynamics simulation software and empirical formulas. According to the resistance, the power required for the rescue boat to travel at the designed speed is determined, and the propulsion system of the rescue boat is designed based on it. Further, a sailing test of the rescue boat was completed under different sea conditions, and its sailing stability and wave adaptivity were analyzed. The experimental results show that the stability of the main hull of the rescue boat is much higher than that of the buoyancy tank. Experiment results show that the rescue boat presented in this paper has good wave-damping ability, which lays an excellent technical foundation for safe and efficient human rescue under severe sea conditions.
The Invenire series: why continue to print archival inventories?

The author explains the scientific reasons for the decision to create an editorial series dedicated to the printed publication of archival descriptive tools.
The Importance of Digital Skills Training Towards Employees’ Development in the Hospitality Industry

Digital skills are a basic requirement in this era of work operation since personnel is required to use applications in executing every task. The skills needed to facilitate employee development are to ensure their participation in the training provided by the company. Several operating systems are used in daily operations in the hospital industry, thus, employees must improve their skills during the applications. This review aims to identify the importance of digital skills training in the hospitality industry and its influences on employees’ development. Based on the secondary data from previous studies, digital training had a significant impact on the development of employees’ skills at their workplace. The development of staff secures their growth through designed and structured processes at any level of management. Thus, the creation of employees is an orchestrated activity for their professional advancement. Presently, most jobs employ a certain level of technology but tasks are more efficiently executed by using advanced technology. Additionally, the employees need to demonstrate a high adoption rate in the usage of technology to align with the development of advanced technology. Therefore, future research involving a primary study should be conducted by collecting data from employees in the hospitality industry. The researcher may assess employees’ perspectives of acquired skills at the workplace. Meanwhile, the management might elucidate the efficiency of digital skills training towards employees’ development before and after the training.
A Case Study of Bateq Community Adapted to Communication Technology in Taman Negara

Bateq, the Aboriginal people living in Pahang National Park in Malaysia, are heavily involved in the tourism industry. Among the uniqueness of the Bateq communities are their unique lifestyle, culture, and traditions. However, digital technologies have proliferated among the younger generation, creating disadvantages in the Bateq Indigenous community’s way of life. This exploratory study was conducted to explore the type of technology used by the Bateq people from the tourism stakeholders’ perspectives. Four villages were visited for this purpose: Kuala Atok Village, Kuala Sg Tabong Village, Kuala Sungai Yong Village and Dedari Village. Observation and in-depth interviews were conducted with eleven Bateq people and three tourism stakeholders. Thematic analysis was used to analyse the data. The result indicates that the Bateq community has already adapted to modern technology. The young respondents agree that technology is important, and most have smartphones. They use their smartphone for social media and watch online videos as the internet connection is available in some areas of their village. Additionally, they used solar power for charging their phones and lighting purposes. However, the tourism stakeholders were against the technology adoption behaviour among the Bateq community. The tourism organisation prefers that the Bateq people continue their traditional lifestyle with minimal technology interaction because it is important for their culture and lifestyle sustainability, which retains the tourism stakeholders’ business activities. Future studies should examine the preferences of technology adoption practices among the Bateq community and tourism stakeholders and how it would benefit the industry. Perhaps, they could adopt technology without affecting their way of living to ensure that future generations continue to practice and enjoy the uniqueness of Bateq ethnic culture and lifestyles.
Implement Security

Security is paramount when considering which data store to implement for your organization’s critical applications. Cloud-native services greatly benefit from the tightly coupled ecosystem in which they reside, providing less friction when implementing things like access, authorization, encryption, and network isolation. Azure Cosmos DB is no different and provides robust security controls for the modern enterprise workload.
Common Sense: The Dark Matter of Language and Intelligence (VLDB 2023 Keynote)

Scale appears to be the winning recipe in today's leaderboards. And yet, extreme-scale neural models are (un)surprisingly brittle and make errors that are often nonsensical and even counterintuitive. In this talk, I will argue for the importance of knowledge, especially commonsense knowledge, as well as inference-time reasoning algorithms, and demonstrate how smaller models developed in academia can still have an edge over larger industry-scale models, if powered with knowledge and/or reasoning algorithms.
Implementing aDevOps Process

DevOps is a set of practices that bring together developers and operations team to ensure services are deployed rapidly and reliably. This includes CI/CD, or continuous integration and continuous delivery. Common DevOps tools in Azure include PowerShell, Azure CLI, Azure Resource Manager (ARM) templates, and Bicep templates. In reference to Azure Cosmos DB, it is simply how you can automate the deployment and configuration of your Azure Cosmos DB and the assets therein like databases and containers.
Design and Implement a Replication Strategy

Azure Cosmos DB is a scalable, globally distributed NoSQL database engine. With a single click, new instances of the service can be created in regions all over the world. Adding additional regions provides your application with the ability to bring your data closer to your users, greatly reducing latency. Unlike most technologies that allow you to create read replicas or cache data in memory to reduce read latency, Azure Cosmos DB allows you to create write replicas near your users. Azure Cosmos DB offers both multi-region deployments where there is a single write region and N + 1 read regions or multi-write deployments which offers N + 1 write regions. The availability of multi-write functionality brings many benefits to globally dispersed workloads, but it also brings some challenges. Azure Cosmos DB automatically synchronizes the data between regions for you. But if data is being written from multiple locations, how can we maintain data consistency?
Plan and Implement Sizing and Scaling

Azure Cosmos DB leverages scale-out architecture to meet high-demand workloads at global scale. This means that new nodes are added to the pool of resources instead of increasing the size of a single node. This is important to understand as this scaling determines how to choose the right PK and what limits exist within a distributed, scale-out architecture.
Implement Data Movement

Your production application leveraging Azure Cosmos DB has been live for a few months and you are beginning to see performance degradation. After analyzing the logs and performance telemetry, you determine that your data is modeled incorrectly for the current query pattern. But the primary key for a container cannot be changed after creation. You now must migrate the data to a new container, which has a partition key that supports your workload. Or another scenario, let’s say that you want to migrate from the Azure Cosmos DB API for MongoDB to the API for NoSQL. How do you begin this process? Additionally, how do you integrate your Azure Cosmos DB with other services within your platform?
Design and Implement Multi-region Write

Multi-region writes in Azure Cosmos DB brings low-latency write operations to your global workloads where client write latency and availability is of the utmost importance. The ability to create additional write regions provides an instance of your database closer to your users but introduces some new challenges. Write conflicts can occur in a multi-region scenario since users in two different regions could be attempting to write the same document. Multi-write also comes with increased availability for writes. When your account has multiple write regions, if one of the regions becomes unavailable the SDK will automatically write to another available region. Compared to a single write region configuration which would require a service managed failover for write availability, a multi-write configuration provides fast, seamless write availability. In this chapter we will review how to work with multi-region configurations in the SDK as well as how to resolve conflicts that arise in Azure Cosmos DB.
Implement Client Connectivity Options

Azure Cosmos DB is a multimodal database, which means there are multiple APIs surfaced by the service for developers to interact with. There is the Core (SQL) API, API for MongoDB, API for Cassandra, API for Gremlin, API for Azure Storage Tables, and the newest API for PostgreSQL. These APIs provide flexibility for developers who want to leverage a key/value store, document store, column-family, or graph. The multimodal nature of Azure Cosmos DB also makes migrating beneficial for developers looking to take advantage of the scalable, globally distributed nature of Azure Cosmos DB.