Backup Research Articles

Analysis and Design of Regional Asset Leasing Management Information System in North Tapanuli Regency

Regional assets are something that has an essential role in the scope of local government because they have a complex value and are quite significant when compared to other components in the local government narrative. This requires local governments to be able to manage and utilize regional assets properly and correctly to increase Original Local Government Revenue in the region. Effective and efficient management of regional assets is one example of the management of the regional economy as shown in the Original Local Government Revenue. Improving the quality of regional asset management that is carried out professionally and modernly is a step taken to prioritize the principles of Good Governance. This research will discuss how to design a model for managing land assets of the North Tapanuli Regency local government that prioritizes the principles of Good Governance by utilizing information technology in the form of designing an information system that is expected to bring changes to the institutions that use it. The information system is expected to make the management of land assets spread across 15 sub-districts neater and more well-organized. In addition, the management of information related to asset leases can facilitate the reporting process and decision making. The purpose of this research is to design an information system as a reference for the Regional Finance and Asset Agency to develop an information system for managing regional assets and leasing regional assets by utilizing web-based and mobile technology. It is expected that through the information system designed in this research, the retribution payers can submit a Lease Application, upload the files of the Application Letter, and download the agreement letter through the application. Another technology that can be utilized in the information system to be built is the use of docker containers to run a lighter database and save time when storing all data related to the object of retribution, retribution payers, applications, lease agreement contracts, bills, and payments. This research also applies data storage technology that divides data into several separate units and then stored in one repository called object storage technology. This technology is used to store large data, create backup copies and archives, and store large amounts of images, graphics, video, or audio files.

The Implementation of AWS Cloud Technology to Enhance the Performance and Security of the Pharmacy Cashier Management System

This study examines the implementation of Amazon Web Services (AWS) in the MEKATEK pharmacy cashier management system to address the limitations of traditional systems, such as slow transaction processing, data loss risks, and challenges in handling transaction surges. The prototyping method was employed, involving user requirements analysis through interviews and observations, followed by iterative development of core features like inventory management, transactions, reporting, and data backups. Black box testing demonstrated a 100% success rate for core functionalities. Performance analysis recorded stable CPU utilisation below 5% under normal workloads and the ability to handle throughput up to 2532 packets/minute. System optimisation reduced AWS operational costs to IDR 150,000–160,000 per month. AWS implementation improved operational efficiency, strengthened data security through encryption and role-based access control, and minimised human errors. Initial user feedback indicated faster workflows, although adjustments are needed for users with limited technical backgrounds. This study recommends further development, including AI-based analytics and digital payment integration, to enhance MEKATEK’s functionality and competitiveness in the future.

Cryopreservation of apple buds to assure a backup copy for pre-base materials held in screenhouses

Cryopreservation of apple buds to assure a backup copy for pre-base materials held in screenhouses

Conventional Banking Strategy in Facing Digital Financial Institutions in the Era of Banking Competition

Industry 4.0 is an era of rapid development or change that covers all aspects of industrial activity and human life using digital technology and the internet. Industry 4.0 is also known as a systematic production activity through the use of wireless technology and big data, which makes data use more precise with server systems, and integrates all operations automatically into the system. The data collected and analyzed in this study were collected and analyzed to produce authoritative studies and achieve research objectives. This study uses a data collection method through library research. The data collected comes from English and Arabic literature, Islamic banking, journals, and other sources found in libraries and other information centers. Digital banks are expected to facilitate the backup and analysis of bank consumer data. To make it easier for banks to maintain customer relationships, handle customer complaints better, and improve products and services that are faster, cheaper, clearer, more accurate, and better for customers. The banking industry faces new challenges and expectations during this digital economy era. Companies are turning to digital banking to retain their old clients and attract new clients from the millennial generation. Digital banking is a term that refers to the use of technology in banks. It refers to banking services that use digital technology to meet client needs and develop the desired digital economy.

USV Fleet-Assisted Collaborative Data Backup in Marine Internet of Things

USV Fleet-Assisted Collaborative Data Backup in Marine Internet of Things

Multiscale Cloud-based Pipeline for Neuronal Electrophysiology Analysis and Visualization.

Electrophysiology offers a high-resolution method for real-time measurement of neural activity. The vast amount of data generated requires efficient storage and sophisticated processing to extract neural function and network dynamics. However, analysis is often challenging due to the need for multiple software tools with different runtime dependencies. Longitudinal recordings from high-density microelectrode arrays (HD-MEAs) can be of considerable size for local storage, complicating data management, sharing, and backup. To address these challenges, we developed an open-source cloud-based pipeline to store, analyze, and visualize neuronal electrophysiology recordings from HD-MEAs. This pipeline is dependency agnostic by utilizing cloud storage, cloud computing resources, and an Internet of Things messaging protocol. We containerized the analysis algorithms to serve as scalable and flexible building blocks within the pipeline. We designed graphical user interfaces and command line tools to remove the requirement of programming skills. The interactive visualizations provide multi-modality information on various neuronal features. This cloud-based pipeline is an efficient solution for electrophysiology data processing, the limitations of local software tools, and storage constraints. It simplifies the electrophysiology data analysis process and facilitates understanding neuronal activity. In this paper, we applied this pipeline on two types of cultures, cortical organoids and ex vivo brain slice recordings.

Structural equations modeling for the entry into becoming a sport sponsorship of the halal product in Thailand

This research study aims 1) to create a structural equation model for sports sponsorship of halal products in Thailand and 2) to examine the direct and indirect influence of variables that are components of the structural equation model for halal products, specifically in the context of becoming a sports sponsorship for halal products in Thailand. The study focused on a sample group of Thai Muslims interested in watching and following the news and participating in Thai sporting events. The researcher chose a sample size of 400 participants from this population, excluding backup data gathering and data analysis, to ensure the questionnaire’s quality and dependability. The results of the data analysis from the structural equation model created show that it is consistent with empirical data. The results of the statistical hypothesis test reveal that the level of religious adherence and the level of awareness of entering into sponsorship have both direct and indirect influences on consumer attitudes and purchase intentions with statistical significance at 0.01. It can also be identified that if a sponsor increases awareness among Muslim viewers through branding or product presentations in events that feature halal symbols or indicate compliance with religious standards, it will lead to a more positive attitude and higher purchase intentions. This insight can be applied to marketing promotion in administrative regions or countries where the majority of the population is Muslim.

High‐speed end‐to‐edge data caching and forwarding architecture based on field programmable gate array

AbstractThe application of the Internet of Things generates massive end‐device data. Traditional end‐to‐edge data caching methods lack parallelism, consume numerous resources, and lack data backup mechanisms. We propose a lightweight high‐speed data caching and forwarding architecture based on a field‐programmable gate array. In the basic scheme, a double‐data‐rate memory read/write mixed control method is proposed to efficiently cache massive amounts of data. To improve reliability, we propose address‐space virtualization to forward data to backup devices. To satisfy the demand for higher performance scenarios, we propose a real‐time data shunting mechanism to realize an optimized scheme that supports higher data rates. These two schemes support single‐link high‐speed data caching and forwarding at 10 and 40 Gbps. Compared with the existing method, the basic and optimized schemes improve the performance by 25% and four times and save 66% and 40% of the resources, respectively. Thus, we provide a lightweight and reliable high‐performance end‐to‐edge data caching solution for resource‐constrained edge devices.

Advancements in AI-Driven Disaster Recovery: Predictive Failure Detection and Automated Data Protection

This article explores the transformative impact of artificial intelligence (AI) on disaster recovery systems in information technology. It examines how AI-driven solutions are revolutionizing traditional approaches to data protection and business continuity through advanced predictive analytics, automated backup mechanisms, and intelligent recovery processes. The research highlights the significant improvements achieved in recovery times, with some implementations reporting up to 60% faster recovery compared to conventional methods. Key aspects discussed include AI-powered predictive failure detection, automated data backup mechanisms, and the acceleration of recovery times. The article also delves into the enhancement of data availability through AI-driven replication strategies and intelligent failover mechanisms, emphasizing their critical role in maintaining operational resilience. Additionally, it addresses the challenges and considerations in implementing these advanced systems, including integration with existing infrastructure and the necessary adaptation of IT personnel. The article concludes by exploring future directions in AI algorithms for disaster recovery, potential integrations with cloud-based solutions, and the broader applications of these technologies across various industries. This comprehensive analysis underscores the pivotal role of AI in shaping the future of disaster recovery and business continuity strategies in an increasingly digital world.

Systematic Literature Review of Cloud Computing Adoption

In the current rapidly growing digital era, cloud computing is a technology that plays a significant role in digital transformation in various industrial sectors. Cloud computing brings several advantages such as high scalability, cost efficiency, flexibility, easy accessibility, collaboration enhancement, more effective data backup and recovery, and automatic software updates. However, the adoption process faces numerous challenges and complex considerations, such as data security, privacy, regulatory compliance, and integration with existing systems. This research employed a systematic literature review (SLR) method to collect, analyze, and synthesize various studies on cloud computing adoption. The results are expected to provide comprehensive guidance for practitioners and researchers in understanding the dynamics of cloud computing adoption, as well as recommendations for organizations to establish more informative and strategic decisions in implementing this technology to improve their competitiveness and operational efficiency.

Effective Archival of Salesforce Stale Data: A Strategy for System Optimization and Cost Efficiency

This paper explores the importance of archiving stale data in Salesforce and how implementing an ongoing archival process helps maintain accurate, up-to-date information while optimizing system performance and reducing storage costs. As businesses generate vast amounts of data daily, the accumulation of outdated information can slow system operations, increase storage costs, and lead to data inaccuracies. The paper will outline best practices for Salesforce data archival, including soft archival strategies, hard deletion, data backup procedures, and integration precautions. Examples of account data archival, key performance indicators (KPIs), and cost-saving opportunities will be discussed, along with recommended tools and methods for successful data management. Keywords Salesforce, Data Archival, Stale Data, Data Backup, Soft Archival, Data Management, System Optimization, Cost Savings, AWS Backup, OwnBackup, Salesforce Queries

ChronoBak: Automated cost-effective incremental backup software for large-scale data

Background: Data backup is an important component of data protection and management. It is especially imperative to back up large-scale data to guard against losses due to hardware failure, unauthorized access, software/system malfunction, and unintended deletion. However, businesses and organizations suffer from the financial investment required for data backup and recovery systems. Health-care systems suffer from data breaches and hacking incidents, which increase annually. Therefore, a cost-effective and highly secure backup approach is necessary. Methods: Seven different backup scripts were written in bash within Linux, and Crontab was used as the core chronological scheduler to execute the backup scripts on specific dates and times. These bash scripts, together with Crontab as their scheduler, were used to implement automated incremental backups on a Unix/Linux-based system. Results: ChronoBak is a collection of bash scripts that are compiled and executed through Crontab, which is a standard Unix/Linux function used to schedule hourly, daily, weekly, and monthly maintenance routines using Linux scripts. This strategy enabled us to implement cost-effective incremental backups within any time range. Conclusion: We developed ChronoBak software, which executes an automated incremental backup that is scheduled efficiently and systematically using standard and hidden directories, thereby providing an additional layer of security against cyber threats and system malfunctions.

Construction of Hydrogen Fuel Backup Power Supply System based on Data Communication Technology

The study presents a comprehensive examination of integrating hydrogen gas cells into backup electricity systems, strengthened by superior records verbal exchange technologies. This modern approach targets to address the growing interest for reliable and sustainable strength sources within the context of developing issues about environmental sustainability and the restrictions of traditional fossil gasoline-based totally power structures. On the middle of this studies is the improvement of a hydrogen gasoline cellular-based totally backup strength device. Hydrogen fuel cells, regarded for his or her excessive strength performance and low environmental impact, offer a promising opportunity to standard energy resources. The device leverages the inherent advantages of hydrogen as a clean strength carrier, making sure reduced carbon emissions and greater energy safety. A giant component of this have a look at is the combination of contemporary data communication generation. This integration facilitates real-time tracking and control of the electricity gadget, ensuring surest performance and reliability. Advanced statistics analytics are hired to are expecting energy demand, reveal gas cell health, and optimize the machine’s operation. This approach no longer handiest complements the performance of the energy supply but also ensures a unbroken transition between the number one energy supply and the backup device at some point of outages. The studies methodology encompasses a blend of theoretical analysis and realistic experimentation. Simulation models are used to test the device’s efficacy underneath numerous scenarios, followed via a prototype implementation to validate the theoretical findings. The look at also explores the monetary viability and scalability of the proposed machine, making it relevant for big adoption.

An Analysis of Managing the Cloud: Obstacles and Solutions for Efficient Administration and Protection

Cloud management offers possibilities and difficulties to enterprises looking for effective management and strong data security. This essay examines the challenges associated with cloud administration and suggests workarounds for these issues. Assuring data security, upholding legal compliance, cutting expenses, and overseeing intricate multi-cloud setups are important obstacles. The use of cloud-native monitoring and governance tools, the implementation of extensive data backup and recovery plans, the use of automation for resource provisioning and administration, and the implementation of strong security measures like encryption and access restrictions are all necessary for finding solutions. Organizations may improve the security of their important data assets and expedite their cloud administration procedures by tackling these challenges with suitable solutions. Ensuring data security is a major concern in cloud administration. Organizations are concerned about data breaches, illegal access, and industry regulatory compliance when they move critical data to the cloud. Organizations need to have strong security mechanisms like identity management, access restrictions, and encryption in place to lessen these risks. Furthermore, implementing a defense-in-depth strategy that incorporates several security tiers might improve cloud environments' overall resilience. Upholding legal requirements and industry norms is another challenge for cloud managers. To secure sensitive data and uphold client confidence, businesses in regulated sectors like healthcare and finance are subject to strict compliance regulations. Adherence to frameworks like HIPAA, GDPR, and PCI DSS, as well as thorough policies and frequent audits are necessary to achieve compliance in the cloud. Organizations may minimize the risk of non-compliance penalties and expedite compliance processes by putting governance tools and compliance automation systems into place. For enterprises using cloud resources, cost optimization is another major concern. Pay-as-you-go cloud services might result in overspending and financial restrictions due to improper resource utilization.

B2DFL: Bringing butterfly to decentralized federated learning assisted with blockchain

We propose a novel decentralized federated learning framework called B2DFL. It decomposes the aggregation process of vanilla FL into layered and serialized sub-aggregation processes and offloads the communication and computation from a single point to distributed nodes, thus addressing the single point of failure issue in centralized FL. The decentralization of B2DFL is based on the Butterfly, a distributed network topology, to organize and orchestrate the order and rules of node aggregation. Additionally, to mitigate potential risks such as dropouts or tampering, we leverage the blockchain and IPFS systems. Specifically, after each node completes its computation (including training and aggregation), it generates a hash value of the results as proof. We maintain a Tamper-evident Data Structure (TDS) on the blockchain, which records these proofs to ensure tamper-proofing and fast verification. To reduce the storage burden on the blockchain and improve throughput, we store the aggregated results on IPFS, a system that enables quick data location through hash values of data, for data backup. We also design a node replacement mechanism for quick dropout handling. We conduct a comprehensive performance evaluation and experimental results demonstrate that B2DFL presents a significant performance improvement while achieving privacy and decentralization.

A Novel Authenticated Quantum Anonymous Secret Sharing for Classical and Quantum Information

AbstractAnonymous secret sharing (ASS) is an essential cryptographic concept that facilitates the sharing and reconstruction of secret information while safeguarding the identity of the involved secret receivers, which has broad applications in key management, data backup, and distributed systems. In this study, a novel authenticated quantum anonymous secret sharing (QASS) protocol that emphasizes information privacy and identity anonymity protection is proposed. Employing ‐level multipartite GHZ states as a quantum resource, one‐sided anonymous entanglement (AE) is innovatively established between the dealer and anonymous receivers, enabling the dealer to distribute a random share of secret information. Additionally, by establishing a one‐sided AE between anonymous receivers and restorer, the restorer can securely collect and reconstruct the secret information using quantum teleportation (QT). Rigorous security analysis demonstrates that protocol can resist attacks from active adversaries and potentially dishonest users. Quantum experiments on IBM Qiskit validate the correctness and feasibility of the proposed QASS protocol. This work contributes to the advancement of quantum anonymous communication, addressing the requirements for information privacy and identity anonymity in practical application environments.

Best Practice of Moodle Implementation for E-Learning: A Perspective of Public University Lecturers

Moodle is a popular open-source learning management system (LMS) used for online learning and course management. It provides educators with tools to create online courses, manage learning content, track student progress, conduct assessments, and facilitate communication and collaboration among students and instructors. Moodle is widely used in educational institutions, corporate training settings, and various other learning environments around the world. The aim of this article was to study the best practices for implementing Moodle in e-learning, as perceived by public university lecturers. This study employed a qualitative approach, utilizing Focus Group Discussions (FGDs) among lecturers from public universities. All data were meticulously transcribed and subsequently analyzed thematically. The results show, experts agreed that three best practices were i) Optimizing the task of e-learning manager, ii) Utilize the restriction option to uphold student integrity and, iii) Implementing regular data backups. Therefore, this study enriches the field by providing practical recommendations for implementing Moodle, drawing from the insights of public university lecturers.

Integrated Home Energy Management with Hybrid Backup Storage and Vehicle-to-Home Systems for Enhanced Resilience, Efficiency, and Energy Independence in Green Buildings

This study presents an innovative home energy management system (HEMS) that incorporates PV, WTs, and hybrid backup storage systems, including a hydrogen storage system (HSS), a battery energy storage system (BESS), and electric vehicles (EVs) with vehicle-to-home (V2H) technology. The research, conducted in Liaoning Province, China, evaluates the performance of the HEMS under various demand response (DR) scenarios, aiming to enhance resilience, efficiency, and energy independence in green buildings. Four DR scenarios were analyzed: No DR, 20% DR, 30% DR, and 40% DR. The findings indicate that implementing DR programs significantly reduces peak load and operating costs. The 40% DR scenario achieved the lowest cumulative operating cost of $749.09, reflecting a 2.34% reduction compared with the $767.07 cost in the No DR scenario. The integration of backup systems, particularly batteries and fuel cells (FCs), effectively managed energy supply, ensuring continuous power availability. The system maintained a low loss of power supply probability (LPSP), indicating high reliability. Advanced optimization techniques, particularly the reptile search algorithm (RSA), are crucial in enhancing system performance and efficiency. These results underscore the potential of hybrid backup storage systems with V2H technology to enhance energy independence and sustainability in residential energy management.

Novel Use of Concentrated Solar Thermal Energy for Producing Highly Thermal Activated Materials for CCUS via Mineral Carbonation of Mine Waste

An assessment of the levelised cost and associated CO2-eq emissions for the thermal activation of serpentine mine tailings to be used as activated feedstock for CCUS processes via mineral carbonation, is reported here for the first time. Two main technological scenarios were assessed, based on either direct fuel sources heating (natural gas and hydrogen) or indirect, CST-based heating with a back-up burner and storage to provide continuous operations, for a 200 ton/hr of processed ore and a targeted roasting ore temperature of 700°C. For CST-based systems, 3 different solar input scales, namely 50, 150 and 450 MWth, were considered, and simulations performed over a year timeline with a 10 minutes time step, using Mt Keith Nickel mine in Western Australia as the reference location. The analysis highlighted that the proposed CST-hybrid plant layout can achieve similar cost to that of fuel-only cases with current Australian fuel prices for natural gas and hydrogen, with lower CO2-eq emissions, and a parity cost with fuel-only scenarios of some 16 USD/GJ. The proposed CST-hybrid plant layout was also identified as the potential, preferred route over direct CST routes to achieve 24/7 continuous heat supply while retaining fine tuning of activation temperature, given a very narrow temperature window of activation for the chosen mine tailings for mineral carbonation processes.

Disaster Recovery of Near Field Communication (NFC) Systems

This paper explores the vulnerabilities inherent in NFC systems and presents a comprehensive disaster recovery framework designed to enhance resilience. By reviewing existing literature on disaster recovery, analyzing past failures of NFC systems, and proposing strategies such as data backups, real-time monitoring, and blockchain integration, this study aims to bolster the reliability of NFC systems and ensure their continued operation during crises.