Data Transfer Research Articles

A coupled peridynamics–smoothed particle hydrodynamics model for fluid–structure interaction with large deformation

Fluid–structure interaction (FSI) is ubiquitous in various engineering disciplines, and effectively managing FSI often appears to be the key for successful failure analysis and safety-oriented design. Smoothed particle hydrodynamics (SPH) serves as a potent nonlocal meshfree method for fluid dynamics modeling, while peridynamics (PD) demonstrates exceptional capability in addressing structural dynamics involving large deformations and discontinuities. Thus, leveraging their respective strengths in a combined approach holds significant promise for tackling FSI challenges. In this work, we propose a new peridynamics–smoothed particle hydrodynamics (PD-SPH) coupling model for addressing FSI. A stable and efficient coupling algorithm for data transfer between PD and SPH is put forward. In this coupling strategy, a PD particle directly participates in solving the SPH governing equations when it is identified to be within the support domain of an SPH particle. This can be done since the SPH quantities including the density, velocity, and pressure of a PD particle are naturally attainable within the framework of non-ordinary state-based peridynamics theory. Concurrently, in solving PD governing equations, reaction forces from SPH particles act as external forces for PD particles, determined straightforwardly through Newton's third law. As such, the proposed PD-SPH coupling strategy is straightforward to implement and offers high computational efficiency. Validation examples demonstrate that the proposed PD-SPH coupling model is computationally robust and adept at capturing physical phenomena in diverse FSI scenarios involving breaking free surfaces of fluid and large structural deformations of solid. Moreover, the proposed PD-SPH coupling model is flexible introducing no constraint conditions for applications and can accommodate different particle resolutions for PD and SPH domains. These features enable a broad application range of the proposed PD-SPH coupling model including simulations of explosion-induced soil fragmentation, rock fracture, and concrete dam failure, which will be conducted by authors in the near future.

Cottontail Rabbit Papillomavirus (CRPV) Related Animal Models for Head and Neck Cancer Research: A Comprehensive Review of the Literature

Having suitable animal models is crucial to mimic human disease states and for the successful transfer of experimental data into clinical practice. In the field of papillomavirus research, the domestic rabbit (Oryctolagus cuniculus) has served as an indispensable model organism for almost 100 years. The identification and characterization of the first papillomaviruses in rabbits, their carcinogenic potential and their immunogenicity have contributed significantly to the state of knowledge on the genetics and life cycle of papillomaviruses in general, as well as the development of antiviral strategies such as vaccination procedures. Due to the high species specificity of papillomaviruses, only rabbit papillomaviruses (RPVs) can be used for animal studies on papilloma-based tumor diseases in the rabbit. The major focus of this article is on cottontail rabbit papillomavirus (CRPV)-related rabbit squamous cell carcinoma (RSCC). A brief history outlines the discovery and generation of experimentally used RSCC tumors. A comprehensive overview of the current CRPV-associated VX2 carcinoma-based tumor models with a major focus on human head and neck squamous cell carcinoma (HNSCC) tumor models is provided, and their strengths in terms of transferability to human HNSCC are discussed.

Driving into the Future: Creating a Cloud-Based Platform for Seamless Data Transfer and Enhanced Autonomous

Driving into the Future: Creating a Cloud-Based Platform for Seamless Data Transfer and Enhanced Autonomous

Optimizing IOT Network Performance: A Study on Low-Power Wide-Area Network (LPWAN) Technologies for Smart City Applications

Abstract: This research explores with a specific focus on smart city applications, how to optimise the execution of Web of Things (IoT) networks by utilising breakthroughs in Low-Powered Wide Area Networks (LPWAN). As IoT devices proliferate and generate vast amounts of data, having a competent network becomes essential, especially when dealing with low device thickness and limited power availability. This analysis provides a detailed energy consumption model tailored to LoRaWAN, based on a deeper understanding of its functional components in Internet of Things scenarios. The review uses MATLAB for replication and looks at two clear scenarios: the standard allocation of spreading factors without optimisation and an improved method that uses particle swarm optimisation (PSO) for dynamic spreading factor work. The results show that the network energy consumption dropped significantly, from 6.3997×10^ (- 17) Joules to 2.5230×10^(- 17) Joules, along with increased throughput, decreased parcel misfortune, and decreased idleness. Through a detailed analysis of several parameters, such as network density and data transfer efficiency, this study demonstrates the feasibility of the suggested optimisation model in terms of improving battery efficiency and overall network performance. Finally, the findings demonstrate how efficient LPWAN systems may provide robust and useful IoT environments, which are essential for the successful implementation of smart city initiatives.

Digital watermarking algorithm for QR code based on hybrid PSOGWO optimization

Abstract With the rapid development of digital media, QR codes have become widely used as an important medium for information transmission. However, this also presents serious security challenges, such as frequent image infringement and inevitable compression and scaling issues during data transfer. These challenges directly threaten the effectiveness and integrity of image information, and effective protection measures must be taken. Under this background, digital watermarking technology comes into being as an innovative method to enhance security. This paper presents an innovative Hybrid Particle Swarm Optimization and Gray Wolf optimization (HPG) algorithm, which combines the advantages of PSO and overcomes the limitations of traditional GWO algorithm. The algorithm is further improved by using Bernoulli chaotic mapping and nonlinear convergence factor. The experiments focus on the global and local search balance of the algorithm and its ability to resist repeated scaling attacks. The results show that the nonlinear convergence factor of HPG algorithm slows down the iteration speed at the initial stage, strengthens the global search, and avoids falling into the local optimal. In the later stage, the iteration is accelerated to improve the local search speed and convergence efficiency, thus optimizing the performance of the algorithm and ensuring the safety and quality of image information. In addition, the algorithm has better performance in balancing imperceptibility and robustness of digital watermarking, and its peak signal-to-noise ratio (PSNR) is higher. Even with many scaling iterations, the normalized correlation (NC) value is still close to 1. Compared with the existing typical algorithms, HPG algorithm is more robust to repeated scaling attacks.

Convergence of SaaS, AI, and Telecom in Telehealth: Transforming the future of healthcare delivery through intelligent systems

This paper aims at identifying and analyzing how SaaS, AI, and Telecom are changing the way healthcare is delivered by focusing on telehealth. The goal is to determine the current status of these combining technologies, identify future developments and trends in intelligent telehealth systems, and analyze the opportunities and risks associated with their implementation. Following a systematic review, relevant publications published between January 2014 and January 2024 were gathered from various databases. Finally, eight studies were included for analysis, after exclusion and inclusion criteria were applied. The findings show that SaaS, AI, and Telecom are transforming telehealth by improving the remote patient monitoring, the access to care, and the moving from the reactive to the proactive approach to health. SaaS enhances adaptable and affordable approaches, while AI infuses precise identification and reasoning. Telecom provides secure and steady communication and data transfer while facing issues regarding data security, legislation acts, and disparities in infrastructure. Overall, these research studies highlight the key possibilities of developing the application of telehealth through the integration process of these technologies.

Green Edge: Harnessing situational awareness for sustainable systems

Green computing and Building Management Systems (BMS)are closely related through their shared goal of improving energy efficiency and reducing environmental impact. Field controllers that connect with the sensors and actuators at the field level act as an interface between field devices and enterprise applications. Data transfer, protocol conversion, data processing, computing, and control actuators based on predefined logic are the functions of the field controllers. Fast response time is one of the crucial parameters of these field controllers hence reducing the load on these field controllers by enabling Edge computing functionality is very much required. Maharudrayya Nandimath and others [16] in their “Edge Computing in IBMS (Integrated Building Management Systems). (2024 International Conference on Computer Communication and Informatics (iccci. in)) the paper suggested many of the measures to reduce the load on these field controllers. Building Management Systems are essential for optimizing the operation of modern buildings, ensuring comfort, safety, and energy efficiency. By integrating advanced technologies such as Situation Awareness (SA) and Artificial Intelligence (AI), BMS can be significantly enhanced to provide real-time monitoring, predictive maintenance, and intelligent decision-making. This paper explores the potential of combining SA and AI with BMS, leveraging insights from recent research on industrial processes, IoT cloud-edge continuum, and smart cities. The proposed system architecture includes feedback loops and contextual awareness, aiming to improve building operations and reduce energy consumption, thereby supporting global sustainability goals.

Prospects and challenges of mobile banking in Bangladesh: A case study

Mobile banking is a technology advancement that enables convenient, anytime, anywhere access to financial services. When using mobile banking, customers can access banking services via their phones without having to wait in line. It is a branchless kind of banking. The purpose of the study was to identify the prospects and challenges facing Bangladeshi mobile banking in the twenty-first century. Over 80 respondents were selected using Yaro Yamani formula from a sample of bank clients and bankers and given a standardized questionnaire. The study's goal has been perceived through the application of the descriptive research approach. Based on the study's findings, people's interest in mobile banking is growing daily due to its advantages. Certain banks do not presently offer all mobile banking services, and not all respondents are aware of all the mobile banking options available. Fast data transfer and cost-effective usage are two factors that entice customers. Some of the disadvantages of mobile banking are that it is very expensive, private, complex, etc. Lowering operational risks and increasing consumer confidence in Bangladesh's mobile banking services can be achieved through robust technical information control and security procedures that ensure the integrity and confidentiality of financial transactions.

Assessing the Impact of Cryptography on the Security of Wireless Ad Hoc Networks

The use of wireless networks for communication in bistros, airports, hotels, offices, colleges, and other public locations is increasing as they become more widespread. Although remote organisations and its applications are becoming increasingly widely recognised, security concerns related to them have grown to be of great concern. In this investigation, we'll develop a different plan to implement quantum cryptography for key distribution in 802.11 companies. They are helpful because of their adaptability and quick data transfer in residences, workplaces, and businesses. Given the principles of material science, quantum cryptography enables unfettered security for the exchange of cryptographic keys between two distant meetings. This investigation's main goal is to investigate potential vulnerabilities and security concerns in remote organization correspondence and give a structure to unqualified security in remote systems administration utilizing quantum key dispersion (QKD).

Advancements in Network Attached Storage (NAS) for Mobile Devices: Technological Developments and Performance Assessment

Network-attached storage (NAS) technology has emerged as a vital solution in the evolving landscape of data management and storage. With the exponential growth of data and the increasing demand for efficient, scalable storage solutions, NAS systems offer a centralized, cost-effective, and flexible alternative to traditional storage methods. This paper explores the application and advantages of NAS technology in various scenarios, from home and small business environments to large enterprises. It highlights the key strengths of NAS systems in optimizing data storage, ensuring data security, and facilitating cross-device sharing. The study delves into the architectural components of NAS, including file systems, RAID configurations, and network protocols, to demonstrate how these technologies enhance storage performance and reliability. Technical details on NAS system design, such as the integration of advanced file systems and user-level networking technologies, are discussed to showcase their impact on data transfer efficiency and overall system performance. Experimental results validate the effectiveness of NAS in different environments, illustrating its ability to provide high availability, data redundancy, and low-latency data access. The findings underscore NAS technology’s potential as a versatile and scalable storage solution, with recommendations for future research focused on developing new file systems, optimizing network protocols, and exploring edge computing integrations to further enhance NAS capabilities.

Design and Implementation of Digital Twin Factory Synchronized in Real-Time Using MQTT

As information technology progresses, the need for digital transformation within the industrial sector has become increasingly apparent, and digital twin technology has emerged as a significant trend in manufacturing. Digital twins synchronize physical and digital environments, overcoming spatial and temporal limitations to create various added values that are unattainable in reality. This paper presents a model that integrates digital twin technology with production and operational technologies at manufacturing sites, enabling remote, centrally controlled manufacturing services that transcend physical constraints. Specifically, by utilizing Message Queuing Telemetry Transport (MQTT) for real-time synchronization, this approach ensures efficient and timely data transfer between physical and digital environments. While traditional approaches often encounter challenges due to high investment costs and design complexities, this paper proposes a cost-effective and practical solution that reflects actual factory conditions.

Design and Implementation of a Synchronous AHB to APB Bridge in System-on-Chip Applications

The requirement of effectively combining key units in an integrated system is proliferating. SoC system is developed to provide a chip-level integration, which become the inevitable trend of integrated circuit development and is widely used in smartphones, industrial applications, and microcontrollers. The ARM AMBA protocol works as a universally adopted way of interaction between various parts of the system. In AMBA architecture, the AHB to APB bridge significantly contributes to combining the high-performance AHB bus and low-power APB bus in the SoC system. This project is to implement an AHB to APB bridge using Verilog, enabling stable data transfer between these two buses. The proposed AHB to APB bridge is intended to fit different read or write strategies and ensure the proper working of the peripherals on the APB bus. The bridge has been implemented via Verilog Hardware description language (HDL). A test bench was created with a virtual AHB host and an optimized SRAM as the high-speed APB peripheral. Verdi simulation shows the bridge completely meets the design intention.

Performance comparison on improved data-driven building energy prediction under data shortage scenarios in four perspectives: Data generation, incremental learning, transfer learning, and physics-informed

Accurate building energy predictions (BEPs) are crucial for maintaining a built environment's sustainability and energy systems. Many data-driven BEPs rely heavily on sufficient data. However, circumstances of practical data shortage restrict the application of these data-driven models to information-poor buildings. This study aims to address this research gap by enhancing BEP performance via the consideration of four perspectives: data generation (DG), incremental learning (IL), transfer learning (TL) and physics-informed (PI). Long short-term memory (LSTM) is selected as the baseline model for comparing performance under extreme (target building dataset: 1-week), heavy (4-weeks) and mild (13-weeks) data shortage scenarios with respect to prediction errors, time costs and the Taylor diagram, among others. The implementation algorithms of four LSTM improved models are conditional variational autoencoder (CVAE), crude incremental learning, domain-adversarial neural network and statistics-informed (SI) for DG, IL, TL and PI, respectively. The effectiveness of the four enhanced models was confirmed using the open-source dataset Building Data Genome Project 2. A comprehensive and fair performance comparison recommends CVAE for extreme and heavy data shortage scenarios with average mean absolute per cent error (MAPE) of 12.79 % and 8.63 % as well as performance improvement ratios (PIRs) of 0.45 and 0.57. SI should be recommended for mild data shortage scenarios with MAPE of 8.01 % and PIR of 0.66.

The French experiential knowledge resource center: strengthening and extending its scope of action

Abstract Issue The national committee for experiential knowledge in health promotion (EKHP) aims to promote EKHP and improve professional practices. Since 2017, the committee has created methods and toolkits formalizing the capitalization of EKHP. The levers to put the method into practice are in place, now comes the time to find the best means to foster promotion and appropriation of EKHP works. Description of the problem The national EKHP resource center has been launched in May 2022, online: www.capitalisationsante.fr. It acts as a database where HP practitioners can read, download and upload EKHP capitalization works (∼12-page documents detailing one HP intervention each) and cross-analyses reports. It is driven by three main objectives: 1/ promoting and disseminating HP practitioners’ experiential knowledge, 2/ building a community of practice to improve capitalization practices and 3/ making a useful and transferable data available to practitioners. Results The now two-year-old website has been visited by 32 000+ individuals. More than 120 works, 12 cross-analyses are published. They were submitted by trained HP practitioners and reviewed by an editorial board before publication. The national EKHP resource center offers insight on how HP interventions work from practitioners themselves who share knowledge on their implementation. Compared to best-practices portals, it offers an innovative bottom-up approach to knowledge transfer. The community of practice (CoP) now supports a network of 200+ trained practitioners. This CoP aims to improve knowledge management and ensure the quality of the works produced. Surveys and feedback show that both building up and accessing EKHP meet a high level of interest. Lessons The innovative bottom-up approach and the focus on knowledge management can serve as a model for other settings/countries. In 2024, levers of appropriation will be investigated and collaboration with other HP resource centers will be better identified. Key messages • The now two-year-old national NEKHPRC enhances EK’s part in the HP field by making otherwise unknown data available to the French-speaking HP community. • Building of a strong community of practice ensures the high quality of the bottom-up approach to the uploading of the works.

OSC-GOR: Optimal Security-Aware Cluster-Based Hybrid Geographical and Opportunistic Routing for Vehicular ad hoc Networks

Vehicular ad hoc networks (VANETs) are crucial for infrastructure-less vehicular communication. The dynamic and complex nature of VANETs necessitates efficient routing strategies. This paper introduces an optimal security-aware cluster-based hybrid geographical and opportunistic routing (OSC-GOR) for VANETs. By utilizing the improved bald eagle optimization (IBEO) algorithm, we achieve optimal clustering that enhances energy efficiency. Cluster heads (CHs) are elected based on trust, calculated from metrics like energy consumption and signal strength. A Poplar optimization algorithm (POA) further refines these metrics. Subsequently, an optimal min–max recurrent neural network (OMM-RNN) determines the next forwarder nodes, facilitating data transfer in VANETs. Implemented using the NS-2 tool and SUMO traffic generator, OSC-GOR showcases optimized clustering and superior network efficiency. Comparative simulations reveal OSC-GOR’s advantages in energy use, latency, delivery ratio, goodput, and routing overhead, outperforming existing methods. Notably, OSC-GOR effectively counters VANET attacks such as GPS spoofing and Sybil threats.

Theories and Methods for Indoor Positioning Systems: A Comparative Analysis, Challenges, and Prospective Measures

In the era of the Internet of Things (IoT), the demand for accurate positioning services has become increasingly critical, as location-based services (LBSs) depend on users’ location data to deliver contextual functionalities. While the Global Positioning System (GPS) is widely regarded as the standard for outdoor localization due to its reliability and comprehensive coverage, its effectiveness in indoor positioning systems (IPSs) is limited by the inherent complexity of indoor environments. This paper examines the various measurement techniques and technological solutions that address the unique challenges posed by indoor environments. We specifically focus on three key aspects: (i) a comparative analysis of the different wireless technologies proposed for IPSs based on various methodologies, (ii) the challenges of IPSs, and (iii) forward-looking strategies for future research. In particular, we provide an in-depth evaluation of current IPSs, assessing them through multidimensional matrices that capture diverse architectural and design considerations, as well as evaluation metrics established in the literature. We further examine the challenges that impede the widespread deployment of IPSs and highlight the potential risk that these systems may not be recognized with a single, universally accepted standard method, unlike GPS for outdoor localization, which serves as the golden standard for positioning. Moreover, we outline several promising approaches that could address the existing challenges of IPSs. These include the application of transfer learning, feature engineering, data fusion, multisensory technologies, hybrid techniques, and ensemble learning methods, all of which hold the potential to significantly enhance the accuracy and reliability of IPSs. By leveraging these advanced methodologies, we aim to improve the overall performance of IPSs, thus paving the way for more robust and dependable LBSs in indoor environments.

Experimental Outdoor Vehicle Acoustic Testing Based on ISO-362 Pass-by-Noise and Tyre Noise Contribution for Electric Vehicles

This paper focuses on the novel and unique training provision of acoustics relevant for noise, vibration, and harshness (NVH), focused on the ISO-362 standard highlighting important design aspects for electric vehicles. A case study of the practical implementation of off-site vehicle testing supporting an acoustics module is described, detailing a time-constrained test for automotive pass-by-noise and tyre-radiated noise with speed. Industrial test standards are discussed, with education as a primary motivation. The connections between low-cost, accessible equipment and future electric vehicle acoustics are made. The paper contains a full equipment breakdown to demonstrate the ability to link digital data transfer, analogue-to-digital communication, telemetry, and acquisition skills. The benchmark results of novel pass-by-noise and tyre testing are framed around discussion points for assessments. Inexpensive Arduino Uno boards provide data acquisition with class 1 sound pressure meters, XBee radios provide telemetry to a vehicle, and a vehicle datalogger provides GPS position with CANBUS data. Data acquisition is triggered through the implementation of light gate sensors on the test track, with the whole test lasting 90 minutes.

Security analysis and provision of authentication protocol, based on peer-to-peer structure in IOT platform

The Internet of Things technology allows you to transfer data to any asset through communication networks such as the Internet or intranet. One of the most important problems is security, which includes confidentiality, authenticity validation, and completeness. Among security problems, the most important ones are ensuring authenticity and protecting privacy. The elliptic curve encryption algorithm is famous protocols for maintaining privacy and verifying authenticity. Despite the capabilities they have and provide good security against network attacks, they face challenges such as response time, delay in the authentication and authentication process, as well as the amount of memory consumed. Two-factor authentication (2FA) is a security process where users provide two different authentication factors to authenticate themselves. It also provides a higher level of security than authentication methods that rely on single-factor authentication (SFA). This article presents two novel methods for 2FA that use encryption techniques, scramble architecture, and chord architecture. These methods allow for the authentication process to be initiated by both parties involved in the communication. Three scenarios and three metrics of reaction time, memory usage, and connection latency were used to assess the efficacy of the suggested approach. The average reaction time is improved and is 0.012 s when the lengths of the finger table in the chord structure are increased to 10, 15, and 20. The findings show that the suggested approach reduces computing complexity, reaction time, and communication latency. It has an average reaction time of 0.016 s, an average memory use of 30,360 kb, and an average connection latency of 0.042 s.

A comprehensive analysis of security mechanism for CSMA/CD Networks: A Survey

In this essay, we examine security against several types of harmful assaults. We also include several known practicable assaults in this. We also learn about secure communication for various mechanisms that offer confidentiality, security, and authentication for the majority of security concerns. An active repeater in CSMA/CD for network comparison for data transfer between two addresses is what we learn about in a logical part. If there is no match, the logic portion instructs the transmitter to switch from broadcasting the data packet to transmitting the clock signal. Bidirectional routing messages are sent from the wireless network to the wired network.At the conclusion, we receive comparison results for the transmitted and received messages to determine if a collision has happened.

Current State of Connected Sensor Technologies Used During Rehabilitation Care: Protocol for a Scoping Review.

Connected sensor technologies can capture raw data and analyze them using advanced statistical methods such as machine learning or artificial intelligence to generate interpretable behavioral or physiological outcomes. Previous research conducted on connected sensor technologies has focused on design, development, and validation. Published review studies have either summarized general technological solutions to address specific behaviors such as physical activity or focused on remote monitoring solutions in specific patient populations. This study aimed to map research that focused on using connected sensor technologies to augment rehabilitation services by informing care decisions. The Population, Concept, and Context framework will be used to define inclusion criteria. Relevant articles published between 2008 to the present will be included if (1) the study enrolled adults (population), (2) the intervention used at least one connected sensor technology and involved data transfer to a clinician so that the data could be used to inform the intervention (concept), and (3) the intervention was within the scope of rehabilitation (context). An initial search strategy will be built in Embase; peer reviewed; and then translated to Ovid MEDLINE ALL, Web of Science Core Collection, and CINAHL. Duplicates will be removed prior to screening articles for inclusion. Two independent reviewers will screen articles in 2 stages: title/abstract and full text. Discrepancies will be resolved through group discussion. Data from eligible articles relevant to population, concept, and context will be extracted. Descriptive statistics will be used to report findings, and relevant outcomes will include the type and frequency of connected sensor used and method of data sharing. Additional details will be narratively summarized and displayed in tables and figures. Key partners will review results to enhance interpretation and trustworthiness. We conducted initial searches to refine the search strategy in February 2024. The results of this scoping review are expected in October 2024. Results from the scoping review will identify critical areas of inquiry to advance the field of technology-augmented rehabilitation. Results will also support the development of a longitudinal model to support long-term health outcomes. Open Science Framework jys53; https://osf.io/jys53. DERR1-10.2196/60496.