File Transfer Protocol Research Articles

The PRIDE database at 20 years: 2025 update.

The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world's leading mass spectrometry (MS)-based proteomics data repository and one of the founding members of the ProteomeXchange consortium. This manuscript summarizes the developments in PRIDE resources and related tools for the last three years. The number of submitted datasets to PRIDE Archive (the archival component of PRIDE) has reached on average around 534 datasets per month. This has been possible thanks to continuous improvements in infrastructure such as a new file transfer protocol for very large datasets (Globus), a new data resubmission pipeline and an automatic dataset validation process. Additionally, we will highlight novel activities such as the availability of the PRIDE chatbot (based on the use of open-source Large Language Models), and our work to improve support for MS crosslinking datasets. Furthermore, we will describe how we have increased our efforts to reuse, reanalyze and disseminate high-quality proteomics data into added-value resources such as UniProt, Ensembl and Expression Atlas.

Near-real-time atmospheric and oceanic science products of Himawari-8 and Himawari-9 geostationary satellites over the South China Sea

Abstract. The initial release of near-real-time (NRT) atmospheric and oceanic science products from Japanese Himawari-8 and Himawari-9 (H8/9) geostationary (GEO) satellites over the South China Sea (SCS) was unveiled in 2024. The primary objective behind crafting these NRT H8/9 satellite products is to facilitate weather and marine environment monitoring, enhance maritime security, and aid ocean navigation, among other purposes. As part of this investigation, a novel NRT data processing system was devised to generate a variety of regional H8/9 GEO satellite science products within a resolution of 10 min and a gridded resolution of 0.05° × 0.05° from 3 November 2022 to the present. This algorithm system was built upon the preceding Fengyun (FY) geostationary satellite algorithm test bed (FYGAT), which was the prototype of the FY-4 GEO meteorological satellite science product operational processing system. These regional H8/9 GEO satellite science products encompass a range of crucial data such as cloud mask, fraction, height, phase, optical, and microphysical properties; layered precipitable water; and sea surface temperature. We subjected these products to rigorous evaluations against high-quality analogous satellite products and reanalysis data spanning 1 year in 2023. The validations underscore a strong consistency between the H8/9 GEO satellite atmospheric and oceanic science products over the SCS and the referenced products. Nevertheless, slight discrepancies in these satellite science products were identified, primarily stemming from variations in sensor/dataset characteristics, retrieval algorithms, and geometric conditions. These outcomes demonstrate the suitability of the first edition of NRT atmospheric and oceanic science products of H8/9 satellites over the SCS in supporting the intended quantitative applications. This NRT GEO satellite data record is publicly accessible through the File Transfer Protocol (FTP) provided by the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) in China. Free access to the dataset is possible via https://doi.org/10.6084/m9.figshare.25015853 (Liu et al., 2024).

Efficient load balancer for local internet service providers based on operation research

Load balancing in internet services acts as a reverse proxy to distribute network bandwidth or application traffic across multiple servers. To decrease the internet route cost and to make the network intermediate devices more intelligent distance, number of hops, bandwidth capacity, equipment maintenance, power consumption ...etc must be considered. .. The aim is for the devices to have self-decision: acting upon data found in the network and transport layer protocols (Internet Protocol IP, Transmission Control Protocol TCP, File Transfer Protocol FTP, User Datagram Protocol UDP), and delivering the services to the secondary internet (wireless or optical fibers) ISPs. To achieve this target, the use of an operation research algorithm, such as linear programming, has been proposed to solve the problem of minimizing transport and distribution costs by developing and overcoming the transmission load cost of the path selection. The proposed EWRRLB (Efficient Weighted Round Robin Load Balancer) will assign different costs to each internet connection based not only on its capacity or priority but also on the cost of transmission paths. This allows load balancers to allocate the best economic path and the share of the bandwidth to certain connections.

From Fax to Secure File Transfer Protocol: The 25-Year Evolution of Real-Time Syndromic Surveillance in England.

The purpose of syndromic surveillance is to provide early warning of public health incidents, real-time situational awareness during incidents and emergencies, and reassurance of the lack of impact on the population, particularly during mass gatherings. The United Kingdom Health Security Agency (UKHSA) currently coordinates a real-time syndromic surveillance service that encompasses 6 national syndromic surveillance systems reporting on daily health care usage across England. Each working day, UKHSA analyzes syndromic data from over 200,000 daily patient encounters with the National Health Service, monitoring over 140 unique syndromic indicators, risk assessing over 50 daily statistical exceedances, and taking and recommending public health action on these daily. This English syndromic surveillance service had its origins as a small exploratory pilot in a single region of England in 1999 involving a new pilot telehealth service, initially reporting only on "cold or flu" calls. This pilot showed the value of syndromic surveillance in England, providing advanced warning of the start of seasonal influenza activity over existing laboratory-based surveillance systems. Since this initial pilot, a program of real-time syndromic surveillance has evolved from the single-system, -region, -indicator pilot (using manual data transfer methods) to an all-hazard, multisystem, automated national service. The suite of systems now monitors a wide range of syndromes, from acute respiratory illness to diarrhea to cardiac conditions, and is widely used in routine public health surveillance and for monitoring seasonal respiratory disease and incidents such as the COVID-19 pandemic. Here, we describe the 25-year evolution of the English syndromic surveillance system, focusing on the expansion and improvements in data sources and data management, the technological and digital enablers, and novel methods of data analytics and visualization.

OTHR-10. PILOT STUDY TO EVALUATE AUTOMATED LABORATORY DATA TRANSFER INTO MEDIDATA RAVE ACROSS THE NATIONAL CANCER INSTITUTE (NCI)-SUPPORTED PEDIATRIC BRAIN TUMOR CONSORTIUM (PBTC) AND PEDIATRIC EARLY PHASE CLINICAL TRIAL NETWORK (PEP-CTN) COOPERATIVE GROUPS

Abstract BACKGROUND Electronic data capture (EDC) has the potential to improve data accuracy and efficiency in oncology. The PBTC and PEP-CTN cooperative groups conducted a pilot project to 1) assess the feasibility of automated transfer of laboratory data from participating institutions’ electronic health records (EHR) to the Medidata Rave EDC housed within each consortium’s Uniform Resource Locator (URL); 2) evaluate discrepancies between retrospective automated laboratory data extraction from the EHR and manual data ascertainment during the original conduct of the study (MANUAL). METHODS Data from patients treated on 7 completed PBTC or PEP-CTN trials at 7 hospitals were included. Each consortium created a Rave instance to receive data. Sites elected to use local methods or the ExtractEHR R package to map and extract laboratory data for designated patients. Post-extraction data were uploaded to the Rave Batch Uploader (BU)-associated file transfer protocol (FTP) and BU uploaded data into Rave. After successful upload, discrepancies between EHR and MANUAL data were categorized. Two hospitals reviewed discrepancies at their sites to identify reasons for discrepancies. RESULTS Automated extraction and upload required significant PBTC/PEP-CTN operational effort and close work with hospital technical teams to map and extract data. All sites successfully extracted specified laboratory data and had ≥1 complete upload via BU to Rave; 2 sites had 2 uploads. Discrepancies were most commonly due to more data in EHR datasets (>1 result on a given day, data on additional study window days) or mismatched values or units. Differences in percentages of discrepant results between hospitals were likely due to mapping differences for EHR extraction. CONCLUSIONS This study demonstrated that in the pediatric cooperative oncology group setting automated laboratory data ascertainment can be performed. Accomplishing this required upfront central operational and hospital-based effort to prepare for data upload and transfer. This effort varied by site.

Pilot study to evaluate automated laboratory data transfer into Medidata Rave for NCI-supported pediatric cooperative group trials in the Pediatric Early Phase Clinical Trials Network (PEP-CTN) and Pediatric Brain Tumor Consortium (PBTC).

e23017 Background: Electronic data capture (EDC) has the potential to improve data accuracy and efficiency. As an initial step toward improvement in the accuracy and completeness of data acquisition for clinical trials, PEP-CTN and PBTC conducted a pilot project to assess the feasibility of automated transfer of laboratory data from participating institutions’ electronic health records to the NCI Medidata Rave EDC that is housed within each consortium’s Uniform Resource Locator (URL). The pilot aimed to assess feasibility of automated laboratory data extraction and transfer and to evaluate discrepancies between laboratory data obtained retrospectively through automated extraction and data manually ascertained during the original conduct of the study. Methods: Data from patients treated on 7 completed PEP-CTN or PBTC trials at 7 sites were included. Each consortium created a Rave EDC study to receive data. Sites used the ExtractEHR R package or local methods to map and extract laboratory data for designated patients. Post-extraction data were uploaded via a file transfer protocol (FTP) periodically polled by the Rave Batch Uploader (BU) that uploaded data into Rave EDC. After successful upload, extracted data (EHR) were compared to laboratory data that had been manually reported when patients were enrolled on the trials (MANUAL) and discrepancies were identified. Discrepancy types were categorized and 2 sites reviewed discrepancies at their sites to identify reasons. Results: Preparation and support for automated extraction and upload required significant central operations and local site effort. All sites successfully extracted specified laboratory data and had at least one complete upload via BU to Rave EDC. There were more laboratory data in the EHR datasets than MANUAL datasets across most sites. These results were due to multiple EHR results on a given day or from additional days in the study window than specified in MANUAL. Sites verified that laboratory data in MANUAL and not EHR were stored in un-extractable formats (e.g. PDFs) or outside laboratories. Most discrepant results in both EHR and MANUAL were mismatched values or units. Conclusions: This pilot demonstrated the feasibility of implementing automated laboratory data extraction and transfer in the cooperative group setting. Automated data transfer requires significant central operational support as well as detailed protocols, data specifications, and case report forms and engagement of site technical teams to be successful, but also permits collection of more comprehensive data with reduced manual data entry. Clinical trial information: NCT05020951 .

Detecting Brute Force Attacks on SSH and FTP Protocol Using Machine Learning: A Survey

The significance of detecting network traffic anomalies in cybersecurity cannot be overstated, especially given the increasing frequency and complexity of computer network attacks. As new Internet-related technologies emerge, so do more intricate attacks. One particularly daunting challenge is represented by dictionary-based brute-force attacks, which require effective real- time detection and mitigation methods. In this paper, we investigate Secure Shell or Secure Socket Shell, is a network protocol that gives users, particularly system administrators, a secure way to access a computer over an unsecured network(SSH)and File Transfer Protocol is a standard network protocol used for the transfer of files from one host to another over a TCP-based network, such as the Internet (FTP) brute-force attack detection by using Our research focuses on using the machine learning approach to detect SSH and FTP brute-force attacks. A reasonably thorough investigation of machine learners' efficacy in identifying brute force assaults on SSH and FTP is made possible by employing several classifiers. Brute-force assaults are a popular and risky method of obtaining usernames and passwords. Applying ethical hacking is an excellent technique to examine the effects of a brute-force assault. This article discusses many defense strategies and approaches to using brute-force assaults. The pros and cons of several defense strategies are enumerated, along with information on which kind of assault is easiest to identify. we made use of machine learning classifiers: Naive Bayes, Random Forest, Logistic Regression, we determined that the Random Forest algorithm achieved the highest level with an accuracy the contribution lies in demonstrating the feasibility of training and evaluating basic Random Forest models with two independent variables to classify CSE-CIC-IDS2018 dataset.

The Relevance of Development and Deployment of Software Defined Networking Solutions for a University Network

The rapid advancement of technology in today's world necessitates the development and deployment of robust and efficient networking architectures. This paper focuses on the relevant of creation and implementation of software defined networking (SDN) solutions for a university network, which offer improved network reachability and ease of navigation for network technicians. Utilizing the Ubuntu server command line interface within a virtual platform, all software defined networking components were seamlessly installed using a secure file transfer protocol client. To evaluate the effectiveness of the implemented SDN, Mininet was employed to supply OpenFlow switches within the software defined networking environment. This allowed for the integration of commands into a controller for thorough testing and assessment. The main parameters used in this paper are hosts, switches and a controller as the focus is on a single controller network. Because software defined networking centralizes and optimizes computer networks and removes irrelevant packets and frequent assaults for quick network performance, it makes networking intelligent and has several advantages over traditional networks. The successful implementation of software defined networking, as demonstrated in this paper, ensures that network technicians can swiftly identify and address challenges within computer networks of universities. This not only simplifies their tasks but also contributes to the overall efficiency and reliability of the network infrastructure.

Collecting non-native English speech through a web-and mobile-based application

The motivation behind this study is to collect non-native English speech recordings seamlessly. Even though numerous corpora containing non-native English speakers exist, there are not so many resources of Polish speakers uttering sentences in English. That is why a web-based application is built to record L2 English speakers. The same application is also developed in the mobile form as it provides easy access to the software created and, at the same time, built-in microphones ensure sufficient quality of recordings. A set of sentences is prepared, including four main types, i.e., declarative, imperative, interrogative, and exclamatory. Recordings are saved in WAV audio format. Local data are first saved in the memory of the device on which the application is installed, and then, the user may listen to the recordings and then send them to the server using FTP (File Transfer Protocol). The user interface allows for English language level selection, by choosing one of the four possible options, i.e., basic, intermediate, advanced, and fluent. A group of volunteers provided speech samples, resulting in the collection of utterances from more than 600 speakers, available in the created corpus. Future development envisions adding additional modules that will allow for speech signal analyses.

Sterling Integrator File Transfer Protocol Configurations

IBM Sterling Integrator supports a wide range of file transfer and communication protocols, including SFTP, Connect: Direct, and Mailbox (HTTP). While connecting with client servers, it’s imperative that these protocols and all other prerequisites for a successful file transfer, including authentication protocols, encryption, and file naming conventions, match between the IBM Sterling adapter for a connection and the client server.

Agile FPGA Computing at the 5G Edge: Joint Management of Accelerated and Software Functions for Open Radio Access Technologies

This paper presents ReproRun, a flexible and extensible run-time framework for the reconfiguration of functions in field programmable gate array (FPGA) devices used in popular software-defined radio (SDR) platforms. The FPGA devices embed a hardwired or soft processing system (PS) which communicates with the programmable logic (PL) using a standard embedded bus interface. In order to apply a seamless run-time partial reconfiguration, we made use of all the related building blocks, design guidelines, and tools offered by AMD-Xilinx. In ReproRun, each partial bitstream targeting a reconfigurable region (RR) of the PL area comes with its respective firmware (i.e., software functions) that runs on the PS side. Our work guarantees run-time updates of the firmware without interrupting the functionality of other software processes running in the PS or PL, by employing a specialized controller, denoted as Run-timE firmWare reconfIguration contRollEr (REWIRE). The latter leverages the open asymmetric multiprocessing framework (OpenAMP). The partial bitstreams and respective firmware are fetched from a remote location using the trivial file transfer protocol (TFTP). ReproRun can be applied in different FPGA accelerators residing in disaggregated open radio access network (RAN) equipment, adaptive radio access technologies, and Edge servers hosting virtualized functions.

Cloud-Based Infrastructure and DevOps for Energy Fault Detection in Smart Buildings

We have designed a real-world smart building energy fault detection (SBFD) system on a cloud-based Databricks workspace, a high-performance computing (HPC) environment for big-data-intensive applications powered by Apache Spark. By avoiding a Smart Building Diagnostics as a Service approach and keeping a tightly centralized design, the rapid development and deployment of the cloud-based SBFD system was achieved within one calendar year. Thanks to Databricks’ built-in scheduling interface, a continuous pipeline of real-time ingestion, integration, cleaning, and analytics workflows capable of energy consumption prediction and anomaly detection was implemented and deployed in the cloud. The system currently provides fault detection in the form of predictions and anomaly detection for 96 buildings on an active military installation. The system’s various jobs all converge within 14 min on average. It facilitates the seamless interaction between our workspace and a cloud data lake storage provided for secure and automated initial ingestion of raw data provided by a third party via the Secure File Transfer Protocol (SFTP) and BLOB (Binary Large Objects) file system secure protocol drivers. With a powerful Python binding to the Apache Spark distributed computing framework, PySpark, these actions were coded into collaborative notebooks and chained into the aforementioned pipeline. The pipeline was successfully managed and configured throughout the lifetime of the project and is continuing to meet our needs in deployment. In this paper, we outline the general architecture and how it differs from previous smart building diagnostics initiatives, present details surrounding the underlying technology stack of our data pipeline, and enumerate some of the necessary configuration steps required to maintain and develop this big data analytics application in the cloud.

Comparative performance analysis of different queuing techniques for campus area network

<span>A quality network infrastructure is a user demand for the increment of traffic nowadays. Due to data traffic congestion, a network’s service quality cannot fulfill the user demand, especially for streaming-type traffic. For this, an appropriate queuing method can be a convenient solution for network congestion at the time of picking traffic load. In this paper, a simulation was conducted using the OPNET application to examine the feasibility of three types of queuing methods, namely first in first out (FIFO), priority queuing (PQ), and weighted fair queuing (WFQ). During the simulation, several important parameters such as delay, throughput, and response time are considered as performance metrics and compared among four types of applications as file transfer protocol (FTP), hypertext transfer protocol (HTTP), voice over internet protocol (VoIP), and video conferencing. According to the result, it is observed that WFQ provides comparatively improved results than PQ and FIFO.</span>

Hybrid Internet Architecture and Protocol (HIAP): A Self-Evolving and Transformative Framework for Enabling Seamless Real-Time Applications and Secure Peer-to-Peer File Sharing in the Internet of Everything (IoE)

The Internet of Everything (IoE) is rapidly growing and utilized in various applications. However, the growing mobile traffic and services pose significant challenges in flexibility, movement, accessibility, and safety. The existing internet architecture and protocol must be improved to address the challenges. The article examines the attributes and prerequisites of forthcoming networking applications while emphasizing the constraints of conventional network architecture and protocols in fulfilling these needs. The research presents a new Hybrid Internet Architecture and Protocol (HIAP), the Self-Evolving and Transformative (SET) architecture. This architecture is designed to provide diverse control works and smart configuration options for different applications and networking conditions. This HIAP framework's primary emphasis lies in transport protocols and mechanisms for peer-to-peer file sharing. This study proposes implementing a deadline-aware multipath transport protocol within the framework of the Internet architecture with seamless support of real-time applications requiring strict adherence to latency demands. The HIAP framework incorporates evolvability, adaptable routing, and in-network cache mechanisms to enhance contentdelivery. To conduct a more comprehensive examination and conceptualize the peer-to-peer file-sharing system, the research created a pragmatic blueprint for setting the file transfer protocol on the HIAP. The study presented the groundwork for an Internet architecture better suited to the changing demands of the IoE and its various applications. This HIAP architecture aims to be more adaptable, efficient, and transformative. The present study involves a comparative analysis between the proposed research and current architecture. The findings provide evidence of the progress made by the suggested research in addressing the challenges related to multipath and safety in future architectural designs.

Congestion Analysis of Transport Layer in a Multicell 5G DL Communication System.

The fifth generation (5G) marks an important advance in mobile network capabilities. When it comes to high data rates, capacity, spectrum efficiency, and availability, 5G mobile broadband goes above and beyond what was previously possible with standard mobile broadband. The construction of 5G networks is still in the planning stages. These 5G networks will create intelligent networked communication environments by connecting people, things, data, applications, and transport networks. Mobile networks have made it possible for customers' mobile devices (such as smartphones, tablets, laptops, and so on) to connect to the internet. A variety of distinct protocols will be required to take into consideration the various aspects that 5G possess. One of these is the transport protocol, which is intended to deliver extremely high data transfer rates up to 400 Gbps. The transmission control protocol (TCP) is one of the numerous protocols that are necessary for supporting 5G's many capabilities. Our work focuses on the detection and analysis, on the downlink (DL) side, of the congestion of the transport layer in single- and multicell environments. For the purpose of the analysis, the following metrics were analyzed: physical resource blocks (PRBs), user throughput, cell throughput, cell edge user throughput, and delay. The work emphasizes the activation of the TCP slow-start algorithm using file transfer protocol (FTP) model two according to 3GPP standards.

Model view controller (MVC) architecture and client-to-client file transfer protocol with binarized spiking neural network for building a smart home appliances control in IoT

Model view controller (MVC) architecture and client-to-client file transfer protocol with binarized spiking neural network for building a smart home appliances control in IoT

Analysis of the Dynamic Source Routing Protocol on the Performance of File Transfer Protocol and Video Conference Services in the Mobile AdHoc Network Simulation

Current technological advancements make it easier for users to do their work effectively and efficiently, including the use of wireless networks to exchange data via File Transfer Protocol (FTP) and video conferencing services (VCS). A Mobile AdHoc Network (MANET) is a wireless network technology that applies a dynamic set of nodes. Data transmission on the MANET does not require the use of devices such as base stations. Because each node on the MANET can act as a router in determining the direction of the data sent, the number of nodes in the MANET will influence the quality of the data sent. Using the OPNET Modeler simulator, this paper shows how to assess the quality of FTP and VCS based on delay, jitter, and packet loss parameters. The simulation scenario employs five, fifteen, and thirty nodes with low, medium, and high traffic loads, using the Dynamic Source Routing (DSR) protocol. According to the measurement results, the FTP service with the bad category is the packet loss parameter in high traffic loads, which has the highest packet loss value of 56.6 percent with 15 nodes. In contrast, good results for VCS are only produced on the delay parameter. The jitter increases with the number of nodes, and it is 5 in this case. In all scenarios, the packet loss parameter yields poor results, with the highest packet loss value approaching 100%.

FTP Server Client Using Android Application

On a computer network, the File Transfer Protocol (FTP) is a common communication protocol used to transfer data from a server to a client. FTP uses distinct control and data connections between the client and the server in client-server architecture. FTP offers two transfer methods: an anonymous technique and a password-based authentication method. The primary goal of FTP is to encourage file sharing. Clients can connect to the server using third-party applications (eg. FileZilla). A single FTP object can manage status, connection, settings, etc. is the centre of the Apache Commons Libraries. Obtaining a remote connection to involves a set of details, including the server's hostname or IP address, a username and a password.

Recognize corrupted data packeted while transferring data through ensemble machine learning techniques

In today’s world, every technology is moving towards cloud storage which makes file transfer protocols a cornerstone for any platform to run smoothly. Therefore, identifying damaged files is a crucial responsibility in the area of data management and integrity. In this study, we suggest an AdaBoost-based machine learning technique for identifying damaged files. AdaBoost is an ensemble method that combines many weak classifiers into one powerful classifier. In our method, we train weak classifiers called decision stumps using a dataset that includes both damaged and healthy files. The final prediction was decided by a weighted majority vote of all the weak classifiers. We evaluated our method on a dataset generated by collecting metadata information of files and passed it to the algorithms. We used the AdaBoost approach as a base algorithm for comparison along with more established techniques like Naive Bayes, Logistic Regression, and Linear Discriminant Analysis. The results show that the AdaBoost algorithm is effective in detecting corrupted files, and it performs better than other traditional methods. Additionally, our method is computationally efficient and can be easily integrated into existing data management systems. It is expected to have a positive impact on data integrity and management in various fields such as digital forensics, cloud computing, and storage systems.

Hybrid load-balancing algorithm for distributed fog computing in internet of things environment

Fog computing is a novel idea created by Cisco that provides the same capabilities as cloud computing but close to objects to improve performance, such as by minimizing latency and reaction time. Packet failure can happen on a single fog server across a large number of messages from internet of things (IoT) sensors due to several variables, including inadequate bandwidth and server queue capacity. In this paper, a fog-to-server architecture based on the IoT is proposed to solve the problem of packet loss in fog and servers using hybrid load balancing and a distributed environment. The proposed methodology is based on hybrid load balancing with least connection and weighted round robin algorithms combined together in fog nodes to take into consideration the load and time to distribute requests to the active servers. The results show the proposed system improved network evaluation parameters such as total response time of 131.48 ms, total packet loss rate of 15.670%, average total channel idle of 99.55%, total channel utilization of 77.44%, average file transfer protocol (FTP) file transfer speed (256 KB to 15 MB files) of 260.77 KB/sec, and average time (256 KB to 15 MB) of 19.27 sec.