Showing papers on "Distributed File System published in 2023"

Figure S15 from Integration of Genomic and Transcriptomic Markers Improves the Prognosis Prediction of Acute Promyelocytic Leukemia

Abstract: <p>Figure S15. Kaplan-Meier plots of Combined Sanz groups and ROC plots between the Sanz score and the revised risk score. Kaplan-Meier estimates of OS (A), EFS (B), and DFS (C) when combining the Sanz low- and intermediate-risk into a single category. Comparision of the OS (D), EFS (E), and DFS (F) ROC curves between the Sanz score and the revised model score. P-value is calculated using the log-rank test. OS, overall survival; EFS, event-free survival; DFS, disease-free survival; ROC，receiver operating characteristic.</p>

Research on College English Resources Sharing Platform Based on Distributed Storage

Abstract: Distributed storage provides a more secure and convenient way of storing data by linking nodes together through computer networks. In order to meet the needs of online college English teaching, this paper builds a college English resource sharing platform based on the distributed storage IPFS technology, which decentralises data storage on multiple independent devices, significantly reducing the system’s construction cost and energy consumption. IPFS supports the creation of fully distributed applications where large files will be split into small file blocks stored in multiple server nodes and the resource platform invokes the deployed smart contracts to provide a basis for future resource copyright disputes. At the same time, IPFS provides a high-throughput content-addressable block storage model that can provide support for a wider range of applications.

Supplementary Tables 1 - 2 from Molecular Testing for Lymph Node Metastases as a Determinant of Colon Cancer Recurrence: Results from a Retrospective Multicenter Study

Abstract: <p>PDF file - 90K, Supplementary Table 1: Adjusted Association between LNR Status and Outcomes in Untreated T3N0 Colon Cancer Undergoing Molecular Staging; Supplementary Table 2: Unadjusted and adjusted association between LNR status and TTR, OS, and DFS within pMMR subgroup (N = 262).</p>

Development of hybrid storage system based on Open CAS technology, optimized for HPC workload

Abstract: HPC runs in a distributed structure with a single shared pool of data. In our case, the distributed structure is Lustre file system [4], and the single shared pool of data is our declustered HDD RAID (denoted as DCR). To increase performance, it is suggested to use Open CAS technology [3] as a cache on RAM/NVDIMM with special parameters, optimized for heavy data-intensive sequential HPC workload and an online-algorithm which reduces the number of RMW operations, by merging sequential requests into one full-stripe one.

BIFLC: A Blockchain and IPFS-Based Multi-Consensus Federated Learning Framework

Abstract: Federated learning is an efficient technology that implements distributed model training among multiple data sources with local data, and can realize data privacy protection and data sharing computing .However, existing federated learning models may involve a large number of external attacks that can reconstruct the original training data using the acquired model, resulting in possible global model or user privacy data attacks. To address the above problem, we propose a new decentralized multiconsensus federated learning model by combining blockchain and interplanetary file system (IPFS), named as BIFLC. To be specific, we firstly design an on-chain consensus process based on a blockchain hybrid consensus mechanism by introducing a proof- of-work (PoW) and a proof-of-stake (PoS) mechanism, which can ensure the integrity of the on-chain consensus process and provide a chained data hash index for data. Furthermore, we introduce the interplanetary file system to reduce the cost of storing data on the chain and employ its distributed content delivery mechanism to save bandwidth. Extensive experiments demonstrate that our proposed scheme has higher accuracy and lower IPFS transmission time.

A Dynamic Tuning Decision-Making Model Using Multi-Feature Fusion

Abstract: Dielectric Filters (DFs) are tuned to meet the requirements of 5G communication systems. The tuning methods based on Tuning Decision-Making Models (TDMMs) are efficient. However, how to build TDMMs accurately and fast is rather difficult due to the complex performance representation and the poor consistency of DFs. In this brief, a dynamic tuning decision-making model using multi-feature fusion is proposed. The contributions of this paper are as follows: 1) For the problem of incomplete feature representation of DFs performance, the multiple features are fused to improve the accuracy of TDMMs; 2) to deal with the problem that high-quality samples are challenging to obtain, a guided sampling method is designed to determine the sampling range, driven by the characteristics of DFs; 3) to solve the problem of inefficient modeling for inconsistent DFs, TDMMs are built dynamically using transfer learning. Finally, the excellent performance of the proposed method is demonstrated through comparative simulations.

Supplementary Table S3: Hazard ratios (HR) and confidence intervals (CI) for disease-free survival (DFS) using the two CTC variables and absolute CTC numbers before therapy from Prognostic Impact of Circulating Tumor Cells for Breast Cancer Patients Treated in the Neoadjuvant "Geparquattro" Trial

Abstract: <p>Changes of CTC numbers in the total study cohort or in any of the different subgroups were not related to DFS.</p>

Blockchain Based Inter-Organizational Secure File Sharing System

Abstract: A consortium of organizations collaborates and exchanges information to create synergies in their operations. Centralized systems of file-sharing cannot provide distributed trust and transparency. Blockchain technology can be used to share files securely and transparently.This paper proposes a blockchain-based inter-organizational secure file-sharing system. It can be used by a consortium of organizations to securely exchange files in a distributed fashion. Hyperledger Fabric, an enterprise blockchain framework, is used for blockchain network setup and the development of smart contracts. The Inter Planetary File System (IPFS) is used for storing files in a distributed way. The paper provides the workflow for identity management and file-sharing processes. The proposed system allows a consortium of organizations to share files with confidentiality, integrity, and availability using blockchain.

HRFP: Highly Relevant Frequent Patterns-Based Prefetching and Caching Algorithms for Distributed File Systems

Abstract: Data-intensive applications are generating massive amounts of data which is stored on cloud computing platforms where distributed file systems are utilized for storage at the back end. Most users of those applications deployed on cloud computing systems read data more often than they write. Hence, enhancing the performance of read operations is an important research issue. Prefetching and caching are used as important techniques in the context of distributed file systems to improve the performance of read operations. In this research, we introduced a novel highly relevant frequent patterns (HRFP)-based algorithm that prefetches content from the distributed file system environment and stores it in the client-side caches that are present in the same environment. We have also introduced a new replacement policy and an efficient migration technique for moving the patterns from the main memory caches to the caches present in the solid-state devices based on a new metric namely the relevancy of the patterns. According to the simulation results, the proposed approach outperformed other algorithms that have been suggested in the literature by a minimum of 15% and a maximum of 53%.

Comparative Evaluation of Hydraulic Performance of a Newly Design Dynamic Fluidic, Complete Fluidic, and D3000 Rotating Spray Sprinklers

Abstract: This chapter presents the comparison of DFS, CFS and D3000 rotating spray sprinklers at different operating pressures. The following conclusions were made. The results showed that the discharge coefficient of the DFS and D3000 was slightly larger than that of the CFS. The water distribution profiles of the DFS, D3000, and CFS were parabola-shaped, ellipse-shaped, and doughnut-shaped, respectively. It was observed that CFS had the largest radius of throw under 200 kPa than DFS and D3000. The mean value of the coefficient of discharge was 0.83, 0.86 and 0.0.843, CFS, D 3000 and DFS, respectively. The comparison of velocity distribution showed that the maximum frequency value was obtained at velocities of 1 ms −1 for each combination. Velocities for DFS and D3000 droplets were similar but not identical. Overall, CFS tends to give greater velocities than DFS or D3000. Individual spray sprinkler water distributions were mathematically overlapped to calculate the combined uniformity coefficient (CU). Maximal combined CUs of 81.83, 81.2, and 80.83% were found for the DFS, D3000, and CFS, respectively. Both the DFS and D3000 were found to have greater CU values than the CFS, which indicates that the DFS and D3000 provided a better water distribution pattern than the CFS at low pressure.

Nearly Work-Efficient Parallel DFS in Undirected Graphs

Abstract: We present the first parallel depth-first search algorithm for undirected graphs that has near-linear work and sublinear depth. Concretely, in any $n$-node $m$-edge undirected graph, our algorithm computes a DFS in $\tilde{O}(\sqrt{n})$ depth and using $\tilde{O}(m+n)$ work. All prior work either required $\Omega(n)$ depth, and thus were essentially sequential, or needed a high $poly(n)$ work and thus were far from being work-efficient.

Disease-free survival (DFS) as a surrogate endpoint (SE) for overall survival (OS) in early-stage resected esophageal/gastroesophageal junction cancer (EC/GEJC): An analysis of SEER-Medicare data.

Abstract: 321 Background: OS is the gold standard efficacy measure in oncology; however, its need for prolonged follow-up motivates the establishment of SEs for earlier assessments of emerging treatments. We assessed DFS as a candidate SE for OS in early-stage EC/GEJC using data from Medicare beneficiaries with cancer in the SEER registry. Methods: Patients aged > 65 years in the US with resective surgery after a primary diagnosis of stage 2 or 3 EC/GEJC between 2009-2017 were analyzed (N=925; median follow-up 26.2 months). Surrogacy was assessed via both individual-level association of DFS to OS, and via the association between the treatment effects on DFS and OS. Strength of individual-level association was measured via Spearman’s rank correlation (ρ) non-parametrically and Kendall’s τ using copula functions. The strength of correlation between the treatment effects on DFS and OS—measured by the coefficient of determination (R2) and the surrogate threshold effect (STE), which is the minimum DFS benefit that would translate into statistically significant OS benefit—was derived from a regression model predicting OS hazard ratio (HR) from DFS HR. Patients were classified in clusters based on treatments they received and baseline characteristics (age, sex, index year, staging, and race/ethnicity). Propensity score matching addressed imbalances in baseline characteristics between the treatment and control groups in the constructed clusters. Predictive accuracy of the surrogacy equation was assessed internally via leave-one-out cross-validation and externally via predictions made for 26 RCTs of early-stage EC/GEJC. Results: Patients were mostly male (84%), non-Hispanic white (89.3%), with median age of 71.8 years and almost evenly distributed between cancer stages 2 (50.4%) and 3 (49.6%). Among patients receiving adjuvant (23.6%) or neoadjuvant (82.8%) treatment, most (81.7% of adjuvant and 92.0% of neoadjuvant therapies) received multi-agent chemotherapy. Spearman’s ρ was estimated to be 0.76 (95% CI: 0.70, 0.89) whereas estimates for Kendall’s τ ranged between 0.62 and 0.79. Estimated R2 for the correlation between treatment effects was 0.92 (95% CI: 0.56, 1.00) and estimated from the surrogacy equation log(HROS) = 0.02 + 1.09 × log(HRDFS) with a corresponding STE of 0.86. The 95% prediction intervals generated from this equation contained the raw OS HRs for 91% of the clusters in the internal validation, and 89% of the RCTs in the external validation. Conclusions: Correlations between DFS and OS, and between the treatment effects on these endpoints, were both moderate. The highly accurate surrogacy equation between the treatment effects can enable earlier assessments of OS benefit from the DFS benefit for early-stage EC/GEJC treatments in the real-world setting.

Design for Sustainability in Manufacturing – Taxonomy and State-of-the-Art

Abstract: Abstract To meet sustainability goals, manufacturing companies are faced with the challenge of using renewable resources as well as innovative processes to design and manufacture sustainable products. For this purpose, the Design for Sustainability (DfS) approach has been suggested. Since there is no uniform understanding of how such a concept should work and which methods should be applied within it, the paper is intended to provide an overview of existing approaches. Therefore, a taxonomy of DfS approaches is introduced to enable a systematic and differentiated analysis. Afterwards, a literature review is conducted and a comprehensive overview of DfS concepts is provided. This allows for uncovering research needs towards an established DfS approach.

Small Files Access Efficiency in Hadoop Distributed File System a Case Study performed on British Library .rtf files

Abstract: Abstract In today’s world storing a large amount of data, large datasets, handling data in various forms is a challenging task. Data is getting produced rapidly with major small sized files. Hadoop is the solution for the big data problem except few limitations. This method is suggested to provide a better one for small file sizes in terms of storage, access effectiveness, and time. In contrast to the current methods, such as HDFS sequence files, HAR, and NHAR, a revolutionary strategy called VFS-HDFS architecture is created with the goal of optimizing small-sized files access problems. The existing HDFS architecture has been wrapped with a virtual file system layer in the proposed development. However, the research is done without changing the HFDS architecture. Using this proposed system, better results are obtained in terms of access efficiency of small sized files in HDFS. A case study is performed on the British Library datasets on .txt and .rtf files. The proposed system can be used to enhance the library if the catalogue is categorized as per their category in a container reducing the storage, improving the access efficiency at the cost of memory.

DFS: Joint data formatting and sparsification for efficient communication in Distributed Machine Learning

Abstract: Efficient communication is crucial to Distributed Machine Learning (DML). In this work, we propose an approach jointing Data Formatting and Sparsification (DFS) to optimize the communication in DML systems based on the parameter server framework. By doing so, we can reduce the time to transmit (aggregated) gradients between the parameter server and workers, and consequently the time to complete training jobs. More specifically, in DFS, every worker first tries to derive as many blocks with all-zero gradients as possible via sparsification, and transmits gradients block by block in a streaming fashion. By skipping blocks with all-zero gradients, we can reduce the communication cost for gradient transmission. Different from previous works on optimizing the communication in DML systems, DFS has three distinct features: (i). it dynamically determines the gradient block size; (ii). it takes into consideration both the data transfer from workers to the parameter server and that from the parameter server to workers; and (iii). it jointly optimizes the data formatting and sparsification. In other words, it performs sparsification in the way that helps form more (or larger) all-zero blocks and save more communication cost. By implementing DFS on a real testbed, we find that it can reduce the time to train a ResNet-18 model by 74.12%. Through extensive simulations, we demonstrate that DFS outperforms the state-of-the-art technique, i.e., OmniReduce (Fei et al., 2021), by up to 87.17% in terms of reducing communication cost in DML systems.

Global Research Productions Pertaining to Design for Safety: A Bibliometric Analysis Based on WoS Database

Abstract: Design for Safety (DFS) is a crucial tool that assists humans in paying closer attention to safety and health in project life cycles of buildings and other facilities. Analyzing DFS through a bibliometric perspective can facilitate the development of new theories, promote disciplinary content, and reveal the direction of development in the subject area. This paper presents a systematic, holistic, and comprehensive overview of the global literature focused on DFS, summarizing the number of publications, research hotspots, research methods, and distribution. Scientific publications are a measure of academic level and scientific strength of institutions and individuals, and this article provides an overview of interdisciplinary research on DFS from 1 January 1997 to 31 December 2020, based on literature related to DFS in the Web of Science database (WoS-database). The paper highlights current research hotspots, ideas, and trends around the world, offering a global overview of contemporary and interdisciplinary research in DFS. By utilizing both keyword clustering and co-citation clustering techniques, the paper proposes the 4P framework (i.e., purpose, people, procedures, and phenomena) to better understand current global achievements and to achieve a complex structure for future development. This concise description of DFS trends may provide a logical mechanism for assessing and understanding the development of DFS research.

Dynamic Replication Policy on HDFS Based on Machine Learning Clustering

Abstract: Data growth in recent years has been swift, leading to the emergence of big data science. Distributed File Systems (DFS) are commonly used to handle big data, like Google File System (GFS), Hadoop Distributed File System (HDFS), and others. The DFS should provide the availability of data and reliability of the system in case of failure. The DFS replicates the files in different locations to provide availability and reliability. These replications consume storage space and other resources. The importance of these files differs depending on how frequently they are used in the system. So some of these files do not deserve to replicate many times because it is unimportant in the system. This paper introduces a Dynamic Replication Policy using Machine Learning Clustering (DRPMLC) on HDFS, which uses Machine Learning to cluster the files into different groups and apply other replication policies to each group to reduce the storage consumption, improve the read and write operations time and keep the availability and reliability of HDFS as a High-Performance Distributed Computing (HPDC).

Decentralizing File Sharing: The Potential of Blockchain and IPFS

Abstract: This research paper delves into the potential of using blockchain technology and the Interplanetary File System (IPFS) for file sharing. The current state of file sharing is analyzed, and it is found that centralized servers pose many challenges, such as security and privacy issues. The paper then investigates how blockchain and IPFS can provide a decentralized and secure solution for file sharing. The analysis of specific use cases and existing projects such as File Coin, which utilizes IPFS and a blockchain-based marketplace to allow users to rent out unused storage space, is also presented. The paper also addresses the limitations and challenges of using this technology, including scalability and regulatory issues. The research concludes that the combination of blockchain and IPFS has the potential to revolutionize the way digital content is shared and distributed, providing new opportunities for secure and efficient file sharing. The paper also explores other decentralized storage solutions, such as Sia, Storj, and MaidSafe, and how they compare to IPFS and blockchain-based file-sharing solutions. The research also evaluates the potential impact of this technology on various sectors, such as the media, entertainment, and healthcare industries. Overall, this research aims to provide a comprehensive understanding of the topic and its potential impact on the future of file sharing. The advancement of technology has impacted the way information is shared and distributed, with traditional file-sharing methods facing numerous security and privacy challenges. This research paper investigates the potential of using blockchain technology and the Interplanetary File System (IPFS) for file sharing as a means of addressing these challenges. This research paper argues that the combination of blockchain technology and IPFS holds great promise for the future of file sharing.

An Efficient Blockchain-Based Framework For File Sharing

Abstract: Abstract File sharing is the foundation of the Internet. But the traditional centralized service architecture will result in huge infrastructure costs and maintenance costs. Due to the lack of effective file management system, a lot of sensitive information is out of control and loss of confidentiality document has occur from time to time. In order to address the difficulty of tamper detection and the lack of supervision in the entire process of file transmission in the current Internet environment, this paper designs a block-chain-based system architecture for secure sharing of electronic documents. An efficient Blockchain model is used in our framework, and with the help of distributed storage system and asymmetric encryption technology, file sharing can be controlled, reliable and traceable in the transmission process.Referring to existing consensus mechanism, e.g., Delegated Proof of Stake (DPoS) and Practical Byzantine Fault Tolerance (PBFT), we propose a new consensus for efficient and secure file sharing.

An indirect assessment of individual-level association between disease-free survival (DFS) and overall survival (OS) for resectable esophageal or gastroesophageal junction cancer (EC/GEJC): A pooled analysis of randomized controlled trials (RCTs) by an illness-death model.

Abstract: 369 Background: Validation of intermediate endpoints such as DFS as surrogates for overall survival (OS) in RCTs at individual-level remains as a challenge due to difficulty of collection of individual-level patient data. This study explores the individual-level correlation between DFS and OS indirectly using reconstructed Kaplan-Meier (KM) curves from the RCTs assessing therapies for (neo)adjuvant and perioperative treatment of EC/GEJC. Methods: An illness-death model previously validated in estimating individual-level association between DFS and OS for four correlation meta-analyses, two of which were published by the GASTRIC group, in early and late stage treatment of gastric cancer was employed. Reconstructed DFS and OS data from 25 RCTs published between 1994 - 2020 was pooled separately for each arm and each endpoint. Pooled data was analyzed to estimate the correlation between DFS and OS, as measured by Pearson’s r, Spearman’s rho, and Kendall’s tau. Predictive accuracy of the approach was evaluated by comparing its OS and restricted mean survival time (RMST) predictions to their counterparts obtained from the reported OS data from the RCTs. Sensitivity of correlation measures were assessed with respect to pre-specified variations in pre-recurrence death probability, post-recurrence mortality rate, and choice of the survival model used to extrapolate reported DFS curves from the RCTs. Results: Across all RCTs, the primary cancers covered were EC (n=13), EC/GEJC(n=9), GEJC (n=2) and GEJC/gastric cancer (n=1). According to the histology, 10 RCTs studied only squamous cell carcinoma (SCC) and 9 RCTs studied only adenocarcinoma (AC) of the disease, whereas the remaining 6 RCTs included varying mixtures of SCC and AC patients. The follow-up duration ranged between 27 and 72 months across RCTs. Comparator and intervention arms of the pooled data had 2499 and 2490 patients, respectively. Predicted Pearson’s r, Spearman’s rho, Kendall’s tau were 0.67, 0.79, and 0.70, respectively with negligibly narrow 95% CIs. Across both arms of the pooled data, on average, predicted OS curves laid within the 95% CIs of the pooled OS KM-curves 92% of the time. Average deviation between the RMSTs under the model-predicted OS curves and pooled OS KM curves was 2%. In sensitivity analyses, the ranges for r, r, and t were (0.56-0.88), (0.69-0.89), and (0.61-0.80), respectively. Conclusions: Results indicate moderate-to-strong correlation between DFS and OS in early-stage treatment of EC/GEJC providing supportive evidence for the validation of DFS as a surrogate for OS. Our approach mitigates the lack of patient level data in endpoint correlation assessment but may be prone to changes in the predicted value of pre-recurrence death probability.

Implementation of design for construction safety (DfS) in the Vietnam context: awareness, attitude and practices

Abstract: Purpose This paper aims to inquire into the awareness of Vietnamese architects about design for safety (DfS) and the level of engagement in applying DfS among them to get a generic view of the implementation of DfS in Vietnam. Design/methodology/approach Quantitative research was used, in which a questionnaire was sent to Vietnamese architects to evaluate how they consider and apply DfS in the design process. Inferential and descriptive statistics then analysed the obtained data to identify the role of each factor. Findings The results from the survey conclude that Vietnamese architects have low engagement in applying DfS despite their high awareness and positive attitude towards DfS. Besides, the participants showed the need for further DfS education and training, which is lacking in Vietnamese formal education. In addition, the research also confirms that DfS education and training have positive impacts on the frequency of DfS implementation in Vietnam. Research limitations/implications This research contributes to the knowledge of DfS implementation in developing countries. In line with this, further studies on the DfS concept in developing countries are needed to draw a more objective overview and give the solution for the low DfS appliance. Originality/value To the best of the authors’ knowledge, this is the first study inquiring into the implication of DfS in Vietnam, contributing to improving the lack of knowledge in this field in developing countries and Vietnam in particular.