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Multidisciplinary Sciences
Adina S. Wagner, Laura K. Waite, Malgorzata Wierzba, Felix Hoffstaedter, Alexander Q. Waite, Benjamin Poldrack, Simon B. Eickhoff, Michael Hanke
Summary: This paper introduces a DataLad-based framework for reproducible data processing in compliance with open science mandates. The framework allows capturing machine-actionable computational provenance records to trace and verify research outcomes, as well as re-executing them on different computing infrastructures.
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Multidisciplinary Sciences
Ahmed Sharafeldeen, Mohammed Alrahmawy, Samir Elmougy
Summary: This paper proposes two new MapReduce algorithms based on graph partitioning, which solve the problem of duplicate counting triangles in other algorithms. The experimental results show that these two algorithms are highly efficient, especially in very large-scale graphs, outperforming an existing algorithm in terms of execution time performance.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Artificial Intelligence
Sapana Rani, Raju Halder
Summary: This paper proposes an efficient distortion-free watermarking technique for large-scale datasets in various formats using parallel and distributed computing environment. Experimental evaluation shows performance depends on data format and chosen computing paradigm.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Theory & Methods
Steven J. Plimpton, Christopher Knight
Summary: Rendezvous algorithms are effective for communication patterns in scientific computing when processors do not know the counterpart processors for data exchange. They are particularly useful for large-scale simulations and massive parallel processing, demonstrating significant performance improvements over simpler algorithms.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Yuhua Chen, Hasri Mustafa, Xuandong Zhang, Jing Liu
Summary: In order to improve the information application level of financial management and the business value of financial big data, this article automatically classifies financial data using the fuzzy clustering algorithm and detects abnormal data using the local outlier factor (LOF) algorithm based on neighborhood relation. A financial data management platform based on distributed Hadoop architecture is designed, combining MapReduce framework with the fuzzy clustering algorithm and LOF algorithm to enhance the algorithm's performance and accuracy, thus improving operational efficiency of enterprise financial data processing. Comparative experimental results demonstrate that the proposed platform achieves the best running efficiency and financial data classification accuracy compared with other methods, illustrating the effectiveness and superiority of the platform.
PEERJ COMPUTER SCIENCE
(2023)
Article
Computer Science, Information Systems
Shiva Asadianfam, Mahboubeh Shamsi, Abdolreza Rasouli Kenari
Summary: Maintaining fluid and safe traffic is a major challenge for human societies, and using Hadoop to process large-scale data can effectively address traffic issues.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Rui Han, Chi Harold Liu, Shilin Li, Lydia Y. Chen, Guoren Wang, Jian Tang, Jieping Ye
Summary: This article challenges the prevalent assumption in machine learning that all data points are equally relevant to model parameter updating, proposing a new SlimML framework that trains models only on critical data points to significantly improve training performance. Experimental results show that SlimML accelerates the model training process by an average of 3.61 times for large datasets, with only a 0.37% accuracy loss.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Mohamed A. Helala, Faisal Z. Qureshi, Ken Q. Pu
Summary: This paper discusses the challenges in building and optimizing large-scale computer vision systems and proposes a formal algebra framework and a general optimizer to address these challenges.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Bryan Martin, Karen C. Davis
Summary: Advancements in modern hardware architectures and database technology have led to the increased adoption of logical data warehouses (LDWs) as complements to traditional physical data warehousing (PDW) approaches. LDWs allow for integration and transformation of data at run-time, with a focus on replicating high value data to physical core for spatial locality in premium hardware environments. This study explores the support and evaluation of LDW design algorithms in multi-temperature storage systems.
Article
Engineering, Electrical & Electronic
Victor Croisfelt, Abolfazl Amiri, Taufik Abrao, Elisabeth de Carvalho, Petar Popovski
Summary: In M-MIMO systems, the issue of sparse linear equations can significantly deteriorate the performance of the RK algorithm. This article introduces three new RK-based low-complexity receiver designs that are more robust against inter-user interference and sparse channel matrices in the XL-MIMO regime. These methods show promise in overcoming previous schemes and approximating the regularized zero-forcing scheme used by SIC receivers.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Zineb Dafir, Yasmine Lamari, Said Chah Slaoui
Summary: Recent research has developed many parallel clustering algorithms under the concept of parallel computing to address the speed and scalability issues of traditional clustering algorithms in the Big Data context. These algorithms are divided into two categories of horizontal and vertical scaling platforms, categorized based on the Big Data processing platforms.
ARTIFICIAL INTELLIGENCE REVIEW
(2021)
Article
Computer Science, Information Systems
Herodotos Herodotou, Elena Kakoulli
Summary: The recent advancements in storage technologies have popularized the use of tiered storage systems in data-intensive compute clusters. Trident, a task scheduling approach that makes optimal task assignment decisions based on both locality and storage tier information, has been implemented in both Spark and Hadoop, demonstrating significant benefits in terms of application performance and cluster efficiency.
PROCEEDINGS OF THE VLDB ENDOWMENT
(2021)
Article
Computer Science, Artificial Intelligence
Le Yao, Weiming Shao, Zhiqiang Ge
Summary: This article introduces a hierarchical quality monitoring (HQM) algorithm based on the distributed parallel semisupervised Gaussian mixture model (dp-S(2)GMM) for large-scale industrial plants, which decomposes the process into unit blocks and builds a quality regression model with multimode big process data. The proposed algorithm enables hierarchical fault detection and diagnosis from variable level to plant-wide level.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Computer Science, Software Engineering
Rafael Kuffner dos Anjos, Richard Andrew Roberts, Benjamin Allen, Joaquim Jorge, Ken Anjyo
Summary: Highly complex and dense models of 3D objects are crucial in digital industries. Mesh decimation is important for efficiently simplifying complex meshes, and a preferred approach is to detect saliency and allow artists to iterate before simplification. We propose an efficient multi-scale method to compute mesh saliency, ensuring robust calculation even for densely tessellated models. Our implementation achieves significant speedups and is applicable to real use-case scenarios.
COMPUTERS & GRAPHICS-UK
(2023)
Article
Computer Science, Artificial Intelligence
Carolina Salto, Gabriela Minetti, Enrique Alba, Gabriel Luque
Summary: This article discusses the use of MapReduce as a computing paradigm to solve large-scale combinatorial optimization problems, focusing on the potential and advantages of developing genetic algorithms using Hadoop, Spark, and MPI as middleware platforms. The results show that MRGA performs better on the Hadoop framework compared to Spark and MPI when dealing with high-dimensional datasets.
Article
Cardiac & Cardiovascular Systems
Amjad M. Ahmed, Waqas T. Qureshi, Sherif Sakr, Michael J. Blaha, Clinton A. Brawner, Jonathan K. Ehrman, Steven J. Keteyian, Mouaz H. Al-Mallah
CLINICAL CARDIOLOGY
(2018)
Review
Peripheral Vascular Disease
Mouaz H. Al-Mallah, Sherif Sakr, Ada Al-Qunaibet
CURRENT ATHEROSCLEROSIS REPORTS
(2018)
Article
Computer Science, Theory & Methods
Huijun Wu, Chen Wang, Yinjin Fu, Sherif Sakr, Kai Lu, Liming Zhu
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2018)
Article
Multidisciplinary Sciences
Sherif Sakr, Radwa Elshawi, Amjad Ahmed, Waqas T. Qureshi, Clinton Brawner, Steven Keteyian, Michael J. Blaha, Mouaz H. Al-Mallah
Article
Computer Science, Theory & Methods
Marcin Wylot, Manfred Hauswirth, Philippe Cudre-Mauroux, Sherif Sakr
ACM COMPUTING SURVEYS
(2018)
Article
Cardiac & Cardiovascular Systems
Tahani A. Daghistani, Radwa Elshawi, Sherif Sakr, Amjad M. Ahmed, Abdullah Al-Thwayee, Mouaz H. Al-Mallah
INTERNATIONAL JOURNAL OF CARDIOLOGY
(2019)
Article
Computer Science, Information Systems
Martin Hirzel, Guillaume Baudart, Angela Bonifati, Emanuele Della Valle, Sherif Sakr, Akrivi Vlachou
Meeting Abstract
Cardiac & Cardiovascular Systems
Mahmoud Sobhi Al Rifai, Amjad Ahmed, Michael Blaha, Fatimah Almasoudi, Sherif Sakr, Waqas Qureshi, Clinton Brawner, Jonathan Ehrman, Steven Keteyian, Mouaz Al-Mallah
JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY
(2019)
Editorial Material
Computer Science, Theory & Methods
Sherif Sakr, Albert Zomaya, Athanasios V. Vasilakos
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2019)
Meeting Abstract
Cardiac & Cardiovascular Systems
Jonathan K. Ehrman, Steven J. Keteyian, Waqas Qureshi, Sherif Sakr, Michelle C. Johansen, Michael J. Blaha, Mouaz H. Al-Mallah, Clinton A. Brawner
Proceedings Paper
Computer Science, Theory & Methods
Ahmed Ramzy, Ahmed Awad, Amr A. Kamel, Osman Hegazy, Sherif Sakr
2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP)
(2019)
Article
Computer Science, Information Systems
Sherif Sakr, Tilmann Rabl, Martin Hirzel, Paris Carbone, Martin Strohbach
Article
Computer Science, Information Systems
Sherif Sakr, Zakaria Maamar, Ahmed Awad, Boualem Benatallah, Wil M. P. Van Der Aalst
Article
Computer Science, Information Systems
Dongyao Wu, Liming Zhu, Qinghua Lu, Sherif Sakr
IEEE TRANSACTIONS ON BIG DATA
(2018)
Review
Computer Science, Artificial Intelligence
Radwa Elshawi, Sherif Sakr, Domenico Talia, Paolo Trunfio