Results 41 to 50 of about 20,810 (198)

Real-time predictive maintenance for wind turbines using Big Data frameworks

, 2017
This work presents the evolution of a solution for predictive maintenance to a Big Data environment. The proposed adaptation aims for predicting failures on wind turbines using a data-driven solution deployed in the cloud and which is composed by three ...
Canizo, Mikel, Charramendieta, Santiago, Conde, Angel, Onieva, Enrique, Trujillo, Salvador   +4 more
core   +1 more source

Matrix Computations and Optimization in Apache Spark

, 2016
We describe matrix computations available in the cluster programming framework, Apache Spark. Out of the box, Spark provides abstractions and implementations for distributed matrices and optimization routines using these matrices. When translating single-
Meng, Xiangrui, Pu, Li, Sparks, Evan, Staple, Aaron, Ulanov, Alexander, Venkataraman, Shivaram, Yavuz, Burak, Zadeh, Reza Bosagh, Zaharia, Matei   +8 more
core   +1 more source

ReForeSt: Random Forests in Apache Spark [PDF]

, 2017
Random Forests (RF) of tree classifiers are a popular ensemble method for classification. RF are usually preferred with respect to other classification techniques because of their limited hyperparameter sensitivity, high numerical robustness, native capacity of dealing with numerical and categorical features, and effectiveness in many real world ...
Lulli A., Oneto L., Anguita D.
openaire   +1 more source

Emergency Cholecystectomy in Patients Classified as High Risk According to the Tokyo Guidelines 2018: A Real‐World Analysis

Annals of Gastroenterological Surgery, EarlyView.
Emergency cholecystectomy was evaluated in patients with acute cholecystitis classified as non‐recommended for surgery by the Tokyo Guidelines 2018. Major postoperative complications, rather than mortality, better reflected operative risk. Physiological instability, particularly ASA‐PS ≥ 3 and shock status, identified high‐risk patients, suggesting ...
Satoshi Mii, So Yamaki, Daisuke Hashimoto, Kazuki Matsumura, Hiroyuki Ishida, Hidetaka Miyazaki, Yuki Matsui, Yuji Ikeda, Tsukasa Ikeura, Sohei Satoi   +9 more
wiley   +1 more source

Real-time high-throughput cotton phenotyping using distributed computing and deep learning

Smart Agricultural Technology
In this paper, we present an approach for real-time high-throughput cotton phenotyping using distributed computing and deep learning. The objective of this study is to develop a big data pipeline to efficiently ingest and process large amounts of image ...
Vaishnavi Thesma, Glen C. Rains, Javad Mohammadpour Velni   +2 more
doaj   +1 more source

Model of Point Cloud Data Management System in Big Data Paradigm

ISPRS International Journal of Geo-Information, 2018
Modern geoinformation technologies for collecting and processing data, such as laser scanning or photogrammetry, can generate point clouds with billions of points. They provide abundant information that can be used for different types of analysis. Due to
Vladimir Pajić, Miro Govedarica, Mladen Amović   +2 more
doaj   +1 more source

Apache Spark Tabanlı Duygu Analizi

Osmaniye Korkut Ata Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2021
Bu çalışmada, büyük verileri bellek içi hesaplama yöntemi ile hızlı bir şekilde işleyebilen Apache Spark açık kaynak kodlu çerçeve kullanılarak duygu analizi gerçekleştirilmiştir. Duygu analizi işleminde Spark içerisinde bulunan MLlib makine öğrenimi kütüphanesi kullanılmıştır.
Emre YILDIRIM, Ali ÇALHAN
openaire   +2 more sources

Optimizing 3D Bin Packing of Heterogeneous Objects Using Continuous Transformations in SE(3)

Advanced Intelligent Systems, EarlyView.
This article presents a method for solving the three‐dimensional bin packing problem for heterogeneous objects using continuous rigid‐body transformations in SE(3). A heuristic optimization framework combines signed‐distance functions, neural network approximations, point‐cloud bin modeling, and physics simulation to ensure feasibility and stability ...
Michele Angelini, Marco Carricato
wiley   +1 more source

Major Cybersecurity Breaches: Shaping Corporate Cybersecurity Policies and Closing the Gaps

Journal of Corporate Accounting &Finance, EarlyView.
ABSTRACT As digitalization accelerates, cybercrime has intensified in both scale and impact over the past two decades. This study aims to critically examine major cybersecurity events, assess them through the lens of routine activity theory, examine insight from three other established criminological and organizational theories, and address central ...
Laura K. Rickett, Deborah Smith
wiley   +1 more source

Performance Characterization of In-Memory Data Analytics on a Modern Cloud Server

, 2015
In last decade, data analytics have rapidly progressed from traditional disk-based processing to modern in-memory processing. However, little effort has been devoted at enhancing performance at micro-architecture level.
Awan, Ahsan Javed, Ayguade, Eduard, Brorsson, Mats, Vlassov, Vladimir   +3 more
core   +1 more source