Results 51 to 60 of about 5,449,873 (343)

Efficient Unsupervised Classification of Hyperspectral Images Using Voronoi Diagrams and Strong Patterns

open access: yesSensors, 2020
Hyperspectral images (HSIs) are a powerful tool to classify the elements from an area of interest by their spectral signature. In this paper, we propose an efficient method to classify hyperspectral data using Voronoi diagrams and strong patterns in the ...
Laura Bianca Bilius   +1 more
doaj   +1 more source

Distributed State Estimation Based Distributed Model Predictive Control

open access: yesMathematics, 2021
In this work, we consider output-feedback distributed model predictive control (DMPC) based on distributed state estimation with bounded process disturbances and output measurement noise. Specifically, a state estimation scheme based on observer-enhanced
Jing Zeng, Jinfeng Liu
doaj   +1 more source

Applying Prolog to Develop Distributed Systems [PDF]

open access: yes, 2010
Development of distributed systems is a difficult task. Declarative programming techniques hold a promising potential for effectively supporting programmer in this challenge.
ANDREY RYBALCHENKO   +17 more
core   +3 more sources

Survival for Children Diagnosed With Wilms Tumour (2012–2022) Registered in the UK and Ireland Improving Population Outcomes for Renal Tumours of Childhood (IMPORT) Study

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background The Improving Population Outcomes for Renal Tumours of childhood (IMPORT) is a prospective clinical observational study capturing detailed demographic and outcome data on children and young people diagnosed with renal tumours in the United Kingdom and the Republic of Ireland.
Naomi Ssenyonga   +56 more
wiley   +1 more source

Improving the Performance of CPU Architectures by Reducing the Operating System Overhead (Extended Version)

open access: yesElectrical, Control and Communication Engineering, 2016
The predictable CPU architectures that run hard real-time tasks must be executed with isolation in order to provide a timing-analyzable execution for real-time systems.
Zagan Ionel, Gaitan Vasile Gheorghita
doaj   +1 more source

Stereotactic Body Radiation Therapy for Pediatric, Adolescent, and Young Adult Patients With Osteosarcoma: Local Control Outcomes With Dosimetric Analysis

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Background/Objectives Osteosarcoma is a radioresistant tumor that may benefit from stereotactic body radiation therapy (SBRT) for locoregional control in metastatic/recurrent disease. We report institutional practice patterns, outcomes, toxicity, and failures in osteosarcoma patients treated with SBRT.
Jenna Kocsis   +13 more
wiley   +1 more source

A fluid flow model for the software defined wide area networks analysis

open access: yesScientific Reports
The advancement of IT systems necessitates efficient communication methods essential across various sectors, from streaming platforms to cloud-based solutions and Industry 4.0 applications.
Karol Marszałek, Adam Domański
doaj   +1 more source

SELF-ADJUSTING DISTRIBUTED CONTROL SYSTEMS

open access: yesСовременная наука и инновации, 2023
Distributed control systems are considered that have the ability to change the parameters of a distributed controller depending on changes in the parameters of a distributed object.
I. M. Pershin   +2 more
doaj   +1 more source

Changes in Body Composition in Children and Young People Undergoing Treatment for Acute Lymphoblastic Leukemia: A Systematic Review and Meta‐Analysis

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Ongoing evidence indicates increased risk of sarcopenic obesity among children and young people (CYP) with acute lymphoblastic leukemia (ALL), often beginning early in treatment, persisting into survivorship. This review evaluates current literature on body composition in CYP with ALL during and after treatment.
Lina A. Zahed   +5 more
wiley   +1 more source

Dynamic Control Flow in Large-Scale Machine Learning

open access: yes, 2018
Many recent machine learning models rely on fine-grained dynamic control flow for training and inference. In particular, models based on recurrent neural networks and on reinforcement learning depend on recurrence relations, data-dependent conditional ...
Abadi, Martín   +14 more
core   +1 more source

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