scholarly journals A DICOM-based streaming service for the Digital Operating Room

2009 ◽  
Author(s):  
Adrian m. Vazquez ◽  
Rafael Mayoral ◽  
Oliver Burgert
Keyword(s):  
Operating Room ◽  
Data Access ◽  
Streaming Data ◽  
Context Information ◽  
Data Streaming ◽  
Early Integration ◽  
Common Interface ◽  
Streaming Service ◽  
Application Specific ◽  
Digital Operating Room

In the Digital Operating Room there is a need to support data streaming to create advanced integrated surgical assist systems. In this paper we propose a DICOM-based streaming mechanism which leverages the interoperability definitions offered by DICOM to offer a common interface to manage all kinds of streaming data sources, while allowing data and application-specific protocols and infrastructure for the actual data access. We have implemented the proposed solution within the ASTMA project and have shown that thanks to the flexibility in choosing an appropriate streaming protocol we can achieve the necessary streaming quality while transmitting the context information required to create valid DICOM instances. This approach ensures an early integration of streaming data with the rest of the imaging information providing for a simpler data workflow.

scholarly journals ESTIMATION OF VIRTUAL CHANNELS BANDWIDTH FOR TRAFFIC MANAGEMENT IN SPACEFIBRE NETWORKS

2018 ◽  
pp. 154-162
Author(s):  
I. L. Korobkov
Keyword(s):  
Mathematical Method ◽  
Traffic Control ◽  
Traffic Management ◽  
Data Transfer ◽  
Streaming Data ◽  
Transport Protocol ◽  
Data Streaming ◽  
Math Model ◽  
Virtual Channels ◽  
Streaming Service

The application of SpaceFibre network standard and ESDP transport protocol (the previous name is «STP-2») for streaming data transfer in onboard spacecraft networks is considered in the paper. The paper demonstrates that traffic management is needed in SpaceFibre networks. To solve this problem Adaptive Data Streaming Service (ADSS) could be used. ADSS Traffic management is based on the traffic control via changing of SpaceFibre configuration parameters and ESDP protocol’s mechanisms. Genetic Algorithm (GA) is proposed to determine new SpaceFibre configuration parameters. The key function of GA is the quantity estimation of streaming data through SpaceFibre. To the best of our knowledge, there is no such methods for SpaceFibre networks. It is for this reason that the mathematical method of quantity estimation has been developed and presented in the paper. The math model of streaming over SpaceFibre was also developed for this method. It is based on Markovian chain. Examples of calculations are given. The proposed method could be used for SpaceWire networks with STP-ISS-14 protocol.

scholarly journals Deep learning framework for handling concept drift and class imbalanced complex decision-making on streaming data

2021 ◽  
Author(s):  
S. Priya ◽  
R. Annie Uthra
Keyword(s):  
Decision Making ◽  
Deep Learning ◽  
Concept Drift ◽  
Class Imbalance ◽  
Streaming Data ◽  
Superior Performance ◽  
Data Streaming ◽  
Minority Class ◽  
Concept Drift Detection

AbstractIn present times, data science become popular to support and improve decision-making process. Due to the accessibility of a wide application perspective of data streaming, class imbalance and concept drifting become crucial learning problems. The advent of deep learning (DL) models finds useful for the classification of concept drift in data streaming applications. This paper presents an effective class imbalance with concept drift detection (CIDD) using Adadelta optimizer-based deep neural networks (ADODNN), named CIDD-ADODNN model for the classification of highly imbalanced streaming data. The presented model involves four processes namely preprocessing, class imbalance handling, concept drift detection, and classification. The proposed model uses adaptive synthetic (ADASYN) technique for handling class imbalance data, which utilizes a weighted distribution for diverse minority class examples based on the level of difficulty in learning. Next, a drift detection technique called adaptive sliding window (ADWIN) is employed to detect the existence of the concept drift. Besides, ADODNN model is utilized for the classification processes. For increasing the classifier performance of the DNN model, ADO-based hyperparameter tuning process takes place to determine the optimal parameters of the DNN model. The performance of the presented model is evaluated using three streaming datasets namely intrusion detection (NSL KDDCup) dataset, Spam dataset, and Chess dataset. A detailed comparative results analysis takes place and the simulation results verified the superior performance of the presented model by obtaining a maximum accuracy of 0.9592, 0.9320, and 0.7646 on the applied KDDCup, Spam, and Chess dataset, respectively.

Context Sensitive Mobile Services

2011 ◽  
pp. 130-143
Author(s):  
Indranil Bose ◽  
Xi Chen
Keyword(s):  
Service Providers ◽  
Mobile Services ◽  
Mobile Technologies ◽  
Context Information ◽  
Specific Information ◽  
Context Sensitive ◽  
Personalized Services ◽  
Application Specific ◽  
Push Model ◽  
Good Support

The advancements in mobile technologies make the collection of customers’ context information feasible. Service providers can now incorporate context information of customers when providing personalized services to them. This type of services is called context sensitive mobile services (CSMS). Context refers to the environment around customers when there are business transactions between customers and service providers. Location, time, mobile device, services, and other application specific information are all possible components of context. Compared to other types of mobile services, CSMS can fit to customers’ demands better. CSMS can follow push model or pull model. Different context sensitive services are sensitive to different context information with different degrees of sensitivity. In the future, CSMS can find good support from data mining approaches to understand customers better. Security is currently an important issue for CSMS.

A low cost digital operating room

2014 ◽  
Author(s):  
A. Klinger ◽  
G. L. de Lima ◽  
V. Roesler ◽  
G. Maron ◽  
G. Longoni ◽  
...  
Keyword(s):  
Operating Room ◽  
Low Cost ◽  
Digital Operating Room
Sign in / Sign up

Export Citation Format

Share Document