Efficient and flexible architecture for AES

2006 ◽  
Vol 153 (6) ◽  
pp. 533 ◽  
Author(s):  
H. Li
Keyword(s):  
Flexible Architecture

scholarly journals Flexible architecture for real-time synchronized processing of multimedia signals

2021 ◽  
Author(s):  
Mohamed Awad ◽  
Islam T. Abougindia ◽  
Ahmed Elliethy ◽  
Hussein A. Aly
Keyword(s):  
Real Time ◽  
Flexible Architecture

scholarly journals A Cloud Game-Based Educative Platform Architecture: The CyberScratch Project

2021 ◽  
Vol 11 (2) ◽  
pp. 807
Author(s):  
Llanos Tobarra ◽  
Alejandro Utrilla ◽  
Antonio Robles-Gómez ◽  
Rafael Pastor-Vargas ◽  
Roberto Hernández
Keyword(s):  
Data Storage ◽  
Data Privacy ◽  
Data Science ◽  
Critical Issue ◽  
Privacy Management ◽  
Instructional Process ◽  
Legal Context ◽  
Flexible Architecture ◽  
Efficient Data ◽  
Implementation Guidelines

The employment of modern technologies is widespread in our society, so the inclusion of practical activities for education has become essential and useful at the same time. These activities are more noticeable in Engineering, in areas such as cybersecurity, data science, artificial intelligence, etc. Additionally, these activities acquire even more relevance with a distance education methodology, as our case is. The inclusion of these practical activities has clear advantages, such as (1) promoting critical thinking and (2) improving students’ abilities and skills for their professional careers. There are several options, such as the use of remote and virtual laboratories, virtual reality and game-based platforms, among others. This work addresses the development of a new cloud game-based educational platform, which defines a modular and flexible architecture (using light containers). This architecture provides interactive and monitoring services and data storage in a transparent way. The platform uses gamification to integrate the game as part of the instructional process. The CyberScratch project is a particular implementation of this architecture focused on cybersecurity game-based activities. The data privacy management is a critical issue for these kinds of platforms, so the architecture is designed with this feature integrated in the platform components. To achieve this goal, we first focus on all the privacy aspects for the data generated by our cloud game-based platform, by considering the European legal context for data privacy following GDPR and ISO/IEC TR 20748-1:2016 recommendations for Learning Analytics (LA). Our second objective is to provide implementation guidelines for efficient data privacy management for our cloud game-based educative platform. All these contributions are not found in current related works. The CyberScratch project, which was approved by UNED for the year 2020, considers using the xAPI standard for data handling and services for the game editor, game engine and game monitor modules of CyberScratch. Therefore, apart from considering GDPR privacy and LA recommendations, our cloud game-based architecture covers all phases from game creation to the final users’ interactions with the game.

VCA Protocol-Based Multilevel Flexible Architecture on Embedded PLCs for Visual Servo Control

2020 ◽  
Vol 67 (3) ◽  
pp. 2450-2459 ◽  
Author(s):  
Huifeng Wu ◽  
Yi Yan ◽  
Danfeng Sun ◽  
Rene Simon
Keyword(s):  
Servo Control ◽  
Visual Servo ◽  
Visual Servo Control ◽  
Flexible Architecture

CADDAC: Multi-Client Collaborative Shape Design System with Server-based Geometry Kernel

2003 ◽  
Vol 3 (2) ◽  
pp. 170-173 ◽  
Author(s):  
Karthik Ramani, ◽  
Abhishek Agrawal, and ◽  
Mahendra Babu ◽  
Christoph Hoffmann
Keyword(s):  
Global Economy ◽  
Design System ◽  
Shape Design ◽  
Server Side ◽  
Collaborative Product Design ◽  
Flexible Architecture ◽  
Computationally Intensive ◽  
New Feature ◽  
Rendering Pipeline ◽  
Client Side

New and efficient paradigms for web-based collaborative product design in a global economy will be driven by increased outsourcing, increased competition, and pressures to reduce product development time. We have developed a three-tier (client-server-database) architecture based collaborative shape design system, Computer Aided Distributed Design and Collaboration (CADDAC). CADDAC has a centralized geometry kernel and constraint solver. The server-side provides support for solid modeling, constraint solving operations, data management, and synchronization of clients. The client-side performs real-time creation, modification, and deletion of geometry over the network. In order to keep the clients thin, many computationally intensive operations are performed at the server. Only the graphics rendering pipeline operations are performed at the client-side. A key contribution of this work is a flexible architecture that decouples Application Data (Model), Controllers, Viewers, and Collaboration. This decoupling allows new feature development to be modular and easy to develop and manage.

PHD A Generic and Flexible Architecture for IPTV in Authorized Domains

2009 ◽  
Author(s):  
Marcos Antonio Simplício Jr. ◽  
Vlad Coroama ◽  
Yeda R. Venturini ◽  
Tereza Carvalho ◽  
Mats Naslund ◽  
...  
Keyword(s):  
Flexible Architecture

scholarly journals Estimating economic damage from climate change in the United States

Science ◽  
2017 ◽  
Vol 356 (6345) ◽  
pp. 1362-1369 ◽  
Author(s):  
Solomon Hsiang ◽  
Robert Kopp ◽  
Amir Jina ◽  
James Rising ◽  
Michael Delgado ◽  
...  
Keyword(s):  
Climate Change ◽  
United States ◽  
Climate Science ◽  
The United States ◽  
Process Models ◽  
Economic Damage ◽  
Global Mean Temperature ◽  
Flexible Architecture ◽  
Econometric Analyses ◽  
Business As Usual

Estimates of climate change damage are central to the design of climate policies. Here, we develop a flexible architecture for computing damages that integrates climate science, econometric analyses, and process models. We use this approach to construct spatially explicit, probabilistic, and empirically derived estimates of economic damage in the United States from climate change. The combined value of market and nonmarket damage across analyzed sectors—agriculture, crime, coastal storms, energy, human mortality, and labor—increases quadratically in global mean temperature, costing roughly 1.2% of gross domestic product per +1°C on average. Importantly, risk is distributed unequally across locations, generating a large transfer of value northward and westward that increases economic inequality. By the late 21st century, the poorest third of counties are projected to experience damages between 2 and 20% of county income (90% chance) under business-as-usual emissions (Representative Concentration Pathway 8.5).

A POWER CONSUMPTION ACTIVITY BASED HETEROGENEOUS SOA FRAMEWORK FOR CONTEXT-AWARE HOME SERVICES

2011 ◽  
Vol 20 (07) ◽  
pp. 1211-1230 ◽  
Author(s):  
HYUN SANG CHO ◽  
TAKEKAZU KATO ◽  
TATSUYA YAMAZAKI ◽  
MINSOO HAHN
Keyword(s):  
Web Services ◽  
Power Consumption ◽  
Service Oriented Architecture ◽  
Control Function ◽  
Home Network ◽  
Network System ◽  
Context Aware ◽  
Flexible Architecture ◽  
And Control ◽  
Monitor And Control

The home network is one of the emerging areas from the last century. However, the growth of the home network market is stationary at present. This paper describes the limitations of the home network system and the requirements for overcoming the current limitations. Also described is a new home network service system known as COWS and its easy installation and scalable operation. COWS consists of power consumption monitor and control devices along with a service server that is a complementary combination of Open Service Gateway initiative (OSGi) and web services. A home network system has a dynamic, heterogeneous, distributed, and scalable topology. Service Oriented Architecture (SOA) has been proposed as a solution that satisfies the requirement of a home network, and OSGi and web services are two successful SOA-based frameworks. An included service server has a flexible architecture that consists of a core and extendable service packages. A power consumption monitor and control function provides useful context information for activity-based context-aware services and optimizes the power consumption. The system can be installed easily into existing and new houses to solve the current barrier of the popularization of home network services.

Flexible architecture for the implementation of the two-dimensional discrete wavelet transform (2D-DWT) oriented to FPGA devices

2004 ◽  
Vol 28 (9) ◽  
pp. 509-518 ◽  
Author(s):  
Ricardo José Colom-Palero ◽  
Rafael Gadea-Girones ◽  
Francisco José Ballester-Merelo ◽  
Marcos Martı́nez-Peiro
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Two Dimensional ◽  
Flexible Architecture

scholarly journals ECRU: An Encoder-Decoder Based Convolution Neural Network (CNN) for Road-Scene Understanding

2018 ◽  
Vol 4 (10) ◽  
pp. 116 ◽  
Author(s):  
Robail Yasrab
Keyword(s):  
Neural Network ◽  
Visual Recognition ◽  
Substantial Reduction ◽  
Scene Understanding ◽  
Semantic Segmentation ◽  
Research Area ◽  
Smart Systems ◽  
Proposed Model ◽  
Driving Assistance ◽  
Flexible Architecture

This research presents the idea of a novel fully-Convolutional Neural Network (CNN)-based model for probabilistic pixel-wise segmentation, titled Encoder-decoder-based CNN for Road-Scene Understanding (ECRU). Lately, scene understanding has become an evolving research area, and semantic segmentation is the most recent method for visual recognition. Among vision-based smart systems, the driving assistance system turns out to be a much preferred research topic. The proposed model is an encoder-decoder that performs pixel-wise class predictions. The encoder network is composed of a VGG-19 layer model, while the decoder network uses 16 upsampling and deconvolution units. The encoder of the network has a very flexible architecture that can be altered and trained for any size and resolution of images. The decoder network upsamples and maps the low-resolution encoder’s features. Consequently, there is a substantial reduction in the trainable parameters, as the network recycles the encoder’s pooling indices for pixel-wise classification and segmentation. The proposed model is intended to offer a simplified CNN model with less overhead and higher performance. The network is trained and tested on the famous road scenes dataset CamVid and offers outstanding outcomes in comparison to similar early approaches like FCN and VGG16 in terms of performance vs. trainable parameters.

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