scholarly journals Towards a Cost-Effective Interconnection Network Architecture with QoS and Congestion Management Support

2006 ◽  
pp. 884-895 ◽  
Author(s):  
A. Martínez ◽  
P. J. García ◽  
F. J. Alfaro ◽  
J. L. Sánchez ◽  
J. Flich ◽  
...  
Keyword(s):  
Network Architecture ◽  
Interconnection Network ◽  
Cost Effective ◽  
Congestion Management ◽  
Management Support

scholarly journals Gas Detection and Identification Using Multimodal Artificial Intelligence Based Sensor Fusion

2021 ◽  
Vol 4 (1) ◽  
pp. 3
Author(s):  
Parag Narkhede ◽  
Rahee Walambe ◽  
Shruti Mandaokar ◽  
Pulkit Chandel ◽  
Ketan Kotecha ◽  
...  
Keyword(s):  
Sensor Fusion ◽  
Network Architecture ◽  
Cost Effective ◽  
Sensor Data ◽  
Dense Layer ◽  
Gaseous Emissions ◽  
Multiple Sensors ◽  
Single Output ◽  
Novel Approach ◽  
Single Sensor

With the rapid industrialization and technological advancements, innovative engineering technologies which are cost effective, faster and easier to implement are essential. One such area of concern is the rising number of accidents happening due to gas leaks at coal mines, chemical industries, home appliances etc. In this paper we propose a novel approach to detect and identify the gaseous emissions using the multimodal AI fusion techniques. Most of the gases and their fumes are colorless, odorless, and tasteless, thereby challenging our normal human senses. Sensing based on a single sensor may not be accurate, and sensor fusion is essential for robust and reliable detection in several real-world applications. We manually collected 6400 gas samples (1600 samples per class for four classes) using two specific sensors: the 7-semiconductor gas sensors array, and a thermal camera. The early fusion method of multimodal AI, is applied The network architecture consists of a feature extraction module for individual modality, which is then fused using a merged layer followed by a dense layer, which provides a single output for identifying the gas. We obtained the testing accuracy of 96% (for fused model) as opposed to individual model accuracies of 82% (based on Gas Sensor data using LSTM) and 93% (based on thermal images data using CNN model). Results demonstrate that the fusion of multiple sensors and modalities outperforms the outcome of a single sensor.

scholarly journals 5G Wireless/Wired Convergence of UFMC Based Modulation for Intensity Modulation Direct Detection

2021 ◽  
Author(s):  
Keerthivasan K ◽  
Shibu S
Keyword(s):  
Network Architecture ◽  
Direct Detection ◽  
Low Cost ◽  
Cost Effective ◽  
Theoretical Work ◽  
Base Stations ◽  
Complex Nature ◽  
Implementation Model ◽  
Effective Manner ◽  
Media Applications

Faster data speeds, shorter end-to-end latencies, improved end-user service efficiency, and a wider range of multi-media applications are expected with the new 5G wireless services. The dramatic increase in the number of base stations required to meet these criteria, which undermines the low-cost constraints imposed by operators, demonstrates the need for a paradigm shift in modern network architecture. Alternative formats will be required for next-generation architectures, where simplicity is the primary goal. The number of connections is expected to increase rapidly, breaking the inherent complexity of traditional coherent solutions and lowering the resulting cost percentage. A novel implementation model is used to migrate complex-nature modulation structures in a highly efficient and cost-effective manner. Theoretical work to analyses modulations’ behavior over a wired/fiber setup and wireless mode is also provided. The state-of-the-art computational complexity, simplicity, and ease of execution while maintaining efficiency throughput and bit error rate.

Towards cost-effective and low latency data center network architecture

2016 ◽  
Vol 82 ◽  
pp. 1-12 ◽  
Author(s):  
Ting Wang ◽  
Zhiyang Su ◽  
Yu Xia ◽  
Bo Qin ◽  
Mounir Hamdi
Keyword(s):  
Data Center ◽  
Network Architecture ◽  
Cost Effective ◽  
Low Latency ◽  
Data Center Network ◽  
Latency Data

Improving E-Government Project Management

2012 ◽  
pp. 1314-1332
Author(s):  
Stephen K. Aikins
Keyword(s):  
Project Management ◽  
State Government ◽  
Portfolio Management ◽  
Success Factors ◽  
Stakeholder Involvement ◽  
Cost Effective ◽  
Management Support ◽  
Critical Success ◽  
Award Winning ◽  
Government Project

E-government is becoming an enabler for better government through cost-effective and efficient service delivery, and can become a useful tool for effective governance, public administration, and public sector transformation. However, e-government projects are noted for many failures due to several reasons. These include inadequate planning, poor project management, lack of top management support, lack of stakeholder involvement, scope creep, etc. Dwelling on the project management literature as well as reviews of award winning e-government project and portfolio management best practices in a state government and a local utility district, this chapter concludes that e-government initiatives should adopt a more concrete project management methodology, align e-government goals with organizational strategic goals, develop project management competences, as well as understand and apply critical success factors to ensure the successful planning and implementation of e-government projects.

Improving E-Government Project Management

2011 ◽  
pp. 42-60 ◽  
Author(s):  
Stephen K. Aikins
Keyword(s):  
Project Management ◽  
State Government ◽  
Portfolio Management ◽  
Success Factors ◽  
Stakeholder Involvement ◽  
Cost Effective ◽  
Management Support ◽  
Critical Success ◽  
Award Winning ◽  
Government Project

E-government is becoming an enabler for better government through cost-effective and efficient service delivery, and can become a useful tool for effective governance, public administration, and public sector transformation. However, e-government projects are noted for many failures due to several reasons. These include inadequate planning, poor project management, lack of top management support, lack of stakeholder involvement, scope creep, etc. Dwelling on the project management literature as well as reviews of award winning e-government project and portfolio management best practices in a state government and a local utility district, this chapter concludes that e-government initiatives should adopt a more concrete project management methodology, align e-government goals with organizational strategic goals, develop project management competences, as well as understand and apply critical success factors to ensure the successful planning and implementation of e-government projects.

In-Vehicle Network Architecture for the Next-Generation Vehicles

2010 ◽  
pp. 283-302 ◽  
Author(s):  
Syed Masud Mahmud
Keyword(s):  
Communication Networks ◽  
Network Architecture ◽  
Fault Tolerant ◽  
Fuel Efficiency ◽  
Simulation Models ◽  
Cost Effective ◽  
Multimedia Systems ◽  
Safety Features ◽  
Vehicle Network

New types of communication networks will be necessary to meet various consumer and regulatory demands as well as satisfy requirements of safety and fuel efficiency. Various functionalities of vehicles will require various types of communication networks and networking protocols. For example, driveby- wire and active safety features will require fault tolerant networks with time-triggered protocols to guarantee deterministic latencies. Multimedia systems will require high-bandwidth networks for video transfer, and body electronics need low-bandwidth networks to keep the cost down. As the size and complexity of the network grows, the ease of integration, maintenance and troubleshooting has become a major challenge. To facilitate integration and troubleshooting of various nodes and networks, it would be desirable that networks of future vehicles should be partitioned, and the partitions should be interconnected by a hierarchical or multi-layer physical network. This book chapter describes a number of ways using which the networks of future vehicles could be designed and implemented in a cost-effective manner. The book chapter also shows how simulation models can be developed to evaluate the performance of various types of in-vehicle network topologies and select the most appropriate topology for given requirements and specifications.

scholarly journals Efficient Semantic Segmentation Using Multi-Path Decoder

2020 ◽  
Vol 10 (18) ◽  
pp. 6386
Author(s):  
Xing Bai ◽  
Jun Zhou
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Network Architecture ◽  
Resource Constraints ◽  
Cost Effective ◽  
Semantic Segmentation ◽  
Classification Model ◽  
Neural Network Architecture ◽  
Great Progress ◽  
Different Types

Benefiting from the booming of deep learning, the state-of-the-art models achieved great progress. But they are huge in terms of parameters and floating point operations, which makes it hard to apply them to real-time applications. In this paper, we propose a novel deep neural network architecture, named MPDNet, for fast and efficient semantic segmentation under resource constraints. First, we use a light-weight classification model pretrained on ImageNet as the encoder. Second, we use a cost-effective upsampling datapath to restore prediction resolution and convert features for classification into features for segmentation. Finally, we propose to use a multi-path decoder to extract different types of features, which are not ideal to process inside only one convolutional neural network. The experimental results of our model outperform other models aiming at real-time semantic segmentation on Cityscapes. Based on our proposed MPDNet, we achieve 76.7% mean IoU on Cityscapes test set with only 118.84GFLOPs and achieves 37.6 Hz on 768 × 1536 images on a standard GPU.

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