This paper demonstrates the structural modeling and implementation of smart sensor and actuator networks. The modeling is shown using a two-dimensional methodology from capturing system requirements phase to design an...
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ISBN:
(纸本)9781728144610;9781728144603
This paper demonstrates the structural modeling and implementation of smart sensor and actuator networks. The modeling is shown using a two-dimensional methodology from capturing system requirements phase to design and implementation phases. The implementation is based on ieee 1451 family of standards proposed for design and development of smart transducers which has a great potential to be the enabling technology for distributed control and measurement systems. A pick-and-place robotic station is used in order to demonstrate the applicability of the proposed distributed control scheme.
The principle of extension is defined for linear time-invariant descriptor-type distributed-time-delay systems. Necessary and sufficient conditions for one system being an extension of another are also presented.
ISBN:
(纸本)9781728198095
The principle of extension is defined for linear time-invariant descriptor-type distributed-time-delay systems. Necessary and sufficient conditions for one system being an extension of another are also presented.
Time series anomaly detection strives to uncover potential abnormal behaviors and patterns from temporal data, and has fundamental significance in diverse application scenarios. Constructing an effective detection mod...
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Time series anomaly detection strives to uncover potential abnormal behaviors and patterns from temporal data, and has fundamental significance in diverse application scenarios. Constructing an effective detection model usually requires adequate training data stored in a centralized manner, however, this requirement sometimes could not be satisfied in realistic scenarios. As a prevailing approach to address the above problem, federated learning has demonstrated its power to cooperate with the distributed data available while protecting the privacy of data providers. However, it is still unclear that how existing time series anomaly detection algorithms perform with decentralized data storage and privacy protection through federated learning. To study this, we conduct a federated time series anomaly detection benchmark, named FedTADBench, which involves five representative time series anomaly detection algorithms and four popular federated learning methods. We would like to answer the following questions: (l)How is the performance of time series anomaly detection algorithms when meeting federated learning? (2) Which federated learning method is the most appropriate one for time series anomaly detection? (3) How do federated time series anomaly detection approaches perform on different partitions of data in clients? Numbers of results as well as corresponding analysis are provided from extensive experiments with various settings. The source code of our benchmark is publicly available at https://***/fanxindiu2020/FedTADBench.
There is a significant rise in the adaptation of streaming applications in the past decade by individuals researchers and organizations in both industry and academia. These applications are all based on the modern dat...
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ISBN:
(纸本)9781728141985
There is a significant rise in the adaptation of streaming applications in the past decade by individuals researchers and organizations in both industry and academia. These applications are all based on the modern data stream processing systems that implement resource allocation and management in order to provide an uninterrupted track of queries over incoming input distributed data streams. More than a few stream processing engines exists to handle these distributed streaming applications. These distributed applications have open challenges like backpressure. In this paper, we introduce a backpressure mitigation mechanism for the distributed stream processing systems. The proposed backpressure mitigation technique is a generic one and is feasible to be implemented on top of a number of popular streaming frameworks. We use Flink as a testbed for this work and use its available APIs.
Machine learning (ML) algorithms have been regaining momentum thanks to their ability to analyze substantial and complex data, supporting artificial intelligence decisions in cloud computing but also in near-sensor co...
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ISBN:
(纸本)9781728160443
Machine learning (ML) algorithms have been regaining momentum thanks to their ability to analyze substantial and complex data, supporting artificial intelligence decisions in cloud computing but also in near-sensorcomputing in end-point devices. Both cloud and near-sensorcomputing are liable to radiation-induced soft errors, especially in automotive and aerospace safety-critical applications. In this regard, this paper contributes by comparing the accuracy of two prominent machine learning algorithms running on a low-power processor upset by radiation-induced soft errors. Both ML algorithms have been assessed with the help of a fault injection-based method able to natively emulate soft errors directly in a development board. In addition, neutron radiation test results suggest the most critical situations in which mitigation solutions should address.
This work presents the first steps towards the development of a toolkit for aiding in the construction of distributed Cognitive systems, designed within the spirit of the System of systems (SoS) paradigm. The Toolkit ...
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Nowadays, demand for rental vehicle sharing is increasing. People are preferring to rent vehicles instead of putting a lot of money in a new vehicle. This renting system is beneficial for not only the consumer but als...
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Nowadays, demand for rental vehicle sharing is increasing. People are preferring to rent vehicles instead of putting a lot of money in a new vehicle. This renting system is beneficial for not only the consumer but also to the owner of the vehicle. Many issues such as theft, use of vehicle, bad condition of vehicles are not considered in the conventional rental systems. With the help of blockchain and Cyber Physical systems (CPS), these issues are resolved in this system. Blockchain has many advantages due to its peer to peer sharing network. Smart contracts in Blockchain technology are contracts that run on their own in which context for the buyer-seller consensus are inscribed directly into the code. This system proposes a smart vehicle rental system which works with Blockchain, CPS and Internet of Things (IoT). The system utilizes IoT sensors to collect automatic data about car usage in real-time. For transactions of both customer and owner, these data make car availability and usage more authentic and credible. The implementation of this system uses Ethereum, Solidity, ***, distributed Applications (dApp), Truffle. The proposed rental vehicle system with blockchain provides better reliability, traceability and security to both the owner as well as consumer.
The proposal of an Advanced Metering Infrastructure based on short-range communication is suggested for the continuous monitoring of Particulate Matter. A prototype of Automatic Measurement System (AMS), including a l...
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ISBN:
(纸本)9781728144337
The proposal of an Advanced Metering Infrastructure based on short-range communication is suggested for the continuous monitoring of Particulate Matter. A prototype of Automatic Measurement System (AMS), including a low-cost off-the-shelf PM sensor, has been developed as a remote node to be adopted in the radio Local Area Network. The results of the system calibration and comparison with the data quality requirements of the PM measurement according to European regulations, as well as the simulation of a typical Smart City scenario in terms of communication performance, confirm the feasibility of the proposed distributed AMS for an effective adoption within an urban area.
Wireless sensor Network (WSN)is the most promising area which is widely used in the field of military, healthcare systems, flood control, and weather forecasting system. In WSN every node is connected with another nod...
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Under the trend of deregulated Volt/VAR ancillary service market, power distribution grid (PDG) is seeing a growing demand for personally owned distributed energy resources (DERs) installed behind-the-meter as value a...
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