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检索条件"任意字段=1st IEEE International Conference on Distributed Computing in Sensor Systems"

共 3333 条记录，以下是551-560 订阅

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Water in the Cloud: Understanding Water Chemistry via the Internet of Things 15

Water in the Cloud: Understanding Water Chemistry via the In...

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15th Annual international conference on distributed computing in sensor systems (DCOSS)

作者： Chamberlain, Roger D. Chambers, Mike Greenwalt, Darren Scharth, Maria steinbrueck, Brett steinbrueck, Todd Thomas, David Washington Univ Dept Comp Sci & Engn St Louis MO 63110 USA BECS Technol Inc St Louis MO 63132 USA

ISBN: (纸本)9781728105703

Water treatment is one of those essential elements of modern life that is taken for granted by the general population. We describe the ability to remotely understand and improve water chemistry using IoT devices attached to the cloud. The commercial benefits of this IoT connectivity are substantial, including: reduced chemical usage, improved chemical inventory management, safer operation (fewer and less critical alarms), reduced maintenance costs, and higher quality water.

关键词： IoT water chemistry

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distributed Cooperative and Noncooperative Joint Power and Beamforming Adaptation Game for MIMO sensor Network 1

Distributed Cooperative and Noncooperative Joint Power and B...

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1st international conference Information Technology to Enhance E-Learning and other Application, IT-ELA 2020

作者： Khairullah, Ali Kamil Tureli, Ufuk Kivanc, Didem Yildiz Technical University Istanbul Turkey Istanbul Okan University Istanbul Turkey

ISBN: (纸本)9781728182339

distributed Joint beamforming and power adaptation algorithms are of interest for MIMO ad hoc networks. Cooperative and non-cooperative games have been presented to decrease interference (mutual) at each sensor node, under receiver signal-to-interference and noise (SINR) constraints. In reduced feedback algorithms, the optimum transmitter node beamformer is selected from a predefined codebook. This paper introduces a cooperative optimal beamformer selection algorithm to minimize the total power consumption for cluster-based network topology under different minimum SINR constraints. The algorithm reduces overhead incurred by 48% and 10% while increasing the convergence rate to the steady-state allocation by 17% and 9% for the cooperative and non-cooperative beamformer selection games, respectively. Simulation results verify the proposed theoretical analysis, and demonstrate the performance of the Enhanced Co-Operative Power Minimization Algorithm (ECOPMA), Reinforcement Learning based Power allocation and Beamformer Algorithm (RLPBA) for the non-cooperative game [1], with state of the art methods and centralized (optimal) solutions as a fair benchmark. © 2020 ieee.

关键词： Beamforming MIMO Ad hoc network Overhead Rate Potential Game Reinforcement Learning SINR

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student learning communities' detection based on betweenness centrality algorithm: Validation and Optimization 1

Student learning communities' detection based on betweenness...

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1st international conference on Innovative Research in Applied Science, Engineering and Technology, IRASET 2020

作者： Salhi, Intissar Qbadou, Mohammed University Hassan II Laboratory Signals Distributed systems and artificial intelligence ENSETM Casablanca Morocco

ISBN: (纸本)9781728149790

Real-world observations from streaming data sources such as sensors, click streams, and social media are becoming more common in many areas, including education, with the emergence of universities towards 'Digital University' which has already been present for a few years. A new approach is to leverage this behavioural data provided by learners' activity in a learning management system, and use it to group students into communities using standard community detection algorithms, to create qualitative and accessible software systems that will allow teachers to constantly improve their teaching approaches. This paper provides a statistical and a correlation analysis of the results of the method of detection of student learning communities which is based on the notion of centrality, in order to verify its effectiveness, optimize it and improve decision-making. © 2020 ieee.

关键词： students

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1st international conference on Neural computing for Advanced Applications, NCAA 2020

1st International Conference on Neural Computing for Advance...

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1st international conference on Neural computing for Advanced Applications, NCAA 2020

ISBN: (纸本)9789811576690

The proceedings contain 42 papers. The special focus in this conference is on Neural computing for Advanced Applications. The topics include: Image registration algorithm based on manifold regularization with thin-plate spline model;optimal control of nonlinear time-delay systems with input constraints using reinforcement learning;disaggregated power system signal recognition using capsule network;multiagent reinforcement learning for combinatorial optimization;design of echo state network with coordinate descent method and l1 Regularization;an advanced actor-critic algorithm for training video game ai;neural network-based adaptive control for ems type maglev vehicle systems with time-varying mass;a novel collision-avoidance tdma mac protocol for fog-assisted vcns;design optimization of plate-fin heat exchanger using sine cosine algorithm;mr-resnext: A multi-resolution network architecture for detection of obstructive sleep apnea;scalable multi-agent reinforcement learning architecture for semi-mdp real-time strategy games;stacked deep learning structure with bidirectional long-short term memory for stock market prediction;multi-period distributed delay-sensitive tasks offloading in a two-layer vehicular fog computing architecture;template-enhanced aspect term extraction with bi-contextual convolutional neural networks;extended kalman filter-based adaptively sliding mode control with dead-zone compensator for an anchor-hole driller;privacy sensitive large-margin model for face de-identification;balancing of bike-sharing system via constrained model predictive control;a tree-structure convolutional neural network for temporal features exaction on sensor-based multi-resident activity recognition;exploring multi-scale deep encoder-decoder and patchgan for perceptual ultrasound image super-resolution;reliable neighbors-based collaborative filtering for recommendation systems;downhole condition identification for geological drilling processes based on qualitative trend a

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Effect of Change in Environmental Factors on Coordination of Overcurrent Relays with DG Integration 1

Effect of Change in Environmental Factors on Coordination of...

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1st international conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET)

作者： Tripathi, Jayant Mani Srivastava, Adhishree Mallik, Sanjeev Kumar Rajkiya Engn Coll Elect Engn Dept Mainpuri UP India Birla Inst Technol Elect & Elect Engn Dept Patna Bihar India Natl Inst Technol Elect Engn Dept Patna Bihar India

ISBN: (纸本)9781728175492

With the increase in distributed Generation (DG) in distribution systems to maintain the reliability of the supply, there occurs problem of relay coordination. Therefore, it has become important to address this issue as it has become a big challenge for the power system protection engineers. With the incorporation of DG, the radial nature of distribution system is lost and short circuit level is also increased therefore, it leads to maloperation of relays as the previous settings of the relays needs to change. The goal of this paper is to address the issue of relay coordination at different wind speeds encountered by wind turbine. GA and PSO optimization techniques are applied to achieve optimum coordination of over-current relays in a three bus system with a detailed model of wind used as distributed Generation. MATLAB and SIMULINK have been used for all programming and simulation requirements.

关键词： Coordination distributed genetic algorithm PSO Relay Wind

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Beetle Swarm Optimized Priority Heuristic Management for distributed Real Time Database 1

Beetle Swarm Optimized Priority Heuristic Management for Dis...

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1st international conference on Contemporary computing and Applications, IC3A 2020

作者： Ram, Nupa Tripathi, S.P. F.G.I.E.T Computer Science Engineering Raebareli India I.E.T Computer Science Engineering Lucknow India

ISBN: (纸本)9781728154329

Many real time applications required data services in distributed environment. In distributed real time database system (DRTDBS), all the transactions have special characteristics of timing constraints. It is very difficult to complete these transactions before the deadline. Transactions that miss their deadlines are just destroyed and rejected by the system. For better performance, proper management of transaction is essential. In this paper a priority based sub transaction management with beetle swarm optimization is used for finding the highest priority cohorts. Priority is determined by means of the quantity of write locks and the size of data items. The proposed method improves the performance of DRTDBS by reducing miss rate. The performance of the introduced system in terms of miss rate and data conflict is evaluated with the previous priority management methods. © 2020 ieee.

关键词： Optimization

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Computation-Efficient Algorithm for distributed Feedback Optimization of Distribution Grids

Computation-Efficient Algorithm for Distributed Feedback Opt...

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2020 international conference on Communications Control and computing Technologies for Smart Grids

作者： Chang, Chin-Yao Zhou, Xinyang Bernstein, Andrey Natl Renewable Energy Lab Power Syst Engn Ctr Golden CO 80401 USA

ISBN: (纸本)9781728161273

Feedback-based optimization algorithms use real-time measurements to update the optimal control for the underlying system which may not be fully identified. Recently, we have developed a distributed feedback-based algorithm [1] that avoids the requirement of fast communication between central computing and local actuator/sensor agents. This paper extends the work by greatly reducing the number of copies of variables involved in the distributed feedback-based algorithm, which results in faster convergence and lower communication requirement. The main idea is to leverage the specific structural properties of the admittance matrix for distribution systems with tree network topology. We also show the effectiveness of the proposed algorithm in simulations.

关键词： Feedback

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A distributed Fault Tolerance Mechanism for an IoT Healthcare system 21

A Distributed Fault Tolerance Mechanism for an IoT Healthcar...

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21st international Arab conference on Information Technology (ACIT)

作者： Zaiter, Meriem Hacini, Salima Moussa, Guedrez Larbi Ben Mhidi Univ Oum El Bouaghi Oum El Bouaghi Algeria Abdelhamid Mehri Univ Constantine 2 LIRE Lab Constantine Algeria BDL Bank Blida Algeria

ISBN: (纸本)9781728188553

IoT environment is one of important upshots of IT development;it offers comfort to human daily life. We are interested in our paper in the healthcare IoT field which aims to remotely monitor the patient's health state using a set of physiological IoT sensors. In IoT systems dependability is a strong constraint because the fault occurrence can have a bad consequence on human life. The fault tolerance is one of the mechanisms that can insure a dependable function of the IoT healthcare system. To do this, we improve in this paper the centralized agent based architecture [1] by proposing more robust distributed one. That is by eliminating the weakness due to the centralization of the control. This upgrading is motivated by the fact that the current improvement of the network technologies and the occurrence of new promising paradigms like edge computing and 5G [2] require different reasoning philosophy.

关键词： IoT Medical System Dependability Fault Tolerance Agent

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Multiple UAV path-planning for data collection in cluster-based wireless sensor network 1

Multiple UAV path-planning for data collection in cluster-ba...

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1st international conference on Power, Control and computing Technologies, ICPC2T 2020

作者： Chawra, Vrajesh Kumar Gupta, Govind. P. National Institute of Technology Raipur Department of Information Technology Raipur India

ISBN: (纸本)9781728120683

In a multiple UAV-based data collection from the cluster-based wireless sensor network, selection of an optimal set of load-balanced cluster heads and calculation of optimal path for each Unmanned Aerial Vehicles(UAV) are very challenging research issues. Most of the existing cluster head selection schemes do not consider the uniform distribution of cluster heads and also do not consider delay incurs in data collection. Thus, in this paper, the Salp-Swam optimization method is used for the selection of an optimal set of load-balanced Cluster Heads(CHs) and Differential Evolution(DE) based meta-heuristic is used for estimation of delay efficient optimal path for each UAV. In this paper, multiple-UAV is deployed for data collection task in order to reduce data collection time. All UAVs start its journey from the base station, collect data from its cluster heads and return back to the base station. The performance of the proposed scheme is compared with two well-known existing schemes in a different network scenario in terms of travel distance and travel time. Through simulation results, it is observed that the proposed scheme outperforms the existing schemes with respect to the travel time. © 2020 ieee.

关键词： Motion planning

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Towards avatar-based discovery for IoT services using social networking and clustering mechanisms 16

Towards avatar-based discovery for IoT services using social...

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16th international conference on Network and Service Management (CNSM) / 2nd international Workshop on Analytics for Service and Application Management (AnServApp) / 1st international Workshop on the Future Evolution of Internet Protocols (IPFuture)

作者： Khadir, Karima Guermouche, Nawal Monteil, Thierry Guittoum, Amal Univ Toulouse INSA LAAS CNRS Toulouse France

ISBN: (数字)9783903176317

ISBN: (纸本)9783903176317

The Internet of Things (IoT) paradigm is defined as a complex large scale and distributed, and dynamic infrastructure composed of a huge number of heterogeneous devices. Identifying particular services provided by a massive number of IoT devices remains a challenging problem. The classical centralized discovery approaches are no more suitable. In our previous work, we have proposed an avatar-based Fog-Cloud architecture to support IoT object management. The avatars are defined as virtual entities of heterogeneous IoT objects. They are endowed with reasoning capabilities that make them able to coordinate with each other to accomplish an IoT application. Through this paper, we propose to extend our previous work by a new distributed mechanism for efficient discovery of IoT services relying on Social Networking (SN) and clustering methods. This is particularly interesting in large scale IoT systems since it allows to reduce the search space so that only the neighboring social avatars most apt to participate in the collaboration to accomplish an IoT application are considered. The proposed solution has been evaluated in connected vehicles context.

关键词： Avatars Social Web of Things Fuzzy c-means IoT Services distributed discovery Semantic

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