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检索条件"任意字段=4th IEEE International Conference on Distributed Computing in Sensor Systems"

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On Performance of Cooperative Transmission in Uplink Non-Orthogonal Multiple Access Wireless sensor Networks 4

On Performance of Cooperative Transmission in Uplink Non-Ort...

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4th international conference on Recent Advances in Signal Processing, Telecommunications and computing, SigTelCom 2020

作者： Truong, Van-Truong Ha, Dac-Binh Lee, Yoonill Nguyen, Anh-Nhat Duy Tan University Faculty of Electrical-Electronic Engineering Da Nang550000 Viet Nam Purdue University Northwest Department of Engineering Technology IN United States Khon Kaen University Applied Network Technology Laboratory Thailand

ISBN: (纸本)9781728168661

In this paper, we study the cooperative transmission of uplink non-orthogonal multiple access (NOMA) wireless sensor networks in terms of performance analysis. Specifically, two sensor nodes applying the NOMA scheme intent to transmit the messages to the sink with the cooperation of multiple amplify-and-forward (AF) relays. We propose a protocol that the best cooperative relay is selected to retransmit the messages from sensor nodes to sink based on channel state information. To evaluate the performance of this proposed system, the closed-form expressions of outage probability for two users are derived based on the signal-to-noise ratio (SNR) and signal-to-interference-plus-noise ratio (SINR) of transmission links. Furthermore, to look insight the behaviour of the proposed system, the numerical results are provided according to the operation key parameters, e.g., number of relay nodes, transmit power, and distances. Finally, to clarify the advantage of this proposed protocol, we provide a comparison of random relay selection and non-cooperative transmission. the Monte-Carlo simulation verifies the correctness of our analysis. © 2020 ieee.

关键词： Channel state information

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5th international conference on Nanoelectronics, Circuits and Communication systems, NCCS 2019

5th International Conference on Nanoelectronics, Circuits an...

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5th international conference on Nanoelectronics, Circuits and Communication systems, NCCS 2019

ISBN: (纸本)9789811574856

the proceedings contain 70 papers. the special focus in this conference is on Nanoelectronics, Circuits and Communication systems. the topics include: Design of Superlens Using 2D Triangular Photonic Crystal Under Both TE and TM Mode of Propagations;smart Intelligent System Design for Accident Prevention and theft Protection of Vehicle;computing threshold Voltage Shift in Submicron MOSFET in Presence of Body Effect and Induced Lateral Field;Proficient Discrete Wavelet Transform Using distributed Arithmetic Architecture on FPGA;application of Knowledge and Data Mining to Build Intelligent systems;Propagation Characteristics of SIW and Waveguide: A Comparison;predicting Software Cost through Entity–Relationship Diagrams: An Empirical View;OpenCLTM Implementation of Fast Frequency Domain Image Denoisification Kernels for Parallel Environments;FPGA Implementation of Radix-4-Based Two-Dimensional FFT with and Without Pipelining Using Efficient Data Reordering Scheme;Design and Simulation of Fourth-Order Delta-Sigma Modulator-MASH Architecture;Multiplexer-based High-speed S-box Architecture for PRESENT Cipher in FPGA;effective Delay and Energy Conservation Strategies for Query-Driven Wireless sensor Networks;segregation of Speech and Music Signals for Aiding the Hearing Impaired;designing of Low-Noise Amplifier and Voltage-Controlled Oscillator for Satellite Receiver in Ku Band;language Diversity and their Preservation in Jharkhand;Digital Implementation of Sigmoid Function in Artificial Neural Network Using VHDL;design of Energy Harvestor Using Piezoelectric Material;kisaan Seva—A Web site for Serving the Farmers;Design of Low Power Barrel Shifter Architecture by Using Proposed MUX Based CORDIC in CMOS Logic;Efficient HDL Implementation of Turbo Coded MIMO-OFDM Physical Layer;Design of a 2–30 GHz Low-Noise Amplifier: A Review;preface;voice-Based Biometric Authentication.

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An Innovative Mobile Terminal Positioning Technique based on UAV-Femtocell systems 15

An Innovative Mobile Terminal Positioning Technique based on...

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

作者： Avanzato, Roberta Beritelli, Francesco Rametta, Corrado Vaccaro, Mario Univ Catania Dept Eletr Elect & Comp Engn Catania Italy

ISBN: (纸本)9781728105703

this paper proposes an innovative technique for identifying any missing persons in natural disaster scenarios using an algorithm that exploits the femtocell sensor's ability to univocally hook a mobile terminal and that of a UAV system to easily approach to the monitoring area. the algorithm locates any mobile terminals with an accuracy of about 2 m.

关键词： UAV systems Femtocell Reference Signal Received Power Positioning algorithm 4G/LTE radio technologies

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Monocular 3D Object Detection Using Feature Map Transformation: Towards Learning Perspective-Invariant Scene Representations 4

Monocular 3D Object Detection Using Feature Map Transformati...

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4th ieee international conference on Robotic computing (ieee IRC)

作者： Schroeder, Enrico Maehlisch, Mirko Vitay, Julien Hamker, Fred AUDI AG Dept Dev Sensor Data Fus & Localizat Ingolstadt Germany Tech Univ Chemnitz Dept Artif Intelligence Fac Comp Sci Chemnitz Germany

ISBN: (纸本)9781728152370

In this paper we propose to use a feature map transformation network for the task of monocular 3D object detection. Given a monocular camera image, the transformation network encodes features of the scene in an abstract, perspective-invariant latent representation. this latent representation can then be decoded into a bird's-eye view representation to estimate objects' position and rotation in 3D space. In our experiments on the Kitti object detection dataset we show that our model is able to learn to estimate objects' 3D position from a monocular camera image alone without having any explicit geometric model or other prior information on how to perform the transformation. While performing slightly worse than networks which are purpose-built for this task, our approach allows feeding the same bird's-eye view object detection network with input data from different sensor modalities. this can increase redundancy in a safety-critical environment. We present additional experiments to gain insight into the properties of the learned perspective-invariant abstract scene representation.

关键词： Monocular Object Detection 3D Object Detection Autonomous Driving Feature Map Transformation

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distributed Adaptive Controller for Output-Synchronization of Networked Strict Feedback systems with Dead-Zone Nonlinearity with Application in the Voltage Equalization Control of Ultra-Capacitor Type Power Source

Distributed Adaptive Controller for Output-Synchronization o...

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ieee international conference on Automation, Electronics and Electrical Engineering (AUTEEE)

作者： Liming Zhang Miao Yu State Grid Zhejiang Tongxiang Power Supply Company Jiaxing China College of Electrical Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9781665428408

In this paper, distributed robust adaptive backstepping control algorithm is developed for the output synchronization of multiple strict feedback systems with dead-zone nonlinearity. No knowledge could be assumed on the dead-zone for the design and implementation of controller and also the unknown system parameters. By combining graph theory with backstepping method, a distributed controller is designed for each agent recursively in order to make its output synchronized with the output of its neighbors, meanwhile, the overall system maintains bounded. It is proven that the output of all agents in the network could be synchronized when we connects the undirected graph, i.e., cooperative output synchronization of the network can be realized. the voltage equalization control of ultra-capacitor is presented as a numerical example to prove the effectiveness of the proposed controllers.

关键词： Electrical engineering Electric potential Backstepping Adaptive systems Laplace equations Graph theory Topology

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Fault Detection Mechanism of a Predictive Maintenance System Based on Autoregressive Integrated Moving Average Models 16th

Fault Detection Mechanism of a Predictive Maintenance System...

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16th international Symposium on distributed computing and Artificial Intelligence (DCAI)

作者： Fernandes, Marta Canito, Alda Corchado, Juan Manuel Marreiros, Goreti Polytech Porto ISEP IPP GECAD Res Grp Intelligent Engn & Comp Adv Innovat Porto Portugal Univ Salamanca USAL BISITE Res Ctr Salamanca Spain

ISBN: (纸本)9783030238872;9783030238865

the industrial world is amid a revolution, titled Industry 4.0, which entails the use of IoT technologies to enable the exchange of information between sensors, industrial machines and end users. A major issue in many industrial sectors is production inefficiency, with process downtime representing a loss for companies. Predictive maintenance, whereby maintenance is performed only when needed and before a failure occurs, has the potential to substantially reduce costs. this paper describes the fault detection mechanism of a predictive maintenance system developed for the metallurgic industry. Considering no previous information about faults is available, learning happens in an unsupervised manner. Imminent faults are predicted by estimating autoregressive integrated moving average models using real-world sensor data obtained from monitoring different machine components and parameters. the models' outputs are fused to assess the significance of an anomaly (or anomalies) along the time domain and determine how likely a fault is to occur, with alarms being issued when the prospect of a fault is high enough.

关键词： Predictive maintenance Anomaly detection ARIMA models sensor data

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A Fire Detection System Using Multi-sensor Networks Based on Fuzzy Logic in Indoor Scenarios 8

A Fire Detection System Using Multi-Sensor Networks Based on...

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8th international conference on Information and Communication Technology, ICoICT 2020

作者： Rachman, Fathur Zaini Hendrantoro, Gamantyo Wirawan Institut Teknologi Sepuluh Nopember Department of Electrical Engineering Surabaya Indonesia State Polytechnic of Balikpapan Balikpapan Indonesia

ISBN: (纸本)9781728161426

this paper presents the development of a fire detection system using a wireless multi-sensor network based on fuzzy logic rules. Until recently, the fire detection systems have been limited in the coverage area and installation of the device, so that the sensitivity of the sensor becomes limited indoor. this research proposes the use of multi-sensor system to detect indoor phenomena. the Fuzzy logic method is used to process data on multiple sensors and the cluster head (CH). the result of multi-sensor data processing is the condition level on the end device (ED). the test results show that the data processing using fuzzy logic for the measurements from distributed sensors reduces the data storage and computing complexity at the fusion center (FC). Fire detection application (FDA) displays the status condition (SC), where data sources from multi-sensor nodes are displayed as room conditions. © 2020 ieee.

关键词： Fuzzy logic

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Flexibility - enabling technologies using electric vehicles

Flexibility - enabling technologies using electric vehicles

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20th ieee international conference on Environment and Electrical Engineering (EEEIC) / 4th ieee Industrial and Commercial Power systems Europe conference (I and CPS Europe)

作者： Carere, Federico Bellesini, Francesco Bragatto, Tommaso Croce, Vincenzo Raveduto, Giuseppe Santori, Francesca Verber, Matteo Sapienza Univ Rome Dept Astronaut Elect & Energy Engn Rome Italy EMOTION SRL Deruta Italy ASM Terni SpA Terni Italy Engn Ingn Informat SpA Res & Dev Lab Palermo Italy Engn Ingn Informat SpA Res & Dev Lab Trento Italy

ISBN: (数字)9781728174556

ISBN: (纸本)9781728174556

Electric car usage has been growing rapidly over the past ten years, cars stock in 2018 exceeded 5 millions, +63% from 2019, Europe is accounting for 24% of the global fleet. the request of fast, rapid and ultra rapid charge is, on the other side, posing electric power network challenges. In this scenario the DSO is interested in exploiting EV charges in terms of flexibility that can be planned in optimized way, especially when it is combined with high penetration of RES. this paper provides evidence that EVs charging sessions, planned using a dedicated forecasting module, can contribute to balance the distribution power network;for this purpose suitable flexibility-enabling technologies developed under the H2020 project SOFIE have been used. Data analysis has pointed out that a proper program of charging sessions could significantly increase self-consumption index;moreover, an optimal scheduling has been validated taking into account realistic constraints for its actual implementation. Finally, the paper shows how the enabling technologies for flexibility exploitation have been implemented and validated;notably, a rescheduling of the charging sessions is allowed through the usage of forecasting techniques as well as the implementation of blockchain technologies for enabling a flexibility marketplace.

关键词： Electric Vehicles flexibility self-consumption reverse power flow distributed Ledger Technology forecasting algorithm

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Design and research of a distributed and scalable information platform for electric power sensing 9

Design and research of a distributed and scalable informatio...

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9th ieee Joint international Information Technology and Artificial Intelligence conference, ITAIC 2020

作者： Zeng, Pengfei Liang, Yun Tian, Wenfeng Sun, Xiaoyan Global Energy Interconnection Research Institute Co.Ltd. Beijing China Elec. Power Intelligent Sensing Technology and Application State Grid Corporation Joint Laboratory Beijing China

the development of power systems has called higher requirements for sensor information platforms, and sensor information platforms have become one key supporting technology for efficient and stable operation of power grids. this article first analyzes the current IoT reference architecture and the development trend of IoT platforms. then, a distributed sustainable integrated architecture sensor information platform is proposed to cater to the sensor requirements of the current power grid. Specifically, for the architecture, the distributed design and continuous integration design of the platform are introduced in detail. Finally, based on the designed architecture in this article, the practical work carried out by the information platform is introduced. this platform can be used for partial discharge detection of power equipment, providing edge intelligent computing support for the detection and analysis of radio frequency pulse signals. © 2020 ieee.

关键词： Internet of things

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EdgeLD: Locally distributed Deep Learning Inference on Edge Device Clusters 22

EdgeLD: Locally Distributed Deep Learning Inference on Edge ...

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22nd ieee international conference on High Performance computing and Communications, 18th ieee international conference on Smart City and 6th ieee international conference on Data Science and systems, HPCC-SmartCity-DSS 2020

作者： Xue, Feng Fang, Weiwei Xu, Wenyuan Wang, Qi Ma, Xiaodong Ding, Yi Beijing Jiaotong University School of Computer and Information Technology Beijing China Key Laboratory of Industrial Internet of Things Networked Control Ministry of Education Chongqing China Beijing Wuzi University School of Information Beijing China

ISBN: (纸本)9781728176499

Deep Neural Networks (DNN) have been widely used in a large number of application scenarios. However, DNN models are generally both computation-intensive and memory-intensive, thus difficult to be deployed on resource-constrained edge devices. Most previous studies focus on local model compression or remote cloud offloading, but overlook the potential benefits brought by distributed DNN execution on multiple edge devices. In this paper, we propose EdgeLD, a new framework for locally distributed execution of DNN-based inference tasks on a cluster of edge devices. In EdgeLD, DNN models' time cost will be firstly profiled in terms of computing capability and network bandwidth. Guided by profiling, an efficient model partition scheme is designed in EdgeLD to balance the assigned workload and the inference runtime among different edge devices. We also propose to employ layer fusion to reduce communication overheads on exchanging intermediate data among devices. Experiment results show that our proposed partition scheme saves up to 15.82% of inference time with regard to the conventional solution. Besides, applying layer fusion can speedup the DNN inference by 1.11-1.13X. When combined, EdgeLD can accelerate the original inference time by 1.77-3.57X on a cluster of 2-4 edge devices. © 2020 ieee.

关键词： Deep neural networks

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