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4th International conference on Advanced Engineering Theory and applications, AETA 2017

4th International Conference on Advanced Engineering Theory ...

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4th International conference on Advanced Engineering Theory and applications, AETA 2017

ISBN: (纸本)9783319698137

The proceedings contain 103 papers. The special focus in this conference is on Advanced Engineering Theory and applications. The topics include: A Method for Tuning the Frequency Series Wave Speed in Hydraulic Flexible Hose;Optimal Design of RFECT System for Inspection of 16-inch Ferromagnetic Pipe;building Management algorithms in Automated Warehouse Using Continuous Cluster Analysis Method;Development of VR Based Authoring Tool for Smart Factory;a Review of Real-World applications of Particle Swarm Optimization Algorithm;differential Evolution for Constrained Industrial Optimization;multi-sensor Data fusion Technique to Detect Radiation Emission in Wireless sensor Networks;Analytical Study of the IEEE 1609.4 MAC in Vehicular Ad Hoc Networks;Enhanced Self-sorting Based MAC Protocol for Vehicular Ad-Hoc Networks;Adaptive TDMA and CSMA-Based MAC Protocols for Vehicular Ad Hoc Networks: A Survey;a Low-Power Embedded IoT Microprocessor Design and Validation;a Deep Through-Microhole Fabricated Inside a Glass Optical Fiber by Use of a Near Ultraviolet Femtosecond Laser;MicroEYE: A Wireless Multiple-Lenses Panoramic Endoscopic System;an Overview of Cyber Insecurity and Malicious Uses of Cyberspace;enhancement of Distributed Fiber Optic Vibration sensors;Improving the Optical Properties of the 8500, K In-cup Packaging WLEDs by Using the Green-emitting CaF2:Ce3+, Tb3+Phosphor;simulation Study of Microstructure of the Amorphous ZnO;the Thixoforming Process with Different Pressing Speed for Aluminum Material;the Impact of Distance Between Two Phosphor Layers on Luminous Flux and Color Quality of Remote Phosphor Package;a Novel Approach to Fabricate Silicon Nanowire Field Effect Transistor for Biomolecule Sensing;development of Ray-Type Underwater Glider.

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A Survey of Multisensor fusion Techniques, architectures and Methodologies

A Survey of Multisensor Fusion Techniques, Architectures and...

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IEEE SoutheastCon conference

作者： Chandrasekaran, Balasubramaniyan Gangadhar, Shruti Conrad, James M. Univ N Carolina Dept Elect & Comp Engn Charlotte NC 28223 USA

ISBN: (纸本)9781538615393

In this paper, an overview of multi-sensor fusion is presented. Topics such as sensor fusion types, topologies and basic architectures used for multi-sensor fusion are reviewed. Also, fusion methods for signal level processing and decision level or symbol level are covered to provide the reader with basic understanding and techniques encountered in sensor fusion applications.

关键词： multi-sensor fusion classification sensor topologies and configurations signal fusion track-to-track fusion symbol level fusion dempster-shafer evidential reasoning

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Multisensor fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System 1st ed.

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丛书名： Lecture Notes in Electrical Engineering 501

2018年

作者： Sukhan Lee, Hanseok Ko, Song...

ISBN: (数字)9783319905099

ISBN: (纸本)9783319905082

This book includes selected papers from the 13th IEEE International conference on Multisensor Integration and fusion for Intelligent Systems (MFI 2017) held in Daegu, Korea, November 1622, 2017. It covers various topics, including sensor/actuator networks, distributed and cloud architectures, bio-inspired systems and evolutionary approaches, methods of cognitive sensor fusion, Bayesian approaches, fuzzy systems and neural networks, biomedical applications, autonomous land, sea and air vehicles, localization, tracking, SLAM, 3D perception, manipulation with multifinger hands, robotics, micro/nano systems, information fusion and sensors, and multimodal integration in HCI and HRI. The book is intended for robotics scientists, data and information fusion scientists, researchers and professionals at universities, research institutes and laboratories.

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WISDOM - A Wireless Debugging and Power Measurement System for Field Tests and Device Observation in WSN 21

WISDOM - A Wireless Debugging and Power Measurement System f...

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conference on Signal Processing: algorithms, architectures, Arrangements, and applications (SPA)

作者： Frohberg, Max Batlkhagva, Enkhdavaa Schoelzel, Mario IHP Technol Pk 25 Frankfurt Oder Germany

ISBN: (纸本)9788362065301

Energy consumption is a major concern in battery powered wireless sensor networks (WSN). For that reason there is a strong demand for the evaluation of power consumption of nodes in a wireless sensor network during its development phase. This evaluation can be done in early design stages by using simulations and models, but there is also the need for an evaluation in a real setup. This paper presents the WISDOM platform, which is a sensor node by itself, equipped with a 24 bit ADC converter that is used to measure power consumption of sensor nodes in a WSN. Monitored measurements can be transmitted wireless to a sink. In that way a power consumption profile can be created for a large scale WSN under realistic load conditions. The WISDOM platform provides a very high dynamic range for power metering, which is important for monitoring sensor nodes that operate in deep sleep modes as well as in high power transmission modes.

关键词： Wireless sensor networks Power demand Batteries Power measurement Wireless communication Voltage measurement Temperature measurement

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Single Pixel Spectral Image fusion with Side Information from a Grayscale sensor

Single Pixel Spectral Image Fusion with Side Information fro...

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IEEE Colombian conference on applications in Computational Intelligence (ColCACI)

作者： Andrés Jerez Hans Garcia Henry Arguello Dept. of Physics Universidad Industrial de Santander Bucaramanga Colombia Dept. of Electrical Engineering Universidad Industrial de Santander Bucaramanga Colombia Dept. of Computer Science Universidad Industrial de Santander Bucaramanga Colombia

ISBN: (纸本)9781538667415

Compressive spectral imaging (CSI) allows the acquisition of the spectral information of a three dimensional scene by using two dimensional coded projections. However, compressed sampling of information with simultaneously high spatial and high spectral resolution demands expensive highresolution sensors. Single pixel imaging is an approach that has had a high impact in spectroscopy, due to its low-cost implementation compared to architectures with larger sensors. One of the main challenges in CSI is to obtain high quality image reconstructions using low-cost architectures. Recent works have been shown that image fusion using measurements from a CSI sensor based on side information leads to improvement in the quality of the fused image. This work proposes a methodology that combines the spectral information of a single pixel camera (SPC) and the side information of a grayscale sensor in order to improve the reconstruction quality of the spatio-spectral data cube. Simulations and experimental results for the proposed method are shown, and its performance is compared with respect to the traditional approach of upsampling the single pixel image reconstruction through bilinear interpolation.

关键词： Gray-scale Image reconstruction Spatial resolution Apertures Detectors

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Multi-Task Ensemble Learning for Affect Recognition 18

Multi-Task Ensemble Learning for Affect Recognition

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ACM International Joint conference on Pervasive and Ubiquitous Computing / ACM International Symposium on Wearable Computers (UbiComp/ISWC)

作者： Gjoreski, Martin Lustrek, Mitja Gams, Matjaz Jozef Stefan Int Postgrad Sch Dept Intelligent Syst Ljubljana Slovenia Jozef Stefan Inst Dept Intelligent Syst Ljubljana Slovenia

ISBN: (纸本)9781450359665

Emotions are paramount in the human communication. They serve as a medium to enrich the communication, to express preferences, to communicate subjective cues, and even to manipulate others. The scientific research on emotions has been introduced back in 1868 when Charles Darwin undertook a study to prove that humans have an innate and universal set of emotional expressions [1]. In 1997, Picard published her book "Affective Computing" [2], which many consider the start of this scientific field. Two decades afterwards, when Affective Computing is a well-established research field, modeling emotional states still remains a challenging task. Among the main reasons are human subjectivity and inability of artificial intelligent systems to generalize - the lack of general intelligence, where humans excel and AI fails. Affective states are complex states that results in psychological and physiological changes that influence behaving and thinking [5]. A wearable device equipped with galvanic skin response (GSR - measures sweating rate), Electrocardiography (ECG - measures heart electrical activity) or blood volume pulse (BVP - measures cardiovascular dynamics) sensors can capture these psycho-physiological changes. Based on the data from the physiological sensors, machine learning (ML) models for affect recognition can be built. The two specific problems that our work addresses are method quality (affect recognition accuracy) and method generality (the ability to work on diverse datasets). Method quality: The straightforward approach for improving the method quality is to collect larger datasets and use M L algorithms with large learning capacity, such as the deep learning architectures. However, collecting a large dataset in affective computing is time consuming and expensive. Instead of collecting one single dataset, one can combine datasets from several affect recognition domains that are collected with similar physiological sensors, and then learn a unified deep multimod

关键词： Affective Computing Human Computer Interaction Multimodal sensor fusion Deep Neural Networks

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3rd International Symposium on Intelligent Systems Technologies and applications, ISTA 2017

3rd International Symposium on Intelligent Systems Technolog...

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3rd International Symposium on Intelligent Systems Technologies and applications, ISTA 2017

ISBN: (纸本)9783319683843

The proceedings contain 34 papers. The special focus in this conference is on Intelligent Systems Technologies and applications. The topics include: Markov Chain monte carlo methods and evolutionary algorithms for automatic feature selection from legal documents;an adaptive soft set based diagnostic risk prediction system;weighted bipartite graph model for recommender system using entropy based similarity measure;automated quiz generator;temporal modelling of bug numbers of open source software applications using LSTM;direct demodulator for amplitude modulated signals using artificial neural network;real-time detection of atrial fibrillation from short time single lead ECG traces using recurrent neural networks;styloLIT: Stylometry and location indicative terms based geographic location estimation using convolutional neural networks;an energy-efficient fuzzy based data fusion and tree based clustering algorithm for wireless sensor networks;eMG pattern classification using neural networks;crime against women: A state level analysis using a hierarchical and k-means clustering techniques;zero pronouns and their resolution in Sanskrit texts;semantic analysis using pairwise sentence comparison with word embeddings;illuminant color inconsistency as a powerful clue for detecting digital image forgery: A survey;a fast, block based, copy-move forgery detection approach using image gradient and modified K-means;oR operation based deterministic extended visual cryptography using complementary cover images;empirical comparison of different key frame extraction approaches with differential evolution based algorithms;breast cancer diagnosis and prognosis using machine learning techniques;performance assessment framework for computational models of visual attention;biologically-inspired foraging decision making in distributed cognitive radio networks;pAM4-based RADAR counter-measures in hostile environments.

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In-network Stochastic Consensus for WSN Surveillance applications 9

In-network Stochastic Consensus for WSN Surveillance Applica...

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9th International conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Dragana, Cristian Mihai, Viorel Stamatescu, Grigore Popescu, Dan Univ Politehn Bucuresti Dept Automat Control & Ind Informat Bucharest 060042 Romania

ISBN: (纸本)9781509064588

Surveillance applications require reliable monitoring system architectures and cost-efficient in-network data processing mechanisms able to provide effective information extraction for event tracking. Wireless sensor Networks (WSNs) appear to be the most suitable technology due to some well known benefits and the rapid development of embedded devices. Current research is mostly focused on improving and developing new decentralized sensor fusion schemes able to overcome the limitations introduced by the battery operated sensor nodes, but most of the time evaluating the proposed algorithms is performed with a serious lack of precise channel modeling. To close this gap, we provide a stochastic consensus implementation for lossy wireless networks comprising fixed and mobile sensor nodes, as a heterogeneous surveillance system based on ground sensor nodes and UAVs (Unmanned Aerial Vehicles). We developed a simulation framework tailored for fixed and mobile sensor nodes and we are able to evaluate the performance of consensus algorithms from a comparative standpoint, considering deterministic and probabilistic packet propagation models described by common models such as Free Space and Nakagami models. In this paper, we consider a complex in-network adaptive estimation using the distributed least-mean square algorithm tailored for WSN. We perform a mean-square error (MSE) performance analysis for both deterministic and probabilistic propagation models.

关键词： consensus WSN stochastic monitoring systems probabilistic models

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Exploration and Tradeoff of Advanced sensor fusion architectures in Designing for Reduced Congestion using Advanced Traffic Management Techniques 13

Exploration and Tradeoff of Advanced Sensor Fusion Architect...

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13th IEEE International conference on Control & Automation (ICCA)

作者： Robinson, John Balchanos, Michael Mavris, Dimitri Georgia Inst Technol Sch Aerosp Engn ASDL Atlanta GA 30332 USA

ISBN: (纸本)9781538626795

As a response to rapidly increasing costs due to congestion in urban traffic environments, the development of Intelligent Transport Systems (ITS) has paved the way towards new and innovative mobility concepts. With most of these concepts offering benefits in travel time and congestion relief, they also come with requirements of a fully participating vehicle network and a centralized routing architecture which is encountered with skepticism. To bridge the gap between concepts and reality, an intermediate, transitional centralized routing solution is recommended. With the selection of a viable routing control method as a key objective, this work is proposing a sensor fusion approach that is informed by traffic situational awareness. Testing and evaluation through a virtual experimentation framework will allow for assessment of alternative control methods, and will enable tradeoffs for the selection of more capable sensor fusion architectures. A demonstration of the virtual experimentation environment is provided, showing trades in travel time reduction for differing levels of vehicle participation in the routing solution.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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A new multi-sensor fusion algorithm based on the information filter framework 7

A new multi-sensor fusion algorithm based on the information...

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7th Seminar on Detection Systems architectures and Technologies (DAT)

作者： Cherchar, Ammar Thameri, Messaoud Belouchrani, Adel Ecole Super Ali CHABATI Reghaia Algeria Ecole Natl Polytech Algiers Algeria

ISBN: (纸本)9781509045082

his paper presents a new efficient track-to-track fusion (T2TF) algorithm based on the Information Filter (IF) framework which takes into account phenomena encountered in practical applications. In fact, it combines a modified version of the IF framework and a self-tuning fusion procedure based on likelihood functions to address issues such as the correlation of the estimates, the transmission shortcomings and the measurement origin uncertainty. The proposed method is evaluated through simulations and the obtained results show that the proposed algorithm performs as well the optimal centralized fusion schema in an idealized environment while it exhibits better robustness capabilities than existing decentralized algorithms when observation origin uncertainty is considered. Moreover, its reduced complexity cost is suitable for real time applications.

关键词： Information Filter Likelihood function T2TF Kalman filter

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