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共 1449 条记录，以下是421-430 订阅

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Body sensor networks for human activity recognition

Body sensor networks for human activity recognition

引用

international Conference on Signal processing and Integrated networks (SPIN)

作者： Girija Chetty Matthew White Faculty of ESTeM University of Canberra Australia Infinity Imaging Group Melbourne Australia

ISBN: (纸本)9781467391986

Body sensor networks aim to capture the state of the user and its environment by utilizing from information heterogeneous sensors, and allow continuous monitoring of numerous physiological signals, where these sensors are attached to the subject's body. This can be immensely useful in activity recognition for identity verification, health and ageing and sport and exercise monitoring applications. In this paper, the application of body sensor networks for automatic and intelligent daily activity monitoring for elderly people, using wireless body sensors and smartphone inertial sensors has been reported. The scheme uses information theory-based feature ranking algorithms and classifiers based on random forests, ensemble learning and lazy learning. Extensive experiments using different publicly available datasets of human activity show that the proposed approach can assist in the development of intelligent and automatic real time human activity monitoring technology for eHealth application scenarios for elderly, disabled and people with special needs.

关键词： Intelligent sensors Databases sensor phenomena and characterization Smart phones Decision trees

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Energy Consumption Model for Data processing and Transmission in Energy Harvesting Wireless sensors 31st

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31st international symposium on Computer and information Sciences (ISCIS)

作者： Kadioglu, Yasin Murat Imperial Coll Dept Elect & Elect Engn Intelligent Syst & Networks Grp London SW7 2BT England

ISBN: (纸本)9783319472171

This paper studies energy harvesting wireless sensor nodes in which energy is gathered through harvesting process and data is gathered through sensing from the environment at random rates. These packets can be stored in node buffers as discrete packet forms which were previously introduced in "Energy Packet Network" paradigm. We consider a standby energy loss in the energy buffer (battery or capacitor) in a random rate, due to the fact that energy storages have self discharge characteristic. The wireless sensor node consumes K-e and Kt amount of harvested energy for node electronics (data sensing and processing operations) and wireless data transmission, respectively. Therefore, whenever a sensor node has less than Ke amount of energy, data can not be sensed and stored, and whenever there is more than Ke amount of energy, data is sensed and stored and also it could be transmitted immediately if the remaining energy is greater or equal than the Kt. We assume that the values of both Ke and Kt as one energy packet, which leads us a one-dimensional random walk modeling for the transmission system. We obtain stationary probability distribution as a product form solution and study on other quantities of interests. We also study on transmission errors among a set of M identical sensor with the presence of interference and noise.

关键词： Wireless sensors Energy harvesting Energy packets Data packets Standby energy loss Energy leakage Data leakage Markov modeling

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Prototype of a sensor device for learning environments

Prototype of a sensor device for learning environments

引用

IEEE international symposium on Wireless Systems (IDAACS-SWS)

作者： Vladimir Brovkov Albrecht Fortenbacher Haeseon Yun Daniel Junker Hochschule für Technik und Wirtschaft Berlin University of Applied Sciences Berlin Germany

This paper presents a prototype of a sensor device including heart rate, EDA and accelerometer sensors to investigate learners' internal state. Through experiments, sensor data were collected, visualized and correlated with information on learner's' emotional state derived from a self-report questionnaire. The results can be used to improve signal processing, and help find appropriate indicators from physiological data for learning environment design.

关键词： Prototypes Heart rate Acceleration Accelerometers Data visualization Physiology Context

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SINGLE-IMAGE SUPER RESOLUTION FOR MULTISPECTRAL REMOTE SENSING DATA USING CONVOLUTIONAL NEURAL networks 23

SINGLE-IMAGE SUPER RESOLUTION FOR MULTISPECTRAL REMOTE SENSI...

引用

23rd Congress of the international-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS)

作者： Liebel, L. Koerner, M. Tech Univ Munich Comp Vis Res Grp Remote Sensing Technol Arcisstr 21 D-80333 Munich Germany

In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations-e.g., segmentation or feature extraction-can benefit from detailed and distinguishable structures. In this paper, we show that recently introduced state-of-the-art approaches for single-image super resolution of conventional photographs, making use of deep learning techniques, such as convolutional neural networks (CNN), can successfully be applied to remote sensing data. With a huge amount of training data available, end-to-end learning is reasonably easy to apply and can achieve results unattainable using conventional handcrafted algorithms. We trained our CNN on a specifically designed, domain-specific dataset, in order to take into account the special characteristics of multispectral remote sensing data. This dataset consists of publicly available SENTINEL-2 images featuring 13 spectral bands, a ground resolution of up to 10m, and a high radiometric resolution and thus satisfying our requirements in terms of quality and quantity. In experiments, we obtained results superior compared to competing approaches trained on generic image sets, which failed to reasonably scale satellite images with a high radiometric resolution, as well as conventional interpolation methods.

关键词： Single-Image Super Resolution Deep Learning Convolutional Neural networks Sentinel-2

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IS and T international symposium on Electronic Imaging Science and Technology

IS and T International Symposium on Electronic Imaging Scien...

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Visual information processing and Communication VII 2016

The proceedings contain 19 papers. The topics discussed include: guided filter demosaicking for Fourier spectral filter array;a subjective study for the design of multi-resolution ABR video streams with the vp9 codec;pixel decimation of rd-cost functions in the HEVC encoder;fingerprint liveness detection using ensemble of local image quality assessments;machine learning-based early termination in prediction block decomposition for VP9;motion deblurring for depth-varying scenes;a sample adaptive offset early termination method for HEVC parallel encoding;towards region-of-attention analysis in eye tracking protocols;optimizing color information processing inside an SVM network;register multimodal images of large scene depth variation with global information;haze removal of single remote sensing image by combining dark channel prior with superpixel;VPx error resilient video coding using duplicated prediction information;block equivalence algorithm for labeling 2D and 3D images on GPU;a doubly error resilient coder of image sequences;optimizing transcoder quality targets using a neural network with an embedded bitrate model;and using deep convolutional neural networks for image retrieval.

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Using ADAS sensors in implementation of novel automotive features for increased safety and guidance

Using ADAS sensors in implementation of novel automotive fea...

引用

international Conference on Signal processing and Integrated networks (SPIN)

作者： Jihas Khan TATA ELXSI India

ISBN: (纸本)9781467391986

Advanced Driver Assistance Systems which was once limited to high end luxury vehicles are available to low end economy vehicles. This is as a result of the advancements in high density chip manufacturing and cost efficient sensor fusion techniques. Most of these features are implemented using a forward looking long/mid-range RADAR, rear radar, stereo and mono cameras which can monitor the entire surroundings of the vehicle, LIDAR sensors, IR sensors and ultrasonic sensors. This paper explores on some novel features that can be implemented using these sensors which are presently not researched on by the automotive community. Automatic power door, power tailgate and power hood opening limiter based on the static and dynamic obstacle information from ultrasonic sensor and radar is explored here. The application level algorithm, implementation details, sensors and actuators used and the bus interface are discussed too. The Paper also deals with how the dynamic traffic details and traffic sign status from the camera and information from V2V and V2X sensors can be used in fine tuning and recalculation of the Estimated Time of Arrival in navigation feature. Another novel feature is to assist the driver in safe overtaking of the vehicle. Such features and its implementation details are discussed in detail which can pave way to its realization in future vehicles.

关键词： Signal processing algorithms Automobiles Radar Cameras sensor phenomena and characterization

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Implementation of a Modular Growing When Required Neural Gas Architecture for Recognition of Falls 1

引用

23rd international Conference on Neural information processing (ICONIP)

作者： Klein, Frederico B. Stepanova, Karla Cangelosi, Angelo Univ Plymouth Sch Comp Elect & Math Plymouth Devon England Czech Tech Univ Dept Cybernet Prague Czech Republic

ISBN: (数字)9783319466873

ISBN: (纸本)9783319466873;9783319466866

In this paper we aim for the replication of a state of the art architecture for recognition of human actions using skeleton poses obtained from a depth sensor. We review the usefulness of accurate human action recognition in the field of robotic elderly care, focusing on fall detection. We attempt fall recognition using a chained Growing When Required neural gas classifier that is fed only skeleton joints data. We test this architecture against Recurrent SOMs (RSOMs) to classify the TST Fall detection database ver. 2, a specialised dataset for fall sequences. We also introduce a simplified mathematical model of falls for easier and faster bench-testing of classification algorithms for fall detection. The outcome of classifying falls from our mathematical model was successful with an accuracy of 97.12 +/- 1.65% and from the TST Fall detection database ver. 2 with an accuracy of 90.2 +/- 2.68% when a filter was added.

关键词： Action recognition Falls Neural networks Neural gas Topological classifiers Socially assistive robotics

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Arduino based automatic wireless weather station with remote graphical application and alerts

Arduino based automatic wireless weather station with remote...

引用

international Conference on Signal processing and Integrated networks (SPIN)

作者： Hardeep Saini Abhishek Thakur Satinderpar Ahuja Nitant Sabharwal Naveen Kumar ECED Indo Global College of Engineering (IGCE) Mohali Punjab India ATHAL Services Private Limited Chandigarh India

ISBN: (纸本)9781467391986

In this paper we have proposed, developed and tested a hardware module based on Arduino Uno Board and Zigbee wireless technology, which measures the meteorological data, including air temperature, dew point temperature, barometric pressure, relative humidity, wind speed and wind direction. This information is received by a specially designed application interface running on a PC connected through Zigbee wireless link. The proposed system is also a mathematical model capable of generating short time local alerts based on the current weather parameters. It gives an on line and real time effect. We have also compared the data results of the proposed system with the data values of Meteorological Station Chandigarh and Snow & Avalanche Study Establishment Chandigarh Laboratory. The results have come out to be very precise. The idea behind to this work is to monitor the weather parameters, weather forecasting, condition mapping and warn the people from its disastrous effects.

关键词： sensors ZigBee Humidity Wireless sensor networks Wind speed

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An overview of dynamic data mining

An overview of dynamic data mining

引用

international Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Jingxin Du Jun Zhou Chang Li Lin Yang School of Electronics and Information Engineering Liaoning University of Technology Jinzhou Liaoning

With the advent of the era of big data, the dynamic characteristic of data performance is more outstanding. People on the data of “freshness” require increasingly higher, and the traditional static database which is based on data mining has not satisfied the demand of real-time. In modern world, the data generated constantly in the various fields, such as sensor networks, finance, Web logs, and data communications and other fields, which has generated a lot of dynamic data. Dynamic data mining is a way to find hidden knowledge approach of dynamic data approach. For the dynamic data, the paper reviews the processing methods of dynamic mining which includes the treatment stream data mining, distributed processing framework and approach incremental mining in now days. It introduces the main ideas of the various treatment methods, specific methods and related features.

关键词： Data mining Sparks Itemsets Real-time systems Data models Distributed databases

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Applications of Wireless sensor Network in the Field of Medical and Healthcare

Applications of Wireless Sensor Network in the Field of Medi...

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2016 3rd international Conference on Materials Engineering,Manufacturing Technology and Control(ICMEMTC 2016)

作者： Chunmei Wang Tianyu Cao Tianlei Gao Zhaoyang Liu Shandong Provincial Key Laboratory of Computer Networks Shandong Computer Science Center (National Supercomputer Center in Jinan) School of Mathematical Sciences Dalian University of Technology

Wireless sensor network(WSN) is an emerging technology which integrated sensor technology, embedded computing technology, modern network, wireless communication technology, distributed information processing technology. This technology has wide applications. With the development of technology, WSN will be a great influence in many aspects of medical practice. This paper discusses the application of WSN in the medical field.

关键词： WSN System structure Medical application

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