Search results: Found 13

Listing 1 - 10 of 13 << page
of 2
>>
Sort by
Realization Limits of Impulse-Radio UWB Indoor Localization Systems

Author:
Book Series: Karlsruher Forschungsberichte aus dem Institut für Hochfrequenztechnik und Elektronik ISSN: 18684696 ISBN: 9783731501145 Year: Volume: 71 Pages: VIII, 192 p. DOI: 10.5445/KSP/1000036616 Language: ENGLISH
Publisher: KIT Scientific Publishing
Subject: Technology (General)
Added to DOAB on : 2019-07-30 20:01:59
License:

Loading...
Export citation

Choose an application

Abstract

In this work, the realization limits of an impulse-based Ultra-Wideband (UWB) localization system for indoor applications have been thoroughly investigated and verified by measurements. The analysis spans from the position calculation algorithms, through hardware realization and modeling, up to the localization experiments conducted in realistic scenarios. The main focus was put on identification and characterization of limiting factors as well as developing methods to overcome them.

Emerging Technologies to Promote and Evaluate Physical Activity

Authors: --- --- ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889192984 Year: Pages: 140 DOI: 10.3389/978-2-88919-298-4 Language: English
Publisher: Frontiers Media SA
Subject: Public Health --- Medicine (General)
Added to DOAB on : 2015-12-10 11:59:07
License:

Loading...
Export citation

Choose an application

Abstract

Increasingly, efforts to promote and measure physical activity are achieving greater precision, greater ease of use, and/or greater scope by incorporating emerging technologies. This is significant for physical activity promotion because more precise measurement will allow investigators to better understand where, when, and how physical activity is and is not occurring, thus enabling more effective targeting of particular behavior settings. Emerging technologies associated with the measurement and evaluation of physical activity are noteworthy because: (1) Their ease of use and transferability can greatly increase external validity of measures and findings; (2) Technologies can significantly increase the ability to analyze patterns; (3) They can improve the ongoing, systematic collection and analysis of public health surveillance due to real-time capabilities associated with many emerging technologies; (4) There is a need for research and papers about the cyberinfrastructure required to cope with big data (multiple streams, processing, aggregation, visualization, etc.); and (5) Increasingly blurred boundaries between measurement and intervention activity (e.g., the quantified-self /self-tracking movement) may necessitate a reevaluation of the conventional scientific model for designing and evaluating these sorts of studies. There have been many recent, disparate advances related to this topic. Advances such as crowdsourcing allow for input from large, diverse audiences that can help to identify and improve infrastructure for activity (e.g., large group identification of environmental features that are conducive or inhibiting to physical activity on a national and even global scale). Technologies such as Global Positioning Systems (GPS) and accelerometry are now available in many mobile phones and can be used for identifying and promoting activity and also understanding naturalistically-occurring activity. SenseCam and other personal, visual devices and mobile apps provide person point of view context to physical activity lifestyle and timing. Further, multiple sensor systems are enabling better identification of types of activities (like stair climbing and jumping) that could not previously be identified readily using objective measures like pedometers or accelerometers in isolation. The ability of activity sensors to send data to remote servers allows for the incorporation of online technology (e.g., employing an online social-network as a source of inspiration or accountability to achieve physical activity goals), and websites such as Stickk.com enable individuals to make public contracts visible to other users and also incorporates financial incentives and disincentives in order to promote behaviors including physical activity. In addition, the increasing use of active-gaming (e.g., Wii, XBox Kinect) in homes, schools, and other venues further underscores the growing link between technology and physical activity. Improvements in mathematical models and computer algorithms also allow greater capacity for classifying and evaluating physical activity, improving consistency across research studies. Emerging technologies in the promotion and evaluation of physical activity is a significant area of interest because of its ability to greatly increase the amount and quality of global recorded measurements of PA patterns and its potential to more effectively promote PA. Emerging technologies related to physical activity build on our own and others’ interdisciplinary collaborations in employing technology to address public health challenges. This research area is innovative in that is uses emerging resources including social media, crowdsourcing, and online gaming to better understand patterns of physical activity.

Compartment Syndrome

Authors: --- ---
ISBN: 9783030223311 / 9783030223304 Year: Pages: 181 DOI: 10.1007/978-3-030-22331-1 Language: English
Publisher: Springer
Subject: Medicine (General)
Added to DOAB on : 2019-10-01 11:36:08
License:

Loading...
Export citation

Choose an application

Abstract

Compartment syndrome is a complex physiologic process with significant potential harm, and though an important clinical problem, the basic science and research surrounding this entity remains poorly understood. This unique open access book fills the gap in the knowledge of compartment syndrome, re-evaluating the current state of the art on this condition. The current clinical diagnostic criteria are presented, as well as the multiple dilemmas facing the surgeon. Pathophysiology, ischemic thresholds and pressure management techniques and limitations are discussed in detail. The main surgical management strategy, fasciotomy, is then described for both the upper and lower extremities, along with wound care. Compartment syndrome due to patient positioning, in children and polytrauma patients, and unusual presentations are likewise covered. Novel diagnosis and prevention strategies, as well as common misconceptions and legal ramifications stemming from compartment syndrome, round out the presentation.Unique and timely, Compartment Syndrome: A Guide to Diagnosis and Management will be indispensable for orthopedic and trauma surgeons confronted with this common yet challenging medical condition.

Application of Artificial Neural Networks in Geoinformatics

Author:
ISBN: 9783038427421 9783038427414 Year: Pages: VI, 222 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Environmental Sciences
Added to DOAB on : 2018-04-27 16:05:32
License:

Loading...
Export citation

Choose an application

Abstract

Recently, a need has arisen for prediction techniques that can address a variety of problems by combining methods from the rapidly developing field of machine learning with geoinformation technologies such as GIS, remote sensing, and GPS. As a result, over the last few decades, one particular machine learning technology, known as artificial neural networks, has been successfully applied to a wide range of fields in science and engineering. In addition, the development of computational and spatial technologies has led to the rapid growth of geoinformatics, which specializes in the analysis of spatial information. Thus, recently, artificial neural networks have been applied to geoinformatics and have produced valuable results in the fields of geoscience, environment, natural hazards, natural resources, and engineering. Hence, this Special Issue of the journal Applied Sciences, “Application of Artificial Neural Networks in Geoinformatics,” was successfully planned, and we here publish a collection of papers detailing novel contributions that are of relevance to these topics.

Visible Light Communication and Positioning

Author:
ISBN: 9783039214358 / 9783039214365 Year: Pages: 144 DOI: 10.3390/books978-3-03921-436-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Added to DOAB on : 2019-12-09 11:49:16
License:

Loading...
Export citation

Choose an application

Abstract

In recent years, wireless communications have significantly evolved due to the advanced technology of smartphones;, portable devices; and the rapid growth of Internet of Things, e-Health, and intelligent transportation systems . Moreover, there is anare increasing need fors of emerging intelligent services like positioning and sensing in athe future intelligence society. Recent years have witnessed the growing research interests and activities in the communication and intelligencet services in the optical wireless spectrum, as a complementary technology to more

MEMS Accelerometers

Authors: --- ---
ISBN: 9783038974147 / 9783038974154 Year: Pages: 252 DOI: 10.3390/books978-3-03897-415-4 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
License:

Loading...
Export citation

Choose an application

Abstract

Micro-electro-mechanical system (MEMS) devices are widely used for inertia, pressure, and ultrasound sensing applications. Research on integrated MEMS technology has undergone extensive development driven by the requirements of a compact footprint, low cost, and increased functionality. Accelerometers are among the most widely used sensors implemented in MEMS technology. MEMS accelerometers are showing a growing presence in almost all industries ranging from automotive to medical. A traditional MEMS accelerometer employs a proof mass suspended to springs, which displaces in response to an external acceleration. A single proof mass can be used for one- or multi-axis sensing. A variety of transduction mechanisms have been used to detect the displacement. They include capacitive, piezoelectric, thermal, tunneling, and optical mechanisms. Capacitive accelerometers are widely used due to their DC measurement interface, thermal stability, reliability, and low cost. However, they are sensitive to electromagnetic field interferences and have poor performance for high-end applications (e.g., precise attitude control for the satellite). Over the past three decades, steady progress has been made in the area of optical accelerometers for high-performance and high-sensitivity applications but several challenges are still to be tackled by researchers and engineers to fully realize opto-mechanical accelerometers, such as chip-scale integration, scaling, low bandwidth, etc.

Keywords

low-temperature co-fired ceramic (LTCC) --- capacitive accelerometer --- wireless --- process optimization --- performance characterization --- MEMS accelerometer --- mismatch of parasitic capacitance --- electrostatic stiffness --- high acceleration sensor --- piezoresistive effect --- MEMS --- micro machining --- turbulent kinetic energy dissipation rate --- probe --- microelectromechanical systems (MEMS) piezoresistive sensor chip --- Taguchi method --- marine environmental monitoring --- accelerometer --- frequency --- acceleration --- heat convection --- motion analysis --- auto-encoder --- dance classification --- deep learning --- self-coaching --- wavelet packet --- classification of horse gaits --- MEMS sensors --- gait analysis --- rehabilitation assessment --- body sensor network --- MEMS accelerometer --- electromechanical delta-sigma --- built-in self-test --- in situ self-testing --- digital resonator --- accelerometer --- activity monitoring --- regularity of activity --- sleep time duration detection --- indoor positioning --- WiFi-RSSI radio map --- MEMS-IMU accelerometer --- zero-velocity update --- step detection --- stride length estimation --- field emission --- hybrid integrated --- vacuum microelectronic --- cathode tips array --- interface ASIC --- micro-electro-mechanical systems (MEMS) --- delaying mechanism --- safety and arming system --- accelerometer --- multi-axis sensing --- capacitive transduction --- inertial sensors --- three-axis accelerometer --- micromachining --- miniaturization --- stereo visual-inertial odometry --- fault tolerant --- hostile environment --- MEMS-IMU --- mode splitting --- Kerr noise --- angular-rate sensing --- whispering-gallery-mode --- optical microresonator --- three-axis acceleration sensor --- MEMS technology --- sensitivity --- L-shaped beam --- n/a

Product/Process Fingerprint in Micro Manufacturing

Author:
ISBN: 9783039210343 / 9783039210350 Year: Pages: 274 DOI: 10.3390/books978-3-03921-035-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General)
Added to DOAB on : 2019-06-26 08:44:06
License:

Loading...
Export citation

Choose an application

Abstract

The continuous miniaturization of products and the growing complexity of their embedded multifunctionalities necessitates continuous research and development efforts regarding micro components and related micro manufacturing technologies. Highly miniaturized systems, manufactured using a wide variety of materials, have found application in key technological fields, such as healthcare devices, micro implants, mobility, communications, optics, and micro electromechanical systems. Innovations required for the high-precision manufacturing of micro components can specifically be achieved through optimizations using post-process (i.e., offline) and in-process (i.e., online) metrology of both process input and output parameters, as well as geometrical features of the produced micro parts. However, it is of critical importance to reduce the metrology and optimization efforts, since process and product quality control can represent a significant portion of the total production time in micro manufacturing. To solve this fundamental challenge, research efforts have been undertaken in order to define, investigate, implement, and validate the so-called “product/process manufacturing fingerprint” concept. The “product manufacturing fingerprint” concept refers to those unique dimensional outcomes (e.g., surface topography, form error, critical dimensions, etc.) on the produced component that, if kept under control and within specifications, ensure that the entire micro component complies to its specifications. The “process manufacturing fingerprint” is a specific process parameter or feature to be monitored and controlled, in order to maintain the manufacture of products within the specified tolerances. By integrating both product and process manufacturing fingerprint concepts, the metrology and optimization efforts are highly reduced. Therefore, the quality of the micro products increases, with an obvious improvement in production yield. Accordingly, this Special Issue seeks to showcase research papers, short communications, and review articles that focus on novel methodological developments and applications in micro- and sub-micro-scale manufacturing, process monitoring and control, as well as micro and sub-micro product quality assurance. Focus will be on micro manufacturing process chains and their micro product/process fingerprint, towards full process optimization and zero-defect micro manufacturing.

Keywords

micro-injection moulding --- quality assurance --- process monitoring --- micro metrology --- positioning platform --- Halbach linear motor --- commercial control hardware --- diffractive optics --- gratings --- microfabrication --- computer holography --- manufacturing signature --- process fingerprint --- Fresnel lenses --- injection compression molding --- injection molding --- micro structures replication --- confocal microscopy --- optical quality control --- uncertainty budget --- optimization --- precision injection molding --- quality control --- process monitoring --- product fingerprint --- process fingerprint --- electrical discharge machining --- electrical discharge machining (EDM) --- surface roughness --- surface integrity --- optimization --- desirability function --- satellite drop --- electrohydrodynamic jet printing --- charge relaxation time --- laser ablation --- superhydrophobic surface --- process fingerprint --- product fingerprint --- surface morphology --- artificial compound eye --- multi-spectral imaging --- lithography --- spectral splitting --- plasma-electrolytic polishing --- PeP --- surface modification --- finishing --- electro chemical machining --- ECM --- Electro sinter forging --- resistance sintering --- electrical current --- fingerprints --- electrical discharge machining --- micro drilling --- process monitoring --- quality control --- electrochemical machining (ECM) --- process control --- current monitoring --- current density --- surface roughness --- inline metrology --- haptic actuator --- impact analysis --- high strain rate effect --- damping --- 2-step analysis --- micro-grinding --- bioceramics --- materials characterisation --- dental implant --- microinjection moulding --- process fingerprints --- flow length --- quality assurance --- n/a

Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing

Authors: ---
ISBN: 9783039212156 / 9783039212163 Year: Pages: 438 DOI: 10.3390/books978-3-03921-216-3 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Mechanical Engineering
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

As computer and space technologies have been developed, geoscience information systems (GIS) and remote sensing (RS) technologies, which deal with the geospatial information, have been rapidly maturing. Moreover, over the last few decades, machine learning techniques including artificial neural network (ANN), deep learning, decision tree, and support vector machine (SVM) have been successfully applied to geospatial science and engineering research fields. The machine learning techniques have been widely applied to GIS and RS research fields and have recently produced valuable results in the areas of geoscience, environment, natural hazards, and natural resources. This book is a collection representing novel contributions detailing machine learning techniques as applied to geoscience information systems and remote sensing.

Keywords

landslide --- bagging ensemble --- Logistic Model Trees --- GIS --- Vietnam --- colorization --- random forest regression --- grayscale aerial image --- change detection --- gully erosion --- environmental variables --- data mining techniques --- SCAI --- GIS --- mapping --- single-class data descriptors --- materia medica resource --- Panax notoginseng --- one-class classifiers --- geoherb --- change detection --- convolutional network --- deep learning --- panchromatic --- remote sensing --- remote sensing image segmentation --- convolutional neural networks --- Gaofen-2 --- hybrid structure convolutional neural networks --- winter wheat spatial distribution --- classification-based learning --- real-time precise point positioning --- convergence time --- ionospheric delay constraints --- precise weighting --- landslide --- weights of evidence --- logistic regression --- random forest --- hybrid model --- traffic CO --- traffic CO prediction --- neural networks --- GIS --- land use/land cover (LULC) --- unmanned aerial vehicle --- texture --- gray-level co-occurrence matrix --- machine learning --- crop --- landslide susceptibility --- random forest --- boosted regression tree --- information gain --- landslide susceptibility map --- ALS point cloud --- multi-scale --- classification --- large scene --- coarse particle --- particulate matter 10 (PM10) --- landsat image --- machine learning --- support vector machine --- high-resolution --- optical remote sensing --- object detection --- deep learning --- transfer learning --- land subsidence --- Bayes net --- naïve Bayes --- logistic --- multilayer perceptron --- logit boost --- change detection --- convolutional network --- deep learning --- panchromatic --- remote sensing --- leaf area index (LAI) --- machine learning --- Sentinel-2 --- sensitivity analysis --- training sample size --- spectral bands --- spatial sparse recovery --- constrained spatial smoothing --- spatial spline regression --- alternating direction method of multipliers --- landslide prediction --- machine learning --- neural networks --- model switching --- spatial predictive models --- predictive accuracy --- model assessment --- variable selection --- feature selection --- model validation --- spatial predictions --- reproducible research --- Qaidam Basin --- remote sensing --- TRMM --- artificial neural network --- n/a

Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters

Authors: --- ---
ISBN: 9783039212392 / 9783039212408 Year: Pages: 334 DOI: 10.3390/books978-3-03921-240-8 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-12-09 11:49:15
License:

Loading...
Export citation

Choose an application

Abstract

Monitoring of vegetation structure and functioning is critical to modeling terrestrial ecosystems and energy cycles. In particular, leaf area index (LAI) is an important structural property of vegetation used in many land surface vegetation, climate, and crop production models. Canopy structure (LAI, fCover, plant height, and biomass) and biochemical parameters (leaf pigmentation and water content) directly influence the radiative transfer process of sunlight in vegetation, determining the amount of radiation measured by passive sensors in the visible and infrared portions of the electromagnetic spectrum. Optical remote sensing (RS) methods build relationships exploiting in situ measurements and/or as outputs of physical canopy radiative transfer models. The increased availability of passive (radar and LiDAR) RS data has fostered their use in many applications for the analysis of land surface properties and processes, thanks also to their insensitivity to weather conditions and the capability to exploit rich structural and textural information. Data fusion and multi-sensor integration techniques are pressing topics to fully exploit the information conveyed by both optical and microwave bands.

Keywords

conifer forest --- leaf area index --- smartphone-based method --- canopy gap fraction --- terrestrial laser scanning --- forest inventory --- density-based clustering --- forest aboveground biomass --- root biomass --- tree heights --- GLAS --- artificial neural network --- allometric scaling and resource limitation --- structure from motion (SfM) --- 3D point cloud --- remote sensing --- local maxima --- fixed tree window size --- managed temperate coniferous forests --- point cloud --- spectral information --- structure from motion (SfM) --- unmanned aerial vehicle (UAV) --- chlorophyll fluorescence (ChlF) --- drought --- Mediterranean --- photochemical reflectance index (PRI) --- photosynthesis --- R690/R630 --- recovery --- BAAPA --- remote sensing --- household survey --- forest --- farm types --- automated classification --- sampling design --- adaptive threshold --- over and understory cover --- LAI --- leaf area index --- EPIC --- simulation --- satellite --- MODIS --- biomass --- evaluation --- southern U.S. forests --- VIIRS --- leaf area index (LAI) --- Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) --- MODIS --- consistency --- uncertainty --- evaluation --- downscaling --- Pléiades imagery --- unmanned aerial vehicle --- stem volume estimation --- remote sensing --- clumping index --- leaf area index --- trunk --- terrestrial LiDAR --- HemiView --- forest above ground biomass (AGB) --- polarization coherence tomography (PCT) --- P-band PolInSAR --- tomographic profiles --- canopy closure --- global positioning system --- hemispherical sky-oriented photo --- signal attenuation --- geographic information system --- digital aerial photograph --- aboveground biomass --- leaf area index --- photogrammetric point cloud --- recursive feature elimination --- machine-learning --- forest degradation --- multisource remote sensing --- modelling aboveground biomass --- random forest --- Brazilian Amazon --- validation --- phenology --- NDVI --- LAI --- spectral analyses --- European beech --- altitude --- forests biomass --- remote sensing --- REDD+ --- random forest --- Tanzania --- RapidEye

Mobile Mapping Technologies

Authors: --- --- ---
ISBN: 9783039280186 / 9783039280193 Year: Pages: 334 DOI: 10.3390/books978-3-03928-019-3 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-01-07 09:08:26
License:

Loading...
Export citation

Choose an application

Abstract

Mobile Mapping technologies have seen a rapid growth of research activity and interest in the last years, due to the increased demand of accurate, dense and geo-referenced 3D data. Their main characteristic is the ability of acquiring 3D information of large areas dynamically. This versatility has expanded their application fields from the civil engineering to a broader range (industry, emergency response, cultural heritage...), which is constantly widening. This increased number of needs, some of them specially challenging, is pushing the Scientific Community, as well as companies, towards the development of innovative solutions, ranging from new hardware / open source software approaches and integration with other devices, up to the adoption of artificial intelligence methods for the automatic extraction of salient features and quality assessment for performance verification The aim of the present book is to cover the most relevant topics and trends in Mobile Mapping Technology, and also to introduce the new tendencies of this new paradigm of geospatial science.

Keywords

cultural heritage --- restoration --- indoor mapping --- laser scanning --- wearable mobile laser system --- 3D digitalization --- SLAM --- visual landmark sequence --- indoor topological localization --- convolutional neural network (CNN) --- second order hidden Markov model --- ORB-SLAM2 --- binary vocabulary --- small-scale vocabulary --- rapid relocation --- terrestrial laser scanning --- tunnel central axis --- tunnel cross section --- enhanced RANSAC --- quadric fitting --- constrained nonlinear least-squares problem --- visual simultaneous localization and mapping --- dynamic environment --- RGB-D camera --- encoder --- OctoMap --- IMMS --- indoor mapping --- MLS --- mobile laser scanning --- SLAM --- point clouds --- 2D laser scanner --- 2D laser range-finder --- LiDAR --- LRF --- sensors configurations --- Lidar localization system --- unmanned vehicle --- segmentation-based feature extraction --- category matching --- multi-group-step L-M optimization --- map management --- indoor mapping --- room type tagging --- semantic enrichment --- grammar --- Bayesian inference --- indoor localization --- crowdsourcing trajectory --- fingerprinting --- smartphone --- mobile mapping --- laser scanning --- self-calibration --- 3D point clouds --- geometric features --- motion estimation --- trajectory fusion --- mobile mapping --- sensor fusion --- optical sensors --- robust statistical analysis --- portable mobile mapping system --- handheld --- 3D processing --- point cloud --- Vitis vinifera --- terrestrial laser scanning --- plant vigor --- mobile mapping --- precision agriculture --- vine size --- visual positioning --- indoor scenes --- automated database construction --- image retrieval

Listing 1 - 10 of 13 << page
of 2
>>
Sort by
Narrow your search
-->