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Book
Bioelectric Sensors
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

Bioelectric sensors are unique diagnostic principles and technologies. Although they share many traits with electrochemical sensors, especially regarding the common features of instrumentation, they are focused on the measurement of the electric properties of biorecognition elements as a reflection of cellular, biological, and biomolecular functions in a rapid, very sensitive, and often non-invasive manner. Bioelectric sensors offer a plethora of options in terms both of assay targets (molecules, cells, organs, and organisms) and methodological approaches (e.g., potentiometry, impedance spectrometry, and patch-clamp electrophysiology). Irrespective of the method of choice, “bioelectric profiling” is being rapidly established as a superior concept for a number of applications, including in vitro toxicity, signal transduction, real-time medical diagnostics, environmental risk assessment, and drug development. This Special Issue is the first that is exclusively dedicated to the advanced and emerging concepts and technologies of bioelectric sensors. Topics include, but are not restricted to, bioelectric sensors for single cell analysis, electrophysiological olfactory and volatile organic compounds sensors, impedimetric biosensors, microbial fuel cell biosensors, and implantable autonomous bioelectric micro- and nano-sensors.


Book
Bioelectric Sensors
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

Bioelectric sensors are unique diagnostic principles and technologies. Although they share many traits with electrochemical sensors, especially regarding the common features of instrumentation, they are focused on the measurement of the electric properties of biorecognition elements as a reflection of cellular, biological, and biomolecular functions in a rapid, very sensitive, and often non-invasive manner. Bioelectric sensors offer a plethora of options in terms both of assay targets (molecules, cells, organs, and organisms) and methodological approaches (e.g., potentiometry, impedance spectrometry, and patch-clamp electrophysiology). Irrespective of the method of choice, “bioelectric profiling” is being rapidly established as a superior concept for a number of applications, including in vitro toxicity, signal transduction, real-time medical diagnostics, environmental risk assessment, and drug development. This Special Issue is the first that is exclusively dedicated to the advanced and emerging concepts and technologies of bioelectric sensors. Topics include, but are not restricted to, bioelectric sensors for single cell analysis, electrophysiological olfactory and volatile organic compounds sensors, impedimetric biosensors, microbial fuel cell biosensors, and implantable autonomous bioelectric micro- and nano-sensors.


Book
Bioelectric Sensors
Author:
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Bookmark

Abstract

Bioelectric sensors are unique diagnostic principles and technologies. Although they share many traits with electrochemical sensors, especially regarding the common features of instrumentation, they are focused on the measurement of the electric properties of biorecognition elements as a reflection of cellular, biological, and biomolecular functions in a rapid, very sensitive, and often non-invasive manner. Bioelectric sensors offer a plethora of options in terms both of assay targets (molecules, cells, organs, and organisms) and methodological approaches (e.g., potentiometry, impedance spectrometry, and patch-clamp electrophysiology). Irrespective of the method of choice, “bioelectric profiling” is being rapidly established as a superior concept for a number of applications, including in vitro toxicity, signal transduction, real-time medical diagnostics, environmental risk assessment, and drug development. This Special Issue is the first that is exclusively dedicated to the advanced and emerging concepts and technologies of bioelectric sensors. Topics include, but are not restricted to, bioelectric sensors for single cell analysis, electrophysiological olfactory and volatile organic compounds sensors, impedimetric biosensors, microbial fuel cell biosensors, and implantable autonomous bioelectric micro- and nano-sensors.

Keywords

Technology: general issues --- organic optoelectronic device --- pulse meter --- biosensor --- Bluetooth low energy (BLE) --- photoplethysmogram (PPG) --- chronic wounds --- electrical stimulation --- direct microcurrent --- non-invasive --- pressure ulcer --- wireless technology --- biochips --- impedance spectroscopy --- electrical equivalent circuit --- biomaterial --- Lysinibacillus sphaericus JG-A12 --- anticancer therapeutic strategies --- apoptosis --- bioelectric --- 5-fluorouracil --- HeLa cell line --- superoxide --- cell immobilization --- 3D-printed well --- bioelectric profiling --- impedance analysis --- real-time measurements --- electrochemical biosensors --- SWCNT --- point-of-care diagnostics --- label-free biosensors --- ELISA --- carbon nanotubes --- bovine serum albumin --- pacemaker --- threat modeling --- internet of things (IoT) medical devices --- vulnerabilities --- organic optoelectronic device --- pulse meter --- biosensor --- Bluetooth low energy (BLE) --- photoplethysmogram (PPG) --- chronic wounds --- electrical stimulation --- direct microcurrent --- non-invasive --- pressure ulcer --- wireless technology --- biochips --- impedance spectroscopy --- electrical equivalent circuit --- biomaterial --- Lysinibacillus sphaericus JG-A12 --- anticancer therapeutic strategies --- apoptosis --- bioelectric --- 5-fluorouracil --- HeLa cell line --- superoxide --- cell immobilization --- 3D-printed well --- bioelectric profiling --- impedance analysis --- real-time measurements --- electrochemical biosensors --- SWCNT --- point-of-care diagnostics --- label-free biosensors --- ELISA --- carbon nanotubes --- bovine serum albumin --- pacemaker --- threat modeling --- internet of things (IoT) medical devices --- vulnerabilities


Book
Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS)
Authors: ---
ISBN: 3039213768 303921375X Year: 2019 Publisher: MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

This book contains the latest research on machine learning and embedded computing in advanced driver assistance systems (ADAS). It encompasses research in detection, tracking, LiDAR

Keywords

n/a --- FPGA --- recurrence plot (RP) --- residual learning --- neural networks --- driver monitoring --- navigation --- depthwise separable convolution --- optimization --- dynamic path-planning algorithms --- object tracking --- sub-region --- cooperative systems --- convolutional neural networks --- DSRC --- VANET --- joystick --- road scene --- convolutional neural network (CNN) --- multi-sensor --- p-norm --- occlusion --- crash injury severity prediction --- deep leaning --- squeeze-and-excitation --- electric vehicles --- perception in challenging conditions --- T-S fuzzy neural network --- total vehicle mass of the front vehicle --- electrocardiogram (ECG) --- communications --- generative adversarial nets --- camera --- adaptive classifier updating --- Vehicle-to-X communications --- convolutional neural network --- predictive --- Geobroadcast --- infinity norm --- urban object detector --- machine learning --- automated-manual transition --- red light-running behaviors --- photoplethysmogram (PPG) --- panoramic image dataset --- parallel architectures --- visual tracking --- autopilot --- ADAS --- kinematic control --- GPU --- road lane detection --- obstacle detection and classification --- Gabor convolution kernel --- autonomous vehicle --- Intelligent Transport Systems --- driving decision-making model --- Gaussian kernel --- autonomous vehicles --- enhanced learning --- ethical and legal factors --- kernel based MIL algorithm --- image inpainting --- fusion --- terrestrial vehicle --- driverless --- drowsiness detection --- map generation --- object detection --- interface --- machine vision --- driving assistance --- blind spot detection --- deep learning --- relative speed --- autonomous driving assistance system --- discriminative correlation filter bank --- recurrent neural network --- emergency decisions --- LiDAR --- real-time object detection --- vehicle dynamics --- path planning --- actuation systems --- maneuver algorithm --- autonomous driving --- smart band --- the emergency situations --- two-wheeled --- support vector machine model --- global region --- biological vision --- automated driving

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