Search results for "Detection"
showing 10 items of 2543 documents
Usability and acceptability of a fall monitoring system
2017
Falls and injurious falls affect one third of the older people. Those experiencing a fall might be unable to call for help remaining unattended for a long time. Pain, hypothermia and dehydration are common consequences. Additionally, ensuing fear of falling may reduce physical activity leading to functional decline and possibly institutionalization. Monitoring fall events the CONFIDENCE system could summon emergency assistance automatically thus reducing the negative consequences of falls. This thesis is part of the European FP7 project “Ubiquitous care system to support independent living” (CONFIDENCE) which developed a fall monitoring system based on three-dimensional (3D) localization of…
Knowledge discovery using diffusion maps
2013
Digitāla vizuālo spēju testēšanas rīka izstrāde un eksperimentāla analīze klīnisku un ikdienas populāciju gadījumā
2022
Mūsdienās neirodeģeneratīvo slimību ārstēšanas ir efektīva tad, ja slimības pazīmes tika atrastas agrīnā stadijā. Bakalaura darba ietvaros autors izstrādā kognitīvo traucējumu noteikšanas rīku, kas varētu palīdzēt cilvēkiem ātrāk identificēt simptomus. Darbā tika paveikts literatūras pārskats, kursa darba izstrādāta digitāla mentālas rotācijas prototipa apraksts, analīze un pilnveidošana līdz minimāla darbspējīga produkta stāvoklim. Tiek detalizēti aprakstīts kognitīvo traucējumu noteikšanas rīka izstrādes process, darba organizācija, pielietotas tehnoloģijas, plānošana, lietotnes palaišana un testēšana. Rīka testēšana piedalījās vairāk par 50 cilvēkiem, kuri pirmajā posmā pārbaudīja trīs d…
Anomaly detection in wireless sensor networks
2016
Wireless Sensor Network can be defined as a network of integrated sensors responsible for environmental sensing, data processing and communication with other sensors and the base station while consuming low power. Today, WSNs are being used in almost every part of life. The cost effective nature of WSNs is beneficial for environmental monitoring, production facilities and security monitoring. At the same time WSNs are vulnerable to security breaches, attacks and information leakage. Anomaly detection techniques are used to detect such activities over the network that do not conform to the normal behavior of the network communication. Supervised Machine learning approach is one way to detect…
Large Azobenzene Macrocycles : Formation and Detection by NMR and MS Methods
2023
Azobenzene macrocycles are widely investigated as potential drug delivery systems and as part of molecular machines due to their photo-responsive properties. Herein, we detect the formation of a series of new azobenzene macrocycles that feature up to eight switchable repeating units. High-resolution mass spectrometry and ion mobility (IM) mass spectrometry experiments and 1H and diffusion-ordered spectroscopy (DOSY) NMR are used to detect the presence of the macrocycles that contain 10 to 40 aromatic rings in the gas phase and solution, respectively. The responsiveness of the Z-to-E photo-switching of the smallest of the macrocycles, exhibiting two azobenzene units and in total 10 aromatic …
HYPERSPECTRAL REFLECTANCE SIGNATURES AND POINT CLOUDS FOR PRECISION AGRICULTURE BY LIGHT WEIGHT UAV IMAGING SYSTEM
2018
Abstract. The objective of this investigation was to study the use of a new type of a low-weight unmanned aerial vehicle (UAV) imaging system in the precision agriculture. The system consists of a novel Fabry-Perot interferometer based hyperspectral camera and a high-resolution small-format consumer camera. The sensors provide stereoscopic imagery in a 2D frame-format and they both weigh less than 500 g. A processing chain was developed for the production of high density point clouds and hyperspectral reflectance image mosaics (reflectance signatures), which are used as inputs in the agricultural application. We demonstrate the use of this new technology in the biomass estimation process, w…
Minimal learning machine in anomaly detection from hyperspectral images
2020
Abstract. Anomaly detection from hyperspectral data needs computationally efficient methods to process the data when the data gathering platform is a drone or a cube satellite. In this study, we introduce a minimal learning machine for hyperspectral anomaly detection. Minimal learning machine is a novel distance-based classification algorithm, which is now modified to detect anomalies. Besides being computationally efficient, minimal learning machine is also easy to implement. Based on the results, we show that minimal learning machine is efficient in detecting global anomalies from the hyperspectral data with low false alarm rate.
Phase-Sensitive Detection for Optical Sensing With Porous Silicon
2012
We report on a photonic sensor with an ultralow limit of detection (LoD) based on a phase interrogation readout scheme together with an anisotropic porous silicon (PSi) membrane. First, the fabrication of porous free-standing membranes from medium doped (100) surface oriented silicon, with pore diameters suitable for the infiltration of biomolecules, around 50 nm, is reported. Then, the phase interrogation scheme for characterizing the PSi membranes is presented whose results show that while volumetric sensitivity increases with the membrane thickness, the resolution in the birefringence measurements decrease dramatically due to depolarization effects. The best LoD was found to be equal to …
Shoreline Extraction and Change Detection using 1:5000 Scale Orthophoto Maps: A Case Study of Latvia-Riga
2015
Coastal management requires rapid, up-to-date, and
 correct information. Thus, the determination of coastal movements and its
 directions has primary importance for coastal managers. For monitoring the
 change of shorelines, remote sensing data, very high resolution aerial images
 and orthophoto maps are utilized for detections of change on shorelines. It is
 possible to monitor coastal changes by extracting the coastline from orthophoto
 maps. Along the Baltic Sea and Riga Gulf, Latvian coastline length is 496 km.
 It is rich of coastal resources and natural biodiversity.  Around 120 km of coastline are affected by
 significant coastal chang…
Design and development of safety and control systems in ATLAS
2021
El gran colisionador de hadrones, o LHC, es el acelerador de partículas más grande y potente del mundo. Ha sido construido por el CERN, la Organización Europea para la Investigación Nuclear, entre 1998 y 2008 en Ginebra, Suiza. Sucesivas mejoras en el LHC supondrán a partir de mediados del 2027 un incremento de la luminosidad, cuando pasará a llamarse High Luminosity LHC (HL-LHC). Esta tesis se divide en dos partes, por una parte la seguridad y operación de la infraestructura y por otra los sistemas de control y toma de datos. La primera parte de la tesis se dedica a la seguridad y operación de la infraestructura. Después de más de 10 años de funcionamiento, el riesgo de posibles fallos en …