01341nam2 2200337 i 450 CFI063936020231121125455.08837304404IT2005-8938 20171026d2004 ||||0itac50 baitaitz01i xxxe z01n˜4: œ1934-1944Silvio D'AmicoPalermoNovecento©2004stampa 20053 v. (785 p. compless.)3 ritr.20 cmIn custodia.001CFI05265982001 Cronache 1914-1955Silvio d'Amicoantologia a cura di Alessandro d'Amico e Lina Vitointroduzioni di Gianfranco Pedullànote, bibliografia e indici a cura di Lina Vito4001CFI06393622000 1: 1934-1936Silvio D'Amico1001CFI06393642000 2: 1937-1941Silvio D'Amico2001CFI06393662000 3: 1942-1944Silvio D'Amico3D'Amico, SilvioCFIV10434307036359ITIT-0120171026IT-FR0017 Biblioteca umanistica Giorgio ApreaFR0017 CFI0639360Biblioteca umanistica Giorgio Aprea 52MAG 9/691-4.2 52MAG 9/691-4.3 52MAG 9/691-4.1 521934-19443606266UNICAS04021nam 2201045z- 450 991055729660332120210501(CKB)5400000000041073(oapen)https://directory.doabooks.org/handle/20.500.12854/69275(oapen)doab69275(EXLCZ)99540000000004107320202105d2020 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierGeo-Informatics in Resource ManagementBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20201 online resource (206 p.)3-03943-739-9 3-03943-740-2 The management of natural resources can be approached using different data sources and techniques, from images registered by sensors of onboard satellites to UAV platforms, using remote sensing techniques and geographic information systems, among others. The variability of problems and projects to be analyzed, studied, and solved is very wide. This book presents a collection of different experiences, ranging from the location of areas of interest to the simulation of future scenarios of a territory at local and regional scales, considering spatial resolutions ranging from centimeters to hundreds of meters. The common objective of all the works compiled in this book is to support decision-making in environmental management.Research & information: generalbicssc21st Century Maritime Silk Road regionactive fire dataadaptive K-means algorithmaerial imageryagent based modelingalpine grasslandanalytic hierarchy processarchival photographsassociated influencing factorsautomatic identification system datab-valuebearing capacitycrop growth perioddisaster managementdynamic of land useearthquake catalogEBKfarmland abandonment mappingfirst come first servefractional vegetation coverfuture scenariosgeographic information systemgeographical information systemgeographical survey of national conditionsGISGLCMgranulometric analysisground surveyheavy industry heat sourceshigh severity levelhotspot analysisland usemainland Chinamaritime oil chokepointMiddle East Respiratory Syndromemulti-scale LAI product validationNatura 2000 threatsnatural wetlands changesnight-time light dataNPP-VIIRSoil flow analysisPoznańprecision evaluationpreludePROSAIL modelremote sensingresource allocationsecondary succession monitoringseismic parametersseismicityspatial analysisspatial autocorrelationSpatial Decision Support System, CORINE Land Coverspatial patternspatial relationshipspectro-textural classificationtextural segmentationtopsis algorithmtree detectionResearch & information: generalMesas Carrascosa Francisco Javieredt1302206Mesas Carrascosa Francisco JavierothBOOK9910557296603321Geo-Informatics in Resource Management3026249UNINA04971nam 2201237z- 450 991056647390332120220506(CKB)5680000000037640(oapen)https://directory.doabooks.org/handle/20.500.12854/81209(oapen)doab81209(EXLCZ)99568000000003764020202205d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierSignal Processing Using Non-invasive Physiological SensorsBaselMDPI - Multidisciplinary Digital Publishing Institute20221 online resource (222 p.)3-0365-3720-1 3-0365-3719-8 Non-invasive biomedical sensors for monitoring physiological parameters from the human body for potential future therapies and healthcare solutions. Today, a critical factor in providing a cost-effective healthcare system is improving patients' quality of life and mobility, which can be achieved by developing non-invasive sensor systems, which can then be deployed in point of care, used at home or integrated into wearable devices for long-term data collection. Another factor that plays an integral part in a cost-effective healthcare system is the signal processing of the data recorded with non-invasive biomedical sensors. In this book, we aimed to attract researchers who are interested in the application of signal processing methods to different biomedical signals, such as an electroencephalogram (EEG), electromyogram (EMG), functional near-infrared spectroscopy (fNIRS), electrocardiogram (ECG), galvanic skin response, pulse oximetry, photoplethysmogram (PPG), etc. We encouraged new signal processing methods or the use of existing signal processing methods for its novel application in physiological signals to help healthcare providers make better decisions.Medical equipment and techniquesbicsscacousticAMR voiceauscultation sitesbiomedical signal processingblinkbrain-computer interfacebrain-computer interfaceBrain-Computer Interfacechannel of interestchannel selectionclassificationcomputer aided diagnosiscongenital heart diseaseconvolution neural network (CNN)convolutional neural network (CNN)deep neural networkdiscrete wavelet transformECGECG derived respiration (EDR)EEGElectrocardiogram (ECG)electroencephalogram (EEG)electroencephalographyEMGemotion recognitionempirical mode decompositioneye blinkfeature extractionfeature selection and reductionfunctional near-infrared spectroscopyGSRhome automationhuman machine interface (HMI)hybrid brain-computer interface (BCI)hypertensionimage gradientimage processinglong short-term memory (LSTM)machine learningmel-frequency cepstral coefficientsmental imagerymobilemotor imagerymovement intentionmovement-related cortical potentialmultiscale principal component analysismyoelectric controlneurorehabilitationOpen-CVpattern recognitionphonocardiogramphysiological signalspulse plethysmographquadriplegiaRaspberry Pireactionreflexregion of interestrehabilitationrespiratory rate (RR)responseshort-time Fourier transform (STFT)soundstartlestatistical analysissteady-state visually evoked potential (SSVEP)strokesuccessive decomposition indexsupport vector machineswheelchairz-score methodMedical equipment and techniquesNiazi Imran Khanedt1314109Naseer NomanedtSantosa HendrikedtNiazi Imran KhanothNaseer NomanothSantosa HendrikothBOOK9910566473903321Signal Processing Using Non-invasive Physiological Sensors3031716UNINA