Search results for "probability"
showing 10 items of 3417 documents
Dynamic network identification from non-stationary vector autoregressive time series
2018
Learning the dynamics of complex systems features a large number of applications in data science. Graph-based modeling and inference underpins the most prominent family of approaches to learn complex dynamics due to their ability to capture the intrinsic sparsity of direct interactions in such systems. They also provide the user with interpretable graphs that unveil behavioral patterns and changes. To cope with the time-varying nature of interactions, this paper develops an estimation criterion and a solver to learn the parameters of a time-varying vector autoregressive model supported on a network of time series. The notion of local breakpoint is proposed to accommodate changes at individu…
Rapid parameter estimation of discrete decaying signals using autoencoder networks
2021
Machine learning: science and technology 2(4), 045024 (2021). doi:10.1088/2632-2153/ac1eea
Causal Inference in Geoscience and Remote Sensing From Observational Data
2020
Establishing causal relations between random variables from observational data is perhaps the most important challenge in today’s science. In remote sensing and geosciences, this is of special relevance to better understand the earth’s system and the complex interactions between the governing processes. In this paper, we focus on an observational causal inference, and thus, we try to estimate the correct direction of causation using a finite set of empirical data. In addition, we focus on the more complex bivariate scenario that requires strong assumptions and no conditional independence tests can be used. In particular, we explore the framework of (nondeterministic) additive noise models, …
Synergistic integration of optical and microwave satellite data for crop yield estimation
2019
Developing accurate models of crop stress, phenology and productivity is of paramount importance, given the increasing need of food. Earth observation (EO) remote sensing data provides a unique source of information to monitor crops in a temporally resolved and spatially explicit way. In this study, we propose the combination of multisensor (optical and microwave) remote sensing data for crop yield estimation and forecasting using two novel approaches. We first propose the lag between Enhanced Vegetation Index (EVI) derived from MODIS and Vegetation Optical Depth (VOD) derived from SMAP as a new joint metric combining the information from the two satellite sensors in a unique feature or des…
Performance Analysis of Cooperative V2V and V2I Communications Under Correlated Fading
2019
Cooperative vehicular networks will play a vital role in the coming years to implement various intelligent transportation-related applications. Both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications will be needed to reliably disseminate information in a vehicular network. In this regard, a roadside unit (RSU) equipped with multiple antennas can improve the network capacity. While the traditional approaches assume antennas to experience independent fading, we consider a more practical uplink scenario where antennas at the RSU experience correlated fading. In particular, we evaluate the packet error probability for two renowned antenna correlation models, i.e., cons…
Event signal characterization for disturbance interpretation in power grid
2018
This paper presents the signal processing approach to detect and characterize the physical events that occur in power system using PMUs signals. A small window is applied so that the extracted spectral features belong to a stationary signal. This is based on applying empirical mode decomposition, followed by square root of spectral kurtosis (SRSK) for computation of statistical indices to indicate the event occurrence. Subsequently, features from these events are extracted using mel frequency cepstral coefficients on SRSK. © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/re…
Numerical investigation of the influence of EM-fields on fluid motion and resistivity distribution during floating-zone growth of large silicon singl…
2001
The floating-zone-process with needle-eye inductor is a complex process with many coupled parameters that have nonlinear influence on the process stability and resistivity distribution in the silicon single crystal. To fulfill the requirements of semiconductor industry for tighter specification of resistivity distribution, additional means like magnetic fields can be used to reach a more homogeneous resistivity distribution without disturbing process stability. The current paper analyses the influence of static and alternating fields on the fluid motion and macroscopic and microscopic resistivity profile by means of numerical calculations. It is found that with a lower frequency of the HF-i…
An enhanced random walk algorithm for delineation of head and neck cancers in PET studies
2017
An algorithm for delineating complex head and neck cancers in positron emission tomography (PET) images is presented in this article. An enhanced random walk (RW) algorithm with automatic seed detection is proposed and used to make the segmentation process feasible in the event of inhomogeneous lesions with bifurcations. In addition, an adaptive probability threshold and a k-means based clustering technique have been integrated in the proposed enhanced RW algorithm. The new threshold is capable of following the intensity changes between adjacent slices along the whole cancer volume, leading to an operator-independent algorithm. Validation experiments were first conducted on phantom studies:…
Methods of spatial cluster detection in rare childhood cancers: Benchmarking data and results from a simulation study on nephroblastoma
2021
Abstract The potential existence of spatial clusters in childhood cancer incidence is a debated topic. Identification of rare disease clusters in general may help to better understand disease etiology and develop preventive strategies against such entities. The incidence of newly diagnosed childhood malignancies under 15 years of age is 140/1,000,000. In this context, the subgroup of nephroblastoma represents an extremely rare entity with an annual incidence of 7/1,000,000. We evaluated widely used statistical approaches for spatial cluster detection in childhood cancer (Ref. [22] Schundeln et al., 2021, Cancer Epidemiology). For the simulation study, random high risk clusters of 1 to 50 ad…
A new expression of the slope length factor to apply USLE-MM at Sparacia experimental area (Southern Italy)
2013
Abstract Predicting soil loss due to water erosion by empirical models is useful to assess the severity of the phenomenon in an area of interest and to predict the effect of alternative soil erosion control practices. The USLE scheme cannot be used at the Sparacia experimental area (Sicily, South Italy) to predict event soil loss per unit plot area, Ae, because experimental data suggest that, generally, Ae does not increase with plot length, λ. The USLE-MM scheme uses the runoff coefficient, QR, as an additional independent variable in order to develop an empirical model allowing prediction of storm soil loss values that do not necessarily increase with λ. According to this model, Ae is exp…