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BACKGROUND Nitrate, acting as both a nitrogen source and a signaling molecule, controls many aspects of plant development. However, gene networks involved in plant adaptation to fluctuating nitrate environments have not yet been identified. RESULTS Here we use time-series transcriptome data to decipher gene relationships and consequently to build core(More)
OBJECTIVE Research in seizure prediction from intracranial EEG has highlighted the usefulness of bivariate measures of brainwave synchronization. Spatio-temporal bivariate features are very high-dimensional and cannot be analyzed with conventional statistical methods. Hence, we propose state-of-the-art machine learning methods that handle high-dimensional(More)
Recent research suggests that electrophysiological changes develop minutes to hours before the actual clinical onset in focal epileptic seizures. Seizure prediction is a major field of neurological research, enabled by statistical analysis methods applied to features derived from intracranial Electroencephalographic (EEG) recordings of brain activity.(More)
Various methods have been developed for indoor localisation using WLAN signals. Algorithms that fingerprint the Received Signal Strength Indication (RSSI) of WiFi for different locations can achieve tracking accuracies of the order of a few meters. RSSI fingerprinting suffers though from two main limitations: first, as the signal environment changes, so(More)
—Various methods have been developed for indoor localization using WLAN signals. Algorithms that fingerprint the Received Signal Strength Indication (RSSI) of WiFi for different locations can achieve tracking accuracies of the order of a few meters. RSSI fingerprinting suffers though from two main limitations: first, as the signal environment changes, so(More)
—RF fingerprinting is an interesting solution for indoor localization and tracking because it uses existing devices and infrastructure and involves minimal intervention to ongoing activities. The method involves constructing a database of signal strengths at different locations in an indoor space. Real-time measurements are compared to the database to(More)
—Radio-Frequency fingerprinting is an interesting solution for indoor localization. It exploits existing telecom-munication infrastructure, such as WiFi routers, along with a database of signal strengths at different locations, but requires manually collecting signal measurements along with precise position information. To automatically build signal maps,(More)
This research focuses on the development of a machine learning technique based on Time-Delay Neural Networks (TDNN) and Independent Component Analysis (ICA), to analyze EEG signal dynamics related to the initiation and propagation of epileptic seizures. We aim at designing a generative model to simulate EEG time-series after alteration of specific localized(More)