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Monitoring flow volumes is a fundamental capability in network measurement. Sampling is often used to cope with the line speed and the applied methods typically rely on uniform packet sampling. However, it is inaccurate when there is a large variance in packet sizes. In this work we introduce Byte Uniform Sampling (BUS), a sampling method for estimating flow volumes. We show that BUS can be combined...
Vital sign (e.g., breathing rate) monitoring has become increasingly more important because it can offer useful clues to medical conditions such as sleep disorders or anomalies. There is a compelling need for technologies that enable contact-free, easy deployment, and long-term vital sign monitoring for healthcare. In this paper, we present a SonarBeat system to leverage a phase based active sonar...
Space-borne interferometric SAR has advanced significantly in the last decades, with many successful Earth monitoring applications. The key point of this success lies in the fact that interferometric SAR supplies unprecedented phase and amplitude information characterizing target's physical parameters. This paper presents the role of interferometric SAR, specifically considering the bistatic mission...
Recently many studies for application of multi-temporal interferometric SAR technique in monitoring ground motion have been reported. When we focus on number of scenes in high resolution mode of ALOS/PALSAR and ALOS-2/PALSAR-2, available number of scenes for interferometry are limited because of their global observation scenario. ALOS/PALSAR and ALOS-2/PALSAR-2 observation has been conducted with...
Due to the limited spatial resolution of past and existing satellite altimeters, only about 15% of global reservoirs (by storage capacity) can be monitored from space. To estimate the storage variations of more reservoirs via satellite observations, a 3-step algorithm using Moderate Resolution Imaging Spectroradiometer (MODIS) images in combination with the Digital Elevation Model (DEM) from the Shuttle...
We propose to use the temporal coherence of a time series to extract using Vertex Component Analysis (VCA) the suitable set of endmembers for each scene. The reconstruction error computed on the two previous scenes for each date is used to constrain the selection of the set of endmembers produced by VCA. Snow cover estimation is considered as application. We tested different approaches for abundance...
We present a simple and low-cost method for estimating the symbol error rate (SER) and bit error rate (BER) for 4-ary pulse amplitude modulation (PAM-4) signals from the reconstructed eye diagrams obtained by using asynchronous sampling technique. The reconstructed PAM-4 eye diagram is divided into three separate sub-eyes. The optimal sampling position of the signal phase is obtained by overlapping...
Air pollution poses disproportionate health hazard in developing countries, due to juxtaposition of industrial units and residences. While excessive emission is routinely detected, enforcement of emission norms remains rare due to present technological limitations in pinpointing sources. To fill this gap, we propose a method of source localization and emission rate estimation via AERMOD-based simulation...
The traffic monitoring system is an imperative tool for traffic analysis and transportation planning. In this paper, we present WiTraffic: the first WiFi-based traffic monitoring system. Compared with existing solutions, it is non-intrusive, cost- effective, and easy-to-deploy. Unique WiFi Channel State Information (CSI) patterns of passing vehicles are captured and analyzed to effectively perform...
Photoplethysmography(PPG) heart rate(HR) measurement technologies have the drawback of robustness. The traditional threshold method is not able to compute HR from the disorderly and unsystematic PPG signal (especially the PPG signal come from the people who has hypertension). To enhance HR estimation robustness, we present a strong robustness fusion method (SRFM) which fuses discrete fourier transform...
In this paper, the application of independent component analysis (ICA) to statistical process monitoring is studied. This paper mainly focuses on studying on the fault detection and isolation principle based on the data model of ICA. Contributions of this paper are: (1) for the purpose of fault detection, two monitoring statistics are designated by detailed analysis on the data model of ICA; (2) a...
Crowd behaviour analysis is a challenging task in computer vision, mainly due to the high complexity of the interactions between groups and individuals. This task is particularly crucial given the magnitude of manual monitoring required for effective crowd management. Within this context, a key challenge is to conceive a highly generic, fine and context-independent characterisation of crowd behaviours...
Monitoring motor function of patients with Parkinson's disease (PD) over long periods of time is essential in order to improve symptom management and avoid complications. Wearable technologies can be useful in this context as long as they do not unnecessarily increase patient and caregiver burden. The goal of the current study was to identify whether using more wearable sensors improved the estimation...
In this paper, we present the design of a wearable photoplethysmography (PPG) system, R-band for acquiring the PPG signals. PPG signals are influenced by the respiration or breathing process and hence can be used for estimation of respiration rate. R-Band detects the PPG signal that is routed to a Bluetooth low energy device such as a nearbyplaced smartphone via microprocessor. Further, we developed...
Estimating the Quality of Transmission (QoT) of lightpaths is crucial for reducing provisioned margins, making optimized dynamic decisions, and localizing failures. We leverage a QoT estimation tool that uses feedback from the network in order to provide accurate QoT estimations. We propose a scheme to establish active monitoring lightpaths (i.e., probe lightpaths used only for monitoring purposes)...
We present a method for developing executable algorithms for quantitative cyber-risk assessment. Exploiting techniques from security risk modeling and actuarial approaches, the method pragmatically combines use of available empirical data and expert judgments. The input to the algorithms are indicators providing information about the target of analysis, such as suspicious events observed in the network...
Some remote sensing sensors, acquire multispectral images of different spatial resolutions in variable spectral ranges (e.g. Sentinel-2, MODIS). The aim of this research is to infer all the spectral bands, of multiresolution sensors, in the highest available resolution of the sensor. We formulate this problem as a minimisation of a convex objective function with an adaptive (edge-reserving) regulariser...
We developed a low cost floor-based personnel detection system, we call a smart carpet, which consists of a sensor pad placed under a carpet, the electronics reads walking activity to provide an automated health monitoring and alert system. We extended the functionalities of the smart carpet to improve its ability to detect falls, alert health care personnel, estimate gait parameters, and count number...
We study optimal input design and bias-compensating parameter estimation methods for continuous-time models applied on a mechanical laboratory experiment. Within this task we compare two online estimation methods that are based on Poisson moment functions with focus on quantized system outputs due to an angular encoder: The standard recursive least-squares (RLS) approach and a bias-compensating recursive...
Patients affected by Amyotrophic Lateral Sclerosis (ALS) show specific dysarthric clues in speech. These marks could be used to detect early symptoms and monitor the evolution of the disease in time. Classically articulation marks have been mainly based on static premises. Articulation Kinematics from acoustic correlates may help in producing measurements based on the dynamic behavior of speech. Specifically,...
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