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Feature learning has become popular in robotics due to recent advances in machine learning. In this paper, we propose a novel method to utilize the high-dimensional features from these techniques as observations in Bayesian estimation problems in a real-time manner. We develop an approach that: 1) pre-processes the observations and maps them into a new space with both reduced dimensions and a linear...
Traffic engineering (TE) plays an essential role in deciding routes that effectively use network resources. The TE controller should handle the uncertainty due to the lags and lacks of collected network information. Many previous work partially tackled this uncertainty problem in various aspects e.g. data collection, estimation, prediction, routing with uncertain traffic. However there are few studies...
Mobile symptom reporting apps can conveniently gather health-related information at low cost from day to day, fundamentally altering the relationship between patients, health data, and care providers. However, current mobile systems face a difficult trade-off between the quality of the information they collect and the burden placed on patients. In this paper, we propose an algorithm for adaptive system...
In order to reduce the curtailment of renewable generation in periods of low load, operators can limit the import net transfer capacity (NTC) of interconnections. This paper presents a probabilistic approach to support the operator in setting the maximum import NTC value in a way that the risk of curtailment remains below a pre-specified threshold. Main inputs are the probabilistic forecasts of wind...
Regrasping is the process of adjusting the position and orientation of an object in one's hand. The study of robotic regrasping has generally been limited to use of theoretical analytical models and cases with little uncertainty. Analytical models and simulations have so far proven unable to capture the complexity of the real world. Empirical statistical models are more promising, but collecting good...
Wind energy is supplying an increasing proportion of demand in the electrical grid. An accompanied problem is that the operational reliability of the power system is affected by the inherent uncertainty and stochastic variation of wind generation which also leads to the wind power forecasts of low accuracy. Therefore, the point prediction of wind power produced by a traditional deterministic forecasting...
The issue of applying high performance computing (HPC) techniques to computation-intensive probabilistic optimal power flow has not been well discussed in literature. In this paper, the probabilistic convex AC OPF based on second order cone programming (P-SOCPF) is formulated. The application of P-SOCPF is demonstrated by accounting uncertainties of loads. To estimate the distributions of nodal prices...
Multirotor helicopters are expected to be utilized various tasks including rescue missions and surveillance. For those missions, sensors are equipped with helicopters in order to recognize the environment, and auditory information is one of such information that can be utilized to find the target sound source even if it is occluded by objects. One of the difficulty comes from the fact that the noise...
In foot-mounted positioning systems, it is hard to align multi-agent trajectories. In addition, the positioning accuracy is hard to maintain due to inertial drifts. An approach for trajectory initialization and calibration using iBeacons is proposed in this paper. This approach is under the framework of a particle filter. In the observation model of the particle filter, a nonparametric Gaussian Process...
Regional quantification is often considered the end-point of many studies in Positron Emission Tomography (PET). However, in neurological small animal imaging, features can be sufficiently small that device resolution and voxel granularity inhibit the definition of segmentation boundaries that closely conform to organs or regions of interest. Even if well defined, estimation of uncertainty over small...
in this research, the estimation method using IT2FLS (Interval Type 2 Fuzzy Logic System) and ANFIS (Adaptive Neuro-Fuzzy Inference System) as a base to build the membership functions and the rule base is constructed. The differences area of uncertainty is used to determine a model of type 2 fuzzy systems based on the smallest RMSE value. This study uses two methods of type-reducer, namely Enhanced...
Remaining Useful Life (RUL) prediction plays a critical part in many battery-powered applications. Statistical filter, i.e., particle filter (PF) is widely used to predict RUL with various models as well as its uncertainty representation. However, PF commonly used suffers from the lack of poor adaption of long-term prediction and iterative prediction. This disadvantage may further reduce the RUL estimation...
This paper deals with assessment of desired signal extraction accuracy using the estimation reproduction method in the conditions of a priori indeterminacy by residuals. Another words we compare estimations of differential probability density, correlation functions and statistical characteristics (mathematical expectation and variance) of the additive noise component and the residual between measured...
The estimation of environmental contours of extreme sea states characterized by significant wave height and energy period for the purposes of reliability-based offshore design is a problem that has been tackled in many different ways. Many of the methods used to generate such contours rely on parametric approaches that require an a priori assumption of the relationship between the variables of interest...
Underwater acoustic localization is important for supporting underwater sensor networks. However, the hostile underwater environment makes it a very challenging mission. In this paper, we take uncertainties in sound propagation speed and time synchronization into account and propose a localization method. All anchors with known positions are synchronized, while all agents that need to perform localization...
This article introduces an innovativeness estimation approach especially for conceptual product design. In particular, the definition of innovativeness of conceptual product design (ICPD) is carefully discussed, and a multi-perspective and multi-dimension construct is established to conceptualize ICPD definition. Moreover, an improved innovativeness estimation approach with higher tolerance for fuzziness...
We have previously showed that it is possible to achieve parameter identification of discrete-time structured uncertainties without requiring persistency of excitation when using Concurrent Learning. Instead, granted a less restrictive condition compared to that of persistency of excitation is verified, exponential convergence of parameter estimates to their true values ensues. The present study applies...
In this paper, we propose an optimization scheme for avoiding void zone and minimization of uncertainty in glider's position estimation. Gliders stay at sojourn positions for predefined time. At these stops, self-confidence (s-confidence) and neighbor-confidence (n-confidence) regions are estimated. On the basis of present state of glider, it estimates s-confidence region and share control information...
Distribution System State Estimation (DSSE) is nowadays essential to enable the smart management of medium and low voltage grids. Due to the lack of a suitable measurement infrastructure, DSSE usually relies on the use of power injection pseudo-measurements derived from the knowledge of the historical and statistical behaviour of loads and generators. The uncertainty of these pseudo-measurements could...
In the present scenario of restructured power system, there is necessity for accurate quantification of Available transfer capability (ATC). ATC can be determined appropriately by exact calculation of marginal components of Total transfer capability (TTC). One of the margins we are concerned with is Transmission reliability margin (TRM). Accurate estimation of TRM ensures reliable power transactions...
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