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Salient object detection using RGB-D data is an emerging field in computer vision. Salient regions are often characterized by an unusual surface orientation profile with respect to the surroundings. To capture such profile, we introduce the histogram of surface orientation (HOSO) feature to measure surface orientation distribution contrast for RGB-D saliency. We propose a new unified model that integrates...
Non-invasive blood glucose measurement is a crucial challenge in both academic and industry communities. Currently, most of non-invasive solutions are developed based on optical signals. However, their accuracy is still far from clinical requirements if these measured optical signals directly used to estimate corresponding glucose levels. To solve this challenge, a novel Back-propagation Monte Carlo...
Residential Demand Response has emerged as an instrument of the modern smart grid to alleviate supply and demand imbalances of electricity. Utilizing their flexibility of electricity demand, residential households are offered monetary incentives to temporarily reduce energy consumption during times when the grid is strained due to a supply shortage. In this paper, we estimate the magnitude of reductions...
Sparse Discriminant Analysis (SDA) has been widely used to improve the performance of classical Fisher's Linear Discriminant Analysis in supervised metric learning, feature selection and classification. With the increasing needs of distributed data collection, storage and processing, enabling the Sparse Discriminant Learning to embrace the Multi-Party distributed computing environments becomes an...
It is difficult for managers to do real-time traffic estimation under urban road network because of the incompletion of information collection and the complexity of road network. This paper will improve the precision of data expansion algorithm presented by Lederman R and Wynter L. (2011) using Kalman Filter during real-time estimation. Computation is composed of a heavyweight offline calibration...
Model-based software estimation uses algorithms and past project data to make predictions for new projects. This paper presents a comparative assessment of four modeling approaches, including the original COCOMO, COCOMO calibration, k-Nearest Neighbors, and a combination of COCOMO calibration and k-Nearest Neighbors. Our results indicate that using kNN to select the nearest projects and calibrating...
This work investigates the anonymous tag cardinality estimation problem in radio frequency identification systems with frame slotted aloha-based protocol. Each tag, instead of sending its identity upon receiving the reader's request, randomly responds by only one bit in one of the time slots of the frame due to privacy and security. As a result, each slot with no response is observed as in an empty...
This paper formulates and studies the problem of distributed filtering based on randomized gossip strategy in order to estimate the state of a dynamic system via all sensors in a network. First we introduce the randomized gossip algorithm by which the fastest averaging strategy can be obtained for a network with an arbitrary topology. Then we combine the randomized gossip algorithm with the information...
The human visual system employs an information selection mechanism, visual attention, so that higher-level cognitive processes can be restricted to a potentially important subset of the incoming information. This mechanism is amenable to efficient computational implementation and, consequently, it has been incorporated into many technological applications. Among these applications is autonomous mobile...
In 3D object recognition, local feature-based recognition is known to be robust against occlusion and clutter. Local feature estimation requires feature correspondences, including feature extraction and matching. Feature extraction is normally a two-stage process that estimates keypoints and keypoint descriptors, and existing studies show repeatability to be a good indicator of keypoint feature detector...
Power battery is the heart of electric vehicles, and the accurate state of charge (SOC) estimation is crucial for the management of the power battery. This paper proposes an adaptive strong tracking unscented Kalman filter (ASTUKF) algorithm to estimate the SOC of lithium-ion battery. This method doesn't need to compute the Jacobian matrix compared with the traditional strong tracking filter. This...
In order to maximize capacity utilization and guarantee safe operation of Li-ion battery pack, state-of-charge (SOC) inconsistency estimation is essential. And estimating cell electrochemical internal variables is also the requirement of next generation battery management system (BMS). However, it is challenging for the BMS in electric vehicles due to dynamic current conditions and limited computational...
Techniques for dense semantic correspondence have provided limited ability to deal with the geometric variations that commonly exist between semantically similar images. While variations due to scale and rotation have been examined, there is a lack of practical solutions for more complex deformations such as affine transformations because of the tremendous size of the associated solution space. To...
In order to improve the estimation accuracy of radio propagation simulation using a 3D model reconstructed by depth sensors, recovering missing regions of the 3D model is important. In this paper, we report an evaluation result of indoor radio estimation accuracy by using such a completed 3D model. We first describe the evaluation scene and the measurement method of radio powers we used for experiments...
Model-based condition monitoring for lithium-ion (Li-ion) batteries involves estimating physical model parameters and operational states such state of charge (SOC) and state of health (SOH), and is crucial for building high-performance and safety-critical battery systems. This paper proposes a real-time model-based condition monitoring algorithm based on a second-order RC electrical circuit battery...
This paper provides detailed analytical modeling and finite elements method (FEM) analysis of the medium frequency transformer (MFT) leakage inductance, as one of the key design factors governing the operation of galvanically isolated power electronics converters. Precise leakage inductance modeling in design stage is especially important for converter topologies based on resonant conversion where...
Lithium Iron Phosphate (LiFePO4) batteries have obtained extensive interests for the high energy density, little contamination, and ready availability. To enhance the compatibility of the batteries in electrical systems, the accurate estimation of the state of charge (SOC) is remarkably significant. Conventionally, Kalman filter algorithm and its derivations can be utilized for SOC estimation. To...
Aiming at the integrated navigation system with model errors, the model errors is assumed as a process noise for Gaussian white noise to process in Kalman filtering, thus causing larger state estimation error of nonlinear filtering system and even divergent. This paper presents a nonlinear model predictive particle filtering method considers the model error of real-time estimation, and then corrects...
The estimation of state-of-charge (SOC) is the fundamental technology to improve battery working status and life. But severe external environment, dynamic nonlinearity of battery model, and measurement errors make SOC estimation challengable. In this paper, a multi-strategy probabilities based fusion method is proposed. It can combine the dynamic tracking capability of Proportional-Integral Observer...
Omnidirectional images describe the color information at a given position from all directions. Affordable 360° cameras have recently been developed leading to an explosion of the 360° data shared on social networks. However, an omnidirectional image does not contain interesting content everywhere. Some part of the images are indeed more likely to be looked at by some users than others. Knowing these...
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