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Parallelizability of an algorithm is nowadays a highly desirable property as computer hardware is becoming increasingly parallel. In this paper, a formulation of the particle filtering algorithm, suitable for parallel or distributed computing, is proposed. From the particle set, a series expansion is fitted to the posterior probability density function. The global information provided by the particles...
In swarm robotics, a multitude of very simple robots often move to achieve pre-defined geometric patterns while communicating with each other. Robots are able to estimate their position and relocate themselves by obtaining other robots' position information. However, as is the often the case in wireless communication, robots cannot receive other robots' position information reliably. Thus, they need...
Image registration is extensively used in many application domains such as medical, remote sensing, computer vision etc. The basic purpose of image registration is to obtain finest geometrical and radio-metrically aligned image from temporal or multi-modal image sensors. In this study, a novel salient feature-based image registration scheme has been designed and implemented by establishing a set of...
A new region-based local stereo matching algorithm with accurate disparity estimation is proposed. For the local stereo matching, finding an appropriate support window is crucial to the performance of disparity estimation. In order to generate an accurate support region, a modified cross-based local approach combined with mean-shift segmentation is performed. We then further improve the reliability...
For efficient wide-area exploration by an autonomous planetary rover, the generation of a global environmental map is very important. A global map is generated by aligning overlapping terrain features from digital elevation maps that are obtained during a rover traveling in a region. Each set of data contains information in different areas, and the overlapping part in each set of data may be missing...
This paper addresses the channel estimation in receivers of multicarrier communication signals, particularly in multiuser scenarios of the LTE uplink. B-splines are proposed for estimation of the time-frequency channel response. Cubic B-splines are considered as the appropriate basis functions allowing a trade-off between the estimation accuracy and complexity. We investigate the iterative channel...
Effort estimation is a project management activity that is mandatory for the execution of software projects. Despite its importance, there have been just a few studies published on such activities within the Agile Global Software Development (AGSD) context. Their aggregated results were recently published as part of a secondary study that reported the state of the art on effort estimation in AGSD...
Location estimation is essential to the success of location based services. Since GPS does not work well in indoor and the urban areas, several indoor localization systems have been proposed in the literature. Among these, the fingerprinting-based localization systems involving two phases: training phase and positioning phase, are used mostly. In the training phase, a radio map is constructed by collecting...
Heating, ventilation, and air conditioning (HVAC) control is used to effectively reduce energy consumption in a home energy management system (HEMS). For the HVAC control, it is necessary to evaluate the indoor comfort level because the HVAC operation is significantly related to indoor environmental conditions. Although there are some indices for indoor comfort, individuals have different comfort...
In this paper, three individual indices, as well as a new comprehensive index, are introduced to evaluate prediction intervals. Then, two practical methods, namely, Interval Extension Method and Optimal Scalar Method are proposed to build the prediction intervals based on an ensemble of Extreme Learning Machines. Case studies on hour-ahead load interval forecasting with respect to Chicago Metro Area...
With emerging synchronized phasor measurement technology, estimating dynamic state in real time (post fault) for the grid operation become feasible. However, PMU measurements undergo random errors and bad data unavoidably caused by the sensor errors, disturbances, etc. The traditional centralized state estimation methods for power system static state are not applicable for the electro-mechanical transient...
ELM works for the “generalized” singlehidden layer feedforward networks (SLFNs) but the hidden layer (or called feature mapping) in ELM needs not be tuned. Extreme Support Vector Machine (ESVM), combining Support Vector Machine (SVM) and Extreme Learning Machine (ELM) kernels, can lead to a better prediction capability. ESVM can usually have a relatively good predictive capability, and its training...
Very High Resolution (VHR) multitemporal images show a residual misalignment even after applying effective state of the art co-registration. This residual misalignment is caused by the dissimilarities of the acquisition circumstances such as off-nadir angle of the sensor, stability of the acquisition platform, structure of the considered scene, and so on. This paper aims at mitigating the residual...
Metabolic equivalent of task (MET) indicates the intensity of physical activities. This measurement is used in providing physical activity intervention in many chronic illnesses such as coronary heart disease, type-2 diabetes, and cancer. Due to the small size, portability, low power consumption, and low cost, wearable motion sensors are widely used to estimate MET values. However, one major obstacle...
In the context of radiolocation in Wireless Body Area Networks (WBANs), nodes positions can be estimated through time-based ranging algorithms. For instance, the distance separating a couple of nodes can be estimated accurately by measuring the Round Trip Time of Flight of an Impulse Radio Ultra Wideband (IR-UWB) link. This measure usually relies on two or three messages transactions. Such exchanges...
Biometric gait analysis using wearable sensors offers an objective and quantitative method for gait parameter extraction. However, current techniques are constrained to specific platform parameters, and hence significantly lack generality, scalability and sustainability. In this paper, we propose a platform-independent and self-adaptive approach for gait cycle detection and cadence estimation. Our...
The use of sweat pores in fingerprint recognition is becoming increasingly popular, mostly because of the wide availability of pores, which provides complementary information for matching distorted or incomplete images. In this work we present a fully automatic pore-based fingerprint recognition framework that combines both pores and ridges to measure the similarity of two images. To obtain the ridge...
Two dimensional target localization using AOA measurements is considered in this paper. By conducting repeated experiments, the complex AOA (CAOA) method found that for the two-sensor and single-target scenario, the accuracy of the intersection of two bearing lines can be divided into different layers. However, the experiments are very time consuming. Also, the division of the intersection region...
This paper proposes the innovative features of tempogram for the selection of predominant tempo in a two-stage tempo estimation system. At stage one, a tempo-pair estimator identifies the dominant tempo pair from a given audio music. At stage two, the statistical features called tempogram shape vector (tsv) discriminates the predominant tempo from the identified tempo pair. Our experiments demonstrate...
This paper presents a novel method to conduct camera pose estimation though combining Kinect and Perspective-n-points algorithms. Most existing camera pose estimation methods suffer from the errors caused by inevitable outliers between 2D–3D correspondences. To this end, we propose to use a random down sampling process to deal with outliers in this paper. The proposed method is divided into two main...
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