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This paper introduces a new approach for the optimal management of reactive power, with emphasis on offshore wind power plants. The approach follows a predictive optimization scheme (i.e. day-ahead, intraday application). Predictive optimization is based on the principle of minimizing the real power losses, as well the number of On-load Tap Changer (OLTC) operations for daily time horizon (discretized...
Special preprocessing techniques for denoising quasi-stationary signals (SN) acquired from the secondary winding of the excitation transformer in a power plant are addressed. Sequences of 30 periods were analyzed. SN were polluted by white Gaussian noise and “average” signals (AS) of one period length were deduced. Because vectors of samples were handled, corrective measures (CM) were applied firstly...
This paper focuses on the evaluation of postgraduates' innovation ability based on cloud model. Considering that the innovation capability is mostly qualitative index and has strong fuzziness, the cloud model method can realize the effective conversion between the qualitative index and the quantitative value. Compared with traditional methods, the evaluation method is more scientific and the result...
How sensory information from the external world is extracted, learnt, stored within, and retrieved from the brain ultimately relies on both the strengths and patterning of connections converging onto neuronal dendrites and the nonlinear nature of the membrane. The underlying processes that permit this ultimately relies upon the non trivial interplay between the nonlinear nature of the dendrite, synapse...
Network pruning is an effective way to accelerate Convolutional Neural Networks (CNNs). In recent years, structured pruning methods are proposed in favor of unstructured methods as they have shown greater speedup in practical use. Existing structured methods does pruning along two main dimensions: 3D-filter wise, i.e., remove a 3D-fllter as a whole, and filter-shape wise, i.e., remove a same position...
Automated object's activity analysis has been and still remains a challenging problem and motion trajectories provide rich spatiotemporal information for this purpose. This paper presents a novel descriptor to analyze object activity based on object trajectories. In the proposed descriptor extraction technique, object's change in direction is extracted in different level of resolution. One of the...
Patients with major depressive disorder (MDD) who do not achieve full symptomatic recovery after antidepressant treatment have a higher risk of relapse. Compared to pharmacotherapies, electroconvulsive therapy (ECT) more rapidly produces a greater extent of response in severely depressed patients. However, prediction of which candidates are most likely to improve after ECT remains challenging. Using...
Automated pose estimation is a fundamental task in computer vision. In this paper, we investigate the generic framework of Cascaded Pose Regression (CPR), which demonstrates practical effectiveness in pose estimation on deformable and articulated objects. In particular, we focus on the use of CPR for face alignment by exploring existing techniques and verifying their performances on different public...
We introduce a novel segmentation method for time-lapse image stacks of neurites based on the co-segmentation principle. Our method aggregates information from multiple stacks to improve the segmentation task, using a neurite model and a tree similarity term. The neurite model takes into account branching characteristics, such as local shape smoothness and continuity, while the tree similarity term...
In order to solve the problem of calculating speed and accuracy of the large-scale ultra-short term load forecasting in micro-grid engineering practice, the characteristics of various kinds of load types are analyzed. The optimal local shape similarity model is established. The similarity of the two local similarity curves is expressed by similarity coefficient. This paper introduces the human comfort...
The curved debris separated from rockets, the most objects frequently appeared in the threat complex, make the classification of ballistic targets very hard. However, rocket debris has not drawn enough research attention and current data generative model of convex objects is not applied to non-closed curved debris. This paper explores the method of modeling the infrared (IR) irradiance signatures...
Polyp identification in human Gastro Intestinal (GI) Tract employing endoscopy and colonoscopy through various computer vision and image processing techniques has achieved lot of success and maturity in its field. Over the last decade Wireless Capsule Endoscopy (WCE) has emerged as an innovative diagnostic system for identification of ailments such as polyps in GI tract. Polyp detection through WCE...
We present a variant of the regularized dual averaging (RDA) algorithm for stochastic sparse optimization. Our approach differs from the previous studies of RDA in two respects. First, a sparsity-promoting metric is employed, originated from the proportionate-type adaptive filtering algorithms. Second, the squared-distance function to a closed convex set is employed as a part of the objective functions...
Independent component analysis (ICA) is a powerful method for blind source separation based on the assumption that sources are statistically independent. Though ICA has proven useful and has been employed in many applications, complete statistical independence can be too restrictive an assumption in practice. Additionally, important prior information about the data, such as sparsity, is usually available...
We propose a method for disparity estimation in stereo video. We address the problems associated with spatially-temporally-correlated disparity variations (STCDV). STCDV problems are caused by complex motions, e.g., yaw-rotation, pan-tilt-zoom camera movements, etc. The key novelty of this study is to introduce a spatio-temporal disparity hyperplane (STDH) model. The proposed STDH model represents...
Makeup can be used to alter the facial appearance of a person. Previous studies have established the potential of using makeup to obfuscate the identity of an individual with respect to an automated face matcher. In this work, we analyze the potential of using makeup for spoofing an identity, where an individual attempts to impersonate another person's facial appearance. In this regard, we first assemble...
Modern reconfigurable computing chips, such as FPGAs, offer an unprecedented opportunity to achieving both multifunctionality and real-time responsiveness for memoryintensive embedded applications. However, how to cost-effectively synthesize application-specific hardware constructs that fully exploit memory-level parallelism remains to be a key challenge. To address this problem, we propose a new...
The density peak based clustering algorithm is a simple yet effective clustering approach. This algorithm firstly calculates the local density of each data and the distance to the nearest neighbor with higher density. Based on the assumption that cluster centers are density peaks and they are relatively far from each other, this algorithm isolates the candidates of cluster centers from the non-center...
This paper investigates the application of flexible and effective fast-convolution (FC) filtering scheme for multiplexing OFDM physical resource blocks (PRBs) in a spectrally well-localized manner. The scheme is able to suppress interference leakage between adjacent PRBs, thus supporting independent waveform parametrization for different PRBs, as well as asynchronous multiuser operation. These are...
Temporal contour shapes are closely linked to the narrative structure of multimedia content and provide important reference points in content-based multimedia timeline analysis. In this paper, multimedia timeline is extracted from content as time varying video and audio signal features. A temporal contour representation is implemented based on sequential pattern discovery algorithm for modeling the...
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