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Full-Text Articles in Physical Sciences and Mathematics
A New Approach To Harmonic Allocation For Mv Installations, Victor Gosbell, Robert Barr
A New Approach To Harmonic Allocation For Mv Installations, Victor Gosbell, Robert Barr
Robert Barr
Distributors need to allocate a maximum allowed level of harmonic current to MV customers to keep voltage distortion acceptable. The paper describes a new approach, based on the concept of voltage droop, requiring much less calculation and data than required by the present approach based on an IEC technical report. The discrepancy between the new method and the present is studied by comparing some carefully selected scenarios. It is shown that the proposed method gives results within 20% of the standards-based approach which makes it a very attractive alternative for harmonic allocation.
Electrochemical Deposition Of Porous Vox And Mno2 Nanowires On Stainless Steel Mesh For Flexible Supercapacitors, Shulei Chou, Jiazhao Wang, Hua Liu, S Dou
Electrochemical Deposition Of Porous Vox And Mno2 Nanowires On Stainless Steel Mesh For Flexible Supercapacitors, Shulei Chou, Jiazhao Wang, Hua Liu, S Dou
Shulei Chou
Porous vanadium oxide (VOx) and MnO2 nanowires were synthesized by an electrochemical deposition method using stainless steel mesh as substrate. The as-prepared porous VOx and MnO2 nanowire films were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and Raman spectroscopy. The cyclic voltammetry (CV) results show that the MnO2 nanowire film shows specific capacitance of 195, 170, 158, and 91 F g-1 at scan rates of 5, 10, 20, and 50 mV s-1, respectively. The porous VOx film displays specific capacitance of 152, 124, 99, and 76 F g …
On The Combination Of Local Texture And Global Structure For Food Classification, Zhimin Zong, Duc Thanh Nguyen, Philip Ogunbona, Wanqing Li
On The Combination Of Local Texture And Global Structure For Food Classification, Zhimin Zong, Duc Thanh Nguyen, Philip Ogunbona, Wanqing Li
Professor Philip Ogunbona
This paper proposes a food image classification method using local textural patterns and their global structure to describe the food image. In this paper, a visual codebook of local textural patterns is created by employing Scale Invariant Feature Transformation (SIFT) interest point detector with the Local Binary Pattern (LBP) feature. In addition to describing the food image using local texture, the global structure of the food object is represented as the spatial distribution of the local textural structures and encoded using shape context. We evaluated the proposed method on the Pittsburgh Fast-Food Image (PFI) dataset. Experimental results showed that the …