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We demonstrate a microwave imaging radar experimental platform, using photonic generation of linear frequency modulated waveform centered at 10GHz with 4GHz bandwidth. Distance and velocity resolution of about 5cm and 2m/s are obtained experimentally.
Based on the reflection and refraction of traveling waves and vacuum circuit breaker(VCB) characteristics, transformers interruption by VCB may produce current chopping and re-ignition that will cause severe high-frequency transient overvoltages in collection grid of offshore wind farms(OWFs). In such applications, overvoltages protection should be used. In order to study such overvoltage in OWFs,...
Uncontrolled energization of unloaded transformers is usually associated with a large inrush current, several times larger than the rated transformer current. This transient can cause unfavourable consequences including reduction of transformer lifecycle, protective relay misoperations, and reduced power quality of the system. Controlled switching can efficiently eliminate these transients when energizing...
This paper proposes a SPAD array sensor based on breakdown pixel extraction architecture with background readout for scintillation detectors. The proposed architecture extracts the addresses of only the breakdown pixels during the exposure time of the next frame. Therefore, this sensor minimizes the dead time and improve the readout efficiency. A SPAD array sensor was fabricated in a 0.18 μm CMOS...
We present an end-to-end, multimodal, fully convolutional network for extracting semantic structures from document images. We consider document semantic structure extraction as a pixel-wise segmentation task, and propose a unified model that classifies pixels based not only on their visual appearance, as in the traditional page segmentation task, but also on the content of underlying text. Moreover,...
The issue of remaining useful life (RUL) prediction has already become a quite interesting topic in industrial product. The data driven RUL prediction has been applied to the current research by taking advantage of a long-short term memory (LSTM)-recurrent neural network (RNN) approach. This means that even in a specified long-short term memory bound and limited available data sets, the RUL predictions...
Scene text detection has attracted great attention these years. Text potentially exist in a wide variety of images or videos and play an important role in understanding the scene. In this paper, we present a novel text detection algorithm which is composed of two cascaded steps: (1) a multi-scale fully convolutional neural network (FCN) is proposed to extract text block regions, (2) a novel instance...
OpenFlow has been applied to a variety of demands of the transmission quality of the Internet business and it is still growing on its way. To test this protocol with its evolution consideration, we analyzed the working process of OpenFlow protocol and constructed the CPN model through phasing firstly and then role division for version 1.0. In addition, the selection of tokens and their given values...
Sparse coding (SC) is a unsupervised learning scheme that has received an increasing amount of interests in recent years. However, conventional SC vectorizes the input images, which destructs the intrinsic spatial structures of the images. In this paper, we propose a novel graph regularized tensor sparse coding (GTSC) for image representation. GTSC preserves the local proximity of elementary structures...
A Ku Band (15∼18 GHz) 4-Element (4 Transmitters/4 Receivers) fully differential phased array transceiver is designed and fabricated using a 180nm CMOS process. The proposed phased array integrated with T/R switches and SPI controller is based on an all-RF structure. TX and RX channels are placed side-by-side to improve integration density and isolation. Each channel consists of a 5-bit phase shifter...
Physical library collections are valuable and long standing resources for knowledge and learning. However, managing and finding books or other volumes on a large collection of bookshelves often leads to tedious manual work, especially for large collections where books or others might be missing or misplaced. Recently, deep neural-based models have been successful in detecting and recognizing text...
The broad implementation of cloud computing have led to a dramatically growing in exchanging and using data throughout multiple parties. The main problem restricting the implementation of cloud computing is that users lack controls in cloud systems, from which security and privacy concerns become a major issue for cloud users. Logically, an applicable Fully Homomorphic Encryption (FHE) scheme is an...
A feedforward linearization technique to cancel the third-order intermodulation (IM3) of the down-conversion mixers is proposed, in which a low-frequency second-order intermodulation tone (IM2) is created and multiplied by the mixer's output to generate the IM3 tones for the cancellation. The proposed linearization technique is applied to an active mixer operating at 2 GHz. Fabricated in a 0.13-µm...
Stereo matching is the key problem in many stereo vison based 3D applications. One of the factors make local stereo matching time-consuming is that every pixel has the same disparity range as the pre-set one, which should be larger than all possible disparities. An improper pre-set disparity range may lead to redundant computation for some pixels and inadequate computation for some others. In this...
We introduce a deep encoder-decoder architecture for image deformation prediction from multimodal images. Specifically, we design an image-patch-based deep network that jointly (i) learns an image similarity measure and (ii) the relationship between image patches and deformation parameters. While our method can be applied to general image registration formulations, we focus on the Large Deformation...
Registration involving one or more images containing pathologies is challenging, as standard image similarity measures and spatial transforms cannot account for common changes due to pathologies. Low-rank/Sparse (LRS) decomposition removes pathologies prior to registration; however, LRS is memory-demanding and slow, which limits its use on larger data sets. Additionally, LRS blurs normal tissue regions,...
This paper reports the design, fabrication, electrical and thermal characterization, as well as attachment and stability of a flexible photoelectric neural interface (PENI). Upon the wire-bonding technology, three micro LED (μLED) chips are well-connected to the polyimide substrate as an array, with their luminous surfaces over against the holes. Meanwhile, a Parylene-C-based array with four microelectrodes...
This paper reports a novel flexible neural probe fabricated by cylindrical substrates lithography for Brain-Computer-Interface (BCI) applications. The electrode sites were patterned on the cylindrical surface to acquire high space selectivity and the micro channel was integrated to deliver drags or optical stimulation. The electrode sites of the probe were further modified with graphene enhanced conductive...
This paper proposes a breakdown-pixel-extraction architecture for SPAD sensor. The proposed readout circuit detects the breakdown pixels and their addresses are readout. Therefore, under the faint light environment, this SPAD sensor significantly improves the data readout efficiency. A 15 × 15 SPAD sensor was fabricated in a 0.18 um CMOS process, and a high speed readout is verified by measurement.
Link prediction is an important problem in the traditional field of data mining. Thus in the past several years, abundant traditional algorithms from a global perspective have been proposed. But, they all fail to accurately and individually recommending friends in social networks. Hence, the personalized link prediction has been introduced in this paper, in which each individual will get equal number...
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