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Synthetic aperture radar (SAR) is a promising technology for mapping forest characteristics, and the anticipated open-access, L-band data from the NISAR mission holds potential for rapid and near-continuous monitoring. A dominant method for assessing forest characteristics using SAR backscatter is fitting and inversion of simple, semi-physical models. Models such as the Simple Water Cloud Model (SWCM) can be inverted mathematically; however, it is not necessarily true that the inverted model provides reliable predictions of forest characteristics, even when backscatter falls between the limits predicted by the original model. The challenge is inherently statistical, and not entirely dependent on model formulation. We illustrate the problem using forest aboveground biomass and L-band backscatter from a previous study in New Hampshire and Maine, USA. We suggest a greater focus on the role and purpose of regression models can help alleviate misconceptions and potential misapplications, leading to more informed and reliable prediction.

In light curves (LCs), the brightness of stars is associated with time, and so is its image. The traditional data processing methods cannot effectively handle real-time and large-volume data of various LCs. To address this issue, this work develops a deep neural network named Dropout-based Recurrent Neural Networks (DRNN). It extracts complicated features of all images captured by Mini Ground-based Wide-Angle Camera array (Mini-GWAC) for point source extraction and cross-certification through Long Short-Term Memory units. DRNN can also produce warnings for abnormal values of light change curves. Furthermore, this work optimizes the training model by combining a dropout method with an adaptive moment estimation algorithm to iteratively update the network weight of the RNN based on the LCs data. Extensive experiments with a Mini-GWAC dataset demonstrate that DRNN outperforms several typical methods in terms of prediction performance of star brightness in large-scale astronomical LCs.

InGaZnO is easy to absorb moisture, thus leading to the formation of metal-hydroxyl (M-OH) defects. The effects of M-OH on the performance of InGaZnO thin-film transistor (TFT) as well as the methods to improve the performance are investigated by characterizing TFTs with various post-metallization-annealing (PMA) treatments. The formation of M-OH has an adverse influence on the TFT electrical parameters including threshold voltage (V th ), mobility, off-current and sub-threshold swing. M-OH also leads to an abnormal V th shift under a positive-gate bias stress. Forming-gas annealing (N 2 /H 2 = 95%/5%) is effective to reduce the formation of M-OH due to the passivation effect of H 2 and thus can effectively suppress the adverse influence caused by the M-OH. Moreover, due to its extremely strong passivation ability, the formation of M-OH as well as the effects on the TFT performance can be significantly suppressed by fluorine treatment.

The effects of annealing temperatures on the electrochemical properties of silicon carbide anode films are investigated for lithium-ion battery applications. The SiC film shows improved electrochemical performance with increasing annealing temperature. The 900 ° C-annealed SiC film exhibits a reversible capacity of 580 mAh g $^{-1}$ over 100 cycles. Moreover, the 900 ° C-annealed film displays better rate performance with less severe degradation $(\sim 12.2$%) than the other two films.

Polyaniline (PANI) with a well-ordered 3D micro array is prepared by using MEMS processes and its electrochromic properties are investigated by comparison with a 2D planar one. The 3D sample has similar response speeds to the 2D one but displays (~1.2×) higher specific capacitance than the latter due to its more PANI content under the same footprint. The 3D micro array is also helpful to enhance the mechanical strength of the PANI film against repeated electrochemical cycling. Moreover, because the 3D array is well-ordered and also its feature size (~4 μm) is comparable to the infrared wavelength, strong interaction occurs between the infrared light and the structure; consequently, the 3D sample shows much larger emissivity modulation (~0.3) than the 2D one (~0.1).

Two categories of planar log-periodic monopole array antennas are presented, which exhibit wideband directional radiation with reverse-firing. Compared with the conventional log-periodic monopole antennas, the proposed antennas have lower profile and/or wider operation bandwidth. Through realizing the phase reversal on the feedline (the first category) or placing inverters between the monopole elements and the feedline (the second category), the energy is beamed end fire in the direction of the shorter elements where the antennas are fed. For verification, the planar log-periodic monopole array antennas with eighteen printed monopole elements are designed and simulated. In simulations, the operation (impedance) band of those antennas have reached from 1.7 to 5.8 GHz ( $\text{VSWR} ) at most frequencies in both categories, whereas the gain of the second category is up to 7.9 dBi.

Compressive sensing for sparse signal reconstruction has attracted great research interest in the last decade. In particular, compressive sensing has been successfully applied to direction of arrival (DOA) estimation with infinitely precise measurements. However, in certain applications, low-rate quantization is applied to reduce the hardware complexity and cost. Thus, in this paper, the problem of DOA estimation with one-bit quantization measurements is investigated. An improved fixedpoint continuation (FPC) reconstruction algorithm, namely FPC$-{\ell}_{1}$, is developed to deal with complex-valued signals such that it is applicable to DOA estimation with one-bit measurements. Numerical examples are carried out to evaluate the performance of the proposed FPC$-l_{1}$ based one-bit DOA estimator.

The ability of SiO2 prepared by plasma-enhanced chemical vapor deposition (PE-CVD) and inductively coupled plasma CVD (ICP-CVD) as the lithium diffusion barrier layer is investigated. The PE-CVD SiO2 shows stronger ability against the Li+ diffusion and electrochemical reaction with Li+ than the ICP-CVD one under the same thickness mainly due to its stronger bonding structure as demonstrated by X-ray photoelectron spectroscopy. It is further demonstrated that PE-CVD SiO2 with 1000 nm is effective to block the Li+ diffusion towards the substrate.

In this paper, a novel printed quasi log-periodic dipole antenna is proposed. It is based on a conventional log-periodic dipole antenna (LPDA) with modifications of the lengths of the dipole units. The proposed antenna has an exponential profile by cutting the opened ends of the radiating dipoles. Compared to the corresponding LPDA, it has improved gain of about 1.0–2.0 dB at high frequencies with the same antenna size and remains good matching in the operation band.

A novel linearly tapered slot antenna(LTSA) with improved performance is presented. By introducing a parasitic patch in the aperture of a traditional LTSA, the current distribution along the tapered slot edge can be smoothed, resulting in the reduction of the lower cut-off frequency and enhancement of the antenna gain. The comparison between the proposed antenna, a traditional LTSA and a Vivaldi antenna with the same size are given. The simulated results show that the proposed antenna has better VSWR compared with the traditional LTSA, and higher gain than the Vivaldi antenna.

A simple target scattering model is developed integrating the shape factor and geometric randomness that are less influenced by the SAR configuration, dielectric properties of crop, and the underlying soil conditions, to describe the shape and statistical distribution of the targets, respectively. 47 fully polarimetric RADARSAT-2 images in FQ1W, FQ6W, FQ10W, FQ15W and FQ19W modes with different incidence angles acquired over Temiskaming Shores, Ontario, Canada in 2015 are adopted for the validation. Comparisons of the geometric features with H, α, and RVI, demonstrate that geometric features of wheat, oat, alfalfa, and barely show less fluctuation and more consistent with their growing stages over time till their harvest, but crops with broad leaves such as corn and soybean still show some fluctuations with high geometric randomness. In addition, the plots of n and δ of different crops also shows their potential on the crop classification.

Two new equivalences in transmission line (TL) networks are proposed. The first one is found between a shunt fed stepped-impedance ring and a T-shaped TL network with a short-circuited series stub. Both the networks are composed of TL segments with the same electrical length. By using the Y and the ABCD matrices, an equivalent condition can be obtained, which is independent in frequency. Meeting the condition, the two networks with different topologies could generate exactly the same response. As the counterpart of the first one, the second equivalence is found between a series fed ring and a T-shaped network with an open-circuited shunt stub. The two equivalences are useful in circuit modelling and analysis; and provide extra design flexibility in circuit implementations.

In this paper, a miniaturized Vivaldi antenna is presented. A Vivaldi antenna with a novel feeding structure is selected as the basic design and resistive loading is used at the end of it to make a compact structure. The proposed antenna is fabricated with the size of 140mm (length) ∗139mm (width)∗1mm (thickness). The test results, which agree with the simulation results, indicate that the bandwidth is 0.44∼3GHz (S 11

The rapid development of modern wireless communication system has greatly promoted the development of the reconfigurable filters. This paper presents a hexagonal structure reconfigurable filter which operates at five different frequencies. The resonant characteristics of stepped impedance resonator (SIR) is utilized by equaling the transmission line of low impedance to multiple parallel lines of high impedance. And four PIN diodes are loaded to control the access state of equivalent lines of high impedance. The filter operates at 2GHz, 2.3GHz, 2.5GHz, 2.7GHz and 3GHz, with 3dB absolute bandwidth of constant 100MHz. Experimental results agree well with theoretical and simulated predications.

A novel high gain ultra-wideband (UWB) antenna is proposed. In its planar configuration, multiple radiation elements are employed in order to achieve both miniaturization and high gain. Meanwhile, a symmetric polygon is etched on the metal ground for improving the impedance matching in such a wide frequency band. The optimized geometric dimensions are obtained via full-wave simulation. A prototype of the proposed antenna is fabricated and measured results are compared with simulated results. The results show that the proposed antenna design achieves good performance as predicted.

Considering the rapid increasing of building integrated photovoltaic, a design method based on Ecotect Analysis is proposed in this article. Modeling analysis of the building's sunshine condition is processed to get the annual total solar radiation and sunshine hours per unit area of the building facade and roof. According to the analysis result, the setting position of the photovoltaic system can be determined and the annual generation capacity of the photovoltaic system can be estimated, and all of these can provide references for the design of building integrated photovoltaic. In addition, several high voltage grid connected schemes are given analyzing the Hangzhou south railway station case.

This paper examines the potential of Radarsat-2 C-band synthetic aperture radar (SAR) data for quantifying the spatial variability of soil moisture during the agriculture growth period. To remove the effect of crop within total backscattering, a method that adequately represents the scattering behavior of vegetation-covered area by defining the scattering of the vegetation and underlying soil was developed. The Dubois model was employed to determine the backscattering from the underlying soil. The modified Water Cloud Model was used to reduce the effect of backscattering caused by the vegetation. Soil moisture was derived by the inversion scheme which uses of the dual polarizations (HH and VV) available from the quad polarization Radarsat-2 data.

Monitoring the extent and pattern of snow cover in the high altitude, Tibetan Plateau (TP) region is significant to understand the local and regional impact of ongoing climate change and variability. The freely available Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover images, with 500 m spatial and daily temporal resolution, can provide a basis for regional snow cover mapping, monitoring and hydrological modeling. However, high cloud obscuration remains the main limitation. In this study, a new MODIS daily cloud-free snow cover product was generated by integrated and improved the current cloud reducing approaches. The result shows that the daily cloud-free snow cover product not only has the advantages of AMSR-E (unaffected by weather conditions) and MODIS (relatively higher resolution), but also the high snow and overall classification accuracies (∼85% and ∼98%, respectively), much higher than those of existing daily snow cover products in all sky conditions, and are very closer to or even slightly higher than those in clear sky condition of the daily MODIS products.

A novel ultra-wideband antenna is proposed. To achieve both the compact size and wide bandwidth, multiple radiation arms are employed in its planar configuration. Meanwhile, a symmetric polygon is etched on the metal ground in order to improve the impedance matching in such a wide frequency band. Based on the optimized geometric dimensions, the simulated results obtained via full-wave simulation show that the proposed antenna design achieves good performance as predicted.

Many research studies have investigated the retrieval of surface parameters for bare soils. This study attempts to take into account agricultural fields with crop residues and low vegetation cover. An adaptive two-component decomposition (ATCD) method is developed in this paper to invert surface parameters in these fields. The study area is located in Southwestern Ontario, Canada where two wheat fields and two corn-residue fields are selected as sample sites. Three fully polarimetric RADARSAT-2 data, which were acquired in 2013 and 2014 respectively, are employed for the validation. The ATCD has 100% inversion rate compared with the Bragg and X-Bragg models, while its root mean square errors (RMSE) of the soil moisture and roughness have the lowest value of 6.72% and 0.33, respectively. The derived soil moisture in wheat field also has the lowest RMSE value of 3.97% compared with the Y-CIEM.

This paper proposes an automated water body detection method to delineate detailed water bodies from high-resolution satellite images. It consists of three steps: a) coarse water mask detection from optical imagery using unsupervised classification; b) water mask refinement using backscatter value from synthetic aperture radar (SAR) images; and c) advanced morphological filtering to produce a final water mask. The experiments over Calgary Alberta demonstrate the importance of each step and show the advantages of this method relative to traditional methods, namely, its high degree of accuracy, ability to be full-automated, stability and potential for transferability. It is designed for water mask detection at sub-meter accuracy for industrial and governmental users undertaking hydraulic modeling in an urban environment.

In this paper, a novel panorama stitching method for Ultra HD images using edge matching is proposed. Our method, which replaces the popular Scale-invariant Feature Transform (SIFT) matching, provides effective solution for panorama stitching involving non-coplanar scenes without using the method of dynamic seam finding to avoid misalignments. We utilize the algorithm of As-Rigid-As-Possible (ARAP) to minimize misalignments by correcting the images during the stitching step. Furthermore, our method can be easily used to stitch panorama videos. In this paper, we present the analysis of the proposed method and provide evidence of its effectiveness in dealing with misalignments through implementation on images captured in a 2×2 panoramic array setting.

The High Efficiency Video Coding (HEVC) aims to provide significantly improved compression performance in comparison with the previous video standards. The deblocking filter performs detection of the artifacts at the coded block boundaries and attenuates them by applying a selected filter. In this paper, we proposed a novel and efficient deblocking filter algorithm baed on the improved boundary decision method. Prediction unit or transform unit boundaries can be selected to filter all boundaries of 8×8 block according to the Depth, TransformIdx and PartitionSize information from all 8×8 block. Experiment results show that the proposed algorithm can achieve significant coding efficiency improvements and better parallel processing capabilities with the same performance and bit-rate compared with the DF algorithm in HM.

Aiming at the team training under man-machine cooperation environment, an equipment oriented event-based hardware-in-the-loop simulation principle is expounded. Based on it, a simulation framework is designed. Then, a concept modeling approach of simulation system is proposed based on theory of concept lattices. Finally, a hardware-in-the-loop simulation test system is realized for a type of communication station. The successful application shows that the proposed approach following the principle is effective and feasible.

To narrow down the semantic gap and increase the retrieval efficiency in image retrieval, relevance feedback (RF) has long been an important approach, where the active support vector machine (SVM) based RFs are widely applied to content-based image retrieval (CBIR). However, the performance of these methods are often poor because the low speed of SVM algorithm in high dimension data. Meanwhile, the model of SVM is not discriminative, because the labels of the image features are insufficient exploited. To overcome the problems, we propose discriminative extreme learning machine (DELM) in this paper. Both within-class and between-class scatter matrices are involved in DELM to enhance the discrimination capacity of ELM for RF. The experimental results on two benchmark datasets (Corel-1K and Corel-10K) illustrate that our proposed method of this paper achieves a better performance than the state-of-the-art methods.

The video text is an important clue to infer semantic information of video. The accuracy of text extraction is crucial to the video text retrieval. Most of previous proposed methods can not completely extract the text characters when the text blocks own complicated background or when the stroke width of the text character is unpredictable. In this paper, we put forward a text extraction method, which can accurately extract video texts with complex background and various text character sizes. Experiments are conducted on TV news videos, which show that the performance of the proposed method is encouraging.

Intra prediction with fine directions is a critical feature in the new High Efficiency Video Coding (HEVC) standard because it provides significant performance gain. Different from the intra prediction in the H.264/AVC, this approach is more complicated in terms of computation and memory access, which makes the VLSI design very difficult. In this paper, with the analysis of the algorithm of the DC prediction mode and the planar prediction mode in HM, a reused adder VLSI architecture for DC mode and a high efficient VLSI architecture for planar mode are proposed for intra prediction. Implementation with TSMC 90 nm CMOS technology indicates that the proposed architecture can work at 357MHz operation frequency and 12970 logic gates acquired for DC prediction and can work at 308 MHz operation frequency and 57500 logic gates acquired for planar prediction. The processing latency of the proposed VLSI architecture can support the real-time processing of 4:2:0 format 4096×2048@30fps video sequences.

The complexity of High Efficiency Video Coding (HEVC) intra prediction design mainly comes from two aspects. First, as compared with the predecessor H.264/AVC, HEVC increases the number of prediction angles from 9 up to 33. Second, HEVC employs 5 kinds of n×n prediction unit size, including 4×4, 8×8, 16×16, 32×32 and 64×64. The computation intensity of intra encoding is increased by one order. In this paper, we provide the high efficient reconfigurable VLSI architecture for all intra directional prediction modes. The proposed design possesses the following merits: (1) Our prediction engine is equipped with sixteen uniform modules, and can be configured to produce 2 · m number row-wise n prediction samples in each cycle, where n = {4, 8, 16, 32, 64} and m = 64/n; (2) As our design always produces the row-wise samples, the hardware consuming transpose register array between the prediction residue module and the following DCT engine is eliminated. This feature further avoids the bubble operations in the horizontal predictions. With TSMC 90nm CMOS technology, the proposed architecture achieves 357MHz operating frequency at the cost of 817.3k gates, and the corresponding power dissipation is 114mW. Our implementation can fulfill the throughput requirement of HD2560 × 1600@46fps real-time encoding.

The charge-trapping characteristics of HfON/LaON composite film (denoted as HfLaON) were investigated based on an Al/Al 2 O 3 /HfLaON/SiO 2 /Si (MONOS) capacitor. The physical properties of the high-k film were analyzed by transmission electron microscopy and electron diffraction spectroscopy. Compared with another MONOS capacitor with nitrided La 2 O 3 as charge-trapping layer, the one with HfLaON showed better memory characteristics in terms of larger memory window, higher program speed (6.3 V at +14 V for 100 µs), and smaller charge loss (8.2% after 104 sec), due to the HfLaON composite film exhibiting an amorphous structure and the suppressed formation of an interlayer at the HfLaON/SiO 2 interface.

Primary-backup replication based on shared storage is a classical approach to ensuring high availability and data durability of stock trading systems, but it is difficult to further reduce the system latency due to persistence bottleneck. To solve this problem, a memory data replication approach based on Paxos algorithm is proposed, which accomplishes primary-backup replication through messaging, ensures the strong consistency of data replicas and tolerates possible benign failures. Experiment results have shown that this approach, compared with the shared storage approach, manages to greatly reduce the order processing latency of trading systems and achieve hot failover correctly in the case of server failure.

The popularity of Web 2.0 and social networking has greatly promoted user interactions in Internet services and changed the service delivery model. As typical Internet service providers, traditional digital repositories are facing two increasing demands: introducing user participation and providing personalized services. For the former, annotating digital resources and sharing the annotations with other users has been a natural service paradigm in the social networking context. For the latter, user-generated annotations in return can help digital repositories to supply personalized services such as recommendation. This paper proposes a Generic Annotation and Recommendation Service System (GARSS), which provides a SaaS solution to enhancing digital repositories with annotation and recommendation services. We presented the design and implementation of GARSS, and an example is shown to demonstrate the usage of GARSS services.

In this paper we present a novel approach to detecting scene text based on the edge and color features. Firstly, because the character edge feature is not sensitive to the luminance changes, we extract the edge features to locate the candidate text region coarsely. Secondly, according to the text row character will keep similar color, we use the K-means clustering to extract color feature and locate the candidate text regions accurately. Finally, we use a trained SVM classifier to distinguish the text region from non-text region in these candidate regions. Experimental results show that our algorithm performs well for detecting scene text with various color, font-size and text alignment.

Video text recognition is crucial to the research in all video indexing and summarization and has been used in video semantics analysis. Video text detection and localization is important for video text recognition. In this paper we present a new approach to implement video text detection and localization. In the text detection, we perform motion detection in 30 frames to get the motion mask. Then we get the synthesized frame based multi-frame integration. Finally, we retrieve an edge map of the synthesized frame using wavelet, and we detect text rows based on statistic coarseness of the edge map. In text localization, we locate the accurate boundary of text row based on edge map. Then we use the multi-frame verification (MFV) to remove the candidate text regions with motion occurrence on 30 consecutive frames. Experimental results show that our method is able to obtain a robust performance in the variation of language, font, size, color.

In this work, the effects of fluorine incorporation by using plasma on the electrical properties of Si MOS capacitor with La 2 O 3 gate dielectric are investigated. From the capacitance-voltage (C-V) curve and gate leakage current, it is demonstrated that the F-plasma treatment can effectively suppress the growth of interfacial layer, and thus improve the electrical properties of the device in terms of accumulation capacitance, interface-state density and breakdown voltage.

Video text brings important semantic clues about video content. Text extraction is a crucial stage of analyzing the video text. Most of papers perform video text extraction using stroke, intensity features, which are sensitive to the video background. Text character extraction is difficult due to the complex background of video frames. The structure of text characters exists in its phase information, which is insensitive to the background. The phase map is first generated to retrieve the phase angle image using Log-Gabor filter. Then, we propose a novel text extraction algorithm based on phase map. First, for the text row in single frame, we retrieve the phase map. Second, we perform k-means clustering in the phase map and select one clustering result as the text character image. Third, in 30 consecutive frames which contain same text character, we select the four text character images and combine them into one binary character image. Finally we use the dam point labeling and inward filling [1] to remove some noise and get the binary character image. Experimental results show that this approach is robust and can be effectively applied to text extraction in video.