Showing papers by "Nanjing University of Information Science and Technology published in 2015"
TL;DR: An extensive evaluation of the state-of-the-art online object-tracking algorithms with various evaluation criteria is carried out to identify effective approaches for robust tracking and provide potential future research directions in this field.
Abstract: Object tracking has been one of the most important and active research areas in the field of computer vision. A large number of tracking algorithms have been proposed in recent years with demonstrated success. However, the set of sequences used for evaluation is often not sufficient or is sometimes biased for certain types of algorithms. Many datasets do not have common ground-truth object positions or extents, and this makes comparisons among the reported quantitative results difficult. In addition, the initial conditions or parameters of the evaluated tracking algorithms are not the same, and thus, the quantitative results reported in literature are incomparable or sometimes contradictory. To address these issues, we carry out an extensive evaluation of the state-of-the-art online object-tracking algorithms with various evaluation criteria to understand how these methods perform within the same framework. In this work, we first construct a large dataset with ground-truth object positions and extents for tracking and introduce the sequence attributes for the performance analysis. Second, we integrate most of the publicly available trackers into one code library with uniform input and output formats to facilitate large-scale performance evaluation. Third, we extensively evaluate the performance of 31 algorithms on 100 sequences with different initialization settings. By analyzing the quantitative results, we identify effective approaches for robust tracking and provide potential future research directions in this field.
2,974 citations
TL;DR: Using MODIS data from 2003 to 2012, it is shown that the UHI effect decayed exponentially toward rural areas for majority of the 32 Chinese cities, and an obvious urban/rural temperature “cliff” is found.
Abstract: Urban heat island (UHI) is one major anthropogenic modification to the Earth system that transcends its physical boundary. Using MODIS data from 2003 to 2012, we showed that the UHI effect decayed exponentially toward rural areas for majority of the 32 Chinese cities. We found an obvious urban/rural temperature “cliff”, and estimated that the footprint of UHI effect (FP, including urban area) was 2.3 and 3.9 times of urban size for the day and night, respectively, with large spatiotemporal heterogeneities. We further revealed that ignoring the FP may underestimate the UHI intensity in most cases and even alter the direction of UHI estimates for few cities. Our results provide new insights to the characteristics of UHI effect and emphasize the necessity of considering city- and time-specific FP when assessing the urbanization effects on local climate.
1,523 citations
TL;DR: The main difference to the traditional methods is that the proposed scheme first segments the test image into semantically independent patches prior to keypoint extraction, and the copy-move regions can be detected by matching between these patches.
Abstract: In this paper, we propose a scheme to detect the copy-move forgery in an image, mainly by extracting the keypoints for comparison. The main difference to the traditional methods is that the proposed scheme first segments the test image into semantically independent patches prior to keypoint extraction. As a result, the copy-move regions can be detected by matching between these patches. The matching process consists of two stages. In the first stage, we find the suspicious pairs of patches that may contain copy-move forgery regions, and we roughly estimate an affine transform matrix. In the second stage, an Expectation-Maximization-based algorithm is designed to refine the estimated matrix and to confirm the existence of copy-move forgery. Experimental results prove the good performance of the proposed scheme via comparing it with the state-of-the-art schemes on the public databases.
780 citations
TL;DR: It is found only 25 out of 190 cities could meet the National Ambient Air Quality Standards of China, and the population-weighted mean of PM2.5 in Chinese cities are 61 μg/m3, ~3 times as high as global population- Weighted mean, highlighting a high health risk.
Abstract: This study presents one of the first long term datasets including a statistical summary of PM2.5 concentrations obtained from one-year monitoring in 190 cities in China. We found only 25 out of 190 cities could meet the National Ambient Air Quality Standards of China, and the population-weighted mean of PM2.5 in Chinese cities are 61 μg/m3, ~3 times as high as global population-weighted mean, highlighting a high health risk. PM2.5 concentrations are generally higher in north than in south regions due to relative large PM emissions and unfavorable meteorological conditions for pollution dispersion. A remarkable seasonal variability of PM2.5 is observed with the highest during the winter and the lowest during the summer. Due to the enhanced contributions from dust particles and open biomass burning, high PM2.5 abundances are also found in the spring (in Northwest and West Central China) and autumn (in East China), respectively. In addition, we found the lowest and highest PM2.5 often occurs in the afternoon and evening hours, respectively, associated with daily variation of the boundary layer depth and anthropogenic emissions. The diurnal distribution of the PM2.5-to-CO ratio consistently displays a pronounced peak during the afternoon periods, reflecting a significant contribution of secondary PM formation.
750 citations
TL;DR: This paper surveys state-of-the-art transfer learning algorithms in visual categorization applications, such as object recognition, image classification, and human action recognition, to find out if they can be efficiently solved.
Abstract: Regular machine learning and data mining techniques study the training data for future inferences under a major assumption that the future data are within the same feature space or have the same distribution as the training data. However, due to the limited availability of human labeled training data, training data that stay in the same feature space or have the same distribution as the future data cannot be guaranteed to be sufficient enough to avoid the over-fitting problem. In real-world applications, apart from data in the target domain, related data in a different domain can also be included to expand the availability of our prior knowledge about the target future data. Transfer learning addresses such cross-domain learning problems by extracting useful information from data in a related domain and transferring them for being used in target tasks. In recent years, with transfer learning being applied to visual categorization, some typical problems, e.g., view divergence in action recognition tasks and concept drifting in image classification tasks, can be efficiently solved. In this paper, we survey state-of-the-art transfer learning algorithms in visual categorization applications, such as object recognition, image classification, and human action recognition.
698 citations
TL;DR: Numerical experiments on the several benchmark and real-world data sets show that the incremental algorithm can converge to the optimal solution in a finite number of steps, and is faster than the existing batch and incremental SVOR algorithms.
Abstract: Support vector ordinal regression (SVOR) is a popular method to tackle ordinal regression problems. However, until now there were no effective algorithms proposed to address incremental SVOR learning due to the complicated formulations of SVOR. Recently, an interesting accurate on-line algorithm was proposed for training $
u $ -support vector classification ( $
u $ -SVC), which can handle a quadratic formulation with a pair of equality constraints. In this paper, we first present a modified SVOR formulation based on a sum-of-margins strategy. The formulation has multiple constraints, and each constraint includes a mixture of an equality and an inequality. Then, we extend the accurate on-line $
u $ -SVC algorithm to the modified formulation, and propose an effective incremental SVOR algorithm. The algorithm can handle a quadratic formulation with multiple constraints, where each constraint is constituted of an equality and an inequality. More importantly, it tackles the conflicts between the equality and inequality constraints. We also provide the finite convergence analysis for the algorithm. Numerical experiments on the several benchmark and real-world data sets show that the incremental algorithm can converge to the optimal solution in a finite number of steps, and is faster than the existing batch and incremental SVOR algorithms. Meanwhile, the modified formulation has better accuracy than the existing incremental SVOR algorithm, and is as accurate as the sum-of-margins based formulation of Shashua and Levin.
689 citations
632 citations
TL;DR: The authors used passive microwave observations to provide global estimates for forest and non-forest biomass trends over the past two decades and found that vegetation change is a key component of the carbon cycle, but quantifying these changes is challenging.
Abstract: Vegetation change is a key component of the carbon cycle, but quantifying these changes is challenging. Research using passive microwave observations now provides global estimates for forest and non-forest biomass trends over the past two decades.
466 citations
TL;DR: Experimental results demonstrate that the proposed approaches not only speed up the training and incremental learning processes of AdaBoost, but also yield better or competitive vehicle classification accuracies compared with several state-of-the-art methods, showing their potential for real-time applications.
460 citations
TL;DR: This paper introduces a new generalized hierarchical FCM (GHFCM), which is more robust to image noise with the spatial constraints: the generalized mean, and introduces a more flexibility function which considers the distance function itself as a sub-FCM.
Abstract: Fuzzy c-means (FCM) has been considered as an effective algorithm for image segmentation. However, it still suffers from two problems: one is insufficient robustness to image noise, and the other is the Euclidean distance in FCM, which is sensitive to outliers. In this paper, we propose two new algorithms, generalized FCM (GFCM) and hierarchical FCM (HFCM), to solve these two problems. Traditional FCM can be considered as a linear combination of membership and distance from the expression of its mathematical formula. GFCM is generated by applying generalized mean on these two items. We impose generalized mean on membership to incorporate local spatial information and cluster information, and on distance function to incorporate local spatial information and image intensity value. Thus, our GFCM is more robust to image noise with the spatial constraints: the generalized mean. To solve the second problem caused by Euclidean distance (l2 norm), we introduce a more flexibility function which considers the distance function itself as a sub-FCM. Furthermore, the sub-FCM distance function in HFCM is general and flexible enough to deal with non-Euclidean data. Finally, we combine these two algorithms to introduce a new generalized hierarchical FCM (GHFCM). Experimental results demonstrate the improved robustness and effectiveness of the proposed algorithm.
434 citations
07 Dec 2015
TL;DR: A low-rank tensor constraint is introduced to explore the complementary information from multiple views and, accordingly, a novel method called Low-rank Tensor constrained Multiview Subspace Clustering (LT-MSC) is established.
Abstract: In this paper, we explore the problem of multiview subspace clustering. We introduce a low-rank tensor constraint to explore the complementary information from multiple views and, accordingly, establish a novel method called Low-rank Tensor constrained Multiview Subspace Clustering (LT-MSC). Our method regards the subspace representation matrices of different views as a tensor, which captures dexterously the high order correlations underlying multiview data. Then the tensor is equipped with a low-rank constraint, which models elegantly the cross information among different views, reduces effectually the redundancy of the learned subspace representations, and improves the accuracy of clustering as well. The inference process of the affinity matrix for clustering is formulated as a tensor nuclear norm minimization problem, constrained with an additional L2,1-norm regularizer and some linear equalities. The minimization problem is convex and thus can be solved efficiently by an Augmented Lagrangian Alternating Direction Minimization (AL-ADM) method. Extensive experimental results on four benchmark datasets show the effectiveness of our proposed LT-MSC method.
TL;DR: Simulation results show that the proposed LARP outperforms the existing routing protocols in terms of packet delivery ratio and normalized routing overhead, and are expected to be of greater value than other existing solutions in underwater environment.
Abstract: As the network communications technology developing, a new type of networks has appeared in the daily life which is named underwater sensor networks (UWSNs). UWSNs are a class of emerging networks that experience variable and high propagation delays and limited available bandwidth. There are comprehensive applications in this area such as oceanographic data collection, pollution monitoring, offshore exploration, assisted navigation and so on. Due to the different environment under the ocean, routing protocols in UWSNs should be re-designed to fit for the surroundings. In particular, routing protocols in UWSNs should ensure the reliability of message transmission, not just decrease the delay. In this paper, we propose a novel routing protocol named Location-Aware Routing Protocol (LARP) for UWSNs, where the location information of nodes is used to help the transmission of the message. Simulation results show that the proposed LARP outperforms the existing routing protocols in terms of packet delivery ratio and normalized routing overhead. We expect LARP to be of greater value than other existing solutions in underwater environment.
TL;DR: An efficient ME and DE algorithm for reducing the computational complexity of MVC that can be applied to not only the odd views but also the even views and the RD performance degradation is negligible.
Abstract: The use of variable block-size motion estimation (ME), disparity estimation (DE), and multiple reference frames selection aims to improve the coding efficiency of multiview video coding (MVC), however, this is at the cost of high computational complexity of these advanced coding techniques, which are not suitable for real-time video broadcasting applications. In this paper, we propose an efficient ME and DE algorithm for reducing the computational complexity of MVC. Firstly, according to the characteristics of the coded block pattern and rate distortion (RD) cost, an early DIRECT mode decision algorithm is proposed. Then, based on the characteristics of the initial search point in the ME/DE process and the observation that the best point is center-biased, an early ME/DE termination strategy is proposed. If the ME/DE early termination is not satisfied, the ME/DE search window will be reduced by applying the optimal theory. At last, two block matching search strategies are proposed to predict the best point for the ME/DE. Experimental results show that the proposed algorithm can achieve 50.05% to 77.61%, 64.83% on average encoding time saving. Meanwhile, the RD performance degradation is negligible. Especially, the proposed algorithm can be applied to not only the odd views but also the even views.
TL;DR: This paper revise the user-based collaborative filtering (CF) technique, and proposes two recommendation approaches fusing usergenerated tags and social relations in a novel way that achieve more precise recommendations than the compared approaches.
Abstract: Recommender systems, which provide users with recommendations of content suited to their needs, have received great attention in today’s online business world. However, most recommendation approaches exploit only a single source of input data and suffer from the data sparsity problem and the cold start problem. To improve recommendation accuracy in this situation, additional sources of information, such as friend relationship and user-generated tags, should be incorporated in recommendation systems. In this paper, we revise the user-based collaborative filtering (CF) technique, and propose two recommendation approaches fusing usergenerated tags and social relations in a novel way. In order to evaluate the performance of our approaches, we compare experimental results with two baseline methods: user-based CF and user-based CF with weighted friendship similarity using the real datasets (Last.fm and Movielens). Our experimental results show that our methods get higher accuracy. We also verify our methods in cold-start settings, and our methods achieve more precise recommendations than the compared approaches. key words: recommender system, collaborative filtering, social tagging, social network
TL;DR: In this paper, the standardized precipitation evapotranspiration index (SPEI) is computed and compared in China using reference evapotspiration calculated using the Thornthwaite (TH) approach and the Penman-Monteith (PM) equation.
Abstract: The standardized precipitation evapotranspiration index (SPEI) is computed and compared in China using reference evapotranspiration calculated using the Thornthwaite (TH) approach and the Penman‐Monteith (PM) equation. The analysis reveals that SPEI_PM outperforms the SPEI_TH with regard to drought monitoring during the period 1961‐2012 over China, especially in arid regions of China. Furthermore, the SPEI_PM also performs better with regard to observed variations in soil moisture and streamflow in China. Thus, changes in drought characteristics over China are detected on the basis of variations in the SPEI_PM. The results indicate that droughts over China exhibit pronounced decadal variations over the past 50yr, with more frequent and severe droughts occurring before the 1980s and in the 2000s compared with the 1980s and 1990s. Since the late 1990s, droughts have become more frequent and severe across China, especially in some regions of northern China. Concurrently, consecutive drought events have also increased across China. This suggests that dry conditions in China have been enhanced in recent years. Further analyses illustrate that the temperature and precipitation anomalies exhibit different roles in detecting droughts across China, which is primarily due to the magnitude of their variations and different climate variability. Considering temperature and precipitation perturbations, droughts exhibit relatively larger responses to temperature fluctuations in northern China and relatively larger responses to precipitation anomalies in southern China.
TL;DR: In this article, the authors studied the effect of teleconnection patterns on the precipitation anomaly in the eastern part of East Asia and found that the effect was mainly dominated by the Pacific-Japan and Silk-Road teleconnections.
Abstract: East Asia is greatly impacted by drought. North and southwest China are the regions with the highest drought frequency and maximum duration. At the interannual time scale, drought in the eastern part of East Asia is mainly dominated by two teleconnection patterns (i.e., the Pacific–Japan and Silk Road teleconnections). The former is forced by SST anomalies in the western North Pacific and the tropical Indian Ocean during El Nino decaying year summers. The precipitation anomaly features a meridional tripolar or sandwich pattern. The latter is forced by Indian monsoon heating and is a propagation of stationary Rossby waves along the Asian jet in the upper troposphere. It can significantly influence the precipitation over north China. Regarding the long-term trend, there exists an increasing drought trend over central parts of northern China and a decreasing tendency over northwestern China from the 1950s to the present. The increased drought in north China results from a weakened tendency of summer ...
TL;DR: This paper provides a general formula of QTMs from which a set of quaternion-valued QTM invariants (QTMIs) are derived to image rotation, scale and translation transformations by eliminating the influence of transformation parameters.
Abstract: In this paper, by using the quaternion algebra, the conventional complex-type moments (CTMs) for gray-scale images are generalized to color images as quaternion-type moments (QTMs) in a holistic manner. We first provide a general formula of QTMs from which we derive a set of quaternion-valued QTM invariants (QTMIs) to image rotation, scale and translation transformations by eliminating the influence of transformation parameters. An efficient computation algorithm is also proposed so as to reduce computational complexity. The performance of the proposed QTMs and QTMIs are evaluated considering several application frameworks ranging from color image reconstruction, face recognition to image registration. We show they achieve better performance than CTMs and CTM invariants (CTMIs). We also discuss the choice of the unit pure quaternion influence with the help of experiments. $$(i-j-k)/\sqrt{3}$$ ( i - j - k ) / 3 appears to be an optimal choice.
TL;DR: In this paper, the authors examined the haze variations over North China and their associated atmospheric circulations for the period of 1960-2012 using daily visibility data and found that the haze events over this region primarily occur in boreal winter of year and mainly in the morning of day.
Abstract: Haze is a severe hazard that greatly influences traffic and daily life with great economic losses and threats to human health. To enhance understanding of the haze occurrences, this study examined the haze variations over North China and their associated atmospheric circulations for the period of 1960–2012 using daily visibility data. Results indicate that the haze events over this region primarily occur in boreal winter of year and mainly in the morning of day. The results of the analysis of the long-term variations indicate that the annual haze days were relatively few in the 1960s but increased steeply in the 1970s and have remained stable to the present. Some differences are obvious among seasons. A stably increasing trend is discernable in summer and autumn, relatively low in the 1960s and the 1990s–2000s and relatively high in the 1970s–1980s in spring and winter. Haze variations in urban regions are quite similar to haze variations in rural regions but with more haze days in urban regions because of the high aerosol emissions. Further analyses indicate that the occurrences of severe haze events in boreal winter generally correlate with the weakened northerly winds and the development of inversion anomalies in the lower troposphere, the weakened East Asian trough in the midtroposphere, and the northward East Asian jet in the high troposphere. All of these factors provide a favorable atmospheric background for the maintenance and development of haze events in this region.
TL;DR: Yupengyuan et al. as discussed by the authors proposed a new lab for Clean Energy and Green Catalysis Anhui University Hefei 230036, P.R. China.
Abstract: R. Wang, Dr. L. Gu, J. Zhou, X. Liu, Dr. C. Li, Prof. Y. Shen, Dr. Y. Yuan School of Chemistry and Chemical Engineering and Innovation Lab for Clean Energy and Green Catalysis Anhui University Hefei 230036 , P.R. China E-mail: yupengyuan@ahu.edu.cn Prof. F. Teng, Dr. Y. Yuan School of Environmental Sciences and Engineering Nanjing University of Information Science and Technology Nanjing 210044 , P.R. China
TL;DR: In this article, the Ni x Zn (1− x ) Fe 2 O 4 ( x ǫ= 0.8) ferrite nanofibers were synthesized by electrospinning method.
TL;DR: The receptor model, Pb isotopic mixing model and Pb source by isotopic model were developed to quantify the source contribution for typical HMs in urban park soils of Xiamen, a representative megacity in southeast China.
TL;DR: In this article, long-term measurements of aerosol optical depths (AODs) at 440 nm and Angstrom exponents (AE) between 440 and 870 nm made for CARSNET were compiled into a climatology of airborne optical properties for China.
Abstract: . Long-term measurements of aerosol optical depths (AODs) at 440 nm and Angstrom exponents (AE) between 440 and 870 nm made for CARSNET were compiled into a climatology of aerosol optical properties for China. Quality-assured monthly mean AODs are presented for 50 sites representing remote, rural, and urban areas. AODs were 0.14, 0.34, 0.42, 0.54, and 0.74 at remote stations, rural/desert regions, the Loess Plateau, central and eastern China, and urban sites, respectively, and the corresponding AE values were 0.97, 0.55, 0.82, 1.19, and 1.05. AODs increased from north to south, with low values ( 0.60) in central and eastern China where industrial emissions and anthropogenic activities were likely sources. AODs were 0.20–0.40 in semi-arid and arid regions and some background areas in northern and northeastern China. AEs were > 1.20 over the southern reaches of the Yangtze River and at clean sites in northeastern China. In the northwestern deserts and industrial parts of northeast China, AEs were lower (
TL;DR: In this paper, the authors present a review of metal-functionalized nanostructured materials by carbothermal reduction integrated with other advanced technologies, particularly for strengthening efforts towards novel materials for clean energy and environmental applications in the future sustainable society.
Abstract: Carbothermal reduction could be employed as a facile technology for the synthesis of various novel materials, especially transition-metal-functionalized nanostructures. In particular, energy materials, such as ZnO, MnO2, and LiFePO4, combined with different carbon nanostructures have been widely synthesized via carbothermal reduction, which could be well established industrially due to its low-cost starting materials. In addition, a variety of carbon sources can be employed as comparatively low-cost carbon precursors for the synthesis of carbonaceous functional materials, such as porous carbon-coated magnetic nanoparticles (e.g., Co3O4@C, Fe3O4@C, and FeC3–C). These functional materials have great potential for use in energy and environmental applications. Carbothermal reduction methods possess some incomparable advantages, such as convenience, relatively low cost, and good repeatability, for commercial applications. However, they normally require a relatively high temperature for sustaining carbothermic reaction. Consequently, novel structures can also be derived from renewable, abundant carbon precursors. Examples include lignocellulosic biomass or other biological products derived from food or agricultural wastes (carbohydrates, cellulose, hemicellulose, lignin, chitin, inorganics, and proteins). Thermochemical conversion of biomass, including pyrolysis in an inert environment, has been developed for the production of energy and carbon materials. Furthermore, it is still a potential challenge to simultaneously produce high-quality biofuel products and synthesize value-added functionalized materials via in situ carbothermal reduction. This review will be a powerful resource for stimulating the development of sustainable metal-functionalized nanostructured materials by carbothermal reduction integrated with other advanced technologies, particularly for strengthening efforts towards novel materials for clean energy and environmental applications in the future sustainable society.
TL;DR: In this article, simulations in 31 climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) have been quantitatively assessed using skill-score metrics, including total precipitation (PRCPTOT), maximum consecutive dry days (CDD), precipitation intensity (SDII), and fraction of total rainfall from heavy events (R95T).
Abstract: Compared to precipitation extremes calculated from a high-resolution daily observational dataset in China during 1960–2005, simulations in 31 climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) have been quantitatively assessed using skill-score metrics. Four extreme precipitation indices, including the total precipitation (PRCPTOT), maximum consecutive dry days (CDD), precipitation intensity (SDII), and fraction of total rainfall from heavy events (R95T) are analyzed. Results show that CMIP5 models still have wet biases in western and northern China. Especially in western China, the models’ median relative error is about 120% for PRCPTOT; the 25th and 75th percentile errors are of 70% and 220%, respectively. However, there are dry biases in southeastern China, where the underestimation of PRCPTOT reach 200 mm. The performance of CMIP5 models is quite different between western and eastern China. The simulations are more reliable in the east than in the west in terms of...
TL;DR: In this article, CdS nanoparticles acting as photosensitizer were grown in situ upon UiO-66 metal-organic framework octahedrons through a hydrothermal process.
TL;DR: It is shown that this recent failure in predicting ISMR is largely due to the models' inability to capture new predictability sources emerging during recent global warming, that is, the development of the central-Pacific El Nino-Southern Oscillation, the rapid deepening of the Asian Low and the strengthening of North and South Pacific Highs during boreal spring.
Abstract: Prediction of Indian summer monsoon rainfall (ISMR) is at the heart of tropical climate prediction. Despite enormous progress having been made in predicting ISMR since 1886, the operational forecasts during recent decades (1989–2012) have little skill. Here we show, with both dynamical and physical–empirical models, that this recent failure is largely due to the models' inability to capture new predictability sources emerging during recent global warming, that is, the development of the central-Pacific El Nino-Southern Oscillation (CP–ENSO), the rapid deepening of the Asian Low and the strengthening of North and South Pacific Highs during boreal spring. A physical–empirical model that captures these new predictors can produce an independent forecast skill of 0.51 for 1989–2012 and a 92-year retrospective forecast skill of 0.64 for 1921–2012. The recent low skills of the dynamical models are attributed to deficiencies in capturing the developing CP–ENSO and anomalous Asian Low. The results reveal a considerable gap between ISMR prediction skill and predictability.
TL;DR: Two kinds of minimum cost models are proposed with regard to all the individuals and one particular individual respectively, and the economic significance of these two models is shown by exploring their dual models grounded in the primal–dual linear programming theory.
TL;DR: A machine learning-based fast coding unit (CU) depth decision method for High Efficiency Video Coding (HEVC), which optimizes the complexity allocation at CU level with given rate-distortion (RD) cost constraints.
Abstract: In this paper, we propose a machine learning-based fast coding unit (CU) depth decision method for High Efficiency Video Coding (HEVC), which optimizes the complexity allocation at CU level with given rate-distortion (RD) cost constraints. First, we analyze quad-tree CU depth decision process in HEVC and model it as a three-level of hierarchical binary decision problem. Second, a flexible CU depth decision structure is presented, which allows the performances of each CU depth decision be smoothly transferred between the coding complexity and RD performance. Then, a three-output joint classifier consists of multiple binary classifiers with different parameters is designed to control the risk of false prediction. Finally, a sophisticated RD-complexity model is derived to determine the optimal parameters for the joint classifier, which is capable of minimizing the complexity in each CU depth at given RD degradation constraints. Comparative experiments over various sequences show that the proposed CU depth decision algorithm can reduce the computational complexity from 28.82% to 70.93%, and 51.45% on average when compared with the original HEVC test model. The Bjontegaard delta peak signal-to-noise ratio and Bjontegaard delta bit rate are −0.061 dB and 1.98% on average, which is negligible. The overall performance of the proposed algorithm outperforms those of the state-of-the-art schemes.
TL;DR: In this article, Li diffusion on the surfaces of black and blue P has relatively low energy barriers and the single-layer blue P and double-layer black P possess high charge capacities.
Abstract: Black phosphorus (P) has been considered as a promising candidate for anodes due to its ability to absorb a large amount of Li atoms. Unfortunately, lithiation of bulk black P induces huge structural deformation, which limits its application. Here, on the basis of the density functional theory calculation, we predict that the newly found two-dimensional (2D) black and blue P are good electrodes for high-capacity lithium-ion batteries. Our theoretical calculations indicate that, in contrast to bulk black P, the monolayer and double-layer black and blue P can maintain their layered structures during lithiation and delithiation cycles. Moreover, it is found that Li diffusion on the surfaces of black and blue P has relatively low energy barriers (<0.4 eV), and the single-layer blue P and double-layer black and blue P possess high charge capacities.
TL;DR: In this paper, the Rossler system is used as a candidate for demonstrating the symmetry construction since it is an asymmetric system with a single-scroll attractor and a symmetric pair of coexisting strange attractors are produced, along with the desired partial or total amplitude control.
Abstract: Chaotic dynamical systems that are symmetric provide the possibility of multistability as well as an independent amplitude control parameter.The Rossler system is used as a candidate for demonstrating the symmetry construction since it is an asymmetric system with a single-scroll attractor. Through the design of symmetric Rossler systems, a symmetric pair of coexisting strange attractors are produced, along with the desired partial or total amplitude control.