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Calibration for Improving the Medium-Range Soil Forecast over Central Tibet: Effects of Objective Metrics' Diversity

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ATMOSPHERE 2024年第9期15卷 1107页

作者： Guo, Yakai Shao, Changliang Niu, Guanjun Xu, Dongmei Gao, Yong Yuan, Baojun China Meteorol Adm Henan Meteorol Bur Zhengzhou 450003 Peoples R China Nanjing Univ Informat Sci & Technol NUIST Key Lab Meteorol Disaster KLME Minist Educ Nanjing 210044 Peoples R China Nanjing Univ Informat Sci & Technol NUIST Collaborat Innovat Ctr Forecast & Evaluat Meteorol Nanjing 210044 Peoples R China China Meteorol Adm Meteorol Observat Ctr Beijing 100081 Peoples R China China Meteorol Adm Meteorol Dev & Planning Inst Beijing 100081 Peoples R China China Meteorol Adm Tibet Meteorol Observ Lhasa 850000 Peoples R China

The high spatial complexities of soil temperature modeling over semiarid land have challenged the calibration-forecast framework, whose composited objective lacks comprehensive evaluation. Therefore, this study, based on the Noah land surface model and its full parameter table, utilizes two global searching algorithms and eight kinds of objectives with dimensional-varied metrics, combined with dense site soil moisture and temperature observations of central Tibet, to explore different metrics' performances on the spatial heterogeneity and uncertainty of regional land surface parameters, calibration efficiency and effectiveness, and spatiotemporal complexities in surface forecasting. Results have shown that metrics' diversity has shown greater influence on the calibration-predication framework than the global searching algorithm's differences. The enhanced multi-objective metric (EMO) and the enhanced Kling-Gupta efficiency (EKGE) have their own advantages and disadvantages in simulations and parameters, respectively. In particular, the EMO composited with the four metrics of correlated coefficient, root mean square error, mean absolute error, and Nash-Sutcliffe efficiency has shown relatively balanced performance in surface soil temperature forecasting when compared to other metrics. In addition, the calibration-forecast framework that benefited from the EMO could greatly reduce the spatial complexities in surface soil modeling of semiarid land. In general, these findings could enhance the knowledge of metrics' advantages in solving the complexities of the LSM's parameters and simulations and promote the application of the calibration-forecast framework, thereby potentially improving regional surface forecasting over semiarid regions.

关键词： metrics diversity Kling-Gupta efficiency soil temperature modeling spatial complexity land surface parameters

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Behavior and aquatic plants as factors affecting predation by three species of larval predaceous diving beetles (Coleoptera: Dytiscidae)

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HYDROBIOLOGIA 2010年第1期637卷 33-43页

作者： Yee, Donald A. Univ Calgary Dept Biol Sci Calgary AB T2N 1N4 Canada

Predation among aquatic invertebrate predators can have important effects on patterns of exclusion and coexistence in aquatic habitats, especially if these predators also act as intraguild predators. Such patterns may be explained by variation in predator foraging mode and in the extent and overlap of habitat use. Predaceous diving beetles (Coleoptera: Dytiscidae) are abundant in isolated bodies of water and are effective predators on many aquatic organisms, including other dytiscids. The under-investigated role of hunting behavior and habitat use in altering outcomes of predation under different plant densities may offer insights into patterns of coexistence among larval dytiscids. I performed experiments that quantified behavior of larvae of three common genera of dytiscids that share common prey and then measured predation among genera in the presence or absence of aquatic plants. Behavioral analyses concluded that there were significant differences in foraging modes, with Dytiscus primarily exhibiting sit-and-wait tactics, Graphoderus engaging in active, open water searching, and Rhantus displaying combinations of these behaviors. Predation among larvae was common and occurred when predators were larger than the prey, with no indication of prey preference. Incidence of predation among generic combinations depended on the presence of plants and appeared to be related to behavioral differences among genera. The presence or absence of plants and differences in larval behavior may help to mitigate predation by reducing negative interactions in natural aquatic systems. These results have implications for IGP interactions and may be one of the explanations for the observed richness of this group of predators within aquatic habitats.

关键词： Behavior Habitat domain Intraguild predation spatial complexity Temporary wetlands

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Fractal characterization of hyperspectral imagery

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PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING 1999年第1期65卷 63-71页

作者： Qiu, HL Lam, NSN Quattrochi, DA Gamon, JA Calif State Univ Los Angeles Dept Geog & Urban Anal Los Angeles CA 90032 USA Louisiana State Univ Dept Geog & Anthropol Baton Rouge LA 70803 USA NASA Global Hydrol & Climate Ctr George C Marshall Space Flight Ctr Huntsville AL 35812 USA Calif State Univ Los Angeles Dept Biol & Microbiol Los Angeles CA 90032 USA

Two AVIRIS hyperspectral images selected from the Los Angeles area, one representing urban and the other rural, were used to examine their spatial complexity across their entire spectrum of the remote sensing data. Using the ICAMS (Image Characterization And Modeling System) software, we computed the fractal dimension values using the isarithm and triangular prism methods for all 224 bands in the two AVIRIS scenes. The resultant fractal dimensions reflect changes in image complexity across the spectral range of the hyperspectral images. Both the isarithm and triangular prism methods detect unusually high D values on the spectral bands that fall within the atmospheric absorption and scattering zones where signal-to-noise ratios are low. Fractal dimensions for the urban area resulted in higher values than for the rural landscape, and the differences between the resulting D values are more distinct in the visible bands. The triangular prism method is sensitive to a few random speckles in the images, leading to a lower dimensionality. On the contrary the isarithm method will ignore the speckles and focus on the major variation dominating the surface, thus resulting in a higher dimension. It is seen where the fractal curves plotted for the entire bandwidth range of the hyperspectral images could be used to distinguish landscape types as well as for screening noisy bands.

关键词： .modeling system scenes spectral bands California State fractal dimensions spatial complexity Fractal Characterization ICAMs dimension values hyperspectral images triangular prism method isarithm method

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DeepVCA: Deep Video complexity Analyzer

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2024年第9期34卷 8836-8847页

作者： Amirpour, Hadi Schoeffmann, Klaus Ghanbari, Mohammad Timmerer, Christian Alpen Adria Univ Christian Doppler Lab ATHENA A-9020 Klagenfurt Austria Alpen Adria Univ Inst Informat Technol A-9020 Klagenfurt Austria Univ Essex Sch Comp Sci & Elect Engn Colchester CO4 3SQ Essex England

Video streaming and its applications are growing rapidly, making video optimization a primary target for content providers looking to enhance their services. Enhancing the quality of videos requires the adjustment of different encoding parameters such as bitrate, resolution, and frame rate. To avoid brute force approaches for predicting optimal encoding parameters, video complexity features are typically extracted and utilized. To predict optimal encoding parameters effectively, content providers traditionally use unsupervised feature extraction methods, such as ITU-T's spatial Information (SI) and Temporal Information (TI) to represent the spatial and temporal complexity of video sequences. Recently, Video complexity Analyzer (VCA) was introduced to extract DCT-based features to represent the complexity of a video sequence (or parts thereof). These unsupervised features, however, cannot accurately predict video encoding parameters. To address this issue, this paper introduces a novel supervised feature extraction method named DeepVCA, which extracts the spatial and temporal complexity of video sequences using deep neural networks. In this approach, the encoding bits required to encode each frame in intra-mode and inter-mode are used as labels for spatial and temporal complexity, respectively. Initially, we benchmark various deep neural network structures to predict spatial complexity. We then leverage the similarity of features used to predict the spatial complexity of the current frame and its previous frame to rapidly predict temporal complexity. This approach is particularly useful as the temporal complexity may depend not only on the differences between two consecutive frames but also on their spatial complexity. Our proposed approach demonstrates significant improvement over unsupervised methods, especially for temporal complexity. As an example application, we verify the effectiveness of these features in predicting the encoding bitrate and encoding time of v

关键词： Video complexity video streaming spatial complexity temporal complexity VCA DNN

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Characterization of the spatial complex behavior and transition to chaos in flow systems

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PHYSICA D-NONLINEAR PHENOMENA 1999年第1-2期125卷 65-78页

作者： Falcioni, M Vergni, D Vulpiani, A Univ Roma La Sapienza Dipartimento Fis I-00185 Rome Italy Univ Roma La Sapienza Ist Nazl Fis Mat I-00185 Rome Italy

We introduce a "spatial" Lyapunov exponent to characterize the complex behavior of non-chaotic but convectively unstable flow sytems. This complexity is of spatial type and is due to sensitivity to the boundary conditions. We show that there exists a relation between the spatial-complexity index we define and the comoving Lyapunov exponents. In such systems the transition to chaos, i.e., the occurrence of a positive Lyapunov exponent, can manifest itself in two different ways. In the first case (from neither chaotic nor spatially complex behavior to chaos) one observes the typical scenario;i.e., as the system size grows up the spectrum of the Lyapunov exponents gives rise to a density. In the second case (when the chaos develops from a convectively unstable situation) one observes only a finite number of positive Lyapunov exponents. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： spatial complexity non-chaotic systems flow systems

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A complexity perspective to deploy artistic exhibits

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2005年第10期56卷 1151-1158页

作者： Lan, CH Hsui, CY Wei, LC Nanhua Univ Grad Inst Management Sci Chiayi Taiwan Hosanna Museum Chiayi Taiwan

The design for the deployment of artistic statues in an exhibition area comes from the designer's experience, and whether such a design is adequate having no simple applicable criterion. The proposed model, deploying statues (DSs) model, not only applies the fractal dimension to measure the spatial complexity as its objective but also considers the traffic flow zone, the number of DSs, the average diameter of the statue, and the minimum allowable distance of adjacent artistic statues to arrange the spatial configuration in an exhibition area. The minimal complexity ( fractal dimension) is mainly focused on because exhibiting designers deem that the spatial simplicity of an exhibition area leads to comfortable vision for a visitor. Indeed, this paper describes an applicable aspect of fractals. A computational intelligence written in Fortran Program to perform the spatial arrangement of artistic statues in an exhibition area is provided, and its adaptability has been explored by pilot tests of benchmark cases. Then, a case study through visual reality deployment for the Hosanna Museum at Chiayi Taiwan is followed. This study indeed provides a valuable tool in conducting the pre-stage of thinking process for exhibiting designers in deploying exhibits.

关键词： fractal dimension spatial complexity exhibition area pilot test benchmark case aesthetic

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High-Order spatial Simulation Using Legendre-Like Orthogonal Splines

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MATHEMATICAL GEOSCIENCES 2018年第7期50卷 753-780页

作者： Minniakhmetov, Ilnur Dimitrakopoulos, Roussos Godoy, Marcelo McGill Univ COSMO Stochast Min Planning Lab Montreal PQ H3A 0E8 Canada Newmont Min Corp Denver CO USA

High-order sequential simulation techniques for complex non-Gaussian spatially distributed variables have been developed over the last few years. The high-order simulation approach does not require any transformation of initial data and makes no assumptions about any probability distribution function, while it introduces complex spatial relations to the simulated realizations via high-order spatial statistics. This paper presents a new extension where a conditional probability density function (cpdf) is approximated using Legendre-like orthogonal splines. The coefficients of spline approximation are estimated using high-order spatial statistics inferred from the available sample data, additionally complemented by a training image. The advantages of using orthogonal splines with respect to the previously used Legendre polynomials include their ability to better approximate a multidimensional probability density function, reproduce the high-order spatial statistics, and provide a generalization of high-order simulations using Legendre polynomials. The performance of the new method is first tested with a completely known image and compared to both the high-order simulation approach using Legendre polynomials and the conventional sequential Gaussian simulation method. Then, an application in a gold deposit demonstrates the advantages of the proposed method in terms of the reproduction of histograms, variograms, and high-order spatial statistics, including connectivity measures. The C++ course code of the high-order simulation implementation presented herein, along with an example demonstrating its utilization, are provided online as supplementary material.

关键词： Stochastic simulation Orthogonal splines High-order spatial statistics Non-Gaussian distribution spatial complexity

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Power quality disturbances classification using rotation forest and multi-resolution fast S-transform with data compression in time domain

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第22期13卷 5091-5101页

作者： Huang, Nantian Wang, Da Lin, Lin Cai, Guowei Huang, Guilin Du, Jiping Zheng, Jian Northeast Elect Power Univ Key Lab Modern Power Syst Simulat & Control & Ren Minist Educ Jilin 132012 Jilin Peoples R China State Grid Shandong Elect Power Co Ltd Dezhou Power Supply Co Dezhou 253000 Peoples R China Jilin Inst Chem Technol Coll Informat & Control Engn 45 Chengde St Jilin 132022 Jilin Peoples R China State Grid Jiangxi Elect Power Corp Elect Power Econ Res Inst 1588 Yingbin North Ave Nanchang 330043 Jiangxi Peoples R China Jiangxi Elect Power Co Ltd State Grid 666 Hubin East Rd Nanchang 330077 Jiangxi Peoples R China

Considering the high spatial complexity of signal processing methods and the low diversity between the base classifiers in the ensemble classifier, a new method with optimal multi-resolution fast S-transform (OMFST) with low spatial complexity and rotation forest (ROF) was proposed. Firstly, Gini importance of features is evaluated by random forest (RF), and the sequence forward search method was adopted for feature selection. Then, the intermediate matrix was constructed on the optimal feature set. The results of inverse fast Fourier transform in the main frequency points of signals based on OMFST are compressed in time domain. The intermediate matrix was used to extract features for power quality (PQ) disturbances recognition. Finally, the ROF was adopted to encourage simultaneously individual accuracy and diversity within the ensemble. The optimal ROF was applied to identify 17 kinds of PQ disturbance signals. The simulation results show that the new method can effectively compress the time-frequency matrix of the existing S-transform (ST) method;the space complexity of the ST modular matrix is reduced significantly and has higher accuracy. Besides, the results of the experiment with real PQ data prove that the new method was effective for practical industrial applications.

关键词： feature extraction learning (artificial intelligence) data compression pattern classification power supply quality fast Fourier transforms time-frequency analysis decision trees power system faults optimal feature set inverse fast Fourier OMFST time domain intermediate matrix optimal ROF PQ disturbance signals time-frequency matrix S-transform method space complexity ST modular matrix RF classifiers ROF classifier PQ data power quality disturbance classification rotation forest data compression base classifiers ensemble classifier optimal multiresolution fast S-transform spatial complexity Gini importance random forest sequence forward search method feature selection

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Determining the parameters of emotion by analyzing environmental images captured by a mobile device

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MULTIMEDIA TOOLS AND APPLICATIONS 2019年第20期78卷 28375-28389页

作者： Hwang, Hyeonsang Lee, Eui Chul Sangmyung Univ Dept Comp Sci Hongjimun 2 Gil 20 Seoul 03016 South Korea Sangmyung Univ Dept Intelligent Engn Informat Human Hongjimun 2 Gil 20 Seoul 03016 South Korea

This paper proposes a method to quantitatively extract human emotions by analyzing images of the surrounding environment captured by a smartphone camera in real time. In the field of psychology, it is known that visual elements such as colors and complexity affect human emotions. Based on this knowledge, we developed an application for the extraction of emotions in real time using the colors and spatial complexity of images obtained with Android smartphones. Among the color components of images, the hue component, which indicates the color, is extracted as the color element and the spatial complexity is extracted by quantitatively determining the high- and low-frequency components that are visible in the images. The corresponding two-dimensional emotion is identified by using two support vector regression modules. The results show that the root-mean-square error between the estimated emotion and the subjectively evaluated emotion is approximately 0.36 on the -1 to +1 axes plane.

关键词： Mobile app Life-logging Visual parameter Color spatial complexity Emotion

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Environmental complexity and predator density mediate a stable earwig-woolly apple aphid interaction

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BASIC AND APPLIED ECOLOGY 2024年 74卷 108-114页

作者： Bischoff, Robert Pokharel, Prayan Miedtke, Paul Piepho, Hans -Peter Petschenka, Georg Univ Hohenheim Inst Phytomed Dept Appl Entomol Otto Sander Str 5 D-70599 Stuttgart Germany Univ Hohenheim Inst Crop Sci Biostat Unit Fruwirthstr 23 D-70599 Stuttgart Germany

Regulation of insect pests by predators is an integral component of biological pest control. However, predatorprey interactions often reach a stable state leading to coexistence, which can be problematic for plant protection if the persisting herbivores exceed a damage threshold. Consequently, understanding the factors mediating this stability is crucial for successful biocontrol. Here, we investigated the predator-prey interaction of an important apple pest, the woolly apple aphid (WAA) (Eriosoma lanigerum Hausm.) (Hemiptera: Aphididae), and its predator, the omnivorous common earwig (Forficula auricularia L.) (Dermaptera: Forficulidae). To this end, we introduced increasing densities of earwigs in gauze-bagged branches harbouring defined amounts of WAA and recorded predation on individual WAA colonies for almost one month. We showed that the spatial complexity of the predation environment and the earwig density determined the predation efficiency on WAAs. Earwigs could eradicate WAAs regardless of density on short apple branches without lateral twigs (first trial). However, on longer, more complex branches (second trial), stable states of WAAs and earwigs were observed. Only the highest earwig density could completely consume WAA regardless of branch complexity. We introduce a conceptual model to describe the searching capability of earwigs, which determines their efficiency in locating prey. Our model predicts that searching capability is reduced by environmental complexity;this effect is alleviated by increased earwig density, as more predators possess a higher searching capability. Conclusively, our model explains why only the highest earwig density could completely consume WAA irrespective of complexity and illustrates how predator density and environmental complexity jointly influence predation. Thus environmental characteristics not inherent to our predator-prey interaction were a decisive factor for effective predation on gauze-bagged branches. Based on the

关键词： Forficula auricularia Eriosoma lanigerum Biocontrol spatial complexity Searching capability Stable state Stability Predator-prey interaction Predator density

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