Vegetation Angular Signatures of Equatorial Forests From DSCOVR EPIC and Terra MISR Observations

In vegetation canopies cross-shading between finite dimensional leaves leads to a peak in reflectance in the retro-illumination direction. This effect is called the hot spot in optical remote sensing. The hotspot region in reflectance of vegetated surfaces represents the most information-rich directions in the angular distribution of canopy reflected radiation. This paper presents a new approach for generating hot spot signatures of equatorial forests from synergistic analyses of multiangle observations from the Multiangle Imaging SpectroRadiometer (MISR) on Terra platform and near backscattering reflectance data from the Earth Polychromatic Imaging Camera (EPIC) onboard NOAA’s Deep Space Climate Observatory (DSCOVR). A canopy radiation model parameterized in terms of canopy spectral invariants underlies the theoretical basis for joining Terra MISR and DSCOVR EPIC data. The proposed model can accurately reproduce both MISR angular signatures acquired at 10:30 local solar time and diurnal courses of EPIC reflectance (NRMSE < 9%, R2 > 0.8). Analyses of time series of the hot spot signature suggest its ability to unambiguously detect seasonal changes of equatorial forests.

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An Interplay between Photons, Canopy Structure, and Recollision Probability: A Review of the Spectral Invariants Theory of 3D Canopy Radiative Transfer Processes

Remote Sensing ◽

10.3390/rs10111805 ◽

2018 ◽

Vol 10 (11) ◽

pp. 1805 ◽

Cited By ~ 3

Author(s):

Weile Wang ◽

Ramakrishna Nemani ◽

Hirofumi Hashimoto ◽

Sangram Ganguly ◽

Dong Huang ◽

...

Keyword(s):

Remote Sensing ◽

Radiative Transfer ◽

Hot Spot ◽

Structural Characteristics ◽

Pair Correlation ◽

Canopy Structure ◽

Remote Sensing Data ◽

Optical Remote Sensing ◽

Spectral Invariants ◽

3D Information

Earth observations collected by remote sensors provide unique information to our ever-growing knowledge of the terrestrial biosphere. Yet, retrieving information from remote sensing data requires sophisticated processing and demands a better understanding of the underlying physics. This paper reviews research efforts that lead to the developments of the stochastic radiative transfer equation (RTE) and the spectral invariants theory. The former simplifies the characteristics of canopy structures with a pair-correlation function so that the 3D information can be succinctly packed into a 1D equation. The latter indicates that the interactions between photons and canopy elements converge to certain invariant patterns quantifiable by a few wavelength independent parameters, which satisfy the law of energy conservation. By revealing the connections between plant structural characteristics and photon recollision probability, these developments significantly advance our understanding of the transportation of radiation within vegetation canopies. They enable a novel physically-based algorithm to simulate the “hot-spot” phenomenon of canopy bidirectional reflectance while conserving energy, a challenge known to the classic radiative transfer models. Therefore, these theoretical developments have a far-reaching influence in optical remote sensing of the biosphere.

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Intelligent recognition of semantic relationships based on antonymy

Multiagent and Grid Systems ◽

10.3233/mgs-200332 ◽

2020 ◽

Vol 16 (3) ◽

pp. 263-290

Author(s):

Hui Guan ◽

Chengzhen Jia ◽

Hongji Yang

Keyword(s):

Semantic Similarity ◽

New Approach ◽

Word Similarity ◽

Semantic Relationships ◽

Proposed Model ◽

Path Distance ◽

The Hierarchical Structure ◽

Thinking Process ◽

Similarity Measuring ◽

Intelligent Recognition

Since computing semantic similarity tends to simulate the thinking process of humans, semantic dissimilarity must play a part in this process. In this paper, we present a new approach for semantic similarity measuring by taking consideration of dissimilarity into the process of computation. Specifically, the proposed measures explore the potential antonymy in the hierarchical structure of WordNet to represent the dissimilarity between concepts and then combine the dissimilarity with the results of existing methods to achieve semantic similarity results. The relation between parameters and the correlation value is discussed in detail. The proposed model is then applied to different text granularity levels to validate the correctness on similarity measurement. Experimental results show that the proposed approach not only achieves high correlation value against human ratings but also has effective improvement to existing path-distance based methods on the word similarity level, in the meanwhile effectively correct existing sentence similarity method in some cases in Microsoft Research Paraphrase Corpus and SemEval-2014 date set.

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A New Approach to Inform Restoration and Management Decisions for Sustainable Apiculture

Sustainability ◽

10.3390/su13116109 ◽

2021 ◽

Vol 13 (11) ◽

pp. 6109

Author(s):

Joanne Lee Picknoll ◽

Pieter Poot ◽

Michael Renton

Keyword(s):

Floral Resources ◽

Pollination Services ◽

New Approach ◽

Honey Production ◽

Proposed Model ◽

Colony Loss ◽

Supply Potential ◽

Australian Case ◽

Stocking Rates

Habitat loss has reduced the available resources for apiarists and is a key driver of poor colony health, colony loss, and reduced honey yields. The biggest challenge for apiarists in the future will be meeting increasing demands for pollination services, honey, and other bee products with limited resources. Targeted landscape restoration focusing on high-value or high-yielding forage could ensure adequate floral resources are available to sustain the growing industry. Tools are currently needed to evaluate the likely productivity of potential sites for restoration and inform decisions about plant selections and arrangements and hive stocking rates, movements, and placements. We propose a new approach for designing sites for apiculture, centred on a model of honey production that predicts how changes to plant and hive decisions affect the resource supply, potential for bees to collect resources, consumption of resources by the colonies, and subsequently, amount of honey that may be produced. The proposed model is discussed with reference to existing models, and data input requirements are discussed with reference to an Australian case study area. We conclude that no existing model exactly meets the requirements of our proposed approach, but components of several existing models could be combined to achieve these needs.

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From Geometric-Optical Remote Sensing Modeling to Quantitative Remote Sensing Science—In Memory of Academician Xiaowen Li

Remote Sensing ◽

10.3390/rs10111764 ◽

2018 ◽

Vol 10 (11) ◽

pp. 1764 ◽

Cited By ~ 2

Author(s):

Qinhuo Liu ◽

Guangjian Yan ◽

Ziti Jiao ◽

Qing Xiao ◽

Jianguang Wen ◽

...

Keyword(s):

Remote Sensing ◽

Thermal Emission ◽

Scale Effects ◽

Remote Sensing Data ◽

Geometric Optic ◽

Optical Remote Sensing ◽

Research Activities ◽

Quantitative Remote Sensing ◽

Vegetation Canopies ◽

High Regard

The academician Xiaowen Li devoted much of his life to pursuing fundamental research in remote sensing. A pioneer in the geometric-optical modeling of vegetation canopies, his work is held in high regard by the international remote sensing community. He codeveloped the Li–Strahler geometric-optic model, and this paper was selected by a member of the International Society for Optical Engineering (SPIE) milestone series. As a chief scientist, Xiaowen Li led a scientific team that made outstanding advances in bidirectional reflectance distribution modeling, directional thermal emission modeling, comprehensive experiments, and the understanding of spatial and temporal scale effects in remote sensing information, and of quantitative inversions utilizing remote sensing data. In addition to his broad research activities, he was noted for his humility and his dedication in making science more accessible for the general public. Here, the life and academic contributions of Xiaowen Li to the field of quantitative remote sensing science are briefly reviewed.

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Remaining Useful Life Prediction for Rotating Machinery Based on Optimal Degradation Indicator

Shock and Vibration ◽

10.1155/2017/6754968 ◽

2017 ◽

Vol 2017 ◽

pp. 1-12 ◽

Cited By ~ 4

Author(s):

Aisong Qin ◽

Qinghua Zhang ◽

Qin Hu ◽

Guoxi Sun ◽

Jun He ◽

...

Keyword(s):

Health Management ◽

Rotating Machinery ◽

Remaining Useful Life ◽

Programming Algorithm ◽

Wiener Model ◽

New Approach ◽

Degradation Modeling ◽

Proposed Model ◽

Useful Life ◽

Degradation Indicator

Remaining useful life (RUL) prediction can provide early warnings of failure and has become a key component in the prognostics and health management of systems. Among the existing methods for RUL prediction, the Wiener-process-based method has attracted great attention owing to its favorable properties and flexibility in degradation modeling. However, shortcomings exist in methods of this type; for example, the degradation indicator and the first predicting time (FPT) are selected subjectively, which reduces the prediction accuracy. Toward this end, this paper proposes a new approach for predicting the RUL of rotating machinery based on an optimal degradation indictor. First, a genetic programming algorithm is proposed to construct an optimal degradation indicator using the concept of FPT. Then, a Wiener model based on the obtained optimal degradation indicator is proposed, in which the sensitivities of the dimensionless parameters are utilized to determine the FPT. Finally, the expectation of the predicted RUL is calculated based on the proposed model, and the estimated mean degradation path is explicitly derived. To demonstrate the validity of this model, several experiments on RUL prediction are conducted on rotating machinery. The experimental results indicate that the method can effectively improve the accuracy of RUL prediction.

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Understanding the electrical behavior of the action potential in terms of elementary electrical sources

AJP Advances in Physiology Education ◽

10.1152/advan.00130.2014 ◽

2015 ◽

Vol 39 (1) ◽

pp. 15-26 ◽

Cited By ~ 6

Author(s):

Javier Rodriguez-Falces

Keyword(s):

Action Potential ◽

Action Potentials ◽

Present Report ◽

Electrical Potential ◽

Ionic Currents ◽

New Approach ◽

Electrical Potentials ◽

Proposed Model ◽

Ionic Mechanisms ◽

Human Electrophysiology

A concept of major importance in human electrophysiology studies is the process by which activation of an excitable cell results in a rapid rise and fall of the electrical membrane potential, the so-called action potential. Hodgkin and Huxley proposed a model to explain the ionic mechanisms underlying the formation of action potentials. However, this model is unsuitably complex for teaching purposes. In addition, the Hodgkin and Huxley approach describes the shape of the action potential only in terms of ionic currents, i.e., it is unable to explain the electrical significance of the action potential or describe the electrical field arising from this source using basic concepts of electromagnetic theory. The goal of the present report was to propose a new model to describe the electrical behaviour of the action potential in terms of elementary electrical sources (in particular, dipoles). The efficacy of this model was tested through a closed-book written exam. The proposed model increased the ability of students to appreciate the distributed character of the action potential and also to recognize that this source spreads out along the fiber as function of space. In addition, the new approach allowed students to realize that the amplitude and sign of the extracellular electrical potential arising from the action potential are determined by the spatial derivative of this intracellular source. The proposed model, which incorporates intuitive graphical representations, has improved students' understanding of the electrical potentials generated by bioelectrical sources and has heightened their interest in bioelectricity.

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A New Approach to Improve Accuracy of Grey Model GMC(1,n)in Time Series Prediction

Modelling and Simulation in Engineering ◽

10.1155/2015/126738 ◽

2015 ◽

Vol 2015 ◽

pp. 1-10 ◽

Cited By ~ 1

Author(s):

Sompop Moonchai ◽

Wanwisa Rakpuang

Keyword(s):

Prediction Accuracy ◽

Time Series Prediction ◽

Electricity Consumption ◽

Prediction Equation ◽

Grey Model ◽

System Behavior ◽

New Approach ◽

Proposed Model ◽

Improve Accuracy ◽

Relative Factors

This paper presents a modified grey model GMC(1,n)for use in systems that involve one dependent system behavior andn-1relative factors. The proposed model was developed from the conventional GMC(1,n)model in order to improve its prediction accuracy by modifying the formula for calculating the background value, the system of parameter estimation, and the model prediction equation. The modified GMC(1,n)model was verified by two cases: the study of forecasting CO2emission in Thailand and forecasting electricity consumption in Thailand. The results demonstrated that the modified GMC(1,n)model was able to achieve higher fitting and prediction accuracy compared with the conventional GMC(1,n)and D-GMC(1,n)models.

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Reduction approach to second order perturbed state-dependent sweeping process

Creative Mathematics and Informatics ◽

10.37193/cmi.2019.02.13 ◽

2019 ◽

Vol 28 (2) ◽

Author(s):

MUSTAPHA FATEH YAROU

Keyword(s):

Fixed Point Theory ◽

Point Theory ◽

Second Order ◽

Sweeping Process ◽

New Approach ◽

Standard Methods ◽

First Order ◽

Finite Dimensional ◽

Perturbed State ◽

State Dependent

In this paper, we present a new approach to solving second order nonconvex perturbed sweeping process in finite dimensional setting. It consists in a reduction of the problem to a first order one without use of the standard methods of fixed point theory. The perturbation, that is the external force applied on the system is not necessary with bounded values.

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PROVIDING A DEPENDABLE OPERATION OF THE DATA PROCESSING SYSTEM WITH INTERVAL CHANGES IN THE FLOW CHARACTERISTICS BASED ON ANALYTICAL SIMULATIONS

Automation and modeling in design and management of ◽

10.30987/2658-6436-2021-3-4-25-30 ◽

2021 ◽

Vol 2021 (3-4) ◽

pp. 25-30

Author(s):

Kirill Tkachenko

Keyword(s):

Data Processing ◽

Flow Characteristics ◽

Processing System ◽

Data Processing System ◽

New Approach ◽

Analytical Simulation ◽

Proposed Model ◽

Computing Node ◽

Computer Node ◽

Adequate Data

The article proposes a new approach for adjusting the parameters of computing nodes being a part of a data processing system based on analytical simulation of a queuing system with subsequent estimation of probabilities of hypotheses regarding the computing node state. Methods of analytical modeling of queuing systems and mathematical statistics are used. The result of the study is a mathematical model for assessing the information situation for a computing node, which differs from the previously published system model used. Estimation of conditional probabilities of hypotheses concerning adequate data processing by a computing node allows making a decision on the need of adjusting the parameters of a computing node. This adjustment makes it possible to improve the efficiency of working with tasks on the computing node of the data processing system. The implementation of the proposed model for adjusting the parameters of the computer node of the data processing system increases both the efficiency of process applications on the node and, in general, the efficiency of its operation. The application of the approach to all computing nodes of the data processing system increases the dependability of the system as a whole.

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Study on fabric compression under seam vis a vis quantitative measurement of seam boldness and thread consumption for lockstitch 301

Research Journal of Textile and Apparel ◽

10.1108/rjta-06-2020-0071 ◽

2020 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Md Vaseem Chavhan ◽

Mandapati Ramesh Naidu

Keyword(s):

Quantitative Measurement ◽

Multilinear Regression ◽

New Approach ◽

Content Type ◽

Single View ◽

Sewing Thread ◽

Stitch Density ◽

Proposed Model ◽

Fabric Weight ◽

Single View Metrology

Purpose This paper aims to develop at sewing thread during the seam formation may lead to the compression of fabric under seam. In the present study, the model has been proposed to predict the seam compression and calculation of seam boldness, as well as thread consumption by considering seam compression. Design/methodology/approach The effect of sewing parameters on the fabric compression at the seam (Cf) for fabrics of varying bulk density was studied by the Taguchi method and also the multilinear regression equation is obtained to predict seam compression by considering these parameters. The framework has been set as per the single view metrology approach to measuring structural seam boldness (Bs). One of the basic geometrical models (Ghosh and Chavhan, 2014) for the prediction of thread consumption at lock stitch has been modified by considering fabric compression at the seam (Cf). Findings The multilinear regression model has been proposed which can predict the compression under seam using easily measurable fabric parameters and stitch density. The seam boldness is successfully calculated quantitatively using the proposed formula with a good correlation with the seam boldness rated subjectively. The thread consumption estimation from the proposed approach was found to be more accurate. Originality/value The compression under seam is found out using easily measurable parameters; fabric thickness, fabric weight and stitch density from the proposed model. The attempt has been made to calculate seam boldness quantitatively and the new approach to find out thread consumption by considering the seam compression has been proposed.

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