Articles de revues : « Optical diversity metrics »

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Imran, Hafiz Ali, Damiano Gianelle, Michele Scotton, Duccio Rocchini, Michele Dalponte, Stefano Macolino, Karolina Sakowska, Cristina Pornaro et Loris Vescovo. « Potential and Limitations of Grasslands α-Diversity Prediction Using Fine-Scale Hyperspectral Imagery ». Remote Sensing 13, n^o 14 (6 juillet 2021) : 2649. http://dx.doi.org/10.3390/rs13142649.

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Plant biodiversity is an important feature of grassland ecosystems, as it is related to the provision of many ecosystem services crucial for the human economy and well-being. Given the importance of grasslands, research has been carried out in recent years on the potential to monitor them with novel remote sensing techniques. In this study, the optical diversity (also called spectral diversity) approach was adopted to check the potential of using high-resolution hyperspectral images to estimate α-diversity in grassland ecosystems. In 2018 and 2019, grassland species composition was surveyed and canopy hyperspectral data were acquired at two grassland sites: Monte Bondone (IT-MBo; species-rich semi-natural grasslands) and an experimental farm of the University of Padova, Legnaro, Padua, Italy (IT-PD; artificially established grassland plots with a species-poor mixture). The relationship between biodiversity (species richness, Shannon’s, species evenness, and Simpson’s indices) and optical diversity metrics (coefficient of variation-CV and standard deviation-SD) was not consistent across the investigated grassland plant communities. Species richness could be estimated by optical diversity metrics with an R = 0.87 at the IT-PD species-poor site. In the more complex and species-rich grasslands at IT-MBo, the estimation of biodiversity indices was more difficult and the optical diversity metrics failed to estimate biodiversity as accurately as in IT-PD probably due to the higher number of species and the strong canopy spatial heterogeneity. Therefore, the results of the study confirmed the ability of spectral proxies to detect grassland α-diversity in man-made grassland ecosystems but highlighted the limitations of the spectral diversity approach to estimate biodiversity when natural grasslands are observed. Nevertheless, at IT-MBo, the optical diversity metric SD calculated from post-processed hyperspectral images and transformed spectra showed, in the red part of the spectrum, a significant correlation (up to R = 0.56, p = 0.004) with biodiversity indices. Spatial resampling highlighted that for the IT-PD sward the optimal optical pixel size was 1 cm, while for the IT-MBo natural grassland it was 1 mm. The random pixel extraction did not improve the performance of the optical diversity metrics at both study sites. Further research is needed to fully understand the links between α-diversity and spectral and biochemical heterogeneity in complex heterogeneous ecosystems, and to assess whether the optical diversity approach can be adopted at the spatial scale to detect β-diversity. Such insights will provide more robust information on the mechanisms linking grassland diversity and optical heterogeneity.

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Riemer, N., et M. West. « Quantifying aerosol mixing state with entropy and diversity measures ». Atmospheric Chemistry and Physics Discussions 13, n^o 6 (12 juin 2013) : 15615–62. http://dx.doi.org/10.5194/acpd-13-15615-2013.

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Abstract. This paper presents the first quantitative metric for aerosol population mixing state, defined as the distribution of per-particle chemical species composition. This new metric, the mixing state index χ, is an affine ratio of the average per-particle species diversity Dα and the bulk population species diversity Dγ, both of which are based on information-theoretic entropy measures. The mixing state index χ enables the first rigorous definition of the spectrum of mixing states from so-called external mixture to internal mixture, which is significant for aerosol climate impacts, including aerosol optical properties and cloud condensation nuclei activity. We illustrate the usefulness of this new mixing state framework with model results from the stochastic particle-resolved model PartMC-MOSAIC. These results demonstrate how the mixing state metrics evolve with time for several archetypal cases, each of which isolates a specific process such as coagulation, emission, or condensation. Further, we present an analysis of the mixing state evolution for a complex urban plume case, for which these processes occur simultaneously. We additionally derive theoretical properties of the mixing state index and present a family of generalized mixing state indexes that vary in the importance assigned to low-mass-fraction species.

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Riemer, N., et M. West. « Quantifying aerosol mixing state with entropy and diversity measures ». Atmospheric Chemistry and Physics 13, n^o 22 (25 novembre 2013) : 11423–39. http://dx.doi.org/10.5194/acp-13-11423-2013.

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Abstract. This paper presents the first quantitative metric for aerosol population mixing state, defined as the distribution of per-particle chemical species composition. This new metric, the mixing state index χ, is an affine ratio of the average per-particle species diversity Dα and the bulk population species diversity Dγ, both of which are based on information-theoretic entropy measures. The mixing state index χ enables the first rigorous definition of the spectrum of mixing states from so-called external mixture to internal mixture, which is significant for aerosol climate impacts, including aerosol optical properties and cloud condensation nuclei activity. We illustrate the usefulness of this new mixing state framework with model results from the stochastic particle-resolved model PartMC-MOSAIC. These results demonstrate how the mixing state metrics evolve with time for several archetypal cases, each of which isolates a specific process such as coagulation, emission, or condensation. Further, we present an analysis of the mixing state evolution for a complex urban plume case, for which these processes occur simultaneously. We additionally derive theoretical properties of the mixing state index and present a family of generalized mixing state indexes that vary in the importance assigned to low-mass-fraction species.

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Qi, Jing Jia, Chuan Jun Guo et Yang Nan. « Study on Application of Super-Resolution Image Reconstruction Method Used in Video Image Processing ». Advanced Materials Research 476-478 (février 2012) : 1142–45. http://dx.doi.org/10.4028/www.scientific.net/amr.476-478.1142.

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Super resolution image reconstruction is a computational process of using multiple low-resolution observations to reconstruct a higher resolution image, which differs from improvement of optical devices. With magnification diversity among those low-resolution imagers, significant performance improvement, compared to traditional methods, is demonstrated. Results include fidelity metrics and simulated reconstructions. Performance improvement of super-resolution imaging systems with magnification diversity is studied in this paper.

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Palacios Játiva, Pablo, Iván Sánchez, Ismael Soto, Cesar A. Azurdia-Meza, David Zabala-Blanco, Muhammad Ijaz, Ali Dehghan Firoozabadi et David Plets. « A Novel and Adaptive Angle Diversity-Based Receiver for 6G Underground Mining VLC Systems ». Entropy 24, n^o 11 (22 octobre 2022) : 1507. http://dx.doi.org/10.3390/e24111507.

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Visible light communication (VLC) is considered an enabling technology for future 6G wireless systems. Among the many applications in which VLC systems are used, one of them is harsh environments such as Underground Mining (UM) tunnels. However, these environments are subject to degrading environmental and intrinsic challenges for optical links. Therefore, current research should focus on solutions to mitigate these problems and improve the performance of Underground Mining Visible Light Communication (UM-VLC) systems. In this context, this article presents a novel solution that involves an improvement to the Angle Diversity Receivers (ADRs) based on the adaptive orientation of the Photo-Diodes (PDs) in terms of the Received Signal Strength Ratio (RSSR) scheme. Specifically, this methodology is implemented in a hemidodecahedral ADR and evaluated in a simulated UM-VLC scenario. The performance of the proposed design is evaluated using metrics such as received power, user data rate, and bit error rate (BER). Furthermore, our approach is compared with state-of-the-art ADRs implemented with fixed PDs and with the Time of Arrival (ToA) reception method. An improvement of at least 60% in terms of the analyzed metrics compared to state-of-the-art solutions is obtained. Therefore, the numerical results demonstrate that the hemidodecahedral ADR, with adaptive orientation PDs, enhances the received optical signal. Furthermore, the proposed scheme improves the performance of the UM-VLC system due to its optimum adaptive angular positioning, which is completed according to the strongest optical received signal power. By improving the performance of the UM-VLC system, this novel method contributes to further consideration of VLC systems as potential and enabling technologies for future 6G deployments.

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Varotsos, GeorgeK, Hector E. Nistazakis, Argyris N. Stassinakis, Christos K. Volos, Vasileios Christofilakis et George S. Tombras. « Mixed Topology of DF Relayed Terrestrial Optical Wireless Links with Generalized Pointing Errors over Turbulence Channels ». Technologies 6, n^o 4 (17 décembre 2018) : 121. http://dx.doi.org/10.3390/technologies6040121.

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This study investigated the outage performance of a terrestrial FSO communication system that uses mixed series and parallel decode-and-forward (DF) relay-assisted (i.e., cooperative diversity) configurations, taking into account the influence of both atmospheric turbulence and pointing error effects. Turbulence-induced optical signal fading is modeled by gamma-gamma or the negative exponential distribution for weak to strong and saturated turbulence conditions, respectively. Additionally, weak to strong non-zero boresight misalignment-induced optical signal fading is modeled by the generalized Beckmann distribution. Under these conditions, an outage analysis of the examined FSO system is performed, in terms of both outage probability and mean outage duration metrics. Thus, fairly accurate closed-form mathematical expressions for both performance metrics are derived, while their corresponding analytical results demonstrate concrete performance and availability improvements for the total FSO system, especially when the number of the connected in parallel DF relays increases. Moreover, the obtained results are verified through the corresponding simulation results.

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Androutsos, Nikolaos A., Hector E. Nistazakis, Efstratios V. Chatzikontis, Argyris N. Stassinakis et George S. Tombras. « Spatial Jitter Influence on the Average BLER Performance of SIMO FSO Links over Atmospheric Turbulence Channels ». Electronics 10, n^o 16 (22 août 2021) : 2033. http://dx.doi.org/10.3390/electronics10162033.

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In the recent years, Free Space Optics (FSO) technology has attracted significant research and commercial interest mostly because of its many advantages in comparison with other radio systems used for point-to-point connections. However, the reliable operation of these systems significantly depends on the conditions of the atmosphere in the area in which the optical beam propagates. The most important of these conditions are atmospheric turbulence and the misalignment between the optical beam and the receiver, which is also known as the pointing errors effect. In this work, in order to obviate the performance mitigation caused by these phenomena, we examined the most widely accepted and one of the most effective techniques, i.e., the implementation of receivers’ diversity. Various metrics have been investigated to evaluate the performance of such systems, but most of them do not take into account that the ultra-fast modern optical communication systems use blocks of bits for the transmission and codes for the detection and/or correction of erroneous bits. Thus, by taking these aspects into account, in this work, we investigated the combined impact of spatial jitter and atmospheric turbulence on the total average block error rate of an optical wireless system with receivers’ diversity. Novel closed-form analytical formulas were derived.

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Chauhan, Sonali, Rajan Miglani, Lavish Kansal, Gurjot Singh Gaba et Mehedi Masud. « Performance Analysis and Enhancement of Free Space Optical Links for Developing State-of-the-Art Smart City Framework ». Photonics 7, n^o 4 (16 décembre 2020) : 132. http://dx.doi.org/10.3390/photonics7040132.

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In this paper, we have investigated and reported the performance of free-space optical (FSO) links operating in adverse atmospheric conditions. Since FSO links share operational similarity with fiber communication; hence, we believe that a cost-effective FSO framework can play a significant role in the transparent integration of high-speed network access backbones with the end-users. Different modulation formats, complemented with spatial diversity techniques, are discussed in this paper to strategize performance optimization of FSO links. Using bit error rate (BER) and signal-to-noise ratio (SNR) as performance metrics, it was found that binary phase-shift keying (BPSK) qualifies as the best technique modulation technique delivering SNR gain of 10 dB over on–off keying (OOK) operating link under similar channel conditions. Further performance optimization was achieved using space diversity reception wherein SNR witnessed a gain of 3 dB gain over the single-channel FSO link. In terms of application, the proposed model can help in developing a citizen-centric smart city ecosystem that can support seamless communication between heterogeneous smart devices.

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Taugourdeau, Simon, Mathilde Dionisi, Mylène Lascoste, Matthieu Lesnoff, Jean Marie Capron, Fréderic Borne, Philippe Borianne et Lionel Julien. « A First Attempt to Combine NIRS and Plenoptic Cameras for the Assessment of Grasslands Functional Diversity and Species Composition ». Agriculture 12, n^o 5 (17 mai 2022) : 704. http://dx.doi.org/10.3390/agriculture12050704.

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Grassland represents more than half of the agricultural land. Numerous metrics (biomass, functional trait, species composition) can be used to describe grassland vegetation and its multiple functions. The measures of these metrics are generally destructive and laborious. Indirect measurements using optical tools are a possible alternative. Some tools have high spatial resolutions (digital camera), and others have high spectral resolutions (Near Infrared Spectrometry NIRS). A plenoptic camera is a multifocal camera that produces clear images at different depths in an image. The objective of this study was to test the interest of combining plenoptic images and NIRS data to characterize different descriptors of two Mediterranean legumes mixtures. On these mixtures, we measured biomass, species biomass, and functional trait diversity. NIRS and plenoptic images were acquired just before the field measurements. The plenoptic images were analyzed using Trainable Weka Segmentation ImageJ to evaluate the percentage of each species in the image. We calculated the average and standard deviation of the different colors (red, green, blue reflectance) in the image. We assessed the percentage of explanation of outputs of the images and NIRS analyses using variance partition and partial least squares. The biomass Trifolium michelianum and Vicia sativa were predicted with more than 50% variability explained. For the other descriptors, the variability explained was lower but nevertheless significant. The percentage variance explained was nevertheless quite low, and further work is required to produce a useable tool, but this work already demonstrates the interest in combining image analysis and NIRS.

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Sessions, W. R., J. S. Reid, A. Benedetti, P. R. Colarco, A. da Silva, S. Lu, T. Sekiyama et al. « Development towards a global operational aerosol consensus : basic climatological characteristics of the International Cooperative for Aerosol Prediction Multi-Model Ensemble (ICAP-MME) ». Atmospheric Chemistry and Physics Discussions 14, n^o 10 (6 juin 2014) : 14933–98. http://dx.doi.org/10.5194/acpd-14-14933-2014.

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Abstract. Over the past several years, there has been a rapid development in the number and quality of global aerosol models intended for operational forecasting use. Indeed, most centers with global numerical weather prediction (NWP) capabilities have some program for aerosol prediction. These aerosol models typically have differences in their underlying meteorology as well as aerosol sources, sinks, microphysics and transformations. However, like similar diversity in aerosol climate models, the aerosol forecast models have fairly similar overall bulk error statistics for aerosol optical thickness (AOT)-one of the few aerosol metrics that is globally available. Experience in climate and weather prediction has shown that in situations such as this where there are several independent models, a multi-model ensemble or consensus will be top performing in many key error metrics. Further, multi-model ensembles provide a highly valuable tool for forecasters attempting to predict severe aerosol events. Here we present the first steps in developing a global multi-model aerosol forecasting ensemble intended for eventual operational and basic research use. Drawing from members of the International Cooperative for Aerosol Prediction (ICAP) latest generation of quasi-operational aerosol models, five day AOT forecasts are analyzed for December 2011 through November 2012 from four institutions: ECMWF, JMA, NASA GSFC, and NRL/FNMOC. For dust, we also include the NOAA NGAC product in our analysis. The Barcelona Supercomputing Centre (NMMC) and UK Met office dust product have also recent become available with ICAP, but have insufficient data to be included in this analysis period. A simple consensus ensemble of member and mean AOT fields for modal species (e.g., fine and coarse mode, and a separate dust ensemble) is used to create the ICAP Multi-Model Ensemble (ICAP-MME). The ICAP-MME is run daily at 0Z for 6 hourly forecasts out to 120 h. Basing metrics on comparisons to 21 regionally representative Aerosol Robotic Network (AERONET) sites, all models generally captured the basic aerosol features of the globe. However, there is an overall AOT low bias among models, particularly for high AOT events. Biomass burning regions have the most diversity in seasonal average AOT. The southern oceans, though low in AOT, nevertheless also have high diversity. In regard to root mean square error, as expected the ICAP-MME placed first over all models worldwide, and was typically first or second in ranking against all models at individual sites. These results are encouraging; as more global operational aerosol models come on line, we expect their inclusion in a robust operational multi-model ensemble will provide valuable aerosol forecasting guidance.

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Phal, Yamuna, Kevin Yeh et Rohit Bhargava. « Design Considerations for Discrete Frequency Infrared Microscopy Systems ». Applied Spectroscopy 75, n^o 9 (20 avril 2021) : 1067–92. http://dx.doi.org/10.1177/00037028211013372.

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Discrete frequency infrared chemical imaging is transforming the practice of microspectroscopy by enabling a diversity of instrumentation and new measurement capabilities. While a variety of hardware implementations have been realized, design considerations that are unique to infrared (IR) microscopes have not yet been compiled in literature. Here, we describe the evolution of IR microscopes, provide rationales for design choices, and catalog some major considerations for each of the optical components in an imaging system. We analyze design choices that use these components to optimize performance, under their particular constraints, while providing illustrative examples. We then summarize a framework to assess the factors that determine an instrument’s performance mathematically. Finally, we provide a validation approach by enumerating performance metrics that can be used to evaluate the capabilities of imaging systems or suitability for specific intended applications. Together, the presented concepts and examples should aid in understanding available instrument configurations, while guiding innovations in design of the next generation of IR chemical imaging spectrometers.

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Odermatt, Daniel, Olaf Danne, Petra Philipson et Carsten Brockmann. « Diversity II water quality parameters from ENVISAT (2002–2012) : a new global information source for lakes ». Earth System Science Data 10, n^o 3 (24 août 2018) : 1527–49. http://dx.doi.org/10.5194/essd-10-1527-2018.

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Abstract. The use of ground sampled water quality information for global studies is limited due to practical and financial constraints. Remote sensing is a valuable means to overcome such limitations and to provide synoptic views of ambient water quality at appropriate spatio-temporal scales. In past years several large data processing efforts were initiated to provide corresponding data sources. The Diversity II water quality dataset consists of several monthly, yearly and 9-year averaged water quality parameters for 340 lakes worldwide and is based on data from the full ENVISAT MERIS operation period (2002–2012). Existing retrieval methods and datasets were selected after an extensive algorithm intercomparison exercise. Chlorophyll-a, total suspended matter, turbidity, coloured dissolved organic matter, lake surface water temperature, cyanobacteria and floating vegetation maps, as well as several auxiliary data layers, provide a generically specified database that can be used for assessing a variety of locally relevant ecosystem properties and environmental problems. For validation and accuracy assessment, we provide matchup comparisons for 24 lakes and a group of reservoirs representing a wide range of bio-optical conditions. Matchup comparisons for chlorophyll-a concentrations indicate mean absolute errors and bias in the order of median concentrations for individual lakes, while total suspended matter and turbidity retrieval achieve significantly better performance metrics across several lake-specific datasets. We demonstrate the use of the products by illustrating and discussing remotely sensed evidence of lake-specific processes and prominent regime shifts documented in the literature. The Diversity II data are available from https://doi.pangaea.de/10.1594/PANGAEA.871462, and Python scripts for their analysis and visualization are provided at https://github.com/odermatt/diversity/.

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He, Xin, et Frank Y. Li. « Metric-Based Cooperative Routing in Multihop Ad Hoc Networks ». Journal of Computer Networks and Communications 2012 (2012) : 1–12. http://dx.doi.org/10.1155/2012/893867.

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Cooperative communication fully leverages the broadcast nature of wireless channels and exploits time/spatial diversity in a distributed manner, thereby achieving significant improvements in system capacity and transmission reliability. Cooperative diversity has been well studied from the physical layer perspective. Thereafter, cooperative MAC design has also drawn much attention recently. However, very little work has addressed cooperation at the routing layer. In this paper, we propose a simple yet efficient scheme for cooperative routing by using cooperative metrics including packet delivery ratio, throughput, and energy consumption efficiency. To make a routing decision based on our scheme, a node needs to first determine whether cooperation on each link is necessary or not, and if necessary, select the optimal cooperative scheme as well as the optimal relay. To do so, we calculate and compare cooperative routing metric values for each potential relay for each different cooperative MAC scheme (C-ARQ and CoopMAC in this study), and further choose the best value and compare it with the noncooperative link metric. Using the final optimal metric value instead of the traditional metric value at the routing layer, new optimal paths are set up in multihop ad hoc networks, by taking into account the cooperative benefits from the MAC layer. The network performance of the cooperative routing solution is demonstrated using a simple network topology.

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Rishmawi, Khaldoun, Chengquan Huang et Xiwu Zhan. « Monitoring Key Forest Structure Attributes across the Conterminous United States by Integrating GEDI LiDAR Measurements and VIIRS Data ». Remote Sensing 13, n^o 3 (27 janvier 2021) : 442. http://dx.doi.org/10.3390/rs13030442.

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Accurate information on the global distribution and the three-dimensional (3D) structure of Earth’s forests is needed to assess forest biomass stocks and to project the future of the terrestrial Carbon sink. In spite of its importance, the 3D structure of forests continues to be the most crucial information gap in the observational archive. The Global Ecosystem Dynamics Investigation (GEDI) Light Detection and Ranging (LiDAR) sensor is providing an unprecedented near-global sampling of tropical and temperate forest structural properties. The integration of GEDI measurements with spatially-contiguous observations from polar orbiting optical satellite data therefore provides a unique opportunity to produce wall-to-wall maps of forests’ 3D structure. Here, we utilized Visible Infrared Imaging Radiometer Suite (VIIRS) annual metrics data to extrapolate GEDI-derived forest structure attributes into 1-km resolution contiguous maps of tree height (TH), canopy fraction cover (CFC), plant area index (PAI), and foliage height diversity (FHD) for the conterminous US (CONUS). The maps were validated using an independent subset of GEDI data. Validation results for TH (r2 = 0.8; RMSE = 3.35 m), CFC (r2 = 0.79; RMSE = 0.09), PAI (r2 = 0.76; RMSE = 0.41), and FHD (r2 = 0.83; RMSE = 0.25) demonstrated the robustness of VIIRS data for extrapolating GEDI measurements across the nation or even over larger areas. The methodology developed through this study may allow multi-decadal monitoring of changes in multiple forest structural attributes using consistent satellite observations acquired by orbiting and forthcoming VIIRS instruments.

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Schutgens, Nick, Andrew M. Sayer, Andreas Heckel, Christina Hsu, Hiren Jethva, Gerrit de Leeuw, Peter J. T. Leonard et al. « An AeroCom–AeroSat study : intercomparison of satellite AOD datasets for aerosol model evaluation ». Atmospheric Chemistry and Physics 20, n^o 21 (30 octobre 2020) : 12431–57. http://dx.doi.org/10.5194/acp-20-12431-2020.

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Abstract. To better understand and characterize current uncertainties in the important observational constraint of climate models of aerosol optical depth (AOD), we evaluate and intercompare 14 satellite products, representing nine different retrieval algorithm families using observations from five different sensors on six different platforms. The satellite products (super-observations consisting of 1∘×1∘ daily aggregated retrievals drawn from the years 2006, 2008 and 2010) are evaluated with AErosol RObotic NETwork (AERONET) and Maritime Aerosol Network (MAN) data. Results show that different products exhibit different regionally varying biases (both under- and overestimates) that may reach ±50 %, although a typical bias would be 15 %–25 % (depending on the product). In addition to these biases, the products exhibit random errors that can be 1.6 to 3 times as large. Most products show similar performance, although there are a few exceptions with either larger biases or larger random errors. The intercomparison of satellite products extends this analysis and provides spatial context to it. In particular, we show that aggregated satellite AOD agrees much better than the spatial coverage (often driven by cloud masks) within the 1∘×1∘ grid cells. Up to ∼50 % of the difference between satellite AOD is attributed to cloud contamination. The diversity in AOD products shows clear spatial patterns and varies from 10 % (parts of the ocean) to 100 % (central Asia and Australia). More importantly, we show that the diversity may be used as an indication of AOD uncertainty, at least for the better performing products. This provides modellers with a global map of expected AOD uncertainty in satellite products, allows assessment of products away from AERONET sites, can provide guidance for future AERONET locations and offers suggestions for product improvements. We account for statistical and sampling noise in our analyses. Sampling noise, variations due to the evaluation of different subsets of the data, causes important changes in error metrics. The consequences of this noise term for product evaluation are discussed.

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Sessions, W. R., J. S. Reid, A. Benedetti, P. R. Colarco, A. da Silva, S. Lu, T. Sekiyama et al. « Development towards a global operational aerosol consensus : basic climatological characteristics of the International Cooperative for Aerosol Prediction Multi-Model Ensemble (ICAP-MME) ». Atmospheric Chemistry and Physics 15, n^o 1 (13 janvier 2015) : 335–62. http://dx.doi.org/10.5194/acp-15-335-2015.

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Abstract. Here we present the first steps in developing a global multi-model aerosol forecasting ensemble intended for eventual operational and basic research use. Drawing from members of the International Cooperative for Aerosol Prediction (ICAP) latest generation of quasi-operational aerosol models, 5-day aerosol optical thickness (AOT) forecasts are analyzed for December 2011 through November 2012 from four institutions: European Centre for Medium-Range Weather Forecasts (ECMWF), Japan Meteorological Agency (JMA), NASA Goddard Space Flight Center (GSFC), and Naval Research Lab/Fleet Numerical Meteorology and Oceanography Center (NRL/FNMOC). For dust, we also include the National Oceanic and Atmospheric Administration-National Geospatial Advisory Committee (NOAA NGAC) product in our analysis. The Barcelona Supercomputing Centre and UK Met Office dust products have also recently become members of ICAP, but have insufficient data to be included in this analysis period. A simple consensus ensemble of member and mean AOT fields for modal species (e.g., fine and coarse mode, and a separate dust ensemble) is used to create the ICAP Multi-Model Ensemble (ICAP-MME). The ICAP-MME is run daily at 00:00 UTC for 6-hourly forecasts out to 120 h. Basing metrics on comparisons to 21 regionally representative Aerosol Robotic Network (AERONET) sites, all models generally captured the basic aerosol features of the globe. However, there is an overall AOT low bias among models, particularly for high AOT events. Biomass burning regions have the most diversity in seasonal average AOT. The Southern Ocean, though low in AOT, nevertheless also has high diversity. With regard to root mean square error (RMSE), as expected the ICAP-MME placed first over all models worldwide, and was typically first or second in ranking against all models at individual sites. These results are encouraging; furthermore, as more global operational aerosol models come online, we expect their inclusion in a robust operational multi-model ensemble will provide valuable aerosol forecasting guidance.

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Alexander, David M., Tamara M. Davis, E. Chaussidon, V. A. Fawcett, Alma X. Gonzalez-Morales, Ting-Wen Lan, Christophe Yèche et al. « The DESI Survey Validation : Results from Visual Inspection of the Quasar Survey Spectra ». Astronomical Journal 165, n^o 3 (22 février 2023) : 124. http://dx.doi.org/10.3847/1538-3881/acacfc.

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Abstract A key component of the Dark Energy Spectroscopic Instrument (DESI) survey validation (SV) is a detailed visual inspection (VI) of the optical spectroscopic data to quantify key survey metrics. In this paper we present results from VI of the quasar survey using deep coadded SV spectra. We show that the majority (≈70%) of the main-survey targets are spectroscopically confirmed as quasars, with ≈16% galaxies, ≈6% stars, and ≈8% low-quality spectra lacking reliable features. A nonnegligible fraction of the quasars are misidentified by the standard spectroscopic pipeline, but we show that the majority can be recovered using post-pipeline “afterburner” quasar-identification approaches. We combine these “afterburners” with our standard pipeline to create a modified pipeline to increase the overall quasar yield. At the depth of the main DESI survey, both pipelines achieve a good-redshift purity (reliable redshifts measured within 3000 km s−1) of ≈99%; however, the modified pipeline recovers ≈94% of the visually inspected quasars, as compared to ≈86% from the standard pipeline. We demonstrate that both pipelines achieve a median redshift precision and accuracy of ≈100 km s−1 and ≈70 km s−1, respectively. We constructed composite spectra to investigate why some quasars are missed by the standard pipeline and find that they are more host-galaxy dominated (i.e., distant analogs of “Seyfert galaxies”) and/or more dust reddened than the standard-pipeline quasars. We also show example spectra to demonstrate the overall diversity of the DESI quasar sample and provide strong-lensing candidates where two targets contribute to a single spectrum.

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Huizing, Geert-Jan, Gabriel Peyré et Laura Cantini. « Optimal transport improves cell–cell similarity inference in single-cell omics data ». Bioinformatics 38, n^o 8 (14 février 2022) : 2169–77. http://dx.doi.org/10.1093/bioinformatics/btac084.

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Abstract Motivation High-throughput single-cell molecular profiling is revolutionizing biology and medicine by unveiling the diversity of cell types and states contributing to development and disease. The identification and characterization of cellular heterogeneity are typically achieved through unsupervised clustering, which crucially relies on a similarity metric. Results We here propose the use of Optimal Transport (OT) as a cell–cell similarity metric for single-cell omics data. OT defines distances to compare high-dimensional data represented as probability distributions. To speed up computations and cope with the high dimensionality of single-cell data, we consider the entropic regularization of the classical OT distance. We then extensively benchmark OT against state-of-the-art metrics over 13 independent datasets, including simulated, scRNA-seq, scATAC-seq and single-cell DNA methylation data. First, we test the ability of the metrics to detect the similarity between cells belonging to the same groups (e.g. cell types, cell lines of origin). Then, we apply unsupervised clustering and test the quality of the resulting clusters. OT is found to improve cell–cell similarity inference and cell clustering in all simulated and real scRNA-seq data, as well as in scATAC-seq and single-cell DNA methylation data. Availability and implementation All our analyses are reproducible through the OT-scOmics Jupyter notebook available at https://github.com/ComputationalSystemsBiology/OT-scOmics. Supplementary information Supplementary data are available at Bioinformatics online.

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Zhang, Lan. « Hybrid QPSO-NNIA2 Algorithm for Multi-Objective Optimization Problem ». International Journal of Pattern Recognition and Artificial Intelligence 33, n^o 08 (25 juin 2019) : 1959025. http://dx.doi.org/10.1142/s0218001419590250.

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To improve the convergence and distribution of a multi-objective optimization algorithm, a hybrid multi-objective optimization algorithm, based on the quantum particle swarm optimization (QPSO) algorithm and adaptive ranks clone and neighbor list-based immune algorithm (NNIA2), is proposed. The contribution of this work is threefold. First, the vicinity distance was used instead of the crowding distance to update the archived optimal solutions in the QPSO algorithm. The archived optimal solutions are updated and maintained by using the dynamic vicinity distance based m-nearest neighbor list in the QPSO algorithm. Secondly, an adaptive dynamic threshold of unfitness function for constraint handling is introduced in the process. It is related to the evolution algebra and the feasible solution. Thirdly, a new metric called the distribution metric is proposed to depict the diversity and distribution of the Pareto optimal. In order to verify the validity and feasibility of the QPSO-NNIA2 algorithm, we compare it with the QPSO, NNIA2, NSGA-II, MOEA/D, and SPEA2 algorithms in solving unconstrained and constrained multi-objective problems. The simulation results show that the QPSO-NNIA2 algorithm achieves superior convergence and superior performance by three metrics compared to other algorithms.

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Nunes, Laura A., Samuel T. Turvey et James Rosindell. « The price of conserving avian phylogenetic diversity : a global prioritization approach ». Philosophical Transactions of the Royal Society B : Biological Sciences 370, n^o 1662 (19 février 2015) : 20140004. http://dx.doi.org/10.1098/rstb.2014.0004.

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The combination of rapid biodiversity loss and limited funds available for conservation represents a major global concern. While there are many approaches for conservation prioritization, few are framed as financial optimization problems. We use recently published avian data to conduct a global analysis of the financial resources required to conserve different quantities of phylogenetic diversity (PD). We introduce a new prioritization metric (ADEPD) that After Downlisting a species gives the Expected Phylogenetic Diversity at some future time. Unlike other metrics, ADEPD considers the benefits to future PD associated with downlisting a species (e.g. moving from Endangered to Vulnerable in the International Union for Conservation of Nature Red List). Combining ADEPD scores with data on the financial cost of downlisting different species provides a cost–benefit prioritization approach for conservation. We find that under worst-case spending $3915 can save 1 year of PD, while under optimal spending $1 can preserve over 16.7 years of PD. We find that current conservation spending patterns are only expected to preserve one quarter of the PD that optimal spending could achieve with the same total budget. Maximizing PD is only one approach within the wider goal of biodiversity conservation, but our analysis highlights more generally the danger involved in uninformed spending of limited resources.

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Shinozuka, Yohei, Pablo E. Saide, Gonzalo A. Ferrada, Sharon P. Burton, Richard Ferrare, Sarah J. Doherty, Hamish Gordon et al. « Modeling the smoky troposphere of the southeast Atlantic : a comparison to ORACLES airborne observations from September of 2016 ». Atmospheric Chemistry and Physics 20, n^o 19 (7 octobre 2020) : 11491–526. http://dx.doi.org/10.5194/acp-20-11491-2020.

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Abstract. In the southeast Atlantic, well-defined smoke plumes from Africa advect over marine boundary layer cloud decks; both are most extensive around September, when most of the smoke resides in the free troposphere. A framework is put forth for evaluating the performance of a range of global and regional atmospheric composition models against observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) airborne mission in September 2016. A strength of the comparison is a focus on the spatial distribution of a wider range of aerosol composition and optical properties than has been done previously. The sparse airborne observations are aggregated into approximately 2∘ grid boxes and into three vertical layers: 3–6 km, the layer from cloud top to 3 km, and the cloud-topped marine boundary layer. Simulated aerosol extensive properties suggest that the flight-day observations are reasonably representative of the regional monthly average, with systematic deviations of 30 % or less. Evaluation against observations indicates that all models have strengths and weaknesses, and there is no single model that is superior to all the others in all metrics evaluated. Whereas all six models typically place the top of the smoke layer within 0–500 m of the airborne lidar observations, the models tend to place the smoke layer bottom 300–1400 m lower than the observations. A spatial pattern emerges, in which most models underestimate the mean of most smoke quantities (black carbon, extinction, carbon monoxide) on the diagonal corridor between 16∘ S, 6∘ E, and 10∘ S, 0∘ E, in the 3–6 km layer, and overestimate them further south, closer to the coast, where less aerosol is present. Model representations of the above-cloud aerosol optical depth differ more widely. Most models overestimate the organic aerosol mass concentrations relative to those of black carbon, and with less skill, indicating model uncertainties in secondary organic aerosol processes. Regional-mean free-tropospheric model ambient single scattering albedos vary widely, between 0.83 and 0.93 compared with in situ dry measurements centered at 0.86, despite minimal impact of humidification on particulate scattering. The modeled ratios of the particulate extinction to the sum of the black carbon and organic aerosol mass concentrations (a mass extinction efficiency proxy) are typically too low and vary too little spatially, with significant inter-model differences. Most models overestimate the carbonaceous mass within the offshore boundary layer. Overall, the diversity in the model biases suggests that different model processes are responsible. The wide range of model optical properties requires further scrutiny because of their importance for radiative effect estimates.

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Butler, Harris K., Mark A. Friend, Kenneth W. Bauer et Trevor J. Bihl. « The effectiveness of using diversity to select multiple classifier systems with varying classification thresholds ». Journal of Algorithms & ; Computational Technology 12, n^o 3 (14 mai 2018) : 187–99. http://dx.doi.org/10.1177/1748301818761132.

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In classification applications, the goal of fusion techniques is to exploit complementary approaches and merge the information provided by these methods to provide a solution superior than any single method. Associated with choosing a methodology to fuse pattern recognition algorithms is the choice of algorithm or algorithms to fuse. Historically, classifier ensemble accuracy has been used to select which pattern recognition algorithms are included in a multiple classifier system. More recently, research has focused on creating and evaluating diversity metrics to more effectively select ensemble members. Using a wide range of classification data sets, methodologies, and fusion techniques, current diversity research is extended by expanding classifier domains before employing fusion methodologies. The expansion is made possible with a unique classification score algorithm developed for this purpose. Correlation and linear regression techniques reveal that the relationship between diversity metrics and accuracy is tenuous and optimal ensemble selection should be based on ensemble accuracy. The strengths and weaknesses of popular diversity metrics are examined in the context of the information they provide with respect to changing classification thresholds and accuracies.

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Levick, Shaun R., Tim Whiteside, David A. Loewensteiner, Mitchel Rudge et Renee Bartolo. « Leveraging TLS as a Calibration and Validation Tool for MLS and ULS Mapping of Savanna Structure and Biomass at Landscape-Scales ». Remote Sensing 13, n^o 2 (13 janvier 2021) : 257. http://dx.doi.org/10.3390/rs13020257.

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Savanna ecosystems are challenging to map and monitor as their vegetation is highly dynamic in space and time. Understanding the structural diversity and biomass distribution of savanna vegetation requires high-resolution measurements over large areas and at regular time intervals. These requirements cannot currently be met through field-based inventories nor spaceborne satellite remote sensing alone. UAV-based remote sensing offers potential as an intermediate scaling tool, providing acquisition flexibility and cost-effectiveness. Yet despite the increased availability of lightweight LiDAR payloads, the suitability of UAV-based LiDAR for mapping and monitoring savanna 3D vegetation structure is not well established. We mapped a 1 ha savanna plot with terrestrial-, mobile- and UAV-based laser scanning (TLS, MLS, and ULS), in conjunction with a traditional field-based inventory (n = 572 stems > 0.03 m). We treated the TLS dataset as the gold standard against which we evaluated the degree of complementarity and divergence of structural metrics from MLS and ULS. Sensitivity analysis showed that MLS and ULS canopy height models (CHMs) did not differ significantly from TLS-derived models at spatial resolutions greater than 2 m and 4 m respectively. Statistical comparison of the resulting point clouds showed minor over- and under-estimation of woody canopy cover by MLS and ULS, respectively. Individual stem locations and DBH measurements from the field inventory were well replicated by the TLS survey (R2 = 0.89, RMSE = 0.024 m), which estimated above-ground woody biomass to be 7% greater than field-inventory estimates (44.21 Mg ha−1 vs 41.08 Mg ha−1). Stem DBH could not be reliably estimated directly from the MLS or ULS, nor indirectly through allometric scaling with crown attributes (R2 = 0.36, RMSE = 0.075 m). MLS and ULS show strong potential for providing rapid and larger area capture of savanna vegetation structure at resolutions suitable for many ecological investigations; however, our results underscore the necessity of nesting TLS sampling within these surveys to quantify uncertainty. Complementing large area MLS and ULS surveys with TLS sampling will expand our options for the calibration and validation of multiple spaceborne LiDAR, SAR, and optical missions.

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Yu, Hai-Tao. « Optimize What You Evaluate With : Search Result Diversification Based on Metric Optimization ». Proceedings of the AAAI Conference on Artificial Intelligence 36, n^o 9 (28 juin 2022) : 10399–407. http://dx.doi.org/10.1609/aaai.v36i9.21282.

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Most of the existing methods for search result diversification (SRD) appeal to the greedy strategy for generating diversified results, which is formulated as a sequential process of selecting documents one-by-one, and the locally optimal choice is made at each round. Unfortunately, this strategy suffers from the following shortcomings: (1) Such a one-by-one selection process is rather time-consuming for both training and inference. (2) It works well on the premise that the preceding choices are optimal or close to the optimal solution. (3) The mismatch between the objective function used in training and the final evaluation measure used in testing has not been taken into account. We propose a novel framework through direct metric optimization for SRD (referred to as MO4SRD) based on the score-and-sort strategy. Specifically, we represent the diversity score of each document that determines its rank position based on a probability distribution. These distributions over scores naturally give rise to expectations over rank positions. Armed with this advantage, we can get the differentiable variants of the widely used diversity metrics. Thanks to this, we are able to directly optimize the evaluation measure used in testing. Moreover, we have devised a novel probabilistic neural scoring function. It jointly scores candidate documents by taking into account both cross-document interaction and permutation equivariance, which makes it possible to generate a diversified ranking via a simple sorting. The experimental results on benchmark collections show that the proposed method achieves significantly improved performance over the state-of-the-art results.

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Varotsos, George K., Hector E. Nistazakis, Konstantinos Aidinis, Fadi Jaber, Mohd Nasor et Kanhira Kadavath Mujeeb Rahman. « Error Performance Estimation of Modulated Retroreflective Transdermal Optical Wireless Links with Diversity under Generalized Pointing Errors ». Telecom 2, n^o 2 (1 avril 2021) : 167–80. http://dx.doi.org/10.3390/telecom2020011.

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Recent developments in both optical wireless communication (OWC) systems and implanted medical devices (IMDs) have introduced transdermal optical wireless (TOW) technology as a viable candidate for extremely high-speed in-body to out-of-body wireless data transmissions, which are growing in demand for many vital biomedical applications, including telemetry with medical implants, health monitoring, neural recording and prostheses. Nevertheless, this emerging communication modality is primarily hindered by skin-induced attenuation of the propagating signal bit carrier along with its stochastic misalignment-induced fading. Thus, by considering a typical modulated retroreflective (MRR) TOW system with spatial diversity and optimal combining (OC) for signal reception in this work, we focus, for the first time in the MRR TOW literature, on the stochastic nature of generalized pointing errors with non-zero boresight (NZB). Specifically, under these circumstances, novel analytical mathematical expressions were derived for the total average bit error rate (BER) of various system configurations. Their results revealed significant outage performance enhancements when spatial diversity was utilized. Moreover, taking into consideration the total transdermal pathloss along with the effects of stochastic NZB pointing errors, the critical average signal-to-noise ratio (SNR) metric was evaluated for typical power spectral-density values.

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Bos, S. P., S. Vievard, M. J. Wilby, F. Snik, J. Lozi, O. Guyon, B. R. M. Norris et al. « On-sky verification of Fast and Furious focal-plane wavefront sensing : Moving forward toward controlling the island effect at Subaru/SCExAO ». Astronomy & ; Astrophysics 639 (juillet 2020) : A52. http://dx.doi.org/10.1051/0004-6361/202037910.

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Context. High-contrast imaging (HCI) observations of exoplanets can be limited by the island effect (IE). The IE occurs when the main wavefront sensor (WFS) cannot measure sharp phase discontinuities across the telescope’s secondary mirror support structures (also known as spiders). On the current generation of telescopes, the IE becomes a severe problem when the ground wind speed is below a few meters per second. During these conditions, the air that is in close contact with the spiders cools down and is not blown away. This can create a sharp optical path length difference between light passing on opposite sides of the spiders. Such an IE aberration is not measured by the WFS and is therefore left uncorrected. This is referred to as the low-wind effect (LWE). The LWE severely distorts the point spread function (PSF), significantly lowering the Strehl ratio and degrading the contrast. Aims. In this article, we aim to show that the focal-plane wavefront sensing (FPWFS) algorithm, Fast and Furious (F&F), can be used to measure and correct the IE/LWE. The F&F algorithm is a sequential phase diversity algorithm and a software-only solution to FPWFS that only requires access to images of non-coronagraphic PSFs and control of the deformable mirror. Methods. We deployed the algorithm on the SCExAO HCI instrument at the Subaru Telescope using the internal near-infrared camera in H-band. We tested with the internal source to verify that F&F can correct a wide variety of LWE phase screens. Subsequently, F&F was deployed on-sky to test its performance with the full end-to-end system and atmospheric turbulence. The performance of the algorithm was evaluated by two metrics based on the PSF quality: (1) the Strehl ratio approximation (SRA), and (2) variance of the normalized first Airy ring (VAR). The VAR measures the distortion of the first Airy ring, and is used to quantify PSF improvements that do not or barely affect the PSF core (e.g., during challenging atmospheric conditions). Results. The internal source results show that F&F can correct a wide range of LWE phase screens. Random LWE phase screens with a peak-to-valley wavefront error between 0.4 μm and 2 μm were all corrected to a SRA > 90% and an VAR ⪅ 0.05. Furthermore, the on-sky results show that F&F is able to improve the PSF quality during very challenging atmospheric conditions (1.3–1.4″seeing at 500 nm). Closed-loop tests show that F&F is able to improve the VAR from 0.27–0.03 and therefore significantly improve the symmetry of the PSF. Simultaneous observations of the PSF in the optical (λ = 750 nm, Δλ = 50 nm) show that during these tests we were correcting aberrations common to the optical and NIR paths within SCExAO. We could not conclusively determine if we were correcting the LWE and/or (quasi-)static aberrations upstream of SCExAO. Conclusions. The F&F algorithm is a promising focal-plane wavefront sensing technique that has now been successfully tested on-sky. Going forward, the algorithm is suitable for incorporation into observing modes, which will enable PSFs of higher quality and stability during science observations.

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Morelli, Federico, Fabio Pruscini, Riccardo Santolini, Paolo Perna, Yanina Benedetti et Davide Sisti. « Landscape heterogeneity metrics as indicators of bird diversity : Determining the optimal spatial scales in different landscapes ». Ecological Indicators 34 (novembre 2013) : 372–79. http://dx.doi.org/10.1016/j.ecolind.2013.05.021.

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Liu, Yi, Jun Guo, Huaiwei Sun, Wei Zhang, Yueran Wang et Jianzhong Zhou. « Multiobjective Optimal Algorithm for Automatic Calibration of Daily Streamflow Forecasting Model ». Mathematical Problems in Engineering 2016 (2016) : 1–13. http://dx.doi.org/10.1155/2016/8215308.

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Single-objection function cannot describe the characteristics of the complicated hydrologic system. Consequently, it stands to reason that multiobjective functions are needed for calibration of hydrologic model. The multiobjective algorithms based on the theory of nondominate are employed to solve this multiobjective optimal problem. In this paper, a novel multiobjective optimization method based on differential evolution with adaptive Cauchy mutation and Chaos searching (MODE-CMCS) is proposed to optimize the daily streamflow forecasting model. Besides, to enhance the diversity performance of Pareto solutions, a more precise crowd distance assigner is presented in this paper. Furthermore, the traditional generalized spread metric (SP) is sensitive with the size of Pareto set. A novel diversity performance metric, which is independent of Pareto set size, is put forward in this research. The efficacy of the new algorithm MODE-CMCS is compared with the nondominated sorting genetic algorithm II (NSGA-II) on a daily streamflow forecasting model based on support vector machine (SVM). The results verify that the performance of MODE-CMCS is superior to the NSGA-II for automatic calibration of hydrologic model.

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Bender Ignacio, Rachel A., Sayan Dasgupta, Terry Stevens-Ayers, Tomasz Kula, Joshua A. Hill, Stephanie J. Lee, Marco Mielcarek, Ann Duerr, Stephen J. Elledge et Michael Boeckh. « Comprehensive viromewide antibody responses by systematic epitope scanning after hematopoietic cell transplantation ». Blood 134, n^o 6 (8 août 2019) : 503–14. http://dx.doi.org/10.1182/blood.2019897405.

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Abstract Further insight into humoral viral immunity after hematopoietic cell transplantation (HCT) could have potential impact on donor selection or monitoring of patients. Currently, estimation of humoral immune recovery is inferred from lymphocyte counts or immunoglobulin levels and does not address vulnerability to specific viral infections. We interrogated the viral antibody repertoire before and after HCT using a novel serosurvey (VirScan) that detects immunoglobulin G responses to 206 viruses. We performed VirScan on cryopreserved serum from pre-HCT and 30, 100, and 365 days after myeloablative HCT from 37 donor-recipient pairs. We applied ecologic metrics (α- and β-diversity) and evaluated predictors of metrics and changes over time. Donor age and donor/recipient cytomegalovirus (CMV) serostatus and receipt systemic glucocorticoids were most strongly associated with VirScan metrics at day 100. Other clinical characteristics, including pre-HCT treatment and conditioning, did not affect antiviral repertoire metrics. The recipient repertoire was most similar (pairwise β-diversity) to that of donor at day 100, but more similar to pre-HCT self by day 365. Gain or loss of epitopes to common viruses over the year post-HCT differed by donor and recipient pre-HCT serostatus, with highest gains in naive donors to seropositive recipients for several human herpesviruses and adenoviruses. We used VirScan to highlight contributions of donor and recipient to antiviral humoral immunity and evaluate longitudinal changes. This work builds a foundation to test whether such systematic profiling could serve as a biomarker of immune reconstitution, predict clinical events after HCT, or help refine selection of optimal donors.

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Bosco, G., P. Poggiolini, M. Visintin, Li Liangchuan et Chen Ming. « New Branch Metrics for MLSE Receivers Based on Polarization Diversity for PMD Mitigation ». Journal of Lightwave Technology 27, n^o 21 (novembre 2009) : 4793–803. http://dx.doi.org/10.1109/jlt.2009.2026720.

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Polley, H., Chenghai Yang, Brian Wilsey et Philip Fay. « Spectral Heterogeneity Predicts Local-Scale Gamma and Beta Diversity of Mesic Grasslands ». Remote Sensing 11, n^o 4 (23 février 2019) : 458. http://dx.doi.org/10.3390/rs11040458.

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Plant species diversity is an important metric of ecosystem functioning, but field assessments of diversity are constrained in number and spatial extent by labor and other expenses. We tested the utility of using spatial heterogeneity in the remotely-sensed reflectance spectrum of grassland canopies to model both spatial turnover in species composition and abundances (β diversity) and species diversity at aggregate spatial scales (γ diversity). Shannon indices of γ and β diversity were calculated from field measurements of the number and relative abundances of plant species at each of two spatial grains (0.45 m2 and 35.2 m2) in mesic grasslands in central Texas, USA. Spectral signatures of reflected radiation at each grain were measured from ground-level or an unmanned aerial vehicle (UAV). Partial least squares regression (PLSR) models explained 59–85% of variance in γ diversity and 68–79% of variance in β diversity using spatial heterogeneity in canopy optical properties. Variation in both γ and β diversity were associated most strongly with heterogeneity in reflectance in blue (350–370 nm), red (660–770 nm), and near infrared (810–1050 nm) wavebands. Modeled diversity was more sensitive by a factor of three to a given level of spectral heterogeneity when derived from data collected at the small than larger spatial grain. As estimated from calibrated PLSR models, β diversity was greater, but γ diversity was smaller for restored grassland on a lowland clay than upland silty clay soil. Both γ and β diversity of grassland can be modeled by using spatial heterogeneity in vegetation optical properties provided that the grain of reflectance measurements is conserved.

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Jensen, Evelyn L., Arne Ø. Mooers, Adalgisa Caccone et Michael A. Russello. « I-HEDGE : determining the optimum complementary sets of taxa for conservation using evolutionary isolation ». PeerJ 4 (23 août 2016) : e2350. http://dx.doi.org/10.7717/peerj.2350.

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In the midst of the current biodiversity crisis, conservation efforts might profitably be directed towards ensuring that extinctions do not result in inordinate losses of evolutionary history. Numerous methods have been developed to evaluate the importance of species based on their contribution to total phylogenetic diversity on trees and networks, but existing methods fail to take complementarity into account, and thus cannot identify the best order or subset of taxa to protect. Here, we develop a novel iterative calculation of the heightened evolutionary distinctiveness and globally endangered metric (I-HEDGE) that produces the optimal ranked list for conservation prioritization, taking into account complementarity and based on both phylogenetic diversity and extinction probability. We applied this metric to a phylogenetic network based on mitochondrial control region data from extant and recently extinct giant Galápagos tortoises, a highly endangered group of closely related species. We found that the restoration of two extinct species (a project currently underway) will contribute the greatest gain in phylogenetic diversity, and present an ordered list of rankings that is the optimum complementarity set for conservation prioritization.

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Shi, Yun, et Mark von Itzstein. « How Size Matters : Diversity for Fragment Library Design ». Molecules 24, n^o 15 (5 août 2019) : 2838. http://dx.doi.org/10.3390/molecules24152838.

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Fragment-based drug discovery (FBDD) has become a major strategy to derive novel lead candidates for various therapeutic targets, as it promises efficient exploration of chemical space by employing fragment-sized (MW < 300) compounds. One of the first challenges in implementing a FBDD approach is the design of a fragment library, and more specifically, the choice of its size and individual members. A diverse set of fragments is required to maximize the chances of discovering novel hit compounds. However, the exact diversity of a certain collection of fragments remains underdefined, which hinders direct comparisons among different selections of fragments. Based on structural fingerprints, we herein introduced quantitative metrics for the structural diversity of fragment libraries. Structures of commercially available fragments were retrieved from the ZINC database, from which libraries with sizes ranging from 100 to 100,000 compounds were selected. The selected libraries were evaluated and compared quantitatively, resulting in interesting size-diversity relationships. Our results demonstrated that while library size does matter for its diversity, there exists an optimal size for structural diversity. It is also suggested that such quantitative measures can guide the design of diverse fragment libraries under different circumstances.

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Karakolis, Evangelos, Panagiotis Kokkinakos et Dimitrios Askounis. « Provider Fairness for Diversity and Coverage in Multi-Stakeholder Recommender Systems ». Applied Sciences 12, n^o 10 (14 mai 2022) : 4984. http://dx.doi.org/10.3390/app12104984.

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Nowadays, recommender systems (RS) are no longer evaluated only for the accuracy of their recommendations. Instead, there is a requirement for other metrics (e.g., coverage, diversity, serendipity) to be taken into account as well. In this context, the multi-stakeholder RS paradigm (MSRS) has gained significant popularity, as it takes into consideration all beneficiaries involved, from item providers to simple users. In this paper, the goal is to provide fair recommendations across item providers in terms of diversity and coverage for users to whom each provider’s items are recommended. This is achieved by following the methodology provided by the literature for solving the recommendation problem as an optimization problem under constraints for coverage and diversity. As the constraints for diversity are quadratic and cannot be solved in sufficient time (NP-Hard problem), we propose a heuristic approach that provides solutions very close to the optimal one, as the proposed approach in the literature for solving diversity constraints was too generic. As a next step, we evaluate the results and identify several weaknesses in the problem formulation as provided in the literature. To this end, we introduce new formulations for diversity and provide a new heuristic approach for the solution of the new optimization problem.

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Greffier, Florian, Valérie Muzet, Vincent Boucher, Fabrice Fournela, Laure Lebouc et Sébastien Liandrat. « Influence of Pavement Heterogeneity and Observation Angle on Lighting Design : Study with New Metrics ». Sustainability 13, n^o 21 (25 octobre 2021) : 11789. http://dx.doi.org/10.3390/su132111789.

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Optimization of lighting installations should be a priority in order to reduce energy consumption and obtrusive light while providing optimal visibility conditions for road users. For the design of lighting installations, it is assumed that the road has homogeneous photometric characteristics and only one viewing angle is used. There are often significant differences between the design of lighting installations and their actual performance. In order to examine whether these differences are due to the photometry of the road, this study proposes metrics to assess the influence of road heterogeneity and observation angle. These metrics have been used on many measurements conducted on site and in the laboratory for different pavements. A calculation engine has been developed to realize road lighting design with several r-tables in the same calculation or for different observation angles. Thus, this study shows that a root mean squared deviation (RMSD) calculation, including average luminance and uniformities associated with different r-tables, is directly correlated to a normalized root mean squared deviation (NRMSD) calculation between these r-tables. With these proposed metrics it is possible to optimize lighting installation while taking into account different types of urban surfaces and the diversity of users.

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Nicholls, Rory, et Antonio Torija Martinez. « An investigation into the impact of unmanned aerial vehicles on soundscape perception in urban and rural environments ». INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, n^o 6 (1 août 2021) : 577–88. http://dx.doi.org/10.3397/in-2021-1570.

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It is predicted that urban air mobility, including the use of small to medium sized unmanned aerial vehicle (UAV) delivery systems, will be introduced into cities across the globe within the next 15 years. It is known, however, that noise is one of the main limiting factors for the wider adoption of these vehicles. Neither the metrics nor the methods used for conventional aircraft seem to be optimal for this novel source of noise. This research will aid in developing suitable psychoacoustic methodologies and metrics, specifically designed to quantify community noise impact of these vehicles. This paper describes a psychoacoustic experiment used to gather participant responses to UAV sound recordings, both isolated and with typical background noise in a diversity of soundscapes. Results from this psychoacoustic experiment will be used to correlate perceptions of UAV noise with objective sound quality metrics, and build new regression relationships that could describe the impact of a given UAV on the perception of soundscape environments. Future extension to the research may include evaluating the differences in psychoacoustic responses when introducing more accurate reproduction methods, such as virtual reality systems, and how these could be incorporated into a standardised human response measurement procedure.

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Kero, Katja, Niina Hieta, Teemu Kallonen, Anne Ahtikoski, Hanna K. Laine, Jaana Rautava et Eveliina Munukka. « Optimal sampling and analysis methods for clinical diagnostics of vaginal microbiome ». European Journal of Clinical Microbiology & ; Infectious Diseases 42, n^o 2 (10 janvier 2023) : 201–8. http://dx.doi.org/10.1007/s10096-022-04545-x.

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AbstractNext-generation sequencing-based microbiological analysis is a complex way to profile vaginal microbiome samples since each step affects the results gained. Methodologies for sample collection lack golden standards. We compared Puritan DNA/RNA swab (PS) and Copan FLOQ swab (CS) and provided consistent and reliable microbiome profiles analyzed by 16S rRNA gene sequencing. We collected two consecutive vaginal samples utilizing PS with room temperature storing and CS with instant freezing from 26 women. Variable region 4 of bacterial 16S rRNA gene was amplified with single PCR by custom-designed dual-indexed primers and sequenced with Illumina MiSeq system. Read quality control, operational taxonomic unit tables, and alpha and beta diversities analysis were performed, and community richness, diversity, and evenness were evaluated and compared between the two samplings and tests. Nineteen sample pairs produced detectable, intact DNA during the extraction protocol and/or further microbial profiles. Alpha bacterial diversity indices were independent on the collection protocol. No significant statistical differences were found in the measured beta diversity metrics between the collection methods. Of the women, 43% had Lactobacillus-dominated vaginal microbiome profile despite of collection method. Previously reported important vaginal microbiome phyla Actinobacteria, Bacteroidetes, Firmicutes, Fusobacteria, and Proteobacteria were present in the sample set although their relative abundances varied among individuals. PS and CS enable constant vaginal microbiota sampling. The PS method with no need for instant freezing is suitable for on-site collections at clinics. Furthermore, it seems to be possible to take two samples instead of one with constant microbiological results.

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Supraja, V., P. Nageswara Rao et M. N. Giriprasad. « Quality Assessment of Ambulatory Electrocardiogram Signals by Noise Detection using Optimal Binary Classification ». International Journal on Recent and Innovation Trends in Computing and Communication 10, n^o 10 (31 octobre 2022) : 91–108. http://dx.doi.org/10.17762/ijritcc.v10i10.5739.

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In order to improve the diagnostic capability in Ambulatory Electrocardiogram signal and to reduce the noise signal impacts, there is a need for more robust models in place. In terms of improvising to the existing solutions, this article explores a novel binary classifier that learns from the features optimized by fusion of diversity assessment measures, which performs Quality Assessment of Ambulatory Electrocardiogram Signals (QAAES) by Noise Detection. The performance of the proposed model QAAES has been scaled by comparing it with contemporary models. Concerning performance analysis, the 10-fold cross-validation has been carried on a benchmark dataset. The results obtained from experiments carried on proposed and other contemporary models for cross-validation metrics have been compared to signify the sensitivity, specificity, and noise detection accuracy.

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Xing, Lining, Rui Wu, Jiaxing Chen et Jun Li. « Handling Irregular Many-Objective Optimization Problems via Performing Local Searches on External Archives ». Mathematics 11, n^o 1 (20 décembre 2022) : 10. http://dx.doi.org/10.3390/math11010010.

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Adaptive weight-vector adjustment has been explored to compensate for the weakness of the evolutionary many-objective algorithms based on decomposition in solving problems with irregular Pareto-optimal fronts. One essential issue is that the distribution of previously visited solutions likely mismatches the irregular Pareto-optimal front, and the weight vectors are misled towards inappropriate regions. The fact above motivated us to design a novel many-objective evolutionary algorithm by performing local searches on an external archive, namely, LSEA. Specifically, the LSEA contains a new selection mechanism without weight vectors to alleviate the adverse effects of inappropriate weight vectors, progressively improving both the convergence and diversity of the archive. The solutions in the archive also feed back the weight-vector adjustment. Moreover, the LSEA selects a solution with good diversity but relatively poor convergence from the archive and then perturbs the decision variables of the selected solution one by one to search for solutions with better diversity and convergence. At last, the LSEA is compared with five baseline algorithms in the context of 36 widely-used benchmarks with irregular Pareto-optimal fronts. The comparison results demonstrate the competitive performance of the LSEA, as it outperforms the five baselines on 22 benchmarks with respect to metric hypervolume.

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Bouchard, Cindy, Étienne Lord, Nathalie Tessier et François-Joseph Lapointe. « Applying novel connectivity networks to wood turtle populations to provide comprehensive conservation management strategies for species at risk ». PLOS ONE 17, n^o 8 (12 août 2022) : e0271797. http://dx.doi.org/10.1371/journal.pone.0271797.

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Genetic diversity within and among populations is frequently used in prioritization processes to rank populations based on their vulnerability or distinctiveness, however, connectivity and gene flow are rarely considered within these frameworks. Using a wood turtle (Glyptemys insculpta) population graph, we introduce BRIDES as a new tool to evaluate populations for conservation purpose without focusing solely on individual nodes. BRIDES characterizes different types of shortest paths among the nodes of a subgraph and compares the shortest paths among the same nodes in a complete network. The main objectives of this study were to (1) introduce a BRIDES selection process to assist conservation biologists in the prioritization of populations, and (2) use different centrality indices and node removal statistics to compare BRIDES results and assess gene flow among wood turtle populations. We constructed six population subgraphs and used a stepwise selection algorithm to choose the optimal number of additional nodes, representing different populations, required to maximize network connectivity under different weighting schemes. Our results demonstrate the robustness of the BRIDES selection process for a given scenario, while inconsistencies were observed among node-based metrics. Results showed repeated selection of certain wood turtle populations, which could have not been predicted following only genetic diversity and distinctiveness estimation, node-based metrics and node removal analysis. Contrary to centrality measures focusing on static networks, BRIDES allowed for the analysis of evolving networks. To our knowledge, this study is the first to apply graph theory for turtle conservation genetics. We show that population graphs can reveal complex gene flow dynamics and population resiliency to local extinction. As such, BRIDES offers an interesting complement to node-based metrics and node removal to better understand the global processes at play when addressing population prioritization frameworks.

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Nuh, Jamal Abdullahi, Tieng Wei Koh, Salmi Baharom, Mohd Hafeez Osman et Si Na Kew. « Performance Evaluation Metrics for Multi-Objective Evolutionary Algorithms in Search-Based Software Engineering : Systematic Literature Review ». Applied Sciences 11, n^o 7 (31 mars 2021) : 3117. http://dx.doi.org/10.3390/app11073117.

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Many recent studies have shown that various multi-objective evolutionary algorithms have been widely applied in the field of search-based software engineering (SBSE) for optimal solutions. Most of them either focused on solving newly re-formulated problems or on proposing new approaches, while a number of studies performed reviews and comparative studies on the performance of proposed algorithms. To evaluate such performance, it is necessary to consider a number of performance metrics that play important roles during the evaluation and comparison of investigated algorithms based on their best-simulated results. While there are hundreds of performance metrics in the literature that can quantify in performing such tasks, there is a lack of systematic review conducted to provide evidence of using these performance metrics, particularly in the software engineering problem domain. In this paper, we aimed to review and quantify the type of performance metrics, number of objectives, and applied areas in software engineering that reported in primary studies—this will eventually lead to inspiring the SBSE community to further explore such approaches in depth. To perform this task, a formal systematic review protocol was applied for planning, searching, and extracting the desired elements from the studies. After considering all the relevant inclusion and exclusion criteria for the searching process, 105 relevant articles were identified from the targeted online databases as scientific evidence to answer the eight research questions. The preliminary results show that remarkable studies were reported without considering performance metrics for the purpose of algorithm evaluation. Based on the 27 performance metrics that were identified, hypervolume, inverted generational distance, generational distance, and hypercube-based diversity metrics appear to be widely adopted in most of the studies in software requirements engineering, software design, software project management, software testing, and software verification. Additionally, there are increasing interest in the community in re-formulating many objective problems with more than three objectives, yet, currently are dominated in re-formulating two to three objectives.

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Ebel, Brian A., Joseph W. Wagenbrenner, Alicia M. Kinoshita et Kevin D. Bladon. « Hydrologic recovery after wildfire : A framework of approaches, metrics, criteria, trajectories, and timescales ». Journal of Hydrology and Hydromechanics 70, n^o 4 (16 novembre 2022) : 388–400. http://dx.doi.org/10.2478/johh-2022-0033.

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Abstract Deviations in hydrologic processes due to wildfire can alter streamflows across the hydrograph, spanning peak flows to low flows. Fire-enhanced changes in hydrologic processes, including infiltration, interception, and evapotranspiration, and the resulting streamflow responses can affect water supplies, through effects on the quantity, quality, and timing of water availability. Post-fire shifts in hydrologic processes can also alter the timing and magnitude of floods and debris flows. The duration of hydrologic deviations from a pre-fire condition or function, sometimes termed hydrologic recovery, is a critical concern for land, water, and emergency managers. We reviewed and summarized terminology and approaches for defining and assessing hydrologic recovery after wildfire, focusing on statistical and functional definitions. We critically examined advantages and drawbacks of current recovery assessment methods, outline challenges to determining recovery, and call attention to selected opportunities for advancement of post-fire hydrologic recovery assessment. Selected challenges included hydroclimatic variability, post-fire land management, and spatial and temporal variability. The most promising opportunities for advancing assessment of hydrologic recovery include: (1) combining statistical and functional recovery approaches, (2) using a greater diversity of post-fire observations complemented with hydrologic modeling, and (3) defining optimal assemblages of recovery metrics and criteria for common hydrologic concerns and regions.

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Zeltni, Kamel, Souham Meshoul et Heyam H. Al-Baity. « On the Convergence and Diversity of Pareto Fronts Using Swarm Intelligence Metaheuristics for Constrained Search Space ». International Journal of Swarm Intelligence Research 9, n^o 1 (janvier 2018) : 20–38. http://dx.doi.org/10.4018/ijsir.2018010102.

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This article reviews existing constraint-handling techniques then presents a new design for Swarm Intelligence Metaheuristics (SIM) to deal with constrained multi-objective optimization problems (CMOPs). This new design aims to investigate potential effects of leader concepts that characterize the dynamic of SIM in the hope to help the population to reach Pareto optimal solutions in a constrained search space. The new leader-based constraint handling mechanism is incorporated in Constrained Multi-Objective Cuckoo Search (C-MOCS) and Constrained Multi-Objective Particle Swarm Optimization (C-MOPSO) as specific instances of a more general class of SIMs. The experimental results are carried out using a set of six well-known test functions and two performance metrics. The convergence and diversity of C-MOCS and C-MOPSO are analysed and compared to the well-known Multi-Objective Evolutionary Algorithm (MOEA) NSGA-II and discussed based on the obtained results.

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Wang, Yong, Kuichao Li et Gai-Ge Wang. « Combining Key-Points-Based Transfer Learning and Hybrid Prediction Strategies for Dynamic Multi-Objective Optimization ». Mathematics 10, n^o 12 (17 juin 2022) : 2117. http://dx.doi.org/10.3390/math10122117.

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Dynamic multi-objective optimization problems (DMOPs) have been of interest to many researchers. These are problems in which the environment changes during the evolutionary process, such as the Pareto-optimal set (POS) or the Pareto-optimal front (POF). This kind of problem imposes more challenges and difficulties for evolutionary algorithms, mainly because it demands population to track the changing POF efficiently and accurately. In this paper, we propose a new approach combining key-points-based transfer learning and hybrid prediction strategies (KPTHP). In particular, the transfer process combines predictive strategy with obtaining anticipated key points depending on the previous moments to acquire the optimal individuals at the new instance during the evolution. Additionally, center-point-based prediction is used to complement transfer learning to comprehensively generate initial populations. KPTHP and six state-of-the-art algorithms are tested on various test functions for MIGD, DMIGD, MMS, and HVD metrics. KPTHP obtains superior results on most of the tested functions, which shows that our algorithm performs excellently in both convergence and diversity, with more competitiveness in addressing dynamic problems.

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Bhaladhare, Pawan R., et Devesh C. Jinwala. « A Clustering Approach for the l-Diversity Model in Privacy Preserving Data Mining Using Fractional Calculus-Bacterial Foraging Optimization Algorithm ». Advances in Computer Engineering 2014 (16 septembre 2014) : 1–12. http://dx.doi.org/10.1155/2014/396529.

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In privacy preserving data mining, the l-diversity and k-anonymity models are the most widely used for preserving the sensitive private information of an individual. Out of these two, l-diversity model gives better privacy and lesser information loss as compared to the k-anonymity model. In addition, we observe that numerous clustering algorithms have been proposed in data mining, namely, k-means, PSO, ACO, and BFO. Amongst them, the BFO algorithm is more stable and faster as compared to all others except k-means. However, BFO algorithm suffers from poor convergence behavior as compared to other optimization algorithms. We also observed that the current literature lacks any approaches that apply BFO with l-diversity model to realize privacy preservation in data mining. Motivated by this observation, we propose here an approach that uses fractional calculus (FC) in the chemotaxis step of the BFO algorithm. The FC is used to boost the computational performance of the algorithm. We also evaluate our proposed FC-BFO and BFO algorithms empirically, focusing on information loss and execution time as vital metrics. The experimental evaluation shows that our proposed FC-BFO algorithm derives an optimal cluster as compared to the original BFO algorithm and existing clustering algorithms.

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Liao, Qixiang, Zheng Sheng, Hanqing Shi, Lei Zhang, Lesong Zhou, Wei Ge et Zhiyong Long. « A Comparative Study on Evolutionary Multi-objective Optimization Algorithms Estimating Surface Duct ». Sensors 18, n^o 12 (14 décembre 2018) : 4428. http://dx.doi.org/10.3390/s18124428.

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The problem of atmospheric duct inversion is usually solved as a single objective optimization problem. Based on ground-based Global Positioning System (GPS) phase delay and propagation loss, this paper develops a multi-objective method including the effect of source frequency and receiving antenna height. The diversity and convergence of solution sets are evaluated for seven multi-objective evolutionary algorithms with three performance metrics: Hypervolume (HV), Inverted Generational Distance (IGD), and the averaged Hausdorff distance (Δ2). The inversion results are compared with the simulation results, and the experimental comparison is conducted on three groups of test situations. The results demonstrate that the ranking of algorithm performance varies because of the different methods used to calculate performance metrics. Moreover, when the algorithms show overwhelming performance using performance metrics, the inversion result is not more close to the real value. In the comparison of computational experiments, it was found that, as the retrieved parameter dimension increases, the inversion result becomes more unstable. When the observed data are sufficient, the inversion result seems to be improved.

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Wu, Qiong, Zhaoyi Li, Changbao Yang, Hongqing Li, Liwei Gong et Fengxiang Guo. « On the Scale Effect of Relationship Identification between Land Surface Temperature and 3D Landscape Pattern : The Application of Random Forest ». Remote Sensing 14, n^o 2 (7 janvier 2022) : 279. http://dx.doi.org/10.3390/rs14020279.

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Urbanization processes greatly change urban landscape patterns and the urban thermal environment. Significant multi-scale correlation exists between the land surface temperature (LST) and landscape pattern. Compared with traditional linear regression methods, the regression model based on random forest has the advantages of higher accuracy and better learning ability, and can remove the linear correlation between regression features. Taking Beijing’s metropolitan area as an example, this paper conducted multi-scale relationship analysis between 3D landscape patterns and LST using Pearson Correlation Coefficient (PCC), Multiple Linear Regression and Random Forest Regression (RFR). The results indicated that LST was relatively high in the central area of Beijing, and decreased from the center to the surrounding areas. The interpretation effect of 3D landscape metrics on LST was more obvious than that of the 2D landscape metrics, and 3D landscape diversity and evenness played more important roles than the other metrics in the change of LST. The multi-scale relationship between LST and the landscape pattern was discovered in the fourth ring road of Beijing, the effect of the extent of change on the landscape pattern is greater than that of the grain size change, and the interpretation effect and correlation of landscape metrics on LST increase with the increase in the rectangle size. Impervious surfaces significantly increased the LST, while the impervious surfaces located at low building areas were more likely to increase LST than those located at tall building areas. It seems that increasing the distance between buildings to improve the rate of energy exchange between urban and rural areas can effectively decrease LST. Vegetation and water can effectively reduce LST, but large, clustered and irregularly shaped patches have a better effect on land surface cooling than small and discrete patches. The Coefficients of Rectangle Variation (CORV) power function fitting results of landscape metrics showed that the optimal rectangle size for studying the relationship between the 3D landscape pattern and LST is about 700 m. Our study is useful for future urban planning and provides references to mitigate the daytime urban heat island (UHI) effect.

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Zhang, Haijuan, Gai-Ge Wang, Junyu Dong et Amir H. Gandomi. « Improved NSGA-III with Second-Order Difference Random Strategy for Dynamic Multi-Objective Optimization ». Processes 9, n^o 6 (21 mai 2021) : 911. http://dx.doi.org/10.3390/pr9060911.

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Most real-world problems that have two or three objectives are dynamic, and the environment of the problems may change as time goes on. For the purpose of solving dynamic multi-objective problems better, two proposed strategies (second-order difference strategy and random strategy) were incorporated with NSGA-III, namely SDNSGA-III. When the environment changes in SDNSGA-III, the second-order difference strategy and random strategy are first used to improve the individuals in the next generation population, then NSGA-III is employed to optimize the individuals to obtain optimal solutions. Our experiments were conducted with two primary objectives. The first was to test the values of the metrics mean inverted generational distance (MIGD), mean generational distance (MGD), and mean hyper volume (MHV) on the test functions (Fun1 to Fun6) via the proposed algorithm and the four state-of-the-art algorithms. The second aim was to compare the metrics’ value of NSGA-III with single strategy and SDNSGA-III, proving the efficiency of the two strategies in SDNSGA-III. The comparative data obtained from the experiments demonstrate that SDNSGA-III has good convergence and diversity compared with four other evolutionary algorithms. What is more, the efficiency of second-order difference strategy and random strategy was also analyzed in this paper.

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Liu, Wei, Fengming Luo, Yuanhong Liu et Wei Ding. « Optimal Siting and Sizing of Distributed Generation Based on Improved Nondominated Sorting Genetic Algorithm II ». Processes 7, n^o 12 (13 décembre 2019) : 955. http://dx.doi.org/10.3390/pr7120955.

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With the development of distributed generation technology, the problem of distributed generation (DG) planning become one of the important subjects. This paper proposes an Improved non-dominated sorting genetic algorithm-II (INSGA-II) for solving the optimal siting and sizing of DG units. Firstly, the multi-objective optimization model is established by considering the energy-saving benefit, line loss, and voltage deviation values. In addition, relay protection constraints are introduced on the basis of node voltage, branch current, and capacity constraints. Secondly, the violation constrained index and improved mutation operator are proposed to increase the population diversity of non-dominated sorting genetic algorithm-II (NSGA-II), and the uniformity of the solution set of the potential crowding distance improvement algorithm is introduced. In order to verify the performance of the proposed INSGA-II algorithm, NSGA-II and multiple objective particle swarm optimization algorithms are used to perform various examples in IEEE 33-, 69-, and 118-bus systems. The convergence metric and spacing metric are used as the performance evaluation criteria. Finally, static and dynamic distribution network planning with the integrated DG are performed separately. The results of the various experiments show the proposed algorithm is effective for the siting and sizing of DG units in a distribution network. Most importantly, it also can achieve desirable economic efficiency and safer voltage level.

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Khan, Muhammad Waleed, Yasir Muhammad, Muhammad Asif Zahoor Raja, Farman Ullah, Naveed Ishtiaq Chaudhary et Yigang He. « A New Fractional Particle Swarm Optimization with Entropy Diversity Based Velocity for Reactive Power Planning ». Entropy 22, n^o 10 (1 octobre 2020) : 1112. http://dx.doi.org/10.3390/e22101112.

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Optimal Reactive Power Dispatch (ORPD) is the vital concern of network operators in the planning and management of electrical systems to reduce the real and reactive losses of the transmission and distribution system in order to augment the overall efficiency of the electrical network. The principle objective of the ORPD problem is to explore the best setting of decision variables such as rating of the shunt capacitors, output voltage of the generators and tap setting of the transformers in order to diminish the line loss, and improve the voltage profile index (VPI) and operating cost minimization of standard electrical systems while keeping the variables within the allowable limits. This research study demonstrates a compelling transformative approach for resolving ORPD problems faced by the operators through exploiting the strength of the meta-heuristic optimization model based on a new fractional swarming strategy, namely fractional order (FO)–particle swarm optimization (PSO), with consideration of the entropy metric in the velocity update mechanism. To perceive ORPD for standard 30 and 57-bus networks, the complex nonlinear objective functions, including minimization of the system, VPI improvement and operating cost minimization, are constructed with emphasis on efficacy enhancement of the overall electrical system. Assessment of the results show that the proposed FO-PSO with entropy metric performs better than the other state of the art algorithms by means of improvement in VPI, operating cost and line loss minimization. The statistical outcomes in terms of quantile–quantile illustrations, probability plots, cumulative distribution function, box plots, histograms and minimum fitness evaluation in a set of autonomous trials validate the capability of the proposed optimization scheme and exhibit sufficiency and also vigor in resolving ORPD problems.

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