Gotowe bibliografie tematyczne / Birds – Identification

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Gotowa bibliografia na temat „Birds – Identification”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 1 lutego 2022

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Artykuły w czasopismach na temat "Birds – Identification"

Zhang, Shanshan, Hong Ying, Gesang Pingcuo, Shuo Wang, Fan Zhao, Yongning Cui, Jian Shi, Hu Zeng, and Xiuli Zeng. "Identification of Potential Metabolites Mediating Bird’s Selective Feeding on Prunus mira Flowers." BioMed Research International 2019 (June 23, 2019): 1–8. http://dx.doi.org/10.1155/2019/1395480.

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In peach orchards, birds severely damage flowers during blossom season, decreasing the fruit yield potential. However, the wild peach species Prunus mira shows intraspecific variations of bird damage, indicating that some of the wild trees have developed strategies to avert bird foraging. Motivated by this observation, we formulated the present study to identify the potential flower metabolites mediating the bird’s selective feeding behavior in P. mira flowers. The birds’ preferred (FG) and avoided (BFT) flowers were collected from wild P. mira trees at three different locations, and their met

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Purwaningrum, Medania, Herjuno Ari Nugroho, Machmud Asvan, Karyanti Karyanti, Bertha Alviyanto, Randy Kusuma, and Aris Haryanto. "Molecular techniques for sex identification of captive birds." Veterinary World 12, no. 9 (September 2019): 1506–13. http://dx.doi.org/10.14202/vetworld.2019.1506-1513.

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Background and Aim: Many avian species are considered sexually monomorphic. In monomorphic bird species, especially in young birds, sex is difficult to identify based on an analysis of their external morphology. Accurate sex identification is essential for avian captive breeding and evolutionary studies. Methods with varying degrees of invasiveness such as vent sexing, laparoscopic surgery, steroid sexing, and chromosome inspection (karyotyping) are used for sex identification in monomorphic birds. This study aimed to assess the utility of a non-invasive molecular marker for gender identificat

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Griffiths, Richard. "Sex identification in birds." Seminars in Avian and Exotic Pet Medicine 9, no. 1 (January 2000): 14–26. http://dx.doi.org/10.1016/s1055-937x(00)80012-2.

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Sinyo, Bayu A., L. Lambey, F. Kairupan, and J. Keintjem. "KAJIAN WARNA DAN CORAK BULU PADA BURUNG WERIS DI KOTA KOTAMOBAGU SULAWESI UTARA." ZOOTEC 34, no. 1 (February 28, 2014): 124. http://dx.doi.org/10.35792/zot.34.1.2014.3878.

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ABSTRACT STUDY ON FEATHER PATTERN AND COLORS OF “WERIS” BIRDS IN CITY OF KOTAMOBAGU. Mandar bird (Gallirallus) which in local language known as Weris (Minahasa), and Boruit (Kotamobagu) is a bird in the family Rallidae, are a family of birds that have small to medium body size. General habitat of this bird species is swamp, near a river or lake. Weris birds generally breed in densely vegetated areas According Rusila (1994). Identify an issue in the study is the identification of colors and feather patterns, two species weris birds that exist in Kotamobagus (North Sulawesi). The purpose of this

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Brom, Tim G. "Microscopic Identification of Feathers and Feather Fragments of Palearctic Birds." Bijdragen tot de Dierkunde 56, no. 2 (1986): 181–204. http://dx.doi.org/10.1163/26660644-05602001.

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Using light microscopy, a method has been developed for the identification of feathers and feather fragments collected after collisions between birds and aircraft. Characters of the downy barbules of feathers are described for 22 orders of birds. The use of a key in combination with the macroscopic method of comparing feathers with bird skins in a museum collection results in identification to order or family level in 97% of the analysed bird strikes. Application of the method to other fields of biological research including taxonomy is discussed.

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Giorgio, Antonella, Salvatore De Bonis, Rosario Balestrieri, Giovanni Rossi, and Marco Guida. "The Isolation and Identification of Bacteria on Feathers of Migratory Bird Species." Microorganisms 6, no. 4 (December 5, 2018): 124. http://dx.doi.org/10.3390/microorganisms6040124.

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Worldwide, bacteria are the most ubiquitous microorganisms, and it has been extensively demonstrated that migratory wild birds can increase bacterial global scale dispersion through long-distance migration and dispersal. The microbial community hosted by wild birds can be highly diverse, including pathogenic strains that can contribute to infections and disease spread. This study focused on feather and plumage bacteria within bird microbial communities. Samples were collected during ornithological activities in a bird ringing station. Bacterial identification was carried out via DNA barcoding

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Torres, Christopher R., Mark A. Norell, and Julia A. Clarke. "Bird neurocranial and body mass evolution across the end-Cretaceous mass extinction: The avian brain shape left other dinosaurs behind." Science Advances 7, no. 31 (July 2021): eabg7099. http://dx.doi.org/10.1126/sciadv.abg7099.

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Birds today are the most diverse clade of terrestrial vertebrates, and understanding why extant birds (Aves) alone among dinosaurs survived the Cretaceous-Paleogene mass extinction is crucial to reconstructing the history of life. Hypotheses proposed to explain this pattern demand identification of traits unique to Aves. However, this identification is complicated by a lack of data from non-avian birds. Here, we interrogate survivorship hypotheses using data from a new, nearly complete skull of Late Cretaceous (~70 million years) bird Ichthyornis and reassess shifts in bird body size across th

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Zaugg, Serge, Gilbert Saporta, Emiel van Loon, Heiko Schmaljohann, and Felix Liechti. "Automatic identification of bird targets with radar via patterns produced by wing flapping." Journal of The Royal Society Interface 5, no. 26 (March 10, 2008): 1041–53. http://dx.doi.org/10.1098/rsif.2007.1349.

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Bird identification with radar is important for bird migration research, environmental impact assessments (e.g. wind farms), aircraft security and radar meteorology. In a study on bird migration, radar signals from birds, insects and ground clutter were recorded. Signals from birds show a typical pattern due to wing flapping. The data were labelled by experts into the four classes BIRD, INSECT, CLUTTER and UFO (unidentifiable signals). We present a classification algorithm aimed at automatic recognition of bird targets. Variables related to signal intensity and wing flapping pattern were extra

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Khatri-Chhetri, Upama, John G. Woods, Ian R. Walker, and P. Jeff Curtis. "Origin identification of migratory pests (European Starling) using geochemical fingerprinting." PeerJ 8 (May 4, 2020): e8962. http://dx.doi.org/10.7717/peerj.8962.

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The European Starling (Sturnidae: Sturnus vulgaris L.) is an invasive bird in North America where it is an agricultural pest. In British Columbia (Canada), the starling population increases in orchards and vineyards in autumn, where they consume and damage ripening fruits. Starlings also cause damage in dairy farms and feedlots by consuming and contaminating food and spreading diseases. Damage can be partly mitigated by the use of scare devices, which can disperse flocks until they become habituated. Large-scale trapping and euthanizing before starlings move to fields and farms could be a prac

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Yudkin, V. A., and M. A. Grabovski. "QUANTITATIVE METHOD OF ESTIMATE OF AERODROME BIRDS HAZARD RISK." Civil Aviation High TECHNOLOGIES 21, no. 4 (August 28, 2018): 48–59. http://dx.doi.org/10.26467/2079-0619-2018-21-4-48-59.

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The formalized parameters of bird hazard assessment at the aerodrome are presented. The size of total biomass of all birds that are in a zone of aircraft movement reflects the aggregate characteristic of ornithological hazard. This is a dynamic parameter, its dimensionality is kg/hour‧km2. The size of biomass is differentiated on high-altitude layers and the directions of its movement. In addition, it is necessary to estimate activity of each bird species at the aerodrome as component parts of bird hazard. Its dimensionality is individuals/hour‧km2. One more parameter of aerodrome bird hazard

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Rozprawy doktorskie na temat "Birds – Identification"

Fox, Elizabeth J. S. "Call-independent identification in birds." University of Western Australia. School of Animal Biology, 2008. http://theses.library.uwa.edu.au/adt-WU2008.0218.

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[Truncated abstract] The identification of individual animals based on acoustic parameters is a non-invasive method of identifying individuals with considerable advantages over physical marking procedures. One requirement for an effective and practical method of acoustic individual identification is that it is call-independent, i.e. determining identity does not require a comparison of the same call or song type. This means that an individuals identity over time can be determined regardless of any changes to its vocal repertoire, and different individuals can be compared regardless of whether

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Lau, Hok-nang, and 劉學能. "Identification of novel coronaviruses in dead birds in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B44660108.

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Eakle, Wade Laney 1959. "SONAGRAPHIC IDENTIFICATION OF INDIVIDUAL BREEDING BALD EAGLES (HALIAEETUS LEUCOCEPHALUS) IN ARIZONA." Thesis, The University of Arizona, 1986. http://hdl.handle.net/10150/276369.

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Mead, Reginald Marshall. "A system for automating identification of biological echoes in NEXRAD level II radar data." Thesis, Montana State University, 2009. http://etd.lib.montana.edu/etd/2009/mead/MeadR1209.pdf.

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Since its inception in the mid twentieth century, radar ornithology has provided scientists with new tools for studying the behavior of birds, especially with regards to migration. A number of studies have shown that birds can be detected using a wide variety of radar devices. Generally, these studies have focused on small portable radars that typically have a finer resolution than large weather surveillance radars. Recently, however, a number of researchers have presented qualitative evidence suggesting that birds, or at least migration events, can be identified using large broad scale radars

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Rogers, Daniel James. "Intraspecific variation in the acoustic signals of birds and one species of frog : implications for the acoustic identification of individuals." Title page, contents and abstract only, 2002. http://web4.library.adelaide.edu.au/theses/09PH/09phr7251.pdf.

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Bibliography: leaves 203-218. This thesis investigated patterns of intraspecific variation in the acoustic signals of a range of vocal animal species with the ultimate objective of demonstrating vocal individuality in these species, focussing on two methods of quantitative song analysis, discriminant function analysis and cross-correlation analysis. Two species were studied: Bibron's toadlet (Pseudophryne bibronii) and Rufous bristlebird (Dasyornis broadbenti).

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Grando, Angélica Paula. "Utilização de tomografia por ressonância magnética nuclear para sexagem de aves silvestres sem dimorfismo sexual." Universidade de São Paulo, 2002. http://www.teses.usp.br/teses/disponiveis/82/82131/tde-07012003-092830/.

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O rápido declínio da vida silvícola do planeta tem levado inúmeros pesquisadores a discutirem diferentes estratégias de conservação, tanto com a manutenção dos animais em seus próprios habitats naturais, como pela propagação em cativeiro. A reprodução de aves em cativeiro é dificultada quando esses animais não apresentam dimorfismo sexual (ausente em muitas espécies, especialmente em psitacídeos), requerendo a realização de métodos de sexagem para a formação de casais. Dessa forma, foi estudado o uso da tomografia por ressonância magnética nuclear (TRMN) para a sexagem de aves silvestres sem d

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Vundavalli, Suveen Kumar, and Sri Rama Srinivasa Varma Danthuluri. "Bird Chirps Annotation UsingTime-Frequency Domain Analysis." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13624.

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There are around 10,426 bird species around the world. Recognizing the bird species for an untrained person is almost impossible either by watching or listening them. In order to identify the bird species from their sounds, there is a need for an application that can detect the bird species from its sound. Time-frequency domain analysis techniques are used to implement the application. We implemented two time-frequency domain feature extraction methods. In feature extraction, a signature matrix which consist of extracted features is created for bird sound signals. A database of signature matri

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Zakeri, Masoud. "Automatic bird species identification employing an unsupervised discovery of vocalisation units." Thesis, University of Birmingham, 2017. http://etheses.bham.ac.uk//id/eprint/7833/.

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An automatic analysis of bird vocalisations for the identification of bird species, the study of their behaviour and their means of communication is important for a better understanding of the environment in which we are living and in the context of environmental protection. The high variability of vocalisations within different individuals makes species’ identification challenging for bird surveyors. Hence, the availability of a reliable automatic bird identification system through their vocalisations, would be of great interest to professionals and amateurs alike. A part of this thesis provi

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Rizzitelli, Federico. "Design and implementation of BIRDY satellite data and Radiation Payload simulators." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016.

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Numerical modelling and simulations are needed to develop and test specific analysis methods by providing test data before BIRDY would be launched. This document describes the "satellite data simulator" which is a multi-sensor, multi-spectral satellite simulator produced especially for the BIRDY mission which could be used as well to analyse data from other satellite missions providing energetic particles data in the Solar system.

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Burden, Joanne Jemima Ellen. "Identification and characterisation of a novel intracellular protein that binds the low density lipoprotein (LDL) receptor." Thesis, Imperial College London, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.271420.

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Książki na temat "Birds – Identification"

Burnie, David. Birds. New York: DK Pub., 2012.

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Irish birds. London: HarperCollins Publishers, 1995.

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Eastern birds. New York: McGraw-Hill, 1988.

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Farrand, John. Western birds. New York: McGraw-Hill, 1988.

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Irish birds. London: HarperCollins, 2004.

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Penny, Meakin, and Goode Douglas, eds. Common birds. Harare, Zimbabwe: Zimbabwe Pub. House, 1994.

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Zim, Herbert S. Birds: A guide to familiar American birds. New York: Golden Press, 1987.

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Seabirds: An identification guide. Boston: Houghton Mifflin Co., 1988.

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Seabirds: An identification guide. London: Christopher Helm, 1989.

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Peter, Harrison. Seabirds, an identification guide. Boston: Houghton Mifflin, 1985.

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Części książek na temat "Birds – Identification"

Lasseck, Mario. "Towards Automatic Large-Scale Identification of Birds in Audio Recordings." In Lecture Notes in Computer Science, 364–75. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24027-5_39.

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Kale, Vini, and Rajesh Kumar. "Forensic Identification of Birds from Feathers Using Hue and Saturation Histogram." In Communications in Computer and Information Science, 188–95. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0493-5_17.

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Joly, Alexis, Hervé Goëau, Christophe Botella, Stefan Kahl, Maximillien Servajean, Hervé Glotin, Pierre Bonnet, et al. "Overview of LifeCLEF 2019: Identification of Amazonian Plants, South & North American Birds, and Niche Prediction." In Lecture Notes in Computer Science, 387–401. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28577-7_29.

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Niemi, Juha, and Juha T. Tanttu. "Automatic Bird Identification for Offshore Wind Farms." In Wind Energy and Wildlife Impacts, 135–51. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-05520-2_9.

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Li, H., J. K. Liu, and Z. R. Lu. "Bird Mating Optimizer in Structural Damage Identification." In Advances in Swarm and Computational Intelligence, 49–56. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20466-6_5.

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Carvalho, Silvestre, and Elsa Ferreira Gomes. "Automatic Identification of Bird Species from Audio." In Intelligent Information and Database Systems, 41–52. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-73280-6_4.

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Pillai, Sofia K., M. M. Raghuwanshi, and Urmila Shrawankar. "Deep Learning Neural Network for Identification of Bird Species." In Lecture Notes in Networks and Systems, 291–98. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7150-9_31.

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Villareal Olvera, Toaki Esaú, Caleb Rascón, and Ivan Vladimir Meza Ruiz. "Emotion Based Features of Bird Singing for Turdus migratorius Identification." In Lecture Notes in Computer Science, 521–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-45111-9_45.

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Niemi, Juha, and Juha T. Tanttu. "Deep Learning Case Study on Imbalanced Training Data for Automatic Bird Identification." In Deep Learning: Algorithms and Applications, 231–62. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31760-7_8.

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Surender, M., K. Chandra Shekar, K. Ravikanth, and R. Saidulu. "Automatic Identification of Bird Species from the Image Through the Approaches of Segmentation." In Innovations in Computer Science and Engineering, 203–14. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7082-3_25.

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Streszczenia konferencji na temat "Birds – Identification"

Bayat, Seda, and Gultekin Isik. "Identification of Aras Birds with Convolutional Neural Networks." In 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT). IEEE, 2020. http://dx.doi.org/10.1109/ismsit50672.2020.9255205.

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Can, Chen, Xiong Yan, and Yan Baoping. "Morphology classification and behaviors identification of birds in scientific video." In 3rd International Conference on Multimedia Technology(ICMT-13). Paris, France: Atlantis Press, 2013. http://dx.doi.org/10.2991/icmt-13.2013.178.

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Karmaker, Debajyoti, Ingo Schiffner, Reuben Strydom, and Mandyam V. Srinivasan. "WHoG: A weighted HoG-based scheme for the detection of birds and identification of their poses in natural environments." In 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV). IEEE, 2016. http://dx.doi.org/10.1109/icarcv.2016.7838650.

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Watanabe, Masaji, and Tertia Delia Nova. "Study on Bird Flu Infection Process within a Poultry Farm with Modeling and Simulation." In Modelling, Identification and Control. Calgary,AB,Canada: ACTAPRESS, 2012. http://dx.doi.org/10.2316/p.2012.769-059.

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Blower, Christopher J., and Adam M. Wickenheiser. "The Validation of a Generalized Aerodynamic Model for a Multi-Body Bio-Inspired Wing." In ASME 2013 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/smasis2013-3075.

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Bio-inspiration has introduced new and innovative flow control methods in gust alleviation, maneuverability and stability improvement for morphing aircraft wings. The bio-inspired wing model under consideration imitates the techniques used by birds to manipulate localized air flow through the installation of feather-like panels across the airfoil’s upper and lower surface, replacing the traditional wing’s surface and trailing edge flap. Each flap is designed to rotate into both the airfoil profile and inbound air flow, using a single degree of freedom about their individual hinge points locate

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Debnath, Sujoy, Partha Protim Roy, Amin Ahsan Ali, and M. Ashraful Amin. "Identification of bird species from their singing." In 2016 International Conference on Informatics, Electronics and Vision (ICIEV). IEEE, 2016. http://dx.doi.org/10.1109/iciev.2016.7759992.

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Marini, A., A. J. Turatti, A. S. Britto, and A. L. Koerich. "Visual and acoustic identification of bird species." In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2015. http://dx.doi.org/10.1109/icassp.2015.7178383.

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Ragib, Kazi Md, Raisa Taraman Shithi, Shihab Ali Haq, Md Hasan, Kazi Mohammed Sakib, and Tanjila Farah. "PakhiChini: Automatic Bird Species Identification Using Deep Learning." In 2020 Fourth World Conference on Smart Trends in Systems Security and Sustainablity (WorldS4). IEEE, 2020. http://dx.doi.org/10.1109/worlds450073.2020.9210259.

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Lopes, Marcelo Teider, Alessandro Lameiras Koerich, Carlos Nascimento Silla, and Celso Antonio Alves Kaestner. "Feature set comparison for automatic bird species identification." In 2011 IEEE International Conference on Systems, Man and Cybernetics. IEEE, 2011. http://dx.doi.org/10.1109/icsmc.2011.6083794.

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Sukri, Muhammad Mujjajdid Mohd, Umi Fadlilah, Sharifah Saon, Abd Kadir Mahamad, Mohamad Md Som, and Azmi Sidek. "Bird Sound Identification based on Artificial Neural Network." In 2020 IEEE Student Conference on Research and Development (SCOReD). IEEE, 2020. http://dx.doi.org/10.1109/scored50371.2020.9250746.

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