Do Remote Camera Arrangements and Image Capture Settings Improve Individual Identification of Golden Eagles?

2021 ◽  
Author(s):  
Mark Vukovich ◽  
James E. Garabedian ◽  
Stanley J. Zarnoch ◽  
John C. Kilgo
Keyword(s):  
Individual Identification ◽  
Image Capture ◽  
Golden Eagles ◽  
Remote Camera

Correlative video enhanced differential interference contrast light microscopy (VDIC)-LM), low-voltage high-resolution SEM (LV-HR-SEM), and high-voltage electron microscopy (HVEM) in the observation of gold-labelled surface antigens and the subjacent cytoskeletal matrix

1989 ◽  
Vol 47 ◽  
pp. 904-905
Author(s):  
Ralph M. Albrecht ◽  
Scott R. Simmons ◽  
Marek Malecki
Keyword(s):  
High Resolution ◽  
Light Microscopy ◽  
Low Voltage ◽  
Microscopic Analysis ◽  
Cell Labelling ◽  
Video Technology ◽  
Electron Microscopic ◽  
Image Capture ◽  
High Voltage Electron Microscopy ◽  
Fluorescence Studies

The development of video-enhanced light microscopy (LM) as well as associated image processing and analysis have significantly broadened the scope of investigations which can be undertaken using (LM). Interference/polarization based microscopies can provide high resolution and higher levels of “detectability” especially in unstained living systems. Confocal light microscopy also holds the promise of further improvements in resolution, fluorescence studies, and 3 dimensional reconstruction. Video technology now provides, among other things, a means to detect differences in contrast difficult to detect with the human eye; furthermore, computerized image capture, processing, and analysis can be used to enhance features of interest, average images, subtract background, and provide a quantitative basis to studies of cells, cell features, cell labelling, and so forth. Improvements in video technology, image capture, and cost-effective computer image analysis/processing have contributed to the utility and potential of the various interference and confocal microscopic instrumentation.Electron microscopic technology has made advances as well. Microprocessor control and improved design have contributed to high resolution SEMs which have imaging capability at the molecular level and can operate at a range of accelerating voltages starting at 1KV. Improvements have also been seen in the HVEM and IVEM transmission instruments. As a whole, these advances in LM and EM microscopic technology provide the biologist with an array of information on structure, composition, and function which can be obtained from a single specimen. Corrrelative light microscopic analysis permits examination of living specimens and is critical where the “history” of a cell, cellular components, or labels needs to be known up to the time of chemical or physical fixation. Features such as cytoskeletal elements or gold label as small as 0.01 μm, well below the 0.2 μm limits of LM resolution, can be “detected” and their movement followed by VDIC-LM. Appropriate identification and preparation can then lead to the examination of surface detail and surface label with stereo LV-HR-SEM. Increasing the KV in the HR-SEM while viewing uncoated or thinly coated specimens can provide information from beneath the surface as well as increasing Z contrast so that positive identification of surface and subsurface colloidal gold or other heavy metal labelled/stained material is possible. Further examination of the same cells using stereo HVEM or IVEM provides information on internal ultrastructure and on the relationship of labelled material to cytoskeletal or organellar distribution, A wide variety of investigations can benefit from this correlative approach and a number of instrumentational configurations and preparative pathways can be tailored for the particular study. For a surprisingly small investment in time and technique, it is often possible to clear ambiguities or questions that arise when a finding is presented in the context of only one modality.

IRIS AND FINGER VEIN MULTI MODEL RECOGNITION SYSTEM BASED ON SIFT FEATURES

2018 ◽  
Vol 1 (2) ◽  
pp. 34-44
Author(s):  
Faris E Mohammed ◽  
Dr. Eman M ALdaidamony ◽  
Prof. A. M Raid
Keyword(s):  
Iris Recognition ◽  
Recognition Performance ◽  
Recognition System ◽  
Individual Identification ◽  
Work Place ◽  
Identification Process ◽  
Finger Vein ◽  
Noise Point ◽  
Vein Recognition ◽  
A New Technique

Individual identification process is a very significant process that resides a large portion of day by day usages. Identification process is appropriate in work place, private zones, banks …etc. Individuals are rich subject having many characteristics that can be used for recognition purpose such as finger vein, iris, face …etc. Finger vein and iris key-points are considered as one of the most talented biometric authentication techniques for its security and convenience. SIFT is new and talented technique for pattern recognition. However, some shortages exist in many related techniques, such as difficulty of feature loss, feature key extraction, and noise point introduction. In this manuscript a new technique named SIFT-based iris and SIFT-based finger vein identification with normalization and enhancement is proposed for achieving better performance. In evaluation with other SIFT-based iris or SIFT-based finger vein recognition algorithms, the suggested technique can overcome the difficulties of tremendous key-point extraction and exclude the noise points without feature loss. Experimental results demonstrate that the normalization and improvement steps are critical for SIFT-based recognition for iris and finger vein , and the proposed technique can accomplish satisfactory recognition performance. Keywords: SIFT, Iris Recognition, Finger Vein identification and Biometric Systems.   © 2018 JASET, International Scholars and Researchers Association    

Individual identification and paternity testing of bulls using microsatellite

2009 ◽  
Vol 31 (3) ◽  
pp. 285-289 ◽  
Author(s):  
Jing WANG ◽  
Chou-Sheng LIU ◽  
Li-Ping ZHANG ◽  
Zhi-Gang WANG ◽  
Fu-Qing YU ◽  
...  
Keyword(s):  
Paternity Testing ◽  
Individual Identification

Unique views on obesity-related behaviors and environments: research using still and video images (Preprint)

2018 ◽  
Author(s):  
Jordan Carlson ◽  
J. Aaron Hipp ◽  
Jacqueline Kerr ◽  
Todd Horowitz ◽  
David Berrigan
Keyword(s):  
Physical Activity ◽  
Ethical Issues ◽  
Data Extraction ◽  
Dietary Assessment ◽  
Extraction Methods ◽  
Image Capture ◽  
Still Images ◽  
Key Informants ◽  
Technological Advances ◽  
Computer Scientists

BACKGROUND Image based data collection for obesity research is in its infancy. OBJECTIVE The present study aimed to document challenges to and benefits from such research by capturing examples of research involving the use of images to assess physical activity- or nutrition-related behaviors and/or environments. METHODS Researchers (i.e., key informants) using image capture in their research were identified through knowledge and networks of the authors of this paper and through literature search. Twenty-nine key informants completed a survey covering the type of research, source of images, and challenges and benefits experienced, developed specifically for this study. RESULTS Most respondents used still images in their research, with only 26.7% using video. Image sources were categorized as participant generated (N = 13; e.g., participants using smartphones for dietary assessment), researcher generated (N = 10; e.g., wearable cameras with automatic image capture), or curated from third parties (N = 7; e.g., Google Street View). Two of the major challenges that emerged included the need for automated processing of large datasets (58.8%) and participant recruitment/compliance (41.2%). Benefit-related themes included greater perspectives on obesity with increased data coverage (34.6%) and improved accuracy of behavior and environment assessment (34.6%). CONCLUSIONS Technological advances will support the increased use of images in the assessment of physical activity, nutrition behaviors, and environments. To advance this area of research, more effective collaborations are needed between health and computer scientists. In particular development of automated data extraction methods for diverse aspects of behavior, environment, and food characteristics are needed. Additionally, progress in standards for addressing ethical issues related to image capture for research purposes are critical. CLINICALTRIAL NA

Introduction

2017 ◽  
Author(s):  
M.G.L. Mills ◽  
M.E.J. Mills
Keyword(s):  
South Africa ◽  
Arid Region ◽  
Statistical Tests ◽  
Distribution Range ◽  
Individual Identification ◽  
Behavioural Ecology ◽  
Main Study ◽  
Doubly Labelled Water ◽  
Data Loggers ◽  
Prime Objective

Most cheetah studies have been confined to mesic savannahs, yet much of its distribution range covers arid systems. The prime objective in this study was to examine the species’ adaptations to an arid region, to compare the results with those from other cheetah studies, especially from the Serengeti, and to analyse the data within the framework of carnivore population and behavioural ecology. The study was conducted in the Kgalagadi Transfrontier Park South Africa/Botswana, an area receiving 180–250 mm rainfall per year. Tracking spoor with the help of Bushmen trackers and continuous follows of 21 VHF radio-collared cheetahs were the main study methods used. These were supported by photographic records for individual identification, DNA studies for genetic aspects including paternity, and the use of doubly labelled water and the fitting of miniature data loggers for energetic studies. The statistical tests used to analyse the data are described.

scholarly journals Identifying unknown Indian wolves by their distinctive howls: its potential as a non-invasive survey method

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sougata Sadhukhan ◽  
Holly Root-Gutteridge ◽  
Bilal Habib
Keyword(s):  
Reproductive Behaviour ◽  
Identification Accuracy ◽  
Individual Identification ◽  
Survey Method ◽  
Reliable Estimate ◽  
Mark Recapture ◽  
Test Dataset ◽  
Individual Level ◽  
Non Invasive ◽  
Supervised Classification Methods

AbstractPrevious studies have posited the use of acoustics-based surveys to monitor population size and estimate their density. However, decreasing the bias in population estimations, such as by using Capture–Mark–Recapture, requires the identification of individuals using supervised classification methods, especially for sparsely populated species like the wolf which may otherwise be counted repeatedly. The cryptic behaviour of Indian wolf (Canis lupus pallipes) poses serious challenges to survey efforts, and thus, there is no reliable estimate of their population despite a prominent role in the ecosystem. Like other wolves, Indian wolves produce howls that can be detected over distances of more than 6 km, making them ideal candidates for acoustic surveys. Here, we explore the use of a supervised classifier to identify unknown individuals. We trained a supervised Agglomerative Nesting hierarchical clustering (AGNES) model using 49 howls from five Indian wolves and achieved 98% individual identification accuracy. We tested our model’s predictive power using 20 novel howls from a further four individuals (test dataset) and resulted in 75% accuracy in classifying howls to individuals. The model can reduce bias in population estimations using Capture-Mark-Recapture and track individual wolves non-invasively by their howls. This has potential for studies of wolves’ territory use, pack composition, and reproductive behaviour. Our method can potentially be adapted for other species with individually distinctive vocalisations, representing an advanced tool for individual-level monitoring.

A Novel Thyroid Ultrasound Proficiency Metric Designed Through a Multidisciplinary Delphi Approach

2021 ◽  
pp. 000313482110111
Author(s):  
Yinin Hu ◽  
Alex D. Michaels ◽  
Rachita Khot ◽  
Worthington G. Schenk ◽  
John B. Hanks ◽  
...  
Keyword(s):  
Learning Curves ◽  
Delphi Panel ◽  
Thyroid Ultrasound ◽  
Point Scale ◽  
Image Capture ◽  
Delphi Approach ◽  
Inflection Points ◽  
Operative Planning ◽  
Positioning Technique ◽  
Formally Trained

Background Thyroid ultrasounds extend surgeons’ outpatient capabilities and are essential for operative planning. However, most residents are not formally trained in thyroid ultrasound. The purpose of this study was to create a novel thyroid ultrasound proficiency metric through a collaborative Delphi approach. Methods Clinical faculty experienced in thyroid ultrasound participated on a Delphi panel to design the thyroid Ultrasound Proficiency Scale (UPS-Thyroid). Participants proposed items under the categories of Positioning, Technique, Image Capture, Measurement, and Interpretation. In subsequent rounds, participants voted to retain, revise, or exclude each item. The process continued until all items had greater than 70% consensus for retention. The UPS-Thyroid was pilot tested across 5 surgery residents with moderate ultrasound experience. Learning curves were assessed with cumulative sum. Results Three surgeons and 4 radiologists participated on the Delphi panel. Following 3 iterative Delphi rounds, the panel arrived at >70% consensus to retain 14 items without further revisions or additions. The metric included the following items on a 3-point scale for a maximum of 42 points: Positioning (1 item), Technique (4 items), Image Capture (2 items), Measurement (2 items), and Interpretation (5 items). A pilot group of 5 residents was scored against a proficiency threshold of 36 points. Learning curve inflection points were noted at between 4 to 7 repetitions. Conclusions A multidisciplinary Delphi approach generated consensus for a thyroid ultrasound proficiency metric (UPS-Thyroid). Among surgery residents with moderate ultrasound experience, basic proficiency at thyroid ultrasound is feasible within 10 repetitions.

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