A Manual for Monitoring Wild Boars (Sus scrofa) Using Thermal Infrared Cameras Mounted on an Unmanned Aerial Vehicle (UAV)

This study proposes monitoring methods of wild boars in plains or mountain forest areas using unmanned aerial vehicles (UAVs) equipped with infrared cameras. It is recommended to monitor in winter when the canopy layer is thin and the temperature difference between the ambient temperature and the body temperature of the wild boar is distinct, so that the infrared camera can better detect the wild boars. In flat land, the plane movement of the UAV can be easily monitored using the line transect, the point count survey, the plot sampling method, and the belted transect. In the mountain forest, there are variations in elevation due to slopes. Therefore, we introduced the WAYPOINT function to reflect the difference in altitude. After the investigator designates the waypoint, various information can be modified according to the terrain, and the WAYPOINT can be transmitted to other UAVs, so the utilization is high. In this method, once a route is created using the WAYPOINT, there is no need for additional operation after the start of the flight, and it helps to re-monitor the site by using the WAYPOINT record repeatedly. Therefore, this technical note provides a more repeatedly sustainable and scalable monitoring method than the conventional UAV method.

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Cost-efficiency assessments of marine monitoring methods lack rigor—a systematic mapping of literature and an end-user view on optimal cost-efficiency analysis

Environmental Monitoring and Assessment ◽

10.1007/s10661-021-09159-y ◽

2021 ◽

Vol 193 (7) ◽

Author(s):

Heini Hyvärinen ◽

Annaliina Skyttä ◽

Susanna Jernberg ◽

Kristian Meissner ◽

Harri Kuosa ◽

...

Keyword(s):

Comparative Studies ◽

Cost Efficiency ◽

Cost Benefit ◽

Marine Ecosystems ◽

Actual Cost ◽

Monitoring Methods ◽

Monitoring Method ◽

Marine Monitoring ◽

The Status ◽

The Cost

AbstractGlobal deterioration of marine ecosystems, together with increasing pressure to use them, has created a demand for new, more efficient and cost-efficient monitoring tools that enable assessing changes in the status of marine ecosystems. However, demonstrating the cost-efficiency of a monitoring method is not straightforward as there are no generally applicable guidelines. Our study provides a systematic literature mapping of methods and criteria that have been proposed or used since the year 2000 to evaluate the cost-efficiency of marine monitoring methods. We aimed to investigate these methods but discovered that examples of actual cost-efficiency assessments in literature were rare, contradicting the prevalent use of the term “cost-efficiency.” We identified five different ways to compare the cost-efficiency of a marine monitoring method: (1) the cost–benefit ratio, (2) comparative studies based on an experiment, (3) comparative studies based on a literature review, (4) comparisons with other methods based on literature, and (5) subjective comparisons with other methods based on experience or intuition. Because of the observed high frequency of insufficient cost–benefit assessments, we strongly advise that more attention is paid to the coverage of both cost and efficiency parameters when evaluating the actual cost-efficiency of novel methods. Our results emphasize the need to improve the reliability and comparability of cost-efficiency assessments. We provide guidelines for future initiatives to develop a cost-efficiency assessment framework and suggestions for more unified cost-efficiency criteria.

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A Citizen Science Unmanned Aerial System Data Acquisition Protocol and Deep Learning Techniques for the Automatic Detection and Mapping of Marine Litter Concentrations in the Coastal Zone

Drones ◽

10.3390/drones5010006 ◽

2021 ◽

Vol 5 (1) ◽

pp. 6

Author(s):

Apostolos Papakonstantinou ◽

Marios Batsaris ◽

Spyros Spondylidis ◽

Konstantinos Topouzelis

Keyword(s):

Deep Learning ◽

Data Acquisition ◽

Citizen Science ◽

Coastal Zone ◽

Automatic Detection ◽

Monitoring Methods ◽

Monitoring Method ◽

Marine Litter ◽

Density Maps ◽

Learning Techniques

Marine litter (ML) accumulation in the coastal zone has been recognized as a major problem in our time, as it can dramatically affect the environment, marine ecosystems, and coastal communities. Existing monitoring methods fail to respond to the spatiotemporal changes and dynamics of ML concentrations. Recent works showed that unmanned aerial systems (UAS), along with computer vision methods, provide a feasible alternative for ML monitoring. In this context, we proposed a citizen science UAS data acquisition and annotation protocol combined with deep learning techniques for the automatic detection and mapping of ML concentrations in the coastal zone. Five convolutional neural networks (CNNs) were trained to classify UAS image tiles into two classes: (a) litter and (b) no litter. Testing the CCNs’ generalization ability to an unseen dataset, we found that the VVG19 CNN returned an overall accuracy of 77.6% and an f-score of 77.42%. ML density maps were created using the automated classification results. They were compared with those produced by a manual screening classification proving our approach’s geographical transferability to new and unknown beaches. Although ML recognition is still a challenging task, this study provides evidence about the feasibility of using a citizen science UAS-based monitoring method in combination with deep learning techniques for the quantification of the ML load in the coastal zone using density maps.

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A Product Pose Tracking Paradigm Based on Deep Points Detection

Machines ◽

10.3390/machines9060112 ◽

2021 ◽

Vol 9 (6) ◽

pp. 112

Author(s):

Loukas Bampis ◽

Spyridon G. Mouroutsos ◽

Antonios Gasteratos

Keyword(s):

Neural Network ◽

Deep Neural Network ◽

Visible Spectrum ◽

The Body ◽

Autonomous Control ◽

Pose Tracking ◽

Computer Aided ◽

Manufacturing Procedure ◽

Infrared Cameras ◽

Representative Points

The paper at hand presents a novel and versatile method for tracking the pose of varying products during their manufacturing procedure. By using modern Deep Neural Network techniques based on Attention models, the most representative points to track an object can be automatically identified using its drawing. Then, during manufacturing, the body of the product is processed with Aluminum Oxide on those points, which is unobtrusive in the visible spectrum, but easily distinguishable from infrared cameras. Our proposal allows for the inclusion of Artificial Intelligence in Computer-Aided Manufacturing to assist the autonomous control of robotic handlers.

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Using complementary remote detection methods for retrofitted eco-passages: a case study for monitoring individual koalas in south-east Queensland

Wildlife Research ◽

10.1071/wr15153 ◽

2016 ◽

Vol 43 (5) ◽

pp. 369 ◽

Cited By ~ 7

Author(s):

C. E. Dexter ◽

R. G. Appleby ◽

J. P. Edgar ◽

J. Scott ◽

D. N. Jones

Keyword(s):

Road Construction ◽

Primary Objective ◽

Correlated Data ◽

Camera Traps ◽

Detection Methods ◽

Urban Landscapes ◽

Monitoring Methods ◽

Monitoring Method ◽

Phascolarctos Cinereus ◽

The Individual

Context Vehicle-strike has been identified as a key threatening process for koala (Phascolarctos cinereus) survival and persistence in Australia. Roads and traffic act as barriers to koala movement and can impact dispersal and metapopulation dynamics. Given the high cost of wildlife mitigation structures such as purpose-built fauna-specific underpasses or overpasses (eco-passages), road construction and management agencies are constantly seeking cost-effective strategies that facilitate safe passage for fauna across roads. Here we report on an array of detection methods trialled to verify use of retrofitted road infrastructure (existing water culverts or bridge underpasses) by individual koalas in fragmented urban landscapes in south-east Queensland. Aims The study examined whether the retrofitting of existing road structures at six sites facilitated safe passage for koalas across roads. Our primary objective was to record utilisation of retrofitted infrastructure at the level of the individual. Methods We used a combination of existing monitoring methods such as GPS/VHF collars, camera traps, sand plots, and RFID tags, along with a newly developed animal-borne wireless identification (WID) tag and datalogging system, specifically designed for this project, to realise the study aims. Key results We were able to verify 130 crossings by koalas involving a retrofitted structure or a road surface over a 30-month period by using correlated data from complementary methods. We noted that crossings were generally uncommon and mostly undertaken by only a subset of our tagged individuals at each site (21% overall). Conclusions An important element of this study was that crossing events could be accurately determined at the level of the individual. This allowed for detailed assessment of eco-passage usage, rather than the more usual approach of simply recording species’ presence. Implications This study underscores the value of identifying the constraints of each individual monitoring method in relation to site conditions. It also highlights the benefits of contingency planning to limit data loss (i.e. using more than one method to collect data). We suggest an approach that uses complementary monitoring methods has significant advantages for researchers, particularly with reference to improving understanding of whether eco-passages are meeting their prescribed conservation goals.

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Cerebral oxygenation monitoring in patients during and after cardiac arrest -- a narrative review of current methods and evidence

10.22514/sv.2021.141 ◽

2021 ◽

Keyword(s):

Cardiac Arrest ◽

Near Infrared ◽

Cerebral Oxygenation ◽

The Body ◽

Narrative Review ◽

Oxygen Balance ◽

Monitoring Methods ◽

Venous Oxygen Saturation ◽

Oxygenation Monitoring ◽

The Impact

Hypoxic-ischemic brain injury (HIBI) is a leading cause of mortality in post-cardiac arrest (post-CA) patients who successfully survive the initial cardiopulmonary resuscitation (CPR) but later die in the Intensive Care Unit (ICU). Therefore, a key priority of post-resuscitation ICU care is to prevent and limit the impact of HIBI by optimizing the balance between cerebral oxygen delivery and demand. Traditionally, an optimal systemic oxygen balance is considered to ensure the brain’s oxygen balance. However, the validity of this assumption is uncertain, as the brain constitutes only 2%of the body mass while accounting for approximately 20% of basal oxygen consumption at rest. Hence, there is a real need to monitor cerebral oxygenation realistically. Several imaging and bedside monitoring methods are available for cerebral oxygenation monitoring in post-CA patients. Unfortunately, each of them has its limitations. Imaging methods require transporting a critically ill unstable patient to the scanner. Moreover, they provide an assessment of the oxygenation state only at a particular moment, while brain oxygenation is dynamic. Bedside methods, specifically near-infrared spectroscopy (NIRS), brain tissue oxygen tension (PbtO2), and jugular venous oxygen saturation monitoring (SjvO2), have not often been used in studies involving post-CA patients. Hence there is ambiguity regarding clear recommendations for using these bedside monitors. Presently, the most promising option seems to be using the NIRS as an indicator of effective CPR. We present a narrative review focusing on bedside methods and discuss the evidence for their use in adult patients after cardiac arrest.

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Can Reliable Sage-Grouse Lek Counts Be Obtained Using Aerial Infrared Technology?

Journal of Fish and Wildlife Management ◽

10.3996/032013-jfwm-025 ◽

2013 ◽

Vol 4 (2) ◽

pp. 386-394 ◽

Cited By ~ 9

Author(s):

Gifford L. Gillette ◽

Peter S. Coates ◽

Steven Petersen ◽

John P. Romero

Keyword(s):

Infrared Camera ◽

Centrocercus Urophasianus ◽

Management Tool ◽

Breeding Period ◽

Sage Grouse ◽

Remote Areas ◽

Infrared Technology ◽

Infrared Surveys ◽

Infrared Cameras ◽

Infrared Techniques

Abstract More effective methods for counting greater sage-grouse (Centrocercus urophasianus) are needed to better assess population trends through enumeration or location of new leks. We describe an aerial infrared technique for conducting sage-grouse lek counts and compare this method with conventional ground-based lek count methods. During the breeding period in 2010 and 2011, we surveyed leks from fixed-winged aircraft using cryogenically cooled mid-wave infrared cameras and surveyed the same leks on the same day from the ground following a standard lek count protocol. We did not detect significant differences in lek counts between surveying techniques. These findings suggest that using a cryogenically cooled mid-wave infrared camera from an aerial platform to conduct lek surveys is an effective alternative technique to conventional ground-based methods, but further research is needed. We discuss multiple advantages to aerial infrared surveys, including counting in remote areas, representing greater spatial variation, and increasing the number of counted leks per season. Aerial infrared lek counts may be a valuable wildlife management tool that releases time and resources for other conservation efforts. Opportunities exist for wildlife professionals to refine and apply aerial infrared techniques to wildlife monitoring programs because of the increasing reliability and affordability of this technology.

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3D Printing and NIR Fluorescence Imaging Techniques for the Fabrication of Implants

Materials ◽

10.3390/ma13214819 ◽

2020 ◽

Vol 13 (21) ◽

pp. 4819

Author(s):

Yong Joon Suh ◽

Tae Hyeon Lim ◽

Hak Soo Choi ◽

Moon Suk Kim ◽

Sang Jin Lee ◽

...

Keyword(s):

3D Printing ◽

Fluorescence Imaging ◽

Near Infrared ◽

Imaging Techniques ◽

The Body ◽

Monitoring Method ◽

Printing Technology ◽

3D Printing Technology ◽

Nir Fluorescence ◽

Printing Techniques

Three-dimensional (3D) printing technology holds great potential to fabricate complex constructs in the field of regenerative medicine. Researchers in the surgical fields have used 3D printing techniques and their associated biomaterials for education, training, consultation, organ transplantation, plastic surgery, surgical planning, dentures, and more. In addition, the universal utilization of 3D printing techniques enables researchers to exploit different types of hardware and software in, for example, the surgical fields. To realize the 3D-printed structures to implant them in the body and tissue regeneration, it is important to understand 3D printing technology and its enabling technologies. This paper concisely reviews 3D printing techniques in terms of hardware, software, and materials with a focus on surgery. In addition, it reviews bioprinting technology and a non-invasive monitoring method using near-infrared (NIR) fluorescence, with special attention to the 3D-bioprinted tissue constructs. NIR fluorescence imaging applied to 3D printing technology can play a significant role in monitoring the therapeutic efficacy of 3D structures for clinical implants. Consequently, these techniques can provide individually customized products and improve the treatment outcome of surgeries.

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Non-Intrusive Monitoring Algorithm for Resident Loads with Similar Electrical Characteristic

Processes ◽

10.3390/pr8111385 ◽

2020 ◽

Vol 8 (11) ◽

pp. 1385

Author(s):

Sheng Wu ◽

Kwok L. Lo

Keyword(s):

Neural Network ◽

Probability Distribution ◽

Bp Neural Network ◽

Distribution Curve ◽

Electrical Characteristics ◽

Monitoring Methods ◽

Monitoring Method ◽

Current Frequency ◽

Operation Pattern ◽

Load Monitoring

Non-intrusive load monitoring is a vital part of an overall load management scheme. One major disadvantage of existing non-intrusive load monitoring methods is the difficulty to accurately identify loads with similar electrical characteristics. To overcome the various switching probability of loads with similar characteristics in a specific time period, a new non-intrusive load monitoring method is proposed in this paper which will modify monitoring results based on load switching probability distribution curve. Firstly, according to the addition theorem of load working currents, the complex current is decomposed into the independently working current of each load. Secondly, based on the load working current, the initial identification of load is achieved with current frequency domain components, and then the load switching times in each hour is counted due to the initial identified results. Thirdly, a back propagation (BP) neural network is trained by the counted results, the switching probability distribution curve of an identified load is fitted with the BP neural network. Finally, the load operation pattern is profiled according to the switching probability distribution curve, the load operation pattern is used to modify identification result. The effectiveness of the method is verified by the measured data. This approach combines the operation pattern of load to modify the identification results, which improves the ability to identify loads with similar electrical characteristics.

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Development of Mass Spectrometry Selected Reaction Monitoring Method for Quantitation and Pharmacokinetic Study of Stepharine in Rabbit Plasma

Advances in Pharmacological Sciences ◽

10.1155/2014/961850 ◽

2014 ◽

Vol 2014 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Arthur T. Kopylov ◽

Ksenia G. Kuznetsova ◽

Olga M. Mikhailova ◽

Andrey G. Moshkin ◽

Vladimir V. Turkin ◽

...

Keyword(s):

Mass Spectrometry ◽

Pharmacokinetic Study ◽

Elimination Rate ◽

Apparent Volume ◽

The Body ◽

Selected Reaction Monitoring ◽

Reaction Monitoring ◽

Rabbit Plasma ◽

Monitoring Method ◽

Deviation Coefficient

Highly sensitive liquid chromatography mass spectrometry method on triple quadrupole (QQQ) mass spectrometer was successfully applied for pharmacokinetic study of stepharine in rabbit plasma. Specific ion transitions of stepharine protonated precursor ion were selected and recorded in the certain retention time employing dynamic selected reaction monitoring mode. The developed method facilitated quantitative measurements of stepharine in plasma samples in linear range of five orders of magnitude with high accuracy and low standard deviation coefficient and pharmacokinetics parameters were calculated. The apparent volume of stepharine distribution (estimated as ratio of clearance to elimination rate constant, data not shown) allows us to assume that stepharine was extensively distributed throughout the body.

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Effectiveness of a new one-hour blood pressure monitoring method to diagnose hypertension: a diagnostic accuracy clinical trial protocol

BMJ Open ◽

10.1136/bmjopen-2019-029268 ◽

2019 ◽

Vol 9 (5) ◽

pp. e029268

Author(s):

Luis González-de Paz ◽

Belchin Kostov ◽

Maria del Carme Alvira-Balada ◽

Cristina Colungo ◽

Noemí García ◽

...

Keyword(s):

Blood Pressure ◽

Sensitivity And Specificity ◽

Blood Pressure Monitoring ◽

Random Sequence ◽

Home Blood Pressure ◽

Monitoring Methods ◽

Pressure Monitoring ◽

Monitoring Method ◽

Policy Makers ◽

Patient’S Experience

Introduction24-hour ambulatory blood pressure monitoring (ABPM) is the gold standard diagnostic method for hypertension, but has some shortcomings in clinical practice while clinical settings often lack sufficient devices to accommodate all patients with suspected hypertension. Home blood pressure monitoring (HBPM) and office blood pressure monitoring (OBPM) also have shortcomings, such as the white coat effect or a lack of accuracy. This study aims to study the validity of a new method of diagnosing hypertension consisting of monitoring blood pressure (BP) for 1 hour and comparing it with OBPM and HBPM and examining the sensitivity and specificity of this method compared with 24-hour ABPM. The patient experience will be examined in each method.Methods and analysisA minimum sample of 214 patients requiring a diagnostic test for hypertension from three urban primary healthcare centres will be included. Participants will undergo 24-hour ABPM, 1-hour BP measurement (1-BPM), OBPM for three consecutive weeks and HBPM. Patients will follow a random sequence to first receive 24-hour ABPM or 1-hour ABPM. Daytime 24-hour ABPM records will be compared with the other monitoring methods using the correlation coefficient and Bland Altman plots. The kappa concordance index and the sensitivity and specificity of the methods will be calculated. The patient’s experience will be studied, with selected indicators of efficiency and satisfaction calculated using parametric tests.Ethics and disseminationThe protocol has been authorised by the research ethics committee of the Hospital Clinic of Barcelona (Ref. HCB/2014/0615): protocol details and amendments will be recorded and reported to ClinicalTrials.com. The results will be disseminated in peer-reviewed literature, and to policy makers and healthcare partners.Trial registrationNCT03147573; Pre-results.

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