The Experts below are selected from a list of 108 Experts worldwide ranked by ideXlab platform
Bouché Philippe - One of the best experts on this subject based on the ideXlab platform.
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L'imagerie drone révèle de nouvelles opportunités d'inventaire pour les populations d'hippopotames
'Public Library of Science (PLoS)', 2018Co-Authors: Linchant Julie, Lhoest Simon, Quevauvillers Samuel, Lejeune Philippe, Vermeulen Cédric, Semeki Ngabinzeke Jean, Luse Belanganayi Basile, Delvingt Willy, Bouché PhilippeAbstract:Introduction The common hippopotamus Hippopotamus amphibius L. is a vulnerable species that requires efficient methods to monitor its populations for conservation purposes. Rapid evolution of civil drones provides new opportunities but survey protocols still Need Development. This study aims to determine the optimal flight parameters for accurate population estimates. A second objective is to evaluate the effects of three environmental factors: wind speed, sun reflection and cloud cover. Method We estimated the population of two main hippo schools (Dungu and Wilibadi II) located in Garamba National Park in Democratic republic of Congo. Eight observers reviewed 252 photos taken over the Dungu school, representing a total of 2016 experimental units. A detection rate and a level of certainty were associated with each experimental unit, and five parameters were related to each count: flight height, three environmental parameters (sun reflection on water surface, cloud cover, and wind speed), and observers’ experience. Results Flight height reduced the observers’ confidence in their detection ability, rather than the detection itself. For accurate counts of large groups an average height of 150 m was shown to be a good compromise between animal detection without zooming in and the area covered in one frame. Wind speed had little influence on the counts, but it affected the performance of the UAS. Sun reflection reduced the detection rate of hippos and increased level of certainty, while cloud cover reduced detection rates slightly. Therefore, we recommend flying when the sun is still low on the horizon and when there is little cloud, or when cloud cover is light and even. This last point reinforces our recommendation for flights early in the day. The counts also showed large differences between groups of inexperienced and experienced observers. Experienced observers achieved better detection rates and were generally more confident in their detection. Experienced observers detected 86.5% of the hippos on average (confidence interval = ±0.76%). When applied to data from the second site, the detection was 84.3% (confidence interval = ±1.84%). Two correction factors were then calculated, as the inverse of the detection rate, based on the estimated number of hippos present during one flight (Factor 1) or in the general population respectively (Factor 2). Factor 2 especially was consistent with previous studies using traditional aerial counts (1.22 vs 1.25). Factor 2 was found to be appropriate for use by experienced observers. These results confirm the use of correction factor 2 for hippo surveys, regardless of the study site, as it accounts for hippo behavior. Optimum counting and cost efficiency were achieved with two trained observers counting 7 pictures. Conclusion This study is a promising approach for routine surveys of the hippopotamus which is a species usually ignored in wildlife counts. Drone technology is expected to improve rapidly; therefore UAS could become a very useful and affordable survey tool for other species requiring specific monitoring.Peer reviewe
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L'imagerie drone révèle de nouvelles opportunités d'inventaire pour les populations d'hippopotames
'Public Library of Science (PLoS)', 2018Co-Authors: Linchant Julie, Lhoest Simon, Quevauvillers Samuel, Lejeune Philippe, Vermeulen Cédric, Semeki Ngabinzeke Jean, Luse Belanganayi Basile, Delvingt Willy, Bouché PhilippeAbstract:peer reviewedaudience: researcher, professional, student, popularization, otherIntroduction The common hippopotamus Hippopotamus amphibius L. is a vulnerable species that requires efficient methods to monitor its populations for conservation purposes. Rapid evolution of civil drones provides new opportunities but survey protocols still Need Development. This study aims to determine the optimal flight parameters for accurate population estimates. A second objective is to evaluate the effects of three environmental factors: wind speed, sun reflection and cloud cover. Method We estimated the population of two main hippo schools (Dungu and Wilibadi II) located in Garamba National Park in Democratic republic of Congo. Eight observers reviewed 252 photos taken over the Dungu school, representing a total of 2016 experimental units. A detection rate and a level of certainty were associated with each experimental unit, and five parameters were related to each count: flight height, three environmental parameters (sun reflection on water surface, cloud cover, and wind speed), and observers’ experience. Results Flight height reduced the observers’ confidence in their detection ability, rather than the detection itself. For accurate counts of large groups an average height of 150 m was shown to be a good compromise between animal detection without zooming in and the area covered in one frame. Wind speed had little influence on the counts, but it affected the performance of the UAS. Sun reflection reduced the detection rate of hippos and increased level of certainty, while cloud cover reduced detection rates slightly. Therefore, we recommend flying when the sun is still low on the horizon and when there is little cloud, or when cloud cover is light and even. This last point reinforces our recommendation for flights early in the day. The counts also showed large differences between groups of inexperienced and experienced observers. Experienced observers achieved better detection rates and were generally more confident in their detection. Experienced observers detected 86.5% of the hippos on average (confidence interval = ±0.76%). When applied to data from the second site, the detection was 84.3% (confidence interval = ±1.84%). Two correction factors were then calculated, as the inverse of the detection rate, based on the estimated number of hippos present during one flight (Factor 1) or in the general population respectively (Factor 2). Factor 2 especially was consistent with previous studies using traditional aerial counts (1.22 vs 1.25). Factor 2 was found to be appropriate for use by experienced observers. These results confirm the use of correction factor 2 for hippo surveys, regardless of the study site, as it accounts for hippo behavior. Optimum counting and cost efficiency were achieved with two trained observers counting 7 pictures. Conclusion This study is a promising approach for routine surveys of the hippopotamus which is a species usually ignored in wildlife counts. Drone technology is expected to improve rapidly; therefore UAS could become a very useful and affordable survey tool for other species requiring specific monitoring.Forests and Climate Change in the Congo Research Project, funded under the Letter of Agreement between the Center for International Forestry Research (CIFOR) and Gembloux Agro- Bio-Tech in University of Liège (ULg / GxABT
Rory B Weiner - One of the best experts on this subject based on the ideXlab platform.
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appropriate use criteria a review of Need Development and applications
Expert Review of Cardiovascular Therapy, 2016Co-Authors: Sacha R Bhatia, Mostafa Alabousi, David M Dudzinski, Rory B WeinerAbstract:The costs of healthcare in developed countries have seen a dramatic increase in tandem with the increasing utilization of diagnostic testing. As a result, Appropriate Use Criteria (AUC)-based practices have become more commonplace as a provider-driven solution to reducing unnecessary tests and procedures across various specialty societies. The AUC are meant to serve as a distinct entity from clinical guidelines to help inform clinicians of the 'appropriateness' of a diagnostic test or procedure. In this article, we discuss the Development, implementation, impact, and practical applications of AUC to improve appropriate utilization by providers, healthcare institutions, payers, and policy makers. We also focus on the role of education and feedback as a potentially efficacious future method of implementation of global quality improvement and cost-mitigating strategies. AUC represent a growing quality improvement tool in cardiovascular medicine that can play an important role in reducing inappropriate testing while preserving physician autonomy.
Linchant Julie - One of the best experts on this subject based on the ideXlab platform.
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L'imagerie drone révèle de nouvelles opportunités d'inventaire pour les populations d'hippopotames
'Public Library of Science (PLoS)', 2018Co-Authors: Linchant Julie, Lhoest Simon, Quevauvillers Samuel, Lejeune Philippe, Vermeulen Cédric, Semeki Ngabinzeke Jean, Luse Belanganayi Basile, Delvingt Willy, Bouché PhilippeAbstract:Introduction The common hippopotamus Hippopotamus amphibius L. is a vulnerable species that requires efficient methods to monitor its populations for conservation purposes. Rapid evolution of civil drones provides new opportunities but survey protocols still Need Development. This study aims to determine the optimal flight parameters for accurate population estimates. A second objective is to evaluate the effects of three environmental factors: wind speed, sun reflection and cloud cover. Method We estimated the population of two main hippo schools (Dungu and Wilibadi II) located in Garamba National Park in Democratic republic of Congo. Eight observers reviewed 252 photos taken over the Dungu school, representing a total of 2016 experimental units. A detection rate and a level of certainty were associated with each experimental unit, and five parameters were related to each count: flight height, three environmental parameters (sun reflection on water surface, cloud cover, and wind speed), and observers’ experience. Results Flight height reduced the observers’ confidence in their detection ability, rather than the detection itself. For accurate counts of large groups an average height of 150 m was shown to be a good compromise between animal detection without zooming in and the area covered in one frame. Wind speed had little influence on the counts, but it affected the performance of the UAS. Sun reflection reduced the detection rate of hippos and increased level of certainty, while cloud cover reduced detection rates slightly. Therefore, we recommend flying when the sun is still low on the horizon and when there is little cloud, or when cloud cover is light and even. This last point reinforces our recommendation for flights early in the day. The counts also showed large differences between groups of inexperienced and experienced observers. Experienced observers achieved better detection rates and were generally more confident in their detection. Experienced observers detected 86.5% of the hippos on average (confidence interval = ±0.76%). When applied to data from the second site, the detection was 84.3% (confidence interval = ±1.84%). Two correction factors were then calculated, as the inverse of the detection rate, based on the estimated number of hippos present during one flight (Factor 1) or in the general population respectively (Factor 2). Factor 2 especially was consistent with previous studies using traditional aerial counts (1.22 vs 1.25). Factor 2 was found to be appropriate for use by experienced observers. These results confirm the use of correction factor 2 for hippo surveys, regardless of the study site, as it accounts for hippo behavior. Optimum counting and cost efficiency were achieved with two trained observers counting 7 pictures. Conclusion This study is a promising approach for routine surveys of the hippopotamus which is a species usually ignored in wildlife counts. Drone technology is expected to improve rapidly; therefore UAS could become a very useful and affordable survey tool for other species requiring specific monitoring.Peer reviewe
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L'imagerie drone révèle de nouvelles opportunités d'inventaire pour les populations d'hippopotames
'Public Library of Science (PLoS)', 2018Co-Authors: Linchant Julie, Lhoest Simon, Quevauvillers Samuel, Lejeune Philippe, Vermeulen Cédric, Semeki Ngabinzeke Jean, Luse Belanganayi Basile, Delvingt Willy, Bouché PhilippeAbstract:peer reviewedaudience: researcher, professional, student, popularization, otherIntroduction The common hippopotamus Hippopotamus amphibius L. is a vulnerable species that requires efficient methods to monitor its populations for conservation purposes. Rapid evolution of civil drones provides new opportunities but survey protocols still Need Development. This study aims to determine the optimal flight parameters for accurate population estimates. A second objective is to evaluate the effects of three environmental factors: wind speed, sun reflection and cloud cover. Method We estimated the population of two main hippo schools (Dungu and Wilibadi II) located in Garamba National Park in Democratic republic of Congo. Eight observers reviewed 252 photos taken over the Dungu school, representing a total of 2016 experimental units. A detection rate and a level of certainty were associated with each experimental unit, and five parameters were related to each count: flight height, three environmental parameters (sun reflection on water surface, cloud cover, and wind speed), and observers’ experience. Results Flight height reduced the observers’ confidence in their detection ability, rather than the detection itself. For accurate counts of large groups an average height of 150 m was shown to be a good compromise between animal detection without zooming in and the area covered in one frame. Wind speed had little influence on the counts, but it affected the performance of the UAS. Sun reflection reduced the detection rate of hippos and increased level of certainty, while cloud cover reduced detection rates slightly. Therefore, we recommend flying when the sun is still low on the horizon and when there is little cloud, or when cloud cover is light and even. This last point reinforces our recommendation for flights early in the day. The counts also showed large differences between groups of inexperienced and experienced observers. Experienced observers achieved better detection rates and were generally more confident in their detection. Experienced observers detected 86.5% of the hippos on average (confidence interval = ±0.76%). When applied to data from the second site, the detection was 84.3% (confidence interval = ±1.84%). Two correction factors were then calculated, as the inverse of the detection rate, based on the estimated number of hippos present during one flight (Factor 1) or in the general population respectively (Factor 2). Factor 2 especially was consistent with previous studies using traditional aerial counts (1.22 vs 1.25). Factor 2 was found to be appropriate for use by experienced observers. These results confirm the use of correction factor 2 for hippo surveys, regardless of the study site, as it accounts for hippo behavior. Optimum counting and cost efficiency were achieved with two trained observers counting 7 pictures. Conclusion This study is a promising approach for routine surveys of the hippopotamus which is a species usually ignored in wildlife counts. Drone technology is expected to improve rapidly; therefore UAS could become a very useful and affordable survey tool for other species requiring specific monitoring.Forests and Climate Change in the Congo Research Project, funded under the Letter of Agreement between the Center for International Forestry Research (CIFOR) and Gembloux Agro- Bio-Tech in University of Liège (ULg / GxABT
Sacha R Bhatia - One of the best experts on this subject based on the ideXlab platform.
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appropriate use criteria a review of Need Development and applications
Expert Review of Cardiovascular Therapy, 2016Co-Authors: Sacha R Bhatia, Mostafa Alabousi, David M Dudzinski, Rory B WeinerAbstract:The costs of healthcare in developed countries have seen a dramatic increase in tandem with the increasing utilization of diagnostic testing. As a result, Appropriate Use Criteria (AUC)-based practices have become more commonplace as a provider-driven solution to reducing unnecessary tests and procedures across various specialty societies. The AUC are meant to serve as a distinct entity from clinical guidelines to help inform clinicians of the 'appropriateness' of a diagnostic test or procedure. In this article, we discuss the Development, implementation, impact, and practical applications of AUC to improve appropriate utilization by providers, healthcare institutions, payers, and policy makers. We also focus on the role of education and feedback as a potentially efficacious future method of implementation of global quality improvement and cost-mitigating strategies. AUC represent a growing quality improvement tool in cardiovascular medicine that can play an important role in reducing inappropriate testing while preserving physician autonomy.
Quevauvillers Samuel - One of the best experts on this subject based on the ideXlab platform.
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L'imagerie drone révèle de nouvelles opportunités d'inventaire pour les populations d'hippopotames
'Public Library of Science (PLoS)', 2018Co-Authors: Linchant Julie, Lhoest Simon, Quevauvillers Samuel, Lejeune Philippe, Vermeulen Cédric, Semeki Ngabinzeke Jean, Luse Belanganayi Basile, Delvingt Willy, Bouché PhilippeAbstract:Introduction The common hippopotamus Hippopotamus amphibius L. is a vulnerable species that requires efficient methods to monitor its populations for conservation purposes. Rapid evolution of civil drones provides new opportunities but survey protocols still Need Development. This study aims to determine the optimal flight parameters for accurate population estimates. A second objective is to evaluate the effects of three environmental factors: wind speed, sun reflection and cloud cover. Method We estimated the population of two main hippo schools (Dungu and Wilibadi II) located in Garamba National Park in Democratic republic of Congo. Eight observers reviewed 252 photos taken over the Dungu school, representing a total of 2016 experimental units. A detection rate and a level of certainty were associated with each experimental unit, and five parameters were related to each count: flight height, three environmental parameters (sun reflection on water surface, cloud cover, and wind speed), and observers’ experience. Results Flight height reduced the observers’ confidence in their detection ability, rather than the detection itself. For accurate counts of large groups an average height of 150 m was shown to be a good compromise between animal detection without zooming in and the area covered in one frame. Wind speed had little influence on the counts, but it affected the performance of the UAS. Sun reflection reduced the detection rate of hippos and increased level of certainty, while cloud cover reduced detection rates slightly. Therefore, we recommend flying when the sun is still low on the horizon and when there is little cloud, or when cloud cover is light and even. This last point reinforces our recommendation for flights early in the day. The counts also showed large differences between groups of inexperienced and experienced observers. Experienced observers achieved better detection rates and were generally more confident in their detection. Experienced observers detected 86.5% of the hippos on average (confidence interval = ±0.76%). When applied to data from the second site, the detection was 84.3% (confidence interval = ±1.84%). Two correction factors were then calculated, as the inverse of the detection rate, based on the estimated number of hippos present during one flight (Factor 1) or in the general population respectively (Factor 2). Factor 2 especially was consistent with previous studies using traditional aerial counts (1.22 vs 1.25). Factor 2 was found to be appropriate for use by experienced observers. These results confirm the use of correction factor 2 for hippo surveys, regardless of the study site, as it accounts for hippo behavior. Optimum counting and cost efficiency were achieved with two trained observers counting 7 pictures. Conclusion This study is a promising approach for routine surveys of the hippopotamus which is a species usually ignored in wildlife counts. Drone technology is expected to improve rapidly; therefore UAS could become a very useful and affordable survey tool for other species requiring specific monitoring.Peer reviewe
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L'imagerie drone révèle de nouvelles opportunités d'inventaire pour les populations d'hippopotames
'Public Library of Science (PLoS)', 2018Co-Authors: Linchant Julie, Lhoest Simon, Quevauvillers Samuel, Lejeune Philippe, Vermeulen Cédric, Semeki Ngabinzeke Jean, Luse Belanganayi Basile, Delvingt Willy, Bouché PhilippeAbstract:peer reviewedaudience: researcher, professional, student, popularization, otherIntroduction The common hippopotamus Hippopotamus amphibius L. is a vulnerable species that requires efficient methods to monitor its populations for conservation purposes. Rapid evolution of civil drones provides new opportunities but survey protocols still Need Development. This study aims to determine the optimal flight parameters for accurate population estimates. A second objective is to evaluate the effects of three environmental factors: wind speed, sun reflection and cloud cover. Method We estimated the population of two main hippo schools (Dungu and Wilibadi II) located in Garamba National Park in Democratic republic of Congo. Eight observers reviewed 252 photos taken over the Dungu school, representing a total of 2016 experimental units. A detection rate and a level of certainty were associated with each experimental unit, and five parameters were related to each count: flight height, three environmental parameters (sun reflection on water surface, cloud cover, and wind speed), and observers’ experience. Results Flight height reduced the observers’ confidence in their detection ability, rather than the detection itself. For accurate counts of large groups an average height of 150 m was shown to be a good compromise between animal detection without zooming in and the area covered in one frame. Wind speed had little influence on the counts, but it affected the performance of the UAS. Sun reflection reduced the detection rate of hippos and increased level of certainty, while cloud cover reduced detection rates slightly. Therefore, we recommend flying when the sun is still low on the horizon and when there is little cloud, or when cloud cover is light and even. This last point reinforces our recommendation for flights early in the day. The counts also showed large differences between groups of inexperienced and experienced observers. Experienced observers achieved better detection rates and were generally more confident in their detection. Experienced observers detected 86.5% of the hippos on average (confidence interval = ±0.76%). When applied to data from the second site, the detection was 84.3% (confidence interval = ±1.84%). Two correction factors were then calculated, as the inverse of the detection rate, based on the estimated number of hippos present during one flight (Factor 1) or in the general population respectively (Factor 2). Factor 2 especially was consistent with previous studies using traditional aerial counts (1.22 vs 1.25). Factor 2 was found to be appropriate for use by experienced observers. These results confirm the use of correction factor 2 for hippo surveys, regardless of the study site, as it accounts for hippo behavior. Optimum counting and cost efficiency were achieved with two trained observers counting 7 pictures. Conclusion This study is a promising approach for routine surveys of the hippopotamus which is a species usually ignored in wildlife counts. Drone technology is expected to improve rapidly; therefore UAS could become a very useful and affordable survey tool for other species requiring specific monitoring.Forests and Climate Change in the Congo Research Project, funded under the Letter of Agreement between the Center for International Forestry Research (CIFOR) and Gembloux Agro- Bio-Tech in University of Liège (ULg / GxABT
