scholarly journals Developing a thermal suitability index to assess artificial turf applications for various site-weather and user-activity scenarios

2022 ◽  
Vol 217 ◽  
pp. 104276
Author(s):  
Yuan Shi ◽  
C.Y. Jim
Keyword(s):  
Artificial Turf ◽  
Suitability Index ◽  
User Activity

Predicting bycatch hotspots based on suitable habitat derived from fishery-independent data

2020 ◽  
Vol 641 ◽  
pp. 159-175
Author(s):  
J Runnebaum ◽  
KR Tanaka ◽  
L Guan ◽  
J Cao ◽  
L O’Brien ◽  
...  
Keyword(s):  
Habitat Suitability ◽  
Mixed Model ◽  
Linear Mixed Model ◽  
Gulf Of Maine ◽  
Homarus Americanus ◽  
Management Tool ◽  
American Lobster ◽  
Suitable Habitat ◽  
Climate Conditions ◽  
Suitability Index

Bycatch remains a global problem in managing sustainable fisheries. A critical aspect of management is understanding the timing and spatial extent of bycatch. Fisheries management often relies on observed bycatch data, which are not always available due to a lack of reporting or observer coverage. Alternatively, analyzing the overlap in suitable habitat for the target and non-target species can provide a spatial management tool to understand where bycatch interactions are likely to occur. Potential bycatch hotspots based on suitable habitat were predicted for cusk Brosme brosme incidentally caught in the Gulf of Maine American lobster Homarus americanus fishery. Data from multiple fisheries-independent surveys were combined in a delta-generalized linear mixed model to generate spatially explicit density estimates for use in an independent habitat suitability index. The habitat suitability indices for American lobster and cusk were then compared to predict potential bycatch hotspot locations. Suitable habitat for American lobster has increased between 1980 and 2013 while suitable habitat for cusk decreased throughout most of the Gulf of Maine, except for Georges Basin and the Great South Channel. The proportion of overlap in suitable habitat varied interannually but decreased slightly in the spring and remained relatively stable in the fall over the time series. As Gulf of Maine temperatures continue to increase, the interactions between American lobster and cusk are predicted to decline as cusk habitat continues to constrict. This framework can contribute to fisheries managers’ understanding of changes in habitat overlap as climate conditions continue to change and alter where bycatch interactions could occur.

The Development of Habitat Suitability Index Model of Class I Endangered Wildlife, Sedirea japonica - A Case Study of Korea National Park of Dadohaehaesang -

2020 ◽  
Vol 32 (1) ◽  
pp. 153-172
Author(s):  
Yun-Jin Shim ◽  
Yong-Su Park ◽  
Rae-Ha Jang ◽  
Young-Jun Yoon ◽  
Sun- Ryoung Kim ◽  
...  
Keyword(s):  
Habitat Suitability ◽  
National Park ◽  
Class I ◽  
Habitat Suitability Index ◽  
Index Model ◽  
Suitability Index

The analysis of measurements of flatness of the artificial surfaces of the runway of civil aerodrome

2018 ◽  
pp. 14-23
Author(s):  
А. Богоявленский ◽  
A. Bogoyavlenskiy
Keyword(s):  
Artificial Turf ◽  
Artificial Surfaces ◽  
Physical Quantities

One of the most important characteristics of the runways with artificial turf of civil airfields is their evenness. Passengers of the mainline aircraft – both in domestic and foreign airportssubjectively assess the airfield pavements evenness by the presence or absence of shaking during the movement of the aircraft on the runway both during takeoff and landing. In units of what physical quantities, by what means and methods is measured (estimated) the evenness of aerodrome surfaces? How to ensure of the traceability of measurements from the primary national etalon of parameter to the value of the measured value. About it-this publication.

AO-BBO: A Novel Optimization Algorithm and Its Application in Plant Drug Extraction

2019 ◽  
Vol 19 (2) ◽  
pp. 139-145 ◽  
Author(s):  
Bote Lv ◽  
Juan Chen ◽  
Boyan Liu ◽  
Cuiying Dong
Keyword(s):  
Optimization Algorithm ◽  
Learning Strategy ◽  
Optimal Solution ◽  
Population Diversity ◽  
Global Optimal Solution ◽  
Plant Medicine ◽  
Suitability Index ◽  
Sensing Model ◽  
Local Optimal Solution ◽  
Global Optimal

<P>Introduction: It is well-known that the biogeography-based optimization (BBO) algorithm lacks searching power in some circumstances. </P><P> Material & Methods: In order to address this issue, an adaptive opposition-based biogeography-based optimization algorithm (AO-BBO) is proposed. Based on the BBO algorithm and opposite learning strategy, this algorithm chooses different opposite learning probabilities for each individual according to the habitat suitability index (HSI), so as to avoid elite individuals from returning to local optimal solution. Meanwhile, the proposed method is tested in 9 benchmark functions respectively. </P><P> Result: The results show that the improved AO-BBO algorithm can improve the population diversity better and enhance the search ability of the global optimal solution. The global exploration capability, convergence rate and convergence accuracy have been significantly improved. Eventually, the algorithm is applied to the parameter optimization of soft-sensing model in plant medicine extraction rate. Conclusion: The simulation results show that the model obtained by this method has higher prediction accuracy and generalization ability.</P>

scholarly journals Improving Cloud Storage Search with User Activity

2021 ◽  
Author(s):  
Rolf Jagerman ◽  
Weize Kong ◽  
Rama Kumar Pasumarthi ◽  
Zhen Qin ◽  
Michael Bendersky ◽  
...  
Keyword(s):  
Cloud Storage ◽  
User Activity

scholarly journals Smartphone-Based Activity Recognition in a Pedestrian Navigation Context

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3243
Author(s):  
Robert Jackermeier ◽  
Bernd Ludwig
Keyword(s):  
Activity Recognition ◽  
Recognition Performance ◽  
Activity Patterns ◽  
Detailed Knowledge ◽  
Navigation Systems ◽  
Pedestrian Navigation ◽  
User Activity ◽  
Device Placement ◽  
Locomotion Behavior ◽  
Current Context

In smartphone-based pedestrian navigation systems, detailed knowledge about user activity and device placement is a key information. Landmarks such as staircases or elevators can help the system in determining the user position when located inside buildings, and navigation instructions can be adapted to the current context in order to provide more meaningful assistance. Typically, most human activity recognition (HAR) approaches distinguish between general activities such as walking, standing or sitting. In this work, we investigate more specific activities that are tailored towards the use-case of pedestrian navigation, including different kinds of stationary and locomotion behavior. We first collect a dataset of 28 combinations of device placements and activities, in total consisting of over 6 h of data from three sensors. We then use LSTM-based machine learning (ML) methods to successfully train hierarchical classifiers that can distinguish between these placements and activities. Test results show that the accuracy of device placement classification (97.2%) is on par with a state-of-the-art benchmark in this dataset while being less resource-intensive on mobile devices. Activity recognition performance highly depends on the classification task and ranges from 62.6% to 98.7%, once again performing close to the benchmark. Finally, we demonstrate in a case study how to apply the hierarchical classifiers to experimental and naturalistic datasets in order to analyze activity patterns during the course of a typical navigation session and to investigate the correlation between user activity and device placement, thereby gaining insights into real-world navigation behavior.

scholarly journals Influence of the artificial turf certification on physical performance and muscle damage in football players (QUALTURF PROJECT)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Javier Sanchez-Sanchez ◽  
Jose Luis Felipe ◽  
Antonio Hernandez-Martin ◽  
David Viejo-Romero ◽  
Vicente Javier Clemente-Suarez ◽  
...  
Keyword(s):  
Muscle Damage ◽  
Football Players ◽  
Artificial Turf ◽  
Post Exercise ◽  
Perceived Effort ◽  
Risk Of Injury ◽  
Football Team ◽  
Randomized Design ◽  
Exercise Muscle ◽  
Simulated Match

AbstractThis study aimed to analyse the influence of the FIFA Quality PRO certification of artificial turf pitches on the physical, physiological performance and muscle damage in soccer players. Fifteen healthy male players (21.2 ± 1.4 years; 178.2 ± 4.3 cm; 79.1 ± 8.3 kg) from a university football team were selected to participate in the research. Mechanical properties related to surface–player interaction were assessed on the two surfaces selected for this study. A randomized design was used and the players performed the Ball-sport Endurance and Sprint Test (BEAST90) on the different artificial turf fields. Average time of the 20 m sprints was longer on the FIFA Quality Pro surface than on the non-certified pitch (+ 0.13 s; p < 0.05; CI 95% − 0.01 to 0.27; ES: 0.305). The players’ perceived effort was higher in the first (+ 2.64; p < 0.05; CI 95% 0.92 to 4.35; ES: 1.421) and the second half (+ 1.35; p < 0.05; CI 95% − 0.02 to 2.72; ES: 0.637) of the test on the FIFA Quality Pro field. Comparative analysis between surfaces showed no significant differences in the time spent in each of the heart rate zones and higher concentrations of CK (+ 196.58; p > 0.05; CI 95% 66.54 to 326.61; ES: 1.645) were evidenced in the non-certified pitch surface. In response to a simulated match protocol, markers of post-exercise muscle damage may be reduced on accredited artificial turf fields. These insights can provide the opportunity to maximize the efficiency of training sessions and reduce the risk of injury during the season.

scholarly journals An Information Recommendation Technique Based on Influence and Activeness of Users in Social Networks

2021 ◽  
Vol 11 (6) ◽  
pp. 2530
Author(s):  
Minsoo Lee ◽  
Soyeon Oh
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Recommendation Systems ◽  
Network Services ◽  
The Past ◽  
User Behaviors ◽  
User Influence ◽  
User Activity ◽  
Information Recommendation ◽  
Social Network Services

Over the past few years, the number of users of social network services has been exponentially increasing and it is now a natural source of data that can be used by recommendation systems to provide important services to humans by analyzing applicable data and providing personalized information to users. In this paper, we propose an information recommendation technique that enables smart recommendations based on two specific types of analysis on user behaviors, such as the user influence and user activity. The components to measure the user influence and user activity are identified. The accuracy of the information recommendation is verified using Yelp data and shows significantly promising results that could create smarter information recommendation systems.

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