We are all witnesses to the widespread use of wireless LANs (WLAN) and their easy implementation in indoor environments. Wi-Fi is the most popular technology for the WLAN. However, interference caused by building mate...We are all witnesses to the widespread use of wireless LANs (WLAN) and their easy implementation in indoor environments. Wi-Fi is the most popular technology for the WLAN. However, interference caused by building materials is a common, yet often overlooked, contributor to poor Wi-Fi performance. This interference occurs due to the nature of radio wave propagation and the characteristics of the wireless communication system. Therefore, during the implementation of these networks, one must consider the quasi-static nature of the Wi-Fi signal and its dependence on the influence of various building materials on the propagation of these waves. This paper presents the effects of building materials and structures on indoor environments for Wi-Fi 2.4 GHz and 5 GHz. To establish the interdependencies between factors influencing electric field levels, measurements were conducted in an experimental Wi-Fi network at different distances from the access point (AP). The results obtained show that the electric field strength of the Wi-Fi signal decreases depending on the distance, the building materials, and the transmitted frequency. Concrete material had the most significant impact on the strength of the electric field in Wi-Fi, while glass had a relatively minor effect on reducing it. Wi-Fi operates within the radio frequency spectrum, typically utilizing frequencies in the 2.4 GHz and 5 GHz bands. Additionally, measurements revealed that Wi-Fi signal penetration is more pronounced at lower frequencies (2.4 GHz) as opposed to the Wi-Fi signal 5 GHz. The findings can be used to address the impact of building materials and structures on indoor radio wave propagation, ultimately ensuring seamless Wi-Fi signal coverage within buildings.展开更多
For this study of long-term spatial patterns and trends of active fires in southern hemispheric Africa and on Madagascar from 2001 to 2020,active fire data from the MODIS FIRMS global fire data products were analyzed....For this study of long-term spatial patterns and trends of active fires in southern hemispheric Africa and on Madagascar from 2001 to 2020,active fire data from the MODIS FIRMS global fire data products were analyzed.The annual center of fire concentration tended to migrate toward the preserved rainforests and nature conservation areas in the Congo Basin and the mountain forests on the northeastern coast of Madagascar.Fire frequency varied seasonally at both study areas.We used geo statistical analysis techniques,such as measures of dispersion and emerging hot spot analysis,to reveal long-term trends in spatial patterns of fire events.In southern hemispheric Africa,the observed active fires tended to drift northward toward the Zambia-DRC border in the Congo basin.This northward migration progressed toward humid rainforests,which were better suited to sustaining repeated fire events.On Madagascar,the observed active fires tended to migrate toward the east coast in protected mountain forests.The spatial patterns of long-term trends showed a concentration of fires in the tropical regions of southern hemispheric Africa.Moreover,smaller clusters of new hot spots were located over eastern South Africa,overlapping with undifferentiated woodlands.On Madagascar,both hot and cold spots were identified and were separated by the highland region in the center of the island.Most of the eastern island was characterized by cold spots that received less precipitation than did the rest of the island.The presence of increasing hots spots in the densely vegetated areas highlights the urgent need for fire prevention and management in this region.展开更多
Turkey has a high potential for wildfires along its Mediterranean coast because of its dense forest cover and mild climate.An average of 250 wildfires occurs every year with more than 10,000 hectares destroyed due to ...Turkey has a high potential for wildfires along its Mediterranean coast because of its dense forest cover and mild climate.An average of 250 wildfires occurs every year with more than 10,000 hectares destroyed due to natural and human-related causes.The study area is sensitive to fires caused by lightning,stubble burning,discarded cigarette butts,electric arcing from power lines,deliberate fire setting,and traffic accidents.However,52%of causes could not be identified due to intense wildfires occurring at the same time and insufficient equipment and personnel.Since wildfires destroy forest cover,ecosystems,biodiversity,and habitats,they should be spatially evaluated by separating them according to their causes,considering environmental,climatic,topographic and forest structure variables that trigger wildfires.In this study,wildfires caused by lightning,the burning of agriculture stubble,discarded cigarette butts and power lines were investigated in the provinces of Aydin,Mugla and Antalya,where 22%of Turkey’s wildfires occurred.The MaxEnt method was used to determine the spatial distribution of wildfires to identify risk zones for each cause.Wildfires were used as the species distribution and the probability of their occurrence estimated.Additionally,since the causes of many wildfires are unknown,determining the causes is important for fire prediction and prevention.The highest wildfire occurrence risks were 9.7%for stubble burning,30.2%for lightning,4.5%for power lines and 16.9%by discarded cigarette butts.In total,1,266 of the 1,714 unknown wildfire causes were identified by the analysis of the cause-based risk zones and these were updated by including cause-as signed unknown wildfire locations for verification.As a result,the Area under the ROC Curve(AUC)values were increased for susceptibility maps.展开更多
文摘We are all witnesses to the widespread use of wireless LANs (WLAN) and their easy implementation in indoor environments. Wi-Fi is the most popular technology for the WLAN. However, interference caused by building materials is a common, yet often overlooked, contributor to poor Wi-Fi performance. This interference occurs due to the nature of radio wave propagation and the characteristics of the wireless communication system. Therefore, during the implementation of these networks, one must consider the quasi-static nature of the Wi-Fi signal and its dependence on the influence of various building materials on the propagation of these waves. This paper presents the effects of building materials and structures on indoor environments for Wi-Fi 2.4 GHz and 5 GHz. To establish the interdependencies between factors influencing electric field levels, measurements were conducted in an experimental Wi-Fi network at different distances from the access point (AP). The results obtained show that the electric field strength of the Wi-Fi signal decreases depending on the distance, the building materials, and the transmitted frequency. Concrete material had the most significant impact on the strength of the electric field in Wi-Fi, while glass had a relatively minor effect on reducing it. Wi-Fi operates within the radio frequency spectrum, typically utilizing frequencies in the 2.4 GHz and 5 GHz bands. Additionally, measurements revealed that Wi-Fi signal penetration is more pronounced at lower frequencies (2.4 GHz) as opposed to the Wi-Fi signal 5 GHz. The findings can be used to address the impact of building materials and structures on indoor radio wave propagation, ultimately ensuring seamless Wi-Fi signal coverage within buildings.
文摘For this study of long-term spatial patterns and trends of active fires in southern hemispheric Africa and on Madagascar from 2001 to 2020,active fire data from the MODIS FIRMS global fire data products were analyzed.The annual center of fire concentration tended to migrate toward the preserved rainforests and nature conservation areas in the Congo Basin and the mountain forests on the northeastern coast of Madagascar.Fire frequency varied seasonally at both study areas.We used geo statistical analysis techniques,such as measures of dispersion and emerging hot spot analysis,to reveal long-term trends in spatial patterns of fire events.In southern hemispheric Africa,the observed active fires tended to drift northward toward the Zambia-DRC border in the Congo basin.This northward migration progressed toward humid rainforests,which were better suited to sustaining repeated fire events.On Madagascar,the observed active fires tended to migrate toward the east coast in protected mountain forests.The spatial patterns of long-term trends showed a concentration of fires in the tropical regions of southern hemispheric Africa.Moreover,smaller clusters of new hot spots were located over eastern South Africa,overlapping with undifferentiated woodlands.On Madagascar,both hot and cold spots were identified and were separated by the highland region in the center of the island.Most of the eastern island was characterized by cold spots that received less precipitation than did the rest of the island.The presence of increasing hots spots in the densely vegetated areas highlights the urgent need for fire prevention and management in this region.
文摘Turkey has a high potential for wildfires along its Mediterranean coast because of its dense forest cover and mild climate.An average of 250 wildfires occurs every year with more than 10,000 hectares destroyed due to natural and human-related causes.The study area is sensitive to fires caused by lightning,stubble burning,discarded cigarette butts,electric arcing from power lines,deliberate fire setting,and traffic accidents.However,52%of causes could not be identified due to intense wildfires occurring at the same time and insufficient equipment and personnel.Since wildfires destroy forest cover,ecosystems,biodiversity,and habitats,they should be spatially evaluated by separating them according to their causes,considering environmental,climatic,topographic and forest structure variables that trigger wildfires.In this study,wildfires caused by lightning,the burning of agriculture stubble,discarded cigarette butts and power lines were investigated in the provinces of Aydin,Mugla and Antalya,where 22%of Turkey’s wildfires occurred.The MaxEnt method was used to determine the spatial distribution of wildfires to identify risk zones for each cause.Wildfires were used as the species distribution and the probability of their occurrence estimated.Additionally,since the causes of many wildfires are unknown,determining the causes is important for fire prediction and prevention.The highest wildfire occurrence risks were 9.7%for stubble burning,30.2%for lightning,4.5%for power lines and 16.9%by discarded cigarette butts.In total,1,266 of the 1,714 unknown wildfire causes were identified by the analysis of the cause-based risk zones and these were updated by including cause-as signed unknown wildfire locations for verification.As a result,the Area under the ROC Curve(AUC)values were increased for susceptibility maps.
