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801.
Phenomenal progress has been witnessed in the field of Geographic Information System (GIS) in recent times. The development of webGIS is the result of the growth of the Internet and consequently World Wide Web. The webGIS architecture is continuously changing according to contemporary technologies and requirements. In this paper, webGIS and its architectures are reviewed. Firstly, GIS and invention of the Internet are discussed. Evolution of webGIS is then covered along with major milestones of its development and open source initiatives. It is followed by discussion on client server architecture and its types. Thick and thin client architectures are then described and compared. As the paradigm in the computing world shifted towards web services, service-oriented architecture (SOA) is also discussed in context of webGIS. Spatial cloud computing and cloud-based architecture for webGIS are then described. The paper also provides a comparison of different webGIS architectures so that suitable architecture can be selected by the user based upon the requirements. 相似文献
802.
The present investigation attempts to quantify the temporal variation of Solar Flare Index(SFI)with other activity indices during solar cycles 21-24 by using different techniques such as linear regression,correlation,cross-correlation with phase lag-lead,etc.Different Solar Activity Indices(SAI)considered in this present study are Sunspot Number(SSN),10.7 cm Solar Radio Flux(F10.7),Coronal Index(CI)and MgⅡCore-to-Wing Ratio(MgⅡ).The maximum cycle amplitude of SFI and considered SAI has a decreasing trend from solar cycle 22,and cycle 24 is the weakest solar cycle among all other cycles.The SFI with SSN,F10.7,CI and MgⅡshows hysteresis during all cycles except for solar cycle 22 where both paths for ascending and descending phases are intercepting each other,thereby representing a phase reversal.A positive hysteresis circulation exists between SFI and considered SAI during solar cycles 22 and 23,whereas a negative circulation exists in cycles 21 and 24.SFI has a high positive correlation with coefficient values of 0.92,0.94,0.84 and 0.81 for SSN,F10.7,CI and MgⅡrespectively.According to crosscorrelation analysis,SFI has a phase lag with considered SAI during an odd-number solar cycle(solar cycles21 and 23)but no phase lag/lead during an even-numbered solar cycle(solar cycles 22 and 24).However,the entire smoothed monthly average SFI data indicate an in-phase relationship with SSN,F10.7 and MgⅡ,and a one-month phase lag with CI.The presence of those above characteristics strongly confirms the outcomes of different research work with various solar indices and the highest correlation exists between SFI and SSN as well as F10.7 which establishes that SFI may be considered as one of the prime activity indices to interpret the characteristics of the Sun’s active region as well as for more accurate short-range or long-range forecasting of solar events. 相似文献