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فرقت

فرقت

دل رو رو وقت گزار گیا
غم یار دا سانوں مار گیا

جدوں ماہی دے کول وسدے سی
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دل یار نوں ڈھونڈن چلیا اے
کر وعدہ یار نہ ولیا اے
میرے دل وچ بھانبھڑ بلیا اے
تیر شوق دا ہو ہن پار گیا

دل یار بناء ہون رہندا نئیں
اے درد ہجر دے سہندا نئیں
دکھ درد کسے نوں اے کہندا نئیں
سکھ چین تے نال قرار گیا

عشق دے روگوں رب بچائے
یار بنا ہن چین نہ آئے
شوق سجن دا ودھدا جائے
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ہک دن درشن یار دا پاویں
سوہنا ملے تاں دکھ ہزار گیا

Some Problematic Aspects of Coliform Bacteria Clustering on Medical Images in the Task of Identifying Possible Diseases

Medical image analysis methods are one of the sources for obtaining additional information about the investigated phenomena. We are looking at images of coliform bacteria. Analysis of these images allows you to determine the possibility of developing certain diseases. To do this, it is necessary to cluster the set of bacteria and count the bacteria. The paper highlights the features of clustering for coliform bacteria. Clustering results for real data are presented.

Quantification of Aerosol Properties in Four Locations in Indo-Gangetic Plain: Implications for Climatic Impacts

This thesis provides an intercomparison of aerosol optical depth (AOD) retrievals from satellite-based MODerate resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), Ozone Monitoring Instrument (OMI), and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) instrumentation at four sites with different aerosol environments (Karachi, Lahore, Jaipur, and Kanpur) in Indo-Gangetic Plain (IGP) during 2007-2013, with validation against AOD observations from the ground-based AERosol RObotic NETwork (AERONET). Both MODIS Deep Blue (MODISDB) and MODIS Standard (MODISSTD) products were compared with the AERONET products. The MODISSTD-AERONET comparisons revealed a high degree of correlation for the four investigated sites at Karachi, Lahore, Jaipur, and Kanpur, the MODISDB-AERONET comparisons revealed even better correlations, and the MISR-AERONET comparisons also indicated strong correlations, as did the OMI-AERONET comparisons, while the CALIPSO-AERONET comparisons revealed only poor correlations due to the limited number of data points available. We also computed the Root Mean Square error (RMSE), Mean Absolute Error (MAE) and Root Mean Bias (RMB). Using AERONET data to validate MODISSTD, MODISDB, MISR, OMI, and CALIPSO data revealed that MODISSTD data was more accurate over vegetated locations than over un-vegetated locations, while MISR data was more accurate over areas closer to the ocean than over other areas. The MISR instrument performed better than the other instruments over Karachi and Kanpur, while the MODISSTD AOD retrievals were better than those from the other instruments over Lahore and Jaipur. We also computed the Expected Error Bounds (EEBs) for both MODIS retrievals and found that MODISSTD consistently outperformed MODISDB in all the investigated areas. High AOD values were observed by the MODISSTD, MODISDB, MISR, and OMI instruments during the summer months (April-August); these ranged from 0.32 to 0.78, possibly due to human activity and biomass burning. ix In contrast, high AOD values were observed by the CALIPSO instrument between September and December, due to high concentrations of smoke and soot aerosols. The variable monthly AOD figures obtained with different sensors indicate overestimation by MODISSTD, MODISDB, OMI, and CALIPSO instruments over Karachi, Lahore, Jaipur and Kanpur, relative to the AERONET data, but underestimation by the MISR instrument. The examination of the distribution and spectral behavior of the optical properties of atmospheric aerosols in the IGP were also being performed using an AERONET. The AOD and Angstrom Exponent (AE) results revealed a high AOD with a low AE value over Karachi and Jaipur in July, while a high AOD with a high AE value was reported over Lahore and Kanpur during October and December. The pattern of the aerosol Volume Size Distribution (VSD) was similar across all four sites, with a prominent peak in coarse mode at a radius of 4.0–5.0 μm, and in fine mode at a radius of 0.1–4.0 μm, for all seasons. On the other hand, during the winter months, the fine-mode peaks were comparable to the coarse mode, which was not the case during the other seasons. The Single Scattering Albedo (SSA) was found to be strongly wavelength dependent during all seasons and for all sites, except for Kanpur, where the SSA decreases with increasing wavelength during winter and post-monsoon. It was found that the phase function of the atmospheric aerosol was high at a small angle and stable around a scattering angle of 90°–180° at all sites and during all seasons. Spectral variation of the Asymmetry Parameter (AP) revealed a decreasing trend with increasing wavelength, and this decreasing trend was more pronounced during the summer, winter, and post-monsoon as compared to pre-monsoon. Furthermore, extensive measurements suggest that both Real Refractive Index (RRI) and imaginary Refractive Index (IRI) show contrasting spectral behavior during all seasons. The analysis of the National Oceanic and Atmospheric Administration (NOAA) Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) x model back trajectory revealed that the seasonal variation in aerosol types was influenced by a contribution of air masses from multiple source locations. Discrimination of aerosol types is essential over the IGP because several aerosol types originate from different sources having different atmospheric impacts. We analyzed a seasonal discrimination of aerosol types by multiple clustering techniques using AERONET data sets for the study period over observational sites. We discriminated the aerosols into three major types; dust, biomass burning and urban/industrial. The discrimination was carried out by analyzing different aerosol optical properties such as AOD, AE, SSA, RRI, Extinction Angstrom Exponent (EAE), Absorption Angstrom Exponent (AAE) and their interrelationship to investigate the dominant aerosol types and to examine the variation in their seasonal distribution. The results revealed that during summer and pre-monsoon, dust aerosols were dominant while during winter and post-monsoon prevailing aerosols were biomass burning and urban industrial, and the mixed type of aerosols were present in all seasons. These types of aerosol discriminated from AERONET were in good agreement with CALIPSO measurement. Finally, the long term radiative impacts of aerosol on regional climate of IGP were studied. For this purpose, the spatio-temporal variations of Shortwave Direct Aerosol Radiative Forcing (SDARF) and Shortwave Direct Aerosol Radiative Forcing Efficiency (SDARFE) at the Top Of Atmosphere (TOA), SURface (SUR) and within ATMosphere (ATM) along with atmospheric Heating Rate (HR) were calculated using Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model. It was observed that the monthly averaged SDARFTOA was either positive or negative, whereas SDARFSUR were found to be negative leading to positive ATM during all the months over all sites. The seasonal analysis of SDARF revealed that SDARFTOA and SDARFSUR were negative during all the seasons. The increment in the net atmosphere forcing lead to maximum HR in November-December and May, presenting the strongest atmospheric absorption. Similar to SDARF, the monthly averaged SDARFETOA were xi found to be either positive or negative, while SDARFESUR were negative throughout the months resulting in the more enhanced positive SDARFEATM. Generally, the highest values of SDARFETOA were observed during the winter and lowest during the summer over all the sites except for Karachi where the lowest TOA efficiency was noted in pre-monsoon. Accordingly, the highest values of SDARFESUR were observed during the winter and minimum during the summer over the rest of the sites. The SDARFE at ATM were observed to be maximum during pre-monsoon and lowest during the summer over Karachi, Lahore and Kanpur, while over Jaipur, maximum SDARFE at ATM were noted during winter and minimum during summer. Additionally, to compare the model estimated forcing against AERONET derived forcing, the regression analysis of AERONET-SBDART forcing were carried out. It was observed that SDARF at the SUR and TOA showed relatively higher correlation over Lahore, moderate over Jaipur and Kanpur and lower over Karachi.
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