Development of Kabul under Mughals 1504-1738 AD

Kabul was a bridge between Indian Mughal Empire and Central Asia, the ancestral homeland of the founder of the Mughal Empire. Kabul, the capital of Afghanistan, carries about 3,500 years old historical records mentioning Kabul with different names like, Kubha, Gandahara, Kabura, Ortospana, Kapul, Zavul, and Zabul etc. Many great warriors and conquerors from Central Asia used Kabul as their route to India. It was also known as a gateway to India and Central Asia. Kabul became the foundation stone for the Mughal Empire in India. During the Mughal era Kabul entered into a new phase and with the invasion of Babur the area got the position of the capital of the Mughals. The early Mughal rulers paid much attention to the affairs of Kabul, because their existence to a greater extent was dependent on their strong hold over Kabul. The research work is focused on development of Kabul under Mughal kings particularly Babur, Humayun, Akbar, Shah Jahan and Aurangzeb.  The later Mughal kings after Aurangzeb were not able to end political disturbances in Kabul which not only displeased the people of Kabul but also encouraged the neighbouring powers to invade the valley. Historical and analytical methods are used in this research and Pashtu, Dari, Urdu and English sources have been utilized to gauge development of Kabul during that point in time. No research work has been carried out on this aspect of Kabul so far. The analysis of the development of Kabul under Mughals brings to limelight the geostrategic and politico-economic worth of Kabul as an important Caravanserai on the trade route between Central and South Asia.

Automated Detection of Glaucoma from Fundus and Optical Coherence Tomography Images

Medical image analysis can play a substantial role in diagnosis of different medical problems. Glaucoma is an asymptomatic neurological disease. Oculists mostly use fundoscopy or OpticalCoherence-Tomography (O-C-T) to diagnose glaucoma.Fundoscopy can be used to analyse the external stratum of posterior part of the eye whereas, O-C-T imaging technology has the ability to analyse the internal stratums of posterior part of the eye.In this thesis, a Hybrid Computer Aided Diagnosis (H-CAD) system has been proposed that integrates both fundus and O-C-T imaging technologies for reliable diagnosis. Fundus module has a novel combination of hybrid structural and textural features. The system improves the decision making process after analysing a variety of glaucoma conditions. It further consists of two sub modules Hybrid Structural Feature-set (HSF) and Hybrid Texture Feature-set (HTF). HSF module calculates structural changes i.e. Cupto-Disc-Ratio (C-D-R) and classifies a sample using Support-Vector-Machine (S-V-M). HTF module analyses the textural properties of optic nerve head and again using S-V-M, makes a decision. In O-C-T module, C-D-R has been calculated on the base of the inner stratums of the retina. In the Cup Diameter Extraction (C-D-E) method, cup boundary has been marked on the base of Inner-Limiting-Membrane (I-L-M) stratum. The O-C-T module presents a new method to increase the accuracy of I-L-M stratum segmentation. It also introduces a new method to interpolate missing points on the extracted Upper-Surface of I-L-M stratum (?????). In addition, a novel technique to remove outliers from ????? has been applied. In Disc-Diameter-Extraction (D-D-E) process, Retinal-Pigment-Epithelium (R-P-E) stratum termination points have been used to locate disc margin. Earlier to R-P-E stratum segmentation, I-L-M stratum elimination has been done by a new approach to trace and eliminate I-L-M stratum. Finally, precise R-P-E stratum segmentation has been achieved on the base of new Thickness Value approximation technique. Furthermore, a novel standard for cup boundaries identification, on the base of mean value of R-P-E stratum terminations points is offered. A local-dataset of SD-O-C-T and fundus images annotated by four oculists has been used for evaluation of proposed H-CAD system. Each module ofH_CAD system classifies data independently. The final result of H-CAD system is determined based on decision of three diverse modules. The evaluations and results have shown that the final result of H_CAD system is more trustable than its contemporary automated models.