Background: Normal anal canal contains cushion of submucosa with vascular tissues. When cushions become abnormal , cause symptoms. This clinical condition is known as haemorrhoids. Haemorrhoidectomy is surgery for haemorrhoids, which can be performed by Milligan-Morgan (open technique) or Ferguson (close technique) methods. This study is conducted to compare different surgical modalities of treatment for haemorrhoids.Methods: In total, 232 patients suffering from haemorrhoids with or without fissures were included in the study. Patients were categorized into two groups. Patients undergoing open technique were designated as open group, similarly patients undergoing close technique were designated as close group. In both groups for few patients internal sphincterotomy (I.S.) was performed. Post-operative pain was assessed by visual analogue scale in all groups, per operative haemorrhage was assessed by number of swabs used during surgery and VAS estimation, operating time and post-operative hospital stay were recorded.Results: 136 patients were suffering from haemorrhoids with fissures. Of these 84 patients were operated by open technique and 52 patients by close technique. In all 136 patients, internal sphincterotomy was performed. Remaining 96 patients were suffering from only haemorrhoids. Of these 30 patients were treated by open technique with I.S., 30 patients were treated by close technique only. 25 patients were treated by close technique with I.S. and 10 patients were treated by close technique without I.S. Close group and open group with I.S. experienced less pain compared to without I.S. in both groups. Per operative haemorrhage and hospital stay in close group was less . Operative time in open group was less compared to close group.Conclusions: Ferguson procedure is found to cause less post-operative discomfort. Addition of internal sphincterotomy is having a positive effect in reducing post-operative pain.

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sewn to a Dacron tube graft to fabricate a valved conduit in 45 patients. Composite grafts were used in remaining 5 patients.Results: Average hospital stay was 13 days. There were 5 re explorations, 4 for bleeding and 1 for pericardial effusion. There were 7 early mortalities (5 of which were emergenecies), 4 due to uncontrolled bleed, 2 to myocardial pump failure and 1 due to stroke. 40 patients are in functional class (FCI), one had a stroke and another had CHF. All fabircated valved conduits were functioning well and showed similar results as the composite graft. Conclusions:Elective aortic root replacement can be performed with a low operating risk using an on table fabricated valved conduit and the long term results are similar to composite grafts. On table fabricated valved conduit can be a low cost alternative to composite graft.

In the present world, lots of road accidents take place due to the lack of attention and alertness of driver. This is termed as driver drowsiness. This leads to a lot of unfortunate situations causing adverse damage to human lives. The main goal of this research is the detection of driver drowsiness and an appropriate response to the detection. There are many methods which are based on the motion of the vehicle or based on the driver’s behavior. One of the methods is the physiological method which helps in distracting the driver from drowsiness and making him alert. And few methods require expensive sensors and deals with a lot of data. Therefore, this paper develops a system for detecting drowsiness in real time with proper procedure and accuracy which is acceptable. In this system, the driver’s facial expressions are captured and recorded using a webcam. Every movement in each frame is detected using few techniques of image processing. The Eye Aspect Ratio, Mouth Opening Ratio, and Nose Length Ratio are calculated using the landmark points on the face. The calculated values are compared to the threshold values developed by the system and the difference in value leads to the detection. At the same time, the machine learning algorithms are also implemented in offline manner. Based on the classification, the system has successfully achieved 95.58% of sensitivity and 100% of specificity using Support Vector Machine. This model system is compatible with all kinds of vehicles.

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