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مولانا عبدالشکور

مولانا عبدالشکور
ہمارے پرانے نامور علماء ایک ایک کرکے، اٹھتے جاتے ہیں، افسوس ہے کہ ان کی آخری یادگار مولانا عبدالشکور صاحب نے بھی سفر آخرت اختیار کیا، مولانا کی ذات جامع کمالات اور اس دور میں سلف صالحین کا نمونہ تھی، علم و عمل اور دین و تقویٰ میں ان کا درجہ بہت بلند تھا، تعلیم و تدریس، تالیف و تصنیف، وعظ و تبلیغ، ارشاد و ہدایت ہر راہ میں ان کے نمایاں کارنامے ہیں، تقریباً نصف صدی تک ان کا فیض جاری رہا، اور ان کے ذریعہ بہتوں کو ہدایت حاصل ہوئی، ایک زمانہ میں پورے ہندوستان میں ان کے کارناموں کی شہرت تھی، مگر ادھر پچیس تیس سال سے انھوں نے خاموشی اور گوشی نشینی کی زندگی اختیار کرلی تھی، اور موتو اقبل ان تموتوا کی عملی تفسیر بن گئے تھے، اب ایسے ربانی علماء کا پیدا ہونا مشکل ہے، اﷲ تعالیٰ ان کے خدمات کو قبول اور ان کے مدارج بلند فرمائے۔ (شاہ معین الدین ندوی، جنوری ۱۹۶۲ء)

Ambulatory Hysteroscopy in Abnormal Uterine Bleeding: A Tertiary Care Hospital Perspective

Background: To avoid delays in outpatient facilities for managing benign gynecological conditions like abnormal uterine bleeding (AUB), there is a need to evaluate the usage of unconventional methods like outpatient hysteroscopy. Objectives: To evaluate the usage of outpatient diagnostic hysteroscopy in women with abnormal uterine bleeding. Methods: An observational study was conducted at the Obstetrics and Gynecology Department of Combined Military Hospital, Kharian. The study included 56 women having AUB with or without a history of failed medical treatment. The study participants underwent outpatient diagnostic hysteroscopy. Diagnostic hysteroscopy was done under the local para-cervical block in the Outpatient department. Procedure indications, outcome and biopsy findings were recorded on predesigned proformas. Results: Median age of the study participants was 44 years. The most common indications for diagnostic hysteroscopy were postmenopausal bleeding (34%) and heavy menstrual bleeding (28%). Hysteroscopy outcomes included endometrial biopsy (34%), discharge with no biopsy (25%), further test and evaluations required (21%), and admission due to failed outpatient procedures (20%). Sixty-two percent of the study participants had normal biopsy findings while other biopsy findings included polyps (20%), fibroids (14%) and endometrial hyperplasia (4%). Nine percent had unsuccessful hysteroscopy due to patient refusal to proceed. Conclusion: Outpatient hysteroscopy can be helpful in the early and rapid diagnosis of women with abnormal uterine bleeding.  

Automated scratch detection syseem for the automative industry.

Following the manufacturing process within an automotive industry, a vehicle is prone to defects being present on its body. In the Pakistani industry, one of the largest contributors to these defects are scratches. The current measure being taken to detect scratches on vehicles involve the presence of trained specialists who inspect the body under specific lighting conditions. For this very reason, a low cost and effective automated system is desired which is capable of detection scratches on the front bumper of vehicles on the production line of industries. The main features of this system should its ability to pinpoint a range of areas where the scratches originate from in the manufacturing process as well as to help improve the current manual inspection system in place. To tackle the problem at hand, we propose a scratch detection device, based on a microcontroller interfaced with a distance sensor and a camera module, set up on a robotic arm which is mapped to the front bumper of a vehicle. The system is placed on the manufacturing line. It detects the presence of a vehicle through the threshold being broken on the distance sensor. It then begins the mapping process and takes images of the bumper which it then sends to the image processor located on the microcontroller of the device. The image processor loads the images and begins to preprocess them. This involves the removal of unwanted objects, the removal of reflections of surfaces, etc. It then passes the preprocessed image onto a trained machine learning model which outputs a decision stating whether a scratch is present or not. This data is then logged onto a spreadsheet online which is accessible by the human inspector. The trained machine learning model is based on a Convolutional Neural Network that is trained on a image dataset of around 1500 images of scratches and non-scratches. This model has an accuracy rate of 90% and is capable of telling whether a scratch is present in an image or not. The Robotic Arm has 6 degrees of freedom, allowing it to move in all four directions in a spacial plane as well as extend further into space. This is done to take into account the curved body of a front bumper. The proposed implementation is to place two such Automated Scratch Detection Systems on two sides of the vehicle at a distance of 16 centimeters from the body. This ensures optimal processing time as well as detection accuracy. Each of the systems map towards one half of the bumper and perform the image processing task in a total of 12 minutes
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