الفكر السياسي الإسلامي وتطوره من الشورى إلى الديمقراطية

There has been a tussle going on between Islam and democracy for many decades in the Muslim world which has benefited most certainly the anarchic factions like kings, lords and army dictators. Though democracy is close to Islam and thought to be the best of all types of governments as majority is authority in it that may make or mar the government. In a democratic setup, the individual and personal rights and freedom are considered which is why it is preferred more these days. Many as Muslim thinkers are also in favor of it, but still there is a large faction of clerical scholars who deem democracy as the root of all evils since it empowers general public as an authoritative and decisive force. However with the passage of time, the Islamic counseling system has evolved and come very close to the spirit of democracy. Therefore, may contemporary scholars hold Islamic counseling and democracy almost similar. This article aims to present a preview of democracy and counseling in the light of what the Ulema (Scholars) say about it.

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