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Punjab Education Minister Harjot Singh Bains tweeted, urging students to remain calm and the media to be careful because of the video leak of 60 sensitive students.
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Punjab Education Minister Harjot Singh Bains called for calm after mass protests erupted on the Chandigarh University campus after a video of 60 women taking a bath leaked online. Urging students to remain calm and the media to be careful, the minister said the issue was sensitive and related to the dignity of “our sisters and daughters”. “I humbly request all students of Chandigarh University to remain calm, no guilty person will be spared,” the minister tweeted. “All of us, including the media, must be careful, this is also a test for us today as a society,” he added.
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I humbly request all students of Chandigarh University to remain calm, no one guilty will be spared. This is a sensitive issue and has to do with the dignity of our sisters and daughters. We all including the media should be very careful, this is also a test for us today as a society. — Harjot Singh Bain (@harjotbains) September 18, 2022
Riots broke out in the campus after some videos of dormitory girls bathing were found available on the internet and went viral. It was found that a girl student made this video and sent it to a boy in Shimla who uploaded this video on the internet. About 60 such videos have been leaked. The accused apparently confessed to doing so when she was cornered by another girl and the hostel administration. According to some reports, the management of the dormitory wanted to squelch the incident, and meanwhile, some girls who leaked clips tried to commit suicide, which the police refused. Locked up the accused, students came out and staged a massive protest in the campus after which the police came and arrested the girl.
Mohali SSP denied reports of death or injury or suicide attempt after video leak. “It is about a video shot by a student and distributed. An FIR has been registered in the case and the accused student has been arrested. No death has been reported related to this incident. According to medical records, no (suicide) attempt has been reported,” said Mohali SSP.
“Don’t spread rumours. Let’s talk only based on facts. The medical records of all the students have been taken. We will comment more after the doctor gives his report. This is my request, don’t pay attention to it. rumours. I also spoke to these students. Give We have time to complete the investigation,” said SSP.
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Punjab Women’s Commission Chairperson Manisha Gulati assured the parents of the students that the accused would not be spared. “This is a serious matter. The investigation is ongoing,” he said.
Several videos surrounding the incident were shared on social media. In one of these unconfirmed videos, the accused can be seen being questioned by another student who asks him why he made this video. The accused has apparently admitted that the Shimla boy to whom he sent this video made him do this. Evaluation of the diagnostic performance of automated breast volume scanning compared with manual ultrasound in different breast lesions: a systematic review.
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By Grace Ugochi Nneji 1, Jingye Cai 1, *, Jianhua Deng 1, Senang Nkanta Senen 2, Md Altab Hossin 3 and Saifun Nahar 4
Received: 22 January 2022 / Revised: 9 February 2022 / Accepted: 14 February 2022 / Published: 19 February 2022
It is a known fact that diabetic retinopathy (DR) is one of the most common causes of visual impairment in people aged between 25 and 74 years worldwide. Diabetes is caused by persistently high blood sugar levels, causing blood vessel damage and vision loss. Early diagnosis can minimize the risk of proliferative diabetic retinopathy, which is the stage of this disease and has a greater risk of severe damage. Therefore, it is important to classify the stages of DR. To this end, this paper presents a weighted fusion deep learning network (WFDLN) for automatic feature extraction and DR stage classification from fundus scans. The proposed framework aims to overcome the problem of low quality and identify symptoms of retinopathy in fundus images. Two channels of fundus images, namely histogram constrained adaptive equalization fundus images (CLAHE) and contrast enhanced edge detection (CECED) fundus images are processed by WFDLN. The fundus-related features of the CLAHE images were extracted using the improved Inception V3, while the features of the CECED fundus images were extracted using the adjusted VGG-16. The output of the two channels is combined in a weighted approach and a softmax classifier is used to determine the final recognition result. Experimental results show that the proposed network can identify DR stages with high accuracy. The proposed method was tested on the Messidor dataset reporting an accuracy rate of 98.5%, sensitivity of 98.9% and specificity of 98.0%, while on the Kaggle dataset, the proposed model reported an accuracy rate of 98.0%, sensitivity of 98.7. % and specificity of 97.8%. Compared with other models, our proposed network achieves comparable performance.
CLAHE; CECED; deep learning; fundus scan; diabetic retinopathy; CLAHE image identification; CECED; deep learning; fundus scan; diabetic retinopathy; image identification
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Diabetes is caused by the accumulation of glucose in the bloodstream . Diabetes puts people at risk of various diseases such as kidney failure, loss of vision, bleeding from teeth, nerve failure, seizures of lower limbs, stroke, heart failure, etc. . Diabetic neuropathy is caused by the damage of kidney nephrons, while diabetic retinopathy is caused by the damage of brain neurons, which causes retinal infection and can progressively damage vision in the early stages . As a result, diabetics should undergo a comprehensive eye examination, when the retina should be examined by an ophthalmologist. Optical coherence tomography, fluorescein fundus angiography, slit-lamp biomicroscopy, and fundus imaging are some of the methods used to identify the affected eye .
According to a study conducted by the World Health Organization (WHO), diabetes  is the seventh most deadly disease. Also, with additional statistics, there is a large increase in diabetes patients, which rose to 422 million. According to the data, the number of people over the age of 18 with diabetes has increased from 4.7% to 8.5%, and some of the poorest people are more likely to develop diabetes. The maximum increase in glucose levels has a significant impact on blood vessels, causing blood to leak from the eyes and weaken the human visual system . Humans, on the other hand, are born with the power to cure disease. When the brain detects a blood leak, it stimulates the surrounding tissues to deal with the situation. As a result, it causes the sporadic formation of new blood vessels, but the resulting cells are anemic .
Retinal fundus image analysis is a useful operation for medical processing. Ophthalmologists can use retinal blood vessel segmentation to help them diagnose various eye problems . As a result, diseases including diabetic retinopathy, hypertension, atherosclerosis, and macular degeneration can alter the morphology of arteries, thus causing changes in diameter, tortuosity, and branch angles. Manual segmentation of retinal vascular disease is a difficult and skilled operation.
The severity of the disease can be determined
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