Automatic lane detection for driver assistance is a significant component in developing advanced driver assistance systems and high-level application frameworks since it contributes to driver and pedestrian safety on roads and highways. However, due to several limitations that lane detection systems must rectify, such as the uncertainties of lane patterns, perspective consequences, limited visibility of lane lines, dark spots, complex background, illuminance, and light reflections, it remains a challenging task. The proposed method employs vision-based technologies to determine the lane boundary lines. We devised a system for correctly identifying lane lines on a homogeneous road surface. Lane line detection relies heavily on the gradient and hue lightness saturation (HLS) thresholding which detects the lane line in binary images. The lanes are shown, and a sliding window searching method is used to estimate the color lane. The proposed system achieved 96% accuracy in detecting lane lines on the different roads, and its performance was assessed using data from several road image databases under various illumination circumstances.

Introduction: Hospital-acquired infection is a major global issue for patient safety. Understanding the potential risk factors is important to appreciate the local context. At least 1.2 million people are affected globally by nosocomial infections at any time, the vast majority of these occurring in low-income countries. This study aimed to assess the prevalence and contributing factors of hospital-acquired infections among surgical patients in a selected secondary level hospital. Methodology: A hospital-based cross-sectional study carried out in a selected secondary level hospital; from October 2019 to December 2019 among 137 respondents. The purposive sampling technique was followed to select the study participants; the interview was taken by using a pre-tested semi-structured questionnaire. Statistical analysis was performed using SPSS program version 23. The level of significance was taken 95% and standard error 5%. Results: Out of all the patients 83.2% were admitted to Out Patient Department and 16.8% to emergency. Among them, 0.7% of the respondents were found to develop hospital-acquired infection. About 44.5% having infection before admission and more than three visitors visit a patient per day 65.7%. The scanty number of patients had used blood transfusion, urinary catheter for their treatment. The provisional and final diagnosis was almost the same. Conclusion: Hospital-acquired infections usually only receive public attention when there are epidemics. Although hidden from public attention, HAIs are a very real endemic and on-going problem. Maintaining a safe and hygienic work environment prevents the spread of HAIs.