An abnormal behavior detection algorithm for surveillance is required to correctly identify the targets as being in a normal or chaotic movement. A model is developed here for this purpose. The uniqueness of this algorithm is the use of foreground detection with Gaussian mixture (FGMM) model before passing the video frames to optical flow model using Lucas-Kanade approach. Information of horizontal and vertical displacements and directions associated with each pixel for object of interest is extracted. These features are then fed to feedforward neural network for classification and simulation. The study is being conducted on the real time videos and some synthesized videos. Accuracy of method has been calculated by using the performance parameters for Neural Networks. In comparison of plain optical flow with this model, improved results have been obtained without noise. Classes are correctly identified with an overall performance equal to 3.4e-02 with & error percentage of 2.5.

Surveillance through aerial systems is in place for years. Such systems are expensive, and a large fleet is in operation around the world without upgrades. These systems have low resolution and multiple analog cameras on-board, with Digital Video Recorders (DVRs) at the control station. Generated digital videos have multi-scenes from multi-feeds embedded in a single video stream and lack video stabilization. Replacing on-board analog cameras with the latest digital counterparts requires huge investment. These videos require stabilization and other automated video analysis prepossessing steps before passing it to the mosaicing algorithm. Available mosaicing software are not tailored to segregate feeds from different cameras and scenes, automate image enhancements, and stabilize before mosaicing (image stitching). We present "AirMatch", a new automated system that first separates camera feeds and scenes, then stabilize and enhance the video feed of each camera; generates a mosaic of each scene of every feed and produce a super quality mosaic by stitching mosaics of all feeds. In our proposed solution, state-of-the-art video analytics techniques are tailored to work on videos from vintage cameras in aerial applications. Our new framework is independent of specialized hardware requirements and generates effective mosaics. Affine motion transform with smoothing Gaussian filter is selected for the stabilization of videos. A histogrambased method is performed for scene change detection and image contrast enhancement. Oriented FAST and rotated BRIEF (ORB) is selected for feature detection and descriptors in video stitching. Several experiments on a number of video streams are performed and the analysis shows that our system can efficiently generate mosaics of videos with high distortion and artifacts, compared with other commercially available mosaicing software.

Objective: Objective of the study is to evaluate the oral health knowledge, attitude and oral hygiene practice behavior among undergraduate students of biomedical sciences in Punjab, Pakistan. Method: Methodology consisted of a questionnaire study of 501 sample size (182 males and 319 females). The mean age of the participants was 19 years. The data collected by the study was analyzed by IBM SPSS Statistics v. 25.0. Pearson’s Chi-square test was used to compare the data. P-value less than 0.05 were considered to be statistically significant. Result: Results showed 284 (56.6%) participants brushed their teeth only once a day,253 (50.4%) brushed their teeth right after waking up, for no less than 2 minutes. 342 (68.2%) participants replaced their tooth brush after every 3 months and 367 (73%) participants do not feel an obligation to brush teeth after consuming sugary foods. 203 (40.5%) participants only use horizontal motions for brushing and 234 (46.7%) participants rely only on brushing to maintain oral hygiene.290 participants (58%) believe visiting the dentist after every 6 months can help in prevention of oral diseases, while 159 (32%) participants believe in fluoride application and getting scaling done once a year. 64.4% participants believe scaling is the removal of deposits on teeth and it should only be done when required. 63% participants visited the dentist only when they suffered from an oral disease. Conclusion: The findings of this study will be helpful in making strategies for awareness programs related to oral hygiene practices.

This study is expected to quantify the impact of value image, strategic image, and trajectory image on ethical goods word of mouth behavior based on the recent call for further research (Jayawardhena et al., 2016). We have collected data from 177 consumers from Lahore city, using a mall intercept technique. The response rate remains 48%. Before, testing the hypothesis, we applied reliability analysis, and most of our measures were found to be reliable for further analysis. The results have practical implications for marketers and give more insight into image theory.

Computer-based technology called social media with the result that enables customers to communicate via online forums and exchange knowledge, concepts, and viewpoints. The most frequent users of social platforms are juveniles. This paper involves the impact of social media on academic performance in Islamic society, in Punjab, Pakistan. Data was collected from students of Riphah International University, Faisalabad. A structured examination was used to collect primary data. The finding demonstrates a consequential association between social media and academic performance. Social media has both positive and negative impacts on students’ academic performance. Some social networking sites are useful for academic purposes. By excessive use of social platforms, pupils don’t focus on their studies and spend the majority of their time online.