This is a review article describing the recent developments in Video based Fire Detection (VFD). Video surveillance cameras and computer vision methods are widely used in many security applications. It is also possible to use security cameras and special purpose infrared surveillance cameras for fire detection. This requires intelligent video processing techniques for detection and analysis of uncontrolled fire behavior. VFD may help reduce the detection time compared to the currently available sensors in both indoors and outdoors because cameras can monitor "volumes" and do not have transport delay that the traditional "point" sensors suffer from. It is possible to cover an area of 100 km2 using a single pan-tilt-zoom camera placed on a hilltop for wildfire detection. Another benefit of the VFD systems is that they can provide crucial information about the size and growth of the fire, direction of smoke propagation.

ObjectivesThis investigation was performed in order to determine the prevalence rate of waterpipe smoking in students of Erciyes University and the effects of some socio-demographic factors.MethodsA total of 645 students who study the first three grades of the medical faculty and the engineering faculty of Erciyes University were enrolled in the study. A questionnaire including 48 questions was applied. Chi-square test and logistic regression method were performed for the statistical analyses.ResultsThe total prevalence rate of waterpipe smoking was found to be 32.7%. The prevalence rate of waterpipe smoking was 28.6% in the medical and 37.5% in the non-medical students. It was determined that 41.6% of the males and 20.2% of the females currently smoke waterpipe. Gender, cigarette smoking, and the presence of waterpipe smokers among family members and friends have significant effects on the prevalence of waterpipe smoking. Residence and economical status of the family and with whom the students live have no significant effect on the prevalence rate.ConclusionsApproximately one-third of the students currently smoke waterpipe. Smoking of both cigarette and waterpipe was frequently found. The measures against all tobacco products should be combined.

Cataloged from PDF version of article.This paper proposes a video-based fire detection system which uses color, spatial and temporal information. The system divides the video into spatio-temporal blocks and uses covariance-based features extracted from these blocks to detect fire. Feature vectors take advantage of both the spatial and the temporal characteristics of flame-colored regions. The extracted features are trained and tested using a support vector machine (SVM) classifier. The system does not use a background subtraction method to segment moving regions and can be used, to some extent, with non-stationary cameras. The computationally efficient method can process 320 x 240 video frames at around 20 frames per second in an ordinary PC with a dual core 2.2 GHz processor. In addition, it is shown to outperform a previous method in terms of detection performance

It was concluded that traditional practices were more prevalent in the rural areas and among the older couples.

Sleep duration may be an important factor for obesity and providing > or =10 h of sleep is recommended as a prevention strategy for obesity.

Background: This study was conducted to determine knowledge, attitudes and practices about cervical cancer and HPV vaccination of students studying in various faculties of Erciyes University. Materials and Methods:The study was performed among the first and fourth grade students of Medicine, Theology, Education and Economics and Administrative Sciences (FEAS) faculties of Erciyes University. It was aimed to reach 1,073 students and 718 were evaluated. A questionnaire consisting of 48 questions related to the socio-demographic characteristics, knowledge, attitude and practices about cervical cancer and HPV vaccination was administered to the students. The chi-square test and logistic regression were used for the statistical analyses. Results: Of the students, 78.3% were aware of cervical cancer, while 36.1% of them were aware of the HPV vaccine. The percentage hearing about cervical cancer and HPV vaccination was significantly higher among the students of the medical faculty than the others and among fourth grade students comparing with the first grade. The marital status and the presence of a health worker in the family had no significant impact on the knowledge level of the students. The acceptability of the HPV vaccination was low among all students. Conclusions: The knowledge levels of the university students about cervical cancer and HPV vaccination are inadequate. This deficiency is more pronounced among the non-medical students and there is no significant increase during the faculty years. Non-medical students must be provided with information about important public health issues by elective courses. HPV vaccination could provide many benefits for men and women by decreasing the morbidity and mortality of cervical, anal, and penile cancers.

In this paper, a video based algorithm for fire and flame detection is developed. In addition to ordinary motion and color clues, flame flicker is distinguished from motion of flame colored moving objects using Markov models. Irregular nature of flame boundaries is detected by performing temporal wavelet analysis using Hidden Markov Models as well. Color variations in fire is detected by computing the spatial wavelet transform of moving fire-colored regions. Boundary of flames are represented in wavelet domain and irregular nature of the boundaries of fire regions is also used as an indication of the flame flicker. Decisions from sub-algorithms are linearly combined using an adaptive active fusion method. The main detection algorithm is composed of four sub-algorithms (i) detection of fire colored moving objects, (ii) temporal, and (iii) spatial wavelet analysis for flicker detection and (iv) contour analysis of fire colored region boundaries. Each algorithm yields a continuous decision value as a real number in the range [-1, 1] at every image frame of a video sequence. Decision values from sub-algorithms are fused using an adaptive algorithm in which weights are updated using the least mean square (LMS) method in the training (learning) stage.

Abstract-In this paper, an entropy functional based online adaptive decision fusion framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several subalgorithms, each of which yields its own decision as a real number centered around zero, representing the confidence level of that particular sub-algorithm. Decision values are linearly combined with weights which are updated online according to an active fusion method based on performing entropic projections onto convex sets describing sub-algorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video based wildfire detection system was developed to evaluate the performance of the decision fusion algorithm. In this case, image data arrives sequentially and the oracle is the security guard of the forest lookout tower, verifying the decision of the combined algorithm. The simulation results are presented.Index Terms-Projections onto convex sets, active learning, decision fusion, online learning, entropy maximization, wildfire detection using video.