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Screen viewing time is the total time spent by a child on any digital/electronic device. The objective of the present study was to determine the incidence and predictors of excessive screen viewing time in children in Ujjain, India. This cross-sectional, community-based study was conducted through house-to-house survey by using the three-stage cluster sampling method in 36 urban wards and 36 villages of Ujjain district, India. Excessive screen viewing time was defined as screen viewing for > 2 h/day. The prevalence of excessive screen viewing time was 17.83%. Risk factors identified using the multivariate logistic regression model were: age (OR: 1.5, P < 0.001); mobile phone use before bedtime (OR: 3.17, P = 0.008); parents’ perception about the child habituated to screen (OR: 14.03, P < 0.001); television in bedroom (OR: 48.69, P < 0.001); morning mobile screen viewing time (OR: 9.27, P < 0.001); not reading books other than textbooks (OR: 9.71, P < 0.001); and lack of outdoor play for >2 h (OR: 4.20, P < 0.001). Presence of eye pain was a protective factor for excessive screen viewing time (OR: 0.12, P = 0.011). The study identified multiple modifiable risk factors for excessive screen viewing time.

Screen viewing time is the total time spent by a child on any digital/electronic device. The objective of the present study was to determine the prevalence and predictors of excessive screen viewing time in children in Ujjain, India. This cross-sectional, community-based study was conducted through a house-to-house survey using the three-stage cluster sampling method in 36 urban wards and 36 villages of Ujjain District, India. Excessive screen viewing time was defined as screen viewing for >2 h/day. The prevalence of excessive screen viewing time was 18%. Risk factors identified using the multivariate logistic regression model were age (OR: 1.63, p < 0.001); mobile phone use before bedtime (OR: 3.35, p = 0.004); parents’ perception about the child’s habituation to screen time (OR: 8.46, p < 0.001); television in the bedroom (OR: 35.91, p < 0.001); morning mobile screen viewing time (OR: 6.40, p < 0.001); not reading books other than textbooks (OR: 6.45, p < 0.001); and lack of outdoor play for >2 h (OR: 5.17, p < 0.001). The presence of eye pain was a protective factor for excessive screen viewing time (OR: 0.13, p = 0.012). This study identified multiple modifiable risk factors for excessive screen viewing time.

Forests are the indispensable resource of our life as they cover one third of the land on earth. They provide us with plenty of amenities required to sustain our life. However, for the past few decades, the forest area has been degrading immensely. Recently forest fire has become the greatest menace to our planet. In 2019 Amazon rainforest wildfire destroyed thousands hectors of forest. To get a control over it, a well-organized forest monitoring system is created. This system is based on the emerging technology of IoT and image processing. In our system, these technologies are utilized with the Wireless Sensor Network (WSN). This system provides a continuous live data of the forest environmental conditions. Utilizing this in our work helps us to detect fire intensity which enables water discharge for extinguishing fire when the conditions become unfavourable. This process will be helpful for controlling the wildfire.

Data in today's world is the most important asset one can have, but with it comes the issue of handling it properly. To increase data portability, facilitated by reducing the size of data to be stored due to limited storage space, a strong need for data compression has arisen. A lot of ways have been defined for data compression; since the 1950's we have been digging up and devising many algorithms to modify data compression techniques and over the years, many seemingly powerful algorithms have been developed. With a wide range of compression techniques available, there comes the need to choose the right method for text compression, which gives good results in lesser time. In this paper, we present a hybrid approach to compress text data. This hybrid approach encompasses various methodologies like Run Length Encoding (RLE), Infix Encoding and Bit reduction techniques. We aim to overlay different techniques to achieve the best possible compression ratio for large text files and dictionary data.

ObjectiveSchool readiness is a condition or state indicating that the child is ready to learn in a formal educational set-up. The objective of this study was to estimate the prevalence of and factors associated with school readiness in urban schoolchildren in Ujjain, India.MethodsThis cross-sectional study was conducted from February 2016 to March 2017. Two English-medium schools were conveniently selected. All children aged 5–7 years were eligible to participate. A subscale of Differential Ability Scales-Second Edition, namely ‘school readiness scale’, was used to assess school readiness in three major domains—early number concept, matching letter-like forms and phonological processing. Data on factors associated with school readiness were collected through parent interview. Quantile regression analysis was used to explore school readiness scores.ResultsThis study included 203 school-going children (105 boys and 98 girls) having a mean (SD) age of 67.7 (±0.51) months. The phonological processing and matching letter-like forms had 31.5% and 30.5% children, respectively, in lower quantiles (≤25th). The higher quantile (≥75th) scores were achieved for phonological processing and early number concept (47.7% and 44.8% children, respectively). The results of quantile regression showed negative association of school readiness scores with age of children, lower socioeconomic status and hospitalisation status, especially in the lower quantiles (≤25th). The 10th, 50th and 75th quantile scores were positively correlated with the increasing education status of the mother. Birth weight was positively associated with the median and higher quantile scores (≥75th).ConclusionsSchool readiness in a middle-class urban setting in India was negatively associated with lower age of the child, lower socioeconomic status, hospitalisation and positively correlated with increasing birth weight and maternal education. Lower quantile scores were achieved in matching letter-like forms, which measures complex visual–spatial processing, and phonological ability, which correlates with acquired verbal concepts. Focused interventions are needed to improve these skills.