Water Purification and Disinfection by Using Solar Energy: Towards Green Energy Challenge

The aim of this work was to design a solar water treatment plant for household purpose. Water purification is the process of eradicating detrimental chemicals, biological poisons, suspended solids and gases from contaminated water. In this work we have reported an investigation of compact filter which is cost effective for developing countries and ease of maintenance. We have arranged a solar water disinfection system that improves the microbiological quality of drinking water at household level. We get 14 L pure water and 16 ml water vapour within 240 min by using filtration method. From our work we get hot water up to 49°C. The efficiency of the system at sunny days and cloudy days are 18.23% and 18.13% respectively. This simple solar hybrid system helps to remove turbidity as well as chemical and pathogenic contaminants from water sources in the most affordable, and expedient manner possibly

An Intelligent Decision Support System for the Detection of Meat Spoilage using Multispectral Images

In food industry, quality and safety are considered important issues worldwide that are directly related to health and social progress. The use of vision technology for quality testing of food production has the obvious advantage of being able to continuously monitor a production using non-destructive methods, thus increasing the quality and minimizing cost. The performance of an intelligent decision support system has been evaluated in monitoring the spoilage of minced beef stored either aerobically or under modified atmosphere packaging, at different storage temperatures (0, 5, 10, and 15 °C) utilising multispectral imaging information. This paper utilises a neuro-fuzzy model which incorporates a clustering pre-processing stage for the definition of fuzzy rules, while its final fuzzy rule base is determined by competitive learning. Initially, meat samples are classified according to their storage conditions, while identification models are then utilised for the prediction of the Total Viable Counts of bacteria. The innovation of the proposed approach is further extended to the identification of the temperature used for storage, utilizing only imaging spectral information. Results indicated that spectral information in combination with the proposed modelling scheme could be considered as an alternative methodology for the accurate evaluation of meat spoilage

The places parents go: understanding the breadth, scope, and experiences of activity spaces for parents

The final publication is available at Springer via https://doi.org/10.1007/s10708-015-9690-yNeighborhood environments are related to parenting behaviors, which in turn have a life-long effect on children’s health and well-being. Activity spaces, which measure individual routine patterns of movement, may be helpful in assessing how physical and social environments shape parenting. In this study we use qualitative data and GIS mapping from four California cities to examine parental activity spaces. Parents described a number of factors that shape their activity spaces including caregiving status, the age of their children, and income. Parental activity spaces also varied between times (weekends vs. weekdays) and places (adult-only vs. child-specific places). Knowing how to best capture and study parental activity spaces could identify mechanisms by which environmental factors influence parenting behaviors and child health

Understanding interactions in face-to-face and remote undergraduate science laboratories

This paper reviews the ways in which interactions have been studied, and the findings of such studies, in science education in both face-to-face and remote laboratories. Guided by a systematic selection process, 27 directly relevant articles were analysed based on three categories: the instruments used for measuring interactions, the research findings on student interactions, and the theoretical frameworks used in the studies of student interactions. In face-to-face laboratories, instruments for measuring interactions and the characterisation of the nature of interactions were prominent. For remote laboratories, the analysis of direct interactions was found to be lacking. Instead, studies of remote laboratories were mainly concerned with their practical scope. In addition, it is found that only a limited number of theoretical frameworks have been developed and applied in the research design. Existent theories are summarised and possible theoretical frameworks that may be implemented in studies of interactions in undergraduate laboratories are proposed. Finally, future directions for research on the interrelationship between student interactions and laboratory learning are suggested

Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging

Hyperspectral imaging enables researchers and plant breeders to analyze various traits of interest like nutritional value in high throughput. In order to achieve this, the optimal design of a reliable calibration model, linking the measured spectra with the investigated traits, is necessary. In the present study we investigated the impact of different regression models, calibration set sizes and calibration set compositions on prediction performance. For this purpose, we analyzed concentrations of six globally relevant grain nutrients of the wild barley population HEB-YIELD as case study. The data comprised 1,593 plots, grown in 2015 and 2016 at the locations Dundee and Halle, which have been entirely analyzed through traditional laboratory methods and hyperspectral imaging. The results indicated that a linear regression model based on partial least squares outperformed neural networks in this particular data modelling task. There existed a positive relationship between the number of samples in a calibration model and prediction performance, with a local optimum at a calibration set size of ~40% of the total data. The inclusion of samples from several years and locations could clearly improve the predictions of the investigated nutrient traits at small calibration set sizes. It should be stated that the expansion of calibration models with additional samples is only useful as long as they are able to increase trait variability. Models obtained in a certain environment were only to a limited extent transferable to other environments. They should therefore be successively upgraded with new calibration data to enable a reliable prediction of the desired traits. The presented results will assist the design and conceptualization of future hyperspectral imaging projects in order to achieve reliable predictions. It will in general help to establish practical applications of hyperspectral imaging systems, for instance in plant breeding concepts

Effects of rapid urbanisation on the urban thermal environment between 1990 and 2011 in Dhaka Megacity, Bangladesh

This study investigates the influence of land-use/land-cover (LULC) change on land surface temperature (LST) in Dhaka Megacity, Bangladesh during a period of rapid urbanisation. LST was derived from Landsat 5 TM scenes captured in 1990, 2000 and 2011 and compared to contemporaneous LULC maps. We compared index-based and linear spectral mixture analysis (LSMA) techniques for modelling LST. LSMA derived biophysical parameters corresponded more strongly to LST than those produced using index-based parameters. Results indicated that vegetation and water surfaces had relatively stable LST but it increased by around 2 °C when these surfaces were converted to built-up areas with extensive impervious surfaces. Knowledge of the expected change in LST when one land-cover is converted to another can inform land planners of the potential impact of future changes and urges the development of better management strategies