Survey on wavelet based image fusion techniques

Image fusion is the process of combining multiple images into a single image without distortion or loss of information. The techniques related to image fusion are broadly classified as spatial and transform domain methods. In which, the transform domain based wavelet fusion techniques are widely used in different domains like medical, space and military for the fusion of multimodality or multi-focus images. In this paper, an overview of different wavelet transform based methods and its applications for image fusion are discussed and analysed

Improved Lion Optimization based Enhanced Computation Analysis and Prediction Strategy for Dropout and Placement Performance Using Big Data

Background: Predicting the undergraduate’s placement performance is vital as it impacts the credibility of educational institutions. Hence, it is significant to predict their performance based on placement in the early days of degree program. Objectives: The study intends to predict the undergraduate’s placement performance through the introduced ANN-R (Artificial Neural Network based Regression) as it is able to handle fault tolerance. For efficient prediction, relevant feature selection is needed that is performed by the proposed ILO (Improved Lion Optimization) algorithm as it has the ability to find nearest probable optimal solution. Methodology: Initially, the parameters and population are initialised. Subsequently, first best-agent is stated in accordance with fitness function. Subsequently, position of present search agent is updated. This iteration continues until all the features are selected and optimized result is attained. Here best score is computed using the proposed ILO for feature selection. Finally, the dropout analysis and placement performance of students is predicted using the introduced ANN-R through a train and test split. Results/Conclusion: Performance of the proposed system is analysed in accordance with loss metrics. Additionally, internal comparison is performed to find the extent to which the actual and predicted values correlate with one another during prediction using the existing and proposed system. The outcomes revealed that the proposed system has the ability to predict the student’s placement performance along with domain of interest with minimum errors than the traditional system. This makes the proposed system to be highly suitable for predicting student’s performance

Improved Lion Optimization based Enhanced Computation Analysis and Prediction Strategy for Dropout and Placement Performance Using Big Data

Background: Predicting the undergraduate’s placement performance is vital as it impacts the credibility of educational institutions. Hence, it is significant to predict their performance based on placement in the early days of degree program. Objectives: The study intends to predict the undergraduate’s placement performance through the introduced ANN-R (Artificial Neural Network based Regression) as it is able to handle fault tolerance. For efficient prediction, relevant feature selection is needed that is performed by the proposed ILO (Improved Lion Optimization) algorithm as it has the ability to find nearest probable optimal solution. Methodology: Initially, the parameters and population are initialised. Subsequently, first best-agent is stated in accordance with fitness function. Subsequently, position of present search agent is updated. This iteration continues until all the features are selected and optimized result is attained. Here best score is computed using the proposed ILO for feature selection. Finally, the dropout analysis and placement performance of students is predicted using the introduced ANN-R through a train and test split. Results/Conclusion: Performance of the proposed system is analysed in accordance with loss metrics. Additionally, internal comparison is performed to find the extent to which the actual and predicted values correlate with one another during prediction using the existing and proposed system. The outcomes revealed that the proposed system has the ability to predict the student’s placement performance along with domain of interest with minimum errors than the traditional system. This makes the proposed system to be highly suitable for predicting student’s performance

Synthesis and biological evaluation of sulfonamide-based 1,3,4-oxadiazole derivatives

A novel series of 1,3,4-oxadiazole containing sulfonamide derivatives were synthesized by 5-(5-cyclohexyl-1,3,4-oxadiazol-2-yl)-2-methyl-benzenesulfonyl chloride. A good yield of intermediate with various substituted like aryl/hetero was formed. All the synthesized compounds were characterized by FT-IR, 1H NMR, 13C NMR and mass spectral studies. These compounds were evaluated for their preliminary bioassay in vitro antimicrobial activity, anti-inflammatory and anti-diabetic activities. In this series, most of the compounds have good anti-inflammatory activity. Particularly, compounds 5c, 5d and 5e showed excellent anti-inflammatory activity with IC50 values of 110, 110, and 111 μg/mL than diclofenac (157 μg/mL). The frontier orbital energy and the global reactivity descriptor were discussed for the tested compounds using RB3LYP/311G(d,p) basis set. Results revealed that the theoretical calculations of antimicrobial activity were closely related to quantum chemical parameters.               KEY WORDS: 1,3,4-Oxadiazole, Sulfonamide, Antimicrobial, Anti-diabetic, Anti-inflammatory, FT, SAR Bull. Chem. Soc. Ethiop. 2019, 33(2), 307-319.DOI: https://dx.doi.org/10.4314/bcse.v33i2.1

Prevalence of Malnutrition in Adolescent Girls: A Cross-Sectional Study in the Tribal Regions of Telangana

Malnutrition continues to be one of India's major human development challenge. Despite enormous economic progress achieved in the past two to three decades, malnutrition rates continue to be high especially among children and adolescents in both urban and rural India. The shining India is in shade on these important human development indicators. Adolescents in India especially those residing in tribal regions are at high nutritional risk and face health issues such as anemia and chronic disorders. This paper investigates the prevalence, causes and socio-economic-cultural determinants of malnutrition among 11 to 18 years old adolescent tribal girls from the districts of Adilabad, Komaram-Bheem Asifabad and Mancherial in Telangana state. The cross sectional survey collected data in the year 2017 on socio-economic, demographic, diet and anthropometric indicators from 695 tribal adolescent girls out of 2542 tribal households. The analysis of the anthropometric data reveals that about 67 percent of adolescent girls are undernourished having a BMI of less than 18.5. The results revealed that stunting and thinness was highly prevalent among the tribal adolescent girls. Overweight or obesity is not of particular concern in the studied tribal adolescent girls. These adolescents also lack basic awareness about food, nutrition, health and overall wellbeing. The paper ultimately determines the need for a concerted combination of policies and programs specifically aimed at adolescents in the tribal regions addressing poverty, education, nutrition literacy, empowerment to challenge the existing cultural norms related to food consumption and access to diverse diets both in terms of quantity and quality

Expression of conserved signalling pathway genes during spontaneous vascular differentiation of R1 embryonic stem cells and in Py-4-1 endothelial cells

Embryonic stem (ES) cells are an invaluable model for identifying subtle phenotypes as well as severe outcomes of perturbing gene function that may otherwise result in lethality. However, though ES cells of different origins are regarded as equally pluripotent, their in vitro differentiation potential varies, suggesting that their response to developmental signals is different. The R1 cell line is widely used for gene manipulation due to its good growth characteristics and highly efficient germline transmission. Hence, we analysed the expression of Notch, Wnt and Sonic Hedgehog (Shh) pathway genes during differentiation of R1 cells into early vascular lineages. Notch-, Wnt- and Shh-mediated signalling is important during embryonic development. Regulation of gene expression through these signalling molecules is a frequently used theme, resulting in context-dependent outcomes during development. Perturbing these pathways can result in severe and possibly lethal developmental phenotypes often due to primary cardiovascular defects. We report that during early spontaneous differentiation of R1 cells, Notch-1 and the Wnt target Brachyury are active whereas the Shh receptor is not detected. This expression pattern is similar to that seen in a mouse endothelial cell line. This temporal study of expression of genes representative of all three pathways in ES cell differentiation will aid in further analysis of cell signalling during vascular development