Performance Analysis of Selection Schemes in Genetic Algorithm for Solving Optimization Problem Using De Jong?s Function1

Genetic Algorithm (GA) is known to be a search algorithm based on idea of natural selection and survival of fittest [11]. The main idea behind the approach is, for a population of individuals adapting to some environment, they should behave naturally. Genetic Algorithm and other evolutionary algorithms are used over the years for finding solution to different emerging problems which could be better implemented and solved using approach of Genetic algorithm. Out of many such problems optimization problems are having their own importance and had a great scope for further research. There are different solutions given by different researchers for finding solutions to such optimization problems. This paper is about using De jong?s function 1 adopted for finding a solution to an optimization problem and thereby comparing the performance of chosen selection schemes used in Genetic Algorith

Some Result on fixed point Theorem in Hilbert Space

This paper puts up a result regarding the generalization of the Banach contraction  principle in the Hilbert space, It consist of four rational square terms in the inequality. Further the corollary of Koparde and Wag mode was obtained by considering vanishing values to some constant towards the end of this result. Keywords: Hilbert space, closed subset, Cauchy sequence, Completeness

Unique Invariant Point Theorems for Random operators In Hilbert Space

We find unique common random fixed point of two random operators in closed subset of a separable Hilbert space by considering a sequence of measurable functions satisfying  Theorem 1.1 and Theorem 1.2. Keywords: Separable Hilbert space, random operators, common random fixed point

Flooding through the lens of mobile phone activity

Natural disasters affect hundreds of millions of people worldwide every year. Emergency response efforts depend upon the availability of timely information, such as information concerning the movements of affected populations. The analysis of aggregated and anonymized Call Detail Records (CDR) captured from the mobile phone infrastructure provides new possibilities to characterize human behavior during critical events. In this work, we investigate the viability of using CDR data combined with other sources of information to characterize the floods that occurred in Tabasco, Mexico in 2009. An impact map has been reconstructed using Landsat-7 images to identify the floods. Within this frame, the underlying communication activity signals in the CDR data have been analyzed and compared against rainfall levels extracted from data of the NASA-TRMM project. The variations in the number of active phones connected to each cell tower reveal abnormal activity patterns in the most affected locations during and after the floods that could be used as signatures of the floods - both in terms of infrastructure impact assessment and population information awareness. The representativeness of the analysis has been assessed using census data and civil protection records. While a more extensive validation is required, these early results suggest high potential in using cell tower activity information to improve early warning and emergency management mechanisms.Comment: Submitted to IEEE Global Humanitarian Technologies Conference (GHTC) 201

DESIGN AND PERFORMANCE VERIFICATION OF NEWLY DEVELOPED DISPOSABLE STATIC DIFFUSION CELL FOR DRUG DIFFUSION/PERMEABILITY STUDIES

Objectives: The present study describes a disposable static diffusion cell for in vitro diffusion studies to achieve better results as compared to well existing Franz diffusion cell (FDC) in terms of the absence of bubbles, variable receptor compartment, ease of handling, and faster results.Materials and Methods: The cell consists of a cup-shaped donor compartment made of semi permeable that could be either cellophane membrane or, animal skin fitted to a rigid frame, which is supported on a plastic plate that contains a hole for the sample withdrawal. The receptor compartment is a separate unit, and it could be any container up to 500ml volume capacity. The most preferred receptor compartment is glass beaker. In the present study, goatskin was used as semi-permeable membrane and verification of its performance was carried out through diffusion studies using gel formulations of one each of the four-selected biopharmaceutical classification system (BCS) class drugs. Metronidazole, diclofenac sodium, fluconazole, and sulfadiazine were used as model drugs for BCS Class I, II, III, and IV, respectively.Results: The newly developed diffusion cell (NDDC) was found to provide faster and more reproducible results as compared to FDC. At the time interval of 24 h, the cell was found to exhibit a higher diffusion of metronidazole, diclofenac sodium, fluconazole, and sulfadiazine by 0.65, 0.65, 0.32, and 0.81 folds, respectively. The faster release obtained with NDDC was attributed to a larger surface area of skin as compared to that in FDC.Conclusion: It was concluded that better reproducibility of results could be achieved with NDDC

Deep learning based automated epidermal growth factor receptor and anaplastic lymphoma kinase status prediction of brain metastasis in non-small cell lung cancer

Aim: The aim of this study was to investigate the feasibility of developing a deep learning (DL) algorithm for classifying brain metastases from non-small cell lung cancer (NSCLC) into epidermal growth factor receptor (EGFR) mutation and anaplastic lymphoma kinase (ALK) rearrangement groups and to compare the accuracy with classification based on semantic features on imaging. Methods: Data set of 117 patients was analysed from 2014 to 2018 out of which 33 patients were EGFR positive, 43 patients were ALK positive and 41 patients were negative for either mutation. Convolutional neural network (CNN) architecture efficient net was used to study the accuracy of classification using T1 weighted (T1W) magnetic resonance imaging (MRI) sequence, T2 weighted (T2W) MRI sequence, T1W post contrast (T1post) MRI sequence, fluid attenuated inversion recovery (FLAIR) MRI sequences. The dataset was divided into 80% training and 20% testing. The associations between mutation status and semantic features, specifically sex, smoking history, EGFR mutation and ALK rearrangement status, extracranial metastasis, performance status and imaging variables of brain metastasis were analysed using descriptive analysis [chi-square test (χ2)], univariate and multivariate logistic regression analysis assuming 95% confidence interval (CI). Results: In this study of 117 patients, the analysis by semantic method showed 79.2% of the patients belonged to ALK positive were non-smokers as compared to double negative groups (P = 0.03). There was a 10-fold increase in ALK positivity as compared to EGFR positivity in ring enhancing lesions patients (P = 0.015) and there was also a 6.4-fold increase in ALK positivity as compared to double negative groups in meningeal involvement patients (P = 0.004). Using CNN Efficient Net DL model, the study achieved 76% accuracy in classifying ALK rearrangement and EGFR mutations without manual segmentation of metastatic lesions. Analysis of the manually segmented dataset resulted in improved accuracy of 89% through this model. Conclusions: Both semantic features and DL model showed comparable accuracy in classifying EGFR mutation and ALK rearrangement. Both methods can be clinically used to predict mutation status while biopsy or genetic testing is undertaken

A Common Unique Random Fixed Point Theorem in 2 - Hilbert Space

The object of this paper is to obtain a common unique fixed point theorem for two continuous random operators defined on a non empty closed subset of a separable 2 - Hilbert space. Mathematics Subject Classification: 47H10, 54H25 Keywords: Separable Hilbert space, random operators, common random fixed-poin