SEARCH ENGINES USING EVOLUTIONARY ALGORITHMS

A subset of AI is, evolutionary algorithm (EA) which involves evolutionary computation, a generic populationbased meta heuristic optimization algorithm. An EA uses some mechanisms inspired by biological evolution: reproduction, mutation, recombination, and selection. A genetic algorithm (GA) is a search technique used in computing to find exact or approximate solutions to optimization and search problems. Working of a search engine deals with searching for the indexed pages and referring to the related pages within a very short span of. Search engines commonly work through indexing. The paper deals with how a search engine works and how evolutionary algorithms can be used to develop a search engine that feeds on previous user requests to retrieve alternative documents that may not be returned by more conventional search engines

Chromatographic and Spectrophotometric Evaluation of Progesterone and Estrogen

Steroid hormones viz. progesterone, estrogen were estimated through TLC in a concentration and time dependent manner i.e. 2.5mg/ml, 5.0mg/ml for 30 & 45 minutes and, 0.2mg/ml, 0.4mg/ml for 30 & 45 minutes respectively. Progesterone and estrogen were stained with 50% v/v aq. solution of Conc. H2SO4 and were estimated through TLC in a concentration and time dependent manner. Different steroid hormones travel at different rates due to the differences in their attraction to the stationary phase and because of differences in solubility in the solvent. These Rf values obtained from both the hormones were then compared and it was found that there was a reasonable difference. Further, a study on the interaction of steroid hormones with fatty acids and proteins was undertaken using a spectrophotometer. Steroid hormones viz. progesterone and estrogen were made to interact with measured amounts of alcohol, stearic acid and bovine serum albumin (BSA) and their absorbance were recorded at the excitation wavelength of 410 nm using a spectrophotometer. Progesterone (conc.2mg/ml) and estrogen (conc. 0.5mg/ml) were each mixed with 0.1 ml, 0.2ml and 0.4ml of stearic acid (conc. 0.5mg/ml) and 5 mg, 10 mg and 15 mg of BSA separately and their absorbance were noted at 410nm. A slight shift in the absorbance was found on the overall interaction of steroids: progesterone and estrogen with alcohol, stearic acid and BSA respectively, when excited to 410 nm. Thus an attempt was made to establish a valid spectrophotometric procedure for the study of interaction of steroid hormones with fatty acids and proteins

Classification of Atrial Fibrillation using Random Forest Algorithm

The electrocardiogram is indicates the electrical activity of the heart and it can be used to detect cardiac arrhythmias. In the present work, we exhibited a methodology to classify Atrial Fibrillation (AF), Normal rhythm, and Other abnormal ECG rhythms using a machine learning algorithm by analyzing single-lead ECG signals of short duration. First, the events of ECG signals will be detected, after that morphological features and HRV features are extracted. Finally, these features are applied to the Random Forest classifier to perform classification. The Physionet challenge 2017 dataset with more than 8500 ECG recordings is used to train our model. The proposed methodology yields an F1 score of 0.86, 0.97, and 0.83 respectively in classifying AF, normal, other rhythms, and an accuracy of 0.91 after performing a 5-fold cross-validation

Impact of Capital Budgeting Decision on Profitability of Firm – Selected Listed Automobile Companies in India

Purpose: Profitability plays an important function in the business operations and determines the value by which a business is held. The study set to investigate the impact of capital budgeting decisions on profitability of Automobile firms. Capital budgeting particularly addressed five areas of the study that included capital budgeting decisions (acquisition of long-term assets, replacement of long-term assets, investment appraisal techniques, outsourcing expenditure and working capital decisions) had a biggest and significant effect on profitability of the organizations.   Methodology: This study basically involved survey of the Automobile Companies listed in NSE in India. Any business that seeks to invest its resources in a project without understanding the risks and returns involved would be held as irresponsible by its owners or shareholders. This study considered 10 companies are taken from Automobile sectors, which is listed in NSE. Correlation and paired T test were used.   Findings: This study basically involved survey of the Automobile Companies listed in NSE in India.The findings set up that there was relationship between the independent variables of capital budgeting decisions and profitability. The study was examined the outcome of capital budgeting Impact on profitability of listed firms in India. The independent variables for the study were Capital Budgeting and Profitability.   Research implications:  it is evident that Maruti and Tata Motors produced positive and statistically significant values for this study (high t-values (12.37 and 11.26), p =0.00) respectively. Eicher Motor resulted a Lowest but insignificant values (t= 2.11, p = 0.07).   Originality/Outcome: The study found that positive impact of capital budgeting on profitability of the firms under the study

2,2-Dichloro-N-(4-methyl­phenyl­sulfonyl)acetamide

The N—H and C=O bonds in the title compound, C9H9Cl2NO3S, are trans to each other, similar to what is observed in 2,2,2-trimethyl-N-(phenyl­sulfon­yl)acetamide and 2,2,2-trimethyl-N-(4-methyl­phenyl­sulfon­yl)acetamide. The bond parameters in the title compound are also similar to those in the aforementioned two structures. N—H⋯O hydrogen bonds connect the mol­ecules into chains running along the a axis

2,2,2-Trimethyl-N-(4-methyl­phenyl­sulfon­yl)acetamide

The bond parameters and conformations of the N—H and C=O bonds of the SO2—NH—CO—C group in the title compound, C12H17NO3S, anti to each other, are similar to what has been observed in related structures. The benzene ring and the SO2—NH—CO—C group make a dihedral angle of 71.2 (1)°. Inter­molecular N—H⋯O hydrogen bonds link the mol­ecules into centrosymmetric dimers

A Visual Computing Unified Application Using Deep Learning and Computer Vision Techniques

Vision Studio aims to utilize a diverse range of modern deep learning and computer vision principles and techniques to provide a broad array of functionalities in image and video processing. Deep learning is a distinct class of machine learning algorithms that utilize multiple layers to gradually extract more advanced features from raw input. This is beneficial when using a matrix as input for pixels in a photo or frames in a video. Computer vision is a field of artificial intelligence that teaches computers to interpret and comprehend the visual domain. The main functions implemented include deepfake creation, digital ageing (de-ageing), image animation, and deepfake detection. Deepfake creation allows users to utilize deep learning methods, particularly autoencoders, to overlay source images onto a target video. This creates a video of the source person imitating or saying things that the target person does. Digital aging utilizes generative adversarial networks (GANs) to digitally simulate the aging process of an individual. Image animation utilizes first-order motion models to create highly realistic animations from a source image and driving video. Deepfake detection is achieved by using advanced and highly efficient convolutional neural networks (CNNs), primarily employing the EfficientNet family of models

N-(4-Chloro­phenyl­sulfon­yl)-2,2,2-tri­methyl­acetamide

In the crystal structure of the title compound (N4CPSTMAA), C11H14ClNO3S, the conformations of the N—H and C=O bonds in the amide group are anti to each other, similar to those observed in N-phenyl­sulfonyl-2,2,2-trimethyl­acetamide (NPSTMAA) and 2,2,2-trimethyl-N-(4-methyl­phenyl­sulfon­yl)acetamide (N4MPSTMAA). The bond parameters in N4CPSTMAA are similar to those in NPSTMAA, N4MPSTMAA, N-aryl-2,2,2-trimethyl­acetamides and 4-chloro­benzene­sulfonamide. The –SNHCOC– unit including the amide group is essentially planar and makes a dihedral angle of 82.2 (1)° with the benzene ring, comparable to the values of 79.1 (1) and 71.2 (1)° in NPSTMAA and N4MPSTMAA, respectively. The mol­ecules in N4CPSTMAA are linked into a chain by inter­molecular N—H⋯O hydrogen bonds