Crime Prediction and Analysis against women Using LRSRI-Missing Value Imputation and FIPSO - Optimum Feature Selection Methods

Data investigation is the method of considering crude measurements in arrange to draw conclusions around them. Many statistics evaluation techniques and tendencies had been automated into mechanical techniques and algorithms in such a manner that they provided raw statistics for human consumption. Machine learning could be a portion of artificial intelligence that permits computer frameworks to "analyze" their own statistics and improve them over time without being explicitly programmed. Machine learning algorithms can understand patterns in statistics and analyze them to make their own predictions. Lost esteem ascription is one of the foremost vital procedures in data pre-processing and it is additionally the most prepare of information examination. Ascription of lost information for a variable replaces lost information with a esteem inferred from an assess of the dispersion of that variable. Basic accusation employments as it were one suspicion. Numerous ascriptions employments diverse gauges to reflect the instability in evaluating this dispersion. In this article, The proposed method LRSRI used for impute the missing values on Crime against Women Data-set(CAW).The Linear Regression Imputation and Stochastic regression imputations are used in this method.Feature selection is another important data preprocessing techniques.This is often called attribute selection or feature selection. The most important problem in predictive modeling is the mechanical selection of features in the data. In this work,the proposed method FIPSO implemented for feature selection.This is feature importance and Particle Swarm Optimization based method.The main objective of this work is predict the crime rate against women in India based on 2001 to 2021 crime recorded against women in India.This Data set is collected from Data.gov.in.Finally The predicted result is compared with recent NCRB crime report.The proposed method LRSRI and FIPSO has given 98.34% accuracy of crime prediction.In feature,This outcome will be valuable for the crime office to control the CAW in India

Thermal studies on electrodeposited black oxide coating on magnesium alloys

Thermal behavior of black anodic coatings on magnesium alloy, AZ31B and magnesium lithium alloy, MLA 9 has been investigated. The chemical nature of coating is characterized by infrared spectral studies. The thermoanalytical investigations have been carried out using thermogravimetry (TG), derivative thermogravimetry (DTG), and differential scanning calorimetry (DSC). The decomposition proceeds through three steps viz., dehydration, decomposition of chromium hydroxide and sulphate and decomposition of magnesium chromate to oxide. Measurement of hemispherical emittance of coatings verses temperature was investigated using calorimetric methods. The studies revealed that the thermal emittance of coatings increases with temperature. © 2001 Elsevier Science B.V

Enzymatic hydrolysis of market vegetable waste and subsequent ethanol fermentation-Kinetic evaluation

In this work, kinetic properties evaluation was made for bioethanol production from sugar hydrolysate of vegetable waste. The saccharified sugars were fermented by using Saccharomyces cerevisiae. The effect of various saccharification factors on sugars release were studied and observed that the optimized conditions contributed to 14.4 gL-1of fermentable sugars production. The produced sugars were subjected to batch fermentation by Saccharomyces cerevisiae at pH 4.5 and the kinetic parameters of fermentation were estimated by fitting the experimental data in modified logistic equations. The data revealed product (ethanol) yield (YP/S) of 0.39g/g of reducing sugars. Maximum specific growth rate (μmax), the yield of ethanol on biomass (YP/X) and the yield of biomass on sugars utilization (YX/S) were determined to be 0.18 h-1, 1.097 g/g and 0.313 g/g, respectively. The process yielded 4.13 gL-1 of ethanol by consumption of 10.6 gL-1 sugars with a volumetric production rate of 0.0861±0.002 gL-1 h-1

A Reliable Path Selection Mechanism to Enhance QoS in MANET Routing Protocols

Abstract — MANET is a collection of mobile nodes forming a dynamic autonomous system without using any physical infrastructure. Mobility of mobile nodes leads to dynamic change in topology of the network. The topological change in MANET leads to Path failure which degrades the network performance. A fundamental issue arising in MANETs is the selection of optimal path between any two nodes. In this paper multipath between source and destination are determined; reliability measurement is done towards node and path to predict the risk on the specified path. The proposed RSCPS Reliability Measurement is associated with Service Curve Measurement (RSCPS) to enhance the QoS through node stability, amount of data to be transmitted and bandwidth required to send the data

Optimisation of cryopreservation technique in Mokara golden nugget orchid using PVS2 vitrification.

The study was conducted to evaluate the effects of various sucrose concentrations on Mokara orchid shoots (0.5-1.0 and 1.0-1.5 cm) after precultured at 24 and 48 h. The 1.0-1.5 cm of Mokara shoots preculture at 0.25 M sucrose for 48 h was the best condition based on TTC assay and subsequently used for the following PVS2 vitrification treatment. The selected Mokara orchid shoots were subjected to PVS2 treatment at different time of exposure (min) and temperatures (0 and 24°C). The results showed that viability of shoots reached the highest absorbance value at 10 min and 24°C. However, for the overall treatment with the results shown that 0°C temperature treatment gave the higher absorbance value which could reduce the injurious effects of PVS2. For chlorophyll determination, cryopreservation of shoots at 0°C without LN (LN-) for 5 min exposure to PVS2 recorded as highest chlorophyll content. The result also shows that total chlorophyll a for shoot in all treatment were higher than chlorophyll b