Classification of News Articles using Supervised Machine Learning Approach

Today the big challenge for NEWS organization to well organize the news and well categorize the news in automatically no need the data entry people to enter and select the category and then based on the category and its sub-category they will be manually selected and enter the details and then after this the analysis will later on used for different aspects. The news is almost every second used in different sources of media in soft and hard. We use the both sources of the Pakistan News in dual languages English and Urdu both and process them and prepare them for machine learning and based on the Machine learning trained data we build a very effective and efficient model that can predict the title category of the news and category of description of the news. We use different machine learning algorithms and different features extraction finally we build the model using the machine learning algorithm with 89% accuracy with logistic regression.

Synthesis, Characterization and Analytical Applications of Polypyrrole-Metal Oxide Composites

In the current study, PPy and its composites with V2O5 were synthesized in aqueous medium by chemical oxidation polymerization method using FeCl3.6H2O as an oxidant. The materials were characterized using FT-IR spectroscopic, XRD, TGA, SEM, EDX techniques, surface area and pore size analyzer, UV-visible spectrophotometry and LCR-meter. The FT-IR results confirmed the successful synthesis of PPy and PPy/V2O5 composites. The XRD study showed the amorphous and crystalline nature of PPy and PPy/V2O5 composites, respectively. The TGA analyses showed slight increase in the thermal stability of the composites. The SEM data ratified the porous nature of PPy and PPy/V2O5 composites. The BET surface area of the samples was found to increase with the increase in the content of V2O5. The UV-visible spectrophotometry confirmed the doping of PPy in the composites. The electrical properties of the samples showed their semiconducting nature. The resistance of the samples was found to be dependent on temperature and V2O5 content in the composites. Afterward, the electrochemical gas sensing behavior of the samples was evaluated for ammonia and some common organic liquid vapors. The results showed that the composites were more sensitive and selective towards ammonia and therefore, further studied with respect to V2O5 content in the composites, temperature and ammonia concentration. Among the studied samples, PPy/V2O5 composites with 8wt.% of V2O5 showed best sensitivity response toward ammonia at 25 oC in the range of 5 to 200 ppm with LOD 1.4 ppm. The sensitivity, response and recovery time of this composite was determined from dynamic response curve at 10ppm ammonia and found to be 19.5%, 10.5 and 81.6 s, respectively. The highly selective ammonia sensing performance of PPy/8%V2O5 composites 18 may be due the incorporation of V2O5 in PPy and could be declared as a promising candidate for sensitive gas sensors.