This study was carried out for the investigation of the Late Permian Wargal limestone at Kafar Kot Chashma area, Khisor Range to determine its suitability as an aggregate that is used in road construction and civil structures with the help of geological engineering testing. The results of geological engineering testing of Wargal limestone samples show the tolerable values of all standard engineering parameters including the Loss Angles Abrasion value (23.37%), Aggregate impact (16.8%), Crushing value 13.1%, Unit weight 1.67, Soundness (1.007%), Specific gravity (2.70), Water Absorption (0.48%), Flakiness Index (6.5%), Elongation value (7.1%), Coating of bitumen (> 95%), stripping of bitumen (<5%), California Bearing Ratio (CBR) value (93.6%), Maximum Dry Density 2.307g/c and Optimum Moisture Content (5.79%). As per different International and National Standards like AASHTO, ASTM, BS and NHA, the mentioned results of various engineering tests were within the tolerable limits. The petrography of the selected samples of the Late Permian Wargal limestone revealed very minor value of quartz (0.5%), hematite/limonite (0.6%) and clay content 1.0% showing the insignificant threat of ASR. The values of dolomite are limited to (1%) which shows that there is no ACR reaction with ordinary Portland cement. The results of geological and engineering parameters of the study area strongly suggest its suitability as a potential aggregate (i.e. for the base course, subbase course, cement concrete and asphalt) in the road construction.

No abstract

No abstract

With the advent of online social media, such as articles, websites, blogs, messages, posts, news channels, and by and large web content has drastically changed the way individuals take a glimpse at different things around them. Today, it's an everyday practice for some individuals to read the news on the web. Sentiment analysis (also called opinion mining) alludes to the utilization of natural language processing, content investigation, and computational linguistics to distinguish and separate subjective data in source materials. Sentiment analysis is broadly applied to online reviews, news feeds and social networking for a wide variety of applications, ranging from marketing to client services. Sentiment analysis emphasizes on the classification of textual data into positive, negative and neutral categories. This research is an endeavor to the case study that calculates news polarity or emotions on different sports feeds which may influence changes in sports news development patterns. The interest of this approach is to generate various text analytics that computes feelings from all pertinent ongoing sports news accessible out in the public domain. The significance and application value of sentiment analysis of RSS feeds in this study is to distinguish between positive feeds and negative feeds on sports that could affect readers or users minds in order to improve RSS feeds messaging broadcast among folks. The methodology utilizes the sentiment analysis techniques using two different online open-source sentiment analysis tools in Rich Site Summary (RSS) news feeds that have an influence on sports-related broadcast esteems.