Computing Technology

Remote sensing, powerful computing engines, and agent-based models offer new ways to interpret data and broaden data collection, moving archaeologists closer to their ultimate goal of approximating the individual within an extensive, interpreted, digital environment. The first Web extra is a video that demonstrates how the advanced acquisition and processing of magnetic data has led to new discoveries and insights, such as the "Henge" monument excavated near Stonehenge in 2010. The second Web extra is a video that illustrates how researchers used 3D seismic data, initially collected for use in oil and gas exploration, to reconstruct Doggerland, a lost Mesolithic landscape that was inundated by the North Sea during the last great period of global warming.

People use online platforms such as Facebook, Twitter, etc. for social networking and share their opinions, feelings or beliefs with others. Sharing is done by posts on these platforms. Sentiment analysis or opinion mining of these posts using machine learning techniques is of great significance. The analysis is generally carried out with sentiment, subjectivity analysis or polarity calculations. In this study, we performed a sentiment analysis of text messages using supervised machine learning techniques. They are mainly online product reviews, general tweets in Tweeter and movie reviews. Messages are pre-processed and then used three different machine learning techniques, namely Naïve Bayes, Decision Tree and Support Vector Machine (SVM) for sentiment analysis.

This paper presents a decision support based, dynamic approach to optimal threat evaluation and defensive resource scheduling. The algorithm provides flexibility and optimality by swapping between two objective functions, based on preferential and ...