Background: The COVID-19 pandemic has made people spend more time on online meetings than ever. prolonged looking at the monitor may cause fatigue, which can subsequently impact mental and physical health. A fatigue detection system is needed to Internet users well-being. Previous research related used a fuzzy system, but accuracy was below 85%. In this research, machine learning improve accura...

Concept lattice model, the core structure in Formal Concept Analysis, has been successfully applied in software engineering and knowledge discovery. In this paper, we integrate the simple base classifier (Naïve Bayes or Nearest Neighbor) into each node of the concept lattice to form a new composite classifier. We develop two new classification systems, CLNB and CLNN, that employ efficient const...

A nearest-neighbor classifier compares an unclassified object to a set of preclassified examples and assigns to it the class of the most similar of them (the object’s nearest neighbor). In some applications, many pre-classified examples are available and comparing the object to each of them is expensive. This motivates studies of methods to remove redundant and noisy examples. Another strand of...

The moving k nearest neighbor query, which computes one’s k nearest neighbor set and maintains it while at move, is gaining importance due to the prevalent use of smart mobile devices such as smart phones. Safe region is a popular technique in processing the moving k nearest neighbor query. It is a region where the movement of the query object does not cause the current k nearest neighbor set t...

Vegetation communities are traditionally mapped from aerial photography interpretation. Other semi-automated methods include pixeland object-based image analysis. While these methods have been used for decades, there is a lack of comparative research. We evaluated the cost-effectiveness of seven approaches to map vegetation communities in a northern Australia’s tropical savanna environment. The...