Machine Learning

Anthropometric studies focusing on facial metrics and their proportions form an important research area devoted to observations of the appearance of the human skull. Many different applications include the use of craniometry for maxillofacial reconstruction and surgery. The paper and the associated dataset explores the possibility of using selected craniometric points and associated metric to observe  spatial changes during the maxillofacial surgery treatment.  The experimental dataset includes observations of 27 individuals.

content-based dataset that composes of 12 features for eight common types of files (JPG, PNG, HTML, TXT, MP4, M4A, MOV, and MP3) to be suitable for file type identification (FTI). These features were extracted from pool of file fragment of size 512 byte each from all the prementioned eight types. This dataset is developed in such a way that can be used for supervised and unsupervised ML model. It provides the ability to classifying and clustering the above-mentioned type into two levels.

Early detection of retinal diseases is one of the most important means of preventing partial or permanent blindness in patients. One of the major stumbling blocks for manual retinal examination is the lack of a sufficient number of qualified medical personnel per capita to diagnose diseases.

Access to potable water is a critical requirement for human survival. Beyond drinking, water is also necessary for animal consumption, irrigation, as well as domestic and commercial uses. Laboratory assessments of water samples to determine their fitness for use is a vital step in water quality assurance processes. However, laboratory assessments require adherence to stringent measures, which might be difficult to comply with.