Abstract: An impact blood splatters generation experimental apparatus capable of measuring an applied force includes: a hammer including a rod-shaped body portion, a head portion formed at one end of the body portion, and a striking portion formed on one side of the head portion; a housing receiving a certain amount of blood thereon and including a striking surface on which the striking portion may strike; a tensile force gauge attached to an outer surface of the housing; an elastic member having one end connected to the body portion and the other end connected to the tensile force gauge; and a display unit displaying a force applied to the hammer, the force being measured by the tensile force gauge, when a user lifts the hammer to strike the striking surface.

Abstract: A temperature and humidity chamber type apparatus for taking potential impact marks according to an embodiment includes: a specimen treated with an amino acid reaction reagent to react with potential impact marks to take the potential impact marks; a chamber in which a receiving space for receiving the specimen is secured; a door for opening and closing the chamber; a supporter formed in the receiving space to receive the specimen; an adjuster for adjusting temperature and humidity in the chamber within a set application time range to take the potential impact marks; a display unit attached to one side of the outside of the chamber to display an operation state in the chamber; a power source; a controller for controlling setting of temperature, humidity, and an application time in the chamber; and an input unit in which the controller operates according to a user's input.

Abstract: According to an embodiment, a method of determining tool mark identity using machine learning may include: obtaining surface height data of at least two tool strip marks by photographing tool strip marks generated using at least two tools with a three-dimensional (3D) microscope; generating a data set by calculating a cross-correlation coefficient for the surface height data of the tool strip marks; separating the data set into a training set for machine learning training and a test set for verifying a machine learning result; performing the machine learning training to determine whether the tool strip marks are identical using the training set; and verifying a result of the machine learning training using the test set.