Shaikha Saleh Mohamed Hassan
Implement Artificial Intelligence Machine Learning Add-In to execute Digital Forensics investigations. Searching the evidence from a database feeder with the objective needs to be learned by reinforcement learning. The programmed Add-In programmed with an algorithm aiming and expect the Machine through trial-and-error to achieve that goal attempting to climb over the most object recognition until it finds with different percentages.
The Add-In will utilize the searching in the evidence copy any related pictures or photos which will be uploaded in the internal migrated database. Artificial Intelligence Add-In will help in protecting the suspect's privacy from being seen by the digital forensic examiner/investigator. Moreover, it will illustrate related compared images to the investigator with the compared percentage and permit the digital examiner/investigator to search in a specific time frame, which usually will be in the time frame of the incidents.
The Add-In will assist superiorly in achieving detailed results and achieving the adjuster and fair conclusion without any judgmental and
human error. Likewise, the fast scanning to match time speed which will solve more cases in a shorter time. 33% after day 15 PF. The live ticks started dying from day 40 PF and the last one died 52 days PF. Cow DNA was detected with bright bands in the dead ticks from day 1 PF to day 290 PF which is when the last sample was run, so the detection limit of DNA in dead ticks could not be determined. The persistence of host DNA in ticks showed the utility of ticks in forensic investigations. The methods used in this study can be used in forensic acarology to identify the host species of an arthropod when it is found at a crime scene.
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