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Abstract Facial Recognition Technology (FRT) has become a powerful tool for law enforcement agencies, enabling the automated identification of individuals through their unique facial features. Its growing use across Europe has raised fundamental legal and ethical concerns, particularly regarding privacy and data protection. This article analyses the implications of FRT under European Union (EU) law,…

In Mobile Ad Hoc Networks (MANETs), broadcasting is a fundamental operation for network control and data dissemination. It involves transmitting a message from one node to all other nodes in the network. Effective broadcasting methods are essential for functions such as route discovery, topology maintenance, and group communications. Key Broadcasting Techniques: Flooding The simplest broadcast…

Overview The study “Analysis of Modern Condition of Military Radiocommunication System” examines the current state of military communication infrastructure used in conflict zones in Eastern Ukraine. It reviews several categories of communication systems, including high-frequency (HF) and ultra-high-frequency (UHF) radios, satellite communications, radio-relay systems, and tropospheric communication. The authors evaluate their technical features, strengths, and…

This project showcases a powerful Face Detection and Recognition system intended to improve law enforcement skills by speeding up the identification of suspects in criminal cases. The system uses scalable databases and real-time computation, however instead of using traditional web sources for face detection. Accuracy and dependability are ensured by using the LBPH algorithm for face recognition…

Criminology is an area that focuses the scientific study of crime and criminal behavior and is a process that aims to identify crime characteristics. It is one of the most important fields where the application of data mining techniques can produce important results. A broad analysis of unlawful activity reveals that all criminal behavior shares…

Abstract & Purpose This paper proposes a crime analysis methodology supported by machine learning techniques to predict and analyze criminal behavior patterns. Using historical crime data, the framework applies algorithms such as Random Forest, Decision Tree, SVM, XGBoost, and Multilayer Perceptron to classify crime types, determine severity, and map when and where crimes occur. Visualization…