Alkotmány - választás - választási rendszer

An emblematic personality of the law sciences between 1945 and 1990, ISTVÁN KOVÁCS dealt primarily with constitutional requirements and their implementation. He approached and examined elections from this aspect. The author provided an analysis of his own views on elections, determining five elements which played a fundamental role in the development of his ideas. First, his view on social and political role of constitutions, second, the realization of popular sovereignty and representation, third, the specific social and political circumstances, fourth, the historical-comparative study of socialist constitutional and electoral development, fifth, the history and development of the Hungarian elections. Based on these elements his most important idea was that the representation system expresses the interest- and opinion differences of society and to establish a corresponding electoral system. In addition to the primacy of the territorial principle he envisioned achieving this aim by increasing the role of the workplace-employment principle and social organizations in candidate system which was the most important element in the socialist electoral system. The result of these ideas was the introduction of multimember system, then making it compulsory. Under the given political circumstances this was the most that could possibly be achieved. The work of ISTVÁN KOVÁCS and the electoral history of the socialist era both underpin: without political pluralism and multiparty system the popular will cannot be converted into political power, which was his fundamental thesis

A comparative study on the privacy risks of face recognition libraries

The rapid development of machine learning and the decreasing costs of computational resources has led to a widespread usage of face recognition. While this technology offers numerous benefits, it also poses new risks. We consider risks related to the processing of face embeddings, which are floating point vectors representing the human face in an identifying way. Previously, we showed that even simple machine learning models are capable of inferring demographic attributes from embeddings, leading to the possibility of re-identification attacks. This paper examines three popular Python libraries for face recognition, comparing their face detection performance and inspecting how much risk each library's embeddings pose regarding the aforementioned data leakage. Our experiments were conducted on a balanced face image dataset of different sexes and races, allowing us to discover biases in our results