Reform-törekvések Kovács István munkásságában az alapvető jogok alkotmányi szabályozása kérdésében

During his outstanding professional career of forty years, István Kovács played a decisive role – as a professor at law and as well as the head of the Institute of Law and Political Science (Hungarian Academy of Sciences) – in the teaching and researching of Hungarian constitutional law. In the field of constitutional development, he always paid great attention to the regulation of citizen's /constitutional/ rights and then human rights. The study aims to show, how Kovács came up with proposals that were beyond his age in the course of Constitutional attempts, despite the ideological and political constraints of the socialist era. The results of his work were well documented in the draft constitution of 1962 and the implemented constitutional revision in 1972. In 1988, he described an idea of a constitution that had already proved suitable for the preparation and implementation of the regime change in Hungary. The article argues that Kovács' proposals, despite the constraints of the given period, have always been progressive, and some of them can still be considered relevant in the regulation of human and constitutional rights

Using big data in startup selection : exploring machine learning as a tool to predict successful startups in the age of social media

This research aims to further explore the possibilities in the usage of Machine Learning within the Venture Capital industry. Building on previous research the goal of this paper is to determine whether social media analyses can improve the accuracy of Machine Learning models to predict startup outcomes and valuations for startup companies. The research is built on the following models: Multilayer Perceptron, XGBoost, RandomForest, Naive Bayes, and Voting Regressor. The data used in this research comes from Crunchbase, USPTO, and Twitter. The models in this research achieved an adjusted R2 of 0.5281 for value prediction, which shows that exit value is explainable to a large extent by using publicly available qualitative and quantitative data. Outcome prediction had precision for IPO between 0.1447 to 0.4193 and F1-scores between 0.2360 to 0.4449 for models built from Series A to Series C funding rounds. The results of this research show that Venture Capital firms investing from Series A to Series C would be able to outperform the market in terms of returns by implementing Machine Learning in their investment decision-making process. To further improve these results extracting further social media data is a beneficial future resource. Compared to previous models this research built models for 3 specific early funding rounds and can outperform the markets with data available for VCs at these points in time.Esta investigação visa explorar mais profundamente as possibilidades de utilização da aprendizagem mecânica na indústria do Venture Capital. Com base em pesquisas anteriores, o objectivo deste trabalho é determinar se as análises dos meios de comunicação social podem melhorar a precisão dos modelos de Machine Learning para prever os resultados e as avaliações das empresas em fase de arranque. A investigação baseia-se nos seguintes modelos: Multilayer Perceptron, XGBoost, RandomForest, Naive Bayes, e Voting Regressor. Os dados utilizados nesta pesquisa provêm de Crunchbase, USPTO, e Twitter. Os modelos nesta pesquisa alcançaram um R2 ajustado de 0,5281 para previsão de valor, o que mostra que o valor de saída é explicável em grande medida através da utilização de dados qualitativos e quantitativos disponíveis publicamente. A previsão de resultados teve precisão para IPO entre 0,1447 a 0,4193 e pontuações F1 entre 0,2360 a 0,4449 para modelos construídos das séries A a séries C de financiamento. Os resultados desta investigação mostram que as empresas de Venture Capital que investem da Série A à Série C seriam capazes de superar o mercado em termos de retorno, implementando a Machine Learning no seu processo de tomada de decisões de investimento. Para melhorar ainda mais estes resultados, extrair mais dados dos meios de comunicação social é um recurso futuro benéfico. Em comparação com modelos anteriores, esta investigação construiu modelos para 3 rondas de financiamento antecipado específicas e pode superar os mercados com dados disponíveis para VC nestes pontos no tempo

Robust Trajectory Tracking Control of a Differentially Flat Overhead Crane Using Sliding Mode

The control of overhead cranes is a benchmark problem, since it is an underactuated mechanism and its mathematical model is nonlinear. During operation the mass of the load is unknown, representing an uncertainty in the inertial parameters, which requires robustness of the controlled system. Our paper proposes a novel robust control method, that combines the differentially flat property of the dynamics with the robustness of the sliding mode control. The sliding surface is constructed to ensure the tracking of the configuration variables whose accelerations is calculated using the flatness property of the dynamic model. This formulation also allows achieving the matching conditions of the parameter uncertainties. Considering a simplified overhead crane model where the load motion is restricted in a vertical plane, two sliding surfaces are defined for the rope angle and rope length, since the cart position can be calculated from the previous two. The suggested control method is successfully validated in simulations as well as using a reduced-size overhead crane. For the real crane, the rope angle was estimated by utilizing the dynamical model, which uses the estimated cart acceleration

IDEAS REFLECTED IN THE FUTURE PUBLIC TRANSPORT ASSOCIATION IN THE AREA OF BUDAPEST

Western countries with high motorisation realised years ago the fact that the excessive increase in the rate of motorisation would have to be restricted especially in densely populated urban areas. There have been enormous efforts to promote the public way of transport, which, however, can only be maintained with a highly professional structure and a management coupled with adequate financial provisions from the state. In the ex-socialist countries including Hungary, a great deal of change has been observed in the modal split towards the share of private cars. The increased use of private cars is threatening the dominance of the heritage of the past system, the rather low profile in terms of service standards but quite reliable in terms of timetable density and relatively cheap public transport. Following the examples of the West in this regard without paying attention to adjusting the specific characteristics in solutions of the problem can only bring about committing similar mistakes and thus paying an enormous price

A szociális biztonság alkotmányjogi megítélése Magyarországon a rendszerváltozást követően

The author’s aim was to schematically highlight the exhibitions of theoretical models and approaches of social rights and narrowly the right to social security in point of view of the 1989 Constitution and the 2011 Fundamental Law. The first part of the article analyzes the theoretical questions and definitional refinements regarding social rights, further introduces the different types of constitutional regulations in Europe. In the second part, the author presents and analyzes the Constitution and the Constitutional Court’s jurisprudence build thereon. Afterwards, briefly summarizes the most important attributes of the „paradigm change” introduced by the Fundamental Law, namely the diminution of social security into state objective