Suchergebnisse

Tanulmányomban egy jellegzetes monarchia kori szövegtípus, a fürdői levél műfajával foglalkozom a 19. századi magyar irodalom kontextusában. A birodalom határain belül kialakult jellegzetes fürdőélet társadalmi gyakorlattá válásával megjelenő szövegtípus a modernizálódó sajtó közegében élte virágkorát, de – az episztola műfajának leértékelődése mellett – épp emiatt, mediális megelőzöttsége okán nem válhatott nagy presztízsű irodalmi formává. Ugyanakkor beszédmódjának, nyelvhasználatának nyomai megjelennek a hosszú 19. század magyar prózairodalmában. A műfaj formai-tartalmi jellegzetességeinek és korai magyar klasszikusainak (Gvadányi József, gróf Dessewffy József) ismertetése mellett a 19. századi sajtóban megjelenő fürdőlevelek eszmetörténeti jelentőségére és mediális aspektusaira is kitérek, illetve Mikszáth Kálmán példáján a fürdőleveleket jellemző írásmód paródiáját is bemutatom.

Image and video data are today being shared between government entities and other relevant stakeholders on a regular basis and require careful handling of the personal information contained therein. A popular approach to ensure privacy protection in such data is the use of deidentification techniques, which aim at concealing the identity of individuals in the imagery while still preserving certain aspects of the data after deidentification. In this work, we propose a novel approach towards face deidentification, called k-Same-Net, which combines recent Generative Neural Networks (GNNs) with the well-known k-Anonymity mechanism and provides formal guarantees regarding privacy protection on a closed set of identities. Our GNN is able to generate synthetic surrogate face images for deidentification by seamlessly combining features of identities used to train the GNN model. Furthermore, it allows us to control the image-generation process with a small set of appearance-related parameters that can be used to alter specific aspects (e.g., facial expressions, age, gender) of the synthesized surrogate images. We demonstrate the feasibility of k-Same-Net in comprehensive experiments on the XM2VTS and CK+ datasets. We evaluate the efficacy of the proposed approach through reidentification experiments with recent recognition models and compare our results with competing deidentification techniques from the literature. We also present facial expression recognition experiments to demonstrate the utility-preservation capabilities of k-Same-Net. Our experimental results suggest that k-Same-Net is a viable option for facial deidentification that exhibits several desirable characteristics when compared to existing solutions in this area.

The present and near term military balance of power between the U.S. and the Soviet Union can be expressed in a variety of net assessments. One can examine the strategic nuclear balance, the conventional balance in Europe, the maritime balance, and many others. Such assessments are essential not only for policy making but for arms control purposes and future force structure planning. However, to project the future military balance, one must include an assessment of the base technological balance between the U.S. and the Soviet Union. The West has traditionally relied on a technological edge in weaponry to offset the numerical advantages of the Soviet Union and its surrogates. The foundations of high-Tech weaponry lie in the base technologies. Although the U.S. clearly benefits from the technological development s of its allies, this paper focuses on the U.S. and the Soviet Union. Its objective is to identify the critical issues of the technological balance that affect the future military balance of power. Figure 1 illustrates the interdependence of a nation's technology base, its force objectives, and fielded weapons. While the focus is on the technological bases of the U.S. and the Soviet Union, such an assessment must address these relationships. (kr) ; http://archive.org/details/nettechnicalasse00wegm ; Approved for public release; distribution is unlimited.