Jumala valon, rakkauden ja elämän kommunikaationa : Kevin Vanhoozerin kommunikatiivinen teismi

Tutkielman tehtävänä on selvittää, mitä Kevin Vanhoozer tarkoittaa kommunikatiivisella teismillä. Tutkielman tärkein lähde on Kevin Vanhoozerin teos Remythologizing Theology, jossa hän esittelee kommunikatiivista teismiä. Kommunikatiivinen teismi liittyy yhteen Vanhoozerin kehittämän remytologisaation metodin kanssa, joka kehittelee eteenpäin hänen aikaisemman tuotantonsa hermeneuttisia teemoja. Tutkielmassa esitellään Vanhoozerin puheaktiteoriapohjaista käsitystä kommunikaatiosta ja jumalallisesta draamasta osana hänen kommunikatiivista teismiään, sekä tarkastellaan Vanhoozerin hermeneutiikkaa, joka on kommunikatiivisen teismin taustalla. Kommunikatiivinen teismi käsittelee Jumalan kommunikaatiota ja hänen olemustaan tämän kommunikaation perusteella. Kommunikatiivinen teismi tarkastelee Jumalan kommunikaatiota Raamatussa ja sitä, miten kommunikaatio ilmenee sekä Kolminaisuuden sisällä että Jumalan ja ihmisten välillä. Jumalan kommunikaation sisältönä on kommunikatiivisen teismin mukaan valo, rakkaus ja elämä eri tavoin. Jumalan ja maailman suhdetta tarkastellaan kirjailija-metaforan kautta: Jumala on maailman kirjailija, maailma hänen teoksensa ja ihmiset sen sankareita.

Ajuste estatal sin equilibrio político : la gestión de López Murphy como ministro de economía de la Alianza en marzo de 2001

Resumen: Este trabajo intenta abordar desde la perspectiva de la historia política la corta gestión, de apenas diecisiete días, de López Murphy como Ministro de Economía de la Alianza en marzo de 2001 como un caso de estudio del “triángulo de gobierno” de Matus. Para esto, primero señalaremos la conformación inicial de los equilibrios políticos de la Alianza, explicando por qué se designó como primer Ministro de Economía a Machinea, enfatizando los delicados compromisos sobre los cuales debió actuar, así como su progresivo agotamiento. Luego, analizaremos cómo su reemplazo por López Murphy generó un profundo cambio de alianzas políticas, generando diversos tipos de enfrentamientos y reagrupamientos, que debilitaban la opción que representaba López Murphy. Igualmente, y a pesar de las resistencias iníciales, veremos que López Murphy decidió llevar a cabo un descomunal ajuste estatal, sin miramientos por las condiciones políticas para aplicarlo. Finalmente, nos dedicaremos a plantear el fin de la gestión de López Murphy y el cambio de condiciones que generó su reemplazo por Cavallo, cambio sobre el cual la Alianza hizo depender su suerte política.

Context-Based Vision System for Place and Object Recognition

While navigating in an environment, a vision system has to be able to recognize where it is and what the main objects in the scene are. In this paper we present a context-based vision system for place and object recognition. The goal is to identify familiar locations (e.g., office 610, conference room 941, Main Street), to categorize new environments (office, corridor, street) and to use that information to provide contextual priors for object recognition (e.g., table, chair, car, computer). We present a low-dimensional global image representation that provides relevant information for place recognition and categorization, and how such contextual information introduces strong priors that simplify object recognition. We have trained the system to recognize over 60 locations (indoors and outdoors) and to suggest the presence and locations of more than 20 different object types. The algorithm has been integrated into a mobile system that provides real-time feedback to the user.

Sharing visual features for multiclass and multiview object detection

We consider the problem of detecting a large number of different classes of objects in cluttered scenes. Traditional approaches require applying a battery of different classifiers to the image, at multiple locations and scales. This can be slow and can require a lot of training data, since each classifier requires the computation of many different image features. In particular, for independently trained detectors, the (run-time) computational complexity, and the (training-time) sample complexity, scales linearly with the number of classes to be detected. It seems unlikely that such an approach will scale up to allow recognition of hundreds or thousands of objects. We present a multi-class boosting procedure (joint boosting) that reduces the computational and sample complexity, by finding common features that can be shared across the classes (and/or views). The detectors for each class are trained jointly, rather than independently. For a given performance level, the total number of features required, and therefore the computational cost, is observed to scale approximately logarithmically with the number of classes. The features selected jointly are closer to edges and generic features typical of many natural structures instead of finding specific object parts. Those generic features generalize better and reduce considerably the computational cost of an algorithm for multi-class object detection.

Contextual models for object detection using boosted random fields

We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which uses Boosting to learn the graph structure and local evidence of a conditional random field (CRF). The graph structure is learned by assembling graph fragments in an additive model. The connections between individual pixels are not very informative, but by using dense graphs, we can pool information from large regions of the image; dense models also support efficient inference. We show how contextual information from other objects can improve detection performance, both in terms of accuracy and speed, by using a computational cascade. We apply our system to detect stuff and things in office and street scenes.

The emotional structure of the advertising message in radio

Radio advertising is suffering from a remarkable crisis of creativity as it has yet not found its role in a radio model based on voice locution and information genres. This article suggests the need for implementing a peripheral or heuristic strategy to attract and hold listeners’ attention. Within this framework, the narration and scene representation are proposed as suitable persuasion techniques. The objective is to design a useful conceptual tool for an efficient creative conception of narration at the service of certain commercial strategy. First, the concept of narrative persuasion is grounded according to the possibilities of the sound code. Second, the keys of scene representation and commercial strategy (brand, product, advantage, benefit and target) within the sound message are presented. And third, these keys are articulated in a model. This model is pre-tested by means of analyzing eight different case-radio ads.