The English School of International Relations: A Contemporary Reassessment

Linklater, A. and Suganami, A. (2006). The English School of International Relations: A Contemporary Reassessment. Cambridge Studies in International Relations (No. 102). Cambridge: Cambridge University Press. RAE2008

The Poetics of the Limit : Ethics and Politics in Modern and Contemporary American Poetry

Woods, Timothy, The Poetics of the Limit (New York: Palgrave Macmillan, 2003) RAE2008

Audiences and Receptions of Sexual Violence in Contemporary Cinema

Barkre, M.; Mathijs, E.; Sexton, J.; Egan, K.; Hunter, R. and Selfe, M. (2007). Audiences and Receptions of Sexual Violence in Contemporary Cinema. London: British Board of Film Classification. RAE2008

The Place of the European Foreigner in Contemporary German Drama

Wilkinson, Jane, 'The Place of the European Foreigner in Contemporary German Drama', Third Text (2006) 20(6) pp.753-762 RAE2008 Special Issue: FORTRESS EUROPE: Migration, Culture and Representation

Kulturowy charakter czasu i przestrzeni. Analiza średniowiecznego i wczesnorenesansowego elitarnego budownictwa mieszkalnego i obronnego w Irlandii

Wydział Historyczny: Instytut Prahistorii

Indian Architecture: Social and Political Challenges

The objective of this paper is to reassess the central factors which have shaped the Indian architecture. The author puts forward the concept of plurality introduced by Western art historians and argues that the diversity of the Indian architecture should not be explained in terms of religious differences, but in terms of the socio-economical situation in South Asia. He also elaborates on the Hindu caste system and its impact on the Indian architecture.

The Terrorism Virus: Contemporary Traits and Mechanisms

In order to present and understand the nature of modern terrorism it is important to realize its key properties as well the mechanisms that shape terrorism. Selected properties and mechanisms shaping modern terrorism which can be exemplified by the following: evolutionary nature of terrorism, asymmetry of terrorism, interferentiality of terrorism, multitude of components of terrorism, diffusion of terrorism, duality of terrorism, positive dimension of terrorism, terrorist as the system, diversity of terrorist activity goals, changeability of terrorist threat, the broad and narrow dimension of terrorism, counter-anti-terrorism, the confrontational and cooperational character of relations, calculation and operational strategy, disintegrational nature of terrorism, multidisciplinarity of terrorism, horizontal and vertical dimension of terrorism and a the few other traits or mechanisms.

The Specialized Mappings Architecture

A probabilistic, nonlinear supervised learning model is proposed: the Specialized Mappings Architecture (SMA). The SMA employs a set of several forward mapping functions that are estimated automatically from training data. Each specialized function maps certain domains of the input space (e.g., image features) onto the output space (e.g., articulated body parameters). The SMA can model ambiguous, one-to-many mappings that may yield multiple valid output hypotheses. Once learned, the mapping functions generate a set of output hypotheses for a given input via a statistical inference procedure. The SMA inference procedure incorporates an inverse mapping or feedback function in evaluating the likelihood of each of the hypothesis. Possible feedback functions include computer graphics rendering routines that can generate images for given hypotheses. The SMA employs a variant of the Expectation-Maximization algorithm for simultaneous learning of the specialized domains along with the mapping functions, and approximate strategies for inference. The framework is demonstrated in a computer vision system that can estimate the articulated pose parameters of a human’s body or hands, given silhouettes from a single image. The accuracy and stability of the SMA are also tested using synthetic images of human bodies and hands, where ground truth is known.

Efficient End-Host Architecture for High Performance Communication Using User-level Sandboxing

Current low-level networking abstractions on modern operating systems are commonly implemented in the kernel to provide sufficient performance for general purpose applications. However, it is desirable for high performance applications to have more control over the networking subsystem to support optimizations for their specific needs. One approach is to allow networking services to be implemented at user-level. Unfortunately, this typically incurs costs due to scheduling overheads and unnecessary data copying via the kernel. In this paper, we describe a method to implement efficient application-specific network service extensions at user-level, that removes the cost of scheduling and provides protected access to lower-level system abstractions. We present a networking implementation that, with minor modifications to the Linux kernel, passes data between "sandboxed" extensions and the Ethernet device without copying or processing in the kernel. Using this mechanism, we put a customizable networking stack into a user-level sandbox and show how it can be used to efficiently process and forward data via proxies, or intermediate hosts, in the communication path of high performance data streams. Unlike other user-level networking implementations, our method makes no special hardware requirements to avoid unnecessary data copies. Results show that we achieve a substantial increase in throughput over comparable user-space methods using our networking stack implementation.

Specialized Mappings Architecture with Applications to Vision-based Estimation of Articulated Body Pose

A fundamental task of vision systems is to infer the state of the world given some form of visual observations. From a computational perspective, this often involves facing an ill-posed problem; e.g., information is lost via projection of the 3D world into a 2D image. Solution of an ill-posed problem requires additional information, usually provided as a model of the underlying process. It is important that the model be both computationally feasible as well as theoretically well-founded. In this thesis, a probabilistic, nonlinear supervised computational learning model is proposed: the Specialized Mappings Architecture (SMA). The SMA framework is demonstrated in a computer vision system that can estimate the articulated pose parameters of a human body or human hands, given images obtained via one or more uncalibrated cameras. The SMA consists of several specialized forward mapping functions that are estimated automatically from training data, and a possibly known feedback function. Each specialized function maps certain domains of the input space (e.g., image features) onto the output space (e.g., articulated body parameters). A probabilistic model for the architecture is first formalized. Solutions to key algorithmic problems are then derived: simultaneous learning of the specialized domains along with the mapping functions, as well as performing inference given inputs and a feedback function. The SMA employs a variant of the Expectation-Maximization algorithm and approximate inference. The approach allows the use of alternative conditional independence assumptions for learning and inference, which are derived from a forward model and a feedback model. Experimental validation of the proposed approach is conducted in the task of estimating articulated body pose from image silhouettes. Accuracy and stability of the SMA framework is tested using artificial data sets, as well as synthetic and real video sequences of human bodies and hands.

Assessing the Security of a Clean-Slate Internet Architecture

The TCP/IP architecture was originally designed without taking security measures into consideration. Over the years, it has been subjected to many attacks, which has led to many patches to counter them. Our investigations into the fundamental principles of networking have shown that carefully following an abstract model of Interprocess Communication (IPC) addresses many problems [1]. Guided by this IPC principle, we designed a clean-slate Recursive INternet Architecture (RINA) [2]. In this paper, we show how, without the aid of cryptographic techniques, the bare-bones architecture of RINA can resist most of the security attacks faced by TCP/IP. We also show how hard it is for an intruder to compromise RINA. Then, we show how RINA inherently supports security policies in a more manageable, on-demand basis, in contrast to the rigid, piecemeal approach of TCP/IP.

Estimating Human Body Pose from a Single Image via the Specialized Mappings Architecture

A non-linear supervised learning architecture, the Specialized Mapping Architecture (SMA) and its application to articulated body pose reconstruction from single monocular images is described. The architecture is formed by a number of specialized mapping functions, each of them with the purpose of mapping certain portions (connected or not) of the input space, and a feedback matching process. A probabilistic model for the architecture is described along with a mechanism for learning its parameters. The learning problem is approached using a maximum likelihood estimation framework; we present Expectation Maximization (EM) algorithms for two different instances of the likelihood probability. Performance is characterized by estimating human body postures from low level visual features, showing promising results.