DFKI-LT at QAST 2007: Adapting QA Components to Mine Answers in Speech Transcripts
The paper describes QAst-v1 a robust question answering system for answering factoid questions in manual and automatic transcriptions of speech. The system is an adaptation of our text---based crosslingual open---domain QA system that we used for the CLEF main tasks.

title: Recognizing Textual Relatedness with Predicate-Argument Structures
abstract: In this paper, we first compare several strategies to handle the newly proposed three-way Recognizing Textual Entailment (RTE) task. Then we define a new measurement for a pair of texts, called Textual Relatedness, which is a weaker concept than semantic similarity or paraphrase. We show that an alignment model based on the predicate-argument structures using this measurement can help an RTE system to recognize the Unknown cases at the first stage, and contribute to the improvement of the overall performance in the RTE task. In addition, several heterogeneous lexical resources are tested, and different contributions from them are observed.

title: Inference Rules and their Application to Recognizing Textual Entailment
abstract: In this paper, we explore ways of improving an inference rule collection and its application to the task of recognizing textual entailment. For this purpose, we start with an automatically acquired collection and we propose methods to refine it and obtain more rules using a hand-crafted lexical resource. Following this, we derive a dependency-based structure representation from texts, which aims to provide a proper base for the inference rule application. The evaluation of our approach on the recognizing textual entailment data shows promising results on precision and the error analysis suggests possible improvements.

title: SketchML a representation language for novel sketch recognition approach
abstract: Multimodal interfaces can be profitably used to support increasingly complex services in assistive environments. In particular, sketch-based interfaces offer users an effortless and powerful communication way to represent concepts and commands on different devices. Unlike other modalities, sketch-based interaction can be easily fitted according to heterogeneous services. Moreover it can be quickly personalized according to the user needs.
 Developing a sketch-based interface for a specific service is a time-consuming operation that requires the re-engineering and/or the re-designing of the whole recognizer framework. This paper describes a definitive framework by which the user, simply by using freehand drawing, can define every kind of sketch-based interface. The definition of the interface and its recognition process are performed by using our developed Sketch Modeling Language (SketchML).

title: Ontology-based Query Construction for GeoCLEF
abstract: This paper describes experiments with geographical information retrieval (GIR). Being different from the traditional information IR, we focus more on the query expansion instead of document ranking. We parse each topic into the event part and the geographic part and use different ontologies to expand both parts respectively. The results show promising results of our strategy for this task.

title: Recognizing Textual Entailment Using a Subsequence Kernel Method
abstract: We present a novel approach to recognizing Textual Entailment. Structural features are constructed from abstract tree descriptions, which are automatically extracted from syntactic dependency trees. These features are then applied in a subsequence-kernel-based classifier to learn whether an entailment relation holds between two texts. Our method makes use of machine learning techniques using a limited data set, no external knowledge bases (e.g. WordNet), and no handcrafted inference rules. We achieve an accuracy of 74.5% for text pairs in the Information Extraction and Question Answering task, 63.6% for the RTE-2 test data, and 66.9% for the RET-3 test data.

title: Computation on Programmable Graphics Hardware
abstract: GPUs have evolved into powerful and flexible streaming processors with fully programmable floating-point pipelines and tremendous aggregate computational power and memory bandwidth. With these advances, modern GPUs can now perform more functions than the specific graphics computations for which they were designed. This article describes approaches to using GPU processing power to accelerate traditionally CPU-based tasks. We discuss some important characteristics of algorithms that make them good candidates for GPU acceleration. We discuss a specific GPU image-processing application that is a common postprocess for many physically based rendering systems.

title: Joint cross-layer scheduling and spectrum sensing for OFDMA cognitive radio systems
abstract: In most of the existing works on cognitive radio (CR) systems, the spectrum sensing and the cross-layer scheduling are designed separately. Specifically, the sensing module first determines whether or not a channel resource is available for the CR system based on the sensing information. The scheduling module then schedules the data transmission of different users on the available channels based on the hard-decision sensing information (HSI). In this paper, we shall propose a joint crosslayer and sensing design and study its performance advantages over the aforementioned traditional decoupled approaches. We shall consider the downlink transmission of an OFDMA-based secondary system sharing the spectrum with primary users using cognitive radio technology. We shall rely on the joint design framework to optimize a system utility, which adapts the power allocation and the subcarrier assignment across the secondary users (under a average interference constraint to the primary users) based on both the channel state information (CSI) and the raw sensing information (RSI). In addition, we shall also propose a distributed implementation for the cross-layer sensing and scheduling design using primal-dual decomposition approach. Simulation results reveals the substantial performance gain of the proposed joint design over the conventional CR systems.

title: Outdoor Face Recognition Using Enhanced Near Infrared Imaging
abstract: In this paper, we present a robust and accurate system for outdoor (as well as indoor) face recognition, based on a recently developed enhanced near-infrared (ENIR) imaging device. Using a narrow band NIR laser generator instead of LED lights for active frontal illumination, the ENIR device can provide face images of good quality even under sunlight. Experiments show that the ENIR system performs similarly to the existing NIR system when used indoors, but outperforms it significantly outdoors especially under sunlight.

title: A Market-Based Adaptation for Resolving Competing Needs for Scarce Resources
abstract: The dynamic nature of many real-world domains (e.g., military, emergency first response and hurricane relief, etc) requires adaptive resource allocation to respond to changes in the environment that trigger additional resource requirements. Since the total resources are limited, there are often conflicts among various tasks regarding their resource needs. Thus, resources must be reallocated in order to maximize global utility for the current situation. This problem is further complicated when scarce resources are owned by distributed teams, each of which needs to allocate resources among tasks assigned to them, because each team has limited information about the other teams' resources and states. In this paper, we propose a market-based approach that uses an agent-based auction mechanism to enable teams to communicate and coordinate their utility information about possibly competing resource needs. As a result, the teams can collaboratively assess trade-offs among competing needs to allocate resources efficiently.

title: Mixed Reality-Mediated Collaborative Design System: Concept, Prototype, and Experimentation
abstract: This paper introduces a Mixed Reality-mediated Collaborative design system, named MR-Collab, which combines Mixed Reality (MR), Augmented Reality (AR) and various channels of communication technologies. The concept and system of MR-Collabare developed based on the Benford's Mixed-Reality boundaries theory. This paper presents how this theory is used as a tool to analyze the system framework and guide the design of the MR-Collabsystem. The technique details of prototype and application scenario of this system are also elaborated in the paper. The system, MR-Collab, is designed in the purpose of facilitating collaboration between distributed users through the Mixed Reality environment. Experimentation that can measure the correlations between the design performance/behaviors with the increased degree of co-presence is also planned in this paper.