Recognizing Textual Relatedness with Predicate-Argument Structures
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: 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: 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: Immortal DB: transaction time support for SQL server
abstract: Immortal DB builds transaction time database support into the SQL Server engine, not in middleware. Transaction time databases retain and provide access to prior states of a database. An update "inserts" a new record while preserving the old version. The system supports as of queries returning records current at the specified time. It also supports snapshot isolation concurrency control. Versions are stamped with the times of their updating transactions. The timestamp order agrees with transaction serialization order. Lazy timestamping propagates timestamps to all updates of a transaction after commit. All versions are kept in an integrated storage structure, with historical versions initially stored with current data. Time-splits of pages permit large histories to be maintained, and enable time based indexing. We demonstrate Immortal DB with a moving objects application that tracks cars in the Seattle area.

title: An efficient GPU-based approach for interactive global illumination
abstract: This paper presents a GPU-based method for interactive global illumination that integrates complex effects such as multi-bounce indirect lighting, glossy reflections, caustics, and arbitrary specular paths. Our method builds upon scattered data sampling and interpolation on the GPU. We start with raytraced shading points and partition them into coherent shading clusters using adaptive seeding followed by k-means. At each cluster center we apply final gather to evaluate its incident irradiance using GPU-based photon mapping. We approximate the entire photon tree as a compact illumination cut, thus reducing the final gather cost for each ray. The sampled irradiance values are then interpolated at all shading points to produce rendering. Our method exploits the spatial coherence of illumination to reduce sampling cost. We sample sparsely and the distribution of sample points conforms with the underlying illumination changes. Therefore our method is both fast and preserves high rendering quality. Although the same property has been exploited by previous caching and adaptive sampling methods, these methods typically require sequential computation of sample points, making them ill-suited for the GPU. In contrast, we select sample points adaptively in a single pass, enabling parallel computation. As a result, our algorithm runs entirely on the GPU, achieving interactive rates for scenes with complex illumination effects.

title: An Analysis-by-Synthesis Method for Heterogeneous Face Biometrics
abstract: Face images captured in different spectral bands, e.g. , in visual (VIS) and near infrared (NIR), are said to be heterogeneous. Although a person's face looks different in heterogeneous images, it should be classified as being from the same individual. In this paper, we present a new method, called face analogy , in the analysis-by-synthesis framework, for heterogeneous face mapping, that is, transforming face images from one type to another, and thereby performing heterogeneous face matching. Experiments show promising results.

title: Decentralized Fair Resource Allocation for Relay-Assisted Cognitive Cellular Downlink Systems
abstract: In this paper, we consider a relay-assisted cognitive cellular downlink system dynamically accessing a spectrum licensed to a primary network, thereby improving the efficiency of spectrum usage. A cluster-based relay-assisted architecture is proposed, where relay stations are employed for minimizing the interference to users in the primary network and achieving fairness for cell-edge users. Based on this architecture, an optimal solution is derived for jointly controlling data rate, transmission power, and subband allocation to optimize the weighted sum goodput where proportional fair scheduling (PFS) is included as a special case. As shown by simulations, the proposed solution achieves significant throughput gains and better user fairness compared with existing designs.