Link discovery for Chinese/English cross-language web information retrieval

Nowadays people heavily rely on the Internet for information and knowledge. Wikipedia is an online multilingual encyclopaedia that contains a very large number of detailed articles covering most written languages. It is often considered to be a treasury of human knowledge. It includes extensive hypertext links between documents of the same language for easy navigation. However, the pages in different languages are rarely cross-linked except for direct equivalent pages on the same subject in different languages. This could pose serious difficulties to users seeking information or knowledge from different lingual sources, or where there is no equivalent page in one language or another. In this thesis, a new information retrieval task—cross-lingual link discovery (CLLD) is proposed to tackle the problem of the lack of cross-lingual anchored links in a knowledge base such as Wikipedia. In contrast to traditional information retrieval tasks, cross language link discovery algorithms actively recommend a set of meaningful anchors in a source document and establish links to documents in an alternative language. In other words, cross-lingual link discovery is a way of automatically finding hypertext links between documents in different languages, which is particularly helpful for knowledge discovery in different language domains. This study is specifically focused on Chinese / English link discovery (C/ELD). Chinese / English link discovery is a special case of cross-lingual link discovery task. It involves tasks including natural language processing (NLP), cross-lingual information retrieval (CLIR) and cross-lingual link discovery. To justify the effectiveness of CLLD, a standard evaluation framework is also proposed. The evaluation framework includes topics, document collections, a gold standard dataset, evaluation metrics, and toolkits for run pooling, link assessment and system evaluation. With the evaluation framework, performance of CLLD approaches and systems can be quantified. This thesis contributes to the research on natural language processing and cross-lingual information retrieval in CLLD: 1) a new simple, but effective Chinese segmentation method, n-gram mutual information, is presented for determining the boundaries of Chinese text; 2) a voting mechanism of name entity translation is demonstrated for achieving a high precision of English / Chinese machine translation; 3) a link mining approach that mines the existing link structure for anchor probabilities achieves encouraging results in suggesting cross-lingual Chinese / English links in Wikipedia. This approach was examined in the experiments for better, automatic generation of cross-lingual links that were carried out as part of the study. The overall major contribution of this thesis is the provision of a standard evaluation framework for cross-lingual link discovery research. It is important in CLLD evaluation to have this framework which helps in benchmarking the performance of various CLLD systems and in identifying good CLLD realisation approaches. The evaluation methods and the evaluation framework described in this thesis have been utilised to quantify the system performance in the NTCIR-9 Crosslink task which is the first information retrieval track of this kind.

Integrated configuration of enterprise systems for interoperability : towards process model and business document specification alignment

Enterprise Systems (ES) can be understood as the de facto standard for holistic operational and managerial support within an organization. Most commonly ES are offered as commercial off-the-shelf packages, requiring customization in the user organization. This process is a complex and resource-intensive task, which often prevents small and midsize enterprises (SME) from undertaking configuration projects. Especially in the SME market independent software vendors provide pre-configured ES for a small customer base. The problem of ES configuration is shifted from the customer to the vendor, but remains critical. We argue that the yet unexplored link between process configuration and business document configuration must be closer examined as both types of configuration are closely tied to one another.

An evaluation framework for cross-lingual link discovery

Cross-Lingual Link Discovery (CLLD) is a new problem in Information Retrieval. The aim is to automatically identify meaningful and relevant hypertext links between documents in different languages. This is particularly helpful in knowledge discovery if a multi-lingual knowledge base is sparse in one language or another, or the topical coverage in each language is different; such is the case with Wikipedia. Techniques for identifying new and topically relevant cross-lingual links are a current topic of interest at NTCIR where the CrossLink task has been running since the 2011 NTCIR-9. This paper presents the evaluation framework for benchmarking algorithms for cross-lingual link discovery evaluated in the context of NTCIR-9. This framework includes topics, document collections, assessments, metrics, and a toolkit for pooling, assessment, and evaluation. The assessments are further divided into two separate sets: manual assessments performed by human assessors; and automatic assessments based on links extracted from Wikipedia itself. Using this framework we show that manual assessment is more robust than automatic assessment in the context of cross-lingual link discovery.

Overview of the NTCIR-10 cross-lingual link discovery task

This paper presents an overview of NTCIR-10 Cross-lingual Link Discovery (CrossLink-2) task. For the task, we continued using the evaluation framework developed for the NTCIR-9 CrossLink-1 task. Overall, recommended links were evaluated at two levels (file-to-file and anchor-to-file); and system performance was evaluated with metrics: LMAP, R-Prec and P@N.

NTCIR-10 crosslink-2 task : a link mining strategy

At NTCIR-10 we participated in the cross-lingual link discovery (CrossLink-2) task. In this paper we describe our systems for discovering cross-lingual links between the Chinese, Japanese, and Korean (CJK) Wikipedia and the English Wikipedia. The evaluation results show that our implementation of the cross-lingual linking method achieved promising results.

Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Purpose: Flat-detector, cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. Methods: The rich sources of prior information in IGRT are incorporated into a hidden Markov random field (MRF) model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk (OAR). The voxel labels are estimated using the iterated conditional modes (ICM) algorithm. Results: The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom (CIRS, Inc. model 062). The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. Conclusions: By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. The rich sources of prior information in IGRT are incorporated into a hidden Markov random field model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk. The voxel labels are estimated using iterated conditional modes. The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom. The mean voxel-wise misclassification rate was 6.2\%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

Vision-based estimation of airborne target pseudobearing rate using hidden Markov model filters

The problem of estimating pseudobearing rate information of an airborne target based on measurements from a vision sensor is considered. Novel image speed and heading angle estimators are presented that exploit image morphology, hidden Markov model (HMM) filtering, and relative entropy rate (RER) concepts to allow pseudobearing rate information to be determined before (or whilst) the target track is being estimated from vision information.

Parallel ABM for electricity distribution grids : a case study

This paper introduces a parallel implementation of an agent-based model applied to electricity distribution grids. A fine-grained shared memory parallel implementation is presented, detailing the way the agents are grouped and executed on a multi-threaded machine, as well as the way the model is built (in a composable manner) which is an aid to the parallelisation. Current results show a medium level speedup of 2.6, but improvements are expected by incor-porating newer distributed or parallel ABM schedulers into this implementa-tion. While domain-specific, this parallel algorithm can be applied to similarly structured ABMs (directed acyclic graphs).

Microstructure of an artificial grain boundary weak link in an YBa2Cu3O(7-δ) thin film grown on a (100)(110), [001]-tilt Y-ZrO2 bicrystal

The microstructure of an artificial grain boundary in an YBa2Cu3O7-δ (YBCO) thin film grown on a (100)(110), [001]-tilt yttria-stabilized-zirconia (YSZ) bicrystal substrate has been studied using transmission electron microscopy (TEM). The orientation relationship between the YBCO film and the YSZ substrate was [001]YBCO∥[001]YSZ and [110]YBCO∥[100]YSZ for each half of the bicrystal film. However, the exact boundary geometry of the bicrystal substrate was not transferred to the film. The substrate boundary was straight while the film boundary was wavy. In several cases there was bending of the lattice confined within a distance of a few basal-plane lattice spacings from the boundary plane and microfaceting. No intergranular secondary phase was observed but about 25% of the boundary was covered by c-axis-tilted YBCO grains and a-axis-oriented grains, both of which were typically adjacent to CuO grains or surrounded by a thin Cu-rich amorphous layer.

Exercise-induced phosphorylation of the novel Akt substrates AS160 and filamin A in human skeletal muscle

Skeletal muscle contraction stimulates multiple signaling cascades that govern a variety of metabolic and transcriptional events. Akt/protein kinase B regulates metabolism and growth/muscle hypertrophy, but contraction effects on this target and its substrates are varied and may depend on the mode of the contractile stimulus. Accordingly, we determined the effects of endurance or resistance exercise on phosphorylation of Akt and downstream substrates in six trained cyclists who performed a single bout of endurance or resistance exercise separated by ?7 days. Muscle biopsies were taken from the vastus lateralis at rest and immediately after exercise. Akt Ser 473 phosphorylation was increased (1.8-fold; P = 0.011) after endurance but was unchanged after resistance exercise. Conversely, Akt Thr 308 phosphorylation was unaltered after either bout of exercise. Several exercise-responsive phosphoproteins were detected by immunoblot analysis with a phospho-Akt substrate antibody. pp160 and pp300 were identified as AS160 and filamin A, respectively, with increased phosphorylation (2.0- and 4.9-fold, respectively; P < 0.05) after endurance but not resistance exercise. In conclusion, AS160 and filamin A may provide an important link to mediate endurance exercise-induced bioeffects in skeletal muscle.

Aqueous phase synthesis of copper nanoparticles : a link between heavy metal resistance and nanoparticle synthesis ability in bacterial systems

We demonstrate aqueous phase biosynthesis of phase-pure metallic copper nanoparticles (CuNPs) using a silver resistant bacterium Morganella morganii. This is particularly important considering that there has been no report that demonstrates biosynthesis and stabilization of pure copper nanoparticles in the aqueous phase. Electrochemical analysis of bacterial cells exposed to Cu2+ ions provides new insights into the mechanistic aspect of Cu2+ ion reduction within the bacterial cell and indicates a strong link between the silver and copper resistance machinery of bacteria in the context of metal ion reduction. The outcomes of this study take us a step closer towards designing rational strategies for biosynthesis of different metal nanoparticles using microorganisms.

Galectin-1 : a link between tumor hypoxia and tumor immune privilege

Purpose: To identify a 15-KDa novel hypoxia-induced secreted protein in head and neck squamous cell carcinomas (HNSCC) and to determine its role in malignant progression. Methods: We used surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and tandem MS to identify a novel hypoxia-induced secreted protein in FaDu cells. We used immunoblots, real-time polymerase chain reaction (PCR), and enzyme-linked immunoabsorbent assay to confirm the hypoxic induction of this secreted protein as galectin-1 in cell lines and xenografts. We stained tumor tissues from 101 HNSCC patients for galectin-1, CA IX (carbonic anhydrase IX, a hypoxia marker) and CDS (a T-cell marker). Expression of these markers was correlated to each other and to treatment outcomes. Results: SELDI-TOF studies yielded a hypoxia-induced peak at 15 kDa that proved to be galectin-1 by MS analysis. Immunoblots and PCR studies confirmed increased galectin-1 expression by hypoxia in several cancer cell lines. Plasma levels of galectin-1 were higher in tumor-bearing severe combined immunodeficiency (SCID) mice breathing 10% O 2 compared with mice breathing room air. In HNSCC patients, there was a significant correlation between galectin-1 and CA IX staining (P = .01) and a strong inverse correlation between galectin-1 and CDS staining (P = .01). Expression of galectin-1 and CDS were significant predictors for overall survival on multivariate analysis. Conclusion: Galectin-1 is a novel hypoxia-regulated protein and a prognostic marker in HNSCC. This study presents a new mechanism on how hypoxia can affect the malignant progression and therapeutic response of solid tumors by regulating the secretion of proteins that modulate immune privilege. © 2005 by American Society of Clinical Oncology.

Design and flight testing of an integrated solar powered UAV and WSN for remote gas sensing

This paper describes a generic and integrated solar powered remote Unmanned Air Vehicles (UAV) and Wireless Sensor Network (WSN) gas sensing system. The system uses a generic gas sensing system for CH4 and CO2 concentrations using metal oxide (MoX) and non-dispersive infrared sensors, and a new solar cell encapsulation method to power the UASs as well as a data management platform to store, analyse and share the information with operators and external users. The system was successfully field tested at ground and low altitudes, collecting, storing and transmitting data in real time to a central node for analysis and 3D mapping. The system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, opening the way to a ubiquitous low cost environmental monitoring. A video of the bench and flight test performed can be seen in the following link https://www.youtube.com/watch?v=Bwas7stYIxQ.

Odometry-driven inference to link multiple exemplars of a location

A major challenge for robot localization and mapping systems is maintaining reliable operation in a changing environment. Vision-based systems in particular are susceptible to changes in illumination and weather, and the same location at another time of day may appear radically different to a system using a feature-based visual localization system. One approach for mapping changing environments is to create and maintain maps that contain multiple representations of each physical location in a topological framework or manifold. However, this requires the system to be able to correctly link two or more appearance representations to the same spatial location, even though the representations may appear quite dissimilar. This paper proposes a method of linking visual representations from the same location without requiring a visual match, thereby allowing vision-based localization systems to create multiple appearance representations of physical locations. The most likely position on the robot path is determined using particle filter methods based on dead reckoning data and recent visual loop closures. In order to avoid erroneous loop closures, the odometry-based inferences are only accepted when the inferred path's end point is confirmed as correct by the visual matching system. Algorithm performance is demonstrated using an indoor robot dataset and a large outdoor camera dataset.