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88 results on '"Guan, Jihong"'

1. Optimization and Design of LCC Resonant High-Voltage Wide Range Power Supply for Magnetrons

Author

Hou, Renjie, Liu, Yang, He, Zhixing, Li, Zongjian, Xiao, Muxuan, Guan, Jihong, Chen, Yandong, Wang, Jing, Xiao, Ziheng, and Wang, Hongliang

Abstract

Due to the integration and utilization of the parasitic capacitance of the transformer, the LCC resonant converters with a capacitive output filter are widely used in high-voltage power supplies for microwave generation, X-ray, ion implantation, and other fields. However, it is challenging for the LCC to maintain high efficiency in a wide output voltage range. In this article, an optimal control coordinate trajectories (OCCTs)-based phase-shift pulse-frequency modulation (PS-PFM) control method is proposed to achieve high efficiency by reducing the switching frequency range and the turn-off current. With the normalized time-domain analysis, the operation stage trajectories of LCC and their boundary conditions under the PS-PFM control are derived. Based on this, the OCCTs of the switching frequency and the duty cycle at different voltage gains are precisely calculated. By associating the duty cycle with the switching frequency and the output voltage gain through a fit equation based on the OCCTs data, the proposed PS-PFM control strategy can adaptively adjust the optimal duty cycle, simplifying one of the control freedom degrees. Then, an optimization design algorithm for the resonant network parameter is proposed to reduce the conduction loss of LCC. Finally, a 10–20-kV/15-kW LCC resonant high-voltage power supply prototype is built to verify the feasibility of the proposed control strategy.

Published
2024
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2. Self-Supervised Spatiotemporal Imputation Model for Highly Sparse Chl-a Data via Fusing Multisource Satellite Data

Author

Wang, Shuyu, Li, Wengen, Guan, Jihong, Liu, Xiwei, Zhang, Yichao, and Zhou, Shuigeng

Abstract

Monitoring Chlorophyll-a (Chl-a) concentration in ocean is of considerable significance for early warning of algae disasters, marine ecological environment protection, etc. However, due to various uncontrollable factors such as cloud cover and thick aerosols, the missing rate of observed Chl-a data is quite high, which seriously hinders its applications. The existing data imputation methods are mostly applicable to Chl-a data with a low missing rate, and perform much worse when the missing rate reaches 0.7 or above. To address this issue, we proposed a self-supervised spatiotemporal imputation (S2-STI) model for highly sparse Chl-a data imputation by fusing multisource satellite data. First, to obtain comprehensive information about the missed Chl-a data, we designed a multisource sparse data fusion (MSDF) module to fuse multisource satellite data, including Chl-a data, sea surface temperature (SST) data, and photosynthetically available radiation data. MSDF constructs a spatialtemporal graph network to learn high-quality spatiotemporal representations of SST and photosynthetically active radiation (PAR) data, and fuses the learned representations with Chl-a data to enrich the information for imputation. Then, we developed a generation-based data imputation (GDI) module to model the distribution of Chl-a data based on the outputs of MSDF. Considering the high data sparsity, we designed a self-supervised training strategy to train S2-STI in the absence of ground truth. Finally, we leverage the data generated by the GDI module in the trained S2-STI model to fill in missing values in the sparse Chl-a data. Experiments on real datasets show that S2-STI achieves much better performance than the existing data imputation methods. Specifically, for the Chl-a data with a missing rate of 0.9, S2-STI improves by at least 12% in terms of masked autoencoder (MAE) error when compared with the strong baseline methods.

Published
2024
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3. HPC-Atlas: Computationally Constructing a Comprehensive Atlas of Human Protein Complexes

Author

Pan, Yuliang, Li, Ruiyi, Li, Wengen, Lv, Liuzhenghao, Guan, Jihong, and Zhou, Shuigeng

Abstract

A fundamental principle of biology is that proteins tend to form complexes to play important roles in the core functions of cells. For a complete understanding of human cellular functions, it is crucial to have a comprehensive atlas of human protein complexes. Unfortunately, we still lack such a comprehensive atlas of experimentally validated protein complexes, which prevents us from gaining a complete understanding of the compositions and functions of human protein complexes, as well as the underlying biological mechanisms. To fill this gap, we built Human Protein Complexes Atlas (HPC-Atlas), as far as we know, the most accurate and comprehensive atlas of human protein complexes available to date. We integrated two latest protein interaction networks, and developed a novel computational method to identify nearly 9000 protein complexes, including many previously uncharacterized complexes. Compared with the existing methods, our method achieved outstanding performance on both testing and independent datasets. Furthermore, with HPC-Atlas we identified 751 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-affected human protein complexes, and 456 multifunctional proteinsthat contain many potential moonlighting proteins. These results suggest that HPC-Atlas can serve as not only a computing framework to effectively identify biologically meaningful protein complexes by integrating multiple protein data sources, but also a valuable resource for exploring new biological findings. The HPC-Atlas webserver is freely available at http://www.yulpan.top/HPC-Atlas.

Published
2023
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4. CDFM: A cross‐domain few‐shot model for marine plankton classification

Author

Guo, Jin, Li, Wengen, Guan, Jihong, Gao, Hang, Liu, Baobo, and Gong, Lili

Abstract

Marine plankton classification is important for monitoring marine biological populations and understanding marine ecosystems. However, it is difficult to obtain abundant annotated image data of marine plankton to train classification models of high quality. To classify marine plankton with a small number of image samples, a cross‐domain few‐shot learning model (CDFM) is proposed. First, CDFM learns knowledge from existing labelled images and then transfers the knowledge to new images. In this process, there is an issue of domain differences between the new images and the existing datasets due to differences in data acquisition time and locations. To address this issue, the authors pre‐train a model in the source domain and then use fine‐tuning to adapt it to the target domain. Second, the graph neural network is used as a meta‐learning module to learn a feature distance metric for marine plankton classification with limited samples. Extensive experiments on four marine plankton image datasets are conducted, including Kaggle Plankton, miniPPlankton, ZooScan and WHOI, and CDFM outperforms existing methods for marine plankton classification.

Published
2023
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5. Learning Meta-Stable State Transition Representation of Brain Function for ADHD Identification

Author

Pei, Shengbing, He, Fan, Cao, Shuai, Liang, Wen, Guan, Jihong, and Lv, Zhao

Abstract

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children with complex onset symptoms, and brain function analysis is a helpful way to assist in diagnosis. Functional magnetic resonance imaging (fMRI) studies have revealed that the brain function activity pattern in the resting state is also dynamically changing, that is, there is a meta-stable state transition within the period of acquisition time, which is related to neurological diseases. However, existing studies neglect to mine such state transition pattern information for better disease identification. Here, we propose an end-to-end method that learns meta-stable state transition representation for ADHD identification. First, the fMRI data acquired during the entire period are divided into overlapping segments based on the sliding window operation, and each segment is used to capture the meta-stable state of brain function. Then, for each meta-stable state, a 2-D convolutional neural network (CNN) is adopted to extract functional connectivity (FC) information from FC network (FCN) constructed by fMRI volumes, while a 3-D CNN is used to extract spatial information from fMRI volumes and a bidirectional long short-term memory (Bi-LSTM) is used to extract temporal information from the volume sequence, and the FC feature and spatiotemporal feature are fused to represent the meta-stable state. Finally, a Bi-LSTM with attention mechanism is conducted to learn the state transition pattern from the representations of the meta-stable states, and the state transition feature is used for classification. The results on the ADHD-200 dataset indicate that: 1) the meta-stable transition pattern is indeed useful and can improve identification performance; 2) fusing the static FC feature and dynamic volume sequence feature of brain function can better characterize meta-stable states; and 3) the combination of window size = 50 and step size = 40 is an ideal choice in the sliding window operation, which can obtain the best performance.

Published
2023
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6. Causal Gene Identification Using Non-Linear Regression-Based Independence Tests

Author

Zhang, Hao, Yan, Chuanxu, Xia, Yewei, Guan, Jihong, and Zhou, Shuigeng

Abstract

With the development of biomedical techniques in the past decades, causal gene identification has become one of the most promising applications in human genome-based business, which can help doctors to evaluate the risk of certain genetic diseases and provide further treatment recommendations for potential patients. When no controlled experiments can be applied, machine learning techniques like causal inference-based methods are generally used to identify causal genes. Unfortunately, most of the existing methods detect disease-related genes by ranking-based strategies or feature selection techniques, which generally return a superset of the corresponding real causal genes. There are also some causal inference-based methods that can identify a part of real causal genes from those supersets, but they are just able to return a few causal genes. This is contrary to our knowledge, as many results from controlled experiments have demonstrated that a certain disease, especially cancer, is usually related to dozens or hundreds of genes. In this work, we present an effective approach for identifying causal genes from gene expression data by using a new search strategy based on non-linear regression-based independence tests, which is able to greatly reduce the search space, and simultaneously establish the causal relationships from the candidate genes to the disease variable. Extensive experiments on real-world cancer datasets show that our method is superior to the existing causal inference-based methods in three aspects: 1) our method can identify dozens of causal genes, and $1/3 \sim 1/2$1/3∼1/2 of the discovered causal genes can be verified by existing works that they are really directly related to the corresponding disease; 2) The discovered causal genes are able to distinguish the status or disease subtype of the target patient; 3) Most of the discovered causal genes are closely relevant to the disease variable.

Published
2023
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7. Effectively Clustering Single Cell RNA Sequencing Data by Sparse Representation

Author

Li, Rui-Yi, Wang, Zhiye, Guan, Jihong, and Zhou, Shuigeng

Abstract

Clustering analysis has been widely used in analyzing single-cell RNA-sequencing (scRNA-seq) data to study various biological problems at cellular level. Although a number of scRNA-seq data clustering methods have been developed, most of them evaluate the similarity of pairwise cells while ignoring the global relationships among cells, which sometimes cannot effectively capture the latent structure of cells. In this paper, we propose a new clustering method SPARC for scRNA-seq data. The most important feature of SPARC is a novel similarity metric that uses the sparse representation coefficients of each cell in terms of the other cells to measure the relationships among cells. In addition, we develop an outlier detection method to help parameter selection in SPARC. We compare SPARC with nine existing scRNA-seq data clustering methods on twelve real datasets. Experimental results show that SPARC achieves the state of the art performance. By further analyzing the cell similarity data derived from sparse representations, we find that SPARC is much more effective in mining high quality clusters of scRNA-seq data than two traditional similarity metrics. In conclusion, this study provides a new way to effectively cluster scRNA-seq data and achieves more accurate clustering results than the state of art methods.

Published
2022
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8. The Complexities of Random-Turn Hex, Square, and Triangle Games

Author

Yang, Yi, Zhou, Shuigeng, Guan, Jihong, and Shen, Chuansheng

Abstract

In random-turn games, players toss a coin to decide who moves. This article studies the complexities of the algorithms for playing random-turn connection games perfectly on regular tessellations. Our study theoretically shows that there are algorithms playing random-turn hex, square, and triangle perfectly in $O(n^9\cdot 2.618^n)$, $O(n^9\cdot 2.746^n)$, and $O(n^9\cdot 3.645^n)$ time for each move, respectively, where $n$ is the board size. We then implement the perfect-playing algorithm for the random-turn square and measure the actual running time it costs for each move. We then compute and analyze the game lengths on random-turn square, hex, and triangle and conjecture that the asymptotic complexity of their game lengths are the same. We finally compare the perfect-playing algorithm with the sampling algorithm by competing against each other, and the numbers of their wins and losses are reported.

Published
2022
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9. GITAR: An Open Source Tool for Analysis and Visualization of Hi-C Data

Author

Calandrelli, Riccardo, Wu, Qiuyang, Guan, Jihong, and Zhong, Sheng

Abstract

Interactions between chromatin segments play a large role in functional genomic assays and developments in genomic interaction detection methods have shown interacting topological domains within the genome. Among these methods, Hi-C plays a key role. Here, we present the Genome Interaction Tools and Resources (GITAR), a software to perform a comprehensive Hi-C data analysis, including data preprocessing, normalization, and visualization, as well as analysis of topologically-associated domains(TADs). GITAR is composed of two main modules: (1) HiCtool, a Python library to process and visualize Hi-C data, including TAD analysis; and (2) processed data library, a large collection of human and mouse datasets processed using HiCtool. HiCtool leads the user step-by-step through a pipeline, which goes from the raw Hi-C data to the computation, visualization, and optimized storage of intra-chromosomal contact matrices and TAD coordinates. A large collection of standardized processed data allows the users to compare different datasets in a consistent way, while saving time to obtain data for visualization or additional analyses. More importantly, GITAR enables users without any programming or bioinformatic expertise to work with Hi-C data. GITAR is publicly available at http://genomegitar.orgas an open-source software.

Published
2024
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10. Classifying Cognitive Normal and Early Mild Cognitive Impairment of Alzheimer’s Disease by Applying Restricted Boltzmann Machine to fMRI Data

Author

Pei, Shengbing and Guan, Jihong

Abstract

Background: Neuroimaging is an important tool in early detection of Alzheimer’s disease (AD), which is a serious neurodegenerative brain disease among the elderly subjects. Independent component analysis (ICA) is arguably one of the most widely used algorithm for the analysis of brain imaging data, which can be used to extract intrinsic networks of brain from functional magnetic resonance imaging (fMRI). Methods: Witnessed by recent studies, a more flexible model known as restricted Boltzmann machine (RBM) can also be used to extract spatial maps and time courses of intrinsic networks from resting state fMRI, moreover, RBM shows superior temporal features than ICA. Here, we seek to employ RBM to improve the performance of classifying individuals. Experiments are performed on healthy controls and subjects at the early stage of AD, i.e., cognitive normal (CN) and early mild cognitive impairment participants (EMCI), and two types of data, i.e., structural magnetic resonance imaging (sMRI) and fMRI data. Results: (1) By separately employing ICA for sMRI and fMRI, the features extracted from fMRI improve classification accuracy by 7.5% for CN and EMCI; (2) instead of applying ICA to fMRI, using RBM further improves classification accuracy by 7.75% for CN and EMCI; (3) the lesions at the early stage of AD are more likely to occur in the regions around slices 4, 6, 10, 14, 19, 51 and 59 of the whole brain in the longitudinal direction. Conclusion: By using fMRI instead of sMRI and RBM instead of ICA, we can classify CN and EMCI more efficiently.

Published
2021
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12. RMDB: An Integrated Database of Single-cytosine-resolution DNA Methylation in Oryza Sativa

Author

Zhu, Tiansheng, Guan, Jihong, Liu, Hui, and Zhou, Shuigeng

Abstract

Background: Previous studies have revealed that DNA methylation plays a crucial role in eukaryotic growth and development via involvement in the regulation of gene expression and chromosomal instability. With the advancement of biotechnology, next-generation sequencing (NGS) is emerging as a popular method to explore the functions of DNA methylation, and an increasing number of genome-scale DNA methylation datasets have been published. Several DNA methylation databases, including MethDB, NGSmethDB and MENT have been developed for storing and analyzing the DNA methylation data. However, no public resource dedicated to DNA methylation of Oryza sativa is available to date. Methods & Results: We built a comprehensive database (RMDB) for integration and analysis of DNA methylation data of Oryza sativa. A couple of functional modules were developed to identify the connections between DNA methylation and phenotypes. Moreover, rich graphical visualization tools were employed to facilitate data presentation and interpretation. Conclusion: RMDB is an integrated database dedicated to rice DNA methylation. To the best of our knowledge, this is the first integrated rice DNA methylation database. We believe that RMDB will be helpful to understand the epigenetic mechanisms of Oryza sativa. RMDB is freely available at http://admis.fudan.edu.cn/rmdb.

Published
2019
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13. Predicting Enhancers from Multiple Cell Lines and Tissues across Different Developmental Stages Based On SVM Method

Author

Bu, Hongda, Hao, Jiaqi, Guan, Jihong, and Zhou, Shuigeng

Abstract

Background: Enhancers are short DNA regions that improve transcription efficiency by recruiting transcription factors. Identifying enhancer regions is important to understand the process of gene expression. As enhancers are independent of their distances and orientations to the target genes, it is difficult to locate enhancers accurately. Recently, with the development of highthroughput ChIP-seq (Chromatin Immunoprecipitation sequencing) technologies, several computational methods were developed to predict enhancers. However, most of these methods rely on p300 binding sites and/or DNase I hypersensitive sites (DHSs) for selecting positive training samples, which is imprecise and subsequently leads to unsatisfactory prediction performance. Besides, in the literature, there is no work that predicts enhancers from tissues across different developmental stages. Methods: In this paper, we proposed a method based on support vector machines (SVMs) to investigate enhancer prediction on cell lines and tissues from EnhancerAtlas. Specifically, we focused on predicting enhancers on different developmental stages of heart and lung tissues. Results and Conclusion: Our results show that 1) the proposed method achieves good performance on most cell lines and tissues, especially it outperforms several state of the art methods on heart and lung. 2) It is easier to predict enhancers from tissues of adult stage than from tissues of fetal stage, which is proven on both heart and lung tissues.

Published
2018
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14. GITAR: An Open Source Tool for Analysis and Visualization of Hi-C Data

Author

Calandrelli, Riccardo, Wu, Qiuyang, Guan, Jihong, and Zhong, Sheng

Abstract

Interactions between chromatin segments play a large role in functional genomic assays and developments in genomic interaction detection methods have shown interacting topological domains within the genome. Among these methods, Hi-C plays a key role. Here, we present the Genome Interaction Tools and Resources (GITAR), a software to perform a comprehensive Hi-C data analysis, including data preprocessing, normalization, and visualization, as well as analysis of topologically-associated domains(TADs). GITAR is composed of two main modules: (1) HiCtool, a Python library to process and visualize Hi-C data, including TAD analysis; and (2) processed data library, a large collection of human and mouse datasets processed using HiCtool. HiCtool leads the user step-by-step through a pipeline, which goes from the raw Hi-C data to the computation, visualization, and optimized storage of intra-chromosomal contact matrices and TAD coordinates. A large collection of standardized processed data allows the users to compare different datasets in a consistent way, while saving time to obtain data for visualization or additional analyses. More importantly, GITAR enables users without any programming or bioinformatic expertise to work with Hi-C data. GITAR is publicly available at http://genomegitar.orgas an open-source software.

Published
2018
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15. Group-sparse Modeling Drug-kinase Networks for Predicting Combinatorial Drug Sensitivity in Cancer Cells

Author

Liu, Hui, Luo, Libo, Cheng, Zhanzhan, Sun, Jianjiang, Guan, Jihong, Zheng, Jie, and Zhou, Shuigeng

Abstract

Background: Due to the intrinsic compensatory mechanism and cross-talks mong cellular signaling pathways, single-target drugs often fail to inhibit the survival pathways in cancer cells. Some multi-target combination drugs have demonstrated their high sensitivities and low side effects in cancer therapies, and thus drawn intensive attentions from researchers and pharmaceutical enterprises. Method: Although a few computational methods have been developed to infer combination drug sensitivities based on drug-kinase interactions, they either depend on the binarization of drug-kinase binding affinities, which would lead to the loss of weak drug-target inhibitions known to affect significantly the anticancer effects, or disregard the functional group structure among the kinases involved in cancer signalling pathways. In this paper, we employed a sparse linear model, uncertain group sparse representation (UGSR), to infer essential kinases governing the cellular responses to drug treatments in cancer cells, based on the massively collected drug-kinase interactions and drug sensitivity datasets over hundreds of cancer cell lines. The inferred essential kinases can be subsequently used to calculate the cancer cell sensitivities to combination drugs. Results: The leave-one-out cross validations and two real cases show that our method achieve high performance in predict drug sensitivities of combination drugs. Moreover, a user-friendly web interface with interactive network viewer, tabular viewer and other graphical visualization plugins, has been implemented to facilitate data access and interpretation.

Published
2018
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16. CPredictor 4.0: effectively detecting protein complexes in weighted dynamic PPI networks

Author

Shi, Yunjia, Yao, Heng, Guan, Jihong, and Zhou, Shuigeng

Abstract

The identification of protein complexes is significant to understand the mechanisms of cellular processes. Up to present, many methods on protein complex detection have been developed in static PPI networks. However, static PPI networks cannot accurately describe the behaviours of proteins in the different stages of life cycle of a cell. In this paper, we combine different data sets including gene expression data, GO terms and high-throughput PPI data to reconstruct weighted dynamic PPI networks, on which a new method called CPredictor4.0 are proposed. Specifically, we first calculate protein active probability and protein functional similarity to construct weighted dynamic PPI networks, then define a high-order topological overlap measure of similarity to extract protein complexes based on the core-attachment model. In our experiments, four PPI datasets are used to detect protein complexes. Experimental results indicate that CPredictor4.0 is superior to the existing methods in overall.

Published
2018
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17. HPC-Atlas: Computationally Constructing A Comprehensive Atlas of Human Protein Complexes

Author

Pan, Yuliang, Li, Ruiyi, Li, Wengen, Lv, Liuzhenghao, Guan, Jihong, and Zhou, Shuigeng

Abstract

A fundamental principle of biology is that proteins tend to form complexes to play significant roles in the core functions of cells. For a complete understanding of human cellular functions, it is crucial to have a comprehensive atlas of human protein complexes. Unfortunately, we still lack such a comprehensive atlas of experimentally validated protein complexes, which prevents us from gaining a complete understanding of the compositions and functions of human protein complexes and biological mechanisms. To fill this gap, we built Human Protein Complexes Atlas (HPC-Atlas), as far as we know, the most accurate and comprehensive atlas of human protein complexes available to date. We integrated two latest protein interaction networks, and developed a novel computational method to identify nearly 9000 protein complexes, including many previously uncharacterized complexes. Compared with the existing works, our method achieved outstanding performance on both test and independent sets. Furthermore, with HPC-Atlas we identified 751 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) affected human protein complexes, and 456 multifunctional proteins that contain many potential moonlighting proteins. These results suggest that HPC-Atlas can serve as not only a computing framework to effectively identify biologically meaningful protein complexes by integrating multiple protein data sources, but also a valuable resource for exploring new biological findings. The HPC-Atlas webserver is freely available at http://www.yulpan.top/HPC-Atlas.

Published
2023
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18. A Neighborhood-Based Clustering Algorithm.

Author

Ho, Tu Bao, Cheung, David, Liu, Huan, Zhou, Shuigeng, Zhao, Yue, Guan, Jihong, and Huang, Joshua

Abstract

In this paper, we present a new clustering algorithm, NBC, i.e., Neighborhood Based Clustering, which discovers clusters based on the neighborhood characteristics of data. The NBC algorithm has the following advantages: (1) NBC is effective in discovering clusters of arbitrary shape and different densities; (2) NBC needs fewer input parameters than the existing clustering algorithms; (3) NBC can cluster both large and high-dimensional databases efficiently. [ABSTRACT FROM AUTHOR]

Published
2005
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19. Subjective Trust Inferred by Kalman Filtering vs. a Fuzzy Reputation.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Carbo, Javier, Garcia, Jesus, and Molina, Jose M.

Abstract

Inferring Trust in dynamic and subjective environments is an interesting issue in the way to obtain a complete delegation of human-like decisions in autonomous agents. Complex mathematical algorithms have been proposed by academic researchers to be applied when there are no universally accepted evaluation criteria. In this paper we propose a method based on fuzzy logic that has been successfully compared with several of these alternatives. Our innovative approach is compared with a classic estimation method known as kalman. The convergence of both methods has been tested in a multiagent scenario where the subjectivity of evaluations adopt prefixed variability. [ABSTRACT FROM AUTHOR]

Published
2004

20. Model-Driven Planning and Development of Infrastructures for E-Commerce.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., and Frank, Ulrich

Abstract

For many companies, especially small and medium sized firms (SME), planning and implementing infrastructures for Electronic Commerce (E-Commerce) that are in line with a convincing long term strategy is too much of a challenge. This paper presents a method that supports companies with re-designing their business processes in order to take advantage of the opportunities offered by E-Commerce. For this purpose, it provides concepts to analyse and design corporate strategies as well as various modelling languages for describing and analysing business processes, resources, IT artifacts etc. In addition to that, the method provides generic strategy networks and a library of reference business processes. They allow prospective users to avoid the effort of developing strategies and new organizational settings from scratch. The modelling language that is used to describe business processes allows for transforming a business process into a corresponding workflow schema, thereby supporting the realisation of a supporting workflow management system. [ABSTRACT FROM AUTHOR]

Published
2004

21. On Behavioural Model Transformation in Web Services.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Bordbar, Behzad, and Staikopoulos, Athanasios

Abstract

Web Services are seen as one of the most promising solutions for the integration of autonomous, heterogonous e-business systems. Today's e-commerce systems often involve a combination of multiple Web Services, which are implemented via a mix of technologies such as Business Process Markup Language (BPML), Business Process Execution Language for Web Services (BPEL4WS), and Web Service Choreography Interface (WSCI). Recently, the application of Model Driven Architecture (MDA) to Web Services has received considerable attention. However, most of existing literature deals with the static aspects of Web Service modelling. This paper focuses on the behavioral aspect of the composition of Web Services using a Meta Object Facility (MOF) compliant metamodel for BPEL4WS. The paper presents a transformation of the Unified Modelling Language (UML) Activity diagram to the BPEL4WS. [ABSTRACT FROM AUTHOR]

Published
2004

22. Classification of Business Process Correspondences and Associated Integration Operators.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Grossmann, Georg, Schrefl, Michael, and Stumptner, Markus

Abstract

Integration of business processes requires the integration of both the structure and behaviour of the data objects involved. Research in federated information systems has so far mainly addressed integration of object structure or if based on behavior representation, assumed identity of the lower level operations to be integrated. Based on earlier work that showed how a fine differentiation between the possible semantic correspondences could be used to improve the classification process, in this paper we examine business processes from the perspective of a prospective integration tool or designer and likewise provide a classification of different types of similarities between the activities in a process. From this classification, we develop a set of options for integration of business processes and, going to a more detailed level, present the set of choices available depending on particular types of correspondences between the activities of the processes that are to be integrated. [ABSTRACT FROM AUTHOR]

Published
2004

23. Methodology for the Development of a Sectoral Standard for EDI.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Grangel, Reyes, and Chalmeta, Ricardo

Abstract

The introduction of an EDI (Electronic Data Interchange) system in a particular sector is a complex problem involving different organisational, technological and human aspects. Formal systematic methodologies must be used to resolve these problems and facilitate the implementation of new EDI systems. However, the literature offers no examples of this type of methodology. Therefore, in this paper we present a methodology that describes the activities and techniques required to develop (1) a sectoral profile for EDI messages under internationally accepted standards and (2) a set of guidelines for implementation that helps EDI to be incorporated in a quick and simple manner. The methodology was developed from the experience acquired in the course of different EDI implementation projects carried out in different sectors. In order to illustrate how the process works, in this paper we have used a case study in which our methodology was put into practise to develop an EDI standard for enterprises in the tile sector. [ABSTRACT FROM AUTHOR]

Published
2004

24. A Method and Tool for Wide Audience Requirements Elicitation and Rapid Prototyping for Mobile Systems.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Rossi, Matti, and Tuunanen, Tuure

Abstract

In recent years, consumer oriented information systems development has become increasingly important matter, as more and more complex information systems are targeted towards consumer markets. We argue that developing IS for non-organizational users creates new problems, which IS and requirement engineering (RE) community should attend to. First of all, the elicitation of requirements becomes more difficult as usually consumers do not explicitly know what they want, and it is difficult for them to express their ideas. To support different views of product development, project management and design, the method should present requirements in a ‘rich enough' way to avoid overloading management, but in the same time giving designers the detailed information they need. Furthermore, to facilitate iterative requirements development the method should allow for rapid development of prototypes from designs. To support these goals we have constructed an enhanced requirements elicitation and mobile system construction method and its support environment within Metaedit+ Meta CASE tool. We based our method on Critical Success Chains (CSC) method, which supports top-down approach for planning, but also provides for wide participation of IS customers to get rich information. The high level results of CSC are turned into mobile applications running in Symbian platform by using a novel domain specific method that supports generation of executable environments from specifications. [ABSTRACT FROM AUTHOR]

Published
2004

25. Modeling Business Strategy in E-Business Systems Requirements Engineering.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Bleistein, Steven J., Cox, Karl, and Verner, June

Abstract

This paper proposes a conceptual modeling approach for requirements engineering for e-business systems that enables alignment of systems requirements with business strategy. Jackson problem diagrams and goal modeling are employed to capture business strategy. As a means of linking abstract, high-level business requirements to low-level system requirements, we leverage the paradigm of projection in both problem diagrams and goal models in parallel. We use Jackson context diagrams to describe the business model domain context. Goal modeling is used to both represent requirements and describe the objectives of business strategy. The feasibility of the approach is demonstrated by its application to a case study from the literature. [ABSTRACT FROM AUTHOR]

Published
2004

26. Architecture for Implementing the Mobile Government Services in Korea.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Yoojung Kim, Jongsoo Yoon, Seungbong Park, and Jaemin Han

Abstract

Each nation's architecture for the m-Government including Korea's is being laid out somewhat differently according to its strategy, approach, and its own structural conditions and challenges. Despite such differences, all of them are making numerous efforts to establish the advanced service architecture for the m-Government. In the meantime, they are confused in securing and managing strategic resources which are needed to create constant mobile values, diversifying wired and wireless connection sections, and dealing with technological complexities and differences in various kinds of mobile technologies. Therefore, this study proposes the m-Government service architecture, which can effectively provide nationwide m-Governmental services. It also defines key components of the m-Government service architecture and specific characteristics of applied technologies. [ABSTRACT FROM AUTHOR]

Published
2004

27. Aspects of Regulatory and Legal Implications on e-Voting.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., and Kosmopoulos, Athanassios

Abstract

This paper addresses the democracy-oriented regulatory and legal requirements that e-democracy impacts. The short term perspective of the questions put before the electorate obliterate the long term perspective in which many policy problems have to be seen. A well-designed e-voting system should produce an audit trail that is even stronger than that of conventional systems (including paper-based systems). Remote Internet voting systems pose significant risk to the integrity of the voting process, and should not be fielded for use in public elections until substantial technical and social science issues are addressed. Conclusively the paper focuses on the specific attributes an electronic voting (polling place) system should respect and ensure such as transparency, verifiability, accountability, security and accuracy in relation to the constitutional requirements such as General, Free, Equal, Secret, Direct and Democratic. [ABSTRACT FROM AUTHOR]

Published
2004

28. Ontology-Based Models of Legal Knowledge.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Sagri, Maria-Teresa, and Tiscornia, Daniela

Abstract

In this paper we describe an application of the lexical resource JurWordNet and of the Core Legal Ontology as a descriptive vocabulary for modeling legal domains. It can be viewed as the semantic component of a global standardisation framework for digital governments. A content description model provides a repository of structured knowledge aimed at supporting the semantic interoperability between sectors of Public Administration and the communication processes towards citizen. Specific conceptual models built from this base will act as a cognitive interface able to cope with specific digital government issues and to improve the interaction between citizen and Public Bodies. As a Case study, the representation of the click-on licences for re-using Public Sector Information is presented. [ABSTRACT FROM AUTHOR]

Published
2004

29. WebDG - A Platform for E-Government Web Services.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Bouguettaya, Athman, Medjahed, Brahim, Rezgui, Abdelmounaam, Ouzzani, Mourad, Xumin Liu, and Qi Yu

Abstract

Web services are deemed as the natural choice for deploying e-government applications. Their use enables e-government to fully get advantage of the envisioned Semantic Web. In this paper, we propose WebDG, a comprehensive Web Service Management System for e-government applications. It aims to improve government-citizen interactions through an infrastructure built around the "life experience" of citizens. WebDG provides a framework for automatically composing e-government services, optimized querying services, and preserving privacy. [ABSTRACT FROM AUTHOR]

Published
2004

30. A Study on Camera-Detector System for Traffic Control in Korea.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Chang-Hee Kwon, and Hong-Jin Park

Abstract

Actual detectors of traffic information in Korea adopt the loop detector system. The evaluation of alternative detector of the above system such as camera or microwave detector has been limited to the situation for uninterrupted flow instead of interrupted one. However, recently the installation of camera-detectors tends to be rapidly increased in freeways. In the case of camera detector, it appears to satisfy the requirement of measurement accuracy of traffic variables such as occupancy, traffic amount and speed in the interval unit of 5 or 15 min of uninterrupted flow situation. This study is to understand the traffic information data collection level required in the sophistication of future Korean traffic control in focusing on city map and freeways and to analyze and evaluate the loop detector as alternative for camera detector. [ABSTRACT FROM AUTHOR]

Published
2004

31. IECS: An Integrated E-Community System for Management, Decision and Service.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Yu Bo, Yunhai Tong, Hongding Wang, Zhang Peng, Shiwei Tang, and Dongqing Yang

Abstract

The paper presents an Integrated E-Community System (IECS) for management, decision and service, designed for the e-government project of the Haishu District of Ningbo, Zhejiang, China. The project need is to promote the integration of management information and service information of all communities in the district, providing a unified platform on which different departments of the district government can share and exchange community information, government users can analyze information and make decisions, and outside users can access and request service information. To meet the project need, the IECS consists of five parts: 1) The Central Database (CDB) that stores all information related with management, decision and service of the communities; 2) The Information Extracting Subsystem (IES) that extracts data from many data sources, transforms and loads it into the CDB for system administrators; 3) The Information Management Subsystem (IMS) that provides information querying and sharing for government users, and information maintenance, rights management and log management for system administrators; 4) The Intelligent Analysis Subsystem (IAS) that extracts analysis-related data from the CDB and loads it into a data warehouse, and provides multi-dimensional analysis and decision-making function for government users; 5) The Information Service Website (ISW) by which the government users and system administrators can collect and release management and service information, and outside users can access required information. The IECS supports management, decision and service of a government based on a unified data platform - the CDB. It also ensures data security by providing different workplaces and rights for different users. In the real application, the system works well. [ABSTRACT FROM AUTHOR]

Published
2004

32. AFDM: A UML-Based Methodology for Engineering Intelligent Agents.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Yanjun Tong, O'Hare, Gregory M. P., and Collier, Rem

Abstract

Agents are a potential technology with many applications. It is urgent to develop appropriate methodologies for the development and deployment of agent-oriented applications. This paper presents Agent Factory Development Methodology (AFDM), a cohesive methodology, to support the development of agent-oriented applications. On the other hand agent cloning is considered one of the possible approaches to avoid system overloading. In later sections of this paper, agent cloning is designed and implemented as an example through the AFDM. [ABSTRACT FROM AUTHOR]

Published
2004

33. Model-Driven Agent-Based Web Services IDE.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Yinsheng Li, Weiming Shen, Ghenniwa, Hamada, and Xiaohua Lu

Abstract

Web services have not exploited sufficient semantics and approaches to dynamic service-oriented operations. Software agents have been developed for these operations. Current efforts on integrating Web services and agents are predominantly concerned with enabling the agents in existing systems to request, provide or broker Web services. This paper presents the notion of agent-based Web services (AWS) and describes an integration framework that utilizes software agents' model to construct semantic and dynamic Web services. Essential concerns about the integration have been addressed. Basic AWS meta model and model-driven integrated development environment (IDE) have been developed. The IDE has been evaluated by a case study of an e-Marketplace service, reverse auction. [ABSTRACT FROM AUTHOR]

Published
2004

34. Conceptual Model of BDI Agents within an ITS.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Mowlds, Frances, and Roche, Bernard Joseph

Abstract

The purpose of this paper is to illustrate the conceptual modelling of Belief, Desire and Intention (BDI) Agents within an Intelligent Tutoring System (ITS). A two stage modelling process is presented during which a combination of existing modelling techniques are employed. Initially an overall analysis and functional decomposition of the complex ITS is performed using recognized modelling procedures from the area of object oriented software engineering. Finally, the BDI agents' state (belief, desire, intention, goals and plans) are modelled using techniques particular to the area of agent oriented software engineering. Epistemic and modal logic are employed as a modelling language. Specific attention is paid to the modelling and observations of social interactions among Intelligent Agents (IA) in the ITS. [ABSTRACT FROM AUTHOR]

Published
2004

35. Towards an Ontology for Agent Mobility.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Price, Rosanne, Krishnaswamy, Shonali, Loke, Seng W., and Chhetri, Mohan B.

Abstract

The benefits of agent mobility have been recognized for a variety of applications such as wireless ad hoc environments and network management. Mobile agent toolkits have been developed in response; however, they do not address the need for conceptual modeling techniques required for the analysis and design phases of mobile agent applications. On the other hand, conceptual level modeling techniques developed as part of Agent Oriented Software Engineering methodologies do not specifically address the requirement for modeling mobility. This paper represents a first step towards developing support for conceptual modeling of mobile agents, in terms of an ontology describing the abstract concepts and inter-relationships required to model agent mobility. The specific aim of this paper is to present an ontology that is widely applicable, not constrained by the peculiarities of any one mobile agent toolkit or application, and specified using an easily understood informal vocabulary. [ABSTRACT FROM AUTHOR]

Published
2004

36. Spatio-temporal Relevant Logic as the Logical Basis for Specifying, Verifying, and Reasoning About Mobile Multi-agent Systems.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., and Jingde Cheng

Abstract

To specify, verify, and reason about mobile multi-agent systems, we need a fundamental logic system to provide us with a criterion of logical validity as well as a representation and specification language. Because design and development of mobile multi-agent systems primarily concern that what decisions and how the decisions can be made by mobile agents with incomplete or even inconsistent knowledge acting concurrently in spatial regions changing over time, the fundamental logic must be able to underlie truth-preserving and relevant reasoning in the sense of conditional, ampliative reasoning, paracomplete reasoning, paraconsistent reasoning, spatial reasoning, and temporal reasoning. Since no existing logic system can satisfy the requirements, this paper proposes a new family of logic, named "spatio-temporal relevant logic," and shows that it is a hopeful candidate for the fundamental logic we need. [ABSTRACT FROM AUTHOR]

Published
2004

37. A Sociological Framework for Multi-agent Systems Validation and Verification.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Fuentes, Rubén, Gómez-Sanz, Jorge J., and Pavón, Juan

Abstract

Social and intentional behaviours appear as two main components of the agent paradigm. Methods of conventional software engineering do not seem to be appropriate to gain a full knowledge of these behavioural aspects, as they are not traditional software components. Their study involves new concepts and techniques, belonging to social sciences, to be integrated into software development. In this paper we show how to use the Activity Theory as a support for current Multi-Agent System methodologies. The application of the same social concepts at every stage of the development cycle allows requirements traceability, and provides methods to describe social properties and decide whether the specification satisfies them or not. The use of the approach is shown with a case study. Keywords:Multi-Agent Systems Development, Activity Theory, Activity Checklist, Requirements Elicitation [ABSTRACT FROM AUTHOR]

Published
2004

38. Multitemporal Conditional Schema Evolution.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Jensen, Ole G., and Böhlen, Michael H.

Abstract

Schema evolution is the ability of the database to respond to changes in the real world by allowing the schema to evolve. The multidimensional conditionally evolving schema(MD-CES) is a conceptual model for conditional schema changes, which modify the schema of those tuples that satisfy the change condition. The MD-CES is lossless and preserves schemas, but has an exponential space complexity. In this paper we restrict conditional schema changes to timestamp attributes. Specifically, we develop 1D-CES for schema versioning over one time dimension, and 2D-CES for schema versioning over two time dimensions. We show that the space complexity of these new evolution models is linear or polynomial. 1D-CES and 2D-CES are compared to temporal schema versioning, and we show that, unlike valid time versioning, they are lossless and achieve the same space complexity as temporal versioning if the schema changes are ordered. [ABSTRACT FROM AUTHOR]

Published
2004

39. Facilitating Database Attribute Domain Evolution Using Mesodata.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Vries, Denise, and Roddick, John F.

Abstract

Database evolution can be considered a combination ofschema evolution, in which the structure evolves with the addition and deletion of attributes and relations, together with domain evolution in which an attribute's specification, semantics and/or range of allowable values changes. We present a model in which mesodata - an additional domain definition layer containing domain structure and intelligence - is used to alleviate and in some cases obviate the need for data conversion or coercion. We present the nature and use of mesodata as it affects domain evolution, such as when a domain changes, when the semantics of a domain alter and when the attribute's specification is modified. [ABSTRACT FROM AUTHOR]

Published
2004

40. Schema Versioning in Data Warehouses.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Golfarelli, Matteo, Lechtenbörger, Jens, Rizzi, Stefano, and Vossen, Gottfried

Abstract

As several mature implementations of data warehousing systems are fully operational, a crucial role in preserving their up-to-dateness is played by the ability to manage the changes that the data warehouse (DW) schema undergoes over time in response to evolving business requirements. In this paper we propose an approach to schema versioning in DWs, where the designer may decide to undertake some actions on old data aimed at increasing the flexibility in formulating cross-version queries, i.e., queries spanning multiple schema versions. After introducing an algebra of DW schema operations, we define a history of versions for data warehouse schemata and discuss the relationship between the temporal horizon spanned by a query and the schema on which it can consistently be formulated. [ABSTRACT FROM AUTHOR]

Published
2004

41. Towards the Managment of Time in Data-Intensive Web Sites.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Atzeni, Paolo, and Nostro, Pierluigi

Abstract

The adoption of a logical model for temporal, data-intensive Web sites is proposed together with a methodology for the development. The model allows the definition of page-schemes with temporal aspects (which could be related to the page as a whole or to individual components of it). The design process follows a development that starts with a traditional E-R scheme; the various steps lead to a temporal E-R scheme, to a navigation scheme and finally to a T-ADM scheme. A tool associated with the methodology has been developed: it automatically generates both the relational database (with the temporal features needed) supporting the site and the actual Web pages, which can be dynamic (JSP) or static (plain HTML), or a combination thereof. [ABSTRACT FROM AUTHOR]

Published
2004

42. Evolution of XML-Based Mediation Queries in a Data Integration System.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Lóscio, Bernadette Farias, and Salgado, Ana Carolina

Abstract

One of the main challenges in data integration systems is the maintenance of the mappings between the mediation schema and the source schemas. In a dynamic environment, such mappings must be flexible enough in order to accommodate new data sources and new users' requirements. In this context, we address a novel and complex problem that consists in propagating a change event occurring at the source level or at the user level into the mediation level. We propose an incremental approach to develop the mediation schema and the mediation queries based on the evolution of the data source schemas and the evolution of the users' requirements. The proposed approach allows the mediation level to evolve incrementally and modifications can be handled easier increasing the system flexibility and scalability. [ABSTRACT FROM AUTHOR]

Published
2004

43. Elementary Translations: The Seesaws for Achieving Traceability Between Database Schemata.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Domínguez, Eladio, Lloret, Jorge, Rubio, Ángel L., and Zapata, María A.

Abstract

There exist several recent approaches that leverages the use of model transformations during software development. The existence of different kinds of models, at different levels of abstraction, involves the necessity of transferring knowledge from one model to another. This framework can also be applied in the context of metadata management for database evolution, in which transformations are needed both to translate schemata from one level to another and to modify existing schemata. In this paper we introduce the notions of translation rule and elementary translation which are used within a forward database maintenance strategy. [ABSTRACT FROM AUTHOR]

Published
2004

44. An Ontological Framework for Evolutionary Model Management.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Matsuo, Atsushi, Seta, Kazuhisa, Hayashi, Yusuke, and Ikeda, Mitsuru

Abstract

Ontology provides a system of basic primitives, terms, concepts and axioms that constitute the model. We present an ontology-based evolutionary model management framework that authors can build their models without concern for the complicated consistency and evolutionary management among multiple view models based on the ontology. Our ontological approach to evolutionary management is that we deeply analyze and clarify generic principles of knowledge construction and modeling premises. In this paper, we first consider the fundamental issues of conceptual relations and identity. And we suggest our philosophy that can deal explicitly with authors' viewpoint and their viewpoint change/movement. Then, we show our evolutionary model management framework taking simple examples. [ABSTRACT FROM AUTHOR]

Published
2004

45. Automatic Integrity Constraint Evolution due to Model Subtract Operations.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Cabot, Jordi, and Conesa, Jordi

Abstract

When evolving Conceptual Schemas (CS) one of the most common operations is the removal of some model elements. This removal affects the set of integrity constraints (IC) defined over the CS. Most times they must be modified to remain consistent with the evolved CS. The aim of this paper is to define an automatic evolutionary method to delete only the minimum set of constraints (or some of their parts) needed to keep the consistency with the CS after subtract operations. We consider that a set of constraints is consistent with an evolved CS when: 1) none of them refer to an element removed from the original CS and 2) the set of constraints is equal or less restrictive than the original one. In this paper we present our method assuming CS defined in UML with ICs specified in OCL, but it can be applied to other languages with similar results. [ABSTRACT FROM AUTHOR]

Published
2004

46. Query Rewriting for Extracting Data Behind HTML Forms.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Xueqi (Helen) Chen, Embley, David W., and Liddle, Stephen W.

Abstract

Much of the information on the Web is stored in specialized searchable databases and can only be accessed by interacting with a form or a series of forms. As a result, enabling automated agents and Web crawlers to interact with form-based interfaces designed primarily for humans is of great value. This paper describes a system that can fill out Web forms automatically according to a given user query against an ontological description of an application domain and, to the extent possible, can extract just the relevant data behind these Web forms. Experimental results on two application domains show that the approach can work well. [ABSTRACT FROM AUTHOR]

Published
2004

47. Research and Implementation of CORBA Web Services.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Jianqiang Hu, Bin Zhou, Yan Jia, and Peng Zou

Abstract

CORBA (Common Object Request Broker Architecture) is one of the popular technologies that can be used to construct enterprise level application systems. However, none of conventional middleware technologies will dominate the software industry alone; therefore interoperability becomes one of the most crucial issues. Web Services is a kind of new Web application shape which shields from the existence of different middleware platforms and programming language abstractions. This paper firstly presents two models for wrapping CORBA objects to Web Services, and then analyzes some key technologies such as scalable architecture, SOAP/IIOP protocol datatype mapping, unified service providing infrastructure etc. Finally, it gives some tests and performance comparison on top of StarWebService that is developed by our team. [ABSTRACT FROM AUTHOR]

Published
2004

48. Grammar Based Interface Processing in Web Service Composition.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., XiaoLing Wang, and Chi Cheung Shing

Abstract

Web services have emerged as a new computing paradigm for information integration and sharing. The interfaces of Web services can evolve to adapt to the dynamic and autonomic nature of business workflows. As such, it is difficult to define interface rules between any couple of collaborative services. How to cope with the information exchange among such services is an important and challenging problem in the realization of service composition. This paper studies the problem and presents grammar based method by taking advantage of the XML documents exchanged among the services. Preliminary experiments showed that the grammar based method is promising in terms of efficiency and robustness under the dynamic Web environment. [ABSTRACT FROM AUTHOR]

Published
2004

49. Automatic Location and Separation of Records: A Case Study in the Genealogical Domain.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Walker, Troy, and Embley, David W.

Abstract

Locating specific chunks (records) of information within documents on the web is an interesting and nontrivial problem. If the problem of locating and separating records can be solved well, the longstanding problem of grouping extracted values into appropriate relationships in a record structure can be more easily resolved. Our solution is a hybrid of two well established techniques: (1) ontology-based extraction [ECJ+99] and (2) vector space modeling [SM83]. To show that the technique has merit, we apply it to the particularly challenging task of locating and separating records for genealogical web documents, which tend to vary considerably in layout and format. Experiments we have conducted show this technique yields an average of 92% recall and 93% precision for locating and separating genealogical records in web documents. [ABSTRACT FROM AUTHOR]

Published
2004

50. A New Dynamic Indexing Structure for Searching Time-Series Patterns.

Author

Shan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Guan, Jihong, Dongqing Yang, Grandi, Fabio, Mangina, Eleni, Il-Yeol Song, Mayr, Heinrich C., Zi-Yu Lin, Yong-Sheng Xue, and Xiao-Hua Lv

Abstract

We target at the growing topic of representing and searching time-series data. A new MABI (Moving Average Based Indexing) technique is proposed to improve the performance of the similarity searching in large time-series databases. Notions of Moving average and Euclidean distances are introduced to represent the time-series data and to measure the distance between two series. Based on the distance reducing rate relation theorem, the MABI technique has the ability to prune the unqualified sequences out quickly in similarity searches and to restrict the search to a much smaller range, compare to the data in question. Finally the paper reports some results of the experiment on a stock price data set, and shows the good performance of MABI method. [ABSTRACT FROM AUTHOR]

Published
2004

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