ppxscal/embedding_network huggingface dataset:
Implementation of the Multiagent-based Product Knowledge Extraction System
Authors: Cunrong Li, Chunxia Yang, Ping Xiong
Venue: Proceedings of the 2009 WRI Global Congress on Intelligent Systems - Volume 02 (2009)

Building upon an analysis of traditional product knowledge extraction methods, a new prototype of Product Knowledge Extraction System (PKES) based on multiagent theory is developed. In this system, a Client/Server(C/S) architecture based on a local computer network is adopted for knowledge extraction. The knowledge extraction task is divided into different parts of sub-tasks and distributed to different clients. By making full use of the capability of client computers and coordination of the clients and the server, the product knowledge extraction task could be implemented efficiently. To achieve better use of the extracted product knowledge, the knowledge management functions are also integrated with the PKES system. Finally, a demonstration of the effectiveness and viability of the system is given by a simulation of the PKES.
Water Eutrophication Prevention by Phoslock Flocculation and Sediment Capping Reaction
Authors: Liu Yungen, Tian Kun, Andrew Winks
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

Phoslock, a novel modified bentonite, was developed by CSIRO. With the innovative principle both on Soluble Phosphate (SP) removal and sediment capping, Phoslock has great efficiency in SP removal, normally 95%, and effective capacity to sediment capping of the bottom slurry for avoiding the nutrient release. From the applications in Australia, China and South Africa, Phoslock demonstrated exciting result on eutrophic water purification. With the treatment by Phoslock, the eutrophic water could be transferred to good water quality with variously healthy aquatic planting growing. Phoslock could eventually purify the eutrophic water, in hence, it was an effective way on water eutrophication prevention.
A 5-Parameter Bundle Adjustment Method for Image Mosaic
Authors: Xianyong Fang, Bin Luo, Haifeng Zhao, Yiwen Zhang
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

A 5-parameter bundle adjustment method is proposed in this paper for global mosaic of an image sequence. By decomposing the rotation matrix into a 3-parameter rotation axis and a rotation angle, to each image, there are 5 parameters that need estimate for rotation axis, rotation angle and focal length. The proposed method minimizes the distance between feature matches in 3D space so that these 5 parameters are refined gradually for final stitching of all images together. Experimental results suggest that this method is an useful extension to existing research with the advantages of real 3D camera motion, accurate 5-parameter rotation decomposition and reliable 3D feature definition.
Fuzzy fault tree analysis based on T&#x2013;S model with application to INS/GPS navigation system
Authors: Hua Song, Hong-Yue Zhang, C. W. Chan
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2008)

A novel fault tree analysis (FTA) technique based on the Takagi and Sugeno (T&#x2013;S) model is proposed in this paper. In the proposed technique, referred to as the TS-FTA, the events in the conventional FTA can be expressed in terms of fuzzy possibilities, and the gates that represent the relations among the top event and the primary events are replaced by T&#x2013;S fuzzy gates derived from the T&#x2013;S model. The magnitudes of the faults in the system are expressed in term of fuzzy variables. Since the proposed TS-FTA is derived from fuzzy logic and the T&#x2013;S model, it can readily handle fuzzy information and uncertainties in the relationships among events. Therefore, the TS-FTA is suitable for systems where exact information on the fault probabilities of the components and the failure mechanisms are not available. The proposed TS-FTA is applied to analyze the reliability of an Inertial Navigation System and Global Position System (INS/GPS) integrated navigation system.
Attacks and countermeasures in multi-hop Cognitive Radio Networks
Authors: Fei Hu, De-cun Dong, Yang Xiao
Venue: International Journal of Security and Networks (2009)

In Cognitive Radio Networks (CRNs), there are some new attacks. For instance, an attacker may modify the air interface of a CRN to mimic primary signal's characteristics, thereby causing legitimate Secondary Users (SUs) to erroneously identify the attacker as a Primary User (PU). Most CRNs rely on Common Control Channel (CCC) to allocate channels. An attacker can saturate CCC to make control message exchange difficult. This paper analyses attacks specific to CRN and the countermeasures. We will focus on anti-attack schemes of low layers, i.e., physical and MAC layers. We propose several enhancements to secure CRN.
Fairness in Cooperating Multi-agent Systems --- Using Profit Sharing as an Example
Authors: Ming-Chih Hsu, Von-Wun Soo
Venue: Multi-Agent Systems for Society: 8th Pacific Rim International Workshop on Multi-Agents, PRIMA 2005, Kuala Lumpur, Malaysia, September 26-28, 2005, Revised Selected Papers (2009)

Distributing profit in a coalition of multiple cooperating agents [3] is an important issue in both multi-agent and economics society. Proposed in 1953, Shapley value scheme with its elegant axiomatic derivation is essential to solution concepts for profit sharing. However, Shapley value scheme did not cover fairness issues. A new scheme of profit sharing with fairness awareness is proposed in this work. Axioms considering both fairness and efficiency issues are included in the new scheme. An algorithm is constructed for calculation of profit sharing under this new scheme. The existence of a solution existence and other properties of this algorithm are discussed.
Reaching the Top of the Skyline: An Efficient Indexed Algorithm for Top-k Skyline Queries
Authors: Marlene Goncalves, María-Esther Vidal
Venue: Proceedings of the 20th International Conference on Database and Expert Systems Applications (2009)

Criteria that induce a Skyline naturally represent user's preference conditions useful to discard irrelevant data in large datasets. However, in the presence of high-dimensional Skyline spaces, the size of the Skyline can still be very large, making unfeasible for users to process this set of points. To identify the best points among the Skyline, the Top-k Skyline approach has been proposed. Top-k Skyline uses discriminatory criteria to induce a total order of the points that comprise the Skyline, and recognizes the best or top-k objects based on these criteria. Different algorithms have been defined to compute the top-k objects among the Skyline; while existing solutions are able to produce the Top-k Skyline, they may be very costly. First, state-of-the-art Top-k Skyline solutions require the computation of the whole Skyline; second, they execute probes of the multicriteria function over the whole Skyline points. Thus, if k is much smaller than the cardinality of the Skyline, these solutions may be very inefficient because a large number of non-necessary probes may be evaluated. In this paper, we propose the TKSI, an efficient solution for the Top-k Skyline that overcomes existing solutions drawbacks. The TKSI is an index-based algorithm that is able to compute only the subset of the Skyline that will be required to produce the top-k objects; thus, the TKSI is able to minimize the number of non-necessary probes. We have empirically studied the quality of TKSI, and we report initial experimental results that show the TKSI is able to speed up the computation of the Top-k Skyline in at least 50% percent w.r.t. the state-of-the-art solutions, when k is smaller than the size of the Skyline.
Atlas.txt: linking geo-referenced data to text for NLG
Authors: Kavita E. Thomas, Somayajulu Sripada
Venue: Proceedings of the Eleventh European Workshop on Natural Language Generation (2007)

Geo-referenced data which are often communicated via maps are inaccessible to the visually impaired population. We summarise existing approaches to improving accessibility of geo-referenced data and present the Atlas.txt project which aims to produce textual summaries of such data which can be read out via a screenreader. We outline issues involved in generating descriptions of geo-referenced data and present initial work on content determination based on knowledge acquisition from both parallel corpus analysis and input from visually impaired people. In our corpus analysis we build an ontology containing abstract representations of expert-written sentences which we associate with macros containing sequences of data analysis methods. This helps us to identify which data analysis methods need to be applied to generate text from data.
The Seismic Response Calculating for Marine Gas Hydrate Based on the Theory of Forward Modeling
Authors: Wu Zhiqiang, Tong Siyou, Wang Ruimin, Wang Linfei, Liu Huaishan, Zhang Jin
Venue: Proceedings of the 2009 International Forum on Information Technology and Applications - Volume 03 (2009)

Marine gas hydrate occurs in the top few hundred meters of sediments on the continental slope, it is the important method by using seismic response forward calculating. But the conventional seismic modeling method can't model the characters of the seismic wave propagation. Using The Seismic Elastic Wave Theory (Xu 1997), it is more suitable to emulate the seismic response of BSRs. Simulation shows that BSRs are still one of the best indicators of presence of gas hydrate-bearing sediments. If BSRs are found, gas hydrates can be considered to exist. BSRs are primarily caused by free gas beneath the base of gas hydrate stability zone (BGHS). BSRs are approximately corresponding to the BGHS. The relationships between gas hydrate gas system and BSRs should be studied from view points of dynamic evolution. The seismic response of BSRs is the strong reflections, but when the angles of incidence exceed 30 degree, the BSR amplitudes increase fast. In the AVO inversion of real seismic data related to gas hydrate, the Shuey formula (trinomial) is more precise.
Automatic Chinese abbreviation generation using conditional random field
Authors: Dong Yang, Yi-cheng Pan, Sadaoki Furui
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers (2009)

This paper presents a new method for automatically generating abbreviations for Chinese organization names. Abbreviations are commonly used in spoken Chinese, especially for organization names. The generation of Chinese abbreviation is much more complex than English abbreviations, most of which are acronyms and truncations. The abbreviation generation process is formulated as a character tagging problem and the conditional random field (CRF) is used as the tagging model. A carefully selected group of features is used in the CRF model. After generating a list of abbreviation candidates using the CRF, a length model is incorporated to re-rank the candidates. Finally the full-name and abbreviation co-occurrence information from a web search engine is utilized to further improve the performance. We achieved top-10 coverage of 88.3% by the proposed method.
Assessing and Improving SCADA Security in the Dutch Drinking Water Sector
Authors: Eric Luiijf, Manou Ali, Annemarie Zielstra
Venue: Critical Information Infrastructure Security: Third International Workshop, CRITIS 2008, Rome, Italy, October13-15, 2008. Revised Papers (2009)

International studies have shown that information security for process control systems, in particular SCADA, is weak. As many critical infrastructure (CI) services depend on process control systems, any vulnerability in the protection of process control systems in CI may result in serious consequences for citizens and society. In order to understand their strengths and weaknesses, the drinking water sector in The Netherlands benchmarked the information security of their process control environments. Large differences in their security postures were found. Good Practices for SCADA security were developed based upon the study results. This paper will discuss the simple but effective approach taken to perform the benchmark, the way the results were reported to the drinking water companies, and the way in which the SCADA security good practices were developed. Figures shown in this paper are based on artificially constructed data since the study data contain company and national sensitive information.
Preimage Attacks on One-Block MD4, 63-Step MD5 and More
Authors: Kazumaro Aoki, Yu Sasaki
Venue: Selected Areas in Cryptography: 15th International Workshop, SAC 2008, Sackville, New Brunswick, Canada, August 14-15, Revised Selected Papers (2009)

This paper shows preimage attacks on one-block MD4 and MD5 reduced to 63 (out of 64) steps. Our attacks are based on the meet-in-the-middle attack, and many additional improvements make the preimage computable faster than that of the brute-force attack, 2128 hash computation. A preimage of one-block MD4 can be computed in the complexity of the 2107 MD4 compression function computation, and a preimage of MD5 reduced to 63 steps can be computed in the complexity of the 2121 MD5 compression function computation. Moreover, we optimize the computational order of the brute-force attack against MD5, and a preimage of full-round MD5 can be computed in the complexity of the 2127 MD5 compression function computation.
Dynamic Background Modeling for Foreground Segmentation
Authors: Shaoqiu Xu
Venue: Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science (2009)

This paper presents a dynamic background modeling approach for foreground segmentation. The classification between foreground and background is based on Bayes decision rule. The posterior probability of a pixel being observed as a background or a foreground is directly estimated based on the occurrence frequency of its quantized version. Experimental results show that the presented method can be performed in real time and has good performance in complex and dynamic environments.
Unsupervised multilingual learning for POS tagging
Authors: Benjamin Snyder, Tahira Naseem, Jacob Eisenstein, Regina Barzilay
Venue: Proceedings of the Conference on Empirical Methods in Natural Language Processing (2008)

We demonstrate the effectiveness of multilingual learning for unsupervised part-of-speech tagging. The key hypothesis of multilingual learning is that by combining cues from multiple languages, the structure of each becomes more apparent. We formulate a hierarchical Bayesian model for jointly predicting bilingual streams of part-of-speech tags. The model learns language-specific features while capturing cross-lingual patterns in tag distribution for aligned words. Once the parameters of our model have been learned on bilingual parallel data, we evaluate its performance on a held-out monolingual test set. Our evaluation on six pairs of languages shows consistent and significant performance gains over a state-of-the-art monolingual baseline. For one language pair, we observe a relative reduction in error of 53%.
Near-field microwave and mm-wave noninvasive diagnosis of human skin
Authors: S. Kharkovsky, M. T. Ghasr, M. A. Abou-Khousa, R. Zoughi
Venue: Proceedings of the 2009 IEEE International Workshop on Medical Measurements and Applications (2009)

Microwave and mm-wave reflectometry is one of the potential techniques for diagnosis of human skin for detection of diseases such as skin cancer. It is shown that using an open-ended waveguide probe, non-contact measurements of the reflection properties of skin may be conducted leading to distinction between dielectric properties of normal and diseased skin. This technique can then be extended into a differential technique which enables skin property differentiation independent of the location on the body. This paper discusses the basics of the method along with some preliminary results.
A constraint satisfaction approach to geospatial reasoning
Authors: Martin Michalowski, Craig A. Knoblock
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

The large number of data sources on the Internet can be used to augment and verify the accuracy of geospatial sources, such as gazetteers and annotated satellite imagery. Data sources such as satellite imagery, maps, gazetteers and vector data have been traditionally used in geographic infonnation systems (GIS), but nontraditional geospatial data, such as online phone books and property records are more difficult to relate to imagery. In this paper, we present a novel approach to combining extracted information from imagery, road vector data, and online data sources. We represent the problem of identifying buildings in satellite images as a constraint satisfing problem (CSP) and use constraint programming to solve it. We apply this technique to real-world data sources in EI Segundo, CA and our experimental evaluation shows how this approach can accurately identify buildings when provided with both traditional and nontraditional data sources.
Efficient Sample Reuse in EM-Based Policy Search
Authors: Hirotaka Hachiya, Jan Peters, Masashi Sugiyama
Venue: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (2009)

Direct policy search is a promising reinforcement learning framework in particular for controlling in continuous, high-dimensional systems such as anthropomorphic robots. Policy search often requires a large number of samples for obtaining a stable policy update estimator due to its high flexibility. However, this is prohibitive when the sampling cost is expensive. In this paper, we extend an EM-based policy search method so that previously collected samples can be efficiently reused. The usefulness of the proposed method, called Reward-weighted Regression with sample Reuse (R3), is demonstrated through a robot learning experiment.
Thai grapheme-based speech recognition
Authors: Paisarn Charoenpornsawat, Sanjika Hewavitharana, Tanja Schultz
Venue: Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers on XX (2006)

In this paper we present the results for building a grapheme-based speech recognition system for Thai. We experiment with different settings for the initial context independent system, different number of acoustic models and different contexts for the speech unit. In addition, we investigate the potential of an enhanced tree clustering method as a way of sharing parameters across models. We compare our system with two phoneme-based systems; one that uses a hand-crafted dictionary and another that uses an automatically generated dictionary. Experiment results show that the grapheme-based system with enhanced tree clustering outperforms the phoneme-based system using an automatically generated dictionary, and has comparable results to the phoneme-based system with the hand-crafted dictionary.
Evaluating the effects of treebank size in a practical application for parsing
Authors: Kenji Sagae, Yusuke Miyao, Rune Sætre, Jun'ichi Tsujii
Venue: Software Engineering, Testing, and Quality Assurance for Natural Language Processing (2008)

Natural language processing modules such as part-of-speech taggers, named-entity recognizers and syntactic parsers are commonly evaluated in isolation, under the assumption that artificial evaluation metrics for individual parts are predictive of practical performance of more complex language technology systems that perform practical tasks. Although this is an important issue in the design and engineering of systems that use natural language input, it is often unclear how the accuracy of an end-user application is affected by parameters that affect individual NLP modules. We explore this issue in the context of a specific task by examining the relationship between the accuracy of a syntactic parser and the overall performance of an information extraction system for biomedical text that includes the parser as one of its components. We present an empirical investigation of the relationship between factors that affect the accuracy of syntactic analysis, and how the difference in parse accuracy affects the overall system.
In-situ Monitoring of Active Crack in Steel Structure Using Acoustic Emission Technique
Authors: Li Li, Zhongxiao Peng, Meiyun Zhao
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

The paper introduces a non-destructive testing (NDT) method—Acoustic Emission (AE) technique to detect active crack in steel structure of large lifting machinery used in hydropower stations. A test apparatus has been established, in which a beam with seeded cracks was loaded using a press machine. AE signals were collected during the test. Due to the complexity of the AE signals, Empirical Mode Decomposition (EMD) has been exploited to decompose them. The results have demonstrated that the frequency feature band is low in the crack initiation. With the crack growth, the frequency feature band becomes higher. The total frequency range of the crack propagation is 25KHz-160KHz. The research work has laid a theoretical foundation to application of the AE technology for safety evaluation of steel structures in lifting machinery. It also demonstrates that AE technique is an effective method for in-situ monitoring of the steel structures.
Classifiers fusion for EEG signals processing in human-computer interface systems
Authors: Maryam Esmaeili
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 2 (2007)

In this paper we study the effectiveness of using multiple classifier combination for EEG signals classification aiming to obtain more accurate results than it possible from single classifier system. The developed system employs different features vectors fused at the abstract and measurement levels for integrating information to reach a collective decision. For making decision, the majority voting scheme has been used. While at the measurement level, fuzzy integral, majority vote, decision template and some other types of combination methods have been investigated. The ensemble classification task is completed by feeding the Support Vectors Machines with Redial Basis Kernel functions classifiers with different features extracted from the EEG signal for imagination of right and left hands movements (i.e., at EEG channels C3 and C4). The parameters of SVM classifiers were optimized by genetic algorithm. The results show that using classifier fusion methods improved the overall classification performance.
Using DITA for documenting software product lines
Authors: Oscar Díaz, Felipe I. Anfurrutia, Jon Kortabitarte
Venue: Proceedings of the 9th ACM symposium on Document engineering (2009)

Aligning the software process and the documentation process is a recipe for having both software and documentation in synchrony where changes in software seamlessly ripple along its documentation counterpart. This paper focuses on documentation for Software Product Lines (SPLs). A SPL is not intended to build one application, but a number of them: a product family. In contrast to single-software product development, SPL development is based on the idea that the distinct products of the family share a significant amount of assets. This forces a change in the software process. Likewise, software documentation development should now mimic their code counterpart: product documentation should also be produced out of a common set of assets. Specifically, the paper shows how DITA process and documents are recasted using a feature-oriented approach, a realization mechanism for SPLs. In so doing, documentation artifacts are produced at the same pace and using similar variability mechanisms that those used for code artifacts. This accounts for three main advantages: uniformity, separation of concerns, and timely and accurate delivery of the documentation.