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Decidable fragments of first-order language under stable model semantics and circumscription

Decidable fragments of first-order language under stable mod...

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作者： Zhang, Heng Yinga, Mingsheng State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing China Center of Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney NSW Australia

ISBN: (纸本)9781577354642

The stable model semantics was recently generalized by Ferraris, Lee and Lifschitz to the full first-order language with a syntax translation approach that is very similar to McCarthy's circumscription. In this paper, we investigate the decidability and undecidability of various fragments of first-order language under both semantics of stable models and circumscription. Some maximally decidable classes and undecidable classes are identified. The results obtained in the paper show that the boundaries between decidability and undecidability for these two semantics are very different in spite of the similarity of definition. Moreover, for all fragments considered in the paper, decidability under the semantics of circumscription coincides with that in classical first-order logic. This seems rather counterintuitive due to the second-order definition of circumscription and the high undecidability of first-order circumscription. Copyright © 2010, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Computability and decidability

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Use relative weight to improve the kNN for unbalanced text category

Use relative weight to improve the kNN for unbalanced text c...

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International Conference on Natural Language Processing and Knowledge engineering

作者： Liu, Xiaodong Ren, Fuji Yuan, Caixia Dept. of Information Sciences and Intelligent Systems Faculty of Engineering University of Tokushima Tokushima Japan Center for Intelligence Science and Technology/Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781424468966

The technology of text category is widely used in natural language processing. As one of best text category algorithms, kNN is very popular used in many applications. Traditional kNN assumes that the distribution of training data is even, however, it is not the case for many situations. When we used kNN in our Topic Detection and Tracking (TDT) system, it did not perform well due to the bias of training data set. To overcome the obstacle caused by data bias, this paper proposes an approach which uses relative weight to adjust the weight of kNN (RWKNN). When evaluated on the data of TDT2 and TDT3 Chinese corpus, RWKNN proves to be robust on unbalanced data and yields better performance than the traditional kNN. ©2010 IEEE.

关键词： Natural language processing systems

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A workmanlike orthogonal-type robot for finishing an LED lens mold

A workmanlike orthogonal-type robot for finishing an LED len...

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Joint 5th International Conference on Soft Computing and intelligent systems and 11th International Symposium on Advanced intelligent systems, SCIS and ISIS 2010

作者： Nagata, Fusaomi Mizobuchi, Takanori Watanabe, Keigo Department of Mechanical Engineering Faculty of Engineering Tokyo University of Science Yamaguchi Sanyo-Onoda 756-0884 Japan Department of Intelligent Mechanical Systems Graduate School of Natural Science and Technology Okayama University Okayama 700-8530 Japan

In this paper, a new desktop orthogonal-type robot, which has abilities of compliant motion and stick-slip motion, is first presented for lapping small metallic molds with curved surface. A thin wood-stick tool is attached to the tip of the zaxis. The tool tip has a small ball-end shape. The control system is composed of a force feedback loop, position feedback loop and position feedforward loop. The force feedback loop controls the polishing force consisting of tool contact force and kinetic friction forces. The position feedback loop controls the position in pick feed direction, e.g., z-direction. The position feedforward loop leads the tool tip along a desired trajectory called cutter location data (CL data). The CL data are generated from the main-processor of a CAM system. The proposed robot realizes a compliant motion required for the surface following control along a spiral path. Also, a small stick-slip motion control strategy is added to the control system to improve the lapping performance. The small stick-slip motion is orthogonally generated to the tool moving direction. Generally, the stick-slip motion is an undesirable phenomenon and should be eliminated in precision machineries. However, the proposed robot employs a small stickslip motion to improve the lapping quality. In order to cope with the requirement of long-time run, an automatic truing function is further considered for the wood-stick tool. The effectiveness of the robot is examined through an actual lapping test of an LED lens mold.

关键词： Robots

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Topological relations between convex regions

Topological relations between convex regions

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作者： Li, Sanjiang Liu, Weiming Faculty of Engineering and Information Technology University of Technology Sydney Australia State Key Laboratory of Intelligent Technology and Systems TNLIST Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9781577354642

Topological relations between spatial objects are the most important kind of qualitative spatial information. Dozens of relation models have been proposed in the past two decades. These models usually make a small number of distinctions and therefore can only cope with spatial information at a fixed granularity of spatial knowledge. In this paper, we propose a topological relation model in which the topological relation between two convex plane regions can be uniquely represented as a circular string over the alphabet {u, v, x, y}. A linear algorithm is given to compute the topological relation between two convex polygons. The infinite relation calculus could be used in hierarchical spatial reasoning as well as in qualitative shape description. Copyright © 2010, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Computational geometry

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Texture image retrieval based on gray-primitive co-occurrence matrix

Texture image retrieval based on gray-primitive co-occurrenc...

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IEEE International Conference on Natural Language Processing and Knowledge engineering (NLP-KE)

作者： Wei Wang Motoyuki Suzuki Fuji Ren Department of Info. Science & Intelligent Systems Faculty of Engineering University of Tokushima Tokushima Japan

The research of texture similarity is very important component of content-based image retrieval system. Firstly the rotation invariance of gray-primitive co-occurrence matrix was proved in this paper, then a new texture image retrieval technique based on gray-primitive co-occurrence matrix was presented. The result of experiment indicates that the algorithm proposed has low computational complexity and certain noise resisting ability.

关键词： Image retrieval Feature extraction Pixel Gray-scale Euclidean distance Noise intelligent systems

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Vote-based LELC for positive and unlabeled textual data streams

Vote-based LELC for positive and unlabeled textual data stre...

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10th IEEE International Conference on data Mining Workshops, ICDMW 2010

作者： Liu, Bo Xiao, Yanshan Cao, Longbing Yu, Philip S. Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and IT University of Technology Sydney Australia Department of Computer Science University of Illinois at Chicago 851 S. Morgan Street Chicago IL 60607-0753 United States

ISBN: (纸本)9780769542577

In this paper, we extend LELC (PU Learning by Extracting Likely Positive and Negative Micro-Clusters) method to cope with positive and unlabeled data streams. Our developed approach, which is called vote-based LELC, works in three steps. In the first step, we extract representative documents from unlabeled data and assign a vote score to each document. The assigned vote score reflects the degree of belongingness of an example towards its corresponding class. In the second step, the extracted representative examples, together with their vote scores, are incorporated into a learning phase to build an SVM-based classifier. In the third step, we propose the usage of an ensemble classifier to cope with concept drift involved in the textual data stream environment. Our developed approach aims at improving the performance of LELC by rendering examples to contribute differently to the construction of the classifier according to their vote scores. Extensive experiments on textual data streams have demonstrated that vote-based LELC outperforms the original LELC method. © 2010 IEEE.

关键词： data Streams LELC Positive and Unlabeled Learning SVM-based classifier data structures document extraction documents representation learning learning by extracting likely positive and negative micro-cluster pattern classification support vector machines t

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Use Relative Weight to Improve the kNN for Unbalanced Text Category

Use Relative Weight to Improve the kNN for Unbalanced Text C...

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The 6th International Conference on Natural Language Processing and Knowledge engineering(第六届IEEE自然语言处理与知识工程国际会议 NLP-KE 2010)

作者： Xiaodong LIU Fuji REN Caixia YUAN Dept. of Information Sciences and Intelligent Systems Faculty of Engineering/ the University of Toku Dept. of Information Sciences and Intelligent Systems Faculty of Engineering/ the University of Toku Center for Intelligence Science and Technology/Beijing University of Posts and Telecommunications Be

ISBN: (纸本)9781424468973

关键词： k-nearest neighbor text category relative weight

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Hirokazu Miura Satoshi Kakeda Hideki Tode Hirokazu Taki Faculty of Systems Engineering Wakayama University Wakayama Japan Department Computer Science and Intelligent Systems Osaka Prefecture University Sakai Japan

In vehicular ad-hoc networks (VANETs), moving vehicles carry data and exchange it as they pass each other. Storage in a vehicle, in other words, the amount of saved data is limited resource in general. Therefore, attributes of data that should be carried by vehicles is an important factor in order to efficiently disseminate desired data. In this paper, we focus on popularity of data and propose probabilistic data deployment based on its popularity. The proposed method deploys the data to vehicles randomly according to its relative popularity. By this simple operation, data can be deployed inside a vehicular network and as a result, data with high popularity tends to have larger number of copies inside the network than lower-popularity data. Performance evaluation shows that our deployment can work well in limited storage.

关键词： Ad hoc networks Road vehicles intelligent systems Mobile communication Peer to peer computing Buffer storage Automotive engineering data engineering systems engineering and theory Computer science

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Prediction model of reservoir fluids properties using sensitivity based linear learning method

Prediction model of reservoir fluids properties using sensit...

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International Conference on Multimedia Computing and Information Technology, MCIT'2010

作者： Olatunji, Sunday Olusanya Selamat, Ali Raheem, Abdul Azeez Abdul Intelligent Software Engineering Laboratory Faculty of Computer Science and Information Systems University of Technology Malaysia 81310 UTM Skudai Johor Malaysia Centre for Petroleum and Minerals Research Institute King Fahd University of Petroleum and Mineral Dhahran 31261 Saudi Arabia

ISBN: (纸本)9781424470037

This paper presented a new prediction model for Pressure-Volume-Temperature (PVT) properties based on the recently introduced learning algorithm called Sensitivity Based Linear Learning Method (SBLLM) for two-layer feedforward neural networks. PVT properties are very important in the reservoir engineering computations. The accurate determination of these properties such as bubble-point pressure and oil formation volume factor is important in the primary and subsequent development of an oil field. In this work, we develop Sensitivity Based Linear Learning method prediction model for PVT properties using two distinct databases, while comparing forecasting performance, using several kinds of evaluation criteria and quality measures, with neural network and the three common empirical correlations. Empirical results from simulation show that the newly developed SBLLM based model produced promising results and outperforms others, particularly in terms of stability and consistency of prediction. ©2010 IEEE.

关键词： Learning algorithms

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Prediction model of permeability from well logs using Type-2 Fuzzy Logic systems

Prediction model of permeability from well logs using Type-2...

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15th International Symposium on Artificial Life and Robotics, AROB '10

作者： Olatunji, Sunday Olusanya Selamat, Ali Raheem, Abdul Azeez Abdul Intelligent Software Engineering Laboratory Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia 81310 UTM Skudai Johor Malaysia Centre for Petroleum and Minerals Research Institute King Fahd University of Petroleum and Mineral Dhahran 31261 Saudi Arabia

ISBN: (纸本)9784990288044

In this paper, the viability and capability of using Type-2 Fuzzy Logic systems as a novel approach for predicting permeability from Well Logs has been investigated and implemented. Type-2 fuzzy logic is powerful in handling uncertainties, including uncertainties in measurements and data used to calibrate the parameters. In the formulation used, the value of a membership function corresponding to a particular permeability value is no longer a crisp value;rather, it is associated with a range of values that can be characterized by a function that reflects the level of uncertainty. In this way, the model will be able to adequately account for all forms of uncertainties associated with predicting permeability from well log data, where uncertainties are very high and the need for stable results are highly desirable. Comparative studies have been carried out to compare the performance of the proposed framework with those earlier used methods, using real industrial reservoir data. Empirical results from simulation show that Type-2 FLS approach outperforms others in general and particularly in the area of stability and ability to handle data in uncertain situations, which are the common characteristics of well logs data. Another unique advantage of the newly proposed model is its ability to generate, in addition to the normal target forecast, prediction intervals as its by-products without extra computational cost. © 2010 ISAROB.

关键词： Membership functions

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