Table of Content

    28 April 2012, Volume 17 Issue 2 Previous Issue    Next Issue

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    Grafting Watermelon Seedling Production Management System Based
    on Process Control Strategy
    KE Shun-kuia,b(柯顺魁), DING Mingb(丁明), LI Leia,b (李磊) NIU Qing-liangb (牛庆良), HUANG Dan-fengb* (黄丹枫)
    2012, 17 (2):  129-134.  doi: 10.1007/s12204-012-1241-9
    Abstract ( 2033 )  
    Greenhouse environmental management, seedling bed scheduling, and fertilizer and water management
    are the core technologies of seedling nursery. Precision management and control of the whole production process
    guarantees high grated seedling quality. In order to improve management efficiency of grafted watermelon seedling
    production and seedling quality, this paper designs and develops a grafted watermelon seedling production management
    system based on process control methods by process control strategy, seedling bed planning design, and
    handheld device technology.
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    Ontology-Based Approach for Legal Provision Retrieval
    TANG Qi (唐琪), WANG Ying-lin* (王英林), ZHANG Ming-lu (张明禄)
    2012, 17 (2):  135-140.  doi: 10.1007/s12204-012-1242-8
    Abstract ( 1724 )  
    In this paper, we present an ontology-based approach for legal provision retrieval. The approach aims at assisting the man who knows little about legal knowledge to inquire appropriate provisions. Legal ontology and legal concept probability model are main functional components in our approach. Legal ontology is extracted from Chinese laws by the natural language processing (NLP) techniques. Legal concept probability model is built from corpus, and the model is used to bridge the gap between legal ontology and natural language inquiries.
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    A Relaxed-PPA Contraction Method for Sparse Signal Recovery
    FU Xiao-ling 1* (符小玲), WANG Xiang-feng 2 (王祥丰)
    2012, 17 (2):  141-146.  doi: 10.1007/s12204-012-1243-7
    Abstract ( 1418 )  
    Sparse signal recovery is a topic of considerable interest, and the literature in this field is already quite immense. Many problems that arise in sparse signal recovery can be generalized as a convex programming with linear conic constraints. In this paper, we present a new proximal point algorithm (PPA) termed as relaxed-PPA (RPPA) contraction method, for solving this common convex programming. More precisely, we first reformulate the convex programming into an equivalent variational inequality (VI), and then efficiently explore its inner structure. In each step, our method relaxes the VI-subproblem to a tractable one, which can be solved much more efficiently than the original VI. Under mild conditions, the convergence of the proposed method is proved. Experiments with l1 analysis show that RPPA is a computationally efficient algorithm and compares favorably with the recently proposed state-of-the-art algorithms.
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    Improved Global Context Descriptor for Describing Interest Regions
    LIU Jing-neng (刘景能), ZENG Gui-hua (曾贵华)
    2012, 17 (2):  147-152.  doi: 10.1007/s12204-012-1244-6
    Abstract ( 1444 )  
    The global context (GC) descriptor is improved for describing interest regions, uses gradient orientation for binning, and thus provides more robust invariance for geometric and photometric transformations. The performance of the improved GC (IGC) to image matching is studied through extensive experiments on the Oxford Affine dataset. Empirical results indicate that the proposed IGC yields quite stable and robust results, significantly outperforms the original GC, and also can outperform the classical scale-invariant feature transform (SIFT) in most of the test cases. By integrating the IGC to the SIFT, the resulting of hybrid SIFT+IGC performs best over all other single descriptors in these experimental evaluations with various geometric transformations.
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    Creation of Extension Knowledge Base System About Intelligent Detection in Dendrobium Huoshanense Photosynthesis Process
    LU Rong-dea * (卢荣德), BAO Yong-shengb (鲍永生), QIN Canb (秦璨), DING Xiang-yua (丁翔宇)
    2012, 17 (2):  153-160.  doi: 10.1007/s12204-012-1245-5
    Abstract ( 1328 )  
    Aiming at the limitations of the existing knowledge representations in intelligent detection, a novel extension-based knowledge representation (EKR) is proposed. The definitions, grammar rules, and formal semantics of EKR are presented. A rhombus solving strategy (RSS) based on EKR is discussed in detail, including creation of the problem oriented model, extension operator, the solution formation of contradictions problem and extended inference of matter-element. A knowledge base system based on EKR and RSS is developed, which is applied in intelligent detection in the Dendrobium huoshanense photosynthesis process (DHPP). More reasonable results are obtained than traditional rule-based system. The EKR is feasible in intelligent detection to solve the limitations of traditional knowledge representations.
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    Mining Evolving Association Rules for E-Business Recommendation
    LONG Shun (龙舜), ZHU Wei-heng (朱蔚恒)
    2012, 17 (2):  161-165.  doi: 10.1007/s12204-012-1246-4
    Abstract ( 1394 )  
    Association analysis is an effective data mining approach capable of unveiling interesting associations within a large dataset. Although widely adopted in e-business areas, it still has many difficulties when applied in practice. For instance, there is a mismatch between the static rules discovered and the drifting nature of the user interests, and it is difficult to detect associations from a huge volume of raw user data. This paper presents an effective approach to mine evolving association rules in order to tackle these problems. It is followed by a recommendation model based on the evolving association rules unveiled. Experimental results on an online toggery show that it can effectively unveil people’s shifting interests and make better recommendations accordingly.
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    Lattice-Valued Modal Propositional Logic Based on M-Lattice Implication Algebras
    LIU Yi (刘熠), LIU Jun (刘军), CHEN Shu-wei (陈树伟), XU Yang (徐扬)
    2012, 17 (2):  166-170.  doi: 10.1007/s12204-012-1247-3
    Abstract ( 1515 )  
    The modal lattice implication algebra (i. e., M-lattice implication algebra) is introduced and its properties are investigated. The modal lattice-valued propositional logical system is introduced by considering the M-lattice implication algebra as the valuation field, and the syntax and semantic of the logical system are discussed, respectively.
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    Research on Metamodels Consistency Verification Based on Formalization of Domain-Specific Metamodeling Language
    JIANG Tao (江涛), WANG Xin (王新)
    2012, 17 (2):  171-177.  doi: 10.1007/s12204-012-1248-2
    Abstract ( 1337 )  
    Domain-specific metamodeling language (DSMML) defined by informal method cannot strictly represent its structural semantics, so its properties such as consistency cannot be holistically and systematically verified. In response, the paper proposes a formal representation of the structural semantics of DSMML named extensible markup language (XML) based metamodeling language (XMML) and its metamodels consistency verification method. Firstly, we describe our approach of formalization, based on this, the method of consistency verification of XMML and its metamodels based on first-order logical inference is presented; then, the formalization automatic mapping engine for metamodels is designed to show the feasibility of our formal method.
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    Ideal Resolution Principle for Lattice-Valued First-Order Logic Based on Lattice Implication Algebra
    XU Wei-tao 1,3 (许伟涛), XU Yang 1,2(徐扬)
    2012, 17 (2):  178-181.  doi: 10.1007/s12204-012-1249-1
    Abstract ( 1315 )  
    As a continuate work, ideal-based resolution principle for lattice-valued first-order logic system LF(X) is proposed, which is an extension of α-resolution principle in lattice-valued logic system based on lattice implication algebra. In this principle, the resolution level is an ideal of lattice implication algebra, instead of an element in truth-value field. Moreover, the soundness theorem is given. In the light of lifting lemma, the completeness theorem is established. This can provide a new tool for automated reasoning.
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    TDRM: A Peer-to-Peer-Based Taxonomy Data Ring Model
    QIAO Bai-you (乔百友), WEI Yong (魏勇), WANG Xiao-yang (王潇杨) DING Lin-lin (丁琳琳), WANG Guo-ren (王国仁)
    2012, 17 (2):  182-189.  doi: 10.1007/s12204-012-1250-8
    Abstract ( 11805 )  
    Peer-to-peer (P2P) networks are widely used due to their good scalability and robustness. This paper considers the characteristics of data sources which use some taxonomy hierarchies to classify and organize their data objects, combines P2P techniques, and proposes a P2P based taxonomy data ring model (TDRM). The model makes full use of the semantic information contained in taxonomy hierarchies, places the data objects having similar semantics together, and organizes them into one dimensional ring structure. Super-peers dynamically join the ring according to the requirement. The routing connections among super-peers are created, which are similar to Chord ring, thus a semantics based structured super-peer network is formed. Experiments show that the model has good scalability and search efficiency.
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    Genetic Programming Using Dynamic Population Variation for Computational Efforts Reduction in System Modeling
    TAO Yan-yun1 (陶砚蕴), CAO Jian 1,2 (曹健), LI Ming-lu 1,2 (李明禄)
    2012, 17 (2):  190-196.  doi: 10.1007/s12204-012-1251-7
    Abstract ( 1482 )  
    In this paper, we propose genetic programming (GP) using dynamic population variation (DPV) with four innovations for reducing computational efforts. A new stagnation phase definition and characteristic measure are defined for our DPV. The exponential pivot function is proposed to our DPV method in conjunction with the new stagnation phase definition. An appropriate population variation formula is suggested to accelerate convergence. The efficacy of these innovations in our DPV is examined using six benchmark problems. Comparison among the different characteristic measures has been conducted for regression problems and the new proposed measure outperformed other measures. It is proved that our DPV has the capacity to provide solutions at a lower computational effort compared with previously proposed DPV methods and standard genetic programming in most cases. Meanwhile, our DPV approach introduced in GP could also rapidly find an excellent solution as well as standard GP in system modeling problems.
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    Skin Detection Method Based on Cascaded AdaBoost Classifier
    LU Wan (吕皖), HUANG Jie (黄杰)
    2012, 17 (2):  197-202.  doi: 10.1007/s12204-012-1252-6
    Abstract ( 2176 )  
    Skin detection has been considered as the principal step in many machine vision systems, such as face detection and adult image filtering. Among all these techniques, skin color is the most welcome cue because of its robustness. However, traditional color-based approaches poorly perform on the classification of skin-like pixels. In this paper, we propose a new skin detection method based on the cascaded adaptive boosting (AdaBoost) classifier, which consists of minimum-risk based Bayesian classifier and models in different color spaces such as HSV (hue-saturation-value), YCgCb (brightness-green-blue) and YCgCr (brightness-green-red). In addition, we have constructed our own database that is larger and more suitable for training and testing on filtering adult images than the Compaq data set. Experimental results show that our method behaves better than the state-ofthe- art pixel-based skin detection techniques on processing images with skin-like background.
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    Numeric-Based XML Labeling Schema by Generalized Dynamic Method
    NI Ye-feng (倪叶峰), FAN Yuan-chao (范远超), TAN Xin-cheng (谈昕澄) CUI Jin (崔锦), WANG Xiao-ling (王晓玲)
    2012, 17 (2):  203-208.  doi: 10.1007/s12204-012-1253-5
    Abstract ( 1449 )  
    Most efficient indeces and query techniques over XML (extensible markup language) data are based on a certain labeling scheme, which can quickly determine ancestor-descendant and parent-child relationship between two nodes. The current basic labeling schemes such as containment scheme and prefix scheme cannot avoid relabeling when XML documents are updated. After analyzing the essence of existing dynamic XML labels such as compact dynamic binary string (CDBS) and vector encoding, this paper gives a common unifying framework for the numeric-based generalized dynamic label, which can be implemented into a variety of dynamic labels according to the different user-defined value comparison methods. This paper also proposes a novel dynamic labeling scheme called radical sign label. Extensive experiments show that the radical sign label performs well for the initialization, insertion and query operations, and especially for skewed insertion where the storage cost of the radical sign label is better than that of former methods.
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    Design of Fuzzy Controller for Direct Drive Wind Turbines
    GUO Hong-che1,2 (郭洪澈), QIU Tian-yu3 (邱天雨), JIANG Jiu-chun1 (姜久春)
    2012, 17 (2):  209-214.  doi: 10.1007/s12204-012-1254-4
    Abstract ( 1136 )  
    Based on the research results of these years, this paper proposes a design of 3MW direct-driven wind generation inverter, and takes much effort in the control algorithm research and MATLAB simulation. Some wonderful results are obtained. All this may provide the reference for practical application. The fuzzy controllers are designed, based on fuzzy logic control theory, which can perfect control of wind generation system with no mathematic model. Models of permanent magnet synchronous generator (PMSG) and dual pulse width modulation (PWM) converter with their controllers are set by MATLAB/Simulink. In addition, experiments are made on the simulation platform of variable speed constant frequency (VSCF) wind power generation system. The behavior of dual PWM converter is demonstrated by simulations and experiment, and the control strategy is valid and correct.
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    Personalization Method of E-Catalog Based on User Interesting Degree
    NIE Gui-hua (聂规划), XU Shang-ying (徐尚英), CHEN Dong-lin (陈冬林)
    2012, 17 (2):  215-222.  doi: 10.1007/s12204-012-1255-3
    Abstract ( 1317 )  
    The user interesting degree evaluation index is designed to fulfill the users’ real needs, which includes the user’ attention degree of commodity, hot commodity and preferential commodity. User interesting degree model (UIDM) is constructed to justify the value of user interesting degree; the personalization approach is presented; operations of add and delete nodes (branches) are covered in this paper. The improved e-catalog is more satisfied to users’ needs and wants than the former e-catalog which stands for enterprises, and the improved one can complete the recommendation of related products of enterprises.
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    Energy-Saving Reputation Method for Wireless Sensor Networks
    WANG Fang 1 (王芳), WEI Zhe2 (魏哲)
    2012, 17 (2):  223-227.  doi: 10.1007/s12204-012-1256-2
    Abstract ( 1262 )  
    Reputation mechanism has been recently introduced into wireless sensor networks (WSNs) to overcome the deficiencies incurred by cryptography alone. Unlike most current reputation mechanisms that are based on binomial distribution and to some extent, do not give due attention to the aspect of energy constraint of WSNs, this research deduces and proves the feasibility that negative binomial distribution can well be used in the reputation update with distinctive energy-saving features. Comparison tests with respect to the energy consumption in terms of reputation computing frequencies are done between the traditional reputation method and the one in this study. Results show that our method can save more energy for the reputation update and thus can better meet the power constraints of WSNs.
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    Cooperative Threat Assessment of Multi-aircrafts Based on Synthetic Fuzzy Cognitive Map
    CHEN Jun 1 (陈军), YU Guan-hua 2 (俞冠华), GAO Xiao-guang 1 (高晓光)
    2012, 17 (2):  228-232.  doi: 10.1007/s12204-012-1257-1
    Abstract ( 1130 )  
    Threat assessment is one of the most important parts of the tactical decisions, and it has a very important influence on task allocation. An application of fuzzy cognitive map (FCM) for target threat assessment in the air combat is introduced. Considering the fact that the aircrafts participated in the cooperation may not have the same threat assessment mechanism, two different FCM models are established. Using the method of combination, the model of cooperative threat assessment in air combat of multi-aircrafts is established. Simulation results show preliminarily that the method is reasonable and effective. Using FCM for threat assessment is feasible. Key words: threat assessment| synthetic fuzzy cognitive map (FCM)| multi-aircrafts| cooperative air combat
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    Semantic Driven Design Reuse for 3D Scene Modeling
    CAO Xue (曹雪), CAI Hong-ming (蔡鸿明), BU Feng-lin (步丰林)
    2012, 17 (2):  233-236.  doi: 10.1007/s12204-012-1258-0
    Abstract ( 1231 )  
    The increasing scale and complexity of 3D scene design work urge an efficient way to understand the design in multi-disciplinary team and exploit the experiences and underlying knowledge in previous works for reuse. However the previous researches lack of concerning on relationship maintaining and design reuse in knowledge level. We propose a novel semantic driven design reuse system, including a property computation algorithm that enables our system to compute the properties while modeling process to maintain the semantic consistency, and a vertex statics based algorithm that enables the system to recognize scene design pattern as universal semantic model for the same type of scenes. With the universal semantic model, the system conducts the modeling process of future design works by suggestions and constraints on operation. The proposed framework empowers the reuse of 3D scene design on both model level and knowledge level.
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    Research of Scalability of the Belt-Type Sensor Networks
    XU Zhi-guang1 (徐志广), ZHU Lei-ji1 (朱磊基), SHI Yu-song1 (施玉松), JIANG hua2 (姜华)
    2012, 17 (2):  237-240.  doi: 10.1007/s12204-012-1259-z
    Abstract ( 1205 )  
    For the large-scale application requirements of the belt-type networks, the mathematical modeling as well as quantitative analysis for the scalability of the network based on average path length is completed in this paper, and the theorem for the scale scalability of the belt-type networks is derived. The theorem provides a calculation formula for the upper limit of node scale theory of the belt-type networks and a calculation formula for the upper limit of single node load theory.
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    Modeling of Additive Manufacturing Process Relevant Feature in Layer Based Manufacturing Process Planning
    LIU Xi-juan (刘溪涓)
    2012, 17 (2):  241-244.  doi: 10.1007/s12204-012-1260-6
    Abstract ( 1416 )  
    Compared with general machining processes, additive manufacturing (AM) process has stabler planning route and limited process variables and this makes it to be more easily designed and planned with knowledge based systems and computer aided techniques. Case based reasoning approach is applied to the process planning of additive manufacturing in this paper. The concept of “AM process relevant design features” is proposed after the analysis of the characteristics of AM processes. The concept is used as the basis of the knowledge representation, and AM relevant feature graph is used as the case representation schema. The case retrieval method is discussed based on this graph. The case representation of a machine arm is given to illustrate the brief process of the proposed approach.
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    Exploiting Empirical Variance for Data Stream Classification
    ZIA-UR REHMAN Muhammad1, LI Tian-rui1 (李天瑞), LI Tao2 (李涛)
    2012, 17 (2):  245-250.  doi: 10.1007/s12204-012-1261-5
    Abstract ( 1456 )  
    Classification, using the decision tree algorithm, is a widely studied problem in data streams. The challenge is when to split a decision node into multiple leaves. Concentration inequalities, that exploit variance information such as Bernstein’s and Bennett’s inequalities, are often substantially strict as compared with Hoeffding’s bound which disregards variance. Many machine learning algorithms for stream classification such as very fast decision tree (VFDT) learner, AdaBoost and support vector machines (SVMs), use the Hoeffding’s bound as a performance guarantee. In this paper, we propose a new algorithm based on the recently proposed empirical Bernstein’s bound to achieve a better probabilistic bound on the accuracy of the decision tree. Experimental results on four synthetic and two real world data sets demonstrate the performance gain of our proposed technique.
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    Analytical Solutions for Three-Dimensional Stability of Limited Slopes
    XIA Xiao-he(夏小和), HAN Chang-yu (韩长玉), WANG Jian-hua (王建华)
    2012, 17 (2):  251-256.  doi: 10.1007/s12204-012-1262-4
    Abstract ( 1305 )  
    A method of three-dimensional limited slope stability analysis is presented here based on the upperbound theorem of the limit analysis approach. A rotating collapse mechanism is considered in which energy dissipation takes place along curve velocity discontinuities. In the frictional soils, the failure surface has the shape of logarithm helicoids, with track outline defined by log-spirals. In the cohesive soils, the shape of the failure surface is torus. Angle is considered at slope top, and the critical height is less than top with no inclination. Numerical results of the proposed algorithm are presented in the form of nondimensional graphs. Some examples illustrate the practical use of the results.
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