ESKD-A New Structure of Expert System Based on Knowledge Discovery

A new structure of ESKD (expert system based on knowledge discovery system KD (D&K)) is first presented on the basis of KD (D&K)-a synthesized knowledge discovery system based on double-base (database and knowledge base) cooperating mechanism. With all new features, ESKD may form a new research direction and provide a great probability for solving the wealth of knowledge in the knowledge base. The general structural frame of ESKD and some sub-systems among ESKD have been described, and the dynamic knowledge base based on double-base cooperating mechanism has been emphased on. According to the result of demonstrative experiment, the structure of ESKD is effective and feasible.     

A Semantic-based Clustering Method to Build Domain Ontology from Multiple Heterogeneous Knowledge Sources

IntroductionNowadays ,there are a large number of heterogeneousknowledge sources in an enterprise or a VirtualManufacturing Organization( VMO) . For example ,expertsystems , data warehouse , books , manuals , standards ,experts , and so on. Heterogeneity in knowledge sourcesare due to[1 4]:(1) Some are represented explicitly (eg.expert systems) ,some are represented i mplicitly as schemas of database ordata warehouse , while some are stored in experts brains .Implicitly represented knowledg…     

An Index mechanism for multi-scale view in spatial databases

There are numerous geometric objects stored in the spatial databases. An importance function in a spatial database is that users can browse the geometric objects as a map efficiently. Thus the spatial database should display te geometric objects users concern about swiftly onto the display window. This process includes two operations：retrieve data from database and then draw them onto screen. Accordingly,to improve the efficiency,we should try to reduce time of both retrieving object and displaying them. The former can be achieved with the aid of spatial index such as R-tree,the latter require to simplify the objects. Simplification means that objects are shown with sufficient but not with unnecessary detail which depend on the scale of browse. So the major problem is how to retrieve data at different detail level efficiently. This paper intrrduces the implementation of a multi-scale index in the spatial database SISP (Spatial Information Shared Platform ) which is generalized from R-tree. The difference between the generalization and the R-tree lies on two facets ： One is that every node and geometric object in the generalization is assigne+ with a importance value which +enote the importance of them,and every vertex in the objects are assigned with a importance value,too. The importance value can be use to decide which data should be retrieve from disk in a query. The other difference is that geometric objects in the generalization are divided into one or more sub-blocks,and vertexes are total ortiered by their importance value. With the help of the generalized R-tree,one can easily rtrieve data at differnt detail levels. Some experiments are performed on real-life data to evaluate the performance of solutions that separately use normal spatial index and multi-scale spatial index. The results show that the solution using multi-scale index in SISP is satisfying.     

Ontology-based Knowledge Extraction from Hidden Web

Hidden Web provides groat amount of domain-specific data for constructing knowledge services. Most previous knowledge extraction researches ignore the valuable data hidden in Web database, and related works do not refer how to make extracted information available for knowledge system. This paper describes a novel approach to build a domain-specific knowledge service with the data retrievedfrom Hidden Web, Ontology serves to model the domain knowledge. Queries forms of different Web sites aretranslated into machine-understandable format, defined knowledge concepts, so that they can be accessed automatically. Also knowledge data are extracted from Web pages and organized in ontology format knowledge. The experiment proves the algorithm achieves high accuracy and the system facilitates constructing knowledge services greatly.     

An Efficient Crash Recovery Technique for Real-Time Main Memory Database

This paper presents an efficient recovery scheme suitable for real-time main memory database. In the recovery scheme, log records are stored in non-volatile RAM which is divided into four different partitions based on transaction types. Similarly, a main memory database is divided into four partitions based data types. When the using ratio of log store area exceeds the threshold value, checkpoint procedure is triggered. During executing checkpoint procedure, some useless log records are deleted. During restart recovery after a crash, partition reloading policy is adopted to assure that critical data are reloaded and restored in advance, so that the database system can be brought up before the entire database is reloaded into main memory. Therefore down time is obvionsly reduced. Simulation experiments show our recovery scheme obviously improves the system performance,and does a favor to meet the deadlines of real-time transactions.     

Fast Visual Modeling for Plant Based on Real Images

Structures of natural plants are complex and difficult to model. This paper proposes a fast visual modeling for plants based on a small set of images, and establishes a reasonable plant model.Based on knowledge about growth patterns of the plant, image segmentation and 3D reconstruction are first performed to construct the plant skeleton (trunk and major branches), from which the remainder of the plant grows. Then the system produces the realistic plant model images based on image synthesis and validation. It is unnecessary to acquire the complex structure (such as the complex production rules of L-systems). The method provides a high degree of control over the final shape by image validation,resulting in realistic reconstruction.     

Research on methods of designing and building digital seabed database

With a review of the recent development in digitalization and application of seabed data, this paper systematically proposed methods for integrating seabed data by analyzing its feature based on ORACLE database management system and advanced techniques of spatial data management. We did research on storage structure of seabed data, distributed-integrated database system, standardized spatial database and seabed metadata management system in order to effectively manage and use these seabed information in practical application. Finally, we applied the methods researched and proposed in this paper to build the Bohai Sea engineering geology database that stores engineering geology data and other seabed information from the Bohai Sea area. As a result, the Bohai Sea engineering geology database can effectively integrate huge amount of distributed and complicated seabed data to meet the practical requisition of Bohai Sea engineering geology environment exploration and exploitation.     

Tracking data management using topology of moving object database system for moving object constrained trajectory in LBS application

Advances in wireless technologies and positioning technologies and spread of wireless devices,an interest in LBS (Location Based Service) is arising. To provide location based service,tracking data should have been stored in moving object database management system (called MODBMS) with proper policies and managed efficiently. So the methods which acquire the location information at regular time intervals then,store and manage have been studied. In this paper,we suggest tracking data management techniques using topology that is corresponding to the moving path of moving object. In our techniques,we update the MODBMS when moving object arrived at a street intersection or a curved road which is rpresented as the node in topology and predict the location at past and future with attribute of topology and linear function. In this technique,location data that are corresponding to the node in topology are stored,thus reduce the number of update and amount of data. Also in case predicting the location, because topology are used as well as existing location information,accuracy for prediction is increased than applying linear function or spline function.     

Broadcast Scheduling Strategy Based on the Priority of Real-Time Data in a Mobile Environment

Data broadcast is an important data dissemination approach in mobile environment. On broadcast channel, scalability and efficiency of data transmission are satisfied. In a mobile environment, there exists a kind of real-time database application in which both the transactions and data can have their timing constraints and priorities of different levels. In order to meet the requirement of real-time data disseminating and retrieving, a broadcast scheduling strategy HPF-ED F (Highest Priority First with Earlier Deadline and Frequency) is proposed under the BoD (Broadcast on Demand) model. Using the strategy, data items are scheduled according to their priority the transaction imposed on them or system set for them. The strategy also considers other characteristics of data items such as deadline and popularity of data. The extensive simulation experiments have been conducted to evaluate the performance of the proposed algorithm. Results show that it can achieve excellent performance compared with existing     

Broadcast Scheduling Strategy Based on the Priority of Real.Time Data in a Mobile Environment

Data broadcast is an important data dissemination approach in mobile environment. On broadcast channel,scalability and efficiency of data transmission are satisfied. In a mobile environment, there exists a kind of real-time database application in which both the transactions and data can have their timing constraints and priorities of different levels.In order to meet the requirement of real-time data disseminaring and retrieving, a broadcast scheduling strategy HPF-ED F (Highest Priority First with Earlier Deadline and Frequency) is proposed under the BoD (Broadcast on Demand) model. Using the strategy, data items are scheduled according to their priority the transaction imposed on them or system set for them. The strategy also considers other characteristics of data items such as deadline and popularity of data. The extensive simulation experiments have been conducted to evaluate the performance of the proposed algorithm. Results show that it can achieve excellent performance compared with existing strategies.     

A P2P load balancing-supported ID management algorithm

Load balancing is a critical issue in peer-to-peer networks. DHT (distributed hash tables) do not evenly partition the hash-function range, and some nodes get a larger portion of it. The loads of some nodes are as much as O(log n) times the average. In this paper, a low-cost, decentralized algorithm for ID allocation with complete knowledge in DHT-based system is proposed. It can adjust system load on nodes’ departure. It is proved that the ratio of longest arc to shortest arc is no more than 4 with high probability when network scale increases non-strictly. When network scale decreases from one stable state to another, algorithm can repair the unevenness of nodes distribution. The performance is analyzed in simulation. Simulating results show that updating messages only occupy a little of network bandwidth.     

Influence and hazard of disastrous space weather on power grid in China

Based on the measured data of geomagnetically induced currents(GIC) in Guangdong Ling’ao 500 kV power networks during several magnetic storms at the peak years of 23rd Solar Cycle,the GIC calculation results of 750 kV planning power grid in Shanxi,Gansu,Qinghai and Ningxia,the structure and characteristics of power networks from 500 kV to 1 000 kV,and super magnetic storm in 1859 are analyzed in this paper. Through the analysis,the possible impacts of extreme space weather on the future ultra-high voltage(UHV) grid,the security of large-scale power system in China are expounded,and the research suggestions coping with the strong solar storms are proposed.     

Disaster Reduction Decision Support System Against Debris Flows and Landslides Along Highway in Mountainous Area

Highways in mountainous areas are easy to be damaged by such natural disasters as debris flows and landslides and disaster reduction decision support system (DRDSS) is one of the important means to mitigate these disasters. Guided by the theories and technologies of debris flow and landslide reduction and supported by geographical information system (GIS), remote sensing and database techniques, a DRDSS against debris flow and landslide along highways in mountainous areas has been established on the basis of such principles as pertinence, systematicness, effectiveness, easy to use, open and expandability. The system consists of database, disaster analysis models and decisions on reduction of debris flows and landslides, mainly functioning to zone disaster dangerous degree, analyze debris flow activity,simulate debris flow deposition and diffusion, analyze landslide stability, select optimal highway renovation scheme and plan disaster prevention and control engineering. This system has been applied successfully to the debris flow and landslide treatment works along Palongzangbu Section of Siehuan-Tibet Highway.     

Study and Development of a Simulation System for Dynamic Evaluation on Man-machine Interface Design of Advanced Main Control Rooms of Nuclear Power Plants

Since the man-machine interfaces (MMI) of a main control room provide the control platform of a nuclear power plant (NPP),the development of the design quality of MMIs plays a very important role in the operation of a NPP. With the development of digital technology, the development of the advanced main control rooms (AMCRs) has become an inexorable trend. Therefore, the positive and the negative effects of AMCRs on human factors engineering need to be evaluated. For this p~, a simulation system has been studied and developed to quantitatively evaluate a MMI design from the viewpoint of human factors. The simulation system takes advantage of computer simulation technology to simulate an operating process of an interaction between operators and a MMI design under an instruction of an operation procedure of the AMCR of a NPP. Meanwhile, the necessary data are recorded for evaluation. It integrates two editors and one simulator. In the paper, the simulation system is presented in detail. Furthermore, one sample is given to show the results of each of these three subsystems.     

Support Operator＇s Fault Diagnosis of Complex Plant System through Multilevel Flow Model and Ecological Interface Design

The paper describes a new human-interface system design method by combining the conception of Multilevel Flow Model and Ecological Interface Design to support operators＇ fault diagnosis in the complex plant system. Modern man-made systems are always achieving many complex automatic and intelligent tasks so that they are becoming more and more complex and can be hardly understood by operators, who should be the primary role in system operating. This situation presents a big challenge to the operating support system that it should present the complex system in a direct and clear way to operators to and make operators understand the internal interaction of the system especially in the abnormal status to ensure the operating safety. The Multilevel Flow Model based on the idea of ＂Abstraction Hierarchy＂, aiming at decompressing a system by means-end and part-whole way, can be used to represent a complex system in a standard way and perform intelligent operating tasks such as fault diagnosis and process control. Ecological Interface Design, which based on the human cognitive properties, can present the internal interaction of the system in a direct way. This paper combines this two interface design conceptions to achieve two aspects, intelligent fault diagnosis and direct presentation of causal relationship of operating parameters, to support operators＇ fault diagnosis in complex plant system. The design method is applied to a PWR power plant in this paper as an application example.     

Quantitative Remote Sensing Study on Regional Soil Erosion —— Bin County of Heilongjiang as an Example

Based on Chinese soil loss equation （CSLE） model, this paper utilized technical advantages of RS and geographic information system （GIS） on data access and erosion factors database building to study prediction methods of regional soil erosion. The spatial analysis module of ARCGIS platform was applied to study the spatial distribution of erosion and the inter-relations of the factors influencing regional soil erosion in the research area. As a result, the mean soil erosion modulus of Bin County is 3 555.42 t/（km^2.a）, which suggests moderate degree erosion. The mean soil erosion modulus of clayey meadow soil is higher than those of dark brown soil and black soil. Vegetation factor values are between 0.1-0.2. The mean slope gradient and slope length values are respectively 1.335 and 6.061 which shows slope length is a dominant factor. And soil type, vegetation coverage and topographic factors have remarkable relevance to each other. Therefore, RS, GIS and CSLE are applicable in regional scale to disclose spatial distribution characteristics of soil erosion and to analyze the characteristics of dominant soil erosion factor quantitatively.     

Review of wideband MIMO channel measurement and modeling for IMT-Advanced systems

In October 2005,the next generation mobile communication system was officially named as the International Mobile Telecommunications-Advanced(IMT-Advanced) by the ITU Radiocommunication Sector(ITU-R).Wideband multiple input and multiple output(MIMO) channel models in multiple propagation environments are fundamental for IMT-Advanced systems and such research has been initiated since 2003.The research challenges come from the fact that the wider bandwidth(20-100 MHz) and the advanced multiple antenna technology have been proposed for the IMT-Advanced system,thus leading to higher sampling rates and multiple spatial propagation channels.In this review,four aspects of wideband MIMO channel measurement and modeling are discussed:(1) radio channel measurement procedure and equipment;(2) large scale fading models;(3) small scale fading models;and(4) MIMO channel models.In particular,the large scale fading affected by the carrier frequency is investigated for urban macrocells and it shows that the higher carrier frequency results in greater loss for non-line-of-sight(NLoS) conditions in the cities of China,for which the frequency dependent factor is 32.1.Moreover,the dense and the obviously higher buildings also lead to a larger angle spread(AS) of both the angle of arrival and angle of departure in urban macrocell scenarios.The results indicate that there is the potential to explore the MIMO technique for an IMT-Advanced system with larger ASs,which would lead to the high system capacity.The progress on MIMO models is described and some methods for simplifying geometry-based stochastic channel models(GBSM) are proposed.Finally future research topics on channel measurement and modeling are identified.     

Data Integration Strategy for Database Grids Based on P2P Framework

The differences between the data integration of a dynamic database grid （DBG） and that of a distributed database system are analyzed, and three kinds of data integration strategies are given on the background of DBG based on Peer to Peer （P2P） framework, including the centralized data integration （CDI） strategy, the distributed data integration （DDI） strategy and the filter-based data integration （FDDI） strategy. CDI calls all the database grid services （DGSs） at a single node, DDI disperses the DGSs to multiple nodes, while FDDI schedules the data integration nodes based on filtering the keywords returned from DGSs. The performance of these three integration strategies are compared with and analyzed by simulation experiments. FDDI is more evident for filtering the keywords with data redundancy increasing. Through the reduction of large amount of data transportation, it effectively shortens the executing time for the task and improves its efficiency.     

Knowledge Map Mining of Financial Data

The Knowledge Map (KM) concept, which was derived from the Fuzzy Cognitive Map (FCM), is used to describe and manage knowledge. KM provides insight into the interdependencies and uncertainties contained in the system. This paper uses a model-free method to mine KMs in historical data to analyze component stock corporations of the Shanghai Stock 50 index. The analyses use static and time-domain analyses. The results indicate that a knowledge map is useful for representing knowledge and for monitoring the health of companies. Furthermore, sudden changes of the key features of the KMs should be taken seriously by policymakers as an alarm of a crisis.     

KDD-based rolling schedule model for plate mill

A novel method for generating a rolling schedule is presented, which is fundamentally different from the existing ones.KDD (knowledge discovery in database) techniques are applied for discovering association rules between rolling parameters in a large database of rolling operation, and based on these rules, the schedule for the crucial last six finishing passes is generated. Operational evaluation shows that the schedule generated by the new method outperforms that generated by existing methods. It also shows how in this application the human's domain knowledge is applied to speed up the KDD process and to ensure the validity of the knowledge discovered.