A Conceptual Approach for Data Integration in Business Analytics

We present some basic concepts of a modelling environment for data integration in business analytics. Main emphasis is on defining a process model for the different activities occurring in connection with data integration, which allow later on assessment of the quality of the data. The model is based on combination of knowledge and techniques from statistical metadata management and from workflow processes. The modelling concepts are presented in a problem oriented formulation. The approach is embedded into an open model framework which aims for a modelling platform for all kinds of models useful in business applications.     

Towards True Dynamic Workflow for Emergency Response

Emergency management is a process by which all individuals, groups, and communities manage hazards in an effort to avoid or ameliorate the impact of disasters resulting from the hazards. Emergency response workflow is dynamic because there are lots of uncertainties with the course of hazard development and rescue effort. Existing dynamic workflow modeling technologies are not su±cient to describe the complex emergency response processes which are context aware and data-driven. In this paper, we propose an intelligent agent based approach to supporting the emergency response process management. The approach integrates BDI (Belief-Desire-Intention) agents with WIFA workflow model, which was developed in our previous work, to a powerful tool for truly dynamic workflow modeling and enactment. A BDI agent is an intelligent agent. Beliefs represent the informational state of the agent - in other words its beliefs about the world. Desires (or goals) represent the motivational state of the agent. They represent objectives or situations that the agent would like to accomplish or bring about. Intentions represent the deliberative state of the agent: what the agent has chosen to do. Intentions are desires to which the agent has to some extent committed. Workflows represent sequences of actions that an agent can perform to achieve one or more of its intentions. Based on this approach, we developed an emergency response training tool which is customizable for individual organization use and scalable to incident response settings from rural to urban domestically and foreign outposts for military applications, and can operate at a holistic exercise level.     

NONH:A New Cache-Based Coherence Protocol for Linked List Structure DSM System and Its Performance Evaluation

The management of memory coherence is an important problem in distributed shared memory(DSM)system.In a cache-based coherence DSM system using linked list structure,the key to maintaining the coherence and improving system performance is how to manage the owner in the linked list.This paper presents the design of a new management protocol-NONH(New-Owner New-Head)and its performance evaluation.The analysis results show that this protocol can improve the scalability and performence of a coherent DSM system using linked list.It is also suitable for managing the cache coherency in tree-like hierarchical architecture.     

Development of Wafer Warehouse Management System for Semiconductor Manufacturing Foundry Supply Chain

Efficiency of supply chains management mostly depends on the process coordination and information integration between the supply chain companies.The well-known integrated circuit design houses,the wafer fabrication industries, and the integrated circuit packaging/testing business has together formed a contiguous supply chain from materials to system in Taiwan during the past decades.Logistic management of the wafer hence becomes the key linkage in the semiconductor foundry supply chain.The objective of this paper is to develop the wafer warehouse management system for global wafer logistics.Current operations for wafer logistics management are firstly reviewed. The system requirements are analyzed by the model-driven business transformation approach.The business operation model and the platform-independent solution architecture for the wafer logistics management are constructed.A prototype information system is also developed for validation.Results of this research can improve the effectiveness and efficiency in wafer logistics management for the semiconductor foundry supply chain.     

Automatic Segmentation of News Items Based on Video and Audio Features

The automatic segmentation of news items is a key for implementing the automatic cataloging system of news video.This paper presents an approach which manages audio and video feature infomation to automatically segment news items.The integration of audio and visual analyses can overcome the weakness of the approach using only image analysis techniques.It makes the approach more adaptable to various situations of news items.The proposed approach detects silence segments in accompanying audio,and integrates them with shot segmentation results,as ewll as anchor shot detection results,to determine the boundaries among news items,Expeimental results show that the integration of audio and video features is an effective approach to solving the problem of automatic segmentation of news items.     

Improving the classification accuracy using biomarkers selected from machine learning methods

High-dimensional data encountered in genomic and proteomic studies are often limited by the sample size but has a higher number of predictor variables. Therefore selecting the most relevant variables that are correlated with the outcome variable is a crucial step. This paper describes an approach for selecting a set of optimal variables to achieve a classification model with high predictive accuracy. The work described using a biological classifier published elsewhere but it can be generalized for any application.     

Geometry Services Construction Based on Ontology towards Cooperative Design in Cloud Environment

APIs of CAD system could be encapsulated to construct web services so as to provide standard access interfaces for web-based cooperative design.However,lack of semantic supporting make integration of heterogeneous modelling system limited to operational level.On the purpose of carrying out cooperative design in a flexible cloud environment,an intelligent and effective support mechanism is needed for mass and complex interaction in cooperative work.Therefore,Ontology-based Geometry Modeling Services Environment (OGMSE) is provided to realize a knowledge-level geometry modeling so as to supported semantic 3D model management and intelligent operation support.First,CAD APIs are encapsulated into web service for web invocation.Then,ontology contained structural semantic and operational semantic is built for management of models and modeling process.Lastly,conception-driven modeling mechanism is built to invocate service according to interaction requirement,thus to realize conception-level cooperative design.Based on an open geometry engine,a prototype system has been developed.The result shows that the approach provides a reference direction for large-scale application on the network.     

Modeling in Multi-Resolution and Its Applications

It is becoming common for many designers to work together on very complex assemblies in a collaborative environment. To work efficiently in this environment, the capabilities to simplify the portions of an assembly and to reset it to the original resolution should be added to the current CAD systems. Thus operators realizing multi-resolution on B-rep were proposed in previous work. This paper illustrates a prototype multi-resolution system to integrate the proposed operators and its applications. The multi-resolution system can be used in similarity comparisons to reduce the calculation load and to get the full comparison result in the overall shape. Then the features recognized with this system can be used in more detailed comparisons. This system also can be used conceptually to solve security problems in collaborative design.     

An IconMap-based exploratory analytical approach for multivariate geospatial data

This paper discusses an iconmap-based visualization technique that enables multiple geospatial variables to be illustrated in a single GIS raster layer.This is achieved by extending the conventional pixelbased data structure to an iconic design.In this way,spatial patterns generated by the interaction of geographic variables can be disclosed,and geospatial information mining can be readily achieved.As a case study,a visual analysis of soil organic matter and soil nutrients for Shuangliu County in the city of Chengdu,China,was undertaken using the prototype IconMapper software,developed by the authors.The results show that the static IconMap can accurately exhibit trends in the distribution of organic matter and nutrients in soil.The dynamic iconmap can both reflect interaction patterns between organic matter and the nutrient variables,and display soil fertility levels in a comprehensive way.Thus,the iconmap-based visualization approach is shown to be a non-fused,exploratory analytical approach for multivariate data analysis and as a result is a valuable method for visually analyzing soil fertility conditions.     

2DCMA: An Effective Maintenance Algorithm of Materialized Views in Peer Data Management Systems

Update management is very important for data integration systems. So update management in peer data management systems （PDMSs） is a hot research area. This paper researches on view maintenance in PDMSs. First, the definition of view is extended and the peer view, local view and global view are proposed according to the requirements of applications. There are two main factors to influence materialized views in PDMSs. One is that schema mappings between peers are changed, and the other is that peers update their data. Based on the requirements, this paper proposes an algorithm called 2DCMA, which includes two sub-algorithms： data and definition consistency maintenance algorithm% to effectively maintain views. For data consistency maintenance, Mork＇s rules are extended for governing the use of updategrams and boosters. The new rule system can be used to optimize the execution plan. And are extended for the data consistency maintenance algorithm is based on the new rule system. Furthermore, an ECA rule is adopted for definition consistency maintenance. Finally, extensive simulation experiments are conducted in SPDMS. The simulation results show that the 2DCMA algorithm has better performance than that of Mork＇s when maintaining data consistency. And the 2DCMA algorithm has better performance than that of centralized view maintenance algorithm when maintaining definition consistency.     

Process-Driven Software Development Methodology for Enterprise Information System

In today＇s process-centered business organization, it is imperative that enterprise information system must be converted from task-centered to process-centered system. However, traditional software development methodology is function-oriented, in which each function manages its own data and it results in redundancy because data that belongs to one object are stored by several functions. Proposed in this paper is a process-driven software development methodology, in which business process is a major concern and workflow functionalities are identified and specified throughout the entire development life cycle. In the proposed methodology, the development process, modeling tools and deliverables are clarified explicitly. Proposed methodology can be a guideline to practitioners involved in enterprise software development, of which workflow is an essential part.     

Cyber-physical-social-thinking space based science and technology framework for the Internet of Things

The Internet of Things(Io T)as an emerging network paradigm is bringing the next scientific and technological revolution for ubiquitous things’interactions in cyber-physical-social spaces.The Io T influences the current science and technology system by enabling its relatively stable interrelations for an inevitable architecture reconfiguration.In this paper,we aim to explore an updated science and technology framework for the Io T.Particularly,a novel cyber-physical-social-thinking(CPST)space is established by involving an attractive concept of the Internet of Thinking(Io Tk),and a science and technology framework is accordingly proposed referring to both scientific aspect(i.e.,cyber-physical,social,and noetic sciences)and technological aspect(i.e.,fundamental,physical,cyber,and social technologies).According to the perspective of the traditional Chinese culture,we explain the established science and technology framework,in which the"Five Elements"(i.e.,wood,fire,earth,metal,and water)have common properties with the restructured cyber-physical science in the Io T.Moreover,we introduce a scenario of smart city to identify the technological aspect in the Io T,and discuss the key enabling technologies,including resource management,energy management,data management,session management,security and privacy,loop control,space-time consistency,nanotechnology,and quantum technology.It turns out that the established science and technology framework will launch an innovation for academia and industry communities.     

Spatial Data Mining to Support Environmental Management and Decision Making--A Case Study in Brazil

The growth of geo-technologies and the development of methods for spatial data collection have resulted in large spatial data repositories that require techniques for spatial information extraction, in order to transform raw data into useful previously unknown information. However, due to the high complexity of spatial data mining, the need for spatial relationship comprehension and its characteristics, efforts have been directed towards improving algorithms in order to provide an increase of performance and quality of results. Likewise, several issues have been addressed to spatial data mining, including environmental management, which is the focus of this paper. The main original contribution of this work is the demonstration of spatial data mining using a novel algorithm with a multi-relational approach that was applied to a database related to water resource from a certain region of S~o Paulo State, Brazil, and the discussion about obtained results. Some characteristics involving the location of water resources and the profile of who is administering the water exploration were discovered and discussed.     

Scalable SaaS Indexing Algorithms with Automated Redundancy and Recovery Management

Software-as-a-Service (SaaS) is a new software delivery model with Multi-Tenancy Architecture (MTA). An SaaS system is often mission critical as it often supports a large number of tenants, and each tenant supports a large number of users. This paper proposes a scalable index management algorithm based on B+ tree but with automated redundancy and recovery management as the tree maintains two copies of data. The redundancy and recovery management is done at the SaaS level as data are duplicated with tenant information rather than at the PaaS level where data are duplicated in chunks. Using this approach, an SaaS system can scale out or in based on the dynamic workload. This paper also uses tenant similarity measures to cluster tenants in a multi-level scalability architecture where similar tenants can be grouped together for effcient processing. The scalability mechanism also includes an automated migration strategies to enhance the SaaS performance. The proposed scheme with automated recovery and scalability has been simulated, the results show that the proposed algorithm can scale well with increasing workloads.     

Combining search space partition and abstraction for LTL model checking

The state space explosion problem is still the key obstacle for applying model checking to systems of industrial size. Abstraction-based methods have been particularly successful in this regard. This paper presents an approach based on refinement of search space partition and abstraction which combines these two techniques for reducing the complexity of model checking. The refinement depends on the representation of each portion of search space. Especially, search space can be refined stepwise to get a better reduction. As reported in the case study, the integration of search space partition and abstraction improves the efficiency of verification with respect to the requirement of memory and obtains significant advantage over the use of each of them in isolation.     

Hanzix and Chinese Open System Platform

International use of the UNIX system in recent years provokes a need to expand its functionality.Extensions are needed to process data in various languages as the market requirement dictate^[1,2].With the advent of open systems and interfaces.the method of internationalization(I18N)has become standardized.Hanzix Association was founded by the Institute of Software,The Chinese Academy of Sciences(ISAS,Beijing),Institute of Information Industry ( Ⅲ，Taipei)and Chinese University of Hong Kong(CUHK,Hong Kong),and its aim is to promote an open system standard for Chinese character(Hanzi)processing.This paper presents Hanzix,an open system environment to support Hanzi processing,including enhancement recommended for Hanzi API,input method mechanism codeset conversion and announcement,and reviews the current work.     

An architectural model for intelligent network management

Traditional network management approach involves the management of each vendor‘s equipment and networkd segment in isolation through its own proprietary element management system.It is necessary to set up a new network management architecture that calls for operation consolidation across vendor and technology boundaries.In this paper,an architerctural model for Intelligent Network Management(INM)is presented.The INM system includes a manager system,which controls all subsystems and coordinates different management tasks;an expert system,which is responsible for handling particularly difficult problems,and intelligent agents,which bring the management closer to applications and user requirements by spreading intellignet agents through network segments or domain.In the expert system model proposed,especially an intellignet fault management system is given.The architectural model is to build the INM system to meet the need of managing modern network systems.     

Active resilient defense control against false data injection attacks in smart grids

The emerging of false data injection attacks (FDIAs) can fool the traditional detection methods by injecting false data, which has brought huge risks to the security of smart grids. For this reason, a resilient active defense control scheme based on interval observer detection is proposed in this paper to protect smart grids. The proposed active defense highlights the integration of detection and defense against FDIAs in smart girds. First, a dynamic physical grid model under FDIAs is modeled, in which model uncertainty and parameter uncertainty are taken into account. Then, an interval observer-based detection method against FDIAs is proposed, where a detection criteria using interval residual is put forward. Corresponding to the detection results, the resilient defense controller is triggered to defense the FDIAs if the system states are affected by FDIAs. Linear matrix inequality (LMI) approach is applied to design the resilient controller with H_{{\infty }} performance. The system with the resilient defense controller can be robust to FDIAs and the gain of the resilient controller has a certain gain margin. Our active resilient defense approach can be built in real time and show accurate and quick respond to the injected FDIAs. The effectiveness of the proposed defense scheme is verified by the simulation results on an IEEE 30-bus grid system.     

An Ontology-Based Approach for Semantic Conflict Resolution in Database Integration

An important task in database integration is to resolve data conflicts, on both schema-level and semantic-level. Especially difficult the latter is. Some existing ontology-based approaches have been criticized for their lack of domain generality and semantic richness. With the aim to overcome these limitations, this paper introduces a systematic approach for detecting and resolving various semantic conflicts in heterogeneous databases, which includes two important parts： a semantic conflict representation model based on our classification framework of semantic conflicts, and a methodology for detecting and resolving semantic conflicts based on this model. The system has been developed, experimental evaluations on which indicate that this approach can resolve much of the semantic conflicts effectively, and keep independent of domains and integration patterns.     

Chinese question-answering system

Traditional Chinese text retrieval systems return a ranked list of documents in response to a user‘s request. While a ranked list of documents may be an appropriate response for the user, frequently it is not.Usually it would be better for the system to provide the answer itself instead of requiring the user to search for the answer in a set of documents. Since Chinese text retrieval has just been developed lately, and due to various specific characteristics of Chinese language, the approaches to its retrieval are quite different from those studies and researches proposed to deal with Western language. Thus, an architecture that augments existing search engines is developed to support Chinese natural language question answering. In this paper a new approach to building Chinese question-answering system is described, which is the general-purpose, fully-automated Chinese question-answering system available on the web. In the approach, we attempt to represent Chinese text by its characteristics, and try to convert the Chinese text into ERE (E: entity, R: relation) relation data lists, and then to answer the question through ERE relation model. The system performs quite well giving the simplicity of the techniques being utilized. Experimental results show that question-answering accuracy can be greatly improved by analyzing more and more matching ERE relation data lists. Simple ERE relation data extraction techniques work well in our system making it efficient to use with many backend retrieval engines.