Fast joins using join indices

Two new algorithms, “Jive join” and “Slam join,” are proposed for computing the join of two relations using a join index. The algorithms are duals: Jive join range-partitions input relation tuple ids and then processes each partition, while Slam join forms ordered runs of input relation tuple ids and then merges the results. Both algorithms make a single sequential pass through each input relation, in addition to one pass through the join index and two passes through a temporary file, whose size is half that of the join index. Both algorithms require only that the number of blocks in main memory is of the order of the square root of the number of blocks in the smaller relation. By storing intermediate and final join results in a vertically partitioned fashion, our algorithms need to manipulate less data in memory at a given time than other algorithms. The algorithms are resistant to data skew and adaptive to memory fluctuations. Selection conditions can be incorporated into the algorithms. Using a detailed cost model, the algorithms are analyzed and compared with competing algorithms. For large input relations, our algorithms perform significantly better than Valduriez's algorithm, the TID join algorithm, and hash join algorithms. An experimental study is also conducted to validate the analytical results and to demonstrate the performance characteristics of each algorithm in practice. Received July 21, 1997 / Accepted June 8, 1998     

面向对象数据库的查询转换成关系数据库的查询

文章基于从面向对象数据库(OODB)到关系数据库(RDB)的模式转换,提出了一种从面向对象数据库查询到关系数据库查询的转换算法。该算法主要针对关系数据库中不支持的,而面向对象数据库查询中特有的面向对象特征,诸如,类分层结构、类复合分层结构和集合属性,以及考虑由传统的关系运算来实现它们的语义的一般方法。这项研究的结果可以用于将关系数据库管理系统(RDBMS)升级为面向对象数据库管理系统(OODBMS),也可以用于面向对象数据库和关系数据库之间的互操作。     

Development of a Composite Knowledge Manipulation Tool: K-Expert

A goal of this study is to develop a Composite Knowledge Manipulation Tool (CKMT). Some of traditional medical activities are rely heavily on the oral transfer of knowledge, with the risk of losing important knowledge. Moreover, the activities differ according to the regions, traditions, experts’ experiences, etc. Therefore, it is necessary to develop an integrated and consistent knowledge manipulation tool. By using the tool, it will be possible to extract the tacit knowledge consistently, transform different types of knowledge into a composite knowledge base (KB), integrate disseminated and complex knowledge, and complement the lack of knowledge. For the reason above, I have developed the CKMT called as K-Expert and it has four advanced functionalities as follows. Firstly, it can extract/import logical rules from data mining (DM) with the minimum of effort. I expect that the function can complement the oral transfer of traditional knowledge. Secondly, it transforms the various types of logical rules into database (DB) tables after the syntax checking and/or transformation. In this situation, knowledge managers can refine, evaluate, and manage the huge-sized composite KB consistently with the support of the DB management systems (DBMS). Thirdly, it visualizes the transformed knowledge in the shape of decision tree (DT). With the function, the knowledge workers can evaluate the completeness of the KB and complement the lack of knowledge. Finally, it gives SQL-based backward chaining function to the knowledge users. It could reduce the inference time effectively since it is based on SQL query and searching not the sentence-by-sentence translation used in the traditional inference systems. The function will give the young researchers and their fellows in the field of knowledge management (KM) and expert systems (ES) more opportunities to follow up and validate their knowledge. Finally, I expect that the approach can present the advantages of mitigating knowledge loss and the burdens of knowledge transformation and complementation.     

Knowledge management systems and organizational knowledge processing challenges: A field experiment

This paper investigates the appropriateness of knowledge management system (KMS) designs for different organizational knowledge processing challenges. Building on the theory of task-technology fit (TTF), we argue that different KMS designs are more effective for different knowledge tasks. An exploratory field experiment was conducted in the context of Internet-based knowledge sharing services to provide empirical support for our hypotheses. The results of our experiment show that a KMS designed to support the goal GENERATE is more appropriate for divergent type knowledge problems because of its affordances for iterative brainstorming processes. Conversely, for convergent type knowledge processing challenges, a KMS with the goal CHOOSE that supports the ability to clarify and to analyze is more effective.     

A DSS For Modelling Logistic Chains in Freight Transport Policy Analysis

As the logistics activities of firms are becoming increasingly dynamic and global in nature, private and public decision makers depend more and more on information regarding the expected development of future freight flows. A newly developed Decision Support System (DSS) called SMILE (Strategic Model for Integrated Logistic Evaluations) produces forecasts of freight flows related to the Netherlands for a large number of products and modes of transport. The underlying model describes logistics chains at three levels: production, inventory and (multimodal) transportation. The second level accounts for warehousing by using integrated cost functions comprising handling, stockholding and transport costs, using a new segmentation of goods according to their logistical requirements. By means of a graphical user interface, the DSS assists the user with designing scenarios for simulations up to 25 years ahead and visualises the impacts of policy measures on freight flows and the environment. This paper describes the theory behind the model, characteristics of the DSS and potential policy applications.     

Decision support framework for risk management on sea ports and terminals using fuzzy set theory and evidential reasoning approach

As sea ports and terminals are valuable assets, in today’s uncertain and complex environment further refinements are needed to assess risks and prioritise protective measures for these critical pieces of logistics infrastructure. The major problem that port professionals (e.g. port risk managers and port auditors) are facing is the lack of an appropriate methodology and evaluation techniques to support their risk management (RM) cycle. Therefore in response to the uncertainties and to provide continuous risk control assurance in port industry, this paper uses fuzzy set theory (FST) to describe and evaluate the associated risk factors within the ports and terminals operations and management (PTOM). An evidential reasoning (ER) approach is employed to synthesise the information produced. These processes constitute a decision support framework that will be used to conduct port-to-port risk evaluations or to assess a whole port’s and terminal’s overall risk level in order to facilitate continuous improvement strategies. The proposed framework along with a generic methodology and a risk evaluation model is tested by a case study. The case study analyses pieces of three Southern Iranian ports by using an illustrative operational risk hierarchy. The sensitivity analysis carried out in this paper prove pieces of the applicability of the proposed methodology and model for risk evaluation of the sea ports and terminals in real situations.     

Inheritance rules for flexible model retrieval

Convenient model management requires flexible model retrieval. This paper presents a new flexible retrieval approach for mathematical model bases. The approach defines a multi-valued model inheritance relationship among models at a signature level. The inheritance provides a rich semantic information for the retrieval mechanism to refine inexact retrieval requirements. An inheritance rules reasoning system is proposed to enhance the ability and the efficiency of the model retrieval. The interface of the approach includes an SQL-like command, which enables users to retrieve their required models with inexact requirement expressions. The approach has been implemented in a rule-based mathematical model base system RMMBS. Application examples demonstrate the retrieval approach.     

Integrating scientific modeling and supporting dynamic hazard management with a GeoAgent-based representation of human–environment interactions: A drought example in Central Pennsylvania, USA

Recent natural disasters indicate that modern technologies for environmental monitoring, modeling, and forecasting are not well integrated with cross-level social responses in many hazard-management systems. This research addresses this problem through a Java-based multi-agent prototype system, GeoAgent-based Knowledge System (GeoAgentKS). This system allows: (1) computer representation of institutional regulations and behavioral rules used by multiple social institutions and individuals in cross-level human–environment interactions, (2) integration of this representation with scientific modeling of dynamic hazard development, and (3) application of automated reasoning that suggests to users the appropriate actions for supporting cooperative social responses. This paper demonstrates the software architecture of GeoAgentKS and presents such an integrated approach by modeling the drought management processes in Central Pennsylvania, USA. The results show that it is possible to use GeoAgentKS to represent multilevel human–environment interactions and to use those interactions as input to decision making in hazard management.     

Improving facility planning with decision technology systems

Facility planning is a complex process that requires art, science, and technology. Several methodologies have been generated to facilitate this process. Computer information systems (CIS) have been developed to deliver these methodologies and to provide knowledge relevant for effective facility planning. Since accurate decisions are required at each step of the process, the development effort has focused on CISs that support decision-making.Traditionally, the support has been provided in a segmented fashion and for separate phases of the decision-making process. To be absolutely effective, the support should be integrated and complete. There have been efforts to provide the required CIS support, but these systems have inherent conceptual shortcomings. Moreover, the newer and enhanced systems create additional problems that will prevent them from providing integrated support for all decision making phases in facility planning.This paper examines the facility planning process. Then traditional and enhanced information systems support is reviewed and the inherent shortcomings and unresolved integration problems are explained. Finally, an alternative approach, referred to as a Decision Technology System (DTS), is proposed to resolve the difficulties.     

Assessing water quality management options in the Upper Litani Basin, Lebanon, using an integrated GIS-based decision support system

The widespread and relentless discharge of untreated wastewater into the Upper Litani Basin (ULB) river system in Lebanon has reached staggering levels rendering its water unfit for most uses especially during the drier times of the year. Despite the call by governmental and non-governmental agencies to develop several wastewater treatment plants and sewage networks in an effort to control this problem, these efforts do not seem to be coordinated or based on comprehensive and integrated assessments of current and projected conditions in the basin.This paper provides an overview of the development and implementation of an integrated decision support system (DSS) designed to help policy makers and other stakeholders have a clearer understanding of the key factors and processes involved in the sewage induced degradation of surface water quality in the ULB, and formulate, assess and evaluate alternative management plans. The DSS is developed based on the WEAP model, which provides a GIS based and visual simulation environment and scenario management and analysis capabilities. The DSS was used to assess two main water quality management plans taking into consideration hydrological, spatial and seasonal variabilities. An incremental cost-effectiveness analysis was conducted to identify best buy plans. The results have confirmed the gravity of this problem and demonstrated the importance of taking immediate action on curbing this onslaught on this valuable and scarce fresh water resource.     

Hitting the wall: errors in developing and code inspecting a ‘simple' spreadsheet model

Field audits and experiments have found substantial error rates when students and professionals have built spreadsheet models. In this study, 102 undergraduate MIS majors and 50 MBA students developed a model from a word problem that was relatively simple and free of domain knowledge. Even so, 35% of their 152 models were incorrect. There was no significant difference in errors per model between undergraduates and MBAs. Even among the 17 MBAs with 250 h or more of experience, 24% of the models contained errors. The cell error rate (CER)—the percentage of cells with errors—was 2.0%. When 23 undergraduates attempted to audit their models through code inspection, only three with incorrect spreadsheets (15%) produced clean spreadsheets when they finished the audit.     

Modeling and analysis of the effects of QoS and reliability on pricing, profitability, and risk management in multiperiod grid-computing networks

In this paper we develop a network equilibrium model for optimal pricing and resource allocation in Computational Grid Network. We consider a general network economy model with Grid Resource Providers, Grid Resource Brokers and Grid Users. The proposed framework allows for the modeling and theoretical analysis of Computational Grid Markets that considers a non-cooperative behavior of decision-makers in the same tier of the grid computing network (such as, for example, Grid Resource Providers) as well as cooperative behavior between tiers (between Resource Providers and Grid Brokers). We introduce risk management into the decision making process by analyzing the decision-marker's reliability and quality of service (QoS) requirement. We analyze resource allocation patterns as well as equilibrium price based on demand, supply, and cost structure of the grid computing market network. We specifically answer the following questions with several numerical examples: How do system reliability levels affect the QoS levels of the service providers and brokers under competition? How do system reliability levels affect the profits of resource providers and brokers in a competitive market? How do system reliability levels influence the pricing of the services in a competitive environment? How do users' service request types, QoS requirements, and timing concerns affect users' behaviors, costs and risks in equilibrium? How does the market mechanism allocate resources to satisfy the demands of users? We find that for users who request same services certain timing flexibility can not only reduce the costs but also lower the risks. The results indicated that the value of QoS can be efficiently priced based on the heterogeneous service demands.     

Reliability enhancement of a radial distribution system using coordinated aggregation based particle swarm optimization considering customer and energy based indices

This paper describes an algorithm for optimum modifications for failure rate and repair time for a radial electrical distribution system. The modifications are with respect to a penalty cost function minimization. The cost function has been minimized subject to the energy based and customer oriented indices, i.e. AENS, SAIFI, SAIDI and CAIDI. Coordinated aggregation based particle swarm optimization (CAPSO) has been used for optimization. The algorithm has been implemented on a sample radial distribution system. The results obtained have been compared with those obtained using PSO.     

Decision Support Tool for energy-efficient,sustainable and integrated urban stormwater management

The use of Sustainable Drainage Systems (SuDS) to manage urban runoff and contribute to environmental and landscape improvement is now widely known, but its application is still limited in many regions, like in Mediterranean countries. In addition, there is a lack of Decision Support Tools that consider all their benefits in the decision making process in a clear and integrated holistic way.In this paper, the E²STORMED Decision Support Tool is presented. This tool analyses the impact of stormwater management in the urban environment and introduces energetic and environmental criteria in the decision making process. Therefore, it aims to fill in the existing “gap” between SuDS manuals and guidelines and regional and local decision makers, since it quantifies SuDS benefits and includes them in the comparison of different stormwater scenarios. Finally, the results of applying this tool to compare drainage infrastructures in a real urban development are described.     

Design and implementation of a GIS system for planning

Geographic information system (GIS) provides a flexible and efficient general platform for planning and analysis, especially when large amounts of ever changing spatial information is dealt with. It helps managing the change in an economical and sustainable way. We decided to build a GIS to help in data management and in the dynamic planning process of our developing university, Al-Balqa' Applied University (BAU). In this paper, we present the GIS system, which we built for the campus of BAU and the customization of the needed software to help in decision-making and planning processes. Moreover, the output of our project is web enabled so that it can be used in the web site of Al-Balqa' Applied University as a web GIS application.     

Choosing knowledge management strategies by using a combined ANP and DEMATEL approach

Numerous companies are expecting their knowledge management (KM) to be performed effectively in order to leverage and transform the knowledge into competitive advantages. However, here raises a critical issue of how companies can better evaluate and select a favorable KM strategy prior to a successful KM implementation. The KM strategy selection is a kind of multiple criteria decision-making (MCDM) problem, which requires considering a large number of complex factors as multiple evaluation criteria. A robust MCDM method should consider the interactions among criteria. The analytic network process (ANP) is a relatively new MCDM method which can deal with all kinds of interactions systematically. Moreover, the Decision Making Trial and Evaluation Laboratory (DEMATEL) not only can convert the relations between cause and effect of criteria into a visual structural model, but also can be used as a way to handle the inner dependences within a set of criteria. Hence, this paper proposes an effective solution based on a combined ANP and DEMATEL approach to help companies that need to evaluate and select KM strategies. Additionally, an empirical study is presented to illustrate the application of the proposed method.     

Development,analysis and applications of a quantitative methodology for assessing customer satisfaction using evolutionary optimization

Consumer-oriented companies are getting increasingly more sensitive about customer's perception of their products, not only to get a feedback on their popularity, but also to improve the quality and service through a better understanding of design issues for further development. However, a consumer's perception is often qualitative and is achieved through third party surveys or the company's recording of after-sale feedback through explicit surveys or warranty based commitments. In this paper, we consider an automobile company's warranty records for different vehicle models and suggest a data mining procedure to assign a customer satisfaction index (CSI) to each vehicle model based on the perceived notion of the level of satisfaction of customers. Based on the developed CSI function, customers are then divided into satisfied and dissatisfied customer groups. The warranty data are then clustered separately for each group and analyzed to find possible causes (field failures) and their relative effects on customer's satisfaction (or dissatisfaction) for a vehicle model. Finally, speculative introspection has been made to identify the amount of improvement in CSI that can be achieved by the reduction of some critical field failures through better design practices. Thus, this paper shows how warranty data from customers can be utilized to have a better perception of ranking of a product compared to its competitors in the market and also to identify possible causes for making some customers dissatisfied and eventually to help percolate these issues at the design level. This closes the design cycle loop in which after a design is converted into a product, its perceived level of satisfaction by customers can also provide valuable information to help make the design better in an iterative manner. The proposed methodology is generic and novel, and can be applied to other consumer products as well.     

Expeditious Modelling of Virtual Urban Environments with Geospatial L-systems

L-systems have been used in Computer Graphics, namely for modelling plants, as well as in a few experiments to model urban environments. However, the lack of geospatial awareness is a limitation and in spite of some developments like open L-systems, that introduced the ability to communicate with the environment, there was a need for more flexibility. This paper presents Geospatial L-systems, a new extension of L-systems that incorporates geospatial awareness, and shows an application in the area of expeditious modelling of urban environments. A modelling system, named XL3D, generates virtual urban environments automatically from a XML based document that contains a modelling specification and accesses data sources in an interoperable way. The integration of geospatial L-systems in this modelling system has increased the potential for automation and the potential to generate virtual urban environments with a higher level of detail and visual fidelity, with a lower level of complexity of the modelling processes. These facts are shown in a case study where a virtual urban environment, taken from an area in the Porto downtown, is generated by this solution.     

A framework for evaluating forest landscape model predictions using empirical data and knowledge

Evaluation of forest landscape model (FLM) predictions is indispensable to establish the credibility of predictions. We present a framework that evaluates short- and long-term FLM predictions at site and landscape scales. Site-scale evaluation is conducted through comparing raster cell-level predictions with inventory plot data whereas landscape-scale evaluation is conducted through comparing predictions stratified by extraneous drivers with aggregated values in inventory plots. Long-term predictions are evaluated using empirical data and knowledge. We demonstrate the applicability of the framework using LANDIS PRO FLM. We showed how inventory data were used to initialize the landscape and calibrate model parameters. Evaluation of the short-term LANDIS PRO predictions based on multiple metrics showed good overall performance at site and landscape scales. The predicted long-term stand development patterns were consistent with the established theories of stand dynamics. The predicted long-term forest composition and successional trajectories conformed well to empirical old-growth studies in the region.