Accessing database information using mobile agents

Many real-world applications on the Internet require accessing database information and typical technology employed is client/server plus Web (C/S + Web). Although past few years saw many success applications by using this technique, there are still some drawbacks that need to be overcome. One of the drawbacks is that the transaction often fails if the network connection is unstable. Another disadvantage is high bandwidth requirement and latency. This paper argues that mobile agent technology provide an easy way to overcome the shortcomings in CIS + Web in database access on the Internet. A success case study using mobile agents to admit new students to China's institutions is then presented. The mobile agent was created by using IBM's Aglets Software Development Kit (SDK). Based on the experimental results, it is evident that mobile agent technology is well suited for such applications.

An agent-based hybrid framework for database mining

While knowledge discovery in databases (KDD) is defined as an iterative sequence of the following steps: data pre-processing, data mining, and post data mining, a significant amount of research in data mining has been done, resulting in a variety of algorithms and techniques for each step. However, a single data-mining technique has not been proven appropriate for every domain and data set. Instead, several techniques may need to be integrated into hybrid systems and used cooperatively during a particular data-mining operation. That is, hybrid solutions are crucial for the success of data mining. This paper presents a hybrid framework for identifying patterns from databases or multi-databases. The framework integrates these techniques for mining tasks from an agent point of view. Based on the experiments conducted, putting different KDD techniques together into the agent-based architecture enables them to be used cooperatively when needed. The proposed framework provides a highly flexible and robust data-mining platform and the resulting systems demonstrate emergent behaviors although it does not improve the performance of individual KDD techniques.

Comparison of multifactor productivity indicators for real estate sectors using the OECD input-output database

"Research on the international comparison of productivity has gained significant interest throughout several previous decades. Relatively little work has however been done in the real estate sector. This paper aims to develop a new productivity measurement framework for the international comparison of the real estate sector based on the newly-published OECD input-output database. Three multifactor productivity indicators are formulated using the ratio of the sectoral final demand to value added, the intermediate output to intermediate input and the total output to total input effect respectively in the input-output table. Historical analyses and comparisons are also carried out to indicate the differences of productivities of the real estate sectors in seven selected countries. Findings can improve the understanding of how technological, organisational and policy influences combine to affect productivity growth and aid the policy makers, real estate agencies and researchers in evaluating the competitive ability of the real estate sector."

Economic indicator comparisons of international real estate sectors using the OECD input-output database

With its growing share in national economies, the real estate sector has been considered a vital contributor of economic development. Research efforts are needed in order to gain a better comprehension of the national specificities of the real estate sector and to identify its role in economic development. Due to limited comparable data, the economic indicators of real estate sectors are hard to compare between different countries. This paper aims to explore the quantitative interdependence amongst the real estate sector and other industries in developed economies using input-output analysis, and to investigate their significant linkages. Based on the recently published Organisation for Economic Co-operation and Development (OECD) input-output database at constant prices, the analysis focuses on the real estate's escalating role in terms ofshares in gross output, value added and gross national product. With emphasis on the relative role of manufacturing, construction and services inputs, this paper also highlights the strengths of the push and pull of the real estate sector.

Multifactor productivity measures of construction sectors using OECD input-output database

This research develops a new productivity measurement framework for the construction sector in the light of an input-output table. Three group multifactor productivity indicators are formulated based on the multiplier concepts in the input-output analysis. This measurement framework focuses on the intro-industry flows of products and considers the direct and indirect effects of input and output. Moreover, this framework enables us to measure the multifactor productivity of a specific sector systematically. Historical analyses and international comparisons are carried out to indicate the differences of the productivity of the construction sectors in seven selected countries, using the newly published OECD input-output database. Research findings are expected to clarify how technological, organizational and political factors affect the productivity growth, enabling the policy makers, construction businesses and researchers to quantify the competitive ability of the construction sector.

MDSM: microarray database schema matching using the Hungarian method

Current microarray databases use different terminologies and structures and thereby limit the sharing of data and collating of results between laboratories. Consequently, an effective integrated microarray data model is required. One important process to develop such an integrated database is schema matching. In this paper, we propose an effective schema matching approach called MDSM, to syntactically and semantically map attributes of different microarray schemas. The contribution from this work will be used later to create microarray global schemas. Since microarray data is complex, we use microarray ontology to improve the measuring accuracy of the similarity between attributes. The similarity relations can be represented as weighted bipartite graphs. We determine the best schema matching by computing the optimal matching in a bipartite graph using the Hungarian optimisation method. Experimental results show that our schema matching approach is effective and flexible to use in different kinds of database models such as; database schema, XML schema, and web site map. Finally, a case study on an existing public microarray schema is carried out using the proposed method.

A solution for fault tolerance in replicated database systems

A distributed database system is subject to site failure and link failure. This paper presents a reactive system approach to achieving fault tolerance in such a system. The reactive system concepts are an attractive paradigm for system design, development and maintenance because it separates policies from mechanisms. In the paper we give a solution using different reactive modules to implement the fault tolerant policies and the failure detection mechanisms. The solution shows that they can be separated without impact on each other; thus the system can adapt to constant changes in environments and user requirements.

Development of a food composition database for the estimation of dietary intakes of glucosinolates, the biologically active constituents of cruciferous vegetables

Evidence indicates that cruciferous vegetables are protective against a range of cancers with glucosinolates and their breakdown products considered the biologically active constituents. To date, epidemiological studies have not investigated the intakes of these constituents due to a lack of food composition databases. The aim of the present study was to develop a database for the glucosinolate content of cruciferous vegetables that can be used to quantify dietary exposure for use in epidemiological studies of diet–disease relationships. Published food composition data sources for the glucosinolate content of cruciferous vegetables were identified and assessed for data quality using established criteria. Adequate data for the total glucosinolate content were available from eighteen published studies providing 140 estimates for forty-two items. The highest glucosinolate values were for cress (389 mg/100 g) while the lowest values were for Pe-tsai chinese cabbage (20 mg/100 g). There is considerable variation in the values reported for the same vegetable by different studies, with a median difference between the minimum and maximum values of 5·8-fold. Limited analysis of cooked cruciferous vegetables has been conducted; however, the available data show that average losses during cooking are approximately 36 %. This is the first attempt to collate the available literature on the glucosinolate content of cruciferous vegetables. These data will allow quantification of intakes of the glucosinolates, which can be used in epidemiological studies to investigate the role of cruciferous vegetables in cancer aetiology and prevention.

Collecting quality data for database mining

Data collecting is necessary to some organizations such as nuclear power plants and earthquake bureaus, which have very small databases. Traditional data collecting is to obtain necessary data from internal and external data-sources and join all data together to create a homogeneous huge database. Because collected data may be untrusty, it can disguise really useful patterns in data. In this paper, breaking away traditional data collecting mode that deals with internal and external data equally, we argue that the first step for utilizing external data is to identify quality data in data-sources for given mining tasks. Pre- and post-analysis techniques are thus advocated for generating quality data.

Database access on the internet using mobile agent technology

Traditionally. accessing databases on the Internet is based on client/server paradigm (including web-based paradigm). However. there are some drawbacks when using the techniques. Mobile agent technology provides an excellent solution that can easily eliminate those disadvantages. By conducting a series of experiments and analyzing the experimental results, this paper presents in which circumstance mobile agents can outperform traditional client/server paradigm, and how they can overcome the shortcomings in client/server paradigm in database access on the Internet.

A solution for fault-tolerance in replicated database systems

A distributed database system is subject to site failure and link failure. This paper presents a reactive system approach to achieving the fault-tolerance in such a system. The reactive system concepts are an attractive paradigm for system design, development and maintenance because it separates policies from mechanisms. In the paper we give a solution using different reactive modules to implement the fault-tolerant policies and the failure detection mechanisms. The solution shows that they can be separated without impact on each other thus the system can adapt to constant changes in user requirements.

The cost of recovery protocols in web-based database systems

The cost of recovery protocols is important with respect to system performance during normal operation and failure in terms of overhead, and time taken to recover failed transactions. The cost of recovery protocols for web database systems has not been addressed much. In this paper, we present a quantitative study of cost of recovery protocols. For this purpose, we use an experiment setup to evaluate the performance of two recovery algorithms, namely the, two-phase commit algorithm and log-based algorithm. Our work is a step towards building reliable protocols for web database systems.

A novel middleware based web database model

In this paper, we propose a novel model for web-based database systems based on the multicast and anycast' protocols. In the model, we design a middleware, castway, which locates between the database server and the Web server. Every castway in a distributed system operates as a multicast node and an anycast node independently, respectively. The proposed mechanism can balance the workload among the distributed database servers, and offers the "best" server to serve for a query. Three algorithms are employed for the model: the requirement-based probing algorithm for anycast routing, the atomic multicast update algorithm for database synchronization, and the job deviation algorithm for system workload balance. The simulations and experiments show that the proposed model works very well.

CIDB: Chlamydia Interactive Database for cross-querying genomics, transcriptomics and proteomics data

Chlamydiae are important pathogens of humans, birds and a wide range of animals. They are a unique group of bacteria, characterized by their developmental cycle. Chlamydia has been difficult to study because of their obligate intracellular growth habit and lack of a genetic transformation system. However, the past 5 years has seen the full genome sequencing of seven strains of Chlamydia and a rapid expansion of genomic, transcriptomic (RT-PCR, microarray) and proteomic analysis of these pathogens. The Chlamydia Interactive Database (CIDB) described here is the first database of its type that holds genomic, RT-PCR, microarray and proteomics data sets that can be cross-queried by researchers for patterns in the data. Combining the data of many research groups into a single database and cross-querying from different perspectives should enhance our understanding of the complex cell biology of these pathogens. The database is available at: http://www3.it.deakin.edu.au:8080/CIDB/.