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This paper describes a model that discovers association rules from a medical database to help doctors treat and diagnose a group of patients who show similar prehistoric medical symptoms. The proposed data mining procedure consists of two modules. The first is a clustering module that is based on a neural network, Adaptive Resonance Theory 2 (ART2), which performs affinity grouping tasks on a large...
Dissolved gas-in-oil analysis (DGA) is an important method to find the hidden or incipient insulation faults of oil-immersed power transformer. Matter element theory was employed to research the fault diagnosis of transformer with qualitative and quantity advantages. However, the method did not consider the uncertain essence of the fault diagnosis of transformer. And in the fact, there were two uncertain...
Ocean salinity and temperature variations have been observed for decades to clarify their effect to global climate changes. Data mining techniques are effective in extracting implicit and useful information from large databases. Discovering salinity and temperature variation patterns from Argo ocean data will in turn help reveal the spatio-temporal relationship between salinity and temperature variations...
Providing users with easy access to interesting information is one important goal of information retrieval. However, traditional information retrieval techniques are not suitable for ecological database queries since users are unable to clearly describe the target features. To overcome the problem, an information retrieval system running on handheld devices allowing users to issue queries according...
Concepts can add knowledge to the interpretation of image contents. However, mapping low-level features to high-level image semantics is still an ongoing challenge for researchers. In this paper an integrated model of fuzzy centrality and intensity concepts, together with the concept hierarchy is proposed to efficiently retrieving images. The self-organization feature map is applied to construct a...
Sensor networks have been widely applied to many fields, such as products management, museum guiding, and indoor positioning. PDAs can now be employed as a feasible companion for museum visitors. The positioning of sensors in a museum that allows suitable contents to be actively recommended to viewers in range is a practical issue that deserves investigation. In this paper, a fuzzy adaptive genetic...
A uni-stroke text input strategy for wheel input controls is proposed, such as the ones found on the series of ipod multimedia devices. The popularity of the ipod suggests that the wheel input paradigm is intuitive and usable. The proposed uni-strokes are based on circular motions that follow the contour of the wheel. Spatial mnemonics based on the shape of the alphabetic characters are used to minimise...
This paper presents a novel technique that can be used for fast indexing and retrieval of images based on their dominant texture features. Unlike the existing techniques that use computationally intensive texture features for content-based image retrieval, our proposed features are only derived from the DCT coefficients transformed from the Y-component in YUV color space. The dominant texture feature...
Image retrieval models based on visual perception have traditionally placed more emphasis on object shape than other image features. Indexing and retrieval techniques are two major concerns for efficient management of multimedia databases. In this paper, a new shape-based image retrieval model coupled with grey theory, a fuzzy hashing table and relevance feedback based on association rules is proposed...
Most of the previous studies on mining association rules focused on mining Boolean intra-transaction associations, i.e., the association rules among binary attributes within the same transaction where the notion of the transaction could be the items bought by the same customer. In this paper, we deal with the problem of mining association rules in databases containing quantitative attributes to discover...
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