Soft Methodology for Cost-and-error Sensitive Classification

Many real-world data mining applications need varying cost for different types of classification errors and thus call for cost-sensitive classification algorithms. Existing algorithms for cost-sensitive classification are successful in terms of minimizing the cost, but can result in a high error rate as the trade-off. The high error rate holds back the practical use of those algorithms. In this paper, we propose a novel cost-sensitive classification methodology that takes both the cost and the error rate into account. The methodology, called soft cost-sensitive classification, is established from a multicriteria optimization problem of the cost and the error rate, and can be viewed as regularizing cost-sensitive classification with the error rate. The simple methodology allows immediate improvements of existing cost-sensitive classification algorithms. Experiments on the benchmark and the real-world data sets show that our proposed methodology indeed achieves lower test error rates and similar (sometimes lower) test costs than existing cost-sensitive classification algorithms. We also demonstrate that the methodology can be extended for considering the weighted error rate instead of the original error rate. This extension is useful for tackling unbalanced classification problems.Comment: A shorter version appeared in KDD '1

Investigation on the framework of heritage preservation in the context of sustainable development

Thesis (B.Sc)--University of Hong Kong, 2007.Includes bibliographical references (p. 79-85).published_or_final_versio

How do students from different disciplines perceive the concept of “data”?: A visual elicitation method

Transforming the iSquare draw-and-write technique into the dSquare draw-and-tell approach, we conducted synchronous online visual-elicitation inter-views with 37 college students in six different disciplines to examine how they perceived the concept of “data.” The preliminary findings showed that students across disciplines tend to use group diagrams to present ICT and print materials in their dSquares. When explaining their drawings, students typically relate to functional purposes in academic contexts. While students typically use data in coursework or other work-related contexts in a positive way, students in different disciplines consider data in different original forms and use different types of metaphors to express the concept of data. While science students tend to include files or lab tools and describe data processing through the tools, humanities and social science students tend to include texts or secondary sources and describe data processing or application through personal thinking. Future research suggestions are provided based on the findings

Lasing on nonlinear localized waves in curved geometry

The use of geometrical constraints opens many new perspectives in photonics and in fundamental studies of nonlinear waves. By implementing surface structures in vertical cavity surface emitting lasers as manifolds for curved space, we experimentally study the impacts of geometrical constraints on nonlinear wave localization. We observe localized waves pinned to the maximal curvature in an elliptical-ring, and confirm the reduction in the localization length of waves by measuring near and far field patterns, as well as the corresponding dispersion relation. Theoretically, analyses based on a dissipative model with a parabola curve give good agreement remarkably to experimental measurement on the transition from delocalized to localized waves. The introduction of curved geometry allows to control and design lasing modes in the nonlinear regime.Comment: 6 pages, 6 figure

The Source Detection of 28 September 2018 Sulawesi Tsunami by Using Ionospheric GNSS Total Electron Content Disturbance

The 28 September 2018 magnitude Mw7.8 Palu, Indonesia earthquake (0.178° S, 119.840° E, depth 13 km) occurred at 10:02 UTC. The major earthquake triggered catastrophic liquefaction, landslides, and a near-field tsunami. The ionospheric total electron content (TEC) derived from records of 5 ground-based global navigation satellite system (GNSS) receivers is employed to detect tsunami traveling ionospheric disturbances (TTIDs). In total, 15 TTIDs have been detected. The ray-tracing and beamforming techniques are then used to find the TTID source location. The bootstrap method is applied in order to further explore the possible location of the tsunami source based on results of the two techniques, which show the beamforming technique has a slightly better performance on finding possible locations of the tsunami source. Meanwhile, the circle method is employed to examine tsunami signatures of the sea-surface height and video records, and find possible tsunami origin locations. The coincidence of the TTID source location and the tsunami location shows that the ionospheric TEC recorded by local ground-based GNSS receivers can be used to confirm the tsunami occurrence, find the tsunami location, and support the tsunami early warning