• Journal of KIISE:Databases
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• v.37 no.1
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• pp.22-32
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• 2010

Location-based services have been expanded rapidly in local and overseas markets due to technological advances and increasing applications of wireless internet. Various researches have been made to manage efficiently the location information of moving objects. A basic location-based alert service provides alerting messages automatically when either entering or leaving a specific location and it is expected to become one of the most important location-based services. Location-based alert services require a location polling method to acquire current locations for a large number of moving objects. However, a simple periodical location polling method causes severe system overload because a system should keep updating location information of the moving objects ceaselessly. Most location polling algorithms for location-based alerting services are not suitable for mobile users with dynamic and unsteady moving patterns. In this paper, we propose an improved location polling algorithm for location-based alerting services to reduce the amount of location information acquisition and therefore, to decrease the system load. Various experiments show that the proposed algorithm outperforms other algorithms.

• Journal of Korea Spatial Information System Society
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• v.8 no.3
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• pp.89-103
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• 2006

Location-Based Services(LBS) has been varied and expanded rapidly in local and overseas markets due to technology developments and expanded applications of wireless internet. Location Based Alert Service(LBA) capable of automatically furnishing data when entering or outing a specific location is expected to become one of the most important services in LBS. For LBA operation, it is essential to periodically get location information about moving object. However, this can cause a serious system load because system should continuously and largely receive location information of many moving objects. Existing and current methods for location polling of moving object are not suitable for an efficient location acquisition and a search structure required for LBA. In this study, to acquire large-scaled location information for LBA, a MDR moving object location polling algorithm will be suggested to reduce unnecessary location information and decrease system load by using mobility patterns of moving object.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.371-384
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• 2019

Motion perception has been tremendously improved in neuroscience and computer vision. The baseline motion perception model is mediated by the dorsal visual pathway involving the cortex areas the primary visual cortex (V1) and the middle temporal (V5 or MT) visual area. However, few works have been done on the extension of neural models to improve the efficacy and robustness of motion perception of real sequences. To overcome shortcomings in situations, such as varying illumination and large displacement, an adaptive V1-MT motion perception (Ad-V1MTMP) algorithm enriched to deal with real sequences is proposed and analyzed. First, the total variation semi-norm model based on Gabor functions (TV-Gabor) for structure-texture decomposition is performed to manage the illumination and color changes. And then, we study the impact of image local context, which is processed in extra-striate visual areas II (V2), on spatial motion integration by MT neurons, and propose a V1-V2 method to extract the image contrast information at a given location. Furthermore, we take feedback inputs from V2 into account during the polling stage. To use the algorithm on natural scenes, finally, multi-scale approach has been used to handle the frequency range, and adaptive pyramidal decomposition and decomposed spatio-temporal filters have been used to diminish computational cost. Theoretical analysis and experimental results suggest the new Ad-V1MTMP algorithm which mimics human primary motion pathway has universal, effective and robust performance.