• Journal of Industrial Technology
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• v.20 no.B
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• pp.219-226
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• 2000

In this paper, we propose a new novel method for similarity search that supports time warping. Our primary goal is to innovate on search performance in large databases without false dismissal. To attain this goal, we devise a new distance function $D_{tw-lb}$ that consistently underestimates the time warping distance and also satisfies the triangular inequality. $D_{tw-lb}$ uses a 4-tuple feature vector extracted from each sequence and is invariant to time warping. For efficient processing, we employ a multidimensional index that uses the 4-tuple feature vector as indexing attributes and $D_{tw-lb}$ as a distance function. We prove that our method does not incur false dismissal. To verify the superiority of our method, we perform extensive experiments. The results reveal that our method achieves significant speedup up to 43 times with real-world S&P 500 stock data.

• Nonlinear Functional Analysis and Applications
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• v.28 no.3
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• pp.613-622
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• 2023

In this paper, finite element method is applied to solve boundary control problem governed by elliptic variational inequality with an infinite number of variables. First, we introduce some important features of the finite element method, boundary control problem governed by elliptic variational inequalities with an infinite number of variables in the case of the control and observation are on the boundary is introduced. We prove the existence of the solution by using the augmented Lagrangian multipliers method. A triangular type finite element method is used.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.21-27
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• 2020

This paper studies the impact of domestic and foreign economic activity on mobility among regions. The shortage of human resources and demand continues in Eastern Europeans. Especially Ukrainians, have entered the Polish labor market to make up for the scarce areas. As a result, Poland's supply and demand in Ukraine is disproportionate. Minimum wage increases are putting continued pressure on employers. Therefore, the regression equation in the form of job-seeker's economic activity ratio, y= AX²+B,(x=settlers) can be used to grasp the relationship between curves. According to the domestic and foreign workers who migrated, economic activities was rather than increasing the local population, the settlers of nearby large cities is more proportional. Empirical analysis has shown that the human resource hub has increased migration to large cities and industrial. The hub 'A'nation has been created for mobility in 4th wave re-industry, and the same re-industrialization (N₂) in other cities has attracted nearby human resources, but not settle. After all, the hub relationship between N₁ and N₂ is a mobile relationship. Due to wage inequality or a positive wellbeing chasm, workers are not settled plant area but a nearby city, or commuting between borders is easy to go into the hub central city. However, this proved on emerging from the relatively temporary settlers in the AI era.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.643-654
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• 2001

This paper discusses an effective processing of similarity search that supports time warping in large sequence database. Time warping enables finding sequences with similar patterns even when they are of different length, Previous methods fail to employ multi-dimensional indexes without false dismissal since the time warping distance does not satisfy the triangular inequality. They have to scan all the database, thus suffer from serious performance degradation in large database. Another method that hires the suffix tree also shows poor performance due to the large tree size. In this paper we propose a new novel method for similarity search that supports time warping Our primary goal is to innovate on search performance in large database without false dismissal. to attain this goal ,we devise a new distance function $D_{tw-Ib}$ consistently underestimates the time warping distance and also satisfies the triangular inequality, $D_{tw-Ib}$ uses a 4-tuple feature vector extracted from each sequence and is invariant to time warping, For efficient processing, we employ a distance function, We prove that our method does not incur false dismissal. To verify the superiority of our method, we perform extensive experiments . The results reveal that our method achieves significant speedup up to 43 times with real-world S&P 500 stock data and up to 720 times with very large synthetic data.

• Journal of Industrial Technology
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• v.21 no.A
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• pp.167-179
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• 2001

This paper discusses an index-based subsequence matching that supports time warping in large sequence databases. Time warping enables finding sequences with similar patterns even when they are of different lengths. In earlier work, we suggested an efficient method for whole matching under time warping. This method constructs a multidimensional index on a set of feature vectors, which are invariant to time warping, from data sequences. For filtering at feature space, it also applies a lower-bound function, which consistently underestimates the time warping distance as well as satisfies the triangular inequality. In this paper, we incorporate the prefix-querying approach based on sliding windows into the earlier approach. For indexing, we extract a feature vector from every subsequence inside a sliding window and construct a multi-dimensional index using a feature vector as indexing attributes. For query precessing, we perform a series of index searches using the feature vectors of qualifying query prefixes. Our approach provides effective and scalable subsequence matching even with a large volume of a database. We also prove that our approach does not incur false dismissal. To verily the superiority of our method, we perform extensive experiments. The results reseal that our method achieves significant speedup with real-world S&P 500 stock data and with very large synthetic data.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.23 no.2
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• pp.65-92
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• 2019

We survey a recently developed immersed finite element method (IFEM) for the interface problems. The IFEM uses structured grids such as uniform grids, even if the interface is a smooth curve. Instead of fitting the curved interface, the bases are modified so that they satisfy the jump conditions along the interface. The early versions of IFEM [1, 2] were suboptimal in convergence order [3]. Later, the consistency terms were added to the bilinear forms [4, 5], thus the scheme became optimal and the error estimates were proven. For elasticity problems with interfaces, we modify the Crouzeix-Raviart based element to satisfy the traction conditions along the interface [6], but the consistency terms are not needed. To satisfy the Korn's inequality, we add the stabilizing terms to the bilinear form. The optimal error estimate was shown for a triangular grid. Lastly, we describe the multigrid algorithms for the discretized system arising from IFEM. The prolongation operators are designed so that the prolongated function satisfy the flux continuity condition along the interface. The W-cycle convergence was proved, and the number of V-cycle is independent of the mesh size.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.173-184
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• 2002

This paper discuss an index-based subsequence matching that supports time warping in large sequence databases. Time warping enables finding sequences with similar patterns even when they are of different lengths. In earlier work, Kim et al. suggested an efficient method for whole matching under time warping. This method constructs a multidimensional index on a set of feature vectors, which are invariant to time warping, from data sequences. For filtering at feature space, it also applies a lower-bound function, which consistently underestimates the time warping distance as well as satisfies the triangular inequality. In this paper, we incorporate the prefix-querying approach based on sliding windows into the earlier approach. For indexing, we extract a feature vector from every subsequence inside a sliding window and construct a multidimensional index using a feature vector as indexing attributes. For query processing, we perform a series of index searches using the feature vectors of qualifying query prefixes. Our approach provides effective and scalable subsequence matching even with a large volume of a database. We also prove that our approach does not incur false dismissal. To verify the superiority of our approach, we perform extensive experiments. The results reveal that our approach achieves significant speedup with real-world S&P 500 stock data and with very large synthetic data.