• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1149-1157
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• 2017

The satisfiability problem is always a core problem in artificial intelligence (AI). And how to improve the efficiency of algorithms solving the satisfiability problem is widely concerned. Algorithm IER (Improved Extension Rule) is based on extension rule. The number of atoms and the number of clauses affect the efficiency of the algorithm IER. DPLL rules are helpful to reduce these numbers. Then a complete algorithm CIER based on splitting rule and extension rule is proposed in this paper in order to improve the efficiency. At first, the algorithm CIER (Complete Improved Extension Rule) reduces the scale of a clause set with DPLL rules. Then, the clause set is split into a group of small clause sets. In the end, the satisfiability of the clause set is got from these small clause sets'. A strategy MOAMD (maximum occurrences and maximum difference) for the algorithm CIER is given. With this strategy, a better arrangement of atoms could be got. This arrangement could make the number of small clause sets fewer and the scale of these sets smaller. So, the algorithm CIER will be more efficient.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.147-154
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• 2004

The purpose of this paper is to improve the existing phase split algorithm considering the minimum green time in COSMOS. In the case of a signalized intersection where two wide and narrow streets intersect each other, the time required for the pedestrian crossing is frequently longer than the time alloted to the through traffic on a minor street. In order to meet the minimum green time requirement for the pedestrian less time in alloted automatically to the left-turn traffic, creating heavy congestion on the left-turn approach. To solve this problem, this study suggests a new algorithm which shares the barrier using minimum green time and shares the burden with signal phases alloted to the crossing street traffic on the basis of the equal ratio of the degree of saturation, while maintaining the minimum green time requirement. The new algorithm was compared with the existing algorithm by using a microscopic simulation model for COSMOS evaluation developed at Ajou University. The simulation results show that the new algorithm produces better performance than the existing one.

• The Journal of the Acoustical Society of Korea
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• v.30 no.1
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• pp.1-8
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• 2011

This paper presents a method for improving the performance of ISF coefficients quantizer through compensating the defect of the split structure vector quantization using the ordering property of ISF coefficients. And design the ISF coefficients quantizer for wideband speech codec using proposed method. The wideband speech codec uses split structure vector quantizer which could not use the correlation between ISF coefficients fully to reduce complexity and the size of codebook. The proposed algorithm uses the ordering property of ISF coefficients to overcome the defect. Using the ordering property, the codebook redundancy could be figured out. The codebook redundancy is replaced by the adaptive-extended codebook to improve the performance of the quantizer through using the ordering property, ISF coefficient prediction and interpolation of existing codebook. As a result, the proposed algorithm shows that the adaptive-extended codebook algorithm could get about 2 bit gains in comparison with the existing split structure ISF quantizer of AMR-WB (G.722.2) in the points of spectral distortion.

• The KIPS Transactions:PartD
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• v.12D no.2 s.98
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• pp.233-246
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• 2005

To enhance the user response time of content-based retrieval service for multimedia information, several multi-dimensional index schemes have been proposed. M-tree, a well-known multidimensional index scheme is of metric space access method, and is based on the distance between objects in the metric space. However, since the overlap between index spaces of nodes might enlarge the number of nodes of M-tree accessed for query processing, the user response time for content-based multimedia information retrieval grows longer. In this paper, we propose a node split algorithm which is able to reduce the sire of overlap between index spaces of nodes in M-tree. In the proposed scheme, we choose a virtual center point as the routing object and entry redistribution as the postprocessing after node split in order to reduce the radius of index space of a node, and finally in order to reduce the overlap between the index spaces of routing nodes. From the experimental results, we can see the proposed split algorithm reduce the overlap between index space of nodes and finally enhance the user response time for similarity-based query processing.

• Smart Structures and Systems
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• v.10 no.3
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• pp.253-269
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• 2012

A split spectrum processing (SSP) method is proposed to accurately determine the time-of-flight (ToF) of damage-scattered waves by comparing the instantaneous amplitude variation degree (IAVD) of a wave signal captured from a damage case with that from the benchmark. The fundamental symmetrical ($S_0$) mode in aluminum plates without and with a notch is assessed. The efficiency of the proposed SSP method and Hilbert transform in determining the ToF of damage-scattered $S_0$ mode is evaluated for damage identification when the wave signals are severely contaminated by noise. Broadband noise can overwhelm damage-scattered wave signals in the time domain, and the Hilbert transform is only competent for determining the ToF of damage-scattered $S_0$ mode in a noise-free condition. However, the calibrated IAVD of the captured wave signal is minimally affected by noise, and the proposed SSP method is capable of determining the ToF of damage-scattered $S_0$ mode accurately even though the captured wave signal is severely contaminated by broadband noise, leading to the successful identification of damage (within an error on the order of the damage size) using a triangulation algorithm.

• Journal of Computing Science and Engineering
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• v.8 no.4
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• pp.207-214
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• 2014

In pedestrian detection applications, one of the most popular frameworks that has received extensive attention in recent years is widely known as a 'Hough forest' (HF). To improve the accuracy of detection, this paper proposes a novel split function to exploit the statistical information of the training set stored in each node during the construction of the forest. The proposed split function makes the trees in the forest more robust to noise and illumination changes. Moreover, the errors of each stage in the training forest are minimized using a global loss function to support trees to track harder training samples. After having the forest trained, the standard HF detector follows up to search for and localize instances in the image. Experimental results showed that the detection performance of the proposed framework was improved significantly with respect to the standard HF and alternating decision forest (ADF) in some public datasets.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.33-51
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• 1997

On ATM-based wired/wireless integrated network, we apply the connection re-routing method[1] which reduced the inter-cluster handoff delay by reserving VPI/VCLs for possible inter-cluster handoff calls in advance. Additionally, we propose wired resource reservation methods, which are ausiliary method and split method, for handoff QoS guarantee of various expected services. The characteristics of these methods reserve wired connection resources based on the information on the possible inter-cluster handoff calls. With mathematical analysis, we also propose each algorithm and cost function for deciding an optimal amount in reserving resources. With numberical examples, we can see that the auxiliary method effectively reduces the cost in all cases(.alpha.>.betha., .alpha.=.betha., and .alpha.<.betha.). The split method has a little cost-reduction effects, when handoffs call does not have priority over new calls (that is, .alpha..leq..betha.) and the total capacity is relatively large. In other cases, the split method, however, has effective cost-reduction effects. The numerical resutls show that these reservation methods ca flexibly cope with the time-variant environment and meet the QoS requriements on the inter-cluster handoff calls.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3338-3355
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• 2018

Images acquired by Large Aperture Static Imaging Spectrometer (LASIS) exhibit obvious interference stripes, which are vertical and stationary due to the special imaging principle of interference hyperspectral image (IHI) data. As the special characteristics above will seriously affect the intrinsic structure and sparsity of IHI, decomposition of IHI has drawn considerable attentions of many scientists and lots of efforts have been made. Although some decomposition methods for interference hyperspectral data have been proposed to solve the above problem of interference stripes, too many times of iteration are necessary to get an optimal solution, which will severely affect the efficiency of application. A novel algorithm for decomposition of interference hyperspectral images based on split Bregman iteration is proposed in this paper, compared with other decomposition methods, numerical experiments have proved that the proposed method will be much more efficient and can reduce the times of iteration significantly.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1259-1265
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• 2004

In many applications, producing labeled data is costly and time consuming while an enormous amount of unlabeled data is available with little cost. Therefore, it is natural to ask whether we can take advantage of these unlabeled data in classification teaming. In machine learning literature, the co-training method has been widely used for this purpose. However, the current co-training method requires the entire features to be split into two independent sets. Therefore, in this paper, we improved the current co-training method in a number of ways, and proposed a new co-training method which do not need the feature split. Experimental results show that our proposed method can significantly improve the performance of the current co-training algorithm.

• The KIPS Transactions:PartB
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• v.19B no.4
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• pp.221-224
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• 2012

The most famous algorithm of splitting and connecting Snake for extracting the boundary of multiple objects is the nearest method using the distance between snake points. It often can't split and connect Snake due to object topology. In this paper, its problem was discussed experimentally. The new algorithm using vector between Snake segment is proposed in order to split and connect Snake with complicated topology of objects. It is shown by experiment of two test images with 3 and 5 objects that the proposed one works better than the nearest one.