• Nuclear Engineering and Technology
• /
• v.41 no.8
• /
• pp.995-1004
• /
• 2009

The Advanced Power Reactor 1400 (APR1400) is an evolutionary advanced light water reactor (ALWR) based on the Optimized Power Reactor 1000 (OPR1000), which is in operation in Korea. The APR1400 incorporates a variety of engineering improvements and operational experience to enhance safety, economics, and reliability. The advanced design features and improvements of the APR1400 design include a pilot operated safety relief valve (POSRV), a four-train safety injection system with direct vessel injection (DVI), a fluidic device (FD) in the safety injection tank, an in-containment refueling water storage tank (IRWST), an external reactor vessel cooling system, and an integrated head assembly (IHA). Development of the APR1400 started in 1992 and continued for ten years. The APR1400 design received design certification from the Korean nuclear regulatory body in May of2002. Currently, two construction projects for the APR1400 are in progress in Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.10
• /
• pp.3972-3988
• /
• 2020

Existing methods always rely on statistical features to extract local words for microblog user geolocation. There are many non-local words in extracted words, which makes geolocation accuracy lower. Considering the statistical and semantic features of local words, this paper proposes a microblog user geolocation method by extracting local words based on word clustering and wrapper feature selection. First, ordinary words without positional indications are initially filtered based on statistical features. Second, a word clustering algorithm based on word vectors is proposed. The remaining semantically similar words are clustered together based on the distance of word vectors with semantic meanings. Next, a wrapper feature selection algorithm based on sequential backward subset search is proposed. The cluster subset with the best geolocation effect is selected. Words in selected cluster subset are extracted as local words. Finally, the Naive Bayes classifier is trained based on local words to geolocate the microblog user. The proposed method is validated based on two different types of microblog data - Twitter and Weibo. The results show that the proposed method outperforms existing two typical methods based on statistical features in terms of accuracy, precision, recall, and F1-score.

• Bulletin of the Korean Space Science Society
• /
• 2001.11a
• /
• pp.43-43
• /
• 2001

• Journal of the Korean Society of Industry Convergence
• /
• v.17 no.1
• /
• pp.27-34
• /
• 2014

This paper proposes a new approach to the designed of visual feedback control system based on visual servoing method. The main focus of this paper is presented how it is effective to use many features for improving the accuracy of the visual feedback control of industrial articulated robot for assembling and inspection of parts. Some rank conditions, which relate the image Jacobian, and the control performance are derived. It is also proven that the accuracy is improved by increasing the number of features. The effectiveness of redundant features is verified by the real time experiments on a SCARA type robot(FARA) made in samsung electronics company.

• Journal of Computing Science and Engineering
• /
• v.9 no.4
• /
• pp.204-213
• /
• 2015

Under the conditional independence assumption among local features, the Naive Bayes Nearest Neighbor (NBNN) classifier has been recently proposed and performs classification without any training or quantization phases. While the original NBNN shows high classification accuracy without adopting an explicit training phase, the conditional independence among local features is against the compositionality of objects indicating that different, but related parts of an object appear together. As a result, the assumption of the conditional independence weakens the accuracy of classification techniques based on NBNN. In this work, we look into this issue, and propose a novel Bayesian network for an NBNN based classification to consider the conditional dependence among features. To achieve our goal, we extract a high-level feature and its corresponding, multiple low-level features for each image patch. We then represent them based on a simple, two-level layered Bayesian network, and design its classification function considering our Bayesian network. To achieve low memory requirement and fast query-time performance, we further optimize our representation and classification function, named relation-based Bayesian network, by considering and representing the relationship between a high-level feature and its low-level features into a compact relation vector, whose dimensionality is the same as the number of low-level features, e.g., four elements in our tests. We have demonstrated the benefits of our method over the original NBNN and its recent improvement, and local NBNN in two different benchmarks. Our method shows improved accuracy, up to 27% against the tested methods. This high accuracy is mainly due to consideration of the conditional dependences between high-level and its corresponding low-level features.

• The Journal of the Acoustical Society of Korea
• /
• v.21 no.4E
• /
• pp.156-163
• /
• 2002

We apply independent component analysis (ICA) for extracting an optimal basis to the problem of finding efficient features for representing speech signals of a given speaker The speech segments are assumed to be generated by a linear combination of the basis functions, thus the distribution of speech segments of a speaker is modeled by adapting the basis functions so that each source component is statistically independent. The learned basis functions are oriented and localized in both space and frequency, bearing a resemblance to Gabor wavelets. These features are speaker dependent characteristics and to assess their efficiency we performed speaker identification experiments and compared our results with the conventional Fourier-basis. Our results show that the proposed method is more efficient than the conventional Fourier-based features in that they can obtain a higher speaker identification rate.

• Journal of Korea Multimedia Society
• /
• v.18 no.11
• /
• pp.1268-1280
• /
• 2015

In video surveillance system, the exposure of a person's face is a serious threat to personal privacy. To protect the personal privacy in large amount of videos, an automatic face detection method is required to locate and mask the person's face. However, in real-world surveillance videos, the effectiveness of existing face detection methods could deteriorate due to large variations in facial appearance (e.g., facial pose, illumination etc.) or degraded face (e.g., occluded face, low-resolution face etc.). This paper proposes a new face detection method based on multi-level facial features. In a video frame, different kinds of spatial features are independently extracted, and analyzed, which could complement each other in the aforementioned challenges. Temporal domain analysis is also exploited to consolidate the proposed method. Experimental results show that, compared to competing methods, the proposed method is able to achieve very high recall rates while maintaining acceptable precision rates.

• Journal of Advanced Marine Engineering and Technology
• /
• v.28 no.2
• /
• pp.163-184
• /
• 2004

Vortex flow fundamentals have been investigating for about hundred years and many distinguished features had been discovered and comprehensively studied over that time. Due to unique hydrodynamic features vortex flows are now widely used in many industrial applications, including energy and power systems. combustion chambers. fuel sprayers. heat exchangers. clean-up systems. drying chambers. Up to recently aerospace engineers employed vortex flow only in combustion systems to stabilize a flame zone or in advanced heat exchangers to enhance heat transfer processes. This paper provides an overview of some recently developed aerothermal vortex technologies applied to aerospace engineering.

• Proceedings of the KSPS conference
• /
• 2007.05a
• /
• pp.45-48
• /
• 2007

This paper proposes a flexible selection method of feature vectors for speaker identification. In speaker identification, overlapped region between speaker models lowers the accuracy. Recently, a method was proposed which discards overlapped feature vectors without regard to the source causing the overlap. We suggest a new method using both overlapped features among speakers and non-overlapped features to mitigate the overlap effects.

• Proceedings of the KIPE Conference
• /
• 2002.07a
• /
• pp.480-484
• /
• 2002

A new active lossless snubber for half-bridge dual converter(that is called 'dual converter') is proposed in this paper. It features soft switching(ZVS) as well as turn-off snubbing in both main and auxiliary switches. As it uses parasitic components, such as leakage inductances and switch output capacitances etc, it helps the dual converter to operate at the higher frequency with a higher efficiency and smaller size reactive components. The operational principle, theoretical analysis, and design consideration are presented. To confirm the operation, features and validity of the proposed circuit, simulated results from an 1kW, 24V/DC-250V/DC are presented.