• Journal of the Microelectronics and Packaging Society
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• v.18 no.2
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• pp.1-9
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• 2011

Rare metals, called as vitamins of industry, are defined as the elements which are very few in the earth and are difficult to extract from ores. The requirements for total amounts of rare metals have increased as the global economics grows and the function of electronic components varies considerably. The rare metals have been maldistributed to America, CIS(Commonwealth of Independent States), China, Australia, Canada as about 80% of total natural resources, which also lead to unequal materials flow or distribution. Therefore, it was needed to investigate the feature of rare metals in terms of industry as well as technology. We could identify the industrial issues associated with the supply of critical rare elements in electronic components.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2109-2123
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• 2017

This paper presents a super-resolution reconstruction method based on sparse representation for two-dimensional bar code images. Considering the features of two-dimensional bar code images, Kirsch and LBP (local binary pattern) operators are used to extract the edge gradient and texture features. Feature extraction is constituted based on these two features and additional two second-order derivatives. By joint dictionary learning of the low-resolution and high-resolution image patch pairs, the sparse representation of corresponding patches is the same. In addition, the global constraint is exerted on the initial estimation of high-resolution image which makes the reconstructed result closer to the real one. The experimental results demonstrate the effectiveness of the proposed algorithm for two-dimensional bar code images by comparing with other reconstruction algorithms.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.4
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• pp.524-531
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• 2009

In this paper, we propose an automatic image registration method for multi-sensor image fusion such as visible and infrared images. The registration is achieved by finding corresponding feature points in both input images. In general, the global statistical correlation is not guaranteed between multi-sensor images, which bring out difficulties on the image registration for multi-sensor images. To cope with this problem, mutual information is adopted to measure correspondence of features and to select faithful points. An update algorithm for projective transform is also proposed. Experimental results show that the proposed method provides robust and accurate registration results.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1570-1578
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• 2000

Object motion is an important feature of content in video sequences. By now, various methods to exact feature about the object motion have been reported[1,2]. However they are not suitable to index video using the motion, since a lot of bits and complex indexing parameters are needed for the indexing [3,4] In this paper, we propose object motion map which could provide efficient indexing method for object motion. The proposed object motion map has both global and local motion information during an object is moving. Furthermore, it requires small bit of memory for the indexing. to evaluate performance of proposed indexing technique, experiments are performed with video database consisting of MPEG-1 video sequence in MPEG-7 test set.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4534-4555
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• 2015

We propose a robust object cataloging method using multiple locally distinct heterogeneous features for aiding image retrieval. Due to challenges such as variations in object size, orientation, illumination etc. object recognition is extraordinarily challenging problem. In these circumstances, we adapt local interest point detection method which locates prototypical local components in object imageries. In each local component, we exploit heterogeneous features such as gradient-weighted orientation histogram, sum of wavelet responses, histograms using different color spaces etc. and combine these features together to describe each component divergently. A global signature is formed by adapting the concept of bag of feature model which counts frequencies of its local components with respect to words in a dictionary. The proposed method demonstrates its excellence in classifying objects in various complex backgrounds. Our proposed local feature shows classification accuracy of 98% while SURF,SIFT, BRISK and FREAK get 81%, 88%, 84% and 87% respectively.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.235-236
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• 2006

IEEE 802.16 networks support mobile stations (MSs) to access broadband wireless networks while moving at a vehicular speed. However, IEEE 802.16 networks do not provide link layer native multicast capability because of point-to-multipoint connection characteristic. Due to this feature, it is not easy to adopt protocols or applications which need native link layer multicast capability. In order to solve the multicast support problem, we use the built-in LAN emulation feature of IEEE 802.16 which is based on Convergence Sublayer (CS). Our proposed operational procedures support not only the delivery of link local scope multicast packets, but also the delivery of non-link local scope multicast packets such as site local or global scope multicast packets. We also present the method of forming multicast Connection Identifier (CID) which is used to transport IP packets over IEEE 802.16 networks.

• Korean Journal of Computational Design and Engineering
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• v.6 no.4
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• pp.263-270
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• 2001

In stamping-die manufacturing, the first step is to build die patterns for lost wax casting process. A recent industry trend is to manufacture the die pattern using 3-axis NC machining. This study identifies technical considerations of the pattern machining caused by the characteristics of Styrofoam material, and proposes technical methods related to establishing a process plan and generating tool paths for optimizing the pattern machining. In this paper, the process plan includes the fellowing three items: 1) deter-mining a global machining sequence-a sequence of profile, top, bottom machining and two set-ups, 2) extracting machining features from a pattern model and merging them, and 3) determining a machining sequence of machining features. To each machining feature, this study determines the machining start point, generates the approach tool path, and proposes a tool path linking method fur reducing the distance of the cutter rapid motion. Finally, a smooth tool path generation and an automatic feedrate adjustment (AFA) method are introduced far raising the machining efficiency.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2420-2422
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• 2003

In this paper, two Fuzzy Logics for path planning of an autonomous mobile robot are proposed. If a target point is given, such problems regarding the velocity and object recognition are closely related with path to which the mobile robot navigates. Therefore, to ensure safety navigation of the mobile robot for two fuzzy logic parts, path planning considering the surrounding environment was performed in this paper. First, feature points for local and global path are determined by utilizing Cell Decomposition off-line computation. Second, the on-line robot using two Fuzzy Logics navigates around path when it tracks the feature points. We demonstrated optimized path planning only for local path using object recognition fuzzy logic corresponds to domestic situation. Furthermore, when navigating, the robot uses fuzzy logic for velocity and target angle. The proposed algorithms for path planning has been implemented and tested with pioneer-dxe mobile robot.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.06a
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• pp.399-408
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• 2001

This paper presents a simultaneous optimization approach of case-based reasoning (CBR) using a genetic algorithm(GA) for the prediction of stock price index. Prior research suggested many hybrid models of CBR and the GA for selecting a relevant feature subset or optimizing feature weights. Most studies, however, used the GA for improving only a part of architectural factors for the CBR system. However, the performance of CBR may be enhanced when these factors are simultaneously considered. In this study, the GA simultaneously optimizes multiple factors of the CBR system. Experimental results show that a GA approach to simultaneous optimization of CBR outperforms other conventional approaches for the prediction of stock price index.

• East Asian mathematical journal
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• v.37 no.5
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• pp.599-612
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• 2021

In China, Weibo is one of the social platforms with more users. It has the characteristics of fast information transmission and wide coverage. People can comment on a certain event on Weibo to express their emotions and attitudes. Judging the emotional tendency of users' comments is not only beneficial to the monitoring of the management department, but also has very high application value for rumor suppression, public opinion guidance, and marketing. This paper proposes a two-input Adaboost model based on TextCNN and BiLSTM. Use the TextCNN model that can perform local feature extraction and the BiLSTM model that can perform global feature extraction to process comment data in parallel. Finally, the classification results of the two models are fused through the improved Adaboost algorithm to improve the accuracy of text classification.