• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.83-90
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• 2011

In cell biology area, microscopy enables detecting objects inside cells that are stained or fluorescently tagged. It is disadvantageous for observing these objects because of the noisy characteristics of their environmental surrounding. In this paper, a framework is proposed to increase the throughput and reliability for analysis of these images. First, we apply adaptive beamlet transform to extract edges meaningfully followed by orientation, location, and length in different scales. Then, a post-process is implemented to extend and map them onto original image. Our proposed scheme is compared with Canny edge detector and conventional beamlet transform from four evaluation aspects. It produces better results when experiments are conducted on real images. Much better results for observing internal parts make this framework competitive for analysis of cell images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3194-3216
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• 2018

Slow Feature Discriminant Analysis (SFDA) is a supervised feature extraction method inspired by biological mechanism. In this paper, a novel method called Two Dimensional Slow Feature Discriminant Analysis via $L_{2,1}$ norm minimization ($2DSFDA-L_{2,1}$) is proposed. $2DSFDA-L_{2,1}$ integrates $L_{2,1}$ norm regularization and 2D statically uncorrelated constraint to extract discriminant feature. First, $L_{2,1}$ norm regularization can promote the projection matrix row-sparsity, which makes the feature selection and subspace learning simultaneously. Second, uncorrelated features of minimum redundancy are effective for classification. We define 2D statistically uncorrelated model that each row (or column) are independent. Third, we provide a feasible solution by transforming the proposed $L_{2,1}$ nonlinear model into a linear regression type. Additionally, $2DSFDA-L_{2,1}$ is extended to a bilateral projection version called $BSFDA-L_{2,1}$. The advantage of $BSFDA-L_{2,1}$ is that an image can be represented with much less coefficients. Experimental results on three face databases demonstrate that the proposed $2DSFDA-L_{2,1}/BSFDA-L_{2,1}$ can obtain competitive performance.

• Journal of the Korean Institute of Navigation
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• v.23 no.1
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• pp.75-84
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• 1999

Although many studies on modelling of port competitive situation have been conducted, both theoretical frame and methodology are still very weak. In this study, therefore, a new algorithm called ESD (Extensional System Dynamics) for the evaluation of port competition was presented, and applied to simulate port systems in northeast asia. The detailed objectives of this paper are to develop Unit fort Model by using SD(System Dynamics) method; to develop Competitive Port Model by ESD method; to perform sensitivity analysis by altering parameters, and to propose port development strategies. For these the algorithm for the evaluation of part's competition was developed in two steps. Firstly, SD method was adopted to develop the Unit Port models, and secondly HFP(Hierarchical Fuzzy Process) method was introduced to expand previous SD method. The proposed models were then developed and applied to the five ports - Pusan, Kobe, Yokohama, Kaoshiung, Keelung - with real data on each ports, and several findings were derived. Firstly, the extraction of factors for Unit Port was accomplished by consultation of experts such as research worker, professor, research fellows related to harbor, and expert group, and finally, five factor groups - location, facility, service, cargo volumes, and port charge - were obtained. Secondly, system's structure consisting of feedback loop was found easily by location of representative and detailed factors on keyword network of STGB map. Using these keyword network, feedback loop was found. Thirdly, for the target year of 2003, the simulation for Pusan port revealed that liner's number would be increased from 829 ships to 1,450 ships and container cargo volumes increased from 4.56 million TEU to 7.74 million TEU. It also revealed that because of increased liners and container cargo volumes, length of berth should be expanded from 2,162m to 4,729m. This berth expansion was resulted in the decrease of congested ship's number from 97 to 11. It was also found that port's charge had a fluctuation. Results of simulation for Kobe, Yokohama, Kaoshiung, Keelung in northeast asia were also acquired. Finally, the inter port competition models developed by ESB method were used to simulate container cargo volumes for Pusan port. The results revealed that under competitive situation container cargo volume was smaller than non-competitive situation, which means Pusan port is lack of competitive power to other ports. Developed models in this study were then applied to estimate change of container cargo volumes in competitive relation by altering several parameters. And, the results were found to be very helpful for port mangers who are in charge of planning of port development.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.552-569
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• 2017

The existing steganalysis method based on 2D Gabor filters can achieve a competitive detection performance for content-adaptive JPEG steganography. However, the feature dimensionality is still high and the time-consuming of feature extraction is relatively large because the optimal selection is not performed for 2D Gabor filters. To solve this problem, a new steganalysis method is proposed for content-adaptive JPEG steganography by selecting the optimal 2D Gabor filters. For the proposed method, the 2D Gabor filters with different parameter settings are generated first. Then, the feature is extracted by each 2D Gabor filter and the corresponding detection accuracy is used as the measure for filter selection. Next, some 2D Gabor filters are selected by a greedy strategy and the steganalysis feature is extracted by the selected filters. Last, the ensemble classifier is used to assemble the proposed steganalysis feature as well as the final steganalyzer. The experimental results show that the steganalysis feature extracted by the selected optimal 2D Gabor filters also can achieve a competitive detection performance while the feature dimensionality is reduced greatly.

• Genomics & Informatics
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• v.17 no.2
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• pp.15.1-15.7
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• 2019

Automatically detecting mentions of pharmaceutical drugs and chemical substances is key for the subsequent extraction of relations of chemicals with other biomedical entities such as genes, proteins, diseases, adverse reactions or symptoms. The identification of drug mentions is also a prior step for complex event types such as drug dosage recognition, duration of medical treatments or drug repurposing. Formally, this task is known as named entity recognition (NER), meaning automatically identifying mentions of predefined entities of interest in running text. In the domain of medical texts, for chemical entity recognition (CER), techniques based on hand-crafted rules and graph-based models can provide adequate performance. In the recent years, the field of natural language processing has mainly pivoted to deep learning and state-of-the-art results for most tasks involving natural language are usually obtained with artificial neural networks. Competitive resources for drug name recognition in English medical texts are already available and heavily used, while for other languages such as Spanish these tools, although clearly needed were missing. In this work, we adapt an existing neural NER system, NeuroNER, to the particular domain of Spanish clinical case texts, and extend the neural network to be able to take into account additional features apart from the plain text. NeuroNER can be considered a competitive baseline system for Spanish drug and CER promoted by the Spanish national plan for the advancement of language technologies (Plan TL).

• Korean Journal of Food Science and Technology
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• v.35 no.2
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• pp.297-301
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• 2003

An inhibitor of squalene synthase, a key enzyme in the cholesterol biosynthetic pathways and a target for improved agents to lower plasma levels of low-density lipoprotein, was sequentially purified from Curcuma longa by acetone extraction, silica gel column chromatography, and sephadex LH-20 column chromatography. Active compound, YUF-01, was successfully purified and analyzed as $C_{20}H_{21}O_6$ by electron ionization mass spectrum. Through $^1H-NMR$ and $^{13}C-NMR$ analyses, YUF-01 was identified as curcumin, which showed strong inhibition of squalene synthase.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.611-619
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• 2008

2.5D Mapping system that embody in this paper can make new design by doing draping to live various texture and model picture image of fashion clothes by pattern, and can confirm clothes work to simulation without producing direction sample or product directly. Also, the system can support function that can forecast fabric design and state of end article exactly, and the system can bring competitive power elevation of fashion industry and cost-cutting effect by doing draping using database of fabric and model picture image. 2.5D Mapping system composed and embodied by mesh warp algorithm module, light and shade extraction and application module, mapping path extraction module, mesh creation and transformation module, and 2.5D mapping module for more natural draping. Future work plans to study 3D fashion design system that graft together 3D clothes technology and 3D human body embodiment technology to do based on embodiment technology of 2.5D mapping system and overcomes expression limit of 2.5D mapping technology.

• The Journal of Information Technology and Database
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• v.6 no.1
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• pp.89-101
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• 1999

Increasing number of companies recognize that the understanding of customers and their markets is indispensable for their survival and business success. The companies are rapidly increasing the amount of investments to develop customer databases which is the basis for the database marketing activities. Database marketing is closely related to data mining. Data mining is the non-trivial extraction of implicit, previously unknown and potentially useful knowledge or patterns from large data. Data mining applied to database marketing can make a great contribution to reinforce the company's competitiveness and sustainable competitive advantages. This paper develops the classification model to select the most responsible customers from the customer databases for telemarketing system and evaluates the performance of the developed model using LIFT measure. The model employs the decision tree algorithm, i.e., CHAID which is one of the well-known data mining techniques. This paper also represents the effective database marketing strategy by applying the data mining technique to a credit card company's telemarketing system.

• Journal of computational fluids engineering
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• v.7 no.4
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• pp.1-7
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• 2002

The phase-change transformation processes are relevant in many engineering applications. In particular, this phenomenon plays an important role in the extraction and fabrication operations in the metallurgical industry. The control of the heat transfer and fluid flow patterns is important to achieve casting quality and competitive production times. In the present study, a simple finite-element algorithm is developed for solid-liquid phase change problems. Natural convection in the liquid phase due to the temperature dependency of water density is considered by a numerical model. The predictions are compared with measurements by the particle image velocimetry(PIV). to show that the calculation results are in good agreement with the experiment results.

• Journal of the Korea Fashion and Costume Design Association
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• v.7 no.3
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• pp.83-94
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• 2005

This paper is to analyze patterns for Indonesian traditional textiles. Ikat is the resist-dyeing process in which designs are reserved in warp or weft yams by tying off small bundles of threads with fiber resists to prevent the penetration of dye. Batik is the technique applying a wax resist before dyeing to form a pattern in negative. Ikat and batik are the most renowned textile arts of Indonesia. Patterns are classified as geometric pattern, plant pattern, animal pattern. Also this paper discusses the origins of ikat and batik. Therefore this Paper proposes the classification and feature extraction of ikat and batik patterns. The results of this study can be effectively applied to develop competitive pattern design for Indonesian textile market.