• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.21-31
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• 2002

This study applied each Neural Networks theory and Fuzzy Set theory to improve accuracy in remotely sensed images. Remotely sensed data have been used to map land cover. The accuracy is dependent on a range of factors related to the data set and methods used. Thus, the accuracy of maps derived from conventional supervised image classification techniques is a function of factors related to the training, allocation, and testing stages of the classification. Conventional image classification techniques assume that all the pixels within the image are pure. That is, that they represent an area of homogeneous cover of a single land-cover class. But, this assumption is often untenable with pixels of mixed land-cover composition abundant in an image. Mixed pixels are a major problem in land-cover mapping applications. For each pixel, the strengths of class membership derived in the classification may be related to its land-cover composition. Fuzzy classification techniques are the concept of a pixel having a degree of membership to all classes is fundamental to fuzzy-sets-based techniques. A major problem with the fuzzy-sets and probabilistic methods is that they are slow and computational demanding. For analyzing large data sets and rapid processing, alterative techniques are required. One particularly attractive approach is the use of artificial neural networks. These are non-parametric techniques which have been shown to generally be capable of classifying data as or more accurately than conventional classifiers. An artificial neural networks, once trained, may classify data extremely rapidly as the classification process may be reduced to the solution of a large number of extremely simple calculations which may be performed in parallel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.10
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• pp.1422-1432
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• 1993

Nonlinear mapping function of the HCNN( Hidden Control Neural Network ) can change over time to model the temporal variability of a speech signal by combining the nonlinear prediction of conventional neural networks with the segmentation capability of HMM. We have two things in this paper. first, we showed that the performance of the HCNN is better than that of HMM. Second, the HCNN with its prediction error measure given by weighted distance is proposed to use suitable distance measure for the HCNN, and then we showed that the superiority of the proposed system for speaker-independent speech recognition tasks. Weighted distance considers the differences between the variances of each component of the feature vector extraced from the speech data. Speaker-independent Korean digit recognition experiment showed that the recognition rate of 95%was obtained for the HCNN with Euclidean distance. This result is 1.28% higher than HMM, and shows that the HCNN which models the dynamical system is superior to HMM which is based on the statistical restrictions. And we obtained 97.35% for the HCNN with weighted distance, which is 2.35% better than the HCNN with Euclidean distance. The reason why the HCNN with weighted distance shows better performance is as follows : it reduces the variations of the recognition error rate over different speakers by increasing the recognition rate for the speakers who have many misclassified utterances. So we can conclude that the HCNN with weighted distance is more suit-able for speaker-independent speech recognition tasks.

• Proceedings of the Korean Society of Crop Science Conference
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• 2004.04a
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• pp.12-27
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• 2004

Thanks to spectacular advances in the techniques for identifying proteins separated by two-dimensional electrophoresis and in methods for large-scale analysis of proteome variations, proteomics is becoming an essential methodology in various fields of plant sciences. Plant proteomics would be most useful when combined with other functional genomics tools and approaches. A combination of microarray and proteomics analysis will indicate whether gene regulation is controlled at the level of transcription or translation and protein accumulation. In this review, we described the catalogues of the rice proteome which were constructed in our program, and functional characterization of some of these proteins was discussed. Mass-spectrometry is a most prevalent technique to identify rapidly a large of proteins in proteome analysis. However, the conventional Western blotting/sequencing technique us still used in many laboratories. As a first step to efficiently construct protein data-file in proteome analysis of major cereals, we have analyzed the N-terminal sequences of 100 rice embryo proteins and 70 wheat spike proteins separated by two-dimensional electrophoresis. Edman degradation revealed the N-terminal peptide sequences of only 31 rice proteins and 47 wheat proteins, suggesting that the rest of separated protein spots are N-terminally blocked. To efficiently determine the internal sequence of blocked proteins, we have developed a modified Cleveland peptide mapping method. Using this above method, the internal sequences of all blocked rice proteins (i. e., 69 proteins) were determined. Among these 100 rice proteins, thirty were proteins for which homologous sequence in the rice genome database could be identified. However, the rest of the proteins lacked homologous proteins. This appears to be consistent with the fact that about 30% of total rice cDNA have been deposited in the database. Also, the major proteins involved in the growth and development of rice can be identified using the proteome approach. Some of these proteins, including a calcium-binding protein that fumed out to be calreticulin, gibberellin-binding protein, which is ribulose-1,5-bisphosphate carboxylase/oxygenase activate in rice, and leginsulin-binding protein in soybean have functions in the signal transduction pathway. Proteomics is well suited not only to determine interaction between pairs of proteins, but also to identify multisubunit complexes. Currently, a protein-protein interaction database for plant proteins (http://genome .c .kanazawa-u.ac.jp/Y2H)could be a very useful tool for the plant research community. Recently, we are separated proteins from grain filling and seed maturation in rice to perform ESI-Q-TOF/MS and MALDI-TOF/MS. This experiment shows a possibility to easily and rapidly identify a number of 2-DE separated proteins of rice by ESI-Q-TOF/MS and MALDI-TOF/MS. Therefore, the Information thus obtained from the plant proteome would be helpful in predicting the function of the unknown proteins and would be useful in the plant molecular breeding. Also, information from our study could provide a venue to plant breeder and molecular biologist to design their research strategies precisely.

• The Korean Journal of Pharmacology
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• v.31 no.2
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• pp.241-250
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• 1995

Protein B23 is one of the major nucleolar phosphoproteins associated with pre-ribosomal particles, and is localized in the granular region of the nucleolus. Recent studies suggest that protein B23 shuttles between nucleus and cytoplasm and also interacts with HIV Rev. These findings indicate that protein B23 is important in nucleocytoplasmic relationship and viral replication. However, the exact function of protein B23 is not clear yet. In acute nucleolar hypertrophy of rat liver, treated with thioacetamide, there was observed an increase of not only protein B23 but also B23-like protein p45 when anti-B23 monoclonal antibody (MAb) was used for identification. On the basis of the large B23 specific epitope structure composed of 68 amino acids, a hypothesis was formulated to examine that p45 is the pre-B23 resulting from excessive production of B23. In an attempt to investigate the precursor of B23, we analyzed the subcellular fractions and microsomal subfractions. Subsequently, we analyzed the finger printings of B23-like proteins using the tryptic peptide mapping. The results are summarized: 1) Using B23 MAb, we observed the presence of B23-like proteins in nucleolar fraction, nucleoplasmic fraction and microsomal fraction. 2) In the further microsomal subfractionation, we could partially purify B23-like protein in 2M layer of sucrose gradient. 3) When ion exchange chromatography was employed, there were protein species 80kDa(p80), 65kDa(p65) and 60kDa(p60). 4) Based on the tryptic map analysis of $^{125}I$ labeled proteins, the similarity between B23 and p80 was found only in 9 out of 14(B23) and 21(p80) peptides, and difference was found in the remaining peptides. p80 and p60 had 18 common peptides, and all the peptides of p60 were similar to those of p80. From these results, it is proposed that p45 is an abnormal metabolite resulting from carcinogenesis by thioacetamide, and it is not the precursor of B23. In addition, we suggest that p80 may be a precursor of p45.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.19-30
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• 2012

The context aware service is the service to provide useful information to the users by recognizing surroundings around people who receive the service via computer based on computing and communication, and by conducting self-decision. But CAS(Context Awareness System) shows the weak point of small-scale context awareness processing capacity due to restricted mobile function under the current mobile environment, memory space, and inference cost increment. In this paper, we propose a mobile cloud context system with using Google App Engine based on PaaS(Platform as a Service) in order to get context service in various mobile devices without any subordination to any specific platform. Inference design method of the proposed system makes use of knowledge-based framework with semantic inference that is presented by SWRL rule and OWL ontology and Jess with rule-based inference engine. As well as, it is intended to shorten the context service reasoning time with mapping the regular reasoning of SWRL to Jess reasoning engine by connecting the values such as Class, Property and Individual which are regular information in the form of SWRL to Jess reasoning engine via JessTab plug-in in order to overcome the demerit of queries reasoning method of SparQL in semantic search which is a previous reasoning method.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.6
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• pp.514-528
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• 2004

An emotion-based video scene retrieval algorithm is proposed in this paper. First, abrupt/gradual shot boundaries are detected in the video clip representing a specific story Then, five video features such as 'average color histogram' 'average brightness', 'average edge histogram', 'average shot duration', and 'gradual change rate' are extracted from each of the videos and mapping between these features and the emotional space that user has in mind is achieved by an interactive genetic algorithm. Once the proposed algorithm has selected videos that contain the corresponding emotion from initial population of videos, feature vectors from the selected videos are regarded as chromosomes and a genetic crossover is applied over them. Next, new chromosomes after crossover and feature vectors in the database videos are compared based on the similarity function to obtain the most similar videos as solutions of the next generation. By iterating above procedures, new population of videos that user has in mind are retrieved. In order to show the validity of the proposed method, six example categories such as 'action', 'excitement', 'suspense', 'quietness', 'relaxation', 'happiness' are used as emotions for experiments. Over 300 commercial videos, retrieval results show 70% effectiveness in average.

• Journal of Fashion Business
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• v.12 no.5
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• pp.1-13
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• 2008

This study is largely aimed at presenting ways to improve the working clothes and help companies create more positive images by suggesting designs of the clothes, which take into accounts the corporate image, symbolism, function and aesthetic appreciation through introduction of companies' CIP. And, it is significant to propose working clothes development condition and process with introduction of companies' CIP(Corporate Identity Program : work that systematize and simplify visually images which companies or public bodies have) A way of this study was made up with working clothes design development process which a student planned. First of all, this study looked into Company D's Corporate Identity Program(CIP) to develop the design that corresponds with the characteristics of the company's favorite design, working environment and demands of the employees. And, then, the study conducted a survey of 30 employees and intensive interviews with heads of four teams including the Safety Team, the Working Clothes Management Team and the General Affairs Team to find out the requirements of the clothes and the characteristics of the company. Based on them, the concrete image that the company pursues and the direction of design were set up through image positioning. In the end, three different concept designs were presented through image-mapping and the concrete design of each item was developed. A total of seven items including upper and lower garments (a jacket and trousers) for the spring-summer seasons, upper and lower garments (a jumper and trousers) for the winter season, cold-protecting vest and winter clothes (a coat and trousers) were presented in accordance with the three concepts. One of the concept designs, which was selected through evaluation by employees of Company D, was produced as a sample and then the final design was chosen after a discussion attended by the head of each team and representatives of the employees. Based on the aforementioned design planning, one design was selected from each of the three concept designs for production. And each of these was requested to special production enterprise and manufactured. Following the result of study, by looking into a case of a practical joint design project between a university and a company, this study suggested ideas for business to improve working clothes through the academic-industrial cooperation and presented conditions and process of design development. And, this study also aims to examine the feasibility of academic-industrial cooperation based on the cases in which enterprises and universities staged joint projects to develop working clothes.

• Atmosphere
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• v.29 no.1
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• pp.105-112
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• 2019

Measurements of vertical air motion and microphysics are essential for improving our understanding of convective clouds. In this paper, the author reviews the current research on the retrieval of vertical air motions using the cloud radar. At radar wavelengths of 3 mm (W-band radar; 94-GHz radar; cloud radar), the raindrop backscattering cross-section (${\sigma}b$) varies between successive maxima and minima as a function of the raindrop diameter (D) that are well described by Mie theory. The first Mie minimum in the backscattering cross-section occurs at D~1.68 mm, which translates to a raindrop terminal fall velocity of ${\sim}5.85m\;s^{-1}$ based on the Gunn and Kinzer relationship. Since raindrop diameters often exceed this size, the signal is captured in the radar Doppler spectrum, and thus, the location of the first Mie minimum can be used as a reference for retrieving the vertical air motion. The Mie technique is applied to radar Doppler spectra from the surface-based and airborne, upward pointing W-band radars. The contributions of aircraft motion to the vertical air motion are also described and further the first-order aircraft motion corrected equation is presented. The review also shows that the separate spectral peaks due to the cloud droplets can provide independent validation of the Mie technique retrieved vertical air motion using the cloud droplets as a tracer of vertical air motion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.415-423
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• 2021

Citizen participation and Living Lab are attracting interest as one of the major strategies for the success of smart cities. In a Living Lab, citizens, who are the end-users of technology, participate in the search for alternatives to define and solve problems and repeat experiments to verify alternatives in a circular process. The purpose of this research was to present an operating model of a citizen-participating online community platform to improve urban problems, implement and test it, and show its applicability. To this end, an operation model of a citizen-participating online community platform was proposed to improve urban problems. An online platform was designed and implemented to reflect the functions pursued by the operation model. Finally, a pilot test for the function was performed using the Oma Elementary School case located in Ilsan, Goyang-si, Gyeonggi-do. The operating model was designed with the city's pedestrian environment and children. As a result, the sharing and communicating process of urban issues among community members worked appropriately according to the designed intention. The Living Lab coordinator could visualize and view urban issues posted by users on a map based on location information. Visualizing the urban problem as a heat map confirmed that urban problems were concentrated in a specific area.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1339-1348
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• 2020

Phytoplankton controls marine ecosystems in terms of nutrients, photosynthetic rate, carbon cycle, etc. and the degree of its influence on the marine environment depends on their physical size. Many studies have been attempted to identify marine phytoplankton size classes using the remote sensing techniques. One of successful approach was the three-component model which estimates the chlorophyll concentrations of three phytoplankton size classes (micro-phytoplankton; >20 ㎛, nano-; 2-20 ㎛ and pico-; <2 ㎛) as a function of total chlorophyll. Here, we examined the applicability of Geostationary Ocean Colour Imager (GOCI) to the mapping of the phytoplankton size class distribution in the East Sea. A fit of the three-component model to a biomarker pigment dataset collected in the study area for some years including a large harmful algal bloom period has been carried out to derive size-fractioned chlorophyll concentration (CHL). The tuned three-component model was applied to the hourly GOCI images to identify the fractions of each phytoplankton size class for the entire CHL. Then, we investigated the distribution of phytoplankton community in terms of the size structure in the East Sea during the harmful Cochlodinium polykrikoides blooms in the summer of 2013.