• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.667-680
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• 2007

The bio-data processing is used for a suitable purpose with bio-signals, which are obtained from human individuals. Recently, there is increasing demand that the bio-data has been widely applied to various applications. However, it is often that the number of data within each class is limited and the number of classes is large due to the property of problem domain. Therefore, the conventional pattern recognition systems and classification methods are suffering form low generalization performance because the system using the lack of data is influenced by noises of that. To solve this problem, we propose a modified additive factor model for bio-data generation, with two factors; the class factor which affects properties of each individuals and the environment factor such as noises which affects all classes. We then develop a classification system through defining a new similarity function using the proposed model. The proposed method maximizes to use an information of the class classification. So, we can expect to obtain good generalization performances with robust noises from small number of datas for bio-data. Experimental results show that proposed method outperforms significantly conventional method with real bio-data.

• Journal of Sensor Science and Technology
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• v.14 no.2
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• pp.69-77
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• 2005

The electronic nose (e-nose) has been used in food industry and quality controls in plastic packaging. Recently it finds its applications in medical diagnosis, specifically on detection of diabetes, pulmonary or gastrointestinal problem, or infections by examining odors in the breath or tissues with its odor characterizing ability. Moreover, the use of portable e-nose enables the on-site measurements and analysis of vapors without extra gas-sampling units. This is expected to widen the application of the e-nose in various fields including point-of-care-test or e-health. In this study, a PDA-based portable e-nose was developed using micro-machined gas sensor array and miniaturized electronic interfaces. The rich capacities of the PDA in its computing power and various interfaces are expected to provide the rapid and application specific development of the diagnostic devices, and easy connection to other facilities through information technology (IT) infra. For performance verification of the developed portable e-nose system, Six different vapors were measured using the system. Seven different carbon-black polymer composites were used for the sensor array. The results showed the reproducibility of the measured data and the distinguishable patterns between the vapor species. Additionally, the application of two typical pattern recognition algorithms verified the possibility of the automatic vapor recognition from the portable measurements. These validated the portable e-nose based on PDA developed in this study.

• The KIPS Transactions:PartA
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• v.17A no.1
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• pp.33-44
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• 2010

We present a pipeline monitoring system based on bio-memetic robot in this paper. A bio-memetic robot exploring pipelines measures temperature, humidity, and vibration. The principal function of pipeline monitoring robot for the exploring pipelines is to recognize the shape of pipelines. We use infrared distance sensor to recognize the shape of pipelines and potentiometer to measure the angle of motor mounting infrared distance sensor. For the shape recognition of pipelines, the number of detected pipelines is used during only one scanning of distance. Three fuzzy classifiers are used for the number of detected pipelines, and the classifying results are presented in this paper.

• Bulletin of the Korean Chemical Society
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• v.30 no.12
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• pp.2938-2942
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• 2009

New receptors 1-3 that bind stereoselectively amino alcohols and convert chirality of amino acidsvia imine bond formation were synthesized. The receptors have uryl (1), thiouryl (2) and guanidinium (3) groups all with additional phenylcarbonyl motifs, which are effective hydrogen bonding donors and play a key role in the stereoselective recognitions. The stereoselectivities were measured from the integration of $^1HNMR$ peaks. Compound 1 and 2 showed the stereoselectivities for the imine formation with amino alcohols ($K_R/K_S$) in the range of 2${\sim}$4, and compound 3 in the range of 4${\sim}$8. Chirality conversion efficienciesof 1-3 for amino acids, i.e. D/L ratio at equilibrium, are in the range of 1.5${\sim}$5.6, showing a little higher efficiency with 3. The additional phenylcarbonyl motifs in 1-3 were revealed not to contribute to significant enhancement of the selectivities.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.773-779
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• 1996

Dried oak mushroom have complex and various visual features. Grading and sorting of dried oak mushrooms has been done by the human expert. Though actions involved in human grading looked simple, a decision making underneath the simple action comes from the result of the complex neural processing of the visual image. Through processing details involved in human visual recognition has not been fully investigated yet, it might say human can recognize objects via one of three ways such as extracting specific features or just image itself without extracting those features or in a combined manner. In most cases, extracting some special quantitative features from the camera image requires complex algorithms and processing of the gray level image requires the heavy computing load. This fact can be worse especially in dealing with nonuniform, irregular and fuzzy shaped agricultural products, resulting in poor performance because of the sensitiveness to the crisp criteria or specific ules set up by algorithms. Also restriction of the real time processing often forces to use binary segmentation but in that case some important information of the object can be lost. In this paper, the neuro net based real time recognition algorithm was proposed without extracting any visual feature but using only the directly captured raw gray images. Specially formated adaptable size of grids was proposed for the network input. The compensation of illumination was also done to accomodate the variable lighting environment. The proposed grading scheme showed very successful results.

• Korean Journal of Metals and Materials
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• v.46 no.3
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• pp.131-134
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• 2008

The magnetism of$Fe_3O_4$ nanoparticles was applied to magnetic bio-panning process for finding specific sequences against $Fe_3O_4$ crystal phase. Vibrating sample magnetometer (VSM) measurement showed that the coercivity of 30 Oe and the saturation magnetization of 55 emu/g were sufficient in controlling particle movement and magnetizing particles in the media, respectively. This ferrimagnetism of nanoparticles practically enhanced panning efficiency by exaggerating centrifuge step and preventing particle loss. Sequencing results showed that histidine which was commonly found in peptide sequences played an important role in the binding onto $Fe_3O_4$ nanoparticle surface. However, various possible motifs were also observed from several neighboring amino acids of histidine.

• Journal of the Korea Computer Industry Society
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• v.5 no.1
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• pp.157-166
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• 2004

Consequently substantial research has been done on the development of the bio-metric recognition method as well as technical research in the field of authentication. As a method of bio-metric recognition, personal and unique information such as fingerprints, voice, face, Iris, hand-geometry and vein-pattern are used. The face image system in bio-metric recognition and information authentication reduces the denial response from the users because it is a non-contact system the face image system operates through a PC camera attached to a computer base this makes the system economically viable as well as user friendly. Conversely, the face image system is very sensitive to illumination, hair style and appearance and consequently creates recognition errors easily, therefore we must build a stable authentication system which is not too sensitive to changes in appearance and light. In this study, I proposed user authentication protocol to serve a confidentiality and integrity and to obtain a least Equal Error Rate to minimize the wrong authentication rate when it authenticates the user.

• Journal of Science of Art and Design
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• v.4
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• pp.91-122
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• 2002

`Bio morphism` are constituted in paintings where the artists try to embody the elementary properties of living creature as of growth and durability. They are the most appropriate concept of painting to harmonize human being with nature closely. The formative ways of them attach great importance to both unconsciousness and desire , as well as variations or dynamics, by noticing a flow of natural senses and feelings of human being. In other words, the formative ways are based on a recognition of nature as the intrinsic force of life, with the result that aesthetics of incompleteness is embodied in images. Therefore they are clearly distinguished from that of functional, geometric images. A tendency of painting at that time, in a word, 'return to figure and expression', means a conversion into organic images like the incomplete, atypical, and biomorphic forms, while denying the mechanical or geometric. Elizabeth Murray are analyzed, for these works are remarkable in the characteristics of 'Bio morphism'. Consequently the features of organic images, that is, 'the formative acceptance of natural figures, or an informality' and 'the force of free will, or an incompleteness', could obviously be revealed. It is a type that obtains a motif out of natural figures like an animal, a plant, or the concrete figures of human being. In conclusion, this thesis is focused on not only emphasizing that 'Bio morphism' were a major tendency among the various trends of postmodern painting in the 20th century, but also analysing both the painterly formation of organic images and the structure of them. In addition to these points, it is a central aim to evoke that Bio morphism should accurately be evaluated and positioned in postmodern painting. A new recognition of 'Bio morphism' is a peculiarity of the times that reflects a cultural aspect of the present, hence it should be recognized as another way to approach the postmodern painting.

• The Journal of Korea Robotics Society
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• v.14 no.3
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• pp.211-220
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• 2019

Surface electromyogram (sEMG), which is a bio-electrical signal originated from action potentials of nerves and muscle fibers activated by motor neurons, has been widely used for recognizing motion intention of robotic prosthesis for amputees because it enables a device to be operated intuitively by users without any artificial and additional work. In this paper, we propose a training-free unsupervised sEMG pattern recognition algorithm. It is useful for the gesture recognition for the amputees from whom we cannot achieve motion labels for the previous supervised pattern recognition algorithms. Using the proposed algorithm, we can classify the sEMG signals for gesture recognition and the calculated threshold probability value can be used as a sensitivity parameter for pattern registration. The proposed algorithm was verified by a case study of a patient with partial-hand amputation.

• Journal of Bio-Environment Control
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• v.20 no.2
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• pp.63-71
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• 2011

Pattern recognition of a cucumber were conducted to detect directly the binary images by using thresholding method, which have the threshold level at the optimum intensity value. By restricting conditions of learning pattern, output patterns could be extracted from the same and similar input patterns by the algorithm. The algorithm of pattern recognition was developed to determine the position of the cucumber from a real image within working condition. The algorithm, designed and developed for this project, learned two, three or four learning pattern, and each learning pattern applied it to twenty sample patterns. The restored success rate of output pattern to sample pattern form two, three or four learning pattern was 65.0%, 45.0%, 12.5% respectively. The more number of learning pattern had, the more number of different out pattern detected when it was conversed. Detection of feature pattern of cucumber was processed by using auto scanning with real image of 30 by 30 pixel. The computing times required to execute the processing time of cucumber recognition took 0.5 to 1 second. Also, five real images tested, false pattern to the learning pattern is found that it has an elimination rate which is range from 96 to 98%. Some output patterns was recognized as a cucumber by the algorithm with the conditions. the rate of false recognition was range from 0.1 to 4.2%.