• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2001.06a
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• pp.83-89
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• 2001

Recent advances in the structural and molecular biology uncovered that a set of translation factors resembles a tRNA shape and, in one case, even mimics a tRNA function for deciphering the genetic ：ode. Nature must have evolved this 'art' of molecular mimicry between protein and ribonucleic acid using different protein architectures to fulfill the requirement of a ribosome 'machine'. Termination of protein synthesis takes place on the ribosomes as a response to a stop, rather than a sense, codon in the 'decoding' site (A site). Translation termination requires two classes of polypeptide release factors (RFs)： a class-I factor, codon-specific RFs (RFI and RF2 in prokaryotes; eRFI in eukaryotes), and a class-IT factor, non-specific RFs (RF3 in prokaryotes; eRF3 in eukaryotes) that bind guanine nucleotides and stimulate class-I RF activity. The underlying mechanism for translation termination represents a long-standing coding problem of considerable interest since it entails protein-RNA recognition instead of the well-understood codon-anticodon pairing during the mRNA-tRNA interaction. Molecular mimicry between protein and nucleic acid is a novel concept in biology, proposed in 1995 from three crystallographic discoveries, one, on protein-RNA mimicry, and the other two, on protein-DNA mimicry. Nyborg, Clark and colleagues have first described this concept when they solved the crystal structure of elongation factor EF- Tu：GTP：aminoacyl-tRNA ternary complex and found its overall structural similarity with another elongation factor EF-G including the resemblance of part of EF-G to the anticodon stem of tRNA (Nissen et al. 1995). Protein mimicry of DNA has been shown in the crystal structure of the uracil-DNA glycosylase-uracil glycosylase inhibitor protein complex (Mol et al. 1995; Savva and Pear 1995) as well as in the NMR structure of transcription factor TBP-TA $F_{II}$ 230 complex (Liu et al. 1998). Consistent with this discovery, functional mimicry of a major autoantigenic epitope of the human insulin receptor by RNA has been suggested (Doudna et al. 1995) but its nature of mimic is. still largely unknown. The milestone of functional mimicry between protein and nucleic acid has been achieved by the discovery of 'peptide anticodon' that deciphers stop codons in mRNA (Ito et al. 2000). It is surprising that it took 4 decades since the discovery of the genetic code to figure out the basic mechanisms behind the deciphering of its 64 codons.

• Journal of the Korean Society for Library and Information Science
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• v.28
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• pp.83-107
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• 1995

The purpose of this research is to investigate the attitudes of students, who are used to study at the Library of Duksung Women's University, concerning about the loss and mutilation of books, articles and other research materials m a university library, and to take measures for preventing the library materials from being lost and mutilated. This study made the surveys of student's recognition about the immoral behaviors like larcenous and mutilating acts, the causes of such destructive works and effective preventive measures to keep library materials in good condition, including student's opinion about library services. The investigations were conducted in two times with the same questionnaire on randomly selected 480 students and 540 students of 1989 and 1994 respectively. The sample size is estimated to reach each $10\%$ of the total number of students of 1989 and 1994 in Duksung Women's University. And then, the students were divided into two groups. The one is a group that has had experiences stealing and mutilating the materials from the Library of the University. The other is another group which has done none of them. Thereafter the responses of the two groups are analyzed to compare the differences of the students' behaviors between 1989 and 1994, and thereby finding out important factors inviting the loss and mutilation and accordingly improving effective checks to deter the students from stealing and mutilating the library materials. Some of the research findings suggested in this paper are pointed out as follows: 1) The students who has experienced neither stealing nor mutilating the library materials visited the library more frequently and are more serious about such destructive behavior as stealing and mutilating. 2) The attitudes of the students about services and equipments supplied by the library are slightly different among the students who experienced such immoral activities or not. For example, the experienced students had more preference about an application of self-help duplicating machine being able to use card. 3) To prevent the students from stealing and mutilating the library materials, the non-experienced students demanded an education for them to duly recognize the public interest of the library and also suggested to keep more duplicate materials ready in the library, meanwhile, the experienced students indicated strongly such proposals as strict regulations against stealing and mutilating behaviors, having a correct understanding of costing a lot of time and money to restore the damaged materials to their original state and keeping many duplicates ready in the library. 4) It appears to be that there were different between the experienced and non- experienced students concerning causes invited stealing and mutilated behaviors. 5) Over all, the number of the non-experienced students is more increased in 1994 than that of 1989.

• Imaging Science in Dentistry
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• v.42 no.3
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• pp.139-146
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• 2012

Purpose: An individual surgical stent fabricated from computed tomography (CT) data, called a CT-guided stent, would be useful for accurate installation of implants. The purpose of the present study was to introduce a newly developed CT-guided stent with a simple design and evaluate the accuracy of the stent placement. Materials and Methods: A resin template was fabricated from a hog mandible and a specially designed plastic plate, with 4 metal balls inserted in it for radiographic recognition, was attached to the occlusal surface of the template. With the surgical stent applied, CT images were taken, and virtual implants were placed using software. The spatial positions of the virtually positioned implants were acquired and implant guiding holes were drilled into the surgical stent using a specially designed 5-axis drilling machine. The surgical stent was placed on the mandible and CT images were taken again. The discrepancy between the central axis of the drilled holes on the second CT images and the virtually installed implants on the first CT images was evaluated. Results: The deviation of the entry point and angulation of the central axis in the reference plane were $0.47{\pm}0.27$ mm, $0.57{\pm}0.23$ mm, and $0.64{\pm}0.16^{\circ}$, $0.57{\pm}0.15^{\circ}$, respectively. However, for the two different angulations in each group, the $20^{\circ}$ angulation showed a greater error in the deviation of the entry point than did the $10^{\circ}$ angulation. Conclusion: The CT-guided template proposed in this study was highly accurate. It could replace existing implant guide systems to reduce costs and effort.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5005-5011
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• 2011

The purpose of this work is to know the validity of a new stimulation method in cognitive functional imaging using custom-designed images correspond to words or syllables improving the shortcomings of existing method using text. From March 2011 to May five Subjects in need of language related functional MRI scanning were selected and both of text stimulating method and image stimulating method sacanning were carried out three times each. Using 3.0T Philps MRI machine and Invivo Co's Eloquence system, data acquisition was performed with EPI-BOLD technique. Post processing was performed with SPM 99 while the activated signals were determined within 95 percent confidence level.The number of activation clusters and the activation ratio inside ROI were compared. As as result, all of the subject showed activation inside Broca area but it did not have statistical significance. In conclusion, the image sitimulation method has potential because image itself is a common means of recognition and it can be recognised easily even if there language barrier. This stimulation method can be applied to replacing the exising scanning method especially in the elderly, infants, foerigners who may not fully understand about the examination.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.855-865
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• 2018

Sound event detection is one of the research areas to model human auditory cognitive characteristics by recognizing events in an environment with multiple acoustic events and determining the onset and offset time for each event. DCASE, a research group on acoustic scene classification and sound event detection, is proceeding challenges to encourage participation of researchers and to activate sound event detection research. However, the size of the dataset provided by the DCASE Challenge is relatively small compared to ImageNet, which is a representative dataset for visual object recognition, and there are not many open sources for the acoustic dataset. In this study, the sound events that can occur in indoor and outdoor are collected on a larger scale and annotated for dataset construction. Furthermore, to improve the performance of the sound event detection task, we developed a dual CNN structured sound event detection system by adding a supplementary neural network to a convolutional neural network to determine the presence of sound events. Finally, we conducted a comparative experiment with both baseline systems of the DCASE 2016 and 2017.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.291-299
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• 2020

The purpose of this study was to be used as basic data for the development of future-type curriculum in health. The awareness and preparation of the forth industrial revolution were surveyed on 280 college students in health departments preparing medical technicians. A self-written structured questionnaire was used for data collection, and the recognition of the forth industry revolution was 2.74, 3D printing (3.59) was high, and neural network machine learning(2.33) was the lowest. Students majoring in Physiotherapy (3.00) had the highest perception, and those majored in Dental engineering(2.37) had the lowest perception, and there was a difference in the degree of perception of IoT by major (p=0.024). For the forth industrial revolution, 54.5% of students are preparing, and lack of interest (42.9%) is the most difficult reason to prepare, and 50.6% of educational experience and 60.9% of VR&AR game experience have experience. In the era of the forth industrial revolution, job loss (38.7%) was high, and the required competency was creative capacity (50.6%). Therefore, it is necessary to develop a curriculum related to the fourth industrial revolution and apply teaching methods that can increase the awareness and preparation of health college students in the era of the fourth industrial revolution.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.461-469
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• 2020

In this paper, we propose a PCA-based feature feedback method for extracting important areas of handwritten numeric data sets and face data sets. A PCA-based feature feedback method is proposed by extending the previous LDA-based feature feedback method. In the proposed method, the data is reduced to important feature dimensions by applying the PCA technique, one of the dimension reduction machine learning algorithms. Through the weights derived during the dimensional reduction process, the important points of data in each reduced dimensional axis are identified. Each dimension axis has a different weight in the total data according to the size of the eigenvalue of the axis. Accordingly, a weight proportional to the size of the eigenvalues of each dimension axis is given, and an operation process is performed to add important points of data in each dimension axis. The critical area of the data is calculated by applying a threshold to the data obtained through the calculation process. After that, induces reverse mapping to the original data in the important area of the derived data, and selects the important area in the original data space. The results of the experiment on the MNIST dataset are checked, and the effectiveness and possibility of the pattern recognition method based on PCA-based feature feedback are verified by comparing the results with the existing LDA-based feature feedback method.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.19-30
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• 2018

Visual information understanding is known as one of the most difficult and challenging problems in the realization of machine intelligence. This paper proposes deriving visual verb and construction of ActionNet database as a video database for video semantic understanding. Even though development AI (artificial intelligence) algorithms have contributed to the large part of modern advances in AI technologies, huge amount of database for algorithm development and test plays a great role as well. As the performance of object recognition algorithms in still images are surpassing human's ability, research interests shifting to semantic understanding of video contents. This paper proposes candidates of visual verb requiring in the construction of ActionNet as a learning and test database for video understanding. In order to this, we first investigate verb taxonomy in linguistics, and then propose candidates of visual verb from video description database and frequency of verbs. Based on the derived visual verb candidates, we have defined and constructed ActionNet schema and database. According to expanding usability of ActionNet database on open environment, we expect to contribute in the development of video understanding technologies.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.183-190
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• 2011

In this paper, we propose a prototype system for abnormal sound detection and identification which detects and recognizes the abnormal situations by means of analyzing audio information coming in real time from CCTV cameras under surveillance environment. The proposed system is composed of two layers: The first layer is an one-class support vector machine, i.e., support vector data description (SVDD) that performs rapid detection of abnormal situations and alerts to the manager. The second layer classifies the detected abnormal sound into predefined class such as 'gun', 'scream', 'siren', 'crash', 'bomb' via a sparse representation classifier (SRC) to cope with emergency situations. The proposed system is designed in a hierarchical manner via a mixture of SVDD and SRC, which has desired characteristics as follows: 1) By fast detecting abnormal sound using SVDD trained with only normal sound, it does not perform the unnecessary classification for normal sound. 2) It ensures a reliable system performance via a SRC that has been successfully applied in the field of face recognition. 3) With the intrinsic incremental learning capability of SRC, it can actively adapt itself to the change of a sound database. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.

• Journal of IKEEE
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• v.25 no.2
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• pp.273-279
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• 2021

In this paper, we propose an algorithm that shortens the learning time by performing individual learning using partitioning the deep learning structure. The proposed algorithm consists of four processes: network classification origin setting process, feature vector extraction process, feature noise removal process, and class classification process. First, in the process of setting the network classification starting point, the division starting point of the network structure for effective feature vector extraction is set. Second, in the feature vector extraction process, feature vectors are extracted without additional learning using the weights previously learned. Third, in the feature noise removal process, the extracted feature vector is received and the output value of each class is learned to remove noise from the data. Fourth, in the class classification process, the noise-removed feature vector is input to the multi-layer perceptron structure, and the result is output and learned. To evaluate the performance of the proposed algorithm, we experimented with the Extended Yale B face database. As a result of the experiment, in the case of the time required for one-time learning, the proposed algorithm reduced 40.7% based on the existing algorithm. In addition, the number of learning up to the target recognition rate was shortened compared with the existing algorithm. Through the experimental results, it was confirmed that the one-time learning time and the total learning time were reduced and improved over the existing algorithm.