• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3855-3865
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• 2000

The automatic indexing is a compulsory part for the text retrieval system. However it is impossible to rank the appropriate texts at top. Furthermore, it is more difficult to prevent to rank the inappropriate texts having homonyms at top by only the automatic indexing. In this paper, we proposed the two-level retrieval system to enhance the retrieval efficiency, in which Automatic Keyword Network (AKN) is used at the second-level process. The firsHevel search is carried out with an inverted index file generated by the automatic indexing. On the other hand the second-level search exploits AKN based on the degree of asslxiation between terms. We have developed several formulas for rearranging the rank of texts at second-level search, and evaluated the performance of the effects of them on resolving the word sense ambiguities.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.11 no.2
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• pp.89-100
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• 1993

This paper is a study on the earth volume calculation using CAD and LISP(LIST Processing) in the route alignment. The utility enlargement in the industry field and the considerable progress of computer make the automatic design and manufacture for the development of CAD/CAM/CAE technique possible, and the automatic design of civil engineering works is continuously progressive. In this study we are intend to improve an effect of civil engineering work by the automatic earth volume calculation in route alignment. This paper aims to construct the automatic design system of civil engineering work and the procedures; (1) The programming of the self-scanning program of the land information introducing Digital Terrain Model concept in the map (2) Systematic algorithm construction using LISP and grafting CAD system (3) Automatic design and calculation of the mass curve and earth volume.

• KIISE Transactions on Computing Practices
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• v.22 no.5
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• pp.218-224
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• 2016

This paper proposes a computer-based practical automatic scoring system for Korean short answers through student answer analysis and natural language processing techniques. The proposed system reduces the overall scoring time and budget, while improving the ease-of-use to write answer templates from student answers as well as the accuracy and reliability of automatic scoring system. To evaluate the application of the automatic scoring system and compare to the human scoring process, we performed an experiment using the student answers of social science subject in 2014 National Assessment of Educational Achievement.

• Journal of Korean Library and Information Science Society
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• v.30 no.3
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• pp.27-51
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• 1999

This paper deals with the methods as well as the problems associated with automatic extraction indexing and assignment indexing, expert systems for indexing, and major approaches currently used to index the Internet resources. It also briefly reviews basic methods for establishing hypertext/hypermedia links automatically. The methods used in much of text processing today are not particularly new. Most of the them were used, perhaps in a more rudimentary form, 30 or more years ago by Luhn and many other investigators. Better results can be achieved today because much greater bodies of electronic text are now avaliable and the power of present-day computers allows the processing of such text with reasonable efficiency.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.68-73
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• 2000

This study to embody automatic recognition of VIN(Vehicle Identification Number)character by computer vision system. Automatic recognition characters methods consist of the thining processing and the recognition of each character. VIN character and background classified using counting method of the size of connected pixels. Thining processing applied to segmentation of connected fundamental phonemes by Hilditch's algorithm. Each VIN character contours tracing algorithm used the Freeman's direction tracing algorithm.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2547-2549
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• 1998

Automatic yield-test equipment for micro mirror array using image processing was developed. This computerized test equipment can classify the error states of the micromirrors. The test results are displayed on the monitor as a map which shows the error states and position. It is possible to measure yield and reliability with this test equipment for micromirror array using image processing.

• International Journal of Industrial Entomology and Biomaterials
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• v.47 no.2
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• pp.79-89
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• 2023

This paper is about the development results of an automatic silkworm breeding system to reduce labor and time by automatically performing the works for silkworm droppings changing and feed its food. It consists of an automatic guided vehicle and a processing unit. The automatic guided vehicle transports a silkworm dropping changing frame mounted on a silkworm tray stand, and the processing unit takes over the dropping changing frame on it, removes excrement contained the droppings changing frame and feeds silkworm food. In the case of the current silkworm farming, because the breeding period for large silkworms (4 to 5 stage) is short to 14 days and the supply of mulberry leaves takes 98% of the total amount of mulberry leaves needed for breeding silkworms at this time, labor concentration is intensive, and all breeding works depends on manpower. Therefore, it was difficult to breed large silkworms on a large scale. Moreover, silkworms are bred by adding Silkworm bed (Seop) and mulberry in the silkworm tray, and their droppings changing is to separate silkworms and excrement by moving silkworm trays one by one, and the production cost increases due to the high-cost manpower for silkworm breeding. To solve this problem, technology for automating silkworm breeding has also been developed. However, there is still a limitation that silkworm feeding and droppings changing works are not suitable for mass breeding because a lot of labor and time are spent depending on manual work. Therefore, a new silkworm breeding system for breeding silkworm automatically is needed and so we developed an Automatic Silkworm Breeding System applying the droppings change frame, the inverting unit, the feeding silkworm food device and automatic guided vehicle.

• Journal of the Korean Society for Library and Information Science
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• v.23
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• pp.207-261
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• 1992

The purpose of this study is (1) to design and test a database which can be automatically classified, and (2) to generate automatic classification number by processing the keywords in titles using the code combination method of Colon Classification(CC) as well as an automatic recognition of subjects in order to develop an automatic classification system (Auto BC System) based on CC which can be applied to any research library. To conduct this study, 1,510 words in the fields of agricultrue and medicine were selected, analized in terms of [P], [M], [E], [S], [T] employed in CC, and included in a database for classification. For the above-mentioned subject fields, the principle of an automatic classification was specified in order to generate automatic classification codes as well as to perform an automatic subject recognition of the titles included. Whenever necessary, editing, deleting, appending and reindexing of a database can be made in this automatic classification system. Appendix 1 shows the result of the automatic classification of books in the fields of agriculture and medicine. The results of the study are summarized below. 1. The classification number for the title of a book can be automatically generated by using the facet principles of Colon Classification. 2. The automatic subject recognition of a book is achieved by designing a database making use of a globe-principle, and by specifying the subject field for each word. 3. The automatic subject-recognition of input data is achieved by measuring the number of searched words by each subject field. 4. The combination of classification numbers is achieved by flowcharting of classification formular of each subject field. 5. The efficient control of classification numbers is achieved by designing control codes on the database for classification. 6. The automatic classification by means of Auto BC has been proved to be successful in the research library concentrating on a Single field. The general library may have some problem in employing this system. The automatic classification through Auto BC has the following advantages: 1. Speed of the classification process can be improve. 2. The revision or updating of classification schemes can be facilitated. 3. Multiple concepts can be expressed in a single classification code. 4. The consistency of classification can be achieved with the classification formular rather than the classifier's subjective judgement. 5. A user's retrieving process can be made after combining the classification numbers through keywords relating to the material to be searched. 6. The materials can be classified by a librarian without subject backgrounds. 7. The large body of materials can be quickly classified by means of a machine processing. 8. This automatic classification is expected to make a good contribution to design of the total system for library operations. 9. The information flow among libraries can be promoted owing to the use of the same program for the automatic classification.

• KIISE Transactions on Computing Practices
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• v.23 no.3
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• pp.188-193
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• 2017

In this paper, we propose automatic OpenCL optimization techniques that offer the best performance for image processing programs on any hardware system. Developers should seek a proper way of parallelization and an appropriate work-group size for the architecture of target compute devices to achieve the best performance. However, testing potential devices to find them is both time-consuming and costly. Our techniques automatically set up hardware-optimized parallelization and find a suitable work-group size for the target device. Furthermore, using OpenCL does not always provide better performance in image processing. Hence, we also propose a way to automatically search for a threshold image size to allow image processing programs to decide whether or not to use OpenCL. Our findings demonstrate that out techniques improve the image processing performance significantly.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.542-551
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• 2000

In this paper, a novel technique is presented for automatic brain region segmentation in single channel MR image data sets for 3D visualization and analysis. The method detects brain contours in 2D and 3D processing of four steps. The first and the second make a head mask and an initial brain mask by automatic thresholding using a curve fitting technique. The stage 3 reconstructs 3D volume of the initial brain mask by cubic interpolation and generates an intermediate brain mask using morphological operation and labeling of connected components. In the final step, the brain mask is refined by automatic thresholding using curve fitting. This algorithm is useful for fully automatic brain region segmentation of T1-weighted, T2-weighted, PD-weighted, SPGR MRI data sets without considering slice direction and covering a whole volume of a brain. In the experiments, the algorithm was applied to 20 sets of MR images and showed over 0.97 in comparison with manual drawing in similarity index.