• Journal of the Semiconductor & Display Technology
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• v.23 no.2
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• pp.71-75
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• 2024

This research focuses on processing unstructured data efficiently, containing various formulas in document processing and management regarding the terms and rules of domestic insurance documents using text mining techniques. Through parsing and compilation technology, document context, content, constants, and variables are automatically separated, and errors are verified in order of the document and logic to improve document accuracy accordingly. Through document debugging technology, errors in the document are identified in real time. Furthermore, it is necessary to predict the changes that intelligent document processing will bring to document management work, in particular, the impact on documents and utilization tasks that are double managed due to various formulas and prepare necessary capabilities in the future.

• Journal of the Korean Data and Information Science Society
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• v.24 no.5
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• pp.989-998
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• 2013

We cannot analyze big data, which attracts recent attentions in industry and academy, by batch processing algorithms developed in data mining because big data, by definition, cannot be uploaded and processed in the memory of a single system. So an imminent issue is to develop various leaning algorithms so that they can be applied to big data. In this paper, we review various algorithms for support vector machines in the literature. Particularly, we introduce online type and parallel processing algorithms that are expected to be useful in big data classifications and compare the strengths, the weaknesses and the performances of those algorithms through simulations for linear classification.

• The Korean Journal of Pesticide Science
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• v.13 no.4
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• pp.209-215
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• 2009

This study was performed to produce the processing factors of pesticides in dried carrot. It is essential data for establishing the maximum residue limits (MRLs) of pesticides in dried carrot. The target pesticides were azinphos-methyl, chlorpyrifos, captan, endosulfan and triclorfon. These pesticides are included Korea's MRL list in carrot and USA's MRL list in dried foods. To infiltrate these pesticides up to each MRL level in carrot, the dipping test was performed in laboratory. Also, the supervised residue trial of the pesticide for carrot was conducted in the green house to recognize the field trial's tendency. In the dipping test in laboratory (including drying examination), the processing factors of the carrot at various concentrations and temperatures could be evaluated. In field test, the processing factors were 5.9 for azinphos-methyl, 1.7 for captan, 7.6 for chlorpyrifos, 6 for endosulfan, 0 for trichlorfon, respectively. The dipping test in laboratory on various kinds of conditions showed more precise processing factors than field trial. The processing factors obtained from the dipping test of carrot were 0~4.7 at the various concentration of the pesticides, and 0~6.7 at various drying temperature. The lower level processing factors were 0~0.6 for trichlorfon and the higher level were 3.0~5.8 for chlorpyrifos. The highest processing factor was 9.1 for captan.

• Electronics and Telecommunications Trends
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• v.35 no.3
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• pp.66-75
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• 2020

As the increasing expectations of a practical AI (Artificial Intelligence) service makes AI algorithms more complicated, an efficient processor to process AI algorithms is required. To meet this requirement, processors optimized for parallel processing, such as GPUs (Graphics Processing Units), have been widely employed. However, the GPU has a generalized structure for various applications, so it is not optimized for the AI algorithm. Therefore, research on the development of AI processors optimized for AI algorithm processing has been actively conducted. This paper briefly introduces an AI processor especially for inference acceleration, developed by the Electronics and Telecommunications Research Institute, South Korea., and other global vendors for mobile and server platforms. However, the GPU has a generalized structure for various applications, so it is not optimized for the AI algorithm. Therefore, research on the development of AI processors optimized for AI algorithm processing has been actively conducted.

• Journal of Acupuncture Research
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• v.15 no.2
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• pp.1-15
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• 1998

Purpose : The study for changes in components and acitvities of Artemisiae Herba at various processing temperature is generally regarded as a foundation in setting the optimum heat-processing temperature and for getting the maximum activities for medical usage of this herb. Methods: Therefore some experiments were performed either in vitro or in vivo and various changes were observed - the changes in the weitht of Artemisiae Herba, the changes in the relative amount of three kinds of extracts from Artemisiae Herba ( diluted ethanol extract, water extract, ether extract ), the TLC pattern of essential oil at various processing temperature, the existance of inhibitory effects both on ${\beta}$-Glucuronidase activities, and on heat-induced hemolysis, the effects on increased vascular permeability. The valid results derived from the experiments are as follows. Results: 1. The weight of Artemisiae Herba prominently decreased at 240^{\circ}C$. 2. The contents of diluted ether extract were maximum in the unprocessing condition. Those of water extract were maximum at 180^{\circ}C$ and at 210^{\circ}C$. and the changes of diluted ethanol extract at 150^{\circ}C$. 3. The TLC pattern of essential oil in Artemisiae Herba at various processing temperature showed that a component began to increase at Rf 0.56 and another component began to decrease at Rf 0.86. 4. The contents of Eupatilin in Artemisiae Herba at various processing temperature continued to decreased in proportion to the temperature rise, the extent of which was prominent at 210^{\circ}C$, and was unnoticeable at 270^{\circ}C$. 5. Inhibitory effects on ${\beta}$-Glucuronidase activities, trypsin activities and heat-induced hemolysis increased in proportion to the density of Artemisiae Herba. Inhibitory effects on ${\beta}$-Glucuronidase activities and trypsin activities were relatively high at 180^{\circ}C$ while on the writhing syndrome and inhibitory effects on increased vascular permeability induced by acetic acid were maximum at 240^{\circ}C$. those on heat-induced hemolysis were relatively high at 240^{\circ}C$. 6. In vivo, both analgesic effects Conclusions: To maximize of the effectiveness of Artemmisiae Herba, the ideal heating temperature is in the range of 180^{\circ}C{\sim}240^{\circ}C$.

• Transactions of Materials Processing
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• v.24 no.1
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• pp.5-12
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• 2015

In the current study, fundamental deep drawing characteristics of Ti-6Al-4V alloy sheets were investigated to establish the effect of processing conditions on large size square deep drawn cups. To accomplish this study, FE-simulations (Abaqus) were performed to determine optimum blank size, friction coefficient, the gap between punch and die, etc. The simulated processing parameters were verified experimentally. Based on the FE-simulation results, deep drawing was performed with various blank holding loads and sample sizes. In order to improve the formability of Ti-6Al-4V sheet, various lubricant methods were evaluated. Tensile tests and thickness measurements were conducted on the formed sheets. Processing parameters including blank holding force, lubricants, and optimum blank size, were selected to achieve improved drawing quality. With the optimum processing condition, a $200mm{\times}200mm$ cup was deep drawn successfully.

• Journal of KIISE:Databases
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• v.37 no.5
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• pp.250-257
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• 2010

As the variant of skyline query processing, reverse skyline Queries have been studied. However, the existing methods for processing reverse skyline Queries have the limitation of service domains and spend high costs to provide various location-based services. In this paper, we propose a new reverse skyline Query processing method that efficiently processes a query with the objects in metric spaces. In addition, the proposed method also processes continuous reverse skyline queries efficiently. In order to show the superiority of the proposed scheme, we compare it with the previous reverse skyline 벼ery processing scheme in various environments. As a result, the proposed method achieves better performance than the existing method.

• Proceedings of the Korean Society of Laser Processing Conference
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• 1999.05a
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• pp.24-26
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• 1999

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.320-320
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• 2022

Coriander(Coriandrum sativum L.) belongs to the family Umbelliferae/Apiaceae. It is cultivated as a spice and medicinal herb around the world, including its leaves and seeds. Coriander leaves have soft and fragrant, so they can be used in cuisines such as China, Mexico, and, Southeast Asia. Coriander leaves contain a high amount of vitamin C, carotene, and multiple polyphenols. Coriander essential oils and extracts have various chemical components and are known to have antioxidant, antibacterial, and antifungal activities. This study was carried out for resource discovery, propagation, and DB construction of aromatic plants. In order to evaluate the genetic characteristics, 30 kinds of Coriander seeds were supplied from the Center for Genetic Resources. The evaluation of characteristics of the basal part leaf number, leaf shape, and plant height was investigated. Also, Essential oils extract from various parts of plants including the leaves, flowers, and steam isolated by simultaneous distillation extraction(SDE) apparatus. In the results, heights showed growing to 70 cm over and basal part leaf number 0 to7. The leaves are variable, they are measured according to leaves incisions, and most of the included incision. The qualitative analysis of EOs was performed using gas chromatography-mass spectrometry. EOs had various chemical compositions. Major compounds were trans-2-Decenal, linalool, decanal, 2-Dodecenal, 13-Tetradecanal, 2-Undecenal.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.4
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• pp.306-311
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• 2020

This paper deals with how to improve the performance of Python language with various libraries when developing a model using big data. The Python language uses the Pandas library for processing spreadsheet-format data such as Excel. In processing data, Python operates on an in-memory basis. There is no performance issue when processing small scale of data. However, performance issues occur when processing large scale of data. Therefore, this paper introduces a method for distributed processing of execution tasks in a single cluster and multiple clusters by using a Dask library that can be used with Pandas when processing data. The experiment compares the speed of processing a simple exponential model using only Pandas on the same specification hardware and the speed of processing using a dask together. This paper presents a method to develop a model by distributing a large scale of data by CPU cores in terms of performance while maintaining that python's advantage of using various libraries is easy.