• Tuberculosis and Respiratory Diseases
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• v.42 no.5
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• pp.685-694
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• 1995

Introduction: Transthoracic fine needle aspiration biopsy(TNAB) has shown to be a resonably safe, simple, and accurate procedure in diagnosis of intrathoracic lung lesions. We reviewed the results of 1,005 TNAB of chest lesions performed on 930 patients with 20 or 22-gauze needles over a period of 10 years. Methods: From November 1983 to June 1995, 1,005 cases in 930 patients with an undiagnosed lung lesion underwent TNAB at the Hanyang University Hospital: 66% were men and 34% were women. Most of the patients were 40~60 years old and the youngest patient was 3 years of age. Result: 540 patients had various malignant chest lesions and 322 patients had benign pulmonary lesions. The diagnostic accuracy of TNAB was 96.1 percent in malignant diseases with one false positive result and 90.1% in benign diseases. A definitive diagnosis was not obtained in the remaining 68 patients. The most common diagnoses among 519 malignancy chest lesions with TNAB were the following: squamous cell lung carcinoma, 31.7%; adenocarcinoma, 24.7%; small cell lung carcinoma, 16.7%; metastatic cancer, 14.2%; large cell lung carcinoma, 6.2% and so on. Complications included pneumothorax in 12.3% necessitating chest tube drainage in 0.6%. Minor hemoptysis occurred in 3.6%. There was no death directly attributable to the procedure. Conclusion: We concluded that TNAB permits a direct approach to all kinds of localized lung lesions with a high degree of accuracy and without major complications.

• Journal of The Korean Association For Science Education
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• v.35 no.1
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• pp.53-64
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• 2015

This research was performed of high school science classes. These science classes progressed by using Scratch, and surveyed students' perception after finishing each class. This research was conducted of male students who want to choose department of natural science in the next grade. Those classes are consisted of four classes. This study produced a journal, and contained expressions of their thinking and feeling based on experiences during attending classes and projects. Consequently, that journal was analyzed in view of understanding and perception of Scratch using science classes, and it was also included of utilizing Scratch program. Research shows following three conclusions. First, students preferred Scratch using class to general one. They attend more active with high interest, and they felt senses of accomplishment while they make output by themselves. Second, their studies passed through three stages. These are problem perception, problem solving, and producing. Problem solving stage is especially complicated and difficult stage to students. This stage is consisted of Scratch side and Science side. Scratch side has Design and applying process, and Science side has data gathering and analyzing. Students' comprehension of scientific knowledge is increased and is preserved long time through this stage. Last, students had a hard time using Scratch. Because, it is the first time to them to use that program. Therefore, we deemed that they needed to start this kind of experience at lower grade than they are now, such as middle school stage. It is expected that this type of classes are getting more expanded and more populated as a part of students' core ability.

• Archives of design research
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• v.19 no.2 s.64
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• pp.73-80
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• 2006

The main purpose of this study is to help develop the productional system of the three dimensional digital animation domestically. Many 30 digital animation projects are being developed and finished with foreign computer graphics technology. However, the 3D animation market in Korea is not as good as the ones in other countries. One of the most significant problems is the lack of a program of study in Korea concerning productional systems used to create 3D animation. We previously imported an advanced productional system from the U.S., which was adaptable to big projects, and consequently, expanded the international digital animation market. Now, we need to develop a new production system which is fully adaptable to the Korean market. A non-sequential system of 3D digital animation tailored for small projects is more adaptable to domestic industry than the sequential system known as the 'Pipeline system.' A non-sequential system is good for small productions that are trying to create animation on a limited budget. The workers in this system can learn to make animation fast and effectively. They can also learn how to discuss with the others in order to avoid duplication of action. In contrast, in the Pipeline System, many workers repeat confirmation steps during the process for the same animations. The benefit of the non-sequential system is that the worker's interest and education can speed up production, because he/she can quickly learn every step of the animation process instead of just doing a particular job which does not allow him/her to observe the other steps involved. The 'animatic' step is the most important in the non-sequential system. The final animation is produced from the animatic. It is developed from scratch through to the final product but only after the agreement of all the workers, including a director.

• The KIPS Transactions:PartA
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• v.12A no.2 s.92
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• pp.95-102
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• 2005

The Newton-Raphson iterative algorithm for finding a floating point reciprocal which is widely used for a floating point division, calculates the reciprocal by performing a fixed number of multiplications. In this paper, a variable latency Newton-Raphson's reciprocal algorithm is proposed that performs multiplications a variable number of times until the error becomes smaller than a given value. To find the reciprocal of a floating point number F, the algorithm repeats the following operations: '$'X_{i+1}=X=X_i*(2-e_r-F*X_i),\;i\in\{0,\;1,\;2,...n-1\}'$ with the initial value $'X_0=\frac{1}{F}{\pm}e_0'$. The bits to the right of p fractional bits in intermediate multiplication results are truncated, and this truncation error is less than $'e_r=2^{-p}'$. The value of p is 27 for the single precision floating point, and 57 for the double precision floating point. Let $'X_i=\frac{1}{F}+e_i{'}$, these is $'X_{i+1}=\frac{1}{F}-e_{i+1},\;where\;{'}e_{i+1}, is less than the smallest number which is representable by floating point number. So, $X_{i+1}$ is approximate to $'\frac{1}{F}{'}$. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications per an operation is derived from many reciprocal tables $(X_0=\frac{1}{F}{\pm}e_0)$ with varying sizes. The superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a reciprocal unit. Also, it can be used to construct optimized approximate reciprocal tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia scientific computing, etc.

• Journal of Distribution Science
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• v.7 no.4
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• pp.47-56
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• 2009

The purpose of this study is to present an alternative improving the efficient and reasonable of the physical distribution system management is influenced by many factors. Therefore, the study depends on the documentary method and survey method to achieve the purpose of this study. The major components of a physical distribution system are refers to as elements, include warehouse·storage system, transportation system, inventory system, physical distribution information system. The factors used in this study are ① factor of product(quality·A/S·added value of product·adaption of product·technical competitive power to other enterprises), ② factor of market(market channel·kinds of customer·physical distribution share), ③ factor of warehouse·storage(warehouse design·size·direction·storage ability·warehouse quality), ④ factor of transportation(promptness·reliability·responsibility·kinds of transportation·cooperation united transportation system·national transportation network), ⑤ factor of packaging (packaging design·material·educating program·pollution degree measure program), ⑥ factor of inventory(ordinary inventory criterion·consistence for inventories record), ⑦ factor of unloaded(unloaded machine·having machine ratio), ⑧ factor of information system (physical distribution quantity analysis·usable computer part), ⑨ factor of physical distribution cost(sales ratio to product) ⑩ factor of physical distribution system(physical distribution center etc). The implication of this study can be summarized as follows: ① In firms that have not adopted a systems integrative approach, physical distribution is a fragmented and often uncoordinated set of activities spread throughout various functions with function having its own set of priorities and measurements. ② The physical distribution is recognized as more an important strategic factor than a simple cost reduction factor, ③ It can be used a strategic competition tool to enterprise.

• Conservation Science in Museum
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• v.27
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• pp.147-164
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• 2022

Over 200,000 Korean cultural heritage items are currently located abroad. They have made their way to 22 countries under different circumstances and with unique backgrounds. While some of them continue to contribute to promoting Korean culture around the world, others cannot be exhibited due to damage or poor condition. In view of these circumstances, the Overseas Korean Cultural Heritage Foundation (OKCHF) has since 2013 provided museums and art galleries abroad with support for the conservation, restoration, and utilization of the Korean cultural heritage items that they house. As a part of these efforts and on the occasion of the 120th anniversary of the diplomatic relationship between the Republic of Korea and the Kingdom of Belgium in 2021, a gilt-bronze case for acupuncture needles dating to the Goryeo period (918-1392) from the collection of the Royal Museums of Art and History (RMAH), Belgium was brought to Korea for conservation treatment. The primary purpose of this conservation treatment was to restore the original form of the relic and slow to the degree possible the progress of corrosion. The conservation treatment of the gilt-bronze case followed the fundamental order of conservation treatment: removal of corrosive substances, stabilization, and reinforcement. Since this was the first case of restoring metallic cultural properties under the abovementioned support program by the OKCHF, special methodologies distinct from those available in overseas institutions were required. Diverse scientific methods (e.g., X-ray inspection, CT scanning, 3D microscopy) were applied to identify the metalcraft techniques used in the Goryeo period. The analysis found that several designs, including lotus and scrollwork, were exquisitely engraved on the surface of the case by making dots using a round-edged chisel. A bronze plate engraved with designs was rolled into a cylindrical form. The ends were overlapped by 2 to 3 centimeters and then attached to each other by silver soldering. The overlapping ends were welded flat with nearly no gaps. As the final process in the production, the case was lavishly gilt with gold powder using amalgam gilding. The conservation treatment of the gilt-bronze case for acupunctural needles in the RMAH collection restored the original form of the relic and arrested further corrosion. Above all, it revived the historic and academic value of the overseas Korean cultural heritage through scientific analysis.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.143-174
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• 2023

With the development of deep learning technologies, Artificial Intelligence powered Optical Character Recognition (AI-OCR) has evolved to read multiple languages from various forms of images accurately. For the financial industry, where a large number of diverse documents are processed through manpower, the potential for using AI-OCR is great. In this study, we present a configuration and a design of an AI-OCR modality for use in the financial industry and discuss the platform construction with application cases. Since the use of financial domain data is prohibited under the Personal Information Protection Act, we developed a deep learning-based data generation approach and used it to train the AI-OCR models. The AI-OCR models are trained for image preprocessing, text recognition, and language processing and are configured as a microservice architected platform to process a broad variety of documents. We have demonstrated the AI-OCR platform by applying it to financial domain tasks of document sorting, document verification, and typing assistance The demonstrations confirm the increasing work efficiency and conveniences.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.311-328
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• 2022

Because of the spread of smartphones due to the development of information and communication technology, online shopping mall services can be used on computers and mobile devices. As a result, the number of users using the online shopping mall service increases rapidly, and the types of products traded are also growing. Therefore, to maximize profits, companies need to provide information that may interest users. To this end, the recommendation system presents necessary information or products to the user based on the user's past behavioral data or behavioral purchase records. Representative overseas companies that currently provide recommendation services include Netflix, Amazon, and YouTube. These companies support users' purchase decisions by recommending products to users using ratings, purchase records, and clickstream data that users give to the items. In addition, users refer to the ratings left by other users about the product before buying a product. Most users tend to provide ratings only to products they are satisfied with, and the higher the rating, the higher the purchase intention. And recently, e-commerce sites have provided users with the ability to vote on whether product reviews are helpful. Through this, the user makes a purchase decision by referring to reviews and ratings of products judged to be beneficial. Therefore, in this study, the correlation between the product rating and the helpful information of the review is identified. The valuable data of the evaluation is reflected in the recommendation system to check the recommendation performance. In addition, we want to compare the results of skipping all the ratings in the traditional collaborative filtering technique with the recommended performance results that reflect only the 4 and 5 ratings. For this purpose, electronic product data collected from Amazon was used in this study, and the experimental results confirmed a correlation between ratings and review usefulness information. In addition, as a result of comparing the recommendation performance by reflecting all the ratings and only the 4 and 5 points in the recommendation system, the recommendation performance of remembering only the 4 and 5 points in the recommendation system was higher. In addition, as a result of reflecting review usefulness information in the recommendation system, it was confirmed that the more valuable the review, the higher the recommendation performance. Therefore, these experimental results are expected to improve the performance of personalized recommendation services in the future and provide implications for e-commerce sites.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.