Types of innovation can be categorized into simplification, information, automation, and intelligence. Intelligence is the highest level of innovation, and RPA can be seen as one of intelligence. Robotic Process Automation(RPA), a software robot with artificial intelligence, is an example of intelligence that is suited for simple, repetitive, large-scale transaction processing tasks. The RPA, which is already in operation in many companies in Korea, shows what needs to be done to naturally focus on the core tasks in a situation where the need for a strong organizational culture is increasing and the emphasis is on voluntary leadership, strong teamwork and execution, and a professional working culture. The introduction was considered naturally according to the need to find. Robotic Process Automation, or RPA, is a technology that replaces human tasks with the goal of quickly and efficiently handling structural tasks. RPA is implemented through software robots that mimic humans using software such as ERP systems or productivity tools. RPA robots are software installed on a computer and are called robots by the principle of operation. RPA is integrated throughout the IT system through the front end, unlike traditional software that communicates with other IT systems through the back end. In practice, this means that software robots use IT systems in the same way as humans, repeat the correct steps, and respond to events on the computer screen instead of communicating with the system's application programming interface(API). Designing software that mimics humans to communicate with other software can be less intuitive, but there are many advantages to this approach. First, you can integrate RPA with virtually any software you use, regardless of your openness to third-party applications. Many enterprise IT systems are proprietary because they do not have many common APIs, and their ability to communicate with other systems is severely limited, but RPA solves this problem. Second, RPA can be implemented in a very short time. Traditional software development methods, such as enterprise software integration, are relatively time consuming, but RPAs can be implemented in a relatively short period of two to four weeks. Third, automated processes through software robots can be easily modified by system users. While traditional approaches require advanced coding techniques to drastically modify how they work, RPA can be instructed by modifying relatively simple logical statements, or by modifying screen captures or graphical process charts of human-run processes. This makes RPA very versatile and flexible. This RPA is a good example of the application of digital to intelligence(D2I).
Purpose: Breast cancer is known to be more vulnerable to bone metastasis and lymph node metastasis than other types of cancer, and nuclear examinations whole body bone scan and lymphoscintigraphy are performed commonly before and after breast cancer operation. In case whole body bone scan is performed on the day before lymphoscintigraphy, the radiopharmaceutical taken into and remaining in the bones provides anatomical information for tracking and locating sentinel lymph nodes. Thus, this study purposed to examine how much bone density affects in locating sentinel lymph nodes. Materials and Methods: The subjects of this study were 22 patients (average age $52{\pm}7.2$) who had whole body bone scan and lymphoscintigraphy over two days in our hospital during the period from January to December, 2009. In the blind test, 22 patients (average age $57{\pm}6.5$) who had lymphoscintigraphy using $^{57}Co$ flood phantom were used as a control group. In quantitative analysis, the relative ratio of the background to sentinel lymph nodes was measured by drawing ROIs on sentinel lymph nodes and the background, and in gross examination, each of a nuclear physician and a radiological technologist with five years' or longer field experience examined images through blind test in a five-point scale. Results: In the results of quantitative analysis, the relative ratio of the background to sentinel lymph nodes was 14.2:1 maximum and 8.5:1 ($SD{\pm}3.48$) on the average on the front, and 14.7:1 maximum and 8.5:1 ($SD{\pm}3.42$) on the average on the side. In the results of gross examination, when $^{57}Co$ flood phantom images were compared with images containing bones, the score was relative high as 3.86 ($SD{\pm}0.35$) point for $^{57}Co$ flood phantom images and 4.09 ($SD{\pm}0.42$) for bone images. Conclusion: When whole body bone scan was performed on the day before lymphoscintigraphy, the ratio of the background to sentinel lymph nodes was over 10:1, so there was no problem in locating lymph nodes. In addition, we expect to reduce examination procedures and improve the quality of images by indicating the location of sentinel lymph nodes using bone images as body contour without the use of a source.
With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.
Recent years, the use of multimedia information is rapidly increasing, and the video media is the most rising one than any others, and this field Integrates all the media into a single data stream. Though the availability of digital video is raised largely, it is very difficult for users to make the effective video access, due to its length and unstructured video format. Thus, the minimal interaction of users and the explicit definition of video structure is a key requirement in the lately developing image and video management systems. This paper defines the terms and hierarchical video structure, and presents the system, which construct the clustering-based video hierarchy, which facilitate users by browsing the summary and do a random access to the video content. Instead of using a single feature and domain-specific thresholds, we use multiple features that have complementary relationship for each other and clustering-based methods that use normalization so as to interact with users minimally. The stage of shot boundary detection extracts multiple features, performs the adaptive filtering process for each features to enhance the performance by eliminating the false factors, and does k-means clustering with two classes. The shot list of a result after the proposed procedure is represented as the video hierarchy by the intelligent unsupervised clustering technique. We experimented the static and the dynamic movie videos that represent characteristics of various video types. In the result of shot boundary detection, we had almost more than 95% good performance, and had also rood result in the video hierarchy.
Journal of the Korean Association of Geographic Information Studies
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v.23
no.3
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pp.26-67
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2020
Synthetic Aperture Radar(SAR) is able to photograph the earth's surface regardless of weather conditions, day and night. Because of its possibility to search for hydrological factors such as soil moisture and groundwater, and its importance is gradually increasing in the field of water resources. SAR began to be mounted on satellites in the 1970s, and about 15 or more satellites were launched as of 2020, which around 10 satellites will be launched within the next 5 years. Recently, various types of SAR technologies such as enhancement of observation width and resolution, multiple polarization and multiple frequencies, and diversification of observation angles were being developed and utilized. In this paper, a brief history of the SAR system, as well as studies for estimating soil moisture and hydrological components were investigated. Up to now hydrological components that can be estimated using SAR satellites include soil moisture, subsurface groundwater discharge, precipitation, snow cover area, leaf area index(LAI), and normalized difference vegetation index(NDVI) and among them, soil moisture is being studied in 17 countries in South Korea, North America, Europe, and India by using the physical model, the IEM(Integral Equation Model) and the artificial intelligence-based ANN(Artificial Neural Network). RADARSAT-1, ENVISAT, ASAR, and ERS-1/2 were the most widely used satellite, but the operation has ended, and utilization of RADARSAT-2, Sentinel-1, and SMAP, which are currently in operation, is gradually increasing. Since Korea is developing a medium-sized satellite for water resources and water disasters equipped with C-band SAR with the goal of launching in 2025, various hydrological components estimation researches using SAR are expected to be active.
Journal of the Institute of Electronics and Information Engineers
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v.50
no.4
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pp.219-228
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2013
The surveillance imaging equipments are functioning to observe the shape of the target in real time or to measure its location precisely. The roles of such equipments are becoming more important in today's weapon systems.The aforementioned imaging equipments can be classified based on the modes of operations such as fixed, installed on cars, or composite of those. Also, according to different concepts of sensor operation, a separate type uses independent housing for each sensor whereas in a composite type a set of multiple sensors are housed into a unit altogether. The sensors in general have magnetism, thereby introducing the possible negative effects, particularly in the composite types, in locating the reference position, which is carried out by the digital compass. The use of shielding material/housing could be an option but results in increased weight and reduced portability, restricting its use in composite type equipments. As such, the objective of this paper is to study on how to reduce such magnetic effects on the position location. To do so, in the absence of magnetic shielding, a variety of sensor positions were first modeled. By combing the result with the fact that the functions of PAN & Tilt are used in the equipments, a new position location algorithm is proposed. The use of the new algorithm can automate the position location process as compared to the manual process of the existing approach. In the algorithm developed, twelve locations are measured in connection with both the azimuth and elevation angles in comparison to the six locations alone around the azimuth angle. As a result, it turns out that the measurement range has been widened but the measurement time reduced. Also, note that the effect of errors the operators may make during measurement could be reduced.
Journal of the Korea Academia-Industrial cooperation Society
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v.18
no.9
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pp.425-435
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2017
Structural analysis is used not only for large enterprises, but also for small and medium sized ones, as a necessary procedure for strengthening the certification process for product delivery and shortening the time in the process from concept design to detailed design. Open-source solvers that can be used atlow cost differ from commercial solvers. If there is a problem with the input data, such as with the grid, errors or failures can occur in the calculation step. In this paper, we propose a pre- and post-processor that can be easily applied to the analysis of mechanical structural problems by using the existing structural analysis open source solver (Caculix, Code_Aster). In particular, we propose algorithms for analyzing different types of data using open source solvers in order to extract and generate accurate information,such as 3D models, grids and simulation conditions, and develop and apply information analysis. In addition, to improve the accuracy of open source solvers and to prevent errors, we created a grid that matches the solver characteristics and developed an automatic healing function for the grid model. Finally, to verify the accuracy of the system, the verification and utilization results are compared with the software used.
As part of an effort to leap smart cadastre system by doing rearrangement of various mismatches in the land register, the cadastre renovation project is being recently conducted. In response to this demand, this paper proposes an image-based rapid parcel boundary demarcation plan using the high resolution aerial image with a GSD (Ground Sample Distance) of 5cm that matches to real ground boundary situation in residential area. To review the feasibility and accuracy of this proposed methodology, we compared the accuracy of parcel boundary point and parcel area extracted from the digital stereo plotting on the basis of results of cadastral boundary surveying and land register over the selected two test areas. The comparative accuracy result of all boundary points by digital stereo plotting is satisfied with accuracy requirement according to the criteria of the enforcement regulation of cadastral surveying, whereas it exceeded allowable error of ${\pm}0.07m$, more strictly specified in the Special Act on Cadastral Renovation. And about 20% of the total 70 parcels extracted by digital plotting are out of area tolerance in Jecheon study area, and 10% of the total 19 parcels in Suwon study area. The parcels exceeding accuracy limit are mostly due to the occlusion caused by building roof or eaves, and the obstacles such as trees existing on the boundary. Furthermore, an object identification is impossible in image because of vague boundary reference in case of nonexistence of man-made structures or natural features. Therefore, the utilization of boundary identification stickers is recommended as a solution for these types of land parcel.
Journal of the Institute of Electronics and Information Engineers
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v.54
no.4
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pp.68-74
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2017
This paper presents a joint demosaicking and arbitrary-ratio down sampling algorithm for color filter array (CFA) images. Color demosaiking is a necessary part of image signal processing pipeline for many types of digital image recording system using single sensor. Also, such as smart phone, obtained high resolution image from image sensor has to be down-sampled to be displayed on the screen. The conventional solution is "Demosaicking first and down sampling later". However, this scheme requires a significant amount of memory and computational cost. Also, artifacts can be introduced or details get damaged during demosaicking and down sampling process. In this paper, we propose a method in which demosaicking and down sampling are working simultaneously. We use inverse mapping of Bayer CFA and then joint demosaicking and down sampling with arbitrary-ratio scheme based on signal decomposition of high and low frequency component in input data. Experimental results show that our proposed algorithm has better image quality performance and much less computational cost than those of conventional solution.
Questionaires on symptoms of respiratory disease have been used in Korea to elicit the probable health effects of air pollution in epidemiologic studies: The objectives of such studies often include comparing prevalence of symptoms of respiratory system between different population groups or between the same population groups, at different times. Unfortunately, little attention has, been paid to standardization of those questionaires, whether those are Korean. versions or not. Furthermore, no attempt to develop Korean ,questionaire on respiratory symptoms and relevant information has been made. Followed by 'a comparative study on responses to Korean version questionaires(English origin) of CMI, MRC, and ATS-DLD-78' two types of questionaires on respiratory symptoms and relevant information for Korean adult, which are short form (SUN-81-AS) and long forms (optional questions are added to the short one, SUN-81-AL), have been designed suitable to Korean background by authors (see Annex). The self-administered and closed-question questionaire were tested their validity and reliability by administration to l80 normal adults (medical and nursing students) and 60 clinical patients of Seoul National University Hospital, with spirometric exam. The results obtained and conclusions drawn are as follow: 1. It took less than 10 minutes to complete the questionaire SNU-81-AS and SNU-81-AL. 2. The test-retest reliability of each questions in AS and AL ,were observed as 92.7% and 92.1%, respectively. And all of the level of agreement are statistically significant with kappa statistic. 3. In addition to higher prevalence rate of symptoms in patients group compared, with, normal. group, the correlations between FEV 1.0/FVC predictive value(%) and number of symptoms were statistically significant inpatients group (See Fig. 1 and, Table 7). 4. The answer rate to optional questions in AL form among those who are not to do was about 10%, while the no-answer rate among who are to do was about 15% in Normal (medical and nursing students) group. 5. From the viewpoints of validity and reliability, the new Korean questionaire (SNU-81-AS and AL) developed by authors are to be recommendable to use in epidemiologic studies on respiratory illness in Korea. The self-administration, however, of optional questions in AL form may not assure the quality of data gathered.
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