• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1449-1463
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• 2020

As recent global warming and climate changes become more serious, the importance of CO2 absorption by forests is increasing to cope with the greenhouse gas issues. According to the UN Framework Convention on Climate Change, it is required to calculate national CO2 absorptions at the local level in a more scientific and rigorous manner. This paper presents the gridded expansion of forest flux observations and mapping of daily CO2 absorption by the forests in Korea using numerical weather prediction data and satellite images. To consider the sensitive daily changes of plant photosynthesis, we built a machine learning model to retrieve the daily RACA (reference amount of CO2 absorption) by referring to the climax forest in Gwangneung and adopted the NIFoS (National Institute of Forest Science) lookup table for the CO2 absorption by forest type and age to produce the daily AACA (actual amount of CO2 absorption) raster data with the spatial variation of the forests in Korea. In the experiment for the 1,095 days between Jan 1, 2013 and Dec 31, 2015, our RACA retrieval model showed high accuracy with a correlation coefficient of 0.948. To achieve the tier 3 daily statistics for AACA, long-term and detailed forest surveying should be combined with the model in the future.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.

• Journal of Acupuncture Research
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• v.21 no.3
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• pp.283-302
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• 2004

Background : Angiogenesis is the proliferation of a network of blood vessels emanating from pre-existing vessels, supplying nutrients and oxygen and removing waste products. Angiogenesis occurs in a variety of normal physiologic and pathologic conditions and is regulated by a balance of stimulatory and inhibitory angiogenic factors. Excessive angiogenesis should be suppressed. However, if blood supply is insufficient, it should be encouraged. Hyul-Mek(血脈) or Hyul-Rark(血絡), known as blood vessels in western medicine, is deeply related to Chung-Ki-Hyul(精 氣 血). The goal of this study is to review the effects of herbal medicines on angiogenesis that is involved in wound healing and enhancement of blood supply. Methods : We conducted a systematic and comprehensive literature search for the identification, retrieval, and bibliographic management of independent studies to locate information on the topic. A computerized search of the published literature of Korea(KISS, RISS), China(CNKI), Japan(Kampo medicine, etc), and western countries(MEDLINE) was performed, and further supplemented with manual searches of print sources(1999 to 2003). Results : The herbal medicines with angiogenic activity were mainly found among herbs that carry replenish Shin-Cheng(補腎益精), foster Eum and improve the circulation of blood(養陰活血), or warm and circulate Kyung-Rark(溫經通絡). In particular, herbs with improve the circulation of blood and clear blood(活血化瘀) activity contain a significant amount of tannin, saponin, and pyrazine. Conclusion : Replenish Ki-Hyul(補氣血) and circulate Kyung-Rark(通經絡) could contribute to the induction of angiogenesis because various growth factors and proliferation, differentiation, and migration of vascular endothelial cells are involved in angiogenic activity.

• Korean Journal of Remote Sensing
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• v.32 no.4
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• pp.365-382
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• 2016

The results from the Global Positioning System (GPS) measurements of the Mobile Observation Vehicle (MOVE) on the eastern coast of Korea have been compared with REFerence (REF) values from the fixed GPS sites to assess the performance of Precipitable Water Vapor (PWV) retrievals in a kinematic environment. MOVE-PWV retrievals had comparatively similar trends and fairly good agreements with REF-PWV with a Root-Mean-Square Error (RMSE) of 7.4 mm and $R^2$ of 0.61, indicating statistical significance with a p-value of 0.01. PWV retrievals from the June cases showed better agreement than those of the other month cases, with a mean bias of 2.1 mm and RMSE of 3.8 mm. We further investigated the relationships of the determinant factors of GPS signals with the PWV retrievals for detailed error analysis. As a result, both MultiPath (MP) errors of L1 and L2 pseudo-range had the best indices for the June cases, 0.75-0.99 m. We also found that both Position Dilution Of Precision (PDOP) and Signal to Noise Ratio (SNR) values in the June cases were better than those in other cases. That is, the analytical results of the key factors such as MP errors, PDOP, and SNR that can affect GPS signals should be considered for obtaining more stable performance. The data of MOVE can be used to provide water vapor information with high spatial and temporal resolutions in the case of dramatic changes of severe weather such as those frequently occurring in the Korean Peninsula.

• The KIPS Transactions:PartB
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• v.12B no.6 s.102
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• pp.703-714
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• 2005

Researches in text categorization have been confined to whole-document-level classification, probably due to lacks of full-text test collections. However, full-length documents availably today in large quantities pose renewed interests in text classification. A document is usually written in an organized structure to present its main topic(s). This structure can be expressed as a sequence of sub-topic text blocks, or passages. In order to reflect the sub-topic structure of a document, we propose a new passage-level or passage-based text categorization model, which segments a test document into several Passages, assigns categories to each passage, and merges passage categories to document categories. Compared with traditional document-level categorization, two additional steps, passage splitting and category merging, are required in this model. By using four subsets of Routers text categorization test collection and a full-text test collection of which documents are varying from tens of kilobytes to hundreds, we evaluated the proposed model, especially the effectiveness of various passage types and the importance of passage location in category merging. Our results show simple windows are best for all test collections tested in these experiments. We also found that passages have different degrees of contribution to main topic(s), depending on their location in the test document.

• Journal of KIISE
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• v.44 no.10
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• pp.1112-1123
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• 2017

As content providers further offload content-centric services to the cloud, data retrieval over the cloud typically results in many redundant items because there is a prevalent near-duplication of content on the Internet. Simply fetching all data from the cloud severely degrades efficiency in terms of resource utilization and bandwidth, and data can be encrypted by multiple content providers under different keys to preserve privacy. Thus, locating near-duplicate data in a privacy-preserving way is highly dependent on the ability to deduplicate redundant search results and returns best matches without decrypting data. To this end, we propose an efficient near-duplicate detection scheme for encrypted data in the cloud. Our scheme has the following benefits. First, a single query is enough to locate near-duplicate data even if they are encrypted under different keys of multiple content providers. Second, storage, computation and communication costs are alleviated compared to existing schemes, while achieving the same level of search accuracy. Third, scalability is significantly improved as a result of a novel and efficient two-round detection to locate near-duplicate candidates over large quantities of data in the cloud. An experimental analysis with real-world data demonstrates the applicability of the proposed scheme to a practical cloud system. Last, the proposed scheme is an average of 70.6% faster than an existing scheme.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.73-86
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• 2016

In this study, an algorithm to estimate Aerosol Optical Thickness (AOT) over small cities during nighttime has been developed by using the radiance from artificial light sources in small cities measured from Visible Infrared Imaging Radiometer Suite (VIIRS) sensor's Day/Night Band (DNB) aboard the Suomi-National Polar Partnership (Suomi-NPP) satellite. The algorithm is based on Beer's extinction law with the light sources from the artificial lights over small cities. AOT is retrieved for cloud-free pixels over individual cities, and cloud-screening was conducted by using the measurements from M-bands of VIIRS at infrared wavelengths. The retrieved nighttime AOT is compared with the aerosol products from MODerate resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites. As a result, the correlation coefficients over individual cities range from around 0.6 and 0.7 between the retrieved nighttime AOT and MODIS AOT with Root-Mean-Squared Difference (RMSD) ranged from 0.14 to 0.18. In addition, sensitivity tests were conducted for the factors affecting the nighttime AOT to estimate the range of uncertainty in the nighttime AOT retrievals. The results of this study indicate that it is promising to infer AOT using the DNB measaurements over small cities in Korea at night. After further development and refinement in the future, the developed retrieval algorithm is expected to produce nighttime aerosol information which is not operationally available over Korea.

• Korean Journal of Cognitive Science
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• v.20 no.1
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• pp.79-107
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• 2009

Episodic memory, i.e. memorization of information within a spatiotemporal environment, is affected Alzheimer's disease(AD), but its impairment may also be occurred in the normal aging process. The purpose of this study is to analyze and evaluate memory in with Dementia of Alzheimer Type by examining their cognitive skills in episodic memory using the technique. This new method involves assessing the mental images the subject's own past in the mind like projected and movies. Three patients in the early stage of Dementia of Alzheimer Type, one with mild depression, and 2 healthy controls for comparison were asked to retrieve their episodic memory of the previous day, week, month, and a day testing day. The answers were then analyzed with regards to their specific features as emotional state, color, and time order. In the following day, the subjects were tasked to recall again the images they reproduced in the day's test order to observe of memory. Results showed that all 3 patients failed to arrange the retrieved images in time order and their images of the previous day were unclear in color and were stationary like photographs, even when they reproduced the mental images at much quantity as controls. patients could not remember particular events of yesterday, and only recalled the general occurrences of every day life. These results suggest that in the early stage of Dementia of Alzheimer Type, difficulties in the retrieval of recent episodic memory begin to primarily occur, and qualitative impairment happens earlier than quantitative.

• The KIPS Transactions:PartC
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• v.13C no.6 s.109
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• pp.709-716
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• 2006

According to the increase of various AV media devices and contents in the digital home, the DLNA becomes to play an important role as the interoperability standard between then Since this guideline only focuses on the interoperability among home networked devices, media players, and media contents existing inside of the homenetwork, there is no retrieval and transmission method for sharing multimedia contents located over several homes via Internet. Additionally, this guideline lets device-detection and notification messages to be transmitted using W multicast methods, and current Internet environment cannot guarantee consistent IP multicast services, it has the limitation that it cannot retrieve and control DLNA devices in other digital homes remotely via the Internet. Therefore, in this paper, we propose the IHM(Inter-Home Media) proxy system and its operating mechanism to provide a way of sharing media contents distributed over multiple DLNA-based homes, through analyzing these limitations and building up a sharing method for A/V media contents distributed over the DLNA homes based on the dynamic or private IP networks. Our method removes the limitation on the user locations through sharing distributed media contents, and also makes cost-downs for storing media contents, from the view point of individual residents.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.1-8
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• 2020

The need for storage, management, and retrieval techniques for alternative data has emerged as technologies based on data generated from business activities conducted by enterprises have emerged as the key to business success in recent years. Existing big data platform systems must load a large amount of data generated in real time without delay to process unstructured data, which is an alternative data, and efficiently manage storage space by utilizing a deduplication system of different storages when redundant data occurs. In this paper, we propose a multi-layer distributed data deduplication process system using the similarity of the Cuckoo hashing filter technique considering the characteristics of big data. Similarity between virtual machines is applied as Cuckoo hash, individual storage nodes can improve performance with deduplication efficiency, and multi-layer Cuckoo filter is applied to reduce processing time. Experimental results show that the proposed method shortens the processing time by 8.9% and increases the deduplication rate by 10.3%.