• Title/Summary/Keyword: Network Convergence

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Implant Isolation Characteristics for 1.25 Gbps Monolithic Integrated Bi-Directional Optoelectronic SoC (1.25 Gbps 단일집적 양방향 광전 SoC를 위한 임플란트 절연 특성 분석)

  • Kim, Sung-Il;Kang, Kwang-Yong;Lee, Hai-Young
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.44 no.8
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    • pp.52-59
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    • 2007
  • In this paper, we analyzed and measured implant isolation characteristics for a 1.25 Gbps monolithic integrated hi-directional (M-BiDi) optoelectronic system-on-a-chip, which is a key component to constitute gigabit passive optical networks (PONs) for a fiber-to-the-home (FTTH). Also, we derived an equivalent circuit of the implant structure under various DC bias conditions. The 1.25 Gbps M-BiDi transmit-receive SoC consists of a laser diode with a monitor photodiode as a transmitter and a digital photodiode as a digital data receiver on the same InP wafer According to IEEE 802.3ah and ITU-T G.983.3 standards, a receiver sensitivity of the digital receiver has to satisfy under -24 dBm @ BER=10-12. Therefore, the electrical crosstalk levels have to maintain less than -86 dB from DC to 3 GHz. From analysed and measured results of the implant structure, the M-BiDi SoC with the implant area of 20 mm width and more than 200 mm distance between the laser diode and monitor photodiode, and between the monitor photodiode and digital photodiode, satisfies the electrical crosstalk level. These implant characteristics can be used for the design and fabrication of an optoelectronic SoC design, and expended to a mixed-mode SoC field.

Analysis and Design of Profiling Adaptor for XML based Energy Storage System (XML 기반의 에너지 저장용 프로파일 어댑터 분석 및 설계)

  • Woo, Yongje;Park, Jaehong;Kang, Mingoo;Kwon, Kiwon
    • Journal of Internet Computing and Services
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    • v.16 no.5
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    • pp.29-38
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    • 2015
  • The Energy Storage System stores electricity for later use. This system can store electricity from legacy electric power systems or renewable energy systems into a battery device when demand is low. When there is high electricity demand, it uses the electricity previously stored and enables efficient energy usage and stable operation of the electric power system. It increases the energy usage efficiency, stabilizes the power supply system, and increases the utilization of renewable energy. The recent increase in the global interest for efficient energy consumption has increased the need for an energy storage system that can satisfy both the consumers' demand for stable power supply and the suppliers' demand for power demand normalization. In general, an energy storage system consists of a Power Conditioning System, a Battery Management System, a battery cell and peripheral devices. The specifications of the subsystems that form the energy storage system are manufacturer dependent. Since the core component interfaces are not standardized, there are difficulties in forming and operating the energy storage system. In this paper, the design of the profile structure for energy storage system and realization of private profiling system for energy storage system is presented. The profiling system accommodates diverse component settings that are manufacturer dependent and information needed for effective operation. The settings and operation information of various PCSs, BMSs, battery cells, and other peripheral device are analyzed to define profile specification and structure. A profile adapter software that can be applied to energy storage system is designed and implemented. The profiles for energy storage system generated by the profile authoring tool consist of a settings profile and operation profile. Setting profile consists of configuration information for energy device what composes energy saving system. To be more specific, setting profile has three parts of category as information for electric control module, sub system, and interface for communication between electric devices. Operation profile includes information in relation to the method in which controls Energy Storage system. The profiles are based on standard XML specification to accommodate future extensions. The profile system has been verified by applying it to an energy storage system and testing charge and discharge operations.

An Analysis of Social Perception on Forest Using News Big Data (뉴스 빅데이터를 활용한 산림에 대한 사회적 인식 변화 분석)

  • Jang, Youn-Sun;Lee, Ju-Eun;Na, So-Yeon;Lee, Jeong-Hee;Seo, Jeong-Weon
    • Journal of Korean Society of Forest Science
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    • v.110 no.3
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    • pp.462-477
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    • 2021
  • The purpose of this study was to understand changes in domestic forest policy and social perception of forests from a macro perspective using big data analysis of news articles and editorials. A total of 13,570 'forest' related data were collected from metropolitan and economic journals from 1946-2017 using keyword and CONCOR (Convergence of iterated Correlations) analysis. First, we found the percentage of articles and editorials using the keyword 'forest'increased overall. Second, news data on 'forest' in the field of reporting was concentrated in the "social" sector during the first period (1946-1966), followed by forest-related issues expanding to various fields from the second (1967-1972) to fifth (1988-1997) periods, then toward the "culture" sector in the sixth (1998-2007) and "politics" after the seventh (2008-2017) period. Third, we found changes in the policy paradigm over time significantly changed social awareness. In the first and second periods, people experienced livelihood issues rather than forest greening or forest protection policy and expanded their awareness of planned and scientific afforestation (third) to environmental protection (fourth) and ecological perspectives (sixth to seventh). The key outcome of our analysis was leveraging news big data that reflected polices on forests and public social perception To further derive future social issues,more in-depth analysis of public discourse and perception will be possible using textual big data and GDP of various social network services (SNS), such as combining blogs and YouTube.

Convergence of Remote Sensing and Digital Geospatial Information for Monitoring Unmeasured Reservoirs (미계측 저수지 수체 모니터링을 위한 원격탐사 및 디지털 공간정보 융합)

  • Hee-Jin Lee;Chanyang Sur;Jeongho Cho;Won-Ho Nam
    • Korean Journal of Remote Sensing
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    • v.39 no.5_4
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    • pp.1135-1144
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    • 2023
  • Many agricultural reservoirs in South Korea, constructed before 1970, have become aging facilities. The majority of small-scale reservoirs lack measurement systems to ascertain basic specifications and water levels, classifying them as unmeasured reservoirs. Furthermore, continuous sedimentation within the reservoirs and industrial development-induced water quality deterioration lead to reduced water supply capacity and changes in reservoir morphology. This study utilized Light Detection And Ranging (LiDAR) sensors, which provide elevation information and allow for the characterization of surface features, to construct high-resolution Digital Surface Model (DSM) and Digital Elevation Model (DEM) data of reservoir facilities. Additionally, bathymetric measurements based on multibeam echosounders were conducted to propose an updated approach for determining reservoir capacity. Drone-based LiDAR was employed to generate DSM and DEM data with a spatial resolution of 50 cm, enabling the display of elevations of hydraulic structures, such as embankments, spillways, and intake channels. Furthermore, using drone-based hyperspectral imagery, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were calculated to detect water bodies and verify differences from existing reservoir boundaries. The constructed high-resolution DEM data were integrated with bathymetric measurements to create underwater contour maps, which were used to generate a Triangulated Irregular Network (TIN). The TIN was utilized to calculate the inundation area and volume of the reservoir, yielding results highly consistent with basic specifications. Considering areas that were not surveyed due to underwater vegetation, it is anticipated that this data will be valuable for future updates of reservoir capacity information.

A Study on the Restructuration of Norm System in the Field of ICT for the Smart Media (Smart미디어시대 정보통신·미디어(ICT) 분야 규범체계의 재구조화에 관한 연구)

  • Ji, Seong-Woo
    • Journal of Legislation Research
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    • no.44
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    • pp.33-62
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    • 2013
  • In this paper, the consolidation of ICT basic legislation and ICT special legislation concerning "Ministry of Science, ICT and Future Planning" and "Korea Communications Commission" which came on the back of governmental reorganization in recent years is discussed in the theoretical and practical aspect. Development of "data communication technology" innovatively changed the method of livelihood of mankind, the emergence of network under global dimension provided financial social benefit and posed a challenge and a threat at the same time. Form digital revolution human kind can expect to receive many important blessings. Nevertheless, there are many advantages of development of technology by digital revolution, cyberspace like online media, internet etc. has realistically many problems that must be solved. To maximum positive aspects like the expansion of freedom of expression and creating plan of economy by the advance of transmission technology is needed. And to minimize side effects of informatization is required more. The First, Special Act on ICT has an adaptation in normative standardization to be fit in media convergence beyond convergence of broadcasting and telecommunications. Henceforth, there must be established a legal basis for the achievement of protection of economic evolution and freedom of speech in digital media, information, communication technology and content development. The second, the government action is to accomplish economic development and freedom of information in structural aspect of norm. Therefore minimizing normative problem by reorganization of organization remains clearly unresolved in politics. The third, Special Act on ICT must be basic law covering info-communications field, pay telecommunication and media contents field. The forth, from a technical point of view, net neutrality, conflict of interest for digital content and so on can be fixed easily. Special Act on ICT must not only pursuit of development of industry. Special Act on ICT and pursuit of enhancing quality of life of people and preparing program to promote democratization. From now on, we need to make powerful nation of information& communications technology and in information human rights protection field got to be one step ahead of others with reference to appear all the various aspects must be brought together in the discussion of legislation process of Special Act on ICT.

Immune Cells Are Differentially Affected by SARS-CoV-2 Viral Loads in K18-hACE2 Mice

  • Jung Ah Kim;Sung-Hee Kim;Jeong Jin Kim;Hyuna Noh;Su-bin Lee;Haengdueng Jeong;Jiseon Kim;Donghun Jeon;Jung Seon Seo;Dain On;Suhyeon Yoon;Sang Gyu Lee;Youn Woo Lee;Hui Jeong Jang;In Ho Park;Jooyeon Oh;Sang-Hyuk Seok;Yu Jin Lee;Seung-Min Hong;Se-Hee An;Joon-Yong Bae;Jung-ah Choi;Seo Yeon Kim;Young Been Kim;Ji-Yeon Hwang;Hyo-Jung Lee;Hong Bin Kim;Dae Gwin Jeong;Daesub Song;Manki Song;Man-Seong Park;Kang-Seuk Choi;Jun Won Park;Jun-Won Yun;Jeon-Soo Shin;Ho-Young Lee;Ho-Keun Kwon;Jun-Young Seo;Ki Taek Nam;Heon Yung Gee;Je Kyung Seong
    • IMMUNE NETWORK
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    • v.24 no.2
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    • pp.7.1-7.19
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    • 2024
  • Viral load and the duration of viral shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are important determinants of the transmission of coronavirus disease 2019. In this study, we examined the effects of viral doses on the lung and spleen of K18-hACE2 transgenic mice by temporal histological and transcriptional analyses. Approximately, 1×105 plaque-forming units (PFU) of SARS-CoV-2 induced strong host responses in the lungs from 2 days post inoculation (dpi) which did not recover until the mice died, whereas responses to the virus were obvious at 5 days, recovering to the basal state by 14 dpi at 1×102 PFU. Further, flow cytometry showed that number of CD8+ T cells continuously increased in 1×102 PFU-virus-infected lungs from 2 dpi, but not in 1×105 PFU-virus-infected lungs. In spleens, responses to the virus were prominent from 2 dpi, and number of B cells was significantly decreased at 1×105 PFU; however, 1×12 PFU of virus induced very weak responses from 2 dpi which recovered by 10 dpi. Although the defense responses returned to normal and the mice survived, lung histology showed evidence of fibrosis, suggesting sequelae of SARS-CoV-2 infection. Our findings indicate that specific effectors of the immune response in the lung and spleen were either increased or depleted in response to doses of SARS-CoV-2. This study demonstrated that the response of local and systemic immune effectors to a viral infection varies with viral dose, which either exacerbates the severity of the infection or accelerates its elimination.

Development of Intelligent Severity of Atopic Dermatitis Diagnosis Model using Convolutional Neural Network (합성곱 신경망(Convolutional Neural Network)을 활용한 지능형 아토피피부염 중증도 진단 모델 개발)

  • Yoon, Jae-Woong;Chun, Jae-Heon;Bang, Chul-Hwan;Park, Young-Min;Kim, Young-Joo;Oh, Sung-Min;Jung, Joon-Ho;Lee, Suk-Jun;Lee, Ji-Hyun
    • Management & Information Systems Review
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    • v.36 no.4
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    • pp.33-51
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    • 2017
  • With the advent of 'The Forth Industrial Revolution' and the growing demand for quality of life due to economic growth, needs for the quality of medical services are increasing. Artificial intelligence has been introduced in the medical field, but it is rarely used in chronic skin diseases that directly affect the quality of life. Also, atopic dermatitis, a representative disease among chronic skin diseases, has a disadvantage in that it is difficult to make an objective diagnosis of the severity of lesions. The aim of this study is to establish an intelligent severity recognition model of atopic dermatitis for improving the quality of patient's life. For this, the following steps were performed. First, image data of patients with atopic dermatitis were collected from the Catholic University of Korea Seoul Saint Mary's Hospital. Refinement and labeling were performed on the collected image data to obtain training and verification data that suitable for the objective intelligent atopic dermatitis severity recognition model. Second, learning and verification of various CNN algorithms are performed to select an image recognition algorithm that suitable for the objective intelligent atopic dermatitis severity recognition model. Experimental results showed that 'ResNet V1 101' and 'ResNet V2 50' were measured the highest performance with Erythema and Excoriation over 90% accuracy, and 'VGG-NET' was measured 89% accuracy lower than the two lesions due to lack of training data. The proposed methodology demonstrates that the image recognition algorithm has high performance not only in the field of object recognition but also in the medical field requiring expert knowledge. In addition, this study is expected to be highly applicable in the field of atopic dermatitis due to it uses image data of actual atopic dermatitis patients.

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Analysis of Surface Urban Heat Island and Land Surface Temperature Using Deep Learning Based Local Climate Zone Classification: A Case Study of Suwon and Daegu, Korea (딥러닝 기반 Local Climate Zone 분류체계를 이용한 지표면온도와 도시열섬 분석: 수원시와 대구광역시를 대상으로)

  • Lee, Yeonsu;Lee, Siwoo;Im, Jungho;Yoo, Cheolhee
    • Korean Journal of Remote Sensing
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    • v.37 no.5_3
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    • pp.1447-1460
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    • 2021
  • Urbanization increases the amount of impervious surface and artificial heat emission, resulting in urban heat island (UHI) effect. Local climate zones (LCZ) are a classification scheme for urban areas considering urban land cover characteristics and the geometry and structure of buildings, which can be used for analyzing urban heat island effect in detail. This study aimed to examine the UHI effect by urban structure in Suwon and Daegu using the LCZ scheme. First, the LCZ maps were generated using Landsat 8 images and convolutional neural network (CNN) deep learning over the two cities. Then, Surface UHI (SUHI), which indicates the land surface temperature (LST) difference between urban and rural areas, was analyzed by LCZ class. The results showed that the overall accuracies of the CNN models for LCZ classification were relatively high 87.9% and 81.7% for Suwon and Daegu, respectively. In general, Daegu had higher LST for all LCZ classes than Suwon. For both cities, LST tended to increase with increasing building density with relatively low building height. For both cities, the intensity of SUHI was very high in summer regardless of LCZ classes and was also relatively high except for a few classes in spring and fall. In winter the SUHI intensity was low, resulting in negative values for many LCZ classes. This implies that UHI is very strong in summer, and some urban areas often are colder than rural areas in winter. The research findings demonstrated the applicability of the LCZ data for SUHI analysis and can provide a basis for establishing timely strategies to respond urban on-going climate change over urban areas.

Perceptional Change of a New Product, DMB Phone

  • Kim, Ju-Young;Ko, Deok-Im
    • Journal of Global Scholars of Marketing Science
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    • v.18 no.3
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    • pp.59-88
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    • 2008
  • Digital Convergence means integration between industry, technology, and contents, and in marketing, it usually comes with creation of new types of product and service under the base of digital technology as digitalization progress in electro-communication industries including telecommunication, home appliance, and computer industries. One can see digital convergence not only in instruments such as PC, AV appliances, cellular phone, but also in contents, network, service that are required in production, modification, distribution, re-production of information. Convergence in contents started around 1990. Convergence in network and service begins as broadcasting and telecommunication integrates and DMB(digital multimedia broadcasting), born in May, 2005 is the symbolic icon in this trend. There are some positive and negative expectations about DMB. The reason why two opposite expectations exist is that DMB does not come out from customer's need but from technology development. Therefore, customers might have hard time to interpret the real meaning of DMB. Time is quite critical to a high tech product, like DMB because another product with same function from different technology can replace the existing product within short period of time. If DMB does not positioning well to customer's mind quickly, another products like Wibro, IPTV, or HSPDA could replace it before it even spreads out. Therefore, positioning strategy is critical for success of DMB product. To make correct positioning strategy, one needs to understand how consumer interprets DMB and how consumer's interpretation can be changed via communication strategy. In this study, we try to investigate how consumer perceives a new product, like DMB and how AD strategy change consumer's perception. More specifically, the paper segment consumers into sub-groups based on their DMB perceptions and compare their characteristics in order to understand how they perceive DMB. And, expose them different printed ADs that have messages guiding consumer think DMB in specific ways, either cellular phone or personal TV. Research Question 1: Segment consumers according to perceptions about DMB and compare characteristics of segmentations. Research Question 2: Compare perceptions about DMB after AD that induces categorization of DMB in direction for each segment. If one understand and predict a direction in which consumer perceive a new product, firm can select target customers easily. We segment consumers according to their perception and analyze characteristics in order to find some variables that can influence perceptions, like prior experience, usage, or habit. And then, marketing people can use this variables to identify target customers and predict their perceptions. If one knows how customer's perception is changed via AD message, communication strategy could be constructed properly. Specially, information from segmented customers helps to develop efficient AD strategy for segment who has prior perception. Research framework consists of two measurements and one treatment, O1 X O2. First observation is for collecting information about consumer's perception and their characteristics. Based on first observation, the paper segment consumers into two groups, one group perceives DMB similar to Cellular phone and the other group perceives DMB similar to TV. And compare characteristics of two segments in order to find reason why they perceive DMB differently. Next, we expose two kinds of AD to subjects. One AD describes DMB as Cellular phone and the other Ad describes DMB as personal TV. When two ADs are exposed to subjects, consumers don't know their prior perception of DMB, in other words, which subject belongs 'similar-to-Cellular phone' segment or 'similar-to-TV' segment? However, we analyze the AD's effect differently for each segment. In research design, final observation is for investigating AD effect. Perception before AD is compared with perception after AD. Comparisons are made for each segment and for each AD. For the segment who perceives DMB similar to TV, AD that describes DMB as cellular phone could change the prior perception. And AD that describes DMB as personal TV, could enforce the prior perception. For data collection, subjects are selected from undergraduate students because they have basic knowledge about most digital equipments and have open attitude about a new product and media. Total number of subjects is 240. In order to measure perception about DMB, we use indirect measurement, comparison with other similar digital products. To select similar digital products, we pre-survey students and then finally select PDA, Car-TV, Cellular Phone, MP3 player, TV, and PSP. Quasi experiment is done at several classes under instructor's allowance. After brief introduction, prior knowledge, awareness, and usage about DMB as well as other digital instruments is asked and their similarities and perceived characteristics are measured. And then, two kinds of manipulated color-printed AD are distributed and similarities and perceived characteristics for DMB are re-measured. Finally purchase intension, AD attitude, manipulation check, and demographic variables are asked. Subjects are given small gift for participation. Stimuli are color-printed advertising. Their actual size is A4 and made after several pre-test from AD professionals and students. As results, consumers are segmented into two subgroups based on their perceptions of DMB. Similarity measure between DMB and cellular phone and similarity measure between DMB and TV are used to classify consumers. If subject whose first measure is less than the second measure, she is classified into segment A and segment A is characterized as they perceive DMB like TV. Otherwise, they are classified as segment B, who perceives DMB like cellular phone. Discriminant analysis on these groups with their characteristics of usage and attitude shows that Segment A knows much about DMB and uses a lot of digital instrument. Segment B, who thinks DMB as cellular phone doesn't know well about DMB and not familiar with other digital instruments. So, consumers with higher knowledge perceive DMB similar to TV because launching DMB advertising lead consumer think DMB as TV. Consumers with less interest on digital products don't know well about DMB AD and then think DMB as cellular phone. In order to investigate perceptions of DMB as well as other digital instruments, we apply Proxscal analysis, Multidimensional Scaling technique at SPSS statistical package. At first step, subjects are presented 21 pairs of 7 digital instruments and evaluate similarity judgments on 7 point scale. And for each segment, their similarity judgments are averaged and similarity matrix is made. Secondly, Proxscal analysis of segment A and B are done. At third stage, get similarity judgment between DMB and other digital instruments after AD exposure. Lastly, similarity judgments of group A-1, A-2, B-1, and B-2 are named as 'after DMB' and put them into matrix made at the first stage. Then apply Proxscal analysis on these matrixes and check the positional difference of DMB and after DMB. The results show that map of segment A, who perceives DMB similar as TV, shows that DMB position closer to TV than to Cellular phone as expected. Map of segment B, who perceive DMB similar as cellular phone shows that DMB position closer to Cellular phone than to TV as expected. Stress value and R-square is acceptable. And, change results after stimuli, manipulated Advertising show that AD makes DMB perception bent toward Cellular phone when Cellular phone-like AD is exposed, and that DMB positioning move towards Car-TV which is more personalized one when TV-like AD is exposed. It is true for both segment, A and B, consistently. Furthermore, the paper apply correspondence analysis to the same data and find almost the same results. The paper answers two main research questions. The first one is that perception about a new product is made mainly from prior experience. And the second one is that AD is effective in changing and enforcing perception. In addition to above, we extend perception change to purchase intention. Purchase intention is high when AD enforces original perception. AD that shows DMB like TV makes worst intention. This paper has limitations and issues to be pursed in near future. Methodologically, current methodology can't provide statistical test on the perceptual change, since classical MDS models, like Proxscal and correspondence analysis are not probability models. So, a new probability MDS model for testing hypothesis about configuration needs to be developed. Next, advertising message needs to be developed more rigorously from theoretical and managerial perspective. Also experimental procedure could be improved for more realistic data collection. For example, web-based experiment and real product stimuli and multimedia presentation could be employed. Or, one can display products together in simulated shop. In addition, demand and social desirability threats of internal validity could influence on the results. In order to handle the threats, results of the model-intended advertising and other "pseudo" advertising could be compared. Furthermore, one can try various level of innovativeness in order to check whether it make any different results (cf. Moon 2006). In addition, if one can create hypothetical product that is really innovative and new for research, it helps to make a vacant impression status and then to study how to form impression in more rigorous way.

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A Study on Ontology and Topic Modeling-based Multi-dimensional Knowledge Map Services (온톨로지와 토픽모델링 기반 다차원 연계 지식맵 서비스 연구)

  • Jeong, Hanjo
    • Journal of Intelligence and Information Systems
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    • v.21 no.4
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    • pp.79-92
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    • 2015
  • Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations' data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers' network is created, and the researchers' network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the construction of the integrated knowledge base using the lightweight ontology and topic modeling, and the knowledge map services created based on the knowledge base are also introduced.