• 제목/요약/키워드: 데이터 부족 문제

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Design and Development of Personal Healthcare System Based on IEEE 11073/HL7 Standards Using Smartphone (스마트폰을 이용한 IEEE 11073/HL7 기반의 개인 건강관리 시스템 설계 및 구현)

  • Nam, Jae-Choong;Seo, Won-Kyeong;Bae, Jae-Seung;Cho, You-Ze
    • The Journal of Korean Institute of Communications and Information Sciences
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    • 제36권12B호
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    • pp.1556-1564
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    • 2011
  • The increased life expectancy of human due to the advance of medical techniques has led to many social problems such as rapidly aging populations, increased medical expenses and a lack of medical specialists. Thus, studies on improving the quality of life with the least amount of expense have been going on by incorporating advanced technologies, especially for Personal Health Devices (PHDs), into the medical service market. However, compatibility and extensibility among manufacturers of PHDs have not been taken into account in most of the researches done on the development of PHDs because most of them have been supported by individual medical organizations. The interoperability among medical organizations can not be guaranteed because each medical organization uses different format of the messages. Therefore, in this paper, an expansion module that can enable commercially-available non-standard PHDs to support the IEEE 11073, and a smart-phone-based manager that can support easy and comprehensive management on receiving and transmitting the collected data from each PHD using IEEE 11073 standard were developed. In addition, a u-health system that can transmit the data collected in the manager using the standard data format HL 7 to medical center for real-time medical service from every medical institutions that support this standard was designed and developed.

A Homonym Disambiguation System based on Semantic Information Extracted from Dictionary Definitions (사전의 뜻풀이말에서 추출한 의미정보에 기반한 동형이의어 중의성 해결 시스템)

  • Hur, Jeong;Ock, Cheol-Young
    • Journal of KIISE:Software and Applications
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    • 제28권9호
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    • pp.688-698
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    • 2001
  • A homonym could be disambiguated by anther words in the context such as nouns, predicates used with the homonym. This paper proposes a homonym disambiguation system based on statistical semantic information which is extracted from definitions in dictionary. The semantic information consists of nouns and predicates that are used with the homonym in definitions. In order to extract accurate semantic information, definitions are used with the homonym in definitions. In order to extract accurate semantic information, definitions are classified into two types. One has hyponym-hypernym relation between title word and head word (homonym) in definition. The hyponym-hypernym relation is one level semantic hierarchy and can be extended to deeper levels in order to overcome the problem of data sparseness. The other is the case that the homonym is used in the middle of definition. The system considers nouns and predicates simultaneously to disambiguate the homonym. Nine homonyms are examined in order to determine the weight of nouns and predicates which affect accrutacy of homonym disambiguation. From experiments using training corpus(definitions in dictionary), the average accruracy of homonym disamguation is 96.11% when the weight is 0.9 and 0.1 for noun and verb respectively. And another experiment to meaure the generality of the homonym disambiguation system results in the 80.73% average accuracy to 1,796 untraining sentences from Korean Information Base I and ETRI corpus.

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Re-ranking the Results from Two Image Retrieval System in Cooperative Manner (두 영상검색 시스템의 협력적 이용을 통한 재순위화)

  • Hwang, Joong-Won;Kim, Hyunwoo;Kim, Junmo
    • Journal of the Korean Institute of Intelligent Systems
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    • 제24권1호
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    • pp.7-15
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    • 2014
  • Image retrieval has become a huge part of computer vision and data mining. Although commercial image retrieval systems such as Google show great performances, the improvement on the performances are constantly on demand because of the rapid growth of data on web space. To satisfy the demand, many re-ranking methods, which enhance the performances by reordering retrieved results with independent algorithms, has been proposed. Conventional re-ranking algorithms are based on the assumption that visual patterns are not used on initial image retrieval stage. However, image search engines in present have begun to use the visual and the assumption is required to be reconsidered. Also, though it is possible to suspect that integration of multiple retrieval systems can improve the overall performance, the research on the topic has not been done sufficiently. In this paper, we made the condition that other manner than cooperation cannot improve the ranking result. We evaluate the algorithm on toy model and show that propose module can improve the retrieval results.

Evaluation of Shear Strength of Unreinforced Masonry Walls Retrofitted by Fiber Reinforced Polymer Sheet (FRP로 보강한 비보강 조적 벽체의 전단강도 산정)

  • Bae, Baek-Il;Yun, Hyo-Jin;Choi, Chang-Sik;Choi, Hyun-Ki
    • Journal of the Korea Concrete Institute
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    • 제24권3호
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    • pp.305-313
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    • 2012
  • Unreinforced masonry buildings represent a significant portion of the existing and historical buildings around the world. Recent earthquakes have shown the need for seismic retrofitting for these types of buildings. Various types of retrofitting materials (i.e., shotcrete, ECC and Fiber Reinforced Polymer sheets (FRPs)) for unreinforced masonry buildings (URM) have been developed. Engineers prefer to use FRPs, because these materials enhance the shear strength of the wall without expansion of wall sectional area and adding weight to the total structure. However, the complexity of the mechanical behavior of the masonry wall and the lack of experimental data from walls retrofitted by FRPs may cause problems for engineers to determine an appropriate retrofitting level. This paper investigate in-plane behavior of URM and retrofitted masonry walls using two different types of FRP materials to determine and provide information for the retrofitting effect of FRPs on masonry shear walls. Specimens were designed to idealize the wall of a low-rise apartment which was built in 1970s in Korea with no seismic reinforcements with an aspect ratio of 1. Retrofitting materials were carbon FRP and Hybrid sheets which have different elastic modulus and ultimate strain capacities. Consequently, this study evaluated the structural capacity of masonry shear walls and the retrofitting effect of an FRP sheet for in-plane behavior. Also, the results were compared to the results obtained from the evaluation method for a reinforced concrete beam retrofitted with FRPs.

WebPR : A Dynamic Web Page Recommendation Algorithm Based on Mining Frequent Traversal Patterns (WebPR :빈발 순회패턴 탐사에 기반한 동적 웹페이지 추천 알고리즘)

  • Yoon, Sun-Hee;Kim, Sam-Keun;Lee, Chang-Hoon
    • The KIPS Transactions:PartB
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    • 제11B권2호
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    • pp.187-198
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    • 2004
  • The World-Wide Web is the largest distributed Information space and has grown to encompass diverse information resources. However, although Web is growing exponentially, the individual's capacity to read and digest contents is essentially fixed. From the view point of Web users, they can be confused by explosion of Web information, by constantly changing Web environments, and by lack of understanding needs of Web users. In these Web environments, mining traversal patterns is an important problem in Web mining with a host of application domains including system design and Information services. Conventional traversal pattern mining systems use the inter-pages association in sessions with only a very restricted mechanism (based on vector or matrix) for generating frequent k-Pagesets. We develop a family of novel algorithms (termed WebPR - Web Page Recommend) for mining frequent traversal patterns and then pageset to recommend. Our algorithms provide Web users with new page views, which Include pagesets to recommend, so that users can effectively traverse its Web site. The main distinguishing factors are both a point consistently spanning schemes applying inter-pages association for mining frequent traversal patterns and a point proposing the most efficient tree model. Our experimentation with two real data sets, including Lady Asiana and KBS media server site, clearly validates that our method outperforms conventional methods.

Using Text-mining Method to Identify Research Trends of Freshwater Exotic Species in Korea (텍스트마이닝 (text-mining) 기법을 이용한 국내 담수외래종 연구동향 파악)

  • Do, Yuno;Ko, Eui-Jeong;Kim, Young-Min;Kim, Hyo-Gyeom;Joo, Gea-Jae;Kim, Ji Yoon;Kim, Hyun-Woo
    • Korean Journal of Ecology and Environment
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    • 제48권3호
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    • pp.195-202
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    • 2015
  • We identified research trends for freshwater exotic species in South Korea using text mining methods in conjunction with bibliometric analysis. We searched scientific and common names of freshwater exotic species as searching keywords including 1 mammal species, 3 amphibian-reptile species, 11 fish species, 2 aquatic plant species. A total of 245 articles including research articles and abstracts of conference proceedings published by 56 academic societies and institutes were collected from scientific article databases. The search keywords used were the common names for the exotic species. The $20^{th}$ century (1900's) saw the number of articles increase; however, during the early $21^{st}$ century (2000's) the number of published articles decreased slowly. The number of articles focusing on physiological and embryological research was significantly greater than taxonomic and ecological studies. Rainbow trout and Nile tilapia were the main research topic, specifically physiological and embryological research associated with the aquaculture of these species. Ecological studies were only conducted on the distribution and effect of large-mouth bass and nutria. The ecological risk associated with freshwater exotic species has been expressed yet the scientific information might be insufficient to remove doubt about ecological issues as expressed by interested by individuals and policy makers due to bias in research topics with respect to freshwater exotic species. The research topics of freshwater exotic species would have to diversify to effectively manage freshwater exotic species.

E-Governance Practices in Developing Countries. Its Benefits and Challenges. -The Case of Pakistan- (개발도상국의 전자정부 시행에 따른 장점과 문제 -파키스탄 중심으로-)

  • Aftab, Muhammad
    • Industry Promotion Research
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    • 제4권1호
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    • pp.79-86
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    • 2019
  • The quality of service delivery by governments to their citizens is a subject of concern in the contemporary society. E-governance is a critical aspect that is transforming government operation and service delivery to citizens and other bodies through application of information technology. This research explores the state of e-governing focusing on nations that are developing with special attention to Pakistan. The difficulties and benefits encountered are identified. The results are vital for implementers of e-governing systems in these countries. The methodology applied entails a secondary research that involves analysis and synthesis of literature relating the research topic. The results reveal that Pakistan has made incredible steps in setting up e-governance systems with growth in internet use and access of data from a digital platform. The findings reveal that e-government is associated with multiple benefits including enhanced quality of services, cost efficiency in service provision, enhance transparency and elimination of corruption, provide the basis for eradication of poverty, boost economic stability of a country, and provide room for direct democracy. The research also found that developing countries experience challenges in form of financial constraints, poor ICT infrastructure, illiteracy on e-government, political consensus constraints, legal obstacles, social and cultural constraints. E-government has the capability to transform the quality of governance provided by governments, and policymakers and implementers should address the constraints that act as a hindrance to its implementation.

A Study on the Optimal Setting of Large Uncharged Hole Boring Machine for Reducing Blast-induced Vibration Using Deep Learning (터널 발파 진동 저감을 위한 대구경 무장약공 천공 장비의 최적 세팅조건 산정을 위한 딥러닝 적용에 관한 연구)

  • Kim, Min-Seong;Lee, Je-Kyum;Choi, Yo-Hyun;Kim, Seon-Hong;Jeong, Keon-Woong;Kim, Ki-Lim;Lee, Sean Seungwon
    • Explosives and Blasting
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    • 제38권4호
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    • pp.16-25
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    • 2020
  • Multi-setting smart-investigation of the ground and large uncharged hole boring (MSP) method to reduce the blast-induced vibration in a tunnel excavation is carried out over 50m of long-distance boring in a horizontal direction and thus has been accompanied by deviations in boring alignment because of the heavy and one-directional rotation of the rod. Therefore, the deviation has been adjusted through the boring machine's variable setting rely on the previous construction records and expert's experience. However, the geological characteristics, machine conditions, and inexperienced workers have caused significant deviation from the target alignment. The excessive deviation from the boring target may cause a delay in the construction schedule and economic losses. A deep learning-based prediction model has been developed to discover an ideal initial setting of the MSP machine. Dropout, early stopping, pre-training techniques have been employed to prevent overfitting in the training phase and, significantly improved the prediction results. These results showed the high possibility of developing the model to suggest the boring machine's optimum initial setting. We expect that optimized setting guidelines can be further developed through the continuous addition of the data and the additional consideration of the other factors.

Through load prediction and solar power generation prediction ESS operation plan(Guide-line) study (부하예측 및 태양광 발전예측을 통한 ESS 운영방안(Guide-line) 연구)

  • Lee, Gi-Hyun;Kwak, Gyung-il;Chae, U-ri;KO, Jin-Deuk;Lee, Joo-Yeoun
    • Journal of Digital Convergence
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    • 제18권12호
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    • pp.267-278
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    • 2020
  • ESS is an essential requirement for resolving power shortages and power demand management and promoting renewable energy at a time when the energy paradigm changes. In this paper, we propose a cost-effective ESS Peak-Shaving operation plan through load and solar power generation forecast. For the ESS operation plan, electric load and solar power generation were predicted through RMS, which is a statistical measure, and a target load reduction guideline for one hour was set through the predicted electric load and solar power generation amount. The load and solar power generation amount from May 6th to 10th, 2019 was predicted by simulation of load and photovoltaic power generation using real data of the target customer for one year, and an hourly guideline was set. The average error rate for predicting load was 7.12%, and the average error rate for predicting solar power generation amount was 10.57%. Through the ESS operation plan, it was confirmed that the hourly guide-line suggested in this paper contributed to the peak-shaving maximization of customers.Through the results of this paper, it is expected that future energy problems can be reduced by minimizing environmental problems caused by fossil energy in connection with solar power and utilizing new and renewable energy to the maximum.

A Study on the Design and Implementation of Multi-Disaster Drone System Using Deep Learning-Based Object Recognition and Optimal Path Planning (딥러닝 기반 객체 인식과 최적 경로 탐색을 통한 멀티 재난 드론 시스템 설계 및 구현에 대한 연구)

  • Kim, Jin-Hyeok;Lee, Tae-Hui;Han, Yamin;Byun, Heejung
    • KIPS Transactions on Computer and Communication Systems
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    • 제10권4호
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    • pp.117-122
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    • 2021
  • In recent years, human damage and loss of money due to various disasters such as typhoons, earthquakes, forest fires, landslides, and wars are steadily occurring, and a lot of manpower and funds are required to prevent and recover them. In this paper, we designed and developed a disaster drone system based on artificial intelligence in order to monitor these various disaster situations in advance and to quickly recognize and respond to disaster occurrence. In this study, multiple disaster drones are used in areas where it is difficult for humans to monitor, and each drone performs an efficient search with an optimal path by applying a deep learning-based optimal path algorithm. In addition, in order to solve the problem of insufficient battery capacity, which is a fundamental problem of drones, the optimal route of each drone is determined using Ant Colony Optimization (ACO) technology. In order to implement the proposed system, it was applied to a forest fire situation among various disaster situations, and a forest fire map was created based on the transmitted data, and a forest fire map was visually shown to the fire fighters dispatched by a drone equipped with a beam projector. In the proposed system, multiple drones can detect a disaster situation in a short time by simultaneously performing optimal path search and object recognition. Based on this research, it can be used to build disaster drone infrastructure, search for victims (sea, mountain, jungle), self-extinguishing fire using drones, and security drones.