• 제목/요약/키워드: Classification of Scheme

검색결과 837건 처리시간 0.031초

Anatomical Site Classification for Implant Insertion:ASCIi

  • Jeong, Seung-Mi;Chung, Chae-Heon;Engelke, W.
    • 대한치과보철학회지
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    • 제38권3호
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    • pp.321-327
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    • 2000
  • Statement of Problem. As a standard means of diagnostics, an orthopantomogram(OPT) permits to measure the vertical and mesiodistal dimension of available bone at the desired implant site with the help of suitable radioopaque references. Based on the clinical investigation of the dentition and the edentulous sites, information upon the width of the implant site can be obtained and documented in the dental scheme. Both findings permit together systematic primary planning for endosteal implants. Purpose of Study. Contents of the present article are the representation of a semiquantitative classification of available bone with the aim to simplify the primary phase of a systematic implant planning. Results. Thus the ASCIi- system permits a clear protocol of bone findings for the implant case with all information available during the primary appointment for treatment planning as a basis of further diagnostic and therapeutic measures. Conclusion. With the ASCIi system, important parameters such as alveolar height and sub-crestal alveolar width can be documented systematically, easily and time saving in the dental scheme as a basis for exact treatment planning.

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Toward Energy-Efficient Task Offloading Schemes in Fog Computing: A Survey

  • Alasmari, Moteb K.;Alwakeel, Sami S.;Alohali, Yousef
    • International Journal of Computer Science & Network Security
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    • 제22권3호
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    • pp.163-172
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    • 2022
  • The interconnection of an enormous number of devices into the Internet at a massive scale is a consequence of the Internet of Things (IoT). As a result, tasks offloading from these IoT devices to remote cloud data centers become expensive and inefficient as their number and amount of its emitted data increase exponentially. It is also a challenge to optimize IoT device energy consumption while meeting its application time deadline and data delivery constraints. Consequently, Fog Computing was proposed to support efficient IoT tasks processing as it has a feature of lower service delay, being adjacent to IoT nodes. However, cloud task offloading is still performed frequently as Fog computing has less resources compared to remote cloud. Thus, optimized schemes are required to correctly characterize and distribute IoT devices tasks offloading in a hybrid IoT, Fog, and cloud paradigm. In this paper, we present a detailed survey and classification of of recently published research articles that address the energy efficiency of task offloading schemes in IoT-Fog-Cloud paradigm. Moreover, we also developed a taxonomy for the classification of these schemes and provided a comparative study of different schemes: by identifying achieved advantage and disadvantage of each scheme, as well its related drawbacks and limitations. Moreover, we also state open research issues in the development of energy efficient, scalable, optimized task offloading schemes for Fog computing.

방문간호를 통한 일상생활동작 수행능력 개선에 대한 사례보고: 오마하시스템을 활용하여 (Improvement of Activities of Daily Living through Visiting Nursing Care under Long-Term Care Insurance: A Case Report using the OMAHA System)

  • 송연이;박은진
    • 한국농촌간호학회지
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    • 제15권2호
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    • pp.66-73
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    • 2020
  • Purpose: This study was done to report nursing case for ADL improvement of elders who have CVA(Cerebrovascular Accident) sequelae. Methods: The client had registered in the C visiting nursing center after being decided a long-term care Grade 2. Data were collected through consultation logs for recipients, Activities of Daily Living (ADL) records, fall risk assessment (Huhn) sheets, decubitus ulcer risk assessment (Braden Scale) sheets, cognition assessment (K-MMSE) sheets, long-term care benefit provision records, and interviews with visiting nurse. Data were collected and analyzed according to the Omaha System problem classification. The intervention scheme and the problem rating scale for performance were applied to present the case for home-visit nursing. Results: The client registered in August, 2018, was provided home-visit nursing care once a week as of September 2020. ADL, cognitive levels and decubitus ulcer risks were found to have improved. Conclusion: This case report presents the value of classifying nursing problems and checking nursing intervention provided to patients with problems of ADL. The presentation of home-visit nursing cases applying a standardized nursing problem classification scheme for clients with various problems showed that a high quality level of care is guaranteed and evidence-based nursing can be provided by visiting nurses.

이산웨이블릿 변환과 퍼지추론을 이용한 적응적 물체 분류 (Adaptive Object Classification using DWT and FI)

  • 김윤호
    • 한국항행학회논문지
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    • 제10권3호
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    • pp.219-225
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    • 2006
  • 본 논문에서는 이산웨이블릿 변환과 퍼지추론을 이용하여 물체를 분류하는 방법을 제안 한 바, 컨베이어 혹은 무인 운송장치와 같은 저속도에 적용 할 수 있는 퍼지추론 알고리즘과 알고리즘의 퍼지 규칙수를 최소화하는 방법에 중점을 두었다. 특징추출을 위한 전처리 과정에서 는 이산웨이블릿 변환 계수로부터 물체의 특징 파라미터들을 구하였다. 물체의 특징 파라미터는 계수 블록으로부터 계산된 물체의 면적, 둘레, 면적과 둘레의 비율을 이용하였다. 외부 환경에 기인하는 파라미터들의 변화에 적응할 수 있도록 퍼지 If-then 규칙을 설계하였다. 제안한 추론 알고리즘의 성능 평가를 위하여 Mamdani 및 Larsen의 함의 연산자를 이용하여 실험하였고, 외부 환경 변화에 대하여도 적용 가능성을 보였다.

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자기구성지도 기반 방법을 이용한 이상 탐지 (Novelty Detection using SOM-based Methods)

  • 이형주;조성준
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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    • pp.599-606
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    • 2005
  • Novelty detection involves identifying novel patterns. They are not usually available during training. Even if they are, the data quantity imbalance leads to a low classification accuracy when a supervised learning scheme is employed. Thus, an unsupervised learning scheme is often employed ignoring those few novel patterns. In this paper, we propose two ways to make use of the few available novel patterns. First, a scheme to determine local thresholds for the Self Organizing Map boundary is proposed. Second, a modification of the Learning Vector Quantization learning rule is proposed so that allows one to keep codebook vectors as far from novel patterns as possible. Experimental results are quite promising.

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A New Galaxy Classification Scheme in the WISE Color-Luminosity Diagram

  • Lee, Gwang-Ho;Sohn, Jubee;Lee, Myung Gyoon
    • 천문학회보
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    • 제38권2호
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    • pp.49.1-49.1
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    • 2013
  • We present a new galaxy classification scheme in the Wide-field Infrared Survey Explorer (WISE) [$3.4{\mu}m$]-[$12{\mu}m$] color versus $12{\mu}m$ luminosity diagram. In this diagram, galaxies can be classified into three groups in different evolutionary stages. Late-type galaxies are distributed linearly along "MIR star-forming sequence" identified by Hwang et al. (2012). Some early-type galaxies show another sequence at [3.4]-[12] $(AB){\simeq}-2.0$, and we call this 'MIR blue sequence'. They are quiescent systems with old stellar population older than 10 Gyr. Between the MIR star-forming sequence and the MIR blue sequence, some early- and late-type galaxies are sparsely distributed, and we call these galaxies 'MIR green cloud galaxies'. Interestingly, both MIR blue sequence galaxies and MIR green cloud ones lie on the red sequence in the optical color-magnitude diagram. However, MIR green cloud galaxies have lower stellar masses and younger stellar populations (smaller $D_n4000$) than MIR blue sequence galaxies, suggesting that MIR green cloud galaxies are in the transition stage from MIR star-forming sequence galaxies to MIR blue sequence ones. We present differences in various galaxy properties between the three MIR classes using a multi-wavelength data, combined with the WISE and Sloan Digital Sky Survey Data Release 10, of local (0.03 < z < 0.07) galaxies.

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차량애드혹망을 위한 가변정밀도 러프집합 기반 부정행위 탐지 방법의 설계 및 평가 (Design and evaluation of a VPRS-based misbehavior detection scheme for VANETs)

  • 김칠화;배인한
    • Journal of the Korean Data and Information Science Society
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    • 제22권6호
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    • pp.1153-1166
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    • 2011
  • 차량 네트워크에서 부정행위를 탐지하는 것은 안전 관련 응용 및 혼잡 완화 응용을 포함하는 광범위한 영향을 갖는 매우 중요한 문제이다. 대부분 부정행위 탐지 방법들은 악의적인 노드들의 탐지와 관련이 있다. 대부분 상황들에서, 차량들은 운전자의 이기적인 이유 때문에 틀린 정보를 보낼 수 있다. 합리적인 행위 때문에 부정행위를 하는 노드를 식별하는 것보다 거짓 경보 정보를 탐지하는 것이 더 중요하다. 이 논문에서, 우리는 경보 메시지를 전송한 후, 부정행위를 한 노드들의 행위를 관찰하여 거짓 경보 메시지를 탐지하는 가변 정밀도 러프집합 기반 부정행위 탐지 방법을 제안한다. 차량 네트워크에서 이동하는 노드의 타당한 행위들로부터 경보 프로파일인 경보 정보 시스템이 먼저 구축되어진다. 어떤 이동하는 차량이 다른 차량으로부터 경보 메시지를 받으면, 수신차량은 그 메시지로부터 경보종류를 알아낸다. 경과시간 후, 수신차량이 경보 전송차량으로부터 비콘을 받으면, 수신차량은 경보 정보 시스템으로부터 가변 정밀도 러프집합을 사용하여 상대적 분류 오차를 계산한다. 만일 그 상대적 분류 오차가 그 경보종류의 최대 허용 가능한 분류 오차보다 크면, 수신 차량은 그 메시지를 거짓 경보 메시지로 결정한다. 제안하는 방법의 성능은 모의실험을 통하여 2가지 척도, 즉 정확률과 부정확률로 평가되어진다.

문헌각과 문헌각서목의 분석 -숙종조의 문화적 배경을통한 한국본 서고의 연구- (A Study of the Munheongak and Munheongaksomog)

  • 남권희
    • 한국문헌정보학회지
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    • 제11권
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    • pp.147-183
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    • 1984
  • This is an analytical study on Munheongak (文獻閣) and it's catalogue. The major objective of the study is to get a recognition of Munheongak under the culture of Sukjong (肅宗) period in Korean library history. Most of early studies made on such a category have been concentrated on Jiphyunjeon (集賢殿), Hongmungwan (弘文館), Kyujanggak(奎章閣) and their backgrounds. In this study, the author has invest gated Kungwolji (宮闕志), Munheongakseomg (文獻閣書目) and other materials related to this subject. The findings of the study can be summarized as follows: 1. Munheongak was established by king Sukjong in the 26th year of his reign. According to some records of Kungkwolji, the reason of establishment of the library was to arrange the collection in the Sango (相庫) consisted of various kinds of materials. In case of books, most of them turned out to be Korean books. 2. Munheongak was sited to the estern side of Kyunghyundang (景賢堂), which was located on the Kyungdeokgung (慶德宮). After Youngjo (英祖) the place was called Kyungheuigung (慶熙宮) so as to avoid the name of the precedent king. But these days, both the buildings are not to be found. 3. After its establishment, the library could not play the role as a library because of the then political situation and sectionalism. During the period of the revival of the learning from Youngjo till Jeongjo(正祖) the function of the library was in a stagnant state. Kyujanggak played the part in its place. 4. Referring to the collection management, the Munheongakseomog is equipped with 101 titles, 2,525 volumes, which are arranged by means of the traditional Chinese classification system. 5. The classification scheme is based on the traditional Chinese classification system which might divide all subjects into four categories such as: Confucian classics division, Historical documents division, Master's division, and Collection of literature division. Some illustrations reveal that the classification system was directly influenced by Seogoseomg (書庫書目) : the influence reflected in the classes for the translated literature and writings, poems, genealogy about kings, etc. But some subdivisions such as a class of Annals, Historical Epcerpts were omitted in the classification scheme, which did not strike the balance in the system in terms of the present theory of classification. Most of bibliographical descriptions were also influenced by Seogoseomog but some elements were partly omitted. 6. The special feature of the collection building is the absence of books in Collection of literature division except only three kinds of books in examining the Munheongakseomog. Since this is rather a comprehensive study for such aspects as historical backround, catalogue, and cultural environment of Munheongak and its related record, it is advised that further and additional research should be made.

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Hierarchical Clustering Approach of Multisensor Data Fusion: Application of SAR and SPOT-7 Data on Korean Peninsula

  • Lee, Sang-Hoon;Hong, Hyun-Gi
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.65-65
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    • 2002
  • In remote sensing, images are acquired over the same area by sensors of different spectral ranges (from the visible to the microwave) and/or with different number, position, and width of spectral bands. These images are generally partially redundant, as they represent the same scene, and partially complementary. For many applications of image classification, the information provided by a single sensor is often incomplete or imprecise resulting in misclassification. Fusion with redundant data can draw more consistent inferences for the interpretation of the scene, and can then improve classification accuracy. The common approach to the classification of multisensor data as a data fusion scheme at pixel level is to concatenate the data into one vector as if they were measurements from a single sensor. The multiband data acquired by a single multispectral sensor or by two or more different sensors are not completely independent, and a certain degree of informative overlap may exist between the observation spaces of the different bands. This dependence may make the data less informative and should be properly modeled in the analysis so that its effect can be eliminated. For modeling and eliminating the effect of such dependence, this study employs a strategy using self and conditional information variation measures. The self information variation reflects the self certainty of the individual bands, while the conditional information variation reflects the degree of dependence of the different bands. One data set might be very less reliable than others in the analysis and even exacerbate the classification results. The unreliable data set should be excluded in the analysis. To account for this, the self information variation is utilized to measure the degrees of reliability. The team of positively dependent bands can gather more information jointly than the team of independent ones. But, when bands are negatively dependent, the combined analysis of these bands may give worse information. Using the conditional information variation measure, the multiband data are split into two or more subsets according the dependence between the bands. Each subsets are classified separately, and a data fusion scheme at decision level is applied to integrate the individual classification results. In this study. a two-level algorithm using hierarchical clustering procedure is used for unsupervised image classification. Hierarchical clustering algorithm is based on similarity measures between all pairs of candidates being considered for merging. In the first level, the image is partitioned as any number of regions which are sets of spatially contiguous pixels so that no union of adjacent regions is statistically uniform. The regions resulted from the low level are clustered into a parsimonious number of groups according to their statistical characteristics. The algorithm has been applied to satellite multispectral data and airbone SAR data.

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훈련 자료의 임의 선택과 다중 분류자를 이용한 원격탐사 자료의 분류 (Classification of Remote Sensing Data using Random Selection of Training Data and Multiple Classifiers)

  • 박노욱;유희영;김이현;홍석영
    • 대한원격탐사학회지
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    • 제28권5호
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    • pp.489-499
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    • 2012
  • 이 논문에서는 원격탐사 자료의 분류를 목적으로 서로 다른 훈련 집단들과 분류자들로부터 생성된 분류 결과들을 결합하는 분류 틀을 제안하였다. 제안 분류 틀의 핵심 부분은 서로 다른 훈련 집단과 분류자들을 이용함으로써 분류 결과 사이의 다양성을 증가시켜서 결과적으로 분류 정확도를 향상시키는데 있다. 제안 분류 틀에서는 우선 서로 다른 샘플링 밀도를 가지는 서로 다른 훈련 집단들을 생성한 후에, 이들을 서로 다른 구분 능력을 나타내는 분류자들의 입력 훈련 자료로 사용한다. 그리고 초기 분류 결과들에 다수결 규칙을 적용하여 최종 분류 결과를 얻게 된다. 다중 시기 ENVISAT ASAR 자료를 이용한 토지 피복 분류사례 연구를 통해 제안 방법론의 적용 가능성을 검토하였다. 사례 연구에서 3개의 훈련 집단과 최대우도 분류자, 다층 퍼셉트론 분류자, support vector machine 등과 같은 3개의 분류자를 이용한 9개의 분류 결과를 결합하였다. 사례 연구 결과, 제안 분류 틀 안에서 토지 피복 구분에 관한 상호 보완적인 정보의 이용이 가능해져서 가장 높은 분류 정확도를 나타내었다. 서로 다른 결합들을 비교하였을 때, 다양성이 크지 않은 분류 결과들을 결합한 경우에는 분류 정확도의 향상이 나타나지 않았다. 따라서 다중 분류 시스템의 설계시 분류자들의 다양성을 확보하는 것이 중요함을 확인할 수 있었다.