• Title/Summary/Keyword: Decision matrices

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Web Based Environmental Management System using Predictive Spatial Information Models (예측적 공간정보 모형을 이용한 Web 기반의 환경관리시스템의 개발 및 적용)

  • Kim, Joon Hyun;Han, Young Han
    • Journal of Environmental Impact Assessment
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    • v.8 no.4
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    • pp.47-57
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    • 1999
  • This study is aimed at the development of comprehensive environmental management system, which can be operated on the basis of world wide web, as a topic of G7 project. Even though there should be lots of works remaining to achieve this goal, preliminary products can be summarized as follows : 1) integrated environmental information management system, 2) web based control engine, 3) surface water environment management system, 4) subsurface water environment management system, 5) sewer and waterworks management system. The core methodology of the engine is the generalized multidimensional finite element matrices to depict the terms in the analysis of various partial differential equations. Spatial information management system (ArcView) and Visual Basic were extensively employed to construct GUI oriented web based engine. The developed systems were composed of very intense computer codes due to the necessity of combinatory management of environmental problems. The web based engine could be served as a decision tool for the integrated management of environmental projects in Korea.

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Text Network Analysis of Newspaper Articles on Life-sustaining Treatments (연명의료 관련 신문 기사의 텍스트네트워크분석)

  • Park, Eun-Jun;Ahn, Dae Woong;Park, Chan Sook
    • Research in Community and Public Health Nursing
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    • v.29 no.2
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    • pp.244-256
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    • 2018
  • Purpose: This study tried to understand discourses of life-sustaining treatments in general daily and healthcare newspapers. Methods: A text-network analysis was conducted using the NetMiner program. Firstly, 572 articles from 11 daily newspapers and 258 articles from 8 healthcare newspapers were collected, which were published from August 2013 to October 2016. Secondly, keywords (semantic morphemes) were extracted from the articles and rearranged by removing stop-words, refining similar words, excluding non-relevant words, and defining meaningful phrases. Finally, co-occurrence matrices of the keywords with a frequency of 30 times or higher were developed and statistical measures-indices of degree and betweenness centrality, ego-networks, and clustering-were obtained. Results: In the general daily and healthcare newspapers, the top eight core keywords were common: "patients," "death," "LST (life-sustaining treatments)," "hospice palliative care," "hospitals," "family," "opinion," and "withdrawal." There were also common subtopics shared by the general daily and healthcare newspapers: withdrawal of LST, hospice palliative care, National Bioethics Review Committee, and self-determination and proxy decision of patients and family. Additionally, the general daily newspapers included diverse social interest or events like well-dying, euthanasia, and the death of farmer Baek Nam-ki, whereas the healthcare newspapers discussed problems of the relevant laws, and insufficient infrastructure and low reimbursement for hospice-palliative care. Conclusion: The discourse that withdrawal of futile LST should be allowed according to the patient's will was consistent in the newspapers. Given that newspaper articles influence knowledge and attitudes of the public, RNs are recommended to participate actively in public communication on LST.

Multi-dimensional Analysis and Prediction Model for Tourist Satisfaction

  • Shrestha, Deepanjal;Wenan, Tan;Gaudel, Bijay;Rajkarnikar, Neesha;Jeong, Seung Ryul
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.2
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    • pp.480-502
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    • 2022
  • This work assesses the degree of satisfaction tourists receive as final recipients in a tourism destination based on the fact that satisfied tourists can make a significant contribution to the growth and continuous improvement of a tourism business. The work considers Pokhara, the tourism capital of Nepal as a prefecture of study. A stratified sampling methodology with open-ended survey questions is used as a primary source of data for a sample size of 1019 for both international and domestic tourists. The data collected through a survey is processed using a data mining tool to perform multi-dimensional analysis to discover information patterns and visualize clusters. Further, supervised machine learning algorithms, kNN, Decision tree, Support vector machine, Random forest, Neural network, Naive Bayes, and Gradient boost are used to develop models for training and prediction purposes for the survey data. To find the best model for prediction purposes, different performance matrices are used to evaluate a model for performance, accuracy, and robustness. The best model is used in constructing a learning-enabled model for predicting tourists as satisfied, neutral, and unsatisfied visitors. This work is very important for tourism business personnel, government agencies, and tourism stakeholders to find information on tourist satisfaction and factors that influence it. Though this work was carried out for Pokhara city of Nepal, the study is equally relevant to any other tourism destination of similar nature.

Classification of Aβ State From Brain Amyloid PET Images Using Machine Learning Algorithm

  • Chanda Simfukwe;Reeree Lee;Young Chul Youn;Alzheimer’s Disease and Related Dementias in Zambia (ADDIZ) Group
    • Dementia and Neurocognitive Disorders
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    • v.22 no.2
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    • pp.61-68
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    • 2023
  • Background and Purpose: Analyzing brain amyloid positron emission tomography (PET) images to access the occurrence of β-amyloid (Aβ) deposition in Alzheimer's patients requires much time and effort from physicians, while the variation of each interpreter may differ. For these reasons, a machine learning model was developed using a convolutional neural network (CNN) as an objective decision to classify the Aβ positive and Aβ negative status from brain amyloid PET images. Methods: A total of 7,344 PET images of 144 subjects were used in this study. The 18F-florbetaben PET was administered to all participants, and the criteria for differentiating Aβ positive and Aβ negative state was based on brain amyloid plaque load score (BAPL) that depended on the visual assessment of PET images by the physicians. We applied the CNN algorithm trained in batches of 51 PET images per subject directory from 2 classes: Aβ positive and Aβ negative states, based on the BAPL scores. Results: The binary classification of the model average performance matrices was evaluated after 40 epochs of three trials based on test datasets. The model accuracy for classifying Aβ positivity and Aβ negativity was (95.00±0.02) in the test dataset. The sensitivity and specificity were (96.00±0.02) and (94.00±0.02), respectively, with an area under the curve of (87.00±0.03). Conclusions: Based on this study, the designed CNN model has the potential to be used clinically to screen amyloid PET images.

Clinical Usefulness of PET-MRI in Lymph Node Metastasis Evaluation of Head and Neck Cancer (두경부암 림프절 전이 평가에서 PET-MRI의 임상적 유용성)

  • Kim, Jung-Soo;Lee, Hong-Jae;Kim, Jin-Eui
    • The Korean Journal of Nuclear Medicine Technology
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    • v.18 no.1
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    • pp.26-32
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    • 2014
  • Purpose: As PET-MRI which has excellent soft tissue contrast is developed as integration system, many researches about clinical application are being conducted by comparing with existing display equipments. Because PET-MRI is actively used for head and neck cancer diagnosis in our hospital, lymph node metastasis before the patient's surgery was diagnosed and clinical usefulness of head and neck cancer PET-MRI scan was evaluated using pathological opinions and idiopathy surrounding tissue metastasis evaluation method. Materials and Methods: Targeting 100 head and neck cancer patients in SNUH from January to August in 2013. $^{18}F-FDG$ (5.18 MBq/kg) was intravenous injected and after 60 min of rest, torso (body TIM coil, Vibe-Dixon) and dedication (head-neck TIM coil, UTE, Dotarem injection) scans were conducted using $Bio-graph^{TM}$ mMR 3T (SIEMENS, Munich). Data were reorganized using iterative reconstruction and lymph node metastasis was read with Syngo.Via workstation. Subsequently, pathological observations and diagnosis before-and-after surgery were examined with integrated medical information system (EMR, best-care) in SNUH. Patient's diagnostic information was entered in each category of $2{\times}2$ decision matrix and was classified into true positive (TP), true negative (TN), false positive (FP) and false negative (FN). Based on these classified test results, sensitivity, specificity, accuracy, false negative and false positive rate were calculated. Results: In PET-MRI scan results of head and neck cancer patients, positive and negative cases of lymph node metastasis were 49 and 51 cases respectively and positive and negative lymph node metastasis through before-and-after surgery pathological results were 46 and 54 cases respectively. In both tests, TP which received positive lymph node metastasis were analyzed as 34 cases, FP which received positive lymph node metastasis in PET-MRI scan but received negative lymph node metastasis in pathological test were 4 cases, FN which received negative lymph node metastasis but received positive lymph node metastasis in pathological test was 1 case, and TN which received negative lymph node metastasis in both two tests were 50 cases. Based on these data, sensitivity in PET-MRI scan of head and neck cancer patient was identified to be 97.8%, specificity was 92.5%, accuracy was 95%, FN rate was 2.1% and FP rate was 7.00% respectively. Conclusion: PET-MRI which can apply the acquired functional information using high tissue contrast and various sequences was considered to be useful in determining the weapons before-and-after surgery in head and neck cancer diagnosis or in the evaluation of recurrence and remote detection of metastasis and uncertain idiopathy cervical lymph node metastasis. Additionally, clinical usefulness of PET-MRI through pathological test and integrated diagnosis and follow-up scan was considered to be sufficient as a standard diagnosis scan of head and neck cancer, and additional researches about the development of optimum MR sequence and clinical application are required.

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