• Title/Summary/Keyword: Early decision

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Qualitative Case Study on Psychological Difficulties Found In Each Divorce Decision Making Stage That Senescent Women Face in Their Early Stage of Elderly Life (초기노년기 여성이 경험한 이혼결정단계별 심리적 어려움에 관한 질적사례연구)

  • Moon, Jung Hwa;Kim, Mi Ra
    • Korean Journal of Family Social Work
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    • no.58
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    • pp.67-96
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    • 2017
  • The purpose of this study is to examine psychological difficulties that elderly women experience in each divorce decision making stage and they are shown by counselling cases made with elderly women who got divorced in their early stage of elderly life. For this purpose, total 18 counseling cases were collected from November 2012 to March 2013 and a qualitative analysis was made accordingly. The result of this study was made by analyzing meaningful subjects emerged in individual testimonies during a counseling process and it shows that the decision to divorce goes through stages such as , , , , , and . In addition, psychological difficulties experienced in a divorce decision process appear to be, , , , , , and . It is meaningful that this study provides counseling strategies for psychosocial support of the elderly women who go through difficulties in their divorce decision making process.

Scoring models to detect foreign exchange money laundering (외국환 거래의 자금세탁 혐의도 점수모형 개발에 관한 연구)

  • Hong, Seong-Ik;Moon, Tae-Hee;Sohn, So-Young
    • IE interfaces
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    • v.18 no.3
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    • pp.268-276
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    • 2005
  • In recent years, the money Laundering crimes are increasing by means of foreign exchange transactions. Our study proposes four scoring models to provide early warning of the laundering in foreign exchange transactions for both inward and outward remittances: logistic regression model, decision tree, neural network, and ensemble model which combines the three models. In terms of accuracy of test data, decision tree model is selected for the inward remittance and an ensemble model for the outward remittance. From our study results, the accumulated number of transaction turns out to be the most important predictor variable. The proposed scoring models deal with the transaction level and is expected to help the bank teller to detect the laundering related transactions in the early stage.

The Comparative Study of the relationship between Technology Valuation Index and performance in Ventures (기술평가지표와 기업성과의 관계비교분석 -초기중소벤처와 성장중소벤처-)

  • Yang Dong-Woo
    • Journal of Korea Technology Innovation Society
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    • v.8 no.3
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    • pp.1175-1198
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    • 2005
  • The objective of the study is to verify the relationship between technology valuation indexes and corporate's performance in ventures by business operating periods. The result of the study is expected to be useful in loan evaluation, investment decision, internal management decision making and business improvement. The results of study is as follows. First, in early stage ventures, we find that three major valuation index(technology feasibility, economic efficiency, productivity) are significant ex-ante variables which are discriminating between firms' going concern and firms' failure. Second, in growth stage ventures, we find that three major valuation index(business feasibility, general marketability, technology marketability) are significant ex-ante variables which are discriminating between firms' going concern and firms' failure. Third, in early stage ventures, we find that at least thirty-eight minor valuation index elements are significant ex-ante variables which are discriminating between firms' going concern and firms' failure and in growth stage ventures, thirty-one minor valuation index elements are significant in various analysis' results.

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Performance analysis and comparison of various machine learning algorithms for early stroke prediction

  • Vinay Padimi;Venkata Sravan Telu;Devarani Devi Ningombam
    • ETRI Journal
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    • v.45 no.6
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    • pp.1007-1021
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    • 2023
  • Stroke is the leading cause of permanent disability in adults, and it can cause permanent brain damage. According to the World Health Organization, 795 000 Americans experience a new or recurrent stroke each year. Early detection of medical disorders, for example, strokes, can minimize the disabling effects. Thus, in this paper, we consider various risk factors that contribute to the occurrence of stoke and machine learning algorithms, for example, the decision tree, random forest, and naive Bayes algorithms, on patient characteristics survey data to achieve high prediction accuracy. We also consider the semisupervised self-training technique to predict the risk of stroke. We then consider the near-miss undersampling technique, which can select only instances in larger classes with the smaller class instances. Experimental results demonstrate that the proposed method obtains an accuracy of approximately 98.83% at low cost, which is significantly higher and more reliable compared with the compared techniques.

Fast Intraframe Coding for High Efficiency Video Coding

  • Huang, Han;Zhao, Yao;Lin, Chunyu;Bai, Huihui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.3
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    • pp.1093-1104
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    • 2014
  • The High Efficiency Video Coding (HEVC) is a new video coding standard that can provide much better compression efficiency than its predecessor H.264/AVC. However, it is computationally more intensive due to the use of flexible quadtree coding unit structure and more choices of prediction modes. In this paper, a fast intraframe coding scheme is proposed for HEVC. Firstly, a fast bottom-up pruning algorithm is designed to skip the mode decision process or reduce the candidate modes at larger block size coding unit. Then, a low complexity rough mode decision process is adopted to choose a small candidate set, followed by early DC and Planar mode decision and mode filtering to further reduce the number of candidate modes. The proposed method is evaluated by the HEVC reference software HM8.2. Averaging over 5 classes of HEVC test sequences, 41.39% encoding time saving is achieved with only 0.77% bitrate increase.

문제해결과정의 단계별 회귀가 문제해결시간에 미치는 영향에 관한 연구

  • 손달호;최무진
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1993.04a
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    • pp.73-82
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    • 1993
  • Over the last decades, interest in the application of decision support systems(DSS) in organizations has increased rapidly. Desipte the growing number of investigations examining decision support system, relatively few empirical studies have evaluated the effects of DSS on problem-solving processes. This study examined, using a computer simulation technique, the effect of recursion in problem-solving processes about the problem-solving time. Results indicate that the recursion at the early stage of problem-solving processes scarcely influenced the problem-solving time, which is contrasted with the case of the recursion at the final stage.

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Corresponding between Error Probabilities and Bayesian Wrong Decision Lasses in Flexible Two-stage Plans

  • Ko, Seoung-gon
    • Journal of the Korean Statistical Society
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    • v.29 no.4
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    • pp.435-441
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    • 2000
  • Ko(1998, 1999) proposed certain flexible two-stage plans that could be served as one-step interim analysis in on-going clinical trials. The proposed Plans are optimal simultaneously in both a Bayes and a Neyman-Pearson sense. The Neyman-Pearson interpretation is that average expected sample size is being minimized, subject just to the two overall error rates $\alpha$ and $\beta$, respectively of first and second kind. The Bayes interpretation is that Bayes risk, involving both sampling cost and wrong decision losses, is being minimized. An example of this correspondence are given by using a binomial setting.

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Deciding the Optimal Shutdown time of a Nuclear Power Plant (원자력 발전소의 최적 운행중지 시기 결정 방법)

  • Yang, Hee-Joong
    • IE interfaces
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    • v.13 no.2
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    • pp.211-216
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    • 2000
  • A methodology that determines the optimal shutdown time of a nuclear power plant is suggested. The shutdown time is decided considering the trade off between the cost of accident and the loss of profit due to the early shutdown. We adopt the bayesian approach in manipulating the model parameter that predicts the accidents. We build decision tree models and apply dynamic programming approach to decide whether to shutdown immediately or operate one more period. The branch parameters in decision trees are updated by bayesian approach. We apply real data to this model and provide the cost of accidents that guarantees the immediate shutdown.

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A METHOD OF REVISING RETRIEVED SIMILAR CASES IN GA-CBR COST MODELS

  • Sooyoung Kim;Hyun-Soo Lee;Moonseo Park;Sae-Hyun Ji;Joseph Ahn
    • International conference on construction engineering and project management
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    • 2011.02a
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    • pp.182-186
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    • 2011
  • Early cost estimates are important to decision-making for a construction project. Moreover, the possibility of reducing the project cost is getting less as the project is progressed. Case-based reasoning (CBR), which can be viewed as an effective method for early cost estimating, is widely utilized recently. Early cost estimates using CBR have advantages over the traditional ones as they produce reasonable outputs and self-studying is possible by simply adding new cases. Case-based reasoning is composed of a cycle of retrieve, reuse, revise, and retain process. However, in the majority of research cases, they are focused on how to retrieve the similar cases, instead of revising the cases which is expected to increase accuracy results of cost estimation. This research suggests a method of revising retrieved similar cases in a GA-CBR cost model which is widely studied and utilized for early cost estimating recently. To validate the proposed method, case study is conducted based on Korean public apartment projects.

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The Distribution of Information Sources within the University Selection Decision-Making Process: A Longitudinal Study

  • LE, Tri D.;NGUYEN, Tan T.;NGUYEN, Phuong N.D.;NGUYEN, Thi Quynh Trang
    • Journal of Distribution Science
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    • v.20 no.11
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    • pp.89-98
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    • 2022
  • Purpose: Increasing competition in the higher education sector has prompted universities to enhance their marketing efforts and understand their potential customers. The study aims to explore how information sources are used and changed among prospective Vietnamese students during the decision-making process. Research Design, Data, and Methodology: This study undertakes a longitudinal study involving multiple rounds of data collection to better understand the decision-making process of prospective students. Data was collected from 12th -grade students in Vietnam through two rounds of quantitative surveys with 251 students and one round of qualitative interviews, spanning the duration of their senior year. The three stages of the decision-making process correspond to the three stages of pre-purchase period. Results: Most students decide that attending open days, taking career assessments, and looking up information online are the most important information sources to consider. The WOM sources are more important in the early stages, while university-generated sources and events are important in the later stages. Conclusion: Implications from this study may contribute to the design of more effective marketing communications campaigns as university marketers gain a better understanding of the distribution of information sources utilized for each specific stage of the decision-making process.