• Title/Summary/Keyword: uncertain data

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Robust Particle Filter Based Route Inference for Intelligent Personal Assistants on Smartphones (스마트폰상의 지능형 개인화 서비스를 위한 강인한 파티클 필터 기반의 사용자 경로 예측)

  • Baek, Haejung;Park, Young Tack
    • Journal of KIISE
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    • v.42 no.2
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    • pp.190-202
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    • 2015
  • Much research has been conducted on location-based intelligent personal assistants that can understand a user's intention by learning the user's route model and then inferring the user's destinations and routes using data of GPS and other sensors in a smartphone. The intelligence of the location-based personal assistant is contingent on the accuracy and efficiency of the real-time predictions of the user's intended destinations and routes by processing movement information based on uncertain sensor data. We propose a robust particle filter based on Dynamic Bayesian Network model to infer the user's routes. The proposed robust particle filter includes a particle generator to supplement the incorrect and incomplete sensor information, an efficient switching function and an weight function to reduce the computation complexity as well as a resampler to enhance the accuracy of the particles. The proposed method improves the accuracy and efficiency of determining a user's routes and destinations.

Comparison of Interferon-γ Release Assays and the Tuberculin Skin Test for Diagnosis of Tuberculosis in Human Immunodeficiency Virus: A Systematic Review

  • Overton, Kristen;Varma, Rick;Post, Jeffrey J.
    • Tuberculosis and Respiratory Diseases
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    • v.81 no.1
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    • pp.59-72
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    • 2018
  • Background: It remains uncertain if $interferon-{\gamma}$ release assays (IGRAs) are superior to the tuberculin skin test (TST) for the diagnosis of active tuberculosis (TB) or latent tuberculosis infection (LTBI) in immunosuppressed populations including people with human immunodeficiency virus (HIV) infection. The purpose of this study was to systematically review the performance of IGRAs and the TST in people with HIV with active TB or LTBI in low and high prevalence TB countries. Methods: We searched the MEDLINE database from 1966 through to January 2017 for studies that compared results of the TST with either the commercial QuantiFERON-TB Gold in Tube (QFTGT) assay or previous assay versions, the T-SPOT.TB assay or in-house IGRAs. Data were summarized by TB prevalence. Tests for concordance and differences in proportions were undertaken as appropriate. The variation in study methodology was appraised. Results: Thirty-two studies including 4,856 HIV subjects met the search criteria. Fourteen studies compared the tests in subjects with LTBI in low TB prevalence settings. The QFTGT had a similar rate of reactivity to the TST, although the first-generation version of that assay was reactive more commonly. IGRAs were more frequently positive than the TST in HIV infected subjects with active TB. There was considerable study methodology and population heterogeneity, and generally low concordance between tests. Both the TST and IGRAs were affected by CD4 T-cell immunodeficiency. Conclusion: Our review of comparative data does not provide robust evidence to support the assertion that the IGRAs are superior to the TST when used in HIV infected subjects to diagnose either active TB or LTBI.

A Study on the Optimal Loan Limit Management Using the Newsvendor Model (뉴스벤더 모델을 이용한 최적 대출금 한도 관리에 관한 연구)

  • Sin, Jeong-Hun;Hwang, Seung-June
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.38 no.3
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    • pp.39-48
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    • 2015
  • In this study, granting the optimal loan limit on SME (Small and Medium Enterprise) loans of financial institutions was proposed using the traditional newsvendor model. This study was the first domestic case study that applied the newsvendor model that was mainly used to calculate the optimum order quantity under some uncertain demands to the calculation of the loan limit (debt ceiling) of institutions. The method presented in this study made it possible to calculate the loan limit (debt ceiling) to maximize the revenue of a financial institution using probability functions, applied the newsvendor model setting the order volume of merchandise goods as the loan product order volume of the financial institution, and proposed, through the analysis of empirical data, the availability of additional loan to the borrower and the reduction of the debt ceiling and a management method for the recovery of the borrower who could not generate profit. In addition, the profit based loan money management model presented in this study also demonstrated that it also contributed to some extent to the prediction of the bankruptcy of the borrowing SME (Small and Medium Enterprise), as well as the calculation of the loan limit based on profit, by deriving the result values that the borrowing SME (Small and Medium Enterprise) actually went through bankruptcy at later times once the model had generated a signal of loan recovery for them during the validation of empirical data. accordingly, The method presented in this study suggested a methodology to generated a signal of loan recovery to reduce the losses by the bankruptcy.

A Product Quality Prediction Model Using Real-Time Process Monitoring in Manufacturing Supply Chain (실시간 공정 모니터링을 통한 제품 품질 예측 모델 개발)

  • Oh, YeongGwang;Park, Haeseung;Yoo, Arm;Kim, Namhun;Kim, Younghak;Kim, Dongchul;Choi, JinUk;Yoon, Sung Ho;Yang, HeeJong
    • Journal of Korean Institute of Industrial Engineers
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    • v.39 no.4
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    • pp.271-277
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    • 2013
  • In spite of the emphasis on quality control in auto-industry, most of subcontract enterprises still lack a systematic in-process quality monitoring system for predicting the product/part quality for their customers. While their manufacturing processes have been getting automated and computer-controlled ever, there still exist many uncertain parameters and the process controls still rely on empirical works by a few skilled operators and quality experts. In this paper, a real-time product quality monitoring system for auto-manufacturing industry is presented to provide the systematic method of predicting product qualities from real-time production data. The proposed framework consists of a product quality ontology model for complex manufacturing supply chain environments, and a real-time quality prediction tool using support vector machine algorithm that enables the quality monitoring system to classify the product quality patterns from the in-process production data. A door trim production example is illustrated to verify the proposed quality prediction model.

Study Based on Grounded Theory about Job Experience of Visiting Supervisors for Multicultural Families (다문화가정 방문교육지도사의 직업경험에 관한 근거이론연구)

  • Lee, OBok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.10
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    • pp.6092-6101
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    • 2014
  • This study examined the job experience of visiting supervisors for multicultural families. To achieve the goal of this study, data was collected by in-depth interviews with 7 visiting supervisors for multicultural families. For an analysis of the data, the grounded theory approach by Strauss and Corbin [11] was employed. The results of an analysis of the categories are detailed below. Through an open coding process, a total of 124 concepts, 33 subcategories, and 13 categories were produced. The central phenomenon was 'uncertain employment '. From the axial coding, the causal conditions were 'employment for economic reasons' and 'frequent policy and regulation changes'. The contextual conditions were 'uneasiness about the evaluation result', 'unilateral work instruction system', and 'little improvement of treatment'. Intervention conditions were 'high level of satisfaction with work', 'handy source of income', and 'no other alternative'. Action/interaction strategies were 'efforts for contract extension' and 'receptive attitude'. The consequences were 'hope to retain employment' and 'agonizing over their rights'.

Mothers' experience of caring for home-quarantined children after close contact with COVID-19 in Korea: an exploratory qualitative study

  • Lee, Hyeyeon;Kim, Mihui;Kim, Ocksim;Kim, Sue;Choi, Seongmi
    • Women's Health Nursing
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    • v.27 no.3
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    • pp.220-229
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    • 2021
  • Purpose: The world saw a shift into a new society consequent to the coronavirus disease 2019 (COVID-19), which made home quarantine mandatory for a person in close contact with those who tested positive. For children, however, home quarantine was not limited only to themselves but parents, especially mothers were involved and required to quarantine. This qualitative study aims to explore and understand mothers' experience and their related psychosocial issues while caring for their school-aged children in Korea, who had to home quarantine after coming in close contact with COVID-19 positive individuals. Methods: Data were collected from October 2020 to January 2021 via in-depth, semi-structured interviews with nine mothers of children who had to home quarantine. Interviews were conducted face-to-face in an independent space near the participant's home or workplace (n=5) or via online platforms or telephone (n=4). The data were analyzed using thematic analysis through several iterative team meetings. Results: Thematic analysis revealed the following four themes: "Unable to be relieved due to uncertain situations surrounding me," "Blame and hurt toward me, others, and one another," "Pulling myself together for my children in my broken daily life," and "Changes in the meaning of life amid COVID-19." Conclusion: The narratives show that mothers experienced psychosocial difficulties while caring for their children during home quarantine. It is necessary to reduce the social stigma toward individuals in home quarantine and establish policies to ensure work-family compatibility for such mothers.

Outcomes of Mechanical Thrombectomy in Patients with Large Diffusion-Weighted Imaging Lesions

  • Cho, Yong-Hwan;Choi, Jae Hyung
    • Journal of Korean Neurosurgical Society
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    • v.65 no.1
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    • pp.22-29
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    • 2022
  • Objective : Despite many advancements in endovascular treatment, the benefits of mechanical thrombectomy (MT) in patients with large infarctions remain uncertain due to hemorrhagic complications. Therefore, we aimed to investigate the efficacy and safety of recanalization via MT within 6 hours after stroke in patients with large cerebral infarction volumes (>70 mL). Methods : We retrospectively reviewed the medical data of 30 patients with large lesions on initial diffusion-weighted imaging (>70 mL) who underwent MT at our institution within 6 hours after stroke onset. Baseline data, recanalization rate, and 3-month clinical outcomes were analyzed. Successful recanalization was defined as a modified treatment in cerebral ischemia score of 2b or 3. Results : The recanalization rate was 63.3%, and symptomatic intracerebral hemorrhage occurred in six patients (20%). The proportion of patients with modified Rankin Scale (mRS) scores of 0-3 was significantly higher in the recanalization group than in the non-recanalization group (47.4% vs. 9.1%, p=0.049). The mortality rate was higher in the non-recanalization group, this difference was not significant (15.8% vs. 36.4%, p=0.372). In the analysis of 3-month clinical outcomes, only successful recanalization was significantly associated with mRS scores of 0-3 (90% vs. 50%, p=0.049). The odds ratio of recanalization for favorable outcomes (mRS 0-3) was 9.00 (95% confidence interval, 0.95-84.90; p=0.055). Conclusion : Despite the risk of symptomatic intracerebral hemorrhage, successful recanalization via MT 6 hours after stroke may improve clinical outcomes in patients with large vessel occlusion.

Priority Analysis for Applying Digital Technology to Improve the Efficiency of Building Supervision Work (건축감리 업무의 효율성 제고를 위한 디지털 기술 적용 우선순위 분석)

  • Kim, Chang-Won;Yoo, Wi Sung;Lim, Hyunsu
    • Journal of the Korea Institute of Building Construction
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    • v.23 no.1
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    • pp.93-102
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    • 2023
  • Building supervision can be defined as a major task that involves managing and supervising the construction process to support the creation of high-quality results. To successfully perform supervision work, it is necessary to collect various information generated in uncertain field conditions, but today, supervision is performed based on documents such as reports, so there are limitations in collecting information. In fact, it has also been reported that the recent collapse of an apartment building in Korea was caused by limitations of information communication in th supervision work. Accordingly, this study analyzed the types of digital technologies that can be used to improve the efficiency of building supervision work, and presented the prioritized application of them. Priority application was quantitatively evaluated using analytic hierarchy process on data through a survey. It is expected that the results of this study can be used as basic data to set the roadmap of digital technology for building supervision in the future.

Applying the ANFIS to the Analysis of Rain and Dark Effects on the Saturation Headways at Signalized Intersections (강우 및 밝기에 따른 신호교차로 포화차두시간 분석에의 적응 뉴로-퍼지 적용)

  • Kim, Kyung Whan;Chung, Jae Whan;Kim, Daehyon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.4D
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    • pp.573-580
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    • 2006
  • The Saturation headway is a major parameter in estimating the intersection capacity and setting the signal timing. But Existing algorithms are still far from being robust in dealing with factors related to the variation of saturation headways at signalized intersections. So this study apply the fuzzy inference system using ANFIS. The ANFIS provides a method for the fuzzy modeling procedure to learn information about a data set, in order to compute the membership function parameters that best allow the associated fuzzy inference system to track the given input/output data. The climate conditions and the degree of brightness were chosen as the input variables when the rate of heavy vehicles is 10-25 %. These factors have the uncertain nature in quantification, which is the reason why these are chosen as the fuzzy variables. A neuro-fuzzy inference model to estimate saturation headways at signalized intersections was constructed in this study. Evaluating the model using the statistics of $R^2$, MAE and MSE, it was shown that the explainability of the model was very high, the values of the statistics being 0.993, 0.0289, 0.0173 respectively.

Data-driven Model Prediction of Harmful Cyanobacterial Blooms in the Nakdong River in Response to Increased Temperatures Under Climate Change Scenarios (기후변화 시나리오의 기온상승에 따른 낙동강 남세균 발생 예측을 위한 데이터 기반 모델 시뮬레이션)

  • Gayeon Jang;Minkyoung Jo;Jayun Kim;Sangjun Kim;Himchan Park;Joonhong Park
    • Journal of Korean Society on Water Environment
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    • v.40 no.3
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    • pp.121-129
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    • 2024
  • Harmful cyanobacterial blooms (HCBs) are caused by the rapid proliferation of cyanobacteria and are believed to be exacerbated by climate change. However, the extent to which HCBs will be stimulated in the future due to increased temperature remains uncertain. This study aims to predict the future occurrence of cyanobacteria in the Nakdong River, which has the highest incidence of HCBs in South Korea, based on temperature rise scenarios. Representative Concentration Pathways (RCPs) were used as the basis for these scenarios. Data-driven model simulations were conducted, and out of the four machine learning techniques tested (multiple linear regression, support vector regressor, decision tree, and random forest), the random forest model was selected for its relatively high prediction accuracy. The random forest model was used to predict the occurrence of cyanobacteria. The results of boxplot and time-series analyses showed that under the worst-case scenario (RCP8.5 (2100)), where temperature increases significantly, cyanobacterial abundance across all study areas was greatly stimulated. The study also found that the frequencies of HCB occurrences exceeding certain thresholds (100,000 and 1,000,000 cells/mL) increased under both the best-case scenario (RCP2.6 (2050)) and worst-case scenario (RCP8.5 (2100)). These findings suggest that the frequency of HCB occurrences surpassing a certain threshold level can serve as a useful diagnostic indicator of vulnerability to temperature increases caused by climate change. Additionally, this study highlights that water bodies currently susceptible to HCBs are likely to become even more vulnerable with climate change compared to those that are currently less susceptible.