• 제목/요약/키워드: recurrent

검색결과 3,538건 처리시간 0.029초

Risk factors for recurrent urinary tract infections in young infants under the age of 24 months

  • Min Hwa Son;Hyung Eun Yim
    • Childhood Kidney Diseases
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    • 제28권1호
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    • pp.35-43
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    • 2024
  • Purpose: Recurrent urinary tract infections (UTIs) in children is a major challenge for pediatricians. This study was designed to investigate the risk factors for recurrent UTIs and determine the association between recurrent UTIs and clinical findings, including growth patterns in infants and children younger than 24 months of age. Methods: We retrospectively reviewed the medical records of 147 patients <24 months of age with UTIs who were hospitalized between August 2018 and October 2021. The patients were divided into recurrent and single UTI episode groups. Clinical findings and anthropometric and laboratory data were compared between the two groups. Results: In the recurrent UTI group, the weight-for-length (WFL) percentile at the first UTI diagnosis was lower compared to the single UTI episode group, and the weight-for-age percentile at 3-month and 6-month follow-ups after the first UTI decreased (all P<0.05). In univariable logistic regression analysis, higher birth weight, lower WFL percentile, the presence of hydronephrosis, acute pyelonephritis or vesicoureteral reflux, the use of prophylactic antibiotics, and non-Escherichia coli infections were associated with the development of recurrent UTIs (all P<0.05). However, in the multivariable analysis, only the presence of hydronephrosis and prophylactic antibiotic use were independently related to UTI recurrence (P<0.05). Conclusions: The presence of hydronephrosis at the first UTI can be helpful for predicting UTI recurrence in young children aged <24 months. Antibiotic prophylaxis may be associated with UTI recurrence. Potential growth delay should be carefully monitored in infants with recurrent UTI.

SOME NOTES ON NEARLY COSYMPLECTIC MANIFOLDS

  • Yildirim, Mustafa;Beyendi, Selahattin
    • 호남수학학술지
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    • 제43권3호
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    • pp.539-545
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    • 2021
  • In this paper, we study some symmetric and recurrent conditions of nearly cosymplectic manifolds. We prove that Ricci-semisymmetric and Ricci-recurrent nearly cosymplectic manifolds are Einstein and conformal flat nearly cosymplectic manifold is locally isometric to Riemannian product ℝ × N, where N is a nearly Kähler manifold.

청각모델과 회귀회로망을 이용한 음성인식에 관한 연구 (A Study on Speech Recognition Using Auditory Model and Recurrent Network)

  • 김동준;이재혁;윤태성;박상희
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1990년도 춘계학술대회
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    • pp.51-55
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    • 1990
  • In this study, a peripheral auditory model used as a frequency feature extractor and a recurrent network which has recurrent links on input nodes is constructed in order to show the reliability of the recurrent network as a recognizer by executing recognition tests for 4 Korean placenames and syllables. As a result of this study, a refined weight compensation method is proposed and, using this method, it is possible to improve the system operation. The recurrent network in this study reflects well time information of temporal speech signal.

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ON Φ-RECURRENT (k, μ)-CONTACT METRIC MANIFOLDS

  • Jun, Jae-Bok;Yildiz, Ahmet;De, Uday Chand
    • 대한수학회보
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    • 제45권4호
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    • pp.689-700
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    • 2008
  • In this paper we prove that a $\phi$-recurrent (k, $\mu$)-contact metric manifold is an $\eta$-Einstein manifold with constant coefficients. Next, we prove that a three-dimensional locally $\phi$-recurrent (k, $\mu$)-contact metric manifold is the space of constant curvature. The existence of $\phi$-recurrent (k, $\mu$)-manifold is proved by a non-trivial example.

재발된 위암 환자에서 발생한 천공성 수입각 증후군의 비수술적 치료 (Perforated Afferent Loop Syndrome in a Patient with Recurrent Gastric Cancer: Non-Surgical Treatment with Percutaneous Transhepatic Duodenal Drainage and Endoscopic Stent)

  • 송교영;손창희;박조현;김승남
    • Journal of Gastric Cancer
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    • 제4권3호
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    • pp.176-179
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    • 2004
  • Surgical treatment for afferent loop syndrome (ALS) in patients with recurrent gastric cancer is usually not feasible because of the recurrent tumor mass at the anastomosis site and/or extensive carcinomatosis resulting in bowel loop fixation. Furthermore, ALS usually makes oral intake impossible, resulting in a rapid deterioration in general condition. In this situation, gastroscopic stenting at the anastomotic site and/or percutaneous external drainage may be a more feasible alternative for palliation. We herein report a recurrent gastric cancer whose ALS was successfully treated with internal and external drainage procedures.

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DRNN을 이용한 최적 난방부하 식별 (Optimal Heating Load Identification using a DRNN)

  • 정기철;양해원
    • 대한전기학회논문지:전력기술부문A
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    • 제48권10호
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    • pp.1231-1238
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    • 1999
  • This paper presents an approach for the optimal heating load Identification using Diagonal Recurrent Neural Networks(DRNN). In this paper, the DRNN captures the dynamic nature of a system and since it is not fully connected, training is much faster than a fully connected recurrent neural network. The architecture of DRNN is a modified model of the fully connected recurrent neural network with one hidden layer. The hidden layer is comprised of self-recurrent neurons, each feeding its output only into itself. In this study, A dynamic backpropagation (DBP) with delta-bar-delta learning method is used to train an optimal heating load identifier. Delta-bar-delta learning method is an empirical method to adapt the learning rate gradually during the training period in order to improve accuracy in a short time. The simulation results based on experimental data show that the proposed model is superior to the other methods in most cases, in regard of not only learning speed but also identification accuracy.

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Statistical Analysis of Bivariate Recurrent Event Data with Incomplete Observation Gaps

  • Kim, Yang-Jin
    • Communications for Statistical Applications and Methods
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    • 제20권4호
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    • pp.283-290
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    • 2013
  • Subjects can experience two types of recurrent events in a longitudinal study. In addition, there may exist intermittent dropouts that results in repeated observation gaps during which no recurrent events are observed. Therefore, theses periods are regarded as non-risk status. In this paper, we consider a special case where information on the observation gap is incomplete, that is, the termination time of observation gap is not available while the starting time is known. For a statistical inference, incomplete termination time is incorporated in terms of interval-censored data and estimated with two approaches. A shared frailty effect is also employed for the association between two recurrent events. An EM algorithm is applied to recover unknown termination times as well as frailty effect. We apply the suggested method to young drivers' convictions data with several suspensions.

수면과다증을 반복적으로 보이는 24세 여자환자 (A Case of 24-Year-Old Woman with Recurrent Hypersomnic Complaint)

  • 윤인영;정도언
    • 수면정신생리
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    • 제2권1호
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    • pp.91-96
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    • 1995
  • A 24-year-old woman complained of recurrent episodes of hypersomnia lasting on the average about 15 days with mild mood alternation such as depression and irritability. During interepisode interval, she was free of any symptoms. Depending on the absence of excessive eating and hypersexuality, she was clinically diagnosed as recurrent monosymptomatic hypersomnia or the incomplete form of Kleine-Levin syndrome. When nocturnal polysomnography and multiple sleep latency test were performed 10 days after her recovery from a hypersomnic episode, reduced slow wave sleep % and pathologic daytime sleepiness were still noted. The authors suggest that the clinical recovery in recurrent monosymptomatic hypersomnia precede electrophysiological normalization by several days.

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청각모델과 회귀회로망을 이용한 음성인식에 관한 연구 (A Study on Speech Recognition Using Auditory Model and Recurrent Network)

  • 김동준;이재혁
    • 대한의용생체공학회:의공학회지
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    • 제11권1호
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    • pp.157-162
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    • 1990
  • In this study, a peripheral auditory model is used as a frequency feature extractor and a recurrent network which has recurrent links on input nodes is constructed in order to show the reliability of the recurrent network as a recognizer by executing recognition tests for 4 Korean place names and syllables. In the case of using the general learning rule, it is found that the weights are diverged for a long sequence because of the characteristics of the node function in the hidden and output layers. So, a refined weight compensation method is proposed and, using this method, it is possible to improve the system operation and to use long data. The recognition results are considerably good, even if time worping and endpoint detection are omitted and learning patterns and test patterns are made of average length of data. The recurrent network used in this study reflects well time information of temporal speech signal.

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