• Title/Summary/Keyword: Mean Curve

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The prognostic value of median nerve thickness in diagnosing carpal tunnel syndrome using magnetic resonance imaging: a pilot study

  • Lee, Sooho;Cho, Hyung Rae;Yoo, Jun Sung;Kim, Young Uk
    • The Korean Journal of Pain
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    • v.33 no.1
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    • pp.54-59
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    • 2020
  • Background: The median nerve cross-sectional area (MNCSA) is a useful morphological parameter for the evaluation of carpal tunnel syndrome (CTS). However, there have been limited studies investigating the anatomical basis of median nerve flattening. Thus, to evaluate the connection between median nerve flattening and CTS, we carried out a measurement of the median nerve thickness (MNT). Methods: Both MNCSA and MNT measurement tools were collected from 20 patients with CTS, and from 20 control individuals who underwent carpal tunnel magnetic resonance imaging (CTMRI). We measured the MNCSA and MNT at the level of the hook of hamate on CTMRI. The MNCSA was measured on the transverse angled sections through the whole area. The MNT was measured based on the most compressed MNT. Results: The mean MNCSA was 9.01 ± 1.94 ㎟ in the control group and 6.58 ± 1.75 ㎟ in the CTS group. The mean MNT was 2.18 ± 0.39 mm in the control group and 1.43 ± 0.28 mm in the CTS group. Receiver operating characteristics curve analysis demonstrated that the optimal cut-off value for the MNCSA was 7.72 ㎟, with 75.0% sensitivity, 75.0% specificity, and an area under the curve (AUC) of 0.82 (95% confidence interval [CI], 0.69-0.95). The best cut off-threshold of the MNT was 1.76 mm, with 85% sensitivity, 85% specificity, and an AUC of 0.94 (95% CI, 0.87-1.00). Conclusions: Even though both MNCSA and MNT were significantly associated with CTS, MNT was identified as a more suitable measurement parameter.

Minimal clinically important difference of mouth opening in oral submucous fibrosis patients: a retrospective study

  • Kaur, Amanjot;Rustagi, Neeti;Ganesan, Aparna;PM, Nihadha;Kumar, Pravin;Chaudhry, Kirti
    • Journal of the Korean Association of Oral and Maxillofacial Surgeons
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    • v.48 no.3
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    • pp.167-173
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    • 2022
  • Objectives: The purpose of this study was to estimate the minimal clinically important difference (MCID) of mouth opening (MO) and patient satisfaction in surgically treated oral submucous fibrosis (OSMF) patients. Materials and Methods: The status of MO was collected preoperatively (T0), postoperatively at 3 months (T1), and at a minimum of 6 months postoperatively (T2). MCID was determined through the anchor-based approach with the change difference method, mean change method, and receiver operator characteristic curve (ROC) method. Results: In this study, 35 patients enrolled and completed postoperative follow-up (T2) averaging a duration of 18.1 months. At T1, using the change difference method, MO was 14.89 mm and the ROC curve exhibited a 11.5 gain in MO (sensitivity 81.8% and specificity 100%, area under the curve [AUC] of 0.902) and was classified as MCID as reported by patients. At T2, MCID of MO was 9.75 mm using the change difference method and 11.75 mm by the mean change method. The ROC curve revealed that the MCID of MO at T2 was 10.5 mm with 73.9% sensitivity and 83.3% specificity (AUC of 0.873). The kappa value was 0.91, confirming reliability of the data. Conclusion: This study demonstrated MCID values that indicate the clinical relevance of surgical treatment of OSMF if the minimum possible gain in MO is approximately 10 mm.

Acoustic range estimation of underwater vehicle with outlier elimination (특이값 제거 기법을 적용한 수중 이동체의 음향 거리 추정)

  • Kyung-won Lee;Dan-bi Ou;Ki-man Kim;Tae Hyeong Kim;Heechang Lee
    • The Journal of the Acoustical Society of Korea
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    • v.43 no.4
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    • pp.383-390
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    • 2024
  • When measuring the radiated noise of an underwater vehicle, the range information between the vehicle and the receiver is an important factor, but since Global Positioning System (GPS) is not available in underwater, an alternative method is needed. As an alternative, the range is measured by estimating the arrival time, arrival time difference, and arrival frequency difference using a separate acoustic signal. However, errors occur due to the channel environment, and these outliers become obstacles in continuously measuring range. In this paper, we propose a method to reduce errors by curve fitting with a function in the form of a V-curve as a post-processing to remove outliers that occurred in the process of measuring range information. Simulation, lake and sea trials were conducted to verify the performance of the proposed method. In the results of the lake trial, the range estimation error was reduced by about 85 % from the Root Mean Square Error (RMSE) point of view.

The estimation of river discharge by using the mean velocity equation in a unsteady condition (평균유속공식을 이용한 부정류 하천유량 산정)

  • Choo, Tai Ho;Chae, Soo Kwon;Yoon, Hyeon Cheol;Yun, Gwan Seon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.12
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    • pp.6558-6564
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    • 2013
  • As the average indicator for amount of water flowing in any cross section of a river, the mean discharge has been reported to be a very important factor for examining water circle constructions in a river basin, the design and construction of a hydraulic structure, and water front area use and management. The stage-discharge curve based on discharge and stage data measured in a normal season were basically derived. Using this derivation, the necessary discharge data was obtained. The values produced in this manner corresponded to the measured data in a uniform flow state well, but showed limited accuracy in a flood season (unsteady flow). In the present paper, the mean velocity in unsteady flow conditions, which exhibited loop form properties, was estimated using the new mean velocity formula derived from Chiu's 2-D velocity. The results of RMSE and Polar graph analyses showed that the proposed equation exhibited approximately nineteen times the accuracy compared to the Manning and Chezy equations.

Evaluation of Fatigue Life Characteristic of a Real Waterwork Pipe Using the Probability Density Function (확률밀도함수를 이용한 상수도 실 배관의 피로수명 특성 평가)

  • Choi, Jung-Hun;Koo, Jae-Mean;Seok, Chang-Sung;Song, Weon-Keyu
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.32 no.9
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    • pp.707-712
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    • 2008
  • The fatigue characteristics of a material or a structure are generally derived from fatigue tests of standard specimens. However, test results of standard specimens are different from those of real structures or components. Therefore, to calculate more accurate fatigue life, the geometrical effect and surface condition must be considered by comparing test results of standard specimens with those of real structures or components. Thus the object of this paper is to evaluate the fatigue characteristics of a real waterwork pipe. Also, to evaluate fatigue characteristic based on life distribution, the statistical fatigue characteristics were analyzed by the normal distribution and related data of P-S-N curve.

Enhanced Network Intrusion Detection using Deep Convolutional Neural Networks

  • Naseer, Sheraz;Saleem, Yasir
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.10
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    • pp.5159-5178
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    • 2018
  • Network Intrusion detection is a rapidly growing field of information security due to its importance for modern IT infrastructure. Many supervised and unsupervised learning techniques have been devised by researchers from discipline of machine learning and data mining to achieve reliable detection of anomalies. In this paper, a deep convolutional neural network (DCNN) based intrusion detection system (IDS) is proposed, implemented and analyzed. Deep CNN core of proposed IDS is fine-tuned using Randomized search over configuration space. Proposed system is trained and tested on NSLKDD training and testing datasets using GPU. Performance comparisons of proposed DCNN model are provided with other classifiers using well-known metrics including Receiver operating characteristics (RoC) curve, Area under RoC curve (AuC), accuracy, precision-recall curve and mean average precision (mAP). The experimental results of proposed DCNN based IDS shows promising results for real world application in anomaly detection systems.

2-Step Modeling for Daily Load Curve of Up to and Including 100kVA Distribution Transformer (100kVA 이하급 배전용 변압기 일부하 패턴의 2-Step 모델링)

  • Lee, Young-Suk;Kim, Jae-Chul;Yun, Sang-Yun
    • Proceedings of the KIEE Conference
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    • 2001.11b
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    • pp.371-373
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    • 2001
  • In this paper, we present 2-step load cycle for daily load curve of up to and including 100kVA distribution transformer in domestic. Daily load patterns are classified by two methods dependent upon possession information. In case we possess daily load profiles make use of K-mean algorithm and in case we have not daily load profiles, make use of customer information of KEPCO. As the parameters of the load pattern classification, we use are daily load profiles and customer information of each distribution transformers. Data management system is used for NT oracle. We can present peak load magnitude, initial load magnitude and peak load duration for daily load patterns by 2-step load cycle for daily load curve of up to and including 100kVA distribution transformer in domestic. We think that this paper contributes to enhancing the distribution transformer overload criterion.

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Development of Image Post-processing System for the Cerebral Perfusion Information Mapping of MR Image (MR영상의 뇌관류 정보 Mapping을 위한 영상후처리 시스템개발)

  • 이상민;강경훈;장두봉;김광열;김영일;신태민
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.1
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    • pp.131-138
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    • 2000
  • This paper works on development of an algorithm for mapping of cerebral perfusion parameters using the gamma-variate curve fitting. The signal intensity variate curve according to time measured in each pixel of perfusion MRI is nonlinear, and various hemodynamic parameters are not computed accurately. Levenberg-Marquardt algorithm(LMA), nonlinear optimum algorithm with high convergent speed and stability, is used to compute them. That is, the signal intensity variate curve is fitted by the gamma-variate function. Various hemodynamic parameters - Cerebral Blood Volume(C.B.V), Mean Transit Time(M.T.T), Cerebral Blood Flow(C.B.F), Time-to-Peak(T.T.P), Bolus Arrival Time(B.A.T), Maximum Slope(M.S) - are computed using LMA.

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Bezier curve smoothing of cumulative hazard function estimators

  • Cha, Yongseb;Kim, Choongrak
    • Communications for Statistical Applications and Methods
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    • v.23 no.3
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    • pp.189-201
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    • 2016
  • In survival analysis, the Nelson-Aalen estimator and Peterson estimator are often used to estimate a cumulative hazard function in randomly right censored data. In this paper, we suggested the smoothing version of the cumulative hazard function estimators using a Bezier curve. We compare them with the existing estimators including a kernel smooth version of the Nelson-Aalen estimator and the Peterson estimator in the sense of mean integrated square error to show through numerical studies that the proposed estimators are better than existing ones. Further, we applied our method to the Cox regression where covariates are used as predictors and suggested a survival function estimation at a given covariate.

On the Trajectory Null Scrolls in 3-Dimensional Minkowski Space-Time E13

  • Ersoy, Soley;Tosun, Murat
    • Kyungpook Mathematical Journal
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    • v.48 no.1
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    • pp.81-92
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    • 2008
  • In this paper, the trajectory scroll in 3-dimensional Minkowski space-time $E_1^3$ is given by a firmly connected oriented line moving with Cartan frame along curve. Some theorems and results between curvatures of base curve and distribution parameter of this surface are obtained. Moreover, some theorems and results related to being developable and minimal of this surface are given. And also, some relationships among geodesic curvature, geodesic torsion and the curvatures of base curve of trajectory scroll are found.