• Title/Summary/Keyword: Statistics technique

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THE USE OF NEAR INFRARED REFLECTANCE SPECTROSCOPY(NIRS) TO PREDICT CHEMICAL COMPOSITION ON MAIZE SILAGE

  • D.Cozzolino;Fassio, A.;Mieres, J.;Y.Acosta
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1610-1610
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    • 2001
  • Microbiological examination of silage is of little value in gauging the outcome of silage, and so chemical analysis is more reliable and meaningful indicator of quality. On the other hand chemical assessments of the principal fermentation products provide an unequivocal basis on which to judge quality. Livestock require energy, protein, minerals and vitamins from their food. While fresh forages provide these essential items, conserved forages on the other hand may be deficient in one or more of them. The aim of the conservation process is to preserve as many of the original nutrients as possible, particularly energy and protein components (Woolford, 1984). Silage fermentation is important to preservation of forage with respect of feeding value and animal performance. Chemical and bacteriological changes in the silo during the fermentation process can affect adversely nutrient yield and quality (Moe and Carr, 1984). Many of the important chemical components of silage must be assayed in fresh or by extraction of the fresh material, since drying either by heat or lyophilisation, volatilises components such as acids or nitrogenous components, or effects conversion to other compounds (Abrams et al., 1987). Maize silage dorms the basis of winter rations for the vast majority of dairy and beef cattle production in Uruguay. Since nutrient intake, particularly energy, from forages is influenced by both voluntary dry matter intake and digestibility; there is a need for a rapid technique for predicting these parameters in farm advisory systems. Near Infrared Reflectance Spectroscopy (NIRS) is increasingly used as a rapid, accurate method of evaluating chemical constituents in cereals and dried forages. For many years NIRS was applied to assess chemical composition in dry materials (Norris et al., 1976, Flinn et al., 1992; Murray, 1993, De Boever et al., 1996, De la Roza et al., 1998). The objectives of this study were (1) to determine the potential of NIRS to assess the chemical composition of dried maize samples and (2) to attempt calibrations on undried samples either for farm advisory systems or for animal nutrition research purposes in Uruguay. NIRS were used to assess the chemical composition of whole - plant maize silage samples (Zea mays, L). A representative population of samples (n = 350) covering a wide distribution in chemical characteristics were used. Samples were scanned at 2 nm intervals over the wavelength range 400-2500 nm in a NIRS 6500 (NIRSystems, Silver Spring, MD, USA) in reflectance mode. Cross validation was used to avoid overfitting of the equations. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation (SECV). The calibration statistics were R$^2$ 0. 86 (SECV: 11.4), 0.90 (SECV: 5.7), 0.90 (SECV: 16.9) for dry matter (DM), crude protein (CP), acid detergent fiber (ADF) in g kg$\^$-1/ on dry matter, respectively for maize silage samples. This work demonstrates the potential of NIRS to analyse whole - maize silage in a wide range of chemical characteristics for both advisory farm and nutritive evaluation.

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Assessing Risks and Categorizing Root Causes of Demolition Construction using the QFD-FMEA Approach (QFD-FMEA를 이용한 해체공사의 위험평가와 근본원인의 분류 방법)

  • Yoo, Donguk;Lim, Nam-Gi;Chun, Jae-Youl;Cho, Jaeho
    • Journal of the Korea Institute of Building Construction
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    • v.23 no.4
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    • pp.417-428
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    • 2023
  • The demolition of domestic infrastructures mirrors other significant construction initiatives in presenting a markedly high accident rate. A comprehensive investigation into the origins of such accidents is crucial for the prevention of future incidents. Upon detailed inspection, the causes of demolition construction accidents are multifarious, encompassing unsafe worker behavior, hazardous conditions, psychological and physical states, and site management deficiencies. While statistics relating to demolition construction accidents are consistently collated and reported, there exists an exigent need for a more foundational cause categorization system based on accident type. Drawing from Heinrich's Domino Theory, this study classifies the origins of accidents(unsafe behavior, unsafe conditions) and human errors(human factors) as per the type of accidents experienced during demolition construction. In this study, a three-step model of QFD-FMEA(Quality Function Deployment - Failure Mode Effect Analysis) is employed to systematically categorize accident causes according to the types of accidents that occur during demolition construction. The QFD-FMEA method offers a technique for cause classification at each stage of the demolition process, including direct causes(unsafe behavior, unsafe environment), and human errors(human factors) through a tri-stage process. The results of this accident cause classification can serve as safety knowledge and reference checklists for accident prevention efforts.

Building a Model to Estimate Pedestrians' Critical Lags on Crosswalks (횡단보도에서의 보행자의 임계간격추정 모형 구축)

  • Kim, Kyung Whan;Kim, Daehyon;Lee, Ik Su;Lee, Deok Whan
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.1D
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    • pp.33-40
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    • 2009
  • The critical lag of crosswalk pedestrians is an important parameter in analyzing traffic operation at unsignalized crosswalks, however there is few research in this field in Korea. The purpose of this study is to develop a model to estimate the critical lag. Among the elements which influence the critical lag, the age of pedestrians and the length of crosswalks, which have fuzzy characteristics, and the each lag which is rejected or accepted are collected on crosswalks of which lengths range from 3.5 m to 10.5 m. The values of the critical lag range from 2.56 sec. to 5.56 sec. The age and the length are divided to the 3 fuzzy variables each, and the critical lag of each case is estimated according to Raff's technique, so a total of 9 fuzzy rules are established. Based on the rules, an ANFIS (Adaptive Neuro-Fuzzy Inference System) model to estimate the critical lag is built. The predictability of the model is evaluated comparing the observed with the estimated critical lags by the model. Statistics of $R^2$, MAE, MSE are 0.96, 0.097, 0.015 respectively. Therefore, the model is evaluated to explain the result well. During this study, it is found that the critical lag increases rapidly over the pedestrian's age of 40 years.

Estimation of the Marginal Walking Time of Bus Users in Small-Medium Cities (중·소도시 버스이용자의 한계도보시간 추정)

  • Kim, Kyung Whan;Yoo, Hwan Hee;Lee, Sang Ho
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.4D
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    • pp.451-457
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    • 2008
  • Establishing realistic bus service coverage is needed to build optimum city bus line networks and reasonable bus service coverage areas. The purposes of this study are understanding the characteristics of the present walking time and marginal walking time of small-medium cities and constructing an ANFIS (Adaptive Neuro-Fuzzy Inference System) model to estimate the marginal walking time for certain age and income. The cities of Masan, Chongwon and Jinju are selected for study cities. The 80 percentile of present walking time of bus users of these cities are 10.2-11.1 minutes, thus the values are greater than the 5 minutes of the maximum walking time in USA and the marginal walking times of 21.1-21.8 minutes are much greater. An ANFIS model based on pulled data of the cities are constructed to estimate the marginal walking time of small-medium cities. Analyzing the relationship between marginal walking time and age/income by using the model, the marginal walking time decreases as the age increases, but is near constant from the age of 25 to 35. And the marginal walking time is inversely proportional to the income. In comparing the surveyed and the estimated values, as the statistics of coefficient of determination, MSE and MAE are 0.996, 0.163, 0.333 respectively, it may be judged that the explainability of the model is very high. The technique developed in this study can be applied to other cities.

Medical Costs between Dietary Supplement Users and Non-users Using the Korea Health Panel Data (한국의료패널 자료를 활용한 건강기능식품 섭취에 따른 의료비 지출 비교분석)

  • Hye-Young Kwon;Soohyun Oh
    • Health Policy and Management
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    • v.34 no.1
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    • pp.87-93
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    • 2024
  • Background: In recent years, studies have shown conflicting results regarding the benefits of dietary supplements in reducing healthcare expenditures. This study aimed to address this inconsistency by examining the association between supplement consumption and health expenditures using nationally representative data from the Korea Health Panel Survey (2019-2020). Methods: A 1:1 matched case-control dataset was established using propensity score matching technique based on supplement consumption. Then, total annual healthcare expenditures were compared between the two groups. In addition, a multivariate regression analysis (Proc Surveyreg) was performed to determine the association between the supplement consumption and medical costs. Results: The supplement user group spent about 1.72 million Korean won, while the non-user group spent about 1.43 million Korean won on medical services (p=0.0186). The results of multivariate regression showed that the costs were approximately 26.15% higher in the user group than in the non-user group (p=0.0004). Conclusion: Contrary to the previous studies that have shown the benefits of supplement use in reducing healthcare costs, this study showed that those who consistently consumed supplements spent more on medical services. This can be interpreted in the same context as previous studies suggesting that dietary supplement intake is a healthy behavior for managing one's health. However, we caution against drawing firm conclusions due to data limitations. Further analysis using patient-level epidemiologic data is needed.

A New Method for Aortic Valve Planimetry with High-Resolution 3-Dimensional MRI and Its Comparison with Conventional Cine MRI and Echocardiography for Assessing the Severity of Aortic Valvular Stenosis

  • Hae Jin Kim;Yeon Hyeon Choe;Sung Mok Kim;Eun Kyung Kim;Mirae Lee;Sung-Ji Park;Joonghyun Ahn;Keumhee C. Carriere
    • Korean Journal of Radiology
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    • v.22 no.8
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    • pp.1266-1278
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    • 2021
  • Objective: We aimed to compare the aortic valve area (AVA) calculated using fast high-resolution three-dimensional (3D) magnetic resonance (MR) image acquisition with that of the conventional two-dimensional (2D) cine MR technique. Materials and Methods: We included 139 consecutive patients (mean age ± standard deviation [SD], 68.5 ± 9.4 years) with aortic valvular stenosis (AS) and 21 asymptomatic controls (52.3 ± 14.2 years). High-resolution T2-prepared 3D steady-state free precession (SSFP) images (2.0 mm slice thickness, 10 contiguous slices) for 3D planimetry (3DP) were acquired with a single breath hold during mid-systole. 2D SSFP cine MR images (6.0 mm slice thickness) for 2D planimetry (2DP) were also obtained at three aortic valve levels. The calculations for the effective AVA based on the MR images were compared with the transthoracic echocardiographic (TTE) measurements using the continuity equation. Results: The mean AVA ± SD derived by 3DP, 2DP, and TTE in the AS group were 0.81 ± 0.26 cm2, 0.82 ± 0.34 cm2, and 0.80 ± 0.26 cm2, respectively (p = 0.366). The intra-observer agreement was higher for 3DP than 2DP in one observer: intraclass correlation coefficient (ICC) of 0.95 (95% confidence interval [CI], 0.94-0.97) and 0.87 (95% CI, 0.82-0.91), respectively, for observer 1 and 0.97 (95% CI, 0.96-0.98) and 0.98 (95% CI, 0.97-0.99), respectively, for observer 2. Inter-observer agreement was similar between 3DP and 2DP, with the ICC of 0.92 (95% CI, 0.89-0.94) and 0.91 (95% CI, 0.88-0.93), respectively. 3DP-derived AVA showed a slightly higher agreement with AVA measured by TTE than the 2DP-derived AVA, with the ICC of 0.87 (95% CI, 0.82-0.91) vs. 0.85 (95% CI, 0.79-0.89). Conclusion: High-resolution 3D MR image acquisition, with single-breath-hold SSFP sequences, gave AVA measurement with low observer variability that correlated highly with those obtained by TTE.

Pancreaticoduodenectomy with superior mesenteric artery first-approach combined total meso-pancreas excision for periampullary malignancies: A high-volume single-center experience with short-term outcomes

  • Thanh Khiem Nguyen;Ham Hoi Nguyen;Tuan Hiep Luong;Kim Khue Dang;Van Duy Le;Duc Dung Tran;Van Minh Do;Hong Quang Pham;Hoan My Pham;Thi Lan Tran;Cuong Thinh Nguyen;Hong Son Trinh;Yosuke Inoue
    • Annals of Hepato-Biliary-Pancreatic Surgery
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    • v.28 no.1
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    • pp.59-69
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    • 2024
  • Backgrounds/Aims: Pancreaticoduodenectomy (PD) is the only radical treatment for periampullary malignancies. Superior mesenteric artery (SMA) first approach combined with total meso-pancreas (MP) excision was conducted to improve the oncological results. There has not been any previous research of a technique that combines the SMA first approach and total MP excision with a detailed description of the MP macroscopical shape. Methods: We prospectively assessed 77 patients with periampullary malignancies between October 2020 and March 2022 (18 months). All patients had undergone PD with SMA first approach combined total MP excision. The perioperative indications, clinical data, intra-operative index, R0 resection rate of postoperative pathological specimens (especially mesopancreatic margin), postoperative complications, and follow-up results were evaluated. Results: The median operative time was 289.6 min (178-540 min), the median intraoperative blood loss was 209 mL (30-1,600 mL). Microscopically, there were 19 (24.7%) cases with metastatic MP, and five cases (6.5%) with R1-resection of the MP. The number of lymph nodes (LNs) harvested and metastatic LNs were 27.2 (maximum was 74) and 1.8 (maximum was 16), respectively. Some (46.8%) patients had pancreatic fistula, but mostly in grade A, with 7 patients (9.1%) who required re-operations. Some 18.2% of cases developed postoperative refractory diarrhea. The rate of in-hospital mortality was 1.3%. Conclusions: The PD with SMA first approach combined TMpE for periampullary malignancies was effective in achieving superior oncological statistics (rate of MP R0-resection and number of total resected LNs) with non-inferior short-term outcomes. It is necessary to evaluate survival outcomes with long-term follow-up.

Development of an Anomaly Detection Algorithm for Verification of Radionuclide Analysis Based on Artificial Intelligence in Radioactive Wastes (방사성폐기물 핵종분석 검증용 이상 탐지를 위한 인공지능 기반 알고리즘 개발)

  • Seungsoo Jang;Jang Hee Lee;Young-su Kim;Jiseok Kim;Jeen-hyeng Kwon;Song Hyun Kim
    • Journal of Radiation Industry
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    • v.17 no.1
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    • pp.19-32
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    • 2023
  • The amount of radioactive waste is expected to dramatically increase with decommissioning of nuclear power plants such as Kori-1, the first nuclear power plant in South Korea. Accurate nuclide analysis is necessary to manage the radioactive wastes safely, but research on verification of radionuclide analysis has yet to be well established. This study aimed to develop the technology that can verify the results of radionuclide analysis based on artificial intelligence. In this study, we propose an anomaly detection algorithm for inspecting the analysis error of radionuclide. We used the data from 'Updated Scaling Factors in Low-Level Radwaste' (NP-5077) published by EPRI (Electric Power Research Institute), and resampling was performed using SMOTE (Synthetic Minority Oversampling Technique) algorithm to augment data. 149,676 augmented data with SMOTE algorithm was used to train the artificial neural networks (classification and anomaly detection networks). 324 NP-5077 report data verified the performance of networks. The anomaly detection algorithm of radionuclide analysis was divided into two modules that detect a case where radioactive waste was incorrectly classified or discriminate an abnormal data such as loss of data or incorrectly written data. The classification network was constructed using the fully connected layer, and the anomaly detection network was composed of the encoder and decoder. The latter was operated by loading the latent vector from the end layer of the classification network. This study conducted exploratory data analysis (i.e., statistics, histogram, correlation, covariance, PCA, k-mean clustering, DBSCAN). As a result of analyzing the data, it is complicated to distinguish the type of radioactive waste because data distribution overlapped each other. In spite of these complexities, our algorithm based on deep learning can distinguish abnormal data from normal data. Radionuclide analysis was verified using our anomaly detection algorithm, and meaningful results were obtained.

Cavitation signal detection based on time-series signal statistics (시계열 신호 통계량 기반 캐비테이션 신호 탐지)

  • Haesang Yang;Ha-Min Choi;Sock-Kyu Lee;Woojae Seong
    • The Journal of the Acoustical Society of Korea
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    • v.43 no.4
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    • pp.400-405
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    • 2024
  • When cavitation noise occurs in ship propellers, the level of underwater radiated noise abruptly increases, which can be a critical threat factor as it increases the probability of detection, particularly in the case of naval vessels. Therefore, accurately and promptly assessing cavitation signals is crucial for improving the survivability of submarines. Traditionally, techniques for determining cavitation occurrence have mainly relied on assessing acoustic/vibration levels measured by sensors above a certain threshold, or using the Detection of Envelop Modulation On Noise (DEMON) method. However, technologies related to this rely on a physical understanding of cavitation phenomena and subjective criteria based on user experience, involving multiple procedures, thus necessitating the development of techniques for early automatic recognition of cavitation signals. In this paper, we propose an algorithm that automatically detects cavitation occurrence based on simple statistical features reflecting cavitation characteristics extracted from acoustic signals measured by sensors attached to the hull. The performance of the proposed technique is evaluated depending on the number of sensors and model test conditions. It was confirmed that by sufficiently training the characteristics of cavitation reflected in signals measured by a single sensor, the occurrence of cavitation signals can be determined.

Functional MRI ofThe Supplementary Motor Area in Hand Motor Task: Comparison Study with The Primary Motor Area (수지운동자극을 사용한 부운동중추의 기능적 MR연구: 일차운동중추와의 비교)

  • 이호규;김진서;최충곤;임태환
    • Investigative Magnetic Resonance Imaging
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    • v.1 no.1
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    • pp.103-107
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    • 1997
  • Purpose: To investigate the localization and functional lateralization of the supplementary motor area (SMA) in motor activation tests in comparison to that of the primary motor area. Materials and Methods: Seven healthy volunteers obtained echoplanar imaging blood oxygen level dependent technique. This study was carried on 1.5T Siemens Magnetom Vision system with the standard head coil. Parameters of EPI were followed as; TR/TE : 1.0/66.0msec, flip angle: $90^{\circ}$, field of view: $22cm{\times}22cm,{\;}matrix:{\;}128{\times}128$, slice number/slice thickness/gap: 1O/4mm/0.8mm with fat suppression technique. Motor task as finger opposition in each hand consisted of 3 sets of alternative rest and activation periods. Postprocessing were done on Stimulate 5.0 by using cross-correlation statistics. To compare the functional lateralization of the SMA in the right and left hand tests, each examination was evaluated for the percent change of signal intensity and the number of activated voxels both in the SMA and in the pri¬mary motor area. Hemispheric asymmetry was defined as difference of summation of the activted voxels between each hemisphere. Results: Percent change of signal intensity in the SMA (2.49 -3.06%) is lower than that of primary motor area(4.4 -7.23%). Percent change of signal intensity including activated voxels were observed almost equally in the right and left SMA. As for summation of activated voxels, primary motor area had significant difference between each hemisphere but not did the SMA. Conclusion: Preferred contralateral dominant hemisphere and hemispheric asymmetry were detected in the primary motor area but not in the SMA.

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