• Title/Summary/Keyword: real curve

Search Result 665, Processing Time 0.031 seconds

Decision function for optimal smoothing parameter of asymmetrically reweighted penalized least squares (Asymetrically reweighted penalized least squares에서 최적의 평활화 매개변수를 위한 결정함수)

  • Park, Aa-Ron;Park, Jun-Kyu;Ko, Dae-Young;Kim, Sun-Geum;Baek, Sung-June
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.20 no.3
    • /
    • pp.500-506
    • /
    • 2019
  • In this study, we present a decision function of optimal smoothing parameter for baseline correction using Asymmetrically reweighted penalized least squares (arPLS). Baseline correction is very important due to influence on performance of spectral analysis in application of spectroscopy. Baseline is often estimated by parameter selection using visual inspection on analyte spectrum. It is a highly subjective procedure and can be tedious work especially with a large number of data. For these reasons, an objective procedure is necessary to determine optimal parameter value for baseline correction. The proposed function is defined by modeling the median value of possible parameter range as the length and order of the background signal. The median value increases as the length of the signal increases and decreases as the degree of the signal increases. The simulated data produced a total of 112 signals combined for the 7 lengths of the signal, adding analytic signals and linear and quadratic, cubic and 4th order curve baseline respectively. According to the experimental results using simulated data with linear, quadratic, cubic and 4th order curved baseline, and real Raman spectra, we confirmed that the proposed function can be effectively applied to optimal parameter selection for baseline correction using arPLS.

Efficiency in the Password-based Authenticated Key Exchange (패스워드 기반 인증 키 공유 프로토콜에서의 효율성)

  • 황정연;홍석희;박혜영;장상운;박영호;류희수
    • Journal of the Korea Institute of Information Security & Cryptology
    • /
    • v.12 no.6
    • /
    • pp.113-124
    • /
    • 2002
  • Proposals for a password-based authenticated key exchange protocol that have been published so far almost concentrated on the provable security. But in a real environment such as mobile one, efficiency is a critical issue as security. In this paper we discuss the efficiency of PAK which is secure in the random oracle model [l]. Among 4 hash functions in PAK the instantiation for $H_1$, which outputs a verifier of the password, has most important effect on the computational efficiency. We analyze two different methods for $H_1$ suggested in [1] and we show that $H_{lq}$ has merits in transforming to EC or XTR variants as well as in the efficiency. As an efficient variant. we propose PAK2-EC and PAK2-XTR which do not require any additional step converting a hash output into a point of elliptic curve or XTR subgroup when compared to the previous work on the PAK[2]. Finally we compare PAK2 with the password-based authenticated key exchange protocols such as SPEKE, SRP, and AMP.

Automated Inspection System for Micro-pattern Defection Using Artificial Intelligence (인공지능(AI)을 활용한 미세패턴 불량도 자동화 검사 시스템)

  • Lee, Kwan-Soo;Kim, Jae-U;Cho, Su-Chan;Shin, Bo-Sung
    • Journal of the Korean Society of Industry Convergence
    • /
    • v.24 no.6_2
    • /
    • pp.729-735
    • /
    • 2021
  • Recently Artificial Intelligence(AI) has been developed and used in various fields. Especially AI recognition technology can perceive and distinguish images so it should plays a significant role in quality inspection process. For stability of autonomous driving technology, semiconductors inside automobiles must be protected from external electromagnetic wave(EM wave). As a shield film, a thin polymeric material with hole shaped micro-patterns created by a laser processing could be used for the protection. The shielding efficiency of the film can be increased by the hole structure with appropriate pitch and size. However, since the sensitivity of micro-machining for some parameters, the shape of every single hole can not be same, even it is possible to make defective patterns during process. And it is absolutely time consuming way to inspect all patterns by just using optical microscope. In this paper, we introduce a AI inspection system which is based on web site AI tool. And we evaluate the usefulness of AI model by calculate Area Under ROC curve(Receiver Operating Characteristics). The AI system can classify the micro-patterns into normal or abnormal ones displaying the text of the result on real-time images and save them as image files respectively. Furthermore, pressing the running button, the Hardware of robot arm with two Arduino motors move the film on the optical microscopy stage in order for raster scanning. So this AI system can inspect the entire micro-patterns of a film automatically. If our system could collect much more identified data, it is believed that this system should be a more precise and accurate process for the efficiency of the AI inspection. Also this one could be applied to image-based inspection process of other products.

Trace element analysis of korean car windshield using LA-ICP-MS (LA-ICP-MS를 이용한 한국 자동차 유리의 미량원소 분석)

  • Min, Ji-Sook;Choi, Man-Sik;Heo, Sang-Cheol;Kim, Jae-Kyun
    • Analytical Science and Technology
    • /
    • v.22 no.3
    • /
    • pp.235-246
    • /
    • 2009
  • The analyses of minor and trace elements in glass debris were performed using LA-ICP-MS in order to identify manufacturers using real commercial samples. At first, a calibration curve was made using standard glass samples of NIST 610, 612, 614 and 616. $^{29}Si$ was used as an internal standard, and the ratios of metal/Si for each metal were compared with their concentrations. Based on elements in each sample and standard materials, 24 metals were quantified and the LOD in analysis, according to the blank sample, was in the range of 0.11 mg/kg (Ti)-4.91 mg/kg (Ca). Eleven samples from two manufacturers were collected and five sub-samples were taken from each sample for analysis. 15 elements (Co, Ce, Ca, Mn, Sr, Ba, Li, Rb, U, La, Th, Na, Al, Zr and Hf) were selected to identify manufacturers because some elements (Cu, Cr, Cd and Ni) were below the detection limit and some elements (Ti, Pr, Mg, Nb, Nd) were absent in the analysis of standards and others (Pb and Sn) had a problem of homogeneity. The attempts to identify manufacturers and the manufacturing period were performed through a triangular diagram. In the manufacturer discrimination by discriminant analysis, a canonical discriminant function was made based on Mn, Ce and Rb, and each sample could be identified.

Comparison of miR-106b, miR-191, and miR-30d expression dynamics in milk with regard to its composition in Holstein and Ayrshire cows

  • Marina V. Pozovnikova;Viktoria B. Leibova;Olga V. Tulinova;Elena A. Romanova;Artem P. Dysin;Natalia V. Dementieva;Anastasiia I. Azovtseva;Sergey E. Sedykh
    • Animal Bioscience
    • /
    • v.37 no.6
    • /
    • pp.965-981
    • /
    • 2024
  • Objective: Milk composition varies considerably and depends on paratypical, genetic, and epigenetic factors. MiRNAs belong to the class of small non-coding RNAs; they are one of the key tools of epigenetic control because of their ability to regulate gene expression at the post-transcriptional level. We compared the relative expression levels of miR-106b, miR-191, and miR-30d in milk to demonstrate the relationship between the content of these miRNAs with protein and fat components of milk in Holstein and Ayrshire cattle. Methods: Milk fat, protein, and casein contents were determined in the obtained samples, as well as the content of the main fatty acids (g/100 g milk), including: saturated acids, such as myristic (C14:0), palmitic (C16:0), and stearic (C18:0) acids; monounsaturated acids, including oleic (C18:1) acid; as well as long-, medium- and short-chain, polyunsaturated, and trans fatty acids. Real-time stem-loop one-tube reverse transcription polymerase chain reaction with TaqMan probes was used to measure the miRNA expression levels. Results: The miRNA expression levels in milk samples were found to be decreased in the first two months in Holstein breed, and in the first four months in Ayrshire breed. Correlation analysis did not reveal any dependence between changes in the expression level of miRNA and milk fat content, but showed a multidirectional relationship with individual milk fatty acids. Positive associations between the expression levels of miR-106b and miR-30d and protein and casein content were found in the Ayrshire breed. Receiver operating characteristic curve analysis showed that miR-106b and miR-30d expression levels can cause changes in fatty acid and protein composition of milk in Ayrshire cows, whereas miR-106b expression level determines the fatty acid composition in Holsteins. Conclusion: The data obtained in this study showed that miR-106b, miR-191, and miR-30d expression levels in milk samples have peculiarities associated with breed affiliation and the lactation period.

Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data

  • Subhanik Purkayastha;Yanhe Xiao;Zhicheng Jiao;Rujapa Thepumnoeysuk;Kasey Halsey;Jing Wu;Thi My Linh Tran;Ben Hsieh;Ji Whae Choi;Dongcui Wang;Martin Vallieres;Robin Wang;Scott Collins;Xue Feng;Michael Feldman;Paul J. Zhang;Michael Atalay;Ronnie Sebro;Li Yang;Yong Fan;Wei-hua Liao;Harrison X. Bai
    • Korean Journal of Radiology
    • /
    • v.22 no.7
    • /
    • pp.1213-1224
    • /
    • 2021
  • Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion: CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

An accuracy analysis of Cyberknife tumor tracking radiotherapy according to unpredictable change of respiration (예측 불가능한 호흡 변화에 따른 사이버나이프 종양 추적 방사선 치료의 정확도 분석)

  • Seo, jung min;Lee, chang yeol;Huh, hyun do;Kim, wan sun
    • The Journal of Korean Society for Radiation Therapy
    • /
    • v.27 no.2
    • /
    • pp.157-166
    • /
    • 2015
  • Purpose : Cyber-Knife tumor tracking system, based on the correlation relationship between the position of a tumor which moves in response to the real time respiratory cycle signal and respiration was obtained by the LED marker attached to the outside of the patient, the location of the tumor to predict in advance, the movement of the tumor in synchronization with the therapeutic device to track real-time tumor, is a system for treating. The purpose of this study, in the cyber knife tumor tracking radiation therapy, trying to evaluate the accuracy of tumor tracking radiation therapy system due to the change in the form of unpredictable sudden breathing due to cough and sleep. Materials and Methods : Breathing Log files that were used in the study, based on the Respiratory gating radiotherapy and Cyber-knife tracking radiosurgery breathing Log files of patients who received herein, measured using the Log files in the form of a Sinusoidal pattern and Sudden change pattern. it has been reconstituted as possible. Enter the reconstructed respiratory Log file cyber knife dynamic chest Phantom, so that it is possible to implement a motion due to respiration, add manufacturing the driving apparatus of the existing dynamic chest Phantom, Phantom the form of respiration we have developed a program that can be applied to. Movement of the phantom inside the target (Ball cube target) was driven by the displacement of three sizes of according to the size of the respiratory vertical (Superior-Inferior) direction to the 5 mm, 10 mm, 20 mm. Insert crosses two EBT3 films in phantom inside the target in response to changes in the target movement, the End-to-End (E2E) test provided in Cyber-Knife manufacturer depending on the form of the breathing five times each. It was determined by carrying. Accuracy of tumor tracking system is indicated by the target error by analyzing the inserted film, additional E2E test is analyzed by measuring the correlation error while being advanced. Results : If the target error is a sine curve breathing form, the size of the target of the movement is in response to the 5 mm, 10 mm, 20 mm, respectively, of the average $1.14{\pm}0.13mm$, $1.05{\pm}0.20mm$, with $2.37{\pm}0.17mm$, suddenly for it is variations in breathing, respective average $1.87{\pm}0.19mm$, $2.15{\pm}0.21mm$, and analyzed with $2.44{\pm}0.26mm$. If the correlation error can be defined by the length of the displacement vector in the target track is a sinusoidal breathing mode, the size of the target of the movement in response to 5 mm, 10 mm, 20 mm, respective average $0.84{\pm}0.01mm$, $0.70{\pm}0.13mm$, with $1.63{\pm}0.10mm$, if it is a variant of sudden breathing respective average $0.97{\pm}0.06mm$, $1.44{\pm}0.11mm$, and analyzed with $1.98{\pm}0.10mm$. The larger the correlation error values in both the both the respiratory form, the target error value is large. If the motion size of the target of the sine curve breathing form is greater than or equal to 20 mm, was measured at 1.5 mm or more is a recommendation value of both cyber knife manufacturer of both error value. Conclusion : There is a tendency that the correlation error value between about target error value magnitude of the target motion is large is increased, the error value becomes large in variation of rapid respiration than breathing the form of a sine curve. The more the shape of the breathing large movements regular shape of sine curves target accuracy of the tumor tracking system can be judged to be reduced. Using the algorithm of Cyber-Knife tumor tracking system, when there is a change in the sudden unpredictable respiratory due patient coughing during treatment enforcement is to stop the treatment, it is assumed to carry out the internal target validation process again, it is necessary to readjust the form of respiration. Patients under treatment is determined to be able to improve the treatment of accuracy to induce the observed form of regular breathing and put like to see the goggles monitor capable of the respiratory form of the person.

  • PDF

The Prognostic Role of B-type Natriuretic Peptide in Acute Pulmonary Thromboembolism (급성 폐혈전색전증 환자에서 예후 인자로서 혈중 BNP의 의의)

  • Lee, Su Jin;Lee, Jae Hyung;Park, Ji Young;Jo, Woo Sung;Kim, Ji Eun;Kim, Ki Uk;Park, Hye Kyung;Kim, Yun Seong;Lee, Min Ki;Park, Soon Kew
    • Tuberculosis and Respiratory Diseases
    • /
    • v.60 no.5
    • /
    • pp.540-547
    • /
    • 2006
  • Background : Vital stability and right side heart failure are major prognostic factors of acute pulmonary thromboembolism. While it is important to recognize right side heart failure, it is often difficult in real practice. Recently, several studies have described early diagnostic tools for detecting right side heart failure including echocardiography and biochemical markers. This study, we evaluated the prognostic role of the B-type natriuretic peptide (BNP) in an acute pulmonary thromboembolism. Methods : Thirty-four patients with a diagnosis of acute pulmonary thromboembolism were enrolled in the study. The BNP levels were measured and echocardiography was performed at the Emergency Department. Data on the prognostic factors including ventilatory support, vital stability, pulmonary artery pressure, degree of tricuspid valve regurgitation, complications and death was collected from the patients' medical records. The patients with an acute pulmonary thromboembolism were divided into two groups based on the vital stability and the BNP level and the cutoff values and prognostic factors of the two groups were compared. Results : The predictors of the vital stability that influence the prognosis of patients with acute pulmonary thromboembolism were the BNP level, ventilatory support and death. The plasma BNP levels showed a strong correlation with the vital stability, ventilatory support, thrombolytic therapy and death. When the BNP cutoff level was set to 377.5 pg/dl in a ROC curve, the sensitivity and the specificity for differentiating between the groups with stable or unstable vital signs was 100% and 90%, respectively. Conclusion : This study indicates that a measurement of the plasma BNP levels may be a useful prognostic marker in patients with an acute pulmonary thrombo-embolism.

Determining Nitrogen Topdressing Rate at Panicle Initiation Stage of Rice based on Vegetation Index and SPAD Reading (유수분화기 식생지수와 SPAD값에 의한 벼 질소 수비 시용량 결정)

  • Kim Min-Ho;Fu Jin-Dong;Lee Byun-Woo
    • KOREAN JOURNAL OF CROP SCIENCE
    • /
    • v.51 no.5
    • /
    • pp.386-395
    • /
    • 2006
  • The core questions for determining nitrogen topdress rate (Npi) at panicle initiation stage (PIS) are 'how much nitrogen accumulation during the reproductive stage (PNup) is required for the target rice yield or protein content depending on the growth and nitrogen nutrition status at PIS?' and 'how can we diagnose the growth and nitrogen nutrition status easily at real time basis?'. To address these questions, two years experiments from 2001 to 2002 were done under various rates of basal, tillering, and panicle nitrogen fertilizer by employing a rice cultivar, Hwaseongbyeo. The response of grain yield and milled-rice protein content was quantified in relation to RVIgreen (green ratio vegetation index) and SPAD reading measured around PIS as indirect estimators for growth and nitrogen nutrition status, the regression models were formulated to predict PNup based on the growth and nitrogen nutrition status and Npi at PIS. Grain yield showed quadratic response to PNup, RVIgreen around PIS, and SPAD reading around PIS. The regression models to predict grain yield had a high determination coefficient of above 0.95. PNup for the maximum grain yield was estimated to be 9 to 13.5 kgN/10a within the range of RVIgreen around PIS of this experiment. decreasing with increasing RVIgreen and also to be 10 to 11 kgN/10a regardless of SPAD readings around PIS. At these PNup's the protein content of milled rice was estimated to rise above 9% that might degrade eating quality seriously Milled-rice protein content showed curve-linear increase with the increase of PNup, RVIgreen around PIS, and SPAD reading around PIS. The regression models to predict protein content had a high determination coefficient of above 0.91. PNup to control the milled-rice protein content below 7% was estimated as 6 to 8 kgN/10a within the range of RVIgreen and SPAD reading of this experiment, showing much lower values than those for the maximum grain yield. The recovery of the Npi applied at PIS ranged from 53 to 83%, increasing with the increased growth amount while decreasing with the increasing Npi. The natural nitrogen supply from PIS to harvest ranged from 2.5 to 4 kg/10a, showing quadratic relationship with the shoot dry weight or shoot nitrogen content at PIS. The regression models to estimate PNup was formulated using Npi and anyone of RVIgreen, shoot dry weight, and shoot nitrogen content at PIS as predictor variables. These models showed good fitness with determination coefficients of 0.86 to 0.95 The prescription method based on the above models predicting grain yield, protein content and PNup and its constraints were discussed.

Development of A Network loading model for Dynamic traffic Assignment (동적 통행배정모형을 위한 교통류 부하모형의 개발)

  • 임강원
    • Journal of Korean Society of Transportation
    • /
    • v.20 no.3
    • /
    • pp.149-158
    • /
    • 2002
  • For the purpose of preciously describing real time traffic pattern in urban road network, dynamic network loading(DNL) models able to simulate traffic behavior are required. A number of different methods are available, including macroscopic, microscopic dynamic network models, as well as analytical model. Equivalency minimization problem and Variation inequality problem are the analytical models, which include explicit mathematical travel cost function for describing traffic behaviors on the network. While microscopic simulation models move vehicles according to behavioral car-following and cell-transmission. However, DNL models embedding such travel time function have some limitations ; analytical model has lacking of describing traffic characteristics such as relations between flow and speed, between speed and density Microscopic simulation models are the most detailed and realistic, but they are difficult to calibrate and may not be the most practical tools for large-scale networks. To cope with such problems, this paper develops a new DNL model appropriate for dynamic traffic assignment(DTA), The model is combined with vertical queue model representing vehicles as vertical queues at the end of links. In order to compare and to assess the model, we use a contrived example network. From the numerical results, we found that the DNL model presented in the paper were able to describe traffic characteristics with reasonable amount of computing time. The model also showed good relationship between travel time and traffic flow and expressed the feature of backward turn at near capacity.