• 산업경영시스템학회지
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• 제15권26호
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• pp.119-124
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• 1992

본 논문은 장치산업에서 적용되는 다변량 EWMA 공정제어와 통계적 공정감시 통합시스템을 제안한다. 본 논문에서 제안한 통합시스템은 자동공정제어(APC)의 예측, 조정기능과 통계적 정정감시(SPM)의 이상점 발견 및 제거등의 각각의 장점을 이용하였다. 기존의 다변량 EWMA연구는 데이타간의 독립성을 가정하였으나 본 논문은 데이타간의 종속적인 형태인 IMA(1,1)모델을 대상으로 하였다.

• 한국표면공학회:학술대회논문집
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• 한국표면공학회 2015년도 추계학술대회 논문집
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• pp.242-243
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• 2015

Fault detection using optical emission spectra with modified K-means cluster analysis and principal component anal ysis are demonstrated for inductive coupl ed pl asma cl eaning processes. The optical emission spectra from optical emission spectroscopy (OES) are used for measurement. Furthermore, Principal component analysis and K-means cluster analysis algorithm is modified and applied to real-time detection and sensitivity enhancement for fluorocarbon cleaning processes. The proposed techniques show clear improvement of sensitivity and significant noise reduction when they are compared with single wavelength signals measured by OES. These techniques are expected to be applied to various plasma monitoring applications including fault detections as well as chamber cleaning endpoint detection.

• 정보화연구
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• 제11권2호
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• pp.125-130
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• 2014

Today in different higher educational institutions there is the active on a structure of expert models of monitoring the quality of education in the higher educational institutions, assuming continuous tracking an education status as a whole and its separate components. In most cases creation of a monitoring system of quality of education relies on the intermediate results of activities.

• Journal of Microbiology and Biotechnology
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• 제20권1호
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• pp.21-29
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• 2010

The phenolic compounds are a major contaminant class often found in industrial wastewaters and the biological treatment is an alternative tool commonly employed for their removal. In this sense, monitoring microbial community dynamics is crucial for a successful wastewater treatment. This work aimed to monitor the structure and activity of the bacterial community during the operation of a laboratory-scale continuous submerged membrane bioreactor (SMBR), using PCR and RT-PCR followed by denaturing gradient gel electrophoresis (DGGE) and 16S rRNA libraries. Multivariate analyses carried out using DGGE profiles showed significant changes in the total and metabolically active dominant community members during the 4-week treatment period, explained mainly by phenol and ammonium input. Gene libraries were assembled using 16S rDNA and 16S rRNA PCR products from the fourth week of treatment. Sequencing and phylogenetic analyses of clones from the 16S rDNA library revealed a high diversity of taxa for the total bacterial community, with predominance of Thauera genus (ca. 50%). On the other hand, a lower diversity was found for metabolically active bacteria, which were mostly represented by members of Betaproteobacteria (Thauera and Comamonas), suggesting that these groups have a relevant role in the phenol degradation during the final phase of the SMBR operation.

• Journal of information and communication convergence engineering
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• 제9권4호
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• pp.475-482
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• 2011

In this research, we have attempted to estimate the water quality of fish farms in terms of parameters such as water temperature, dissolved oxygen, pH, and salinity by employing observational data obtained from a coastal ocean observatory of a national institution located close to the fish farm. We requested and received marine data comprising nine factors including water temperature from Korea Hydrographic and Oceanographic Administration. For verifying our results, we also established an experimental fish farm in which we directly placed the sensor module of an optical mode, YSI-6920V2, used for self-cleaning inside fish tanks and used the data measured and recorded by a environment monitoring system that was communicating serially with the sensor module. We investigated the differences in water temperature and salinity among three areas - Goheung Balpo, Yeosu Odongdo, and the experimental fish farm, Keumho. Water temperature did not exhibit significant differences but there was a difference in salinity (significance <5%). Further, multiple regression analysis was performed to estimate the water quality of the fish farm at Keumho based on the data of Goheung Balpo. The water temperature and dissolved-oxygen estimations had multiple regression linear relationships with coefficients of determination of 98% and 89%, respectively. However, in the case of the pH and salinity estimated using the oceanic environment with nine factors, the adjusted coefficient of determination was very low at less than 10%, and it was therefore difficult to predict the values. We plotted the predicted and measured values by employing the estimated regression equation and found them to fit very well; the values were close to the regression line. We have demonstrated that if statistical model equations that fit well are used, the expense of fish-farm sensor and system installations, maintenances, and repairs, which is a major issue with existing environmental information monitoring systems of marine farming areas, can be reduced, thereby making it easier for fish farmers to monitor aquaculture and mariculture environments.

• Journal of Preventive Medicine and Public Health
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• 제39권2호
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• pp.171-176
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• 2006

Objectives : The objective of this study is to assess the factors influencing biological monitoring of textile coating factory workers exposed to N,N-dimethylformamide(DMF). Methods : We studied 35 workers who were occupationally exposed to DMF from 9 textile coating factories. The study was carried out in two phases; summer and winter. While air concentration of DMF, temperature and humidity were assessed in order to monitor the atmospheric conditions, biological monitoring was done to determine the internal dose by analyzing the N-methylformamide(NMF) collected from urine at the beginning and end of the shift. Questionnaires and medical surveillance were also obtained during the two phases. Results : Median air concentrations of DMF in winter and summer were 1.85 ppm and 2.78 ppm respectively. Also the difference between the urinary NMF concentration at the beginning and end of the shift $({\Delta}NMF)$ was always significant in each season (P < 0.001). The correlations between log DMF in air, log end-of-shift urinary NMF (r=0.555, P < 0.001) and log ${\Delta}NMF$ (r = 0.444, P < 0.001) was statistically significant in summer. The temperature, humidity, a shift system and different styles of clothing worn were significantly different during the two phases. In a multivariate analysis, temperature and the concentration of DMF in the air were the main factors influencing biological monitoring of textile coating factory workers. Conclusions : Concerning more comprehensive prevention measures to reduce exposure for those workers occupationally exposed to DMF, dermal exposure conditions such as temperature and humidity together with the air concentration of DMF should be assessed and biological monitoring is necessary to reduce adverse health effects, especially during the summer.

• 품질경영학회지
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• 제45권1호
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• pp.25-38
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• 2017

Purpose: Hot strip rolling mill consists of a lot of mechanical and electrical units. In condition monitoring and diagnosis phase, various units could be failed with unknown reasons. In this study, we propose an effective method to detect early the units with abnormal status to minimize system downtime. Methods: The early warning problem with various units is defined. K-means and PAM algorithm with Euclidean and Manhattan distances were performed to detect the abnormal status. In addition, an performance of the proposed algorithm is investigated by field data analysis. Results: PAM with Manhattan distance(PAM_ManD) showed better results than K-means algorithm with Euclidean distance(K-means_ED). In addition, we could know from multivariate field data analysis that the system reliability of hot strip rolling mill can be increased by detecting early abnormal status. Conclusion: In this paper, clustering-based monitoring and fault detection algorithm using Manhattan distance is proposed. Experiments are performed to study the benefit of the PAM with Manhattan distance against the K-means with Euclidean distance.

• Smart Structures and Systems
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• 제6권4호
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• pp.349-362
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• 2010

Ultrasonic Guided Waves (UGWs) are a useful tool in structural health monitoring (SHM) applications that can benefit from built-in transduction, moderately large inspection ranges and high sensitivity to small flaws. This paper describes a SHM method based on UGWs, discrete wavelet transform (DWT), and principal component analysis (PCA) able to detect and quantify the onset and propagation of fatigue cracks in structural waveguides. The method combines the advantages of guided wave signals processed through the DWT with the outcomes of selecting defect-sensitive features to perform a multivariate diagnosis of damage. This diagnosis is based on the PCA. The framework presented in this paper is applied to the detection of fatigue cracks in a steel beam. The probing hardware consists of a PXI platform that controls the generation and measurement of the ultrasonic signals by means of piezoelectric transducers made of Lead Zirconate Titanate. Although the approach is demonstrated in a beam test, it is argued that the proposed method is general and applicable to any structure that can sustain the propagation of UGWs.

• International Journal of Computer Science & Network Security
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• 제23권9호
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• pp.37-46
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• 2023

The main aim of the article is to solve the problem of automating price monitoring using marketing forecasting methods and Excel functionality under martial law. The study used the method of algorithms, trend analysis, correlation and regression analysis, ANOVA, extrapolation, index method, etc. The importance of monitoring consumer price developments in market pricing at the macro and micro levels is proved. The introduction of a Dummy variable to account for the influence of martial law in market pricing is proposed, both in linear multiple regression modelling and in forecasting the components of the Consumer Price Index. Experimentally, the high reliability of forecasting based on a five-factor linear regression model with a Dummy variable was proved in comparison with a linear trend equation and a four-factor linear regression model. Pessimistic, realistic and optimistic scenarios were developed for forecasting the Consumer Price Index for the situation of the end of the Russian-Ukrainian war until the end of 2023 and separately until the end of 2024.

• Natural Product Sciences
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• 제17권2호
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• pp.147-159
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• 2011

A high-performance liquid chromatography-electrospray ionization-tandem mass spectrometric method was developed to determine simultaneously eight marker constituents of Forsythiae fructus, and subsequently applied it to classify its two botanical origins. The marker compounds of Forsythia suspensa were phillyrin, pinoresinol, phillygenin, lariciresinol and forsythiaside; those of F.viridissima were arctiin, arctigenin and matairesinol. Separation of the eight analytes was achieved on a phenyl-hexyl column (150${\times}$2.0 mm i.d., 3 ${\mu}M$) using gradient elution with the mobile phase: (A) 10% acetonitrile in 0.5% acetic acid, (B) 40% aqueous acetonitrile. A few fragment ions specific to the types of lignans, among the product ions generated by collisonally induced dissociation (CID) of molecular ion clusters, such as [M-H]$^-$ or [M+OAc]$^-$ were used not only for fingerprinting analysis but for the quantification of each epimer by using multiple-reaction monitoring mode. It was shown good linearity ($r^2{\geq}$ 0.9998) over the wide range of all analytes; intra- and inter-day precisions (RSD, %) were within 9.14% and the accuracy ranged from 84.3 to 115.1%. The analytical results of 40 drug samples, combined with multivariate statistical analyses - principal component analysis (PCA) and hierarchical cluster analysis (HCA) - clearly demonstrated the classification of the test samples according to their botanical origins. This method would provide a practical strategy for assessing the authenticity or quality of the herbal drug.