• Title/Summary/Keyword: Combination Processing

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A DENSITOMETRIC STUDY OF THE DENTAL FILMS IN COMBINATION WITH VARIABLE PROCESSING SOLUTIONS (현상법 현상액에 따른 필름특성에 관한 연구)

  • Kim Ho Cheol;Park Jae Kwan
    • Journal of Korean Academy of Oral and Maxillofacial Radiology
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    • v.17 no.1
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    • pp.197-207
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    • 1987
  • This study was undertaken to investigate the relationships between film and processing solution at different processing temperatures. Three kinds of periapical film were used for this study. They included EP-2l film, DF-58, and A film Each film was processed by automatic film processor with RD-Ⅲ X-dol 90, and A processing solutions at 68° 74° 80° 86° and 92°F. Film density was measured with the densitometer, and base plus fog density, film relative speed, film contrast, and subject contrast were evaluated. The following results were obtained; 1. As the processing temperature was increased, base plus density was increased. Inadequate base plus fog densities were obtained with three films in combination with three processing solutions at 92°F. 2. Lowest base plus fog densities were obtained with A film, followed in ascending order by EP-21, and DF-58 film in combination with A or RD-Ⅲ processing solutions. The sequence of base plus fog densities was in ascending order by EP-21, A, and DF-58 film in combination with X-dol 90 processing solution. 3. The sequence of film relative speed values was in ascending order of EP-21, A, and DF-58 film in combination with A and RD-Ⅲ processing solutions, respectively. 4. As the processing temperature was increased, film contrast values was increased. The sequence of film contrast values was in descending order solution. The sequence of film contrast values was in descending order of EP-2l, DF-58, and A film in combination with RD-Ⅲ, X-dol 90 processing solution at 80°F. 5. As the processing temperature was increased, subject contrast was increased. The sequence of subject contrast was in descending order of A, X-dol 90, and RD-Ⅲ processing solution in combination with three films at 80°F. The sequence of subject contrast was in descending order of EP-21, A, and DF-58 film in combination with A processing solution at different processing temperatures.

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Removal characteristics of organic matter during pretreatment for membrane-based food processing wastewater reclamation

  • Jang, Haenam;Lee, Wontae
    • Membrane and Water Treatment
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    • v.9 no.4
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    • pp.205-210
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    • 2018
  • In this study, we investigated coagulants such as polyaluminum chloride (PACl) and ferric chloride ($FeCl_3$) and the combination of a coagulant and powdered activated carbon (PAC) for the removal of dissolved organic matter (DOM) from fish processing effluent to reduce membrane fouling in microfiltration. The efficiency of each pretreatment was investigated through analyses of dissolved organic carbon (DOC) and ultraviolet absorbance at 254 nm ($UVA_{254}$). Membrane flux and silt density index (SDI) analyses were performed to evaluate membrane fouling; molecular weight distributions (MWD) and fluorescence excitation-emission matrix (FEEM) spectroscopy were analyzed to assess DOM characteristics. The results demonstrated that $FeCl_3$ exhibited higher DOC and $UVA_{254}$ removals than PACl for food processing effluent and a combination of $FeCl_3$ and PAC provided comparatively better results than simple $FeCl_3$ coagulation for the removal of DOM from fish processing effluent. This study suggests that membrane fouling could be minimized by proper pretreatment of food processing effluent using a combination of coagulation ($FeCl_3$) and adsorption (PAC). Analyses of MWD and FEEM revealed that the combination of $FeCl_3$ and PAC was more efficient at removing hydrophobic and small-sized DOM.

Biochemical characteristics of functional domains using feline foamy virus integrase mutants

  • Yoo, Gwi-Woong;Shin, Cha-Gyun
    • BMB Reports
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    • v.46 no.1
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    • pp.53-58
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    • 2013
  • We constructed deletion mutants and seven point mutants by polymerase chain reaction to investigate the specificity of feline foamy virus integrase functional domains. Complementation reactions were performed for three enzymatic activities such as 3'-end processing, strand transfer, and disintegration. The complementation reactions with deletion mutants showed several activities for 3'-end processing and strand transfer. The conserved central domain and the combination of the N-terminal or C-terminal domains increased disintegration activity significantly. In the complementation reactions between deletion and point mutants, the combination between D107V and deletion mutants revealed 3'-end processing activities, but the combination with others did not have any activity, including strand transfer activities. Disintegration activity increased evenly, except the combination with glutamic acid 200. These results suggest that an intact central domain mediates enzymatic activities but fails to show these activities in the absence of the N-terminal or C-terminal domains.

An Approximate Evidence Combination Scheme for Increased Efficiency (효율성 제고를 위한 근사적 증거병합 방법)

  • Lee, Gye-Sung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2001.04a
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    • pp.337-340
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    • 2001
  • A major impediment in using the Dempster-Shafer evidence combination scheme is its computational complexity, which in general is exponential since DS scheme allows any subsets over the frame of discernment as focal elements. To avoid this problem, we propose a method called approximate evidence combination scheme. This scheme is applied to a few sample applications and the experiment results are compared with those of VBS. The results show that the approximation scheme achieves a great amount of computational speedup and produces belief values within the range of deviation that the expert allows.

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A Novel Unweighted Combination Method for Business Failure Prediction Using Soft Set

  • Xu, Wei;Yang, Daoli
    • Journal of Information Processing Systems
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    • v.15 no.6
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    • pp.1489-1502
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    • 2019
  • This work introduces a novel unweighted combination method (UCSS) for business failure perdition (BFP). With considering features of BFP in the age of big data, UCSS integrates the quantitative and qualitative analysis by utilizing soft set theory (SS). We adopt the conventional expert system (ES) as the basic qualitative classifier, the logistic regression model (LR) and the support vector machine (SVM) as basic quantitative classifiers. Unlike other traditional combination methods, we employ soft set theory to integrate the results of each basic classifier without weighting. In this way, UCSS inherits the advantages of ES, LR, SVM, and SS. To verify the performance of UCSS, it is applied to real datasets. We adopt ES, LR, SVM, combination models utilizing the equal weight approach (CMEW), neural network algorithm (CMNN), rough set and D-S evidence theory (CMRD), and the receiver operating characteristic curve (ROC) and SS (CFBSS) as benchmarks. The superior performance of UCSS has been verified by the empirical experiments.

Studies on the Stannic Processing for Pure Silk Fabric -Effect of the Aluminium Combination for the Stannic Processing of Pure Silk Fabric- (絹의 錫加工에 관한 硏究 - 鹽化第二錫과 알미늄鹽倂用處理에 關하여 -)

  • Lee, Yong-Woo
    • Journal of Sericultural and Entomological Science
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    • v.23 no.1
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    • pp.65-69
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    • 1981
  • The study has been carried out to investigate how the aluminium combination for the stannic processing influence on the weighty increase and physical characteristics of silk fabric to save the stannic cost. The results obtained are as follows; 1) It was shown that the optimum concentration of the combined aluminium salt was 5 percent for the stannic processing regarding to the weighty increase of silk fabric. 2) The stannic processing with aluminum combination resulted in an increase of 16 percent in silk weight more than that of the conventional stannic processing. 3) The shrinkage of fabric by soaping was reduced in the stannic or stannic aluminuium processed silk more than in the unprocessed silk. 4) The drop out weight of the stannic or stannic alumium processed silk was heavier in the acidic colour dyeing than in the reactive colour dyeing. 5) The softness of the stannic or stannic aluminium processed silk could be improved by the treatment of textile softener.

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PSS Evaluation Based on Vague Assessment Big Data: Hybrid Model of Multi-Weight Combination and Improved TOPSIS by Relative Entropy

  • Lianhui Li
    • Journal of Information Processing Systems
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    • v.20 no.3
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    • pp.285-295
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    • 2024
  • Driven by the vague assessment big data, a product service system (PSS) evaluation method is developed based on a hybrid model of multi-weight combination and improved TOPSIS by relative entropy. The index values of PSS alternatives are solved by the integration of the stakeholders' vague assessment comments presented in the form of trapezoidal fuzzy numbers. Multi-weight combination method is proposed for index weight solving of PSS evaluation decision-making. An improved TOPSIS by relative entropy (RE) is presented to overcome the shortcomings of traditional TOPSIS and related modified TOPSIS and then PSS alternatives are evaluated. A PSS evaluation case in a printer company is given to test and verify the proposed model. The RE closeness of seven PSS alternatives are 0.3940, 0.5147, 0.7913, 0.3719, 0.2403, 0.4959, and 0.6332 and the one with the highest RE closeness is selected as the best alternative. The results of comparison examples show that the presented model can compensate for the shortcomings of existing traditional methods.

A Combination and Calibration of Multi-Model Ensemble of PyeongChang Area Using Ensemble Model Output Statistics (Ensemble Model Output Statistics를 이용한 평창지역 다중 모델 앙상블 결합 및 보정)

  • Hwang, Yuseon;Kim, Chansoo
    • Atmosphere
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    • v.28 no.3
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    • pp.247-261
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    • 2018
  • The objective of this paper is to compare probabilistic temperature forecasts from different regional and global ensemble prediction systems over PyeongChang area. A statistical post-processing method is used to take into account combination and calibration of forecasts from different numerical prediction systems, laying greater weight on ensemble model that exhibits the best performance. Observations for temperature were obtained from the 30 stations in PyeongChang and three different ensemble forecasts derived from the European Centre for Medium-Range Weather Forecasts, Ensemble Prediction System for Global and Limited Area Ensemble Prediction System that were obtained between 1 May 2014 and 18 March 2017. Prior to applying to the post-processing methods, reliability analysis was conducted to identify the statistical consistency of ensemble forecasts and corresponding observations. Then, ensemble model output statistics and bias-corrected methods were applied to each raw ensemble model and then proposed weighted combination of ensembles. The results showed that the proposed methods provide improved performances than raw ensemble mean. In particular, multi-model forecast based on ensemble model output statistics was superior to the bias-corrected forecast in terms of deterministic prediction.

On-Line Linear Combination of Classifiers Based on Incremental Information in Speaker Verification

  • Huenupan, Fernando;Yoma, Nestor Becerra;Garreton, Claudio;Molina, Carlos
    • ETRI Journal
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    • v.32 no.3
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    • pp.395-405
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    • 2010
  • A novel multiclassifier system (MCS) strategy is proposed and applied to a text-dependent speaker verification task. The presented scheme optimizes the linear combination of classifiers on an on-line basis. In contrast to ordinary MCS approaches, neither a priori distributions nor pre-tuned parameters are required. The idea is to improve the most accurate classifier by making use of the incremental information provided by the second classifier. The on-line multiclassifier optimization approach is applicable to any pattern recognition problem. The proposed method needs neither a priori distributions nor pre-estimated weights, and does not make use of any consideration about training/testing matching conditions. Results with Yoho database show that the presented approach can lead to reductions in equal error rate as high as 28%, when compared with the most accurate classifier, and 11% against a standard method for the optimization of linear combination of classifiers.

Development of Classification System for Thermal Comfort Behavior of Pigs by Image Processing and Neural Network (영상처리와 인공신경망을 이용한 돼지의 체온조절행동 분류 시스템 개발)

  • 장동일;임영일;장홍희
    • Journal of Biosystems Engineering
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    • v.24 no.5
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    • pp.431-438
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    • 1999
  • The environmental control based on interactive thermoregulatory behavior for swine production has many advantages over the conventional temperature-based control methods. Therefore, this study was conducted to compare various feature selection methods using postural images of growing pigs under various environmental conditions. A color CCD camera was used to capture the behavioral images which were then modified to binary images. The binary images were processed by thresholding, edge detection, and thinning techniques to separate the pigs from their background. Following feature were used for the input patterns to the neural network ; \circled1 perimeter, \circled2 area, \circled3 Fourier coefficients (5$\times$5), \circled4 combination of (\circled1 + \circled2), \circled5 combination of (\circled1 + \circled3), \circled6 combination of (\circled2 + \circled3), and \circled7 combination of (\circled1 + \circled2 + \circled3). Using the above each input pattern, the neural network could classify training images with the success rates of 96%, 96%, 96%, 100%, 100%, 96%, 100%, and testing images with those of 88%, 86%, 93%, 96%, 91%, 90%, 98%, respectively. Thus, the combination of perimeter, area and Fourier coefficients of the thinning images as neural network features gave the best performance (98%) in the behavioral classification.

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