• Bulletin of the Korean Chemical Society
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• v.13 no.1
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• pp.87-91
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• 1992

The structures of the compounds, 1, 2, 3, and 4, which were precursors of analgesics, were confirmed by modern NMR techniques. The complete $^{13}C-NMR$ assignments of these systems were established by applying COLOC (COrrelated spectroscopy for LOng range Couplings), HETCOR (HETeronuclear CORrelated spectroscopy), RCT (Relay Coherence Transfer), and NOE difference spectroscopy. The limitation of COLOC approach which has been widely used recently is discussed.

• Journal of Environmental Health Sciences
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• v.50 no.2
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• pp.113-124
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• 2024

Background: The increasing need to minimize animal testing has sparked interest in alternative methods with more humane, cost-effective, and time-saving attributes. In particular, in silico-based computational toxicology is gaining prominence. Adverse outcome pathway (AOP) is a biological map depicting toxicological mechanisms, composed of molecular initiating events (MIEs), key events (KEs), and adverse outcomes (AOs). To understand toxicological mechanisms, predictive models are essential for AOP components in computational toxicology, including molecular structures. Objectives: This study reviewed the literature and investigated previous research cases related to AOP and in silico methodologies. We describe the results obtained from the analysis, including predictive techniques and approaches that can be used for future in silico-based alternative methods to animal testing using AOP. Methods: We analyzed in silico methods and databases used in the literature to identify trends in research on in silico prediction models. Results: We reviewed 26 studies related to AOP and in silico methodologies. The ToxCast/Tox21 database was commonly used for toxicity studies, and MIE was the most frequently used predictive factor among the AOP components. Machine learning was most widely used among prediction techniques, and various in silico methods, such as deep learning, molecular docking, and molecular dynamics, were also utilized. Conclusions: We analyzed the current research trends regarding in silico-based alternative methods for animal testing using AOPs. Developing predictive techniques that reflect toxicological mechanisms will be essential to replace animal testing with in silico methods. In the future, since the applicability of various predictive techniques is increasing, it will be necessary to continue monitoring the trend of predictive techniques and in silico-based approaches.

• Applied Science and Convergence Technology
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• v.23 no.6
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• pp.328-339
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• 2014

In this article, plasma monitoring tools and mulivariate analysis techniques were reviewed. Optical emission spectroscopy was reviewed for a chemical composition analysis tool and RF V-I probe for a physical analysis tool for plasma monitoring. Multivariate analysis techniques are discussed to the sensitivity improvement. Principal component analysis (PCA) is one of the widely adopted multivariate analysis techniques and its application to end-point detection of plasma etching process is discussed.

• Journal of Biosystems Engineering
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• v.42 no.3
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• pp.170-189
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• 2017

Purpose: This paper presents Raman chemical imaging technology for inspecting food and agricultural products. Methods The paper puts emphasis on introducing and demonstrating Raman imaging techniques for practical uses in food analysis. Results & Conclusions: The main topics include Raman scattering principles, Raman spectroscopy measurement techniques (e.g., backscattering Raman spectroscopy, transmission Raman spectroscopy, and spatially offset Raman spectroscopy), Raman image acquisition methods (i.e., point-scan, line-scan, and area-scan methods), Raman imaging instruments (e.g., excitation sources, wavelength separation devices, detectors, imaging systems, and calibration methods), and Raman image processing and analysis techniques (e.g., fluorescence correction, mixture analysis, target identification, spatial mapping, and quantitative analysis). Raman chemical imaging applications for food safety and quality evaluation are also reviewed.

• Applied Chemistry for Engineering
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• v.33 no.2
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• pp.145-150
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• 2022

Microalgae are attracting attention as a resource for the production of biofuels, food nutrients, biochemicals, and bioplastics. Among a wide range of sources of the biomass, microalgae have been highlighted due to relatively easy cultivation, ability to eliminate carbon dioxide, and low culturing cost. Despite the great potential of microalgal biomass as a biological material, the complexity and relatively expensive downstream processes have inhibited the commercial use of microalgae. In this study, we reviewed recent techniques for microalgal drying for the production of microalgal based products. As drying processes comprise the largest portion of microalgae processing cost, an efficient drying technique is key to the utilization of microalgal biomass.

• Korea-Australia Rheology Journal
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• v.18 no.1
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• pp.15-24
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• 2006

The first international inter-laboratory study, involving six laboratories, has been conducted to examine issues associated with yield stress measurements in suspensions. The initial focus of the project was to evaluate the reliability and reproducibility of several common yield stress measuring techniques employed in different laboratories and with different instruments. Aqueous suspensions of colloidal $TiO_2$ at concentrations of 40-70 wt% solids were used as the test fluids. A wide range of instruments and techniques employing both direct and indirect methods were used to determine the yield stress of the samples prepared according to a prescribed procedure. The results obtained indicated that although variations of results existed among different techniques, direct yield stress measurements using static methods produced more reliable and repeatable results than other methods. Variability of the yield stress measured using different techniques within any laboratory however was less significant than variability of the results among different laboratories. The nature and condition of the test suspensions was identified as the most likely factor responsible for the poor reproducibility of yield stress measurements from different laboratories.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.263-278
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• 2004

This paper reviews dynamic programming (DP), surveys approximate solution methods for it, and considers their applicability to process control problems. Reinforcement Learning (RL) and Neuro-Dynamic Programming (NDP), which can be viewed as approximate DP techniques, are already established techniques for solving difficult multi-stage decision problems in the fields of operations research, computer science, and robotics. Owing to the significant disparity of problem formulations and objective, however, the algorithms and techniques available from these fields are not directly applicable to process control problems, and reformulations based on accurate understanding of these techniques are needed. We categorize the currently available approximate solution techniques fur dynamic programming and identify those most suitable for process control problems. Several open issues are also identified and discussed.

• Journal of Sensor Science and Technology
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• v.25 no.3
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• pp.161-172
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• 2016

The use of a chemical sensor array can help discriminate between chemicals when comparing one sample with another. The ability to classify pattern characteristics from relatively small pieces of information has led to growing interest in methods of sensor recognition. A variety of pattern recognition algorithms, including the adaptive radial basis function network (RBFN), may be applicable to gas and/ or odor classification. In this paper, we provide a broad review of approaches for various types of gas and/or odor identification techniques based on RBFN and drift compensation techniques caused by sensor poisoning and aging.

• Applied Chemistry for Engineering
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• v.33 no.1
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• pp.1-10
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• 2022

This paper reviews the principles, advantages, and disadvantages of main explosives detection technologies, as well as research areas needed in the future. Explosives detection technology can be classified into spectroscopic methods, sensor techniques, and olfactory type sensors. There have been advances in explosives detection technology, however studies on discriminatory, portability, and sensitivity for explosives detection still remained competitive.

• Bulletin of the Korean Chemical Society
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• v.33 no.12
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• pp.4247-4250
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• 2012