• Korean Chemical Engineering Research
• /
• v.46 no.2
• /
• pp.233-247
• /
• 2008

Process monitoring technology is able to detect the faults and the process changes which occur in a process unpredictably, which makes it possible to find the reasons of the faults and get rid of them, resulting in a stable process operation, high-quality product. Statistical process monitoring method based on data set has a main merit to be a tool which can easily supervise a process with the statistics and can be used in the analysis of process data if a high quality of data is given. Because a real process has the inherent characteristics of nonlinearity, non-Gaussianity, multiple operation modes, sensor faults and process changes, however, the conventional multivariate statistical process monitoring method results in inefficient results, the degradation of the supervision performances, or often unreliable monitoring results. Because the conventional methods are not easy to properly supervise the process due to their disadvantages, several advanced monitoring methods are developed recently. This review introduces the theories and application results of several remarkable monitoring methods, which are a nonlinear monitoring with kernel principle component analysis (KPCA), an adaptive model for process change, a mixture model for multiple operation modes and a sensor fault detection and reconstruction, in order to tackle the weak points of the conventional methods.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.59 no.3
• /
• pp.312-318
• /
• 2014

We evaluated the morphological characteristics of 156 maize inbred lines, which were developed to breeding normal maize variety at Maize Experiment Station, Gangwon Agricultural Research and Extension Services, by examining 11 quantitative and three qualitative characteristics. On the evaluation of three qualitative traits for 156 maize inbred lines, most inbred lines showed yellow (85 and 84 inbred lines) at tassel color (QL1) and silk color (QL2), and showed semi erect (105 inbred lines) at plant type (QL3). While, the evaluation of 11 quantitative traits for 156 maize inbred lines, they showed the morphological variation in days of tasseling (QN1, 56.5 to 76.0 days), days of silking (QN2, 59.0 to 85.5 days), stem thickness (QN3, 12.7 to 42.9 mm), plant height (QN4, 111.8 to 239.8 cm), ear height (QN5, 48.2 to 126.5 cm), 100 kernel weight (QN6, 14.9 to 36.4 g), ear length (QN7, 10.0 to 79.0 cm), setted kernel length (QN8, 8.0 to 70.5 cm), ear thickness (QN9, 4.0 to 22.0 cm), total kernel weight (QN10, 22.0 to 490.0 kg) and water content (QN11, 9.3 to 11.9%), respectively. As a result, 11 inbred lines (00hf3, 00hf19, 00hf30, 00hf36, 02S8069, 02S8072, 02S8090, 02S8099, 05S10011, 06S8085-6, 07S8011) in the 156 normal maize inbred lines have showed comparatively high values. While, the results of PCA (principal component analysis) indicated that the ear length (QN7), setted kernel length (QN8), ear thickness (QN9) and total kernel weight (QN10) greatly contributed in positive direction on the first principal components. And also, days of tasseling (QN1), days of silking (QN2), plant height (QN4) and ear height (QN5) contributed in negative direction on the second principal component. Thus these morphological characters, which were greatly contributed in the first and second principal components, might be considered to be useful for discrimination among 156 normal inbred lines. Specifically, this study's assessment of morphological characteristics of 156 normal inbred lines will be helpful useful for normal maize breeding programs such activities as planning crosses for hybrid and line development at Maize Experiment Station, Gangwon Agricultural Research and Extension Services.

• Journal of Animal Science and Technology
• /
• v.56 no.5
• /
• pp.16.1-16.9
• /
• 2014

Fatty acids (FA) have recently been used in several studies to infer the diet in a number of species. While these studies have been largely successful, most have dealt with predators that have a fairly specialized diet. In this paper, we used FA analysis as a tool to infer the diet of the nearctic river otter (Lontra canadensis). The river otter is an opportunistic predator known to subsist on a wide variety of prey including, fishes, crayfish, molluscs, reptiles and amphibians, among others. We analyzed the principle components of 60 FA from otters and 25 potential prey species in Illinois, USA. Prey species came from 4 major taxonomic divisions: fishes, crayfish, molluscs and amphibians. Within each division, most, but not all, species had significantly different profiles. Using quantitative FA signature analysis, our results suggest that, by mass, fish species are the most significant component of Illinois River otters' diet ($37.7{\pm}1.0%$). Molluscs ranked second ($32.0{\pm}0.8%$), followed by amphibians ($27.3{\pm}4.3%$), and finally, crayfish ($3.0{\pm}0.6%$). Our analysis indicates that molluscs make up a larger portion of the otter diet than previously reported. Throughout much of the Midwest there have been numerous otter reintroduction efforts, many of which appear to be successful. In regions where mollusc species are endangered, these data are essential for management agencies to better understand the potential impact of otters on these species. Our analysis further suggests that quantitative FA signature analysis can be used to infer diet even when prey species are diverse, to the extent that their FA profiles differ. Better understanding of the otter's metabolism of FA would improve inferences of diet from FA analysis.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.6
• /
• pp.834-841
• /
• 2022

Recently, applying artificial intelligence technologies in various fields of production has drawn an upsurge of research interest due to the increase for smart factory and artificial intelligence technologies. A great deal of effort is being made to introduce artificial intelligence algorithms into the defect detection task. Particularly, detection of defects on the surface of metal has a higher level of research interest compared to other materials (wood, plastics, fibers, etc.). In this paper, we compare and analyze the speed and performance of defect classification by combining machine learning techniques (Support Vector Machine, Softmax Regression, Decision Tree) with dimensionality reduction algorithms (Principal Component Analysis, AutoEncoders) and two convolutional neural networks (proposed method, ResNet). To validate and compare the performance and speed of the algorithms, we have adopted two datasets ((i) public dataset, (ii) actual dataset), and on the basis of the results, the most efficient algorithm is determined.

• Journal of Forest and Environmental Science
• /
• v.39 no.2
• /
• pp.73-80
• /
• 2023

Little is known of the life history of Garcinia kola; the objective of this study, therefore, was to assess the fruiting age and tree size of the species in a coastal humid tropical climate plantation condition. A total 103 trees were used in the study viz; 80 ten-year-old trees at reproductive maturity onset and 13 thirty-year-old trees with several cycles of reproduction that constitute two independent variables. Data collected were age of onset of flowering and size at reproductive maturity onset. Relative size at reproductive maturity onset (RSOM) was estimated as size at reproductive maturity onset (SOM) divided by asymptotic maximal size (AMS). Data analysis was conducted using pairwise t-test and principal component analysis (PCA). Reproductive maturity onset (flowering) was recorded in the ten-year-old stand eight (8) years after planting. Mean size at reproductive maturity onset (SOM) was height 5.32±1.7 m, dbh 0.11±0.03 m, total number of branches was 29.6±7.3, crown depth 5.24±1.05 m, crown diameter was 4.78±0.7 m, branch diameter 0.098±0.01 m, leaf length 0.13±0.02 m, leaf breadth 0.37±0.01 m, twig length 0.35±0.11 m and leaf per twig 6±0.84 and asymptotic maximal size (AMS) was height 19.85±0.76 m, dbh 0.95±0.09 m, total number of branches 62±5, crown depth 18.83±0.7 m, crown diameter 12.5±1.64 m, branch diameter 0.5±1.6 m, leaf length 0.16±0.023 m, leaf breadth 0.45±0.12 m, twig length 0.37±0.11 m and leaf per twig 19±7.5. Pairwise t-test analysis showed there was significant differences between SOM and AMS in all growth factors except leaf length, leaf breadth, and twig length. Highest relative size at reproductive maturity onset (RSOM) was recorded in leaf length 0.82, twig length 0.82, and leaf breadth 0.80, while, the lowest was branch diameter 0.11. Four components out of the total of eleven were extracted to explain the relationship in RSOM: Principal component one (PC1) explained 37.23%; PC2 26.4%, PC3 22.73%, and PC4 13.64%.

• Journal of Korean Society on Water Environment
• /
• v.28 no.1
• /
• pp.84-93
• /
• 2012

The study was conducted to analyze the spatio-temporal changes in water quality of the major 36 sampling stations of Nakdong River, depending on each station, season using the 17 water quality variables from 2000 to 2010. The result was verified to interpret the characteristics of water quality variables in a more accurate manners. According to the Principal component analysis (PCA) and Exploratory factor analysis (EFA) results; the results of these analyses were identified 4 factors, Factor 1 (nutrients) included the concentrations of T-N, T-P, $NO_{3}-N$, $PO_{4}-P$, DTN, DTP for sampling station and season, Factor 2 (organic pollutants) included the concentrations of BOD, COD, Chl-a, Factor 3 (microbes) included the concentrations of F.Coli, T.Coli, and Factor 4 (others) included the concentrations of pH, DO. The results of a Cluster analysis indicated that Geumhogang 6 was the most contaminated site, while tributaries and most of the down stream sites of Nakdong River were mainly affected by each nutrients (Factor 1) and organic pollutants (Factor 2). The verification consequence of Confirmatory factor analysis (CFA) from Exploratory factor analysis (EFA) result can be summarized as follows: we could find additional relations between variables besides the structure from EFA, which we obtained through the second-order final modeling adopted in CFA. Nutrients had the biggest impact on water pollution for each sampling station and season. In particular, It was analyzed that P-series pollutant should be controlled during spring and winter and N-series pollutant should be controlled during summer and fall.

• Korean Journal of Food Science and Technology
• /
• v.34 no.1
• /
• pp.13-17
• /
• 2002

The study was to analyze aroma patterns of Gastrodiae Rhizoma by the electronic nose with conducing polymer 32 sensors. Response by the electronic nose was analyzed by the principal component analysis (PCA). Sensory evaluation for the organoleptic characteristics of Gastrodiae Rhizoma was also performed. Raw Gastrodiae Rhizoma was very intensive in overall odor and taste. Hot air-dried $60^{\circ}C$ Gastrodiae Rhizoma was relatively weak in overall odor and taste. Intensity of aroma in the electronic nose was the highest in $60^{\circ}C$ hot air-dried Gastrodiae Rhizoma. As quality factor (QF) calcuated from PCA map of normalized pattern data by thirty two sensors showed less than 2, and so aroma pattern among raw, freezed-dried, and hot-air dried Gastrodiae Rhizoma had no difference. When PCA was performed for normalized pattern data by the selected sensitive ten sensors, QF value between raw and $60^{\circ}C$ hot air-dried Gastrodiae Rhizoma was 2.366. Thus aroma pattern of raw and $60^{\circ}C$ hot air-dried Gastrodiae Rhizoma was discriminated in electronic nose.

• Food Science and Preservation
• /
• v.20 no.3
• /
• pp.348-355
• /
• 2013

This study was conducted to analyze the sensory profiles of commercial rice cookies and snacks in the market and to provide fundamental data on the development of rice cookies and snacks. The sensory characteristics of 10 kinds of Korean commercial rice cookies and snacks were evaluated using a sensory test and were analyzed via quantitative description analysis (QDA) and principal component analysis (PCA), depending on their rice contents and processing methods. The rice cookies and snacks with less than 30% rice contents and that were fried were preferred, and their grainy attribute was related to the preference for them. Then 27 kinds of commercial rice cookies and snacks from three countries, Japan, the U.S.A. and China, were also evaluated and compared with those from Korea. While the Korean commercial rice cookies and snacks were sweet, grainy and crispy, those of Japan were not sweet and instead, were salty and crispy.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.19 no.5
• /
• pp.439-458
• /
• 2013

Temporal and spatial variations of water quality were investigated in the Cheonsu Bay of Yellow Sea, Korea from 2010 to 2011. Water samples were collected at 16 stations and physicochemical parameters were analyzed including water temperature, salinity, suspended solids (SS), chemical oxygen demand (COD), dissolved oxygen (DO), Chlorophyll a and nutrients. Spatial distribution patterns of all survey items were not clear among stations but the bimonthly variations were distinct except the bottom water of the suspended solids. The trend analysis by principal component analysis (PCA) during 2 years revealed the significant variations in water quality in the study area. Spatial water qualities were discriminated into 3 clusters by PCA; station cluster in the surface water 1, 2~11, and 12~16, the bottom water 1, 2~7, and 8~16. Annual bimonthly water qualities were clearly discriminated into 3 clusters by PCA. But tend of cluster in the surface and bottom water was difference, period most of the research was low in nutrient. Ecology-based water quality criteria was a good level of grade II. Bimonthly results are shown as III grade(normal) at June and August, II grade(good) at October and December and I grade for February and April. Water quality was showed by the input of fresh water same as those of Kyoungin coastal area, Asan coastal area, Gunsan coastal and Mokpo coastal area in the Cheonsu.

• Proceedings of the Plant Resources Society of Korea Conference
• /
• 2010.05a
• /
• pp.18-18
• /
• 2010

Glucosinolates(GSLs) are major secondary products($\beta$-thioglucoside N-hydroxysulfates) containing sulfates that are found mainly in Cruciferae family such as cabbage, broccoli, radish, turnip, kale, mustard and rapeseed as the important crops in agronomic and economic aspects. Especially, isothiocyanates(ITCs) have been shown to inhibit carcinogenesis with regulation cancer cell development followed by regulating target enzymes, inducing cell cycle arrest and apoptosis against various human cancer cell lines. Total desulfo(DS)-GSLs of nine type in 210 Korean leaf mustard accessions were isolated and confirmed using electrospray ionization mass spectrometric(ESI-MS/MS) method and DS-GSLs powerful library maked from several reference data. The isolated individual DS-GSLs were identified by removed $\beta$-D-glucopyranose residue ($C_6H_{11}O_5$, MW 163) from MS/MS data. Among them sinigrin(41.7%), glucoiberverin(21.7%) and gluconasturtiin(12.6%) were major components, Especially, despite gluconapin was minor component, accession K046197-1 and K046197-2 showed higher content of 4.11 and 3.31 mg/g(DW), respectively. The total GSLs contents in 210 accessions were ranged from 5.3 to 23.2 mg/g(DW) with a mean value of 13.0 mg/g(DW). As a result of principal component analysis(PCA), the individual GSLs loading plots were composed of three groups and components belonged to each group showed correlationship in quantitative pattern.