• Journal of Food Hygiene and Safety
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• v.27 no.3
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• pp.301-305
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• 2012

This study was conducted to investigate the microbiological contamination levels in rice cakes and rice flour due to climate change in three areas classified to their temperature and precipitation. We investigated the contamination levels of total aerobic bacteria, coliforms, Escherichia coli, Bacillus cereus, Staphylococcus aureus, Clostridium perfringens of rice flour and 3 rice cakes such as Garaetteok, Sirutteok and Gyeongdan. Contamination levels of total aerobic bacteria in rice flour were 4.9 log CFU/g. In a total of 70 rice flour, yeasts & molds and coliforms were detected in 42 and 52 samples at the levels of 43 CFU/g and 1.29 log CFU/g, respectively. S. aureus were detected in only 1 rice flour (1.66 log CFU/g) out of 70. In an investigation of contamination levels in rice cakes, the population of total aerobic bacteria were highest in Gyeongdan (5.18 log CFU/g) and coliforms were highest in Gareattock (2.93 log CFU/g). There was no detection of E. coli and B. cereus except for only 1 Gareattock (1.20 log CFU/g). There were no differences of contamination levels among the three areas. If constant monitoring of rice cakes and rice flour is conducted on the basis of this study, it is expected to be able to analyze the change of contamination levels in rice cakes and rice flour due to climate change.

• Journal of the Korean Geosynthetics Society
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• v.17 no.3
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• pp.9-18
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• 2018

The soil parameters important for the design of the soft ground are the compression index ($C_c$), the consolidation settlement and consolidation speed at the field. Compression index is obtained by laboratory consolidation test. In the laboratory consolidation test, sample disturbance always occurs. In order to correct the disturbance phenomena, the method of calculating the compression index proposed by Schmertmann (1955) is generally used. However, recent developments in sampling technology and Korean soil conditions are different from those proposed by Schmertmann. So it needs to be verified. In this study, each consolidation curve's cross void ratio is evaluated by doing consolidation test varying disturbance on high-plastic clay (CH), low-plastic clay (CL) and low-plastic silt (ML). The test results were $0.521e_0$ for low-plastic silt, $0.404e_0$ for low-plastic clay, and $0.458e_0$ for the high-plastic clay. This results were different from those of Schmertmann's suggested value of $0.42e_0$. Therefor we proposed a correction formula using the plastic index according to soil type. However, since the results of this study are limited test results, further studies on various korean soil are needed to suggest the compression index correction method according to the degree of plasticity index of soil.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.411-421
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• 2012

The stagnant growth in 3D market due to 3D movie contents shortage is encouraging development of techniques for production cost reduction. Elimination of vertical disparity generated during image acquisition requires heaviest time and effort in the whole stereoscopic film-making process. This matter is directly related to competitiveness in the market and is being dealt with as a very important task. The removal of vertical disparity, i.e. image rectification has been treated for a long time in the photogrammetry field. While computer vision methods are focused on fast processing and automation, photogrammetry methods on accuracy and precision. However, photogrammetric approaches have not been tried for the 3D film-making. In this paper, proposed is a photogrammetry-based rectification algorithm that enable to eliminate the vertical disparity precisely by reconstruction of geometric relationship at the time of shooting. Evaluation of proposed algorithm was carried out by comparing the performance with two existing computer vision algorithms. The epipolar constraint satisfaction, epipolar line accuracy and vertical disparity of result images were tested. As a result, the proposed algorithm showed excellent performance than the other algorithms in term of accuracy and precision, and also revealed robustness about position error of tie-points.

• Journal of Korea Water Resources Association
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• v.43 no.2
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• pp.153-165
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• 2010

Large-Scale Particle Image Velocimetry (LSPIV) is an extension of particle image velocimetry (PIV) for measurement of flows spanning large areas in laboratory or field conditions. LSPIV is composed of six elements - seeding, illumination, recording, image transformation, image processing, postprocessing - based on PIV. Possible error elements at each step of Mobile LSPIV (MLSPIV), which is a mobile version of LSPIV, in field applications are identified and summarized the effect of the errors which were quantified in the previous studies. The total number of elemental errors is 27, and five error sources were evaluated previously, seven elemental errors are not effective to the current MLSPIV system. Among 15 elemental errors, four errors - sampling time, image resolution, tracer, and wind - are investigated through an experiment at a laboratory to figure out how those errors affect to velocity calculation. The analysis to figure out the effect of the number of images used for image processing on the velocity calculation error shows that if over 50 images or more are used, the error due to it goes below 1 %. The effect of the image resolution on velocity calculation was investigated through various image resolution using digital camera. Low resolution image set made 3 % of velocity calculation error comparing with high resolution image set as a reference. For the effect of tracers and wind, the wind effect on tracer is decreasing remarkably with increasing the flume bulk velocity. To minimize the velocity evaluation error due to wind, tracers with high specific gravity is favorable.

• Microbiology and Biotechnology Letters
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• v.33 no.2
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• pp.148-153
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• 2005

Malaria is a re-emerging infectious disease that is spreading to areas where it had been eradicated, such as Eastern Europe and Central Asia. To avoid the mortality from malaria, early detection of the parasite is a very important issue. The peripheral blood smear has been the gold standard method for the diagnosis of malaria infection. Recently, several other methods have been introduced for quantitative detection of malaria parasites. Real time PCR that employs fluorescent labels to enable the continuous monitoring of PCR product formation throughout the reaction has recently been used to detect several human malaria parasites. 18S rRNA sequences from malaria parasites have been amplified using Taqman real time PCR assay. Here, a SYBR Green-based real time quantitative PCR assay for the detection of malaria parasite-especially, Plasmodium vivax - was applied for the evaluation of 26 blood samples from Korean malaria patients. Even though SYBR Green-based real time PCR is easier and cheaper than Taqman-based assay, SYBR Green-based assay cannot be used because 18S rRNA cannot be specifically amplified using 1 primer set. Therefore, we used DBP gene sequences from Plasmodium vivax, which is specific for the SYBR Green based assays. We amplified the DBP gene from the 26 blood samples of malaria patients using SYBR Green based assay and obtained the copy numbers of DBP genes for each sample. Also, we selected optimal reference gene between ACTB and B2M using real time assay to get the stable genes regardless of Malaria titer. Using selected ACTB reference genes, we successfully converted the copy numbers from samples into titer, ${\sharp}$ of parasites per microliter. Using the resultant titer from DBP based SYBER Green assay with ACTB reference gene, we compared the results from our study with the titer from Taqman-based assay. We found that our results showed identical tendency with the results of 18S rRNA Taqman assay, especially in lower titer range. Thus, our DBP gene-utilized real time assay can detect Plasmodium vivax in Korean patient group semi-quantitatively and easily.

• Journal of Life Science
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• v.21 no.3
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• pp.412-416
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• 2011

Taste sensation plays a crucial role in selecting and ingesting foods with different qualities which convey information about their nutrient content and/or safety. Sweetness is one of the five modalities in humans and serves as an energy resource for metabolism. There are reports on allelic polymorphisms which influence perception of sweetness in mice and humans. Since the influence of genetic factors on taste disorder has not been studied, we investigated the association of genetic polymorphisms in TAS1R3 and guanine nucleotide binding protein, alpha transducing 3 (GNAT3) genes and taste disorder. A total of 150 individuals composed of 50 patients with taste disorder and 100 healthy controls were recruited for the study and PCR-mediated directing sequencing method was used to genotype for two different single nucleotide polymorphisms (SNPs) - rs307355 (T>C) and rs35744813 (T>C) in the TAS1R3 gene, and rs7792845 (T>C) and rs1524600 (C>T) in the the GNAT3 gene. The allele and genotype frequencies of rs307355 and rs35744813 in the TAS1R3 gene showed a significant association between patients with taste disorder (p=0.022 and p=0.013 in both of SNPs, respectively). In addition, the frequency of T-T haplotype in the TAS1R3 gene was higher in taste disorder cases than in the controls (OR, 1.93: 95%. CI, 1.09-3.39, p=0.022). In the GNAT3, the genotype frequency of rs7792845 in the patients was also different from the controls (p=0.048), but allele frequency was not significantly associated in either group. Our result provides the frequencies of SNPs and haplotypes of the TAS1R3 and GNAT3 genes for the fundamental information of nutrigenetics in perception of the taste of sweetness in the Korean population. Also, the study suggests that the allelic polymorphisms of TAS1R3 and GNAT3 genes may be useful as a molecular marker for evaluating patients with taste disorder. Further studies with large samples are required to clarify our observation.

• Korean journal of food and cookery science
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• v.21 no.3 s.87
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• pp.290-300
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• 2005

Increased sanitation management of foodservice establishments is required because most of the reported foodborne-disease outbreaks were in the foodservice industry. The purpose of this study was to determine the important control points for good sanitation. In this study, we inspected twenty foodservice establishments in Seoul, Kyunggi, Kyungnam with a self-developed monitoring tool. These foodservice establishments included secondary schools, universities, and industries. Six of them had appointed as the HACCP-certified establishments from the Korea Food and Drug Administration. The inspection was conducted from June to August in 2002. The inspection tool consisted of nine dimensions and sixty-five items. The dimensions were 'personal sanitation', 'supply of raw food', 'food storage', 'handling of raw food and ready-to-eat', 'cleaning and sterilization', 'waste control', 'pest control', and 'control of establishment and equipment' The highest possible score of this inspection tool is 105 points. Statistical data analysis was completed using the SPSS Package(11.0) for descriptive analysis Kruskal-Wallis. The score for the secondary schools (83.6 points) was higher than for the others and number of in compliance item was 50.9 on average. Therefore, we concluded that the secondary schools' sanitation condition was good. The foodservice establishments acquired HACCP certification was 89.7 points, which was significantly higher than that of establishments not applying foodservices in total score. Instituting the HACCP system in a foodservice is very effective for sanitation management. Many out of the compliance observations were found in the dimensions of 'waste control', 'control of establishment and equipment', and 'supply of raw food' 'Clean condition of refrigerator' item was $65\%$ out of the compliance that was the highest percent in this study. 'Notify and observance of heating/reheating temperature' was $45\%$ out of compliance. Items which were over $30\%$ out of compliance were 'sterilization of knifes and chopping boards in cooking', 'education of workers', 'maintain refrigerator temperature blow $5^{\circ}C$', and 'countermeasure of infection workers' In the results, most of the foodservice establishments were poorly managed in temperature control and cross-contamination. The important control points revealed in this study were preventing contamination, cooking temperature compliance, management of raw food and refrigerator. Therefore foodservice establishments should pay attention to education and training about important control points. The systematic sanitation management monitoring tool developed in this study can be effectively applied for conducting self-inspection and improving the sanitary conditions of their own foodservice operations.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.295-305
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• 2024

This study aims to analyze the micro-sedimentary structures of the Hwangdo tidal flats using ultra-high resolution unmanned aerial vehicle (UAV) data. Tidal flats, located in the transitional area between land and sea, constantly change due to tidal activities and provide a unique environment important for understanding sedimentary processes and environmental conditions. Traditional field observation methods are limited in spatial and temporal coverage, and existing satellite imagery does not provide sufficient resolution to study micro-sedimentary structures. To overcome these limitations, high-resolution images of the Hwangdo tidal flats in Chungcheongnam-do were acquired using UAVs. This area has experienced significant changes in its sedimentary environment due to coastal development projects such as sea wall construction. From May 17 to 18, 2022, sediment samples were collected from 91 points during field surveys and 25 in-situ points were intensively analyzed. UAV data with a spatial resolution of approximately 0.9 mm allowed identifying and extracting parameters related to micro-sedimentary structures. For mud cracks, the length of the major axis of the polygons was extracted, and the wavelength and ripple symmetry index were extracted for ripple marks. The results of the study showed that in areas with mud content above 80%, mud cracks formed at an average major axis length of 37.3 cm. In regions with sand content above 60%, ripples with an average wavelength of 8 cm and a ripple symmetry index of 2.0 were formed. This study demonstrated that micro-sedimentary structures of tidal flats can be effectively analyzed using ultra-high resolution UAV data without field surveys. This highlights the potential of UAV technology as an important tool in environmental monitoring and coastal management and shows its usefulness in the study of sedimentary structures. In addition, the results of this study are expected to serve as baseline data for more accurate sedimentary facies classification.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.