• Analytical Science and Technology
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• v.35 no.3
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• pp.136-142
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• 2022

According to media reports, the carcasses of euthanized abandoned dogs were processed at high temperature and pressure to make powder, and then used as feed materials (meat and bone meal), raising the possibility of residuals in the feed of the anesthetic ketamine and dexmedetomidine used for euthanasia. Therefore, a simultaneous analysis method using QuEChERS combined with high-performance liquid chromatography coupled with electrospray ionization tandem mass spectrometry was developed for rapid residue analysis. The method developed in this study exhibited linearity of 0.999 and higher. Selectivity was evaluated by analyzing blank and spiked samples at the limit of quantification. The MRM chromatograms of blank samples were compared with those of spiked samples with the analyte, and there were no interferences at the respective retention times of ketamine and dexmedetomidine. The detection and quantitation limits of the instrument were 0.6 ㎍/L and 2 ㎍/L, respectively. The limit of quantitation for the method was 10 ㎍/kg. The results of the recovery test on meat and bone meal, meat meal, and pet food showed ketamine in the range of 80.48-98.63 % with less than 5.00 % RSD, and dexmedetomidine in the range of 72.75-93.00 % with less than 4.83 % RSD. As a result of collecting and analyzing six feeds, such as meat and bone meal, prepared at the time the raw material was distributed, 10.8 ㎍/kg of ketamine was detected in one sample of meat and bone meal, while dexmedetomidine was found to have a concentration below the limit of quantitation. It was confirmed that the detected sample was distributed before the safety issue was known, and thereafter, all the meat and bone meal made with the carcasses of euthanized abandoned dogs was recalled and completely discarded. To ensure the safety of the meat and bone meal, 32 samples of the meat and bone meal as well as compound feed were collected, and additional residue investigations were conducted for ketamine and dexmedetomidine. As a result of the analysis, no component was detected. However, through this investigation, it was confirmed that some animal drugs, such as anesthetics, can remain without decomposition even at high temperature and pressure; therefore, there is a need for further investigation of other potentially hazardous substances not controlled in the feed.

• Korean Association of Arts Management
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• no.59
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• pp.5-31
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• 2021

The purpose of this study is to analyze social perceptions and discourses about creating arts in the era of artificial intelligence with making an implication of responding to the emergence of artificial intelligence. We conceptually understand the principles and limitations of creating visual arts using artificial intelligence whilst this paper addresses ai art in the social context by borrowing the theoretical lens from the sociology of arts. This article considers 472 newspapers about artificial intelligence art as the main data, which are interpreted through semantic network analysis. The analysis of this research shows that it is a controversial issue regarding who/which creates the artworks between humans and computers. However, judging from the dominant influence of a group of words representing the recognition of intellectual property rights, we have detected that social awareness is formed around the perspective of considering artificial intelligence creates visual arts rather than artists. In addition, based on the close relationship between the cluster and the cluster reflecting institutional support, we confirm that the discourse about artificial intelligence art is limited to technological development and legal system maintenance. Thus, this study suggests the need for defining artificial intelligence as the medium of art and constructing policy discourses on artificial intelligence art as an artistic genre.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.95-95
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• 2017

Lodging is a serious issue in rice production, because it drastically decreases the biomass production and grain yield. Since the Green Revolution, the lodging resistance has been increased by lowering the moment of above-ground parts due to the short culm by the semi-dwarf gene sd1. However, it has been pointed out that sd1 alone has suppressive effects for biomass production and yield. To increase rice yield, the long-culm and large panicle type varieties with a superior lodging resistance need to be developed. To improve the lodging resistance and yield of these type varieties, it would be effective to identify novel alleles for these traits underlying natural variations in rice and to pyramid these alleles to a single rice variety. In order to perform this strategy, we have developed new rice lines derived from crosses among varieties with superior alleles. At first, TULT-gh-5-5 was selected from a cross between strong culm and high biomass variety Leaf Star and high-yielding variety Takanari, and TUAT-32HB was selected from a cross between high-yielding variety Akenohoshi and Takanari. Then, we developed the super thick-culm and super grain-bearing line, LTAT-29 derived from a cross between TULT-gh-5-5 and TUAT-32HB. In the current study, to identify the QTLs and genes relating to the strong culm and the high yield of LTAT-29, we performed QTL analysis using SNPs markers with $F_2$ population derived from a cross between LTAT-29 and Takanari. LTAT-29 has never lodged throughout the growth period despite it had long culms and heavy panicles. LTAT-29 had a larger outer diameter of the culm and twice the size of the section modulus than Takanari. As a result, the bending moment at breaking of LTAT-29 was significantly larger than that of Takanari. Brown rice yield of LTAT-29 was $9.2t\;ha^{-1}$ about 10% higher than that of Takanari due to the larger number of spikelets per panicle. LTAT-29 had a greater number of secondary branches per panicle. In the $F_2$ population between LTAT-29 and Takanari, we found continuous frequency distributions in the section modulus and the spikelet number per panicle. Two QTLs increased the section modulus by the alleles of LTAT-29 were detected on Chr.1L and Chr.2L. One QTL increased the spikelet number per panicle of Takanari by the allele of LTAT-29 was detected on Chr.1L, and two QTLs increased the number of secondary branches per panicle by the alleles of LTAT-29 were detected on Chr.1L and Chr.4L. It was found that the alleles of these QTLs were the japonica type originated from Leaf Star or Akenohoshi. The novel QTLs for the traits related to super thick-culm and super grain-bearing and their combinations could be utilized for improving the lodging resistance and yield in rice varieties.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• The Journal of Engineering Geology
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• v.23 no.1
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• pp.37-46
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• 2013

Leakage of leachate from animal carcass disposal is a significant issue because disease can easily spread to humans and other livestock. In this study, we analyzed the physicochemical properties of leachate and tested for the presence of aerobic bacteria in leachate using molecular biology methods, for 16 animal carcass disposals in the first stage (after burial for 5 months). Leachate physicochemical analysis revealed higher total coliforms, TOC, $NH^{4+}$, and $NO^{3-}$ concentrations compared with previously published data. In most leachate samples, the concentrations of $NH^{4+}$ and $NO^{3-}$ exceeded the Korean guideline values for drinking water. In 16S rRNA sequence analysis of the distribution of leachate under aerobic conditions, Bacillus pumilus, Lysinibacillus sphaericus, and B. sphaericus were observed with high frequency, whereas no food-poisoning-related bacteria such as B. cereus or Salmonella were detected. The present findings improve our knowledge of the transport of leachate from animal carcass disposal sites through geologic media, and are useful in risk analysis and for subsequent studies.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.12
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• pp.1895-1904
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• 2015

Foodborne illness associated with food service establishments is an important food safety issue in Korea. In this study, foodborne pathogens (Bacillus cereus, Clostridium perfringens, Escherichia coli, pathogenic Escherichia coli, Listeria monocytogenes, Salmonella spp., Staphylococcus aureus, and Vibrio parahaemolyticus) and hygiene indicator organisms [total viable cell counts (TVC), coliforms] were analyzed for food and environmental samples from foodservice establishments at schools in Gyeonggi province. Virulence factors and antimicrobial resistance of detected foodborne pathogens were also characterized. A total of 179 samples, including food (n=66), utensil (n=68), and environmental samples (n=45), were collected from eight food service establishments at schools in Gyeonggi province. Average contamination levels of TVC for foods (including raw materials) and environmental samples were 4.7 and 4.0 log CFU/g, respectively. Average contamination levels of coliforms were 2.7 and 4.0 log CFU/g for foods and environmental swab samples, respectively. B. cereus contamination was detected in food samples with an average of 2.1 log CFU/g. E. coli was detected only in raw materials, and S. aureus was positive in raw materials as well as environmental swab samples. Other foodborne pathogens were not detected in all samples. The entire B. cereus isolates possessed at least one of the diarrheal toxin genes (hblACD, nheABC, entFM, and cytK enterotoxin gene). However, ces gene encoding emetic toxin was not detected in B. cereus isolates. S. aureus isolates (n=16) contained at least one or more of the tested enterotoxin genes, except for tst gene. For E. coli and S. aureus, 92.7% and 37.5% of the isolates were susceptible against 16 and 19 antimicrobials, respectively. The analyzed microbial hazards could provide useful information for quantitative microbial risk assessment and food safety management system to control foodborne illness outbreaks in food service establishments.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.10
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• pp.4265-4269
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• 2014

Purpose: This study aimed at summarizing epidemiological evidence of the association between gestational diabetes mellitus (GDM) and subsequent risk of cancer. Materials and Methods: We searched Medline, Embase, Cancer Lit and CINAHL for epidemiological studies published by February 1, 2014 examining the risk of cancer in patients with history of GDM using highly inclusive algorithms. Information about first author, year of publication, country of study, study design, cancer sites, sample sizes, attained age of subjects and methods used for determining GDM status were extracted by two researchers and Stata version 11.0 was used to perform the meta-analysis and estimate the pooled effects. Results: A total of 9 articles documented 5 cohort and 4 case-control studies containing 10,630 cancer cases and 14,608 women with a history of GDM were included in this review. Taken together, the pooled odds ratio (OR) between GDM and breast cancer risk was 1.01 (0.87-1.17); yet the same pooled ORs of case-control and cohort studies were 0.87 (0.71-1.06) and 1.25 (1.00-1.56) respectively. There are indications that GDM is strongly associated with higher risk of pancreatic cancer (HR=8.68) and hematologic malignancies (HR=4.53), but no relationships were detected between GDM and other types of cancer. Conclusions: Although GDM increases the risk of certain types of cancer, these results should be interpreted with caution becuase of some methodological flaws. The issue merits added investigation and coordinated efforts between researchers, antenatal clinics and cancer treatment and registration agencies to help attain better understanding.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.11
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• pp.1643-1650
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• 2017

Objective: The control of psychrotrophic bacteria causing milk spoilage and illness due to toxic compounds is an important issue in the dairy industry. In South Korea, Gangwon-do province is one of the coldest terrains in which eighty percent of the area is mountainous regions, and mainly plays an important role in the agriculture and dairy industries. The purposes of this study were to analyze the indigenous microbiota of raw milk in Gangwon-do and accurately investigate a putative microbial group causing deterioration in milk quality. Methods: We collected raw milk from the bulk tank of 18 dairy farms in the Hoengseong and Pyeongchang regions of Gangwon-do. Milk components were analyzed and the number of viable bacteria was confirmed. The V3 and V4 regions of 16S rRNA gene were amplified and sequenced on an Illumina Miseq platform. Sequences were then assigned to operational taxonomic units, followed by the selection of representative sequences using the QIIME software package. Results: The milk samples from Pyeongchang were higher in fat, protein, lactose, total solid, and solid non-fat, and bacterial cell counts were observed only for the Hoengseong samples. The phylum Proteobacteria was detected most frequently in both the Hoengseong and Pyeongchang samples, followed by the phyla Firmicutes and Actinobacteria. Notably, Corynebacterium, Pediococcus, Macrococcus, and Acinetobacter were significantly different from two regions. Conclusion: Although the predominant phylum in raw milk is same, the abundances of major genera in milk samples were different between Hoengseong and Pyeongchang. We assumed that these differences are caused by regional dissimilar farming environments such as soil, forage, and dairy farming equipment so that the quality of milk raw milk from Pyeongchang is higher than that of Hoengseong. These results could provide the crucial information for identifying the microbiota in raw milk of South Korea.

• Sleep Medicine and Psychophysiology
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• v.10 no.1
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• pp.52-60
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• 2003

Objectives: Stage 1 sleep provides important information regarding interpretation of nocturnal polysomnography, particularly sleep onset. It is a short transition period from wakeful consciousness to sleep. The lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, utilization of simultaneous EEG and EOG processing and analyses to detect stage 1 sleep automatically were attempted. Methods: Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. A relative power of alpha waves less than 50% or relative power of theta waves more than 23% was regarded as stage 1 sleep. SEM(slow eye movement) was defined as the duration of both-eye movement ranging from 1.5 to 4 seconds, and was also regarded as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results were compared to the manual rating results done by two polysomnography experts. Results: A total of 169 epochs were analyzed. The agreement rate for stage 1 sleep between automatic detection and manual scoring was 79.3% and Cohen’s Kappa was 0.586 (p<0.01). A significant portion (32%) of automatically detected stage 1 sleep included SEM. Conclusion: Generally, digitally-scored sleep staging shows accuracy up to 70%. Considering potential difficulty in stage 1 sleep scoring, accuracy of 79.3% in this study seems to be strong enough. Simultaneous analysis of EOG differentiates this study from previous ones which mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnari remains a valid one in this study.

• Journal of Biomedical Engineering Research
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• v.25 no.1
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• pp.11-19
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• 2004

Stage 1 sleep provides important information regarding interpretation of nocturnal polysomnography, particularly sleep onset. It is a short transition period from wakeful consciousness to sleep. Lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, we attempted to utilize simultaneous EEC and EOG processing and analyses to detect stage 1 sleep automatically. Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. Either the relative power of alpha waves less than 50％ or the relative power of theta waves more than 23％ was regarded as stage 1 sleep. SEM (slow eye movement) was defined as the duration of both eye movement ranging from 1.5 to 4 seconds and regarded also as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results f ere compared to the manual rating results done by two polysomnography experts. Total of 169 epochs was analyzed. Agreement rate for stage 1 sleep between automatic detection and manual scoring was 79.3％ and Cohen's Kappa was 0.586 (p＜0.01). A significant portion (32％) of automatically detected stage 1 sleep included SEM. Generally, digitally-scored sleep s1aging shows the accuracy up to 70％. Considering potential difficulties in stage 1 sleep scoring, the accuracy of 79.3％ in this study seems to be robust enough. Simultaneous analysis of EOG provides differential value to the present study from previous oneswhich mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnariet at. remains to be a valid one in this study.