Kim, Dae-Gyun;Kim, Jin-Young;Lee, Won-Suk;Kim, Hye-Hyeong;Seo, Myung-Whoon;Park, In-Tae;Hyun, Junge;Yoo, Gayoung
Journal of Environmental Impact Assessment
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v.27
no.6
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pp.695-703
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2018
This study was conducted to suggest a sustainable farming practice forresource recycling in vegetable gardens of North Korea. In North Korea, farmers are allowed to own private vegetable gardens less than $100m^2$. However, usage of fertilizers in private vegetable gardens is very limited due to economic sanctions by UN security council. If North and South Korea initiated the cooperative action in the near future, agricultural sector would be the highest priority cooperation area. Considering the current North Korean situation in agriculture, we would like to suggest a method for producing organic fertilizer manure. For raw materials for producing manure, we selected corn byproduct, which is the most abundant material, and rabbits' feces, which are easily obtained from individual private farms in North Korea. As we cannot get corn byproducts and rabbits' feces from North Korea, we prepared samples of corn byproducts and rabbits; feces from many places in South Korea. After statistical analysis of variance, there was no significant difference in the T-N contents of corn byproducts from Gyeonggi, Gangwon, Chungnam, Chungbuk, Jeollabuk and Gyeongsangnam-dos, which indicates that the fertilizing quality of corn byproducts does not vary significantly in the spatial scale of South. Korea. In this sense, if we use corn samples from Gyeonggi province, they would not be very different from those of North Korean regions. Physicochemical properties of rabbits' feces were different between those eating feed grains and those eating plants only. Hence, we used rabbits' feces of the rabbits from Yeonchun area, which were fed by plants only. Using three different mixing ratios of corn byproducts and rabbits' feces, composting was conducted for 60 days. The mixing ratio of 1:1 produced the manure with % T-N of 1.98% and OM/N ratio of 31.7 after 30 days of composting, which is comparable to the quality of commercial manure.
As a new type of business model in the market competition situation of tour companies, this study has developed to the online form of the travel industry to the business form which is the combination of the electronic commerce function and the mobile service process in the provision of the simple web-site, This study explores the difficulties of change for the development of the travel industry from the point of view that recognition is not a simple marketing strategy diversification means but a change of recognition as a business model for expanding new markets or creating new markets. The factors affecting the choice of online travel agent (OTA) and the factors that influence the choice of online travel agency were analyzed. Were used for the empirical survey. The purpose of this study is to investigate the factors influencing the choice of online travel agents who have experience with or experience using online travel agency (OTA), what factors are important to them, and how they differ in importance when visiting again. The results of this study are as follows: First, there was a significant difference between the first and second visitors of online travel agencies. The results of this study were as follows: Attitude toward resolving complaints, convenience of change and cancellation, delivery of tickets and documents, convenience of complaints, The emphasis should be on establishing and strengthening service environments such as the speed of updating the latest information, the simplicity of the booking procedure, the degree of satisfaction of the past, the ability of employees to handle their work, the safety of various payment methods and settlement, The results of this study are as follows: First, the satisfaction of the online travel agency is influenced by the selection factors of the selected online tour agency, and the A/S such as the convenience of prompt delivery, Environmental factors contributed to satisfaction. It is suggested that the systematic service structure such as customer satisfaction and ease of use is a necessary marketing strategy for survival and development of online travel agencies. It is suggested that the marketing concentration strategy with the first visitors as the target market is effective and this is a part of the marketing strategy for the survival of online travel agencies.
Journal of the Korean Institute of Landscape Architecture
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v.49
no.3
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pp.1-10
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2021
This study aimed to evaluate preferences of Bukhansan dulegil using sentiment analysis, a natural language processing technique, to derive preferred and non-preferred factors. Therefore, we collected blog articles written in 2019 and produced sentimental scores by the derivation of positive and negative words in the texts for 21 dulegil courses. Then, content analysis was conducted to determine which factors led visitors to prefer or dislike each course. In blogs written about Bukhansan dulegil, positive words appeared in approximately 73% of the content, and the percentage of positive documents was significantly higher than that of negative documents for each course. Through this, it can be seen that visitors generally had positive sentiments toward Bukhansan dulegil. Nevertheless, according to the sentiment score analysis, all 21 dulegil courses belonged to both the preferred and non-preferred courses. Among courses, visitors preferred less difficult courses, in which they could walk without a burden, and in which various landscape elements (visual, auditory, olfactory, etc.) were harmonious yet distinct. Furthermore, they preferred courses with various landscapes and landscape sequences. Additionally, visitors appreciated the presence of viewpoints, such as observation decks, as a significant factor and preferred courses with excellent accessibility and information provisions, such as information boards. Conversely, the dissatisfaction with the dulegil courses was due to noise caused by adjacent roads, excessive urban areas, and the inequality or difficulty of the course which was primarily attributed to insufficient information on the landscape or section of the course. The results of this study can serve not only serve as a guide in national parks but also in the management of nearby forest green areas to formulate a plan to repair and improve dulegil. Further, the sentiment analysis used in this study is meaningful in that it can continuously monitor actual users' responses towards natural areas. However, since it was evaluated based on a predefined sentiment dictionary, continuous updates are needed. Additionally, since there is a tendency to share positive content rather than negative views due to the nature of social media, it is necessary to compare and review the results of analysis, such as with on-site surveys.
Objectives: Brain maturation involves brain lateralization and asymmetry to achieve efficient information processing and cognitive controls. This study elucidates normal brain maturation change during the gap between ages 6-9 and age 14-17 using resting EEG. Methods: An EEG dataset was acquired from open source MIPDB (Multimodal Resource for Studying Information Processing in the Developing Brain). Ages 6-9 (n = 24) and ages 14-17 (n = 26) were selected for analysis, and subjects with psychiatric illness or EEG with severe noise were excluded. Finally, ages 6-9 (n = 14) and ages 14-17 (n = 11) were subjected to EEG analysis using EEGlab. A 120-sec length of resting EEG when eyes were closed was secured for analysis. Brain topography was compartmentalized into nine regions, best fitted with brain anatomical structure. Results: Absolute power of the delta band and theta band in ages 6-9 was greater than that of ages 14-17 in the whole brain, and, also is relative power of delta band in frontal compartment, which is same line with previous studies. The relative power of the beta band of ages 14-17 was greater than that of ages 6-9 in the whole brain. In asymmetry evaluation, relative power of the theta band in ages 14-17 showed greater power in the left than right frontal compartment; the opposite finding was noted in the parietal compartment. For the alpha band, a strong relative power distribution in the left parietal compartment was observed in ages 14-17. Absolute and relative power of the alpha band is distributed with hemispheric left lateralization in ages 14-17. Conclusion: During the gap period between ages 6-9 and ages 14-17, brain work becomes more complicated and sophisticated, and alpha band and beta band plays important roles in brain maturation in typically developing children.
Compact Advanced Satellite 500-4 (CAS500-4), which is scheduled to be launched in 2025, is a mid-resolution satellite with a 5 m resolution developed for wide-area agriculture and forest observation. To utilize satellite images, it is important to establish a precision sensor model and establish accurate geometric information. Previous research reported that a precision sensor model could be automatically established through the process of matching ground control point (GCP) chips and satellite images. Therefore, to improve the geometric accuracy of satellite images, it is necessary to improve the GCP chip matching performance. This paper proposes an improved GCP chip matching scheme for improved precision sensor modeling of mid-resolution satellite images. When using high-resolution GCP chips for matching against mid-resolution satellite images, there are two major issues: handling the resolution difference between GCP chips and satellite images and finding the optimal quantity of GCP chips. To solve these issues, this study compared and analyzed chip matching performances according to various satellite image upsampling factors and various number of chips. RapidEye images with a resolution of 5m were used as mid-resolution satellite images. GCP chips were prepared from aerial orthographic images with a resolution of 0.25 m and satellite orthogonal images with a resolution of 0.5 m. Accuracy analysis was performed using manually extracted reference points. Experiment results show that upsampling factor of two and three significantly improved sensor model accuracy. They also show that the accuracy was maintained with reduced number of GCP chips of around 100. The results of the study confirmed the possibility of applying high-resolution GCP chips for automated precision sensor modeling of mid-resolution satellite images with improved accuracy. It is expected that the results of this study can be used to establish a precise sensor model for CAS500-4.
Park, Eun-Ji;Kim, Nam Young;Park, So-Ra;Lee, Jung Mi;Jung, Yong Hyun;Yoon, Hae Jung
Journal of Food Hygiene and Safety
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v.37
no.3
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pp.136-142
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2022
The research aims to develop a rapid and easy analytical method for methoprene using liquid chromatography-tandem mass spectrometry (LC-MS/MS). A simple, highly sensitive, and specific analytical method for the determination of methoprene in livestock products (beef, pork, chicken, milk, eggs, and fat) was developed. Methoprene was effectively extracted with 1% acetic acid in acetonitrile and acetone (1:1), followed by the addition of anhydrous magnesium sulfate (MgSO4) and anhydrous sodium acetate. Subsequently, the lipids in the livestock sample were extracted by freezing them at -20℃. The extracts were cleaned using MgSO4, primary secondary amine (PSA), and octadecyl (C18), which were then centrifuged to separate the supernatant. Nitrogen gas was used to evaporate the supernatant, which was then dissolved in methanol. The matrix-matched calibration curves were constructed using 8 levels (1, 2.5, 5, 10, 25, 50, 100, 150 ng/mL) and the coefficient of determination (R2) was above 0.9964. Average recoveries spiked at three levels (0.01, 0.1, and 0.5 mg/kg), and ranged from 79.5-105.1%, with relative standard deviations (RSDs) smaller than 14.2%, as required by the Codex guideline (CODEX CAC/GL 40). This study could be useful for residue safety management in livestock products.
Purpose: Usefulness of mouse liver S9 fraction was evaluated for the measurement of the metabolites in the in vitro metabolism study of $^{18}F$-labeled radiotracers. Materials and Methods: Mouse liver S9 fraction was isolated at au early step in the course of microsome preparation. The in vitro metabolism studies were tarried out by incubating a mixture containing the radiotracer, S9 fraction and NADPH at $37^{\ciirc}C$, and an aliquot of the mixture was analyzed at the indicated time points by radio-TLC. Metabolic defluorination was further confirmed by the incubation with calcium phosphate, a bone mimic. Results: The radiotracer $[^{18}F]1$ underwent metabolic defluorination within 15 min, which was consistent with the results of the in vivo method and the in vitro method using microsome. Radiotracer $[^{18}F]2$ was metabolized to three metabolites including $4-[^{18}F]fluorobenzoic$ acid within 60 min. It is likely that the one of these metabolites at the origin of radio-TLC was identical with the one that obtained from the in vivo and in vitro (microsome) method. Compared with the in vitro method using microsome, the method using S9 fraction gave a similar pattern of the metabolites but with a different ratio, which can be explained by the presence of cytosol in the S9 fraction. Conclusion: These results suggest that the findings of the in vitro metabolism studies using S9 fraction can reflect the in vivo metabolism of novel radiotracers in the liver. Moreover, this method can be used as a tool to determine metabolic defluorination along with calcium phosphate absorption method.
Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.
The reactive intermediates formed during the metabolism of therapeutic agents, toxicants and carcinogens by cytochromes P450 are frequently capable of covalently binding to tissue macromolecules and causing tissue damage. It has been shown that YH439, a congener of malotilate, is effective in suppressing hepatic P450 2E1 expression. The present study was designed to further establish the mechanistic basis of YH439 protection against toxicant by assessing its effects against chemical-mediated potentiated hepatotoxicity. Retinoyl palmitate (Vit-A) pretreatment of rats for 7 days substantially enhanced carbon tetrachloride hepatotoxicity, as supported by an ${\sim}5-fold$ increase in serum alanine aminotransferase (ALT) activity, as compared to $CCl_4$ treatment alone. The elevation of ALT activity due to Vit-A was completely blocked by the treatment of $GdCl_3$ a selective inhibitor of Kupffer cell activity. Concomitant pretreatment of rats with both YH439 and Vit-A resulted in a 94% decrease in Vit-A-potentiated $CCl_4$ hepatotoxicity. YH439 was also effective against propyl sulfide-potentiated $CCl_4-induced$ hepatotoxicity. Whereas propyl sulfide (50 mg/kg, 7d) enhanced $CCl_4-induced$ hepatotoxicity by >5-fold, relative to $CCl_4$ treatment alone, concomitant treatment of animals with both propyl sulfide and YH439 at the doses of 100 and 200 mg/kg prevented propyl sulfide-potentiated $CCl_4$ hepatotoxicity by 35% and 90%, respectively. Allyl sulfide, a suppressant of hepatic P450 2E1 expression, completely blocked the propyl sulfide-enhanced hepatotoxicity, indicating that propyl sulfide potentiation of $CCl_4$ hepatotoxicity was highly associated with the expression of P450 2E1 and that YH439 blocked the propyl sulfide-enhanced hepatotoxicity through modulation of P450 2E1 levels. Propyl sulfide- and $CCl_4-induced$ stimulation of lipid peroxidation was also suppressed by YH439 in a dose-related manner, as supported by decreases in malonedialdehyde production. The role of P450 2E1 induction in the potentiation of $CCl_4$ toxicity and the effects of YH439 were further evaluated using pyridine as a P450 2E1 inducer. Pyridine pretreatment substantially enhanced the $CCl_4$ hepatotoicity by 23-fold, relative to $CCl_4$ alone. YH439, however, failed to reduce the pyridine-potentiated toxicity, suggesting that the other form(s) of cytochroms P450 inducible by pyridine, but not suppressible by YH439 treatment, may play a role in potentiating $CCl_4-induced$ hepatotoxicity. YH439 was capable of blocking cadmium chloride-induced liver toxicity in mice. These results demonstrated that YH439 efficiently blocks Vit-A-enhanced hepatotoxiciy through Kupffer cell inactivation and that the suppression of P450 2E1 expression by YH439 is highly associated with blocking of propyl sulfide-mediated hepatotoxicity.
1. Introduction: Contrast to the offline purchasing environment, online store cannot offer the sense of touch or direct visual information of its product to the consumers. So the builder of the online shopping mall should provide more concrete and detailed product information(Kim 2008), and Alba (1997) also predicted that the quality of the offered information is determined by the post-purchase consumer satisfaction. In practice, many fashion and apparel online shopping malls offer the picture information with the product on the real person model to enhance the usefulness of product information. On the other virtual product experience has been suggested to the ways of overcoming the online consumers' limited perceptual capability (Jiang & Benbasat 2005). However, the adoption and the facilitation of the virtual reality tools requires high investment and technical specialty compared to the text/picture product information offerings (Shaffer 2006). This could make the entry barrier to the online shopping to the small retailers and sometimes it could be demanding high level of consumers' perceptual efforts. So the expensive technological solution could affects negatively to the consumer decision making processes. Nevertheless, most of the previous research on the online product information provision suggests the VR be the more effective tools. 2. Research Model and Hypothesis: Presented in
, research model suggests VR effect could be moderated by the product types by the usage situations. Product types could be defined as the portable product and installed product, and the information offering type as still picture of the product, picture of the product with the real-person model and VR. 3. Methods and Results: 3.1. Experimental design and measured variables We designed the 2(product types) X 3(product information types) experimental setting and measured dependent variables such as information usefulness, attitude toward the shopping mall, overall product quality, purchase intention and the revisiting intention. In the case of information usefulness and attitude toward the shopping mall were measured by multi-item scale. As a result of reliability test, Cronbach's Alpha value of each variable shows more than 0.6. Thus, we ensured that the internal consistency of items. 3.2. Manipulation check The main concern of this study is to verify the moderate effect by the product type of usage situation.
indicates that our experimental manipulation of the moderate effect of the product type was successful. 3.3. Results As
indicates, there was a significant main effect on the only one dependent variable(attitude toward the shopping mall) by the information types. As predicted, VR has highest mean value compared to other information types. Thus, H1 was partially supported. However, main effect by the product types was not found. To evaluate H2 and H3, a two-way ANOVA was conducted. As
indicates, there exist the interaction effects on the three dependent variables(information usefulness, overall product quality and purchase intention) by the information types and the product types. As predicted, picture of the product with the real-person model has highest mean among the information types in the case of portable product. On the other hand, VR has highest mean among the information types in the case of installed product. Thus, H2 and H3 was supported. 4. Implications: The present study found the moderate effect by the product type of usage situation. Based on the findings the following managerial implications are asserted. First, it was found that information types are affect only the attitude toward the shopping mall. The meaning of this finding is that VR effects are not enough to understand the product itself. Therefore, we must consider when and how to use this VR tools. Second, it was found that there exist the interaction effects on the information usefulness, overall product quality and purchase intention. This finding suggests that consideration of usage situation helps consumer's understanding of product and promotes their purchase intention. In conclusion, not only product attributes but also product usage situations must be fully considered by the online retailers when they want to meet the needs of consumers.
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