• Journal of Life Science
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• v.26 no.8
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• pp.936-942
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• 2016

As the incidence of environmental diseases is increasing due to harmful environmental factors, there is a rising interest in developing eco-friendly materials for housing. In this study, we sought to develop antimicrobial interior fabric blind materials by employing ethanol extract of a medicinal plant Zanthoxylum piperitum DC. As determined by the disc diffusion method, the zones of inhibition of the pericarp ethanol extract at a concentration of 5 mg/disc against Klebsiella pneumoniae, Staphylococcus aureus, and Streptococcus mutans were 13.5±1.5 mm, 14.0±0.5 mm and 15.0±0.1 mm, respectively, whereas the leaf ethanol extract (5 mg/disc) against K. pneumoniae, S. aureus, and S. mutans were 12.8± 0.3 mm, 13.5±1.0 mm, and 12.0±0.1 mm, respectively. The IC₅₀ of the leaf ethanol extract against K. pneumoniae, S. aureus and S. mutans were about 0.5 mg/ml, 0.1 mg/ml and 1.0 mg/ml respectively. To examine whether the leaf ethanol extract possessing antibacterial activity of Z. piperitum DC can be applicable to production of antimicrobial fabric blind materials, the fabrics treated with either 1.0% or 2.0% of the leaf ethanol extract were tested for antibacterial activity against K. pneumoniae and S. aureus using International Standard Fabrics Test Method. The results indicate that the fabric treated with the ethanol extract of Z. piperitum DC possesses an excellent antimicrobial activity against both pathogenic bacteria. These results suggest that Z. piperitum DC may be applicable to producing functional fabrics which are effective in reducing the harmful bacterial factors in indoor environments.

• 대한공업교육학회지
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• v.41 no.1
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• pp.68-87
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• 2016

This research conducted a survey for total 166 teachers of schools so as to analyze validity and satisfaction for performance objectives of SMB administration subsidy the HRDP and the CEP in Specialized High School. The results of research are as follows. First, teachers recognize that purpose of HRDP is to expand employment of specialized high school and provide human resource of SMB. And, they recognize that HRDP is important to improve school outcomes and makes a positive effect on the improvement of school outcomes. Second, teachers recognize that objectives of HRDP are improvement of student's understanding for SMB, improvement of teacher's understanding for SMB, improvement of SMB's understanding of school, cultivation of student's occupational view, systematization of career guiding program based on employment process, strengthening of industry-academia cooperation education, improvement of the level of student's skill, fulfillment of workplace experience and practice focusing workplace learning, training of customized human resource for SMB, improvement of student's adaptation to the workplace, improvement of employment rate for SMB, expansion of job opportunities for students with SMB, preparation of the base of connection between school and SMB, publicity of school, expansion of opportunities to cooperate between SMB and school, establishment of cooperative system among industrial association and school, introduction and operation of the employment connective model for joint education and employment, strengthening of field professionalism of teachers. However, satisfaction for the achievement of objectives of HRDP except for strengthening of industry-academia cooperation education and improvement of employment rate for SMB is relatively lower than the validity. Third, teachers in charge of human resource training business of middle and small sized company's specialized high school recognize that objectives of CEP are expansion of job opportunities for students with SMB, excavation of good-quality SMB, expansion of opportunities to cooperate between SMB and school, fulfillment of workplace learning, improvement of student's major foundation and in-depth skill, improvement of literacy, math, teamwork and communication abilities for students' job performance, improvement of student's working attitude and student's proper career exploration decision. However, satisfaction for achievement of objectives of CEP is relatively lower than the validity.

• Journal of Life Science
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• v.31 no.12
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• pp.1079-1087
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• 2021

To analyze gut microbiota of livestock in Korea and compare taxonomic differences, we conducted 16S rRNA metagenomic analysis through next-generation sequencing. Fecal samples from broiler chickens, pigs, and cattle were collected from domestic feedlots randomly. α-diversity results showed that significant differences in estimated species richness estimates (Chao1 and ACE, Abundance-based coverage estimators) and species richness index (OUTs, Operational taxonomic units) were identified among the three groups. However, NPShannon, Shannon, and Simpson indices revealed that abundance and evenness of the species were statistically significant only for poultry (broiler chickens) and mammals (pigs and cattle). Firmicutes was the most predominant phylum in the three groups of fecal samples. Linear discriminant (LDA) effect size (LEfSe) analysis was conducted to reveal the ranking order of abundant taxa in each of the fecal samples. A size-effect over 2.0 on the logarithmic LDA score was used as a discriminative functional biomarker. As shown by the fecal analysis at the genus level, broiler chickens were characterized by the presence of Weissella and Lactobacillus, as well as pigs were characterized by the presence of provetella and cattele were characterized by the presence of Acinetobacter. A permutational multivariate analysis of variance (PERMANOVA) showed that differences of microbial clusters among three groups were significant at the confidence level. (p=0.001). This study provides basic data that could be useful in future research on microorganisms associated with performance growth, as well as in studies on the livestock gut microbiome to increase productivity in the domestic livestock industry.

• Journal of Life Science
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• v.33 no.9
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• pp.713-723
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• 2023

Lung cancer is a type of cancer that has the highest mortality rate. It is mainly classified into small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC). Chemotherapy is used to treat lung cancer, but long-term treatment causes side effects and drug resistances. Curcumin is a bright yellow polyphenol extracted from the root of turmeric. It has biological activities, such as anti-oxidant, anti-cancer, and anti-inflammatory effects. In this study, we observed differential cell death in human lung cancer cells. Based on the results, curcumin at 10, 30, and 50 μM exhibited a dose-dependent inhibition on the cell survival of several lung cancer cells, with minor differential phenotypes. In addition, apoptosis, autophagy, and reactive oxygen species (ROS) regeneration were observed through flow cytometry. Curcumin dose-dependently increased these phenotypes in A549 (NSCLC) and DMS53 (SCLC), which were restored by corresponding inhibitors. Western blotting was performed to measure the level of expression of apoptosis- and autophagy-related proteins. The results indicate that Bax, PARP, pro-caspase-3, and Bcl-2 were dose-dependently regulated by curcumin, with seemingly higher Bax/Bcl-2 ratios in DMS53. In addition, autophagic proteins, p-AKT, p62, and LC3B, were dose-dependently regulated by curcumin. ROS inhibition by diphenyleneiodonium reduced the induction of apoptosis and autophagy generated by curcumin. Taken together, it is suggested that curcumin induces apoptosis and autophagy via ROS generation, leading to cell death, with minor differences between human lung cancer cells.

• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.149-160
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• 2023

This study develops a time-varying system-based noncontact fabric sensor that can measure cerebral blood-flow signals to explore the possibility of brain blood-signal detection and emotional evaluation. The textile sensor was implemented as a coil-type sensor by combining 30 silver threads of 40 deniers and then embroidering it with the computer machine. For the cerebral blood-flow measurement experiment, subjects were asked to attach a coil-type sensor to the carotid artery area, wear an electrocardiogram (ECG) electrode and a respiration (RSP) measurement belt. In addition, Doppler ultrasonography was performed using an ultrasonic diagnostic device to measure the speed of blood flow. The subject was asked to wear Meta Quest 2, measure the blood-flow change signal when viewing the manipulated image visual stimulus, and fill out an emotional-evaluation questionnaire. The measurement results show that the textile-sensor-measured signal also changes with a change in the blood-flow rate signal measured using the Doppler ultrasonography. These findings verify that the cerebral blood-flow signal can be measured using a coil-type textile sensor. In addition, the HRV extracted from ECG and PLL signals (textile sensor signals) are calculated and compared for emotional evaluation. The comparison results show that for the change in the ratio because of the activation of the sympathetic and parasympathetic nervous systems due to visual stimulation, the values calculated using the textile sensor and ECG signals tend to be similar. In conclusion, a the proposed time-varying system-based coil-type textile sensor can be used to study changes in the cerebral blood flow and monitor emotions.

• Education of Primary School Mathematics
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• v.27 no.2
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• pp.111-137
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• 2024

The purpose of this study is to identify the expected difficulties and necessary support when applying the 2022 revised mathematics curriculum to elementary schools, and to support the establishment of the field. To this end, we explored the major changes in the 2022 revised mathematics curriculum, and based on this, we conducted a survey of elementary school teachers to identify the expected difficulties and necessary support when applying it in the field. In particular, when analyzing the results, we also examined whether there were any differences in the expected difficulties and necessary support depending on the size of the school where it is located and the teaching experience of the teacher. The research results are as follows. First, the proportion of teachers who expect difficulties in applying the 2022 revised mathematics curriculum was mostly below 50%, but the proportion of teachers who demand support was much higher, at around 80%. Second, the difficulty of elementary school teachers in applying the 2022 revised mathematics curriculum was found to be the greatest in evaluation. Third, in relation to the use of edutech, teachers in elementary schools are also expected to have difficulties in teaching and learning methods to foster students' digital literacy, assessment using teaching materials or engineering tools, and assessment in online environments. Fourth, the difficulty of elementary school teachers in applying the 2022 revised mathematics curriculum was also significant in relation to mathematics subject competencies. Fifth, it was found that there is also difficulty in understanding the major changes of the achievement standards, including the addition, deletion, and adjustment of the achievement standards, and the impact on the learning of other achievement standards. Finally, the responses of elementary school teachers to the expected difficulties and necessary support in applying the 2022 revised mathematics curriculum did not differ depending on the size of the school where it is located, but statistically significant differences were found in a number of items depending on the teaching experience of the teacher. Based on these research results, we hope that various support will be provided for the 2022 revised mathematics curriculum, which will be applied annually from 2024.

• Journal of agricultural medicine and community health
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• v.49 no.1
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• pp.37-49
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• 2024

Objectives: This study aimed to explore whether there are differences in smoking status between two regions of Wonju-City and Chuncheon-City, Gangwon State, and to determine whether the experience of smoking cessation programs in the region affects quit attempts. Methods: The study design was a cross-sectional study in which adults aged 19 and older living in two cities were surveyed using a pre-developed mobile app to investigate social capital for smoking cessation, and a total of 600 citizens were participated, including 310 in Wonju-City and 290 in Chuncheon-City. The statistical analysis was conducted using chi-square test and logistic regression analysis. Results: Wonju-City had a higher prevalence of current smoking than Chuncheon-City. Among smoking cessation programs operated by local public health centers, Wonju-City had a lower odds ratio for experience with smoking cessation education than Chuncheon-City (OR=0.52, 95% CI=0.33 to 0.81). When examining the effect of smoking cessation program experience on quit attempts, in Wonju-City, citizens who had completed smoking cessation education and used a smoking cessation clinic were more likely to attempt to quit than those who had not (OR=2.31 and OR=2.29, respectively). In Chuncheon-City, citizens who were aware of smoking cessation support services were 2.26 times more likely to attempt to quit smoking than those who were not, but statistical significance was not reached due to the small sample size. Conclusion: Therefore, healthcare organizations in both regions should develop more practical intervention strategies to increase smokers' quit attempts, reduce smoking rates in the community, and address regional disparities.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• Korean Journal of Environmental Biology
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• v.39 no.1
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• pp.119-135
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• 2021

Korea has stepped up efforts to investigate and catalog its flora and fauna to conserve the biodiversity of the Korean Peninsula and secure biological resources since the ratification of the Convention on Biological Diversity (CBD) in 1992 and the Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits (ABS) in 2010. Thus, after its establishment in 2007, the National Institute of Biological Resources (NIBR) of the Ministry of Environment of Korea initiated a project called the Korean Indigenous Species Investigation Project to investigate indigenous species on the Korean Peninsula. For 15 years since its beginning in 2006, this project has been carried out in five phases, Phase 1 from 2006-2008, Phase 2 from 2009-2011, Phase 3 from 2012-2014, Phase 4 from 2015-2017, and Phase 5 from 2018-2020. Before this project, in 2006, the number of indigenous species surveyed was 29,916. The figure was cumulatively aggregated at the end of each phase as 33,253 species for Phase 1 (2008), 38,011 species for Phase 2 (2011), 42,756 species for Phase 3 (2014), 49,027 species for Phase 4 (2017), and 54,428 species for Phase 5(2020). The number of indigenous species surveyed grew rapidly, showing an approximately 1.8-fold increase as the project progressed. These statistics showed an annual average of 2,320 newly recorded species during the project period. Among the recorded species, a total of 5,242 new species were reported in scientific publications, a great scientific achievement. During this project period, newly recorded species on the Korean Peninsula were identified using the recent taxonomic classifications as follows: 4,440 insect species (including 988 new species), 4,333 invertebrate species except for insects (including 1,492 new species), 98 vertebrate species (fish) (including nine new species), 309 plant species (including 176 vascular plant species, 133 bryophyte species, and 39 new species), 1,916 algae species (including 178 new species), 1,716 fungi and lichen species(including 309 new species), and 4,812 prokaryotic species (including 2,226 new species). The number of collected biological specimens in each phase was aggregated as follows: 247,226 for Phase 1 (2008), 207,827 for Phase 2 (2011), 287,133 for Phase 3 (2014), 244,920 for Phase 4(2017), and 144,333 for Phase 5(2020). A total of 1,131,439 specimens were obtained with an annual average of 75,429. More specifically, 281,054 insect specimens, 194,667 invertebrate specimens (except for insects), 40,100 fish specimens, 378,251 plant specimens, 140,490 algae specimens, 61,695 fungi specimens, and 35,182 prokaryotic specimens were collected. The cumulative number of researchers, which were nearly all professional taxonomists and graduate students majoring in taxonomy across the country, involved in this project was around 5,000, with an annual average of 395. The number of researchers/assistant researchers or mainly graduate students participating in Phase 1 was 597/268; 522/191 in Phase 2; 939/292 in Phase 3; 575/852 in Phase 4; and 601/1,097 in Phase 5. During this project period, 3,488 papers were published in major scientific journals. Of these, 2,320 papers were published in domestic journals and 1,168 papers were published in Science Citation Index(SCI) journals. During the project period, a total of 83.3 billion won (annual average of 5.5 billion won) or approximately US $75 million (annual average of US $5 million) was invested in investigating indigenous species and collecting specimens. This project was a large-scale research study led by the Korean government. It is considered to be a successful example of Korea's compressed development as it attracted almost all of the taxonomists in Korea and made remarkable achievements with a massive budget in a short time. The results from this project led to the National List of Species of Korea, where all species were organized by taxonomic classification. Information regarding the National List of Species of Korea is available to experts, students, and the general public (https://species.nibr.go.kr/index.do). The information, including descriptions, DNA sequences, habitats, distributions, ecological aspects, images, and multimedia, has been digitized, making contributions to scientific advancement in research fields such as phylogenetics and evolution. The species information also serves as a basis for projects aimed at species distribution and biological monitoring such as climate-sensitive biological indicator species. Moreover, the species information helps bio-industries search for useful biological resources. The most meaningful achievement of this project can be in providing support for nurturing young taxonomists like graduate students. This project has continued for the past 15 years and is still ongoing. Efforts to address issues, including species misidentification and invalid synonyms, still have to be made to enhance taxonomic research. Research needs to be conducted to investigate another 50,000 species out of the estimated 100,000 indigenous species on the Korean Peninsula.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.6
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• pp.185-196
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(Quality of Service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to let only the minimum number of servers needed to handle current user requests ON. Previous studies on energy aware server cluster put efforts to reduce power consumption further or to keep QoS, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management based on autonomous learning for energy aware server clusters. Using parameters optimized through autonomous learning, our method adjusts server power mode to achieve maximum performance with respect to power consumption. Our method repeats the following procedure for adjusting the power modes of servers. Firstly, according to the current load and traffic pattern, it classifies current workload pattern type in a predetermined way. Secondly, it searches learning table to check whether learning has been performed for the classified workload pattern type in the past. If yes, it uses the already-stored parameters. Otherwise, it performs learning for the classified workload pattern type to find the best parameters in terms of energy efficiency and stores the optimized parameters. Thirdly, it adjusts server power mode with the parameters. We implemented the proposed method and performed experiments with a cluster of 16 servers using three different kinds of load patterns. Experimental results show that the proposed method is better than the existing methods in terms of energy efficiency: the numbers of good response per unit power consumed in the proposed method are 99.8%, 107.5% and 141.8% of those in the existing static method, 102.0%, 107.0% and 106.8% of those in the existing prediction method for banking load pattern, real load pattern, and virtual load pattern, respectively.