• 대한본초학회지
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• 제33권4호
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• pp.77-85
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• 2018

Objective : This study was intended to examine the effects of water extract of Prunellae Spica (PS), which is a herb with 'cold' nature based on hot and cold theory of traditional Korean medicine. Methods : Hyperthyroidism was induced in SD rats by LT4 (0.5 mg/kg, i.p.) daily for four weeks. After 2 weeks of LT4 injection, rats were divided randomly into four groups; normal, LT4-induced hyperthyroid control, PS extract (500 mg/kg, p.o.)-treated group, and propylthiouracil (PTU, 10 mg/kg, s.c.)-treated positive group. After 2 weeks of drug treatment, all rats were sacrificed and harvested blood samples and thyroid tissues. The changes of body weight, food and water intake, and body temperature were measured weekly. Serological markers were analyzed in sera using an enzyme-based assay, and thyroid tissues were stained with Hematoxylin & Eosin (H&E). Brain and dorsal root ganglion (DRG) tissues were isolated and analyzed the expression of transient receptor potential (TRP) channels by Western blot. Results : PS extract administration attenuated the loss of body weight and the increase of body temperature in LT4-induced hyperthyroidism rats. PS extract increased the level of thyroid stimulating hormone (TSH) and decreased tiiodothyronine (T3) and tetraiodothyronine (T4). In action mechanism, PS extract regulated the expression of transient receptor potential channel subfamily V member 1 (TRPV1) and transient Receptor Potential channel subfamily M member 8 (TRPM8), the thermoregulators. Conclusion : To conclude, PS extract can improve the symptoms of hyperthyroidism through regulation of the thyroid hormones imbalance and thermoregulation via TRP channels.

• Journal of Acupuncture Research
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• 제30권3호
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• pp.39-49
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• 2013

Objectives : The purpose of this study is to assess the effect of Taegeuk acupuncture on reducing mental stress by analyzing heart rate variability in Soeumin. Methods : Six Soeumin-diagnosed men participated in this study. They were randomly divided into group A and group B. Each participant went through 4 sessions every week with 1 week of washout period in between each session. HRV was measured three times at every session; at baseline, after administering mentally stressful circumstances and after applying Soeumin Taegeuk acupuncture or Soyangin Taegeuk acupuncture. This study was designed as a crossover clinical trial. Group A participants were treated with two sets of Soeumin Taegeuk and Soyangin Taegeuk acupuncture treatment in respective order (i.e. Soeumin Taegeuk - Soyangin Taegeuk - Soeumin Taegeuk - Soyangin Taegeuk acupuncture treatment). Group B participants were treated with reverse-ordered acupuncture treatment (i.e. Soyangin Taegeuk - Soeumin Taegeuk - Soyangin Taegeuk - Soeumin Taegeuk acupuncture treatment ). Bayesian analysis was performed by using WinBUGS(Ver. 1.4.3) for comparison between Soeumin Taegeuk acupuncture and Soyangin Taegeuk acupuncture. Results : Overall, Soeumin Taegeuk acupuncture tends to reduce LF/HF ratio, LF, HF, LF(Norm) and increase HF(Norm) more than Soyangin Taegeuk acupuncture, but the difference was not statistically significant. In one participant, however, Soeumin Taegeuk acupuncture reduced LF/HF ratio, LF(Norm) and increased HF(Norm) more than Soyangin Taegeuk acupuncture, and the difference was stastatistically significant. Conclusions : This study suggests that Soeumin Taegeuk acupuncture might be an effective means of stabilizing mental stress-induced imbalance of autonomic nervous system for Soeumin.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권3호
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• pp.830-860
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• 2022

[Introduction] Nowadays, many companies are shifting their businesses online due to the growing trend among customers to buy and shop online, as people prefer online purchasing products. [Problem] Users share a vast amount of information about products, making it difficult and challenging for the end-users to make certain decisions. [Motivation] Therefore, we need a mechanism to automatically analyze end-user opinions, thoughts, or feelings in the social media platform about the products that might be useful for the customers to make or change their decisions about buying or purchasing specific products. [Proposed Solution] For this purpose, we proposed an automated SentiDecpective approach, which classifies end-user reviews into negative, positive, and neutral sentiments and identifies deceptive crowd-users rating information in the social media platform to help the user in decision-making. [Methodology] For this purpose, we first collected 11781 end-users comments from the Amazon store and Flipkart web application covering distant products, such as watches, mobile, shoes, clothes, and perfumes. Next, we develop a coding guideline used as a base for the comments annotation process. We then applied the content analysis approach and existing VADER library to annotate the end-user comments in the data set with the identified codes, which results in a labelled data set used as an input to the machine learning classifiers. Finally, we applied the sentiment analysis approach to identify the end-users opinions and overcome the deceptive rating information in the social media platforms by first preprocessing the input data to remove the irrelevant (stop words, special characters, etc.) data from the dataset, employing two standard resampling approaches to balance the data set, i-e, oversampling, and under-sampling, extract different features (TF-IDF and BOW) from the textual data in the data set and then train & test the machine learning algorithms by applying a standard cross-validation approach (KFold and Shuffle Split). [Results/Outcomes] Furthermore, to support our research study, we developed an automated tool that automatically analyzes each customer feedback and displays the collective sentiments of customers about a specific product with the help of a graph, which helps customers to make certain decisions. In a nutshell, our proposed sentiments approach produces good results when identifying the customer sentiments from the online user feedbacks, i-e, obtained an average 94.01% precision, 93.69% recall, and 93.81% F-measure value for classifying positive sentiments.

• 한국IT서비스학회지
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• 제19권1호
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• pp.103-112
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• 2020

Job seekers are making various efforts to find a good company and companies attempt to recruit good people. Job search activities through self-introduction essay are nowadays one of the most active processes. Companies spend time and cost to reviewing all of the numerous self-introduction essays of job seekers. Job seekers are also worried about the possibility of acceptance of their self-introduction essays by companies. This research builds a classification model and conducted an experiments to classify self-introduction essays into pass or fail using deep learning and decision tree techniques. Real world data were classified using stratified sampling to alleviate the data imbalance problem between passed self-introduction essays and failed essays. Documents were embedded using Doc2Vec method developed from existing Word2Vec, and they were classified using logistic regression analysis. The decision tree model was chosen as a benchmark model, and K-fold cross-validation was conducted for the performance evaluation. As a result of several experiments, the area under curve (AUC) value of PV-DM results better than that of other models of Doc2Vec, i.e., PV-DBOW and Concatenate. Furthmore PV-DM classifies passed essays as well as failed essays, while PV_DBOW can not classify passed essays even though it classifies well failed essays. In addition, the classification performance of the logistic regression model embedded using the PV-DM model is better than the decision tree-based classification model. The implication of the experimental results is that company can reduce the cost of recruiting good d job seekers. In addition, our suggested model can help job candidates for pre-evaluating their self-introduction essays.

• 한국연소학회:학술대회논문집
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• 한국연소학회 2002년도 제24회 KOSCO SYMPOSIUM 논문집
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• pp.85-94
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• 2002

Computational flow dynamics(CFD) has been frequently applied to the waste incinerators to understand the flow performance for various design and operating parameters. Though it needs many simplifications and complicated flow models, the reasonability of its results is not fully evaluated. For example, the inlet condition is calculated from an arbitrarily assumed properties of combustion gas release from the waste bed, since the combustion in the bed is difficult to be predicted. In this study, the computational modeling and calculation procedures of CFD for the grate type waste incinerator were evaluated using comparative simulations. Though the assumption method on the generation of the combustion gas directly affected the temperature and gas species concentrations, the overall flow pattern was dominated by the secondary air jets. The gaseous reaction could be included by assuming the release of the products of incomplete combusion from the bed. However, the reaction effficiency cannot not be directly evaluated from the species concentration, since it is not possible to simulate the actual co-existence of fuel rich or oxygen rich puffs over the bed. In predicting the turbulence, the higher order model, such as Reynolds stress model, gave difference shape of local recirculation zones, but similar results was acquired from the standard $k-{\varepsilon}$ model. Introducing radiation model was required for accurate temperature prediction, but it also caused heat imbalance due to the fixed temperature of the inlet, i.e. the waste bed. Thus, the computational modeling procedures on incinerators and the analysis of the predicted results should be progressed carefully. Though not validated experimentally, current simulation method is capable of comparative evaluation on the flow-related parameters such as the furnace shape and secondary air injection using identical inlet conditions. Quantitative analysis using measures of the residence time and mixing is essential to compare the flow performance efficiently.

• 조명전기설비학회논문지
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• 제18권6호
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• pp.220-229
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• 2004

전기 철도계통은 기존 전력계통과 달리 단상, 대용량 부하로 필연적으로 전압강하, 전압불평형 및 고조파 왜곡 등의 전력품질의 문제가 발생한다. 최근 철도계통의 전력품질문제는 철도차량 및 시스템의 제어 및 안전 때문에 중요한 화두가 되고 있다. 이는 또한 기존 전력계통의 전력품질에도 영향을 미친다 본 논문에서는 전기철도 급전시스템에 발생하는 전력품질문제의 보상에 관한 연구를 수행하고자 한다. 이를 위해 국내 교류전기철도 표준 급전방식인 AT(Auto Transformer)급전시스템, 철도급전변압기인 스콧트 변압기(Scott Transformer), AT변압기, 철도선로 및 철도 차량부하를 모델링 하였다. 과도응답은 전자기과도해석 프로그램인 PSCAD/EMTDC를 사용하여 해석 하였다. 또한 전력품질을 보상하기위한 방안으로 급전선-전차선에 설치되는 전력품질보상기(Unified Power Quality Conditioner : UPQC)를 제안하였고 이의 성능 및 유효성을 시뮬레이션을 통하여 확인하였다.

• 셀메드
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• 제11권3호
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• pp.16.1-16.7
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• 2021

Cancer is an abnormal growth of cells in body which leads to death. These cells are born due to imbalance in cell proliferation mechanism. In 2018, WHO released new statistics on cancer incidence, mortality, and prevalence worldwide i.e., GLOBOCAN 2018 estimates for 28 types of cancer in which more prevalence of cervix and breast cancer. According to survey, in India about 7.8 million cancer deaths and 11.5 million new cases arise in 2018, which will increase to 19.3 million new cases per year by 2025. Though breast cancer as such is not explained anywhere in Ayurvedic compendia, correlations can be done with the Stana Arbuda. Ayurveda, the ancient system of medicine came into existence 1000's of years ago with an objective of maintaining the health of people and treating diseases. Many herbs used in Ayurveda have been screened for activity against cancer and in-vitro and in-vivo studies have given promising leads. The plant, called as "Mother of Medicine", Haritaki has been extensively studied for its various ailments because of its extraordinary healing potency. Haritaki (Terminalia chebula Retz.), Family: Combretaceae have a great therapeutic value and is widely distributed in India. Dried fruit of Terminalia chebula contains high quantities phenolic compounds consist of ellagic acid, gallic acid and chebulic acid. The fruit extract of T. chebula is having different biological properties like anticancer, antioxidant, hepatic and renal protective activities etc. In this study, we focus on the use of CO₂ extract of Terminalia chebula, on the breast cancer cell line MDA-MB-231. All tests proved that CO₂ extract of Terminalia chebula containing active chemical component, therefore our experiment showed the positive results for CO₂ extract of Terminalia chebula against breast cancer cell line cancer MDA-MB-231. The MTT assay results were used to evaluate the anti-cancer activity of the extract. The percentage of cell growth and cell viability were calculated from tabulated result values of MTT assay. Cell viability MTT assay also showed significant growth inhibition, at the same time statistical analysis of MTT assay also proved significant results.

• 산업경영시스템학회지
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• 제44권4호
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• pp.12-22
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• 2021

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F₁-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.

• 한국정보전자통신기술학회논문지
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• 제17권2호
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• pp.83-92
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• 2024

현재 여러 나라에서 생활 속에서 편리하게 자전거를 이용할 수 있도록 자전거 대여 서비스를 제공하며 접근성을 늘리고 있다. 본 논문에서는 우리나라의 창원시 공공자전거 누비자 서비스를 소개하고 누비자 자전거의 수요와 공급의 불균형을 방지하기 위한 최우선 재배치 방법을 제안하고자 한다. 무작위로 터미널을 방문하여 재배치하는 알고리즘과 현재 위치에서 가장 짧은 거리에 있는 터미널을 방문하여 재배치하는 알고리즘을 제안한 방법과 비교하여 더 효율적임을 설명한다. 본 논문에서 제시하는 최우선 재배치 방법은 주위 터미널 중 수요가 가장 높고 거리가 가장 짧은 터미널부터 방문한다. 본 논문에서는 실험을 통하여 제안한 최우선 재배치 방법이 트럭이 운행한 총 거리 평균 817.44km로 가장 낮은 비용을 보이고, 대여 성공 평균 횟수 6437.45회, 88.14%로 가장 높아 두 알고리즘보다 우수함을 보여준다.

• Journal of Animal Science and Technology
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• 제62권1호
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• pp.64-73
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• 2020

Producing animal products from farm to table emits massive amounts of greenhouse gases (GHGs). Modified meal plans, mainly including vegetables and grains, have been recommended to reduce GHG emissions. However, these meal plans have not been developed with regard to the micronutrient content, but rather with regard to the energy requirements of grains and vegetables, which could result in a nutritional imbalance. For this reason, we investigated a common Korean suggested meal plan (SMP) from the National Institute of Agricultural Sciences, in which nutritional conditions were considered, and evaluated its GHG emissions using the Life Cycle Assessment Inventory Database and nutritional values. The SMP, which included meat, was based on the Korean Nutrition Society for adult men age 19 to 29, and was changed to a vegan meal plan (VMP). Animal-based protein sources were substituted for meat alternatives, such as beans and tofu, for which carbon footprint data was available. To compare the nutritional differences, the 9^th Korean Food Composition Tables I and II were consulted. To calculate GHG emissions, the carbon footprint data of the food was converted to a CO₂ equivalent (CO₂e) using a procedure from the Foundation of Agriculture Technology Commercialization and Transfer. It was found that GHG emissions per calorie were 18% lower for the VMP when compared to the SMP. However, if GHG emissions per total amino acids were evaluated, the VMP GHG emissions per total amino acids were 0.12 g CO₂e/mg, while the corresponding value for the SMP was 0.06 g CO₂e/mg. The Korean daily meat intake reported by the Korea Agricultural Statistics Service was 37.1% lower than in the SMP, but when converted to a protein intake the figure was 17.0% lower. It was found that each SMP resulted in more GHG emissions than the VMP, but when considered as GHG emissions per total amino acids, the opposite pattern was apparent. There is a need to conduct more detailed studies of the variation in GHG emissions with different meal plans, using the daily meat intake per person.