• Title/Summary/Keyword: Sales Size

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A Study on the Analysis of the Torso and Breast of Female Students by Age (13-18세 여학생의 상반신과 젖가슴형태 연령별 분석연구)

  • Kim, Youn Joo;Nam, Yun Ja
    • Human Ecology Research
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    • v.57 no.2
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    • pp.159-170
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    • 2019
  • The growth accelerator period from a child's body into an adult body is a huge transition characterized by rapid growth in the near term. Body shape changes at this time of growth should be continually studied because they can result in different outcomes due to various variables. This study is basic study for the production of a junior brassiere patternmaking was conducted to separate the upper torso and breasts of adolescents by growth level. Analysis was conducted by age classification according to sales trends. In this study. 3D body shape data of Korean girls, Based on the 6th Size Korea data, analyzed statistically the upper body and breast according to the rate of growth. The results of this study represent the basis for the development of a junior brassiere to help lead a better life in regards to clothing. The study used 3D-data from girls aged 13 to 18. The analysis indicates that the upper body is in a different shape at age 15 with an increasing circumference, width and shoulder length of the chest; in addition, the sides are analyzed differently, suggesting that the brassiere configuration should be made differently at age 15. The breast form also showed different growth patterns at age 13 and the result was that the shape of the cup in brassiere should be configured differently depending on type.

Analysis of Taxi Combined Surcharge System Using DTG Data (DTG 데이터를 활용한 택시 복합할증제 분석)

  • Kim, Seoung bum;Kim, Ho seon;Jung, Jong heon
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.152-162
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    • 2020
  • In the urban and rural complex, taxis move from downtown to rural areas for business purposes, and operate a combined surcharge system that preserves losses when they back to downtown. However, complaints related to the abolition of the compound surcharge system are increasing due to deformed operation that does not fit the purpose of the system. When the combinedsurcharge system is abolished, the taxi industry can be hit hard by the decrease in profits, and local governments are inevitable to support it. However, it is difficult to set the size of the subsidy considering the decrease of actual income. This study is to estimate the income reduction in the abolition of the combined surcharge system by scientific and objective method by analyzing the DTG data and the sales data collected from the digital driving recorder installed in the corporate taxi of the urban and rural complex area (e.g., Tongyeong city). This study is meaningful in that it used DTG data to solve the current issues in the real region and suggested the use of new DTG data.

Topic Modeling of News Article Related to Franchise Regulation Using LDA (LDA 를 이용한 '프랜차이즈 규제' 관련 뉴스기사 토픽모델링)

  • YANG, Woo-Ryeong;YANG, Hoe Chang
    • The Korean Journal of Franchise Management
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    • v.13 no.4
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    • pp.1-12
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    • 2022
  • Purpose: In 2020, the franchise industry accomplished a significant growth compared to the previous year, as the number of franchise companies increased by 9.0% while the number of franchise brands increased by 12.5%. Despite growth in size, the Korean franchise industry underwent many negative incidents, such as franchise ownership sales to private equity funds, that led to deterioration of businesses. From this point of view, this study aims to make various proposals to help policy makers develop franchise industry policies by analyzing trends of the current and previous presidential administrations' franchise policies and regulations using newspaper articles. Research design, data and methodology: A total of 7,439 articles registered in Naver API from February 25, 2013 to November 29, 2021 were extracted. Among them, 34 unrelated video articles were deleted, and a total of 7,405 articles from both administrations were used for analysis. The R package was used for word frequency analysis, word clouding, word correlation analysis, and LDA (Latent Dirichlet Allocation) topic modeling. Results: The keyword frequency analysis shows that the most frequently mentioned keywords during the previous administration include 'no-brand', 'major company', 'bill', 'business field', and 'SMEs', and those mentioned during the current administration include 'industry' and 'policy'. As a result of LDA topic modeling, 9 topics such as 'global startups' and 'job creation' from the previous administration, and 10 topics such as 'franchise business' and 'distribution industry' from the current administration were derived. The results of LDAvis showed that the previous administration operated a policy based on mutual growth of large and small businesses rather than hostile regulations in the franchise business, whereas the current administration extended the regulation related to franchise business to the employment sector. Conclusions: The analysis of past two administrations' franchise policy, it can be suggested that franchisors and franchisees may complement each other in developing the Fair Transactions in Franchise Business Act and achieving balanced growth. Moreover, political support is needed for sound development of franchisors. Limitations and future research suggestions are presented at the end of this study.

Comparison of Fentanyl-Based Rapid Onset Opioids for the Relief of Breakthrough Cancer Pain: Drug Price Based on Effect Size

  • Seongchul Kim;Hayoun Jung;Jina Park;Jinsol Baek;Yeojin Yun;Junghwa Hong;Eunyoung Kim
    • Korean Journal of Clinical Pharmacy
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    • v.33 no.1
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    • pp.43-50
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    • 2023
  • Background and Objective: With the advancement of cancer treatments and increased life expectancy, managing breakthrough cancer pain (BTcP) is essential to improve the quality of life for cancer patients. This study aimed to compare the major rapid onset opioids in Korea based on their characteristics and costs to determine the best option for each patient. Methods: Based on sales information from IQVIA-MIDAS, sublingual fentanyl tablet (SLF), fentanyl buccal tablet (FBT), and oral transmucosal fentanyl citrate (OTFC) were selected as the top three drugs for the treatment of BTcP in Korea, considering them the most comparable drugs. The cost and cost-pain relief ratio of the drugs for short-term (1 month) and long-term (1 year) treatment were compared and the ease of administration based on various factors, including pharmacokinetics, onset of action, and administration procedures were evaluated. Results: SLF was evaluated as the best overall in terms of rapid onset of action, ease of administration, and drug cost and also had the highest market share. SLF had the lowest cost pain relief ratio for both the initial and supplemental treatment for the 1-month pain intensity difference 15 (PID15) ratio. However, for the 1-month PID30 ratio, SLF was not superior to OTFC or FBT. The longer the breakthrough cancer pain duration, the more cost-effective the other rapid onset opioids. Conclusion: The rapid onset opioids that fit the patient's breakthrough cancer pain pattern have the best cost-effectiveness.

Deep Learning-based Parcel Detection and Classification System Development Research. (딥러닝 기반 택배 탐지 및 분류 시스템 개발 연구)

  • Son, Seongho;Choi, Donggyu;Jang, Jongwook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.323-325
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    • 2021
  • The size of the delivery market in Korea is growing year by year. In recent years, the growth rate has skyrocketed due to the aftermath of the coronavirus. Looking at the domestic delivery market's volume trend in 2020, about 3.4 billion boxes increased by 21% compared to about 2.8 billion boxes last year. In addition, sales amounted to 7.5 trillion won, an increase of about 19% compared to 6.3 trillion won a year earlier. As the delivery market grows, the proportion of courier damage relief is also occurring at a considerable rate. About 33% of 1,000 people have experienced delivery accidents, and about 41% of the week have experienced damage or damage. In this paper, a deep learning model capable of detecting a parcel was created to detect a damaged parcel. A system that can check the performance of this model and detect and classify parcels during the delivery process using a real-time detection camera was studied.

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Personalized Data Restoration Algorithm to Improve Wearable Device Service (웨어러블 디바이스 서비스 향상을 위한 개인 맞춤형 데이터 복원 알고리즘)

  • Kikun Park;Hye-Rim Bae
    • The Journal of Bigdata
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    • v.6 no.2
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    • pp.51-60
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    • 2021
  • The market size of wearable devices is growing rapidly every year, and manufacturers around the world are introducing products that utilize their unique characteristics to keep up with the demand. Among them, smart watches are wearable devices with a very high share in sales, and they provide a variety of services to users by using information collected in real-time. The quality of service depends on the accuracy of the data collected by the smart watch, but data measurement may not be possible depending on the situation. This paper introduces a method to restore data that a smart watch could not collect. It deals with the similarity calculation method of trajectory information measured over time for data restoration and introduces a procedure for restoring missing sections according to the similarity. To prove the performance of the proposed methodology, a comparative experiment with a machine learning algorithm was conducted. Finally, the expected effects of this study and future research directions are discussed.

TDABC Application Case Study of Compounding Company: TDABC Application and Improvement of Profitability of Company K (컴파운딩 업체의 TDABC 적용사례 연구: K사 TDABC 적용 및 수익성 개선)

  • Dae-Young Lyu;Sung-Wook Yi
    • Asia-Pacific Journal of Business
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    • v.14 no.2
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    • pp.101-118
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    • 2023
  • Purpose - The purpose of this study is to find out how a company can do reasonable cost calculations in a simple way and establish profitability improvement strategies based on the results. Design/methodology/approach - In this study, a case that compounding company K applied TDABC was studied. A case study was conducted on the process of company K reviewing and applying TDABC and the process of implementing the cost calculation for each product by applying TDABC, and establishing a profitability improvement strategy for each product based on the results. Findings - Company K rearranged the production standard information of the compounding industry such as productivity and batch size of each product to apply TDABC. Cost calculation was performed for each product according to the revised production standard information. After the cost calculation for each product was carried out, Company K established a strategy to improve profitability of each product. The profitability improvement strategy was implemented in two ways: a cost reduction strategy and a product price increase strategy. As a result of the final strategy execution, the profitability of each product was improved. Research implications or Originality - This study found a reasonable costing standard in consideration of the specificity of the research target company, and applied it to cost calculation cost for each product. It contains the process of establishing production and sales strategies for each product based on the cost calculation results. It is expected that this case study will serve as a good reference material for establishing cost calculation and profitability improvement strategies in similar businesses.

Audience and Media Predictors for Digital Content Purchases: A Multilevel Approach (디지털 콘텐츠 구매를 위한 고객 및 미디어 요인: 다층수준 접근 방식)

  • Bo-Ram Kwon;HanByeol Stella Choi;Junyeong Lee
    • Information Systems Review
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    • v.22 no.4
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    • pp.115-134
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    • 2020
  • Previous studies on willingness to pay for digital content have mainly focused on audience factors and individual level. To complement the limitation of previous research, this study conducts a multilevel analysis to find the factors influence digital content purchases considering two axes: audience/media factors and individual/household levels. Using a sample of 10,172 individuals within 4,313 households, the analysis results show individual media factors including theater-going, experience with cloud services, and multi-screen service usage have the greatest effects on digital content purchases. At the household level, the media ownership factors that the number of laptops, wireless routers, and tablets have a greater influence than audience factors such as household size or household income. Our findings help scholars to enhance the understanding of individuals' media use considering household environmental factors and shed light on the importance of multi-screen service usage, and content providers to improve their digital content sales using multi-screen environment.

Business Intelligence Design for Strategic Decision Making for Small and Midium-size E-Commerce Sellers: Focusing on Promotion Strategy (중소 전자상거래 판매상의 전략적 의사결정을 위한 비즈니스 인텔리전스 설계: 프로모션 전략을 중심으로)

  • Seung-Joo Lee;Young-Hyun Lee;Jin-Hyun Lee;Kang-Hyun Lee;Kwang-Sup Shin
    • The Journal of Bigdata
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    • v.8 no.2
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    • pp.201-222
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    • 2023
  • As the e-Commerce gets increased based on the platform, a lot of small and medium sized sellers have tried to develop the more effective strategies to maximize the profit. In order to increase the profitability, it is quite important to make the strategic decisions based on the range of promotion, discount rate and categories of products. This research aims to develop the business intelligence application which can help sellers of e-Commerce platform make better decisions. To decide whether or not to promote, it is needed to predict the level of increase in sales after promotion. I n this research, we have applied the various machine learning algorithm such as MLP(Multi Layer Perceptron), Gradient Boosting Regression, Random Forest, and Linear Regression. Because of the complexity of data structure and distinctive characteristics of product categories, Random Forest and MLP showed the best performance. It seems possible to apply the proposed approach in this research in support the small and medium sized sellers to react on the market changes and to make the reasonable decisions based on the data, not their own experience.

Hot Place Detection Based on ConvLSTM AutoEncoder Using Foot Traffic Data (유동인구를 활용한 ConvLSTM AutoEncoder 기반 핫플레이스 탐지)

  • Ju-Young Lee;Heon-Jin Park
    • The Journal of Bigdata
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    • v.8 no.2
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    • pp.97-107
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    • 2023
  • Small business owners are relatively likely to be alienated from various benefits caused by the change to a big data/AI-based society. To support them, we would like to detect a hot place based on the floating population to support small business owners' decision-making in the start-up area. Through various studies, it is known that the population size of the region has an important effect on the sales of small business owners. In this study, inland regions were extracted from the Incheon floating population data from January 2019 to June 2022. the Data is consisted of a grid of 50m intervals, central coordinates and the population for each grid are presented, made image structure through imputation to maintain spatial information. Spatial outliers were removed and imputated using LOF and GAM, and temporal outliers were removed and imputated through LOESS. We used ConvLSTM which can take both temporal and spatial characteristics into account as a predictive model, and used AutoEncoder structure, which performs outliers detection based on reconstruction error to define an area with high MAPE as a hot place.