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Chuna Manual Therapy for Primary Dysmenorrhea: A Systematic Review (원발성 월경통의 추나 치료에 대한 체계적 문헌 고찰)

  • Seo, Ha-Ra;Li, Yu-Chen;Lee, Jae-Eun;Kim, Myoung-Kyu
    • Journal of Korean Medicine Rehabilitation
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    • v.27 no.3
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    • pp.81-93
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    • 2017
  • Objectives The purpose of this study is to evaluate the effectiveness of Chuna therapy for primary dysmenorrhea. Methods Researchers searched on 7 electronic databases (Pubmed, National Digital Science Library, China National Knowledge Infrastructure, Wangfang med online, Korean Studies Information Service System, Research Information Sharing Service and Oriental medicine Advanced Searching Integrated System). The search included Korean, English, Chinese reports and there was no limit on the search period. All of randomized controlled clinical trials (RCTs) that used Chuna manual therapy for primary dysmenorrhea were selected. Results 27 RCTs met required condition. Meta-analysis showed positive results for Chuna manual therapy for primary dysmenorrhea in terms of therapeutic effects and reduction of symptom scores compared to west medicine, herbal medicine, acupucture and other treatments. Conclusions Above results showed that performing chuna is effective in treating dysmenorrhea. However, in some studies, there was no statistic significance between the experimental group and the control group. Also, according to Cochrane Risk of Bias (RoB) evaluation method, quality of the studies were not high enough. Since most of the materials were in Chinese, more high-quality clinical trials about Chuna therapy for primary dysmenorrhea are needed in Korea.

Systematic Review of Korean Medicine-related Study on Diagnostic Tools and Pattern Identification registered of Dysmenorrhea in the Korean Journal (국내 전자저널에 수록된 월경통 평가지표 및 변증에 대한 한의학적 임상연구 고찰)

  • Kim, Jihye;Kim, Jongyeol;Jeon, Youngju
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.29 no.5
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    • pp.434-442
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    • 2015
  • The purpose of this review was to survey the Korean Medicine related papers about women with primary dysmenorrhea in order to develop the clinical protocol of the diagnostic medical device. We searched the literature from 2000 through April 2015 using 5 online databases including Oriental Medicine Advanced Searching Integrated Sysptem (OASIS), Research Information Sharing Service (RISS), DataBase Periodical Information Academic (DBpia) and Korean Medical Database (KMBase). We selected papers to meet the following inclusion criteria: the papers involved dysmenorrhea (excluding secondary dysmenorrhea), published papers (excluding textbook, educational materials, conferences, etc.) and the papers matched search keywords or scope, but excluded papers to meet the following exclusion criteria: the duplicative papers, get out of the keywords and scope and not in english or korean language. Finally we found 17 papers and classified the papers according to the three search purposes which were diagnostic tools for evaluating the menstrual pain, dysmenorrhea' pattern identification and menstrual phase. Out of the 16 studies, 4 studies were focused on the diagnostic tools including Visual Analogue Scale (VAS), Measurement of Menstrual Pain (MMP) and etc. Other 5 studies were aimed at menstrual phase, and the other 7 studies were studied for pattern identification. The VAS has been widely used in research and in clinical practice for the detection of the menstrual pain. Treatments for patients with primary dysmenorrhea can be prescribed in consideration of their patterns of sasang constitution or body constitution as following: Qi stagnation-Blood deficiency, cold dampness, Qi deficiency-blood deficiency and liver-kidney deficiency etc. This results of research will be used as a useful material during plan a clinical study of primary dysmenorrhea and acquisition of good clinical data.

TCP Algorithm Improvement for Smartphone Data Transmissions (스마트폰 통신성향을 고려한 TCP 개선방안)

  • Lee, Joon Yeop;Kim, Hyunsoon;Lee, Woonghee;Kim, Hwangnam
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.10
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    • pp.1309-1316
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    • 2016
  • This paper suggests adjusting TCP for smartphones that often have small size data transmission tendency. Usage of smartphones has been risen dramatically in recent years, including frequent usage of real-time map search, public transportation search, online games, and SNS. Because the small size data transmission ends before the phase of the TCP congestion avoidance, this paper suggests an algorithm that increases the transmission speed ahead of the traffic congestion event. The algorithm reduces unnecessary delay by data size-driven adjustment of the Linux Quick ACK and Nagle's algorithm. Therefore, TCP is improved to maintain a high transmission rate steadily in small data transmission.

Improving Accuracy of Noise Review Filtering for Places with Insufficient Training Data

  • Hyeon Gyu Kim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.7
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    • pp.19-27
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    • 2023
  • In the process of collecting social reviews, a number of noise reviews irrelevant to a given search keyword can be included in the search results. To filter out such reviews, machine learning can be used. However, if the number of reviews is insufficient for a target place to be analyzed, filtering accuracy can be degraded due to the lack of training data. To resolve this issue, we propose a supervised learning method to improve accuracy of the noise review filtering for the places with insufficient reviews. In the proposed method, training is not performed by an individual place, but by a group including several places with similar characteristics. The classifier obtained through the training can be used for the noise review filtering of an arbitrary place belonging to the group, so the problem of insufficient training data can be resolved. To verify the proposed method, a noise review filtering model was implemented using LSTM and BERT, and filtering accuracy was checked through experiments using real data collected online. The experimental results show that the accuracy of the proposed method was 92.4% on the average, and it provided 87.5% accuracy when targeting places with less than 100 reviews.

How Enduring Product Involvement and Perceived Risk Affect Consumers' Online Merchant Selection Process: The 'Required Trust Level' Perspective (지속적 관여도 및 인지된 위험이 소비자의 온라인 상인선택 프로세스에 미치는 영향에 관한 연구: 요구신뢰 수준 개념을 중심으로)

  • Hong, Il-Yoo B.;Lee, Jung-Min;Cho, Hwi-Hyung
    • Asia pacific journal of information systems
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    • v.22 no.1
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    • pp.29-52
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    • 2012
  • Consumers differ in the way they make a purchase. An audio mania would willingly make a bold, yet serious, decision to buy a top-of-the-line home theater system, while he is not interested in replacing his two-decade-old shabby car. On the contrary, an automobile enthusiast wouldn't mind spending forty thousand dollars to buy a new Jaguar convertible, yet cares little about his junky component system. It is product involvement that helps us explain such differences among individuals in the purchase style. Product involvement refers to the extent to which a product is perceived to be important to a consumer (Zaichkowsky, 2001). Product involvement is an important factor that strongly influences consumer's purchase decision-making process, and thus has been of prime interest to consumer behavior researchers. Furthermore, researchers found that involvement is closely related to perceived risk (Dholakia, 2001). While abundant research exists addressing how product involvement relates to overall perceived risk, little attention has been paid to the relationship between involvement and different types of perceived risk in an electronic commerce setting. Given that perceived risk can be a substantial barrier to the online purchase (Jarvenpaa, 2000), research addressing such an issue will offer useful implications on what specific types of perceived risk an online firm should focus on mitigating if it is to increase sales to a fullest potential. Meanwhile, past research has focused on such consumer responses as information search and dissemination as a consequence of involvement, neglecting other behavioral responses like online merchant selection. For one example, will a consumer seriously considering the purchase of a pricey Guzzi bag perceive a great degree of risk associated with online buying and therefore choose to buy it from a digital storefront rather than from an online marketplace to mitigate risk? Will a consumer require greater trust on the part of the online merchant when the perceived risk of online buying is rather high? We intend to find answers to these research questions through an empirical study. This paper explores the impact of enduring product involvement and perceived risks on required trust level, and further on online merchant choice. For the purpose of the research, five types or components of perceived risk are taken into consideration, including financial, performance, delivery, psychological, and social risks. A research model has been built around the constructs under consideration, and 12 hypotheses have been developed based on the research model to examine the relationships between enduring involvement and five components of perceived risk, between five components of perceived risk and required trust level, between enduring involvement and required trust level, and finally between required trust level and preference toward an e-tailer. To attain our research objectives, we conducted an empirical analysis consisting of two phases of data collection: a pilot test and main survey. The pilot test was conducted using 25 college students to ensure that the questionnaire items are clear and straightforward. Then the main survey was conducted using 295 college students at a major university for nine days between December 13, 2010 and December 21, 2010. The measures employed to test the model included eight constructs: (1) enduring involvement, (2) financial risk, (3) performance risk, (4) delivery risk, (5) psychological risk, (6) social risk, (7) required trust level, (8) preference toward an e-tailer. The statistical package, SPSS 17.0, was used to test the internal consistency among the items within the individual measures. Based on the Cronbach's ${\alpha}$ coefficients of the individual measure, the reliability of all the variables is supported. Meanwhile, the Amos 18.0 package was employed to perform a confirmatory factor analysis designed to assess the unidimensionality of the measures. The goodness of fit for the measurement model was satisfied. Unidimensionality was tested using convergent, discriminant, and nomological validity. The statistical evidences proved that the three types of validity were all satisfied. Now the structured equation modeling technique was used to analyze the individual paths along the relationships among the research constructs. The results indicated that enduring involvement has significant positive relationships with all the five components of perceived risk, while only performance risk is significantly related to trust level required by consumers for purchase. It can be inferred from the findings that product performance problems are mostly likely to occur when a merchant behaves in an opportunistic manner. Positive relationships were also found between involvement and required trust level and between required trust level and online merchant choice. Enduring involvement is concerned with the pleasure a consumer derives from a product class and/or with the desire for knowledge for the product class, and thus is likely to motivate the consumer to look for ways of mitigating perceived risk by requiring a higher level of trust on the part of the online merchant. Likewise, a consumer requiring a high level of trust on the merchant will choose a digital storefront rather than an e-marketplace, since a digital storefront is believed to be trustworthier than an e-marketplace, as it fulfills orders by itself rather than acting as an intermediary. The findings of the present research provide both academic and practical implications. The first academic implication is that enduring product involvement is a strong motivator of consumer responses, especially the selection of a merchant, in the context of electronic shopping. Secondly, academicians are advised to pay attention to the finding that an individual component or type of perceived risk can be used as an important research construct, since it would allow one to pinpoint the specific types of risk that are influenced by antecedents or that influence consequents. Meanwhile, our research provides implications useful for online merchants (both online storefronts and e-marketplaces). Merchants may develop strategies to attract consumers by managing perceived performance risk involved in purchase decisions, since it was found to have significant positive relationship with the level of trust required by a consumer on the part of the merchant. One way to manage performance risk would be to thoroughly examine the product before shipping to ensure that it has no deficiencies or flaws. Secondly, digital storefronts are advised to focus on symbolic goods (e.g., cars, cell phones, fashion outfits, and handbags) in which consumers are relatively more involved than others, whereas e- marketplaces should put their emphasis on non-symbolic goods (e.g., drinks, books, MP3 players, and bike accessories).

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Effects of Information Sources on Enjoyment, Attitude, and Visit Intention in Restaurant (레스토랑의 정보 원천이 즐거움, 태도, 그리고 방문 의도에 미치는 영향)

  • Kang, Byoung-Seoung;Yang, Jae-Jang;Lee, Soo-Duck
    • The Korean Journal of Franchise Management
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    • v.9 no.3
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    • pp.7-18
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    • 2018
  • Purpose - Consumers have a variety of strategies to find information about restaurants they want to visit. Consumers can search for and use information from a variety of sources before purchasing a product or service. The development of the Internet has made that consumers could access various informations easily. Therefore, this study classified commercial information provided by restaurants, public information shared by other unknown consumers, and personal information shared by customers' personal experiences or friends/family. This study is information sources influence on enjoyment, attitude and visit intention. Research design, data, methodology - In order to verify the research hypothesis, this study created questionnaires for each variable. Hypothesis analysis data were collected through surveys. In order to develop research hypotheses for this study, the scales was developed. The survey was conducted by an online survey company. Among the online panels owned by survey company, those who have visited restaurants through at least one of the 11 sources provided in this study within the last 3 months were surveyed. The survey period was 10 days from March 5 to 14, 2017. A total of 1,500 e-mails and messages were sent back to 301 of them, and 288 were used for analysis except for 13 missing responses. The data was analyzed by using SPSS 21.0 and AMOS 21.0. Results - As a result of analysis, commercial and personal information have a positive effect on enjoyment, but general information did not affect enjoyment. In addition, personal information has a positive effect on attitude, but commercial information and general information did not affect attitude. It was found that commercial information influenced attitude by mediation of pleasure, and pleasure had no significant effect on visit intention. Finally, attitude has a significant effect on visit intention. Conclusions - The restaurant needs to provide accurate information through its homepage or brochure. Accurate information that is not exaggerated can save customers's the cost of believing on a restaurant and the cost of searching for other information. The restaurant which provides unfaithful advertisement would be excluded from customer's choice because customers perceive it as a unreliable restaurant. The marketing of restaurant should be carried out through customer-oriented for the visit of customers. And restaurants need to provide optimized services to their first-time customers in order to increase their revisit.

Implementation of CNN-based Classification Training Model for Unstructured Fashion Image Retrieval using Preprocessing with MASK R-CNN (비정형 패션 이미지 검색을 위한 MASK R-CNN 선형처리 기반 CNN 분류 학습모델 구현)

  • Seunga, Cho;Hayoung, Lee;Hyelim, Jang;Kyuri, Kim;Hyeon-Ji, Lee;Bong-Ki, Son;Jaeho, Lee
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.6
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    • pp.13-23
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    • 2022
  • In this paper, we propose a detailed component image classification algorithm by fashion item for unstructured data retrieval in the fashion field. Due to the COVID-19 environment, AI-based online shopping malls are increasing recently. However, there is a limit to accurate unstructured data search with existing keyword search and personalized style recommendations based on user surfing behavior. In this study, pre-processing using Mask R-CNN was conducted using images crawled from online shopping sites and then classified components for each fashion item through CNN. We obtain the accuaracy for collar of the shirt's as 93.28%, the pattern of the shirt as 98.10%, the 3 classese fit of the jeans as 91.73%, And, we further obtained one for the 4 classes fit of jeans as 81.59% and the color of the jeans as 93.91%. At the results for the decorated items, we also obtained the accuract of the washing of the jeans as 91.20% and the demage of jeans accuaracy as 92.96%.

A Study on MZ Generation's Information Seeking Behavior of Contents Platforms: Focused on Information Users in the Field of Science, Technology, and Information (MZ세대의 콘텐츠 플랫폼 활용행태에 관한 연구 - 과학기술정보 분야의 정보이용자를 중심으로 -)

  • Yoo, Suhyeon;Kim, Hyunjung;Hyun, Mi-Hwan
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.32 no.4
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    • pp.231-263
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    • 2021
  • The purpose of this study is to analyze the information behavior of so-called "MZ Generation" users who are going to be the main information users of the continuously and radically changing scientific information environment due to the advent of various types of information media and rapid increment of digital information resources. Especially, the characteristics of MZ generation is investigated through questionnaire asking questions about their use of contents platforms, and online resources for everyday life information and scholarly information, and their way of producing, responding, and sharing information contents. The results show that they use YouTube most as the contents platform, prefer Naver as their everyday life information source, and use Google as the main scholarly information source. Their main purpose of using the content platform is to search for everyday life information rather than scholarly or professional information, and they are actively producing information, mostly to keep records of their everyday lives.

The Detection of Online Manipulated Reviews Using Machine Learning and GPT-3 (기계학습과 GPT3를 시용한 조작된 리뷰의 탐지)

  • Chernyaeva, Olga;Hong, Taeho
    • Journal of Intelligence and Information Systems
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    • v.28 no.4
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    • pp.347-364
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    • 2022
  • Fraudulent companies or sellers strategically manipulate reviews to influence customers' purchase decisions; therefore, the reliability of reviews has become crucial for customer decision-making. Since customers increasingly rely on online reviews to search for more detailed information about products or services before purchasing, many researchers focus on detecting manipulated reviews. However, the main problem in detecting manipulated reviews is the difficulties with obtaining data with manipulated reviews to utilize machine learning techniques with sufficient data. Also, the number of manipulated reviews is insufficient compared with the number of non-manipulated reviews, so the class imbalance problem occurs. The class with fewer examples is under-represented and can hamper a model's accuracy, so machine learning methods suffer from the class imbalance problem and solving the class imbalance problem is important to build an accurate model for detecting manipulated reviews. Thus, we propose an OpenAI-based reviews generation model to solve the manipulated reviews imbalance problem, thereby enhancing the accuracy of manipulated reviews detection. In this research, we applied the novel autoregressive language model - GPT-3 to generate reviews based on manipulated reviews. Moreover, we found that applying GPT-3 model for oversampling manipulated reviews can recover a satisfactory portion of performance losses and shows better performance in classification (logit, decision tree, neural networks) than traditional oversampling models such as random oversampling and SMOTE.

The Effects of Highlighted Review Type on Consumer's Perception and Behavior: Focusing on Review Usefulness and Skepticism (강조된 리뷰 노출 방식에 따른 소비자 행동 연구: 리뷰의 유용성과 회의감을 중심으로)

  • Junho Kim;Il Im;Taeyoung Kim
    • Information Systems Review
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    • v.23 no.3
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    • pp.25-50
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    • 2021
  • Though there have been a lot of studies about online product review, the effects of highlighted reviewhave not been examined enough. Highlighted review is a type of review that the platform designer changes its size or position in order to highlight without any sponsorship or incentive. The main subject of this study is about how highlighted review type affects consumer's perception and behavior in online information acquisition. We collected data from 171 subjects to test hypotheses. Using three different types of screen captures, we compared three groups - general review group, positive highlighted review only group, and both positive and negative highlighted review group. As a result, disclosing both of positiveand negative highlighted review was perceived more useful than disclosing only positive highlighted review. However, correlation between highlighted review type and review skepticism was not statistically significant. The impacts of review usefulness and skepticism on platform credibility were statistically significant, and the correlation between platform credibility and usage intention was also significant. All of results is almost similar across two product types, search goods and experiential goods. This research provides practical implications to online shopping platform designers when they design review systems to make people use their platforms.