• Title/Summary/Keyword: 4-META

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A Personalized Clothing Recommender System Based on the Algorithm for Mining Association Rules (연관 규칙 생성 알고리즘 기반의 개인화 의류 추천 시스템)

  • Lee, Chong-Hyeon;Lee, Suk-Hoon;Kim, Jang-Won;Baik, Doo-Kwon
    • Journal of the Korea Society for Simulation
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    • v.19 no.4
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    • pp.59-66
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    • 2010
  • We present a personalized clothing recommender system - one that mines association rules from transaction described in ontologies and infers a recommendation from the rules. The recommender system can forecast frequently changing trends of clothing using the Onto-Apriori algorithm, and it makes appropriate recommendations for each users possible through the inference marked as meta nodes. We simulates the rule generator and the inferential search engine of the system with focus on accuracy and efficiency, and our results validate the system.

A Reusability Enhancement Technique of Embedded System using Plug-In Method (플러그인 기법을 이용한 임베디드 시스템의 재사용 향상 기법)

  • Kim, Chul-Jin;Lee, Sook-Hee;Cho, Eun-Sook
    • Journal of the Korea Society for Simulation
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    • v.18 no.4
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    • pp.81-94
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    • 2009
  • Research of reusability and variability design for embedded system development is insufficient. An embedded system should be designed to support new devices. If extensibility of embedded system is not considered, it is difficult to reconstruct. Currently, the development productivity and reusability of embedded system are very poor, and this will be cased about problems of increasing maintenance and development cost, and decreasing system quality such as software crisis. In this paper, we present framework of embedded system that address those problems of embedded system. We suggest a plug-in technique, based on reusability framework, which can support various devices dynamically. Also, we propose a dynamic Meta model which is base on plug-in technique.

Scoping Review of Machine Learning and Deep Learning Algorithm Applications in Veterinary Clinics: Situation Analysis and Suggestions for Further Studies

  • Kyung-Duk Min
    • Journal of Veterinary Clinics
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    • v.40 no.4
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    • pp.243-259
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    • 2023
  • Machine learning and deep learning (ML/DL) algorithms have been successfully applied in medical practice. However, their application in veterinary medicine is relatively limited, possibly due to a lack in the quantity and quality of relevant research. Because the potential demands for ML/DL applications in veterinary clinics are significant, it is important to note the current gaps in the literature and explore the possible directions for advancement in this field. Thus, a scoping review was conducted as a situation analysis. We developed a search strategy following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. PubMed and Embase databases were used in the initial search. The identified items were screened based on predefined inclusion and exclusion criteria. Information regarding model development, quality of validation, and model performance was extracted from the included studies. The current review found 55 studies that passed the criteria. In terms of target animals, the number of studies on industrial animals was similar to that on companion animals. Quantitative scarcity of prediction studies (n = 11, including duplications) was revealed in both industrial and non-industrial animal studies compared to diagnostic studies (n = 45, including duplications). Qualitative limitations were also identified, especially regarding validation methodologies. Considering these gaps in the literature, future studies examining the prediction and validation processes, which employ a prospective and multi-center approach, are highly recommended. Veterinary practitioners should acknowledge the current limitations in this field and adopt a receptive and critical attitude towards these new technologies to avoid their abuse.

Saenghwa-tang Treatment on Postpartum Prolonged Lochia and Uterine Subinvolution: a Systematic Review and Meta-Analysis (산후 오로부절 및 자궁 복구 불완전에 대한 생화탕(生化湯) 치료의 효과 : 체계적 문헌고찰과 메타분석)

  • Ji-Youn Song;Dong-Chul Kim
    • The Journal of Korean Obstetrics and Gynecology
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    • v.36 no.4
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    • pp.121-139
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    • 2023
  • Objectives: This study was performed to analyze randomized controlled trial, which studied the effect of Saenghwa-tang treatment on postpartum prolonged lochia and uterine subinvolution. Methods: Researchers searched for randomized controlled trial of based on postpartum prolonged lochia, uterine subinvolution and Saenghwa-tang. The paper search was conducted through 6 online databases on August 10, 2023. Results: 8 studies were included after selection and exclusion criteria. 5 studies compared Saenghwa-tang alone with western medicine. 3 studies compared combined treatment of Saenghwa-tang and western medicine, with western medicine alone. Comparing with control group, the treatment group showed statistically significant improvement on total effective rate, uterine involution, serum fibrinogen, D-dimer, viscosity of blood and plasma, Erythrocyte aggregation, and various symptoms. Conclusions: This study suggests that Saenghwa-tang has benefit for treating prolonged lochia and uterine subinvolution. For reliable evidence, further research is needed to establish safety of Saenghwa-tang, standardize diagnosis criteria and specify the treatment course.

Recent advances in few-shot learning for image domain: a survey (이미지 분석을 위한 퓨샷 학습의 최신 연구동향)

  • Ho-Sik Seok
    • Journal of IKEEE
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    • v.27 no.4
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    • pp.537-547
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    • 2023
  • In many domains, lack of data inhibits adoption of advanced machine learning models. Recently, Few-Shot Learning (FSL) has been actively studied to tackle this problem. Utilizing prior knowledge obtained through observations on related domains, FSL achieved significant performance with only a few samples. In this paper, we present a survey on FSL in terms of data augmentation, embedding and metric learning, and meta-learning. In addition to interesting researches, we also introduce major benchmark datasets. FSL is widely adopted in various domains, but we focus on image analysis in this paper.

The Effect of ESG Performance on Economic Growth

  • Wei-Keon ZHANG
    • East Asian Journal of Business Economics (EAJBE)
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    • v.11 no.4
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    • pp.11-18
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    • 2023
  • Purpose - By filling the existing research hole and supplying a whole evaluation, this test wants to offer actionable insights for stakeholders navigating the intersection of sustainability and financial prosperity. Ultimately, this study contributes to the evolving speak on ESG, fostering a deeper comprehension of its implications for fostering sustainable economic increase. Research design, data, and methodology - Based on the numerous prior literature, the current study adopts a rigorous and systematic approach to discover the connection between Environmental, Social, and Governance (ESG) performance and its effect on a financial boom. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method is the guiding framework for systematically accumulating and analyzing earlier research studies. Result: The finding of this study indicates that using ESG-pushed innovation, practitioners can force technological advancements inside their respective industries. By combining sustainability with research and improvement tasks, corporations can be leaders in selling economic boom through current, green solutions. Conclusion - In summary, this study concludes that embracing those findings in this study allows practitioners and managers to enhance their organization's easy regular, well-known traditional regular standard overall performance and undoubtedly contribute to a broader financial boom via leveraging the transformative strength of ESG necessities.

A Causal Recommendation Model based on the Counterfactual Data Augmentation: Case of CausRec (반사실적 데이터 증강에 기반한 인과추천모델: CausRec사례)

  • Hee Seok Song
    • Journal of Information Technology Applications and Management
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    • v.30 no.4
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    • pp.29-38
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    • 2023
  • A single-learner model which integrates the user's positive and negative perceptions is proposed by augmenting counterfactual data to the interaction data between users and items, which are mainly used in collaborative filtering in this study. The proposed CausRec showed superior performance compared to the existing NCF model in terms of F1 value and AUC in experiments using three published datasets: MovieLens 100K, Amazon Gift Card, and Amazon Magazine. Compared to the existing NCF model, the F1 and AUC values of CausRec showed 1.2% and 2.6% performance improvement in MovieLens 100K data, and 2.2% and 10% improvement in Amazon Gift Card data, respectively. In particular, in experiments using Amazon Magazine data, F1 and AUC values were improved by 11.7% and 21.9%, respectively, showing a significant performance improvement effect. The performance of CausRec is improved because both positive and negative perceptions of the item were reflected in the recommendation at the same time. It is judged that the proposed method was able to improve the performance of the collaborative filtering because it can simultaneously alleviate the sparsity and imbalance problems of the interaction data.

The Impact of Food Delivery Apps on Urban Hotels after the Pandemic and its Implications

  • Eungoo KANG
    • The Journal of Industrial Distribution & Business
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    • v.15 no.4
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    • pp.11-18
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    • 2024
  • Purpose: The primary purpose of this research is to investigate the multidisciplinary effect of food delivery apps (FDAs) in urban hotels in the wake of the lockdown due to Covid-19 pandemic. Specifically, the study aims: To explore and scrutinize the primary shifts in customer behavior and preferences in modern urban hotels, and to explore and scrutinize the primary shifts in customer behavior and preferences in modern urban hotels. Research design, data and methodology: This study conducted a systematic literature review to gather evidence of the FDA's effect on customer behavior and the hospitality industry during the Covid-19 pandemic. Complying with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) principles guarantees a structured and transparent method to search the literature and its analysis. Results: The result based on the systematic review has indicated that the booming business of food delivery at home companies and changing consumer tastes prove the FDA's growing circuit in the hotel industry, thus demonstrating their ability and power to adapt to changing trends. Conclusions: Therefore, this study concludes that using FDA's platform, future hospitality managers have to focus on agility in operations, innovation, and technology integration to keep up with changing consumer trends and market conditions.

Leveraging Sports Leadership Principles for Employee Leadership Development

  • Jae-Hyung LEE
    • The Journal of Industrial Distribution & Business
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    • v.15 no.4
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    • pp.19-26
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    • 2024
  • Purpose: The present research encircled on a systematic view of leadership in sports, an area that can be used to boost the skilling of employees. Four specific managerial development tools have been formulated during this research based on relevant materials studied in the previous section. Research design, data and methodology: This research used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards to systematically search for, screen, and synthesize relevant past research on using sports leadership principles for team member development. Results: The findings in this research offer four staff leadership development program ideas that are unique and beneficial for firms looking to foster the development of strong leaders. By deploying sport-based principles and methodology, these approaches can solve the limitations of conventional leadership development programs. This will demonstrate how each plan can help HR managers develop the appropriate strategies for their companies. Conclusions: In sum, this research suggests that by incorporating time-honored principles of sports leadership, these models will provide HR managers with an excellent arsenal of tools for developing a generation of leaders endowed with the skills, mindset, and resilience required to ensure the organization's prosperity under the most adverse conditions.

Kinetic Property and Phylogenie Relationship of 2-Hydroxy-muconic Semialdehyde Dehydrogenase Encoded in tomC Gene of Burkholderia cepacia G4

  • Reddy, Alavala-Matta;Min, Kyung-Rak;Lee, Kyoung;Lim, Jai-Yun;Kim, Chi-Kyung;Kim, Young-Soo
    • Archives of Pharmacal Research
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    • v.27 no.5
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    • pp.570-575
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    • 2004
  • 2-Hydroxymuconic semialdehyde (2-HMS) dehydrogenase catalyzes the conversion of 2-HMS to 4-oxalocrotonate, which is a step in the meta cleavage pathway of aromatic hydrocarbons in bacteria. A tomC gene that encodes 2-HMS dehydrogenase of Burkholderia cepacia G4, a soil bacterium that can grow on toluene, cresol, phenol, or benzene, was overexpressed into E. coli HB 101, and its gene product was characterized in this study. 2-HMS dehydrogenase from B. cepacia G4 has a high catalytic efficiency in terms of V$_{max}$K$_{max}$ towards 2-hydroxy-5-methyl-muconic semialdehyde followed by 2-HMS but has a very low efficiency for 5-chloro-2-hydroxymuconic semialdehyde. However, the enzyme did not utilize 2-hydroxy-6-oxo-hepta 2,4-dienoic acid and 2-hydroxy-6-oxo-6-phenylhexa-2,4-dienoic acid as substrates. The molecular weight of 2-HMS dehydrogenase from B. cepacia G4 was predicted to be 52 kDa containing 485 amino acid residues from the nucleotide sequence of the tomC gene, and it exhibited the highest identity of 78% with the amino acid sequence of 2-HMS dehydrogenase that is encoded in the aphC gene of Comamonas testosteroni TA441. 2-HMS dehydrogenase from B. cepacia G4 showed a significant phylogenetic relationship not only with other 2-HMS dehydrogenases, but also with different dehydrogenases from evolutionarily distant organisms.sms.