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개인정보보호법제 관점에서 본 블록체인의 법적 쟁점 GDPR 및 국내 개인정보보호법을 바탕으로
박민정,채상미,이명준 한국데이터전략학회 2018 Journal of information technology applications & m Vol.25 No.2
The technical definition of Blockchain is commonly known ‘distributed ledger’, however, there is no legal definition for being accepted in worldwide. Therefore, unless legal definitions and concepts of Blockchain are presented, there is a possibility that various legal disputes will occur in the future in Blockchain environment. The purpose of this study is to derive legal issues related to personal information protection that can be conflicted in Blockchain environment based on domestic Privacy Act and GDPR. The outcomes of this study can prevent various legal disputes and provide solutions that may occur due to the spread of Blockchain. It also suggests the foundation for the improvement of Privacy Act. Finally, it contributes to activate of Blockchain, industry, in Korea.
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박민정 국제인공지능학회 2026 International Journal of Internet, Broadcasting an Vol.18 No.2
This study examines the predictive determinants of online course completion by comparing behavioral engagement variables with structural learning features. As digital learning environments have rapidly expanded following the COVID-19 pandemic, accurately predicting learner persistence has become increasingly important. However, prior research has predominantly relied on activity-based behavioral logs, such as time spent learning and assignment submission frequency, while giving limited attention to structural characteristics of learning environments. Using a large-scale dataset comprising 100,000 learner profiles, this study compares the predictive performance of Logistic Regression, Random Forest, Support Vector Machine, and XGBoost models. In addition, it statistically evaluates the incremental predictive value of structural learning variables, including learning path type and engagement consistency. The results indicate that boosting-based ensemble methods achieved the strongest overall predictive performance, although linear models remained competitive. More importantly, the inclusion of structural learning features significantly improved model performance, demonstrating that course completion is not solely determined by engagement intensity but is also shaped by the structural design of the learning environment. This study contributes theoretically by reframing online learning persistence beyond behavioral activity measures and methodologically by emphasizing the importance of feature design in predictive modeling. Practically, the findings suggest that digital learning platforms should incorporate structural learning indicators into early risk detection systems and instructional design strategies.
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학습 가능한 멀티모달 프롬프트를 활용한 멀티 어텐션 기반 보행자 속성 인식
박민정,이상윤,김익재,최희승 대한전자공학회 2024 대한전자공학회 학술대회 Vol.2024 No.6
Most of pedestrian attribute recognition (PAR) exploit only visual cues, which has high dependency for image conditions and would lead sub-optimal results. In this paper, we adopt the text descriptions as auxiliary information for PAR. For low training cost but sufficient multi-modal represenstation space, we introduce the mluti-modal prompt learning. Specifically, we construct visual and text prompt which consist of learnable parameters, and it go though the fixed image and text encoders, respectively. To focus effectively on the relationship between different modalities, we introduce the XSA module to fuse the tokens. Our proposed PAR model achieves accuracy of 79.28 and 86.67 of F1-score on PETA dataset. Various experiments are conducted to validate the effectiveness of our model.
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근감소성 비만에 대하여 근육량을 보존할 수 있는 체중 감량 중재에 대한 고찰
박민정,임영우,김은주 대한한의학회 2024 대한한의학회지 Vol.45 No.1
Objectives: The objective of this study was to review clinical studies conducted over the last ten years that investigated weight or fat loss interventions that can preserve muscle or fat-free mass in Sarcopenic obesity Methods: PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), Research Information Sharing Service (RISS) and Korea Studies Information Service (KISS) were searched for Randomized clinical trials that had investigated all-type of interventions on the management of sarcopenic obesity from October 2013 to September 2023. Results: A total of 14 studies met all the inclusion criteria. Interventions that increase muscle mass while reducing body fat at the same time included resistance training (including using elastic bands) and whole-body electromyostimulation(WB-EMS) in exercise intervention and Hypocaloric high-protein diet in nutritional intervention, exercise and nutritional combined intervention, and combination intervention of electrical acupuncture and amino acid supplementation. Among them, the most positive method of changing the body composition in sarcopenic obesity was the electric acupuncture and amino acid supplements. Conclusion: Varying diagnostic criteria and management interventions for sarcopenic obesity in the included studies made it hard to maintain homogeneity across the studies. Well-defined criteria for diagnostic sarcopenic obesity should be considered. In addition, since all of the interventions examined did not show sufficient clinical effectiveness, follow-up studies are needed to confirm effective interventions for sarcopenic obesity patients in the future.
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