박상욱 교수
Sangwook Park
서울대학교 · 공학
연구실 소개
박상욱 교수의 연구실은 공급망의 지속 가능성과 회복탄력성 강화를 핵심 목표로 삼고 있으며, 특히 공급망 리더십과 상호작용 관계의 질이 공급망 전반의 복원력에 미치는 영향을 분석합니다. 기술적 요소로는 X선 천문학을 활용한 초신성 잔재의 열역학적 특성 분석과 함께, 금융기술(FinTech) 분야에서의 보안 인식이 모바일 결제 서비스 성공에 미치는 영향을 탐구하는 등 다학제적 연구를 수행하고 있습니다. 특히 공급망 내 상호작용의 질을 측정하고 개선하는 데 초점을 맞춘 혁신적인 모델링 기법을 개발하고 있습니다.
연구 현황
연구 성과 추이
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주요 논문
15Understanding a supply chain (SC) leader’s role from a collaborative capability management perspective offers insights into strategically managing exchange relationships during disruptions. This study illustrates the importance of leadership responsibility in managing overall resilience capabilities among SC network members. Using insights drawn from leadership theory, SC leader-member exchange (LMX) is operationalised to measure levels in exchange relationships. Furthermore, an integrative prob
The purpose of this study is to systematically identify and design improvement planning for supply chain resilience (SCRES) for a higher level of sustainability and a competitive advantage. Literature-based interpretive structural modelling (ISM), a pairing of the systematic literature review (SLR) and ISM approaches, is proposed for investigating and identifying a set of key performance measures of resilience for supply chain (SC) management. In line with previous research, we identified and up
Financial technology (fintech) services have come to differentiate themselves from traditional financial services by offering unique, niche, and customized services. Mobile payment service (MPS) has emerged as the most crucial fintech service. While many studies have addressed the essential role of security when service providers and users choose to engage in financial transactions, the relationship between users distinct perceptions of security and MPS success determinants are yet to be examine
Toward a maritime surveillance objective, many ship detection and tracking algorithms have been investigated but are faced with poor performance in practical ocean environments. Compact high-frequency (HF) radar has also faced critical issues due to its long coherent processing interval and varying response from its orthogonal antenna structure. Hence, a simulator based on compact HF radar is proposed in this letter to provide a guideline for effective assessment of ship detection and tracking a
ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTStatic and hydrodynamic size of polystyrene coils in various solventsSangwook Park, Taihyun Chang, and Il Hyun ParkCite this: Macromolecules 1991, 24, 20, 5729–5731Publication Date (Print):September 1, 1991Publication History Published online1 May 2002Published inissue 1 September 1991https://pubs.acs.org/doi/10.1021/ma00020a038https://doi.org/10.1021/ma00020a038research-articleACS PublicationsRequest reuse permissionsArticle Views367Altmetric-Citation
While atypical sensory perception is reported among individuals with autism spectrum disorder (ASD), the underlying neural mechanisms of autism that give rise to disruptions in sensory perception remain unclear. We developed a neural model with key physiological, functional and neuroanatomical parameters to investigate mechanisms underlying the range of representations of visual illusions related to orientation perception in typically developed subjects compared to individuals with ASD. Our resu
This paper proposes an effective method of improving ship detection performance of a compact high-frequency (HF) radar system which has been primarily optimized for observing surface radial current velocities and bearings. Previously developed ship detection systems have been vulnerable to error sources such as environmental noise and clutter when they are applied in a compact HF radar optimized for observing surface current. In particular, the influences of error are reduced by applying a princ
Government legislation significantly impacts closed-loop supply chain (CLSC) operations. This study examines the collection rate of and decisions on the product greening improvement level in a three-level CLSC with the government’s reward–penalty and a manufacturer’s subsidy policy. Four game-theoretic models are analyzed in order to evaluate the ways in which the policy and revenue-sharing contracts (RSCs) between the manufacturer and retailer affect the CLSC members’ optimal decisions and prof
A catalogue of the fauna of Korean Xyleborine species is provided with information on the Korean records, local and world distribution and taxonomy. The following seven new species and 11 newly recorded species are added to the Korean fauna: Cyclorhipidion laciniosum Park & Smith sp. nov., Cyclorhipidion triste Park & Smith sp. nov., Microperus molestus Park & Smith sp. nov., Xyleborinus kwangreungensis Park & Smith sp. nov., Xyleborus singhi Park & Smith sp. nov., Xylosandrus dentipennis Park &
In Korea, seven species belonging to five genera of the family Bostrichidae have been recorded to date. To these seven species, we are adding four other species, namely, Psoa rubripennis sp. nov., Dinoderus speculifer Lesne, 1895, Heterobostrychus hamatipennis (Lesne, 1895), and Xylothrips pekinensis (Lesne, 1902: comb. nov.) to the Korean fauna. In addition, the genus Calophagus Lesne, 1902, is synonymized with the genus Xylothrips Lesne, 1901 (syn. nov.) and Xylothrips cathaicus Reichardt, 196
Due to its mobile capability when performing house-cleaning function in absence of home owners, a cleaning robot has sufficient capacity to be fully utilized as an automatic surveillance system for indoor security. While many research efforts have been made recently to provide a robot understand the auditory environment, there are still many obstacles to overcome. One of the most serious challenges encountered in providing accurate auditory scene analysis is the presence of robot ego noise. Robo
Sound event detection is an important facet of audio tagging that aims to identify sounds of interest and define both the sound category and time boundaries for each sound event in a continuous recording. With advances in deep neural networks, there has been tremendous improvement in the performance of sound event detection systems, although at the expense of costly data collection and labeling efforts. In fact, current state-of-the-art methods employ supervised training methods that leverage la
Sound event detection (SED) takes on the task of identifying presence of specific sound events in a complex audio recording. SED has tremendous implications in video analytics, smart speaker algorithms and audio tagging. Recent advances in deep learning have afforded remarkable advances in performance of SED systems; albeit at the cost of extensive labeling efforts to train supervised methods using fully described sound class labels and timestamps. In order to address limitations in availability
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