• Ocean and Polar Research
• /
• v.23 no.3
• /
• pp.223-242
• /
• 2001

This paper presents the depth-mean monthly variation in the circulation of the Yellow Sea and the East China Sea computed using a robust diagnostic model. The mixed three-dimensional finite-difference Galerkin function model developed by Lee et at. (2000, 2001) has been extended to take into account baroclinic effects and then used to calculate the depth-mean flow fields as part of the results. In addition to M2 tide and oceanic flows previously considered, the model has been driven by the monthly mean wind stresses from Na and Seo (1998), the density gradient calculated based on by GDEM data set released by US Navy. Model results are very encouraging in that many of observed features including Jeju Cyclonic Gyre and frontal eddies along the shelfside of the Kuroshio main stream and west of Kyushu, are satisfactorily reproduced and are expected to be of value in interpreting observations in various oceanograhic disciplines.

• Solar Energy
• /
• v.13 no.1
• /
• pp.67-74
• /
• 1993

Solar radiation intensity in Cheju-Do has been measured and analyzed to study the its characteristic and the possibility of the alternative energy, This work will also support the on-going project "Clean Enertopia in Cheju" which is strongly driven by government recently. The results of this project indicate that 1) Insolation in Cheju-Do is 10% lower than Southern coastal area. 2) A significant difference of insolation is observed between western and eastern part of Cheju-Do.

• The Journal of Economics, Marketing and Management
• /
• v.9 no.6
• /
• pp.1-13
• /
• 2021

Purpose: This research explores how domain passion in addition to entrepreneurial passion influences innovation strategy of venture, thus expanding the role of passion in choosing the path for innovation strategy. Passion is considered one of the most debated concepts in entrepreneurship, psychology, and marketing literatures, and yet a framework describing the integrated effect of entrepreneurial and domain passion on innovation strategy of venture is still lacking. Research data and methodology: Based on an inductive qualitative approach, the research addresses these issues via analyzing four unique cases of independently owned restaurants in Pakistan. The research focusses on the entrepreneurs who startup a venture out of a passion for a specific domain and have a passion for entrepreneurship either from start or it fuels up later during entrepreneurial process. Results: In the presence of both types of passions (Domain and entrepreneurial), the individuals will be inclined towards ambidexterity which differ in types from case to case according to different combinations and intensities (harmonious and obsessive) of passion. Conclusion: Research shows how innovation strategy of domain passion driven ventures is influenced by both entrepreneurial and domain passion, so to understand the role of passion in such cases integrated effect of both passions needs to be explored.

• Journal of Sensor Science and Technology
• /
• v.31 no.5
• /
• pp.301-306
• /
• 2022

With the recent widespread implementation of Internet of Things (IoT) technology driven by Industry 4.0, self-powered sensors for wearable and implantable systems are increasingly gaining attention. Piezoelectric nanogenerators (PENGs) and triboelectric nanogenerators (TENGs), which convert biomechanical energy into electrical energy, can be considered as efficient self-powered sensor platforms. These are energy harvesters that are used as low-power energy sources. However, they can also be used as sensors when an output signal is used to sense any mechanical stimuli. For sensors, collecting high-quality data is important. However, the accuracy of sensing for practical applications is equally important. This paper provides a brief review of the performance advanced by the materials and structures of the latest PENG/TENG-based wearable sensors and intelligent applications applied using artificial intelligence (AI)

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.937-944
• /
• 2022

Electric vehicles (EVs) have been growing to reduce energy consumption and greenhouse gas (GHG) emissions in the transportation sector. The increasing number of EVs requires adequate recharging infrastructure, and at the same time, adopts low- or zero-emission electricity production because the GHG emissions are highly dependent on primary sources of electricity production. Although previous research has studied solar photovoltaic (PV) -integrated EV charging stations, it is challenging to optimize spatial areas between where the charging stations are required and where the renewable energy sources (i.e., solar photovoltaic (PV)) are accessible. Therefore, the primary objective of this research is to support decisions of siting EV charging stations using a spatial data clustering method integrated with Geographic Information System (GIS). This research explores spatial relationships of PV power outputs (i.e., supply) and traffic flow (i.e., demand) and tests a community in the state of Indiana, USA for optimal sitting of EV charging stations. Under the assumption that EV charging stations should be placed where the potential electricity production and traffic flow are high to match supply and demand, this research identified three areas for installing EV charging stations powered by rooftop PV in the study area. The proposed strategies will drive the transition of existing energy infrastructure into decentralized power systems. This research will ultimately contribute to enhancing economic efficiency and environmental sustainability by enabling significant reductions in electricity distribution loss and GHG emissions driven by transportation energy.

• The Journal of the Korea Contents Association
• /
• v.22 no.5
• /
• pp.685-696
• /
• 2022

This study explores convergence curriculum for design and data science, and applies data science knowledge on undergraduate design classes for designer's data literacy. First, related studies about data literacy education for non-data science major's, and data driven design project cases are explored, then design competency and data competency based on NCS are studied. Then this study developed 3 step design-data convergence curriculum model for designers' data literacy. The curriculum model is applied on case study classes, which are Big data and UX design(2) classes. The learning results and student's feedback of the case study classes are collected and analyzed to prove the design-data convergence curriculum, and the results provide findings and implications of the design-data convergence class case study.

• Journal of Korea Society of Industrial Information Systems
• /
• v.4 no.4
• /
• pp.32-39
• /
• 1999

Video-On-Demand servers have to provide timely processing guarantees and reduce the storage and reduce the storage and bandwidth requirements for continuous media However, compression techniques used in Video-On-Demand servers make the bit rates of compressed video data significantly variable from frame to frame Consequently, most pervious Video-On-Demand servers which use constant bit rate retrieval to guarantee deterministic service under-utilize the system resources and restrict the number of clients. In this paper, I propose a buffer management scheme called CAP(Caching And Prefetching) for Video-On-Demand server using variable bit rate continuous media. By caching and prefetching the data CAP reduces the variation of the compressed data and increases the number of clients simultaneously served and maximizes the utilization of system resources. Results of trace-driven simulations show the effectiveness of the scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.8
• /
• pp.4133-4145
• /
• 2017

Advances in science and technology are driving us to the better life but also forcing us to make more investment at the same time. Therefore, the government has provided the investment to carry on the promising futuristic technology successfully. Indeed, a lot of resources from the government have supported into the science and technology R&D projects for several decades. However, the performance of the public investments remains unclear in many ways, so thus it is required that planning and evaluation about the new investment should be on data driven decision with fact based evidence. In this regard, the government wanted to know the trend and issue of the science and technology with evidences, and has accumulated an amount of database about the science and technology such as research papers, patents, project reports, and R&D information. Nowadays, the database is supporting to various activities such as planning policy, budget allocation, and investment evaluation for the science and technology but the information quality is not reached to the expectation because of limitations of text mining to drill out the information from the unstructured data like the reports and papers. To solve the problem, this study proposes a practical text mining methodology for the science and technology trend analysis, in case of aerospace technology, and conduct text mining methods such as ontology development, topic analysis, network analysis and their visualization.

• Journal of Distribution Science
• /
• v.21 no.2
• /
• pp.35-43
• /
• 2023

Purpose: As Thailand seeks to become a regional startup hub, Thai startups have been acquiring growth and scalability in the last ten years. Hence, this paper examines influential factors in Thailand's growth of logistics tech startups. The conceptual framework incorporates sensing user needs, sensing technological options, conceptualizing, scaling, and stretching, co-producing, and orchestrating, business strategy, strategic flexibility, and startup growth. Research design, data, and methodology: The quantitative method was applied to distribute the questionnaire to 500 managers and above in logistics tech startups in Thailand. The sampling techniques involve judgmental, convenience, and snowball samplings. Before the data collection, The Item Objective Congruence (IOC) Index and pilot test (n=45) were employed for content validity and reliability. The data were mainly analyzed by Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM). Results: The findings revealed that sensing technological options, scaling, and stretching, co-producing, and orchestrating, and business strategy significantly influence the growth of startups in Thailand. Nevertheless, sensing user needs, conceptualizing, and strategic flexibility have no significant relationship with startup growth. Conclusions: For Thailand to accelerate its digital economy driven by tech startups, firms must emphasize influential factors to accelerate growth by providing the right tech solutions for people's lives.

• Structural Monitoring and Maintenance
• /
• v.9 no.2
• /
• pp.179-200
• /
• 2022

This paper proposes a data-driven methodology for online early damage identification under changing environmental conditions. The proposed method relies on two data analysis methods: feature-based method and hybrid principal component analysis (PCA) and kernel PCA to separate damage from environmental influences. First, spectral sub-band features, namely, spectral sub-band centroids (SSCs) and log spectral sub-band energies (LSSEs), are proposed as damage-sensitive features to extract damage information from measured structural responses. Second, hybrid modeling by integrating PCA and kernel PCA is performed on the spectral sub-band feature matrix for data normalization to extract both linear and nonlinear features for nonlinear procedure monitoring. After feature normalization, suppressing environmental effects, the control charts (Hotelling T² and SPE statistics) is implemented to novelty detection and distinguish damage in structures. The hybrid PCA-KPCA technique is compared to KPCA by applying support vector machine (SVM) to evaluate the effectiveness of its performance in detecting damage. The proposed method is verified through numerical and full-scale studies (a Bridge Health Monitoring (BHM) Benchmark Problem and a cable-stayed bridge in China). The results demonstrate that the proposed method can detect the structural damage accurately and reduce false alarms by suppressing the effects and interference of environmental variations.