• Wind and Structures
• /
• 제39권1호
• /
• pp.1-14
• /
• 2024

Widespread damages from extreme winds have attracted lots of attentions of the resilience assessment of power distribution systems. With many related environmental parameters as well as numerous power infrastructure components, such as poles and wires, the increased challenge of power asset management before, during and after extreme events have to be addressed to prevent possible cascading failures in the power distribution system. Many extreme winds from weather events, such as hurricanes, generate widespread damages in multiple areas such as the economy, social security, and infrastructure management. The livelihoods of residents in the impaired areas are devastated largely due to the paucity of vital utilities, such as electricity. To address the challenge of power grid asset management, power system clustering is needed to partition a complex power system into several stable clusters to prevent the cascading failure from happening. Traditionally, system clustering uses the Binary Decision Diagram (BDD) to derive the clustering result, which is time-consuming and inefficient. Meanwhile, the previous studies considering the weather hazards did not include any detailed weather-related meteorologic parameters which is not appropriate as the heterogeneity of the parameters could largely affect the system performance. Therefore, a fragility-based network hierarchical spectral clustering method is proposed. In the present paper, the fragility curve and surfaces for a power distribution subsystem are obtained first. The fragility of the subsystem under typical failure mechanisms is calculated as a function of wind speed and pole characteristic dimension (diameter or span length). Secondly, the proposed fragility-based hierarchical spectral clustering method (F-HSC) integrates the physics-based fragility analysis into Hierarchical Spectral Clustering (HSC) technique from graph theory to achieve the clustering result for the power distribution system under extreme weather events. From the results of vulnerability analysis, it could be seen that the system performance after clustering is better than before clustering. With the F-HSC method, the impact of the extreme weather events could be considered with topology to cluster different power distribution systems to prevent the system from experiencing power blackouts.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제10권9호
• /
• pp.4087-4107
• /
• 2016

The current cloud computing paradigm is still vulnerable to a significant number of system failures. The increasing demand for fault tolerance and resilience in a cost-effective and device-independent manner is a primary reason for creating an effective means to address system dependability and availability concerns. This paper focuses on online failure prediction for cloud computing systems using system runtime data, which is different from traditional tolerance techniques that require an in-depth knowledge of underlying mechanisms. A 'failure prediction' approach, based on Cloud Theory (CT) and the Hidden Markov Model (HMM), is proposed that extends the HMM by training with CT. In the approach, the parameter ω is defined as the correlations between various indices and failures, taking into account multiple runtime indices in cloud computing systems. Furthermore, the approach uses multiple dimensions to describe failure prediction in detail by extending parameters of the HMM. The likelihood and membership degree computing algorithms in the CT are used, instead of traditional algorithms in HMM, to reduce computing overhead in the model training phase. Finally, the results from simulations show that the proposed approach provides very accurate results at low computational cost. It can obtain an optimal tradeoff between 'failure prediction' performance and computing overhead.

• 종양간호연구
• /
• 제11권2호
• /
• pp.101-107
• /
• 2011

Purpose: This study was to understand and explain the adjustment of cancer patients receiving chemotherapy. Variables in this model were social support, uncertainty, resilience and coping. Methods: The data were collected for approximately five months from May through to September 2006 with cancer patients receiving chemotherapy or cancer patients finished chemotherapy using self-administered questionnaires. Descriptive statistics program, Amos 5.0, was employed to verify the goodness of the hypothetic model and the hypotheses formulated in the study. Results: The fitness of the finalized model turned out to be improved ($X^2$=332.644, df=70, GFI= .809, AGFI= .714, RMSEA= .138, AIC=402.644). Those variables made a 60.8% prediction of the patients adjustment. Conclusion: The hypothetic model presented in the study could serve to explain the adjustment of cancer patients receiving chemotherapy. Moreover, the use of the conceptual framework of the theory of planned nursing intervention would be very worthwhile as a strategy to boost the adjustment of cancer patients when receiving chemotherapy.

• 한국기후변화학회지
• /
• 제5권3호
• /
• pp.257-266
• /
• 2014

This study aims to understand abnormal climate caused by impacts of climate change and to suggest the direction of urban planning focusing on adaptation to climate change. The study consists of theory consideration and case study(Chicago, Philadelphia, Seattle). As a result, the main impacts of climate change faced by urban areas are heat wave, precipitation, and drought. To prevent these impacts, it is important to prepare methods of urban planning as followings: planning for land use, park and green considering the climate patterns, establishing and managing water resources systems similar to the nature, securing renewable energy resources, and transportation facilities and exterior space with proof against climate. It is especially necessary to introduce infrastructures related to storm water, green roof, shading tree planting, green space, and permeable pavement. Finally, in order to realize urban planning for adaptation to climate change, it is needed to make the detailed and specific goal and strategy for the climate change adaptation plan and to extend the scope from the goals to an action plan, a detailed plan, and a design guideline.

• Journal of Contemporary Eastern Asia
• /
• 제19권2호
• /
• pp.40-60
• /
• 2020

Among Filipino entertainers in Japan, trans women (transgender women) or transpinay (Filipino trans woman) entertainers remain understudied compared to cisgender women. Though the number of entertainers has declined, transpinay entertainers remain relevant as transgender issues continue to be salient globally. This study explains the gendered experiences of the transpinay migrants, particularly in entertainment work and their relationships, which are different from cisgender Filipino women entertainers' experiences. Using grounded theory and drawing on concepts of performativity in interactions to analyze the narratives of transpinay entertainers, I delve into how transpinay entertainers negotiate their gender and migrant identities as they establish professional and personal relationships. Moreover, the transpinays' entertainment work is a significant contributing factor to their sense of belonging in Japan, as they form relationships with colleagues, clients, and partners who support them and, thereby, sustain their lifestyles as trans women. The transpinay entertainers' flows of migration between Japan and the Philippines reveal that they embrace various aspects of social remittances and use them to their advantage to create and enhance their transpinay identity in Japan. By examining the transpinays' migrant experiences, this study aims to elucidate the gendered experiences of transpinay entertainers, which involve significant negotiations in their migration pathways notably different from cisgender Filipino women entertainers, reveal resilience.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2023년도 학술발표회
• /
• pp.181-181
• /
• 2023

Flood is a major threat to human society, and scientific assessment of flood risk in human living areas is an important task. In this study, two different methods were used to evaluate the flood in Ulsan City, and the results were comprehensively compared and analyzed. Based on the fuzzy mathematics and VIKOR method of the multi-objective decision system, similar evaluation results were obtained in the study area. The results show that due to the large number of rivers in Ulsan City and the relatively high exposure index, the whole city faces a high risk of flooding. However, fuzzy mathematics theory pays more attention to the negative impact of floods on people, and the adaptability in the Nam-gu District is lower. In contrast, the VIKOR method pays more attention to the positive role of the economy and population in flood protection, and thus obtains a higher score. Both approaches demonstrate that the city of Ulsan faces a high risk of flooding and that its citizens and policymakers need to invest in preventing flood damage.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2021년도 학술발표회
• /
• pp.147-147
• /
• 2021

A partition of water distribution network (WDN) into district metered areas (DMAs) brings the efficiency and efficacy for water network operation and management (O&M), especially in monitoring pressure and leakage. Traditionally, the DMA configurations (i.e., number, shape, and size of DMAs) are permanent and cannot be changed occasionally. This leads to changes in water quality and reduced network redundancy lowering network resilience against abnormal conditions such as water demand variability and mechanical failures. This study proposes a framework to automatically divide a WDN into dynamic DMA configurations, in which the DMA layouts can self-adapt in response to abnormal scenarios. To that aim, a complex graph theory is adopted to sectorize a WDN into multiscale DMA layouts. Then, different failure-based scenarios are investigated on the existing DMA layouts. Here, an optimization-based model is proposed to convert existing DMA layouts into dynamic layouts by considering existing valves and possibly placing new valves. The objective is to minimize the alteration of flow paths (i.e., flow direction and velocity in the pipes) while preserving the hydraulic performance of the network. The proposed method is tested on a real complex WDN for demonstration and validation of the approach.

• Steel and Composite Structures
• /
• 제49권4호
• /
• pp.407-417
• /
• 2023

After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. Many domain schemes based on the measured vibration computations, including least squares estimation and neural fuzzy logic control, have been studied and found to be effective for online/offline monitoring of structural damage. Traditional strategies require all external stimulus data (input data) which have been measured available, but this may not be the generalized for all structures. In this article, a new method with unknown inputs (excitations) is provided to identify structural matrix such as stiffness, mass, damping and other nonlinear parts, unknown disturbances for example. An analytical solution is thus constructed and presented because the solution in the existing literature has not been available. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.

• Computers and Concrete
• /
• 제33권4호
• /
• pp.385-398
• /
• 2024

As concrete dominates the construction industry, alternatives to traditionally used steel reinforcement are being sought. This study explored the suitability of carbon fiber-reinforced polymer (CFRP) as a substitute within rigid frames, focusing on its impact on section ductility and overall structural durability against seismic events. However, current design guidelines address quasi-static loads, leaving a gap for dynamic or extreme circumstances. Our approach included multiscale simulations, parametric study, and energy dissipation analyses, drawing upon a unique adaptation of modified compression field theory. In our efforts to optimize macro and microparameters to improve yield strength, manage brittleness, and govern failure modes, we also recognized the potential of CFRP's high corrosion resistance. This characteristic of CFRP could significantly reduce the frequency of required repairs, thereby contributing to enhanced durability of the structures. The research reveals that CFRP's durability and seismic resistance are attributed to plastic joints within compressed fibers. Notably, CFRP can impart ductility to structural designs, effectively balancing its inherent brittleness, particularly when integrated with quasi-brittle materials. This research challenges the notion that designing bendable components with carbon fiber reinforcement is impractical. It shows that creating ductile bending components with CFRP in concrete is feasible despite the material's brittleness. This funding overturns conventional assumptions and opens new avenues for using CFRP in structural applications where ductility and resilience are crucial.

• Steel and Composite Structures
• /
• 제52권5호
• /
• pp.571-581
• /
• 2024

After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. This work studies the tracking control problem of a class of strict-feedback nonlinear systems with input saturation nonlinearity. Under the framework of dynamic surface control design, RBF neural networks are introduced to approximate the unknown nonlinear dynamics. In order to address the impact of input saturation nonlinearity in the system, an auxiliary control system is constructed, and by introducing a class of first-order low-pass filters, the problems of large computation and computational explosion caused by repeated differentiation are effectively solved. In response to unknown parameters, corresponding adaptive updating control laws are designed. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.