• 한국기계가공학회지
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• 제18권8호
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• pp.31-37
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• 2019

The inter-development of FMECA is very important to assess the effect of potential failures during system operation on mission, safety and performance. Among these, criticality analysis is a core task that identifies items with high risk and selects the analyzed objects as the key management targets and reflects their effects to the design optimization. In this paper, we analyze the theory related to criticality analysis following US military standard, and propose a method to quantify the failure effect probability for objective criticality analysis. The criticality analysis according to the US military standard depends on the subjective judgment of the failure probability. The methodology for quantifying the failure effect probability is presented by using the reliability theory and the Bayes theorem. The failure rate is calculated by applying the method to quantify failure effect probability.

• Radiation Oncology Journal
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• 제38권1호
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• pp.18-25
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• 2020

Purpose: This study was aim to evaluate the patterns of failure according to radiotherapy (RT) target volume for cervical lymph nodes in metastases of unknown primary origin in head and neck region (HNMUO). Materials and Methods: Sixty-two patients with HNMUO between 1998 and 2016 were retrospectively reviewed. We analyzed the clinical outcomes and primary site failure depending on the radiation target volume. The target volume was classified according to whether the potential head and neck mucosal sites were included and whether the neck node was treated involved side only or bilaterally. Results: Potential mucosal site RT (mucosal RT) was done to 23 patients and 39 patients did not receive mucosal RT. Mucosal RT showed no significant effect on overall survival (OS) and locoregional recurrence (LRR). The location of primary site failure encountered during follow-up period was found to be unpredictable and 75% of patients with recurrence received successful salvage therapies. No significant differences in OS and LRR were found between patients treated to unilateral (n = 35) and bilateral neck irradiation (n = 21). Treatment of both necks resulted in significantly higher mucositis. Conclusions: We found no advantages in OS and LRR of patients with HNMUO when mucosal sites and bilateral neck node were included in the radiation target volume.

• International Journal of Heart Failure
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• 제6권1호
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• pp.11-19
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• 2024

The prevalence of heart failure (HF) is increasing, necessitating accurate diagnosis and tailored treatment. The accumulation of clinical information from patients with HF generates big data, which poses challenges for traditional analytical methods. To address this, big data approaches and artificial intelligence (AI) have been developed that can effectively predict future observations and outcomes, enabling precise diagnoses and personalized treatments of patients with HF. Machine learning (ML) is a subfield of AI that allows computers to analyze data, find patterns, and make predictions without explicit instructions. ML can be supervised, unsupervised, or semi-supervised. Deep learning is a branch of ML that uses artificial neural networks with multiple layers to find complex patterns. These AI technologies have shown significant potential in various aspects of HF research, including diagnosis, outcome prediction, classification of HF phenotypes, and optimization of treatment strategies. In addition, integrating multiple data sources, such as electrocardiography, electronic health records, and imaging data, can enhance the diagnostic accuracy of AI algorithms. Currently, wearable devices and remote monitoring aided by AI enable the earlier detection of HF and improved patient care. This review focuses on the rationale behind utilizing AI in HF and explores its various applications.

• Journal of Mechanical Science and Technology
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• 제20권4호
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• pp.473-481
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• 2006

Predicting fatigue life by numerical methods was almost impossible in the field of rubber materials. One of the reasons is that there is not obvious fracture criteria caused by nonstandardization of material and excessively various way of mixing process. But, tearing energy as fracture factor can be applied to a rubber-like material regardless of different types of fillers, relative to other fracture factors and the crack growth process of rubber could be considered as the whole fatigue failure process by the existence of potential defects in industrial rubber components. This characteristic of fatigue failure could make it possible to predict the fatigue life of rubber components in theoretical way. FESEM photographs of the surface of industrial rubber components were analyzed for verifying the existence and distribution of potential defects. For the prediction of fatigue life, theoretical way of evaluating tearing energy for the general shape of test-piece was proposed. Also, algebraic expression for the prediction of fatigue life was derived from the rough cut growth rate equation and verified by comparing with experimental fatigue lives of dumbbell fatigue specimen in various loading condition.

• Asian Journal of Innovation and Policy
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• 제7권1호
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• pp.79-102
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• 2018

In an entrepreneurial ecosystem, the failure rate of startups is extremely high at 90%, and every startup that fails becomes an orphan. This phenomenon leads to higher costs of failure for the entrepreneurs in the ecosystem. Failed startups have many lessons to offer to the ecosystem and offer guidance to the potential entrepreneur, and this area is not fully explored compared to the literature on successful startups. We use a case based method distinguishing a failed startup and a successful startup, studying the entrepreneurial characteristics and firm level factors which cause the failures, in the technology startup ecosystem of Bangalore. We study one of the modes of exit adopted by failed startup entrepreneurs and draw key lessons on causes that culminate in failures. We have identified that factors such as the time to minimum viable product cycle, time for revenue realization, founders' complementary skillsets, age of founders with their domain expertise, personality type of founders, attitude towards financial independence and willingness to avail mentorship at critical stages, will decisively differentiate failed startups from the successful ones. Accordingly, implications have been derived for potential entrepreneurs for reducing the cost of failures in the entrepreneurial ecosystem.

• Molecules and Cells
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• 제46권11호
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• pp.655-663
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• 2023

Autophagy dysfunction is associated with human diseases and conditions including neurodegenerative diseases, metabolic issues, and chronic infections. Additionally, the decline in autophagic activity contributes to tissue and organ dysfunction and aging-related diseases. Several factors, such as down-regulation of autophagy components and activators, oxidative damage, microinflammation, and impaired autophagy flux, are linked to autophagy decline. An autophagy flux impairment (AFI) has been implicated in neurological disorders and in certain other pathological conditions. Here, to enhance our understanding of AFI, we conducted a comprehensive literature review of findings derived from two well-studied cellular stress models: glucose deprivation and replicative senescence. Glucose deprivation is a condition in which cells heavily rely on oxidative phosphorylation for ATP generation. Autophagy is activated, but its flux is hindered at the autolysis step, primarily due to an impairment of lysosomal acidity. Cells undergoing replicative senescence also experience AFI, which is also known to be caused by lysosomal acidity failure. Both glucose deprivation and replicative senescence elevate levels of reactive oxygen species (ROS), affecting lysosomal acidification. Mitochondrial alterations play a crucial role in elevating ROS generation and reducing lysosomal acidity, highlighting their association with autophagy dysfunction and disease conditions. This paper delves into the underlying molecular and cellular pathways of AFI in glucose-deprived cells, providing insights into potential strategies for managing AFI that is driven by lysosomal acidity failure. Furthermore, the investigation on the roles of mitochondrial dysfunction sheds light on the potential effectiveness of modulating mitochondrial function to overcome AFI, offering new possibilities for therapeutic interventions.

• Structural Engineering and Mechanics
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• 제75권3호
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• pp.401-414
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• 2020

Unlike the existing truss models for shear and torsion analysis, in this study, the torsional capacities of reinforced concrete (RC) members were estimated by introducing multi-potential capacity criteria that considered the aggregate interlock, concrete crushing, and spalling of concrete cover. The smeared truss model based on the fixed-angle theory was utilized to obtain the torsional behavior of reinforced concrete member, and the multi-potential capacity criteria were then applied to draw the capacity of the member. In addition, to avoid any iterative calculation in the existing torsional behavior model, a simple strength model was suggested that considers key variables, such as the effective thickness of torsional member, principal stress angle, and strain effect that reduces the resistance of concrete due to large longitudinal tensile strain. The proposed multi-potential capacity concept and the simple strength model were verified by comparing with test results collected from the literature. The study found that the multi-potential capacity could estimate in a rational manner not only the torsional strength but also the failure mode of RC members subjected to torsional moment, by reflecting the reinforcing index in both transverse and longitudinal directions, as well as the sectional and material properties of RC members.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2000년도 가을 학술발표회 논문집
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• pp.167-174
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• 2000

Profiles of discontinuities through scanline method were investigated for the analysis of rock slope stability. Lower hemispheric projection method was used to evaluate the geometric stability and failure potential of these discontinuities. Also, safety factor was evaluated for the discontinuities of failure potential using by limit equilibrium analysis. Then, displacements of rock block due to the discontinuities were displayed by using the program UDEC(Universal Distinct Element Code) which applied the Distinct Element Method. When we determine the cut-slope in design, the characteristics of discontinuities is not represented only by strength parameters of intact rock. Therefore it is more reasonable method in assuring stability that first, construction would be preceded by the cut-slope of preliminary design, and then, cut-slope would be redetermined by elaborate site investigation in processing construction.

• 산업경영시스템학회지
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• 제31권4호
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• pp.162-167
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• 2008

FMEA (failure mode and effect analysis)is a widely used technique to assess or to improve reliability of product not only at early stage of design and development, but at the process and service phase during the product life cycle. In designing a service system, this study proposes a fuzzy service FMEA with the service blueprints as a tool which describes customer actions, onstage contact employees actions, backstage contact employees actions, support processes, and physical evidences, in order to analyse and inform service delivery system design. We fuzzified only two risk factors, occurrence and severity, to more effectively assess the potential failure modes in service. Proposed fuzzy risk grades are applied to Gaussian membership function, defuzzified into Fuzzy Inference System, and eventually identified the ranks on the potential fail points.

• 산업경영시스템학회지
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• 제33권4호
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• pp.209-217
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• 2010

Reliability tools such as QFD and FMEA identify voice of customer related to product design, its use, how failures may occur, the severity of such failures, and the probability of the failure occurring. With these identified items, a development team can focus on the design process and the major issues facing the product in its potential use environment for the customer. The purpose of this research is to develop a reliability estimation process of agricultural machinery components using QFD, FMEA, and field failure data. Based on QFD method, customer requirements, engineering design elements and part characteristics were deployed. Using the field failure data, failures are investigated, and Weibull B10 life are estimated. This estimation process is useful for preparing the design input and planning the durability target.