• Proceedings of the KSR Conference
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• 한국철도학회 2006년도 추계학술대회 논문집
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• pp.1468-1476
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• 2006

The goal of this thesis is to support safety and reliability characteristics of software intensive critical systems. The verification method developed is innovative from current state of the art in what concerns the verification viewpoint adopted: focusing on software faults, and not, like many other approaches purely on fulfilling functional requirements. As a first step and based on a number of well defined criteria a comparison was made of available literature in the area of static non formal non probabilistic software fault removal techniques. But, None of the techniques evaluated fulfilled all criteria set in isolation. Therefore a new technique was developed based on a combination of two existing techniques: the FMEA and FTA. These two techniques complement each other very well. It is possible to integrate both techniques with commonly used techniques at system level. The resulting new technique can be shown to combine nearly all aspects of existing fault removal techniques.

• Journal of KIISE
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• 제43권7호
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• pp.751-762
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• 2016

This paper presents an overview of the emerging field of quantum machine learning which promises an innovative expedited performance of current classical machine learning algorithms by applying quantum theory. The approaches and technical details of recently developed quantum machine learning algorithms that have been able to substantially accelerate existing classical machine learning algorithms are presented. In addition, the quantum annealing algorithm behind the first commercial quantum computer is also discussed.

• Proceedings of the Korean Vacuum Society Conference
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• 한국진공학회 2013년도 제45회 하계 정기학술대회 초록집
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• pp.264.1-264.1
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• 2013

Graphene is a two-dimensional carbon material whose structure is one-atom-thick planar sheet of sp2-bonded carbon atoms densely packed in a honeycomb crystal lattice. It has drawn significant attention with its distinguished structural and electrical properties. Extremely high mobility and a tunable band gap make graphene potentially useful for innovative approaches to electronics. Although mechanical exfoliation of graphite and decomposition of SiC surfaces upon thermal treatment have been the main method for graphene, they have some limitations in quality and scalability of as-produced graphene films. Solutionphase and solvothermal syntheses of graphene achieved a major improvement for processing, however for device fabrication, a reproducible method such as chemical vapor deposition (CVD) growth yielding high quality films of controlled thickness is required. In this research, we synthesized hexagonal graphene flakes on Cu foils by CVD method and controlled its coverage, density and the size of graphene domains by changing reaction parameters. It is important to control these parameters of graphene growth during synthesis in order to achieve tunable properties and optimized device performance.

• Journal of Preventive Medicine and Public Health
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• 제52권5호
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• pp.277-280
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• 2019

The Ministry of Food and Drug Safety of Korea made an official announcement in March 2018 that the total number of inoculations of Hantaan virus vaccine ($Hantavax^{(R)}$) would change from 3 to 4. Some aspects of this decision remain controversial. Based on the characteristics of Hantaan virus (HTNV) and its role in the pathogenesis of hemorrhagic fever with renal syndrome, it might be difficult to develop an effective and safe HTNV vaccine through the isolate-inactivate-inject paradigm. With the development of high-through-put 'omics' technologies in the 21st century, vaccinomics has been introduced. While the goal of vaccinomics is to develop equations to describe and predict the immune response, it could also serve as a tool for developing new vaccine candidates and individualized approaches to vaccinology. Thus, the possibility of applying the innovative field of vaccinomics to develop a more effective and safer HTNV vaccine should be considered.

• International Journal of High-Rise Buildings
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• 제8권2호
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• pp.83-94
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• 2019

Diagrid structures have emerged in recent decades as an innovative solution for tube tall buildings, capable of merging structural efficiency and aesthetic quality. This paper investigates the effect of the building slenderness (grossly quantified by means of the aspect ratio, i.e., the ratio between the height and the plan dimension) on the structural behavior and on the optimal design parameters of diagrid tall buildings. For this purpose, building models with different slenderness values are designed by adopting preliminary design criteria, based on strength or stiffness demands; in addition, a design method based on a sizing optimization process that employs genetic algorithms is also proposed, with the aim to compare and/or refine the results obtained with simplified approaches.

• Laboraroty Animal Research
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• 제34권4호
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• pp.160-165
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• 2018

Breast cancer remains the second leading cause of cancer death among woman, worldwide, despite advances in identifying novel targeted therapies and the development of treating strategies. Classification of clinical subtypes (ER+, PR+, HER2+, and TNBC (Triple-negative)) increases the complexity of breast cancers, which thus necessitates further investigation. Mouse models used in breast cancer research provide an essential approach to examine the mechanisms and genetic pathway in cancer progression and metastasis and to develop and evaluate clinical therapeutics. In this review, we summarize tumor transplantation models and genetically engineered mouse models (GEMMs) of breast cancer and their applications in the field of human breast cancer research and anti-cancer drug development. These models may help to improve the knowledge of underlying mechanisms and genetic pathways, as well as creating approaches for modeling clinical tumor subtypes, and developing innovative cancer therapy.

• Journal of the Korea Institute of Information Security & Cryptology
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• 제18권6B호
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• pp.233-248
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• 2008

Advances in electronics and wireless communication technologies have enabled the development of large-scale wireless sensor networks (WSNs). There are numerous applications for wireless sensor networks, and security is vital for many of them. However, WSNs suffer from many constraints, including low computation capability, small memory, limited energy resources, susceptibility to physical capture, and the lack of infrastructure, all of which impose unique security challenges and make innovative approaches desirable. In this paper, we present a survey on security issues in wireless sensor networks. We address several network models for security protocols in WSNs, and explore the state of the art in research on the key distribution and management schemes, typical attacks and corresponding countermeasures, entity and message authentication protocols, security data aggregation, and privacy. In addition, we discuss some directions of future work.

• Biomolecules & Therapeutics
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• 제30권4호
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• pp.299-308
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• 2022

T cells are attractive targets for the development of immunotherapy to treat cancer due to their biological features, capacity of cytotoxicity, and antigen-specific binding of receptors. Novel strategies that can modulate T cell functions or receptor reactivity provide effective therapies, including checkpoint inhibitor, bispecific antibody, and adoptive transfer of T cells transduced with tumor antigen-specific receptors. T cell-based therapies have presented successful pre-clinical/clinical outcomes despite their common immune-related adverse effects. Ongoing studies will allow us to advance current T cell therapies and develop innovative personalized T cell therapies. This review summarizes immunotherapeutic approaches with a focus on T cells. Anti-cancer T cell therapies are also discussed regarding their biological perspectives, efficacy, toxicity, challenges, and opportunities.

• International Journal of High-Rise Buildings
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• 제11권3호
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• pp.197-205
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• 2022

One of important design challenges in Chongqing Raffles City Plaza project is Sky Bridge structural design and its connection scheme in high level. This article systematically describes the structural system and its design and analysis methodology, with discussing the impacts on structural performance due to different connection approaches. The seismic isolation scheme in high level is innovatively adopted to the final design. Under the conditions of various load cases, the different models and assumptions are implemented. A full assessment on Sky Bridge's structural performance, seismic isolation, and its connection is conducted in terms of seismic performance based design. By co-operating with architecture, MEP and other disciplines, the structural economy index is fulfilled.

• Journal of Internet Computing and Services
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• 제23권2호
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• pp.97-105
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• 2022

Web services show a rapid evolution and integration to meet the increased users' requirements. Thus, web services undergo updates and may have performance degradation due to undetected faults in the updated versions. Due to these faults, many performances and regression anomalies in web services may occur in real-world scenarios. This paper proposed applying the deep learning model and innovative explainable framework to detect performance and regression anomalies in web services. This study indicated that upper bound and lower bound values in performance metrics provide us with the simple means to detect the performance and regression anomalies in updated versions of web services. The explainable deep learning method enabled us to decide the precise use of deep learning to detect performance and anomalies in web services. The evaluation results of the proposed approach showed us the detection of unusual behavior of web service. The proposed approach is efficient and straightforward in detecting regression anomalies in web services compared with the existing approaches.