• Title/Summary/Keyword: Analysis Techniques

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Study on Derivation of Creative Thinking Techniques for the Fashion Design Development Task (패션디자인 개발 직무에 적합한 발상법 연구)

  • Suh, Seunghee
    • Journal of Fashion Business
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    • v.23 no.2
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    • pp.48-61
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    • 2019
  • The objective of this study was to derive a list of creative thinking techniques applied with the requirements of the appropriate technique for the task of fashion design development among the process of fashion product planning. This was done through the analysis of thinking techniques by the type of thinking and idea method. Also, the study presented how each creative thinking technique derived is applied to the task of developing fashion design. The scope of the study was 'Fashion Design Development Task', which corresponds to the design sketch of a fashion item based on the seasonal design concept derived through the fashion design planning stage. Research on the thinking techniques consisted largely of the process of idea thinking, the elements of creative thinking, the patterns and types of thinking. Four studies by Makoto, Michalko, De Bono, and Cox suggesting that the patterns and types of thinking techniques were analyzed for the purpose of this study as empirical studies through FGI of a group of five fashion experts. The analysis results showed that the thinking techniques suitable for the development of fashion design were derived from the technique of fractionation, attributive listing, scamper, morphological analysis, mind mapping, lotus blossom, pattern language, provocative operation, and forced connection. In particular, it can be confirmed that the scamper was treated as an efficient and practical technique in the many studies.

A comparative study on the subspace based system identification techniques applied on civil engineering structures

  • Bakir, Pelin Gundes;Alkan, Serhat;Eksioglu, Ender Mete
    • Smart Structures and Systems
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    • v.7 no.2
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    • pp.153-167
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    • 2011
  • The Subspace based System Identification Techniques (SSIT) have been very popular within the research circles in the last decade due to their proven superiority over the other existing system identification techniques. For operational (output only) modal analysis, the stochastic SSIT and for operational modal analysis in the presence of exogenous inputs, the combined deterministic stochastic SSIT have been used in the literature. This study compares the application of the two alternative techniques on a typical school building in Istanbul using 100 Monte Carlo simulations. The study clearly shows that the combined deterministic stochastic SSIT performs superior to the stochastic SSIT when the techniques are applied on noisy data from low to mid rise stiff structures.

Fileless cyberattacks: Analysis and classification

  • Lee, GyungMin;Shim, ShinWoo;Cho, ByoungMo;Kim, TaeKyu;Kim, Kyounggon
    • ETRI Journal
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    • v.43 no.2
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    • pp.332-343
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    • 2021
  • With cyberattack techniques on the rise, there have been increasing developments in the detection techniques that defend against such attacks. However, cyber attackers are now developing fileless malware to bypass existing detection techniques. To combat this trend, security vendors are publishing analysis reports to help manage and better understand fileless malware. However, only fragmentary analysis reports for specific fileless cyberattacks exist, and there have been no comprehensive analyses on the variety of fileless cyberattacks that can be encountered. In this study, we analyze 10 selected cyberattacks that have occurred over the past five years in which fileless techniques were utilized. We also propose a methodology for classification based on the attack techniques and characteristics used in fileless cyberattacks. Finally, we describe how the response time can be improved during a fileless attack using our quick and effective classification technique.

A Review on the Analytical Techniques for the Determination of Fluorine Contents in Soil and Solid Phase Samples (토양 및 고체시료 중 불소함량 측정기법)

  • An, Jinsung;Kim, Joo-Ae;Yoon, Hye-On
    • Journal of Soil and Groundwater Environment
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    • v.18 no.1
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    • pp.112-122
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    • 2013
  • Current status of soil contamination with fluorine and its source were investigated. The basic principles and procedures of various techniques for the analysis of fluorine contents in soil and solid phase samples were summarized in this review. Analysis of fluorine in solid matrices can be achieved by two types of techniques: (i) UV/Vis spectrophotometer or ion selective electrode (ISE) analysis after performing appropriate extraction steps and (ii) direct solid analysis. As the former cases, the standard method of Korean ministry of environment, alkali fusion-ISE method, pyrohydrolysis, oxygen bomb combustion, aqua regia digestion-automatic analysis, and sequential extraction-ISE method were introduced. In addition, direct analysis methods (i.e., X-ray fluorescence spectrometry and proton induced gamma-ray emission spectrometry) and atomic spectrometry combining with the equipment for introducing solid phase sample were also reviewed. Fluorine analysis techniques can be reasonably selected through site-specific information such as matrix condition, contamination level, the amount of samples and the principles of various methods for the analysis of fluorine presented in this review.

Automated ground penetrating radar B-scan detection enhanced by data augmentation techniques

  • Donghwi Kim;Jihoon Kim;Heejung Youn
    • Geomechanics and Engineering
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    • v.38 no.1
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    • pp.29-44
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    • 2024
  • This research investigates the effectiveness of data augmentation techniques in the automated analysis of B-scan images from ground-penetrating radar (GPR) using deep learning. In spite of the growing interest in automating GPR data analysis and advancements in deep learning for image classification and object detection, many deep learning-based GPR data analysis studies have been limited by the availability of large, diverse GPR datasets. Data augmentation techniques are widely used in deep learning to improve model performance. In this study, we applied four data augmentation techniques (geometric transformation, color-space transformation, noise injection, and applying kernel filter) to the GPR datasets obtained from a testbed. A deep learning model for GPR data analysis was developed using three models (Faster R-CNN ResNet, SSD ResNet, and EfficientDet) based on transfer learning. It was found that data augmentation significantly enhances model performance across all cases, with the mAP and AR for the Faster R-CNN ResNet model increasing by approximately 4%, achieving a maximum mAP (Intersection over Union = 0.5:1.0) of 87.5% and maximum AR of 90.5%. These results highlight the importance of data augmentation in improving the robustness and accuracy of deep learning models for GPR B-scan analysis. The enhanced detection capabilities achieved through these techniques contribute to more reliable subsurface investigations in geotechnical engineering.

Timing Analysis Techniques Review for sub-30 nm Circuit Designs

  • Kim, Ju-Ho;Han, Sang-Woo;Jewell, Roy
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.10 no.4
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    • pp.292-299
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    • 2010
  • With scaled technology, timing analysis of circuits becomes more and more difficult. In this paper, we review recently developed circuit simulation techniques created to deal with the cost issues of transistor-level simulations. Various techniques for fast SPICE simulations and Monte Carlo simulations are introduced. Moreover, process and aging variation issues are mentioned, along with promising methodologies.

Nonlinear Failure Analysis of Reinforced Concrete Structures using Fiber Model (파이버모델에 의한 철근콘크리트 구조물의 비선형 파괴해석)

  • 송하원;김일철;변근주
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1998.04a
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    • pp.127-134
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    • 1998
  • The objectives of this paper is to analyze the reinforced concrete structures by using fiber model. In this study, the fiber modeling techniques including modeling of support conditions are studied. In order to verify the modeling techniques, analysis results obtained for reinforced concrete cantilever beam and reinforced concrete T-girder bridge under cyclic loading are compared with experimental results from full scale test. From the comparison, it is shown that the modeling techniques in this study can be well applied to the nonlinear failure analysis of reinforced concrete structures with porper modifications.

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A Study on the Effect of Innovation Performance Through Business Innovation Activities and Techniques for the Small & Medium Size Company (중소기업의 혁신활동과 기법이 혁신성과에 미치는 영향에 관한 연구)

  • Moon, Hee Young;Chang, Seog Ju
    • Journal of Korean Society for Quality Management
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    • v.43 no.2
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    • pp.151-168
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    • 2015
  • Purpose: The purpose of this study was to investigate the effect of the innovation performance through business innovation activities by small and medium size company as well as to test the moderating effects on the innovation techniques'understanding and conformance. Methods: The data for the empirical analysis was collected from 132 companies mainly located in Jeolla and Gyeonggi Province. Cronbach's alpha factor analysis, multiple regression analysis and hierarchical multiple regression were used for statistical methods. Results: The Statistical analysis results show that innovation performance through business innovation techniques and activities was effected by CEO leadership, company capability and training for employees. Conclusion: Through this study we tried to give some suggestions for improving innovation performance through business innovation activities for the small and medium size company.

Oral Metagenomic Analysis Techniques

  • Chung, Sung-Kyun
    • Journal of dental hygiene science
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    • v.19 no.2
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    • pp.86-95
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    • 2019
  • The modern era of microbial genome analysis began in earnest in the 2000s with the generalization of metagenomics and gene sequencing techniques. Studying complex microbial community such as oral cavity and colon by a pure culture is considerably ineffective in terms of cost and time. Therefore, various techniques for genomic analysis have been developed to overcome the limitation of the culture method and to explore microbial communities existing in the natural environment at the gene level. Among these, DNA fingerprinting analysis and microarray chip have been used extensively; however, the most recent method of analysis is metagenomics. The study summarily examined the overview of metagenomics analysis techniques, as well as domestic and foreign studies on disease genomics and cluster analysis related to oral metagenome. The composition of oral bacteria also varies across different individuals, and it would become possible to analyze what change occurs in the human body depending on the activity of bacteria living in the oral cavity and what causality it has with diseases. Identification, isolation, metabolism, and presence of functional genes of microorganisms are being identified for correlation analysis based on oral microbial genome sequencing. For precise diagnosis and treatment of diseases based on microbiome, greater effort is needed for finding not only the causative microorganisms, but also indicators at gene level. Up to now, oral microbial studies have mostly involved metagenomics, but if metatranscriptomic, metaproteomic, and metabolomic approaches can be taken together for assessment of microbial genes and proteins that are expressed under specific conditions, then doing so can be more helpful for gaining comprehensive understanding.

Evaluation of effectiveness of fault-tolerant techniques in a digital instrumentation and control system with a fault injection experiment

  • Kim, Man Cheol;Seo, Jeongil;Jung, Wondea;Choi, Jong Gyun;Kang, Hyun Gook;Lee, Seung Jun
    • Nuclear Engineering and Technology
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    • v.51 no.3
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    • pp.692-701
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    • 2019
  • Recently, instrumentation and control (I&C) systems in nuclear power plants have undergone digitalization. Owing to the unique characteristics of digital I&C systems, the reliability analysis of digital systems has become an important element of probabilistic safety assessment (PSA). In a reliability analysis of digital systems, fault-tolerant techniques and their effectiveness must be considered. A fault injection experiment was performed on a safety-critical digital I&C system developed for nuclear power plants to evaluate the effectiveness of fault-tolerant techniques implemented in the target system. A software-implemented fault injection in which faults were injected into the memory area was used based on the assumption that all faults in the target system will be reflected in the faults in the memory. To reduce the number of required fault injection experiments, the memory assigned to the target software was analyzed. In addition, to observe the effect of the fault detection coverage of fault-tolerant techniques, a PSA model was developed. The analysis of the experimental result also can be used to identify weak points of fault-tolerant techniques for capability improvement of fault-tolerant techniques