• 한국세라믹학회지
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• 제26권5호
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• pp.645-654
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• 1989

Specimens of WC-Co were indented to measure the resulting crack size and unindented samples were fractured in 3-point flexure to obtain the strength and to measure characteristic features on the fracture surface. Fracture toughness was determined using fractography and compared to those determined using identation techniques. We show that principles of fracture mechanics can be applied WC-Co composites and can be used to analyze the fracture process. The fracture surfaces were examined by scanning electron microscopy and optical microscopy. Characteristic feature observed in glasses, single crystals and polycrystalline materials known as mirror, mist, hackle, and crack branching were identified for these composites. We discuss the importance of fracture surface analysis in determining the failure-initiating sources and the failure behaviorof WC-Co composites.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.612-614
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• 1998

As chip feature size decrease, interconnect delay gains more importance. A accurate timing analysis required to estimate interconnect delay as well as cell delay. In this paper, we present a timing-level delay calculation tool of which the accuracy is bounded within 10% of SPICE results. This delay calculation tool generates delay values in SDF(Standard Delay Format) for parasitic data extracted in SPEF(Standard Parasitic Exchange Format). The efficiency of the tool is easily seen because it uses AWE(Asymptotic Waveform Evaluation) algorithm for interconnect delay calculation, and precharacterized library and effective capacitance model for cell delay calculation.

• 한국초등과학교육학회지:초등과학교육
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• 제24권4호
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• pp.452-464
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• 2005

Since the national curriculum and textbooks are essential to understand the country's educational system, the importance of the textbook analysis should be emphasized to understand the education in North Korea. In this study, the science textbooks of North Korean elementary schools published since the year 2000 were analysed in depth and compared with those of 1990's, then the change in North Korean elementary science education was investigated. As for the external format, the total pages of 3rd grade textbooks of 2000's decreased notably. The 4th grade textbooks show an emphasis on the integrating feature of season-related chapters. The analysis of each category using a content framework of TIMSS shows that the content proportion relating to Earth Science and Physical Science was increased, while the proportion relating to Biological Science was decreased. Besides, changes of proportion of each subcategories were analysed and discussed.

• Smart Structures and Systems
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• 제2권3호
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• pp.253-274
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• 2006

The structural monitoring of multi-wire strands is of importance to prestressed concrete structures and cable-stayed or suspension bridges. This paper addresses the monitoring of strands by ultrasonic guided waves with emphasis on the signal processing and automatic defect classification. The detection of notch-like defects in the strands is based on the reflections of guided waves that are excited and detected by magnetostrictive ultrasonic transducers. The Discrete Wavelet Transform was used to extract damage-sensitive features from the detected signals and to construct a multi-dimensional Damage Index vector. The Damage Index vector was then fed to an Artificial Neural Network to provide the automatic classification of (a) the size of the notch and (b) the location of the notch from the receiving sensor. Following an optimization study of the network, it was determined that five damage-sensitive features provided the best defect classification performance with an overall success rate of 90.8%. It was thus demonstrated that the wavelet-based multidimensional analysis can provide excellent classification performance for notch-type defects in strands.

• International Journal of Computer Science & Network Security
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• 제21권12spc호
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• pp.526-538
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• 2021

Machine and deep learning-based models are emerging techniques that are being used to address prediction problems in biomedical data analysis. DNA sequence prediction is a critical problem that has attracted a great deal of attention in the biomedical domain. Machine and deep learning-based models have been shown to provide more accurate results when compared to conventional regression-based models. The prediction of the gene sequence that leads to cancerous diseases, such as prostate cancer, is crucial. Identifying the most important features in a gene sequence is a challenging task. Extracting the components of the gene sequence that can provide an insight into the types of mutation in the gene is of great importance as it will lead to effective drug design and the promotion of the new concept of personalised medicine. In this work, we extracted the exons in the prostate gene sequences that were used in the experiment. We built a Deep Neural Network (DNN) and Bi-directional Long-Short Term Memory (Bi-LSTM) model using a k-mer encoding for the DNA sequence and one-hot encoding for the class label. The models were evaluated using different classification metrics. Our experimental results show that DNN model prediction offers a training accuracy of 99 percent and validation accuracy of 96 percent. The bi-LSTM model also has a training accuracy of 95 percent and validation accuracy of 91 percent.

• 말소리와 음성과학
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• 제15권2호
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• pp.53-59
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• 2023

Detection of children with autism spectrum disorder (ASD) based on speech has relied on predefined feature sets due to their ease of use and the capabilities of speech analysis. However, clinical impressions may not be adequately captured due to the broad range and the large number of features included. This paper demonstrates that the knowledge-driven speech features (KDSFs) specifically tailored to the speech traits of ASD are more effective and efficient for detecting speech of ASD children from that of children with typical development (TD) than a predefined feature set, extended Geneva Minimalistic Acoustic Standard Parameter Set (eGeMAPS). The KDSFs encompass various speech characteristics related to frequency, voice quality, speech rate, and spectral features, that have been identified as corresponding to certain of their distinctive attributes of them. The speech dataset used for the experiments consists of 63 ASD children and 9 TD children. To alleviate the imbalance in the number of training utterances, a data augmentation technique was applied to TD children's utterances. The support vector machine (SVM) classifier trained with the KDSFs achieved an accuracy of 91.25%, surpassing the 88.08% obtained using the predefined set. This result underscores the importance of incorporating domain knowledge in the development of speech technologies for individuals with disorders.

• 한국정보통신학회논문지
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• 제20권12호
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• pp.2379-2386
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• 2016

본 연구는 최근 급성장하고 있는 모바일 쇼핑시장에서 향후 전략적 마케팅시사점을 얻고자 대학생들을 대상으로 IPA매트릭스를 활용하여 분석하였다. 모바일 쇼핑몰 선택속성에 대한 IPA분석결과는 다음과 같다. 첫째, 21개 속성 중 '제공되는 제품의 신뢰성(6.09)'이 중요도가 가장 높게 나타났으며, '대금결제의 편리성(5.29)'이 수행도가 가장 높게 나타났다. 둘째, 유지 강화가 필요한 영역(Doing great, Keep it up)에는 '대금결제의 편리성', '제공되는 제품의 신뢰성' 등 11개 속성 등이 포함되었다. 셋째, 불만족 영역(Focus here)으로서 시정노력이 필요한 속성으로는 '교환이나 반품처리 및 A/S 등을 위한 대기시간 단축'이 해당되었다. 넷째, 중요도와 수행도 모두 낮은 영역(Low Priority)에는 '푸시/알림이 구매에 도움' 등 3개 속성이 해당되었다. 다섯째, 과잉노력지양 영역(Overdone)에는 '제품종류가 다양' 등 4개 속성이 해당되었다.

• Spatial Information Research
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• 제17권3호
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• pp.381-387
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• 2009

본 연구에서는 항공라이다 측량을 통해 생성된 고해상도 DEM을 산사태 발생 가능성 예측을 위한 객관적인 판단근거로 활용하고자 하였다. 이를 위해 산사태가 발생하지 않은 1개의 사면과 3개의 산사태 발생지역에 대하여 항공레이저 측량데이터에서 얻어진 2m 간격의 DEM을 이용하여 지형해석을 수행하였다. 해석요소에는 경사면 구배와 고유치 비(eigenvalue ratio)를 이용하였으며, 발생한 산사태의 피해현황 파악을 위해 한국도로공사에서 수행한 현장조사 자료를 활용하였다. 고해상도 DEM을 이용한 산사태 발생 가능성 분석 결과, 산사태 발생이 가능한 지형의 특징적인 해석값의 밀도분포가 명확해졌으며, 이러한 밀도분포를 통해 산사태의 발생 예측 및 현재 위험도의 표현이 가능함을 알 수 있었다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.563-565
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• 2021

최근 증가하는 콘텐츠 제공 서비스의 가장 큰 특징은 콘텐츠의 시간의 흐름에 따른 콘텐츠 증가량이 매우 크다는 것이다. 이에 따라 사용자 큐레이션의 중요성이 같이 증가하고 있으며 이를 구현하기 위한 여러 가지 기법들이 사용되고 있다. 본 논문에서는 영상 추천을 위한 기법 중 음성데이터 및 자막을 활용한 분석 기법과 키프레임 추출 기반 영상 비교 기법을 실제 빅데이터 영상 콘텐츠를 대상으로 구현, 적용한 결과에 대하여 비교한다. 또한, 비교결과를 통해 각 분석 기법이 적용될 수 있는 영상 콘텐츠 환경에 대하여 제안한다.

• 한국실내디자인학회논문집
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• 제17권5호
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• pp.157-165
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• 2008

This study confirm the value and the importance of the human sensibility study to add up the new meaning, and to suggest a new value of Korean sensibility study through the understanding of current statusand trend of the sensibility study in the space. The method of the study was to collect date related to the sensibility study and to analyze it focusing on its details. The date was collected from researches published on the website since the establishment of Korean Institute of Interior Design and Architectural Institute of Korea and selected at the keyword search comer. The data was extracted under keywords of research object, research purpose, research method, and analysis method. And then it was quantified with HAYASH lll program and used for analyses according to its pattern and feature. The study shows that nowadays categories representing the current status and trend of the sensibility studies in space consist of the environment, the human, and the space. The contemporary study for sensibility puts the importance on a object and a subject of the study like the environment harmonized with human and space, the humans the subject that essentially uses the spate, and the space for the architecture and the interior that puts human in. Accordingly, the study for human sensibility should develop into the study for the design focused on the intangible relationship such as 'information', 'elements for space design', 'sensibility' beyond the existing tangible categories of environment, human, and space. In addition, in the method ways of study and analysis, those studies for the sensible relationship are required to develop into new types of study applying research methods of various studies beyond the traditional border between human studies, social science, and natural science.