• Explosives and Blasting
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• v.36 no.4
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• pp.9-15
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• 2018

Since the rock fragmentation by blasting can affect the subsequent processes including loading, hauling and secondary crushing, its control is essential for the assessment of blasting efficiency as well as production cost. In this study, we were analyzed the rock fragmentation by the direction of artificial joint. The underground blasting experiments were performed after forming the vertical and horizontal artificial joints. The blast fragmentation was conducted by the split-desktop which is a 2D image processing program. As a result, it was found that the horizontal artificial joint was evaluated to have lower overall the size of muck pile than the vertical artificial joint and the distribution of the size of muck pile was varied. It is possible that the direction of artificial joint could suppress the occur of oversize muck pile and control to a certain size or less.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.5074-5094
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• 2016

Screen splitting is one of the fundamental tasks in different methods including video and image compression, screen classification, screen content coding and the like. These methods in turn support various applications in data communications, remote screen sharing, remote desktop delivery to assist teaching-learning, telemedicine, Desktop as a Service etc. In the literature we find systems requiring splitting assumes a fixed size split that do not change dynamically, also there is no analysis why that split is chosen in terms of performance. By doing mathematical analysis this paper first finds the efficient splitting schemes that can be easily automated to make a system adaptive. Thereafter, taking the screen motion detection as a case study, it demonstrates the effects of various splitting methods on motion detection performance. The simulation results clearly shows how classification performances varies with different splitting which will facilitate to choose the best splitting for a specific application scenario as well as making the system adaptive by providing dynamic splitting.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.419-424
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• 2006

본 연구는 데스크탑 PC 환경에서 사용될 수 있는 다양한 적응형 메뉴 인터페이스의 사용성을 평가한다. 선택 빈도에 따라 자동으로 변화하는 2가지 방식의 Adaptive menu와 사용자가 메뉴 내에서 원하는 항목의 위치를 직접 변경하는 Adaptable menu의 사용성을 일반적으로 많이 이용되는 Traditional menu와 비교하기 위해 사용자를 동원한 평가 실험을 수행하였다. Adaptive menu에는 선택 빈도가 높은 메뉴 항목이 메뉴의 상단으로 이동하는 Adaptive split menu와 자주 선택되는 항목이 굵은 글씨로 표현되는 Adaptive style menu가 포함된다. 각 방식의 적응형 메뉴가 자주 선택되는 메뉴 항목의 변화에 따라 얼마나 민감하게 영향을 받는지 비교하기 위해, 두 개의 각기 다른 선택 빈도 분포가 이용되었다. 각 실험 조건 별로 사용자가 메뉴 항목을 선택하는 데 걸린 시간과 오류 회수를 측정하였으며, 피실험자로 하여금 시인성, 효율성, 전반적 선호도 등의 주관적인 만족도를 평가하도록 하였다. 각각의 종속 변수들은 분산 분석(ANOVA), Chi-square test, Friedman test 등의 기법을 이용해 분석되었다. 분석 결과, Adaptable menu가 다른 방식의 메뉴들에 비해 수행도와 만족도 모두 높은 것으로 나타났으며, Adaptive split menu는 상대적으로 현실적인 조건 하에서 큰 효용을 갖지 못하는 것으로 나타났다. Adaptive style menu는 수행도 측면에서는 일반적인 메뉴와 큰 차이가 없었지만, 자주 선택되는 항목을 쉽게 파악할 수 있게 해 주고, 선택 빈도의 변화에도 민감하지 않기 때문에 사용자들에게 선호되는 것으로 나타났다. 본 연구의 결과는 데스크탑 PC의 적응형 메뉴 설계에 대한 이용될 수 있으며, 추후 휴대용 정보기기의 적응형 메뉴에 대한 사용성 연구의 기초 자료로도 활용될 수 있을 것으로 기대된다.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.143-151
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• 2013

NAND flash-based SSDs (Solid State Drive) have advantages of fast input/output performance and low power consumption so that they could be widely used as storages on tablet, desktop PC, smart-phone, and server. But, SSD has the disadvantage of wear-leveling due to increase of the number of writes. In order to improve the lifespan of the SSD, a variety of data deduplication techniques have been introduced. General fixed-size splitting method allocates fixed size of chunk without considering locality of data so that it may execute unnecessary chunking and hash key generation, and variable-size splitting method occurs excessive operation since it compares data byte-by-byte for deduplication. This paper proposes adaptive chunking method based on application locality and file name locality of written data in SSD-based server storage. The proposed method split data into 4KB or 64KB chunks adaptively according to application locality and file name locality of duplicated data so that it can reduce the overhead of chunking and hash key generation and prevent duplicated data writing. The experimental results show that the proposed method can enhance write performance, reduce power consumption and operation time compared to existing variable-size splitting method and fixed size splitting method using 4KB.