• Steel and Composite Structures
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• v.21 no.2
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• pp.303-321
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• 2016

Tubular column members have been widely adopted in current construction due to its numerous advantages. However, the closed-section profile characteristics of tubular columns severely limit the connection possibilities. Welding type is acceptable but discouraged because of on-site issues. Blind-bolted connection is preferable because of its simplicity, economic benefit, and easy assembly. This paper presents a state-of-the-art review on bolted connections to tubular columns for bare steel tubes, including square and circular sections. Available studies on bolted connections at ambient and elevated temperatures are reviewed, but emphasis is given on the latter. Various methods of determining the connection performance through experimental, analytical, component based, and finite element approaches are examined. Future research areas are also identified.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.812-817
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• 2006

This paper presents an image-space algorithm to real-time collision detection, which is run completely by GPU. For a single object or for multiple objects with no collision, the front and back faces appear alternately along the view direction. However, such alternation is violated when objects collide. Based on these observations, the algorithm has been devised, and the implementation utilizes the state-of-the-art functionalities of GPU such as framebuffer objects(FBO), vertex buffer object(VBO) and occlusion query. The experimental results show the feasibility of GPU-intensive collision detection and its performance gain in real-time applications such as 3D games.

• Bulletin of the Korean Chemical Society
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• v.26 no.5
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• pp.697-706
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• 2005

We review the evolution of electrochemical studies of conducting polymers into the current state-of-the-art based primarily on our work. While conventional electrochemical experiments sufficed for the needs in the phase of studies of both electrochemical synthesis and characterization of conducting polymers, developments of various new experimental techniques have led to their introduction to this field for more refined information. As a result, the conventional electrochemical, spectroelectrochemical, electrochemical quartz crystal microbalance, impedance, and morphological as well as electrical characterization studies all made important contributions to a better understanding of the polymerization mechanisms and the conductive properties of these classes of polymers. From this review, we hereby expect that the electrochemical techniques will continue to play important roles in bringing this field to the practical applications such as nanoscale electronic devices.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.2
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• pp.251-254
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• 2016

An energy-efficient object matching accelerator is proposed for mobile object recognition based on matching prediction scheme. Conventionally, vocabulary tree has been used to save the external memory bandwidth in object matching process but involved massive internal memory transactions to examine each object in a database. In this paper, a novel object matching accelerator is proposed based on matching predictions to reduce unnecessary internal memory transactions by mitigating non-target object examinations, thereby improving the energy-efficiency. Experimental results show a 26% reduction in power-delay product compared to the prior art.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1714-1729
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• 2018

Change detection of remote sensing images is a profound challenge in the field of remote sensing image analysis. This paper proposes a novel change detection method for bitemporal remote sensing images based on feature fusion and fuzzy c-means (FCM). Different from the state-of-the-art methods that mainly utilize a single image feature for difference image construction, the proposed method investigates the fusion of multiple image features for the task. The subsequent problem is regarded as the difference image classification problem, where a modified fuzzy c-means approach is proposed to analyze the difference image. The proposed method has been validated on real bitemporal remote sensing data sets. Experimental results confirmed the effectiveness of the proposed method.

• Journal of Computing Science and Engineering
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• v.11 no.2
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• pp.69-77
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• 2017

Recent GPUs have adopted cache memory to benefit general-purpose GPU (GPGPU) programs. However, unlike CPU programs, GPGPU programs typically have considerably less temporal/spatial locality. Moreover, the L1 data cache is used by many threads that access a data size typically considerably larger than the L1 cache, making it critical to bypass L1 data cache intelligently to enhance GPU cache performance. In this paper, we examine GPU cache access behavior and propose a simple hardware-based GPU cache bypassing method that can be applied to GPU applications without recompiling programs. Moreover, we introduce a hybrid method that integrates static profiling information and hardware-based bypassing to further enhance performance. Our experimental results reveal that hardware-based cache bypassing can boost performance for most benchmarks, and the hybrid method can achieve performance comparable to state-of-the-art compiler-based bypassing with considerably less profiling cost.

• Korean Journal of Child Studies
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• v.28 no.3
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• pp.251-266
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• 2007

The Making-books Program(Byun, unpublished) uses the Arts PROPEL approach based on multiple-intelligences theory(Gardner, 1983). PROPEL is a loose acronym for production, perception and reflection, 3 stages in the learning process. The Making-books Program includes designing rubrics, making-books, and publishing. Effect of the program on creativity was examined by before- and after-testing by TTCT. Participants were 63 7-year-old children with 30 children in the experimental and 33 children in the control group. On the pre-test, there was no between groups difference in the participants' creativity on the TTCT. After 21 treatments, the effectiveness of the Making-books Program was shown by significant between group differences on the post-test.

• Journal of Information Processing Systems
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• v.11 no.2
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• pp.165-172
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• 2015

The inactive student rate is becoming a major problem in most open universities worldwide. In Indonesia, roughly 36% of students were found to be inactive, in 2005. Data mining had been successfully employed to solve problems in many domains, such as for educational purposes. We are proposing a method for preventing inactive students by mining knowledge from student record systems with several state of the art ensemble methods, such as Bagging, AdaBoost, Random Subspace, Random Forest, and Rotation Forest. The most influential attributes, as well as demographic attributes (marital status and employment), were successfully obtained which were affecting student of being inactive. The complexity and accuracy of classification techniques were also compared and the experimental results show that Rotation Forest, with decision tree as the base-classifier, denotes the best performance compared to other classifiers.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2000.04a
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• pp.18-18
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• 2000

In the high lift devices specifications for surface smoothness requirements, as manufacturing tolerances, arise out of aerodynamic consideration to minimize drag. True optimization of tolerances is a multi-disciplinary problem involving fluid mechanics, device performance, manufacturing philosophy and life cycle costing. One of the reasons for degradation of wetted surface is discrete roughness as a consequence of manufacturing defects, collectively termed as one of the excrescences effect. Usually, excrescence drag arising out of discrete roughness is of considerable lower order of magnitude as compared to the total drag of the flight bodies. Nor was there adequate predicting tool to account for the extent of drag degradation. Estimation of excrescence drag remained as a state-of-the art based on experimental results.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.11a
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• pp.169-171
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• 2019

This paper proposes an algorithm to detect persons in bitstream domain by skipping a reconstruction picture process in HEVC decoding. A new 3-channel feature extraction map is introduced in this paper by modelling the relationship between bits per CU density, average PU shape in CU, and total transform coefficients in CU from syntax elements. A state-of-the-art of YOLOv3 detection algorithm is used to detect and localize person on extracted feature maps. Based on the experimental results, the proposed person detection framework can achieve mAP of 0.68 and be able to find persons on feature maps. In addition, the proposed person detection can save decoding time about 60% by removing reconstruction picture process.