• Annual Conference on Human and Language Technology
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• 2014.10a
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• pp.38-43
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• 2014

본 논문은, 현존하는 영어 FrameNet 데이터를 기반으로 하여, FrameNet에 대한 전문 지식이 없는 번역가들을 통해 수행할 수 있는 한국어 FrameNet의 수동 구축 개발 과정을 제시한다. 우리 연구팀은 실제로, NLTK가 제공하는 영어 FrameNet 버전 1.5의 Full Text를 이루고 있는 5,945개의 문장들 중에서, Frame 데이터를 가진 4,025개의 문장들을 추출해내어, 번역가들에 의해 한국어로 수동번역 함으로써, 한국어 FrameNet 구축 개발을 향한 의미 있는 초석을 마련하였으며, 제시한 방법의 실효성을 입증하는 연구결과들을 웹에 공개하기도 하였다.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.42 no.1
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• pp.1-10
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• 2006

Present study was conducted to improve the spring frame net trap for conger eel, Conger myriaster which prevents by-catch and protects immature fish. A series of comparative fishing experiment was carried out in water off the south-east coast of Korea from Nov. 2004 to Jul. 2005. And analyzed the amount of catch, by-catch rate, and CPUE, etc. of experimental traps which were the spring frame net traps, sorted four types of flappers. And the compared gear was a plastic conger eel pot. The conclusions were as follows. By-catch rates of spring frame net trap with the compressed flapper bound by nylon mono-filament was about 0-3%. CPUE of spring frame net trap with the compressed flapper was about 50-60% lower than that of traditional and plastic pot. And in case of conger eel that the total length is over 350mm, CPUE was little different on each type of flapper of every mesh size.

• Smart Media Journal
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• v.9 no.1
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• pp.23-29
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• 2020

This paper presents an approach for dynamic hand gesture recognition by using algorithm based on 3D Convolutional Neural Network (3D_CNN), which is later extended to 3D Residual Networks (3D_ResNet), and the neural network based key frame selection. Typically, 3D deep neural network is used to classify gestures from the input of image frames, randomly sampled from a video data. In this work, to improve the classification performance, we employ key frames which represent the overall video, as the input of the classification network. The key frames are extracted by SegNet instead of conventional clustering algorithms for video summarization (VSUMM) which require heavy computation. By using a deep neural network, key frame selection can be performed in a real-time system. Experiments are conducted using 3D convolutional kernels such as 3D_CNN, Inflated 3D_CNN (I3D) and 3D_ResNet for gesture classification. Our algorithm achieved up to 97.8% of classification accuracy on the Cambridge gesture dataset. The experimental results show that the proposed approach is efficient and outperforms existing methods.

• Journal of IKEEE
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• v.27 no.4
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• pp.531-536
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• 2023

This paper proposes a sliding window method with frame feature insertion for immediate attack detection on in-vehicle networks. This method guarantees real-time attack detection by labeling based on the attack status of the current frame. Experiments show that the proposed method improves detection performance by giving more weight to the current frame in CNN computation. The proposed model was designed based on a lightweight LeNet-5 architecture and it achieves 100% detection for DoS attacks. Additionally, by comparing the complexity with conventional models, the proposed model has been proven to be more suitable for resource-constrained devices like ECUs.

• Journal of Communications and Networks
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• v.1 no.2
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• pp.134-142
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• 1999

We have developed fully functional Video Server and Client applications which can transmit, receive, decompress and display compressed video over various networks. Our video trans-port allows dynamic rate control feedback, loss detection, and repair requests from Clients to the Server. Our experiments show how feedvack-before-degradation scheme for rate adaptation maintains good display frame-rate for video playback. We show how the playback degradation(reduction in display frame-rate) oc-curs and what happens if corrective measures are not taken to im-prove the situation. The degradation is attributed to the increased internal kernel buffering which consumes scarce CPU resources. We demontrate with our experimental results that ServerNet, with improved hardware delivery guarantees, can significantly reduce host CPU resource consumption while serving video streams. We present the maximum number of streams which can be served for each of ATM and ServerNet interconnects. The appropriate user-level packet size for the video server are also determined for each case.

• Journal of Korean Society of Steel Construction
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• v.21 no.1
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• pp.63-70
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• 2009

Failure modes result in fracture or tearing, which may cause deterioration of resistance and reduction of inelastic deformation capacity. The potential failure modes for Special Concentrically Braced Frames (SCBFs) include fracture or tearing of the brace, net section fracture of the brace or gusset plate, fracture of the gusset plate welds, shear fracture of the bolts, block shear, excessive bolt bearing deformation, and buckling of the gusset plate. HSS tubular braces are commonly used in SCBFs, and net section fracture of the tubular brace may also occur through the brace net section at the end of the slot cut into the tube to slip over the gusset plate. This failure mode is categorized as a tension failure mode, and may cause dramatic loss of resistance and brittle behavior. Net section reinforcement is required according to AISC design specifications (AISC 2001). In this paper, the need to reinforce the net section area was discussed. Initially, the results of the net section fracture tests done by the University of California in Berkeley were presented with the modeling of these tests using FE models. To investigate the possibility of net section fracture in an actual frame, the slot end hole model was adapted to the frame FE model, and alternate near-fault histories were applied with tension-dominated cycles, since previous analyses showed that loading history was the most critical factor in net section fracture. The need for this reinforcement (cover plate) and the tension-dominated near-fault history were investigated.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.838-840
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• 1999

In this paper, modeling and analysis of discrete event systems by temporal logic frame works and petri net is considered. The reachability tree of the petri net can be used to solve the safeness, boundedness, conservation and coverability problems of discrete event systems. But the reachability tree of the petri net do not solve reachability and liveness problems in general. We proposed a method that synthesised the petri net and the temporal logic frameworks. This method slove some problems of petri net by logical representation of temporal logic frameworks.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.41 no.2
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• pp.122-128
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• 2005

The experiments were conducted to fine out the handling characteristics of the FMT(Frame Mideater Trawl) in the southern waters of Korea using a trawler "DONGBAEK" belongs to Yosu National University. The realtionship between the net depth D(m) and the warp length L(m) at the towing speeds of 2.5k't and 3.5k't werw as follows ; D(m) = 0.30L - 1.3(2.5k't), D(m) = 0.16L - 1.5(3.5k't). Therefore, the net depth was 3.0m deeper when the warp length was 10m longer at the towing speed of 2.5k't and was 1.6m deeper for 10m longer at the speed of 3.5k't, respectively. The sinking speed of FMT was 6.5m/min when the warp releasing speed was 24m/min at the towing speed of 2.5k't and was 3.8m/min for 25m/min at the towing speed of 3.5k't, respectively. The rising speed of FMT was 6.9m/min when the warp rewinding speed was 28m/min at the towing speed of 2.5k't and was 5.3m/min for 25m/min at the towing speed of 3.5k't, respectively. The mean elapsed time getting to the stable towing condition was 104sec at the towing speed of 2.5k't and was 105sec at the towing speed of 3.5k't, respectively, and there was no time difference for the towing speed variation. During the towing, the net depth was comparatively stable on the condition of no change for the warp length and the towing speed.

• Korean Linguistics
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• v.48
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• pp.223-268
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• 2010

The purpose of this paper is to build a semantic networks of the 'cooking class' verb (based on 'CoreNet' of KAIST). This proceedings needs to adjust the concept classification. Then sub-categories of [Cooking] and [Foodstuff] hierarchy of CoreNet was adjusted for the construction of verb semantic networks. For the building a semantic networks, each meaning of 'Cooking verbs' of Korean has to be analyzed. This paper focused on the Korean 'heating' verbs and 'non-heating'verbs. Case frame structure and argument information were inserted for the describing verb information. This paper use a Propege 3.3 as a tool for building "cooking verb" semantic networks. Each verb and noun was inserted into it's class, and connected by property relation marker 'HasThemeAs', 'IsMaterialOf'.

• 한국어정보학회:학술대회논문집
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• 2016.10a
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• pp.85-89
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• 2016

프레임넷 (FrameNet) 프로젝트는 버클리에서 1997년에 처음 제안했으며, 최근에는 다양한 언어적 특징을 반영하여 여러 국가에서 사용되고 있다. 하지만 문장의 프레임을 분석하는 것은 자연언어처리 전문가들이 많은 시간을 들여야 한다. 이 때문에, 한국어 프레임넷을 처음 만들 때는 충분한 훈련을 받은 번역가들이 영어 프레임넷의 문장들과 그 주석 정보들을 직접 번역하는 방법을 사용했다. 결과적으로 상대적으로 적은 비용이 들지만, 여전히 한 문장에 여러 번 등장하는 프레임 정보를 모두 번역하고 에러를 분석해야 했기에 많은 노력이 들어갔다. 본 연구에서는 일본어와 한국어의 언어적 유사성을 사용하여 비교적 적은 비용으로 한국어 프레임넷을 확장하는 방법을 제시한다. 또한 프레임넷에 친숙하지 않은 사용자가 더욱 쉽게 프레임 정보를 활용할 수 있도록 PubAnnotation 기술을 도입하고 "조사"라는 특성을 고려한 Valence pattern 분류를 통해 한국어 공개 프레임넷 사이트를 개선하였다.