• Structural Monitoring and Maintenance
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• v.11 no.3
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• pp.173-185
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• 2024

Currently, the electro-hydraulic servo loading control system manufactured by MTS, OpenFresco hybrid test interface software and OpenSees finite element software are widely used in structure laboratories to carry out hybrid test, but there is no relevant public information about full structure pseudo-dynamic test based on the above software and hardware. In order to study the feasibility of using the above software and hardware to carry out full structure pseudo-dynamic test, the full structure pseudo-dynamic virtual experiments of a single degree of freedom (SDOF) structure and a two degrees of freedom (2DOFs) structure are carried out based on the MTS 793 Demo Mode, and the results are respectively compared with the finite element analysis method. The results show that the finite element analysis results and full structure pseudo-dynamic virtual experiment results are highly consistent, which verifies the feasibility of carrying out the full structure pseudo-dynamic test based on the above software and hardware. Then, a three story steel frame full structure pseudo-dynamic test is conducted, and the smooth implementation of full structure pseudo-dynamic test of the three story steel frame further verifies the reliability of thistesting method. The implementation method of carrying out the full structure pseudo-dynamic tests are introduced in detail, which can provide some reference for relevant research.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.137-140
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• 2001

In this paper, we propose a multicast routing scheme for an efficient and reliable support of multicast service to mobile hosts in IPv6 based networks. The purpose of this paper is to develop an algorithm to reduce both the number of multicast tree reconstruction and the multicast service disrupt time using the RSVP scheme. The proposed multicast routing scheme is a hybrid method using the advantages of the hi-directional tunneling and the remote subscription proposed by the IETF Mobile IP working group. The proposed scheme satisfies the maximum tolerable transfer delay time and supports the maximum tunneling service. The simulation results show that the proposed scheme has better performance in the number of multicast tree reconstruction and the time of multicast service disrupt than the previous schemes does.

• 한국정보통신설비학회:학술대회논문집
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• 2006.08a
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• pp.47-52
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• 2006

In this paper, we suggested new network architecture to provide seamless service between the cellular system and new wireless broadband network such as IEEE 802.16e, called WiBro. The interworking technologies are very important issue because mobile operator should provide service connectivity between various wireless networks based on different access technologies. Moreover a change and modification on legacy network should be minimized for providing interworking with new wireless broad-band network. We implemented proposed interworking architecture between 3G cellular network and 802.16e network to provide seamless service including interworking unit in real test environment. Also, we performed performance evaluation in hybrid network environments.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.290-296
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• 2022

Big Data is a data analysis technology empowered by late advances in innovations and engineering. In any case, big data involves a colossal responsibility of equipment and handling assets, making reception expenses of big data innovation restrictive to little and medium estimated organizations. Cloud computing offers the guarantee of big data execution to little and medium measured organizations. Big Data preparing is performed through a programming worldview known as MapReduce. Normally, execution of the MapReduce worldview requires organized joined stockpiling and equal preparing. The computing needs of MapReduce writing computer programs are frequently past what little and medium measured business can submit. Cloud computing is on-request network admittance to computing assets, given by an external element. Normal arrangement models for cloud computing incorporate platform as a service (PaaS), software as a service (SaaS), framework as a service (IaaS), and equipment as a service (HaaS).

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.353-354
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• 2014

• Korean Journal of Plant Taxonomy
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• v.53 no.2
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• pp.126-147
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• 2023

The taxonomic identity of Elaeagnus ×maritima and E. ×submacrophylla (Elaeagnaceae) in Korea is unclear, yet they are presumed to be hybrid taxa based on their morphology. To determine their hybrid origins, a morphological analysis (field surveys and specimen examinations) and a molecular analysis involving two nuclear ribosomal DNA (nrDNA) regions (internal transcribed spacer and 5S non-transcribed spacer) and one chloroplast DNA (cpDNA) region (matK) were conducted. The morphological analysis revealed that E. ×maritima showed certain morphological similarities to E. glabra, whereas E. ×submacrophylla showed certain morphological similarities to E. pungens. However, the molecular analysis indicated that E. ×maritima exhibited additive species-specific sites of E. glabra and E. macrophylla in the nrDNA regions. Notably, E. ×submacrophylla showed various aspects, with some individuals exhibiting additive species-specific sites of E. pungens and E. macrophylla in the nrDNA and E. macrophylla sequences in the cpDNA regions, some individuals exhibiting E. macrophylla sequences in the nrDNA and E. pungens sequences in the cpDNA regions, and some individuals displaying E. macrophylla sequences in both the nrDNA and cpDNA regions, despite an intermediate morphology between E. pungens and E. macrophylla. These results indicate that these two species are of hybrid origin and frequently cross between parental and hybrid individuals.

• ETRI Journal
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• v.38 no.3
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• pp.579-588
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• 2016

To improve the ability to determine a vehicle's movement information even in a challenging environment, a hybrid approach called non-Gaussian square rootunscented particle filtering (nGSR-UPF) is presented. This approach combines a square root-unscented Kalman filter (SR-UKF) and a particle filter (PF) to determinate the vehicle state where measurement noises are taken as a finite Gaussian kernel mixture and are approximated using a sparse Gaussian kernel density estimation method. During an outage-free GPS period, the updated mean and covariance, computed using SR-UKF, are estimated based on a GPS observation update. During a complete GPS outage, nGSR-UPF operates in prediction mode. Indeed, because the inertial sensors used suffer from a large drift in this case, SR-UKF-based importance density is then responsible for shifting the weighted particles toward the high-likelihood regions to improve the accuracy of the vehicle state. The proposed method is compared with some existing estimation methods and the experiment results prove that nGSR-UPF is the most accurate during both outage-free and complete-outage GPS periods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.7B
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• pp.592-600
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• 2008

In this paper, a Hybrid Scaling based DTW (HS-DTW) mechanism is proposed for detection of periodic shrew TCP attacks. A low-rate TCP attack which is a type of shrew DoS (Denial of Service) attacks, was reported recently, but it is difficult to detect the attack using previous flooding DoS detection mechanisms. A pattern matching method with DTW (Dynamic Time Warping) as a type of defense mechanisms was shown to be reasonable method of detecting and defending against a periodic low-rate TCP attack in an input traffic link. This method, however, has the problem that a legitimate link may be misidentified as an attack link, if the threshold of the DTW value is not reasonable. In order to effectively discriminate between attack traffic and legitimate traffic, the difference between their DTW values should be large as possible. To increase the difference, we analyze a critical problem with a previous algorithm and introduce a scaling method that increases the difference between DTW values. Four kinds of scaling methods are considered and the standard deviation of the sampling data is adopted. We can select an appropriate scaling scheme according to the standard deviation of an input signal. This is why the HS-DTW increases the difference between DTW values of legitimate and attack traffic. The result is that the determination of the threshold value for discrimination is easier and the probability of mistaking legitimate traffic for an attack is dramatically reduced.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.31-32
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• 2016

본 논문은 ATSC2.0 기반 8-VSB/MH 융합형 3DTV (A/104 Part 5 Service Compatible 3DTV using Main and Mobile Hybrid Delivery, A/104 part 5) 방식의 서비스 커버리지 및 음영지역을 예측할 수 있는 측정 및 분석시스템 개발에 대하여 기술 한다. ATSC2.0 기반 고정/이동 방송시스템은 8-VSB 로 전송되는 고정 TV 방송서비스(좌영상 전송)와 ATSC-MH 로 전송되는 in-band 모바일 방송서비스(우영상 전송)를 모두 수신하여 좌/우영상의 재생 및 동기화를 통해 융합형 3D 영상을 복원하게 된다. 따라서 융합형 3DTV 수신기는 고정 및 모바일 방송신호를 모두 수신하여야 융합형 3D 영상복원을 할 수 있으며, 방송사 입장에서 서비스 커버리지 측정을 하기위해서는 8-VSB 및 ATSC-MH 신호의 수신여부를 모두 측정하여야 한다. 본 논문에서는 이와 같은 RF 수신전계강도 파라미터 및 GPS 정보등을 실시간으로 모니터링하여, 시스템 사용자에가 융합형 3DTV 서비스 커버리지 측정 및 분석을 통해 서비스를 위한 RF 방송망 셀 구성 및 음영지역을 예측할 수 있는 ATSC2.0 융합형 3DTV 서비스 커버리지 분석기 구현에 대한 내용을 기술한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2399-2413
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• 2021

A recommendation system is an information filter tool, which uses the ratings and reviews of users to generate a personalized recommendation service for users. However, the cold-start problem of users and items is still a major research hotspot on service recommendations. To address this challenge, this paper proposes a high-efficient hybrid recommendation system based on Fuzzy C-Means (FCM) clustering and supervised learning models. The proposed recommendation method includes two aspects: on the one hand, FCM clustering technique has been applied to the item-based collaborative filtering framework to solve the cold start problem; on the other hand, the content information is integrated into the collaborative filtering. The algorithm constructs the user and item membership degree feature vector, and adopts the data representation form of the scoring matrix to the supervised learning algorithm, as well as by combining the subjective membership degree feature vector and the objective membership degree feature vector in a linear combination, the prediction accuracy is significantly improved on the public datasets with different sparsity. The efficiency of the proposed system is illustrated by conducting several experiments on MovieLens dataset.