• ETRI Journal
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• v.38 no.5
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• pp.934-940
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• 2016

In this paper, secure multicasting with the help of cooperative decode-and-forward relays is considered for the case in which a source securely sends a common message to multiple destinations in the presence of a single eavesdropper. We show that the secrecy rate maximization problem in the secure multicasting scenario under an overall power constraint can be solved using semidefinite programing with semidefinite relaxation and a bisection technique. Further, a suboptimal approach using zero-forcing beamforming and linear programming based power allocation is also proposed. Numerical results illustrate the secrecy rates achieved by the proposed schemes under secure multicasting scenarios.

• Structural Engineering and Mechanics
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• v.42 no.3
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• pp.425-448
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• 2012

In this paper, a new damage detection and quantification method has been presented to perform detection and quantification of structural damage under ambient vibration loadings. To extract modal properties of the structural system under ambient excitation, natural excitation technique (NExT) and eigensystem realization algorithm (ERA) are employed. Sensitivity matrices of the dynamic residual force vector have been derived and used in the parameter subset selection method to identify multiple damaged locations. In the sequel, the steady state genetic algorithm (SSGA) is used to determine quantified levels of the identified damage by minimizing errors in the modal flexibility matrix. In this study, performance of the proposed damage detection and quantification methodology is evaluated using a finite element model of a truss structure with considerations of possible experimental errors and noises. A series of numerical examples with five different damage scenarios including a challengingly small damage level demonstrates that the proposed methodology can efficaciously detect and quantify damage under noisy ambient vibrations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5A
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• pp.500-508
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• 2008

Direct-sequence ultra-wideband(DS-UWB) system is being considered as one of promising transmission technologies for wireless personal area networks(WPANs). Due to relatively low spreading factors and huge bandwidth of transmit signal, a DS-UWB receiver needs to be equipped not only with a rake receiver but also with an equalizer, of which the equalizer is not required for traditional direct-sequence code division multiple access(DS-CDMA) systems. The number of rake fingers is limited in practice, influencing the performance of the subsequent equalizer. In this paper, we derive a decision feedback equalizer(DFE) for DS-UWB systems based on the minimum mean square error(MMSE) criterion, and investigate the impact of various parameters on the DFE performance in realistic scenarios. In particular, we propose an approach to improving the performance of the DFE using additional channel estimates for multipaths not combined in the rake receiver, and discuss how the accuracy of channel estimation affects desirable DFE configuration. Moreover, we present simulation results that show the impact of turbo equalization on the DFE performance.

• Electronics and Telecommunications Trends
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• v.34 no.4
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• pp.1-14
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• 2019

Recent trends in deep reinforcement learning (DRL) have revealed the considerable improvements to DRL algorithms in terms of performance, learning stability, and computational efficiency. DRL also enables the scenarios that it covers (e.g., partial observability; cooperation, competition, coexistence, and communications among multiple agents; multi-task; decentralized intelligence) to be vastly expanded. These features have cultivated multi-agent reinforcement learning research. DRL is also expanding its applications from robotics to natural language processing and computer vision into a wide array of fields such as finance, healthcare, chemistry, and even art. In this report, we briefly summarize various DRL techniques and research directions.

• Structural Monitoring and Maintenance
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• v.6 no.3
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• pp.237-254
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• 2019

This paper presents an improved time series based damage detection approach with experimental verifications for detection, localization, and quantification of damage in shear-type structures under varying mass effects using output-only vibration data. The proposed method can be very effective for automated monitoring of buildings to develop proactive maintenance strategies. In this method, Auto-Regressive Moving Average models with eXogenous inputs (ARMAX) are built to represent the dynamic relationship of different sensor clusters. The damage features are extracted based on the relative difference of the ARMAX model coefficients to identify the existence, location and severity of damage of stiffness and mass separately. The results from a laboratory-scale shear type structure show that different damage scenarios are revealed successfully using the approach. At the end of this paper, the methodology limitations are also discussed, especially when simultaneous occurrence of mass and stiffness damage at multiple locations.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1210-1216
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• 2018

Site or multi-unit (MU) risk assessment has been a major issue in the field of nuclear safety study since the Fukushima accident in 2011. There have been few methods or experiences for MU risk assessment because the Fukushima accident was the first real MU accident and before the accident, there was little expectation of the possibility that an MU accident will occur. In addition to the lack of experience of MU risk assessment, since an MU nuclear power plant site is usually very complex to analyze as a whole, it was considered that a systematic method such as probabilistic safety assessment (PSA) is difficult to apply to MU risk assessment. This paper proposes a new MU risk assessment methodology by using the conventional PSA methodology which is widely used in nuclear power plant risk assessment. The logical failure structure of a site with multiple units is suggested from the definition of site risk, and a decomposition method is applied to identify specific MU failure scenarios.

• Smart Structures and Systems
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• v.23 no.1
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• pp.15-29
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• 2019

This paper addresses the problem of damage detection in suspension bridge hangers, with an emphasis on the modal flexibility method. It aims at evaluating the capability and the accuracy of the modal flexibility method to detect and locate single and multiple damages in suspension bridge hangers, with different level of severity and various locations. The study is conducted numerically and experimentally on a laboratory suspension bridge mock-up. First, the covariance-driven stochastic subspace identification is used to extract the modal parameters of the bridge from experimental data, using only output measurements data from ambient vibration. Then, the method is demonstrated for several damage scenarios and compared against other classical methods, such as: Coordinate Modal Assurance Criterion (COMAC), Enhanced Coordinate Modal Assurance Criterion (ECOMAC), Mode Shape Curvature (MSC) and Modal Strain Energy (MSE). The paper demonstrates the relative merits and shortcomings of these methods which play a significant role in the damage detection ofsuspension bridges.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.59-66
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• 2019

According to the KT telecommunication statistics, people stayed inside their houses on an average of 11.9 hours a day. As well as, according to NSC statistics in the united states, people regardless of age are injured for a variety of reasons in their houses. For purposes of this research, we have investigated an abnormal event detection algorithm to classify infrequently occurring behaviors as accidents, health emergencies, etc. in their daily lives. We propose a fusion method that combines three classification algorithms with vision pattern, audio pattern, and activity pattern to detect unusual user events. The vision pattern algorithm identifies people and objects based on video data collected through home CCTV. The audio and activity pattern algorithms classify user audio and activity behaviors using the data collected from built-in sensors on their smartphones in their houses. We evaluated the proposed individual pattern algorithm and fusion method based on multiple scenarios.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.48-54
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• 2021

In most existing researches on non-orthogonal multiple access (NOMA) with symmetric superposition coding (SSC), uniform sources have been usually considered. For the first part in this two-part paper, for the strongest channel gain user, we showed that the bit-error rate (BER) for the optimal maximum a-posteriori (MAP) receiver for the non-uniform source improves slightly, compared to that of the conventional receiver for the uniform sources. We demonstrate that in communication scenarios of the non-uniform source NOMA schemes, for the weakest channel gain user, the BER performance of the optimal MAP receiver for a non-uniform source improves greatly, compared to that of the conventional receiver for uniform sources. We first derive an analytical expression of the BER for non-uniform source NOMA with SSC. Then, simulations demonstrate that the BER of the optimal MAP receiver for the non-uniform source improves, compared with that of the conventional maximum likelihood (ML) receiver for the uniform sources. In result, the proposed optimal MAP receiver for the non-uniform source could be a promising scheme for SSC NOMA, with improved BER performances.

• Research in Mathematical Education
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• v.24 no.2
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• pp.111-130
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• 2021

This exploratory study focuses on analyzing three mathematics textbooks in Germany, Singapore and South Korea to reveal similarities and differences in their introductions of fraction concepts. Findings reveal that all three countries' textbooks introduce fraction concepts predominantly by using pictorial representations such as area models, but the introductions of multiple fraction constructs vary. The Singaporean and South Korean textbooks predominantly used a part-whole construct to introduce fractional concepts while the German textbook introduced various constructs sequentially in the first pages using several scenarios from different real-life situations. The findings were represented using visual representations, which we called textbook signatures. The textbook signatures provided configurations of the textbook features across the three countries. At the end of paper, we share insights and limitations about the use of textbook signatures in the research on textbook analysis.