• 전기학회논문지
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• 제64권3호
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• pp.433-437
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• 2015

We have designed and fabricated a low power and high linearity up down convertor for wireless repeaters using $0.35{\mu}m$ SiGe Bipolar CMOS technology. Repeater is composed of a wideband up/down converting mixer, programmable gain amplifiers (PGA), input buffer, LO buffer, filter driver amplifier and integer-N phase locked loop (PLL). As of the measurement results, OIP3 of the down conversion mixer and up conversion mixer are 32 dBm and 17.8 dBm, respectively. The total dynamic gain range is 31 dB with 1 dB gain step resolution. The adjacent channel leakage ratio (ACLR) is 59.9 dBc. The total power consumption is 240 mA at 3.3 V.

• ETRI Journal
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• 제44권5호
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• pp.733-745
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• 2022

In software-defined wireless networking (SDWN), the optimal routing technique is one of the effective solutions to improve its performance. This routing technique is done by many different methods, with the most common using integer linear programming problem (ILP), building optimal routing metrics. These methods often only focus on one routing objective, such as minimizing the packet blocking probability, minimizing end-to-end delay (EED), and maximizing network throughput. It is difficult to consider multiple objectives concurrently in a routing algorithm. In this paper, we investigate the application of machine learning to control routing in the SDWN. An intelligent routing algorithm is then proposed based on the machine learning to improve the network performance. The proposed algorithm can optimize multiple routing objectives. Our idea is to combine supervised learning (SL) and reinforcement learning (RL) methods to discover new routes. The SL is used to predict the performance metrics of the links, including EED quality of transmission (QoT), and packet blocking probability (PBP). The routing is done by the RL method. We use the Q-value in the fundamental equation of the RL to store the PBP, which is used for the aim of route selection. Concurrently, the learning rate coefficient is flexibly changed to determine the constraints of routing during learning. These constraints include QoT and EED. Our performance evaluations based on OMNeT++ have shown that the proposed algorithm has significantly improved the network performance in terms of the QoT, EED, packet delivery ratio, and network throughput compared with other well-known routing algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4364-4384
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• 2021

The dynamic network state and the mobility of the terminals make the service function chain (SFC) orchestration mechanisms based on static and deterministic assumptions hard to be applied in SDN/NFV mobile edge computing networks. Designing dynamic and online SFC orchestration mechanism can greatly improve the execution efficiency of compute-intensive and resource-hungry applications in mobile edge computing networks. In order to increase the overall profit of service provider and reduce the resource cost, the system running time is divided into a sequence of time slots and a dynamic orchestration scheme based on an improved column generation algorithm is proposed in each slot. Firstly, the SFC dynamic orchestration problem is formulated as an integer linear programming (ILP) model based on layered graph. Then, in order to reduce the computation costs, a column generation model is used to simplify the ILP model. Finally, a two-stage heuristic algorithm based on greedy strategy is proposed. Four metrics are defined and the performance of the proposed algorithm is evaluated based on simulation. The results show that our proposal significantly provides more than 30% reduction of run time and about 12% improvement in service deployment success ratio compared to the Viterbi algorithm based mechanism.

• ETRI Journal
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• 제45권5호
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• pp.874-886
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• 2023

A joint resource-optimization scheme is investigated for nonorthogonal multiple access (NOMA)-enhanced scalable video coding (SVC) multicast in unmanned aerial vehicle (UAV)-assisted radio-access networks (RANs). This scheme allows a ground base station and UAVs to simultaneously multicast successive video layers in SVC with successive interference cancellation in NOMA. A video quality-maximization problem is formulated as a mixed-integer nonlinear programming problem to determine the UAV deployment and association, RAN spectrum allocation for multicast groups, and UAV transmit power. The optimization problem is decoupled into the UAV deployment-association, spectrum-partition, and UAV transmit-power-control subproblems. A heuristic strategy is designed to determine the UAV deployment and association patterns. An upgraded knapsack algorithm is developed to solve spectrum partition, followed by fast UAV power fine-tuning to further boost the performance. The simulation results confirm that the proposed scheme improves the average peak signal-to-noise ratio, aggregate videoreception rate, and spectrum utilization over various baselines.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권11호
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• pp.3204-3217
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• 2023

In this paper, the downlink of the multicast based spatial modulation systems is investigated. Specifically, physical layer multicasting is introduced to increase the number of access users and to improve the communication rate of the spatial modulation system in which only single radio frequency chain is activated in each transmission. To minimize the bit error rate (BER) of the multicast based spatial modulation system, a joint optimizing algorithm of antenna selection and multicast precoding is proposed. Firstly, the joint optimization is transformed into a mixed-integer non-linear program based on single-stage reformulation. Then, a novel iterative algorithm based on the idea of branch and bound is proposed to obtain the quasioptimal solution. Furthermore, in order to balance the performance and time complexity, a low-complexity deflation algorithm based on the successive convex approximation is proposed which can obtain a sub-optimal solution. Finally, numerical results are showed that the convergence of our proposed iterative algorithm is between 10 and 15 iterations and the signal-to-noise-ratio (SNR) of the iterative algorithm is 1-2dB lower than the exhaustive search based algorithm under the same BER accuracy conditions.

• 산업경영시스템학회지
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• 제38권3호
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• pp.169-180
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• 2015

Recently, scheduling problems with position-dependent processing times have received considerable attention in the literature, where the processing times of jobs are dependent on the processing sequences. However, they did not consider cases in which each processed job has different learning or aging ratios. This means that the actual processing time for a job can be determined not only by the processing sequence, but also by the learning/aging ratio, which can reflect the degree of processing difficulties in subsequent jobs. Motivated by these remarks, in this paper, we consider a two-agent single-machine scheduling problem with linear job-dependent position-based learning effects, where two agents compete to use a common single machine and each job has a different learning ratio. Specifically, we take into account two different objective functions for two agents: one agent minimizes the total weighted completion time, and the other restricts the makespan to less than an upper bound. After formally defining the problem by developing a mixed integer non-linear programming formulation, we devise a branch-and-bound (B&B) algorithm to give optimal solutions by developing four dominance properties based on a pairwise interchange comparison and four properties regarding the feasibility of a considered sequence. We suggest a lower bound to speed up the search procedure in the B&B algorithm by fathoming any non-prominent nodes. As this problem is at least NP-hard, we suggest efficient genetic algorithms using different methods to generate the initial population and two crossover operations. Computational results show that the proposed algorithms are efficient to obtain near-optimal solutions.

• 디지털융복합연구
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• 제13권6호
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• pp.151-156
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• 2015

본 논문에서는 스마트폰 환경의 얼굴 검출, 인식 및 화자 인증 기반 다중생체인식 개인인증 시스템을 제안한다. 제안된 시스템은 Modified Census Transform과 gabor filter 및 k-means 클러스터 분석 알고리즘을 통해 얼굴의 주요 특징을 추출하여 얼굴인식을 위한 데이터 전처리를 수행한다. 이후 Linear Discriminant Analysis기반 본인 인증을 수행하고(얼굴인식), Mel Frequency Cepstral Coefficient기반 실시간성 검증(화자인증)을 수행한다. 화자인증에 사용하는 음성 정보는 실시간으로 변화하므로 본 논문에서는 Dynamic Time Warping을 통해 이를 해결한다. 제안된 다중생체인식 시스템은 얼굴 및 음성 특징 정보를 융합 및 스마트폰 환경에 최적화하여 실시간 얼굴검출, 인식과 화자인증 과정을 수행하며 단일 생체인식에 비해 약간 낮은 95.1%의 인식률을 보이지만 1.8%의 False Acceptance Ratio를 통해 객관적인 실시간 생체인식 성능을 입증하여 보다 신뢰할 수 있는 시스템을 완성한다.

• 자원환경지질
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• 제28권3호
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• pp.231-241
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• 1995

It is well known that hydroxyapatite [$Ca_{10}(PO_4)_6(OH)_2$] have an exchangeability for various heavy metal ions in aqueous solution. To evalute the feasibility of employing the synthetic hydroxyapatites as an eliminatable exchanger for environmentally noxious caions in waste water, the adsorption properties, the removal capacities and the selectivity of the apatites for various cations were investigated in more detailed. The heavy metal cations have been exchanged in calcium part of hydroxyapatite. The order of the degree of amount exchanged of the investigated cations is $Pb^{2+}>Cd^{2+}>Zn^{2+}>Ba^{2+}$. The molar ratios between released $Cd^{2+}$ ions and remeved divalent metal cations in the reacted solution with hydroxyapatite are roughly close to an integer 1.0, suggesting that an ion-exchange reaction could have played a major role in the removal of heavy metals rather then an adsorption effect. The exchangeability of the hydroxyapatite powder of Ca/P molar ratio 1.67, which have specipic surface area of $104.5m^2g^{-1}$, appeared to be better then $237.6{\mu}g$ per g for $Pb^{2+}$ ions. The removal capacity of the heavy metal ions varies directly as particle size of hydroxyapatites. All evidences obtained indicate that the synthesized hydroxyapatite powders by precipitation reaction method can be employed as an effective cation exchanger for eliminating noxious ions in waste water even in some improvemental.

• Clinical and Experimental Pediatrics
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• 제60권11호
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• pp.353-358
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• 2017

Purpose: To develop and evaluate a simple screening tool to assess hearing loss in newborns. A derived score was compared with the standard clinical practice tool. Methods: This cohort study was designed to screen the hearing of newborns using transiently evoked otoacoustic emission and auditory brain stem response, and to determine the risk factors associated with hearing loss of newborns in 3 tertiary hospitals in Northern Thailand. Data were prospectively collected from November 1, 2010 to May 31, 2012. To develop the risk score, clinical-risk indicators were measured by Poisson risk regression. The regression coefficients were transformed into item scores dividing each regression-coefficient with the smallest coefficient in the model, rounding the number to its nearest integer, and adding up to a total score. Results: Five clinical risk factors (Craniofacial anomaly, Ototoxicity, Birth weight, family history [Relative] of congenital sensorineural hearing loss, and Apgar score) were included in our COBRA score. The screening tool detected, by area under the receiver operating characteristic curve, more than 80% of existing hearing loss. The positive-likelihood ratio of hearing loss in patients with scores of 4, 6, and 8 were 25.21 (95% confidence interval [CI], 14.69-43.26), 58.52 (95% CI, 36.26-94.44), and 51.56 (95% CI, 33.74-78.82), respectively. This result was similar to the standard tool (The Joint Committee on Infant Hearing) of 26.72 (95% CI, 20.59-34.66). Conclusion: A simple screening tool of five predictors provides good prediction indices for newborn hearing loss, which may motivate parents to bring children for further appropriate testing and investigations.

• 한국공간구조학회논문집
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• 제1권1호
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• pp.143-155
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• 2001

Generally, truss design has been determined by the designer's experience and intuition. But if we perform the most economical structural design we must consider not only cross-sections of members but also configurations(howe, warren and pratt types etc.) of single truss as the number of panel and truss height. The purpose of this study is to develope automated optimum design techniques for steel truss structures considering cross-sections of members and shape of trusses simultaneously. As the results, it could be possible to find easily the optimum solutions subject to design conditions at the preliminary structural design stage of the steel truss structures. In this study, the objective function is expressed as the whole member weight of trusses, and the applied constraints are as stresses, slenderness ratio, local buckling, deflection, member cross-sectional dimensions and truss height etc. The automated optimum design algorithm of this study is divided into three-level procedures. The first level on member cross-sectional optimization is performed by the sequential unconstrained minimization technique(SUMT) using dynamic programming method. And the second level about truss height optimization is applied for obtaining the optimum truss height by three-equal interval search method. The last level of optimization is applied for obtaining the optimum panel number of truss by integer programming method. The algorithm of multi-level optimization programming technique proposed in this study is more helpful for the economical design of plane trusses as well as space trusses.