• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.49-56
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• 2010

In this paper, a joint PHY-MAC layer optimized resource allocation scheme for OFDMA based micro base stations is investigated. We propose cross-layer optimized two-stage resource allocation scheme including cross-layer functional description and control information flow between PHY-MAC layers. The proposed two-stage resource allocation scheme consists of a user grouping stage and a resource allocation stage. In the user grouping stage, users are divided into a macro base station user group and a micro base station user group based on the PHY-MAC layer characteristics of each user. In the resource allocation stage, a scheduling scheme and an allotment of resources are determined. In the proposed scheme, diversity and adaptive modulation and coding (AMC) schemes are exploited as schedulers. Simulation results demonstrate that the proposed scheme increases the average cell throughput about 40~80 % compared to the conventional system without micro base stations.

• Information and Communications Magazine
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• v.25 no.5
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• pp.73-79
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• 2008

본 논문에서는 네트워크 코딩 기법이 무선 통신 네트워크에서 적용되는 과정에서 발생하는 여러 특이점과 계층간 최적화 (Cross-layer Optimization) 문제를 소개한다. 또한 이의 해결을 통해서 얻어지는 네트워크 코딩 이득 (Network Coding Gain)의 몇 가지 측면을 소개한다

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.12
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• pp.30-45
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• 2014

Recently, multimedia application users who demand for ubiquitous computing environment are rapidly increasing, and wireless mesh network is receiving attention as a cost-effective key technology for next generation wireless networking. When multiple flows are transmitting data at the same time in the network, routing for path selection of each flow and link resource allocation for data transmission of each flow are one of the key factors that influence to the effectiveness of the network directly. In this paper, we consider problems for path discovery and resource allocation of links at the same time and we propose an algorithm based on mathematical modeling using a technique for cross-layer optimization design in STDMA-based wireless mesh networks that can enhance transfer performance for each flow. We show by performance analysis that the proposed algorithm can enhance the throughput performance by maximally utilizing given bandwidth resources when the number of flows increase in multi-hop wireless mesh networks.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.20-28
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• 2016

In this study, an efficient method of designing laminate composite radar absorbing structures (RAS) is proposed with consideration given to the structural shape so as to improve aircraft stealth performance. The calculation of the radar cross section (RCS) should be decreased to enhance the efficiency of the stochastic optimization when designing an RAS. In the proposed method, RAS are optimized to match up the input impedance of the minimal RCS, which is obtained by using physical optics and the transmission line theory. Single and double layer dielectric RAS for aircraft wings are employed as numerical examples and designed using the proposed method, RCS minimization and reflection coefficient minimization. The availability of the proposed method is assessed by comparing the similarity of the results and computation time with other design methods. According to the results, the proposed method produces the same results as the stochastic optimization, which adopts the RCS as the objective function, and can improve RAS design efficiency by reducing the number of RCS analyses.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.2
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• pp.118-124
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• 2015

The design of radar absorbing structures(RAS) is a discrete optimization problem and is usually processed by stochastic optimization methods. The calculation of radar cross section(RCS) should be decreased to improve the efficiency of designing RAS. In this paper, an efficient method using impedance matching is studied to design RAS for minimizing RCS. Input impedance of the minimal RCS for the specified wave incident conditions is obtained by interlocking physical optics(PO) and optimizations. Complex permittivity and thickness of RAS are designed to satisfy the calculated input impedance by a discrete optimization. The results reveal that the studied method attains the same results as stochastic optimization which have to conduct numerous RCS analysis. The efficiency of designing RAS can be enhanced by reducing the calculation of RCS.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.17-24
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• 2008

At the view of Application layer, there are many researches to achieve the cross-layer optimization with Physical layer. Scalable video coding is good example. Although it is necessary to consider the session layer which lies halfway between two layers, the research about that is insufficient. We present a feasible solution of dynamic session control for scalable video coding over IMS.

• Advances in Computational Design
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• v.6 no.1
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• pp.15-30
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• 2021

With improvement in innovative manufacturing technologies, it became possible to fabricate any complex shaped structural design for practical applications. This allows for the fabrication of curvilinearly stiffened pressure vessels and pipes. Compared to straight stiffeners, curvilinear stiffeners have shown to have better structural performance and weight savings under certain loading conditions. In this paper, an optimization framework for designing curvilinearly stiffened composite pressure vessels and pipes is presented. NURBS are utilized to define curvilinear stiffeners over the surface of the pipe. An integrated tool using Python, Rhinoceros 3D, MSC.PATRAN and MSC.NASTRAN is implemented for performing the optimization. Rhinoceros 3D is used for creating the geometry, which later is exported to MSC.PATRAN for finite element model generation. Finally, MSC.NASTRAN is used for structural analysis. A Bi-Level Programming (BLP) optimization technique, consisting of Particle Swarm Optimization (PSO) and Gradient-Based Optimization (GBO), is used to find optimal locations of stiffeners, geometric dimensions for stiffener cross-sections and layer thickness for the composite skin. A cylindrical pipe stiffened by orthogonal and curvilinear stiffeners under torsional and bending load cases is studied. It is seen that curvilinear stiffeners can lead to a potential 10.8% weight saving in the structure as compared to the case of using straight stiffeners.

• Journal of Information Display
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• v.6 no.2
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• pp.16-18
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• 2005

Hybrid insulator pentacene thin film transistors (TFTs) are fabricated with thermally grown oxide and cross-linked polyvinylalcohol (PVA) including surface treatment by dilute ploymethylmethacrylate (PMMA) layer on $n^+$ doped silicon wafer. Through the optimization of $SiO_2$ layer thickness in hybrid insulator structure, carrier mobility is increased to more than 35 times than that of the TFT which has only a gate insulator of $SiO_2$ at the same electric field. The carrier mobility of $1.80cm^2$/V-s, subthreshold swing of 1.81 V/decade, and $I_{on}/I_{off}$ current ratio> $1.10{\times}10^5$ are obtained less than -30 V bias condition. The result is one of the best reported performances of pentacene TFTs with hybrid insulator including cross-linked PVA layer as a gate insulator at relatively low voltage operation.

• Computers and Concrete
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• v.32 no.3
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• pp.233-246
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• 2023

Accurate prediction of concrete compressive strength can minimize the need for extensive, time-consuming, and costly mixture optimization testing and analysis. This study attempts to enhance the prediction accuracy of compressive strength using stacking ensemble machine learning (ML) with feature engineering techniques. Seven alternative ML models of increasing complexity were implemented and compared, including linear regression, SVM, decision tree, multiple layer perceptron, random forest, Xgboost and Adaboost. To further improve the prediction accuracy, a ML pipeline was proposed in which the feature engineering technique was implemented, and a two-layer stacked model was developed. The k-fold cross-validation approach was employed to optimize model parameters and train the stacked model. The stacked model showed superior performance in predicting concrete compressive strength with a correlation of determination (R²) of 0.985. Feature (i.e., variable) importance was determined to demonstrate how useful the synthetic features are in prediction and provide better interpretability of the data and the model. The methodology in this study promotes a more thorough assessment of alternative ML algorithms and rather than focusing on any single ML model type for concrete compressive strength prediction.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.53-68
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• 2013

We investigate the rate-compatible punctured convolutional (RCPC) codes concatenated with hierarchical QAM for designing a cross-layer unequal error protection scheme for H.264 coded sequences. We first divide the H.264 encoded video slices into three priority classes based on their relative importance. We investigate the system constraints and propose an optimization formulation to compute the optimal parameters of the proposed system for the given source significance information. An upper bound to the significance-weighted bit error rate in the proposed system is derived as a function of system parameters, including the code rate and geometry of the constellation. An example is given with design rules for H.264 video communications and 3.5-4 dB PSNR improvement over existing RCPC based techniques for AWGN wireless channels is shown through simulations.