• ETRI Journal
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• v.36 no.4
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• pp.564-571
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• 2014

Sphere decoding (SD) for multiple-input and multiple-output systems is a well-recognized approach for achieving near-maximum likelihood performance with reduced complexity. SD is a tree search process, whereby a large number of nodes can be searched in an effort to find an estimation of a transmitted symbol vector. In this paper, a simple and generalized approach called layer pruning is proposed to achieve complexity reduction in SD. Pruning a layer from a search process reduces the total number of nodes in a sphere search. The symbols corresponding to the pruned layer are obtained by adopting a QRM-MLD receiver. Simulation results show that the proposed method reduces the number of nodes to be searched for decoding the transmitted symbols by maintaining negligible performance loss. The proposed technique reduces the complexity by 35% to 42% in the low and medium signal-to-noise ratio regime. To demonstrate the potential of our method, we compare the results with another well-known method - namely, probabilistic tree pruning SD.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.116-125
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• 2014

In this paper, we investigate an inventory and production system in a three-layer supply chain system involving a single supplier, single manufacturer and multiple retailers. Earlier study in this type of supply chain only consider a single raw material in order to produce single item, but we consider raw materials in order to produce multiple items. It is assumed that the cycle time at each stage is an integer multiple of the adjacent downstream stage. We develop an iterative solution procedure to find the order quantity for the multiple items and raw materials that minimizes the supply chain-wide total cost per unit time of the supplier and manufacturer's raw materials ordering and holding, setup and finished items holding, the retailer's ordering and inventory holding. Numerical examples are presented to show that the proposed heuristic gives good performance.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.48 no.1
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• pp.57-61
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• 1999

Multiple slab waveguides are analyzed by using the transfer matrix method and by introducing a virtual leaky layer. It is shown that the analysis is conceptually equivalent to the prism coupling phenomenon. The Lorentzian function is made use of toobtain the eigenvalues of multiple waveguides. Computer simulations are performed onsingle layered, double layered wavegurdes. The calculation results are confirmed to agree well with those of the finite difference method.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.633-635
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• 2016

Convolutional Networks (ConvNets) are powerful models that learn hierarchies of visual features, which could also be used to obtain image representations for transfer learning. The basic pipeline for transfer learning is to first train a ConvNet on a large dataset (source task) and then use feed-forward units activation of the trained ConvNet as image representation for smaller datasets (target task). Our key contribution is to demonstrate superior performance of multiple ConvNet layer features over single ConvNet layer features. Combining multiple ConvNet layer features will result in more complex feature space with some features being repetitive. This requires some form of feature selection. We use AdaBoost with single stumps to implicitly select only distinct features that are useful towards classification from concatenated ConvNet features. Experimental results show that using multiple ConvNet layer activation features instead of single ConvNet layer features consistently will produce superior performance. Improvements becomes significant as we increase the distance between source task and the target task.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1072-1075
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• 2019

In this letter, we propose a new soft decoding method for a Core-Layer(CL) signal in ATSC3.0 Layered-Division-Multiplexing Multiple-Inputs-Multiple-Outputs broadcasting systems. Unlike a conventional Gaussian-Approximation(GA) method, the proposed method decodes the CL signal by reducing a Enhanced-Layer signal simply to a QPSK signal, and thus exhibits greatly improved performance compared to the GA method especially for a lower CL injection-level.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5765-5781
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• 2018

Extreme learning machine (ELM) is emerging as a powerful machine learning method in a variety of application scenarios due to its promising advantages of high accuracy, fast learning speed and easy of implementation. However, how to select the optimal hidden layer of ELM is still an open question in the ELM community. Basically, the number of hidden layer nodes is a sensitive hyperparameter that significantly affects the performance of ELM. To address this challenging problem, we propose to adopt multiple kernel learning (MKL) to design a multi-hidden-layer-kernel ELM (MHLK-ELM). Specifically, we first integrate kernel functions with random feature mapping of ELM to design a hidden-layer-kernel ELM (HLK-ELM), which serves as the base of MHLK-ELM. Then, we utilize the MKL method to propose two versions of MHLK-ELMs, called sparse and non-sparse MHLK-ELMs. Both two types of MHLK-ELMs can effectively find out the optimal linear combination of multiple HLK-ELMs for different classification and regression problems. Experimental results on seven data sets, among which three data sets are relevant to classification and four ones are relevant to regression, demonstrate that the proposed MHLK-ELM achieves superior performance compared with conventional ELM and basic HLK-ELM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.261-279
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• 2023

In this article, the uplink achievable rate is investigated for massive multiple-input multiple-output (MIMO) under correlated Ricean fading channel, where each base station (BS) and user are both deployed multiple antennas. Considering the availability of prior knowledge at BS, two different channel estimation approaches are adopted with and without prior knowledge. Based on these channel estimations, a two-layer decoding scheme is adopted with maximum ratio precoding as the first layer decoder and optimal second layer precoding in the second layer. Based on two aforementioned channel estimations and two-layer decoding scheme, the exact closed form expressions for uplink achievable rates are computed with and without prior knowledge, respectively. These derived expressions enable us to analyze the impacts of line-of-sight (LoS) component, two-layer decoding, data transmit power, pilot contamination, and spatially correlated Ricean fading. Then, numerical results illustrate that the system with spatially correlated Ricean fading channel is superior in terms of uplink achievable rate. Besides, it reveals that compared with the single-layer decoding, the two-layer decoding scheme can significantly improve the uplink achievable rate performance.

• Journal of Korea Game Society
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• v.9 no.6
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• pp.171-178
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• 2009

Multiple layer displacement mapping methods are able to represent more complex and general geometries which cannot be presented by single layer displacement mapping methods, and provide a realistic scene to digital contents such as 3D games and movies with relatively low costs. However, as we use more layers for details, data space is wasted more because lower layers have less displacement data than higher layers. In this paper, we suggest a lossless compression and rendering method of a multiple layer displacement map. Since we compress the map without data loss, the proposed method provides the same quality as the rendering result that uses an original multiple layer displacement map.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.677-688
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• 2017

In order to solve the undetected probability of multiple targets in ultra-wideband (UWB) through-the-wall radar imaging (TWRI), a time-delay and amplitude modified back projection (BP) algorithm is proposed. The refraction point is found by Fermat's principle in the presence of a wall, and the time-delay is correctly compensated. On this basis, transmission loss of the electromagnetic wave, the absorption loss of the refraction wave, and the diffusion loss of the spherical wave are analyzed in detail. Amplitude compensation is deduced and tested on a model with a single-layer wall. The simulating results by finite difference time domain (FDTD) show that it is effective in increasing the scattering intensity of the targets behind the wall. Compensation for the diffusion loss in the spherical wave also plays a main role. Additionally, the two-layer wall model is simulated. Then, the calculating time and the imaging quality are compared between a single-layer wall model and a two-layer wall model. The results illustrate the performance of the time-delay and amplitude-modified BP algorithm with multiple targets and multiple-layer walls of UWB TWRI.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.442-449
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• 2013

In this paper, a simulation system based on X-Plane and MATLAB/Simulink for multiple UAVs is presented. For the conceptual design of this proposed system, a hierarchical system architecture for multiple UAVs is presented. This architecture has object-oriented data structure which consists of three objects (UAV status, mission and task, and environment) and a hierarchy consisting of four layers (decision making layer, task assignment layer, path and motion planning layer, and collision avoidance layer) is also proposed. In addition, this paper shows a implementation of simulation system based on the proposed system architecture using X-Plane and MATLAB/Simulink. The result of simulation from the developed system in this paper validate capability of application for multiple UAVs in real environment.