• Journal of Information Processing Systems
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• v.14 no.3
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• pp.694-708
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• 2018

China possesses a passenger dedicated line system of large scale, passenger flow intensity with uneven distribution, and passenger nodes with complicated relations. Consequently, the significance of passenger nodes shall be considered and the dissimilarity of passenger nodes shall be analyzed in compiling passenger train operation and conducting transportation allocation. For this purpose, the passenger nodes need to be hierarchically divided. Targeting at problems such as hierarchical dividing process vulnerable to subjective factors and local optimum in the current research, we propose a clustering approach based on self-organizing map (SOM) and k-means, and then, harnessing the new approach, hierarchical dividing of passenger dedicated line passenger nodes is effectuated. Specifically, objective passenger nodes parameters are selected and SOM is used to give a preliminary passenger nodes clustering firstly; secondly, Davies-Bouldin index is used to determine the number of clusters of the passenger nodes; and thirdly, k-means is used to conduct accurate clustering, thus getting the hierarchical dividing of passenger nodes. Through example analysis, the feasibility and rationality of the algorithm was proved.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.176-176
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• 2018

This study presents a regional, probabilistic framework for estimating streamflow via spatial scaling in the Great Lakes basin, which is the largest lake system in the world. The framework follows a two-fold strategy including (1) a quadratic-programming based optimization model a priori to explore the model structure, and (2) a time-varying hierarchical Bayesian model based on insights found in the optimization model. The proposed model is developed to explore three innovations in hierarchical modeling for reconstructing historical streamflow at ungaged sites: (1) information of physical characteristics is utilized in spatial scaling, (2) a time-varying approach is introduced based on climate information, and (3) heteroscedasticity in residual errors is considered to improve streamflow predictive distributions. The proposed model is developed and calibrated in a hierarchical Bayesian framework to pool regional information across sites and enhance regionalization skill. The model is validated in a cross-validation framework along with four simpler nested formulations and the optimization model to confirm specific hypotheses embedded in the full model structure. The nested models assume a similar hierarchical Bayesian structure to our proposed model with their own set of simplifications and omissions. Results suggest that each of three innovations improve historical out-of-sample streamflow reconstructions although these improvements vary corrsponding to each innovation. Finally, we conclude with a discussion of possible model improvements considered by additional model structure and covariates.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2000.11a
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• pp.12-15
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• 2000

In this paper, we have evaluated the performance of an OFDM system using hierarchical 16QAM (OFDM/HL-16QAM) for achieving high quality and high speed data and image transmission in multipath fading channel. The wireless channel for performance evaluation is assumed to include AWGN and two ray multipath fading. Through simulation we have obtained the BER performance of the system according to $E_{b}$, $N_{0}$, then compared the received image quality of proposed system with that of conventional system. From the result, it is shown that the OFDM/HL-16QAM system is more effective for data and image transmission.n.n.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.11-12
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• 2006

An algorithm to improve the efficiency of the hierarchical routing in ZigBee Networks is proposed. By forwarding the data to the nearest neighbor in the hierarchy, more efficient path can be achieved without any control and memory overhead. Simulation results shows the proposed algorithm provides about 20% shorter path.

• Journal of Astronomy and Space Sciences
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• v.33 no.4
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• pp.257-264
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• 2016

A planet revolving around binary star system is a familiar system. Studies of these systems are important because they provide precise knowledge of planet formation and orbit evolution. In this study, a method to determine the evolution of an exoplanet revolving around a binary star system using different rates of stellar mass loss will be introduced. Using a hierarchical triple body system, in which the outer body can be moved with the center of mass of the inner binary star as a two-body problem, the long period evolution of the exoplanet orbit is determined depending on a Hamiltonian formulation. The model is simulated by numerical integrations of the Hamiltonian equations for the system over a long time. As a conclusion, the behavior of the planet orbital elements is quite affected by the rate of the mass loss from the accompanying binary star.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.6
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• pp.949-964
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• 2021

Accumulation of high-quality data is crucial for AI learning. The goal of using AI in fashion service is to propose of a creative, personalized solution that is close to the know-how of a human operator. These customized solutions require an understanding of fashion products and emotions. Therefore, it is necessary to accumulate data on the attributes of fashion products and fashion emotion. The first step for accumulating fashion data is to standardize the attribute with coherent system. The purpose of this study is to propose a fashion emotional classification system. For this, images of fashion products were collected, and metadata was obtained by allowing consumers to describe their emotions about fashion images freely. An emotional classification system with a hierarchical structure, was then constructed by performing frequency and CONCOR analyses on metadata. A final classification system was proposed by supplementing attribute values with reference to findings from previous studies and SNS data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.9
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• pp.728-737
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• 2012

An analytical method for identifying terrestrial broadcasting coverages is proposed for a terrestrial broadcasting transmission system adopting a hierarchical modulation technique. Bit Error Rates(BERs) are derived for hierarchically modulated non-uniform QAM constellations based on the Q-function analysis in AWGN environments. The derived BERs depend on the hierarchical modulation factor ${\alpha}$(HMF) and could be mapped to the broadcasting coverages according to the link budget analysis based on the log-distance path loss model. Finally the broadcasting coverage ratios for high priority(HP) streams and low priority(LP) streams are calculated and presented for the determination of the HMF.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10B
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• pp.885-893
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• 2008

In RFID system, reader collision happened when multiple readers try to read the tags at the same time. Because reader collision reduces tag recognition performance, it is required for RFID system to have reader anti-collision algorithm. In this paper, we propose reader anti-collision algorithm based on hierarchical structure, where a master reader controls the slave readers to avoid the reader collisions. It is verified through simulations that the proposed algorithm enhances the performance in terms of leader collision probability and tag reading time.

• The Journal of Korean Association of Computer Education
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• v.3 no.1
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• pp.135-142
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• 2000

Recently the user of distance education system using Intemet-Web are increasing rapidly. This paper shows that Hierarchical WBI documents generator by using CGI is devised and applied to development of distance education system for group-level spoken english. This overcomes the problems of the ready-made programs, which took a lot of time and cost. To generate WBI documents, The key is established to each document saved in server by types of the hierarchical structure and is transmitted to client. By client transmitting this key to server when next documentary is required. Sever can know what documents the client needs. The WBI documentary generator tells the keys transmitted from the client, automatically generates a new documentary to send, and delivery it.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.716-721
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• 2010

In this work we address the use of support vector machine (SVM) in the multi-class gas classification system. The objective is to classify single gases and their mixture with a semiconductor-type electronic nose. The SVM has some typical multi-class classification models; One vs. One (OVO) and One vs. All (OVA). However, studies on those models show weaknesses on calculation time, decision time and the reject region. We propose a hierarchical clustering method (HCM) based on the SVM for real-time gas mixture classification. Experimental results show that the proposed method has better performance than the typical multi-class systems based on the SVM, and that the proposed method can classify single gases and their mixture easily and fast in the embedded system compared with BP-MLP and Fuzzy ARTMAP.