• Nuclear Engineering and Technology
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• v.48 no.3
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• pp.795-798
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• 2016

Transmission X-ray tubes based on carbon nanotube have attracted significant attention recently. In most of these tubes, tungsten is used as the target material. In this article, the well-known simulator Geant4 was used to obtain some of the tungsten target parameters. The optimal thickness for maximum production of usable X-rays when the target is exposed to electron beams of different energies was obtained. The linear variation of optimal thickness of the target for different electron energies was also obtained. The data obtained in this study can be used to design X-ray tubes. A beryllium window was considered for the X-ray tube. The X-ray energy spectra at the moment of production and after passing through the target and window for different electron energies in the 30-110 keV range were also obtained. The results obtained show that with a specific thickness, the target material itself can act as filter, which enables generation of X-rays with a limited energy.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.250-257
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• 2002

Clustering is a data mining method, which consists in discovering interesting data distributions in very large databases. In traditional data clustering, similarity of a cluster of object is measured by pairwise similarity of objects in that paper. In view of the nature of clustering transactions, we devise in this paper a novel measurement called item similarity and utilize this to perform clustering. With this item similarity measurement, we develop an efficient clustering algorithm for target marketing in each group.

• Journal of Applied Reliability
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• v.15 no.4
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• pp.248-255
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• 2015

Purpose : The purpose of this research is to develop the optimized method and process in the reliability-growth target setting, especially for complex and repairable system (or products) such as vehicle and airplane, construction equipment. Method : A reliability-growth test plan specifies a scenario to achieve the planned reliability value (or reliability target). The major elements in test planning are reliability-growth starting time and reliability level at that time, reliability-growth rate and reliability-growth target. All of them except a reliability target can be referred to the previous development data and reference researches. The reliability target level is directly influencing to test period (or time) which is related to test and warranty cost together. There are a few researches about the reliability target setting method and but showing the limitations to consider the views of engineering, business and customer together. There is no research how to handle the target setting process in detail. Result : We develop the optimized method and systematic process in reliability target setting with considering such views. This research also establish the new concept as production capability which means company (or supplier) capability to product its products. Conclusion : In this research result, we apply the new method to a few projects and can set the reasonable test planning. The developing results is showing the good balance between the developing cost and warranty cost at market.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.6
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• pp.457-463
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• 2018

This paper compares the results of ${\Sigma}{\Delta}-STAP$ applied to actual radar test data and simulation data. The radar received a target signal from a virtual target generator and the clutter signal from a signal generator in an anechoic chamber. The simulation data were generated from ideal baseband radar signal modeling using the same parameter as that for the test radar. The ${\Sigma}{\Delta}-STAP$ results of the test and simulation data are similar in terms of the target signal shape and noise level. The SINR(Signal-to-Interfrence-plus-Noise Ratio) loss also had similar aspects, but the simulation result shows 1~2 dB higher SINR loss than the test result. This result verified that the simulation data can be a reasonable alternative test data when the ${\Sigma}{\Delta}-STAP$ is applied.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.872-885
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• 2015

The rapid increase of smart mobile devices and mobile applications has led to explosive growth of data traffic in cellular network. Offloading data traffic becomes one of the most urgent technical problems. Recent work has proposed to exploit opportunistic communications to offload cellular traffic for mobile data dissemination services, especially for accepting large delayed data. The basic idea is to deliver the data to only part of subscribers (called target-nodes) via the cellular network, and allow target-nodes to disseminate the data through opportunistic communications. Human mobility shows temporal and spatial characteristics and predictability, which can be used as effective guidance efficient opportunistic communication. Therefore, based on the regularity of human mobility we propose NodeRank algorithm which uses the encounter characteristics between nodes to choose target nodes. Different from the existing work which only using encounter frequency, NodeRank algorithm combined the contact time and inter-contact time meanwhile to ensure integrity and availability of message delivery. The simulation results based on real-world mobility traces show the performance advantages of NodeRank in offloading efficiency and network redundant copies.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.729-732
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• 2005

This paper describes a time-spatial domain model for simulating raw data acquisition of space-borne SAR system. The position, velocity and attitude information of the platform at a certain time instance is used for deriving sensor-target model. Ground target is modelled by a set of point scatters with reflectivity and two-dimensional ground coordinates. The signal received by SAR is calculated for each slow and fast time instance by integrating the reflectivity and phase values from all target point scatters. Different from frequency domain simulation algorithms, the proposed time domain algorithm can provide fully physical modelling of SAR raw data simulation without any assumptions or approximations.

• Journal of Ocean Engineering and Technology
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• v.34 no.3
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• pp.227-236
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• 2020

Underwater acoustics, which is the domain that addresses phenomena related to the generation, propagation, and reception of sound waves in water, has been applied mainly in the research on the use of sound navigation and ranging (SONAR) systems for underwater communication, target detection, investigation of marine resources and environment mapping, and measurement and analysis of sound sources in water. The main objective of remote sensing based on underwater acoustics is to indirectly acquire information on underwater targets of interest using acoustic data. Meanwhile, highly advanced data-driven machine-learning techniques are being used in various ways in the processes of acquiring information from acoustic data. The related theoretical background is introduced in the first part of this paper (Yang et al., 2020). This paper reviews machine-learning applications in passive SONAR signal-processing tasks including target detection/identification and localization.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1146-1152
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• 2002

This paper proposed a scheme for finding an optimal adaptive data association for multi-target between measurements and tracks. First, we assume the relationships between measurements as Mrkov Random Field. Also assumed a priori of the associations as a Gibbs distribution. Based on these assumptions, it was possible to reduce the MAP estimate of the association matrix to the energy minimization problem. After then, we defined an energy function over the measurement space, that may incorporate most of the important natural constraints. Through the experiments, we analyzed and compared this algorithm with other representative algorithms. The result is that it is stable, robust, fast enough for real timecomputation, as well as more accurate than other methods.

• MALSORI
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• no.67
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• pp.167-180
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• 2008

This paper describes a novel spectral envelope conversion method based on Gaussian mixture model (GMM). The core of this paper is rearranging source feature vectors in input space to the transformed feature vectors in feature space for the better modeling of GMM of source and target features. The quality of statistical modeling is dependent on the distribution and the dimension of data. The proposed method transforms both of the distribution and dimension of data and gives us the chance to model the same data with different configuration. Because the converted feature vectors should be on the input space, only source feature vectors are rearranged in the feature space and target feature vectors remain unchanged for the joint pdf of source and target features using KPCA. The experimental result shows that the proposed method outperforms the conventional GMM-based conversion method in various training environment.

• Bulletin of the Korean Mathematical Society
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• v.53 no.5
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• pp.1439-1446
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• 2016

The execution complexities of the major time memory data tradeoff methods are analyzed in this paper. The multi-target tradeoffs covered are the classical Hellman, distinguished point, and fuzzy rainbow methods, both in their non-perfect and perfect table versions for the latter two methods. We show that their computational complexities are identical to those of the corresponding single-target methods executed under certain matching parameters and conclude that the perfect table fuzzy rainbow tradeoff method is most preferable.