• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.228-231
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• 2006

선박의 위치추적시스템(VMS: Vessel Monitoring System)은 선박의 안전항해를 확보하기 위한 수단으로 다양한 통신망을 사용하여 구성을 확대해나가고 있다. VMS를 위한 통신망으로는 현재 Inmarsat 및 Orbcomm 등 위성통신망과 AIS(Automatic Identification System of ships: 선박자동식별장치)의 VHF(Very High Frequency: 초단파) 통신망 등이 사용되고 있다. 최근에는 5톤 이상의 어선에도 VHF 무선설비의 설치를 단계적으로 강제화하였으며, 소형선박에도 AIS의 탑재를 강제화할 계획을 검토하고 있음에 따라 이에 따른 효율적인 통신망 구축 방안을 사전에 검토할 필요성이 대두되었다. 여기에서는 선박의 안전항해를 확보하고 효율적인 VMS를 구축할 수 있는 VMS 통신망 구축 방안에 대하여 연구 제시하였다.

• Structural Engineering and Mechanics
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• v.85 no.3
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• pp.393-406
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• 2023

Smart structures are those structure that could adopt some behavior to prevent instability in their responses. The recognition of stability deterioration has been performed through rigid mathematical formulations in control theory and unpredicted results could not be addressed in control systems since they are able to only work under their predefined condition. On the other hand, incorporating all affecting parameters could result in high computational cost and delay time in the response of the systems. Artificial intelligence (AI) method has shown to be a promising methodology not only in the computer science by at everyday life and in engineering problems. In the present study, we exploit the capabilities of artificial intelligence method to obtain frequency response of a smart structure. In this regard, a comprehensive development of equations is presented using Hamilton' principle and first order shear deformation theory. The equations were solved by numerical methods and the results are used to train an artificial neural network (ANN). It is demonstrated that ANN modeling could provide accurate results in comparison to the numerical solutions and it take less time than numerical solution.

• Journal of Drive and Control
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• v.20 no.4
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• pp.54-63
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• 2023

High and intermittent loading cycles induce fatigue damage to transmission components, resulting in premature gearbox failure. To identify gearbox defects, numerous vibration-based diagnostics techniques, using several artificial intelligence (AI) algorithms, have recently been presented. In this paper, an optimized deep belief network (DBN) model for gearbox problem diagnosis was designed based on time-frequency visual pattern identification. To optimize the hyperparameters of the model, a particle swarm optimization (PSO) approach was integrated into the DBN. The proposed model was tested on two gearbox datasets: a wind turbine gearbox and an experimental gearbox. The optimized DBN model demonstrated strong and robust performance in classification accuracy. In addition, the accuracy of the generated datasets was compared using traditional ML and DL algorithms. Furthermore, the proposed model was evaluated on different partitions of the dataset. The results showed that, even with a small amount of sample data, the optimized DBN model achieved high accuracy in diagnosis.

• Journal of Sensor Science and Technology
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• v.33 no.2
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• pp.78-85
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• 2024

We proposed a method for visual place recognition that represents images using objects as visual words. Visual words represent the various objects present in urban environments. To detect various objects within the images, we implemented and used a zero-shot detector based on a large-scale image language model. This zero-shot detector enables the detection of various objects in urban environments without additional training. In the process of creating histograms using the proposed method, frequency-based weighting was applied to consider the importance of each object. Through experiments with open datasets, the potential of the proposed method was demonstrated by comparing it with another method, even in situations involving environmental or viewpoint changes.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.2
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• pp.103-112
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• 2012

We demonstrate the preliminary results of ship detection application using synthetic aperture radar (SAR) and automatic identification system (AIS) together. Multi-frequency and multi-temporal SAR images such as TerraSAR-X and Cosmo-SkyMed (X-band), and Radarsat-2 (C-band) are acquired over the West Sea in South Korea. In order to compare with SAR data, we also collected an AIS data. The SAR data are pre-processed considering by the characteristics of scattering mechanism as for sea surface. We proposed the "Adaptive Threshold Algorithm" for classification ship efficiently. The analyses using the combination of the SAR and AIS data with time series will be very useful to ship detection or tracing of the ship.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.1
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• pp.116-124
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• 2009

This paper proposes a new Artificial-Intelligent(AI) Power Quality(PQ) diagnosis algorithm using Discrete Wavelet Transform(DWT), Fast Fourier Transform(FFT), Root-Mean-Square(RMS) value. The developed algorithm is able to detect and classify the PQ problems such as the transient, the voltage sag, the voltage swell, the voltage interruption and the total harmonics distortion. The 15.36[kHz] sampling frequency is used to measure the voltages in a power system. The measured signals are used for DWT, FFT, RMS calculation. For AI diagnosis of the PQ problems, a simple multi-layered Artificial Neural Network(ANN) with the back-propagation algorithm is adopted, programmed in C++ and tested in PSIM simulation studies. Finally, the algorithm, which is installed in MP PQ+256 with TI DSP320C6713, is proved to diagnose the PQ problems efficiently.

• The Journal of Churna Manual Medicine for Spine and Nerves
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• v.7 no.2
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• pp.101-108
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• 2012

Objectives : To evaluate the clinical utility of Muscle Energy Techniques(MET) in Elector Spinae Muscle on subjects. Methods : We compared electrical activity between a before MET and a after MET in Elector Spinae Muscle on subjects in same group(n=26) in dynamic flexion-reextension state during five seconds. We analyzed amplitudes and areas of electrical activity and Asymmetry Index(AI) and Median Edge Frequency(MEF). Results : 1. After MET in Elector Spinae Muscle on subjects were lower electrical activity than before MET in Elector Spinae Muscle on subjects but it is not a pointless observation(p<0.05). 2. AI of the after MET in Elector Spinae Muscle on subjects significantly decreased compared with before MET in Elector Spinae Muscle on subjects(p<0.05). 3. MEF of the after MET in Elector Spinae Muscle on subjects decreased compared with before MET in Elector Spinae Muscle on subjects but it is not a pointless observation(p<0.05). Conclusions : According to above results, there is clinical effect MET on subjects.

• Journal of the Korean Ceramic Society
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• v.36 no.12
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• pp.1350-1355
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• 1999

Sintering characteristics and dielectric properties of low temperature sinterable Glass/Ceramic dielectric materials were investigated. The dielectric materials which were developed for microwave frequency applications consist of SiO2-TiO2-Bi2O3-RO system(RO:BaO-CaO-SrO) crystallizable glass and Al2O3 as a ceramic filler. Sintering experiments showed that no more densification occurred above 80$0^{\circ}C$ and bulk density and shrinkage depended on Al2O3 content only. Results of dielectric measurements showed that $\varepsilon$r Q$\times$f and $\tau$f of the material containing 30wt% Al2O3 were 17.3, 600 and +23 ppm respectively. Those values for 45 and 60wt% Al2O3 samples were 11.6, 1400, +0.7 ppm and 7.2, 2000, -8.5 ppm, repectively. The results clearly showed that the Glas/Ceramic materials of present experiment decreased in $\varepsilon$r and increased in $\times$f value and changed from positive to negative value in $\tau$f value with the increasement of Al2O3 content.

• Journal of Digital Contents Society
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• v.19 no.5
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• pp.981-993
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• 2018

Smart healthcare is convergence of ICT and healthcare services, and interdisciplinary research has been actively conducted in various fields. The objective of this study is to investigate trends of smart healthcare research using topic modeling and ego network analysis. Text analysis, frequency analysis, topic modeling, word cloud, and ego network analysis were conducted for the abstracts of 2,690 articles in Scopus from 2001 to April 2018. Topic Modeling analysis resulted in eight topics, Topics included "AI in healthcare", "Smart hospital", "Healthcare platform", "Blockchain in healthcare", "Smart health data", "Mobile healthcare", " Wellness care", "Cognitive healthcare". In order to examine the topic modeling results core deeply, we analyzed word cloud and ego network analysis for eight topics. This study aims to identify trends in smart healthcare research and suggest implications for establishing future research direction.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.127-132
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• 2022

Among the electrical components mounted on railroad cars, the largest load is the main transformer, which has a low power density of 0.2~0.4 MVA/ton due to the low operating frequency(60Hz), which is an important factor for weight reduction. Therefore, research on molded transformers, semiconductor transformers, etc. is being actively conducted at Domestic and foreign in order to improve the main transformer for railway vehicles. Meanwhile, attempts are being made to apply a permanent magnet synchronous motor (PMSM) to replace an induction motor as a traction motor that is mostly applied to domestic and foreign railway vehicles. Permanent magnet synchronous motors (PMSMs) can secure higher power density and efficiency compared to induction motors, but have disadvantages in that the materials required for manufacturing are expensive and design is somewhat difficult compared to induction motors. Considering these problems, in this paper, we suggest that a small and lightweight semiconductor transformer is applied, and a simple structure, high torque, low cost SRM can be applied in accordance with the requirements such as weight reduction and high efficiency of railroad vehicles. content.