• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.1
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• pp.23-34
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• 2002

This paper proposes a new neuro-fuzzy system that is fast trained by evolution strategy and describes application results of the proposed system to nonlinear system identification to show its usefulness. As training methods of neuro-fuzzy systems, modified error back-propagation algorithms and genetic algorithms have been used so far. However, the former has some drawbacks such as long training time, falling to local optimum, and experimental selecting of learning rates and the latter has difficulty in precise searching solutions because genetic algorithms represents solutions as genotype individuals. The evolution strategy we used can do precise search because its individuals are represented as phenotype real values, it seldom falls into a local optimum, and its training speed is faster than error back-propagation algorithms. We apply our neuro-fuzzy systems to nonlinear system identification. It was found from experiments that training speed is fast and the training results were considerably good.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.95-98
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• 2009

RFID(Radio Frequency IDentification) technology is an automatic identification method using radio frequencies between RFID reader which collects the informatin and tag which transmits the information. RFID technology develops passive RFID which transmit the only ID to active RFID which transmit the additional information such as sensing information. there is ISO/IEC 18000-7 as typical standard of active RFID. it is single channel system of 433.92MHz and has limitation of collection of a number of tags. to overcome limitation of collection of many tags, we propose the new 2.4GHz active RFID technology which can use the multi-channel. if reader has multi-interface and uses another channel in each, reader could fast collect the tags. but, if a reader which has many interfaces collects tags through the specific interface, the performance may not improve any more comparing with a reader using single interface. in this paper, we show the fast collection through design and implementation of protocol for load balancing between interfaces in multi-interface RFID reader.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.7
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• pp.933-940
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• 2017

Draught and trim conditions are highly related to the loading condition of a vessel and are important factors in predicting ship manoeuverability. This paper estimates hydrodynamic coefficients from sea trial measurements with three different trim and draught conditions. A mathematical optimization method for system identification was applied to estimate the forces and moment acting on the hull. Also, fast time simulation software based on the Rheinmetall Defense model was applied to the whole estimation process, and a 4,500 Twenty-foot Equivalent Unit (TEU) class container carrier was chosen to collect sets of measurement data. Simulation results using both optimized coefficients and newly-calculated coefficients for validation agreed well with benchmark data. The results show mathematical optimization using sea measurement data enables hydrodynamic coefficients to be estimated more simply.

• Journal of Veterinary Science
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• v.23 no.1
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• pp.17.1-17.10
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• 2022

Background: Inspection of livestock farms using surveillance cameras is emerging as a means of early detection of transboundary animal disease such as African swine fever (ASF). Object tracking, a developing technology derived from object detection aims to the consistent identification of individual objects in farms. Objectives: This study was conducted as a preliminary investigation for practical application to livestock farms. With the use of a high-performance artificial intelligence (AI)-based 3D depth camera, the aim is to establish a pathway for utilizing AI models to perform advanced object tracking. Methods: Multiple crossovers by two humans will be simulated to investigate the potential of object tracking. Inspection of consistent identification will be the evidence of object tracking after crossing over. Two AI models, a fast model and an accurate model, were tested and compared with regard to their object tracking performance in 3D. Finally, the recording of pig pen was also processed with aforementioned AI model to test the possibility of 3D object detection. Results: Both AI successfully processed and provided a 3D bounding box, identification number, and distance away from camera for each individual human. The accurate detection model had better evidence than the fast detection model on 3D object tracking and showed the potential application onto pigs as a livestock. Conclusions: Preparing a custom dataset to train AI models in an appropriate farm is required for proper 3D object detection to operate object tracking for pigs at an ideal level. This will allow the farm to smoothly transit traditional methods to ASF-preventing precision livestock farming.

• Tunnel and Underground Space
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• v.15 no.1 s.54
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• pp.47-54
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• 2005

One of the standard procedures of discontinuity survey is the joint set identification from the population of field orientation data. Discontinuity set identification is fundamental to rock engineering tasks such as rock mass classification, discrete element analysis, key block analysis. and discrete fracture network modeling. Conventionally, manual method using contour plot had been widely used for this task, but this method has some short-comings such as yielding subjective identification results, manual operations, and so on. In this study, the method of discontinuity set identification using genetic algorithm was introduced, but slightly modified to handle the orientation data. Finally, based on the genetic algorithm, we developed a FORTRAN program, Genetic Algorithm based Clustering(GAC) and applied it to two different discontinuity data sets. Genetic Algorithm based Clustering(GAC) was proved to be a fast and efficient method for the discontinuity set identification task. In addition, fitness function based on variance showed more efficient performance in finding the optimal number of clusters when compared with Davis - Bouldin index.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.959-962
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• 2005

Recently, business integration and interoperability of between the heterogeneous applications are requested by rapid growth of web. Web Services that self-contained for platform and programming language is appeared used to XML of standard data format. Such amid Fast Web Services attract attention at fields necessary to bring rapid communication like Mobile and RFID. In this paper, we inquired about ASN.1 of ITU-T and IS0/IEC standard that a central role of data transform. And we studied encoding process of between ASN.1 and XML for transform SOAP massage of a massage transfer mode of Web Services to binary data.

• Journal of the Korean Society for Marine Environment & Energy
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• v.7 no.3
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• pp.122-130
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• 2004

Crude oil is complex mixture of thousands of different organic compound formed from a variety of organic materials that are chemically converted under differing geological conditions over long periods of time. Also oil composition varies according to crude source, refining, processing, handling and storage. The oil fingerprint method is application of specific knowledge of petrochemicals and use of sophisticated analytical equipment and techniques to identify the source(s) of oil pollution. KNMPA currently utilizes three primary analytical techniques: Gas Chromatography (GC), Fluorescence Spectroscopy(FL) and Infrared Spectroscopy(IR). Of all these techniques, GC technique are most widely used. Gas Chromatography is used as a primary analytical method because high reliableness, high separating efficiency and repeatability, but it is timeconsumable. The study results of identification of waterborne spilled oil by Fast Gas Chromatograph method showed that analytical time is cut down to 30minutes in comparison with packed column method and chromatograms represent high resolution and high repeatability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.5
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• pp.931-936
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• 2016

The PS algorithm divides the number of tags within the identification range of reader into smaller groups by increasing the transmission power incrementally and identifies them. It limits the number of responding tags by grouping the tags within the identification range of the reader, and thus can reduce the probability of tag collision. Also, in the PS algorithm, the reader takes advantages of the difference of identification ranges. This algorithm uses the fixed frame size at every scan. Therefore, it has problems that the performance can be shown variously according to the number of tags and frame size. In this paper, we propose an EPS algorithm that allocates the optimal frame size by estimating the number of tags at each scan, and apply it into the STAC protocol. The simulation results showed that STAC/EPS algorithm can improve the identification delay about 45% compared with STAC protocol. Also, it provides a stable identification delay regardless of power level increase.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.54-60
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• 2006

This study looks over the relation between propeller and noise in ship stern structure. Near field noise and vibration measurements are compared with the analytical results using wave number method. To avoid singularity in wave number integration method, fast field method is introduced. Analytical results show that main transmission mechanism of high frequency noise is structure-borne type and that of low frequency noise is a air-borne type.

• Journal of Industrial Technology
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• v.18
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• pp.295-302
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• 1998

Classification of fingerprints is one of the major subjects on which many researchers have been studying for efficient identification. But fingerprints should be preprocessed in various ways prior to being classified. Factors such as the accuracy and the processing time should be considered in classification of fingerprints. In this paper, we propose a method for classifying fingerprints into several frequent patterns. This method consists of two stages. A fingerprint image is first converted to a skeleton form to find out the center. Then it is identified as a member of one of preclassified pattern by the frequency domain feature. Experiments show that the proposed method is quite useful in classifying fingerprints into typical patterns.