• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.23-30
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• 2010

Flash memory is non-volatile and can retain data even after system is powered off. Besides, it has many other features such as fast access speed, low power consumption, attractive shock resistance, small size, and light-weight. As its price decreases and capacity increases, the flash memory is expected to be widely used in consumer electronics, embedded systems, and mobile devices. Flash storage systems generally adopt a software layer, called FTL. In this research, we proposed a new FTL mechanism for overcoming the major drawback of conventional block mapping algorithm. In addition to the block mapping table, a index block mapping table with a small size is used to indicate sector location. The proposed indexed block mapping algorithm by adding a small size. By the simulation result, the proposed FTL provides an enhanced speed than a conventional hybrid mapping algorithm by around 45% in average, and the requirement of mapping memory is also reduced by around 12%.

• Korean Journal of Optics and Photonics
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• v.11 no.5
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• pp.306-311
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• 2000

This paper deals with the development of Laser Doppler Vibrometer (LDV) that can mea~ure the tlequency and amphlude of the ultrasonic vibralion. Hc-Ne laser (632.8 om) is used as a light source, and Michelson interferometer in winch frequency of the objective beam is shIfted by Bragg cell IS adopted The frequency modulated signal centered at 40 MHz flom the PIN diode IS amplified. down-col1vel1ed to 2.5 MHz, filtered and digiLized. The voltage output that is proportional to the velocity of the vibratwg surface is obtawed using digItal PLL. A microprocessor is used to extract the frequcncy aud amplitude of the vibratIOn from the voltage output. It is found that the developed LDV can measure up to 300 kHz vibratIOn and the mlillmUITI measurable amplitude is I nm at 300 kHz. We believe thatlhis LDV can be used to measure the vibratIOn of the heavy electric maclllnery and micro-size structures. tures.

• Journal of the Korean Society of Hazard Mitigation
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• v.5 no.4 s.19
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• pp.95-105
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• 2005

Korea is located away from plate boundaries which are not safe from earthquakes. However, having witnessed the large-scale earthquake in the Tangshan region in 1976 deemed as a safe plate, it should not be assured that Korea is absolutely safe from earthquakes. In addition, many seismologists have claimed that there indeed is a high possibility of earthquakes above mid scale that would occur in Korea. Because it is impossible to prevent earthquake, studies on seismic design and earthquake disaster control system are widely being conducted. However, studies on early response to earthquakes or recovery process are still very limited, and only a few studies for establishing earthquake damage evaluation system are being conducted. Thus, this study aimed to present essential data for establishing earthquake damage evaluation system that takes into account the real situation of structures in Korea. In this study, a nonseimically reinforced concrete apartment structure in Gangnamgu was selected as an standard type of such structures and its earthquake damage was estimated. The result of damage evaluation based on the derivation of vulnerability function and realtive story displacement was compared to that abtained using HAZUS Program Vulnerability Function.

• Journal of Navigation and Port Research
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• v.27 no.4
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• pp.465-469
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• 2003

It has well known that MUSIC and ESPRIT algorithms estimate angle of arrival(AOA) with high resolution by eigenvalue decomposition of the covariance matrix which were obtained from the array antennas, However, the disadvantage of MUSIC and ESPRIT is that they are computationally ineffective, and then they are difficult to implement in real time. the other problem of MUSIC and ESPRIT is to require calibrated antennas with uniform features, and are sensitive ti the manufacturing fault and other physical uncertainties. To overcome these disadvantages, several method using neural model have been study. For multiple signals, those methods require huge training data prior to AOA estimation. This paper proposes the algorithm for AOA estimation by interconnected Hopfield neural model. Computer simulations show the validity of the proposed algorithm. It follows that the proposed method yields better AOA estimates than MUSIC. Moreover, out method does not require huge training procedure and only assigns interconnected coefficients to the neural network prior to AOA estimation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1740-1749
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• 2009

As mobile devices evolve and digital convergence trend is here to stay, mobile phones are built with multiple functions including cameras, MP3s, TVs and game consoles. As a consequence, such multi-functional mobile phones come to spend more power, facilitating development of next-generation ultra-capacity lithium ion battery. In addition, environmental regulations and rising oil prices cause demand for hybrid cars to keep rising. Accordingly, more and more attention is being paid to medium and large batteries and more efforts are being made to realize lower battery prices, higher outputs and stability. This study presented a patent technology related to the lithium ion battery packing that allows reducing processes related, increasing productivity and recycling parts other than the body. The lithium ion battery pack to which protection circuits are elastically attached provides short circuit protection for the circuit and the body and makes electric connection of the circuit and the body easier.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.27-32
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• 2005

As a large quantity of Genome sequencing has happened to be done a very much a surprising speed in short period, an automatic genome annotation process has become prerequisite. The most difficult process among with this kind of genome annotation works is to finding out the protein-coding genes within a genome. The main 2 subjects of gene prediction are Eukaryotes and Prokaryotes ; their genes have different structures, therefore, their gene prediction methods will also obviously varies. Until now, it is found that among of the 231 genome sequenced species, 200 have been found to be prokaryotes, therefore, for study of biotechnology studies, through comparative genomics, prokaryotes, rather than eukaryotes could may be more appropriate than eukaryotes. Even more, prokaryotes does not have the gene structure called an intron, so it makes the gene prediction easier. Former prokaryotes gene predictions have been shown to be 80%～ to 90% of accuracy. A recent study is aiming at 100% of gene prediction accuracy. In this paper, especially in the case of the E. coli K-12 and S. typhi genomes, gene prediction accuracy which showed 98.5% and 98.7% was more efficient than previous GLIMMER.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.2
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• pp.79-85
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• 2006

As the portable information appliance is developed, the demand of flat panel display equipments and parts are steeply increased. Most of all, the applications of LCD such as LCD TV, monitor, digital camera, CNS(car navigation system) and game machine become diversified. With the result that the number of BLU production enterprise is increased and the research on the design of backlight with the superior optical properties is persistently in progress. In this study we developed the pattern design tools for CCFL(cold cathode flourescent lamp) backlight to improve the conventional pattern design environment in which the pattern is designed manually from the experience and the trial and error. For the verification of our research, we designed the light reflection surface patterns for a real model of backlight and we measured the brightness uniformity using the BM-7. From the brightness uniformity measurement, the BLU designed using the presented tool showed the tolerable performance only in the first try of pattern design rather than the fifth try of pattern design in case of the conventional pattern design.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.730-737
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• 2018

With the increasing number of health consumers aiming for a happy quality of life, the O2O medical marketing market is activated by choosing reliable health care facilities and receiving high quality medical services based on the medical information distributed on web's blog. Because unstructured text data used on the Internet, mobile, and social networks directly or indirectly reflects authors' interests, preferences, and expectations in addition to their expertise, it is difficult to guarantee credibility of medical information. In this study, we propose a blog reading system that provides users with a higher quality medical information service by classifying medical information blogs (medical blog, ad blog) using bigdata and MLP processing. We collect and analyze many domestic medical information blogs on the Internet based on the proposed big data and machine learning technology, and develop a personalized health information recommendation system for each disease. It is expected that the user will be able to maintain his / her health condition by continuously checking his / her health problems and taking the most appropriate measures.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.205-210
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• 2022

Drones, which have rapidly grown along with the 4th industrial revolution, spread over industries and also widely used for military purposes. In recent wars in Europe, drones are being evaluated as a game changer on the battlefield, and their importance for military use is being highlighted. The Republic of Korea Army also planned drone-bot systems including various drones suitable for echelons and missions of the military as future defense forces. The keyword of these drone-bot systems is autonomy by artificial intelligence. In addition, common use of operating platforms is required for the rapid development of various types of drones. In this paper, we propose software framework that applies diverse artificial intelligence technologies such as multi-agent system, cognitive architecture and knowledge-based context reasoning for mission autonomy and common use of military drones.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.81-89
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• 2010

Biological data mining has been noticed as an issue as the volume of biological data is increasing extremely. Grid technology can share and utilize computing data and resources. In this paper, we propose a hybrid system that combines biological data mining with grid technology. Especially, we propose a decision range adjustment algorithm for processing efficiency of biological data mining. We obtain a reliable data mining recognition rate automatically and rapidly through this algorithm. And communication loads and resource allocation are key issues in grid environment because the resources are geographically distributed and interacted with themselves. Therefore, we propose a dynamic load balancing algorithm and apply it to the grid-based biological data mining method. For performance evaluation, we measure average processing time, average communication time, and average resource utilization. Experimental results show that this method provides many advantages in aspects of processing time and cost.