• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.185-194
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• 2016

The effect of artificial changes in geographical features on local wind was analyzed at the construction site of bridge and fill-up bank in the southern part of Haui-do. Geographic Information System (GIS) data and Computational Fluid Dynamics (CFD) model were used in this study. Three-dimensional numerical topography based on the GIS data for the target area was constructed for the surface boundary input data of the CFD model. The wind observations at an Automatic Weather Station (AWS) located in Haui-do were used to set-up the model inflows. The seasonal simulations were conducted. The differences in surface wind speed between after and before artificial changes in geographical features were analyzed. The surface wind speed decreases 5 to 20% at the south-western part and below 2% of the spatial average for salt field. There was also marked the effect of artificial changes in geographical features on local wind in the westerly wind case for the target area.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.3
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• pp.67-73
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• 2016

The present study evaluated the blocking effect of natural and artificial topography on sunshine duration in the southern coastal area of Haui-do. The geospatial data for the target area was constructed by geographic information system(GIS) data. Three-dimensional modeling based on solar azimuth and altitude angles was conducted for the assessment of sunshine environment. The sunshine area was evaluated over 80~90% of the target area in the daytime, especially in summer. The blocking effect of mountainous terrain on sunshine duration was presented at the northern residential area in the late afternoon. There was also the effect of artificial topography by construction of fill-up bank on sunshine environment at the southern residential area early in the morning and the south-western part of salt field in the late afternoon.

• Convergence Security Journal
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• v.23 no.5
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• pp.3-8
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• 2023

The Fourth Industrial Revolution is bringing about great changes in many industrial fields, and among them, active research is being conducted on convergence technology using artificial intelligence. Among them, the demand is increasing day by day in the field of object recognition using artificial intelligence and digital transformation using recognition results. In this paper, we proposed an optimal learning model construction method to accurately recognize letters, symbols, and lines in images and save the recognition results as files in a standardized format so that they can be used in simulations. In order to recognize letters, symbols, and lines in images, the characteristics of each recognition target were analyzed and the optimal recognition technique was selected. Next, a method to build an optimal learning model was proposed to improve the recognition rate for each recognition target. The recognition results were confirmed by setting different order and weights for character, symbol, and line recognition, and a plan for recognition post-processing was also prepared. The final recognition results were saved in a standardized format that can be used for various processing such as simulation. The excellent performance of building the optimal learning model proposed in this paper was confirmed through experiments.

• The Journal of Korean Association of Computer Education
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• v.18 no.2
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• pp.83-90
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• 2015

In an virtualization environment, several virtual machines use physical resources together. If a specific virtual machine uses to much of the computing resources, other machines may not be working properly. There are various method to solve this problem. Most representative study is to migrate a specified virtual machines to a different server, a target server. In this study, server load can be transferred to a target server by the remigrate of the load imposed on virtual machine. It is still problematic that virtual machine has to remigrate to a different server. This thesis has proposed the algorithm determining the remigration targets by applying dynamic thresholds to solve those problems. The migration algorithm applies dynamic thresholds according to the following criteria. Firstly, the usage of CPU, network and memory; secondly, decide the set of artificial machine and the target server based on the resources surpassed thresholds; thirdly, determine artificial machines based on the resource usage in the target server.

• Earthquakes and Structures
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• v.16 no.5
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• pp.563-573
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• 2019

When generating spectrum-compatible artificial ground motion in engineering practices, the effect of the variation in fitting parameters on the distribution of the peak ground displacement (PGD) has not yet drawn enough attention. In this study, a method for simulating ground motion matching for multiple targets is developed. In this method, a frequency-dependent amplitude envelope function with statistical parameters is introduced to simulate the nonstationarity of the frequency in earthquake ground motion. Then, several groups of time-history acceleration with different temporal and spectral nonstationarities were generated to analyze the effect of nonstationary parameter variations on the distribution of PGD. The following conclusions are drawn from the results: (1) In the simulation of spectrum-compatible artificial ground motion, if the acceleration time-history is generated with random initial phases, the corresponding PGD distribution is quite discrete and an uncertain number of PGD values lower than the limit value are observed. Nevertheless, the mean values of PGD always meet the requirement in every group. (2) If the nonstationary frequencies of the ground motion are taken into account when fitting the target spectrum, the corresponding PGD values will increase. A correlation analysis shows that the change in the mean and the dispersion values, from before the frequencies are controlled to after, correlates with the modal parameters of the predominant frequencies. (3) Extending the maximum period of the target spectrum will increase the corresponding PGD value and, simultaneously, decrease the PGD dispersion. Finally, in order to control the PGD effectively, the ground motion simulation method suggested in this study was revised to target a specified PGD. This novel method can generate ground motion that satisfies not only the required precision of the target spectrum, peak ground acceleration (PGA), and nonstationarity characteristics of the ground motion but also meets the required limit of the PGD, improving engineering practices.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.135-140
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• 2009

In this paper, we synthesized active sonar target signals based on highlights model, and then carried out target classification using the synthesized signals. If the target aspect angle is changed, the different signals are synthesized. To know the result, two different experiments are done. First, The classification results with respect to each aspect angle are shown. Second, the results in two group in aspect angle are acquired. Time domain feature extraction is done using matched filter and envelope detection. It shows the pattern of each highlights. Artificial neural networks and multi-class SVM are used for classifying target signals.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.47 no.2
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• pp.146-152
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• 2011

Underwater CCTV camera systems are increasingly replaced the traditional net approach of assessing the species, numbers and aggregation patterns of marine animals distributing around the artificial reefs installed in the inshore fishing grounds, in particular, in relation to the biological investigation of behavior and distribution patterns of target fishes. In relation to these needs, we developed a multi-directional underwater CCTV camera system to use in detecting and tracking marine animals in the artificial reef ground. The marine targets to be investigated were independently tracked by using a camera module toward the bottom and four camera modules installed in the interval of $90^{\circ}$ in horizontal plane and inclination of $45^{\circ}$ in vertical plane of the CCTV system without the overlap of video frames by each camera module. From the results of several field tests at sea, we believe that the developed multi-directional underwater CCTV camera system will contribute to a better understanding in evaluating the effect of artificial reefs installed in the inshore fishing grounds.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.1-5
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• 2023

With recent advancements in artificial intelligence (AI) technology, more products based on AI are being launched and used. However, using AI safely requires an awareness of the potential risks it can pose. These concerns must be evaluated by experts and users must be informed of the results. In response to this need, many countries have implemented certification programs for products based on AI. In this study, we analyze several trends and differences in AI product certification programs across several countries and emphasize the importance of such programs in ensuring the safety and trustworthiness of products that include AI. To this end, we examine four international AI product certification programs and suggest methods for improving and promoting these programs. The certification programs target AI products produced for specific purposes such as autonomous intelligence systems and facial recognition technology, or extend a conventional software quality certification based on the ISO/IEC 25000 standard. The results of our analysis show that companies aim to strategically differentiate their products in the market by ensuring the quality and trustworthiness of AI technologies. Additionally, we propose methods to improve and promote the certification programs based on the results. These findings provide new knowledge and insights that contribute to the development of AI-based product certification programs.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.04a
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• pp.145-150
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• 1999

In the nonlinear dynamic structural analysis, the given ground excitation as an input should be well defined. Because of the lack of recorded accelerograms in Korea, it is required to generate an artificial earthquake by a stochastic model of ground excitation with various dynamic properties rather than recorded accelerograms. It is well known that earthquake motions are generally non-stationary with time-varying intensity and frequency content. Many researchers have proposed non-stationary random process models. Yeh and Wen (1990) proposed a non-stationary stochastic process model which can be modeled as components with an intensity function, a frequency modulation function and a power spectral density function to describe such non-stationary characteristics. This paper shows the process to generate nonstationary artificial earthquake ground motions considering target design response spectrum chosen by ATC14.

• Journal of Welding and Joining
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• v.32 no.2
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• pp.43-47
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• 2014

Famous artificial neural network (ANN) is applied to predict proper process window of arc welding. Target weldment is variously combined lap joint fillet welding of automotive steel plates. ANN's system variable such as number of hidden layers, perceptrons and transfer function are carefully selected through case by case test. Input variables are welding condition and steel plate combination, for example, welding machine type, shield gas composition, current, speed and strength, thickness of base material. The number of each input variable referred in welding experiment is counted and provided to make it possible to presume the qualitative precision and limit of prediction. One of experimental process windows is excluded for predictability estimation and the rest are applied for neural network training. As expected from basic ANN theory, experimental condition composed of frequently referred input variables showed relatively more precise prediction while rarely referred set showed poorer result. As conclusion, application of ANN to arc welding process window derivation showed comparatively practical feasibility while it still needs more training for higher precision.