• International Commerce and Information Review
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• v.18 no.3
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• pp.205-226
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• 2016

As knowledge workers have increased and information interchanges become more diverse, only the resources of internal enterprise is not longer useful, and the practical use of external information through information public sharing network is even more crucial. But, few studies that use both internal and external information sharing systems together have been conducted. In this research, we carried on the depth interview to analyze the main factors that intend to utilize outside information as well as to share inside information voluntarily. In conclusion, sharing internal information is directly involved with the performance of their job exchanging simple data, past documents, and technical materials. On the other hand, using the external information belonged to several other organizations is mostly caused by the voluntary participants' satisfaction sharing their individual experience through the network systems. Based on the study, we propose the idea that can activate both internal and external information sharing network through the system with user feedback function regarding the customized information, and with the space expansion where people can freely raise their private opinion. We also introduce the plan of the construction of communication systems with various experts, and the development of compatible devices with diverse interfaces.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.2
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• pp.172-182
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• 2013

This paper focuses on the modeling and intelligent control of the new Eight-Rotor MAV, which is used to solve the problem of the low coefficient proportion between lift and gravity for the Quadrotor MAV. The Eight-Rotor MAV is a nonlinear plant, so that it is difficult to obtain stable control, due to uncertainties. The purpose of this paper is to propose a robust, stable attitude control strategy for the Eight-Rotor MAV, to accommodate system uncertainties, variations, and external disturbances. First, an interval type-II fuzzy neural network is employed to approximate the nonlinearity function and uncertainty functions in the dynamic model of the Eight-Rotor MAV. Then, the parameters of the interval type-II fuzzy neural network and gain of sliding mode control can be tuned on-line by adaptive laws based on the Lyapunov synthesis approach, and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system. The validity of the proposed control method has been verified in the Eight-Rotor MAV through real-time experiments. The experimental results show that the performance of the interval type-II fuzzy neural network based adaptive sliding mode controller could guarantee the Eight-Rotor MAV control system good performances under uncertainties, variations, and external disturbances. This controller is significantly improved, compared with the conventional adaptive sliding mode controller, and the type-I fuzzy neural network based sliding mode controller.

• Journal of Sensor Science and Technology
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• v.28 no.1
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• pp.64-70
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• 2019

Wireless sensors have been developed in numerous ways for enhancing the convenience of installation, management and maintenance of sensors. Energy harvesting wireless sensors, which can collect energy from the external environment for permanent usage without the need of recharging and exchanging batteries, have been developed and employed used in Internet of Things and at various industrial sites. Energy harvesting wireless sensors are significantly affected by the sensor lifespan to sudden variation in the external environment. Furthermore, reduction in the sensor operating timespan can greatly affect the characteristics of the devices connected through a network. In this paper, a system performance index is proposed that can comprehensively evaluate the lifespan of a solar cell wireless sensor, determine the characteristics of devices connected to the associated network, and recommend dynamic power distribution control for improving the system performance index. Improvement in the system performance index was verified by applying the proposed dynamic power distribution control to an air conditioner network system using a solar cell wireless sensor. Obtained results corroborate that the dynamic power distribution control can extend the lifespan of the incorporated wireless sensor and reduce the air conditioner's power consumption.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.1
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• pp.181-195
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• 2015

Financial industries have operated internal and external network with an unified system for continual business process of customers and other organizations in the past. The financial supervising authority requires more technical and managerial protecting policy to financial industries related to the exposure as danger of external attacks or information leakage. Financial industries performed network separation into internal business and external internet networks for protecting IT assets from malware infection accessing internet or hacking attacks and prohibiting leakage of customers' personal and financial information following financial supervising authority and redefine security policy to fit on network separated-condition. In this study, effectiveness for network separation policy was examined on malware inflow and verified that malware inflow in all routes can be blocked by the policy with analyzing operration data of a financial company, estimating network separation. Result of this study proves that malware infection route by portable storages was not completely blocked even on adapting network-separated condition. As a solution for this, efficient security policy would be suggested in this paper as controlling portable storages for maximizing effectiveness of network separation.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.5
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• pp.400-407
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• 2005

Reverse engineering is defined as the process where the internal structures and dynamics of a given system are inferred and analyzed from external observations and relevant knowledge. The first part of this paper surveys existing techniques for biosystem reverse engineering. Network structure inference techniques such as Correlation Matrix Construction (CMC), Boolean network and Bayesian network-based methods are explained. After the numeric and logical simulation techniques are briefly described, several representative working software tools were introduced. The second part presents our component-based software architecture for biosystem reverse engineering. After three design principles are established, a loosely coupled federation architecture consisting of 11 autonomous components is proposed along with their respective functions.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2747-2749
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• 2005

This paper presents an intelligent control system for an ac servo motor dirve to track periodic commands using a neural network. AC servo motor drive system is rather similar to a linear system. However, the uncertainties, such as machanical parametric variation, external disturbance, uncertainty due to nonideal in transient state. therefore an intelligent control system that isan on-line trained neural network controller with adaptive learning rates.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.120.2-120
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• 2002

In this paper auto-tuning scheme of weight function in the neural networks has been suggested by immune algorithm for nonlinear process. A number of structures of the neural networks are considered as learning methods for control system. A general view is provided that they are the special cases of either the membership functions or the modification of network structure in the neural networks. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also. It can provi..

• Korean Journal of Optics and Photonics
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• v.15 no.6
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• pp.490-494
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• 2004

Bragg gratings were fabricated in Ge-doped silica planar lightwave circuits (PLC) for different writing conditions to study the growth characteristics. The refractive index modulation of the gratings grew in the PLC with total fluence F according to the power law $\Delta$n=A $F^{B}$. The characteristics of the PLC gratings formed for external cavity lasers match closely to those predicted by the power law. The oscillation spectra of the FP-LD with a Bragg grating grown in the PLC waveguide were also presented.d.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.407-410
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• 2012

Recently, wireless network services are widely used, depending on the development of wireless network module technologies and the utilization gradually expanded, and thus is a trend that appears a lot of IT convergence industries. For this study, the OBD-II communication to Import your vehicle information, and other external devices in high-speed driving condition of the vehicle to verify the information system was developed to transfer data to an external server. From various sensors inside the vehicle using the OBD-II connector easily convert all users to read the information, then, Sent to the external server using the wireless network module, high-speed vehicle status check system was implemented. It was to test the performance of the system was developed using the actual circuit in a high-speed road racing vehicles. Transfer data generated from high-speed driving vehicles through the OBD-II scanner and check the status of a high-speed vehicle system was confirmed that this data is normally received. In the future, these new cars convergence of IT technology will grow as a new field of research.

• Journal of Korea Trade
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• v.25 no.4
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• pp.17-36
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• 2021

Purpose - This study provides useful information to stakeholders by forecasting the tramp shipping market, which is a completely competitive market and has a huge fluctuation in freight rates due to low barriers to entry. Moreover, this study provides the most effective parameters for Baltic Dry Index (BDI) prediction and an optimal model by analyzing and comparing deep learning models such as the artificial neural network (ANN), recurrent neural network (RNN), and long short-term memory (LSTM). Design/methodology - This study uses various data models based on big data. The deep learning models considered are specialized for time series models. This study includes three perspectives to verify useful models in time series data by comparing prediction accuracy according to the selection of external variables and comparison between models. Findings - The BDI research reflecting the latest trends since 2015, using weekly data from 1995 to 2019 (25 years), is employed in this study. Additionally, we tried finding the best combination of BDI forecasts through the input of external factors such as supply, demand, raw materials, and economic aspects. Moreover, the combination of various unpredictable external variables and the fundamentals of supply and demand have sought to increase BDI prediction accuracy. Originality/value - Unlike previous studies, BDI forecasts reflect the latest stabilizing trends since 2015. Additionally, we look at the variation of the model's predictive accuracy according to the input of statistically validated variables. Moreover, we want to find the optimal model that minimizes the error value according to the parameter adjustment in the ANN model. Thus, this study helps future shipping stakeholders make decisions through BDI forecasts.