• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1618-1623
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• 2019

In this paper, inductive couplers realizing broadband powerline communication (PLC) are fabricated using Fe-based nanocrystalline alloy and their performance is analyzed. As a result of the field tests using the distribution automation system (DAS), the couplers achieve comparatively excellent data communication in the principal frequency band of broadband PLC although there is a difference in communication rate depending on the presence or absence of a branch. In addition, it has been confirmed that the communication speed is maintained for a real-time transmission even in a high current environment although there is a difference in the transmission rate depending on the distance. Hence, it is considered that the inductive couplers can be used as a core device to realize the intelligent power network by exploiting them for the monitoring and remote controlling of the power plant equipments for the DAS located in the inaccessible areas.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12A
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• pp.982-990
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• 2009

The IEEE 802.15.4 wireless sensor network is composed of the unique sensor devices to monitor and collect physical or environmental conditions. The interests in a positioning technology, which is one of the environment monitoring technologies, are gradually increased according to the development of the sensor technology and IT infrastructure. Generally, it is difficult for the positioning system using RSSI (Received Signal Strength Indication) based implementation to get accurate position because of obstacles, RF wave's delay and multipath. Therefore, in this paper, we investigate the improved positioning technologies for RSSI-based positioning system. This paper also proposes the enhanced scheme to improve the accuracy of positioning system by applying the Gaussian Filter algorithm, which is widely used for enhancing the performance of image processing system. For the implementation of proposed scheme, we firstly make a look-up tables, which represent the distance between target node and master node and corresponding RSSI value of each target node which are recorded as an average value after investigating the characteristics of attenuation of transmitted signal By applying the pre-determined look-up tables and Gaussian Filtering in the proposed scheme, we analyzed the positioning performance and compared with other conventional RSSI-based positioning algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4B
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• pp.566-575
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• 2010

In recent, artificial immune system has become an important research direction in the anomaly detection of networks. The conventional artificial immune systems are usually based on the negative selection that is one of the computational models of self/nonself discrimination. A main problem with self and non-self discrimination is the determination of the frontier between self and non-self. It causes false positive and false negative which are wrong detections. Therefore, additional functions are needed in order to detect potential anomaly while identifying abnormal behavior from analogous symptoms. In this paper, we design novel network attack detection and response schemes based on artificial immune system, and evaluate the performance of the proposed schemes. We firstly generate detector set and design detection and response modules through adopting the interaction between dendritic cells and T-cells. With the sequence of buffer occupancy, a set of detectors is generated by negative selection. The detection module detects the network anomaly with a set of detectors and generates alarm signal to the response module. In order to reduce wrong detections, we also utilize the fuzzy number theory that infers the degree of threat. The degree of threat is calculated by monitoring the number of alarm signals and the intensity of alarm occurrence. The response module sends the control signal to attackers to limit the attack traffic.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.378-379
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• 2012

Nowadays, great energy consumption in advanced electrical industry has called up the great y efficiency. Electric power IT industry such as intelligent electric power system is receiving great attention and being marked up as a new growth engine. Through Intelligent electric power system, the electric power supply can be balance optimized according to demand, giving huge cost savings advantage for energy imports, infrastructure construction and operation. Nevertheless, the intelligent system promotes better reliability in power supply. Manual electric power management using man power appears to be non-practical. Real time electric power management on all facilities and equipment can be done through an intelligent electric power system, any accident break out issue can be easily recorded and recognized. In this paper, a fully integrated intelligent switchgear electric management system is developed to monitor and remote control the electrical switch based on smart phone. The proposed system is superior than the existing switchgear management system's weakness and can sharply improve effectiveness and stability with low cost. In future, the proposed system is expected to be greatly contributed to the advancement of the IT industry in electric power management.

• Ocean and Polar Research
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• v.35 no.1
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• pp.15-26
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• 2013

The toxic, Harmful Algal Blooms (HABs) caused by the Cochlodinium polykrikoides have a serious impact on the coastal waters of Korea. In this study, the acoustic detection system was developed for rapid HABs detection, based on the acoustic backscattering properties of the C. polykrikoides. The developed system was mainly composed of a pulser-receiver board, a signal processor board, a control board, a network board, a power board, ultrasonic sensors (3.5 and 5.0 MHz), an environmental sensor, GPS, and a land-based control unit. To evaluate the performance of the system, a trail was done at a laboratory, and two in situ trials were conducted: (1) when there was no red tide, and (2) when there was red tide. In the laboratory evaluation, the system performed well in accordance with the number of C. polykrikoides in the received level. Second, under the condition when there was no red tide in the field, there was a good correlation between the acoustic data and sampling data. Finally, under the condition when there was red tide in the field, the system successfully worked at various densities in accordance with the number of C. polykrikoides, and the results corresponded with the sampling data and monitoring result of NFRDI (National Fisheries Research & Development Institute). From the laboratory and field evaluations, the developed acoustic detection system for early detecting HABs has demonstrated that it could be a significant system to monitor the occurrence of HABs in coastal regions.

• Journal of the Society of Disaster Information
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• v.20 no.3
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• pp.484-499
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• 2024

Purpose: Recently, due to the aging of safety facilities in national industrial complexes, there has been an increase in the frequency and scale of safety accidents, highlighting the need for a shift toward a prevention-centered disaster management paradigm and the establishment of a digital safety network. In response, this study aims to provide an information system that supports more rapid and precise decision-making during disasters by utilizing digital twin-based integrated control technology to predict the spread of hazardous substances, trace the origin of accidents, and offer safe evacuation routes. Method: We considered various simulation results, such as surface diffusion, upper-level diffusion, and combined diffusion, based on the actual characteristics of hazardous substances and weather conditions, addressing the limitations of previous studies. Additionally, we designed an integrated management system to minimize the limitations of spatiotemporal monitoring by utilizing an IoT sensor-based backtracking model to predict leakage points of hazardous substances in spatiotemporal blind spots. Results: We selected two pilot companies in the Gumi Industrial Complex and installed IoT sensors. Then, we operated a living lab by establishing an integrated management system that provides services such as prediction of hazardous substance dispersion, traceback, AI-based leakage prediction, and evacuation information guidance, all based on digital twin technology within the industrial complex. Conclusion: Taking into account the limitations of previous research, we used digital twin-based AI analysis to predict hazardous chemical leaks, detect leakage accidents, and forecast three-dimensional compound dispersion and traceback diffusion.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1041-1051
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• 2012

Attack on Cloud Computing, an intensive service solution using network infrastructure recently released, generates service breakdown or intrusive incidents incapacitating developmental platforms, web-based software, or resource services. Therefore, it is needed to conduct research on security for the operational information of three kinds of services (3S': laaS, PaaS, SaaS) supported by the Cloud Computing system and also generated data from the illegal attack on service blocking. This paper aims to build a system providing optimal services as a 4-stage defensive method through the test on the attack and defense of Cloud Computing services. It is a defense policy that conducts 4-stage, orderly and phased access control as follows: controlling the initial access to the network, controlling virtualization services, classifying services for support, and selecting multiple routes. By dispersing the attacks and also monitoring and analyzing to control the access by stage, this study performs defense policy realization and analysis and tests defenses by the types of attack. The research findings will be provided as practical foundational data to realize Cloud Computing service-based defense policy.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.426-432
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• 2012

The positions of vessels in JTIDS where each vessel broadcasts its position, can be found using the relative navigation method. Besides positioning, the relative navigation could be adopted for identification friend or foe, tracking targets, monitoring battle field and etc. In this paper, we have explained the fundamental operation and technical structure for the relative navigation and implemented the simulation platform to evaluate the basic function and performance of the system in arbitrary environment. Using platform, the availability of relative navigation within the group network and the characteristic of the algorithm for position prediction was verified. Based on the simulation result, it was verified that EKF based navigation algorithm could produce great initial error and need quite convergence time. To improve the performance, we proposed a new navigation algorithm which uses the minimum norm estimation algorithm until the EKF converges. The simulation results reveal the relative navigation can be effectively used in the formation flight and collision avoidance system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6A
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• pp.389-398
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• 2012

In this study, structural strain responses of the jacket-type Uldolmok tidal current power plant structure under severe tidal environments were measured and analyzed using long-term measurement system during construction and also operation. It was observed that there were significant changes in strain responses at the steps of jacket lifting, block loading, pile ejection and insertion. Strains due to dead loads and tidal loads were analyzed before and after removal of a jacket leg, and it was also found that the strains due to dead load were much significantly changed after jacket leg removal. From the measurement data during operation, it was found that strain responses were fluctuated with M2 and M4 tidal periods and also relatively short period of about 10 min due to the peculiar tidal characteristics in the Uldolmok strait. Finally, the neural network-based non-parametric estimation models were investigated to build up the signal-based structural damage monitoring system.

• Journal of Korean Society on Water Environment
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• v.32 no.6
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• pp.511-519
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• 2016

National Institute of Environmental Research (NIER) has developed the Korean Reach File (KRF) for scientific and systematic analysis of variables related to water quality, pollutant sources and aquatic ecosystems in consideration of steam reach networks. The KRF provides a new framework for data production, storage, management and analysis for water related variables in relation to spatial characteristics, connections, and topologies of stream reaches. However, the current version of KRF (ver.2) has limited applicability because its nodes include not only the stream points based on topological characteristics but also those based on water quality monitoring stations, which may undermine its generality. In this study, a new version of KRF (ver.3) was designed and established to overcome the weak point of version 2. The version 3 is a generalization of the old KRF graphic data and it integrates the attribute data while separating it from the graphic data to minimize additional work that is needed for data association and search. We tested the KRF (ver.3) on actual cases and convenience and adaptability for each application was verified. Further research should focus on developing a database link model and real-world applications that are targeted to process event data.