• Journal of Internet Computing and Services
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• v.19 no.5
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• pp.67-75
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• 2018

According to Symantec's Internet Security Threat Report(2018), Internet security threats such as Cryptojackings, Ransomwares, and Mobile malwares are rapidly increasing and diversifying. It means that detection of malwares requires not only the detection accuracy but also versatility. In the past, malware detection technology focused on qualitative performance due to the problems such as encryption and obfuscation. However, nowadays, considering the diversity of malware, versatility is required in detecting various malwares. Additionally the optimization is required in terms of computing power for detecting malware. In this paper, we present Stream Order(SO)-CNN and Incremental Coordinate(IC)-CNN, which are malware detection schemes using CNN(Convolutional Neural Network) that effectively detect intelligent and diversified malwares. The proposed methods visualize each malware binary file onto a fixed sized image. The visualized malware binaries are learned through GoogLeNet to form a deep learning model. Our model detects and classifies malwares. The proposed method reveals better performance than the conventional method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.141-150
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• 2012

This paper suggests a critical path search algorithm that can easily draw PERT/GANTT chart which manages and plans a project schedule. In order to evaluate a critical path that determines the project schedule, Critical Path Method (CPM) is generally utilized. However, CPM undergoes 5 stages to calculate the critical path for a network diagram that is previously designed according to correlative relationship and execution period of project execution activities. And it may not correctly evaluate $T_E$ (The Earliest Time), since it does not suggest the way how to determine the sequence of the nodes activities that calculate the $T_E$. Also, the sequence of the network diagram activities obtained from CPM cannot be visually represented, and hence Lucko suggested an algorithm which undergoes 9 stages. On the other hand, the suggested algorithm, first of all, decides the sequence in advance, by reallocating the nodes into levels after Breadth-First Search of the network diagram that is previously designed. Next, it randomly chooses nodes of each level and immediately determines the critical path only after calculation of $T_E$. Finally, it enables the representation of the execution sequence of the project activity to be seen precisely visual by means of a small movement of $T_E$ of the nodes that are not belonging to the critical path, on basis of the $T_E$ of the nodes which belong to the critical path. The suggested algorithm has been proved its applicability to 10 real project data. It is able to get the critical path from all the projects, and precisely and visually represented the execution sequence of the activities. Also, this has advantages of, firstly, reducing 5 stages of CPM into 1, simplifying Lucko's 9 stages into 2 stages that are used to clearly express the execution sequence of the activities, and directly converting the representation into PERT/GANTT chart.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1278-1285
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• 2018

For saving electricity bill, energy storage system(ESS) is being installed in factories, public building and commercial building with a Time-of-Use(TOU) tariff which consists of demand charge(KRW/kW) and energy charge(KRW/kWh). However, both of peak reduction and ESS special tariff are not considered in an analysis of initial cost payback period(ICPP) on ESS. Since it is difficult to reflect base rate by an amount of uncertain peak demand reduction during mid-peak and on-peak periods in the future days. Therefore, the ICPP on ESS can be increased. Based on this background, this paper presents the advanced analysis method for the ICPP on ESS. In the proposed algorithm, the representative days of monthly electricity consumption pattern for the amount of peak reduction can be found by the k­means clustering algorithm. Moreover, the total expected energy costs of representative days are minimized by optimal daily ESS operation considering both peak reduction and the special tariff through a mixed-integer linear programming(MILP). And then, the amount of peak reduction becomes a value that the sum of the expected energy costs for 12 months is maximum. The annual benefit cost is decided by the amount of annual peak reduction. Two simulation cases are considered in this study, which one only considers the special tariff and another considers both of the special tariff and amount of peak reduction. The ICPP in the proposed method is shortened by 18 months compared to the conventional method.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.87-96
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• 2016

Red tide, causes aquaculture industry the damages in Korea every summer, was usually detected by using satellite, aquaculture information was difficult to detect by using satellite. Therefore, we suggests the method for detecting the red tide using the coastal observation and the product from the unmanned aerial Vehicle. As a result, we obtained the high resolution unmanned aerial Vehicle images, detected the red tide by using the unsupervised classification from the true color images and the simple algorithm from the RGB color images. Compared the previous color images, unmanned aerial Vehicle images were clearly classified the ocean color, we were able to identify the red tide distribution in sea surface. These methods were determined to accurately monitor the red tide distribution on the aquaculture fields in the coastal waters where is established the aquaculture.

• Journal of the Korean Institute of Gas
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• v.24 no.3
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• pp.27-32
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• 2020

For preventing accident, the risk analysis about gas facilities has been more important since many gas facilities be superannuated. Especially, deriving and simulating risk is very important for preventing and corresponding accidents by means of specific analysis method in complex gas facilities. However, many studies have been not enough not yet in order to derive and simulate risk considering various situations. This paper aims to propose deriving and analyzing risk method around limited area of complex gas facilities. Our study proposes total risk analysis that is composed four methods with individual point of view. The risk analysis system based on RiskMAP immediately informs users changes of e risk in zones according to the status, work and surrounding conditions of the facility. The proposed methods in this research are implemented as software algorithm and applied to risk analysis system using RiskMAP in conjunction with IoT and GPS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.947-950
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• 2015

In the cause of car accidents in Korea, drowsy driving has shown that it is larger fctors than drunk driving. Therefore, in order to prevent drowsy driving accidents, drowsiness detection and warning system for drivers has recently become a very important issue. Furthermore, Many researches have been published that measuring alpha wave of EEG signals is the effective way in order to be aware of drowsiness of drivers. In this study, we have developed EEG measuring device that applies a signal processing algorithm using the LabView program for detecting drowsiness. According to results of drowsiness inducement experiments for small test subjects, it was able to detect the pattern of EEG, which means drowsy state based on the changing of power spectrum, counterpart of alpha wave. After all, Comparing to the results of drowsiness pattern between commercial equipments and developed device, we could confirm acquiring similar pattern to drowsiness pattern. With this results, the driver's drowsiness prevention system expect that it will be able to contribute to lowering the death rate caused by drowsy driving accidents.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.123-129
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• 2017

New mobile phones with high tech-camera and a large size memory have been recently launched and people upload pictures of beautiful scenes or unknown flowers in SNS. This paper develops a flower recognition system that can get information on flowers in the place where mobile communication is not even available. It consists of a registration part for reference flowers and a recognition part based on OpenCV for Android platform. A new color classification method using RGB color channel and K-means clustering is proposed to reduce the recognition processing time. And ORB for feature extraction and Brute-Force Hamming algorithm for matching are used. We use 12 kinds of flowers with four color groups, and 60 images are applied for reference DB design and 60 images for test. Simulation results show that the success rate is 83.3% and the average recognition time is 2.58 s on Huawei ALEUL00 and the proposed system is suitable for a mobile phone without a network.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.3 s.303
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• pp.33-40
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• 2005

In order to successfully exploit underwater resources, the first step would be a marine environmental research and exploration on the seafloor. Traditionally one sets up a long-term underwater experimental unit on the seafloor and retrieves the unit later after a certain period time. Essential to these applications is the reliable teleoperation and telemetering of the unit. This study presents ultrasonic-wave remote control system and an underwater sound recognition algorithm that can identify the sound signal without the influence of disturbances due to underwater environmental changes. The proposed method provides a means suitable for units which require low power dissipation and long-time underwater operation. We demonstrate its ability of securing stability and fast sound recognition through experimental methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.2 s.302
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• pp.151-160
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• 2005

In this paper, we propose a new fast motion estimation algorithm based on successive elimination algorithm (SEA) which can dramatically reduce heavy complexity of the variable block size motion estimation in H.264 encoder. The proposed method applies the conventional SEA in the hierarchical manner to the seven block modes. That is, the proposed algorithm can remove the unnecessary computation of SAD by means of the process that the previous minimum SAD is compared to a current SAD for each mode which is obtained by accumulating sum norms or SAD of $4\times4$ blocks. As a result, we have tighter bound in the inequality between SAD and sum norm than in the ordinary SEA. If the basic size of the block is smaller than $4\times4$, the bound will become tighter but it also causes to increase computational complexity, specifically addition operations for sum norm. Compared with fast full search algorithm of JM of H.264, our algorithm saves 60 to $70\%$ of computation on average for several image sequences.

• Journal of Advanced Navigation Technology
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• v.21 no.3
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• pp.272-278
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• 2017

In order to meet performance requirements specified by the ICAO in drone operation, a system that provides augmentation information such as SBAS is needed. However, the operating range of the drone is limited in situation where the drone can not received the SBAS message continuously. In this paper, we propose a system to transmit SBAS augmentation message using a separate communication channel assuming the SBAS satellite signal to the drone has been shielded. We implemented the proposed system and verified its performance in the static environment. The DGPS positioning results showed that the accuracy difference is about 10cm, which means the accuracy performance was very similar. In addition, the protection level calculated by the system also shows the difference within 2m from the value calculated by the airborne receiver.