• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.12-21
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• 2012

IEEE 802.11 MAC protocol standard, DCF(CSMA/CA), is originally designed to ensure the fair channel access between mobile nodes sharing the local wireless channel. It has been, however, revealed that some misbehavior nodes transmit more data than other nodes through artificial means in hot spot area spreaded rapidly. The misbehavior nodes may modify the internal process of their MAC protocol or interrupt the MAC procedure of normal nodes to achieve more data transmission. This problem has been referred to as a selfish node problem and almost literatures has proposed methods of analyzing the MAC procedures of all mobile nodes to detect the selfish nodes. However, these kinds of protocol analysis methods is not effective at detecting all kinds of selfish nodes enough. This paper address this problem of detecting selfish node using Tsallis-Entropy which is a kind of statistical method. Tsallis-Entropy is a criteria which can show how much is the density or deviation of a probability distribution. The proposed algorithm which operates at a AP node of wireless LAN extracts the probability distribution of data interval time for each node, then compares the one with a threshold value to detect the selfish nodes. To evaluate the performance of proposed algorithm, simulation experiments are performed in various wireless LAN environments (congestion level, how selfish node behaviors, threshold level) using ns2. The simulation results show that the proposed algorithm achieves higher successful detection rate.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.121-131
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• 2014

Traffic speed is an important measure in transportation. It can be employed for various purposes, including traffic congestion detection, travel time estimation, and road design. Consequently, accurate speed prediction is essential in the development of intelligent transportation systems. In this paper, we present an analysis and speed prediction of a certain road section in Busan, South Korea. In previous works, only historical data of the target link are used for prediction. Here, we extract features from real traffic data by considering the neighboring links. After obtaining the candidate features, linear regression, model tree, and k-nearest neighbor (k-NN) are employed for both feature selection and speed prediction. The experiment results show that k-NN outperforms model tree and linear regression for the given dataset. Compared to the other predictors, k-NN significantly reduces the error measures that we use, including mean absolute percentage error (MAPE) and root mean square error (RMSE).

• Journal of Convergence for Information Technology
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• v.7 no.3
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• pp.27-36
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• 2017

In almost industries, such as the logistics industry, marine fisheries, agriculture, industry, and services, small unmanned aerial vehicles are used for aerial photographing or closing flight in areas where human access is difficult or CCTV is not installed. Also, based on the information of small unmanned aerial photographing, application research is actively carried out to efficiently perform surveillance, control, or management. In order to carry out tasks in a mission-based manner in which the set tasks are assigned and the tasks are automatically performed, the small unmanned aerial vehicles must not only fly steadily but also be able to charge the energy periodically, In addition, the unmanned aircraft need to land automatically and precisely at certain points after the end of the mission. In order to accomplish this, an automatic precision landing method that leads landing by continuously detecting and recognizing a marker located at a landing point from a video shot of a small UAV is required. In this paper, it is shown that accurate and stable automatic landing is possible even if simple template matching technique is applied without using various recognition methods that require high specification in using low cost general purpose small unmanned aerial vehicle. Through simulation and actual experiments, the results show that the proposed method will be made good use of industrial fields.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.119-125
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• 2023

Through the Ukraine-Russia war, the military importance of drones is being reassessed, and North Korea has completed actual verification through a drone provocation towards South Korea at 2022. Furthermore, North Korea is actively integrating artificial intelligence (AI) technology into drones, highlighting the increasing threat posed by drones. In response, the Republic of Korea military has established Drone Operations Command(DOC) and implemented various drone defense systems. However, there is a concern that the efforts to enhance capabilities are disproportionately focused on striking systems, making it challenging to effectively counter swarm drone attacks. Particularly, Air Force bases located adjacent to urban areas face significant limitations in the use of traditional air defense weapons due to concerns about civilian casualties. Therefore, this study proposes a new passive air defense method that aims at disrupting the object detection capabilities of AI models to enhance the survivability of friendly aircraft against the threat posed by AI based swarm drones. Using laser-based adversarial examples, the study seeks to degrade the recognition accuracy of object recognition AI installed on enemy drones. Experimental results using synthetic images and precision-reduced models confirmed that the proposed method decreased the recognition accuracy of object recognition AI, which was initially approximately 95%, to around 0-15% after the application of the proposed method, thereby validating the effectiveness of the proposed method.

• Korean Journal of Animal Reproduction
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• v.23 no.4
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• pp.303-311
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• 1999

Nuclear DNA was isolated from the sperm cells representing genetic characteristics and genomic polymorphisms of rainbow trout by polymerase chain reaction(PCR) amplification of DNA using arbitrary primers. Genomic DNA fingerprints were generated from rainbow trout sperm DNA by polymerase chain reaction amplification using 20 arbitrary decamers as primers. Out of these primers, 4 generated 17 highly reproducible RAPD markers, producing almost six polymorphic bands per primers. Four of 6 primers tested generated amplified fragments which were polymorphic between different individuals. Polymorphic DNA fragments were reproducibly amplified from independent DNA preparations made from individuals. Rainbow trout was distinctly observed 3 specific DNA markers (2. 3, 2.0 and 1.3kb) in bandsharing. Individual fragments generated using the same arbitrary primer, demonstrated that a single primer detected at least three independent genomic polymorphisms in rainbow trout sperm DNA. The RAPD polymorphism generated by this primer may be used as a genetic marker for individual identification The RAPD-PCR technique has been shown to reveal informative polymorphism in many species of fish. The present results demonstrate that RAPD markers are abundant, reproducible and provide a basis for future gene mapping and MAS in these important aquaculture species using RAPD polymorphic markers. It is concluded that RAPD polymorphisms are useful as genetic markers for fish breed differentiation.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.33-42
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• 2016

Pin is a framework that creates dynamic program analysis tools and can be used to perform program analysis on user space in Linux and Windows. It is hard to analyze the program such as Anti-reversing program or malware using anti-debugging by Pin. In this paper, we will suggest the implementation of scheme bypassing anti-debugging with Pin. Each pin code is written to bypass anti-debugging detecting Pin. And Pin creates a pin tool combined with Pin codes that bypass anti-debugging methods. The pin tool are tested with files created by anti-debugging protector. The technique in the paper is expected to be a reference of code bypassing anti-debugging and be applied to bypass newly discovered anti-debugging through code modification in the future.

• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.123-127
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• 2020

In order to obtain the overall fire line information of medium and large forest fires at night, the ground control system was developed to determine whether forest fires occurred through real-time video clips and to calculate the location of the forest fires determined using the location of drones, angle information of video cameras, and altitude information on the map to reduce the time required for regular video matches obtained after the completion of the mission. To verify the reliability of the developed function, the error distance of the aiming position information of the flight altitude star and the image camera was measured, and the location information within the reliable range was displayed on the map. As the function developed in this paper allows real-time identification of multiple locations of forest fires, it is expected that overall fire line information for the establishment of forest fire extinguishing measures will be obtained more quickly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1816-1825
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• 2022

In this paper, we propose a new approach for tracking each human in a surveillance camera network with various resolution cameras. When tracking human on multiple non-overlapping cameras, the traditional appearance features are easily affected by various camera viewing conditions. To overcome this limitation, the proposed system utilizes facial information along with appearance information. In general, human images captured by the surveillance camera are often low resolution, so it is necessary to be able to extract useful features even from low-resolution faces to facilitate tracking. In the proposed tracking scheme, texture-based face descriptor is exploited to extract features from detected face after face frontalization. In addition, when the size of the face captured by the surveillance camera is very small, a super-resolution technique that enlarges the face is also exploited. The experimental results on the public benchmark Dana36 dataset show promising performance of the proposed algorithm.

• Journal of Navigation and Port Research
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• v.41 no.4
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• pp.189-194
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• 2017

The Moving Search Radar System (MSRS) monitors sea areas by moving along the coast. Since the radar is initially aligned to the front of the vehicle, it is important to know the changes in the heading azimuth of the vehicle to quickly acquire the target azimuth from the radar after the MSRS has moved. The heading azimuth can be obtained using the gyro compass, the GPS compass or the electronic compass. The electronic compass is suitable for MSRS requiring fast maneuverability due to its small volume, short stabilization time and low price. However, using a geomagnetic sensor may result in an error due to the surrounding magnetic field. Errors can make early automatic tracking of the satellites difficult and can reduce the radar detection accuracy. Therefore, this paper proposes a method to automatically compensate for the error reflecting the correction value on the radar obtained by comparing the reference azimuth calculated by solving the geodesic inverse problem using two coordinates between the radar and the geostationary satellite with the actually-directed azimuth angle of the satellite antenna. The feasibility and convenience of the proposed method were verified by applying it to the MSRS in the field.

• Journal of Satellite, Information and Communications
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• v.1 no.2
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• pp.1-7
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• 2006

GOCi (Geostationary Ocean Color Imager) is one of the COMS payloads that KARI is currently developing and scheduled to be in operation from around 2008. Its primary objective is to monitor the Korean coastal water environmental condition. We report the current progress in development of the integrated optical model as one of the key analysis tools for the GOCI in-orbit performance verification. The model includes the Sun as the emitting light source. The curved Earth surface section of 2500 km x 2500 km includingthe Korean peninsular os defined as a Lambertian scattering surface consisted of land and sea surface. From its geostationary orbit, the GOCI optical system observes the reflected light from the surfaces with varying reflectance representing the changes in its environmental conditions. The optical ray tracing technique was used to demonstrate the GOCI in-orbit performances such as red tide detection. The computational concept, simulation results and its implications to the on-going development of GOCI are presented.