• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.26-33
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• 2017

A drone performs a mission through remote control or automatic control, which uses wireless communications technology. Recently the increasing use of drones, the drone signal RF detection is necessary. In this paper, we propose an efficient dron RF detection method through simulations considering Wi-Fi, Bluetooth and dedicated protocol dron communication method in ISM(Industry Science Medical) band.. After configuring an environment where a common terminal and a drone signal are mixed, a general terminal and a drone signal are distinguished from each other by using a RF characteristic according to a dron movement. The proposed drone RF detection method is the WRMD(Windowed RSSI Moving Detection) operation and the Doppler frequency identification method. The simulation environments consist to mixed for two signals and four signals. We analysis the performance to proposed drone RF detection technique thorough detection rate.

• Proceedings of the KIPE Conference
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• 2011.11a
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• pp.279-280
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• 2011

In order to convert the mechanical movement of a linear generator to electrical power, the amateur current of the generator is controlled in accordance to the mover position. A linear encoder, usually used for direct detection of the mover position, not only is vulnerable to mechanical vibration, but also imposes significant constraint on the mechanical design of the generator system. Thus, this study proposes a method for indirect estimation of the mover position with emfs induced in amateur coils. The estimation algorithm is validated with simulation study.

• The Journal of Korean Physical Therapy
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• v.1 no.1
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• pp.47-61
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• 1989

This paper presents the event approach to motor skill acquisition as a theoretical treatment of the learning and relearning of motor skill. 1) The use of norm-referenced developmental assesment tools and standardized qualitative assessment tool is an important component of infant movement evaluation. 2) The kinesthetic modality relaying movement and position imformation to the central nervous system is important for the detection and corretion of movement error. 3) The event approach treats the actor and the environment as inseparable in the acquisition of skills. 4) Motoy learning focuses almost entirely on how the skill is learned, contRolled and reTained. 5) Developmental assessment have needed an assessment of motor development. 6) A significant difference was found between articulation disorders children and motor coordination problem. 7) verbal ability is not essential for the learning of motor skills. 8) The Control of motor skills is a cognitive ability.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.2
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• pp.228-233
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• 2000

In this paper, we introduce a differential detection method using approximate average noise detection, which improves the noise reduction efficiency in a wireless optical interconnection. Approximate average noise detection reduces the output voltage fluctuation that may result from the instantaneous change of the coupling coefficients with the movement of some objects or human beings. This method is very useful for noise reduction in an environment with optical noise whose spatial distribution varies instantaneously.

• Journal of IKEEE
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• v.24 no.4
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• pp.1148-1155
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• 2020

Fire must be extinguished as quickly as possible because they cause a lot of economic loss and take away precious human lives. Especially, the detection of smoke, which tends to be found first in fire, is of great importance. Smoke detection based on image has many difficulties in algorithm research due to the irregular shape of smoke. In this study, we introduce a new real-time smoke detection algorithm that reduces the detection of false positives generated by irregular smoke shape based on faster r-cnn of factory-installed surveillance cameras. First, we compute the global frame similarity and mean squared error (MSE) to detect the movement of smoke from the input surveillance camera. Second, we use deep learning algorithm (Faster r-cnn) to extract deferred candidate regions. Third, the extracted candidate areas for acting are finally determined using space and temporal features as smoke area. In this study, we proposed a new algorithm using the space and temporal features of global and local frames, which are well-proposed object information, to reduce false positives based on deep learning techniques. The experimental results confirmed that the proposed algorithm has excellent performance by reducing false positives of about 99.0% while maintaining smoke detection performance.

• Smart Structures and Systems
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• v.22 no.5
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• pp.561-574
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• 2018

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.

• Convergence Security Journal
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• v.18 no.5_1
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• pp.45-51
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• 2018

As data utilization and importance becomes important, data-related accidents and damages are gradually increasing. Especially, insider threats are the most harmful threats. And these insider threats are difficult to detect by traditional security systems, so rule-based abnormal behavior detection method has been widely used. However, it has a lack of adapting flexibly to changes in new attacks and new environments. Therefore, in this paper, we propose an adaptive anomaly movement detection framework based on a statistical Markov model to detect insider threats in advance. This is designed to minimize false positive rate and false negative rate by adopting environment factors that directly influence the behavior, and learning data based on statistical Markov model. In the experimentation, the framework shows good performance with a high F2-score of 0.92 and suspicious behavior detection, which seen as a normal behavior usually. It is also extendable to detect various types of suspicious activities by applying multiple modeling algorithms based on statistical learning and environment factors.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.49-64
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• 2008

Recently, many researches about making more comfortable input device based on gaze detection technology have been done in human computer interface. However, the system cost becomes high due to the complicated hardware and there is difficulty to use the gaze detection system due to the complicated user calibration procedure. In this paper, we propose a new gaze detection method based on the 2D analysis and a simple user calibration. Our method used a small USB (Universal Serial Bus) camera attached on a HMD (Head-Mounted Display), hot-mirror and IR (Infra-Red) light illuminator. Because the HMD is moved according to user's facial movement, we can implement the gaze detection system of which performance is not affected by facial movement. In addition, we apply our gaze detection system to 3D first person shooting game. From that, the gaze direction of game character is controlled by our gaze detection method and it can target the enemy character and shoot, which can increase the immersion and interest of game. Experimental results showed that the game and gaze detection system could be operated at real-time speed in one desktop computer and we could obtain the gaze detection accuracy of 0.88 degrees. In addition, we could know our gaze detection technology could replace the conventional mouse in the 3D first person shooting game.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.201-202
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• 1998

In this paper we suggested an automated method for detecting and counting rapid eye movement(REM) using EOG during sleep. This method is formulated by two step fuzzy logic. At first step, the velocity and the distance of single channel eye movement are used for the fuzzy input to get the possibility of being REM at each EOG. At second step, the two possibility values of both EOG from the first step and the correlation coefficient of both eye movements are used for the fuzzy logic input, and the output is the final possibility of being Rapid Eye Movement. We applied this algorithm to the normal and narcoleptic sleep data and compared the difference. We found the possibility that the count of REM can be a parameter that has significant physiological meanings.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.46 no.3
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• pp.232-238
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• 2010

The moving ranges and behavior of four wild abalones, Haliotis discus hannai, were measured by an acoustic telemetry technique. The shape of the sea bottom of the experimental area was surveyed by a bathymetry system and three self-recording type acoustic receivers were used for monitoring the behavior and measuring the movement range. The abalones (WA1-WA4) attached acoustic tags were released and measured the movement during ten months. Three abalones (WA1, WA3 and WA4) were successively detected around the released point during the experiment and were moved to the V2 area where water depth is deeper than the V1 area. The change of inhabitation depth was also detected from the depth sensor of WA4. As the result, abalones were moved to deeper water area accordance with the decrease of the water temperature. The moved ranges of abalones were approximately 200 - 400m from the release point.