• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.46 no.5
• /
• pp.359-367
• /
• 2018

The vortex ring state that occurs during the descending flight of a rotorcraft generates a circulating flow like a donut near the rotating surface, and it often causes a rotorcraft fall due to loss of thrust. In this paper, we have physically identified the flow field in the vortex ring state of the quadcopter, one of the types of unmanned aerial vehicles. The descending flight of the quadcopter was simulated in a 1m subsonic wind tunnel of the Korea Aerospace Research Institute(KARI) and the Particle Image Velocimetry(PIV) was used for the flow field measurement. The induced velocity in the hovering state is estimated by using the momentum theory and the test was carried out in the range of descent rate at which the vortex ring condition could be caused. The development and the direction of the vortex ring were confirmed by the measurement of the flow field according to not only the descent rate but also propeller separation distance. In addition, the results of the study show the vortex ring state can be predicted sufficiently by measuring the flow velocity around the quadcopter.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.19 no.5
• /
• pp.12-19
• /
• 1982

In general the design methods of adaptive filter are divided into two categories, one is based upon the local parameter optimization theory and the other is based upon stability theory. Among the various design techniques, the LMS algorithm by steepest-descent method which is based upon local parameter optimization theory is used widely. In designing the adaptive filter, the most important factor is the convergence rate of the algorithm. In this paper a new algorithm is proposed to improve the convergence rate of adaptive firter compared with the commonly used LMS algorithm. The faster convergence rate is obtained by adjusting the adaptation gain of LMS algorithm. And various aspects of improvement of the adaptive filter characteristics are discussed in detail.

• Clinical and Experimental Pediatrics
• /
• v.63 no.11
• /
• pp.415-421
• /
• 2020

Cryptorchidism or undescended testis is the single most common genitourinary disease in male neonates. In most cases, the testes will descend spontaneously by 3 months of age. If the testes do not descend by 6 months of age, the probability of spontaneous descent thereafter is low. About 1%-2% of boys older than 6 months have undescended testes after their early postnatal descent. In some cases, a testis vanishes in the abdomen or reascends after birth which was present in the scrotum at birth. An inguinal undescended testis is sometimes mistaken for an inguinal hernia. A surgical specialist referral is recommended if descent does not occur by 6 months, undescended testis is newly diagnosed after 6 months of age, or testicular torsion is suspected. International guidelines do not recommend ultrasonography or other diagnostic imaging because they cannot add diagnostic accuracy or change treatment. Routine hormonal therapy is not recommended for undescended testis due to a lack of evidence. Orchiopexy is recommended between 6 and 18 months at the latest to protect the fertility potential and decrease the risk of malignant changes. Patients with unilateral undescended testis have an infertility rate of up to 10%. This rate is even higher in patients with bilateral undescended testes, with intra-abdominal undescended testis, or who underwent delayed orchiopexy. Patients with undescended testis have a threefold increased risk of testicular cancer later in life compared to the general population. Self-examination after puberty is recommended to facilitate early cancer detection. A timely referral to a surgical specialist and timely surgical correction are the most important factors for decreasing infertility and testicular cancer rates.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.9
• /
• pp.781-788
• /
• 2005

This paper proposes an identification method using a self recurrent wavelet neural network (SRWNN) for dynamic systems. The architecture of the proposed SRWNN is a modified model of the wavelet neural network (WNN). But, unlike the WNN, since a mother wavelet layer of the SRWNN is composed of self-feedback neurons, the SRWNN has the ability to store the past information of the wavelet. Thus, in the proposed identification architecture, the SRWNN is used for identifying nonlinear dynamic systems. The gradient descent method with adaptive teaming rates (ALRs) is applied to 1.am the parameters of the SRWNN identifier (SRWNNI). The ALRs are derived from the discrete Lyapunov stability theorem, which are used to guarantee the convergence of an SRWNNI. Finally, through computer simulations, we demonstrate the effectiveness of the proposed SRWNNI.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.11 no.6
• /
• pp.5-13
• /
• 2008

A smart submunition drops through the expected trajectory to have a appropriate target searching footprint for the armored ground vehicles. Parachutes can be used as a tool to decelerate and spin the submunition. Usually submunition's descent velocity, spin rate, submunition inclination angle against vertical and dynamic stability affect to its target searching footprint. Therefore it is important to design optimal parachute and load configuration for the overall system performance. In this paper we described the dynamic motion of submunition by the mathematical model of parachute and load. Through the computer simulation we can analyze the submunition footprint affected by parachute and load design.

• International Journal of Control, Automation, and Systems
• /
• v.3 no.1
• /
• pp.43-55
• /
• 2005

In this paper, a predictive control method using self-recurrent wavelet neural network (SRWNN) is proposed for chaotic systems. Since the SRWNN has a self-recurrent mother wavelet layer, it can well attract the complex nonlinear system though the SRWNN has less mother wavelet nodes than the wavelet neural network (WNN). Thus, the SRWNN is used as a model predictor for predicting the dynamic property of chaotic systems. The gradient descent method with the adaptive learning rates is applied to train the parameters of the SRWNN based predictor and controller. The adaptive learning rates are derived from the discrete Lyapunov stability theorem, which are used to guarantee the convergence of the predictive controller. Finally, the chaotic systems are provided to demonstrate the effectiveness of the proposed control strategy.

• Structural Engineering and Mechanics
• /
• v.45 no.1
• /
• pp.53-67
• /
• 2013

This study aimed to develop a model to accurately predict the acceleration of structural systems during an earthquake. The acceleration and applied force of a structure were measured at current time step and the velocity and displacement were estimated through linear integration. These data were used as input to predict the structural acceleration at next time step. The computation tool used was the Volterra/Wiener neural network (VWNN) which contained the mathematical model to predict the acceleration. For alleviating problems of relatively large-dimensional and nonlinear systems, the VWNN model was utilized as the signal processing tool, including the Taylor series components in the input nodes of the neural network. The number of the intermediate layer nodes in the neural network model, containing the training and simulation stage, was evaluated and optimized. Discussions on the influences of the gradient descent with adaptive learning rate algorithm and the Levenberg-Marquardt algorithm, both for determining the network weights, on prediction errors were provided. During the simulation stage, different earthquake excitations were tested with the optimized settings acquired from the training stage to find out which of the algorithms would result in the smallest error, to determine a proper simulation model.

• Proceedings of the KIPE Conference
• /
• 1998.10a
• /
• pp.293-297
• /
• 1998

This paper presents a newly developed speed sensorless drive using RLS based on Neural Network Training Algorithm. The proposed algorithm has just the time-varying learning rate, while the wellknown back-propagation algorithm based on gradient descent has a constant learning rate. The number of iterations required by the new algorithm to converge is less than that of the back-propagation algorithm. The theoretical analysis and experimental results to verify the effectiveness of the proposed control strategy are described.

• Proceedings of the IEEK Conference
• /
• 2003.07d
• /
• pp.1239-1242
• /
• 2003

The neural networks are a famous model to learn the nonlinear function or nonlinear system. The main point of neural network is that the difference actual output from desired output is used to update weights. Usually, the gradient descent method is used for the learning process. On training process, if learning rate is too large, neural networks hardly guarantee convergence of neural networks. On the other hand, if learning rate is too small, the training spends much time. Therefore, one major problem in use of neural networks are to decrease the teaming time while neural networks are guaranteed convergence. In this paper, we suggest the model of fuzzy logic to neural networks to calibrate learning rate. This method is to tune learning rate dynamically according to error and demonstrates the optimization of training.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.24
• /
• pp.10565-10571
• /
• 2015

Gastric cancer incidence rates vary dramatically by world region with East Asia having the highest rate. The Asian population of the United States (US) is growing rapidly and over 17 million Americans are of Asian descent. A majority of Chinese, Korean and Vietnamese Americans are immigrants. Americans of East and Southeast Asian descent experience marked gastric cancer disparities and the incidence rate among Korean men in the US is over five times higher than the incidence rate among non-Hispanic white men. Randomized controlled trials have provided evidence for the effectiveness of helicobacter pylori identification and eradication in preventing gastric cancer. Additionally, Japan and South Korea have both experienced improvements in gastric cancer mortality following the implementation of programs to detect early stage gastric cancers. There are currently no clear US guidelines regarding the primary and secondary prevention of gastric cancer in high-risk immigrant populations. However, it is likely that a proportion of US physicians are already recommending gastric cancer screening for Asian patients and some Asian immigrants to the US may be completing screening for gastric cancer in their native countries. Surveys of US primary care physicians and Asian American communities should be conducted to assess current provider practices and patient uptake with respect to gastric cancer prevention and control. In the absence of clinical guidelines, US health care providers who serve high-risk Asian groups could consider a shared decision-making approach to helicobacter pylori identification and eradication, as well as gastric endoscopy.