• Journal of the Korean Society for Precision Engineering
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• v.15 no.7
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• pp.149-159
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• 1998

The importance of soundness and safety evaluation in weld zone using by the ultrasonic wave has been recently increased rapidly because of the collapses of huge structures and safety accidents. Especially, the ultrasonic method that has been often used for a major non-destructive testing(NDT) technique in many engineering fields plays an important role as a volume test method. Hence, the defecting any defects of weld Bone in austenitic stainless steel type 304 using by ultrasonic wave and neural network is explored in this paper. In order to detect defects, a distance amplitude curve on standard scan sensitivity and preliminary scan sensitivity represented of the relation between ultrasonic probe, instrument, and materials was drawn based on a quantitative standard. Also, a total of 93％ of defect types by testing 30 defect patterns after organizing neural network system, which is learned with an accuracy of 99％, based on ultrasonic evaluation is distinguished in order to classify defects such as holes or notches in experimental results. Thus, the proposed ultrasonic wave and neural network is useful for defect detection and Ultrasonic Non-Destructive Evaluation(UNDE) of weld zone in austenitic stainless steel 304.

• Journal of Biomedical Engineering Research
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• v.22 no.2
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• pp.145-150
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• 2001

대뇌 피질에 삽입하여 깊이에 따라 신경 신호를 기록하기 위한 탐침형 반도체 미세전극 어레이(depth-type silicon microelectrode array, 일명 SNU probe)를 제작하였다. 붕소를 확산시켜 생성된 고농도 p-type doping된 p＋ 영역을 습식식각 정지점으로 사용하는 기존의 방법과 달리 실리콘 웨이퍼의 앞면을 건식식각하여 원하는 탐침 두께만큼의 깊이로 트렌치(trench)를 형성한 후 뒷면을 습식식각하는 방법으로 탐침 형태의 미세 구조를 만들었다. 제작된 반도체 미세전극 어레이의 탐침 두께는 30 $\mu\textrm{m}$이며 실리콘 건식식각을 위한 마스크로 6 $\mu\textrm{m}$ 두께의 LTO(low temperature oxide)를 사용하였다. 탐침의 두께는 개발된 본 공정을 이용해서 5~90 $\mu\textrm{m}$ 범위까지 쉽게 조절할 수 있었다. 탐침의 두께를 보다 쉽게 조절할 수 있게 됨에 따라 여러 신경조직에 필요한 다양한 구조의 반도체 미세전극 어레이를 개발할 수 있게 되었다. 본 공정을 이용해서 개발된 4채널 SUN probe를 사용하여 흰쥐의 제1차 체감각 피질에서 4채널 신경 신호를 동시에 기록하였으며, 전기적 특성검사에서 기존의 탐침형 반도체 미세전극, 텅스텐 전극과 대등하거나 우수한 신호대 잡음비(signal to noise ratio, SNR)특성을 가짐을 확인하였다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.2 s.233
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• pp.303-310
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• 2005

The systems with probe and SIL(Solid Immersion Lens) mechanisms have been researched as the technology to perform NFR(Near Field Recording). Most of them use the flying head mechanism to accomplish high recording density and fast data transfer rate. In this paper, ABS shape of flying head was optimized with the object of securing the maximum compliance ability of OFH. We suggest low different optimization processes to predict the static flying characteristics for the OFH. Two different approximation methods, regression analysis and back propagation neural network were used. And we compared the result of directly connected(between CAE and optimizer) method and two approximated optimization results. Design Optimization Tool(DOT) and ${\mu}GA$ were used as the optimizers.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.175-176
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• 2007

Radial Basis Function Network (RBFN)을 이용하여 플라즈마 전위의 예측 모델을 개발하였다. RBFN의 예측성능은 Genetic Algorithm (GA)를 이용하여 최적화 하였다. 체계적인 모델링을 위해 통계적인 실험계획법이 적용되었으며, 실험은 반구형 유도 결합형 플라즈마 장비를 이용하여 수행이 되었다. $Cl_2$ 플라즈마에서의 데이터 측정에는 Langmuir probe가 이용되었다. 최적화된 GA-RBFN 모델을 일반 RBFN 모델과 비교하였으며, 15%정도 모델의 예측성능을 향상시켰다.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.391-398
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• 2017

In this paper, we compared the performance of "Network Intrusion Detection System based on attack feature selection using fuzzy control language"[1] and "Intelligent Intrusion Detection System Model for attack classification using RNN"[2]. In this paper, we compare the intrusion detection performance of two techniques using KDD CUP 99 dataset. The KDD 99 dataset contains data sets for training and test data sets that can detect existing intrusions through training. There are also data that can test whether training data and the types of intrusions that are not present in the test data can be detected. We compared two papers showing good intrusion detection performance in training and test data. In the comparative paper, there is a lack of performance to detect intrusions that exist but have no existing intrusion detection capability. Among the attack types, DoS, Probe, and R2L have high detection rate using fuzzy and U2L has a high detection rate using RNN.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.2
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• pp.41-53
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• 2000

In this paper, the Maekjin and the Yangdorak Diagnosis algorithm by using a neuro-fuzzy method is proposed and it is implemented on the DSP-based system. Maekjin is measured by 3-channels of the Maekjin board through Maekjin probe which is attached on Chon, Kwan and Chuk of patient's wrist. First, we experiment Chon, Kwan and Chuk, 3-parts simultaneously and second perform one part of Chon, Kwan and Chuk respectively, The experimental results show that the Maekjin signal is measured precisely with any Maekjin probe. In Yangdorak diagnosis, the pulse generated by electric stimulator stimulates a portion of body and the response signal is measured through electrodes which is attached on representative points of 12 kyungmaks. The experimental methods are (1) 1 channel-measure, (2) 2 channels-measure, (3) 6 channels-measure and (4) 24 channels-measure. A fuzzy diagnosis is performed and neural networks is learned using fuzzy values as inputs, and we show that neuro-fuzzy diagnosis method is performed well.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.268-273
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• 2000

Plasma models are crucial to equipment design and process optimization. A radial basis function network(RBFN) in con-junction with statistical experimental design has been used to model a process plasma. A 2$^4$ full factorial experiment was employed to characterized a hemispherical inductively coupled plasma(HICP) in characterizing HICP, the factors that were varied in the design include source power, pressure, position of shuck holder, and Cl$_2$ flow rate. Using a Langmuir probe, plasma attributes were collected, which include typical electron density, electron temperature. and plasma potential as well as their spatial uniformity. Root mean-squared prediction errors of RBEN are 0.409(10(sup)12/㎤), 0.277(eV), and 0.699(V), for electron density, electron temperature, and Plasma potential, respectively. For spatial uniformity data, they are 2.623(10(sup)12/㎤), 5.704(eV) and 3.481(V), for electron density, electron temperature, and plasma potential, respectively. Comparisons with generalized regression neural network(GRNN) revealed an improved prediction accuracy of RBFN as well as a comparable performance between GRNN and statistical response surface model. Both RBEN and GRNN, however, experienced difficulties in generalizing training data with smaller standard deviation.

• Proceedings of the Korean Society of Applied Pharmacology
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• 1995.10a
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• pp.115-124
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• 1995

The purpose of the present study was to address whether the in vivo noradrenergic neural activities in the locus coeruleus are involved in the regulation of blood pressure. Two groups of the animals were prepared, 1) SHR and 2) age-matched normotensive control, WKY. At the age of 6 and 16 weeks, blood pressure and the releases of NE from the locus coeruleus in SHR and KWY were measured by in vivo microdialysis at three different conditions: 1) normal, 2) elevated state of blood pressure by systemic injected phenylephrine and 3) increased state of neural activity by perfused phenylephrine into the locus coeruleus. The basal release of NE of SHR were significantly higher than that of WKY, Phenylephrine treatment caused elevation of blood pressure in both SHR and WKY in dose-dependent manner. Following phenylephrine injection, the releases of NE from the locus coeruleus of SHR were significantly decreased, whereas the significant change of NE in WKY was observed in the highest dose of phenylephrine. Phenylephrine perfusion into the locus coeruleus through microdialysis probe caused pressor responses and the pressor response in SHR was greater compared with that in WKY. The results from the present study suggests that the noradrenergic nervous system in the locus coeruleus may contribute as one of the development and maintenance factors for hypertension in SHR.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1243-1244
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• 2015

Finding solutions for the disabled is a major challenge for our society. In the case of a disability due to a malfunction of the nervous system, the origin may be accidental, genetic, or induced by environmental factors. This type of loss can cause loss or movement disorders (paraplegia, hemiplegia, quadriplegia, epilepsy, Parkinson's disease, multiple sclerosis, etc.) or malfunction of certain sensory functions (blindness, deafness, chronic pain, etc.). Many alternatives, more technology, have been imported to create interfaces between the human body and an artificial prosthesis in order to restore some functions of the human body. A wireless system, battery neurons probe was developed for one hand reading neural signals in the brain, and on the other hand also able to excite the neuron in the brain using a surface acoustic wave one ports (SAW) delay line reflection.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.20-20
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• 2000

Back-propagation neural network (BPNN) is the most prevalently used paradigm in modeling semiconductor manufacturing processes, which as a neuron activation function typically employs a bipolar or unipolar sigmoid function in either hidden and output layers. In this study, applicability of another linear function as a neuron activation function is investigated. The linear function was operated in combination with other sigmoid functions. Comparison revealed that a particular combination, the bipolar sigmoid function in hidden layer and the linear function in output layer, is found to be the best combination that yields the highest prediction accuracy. For BPNN with this combination, predictive performance once again optimized by incrementally adjusting the gradients respective to each function. A total of 121 combinations of gradients were examined and out of them one optimal set was determined. Predictive performance of the corresponding model were compared to non-optimized, revealing that optimized models are more accurate over non-optimized counterparts by an improvement of more than 30%. This demonstrates that the proposed gradient-optimized teaming for BPNN with a linear function in output layer is an effective means to construct plasma models. The plasma modeled is a hemispherical inductively coupled plasma, which was characterized by a 24 full factorial design. To validate models, another eight experiments were conducted. process variables that were varied in the design include source polver, pressure, position of chuck holder and chroline flow rate. Plasma attributes measured using Langmuir probe are electron density, electron temperature, and plasma potential.