무호흡산소투여가 가스교환에 미치는 영향

조명원,이청,오용석 대한마취과학회 1989 Korean Journal of Anesthesiology Vol.22 No.3

Arterial and mixed venous blood gases were investigated during apnea in anesthetized paralyzed mongrel dogs. Dogs were ventilated with 100% oxygen after endotracheal intubation by intermittent positive pressure ventilation over 30 minutes before apnea. Femoral artery was cannulated for arterial blood gas analysis and Swan-Ganz catheter was inserted through femoral vein to draw mixed venous blood for gas analysis. In group 1 (n=6), the endotracheal tube was left open to room air during apnea and blood gas analysis were measured at 1 minute interval. In group 2 (n=6), the endotracheal tube was left connected to the respirator with 100% oxygen with 1 L/kg/min flow during apnea and blood gas analysis were checked at 5 minute interval. Blood sampling was continued until cardiac problem occured. In group1, PaO₂,fall rapidly below 100 mmHg in 5 minutes and PaCO₂, increased by the rate of 5.2 mmHg/min, In group 2, PaO₂, fall slowly in proportion to increase of PaCO₂, that rised in the rate of 4.1 mmHg/min, but xemia does not occured until 45 minutes. In conclusion, arterial oxygenation can be maintained for long duration with oxygen flow through endotracheal tube but arterial carbon dioxide tension increase continuously during apnea. Useful methods to avoid carbon dioxide accumulation should be sought and investigated for clinical use of apneic oxygenation.

엔후루란 마취심도 지표에 관한 연구

조명원,김종성,곽일룡 대한마취과학회 1994 Korean Journal of Anesthesiology Vol.27 No.7

It is essential for the safe conduction of anesthsia to monitor the depth of anesthesia during aperation. However no one method has been confirmed to be objective and accurate as yet. Hecently lower esophageal contractility (LEC) has emerged as a means of mesuring anesthetic depth. To evaluate the usefulness as an index of anesthetic depth, the author compared the cardio- vascular signs (blood pressure, heart rate), EMG, EEG, plasma epinephrine and norepinephrine concentrations and LEC, until now known to be relevent to the anesthetic depth, at varing conditions of of no anesthesia, under anesthesia and after stimulation. The subjects were 30 ASA class 1 surgical patients, aged from 20 to 49, who had no specific past midical history and no recent medications. Patients were given thiopental sodium 4 mg/kg and vecuronium 0.1 mg/kg for induction and intubation and respiration controlled with 100% oxygen, then baseline measurements were taken (control) and compard the values of under enflurane anesthesia with 1 minimum alveolar concentration (MAC), 1.7%, (anesthesia) and after surgical stimulation (stimulation) with each other. The results were as follows ; 1) EEG, response rate and frequency of spontaneous LEC, amplitude of provoked LEC, LEC index of under enflurane anesthesia and after stimulation revealed significant differences compared with control but no significant differences between under anesthesia and after stimulation values. 2) Systolic, diastolic, mean blood pressure revelaled significant differences among control, under anesthesia and after stimulation values. 3) Heart rate, EMG, plasma epinephrine and norepinephrine concentrations, amplitude of spontaneous LEC revealed no significant differences among control, under anesthesia and after stimulation values. According to the above results, compared to the control value, EEG, and LEC reflected anesthetic depth under 1 MAC enflurane anesthesia but were meaningless in the evaluation of surgical stimulation. Blood pressure change which revealed significant differences among three values could be judged to be useful as an index of anesthetic depth most commonly applicable in practice.

Correlation Functions of Dense Gases and Liquids

조명원 한국물리학회 2017 새물리 Vol.67 No.7

One of the most useful approaches to the theory of dense gases and liquids is the study of correlation (or distribution) functions. We here apply a theoretical method for calculating all the correlation functions in an inhomogeneous system. We reproduce the virial expansion in an inhomogeneous system by using the solution of the one-point correlation function or the density function. Then, we derive the pair correlation function by using the two-point correlation function. We also reveal the solution of the direct correlation function in the Ornstein-Zernike equation. We find that the direct correlation function expanded in a power series in the density relates to the virial expansion.

Two Symmetry-breaking Mechanisms for the Development of Orientation Selectivity in a Neural System

조명원,전민영 한국물리학회 2015 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.67 No.9

Orientation selectivity is a remarkable feature of the neurons located in the primary visual cortex. Provided that the visual neurons acquire orientation selectivity through activity-dependent Hebbian learning, the development process could be understood as a kind of symmetry-breaking phenomenon in the view of physics. This paper examines the key mechanisms of the orientation selectivity development process. Be found that at least two different mechanisms, which lead to the development of orientation selectivity by breaking the radial symmetry in receptive fields. The first is a simultaneous symmetry-breaking mechanism occurring based on the competition between neighboring neurons, and the second is a spontaneous one occurring based on the nonlinearity in interactions. Only the second mechanism leads to the formation of a columnar pattern whose characteristics is in accord with those observed in an animal experiment.

Testing에 있어서 Integrative 接近 硏究

趙明源 한국영어영문학회 1977 영어 영문학 Vol.64 No.-

영어과 중등교사 연수제도 연구

조명원 한국영어교육학회 1989 ENGLISH TEACHING(영어교육) Vol.- No.38

발화신경망 모델에서 내용주소 기억장치에 대한 연구

조명원 한국물리학회 2020 새물리 Vol.70 No.6

The implementation of neural network content-addressable memory (CAM) relates to the attractor dynamics in the firing process. If some firing patterns are carved as fixed-point attractors, one of them can be recalled, depending on initial firing states. Many studies following the landmark achievement by Hopfield, have suggested an algorithm based on an analogy between the asymptotic dynamics of neural networks and the equilibrium properties of magnetic systems. However, the firing process of biological neurons, which progresses depending on minute spiking timings, has distinctive properties of attractor dynamics with those of the classical neuron models. We here study the characteristics of fixed-point attractors in a spiking neural network model preserving the attribute of spiking-timing-dependent interactions between neurons. We show that the attractor dynamics in the model relate to the phase-locking dynamics in a biological neural network when the memorized firing states are orthogonal to one another. We also introduce how non-orthogonal firing states can be memorized in the model and how one of them can be recalled, depending on the initial states, by applying the Hopfield network. 신경망에서 구현되는 내용주소 기억장치는 발화과정의 끌개 운동과 관련이 있다. 발화 패턴들이 신경망의 고정점 끌개로 새겨질 수 있다면 초기 발화상태에 따라 그 중 하나를 기억해 내는 것이 가능하게 된다. 특히 신경망의 발화과정과 자성체의 평형상태 근처에서의 진행속성이 가지는 유사성을 기반으로 홉필드가제안한 획기적인 알고리즘 이후에 신경망에서의 내용주소 기억장치에 대한 많은 연구가 있어왔다. 하지만세밀한 발화시간들에 의해 발화여부가 결정되는 실제 생물학적 신경세포들의 발화과정은 고전적 신경세포들과는 다른 속성의 끌개 운동을 가진다. 여기서 우리는 신경세포들이 발화시간에 의존하여 상호작용하는속성을 유지하고 있는 발화신경망 모델에서 고정점 끌개들의 속성들을 연구하였다. 이 모델에서 고정점끌개로 기억하고자 하는 발화상태들이 서로 직교적인 경우 끌개운동은 생물학적 신경망에서 발견되는위상 잠김 현상과 관련이 있다는 것을 밝힌다. 그리고 홉필드망을 응용하여 이 모델에서 서로 비직교적인발화상태들을 고정점 끌개로 저장한 후 초기 발화상태에 따라 그 중에 하나를 회상해 낼 수 있는 방법을소개한다.

Balzac의 색채 이미지와 페미니즘

조명원 한국프랑스학회 2003 한국프랑스학논집 Vol.42 No.-

Competitive Learning Behavior in a Stochastic Neural Network

조명원 한국물리학회 2015 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.67 No.9

Stochastic behavior is a natural and inevitable property of biological neurons. The effect of stochastic behavior or thermal fluctuation in neural firings on the learning process in a neural system is investigated. A learning model, which is derived from the stochastic differential equation of the firing-rate model, is presented as an estimate of the gradient flow of free energy. The model reveals that the learning process becomes competitive owing to the effect of entropy even through the synapse modifications only follow the simple Hebbian rule.

Simulations in a Spiking Neural Network Model Based on the Free Energy Principle

조명원 한국물리학회 2019 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.75 No.3

The Feynman machine is a neural network model in which the spike-timing-dependent firing process is described through a path integral formulation. In addition, the gradient descent in the free energy is proposed as an ideal learning rule of the model system. The unique formulation of the Feynman machine is useful for studying the substance of the firing and the learning process in a spiking neural network; however, the implementation of the Feynman machine is not a plan problem because of the difficulty in calculating the free energy. We here introduce how to perform the simulation of both the firing and the learning processes in the Feynman machine through the Monte Carlo or the numerical integral method. We demonstrate the adequacy of the methods by applying them to the firing and the learning processes in some neural systems.