• Advances in Traditional Medicine
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• v.6 no.4
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• pp.253-263
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• 2006

The plant is used in India as well as several countries since several centuries for treating different types of ailments. The plant is an important constituent of the Ayurvedic Materia Medica and finds mention in several ancient texts including Caraka Sanhita ($6^{th}$ century A.D.) and the Bhavprakasa ($16^{th}$ century A.D.). The scientific studies on this plant have reported several activities of this plant. Though the plant has cardiotonic, vasoconstrictor, sedative, neuro-muscular blocking, and anticancer activities, it is more popular as memory enhancer. Traditionally, a poultice made of the boiled plant is placed on the chest in acute bronchitis and coughs of children. The plant contains saponins: bacosides A and B, hersaponin, sapogenins: bacogenin $A_{1}$, $A_{2}$, and $A_{3}$ stigmasterol, and flavonoids: luteolin and luteolin-7 glucoside, nicotine, brahmine, and herpestine. This review focuses on the scientific data published since 1931.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.12
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• pp.804-810
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• 2004

There are two important things for the general purpose neural network processor. The first is a capability to build various structures of neural network, and the second is to be able to support suitable learning method for that neural network. Some way to process various learning algorithms is required for on-chip learning, because the more neural network types are to be handled, the more learning methods need to be built into. In this paper, an improved hardware structure is proposed to compute various kinds of learning algorithms flexibly. The hardware structure is based on the existing modular neural network structure. It doesn't need to add a new circuit or a new program for the learning process. It is shown that rearrangements of the existing processing elements can produce several neural network learning modules. The performance and utilization of this module are analyzed by comparing with other neural network chips.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.1
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• pp.76-82
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• 2005

In this paper, validation of Driver Steering Model has been conducted. The comparison between the simulation model and vehicle test results shows that the model is very feasible for describing combined human driver and actual vehicle dynamic behaviors. The 3D vehicle model is consisted of 6-DOF sprung mass and 4-quarter car model for vehicle body dynamics. Powertrain model including differential gear and Pacejka tire model are applied. The driver steering model is also validated with vehicle test result. The driver steering model is based on angle and displacement error from the desired path, recognized by driver.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.1
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• pp.76-84
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• 2012

This paper presents the measurement system of arrow's point of impact using laser scan camera and describes the image calibration method. The calibration process of distorted image is primarily divided into explicit and implicit method. Explicit method focuses on direct optical property using physical camera and its parameter adjustment functionality, while implicit method relies on a calibration plate which assumed relations between image pixels and target positions. To find the relations of image and target position in implicit method, we proposed the performance criteria based polynomial theorem model that overcome some limitations of conventional image calibration model such as over-fitting problem. The proposed method can be verified with 2D position of arrow that were taken by SICK Ranger-D50 laser scan camera.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.1
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• pp.38-44
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• 2001

This paper investigates the direct adaptive control of nonlinear systems using RBFN(radial basis function networks). The structure of the controller consists of a fixed PD controller and a RBFN controller in parallel. An adaptation law for the parameters of RBFN is developed based on the Lyapunov stability theory to guarantee the stability of the overall control system. The filtered tracking error between the system output and the desired output is shown to be UUB(uniformly ultimately bounded). To evaluate the performance of the controller, the proposed method is applied to the trajectory contro of the two-link manipulator.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.227-230
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• 1993

Recently, the development of novel control methodology enables us to improve the performance of AC-machine drives by using pulse width modulation (PWM) technique. Usually, the dynamic characteristic of induction motor (IM) has been represented by the 5-th order nonlinear differential equation. This dynamics, however, can be reduced to 3-rd order dynamics by applying direct control of IM input current. This methodology concludes that it is much easier to control IM by means of the field-oriented methods employing the current controller. Therefore a precise current control is crucial to achieve a high control performance both in dynamic and steady state operations. This paper presents an adaptive fuzzy current controller with artificial neural network (ANN) for field-oriented controlled IM. This new control structure is able to adaptively minimize a current ripple while maintaining constant switching frequency. Especially the proposed controller employs neuro-computing philosophy as well as adaptive learning pattern recognizing principles with respect to variations of the system parameters. The proposed approach is applied to the IM drive system, and its performance is tested through various simulations. Simulation results show that the proposed system, compared among several known classical methods, has a superb performance.

• Journal of Korean Academy of Nursing
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• v.7 no.2
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• pp.11-21
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• 1977

Many in nursing look back on Nursing Research history and proudly point to the fact that emphasis in nursing research has changed from studying the nurse to studying nursing practice. In recent years, much emphasis has been placed on seeking a method of evaluating the quality of nursing care. In spite of these attempts, however, an instrument for evaluating the quality of nursing care that is actually applicable in the clinical area has not been found. The Purposes of this study are as follows: 1) To develop the instrument to be used in evaluating the quality of nursing care provided in the Neuro - Surgery Constant Care Unit of Severance Hospital 2) To evaluate the quality of nursing care in the clinical area. 3) To provide the necessary information for improvement of quality of nursing care. The instrument for evaluating the quality of nursing care, developed by the investigator, was composed of 7 nursing goals and divided into 65 standards of nursing performance. The 7 nursing goal are as follows : 1) Maintenance of airway 2) Maintenance of fluid at electrolyte balance 3) Maintenance of elimination 4) Personal hygiene 5) Optimum activity 6) Prevention of accidents 7) Emotional care The study population defined was composed of all the case (51) who were admitted in the Neuro- Surgery Constant Care Unit of Severance Hospital from May 7-13, 1976. The observation method was used and the data was subjected to the %, X²-test, T-test, F-test and Correlation. The results of tile study were as follows : 1. Levels of nursing performance regarding nursing goals. Seven different nursing care indices were constructed in terms of nursing goals. The index scores were grouped arbitrarily into ,j categories such as "excellent", "good", "moderate", "incomplete", and "poor"based upon the investigator′s personal judgement. a. The nursing index of maintaining airway showed that 78% of the patients fell within the "excellent" and 22% of the patients, fell within the "good" category. b. The nursing index of maintaining fluid & electrolyte balance showed that 95% of the patients fell within the "excellent" and 5 % of the patients fell within the "good" category. c. The nursing index of maintaining elimination showed that 100% of the patients fell within the "excellent" category. d. The nursing index of personal hygiene revealed that 49% of the patients fell within the "excellent" and 51% of the patients fell within the "good" category. e. The nursing index of optimum activity showed that 63% of the patients fell within the "excellent" and 32% of the patients fell within tile "good" and 5% of patients fell within the "moderate" category. f. The nursing index of prevention of accidents showed that 100% of the patients foil within the "excellent" category. g. The nursing index of emotional cart revealed that 27% of the patients fell within the "excellent", 24 % of the patients fell within tile "good", 29 % of the patients fell within the "incomplete" category. From these findings it is disclosed that the quality of nursing care provided in the Neuro- Surgery Constant Care Unit of Severance Hospital was excellent. h. There were statistically significant differences between the nursing index of physical care and emotional care. (t=8.73, D. F. =100. p<0.01) It is revealed that more physical care then emotional care was carried out by nurses. 2. Levels of nursing performance regarding general characteristics of the patients. No significant differences were observed statistically with the nursing indices of nursing goals according to the sex (t=0.084, D. F. =12, p>0.05). Age (F=0.1251, D. F. : 3.18. p 〉0.05), absence or presence of operating experiences (t=0.6032, D. F. =12, p〉0.05, levels of consciousness (F=0.31, D. F. :3. 18, p >0.05) 3. Relationship between the levels of consciousness and the nursing index of each nursing goal. There was negative correlation between the levels of consciousness and the nursing index of maintaining airway (r=-0. 5449, p<0.01) and personal hygiene (r= -0.4075, p<0.01) There was positive correlation between the levels of consciousness and the nursing index of optimum activity (r=0.3936, p <0.01) and emotional care (r=0.7819, p〈0.01). There was slight correlation between the levels of consciousness and the nursing index of maintaining fluid & electrolyte balance (r=-0.3418, 0.010.05) and preventing accidents (r=0.1441, p>0.05.

• Journal of Acupuncture Research
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• v.20 no.5
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• pp.172-186
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• 2003

Acupuncture therapy has demonstrated efficacy in several clinical areas, and of these areas the understanding of pain has progressed immensely in the last two decades. The underlying mechanisms of acupuncture in general and the analgesic effect in particular are still not clearly delineated. The leading hypothesis include the effects of local stimulation, neuronal gating, release of endogenous opiates, and the placebo effect. Accumulating evidence suggests that the central nervous system(CNS) is essential for the processing of these effects, via its modulation of the autonomic nervous system, neuro-immune system, and hormonal regulation. These processes tap into basic survival mechanisms. As such, understanding the effects of acupuncture within a neuroscience-based framework becomes vital. We propose a model which incorporates the stress-induced hypothalamus-pituitary-adrenal axis(HPA-axis) model of Akil et al., the cholinergic anti-inflamatory observations of Tracey et al., and Petrovic et al.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1587-1599
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• 2017

This paper proposes a real-time implementation of an optimal operation of a double stage grid connected wind power system incorporating an active power filter (APF). The system is used to supply the nonlinear loads with harmonics and reactive power compensation. On the generator side, a new adaptive neuro fuzzy inference system (ANFIS) based maximum power point tracking (MPPT) control is proposed to track the maximum wind power point regardless of wind speed fluctuations. Whereas on the grid side, a modified predictive current control (PCC) algorithm is used to control the APF, and allow to ensure both compensating harmonic currents and injecting the generated power into the grid. Also a type 2 fuzzy logic controller is used to control the DC-link capacitor in order to improve the dynamic response of the APF, and to ensure a well-smoothed DC-Link capacitor voltage. The gained benefits from these proposed control algorithms are the main contribution in this work. The proposed control scheme is implemented on a small-scale wind energy conversion system (WECS) controlled by a dSPACE 1104 card. Experimental results show that the proposed T2FLC maintains the DC-Link capacitor voltage within the limit for injecting the power into the grid. In addition, the PCC of the APF guarantees a flexible settlement of real power exchanges from the WECS to the grid with a high power factor operation.

• Smart Media Journal
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• v.9 no.2
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• pp.22-32
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• 2020

The hippocampal volume atrophy is known to be linked with neuro-degenerative disorders and it is also one of the most important early biomarkers for Alzheimer's disease detection. The measurements of hippocampal pure volumes from Magnetic Resonance Imaging (MRI) is a crucial task and state-of-the-art methods require a large amount of time. In addition, the structural brain development is investigated using MRI data, where brain morphometry (e.g. cortical thickness, volume, surface area etc.) study is one of the significant parts of the analysis. In this study, we have proposed a patch-based ensemble model of 3-D convolutional neural network (CNN) to measure the hippocampal pure volume from MRI data. The 3-D patches were extracted from the volumetric MRI scans to train the proposed 3-D CNN models. The trained models are used to construct the ensemble 3-D CNN model and the aggregated model predicts the pure volume in one-step in the test phase. Our approach takes only 5 seconds to estimate the volumes from an MRI scan. The average errors for the proposed ensemble 3-D CNN model are 11.7±8.8 (error%±STD) and 12.5±12.8 (error%±STD) for the left and right hippocampi of 65 test MRI scans, respectively. The quantitative study on the predicted volumes over the ground truth volumes shows that the proposed approach can be used as a proxy.