• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.1
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• pp.95-107
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• 2017

In this study, a preliminary study was undertaken for development of a tunnel incident automatic detection system based on a machine learning algorithm which is to detect a number of incidents taking place in tunnel in real time and also to be able to identify the type of incident. Two road sites where CCTVs are operating have been selected and a part of CCTV images are treated to produce sets of training data. The data sets are composed of position and time information of moving objects on CCTV screen which are extracted by initially detecting and tracking of incoming objects into CCTV screen by using a conventional image processing technique available in this study. And the data sets are matched with 6 categories of events such as lane change, stoping, etc which are also involved in the training data sets. The training data are learnt by a resilience neural network where two hidden layers are applied and 9 architectural models are set up for parametric studies, from which the architectural model, 300(first hidden layer)-150(second hidden layer) is found to be optimum in highest accuracy with respect to training data as well as testing data not used for training. From this study, it was shown that the highly variable and complex traffic and incident features could be well identified without any definition of feature regulation by using a concept of machine learning. In addition, detection capability and accuracy of the machine learning based system will be automatically enhanced as much as big data of CCTV images in tunnel becomes rich.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.93-112
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• 2015

Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

• Bulletin of the Korean Space Science Society
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• 1993.10a
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• pp.17-17
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• 1993

The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70${\pm}$1.32mmHg/min)compared to CF dialyzers(4.32${\pm}$0.55mmHg/min)(p<0.05). However, there was no observable difference in the UFR between the two dialyzers. Neither APD nor UFR showed any significant increase with an increasing number of reuses for up to more than 20reuses. A substantial number of failures observed in APD(larger than 20mmHe/min)on the reused dialyzers(2 out of 40 CP and S out 26 C-DAK) were attributed to the Possible damage on the fibers. The CF 15-11 HFDs which failed APD test did not show changes in the UFR compared to normal dialyzers indicating that APD is a more sensitive test than UFR test to evaluate the integrity of the fibers. 30527 T00401030527 ^x For quantitative measurement of reflected light from a clinical diagnostic strip, a prototype old reflectance photometer was designed. The strip loader and cassette were made to obtain more accurate reflectance parameters. The strip was illuminated at 45˚c through optical fiber and the intensity of reflected light was determined at rectanguLat angle using a photodiode. The kubelka-munk coefficient and reflection optical density were determined ar four different wavelengths(500,550,570 and 610nm) for blood glucose strip. For higher concentration than 300mg/41 about glucose, a saturation state of abforbance was observed at 500,550 and 570nm. The correlation between glucose concentration and parameters was the best at 610nm. 30535 T00401030535 ^x Radiation-induced fibrosarcoma tumors were grown on the flanks of C3H mice. The mice were divided into two groups. One group was injected with Photofrin II, intravenously (2.5mg/kg body weight). The other group received no Photofrin II. Mice from both groups were irradialed for approximately 15 minutes at 100,300, or 500 mW/cm2 with the argon (488nm/514.5 nm), dye(628nm) and gold vapor (pulsed 628 nm) laser light. A photosensitizer behaved as an added absorber. Under our experimental conditions, the presence of Photolfrin II increased surface temperature by at least 40% and the temperature rise due to 300 mW/cm2 irradiation exceeded values for hyperthermia. Light and temperature distributions with depth were estimated by a computer model. The model demonstrated the influence of wavelength on the thermal process and proved to be a valuable tool to investigate internal temperature rise. 30536 T00401030536 ^x We investigated the structural geometry of thirty-eight Korean femurs. The purpose of this study is to identify major geometrical differences between Korean femurs 3nd others that we believe belong to Caucasians so that we would be able to get insights into the femoral component design that fits Asians including Koreans. We utilized computerized tomography (CT) images of femurs extracted from cadavers. The CT images were transformed into bitmap data by using a film scanner, and then analyzed by using a commercially available software called Image v.1.0 and a Macintosh IIci computer.The resulting data were compared with already published data. The major results show that the geometry of the Korean femurs is significantly different from that of Caucasians: (1) the anteversion angle and the canal flare index are greater by the amount of approximately 8˚ and 0.5, respectively, (2) the shape of the isthmus cross section is more round, and (3) the distance between the teaser trochanter and the proximal border of the isthmus is shelter by about 15 mm. The results suggested that the femoral component suitable for Asians should be different from the currently-used components designed and manufactured mostly by European or American companies. 30537 T00401030537 ^x It is well known that nonlinear propagation characteristics of the wave in the tissue may give very useful information for the medical diagnoisis. In this paper, a new method to detect nonlinear propagation characteristics of the internal vibration in the tissue for the low frequency mechanical vibration by using bispectral analysis is proposed. In the method, low frequency vibration of f0( = 100Hz) is applied on the surface of the object, and the waveform of the internal vibration x (t) is measured from Doppler frequency modulation of silmultaneously transmitted probing ultrasonic waves. Then, the bispectra of the signal x (t) at the frequencies (f0, f0) and (f0, 2f0) are calculated to estimate the nonlinear propagation characteristics as their magnitude ratio, w here since bispectrum is free from the gaussian additive noise we can get the value with high S/N. Basic experimental system is constructed by using 3.0 MHz probing ultrasonic waves and the several experiments are carried out for some phantoms. Results show the superiority of the proposed method to the conventional method using power spectrum and also its usefulness for the tissue characterization. 30541 T00401030541 ^x This paper describes the implementation of a computerized radial pulse diagnosis by aids of a clinical expert. On this base, we composed of the radial pulse diagnosis system in korean traditional medicine. The system composed of a radial pulse wave detection system and a radial pulse diagnosis system. With a detection system, we detected Inyoung and Cheongu radial pulse wave and processed it. Then, we have got the characteristic parameters of radial pulse wave and also quantified that according to the method of Inyoung-Cheongu Comparison Radial Pulse Diagnosis. We defined the jugement standard of radial pulse diagnosis system and then we confirmed the possibility for realization of automatic radial pulse diagnosis in korean traditional medicine. 30545 T00401030545 ^x Microspheres are expected to be applied to biomedical areas such as solid-phase immunoassays, drug delivery systems, immunomagnetic cell separation. To synthesize microspheres for biomedical application, "two stage shot growth method" was developed. The uniformity ratio of synthesized microspheres was always smaller than 1.05. And the surface charge density (or the number of ionizable functional groups) of the microspheres synthesized by "two stage shot growth method" was 6~13 times higher than that of the microspheres synthesized by conventional seeded batch copolymerization. As a previous step for biomedical application, adsorption experiments of bovine albumin on microspheres were carried out under various conditions. The maximum adsorbed amount was obtained in the neighborhood of pH 4.5. Isoelectric point of bovine albumin is pH 5.0, so experimental result shows that it shifted to acid area. The adsorption isotherm was obtained, the plateau region was always reached at 2.Og/L (bulk concentration of bovine albumin).The effect of the kind and the amount of surface functional group was also examined. 30575 T00401030575 ^x A medical image workstation was developed using multimedia technique. The system based on PC-486DX was designed to acquire medical images produced by medical imaging instruments and related audio information, that is, doctors' reporting results. Input information was processed and analyzed, then the results were presented in the form of graph and animation. All the informations of the system were hierarchically related with the image as the apex. Processing and analysis algorithms were implemented so that the diagnostic accuracy could be improved. The diagnosed information can be transferred for patient diagnosis through LAN(local area network). 30592 T00401030592 ^x In the conventional infrared imaging system, complex infrared lens systems are usually used for directing collimated narrow infrared beams into the high speed 2-dimensional optic scanner. In this paper, a simple reflective infrared optic system with a 2-dimensional optic scanner is proposed for the realization of medical infrared thermography system. It has been experimentally proven that the intfrared thermography system composed of the proposed optic system has the temperature resolution of 0.1˚c under the spatial resolution of lmrad, the image matrix size of 256 X 240, and tile imaging time of 4 seconds. 30593 T00401030593 ^x In this paper, MIIS (Medical Image Information System) has been designed and implemented using INGRES RDBMS, which is based on a client/server architecture. The implemented system allows users to register and retrieve patient information, medical images and diagnostic reports. It also provides the function to display these information on workstation windows simultaneously by using the designed menu-driven graphic user interface. The medical image compression/decompression techniques are implemented and integrated into the medical image database system for the efficient data storage and the fast access through the network. 30594 T00401030594 ^x In this paper, computerized BEAM was implemented for the space domain analysis of EEG. Trans-formation from temporal summation to two-dimensional mappings is formed by 4 nearest point inter-polaton method. Methods of representation of BEAM are two. One is dot density method which classify brain electrical potential 9 levels by dot density of gray levels and the other is colour method which classify brain electrical 12 levels by red-green colours. In this BEAM, instantaneous change and average energy distribution over any arbitrary time interval of brain electrical activity could be observed and analyzed easily. In the frequency domain, the distribution of energy spectrum of a special band can easily be distinguished normality and abnormality. 30608 T00401030608 ^x Laboratory information system (LIS) is a key tool to manage laboratory data in clinical pathology. Our department has developed an information system for routine hematology using down-sized computer system. We have used an IBM 486 compatible PC with 16MB main memory, 210 MB hard disk drive, 9 RS-232C port and 24 pin dot printer. The operating system and database management system were SCO UNIX and SCO foxbase, respectively. For program development, we used Xbase language provided by SCO foxbase. The C language was used for interface purpose. To make the system use friendly, pull-down menu was used. The system connected to our hospital information system via application program interface (API), so the information related to patient and request details is automatically transmitted to our computer. Our system interfaced with fwd complete blood count analyzers(Sysmex NE-8000 and Coulter STKS) for unidirectional data tansmission from analyzer to computer. The authors suggests that this system based on down-sized computer could provide a progressive approach to total LIS based on local area network, and the implemented system could serve as a model for other hospital's LIS for routine hematology. 30609 T00401030609 ^x To develop an artificial bone substitute that is gradually degraded and replaced by the regenerated natural bone, the authors designed a composite that is consisted of calcium phosphate and collagen. To use as the structural matrix of the composite, collagen was purified from human umbilical cord. The obtained collagen was treated by pepsin to remove telopeptides, and finally, the immune-free atelocollagen was produced: The cross linked atelocollagen was highly resistant to the collagenase induced collagenolysis. The cross linked collagen demonstrated an improved tensile strength. 30618 T00401030618 ^x This paper is a study on the design of adptive filter for QRS complex detection. We propose a simple adaptive algorithm to increase capability of noise cancelation in QRS complex detection with two stage adaptive filter. At the first stage, background noise is removed and at the next stage, only spectrum of QRS complex components is passed. Two adaptive filters can afford to keep track of the changes of both noise and QRS complex. Each adaptive filter consists of prediction error filter and FIR filter The impulse response of FIR filter uses coefficients of prediction error filter. The detection rates for 105 and 108 of MIT/BIH data base were 99.3% and 97.4% respectively. 30619 T00401030619 ^x To develop an artificial bone substitute that is gradually degraded and replaced by the regenerated natural bone, the authors designed and produced a composite that is consisted of calcium phosphate and collagen. Human umbilical cord origin pepsin treated type I atelocollagen was used as the structural matrix, by which sintered or non-sintered carbonate apatite was encapsulated to form an inorganic-organic composite. With cross linking atelocollagen by UV ray irradiation, the resistance to both compressive and tensile strength was increased. Collagen degradation by the collagenase induced collagenolysis was also decreased. 30620 T00401030620 ^x We have developed a monoleaflet polymer valve as an inexpensive and viable alternative, especially for short-term use in the ventricular assist device or total artificial heart. The frame and leaflet of the polymer valve were made from polyurethane, To evaluate the hemodynamic performance of the polymer valve a comparative study of flow dynamics past a polymer valve and a St. Jude Medical prosthetic valve under physiological pulsatile flow conditions in vitro was made. Comparisons between the valves were made on the transvalvular pressure drop, regurgitation volume and maximum valve opening area. The polymer valve showed smaller regurgitation volume and transvalvular pressure drop compared to the mechanical valve at higher heart rate. The results showed that the functional characteristics of the polymer valve compared favorably with those of the mechanical valve at higher heart rate. 30621 T00401030621 ^x Explosive evaporative removal process of biological tissue by absorption of a CW laser has been simulated by using gelatin and a multimode Nd:YAG laser. Because the point of maximun temperature of laser-irradiated gelatin exists below the surface due to surface cooling, evaporation at the boiling temperature is made explosively from below the surface. The important parameters of this process are the conduction loss to laser power absorption (defined as the conduction-to-laser power parameter, Nk), the convection heat transfer at the surface to conduction loss (defined as Bi), dimensionless extinction coefficient (defined as Br.), and dimensionless irradiation time (defined as Fo). Dependence of Fo on Nk and Bi has been observed by experiment, and the results have been compared with the numerical results obtained by solving a 2-dimensional conduction equation. Fo and explosion depth (from the surface to the point of maximun temperature) are increased when Nk and Bi are increased.To find out the minimum laser power for explosive evaporative removal process, steady state analysis has been also made. The limit of Nk to induce evaporative removal, which is proportional to the inverse of the laser power, has been obtained. 30622 T00401030622 ^x N1 and N2 gross neural action potentials were measured from the round window of the guinea pig cochlea at the onset of the acoustic stimuli. N1-N2 audiograms were made by means of regulating stimulant intensities in order to produce constant N1-N2 potentials as criteria for different input tone pip frequencies. The lowest threshold was measured with an input tone pip I5 dB SPL in intensity and 12 KHz in frequency when the animal was in normal physiological condition. The procedure of experimental measurements is explained in detail. This experimental approach is very useful for the investigation of the Cochlear function. Both noN1inear and active functions of the Cochlea can be monitored by N1-N2 audiograms. 30623 T00401030623 ^x In electrical impedance tomography(EIT), we use boundary current and voltage measurements toprovide the information about the cross-sectional distribution of electrical impedance or resistivity. One of the major problems in EIT has been the inaccessibility of internal voltage or current data in finding the internal impedance values. We propose a new image reconstruction method using internal current density data measured by NMR. We obtained a two-dimensional current density distribution within a phantom by processing the real and imaginary MR images from a 4.77 NMR machine. We implemented a resistivity mage reconstruction algorithm using the finite element method and sensitivity matrix. We presented computer simulation results of the mage reconstruction algorithm and furture direction of the research. 30624 T00401030624 ^x A new method of digital image analysis technique for discrimination of cancer cell was presented in this paper. The object image was the Thyroid eland cells image that was diagnosed as normal and abnormal (two types of abnormal: follicular neoplastic cell, and papillary neoplastic cell), respectively. By using the proposed region segmentation algorithm, the cells were segmented into nucleus. The 16 feature parameters were used to calculate the features of each nucleus. A9 a consequence of using dominant feature parameters method proposed in this paper, discrimination rate of 91.11% was obtained for Thyroid Gland cells. 30625 T00401030625 ^x An electrical stimulator was designed to induce locomotion for paraplegic patients caused by central nervous system injury. Optimal stimulus parameters, which can minimize muscle fatigue and can achieve effective muscle contraction were determined in slow and fast muscles in Sprague-Dawley rats. Stimulus patterns of our stimulator were designed to simulate electromyographic activity monitored during locomotion of normal subjects. Muscle types of the lower extremity were classified according to their mechanical property of contraction, which are slow muscle (msoleus m.) and fast muscle (medial gastrocneminus m., rectus femoris m., vastus lateralis m.). Optimal parameters of electrical stimulation for slow muscles were 20 Hz, 0.2 ms square pulse. For fast muscle, 40 Hz, 0.3 ms square pulse was optimal to produce repeated contraction. Higher stimulus intensity was required when synergistic muscles were stimulated simultaneously than when they were stimulated individually. Electrical stimulation for each muscle was designed to generate bipedal locomotion, so that individual muscles alternate contraction and relaxation to simulate stance and swing phases. Portable electrical stimulator with 16 channels built in microprocessor was constructed and applied to paraplegic patients due to lumbar cord injury. The electrical stimulator restored partially gait function in paraplegic patients. 30626 T00401030626 ^x Two-Dimensional modelling of the Cochlear biomechanics is presented in this paper. The Laplace partial differential equation which represents the fluid mechanics of the Cochlea has been transformed into two-dimensional electrical transmission line. The procedure of this transformation is explained in detail. The comparison between one and two dimensional models is also presented. This electrical modelling of the basilar membrane (BM) is clearly useful for the next approach to the further. Development of active elements which are essential in the producing of the sharp tuning of the BM. This paper shows that two-dimension model is qualitatively better than one-dimensional model both in amplitude and phase responses of the BM displacement. The present model is only for frequency response. However because the model is electrical, the two-dimensional transmission line model can be extended to time response without any difficult. 30627 T00401030627 ^x A method has been proposed for the fully automatic detection of left ventricular endocardial boundary in 2D short axis echocardiogram using geometric model. The procedure has the following three distinct stages. First, the initial center is estimated by the initial center estimation algorithm which is applied to decimated image. Second, the center estimation algorithm is applied to original image and then best-fit elliptic model estimation is processed. Third, best-fit boundary is detected by the cost function which is based on the best-fit elliptic model. The proposed method shows effective result without manual intervention by a human operator. 30628 T00401030628 ^x The intelligent trajectory control method that controls moving direction and average velocity for a prosthetic arm is proposed by pattern recognition and force estimations using EMG signals. Also, we propose the real time trajectory planning method which generates continuous accelleration paths using 3 stage linear filters to minimize the impact to human body induced by arm motions and to reduce the muscle fatigue. We use combination of MLP and fuzzy filter for pattern recognition to estimate the direction of a muscle and Hogan's method for the force estimation. EMG signals are acquired by using a amputation simulator and 2 dimensional joystick motion. The simulation results of proposed prosthetic arm control system using the EMf signals show that the arm is effectively followed the desired trajectory depended on estimated force and direction of muscle movements. 30638 T00401030638 ^x A new neural network architecture for the recognition of patterns from images is proposed, which is partially based on the results of physiological studies. The proposed network is composed of multi-layers and the nerve cells in each layer are connected by spatial filters which approximate receptive fields in optic nerve fields. In the proposed method, patterns recognition for complicated images is carried out using global features as well as local features such as lines and end-points. A new generating method of matched filers representing global features is proposed in this network. 30659 T00401030659 ^x An implementation scheme of the magnetic nerve stimulator using a switching mode power supply is proposed. By using a switching mode power supply rather than a conventional linear power supply for charging high voltage capacitors, the weight and size of the magnetic nerve stimulator can be considerably reduced. Maximum output voltage of the developed magnetic nerve stimulator using the switching mode power supply is 3,000 volts and switching time is about 100 msec. Experimental results or human nerve stimulations using the developed stimulator are presented. 30768 T00401030768 ^x In this paper, we describe the design methodology and specifications of the developed module-based bedside monitors for patient monitoring. The bedside monitor consists of a main unit and module cases with various parameter modules. The main unit includes a 12.1" TFT color LCD, a main CPU board, and peripherals such as a module controller, Ethernet LAN card, video card, rotate/push button controller, etc. The main unit can connect at maximum three module cases each of which can accommodate up to 7 parameter modules. They include the modules for electrocardiograph, respiration, invasive blood pressure, noninvasive blood pressure, temperature, and SpO2 with Plethysmograph.