• Proceedings of the Korean Society of Medical Physics Conference
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• 2003.09a
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• pp.78-78
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• 2003

Purpose: This event related fMRI study was to further our understanding about how different brain regions could contribute to effective access of specific information stored in long term memory. This experiment has allowed us to determine the brain regions involved in recognition of familiar faces among non familiar faces. Materials and Methods: Twelve right handed normal, healthy volunteer adults participated in face recognition experiment. The paradigm consists of two 40 familiar faces, 40 unfamiliar faces and control base with scrambled faces in a randomized order, with null events. Volunteers were instructed to press on one of two possible buttons of a response box to indicate whether a face was familiar or not. Incorrect answers were ignored. A 1.5T MRI system(GMENS) was employed to evaluate brain activity by using blood oxygen level dependent (BOLD) contrast. Gradient Echo EPI sequence with TR/TE= 2250/40 msec was used for 17 contiguous axial slices of 7mm thickness, covering the whole brain volume (240mm Field of view, 64 ${\times}$ 64 in plane resolution). The acquired data were applied to SPM99 for the processing such as realignment, normalization, smoothing, statistical ANOVA and statistical preference. Results/Disscusion: The comparison of familiar faces vs unfamiliar faces yielded significant activations in the medial temporal regions, the occipito temporal regions and in frontal regions. These results suggest that when volunteers are asked to recognize familiar faces among unfamiliar faces they tend to activate several regions frequently involved in face perception. The medial temporal regions are also activated for familiar and unfamiliar faces. This interesting result suggests a contribution of this structure in the attempt to match perceived faces with pre existing semantic representations stored in long term memory.

• Journal of Internet Computing and Services
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• v.1 no.2
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• pp.29-37
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• 2000

Asynchronous transfer mode is flexible to support multimedia communication services using asynchronous time-sharing and statistical multimedia techniques to the existing data communication area, ATM ABR service controls network traffic using feedback information on the network congestion situation in order to guarantee the demanded service qualities and the available cell rates, In this paper we apply the control method using queue length prediction to the formation of feedback information for more efficient ABR traffic control. If backward node receive the longer delayed feedback information on the impending congestion, the switch can be already congested from the uncontrolled arriving traffic and the fluctuation of queue length can be inefficiently high in the continuing time intervals, The feedback control method proposed in this paper predicts the queue length in the switch using the slope of queue length prediction function and queue length changes in time-series, The predicted congestion information is backward to the node, NLMS and neural network are used as the predictive control functions, and they are compared from performance on the queue length prediction. Simulation results show the efficiency of the proposed method compared to the feedback control method without the prediction, Therefore, we conclude that the efficient congestion and stability of the queue length controls are possible using the prediction scheme that can resolve the problems caused from the longer delays of the feedback information.

• Korean Journal of Medicinal Crop Science
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• v.19 no.6
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• pp.456-463
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• 2011

The present study examined the effects of Korean white ginseng (WG, Panax ginseng C. A. Meyer) on the learning and memory function and the neural activity in rats with trimethyltin (TMT)-induced memory deficits. The rats were administered with saline or WG (WG 100 or 300 mg/kg, p.o.) daily for 21 days. The cognitive improving efficacy of WG on the amnesic rats, which was induced by TMT, was investigated by assessing the Morris water maze test and by performing immunohistochemistries on choline acetyltransferase (ChAT), acetylcholinesterase (AchE), cAMP responsive element binding protein (CREB) and brain derived neurotrophic factor (BDNF). The rats treated with TMT injection (control group) showed impaired learning and memory of the tasks, but the rats treated with TMT injection and WG administration produced significant improvement of the escape latency to find the platform in the Morris water maze at the 2nd and 4th days compared to that of the control group. In the retention test, the WG 100 and WG 300 groups showed significantly increased crossing number around the platform compared to that of the control group (p < 0.001). Consistently with the behavioral data, result of immunohistochemistry analysis showed that WG 100 mg/kg significantly alleviated the loss of BDNF-ir neurons in the hippocampus compared to that of the control group (p < 0.01). Also, treatment with WG has a trend to be increased the cholinergic neurons in the hippocampal CA1 and CA3 areas as compared to that of the control group. These results suggest that WG may be useful for improving the cognitive function via regulation of neurotrophic activity.

• The Korean Journal of Pain
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• v.13 no.2
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• pp.149-155
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• 2000

Background: Pulsed radiofrequency (RF) lesioning is a painless procedure and causes no neurodestruction and neuritis-like reaction are common following conventional RF lesioning. There is little data about the effect of pulsed RF especially with regard to its suitability for the treatment of acute pain. The possibility of a placebo effect cannot be ruled out because a double-blind study was not performed in previous studies. There is also no neuropathologic study about pulsed RF. Methods: The rats were anesthetized with sodium pentobarbital (40 mg/kg, i.p.; supplemented as necessary). The common sciatic nerve was exposed by blunt dissection through biceps femoris. Pulsed RF was administered to the common sciatic nerve using a 30 ms/s pulse with for 120 seconds. The temperature reached was no more than $42^{\circ}C$. Analgesia was determined using hot-plate assay shortly and, 3 days and 1 week before, and 2 weeks after operation. Lesions were examined with LM (light microscope) and EM (electron microscope) 2 weeks later. Results: There were no differences in response latencies between the control and experimental group. There were many vacuoles with hyaline bodies in the Schwann cell cytoplasm rather than axon in LM and larger electron dense bodies. No changes were found in the axon or unmyelinated fibers. Only small changes were found in the sheaths of myelinated fibers and Schwann cells. Conclusions: We therefore do think that any analgesic effect of pulsed RF is not a result of block of neural conduction. But rather than it can be attributed to others factors. It was also ineffective as a treatment for acute pain such as that caused by the hot-plate test.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.723-732
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• 2001

In this paper, the neurofuzzy controller of optically guided AGV is proposed to improve the path-tracking performance A differential steered AGV has front-side and rear-side optical sensors, which can identify the guiding path. Due to the discontinuity of measured data in optical sensors, optically guided AGVs break away easily from the guiding path and path-tracking performance is being degraded. Whenever the On/Off signals in the optical sensors are generated discontinuously, the motion errors can be measured and updated. After sensing, the variation of motion errors can be estimated continuously by the dead reckoning method according to left/right wheel angular velocity. We define the estimated contour error as the sum of the measured contour in the sensing error and the estimated variation of contour error after sensing. The neurofuzzy system consists of incorporating fuzzy controller and neural network. The center and width of fuzzy membership functions are adaptively adjusted by back-propagation learning to minimize th estimated contour error. The proposed control system can be compared with the traditional fuzzy control and decision system in their network structure and learning ability. The proposed control strategy is experience through simulated model to check the performance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.129-137
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• 2020

Currently, The autonomous vehicle market is researching and developing four-level autonomous vehicles beyond the commercialization of three-level autonomous vehicles. Because unlike the level 3, the level 4 autonomous vehicle has to deal with an emergency directly, the most important aspect of a four-level autonomous vehicle is its stability. In this paper, we propose an Optimized Vehicle Routing System (OVRS) that determines the route with the lowest probability of an accident at the destination of the vehicle rather than an immediate response in an emergency. The OVRS analyzes road and surrounding vehicle information collected by The RSU communication to predict road hazards, and sets the route for the safer and faster road. The OVRS can improve the stability of the vehicle by executing the route guidance according to the road situation through the RSU on the road like the network routing method. As a result, the RPNN of the ASICM, one of the OVRS modules, was about 17% better than the CNN and 40% better than the LSTM. However, because the study was conducted in a virtual environment using a PC, the possibility of accident of the VPDM was not actually verified. Therefore, in the future, experiments with high accuracy on VPDM due to the collection of accident data and actual roads should be conducted in real vehicles and RSUs.

• Biomolecules & Therapeutics
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• v.23 no.6
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• pp.597-603
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• 2015

Synthetic cannabinoids JWH-018 and JWH-250 in 'herbal incense' also called 'spice' were first introduced in many countries. Numerous synthetic cannabinoids with similar chemical structures emerged simultaneously and suddenly. Currently there are not sufficient data on their adverse effects including neurotoxicity. There are only anecdotal reports that suggest their toxicity. In the present study, we evaluated the neurotoxicity of two synthetic cannabinoids (JWH-081 and JWH-210) through observation of various behavioral changes and analysis of histopathological changes using experimental mice with various doses (0.1, 1, 5 mg/kg). In functional observation battery (FOB) test, animals treated with 5 mg/kg of JWH-081 or JWH-210 showed traction and tremor. Their locomotor activities and rotarod retention time were significantly (p<0.05) decreased. However, no significant change was observed in learning or memory function. In histopathological analysis, neural cells of the animals treated with the high dose (5 mg/kg) of JWH-081 or JWH-210 showed distorted nuclei and nucleus membranes in the core shell of nucleus accumbens, suggesting neurotoxicity. Our results suggest that JWH-081 and JWH-210 may be neurotoxic substances through changing neuronal cell damages, especially in the core shell part of nucleus accumbens. To confirm our findings, further studies are needed in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.1-8
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• 2020

Air ducts installed for ventilation inside buildings accumulate contaminants during their service life. Robots are installed to clean the air duct at low cost, but they are still not fully automated and depend on manpower. In this study, an intersection detection algorithm for autonomous driving was applied to an air duct cleaning robot. Autonomous driving of the robot was achieved by calculating the distance and angle between the extracted point and the center point through the intersection detection algorithm from the camera image mounted on the robot. The training data consisted of CAD images of the duct interior as well as the cross-point coordinates and angles between the two boundary lines. The deep learning-based CNN model was applied as a detection algorithm. For training, the cross-point coordinates were obtained from CAD images. The accuracy was determined based on the differences in the actual and predicted areas and distances. A cleaning robot prototype was designed, consisting of a frame, a Raspberry Pi computer, a control unit and a drive unit. The algorithm was validated by video imagery of the robot in operation. The algorithm can be applied to vehicles operating in similar environments.

• Spatial Information Research
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• v.8 no.1
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• pp.141-153
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• 2000

The purpose of this study is to develop and apply spatial landslide information system using Geographic information system (GIS) in concerned with spatial data. Landslide locations detected from interpretation of aerial photo and field survey, and topographic , soil , forest , and geological maps of the study area, Yongin were collected and constructed into spatial database using GIS. As landslide occurrence factors, slope, aspect and curvature of topography were calculated from the topographic database. Texture, material, drainage and effective thickness of soil were extracted from the soil database, and type, age, diameter and density of wood were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the Landsat TM satellite image. In addition, landslide damageable objects such as building, road, rail and other facility were extracted from the topographic database. Landslide susceptibility was analyzed using the landslide occurrence factors by probability, logistic regression and neural network methods. The spatial landslide information system was developed to retrieve the constructed GIS database and landslide susceptibility . The system was developed using Arc View script language(Avenue), and consisted of pull-down and icon menus for easy use. Also, the constructed database can be retrieved through Internet World Wide Web (WWW) using Internet GIS technology.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.8-14
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• 2020

Recently, there was an increasing demand for an integrated access control system which is capable of user recognition, door control, and facility operations control for smart buildings automation. The market available door lock access control solutions need to be improved from the current level security of door locks operations where security is compromised when a password or digital keys are exposed to the strangers. At present, the access control system solution providers focusing on developing an automatic access control system using (RF) based technologies like bluetooth, WiFi, etc. All the existing automatic door access control technologies required an additional hardware interface and always vulnerable security threads. This paper proposes the user identification and authentication solution for automatic door lock control operations using camera based visible light communication (VLC) technology. This proposed approach use the cameras installed in building facility, user smart devices and IoT open source controller based LED light sensors installed in buildings infrastructure. The building facility installed IoT LED light sensors transmit the authorized user and facility information color grid code and the smart device camera decode the user informations and verify with stored user information then indicate the authentication status to the user and send authentication acknowledgement to facility door lock integrated camera to control the door lock operations. The camera based VLC receiver uses the artificial intelligence (AI) methods to decode VLC data to improve the VLC performance. This paper implements the testbed model using IoT open-source based LED light sensor with CCTV camera and user smartphone devices. The experiment results are verified with custom made convolutional neural network (CNN) based AI techniques for VLC deciding method on smart devices and PC based CCTV monitoring solutions. The archived experiment results confirm that proposed door access control solution is effective and robust for automatic door access control.