• The Korean Journal of Physiology and Pharmacology
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• v.3 no.4
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• pp.365-373
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• 1999

Somatostatin (SOM) is one of the major neuropeptides in dorsal root ganglion cells, but its role in spinal nociceptive process has not been well known. In present study we aimed to investigate the effect of SOM on the response of dorsal horn neurons to the various types of peripheral nociceptive stimuli in anesthetized cats. Using carbon-filament microelectrode, the single cell activities of wide dynamic range neurons were recorded from the lumbosacral enlargement after noxious mechanical (squeeze), thermal (radiant heat lamp) and cold (dry ice) stimulation to the receptive field. Sciatic nerve was stimulated electrically to evoke $A\;{\delta}-$ and C-nociceptive responses. SOM analogue, octreotide $(10\;{\mu}g/kg),$ was applied intravenously and the results were compared with those of morphine (2 mg/kg, MOR). Systemic SOM decreased the cellular responses to the noxious heat and the mechanical stimulation, but increased those to the cold stimulation. In the responses to the electric stimuli of sciatic nerve, $A\;{\delta}-nociceptive$ response was increased by SOM, while C-nociceptive response was decreased. On the other hand, MOR inhibited the dorsal horn cell responses to all the noxious stimuli. From the above results, it is concluded that SOM suppresses the transmission of nociceptive heat and mechanical stimuli, especially via C-fiber, while it facilitates those of nociceptive cold stimuli via $A\;{\delta}-fiber$.

• The Korean Journal of Physiology
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• v.24 no.1
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• pp.171-180
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• 1990

In 19 cats anesthetized with ${\alpha}-chloralose$ effects of taurine and ${\beta}-alanine$ on the responses of wide dynamic range (WDR) cells to mechanical, chemical and thermal stimuli were investigated in the lumbar spinal cord of the cat. Also studied was an interaction of strychnine with taurine in affecting the activities of WDR cells. Following intravenous administration of taurine, the responses of WDR cells to all types of mechanical stimuli were markedly enhanced, demonstrating that the response to pressure was most sensitive to taurine action. When the receptive field was exposed to thermal stimuli ($50^{\circ}C$) for 20 sec. taurine increased activity of WDR cell to 169.5% of the control value. The $K^{+}$-induced activation of WDR cells was invariably suppressed after taurine administration. Intravenously administered strychnine remarkably reduced the enhanced response of WDR cell to natural stimuli resulting from intravenous administration of taurine. Also ${\beta}-alanine$ markedly activated the response of spinal dorsal horn cell to natural mechanical stimuli. These findings suggest that neutral amino acid and its derivative such as ${\beta}-alanine$ and taurine can enhance the response of WDR cells to different stimuli in cats.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.10
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• pp.68-77
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• 1990

In this paper, a neural patten recognition method for the automatic circuit diagram reading system is proposed. The proposed procedure to recognize a deformed logic symbols is composed of three stages: feature detection, log mapping, and pattern classification. In the feature detection stage, a modified competitive learning algorithm where each pattern has the inhibition weight as well as the activation weight is developed. The global information of hand-written logic symbols is obtained by the feature detection neural network having both the inhibition and activation weights. The obtained global data is then transformed into a log space by the conformal mapping where according to the Schwartz's theory about the human visual signal process-ing, the degree of rotation and the scale change are mapped into the translation change. Logic symbols are finally classified by a three layer perceptron trained by the error back propagation algorithm. The computer simulation demonstrates that the proposed multistage neural network system can recognize well the deformed patterns of hand-written logic circuit diagrams.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.95-108
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• 2010

In this paper, we present a hybrid neural network model for dynamic hand gesture recognition. The model consists of two modules, feature extraction module and pattern classification module. We first propose a modified CNN(convolutional Neural Network) a pattern recognition model for the feature extraction module. Then we introduce a weighted fuzzy min-max(WFMM) neural network for the pattern classification module. The data representation proposed in this research is a spatiotemporal template which is based on the motion information of the target object. To minimize the influence caused by the spatial and temporal variation of the feature points, we extend the receptive field of the CNN model to a three-dimensional structure. We discuss the learning capability of the WFMM neural networks in which the weight concept is added to represent the frequency factor in training pattern set. The model can overcome the performance degradation which may be caused by the hyperbox contraction process of conventional FMM neural networks. From the experimental results of human action recognition and dynamic hand gesture recognition for remote-control electric home appliances, the validity of the proposed models is discussed.

• The Korean Journal of Physiology
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• v.24 no.2
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• pp.305-317
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• 1990

The present study was performed to investigate modification in the electrophysiological characteristics of cat dorsal horn cells during neurogenic inflammation induced by mustard oil. The results obtained were summarized as follows: 1) Following subcutaneous injection of mustard oil the majority of wide dynamic range (WDR) cells (10/15 units) showed enhanced responses (80%) to brush, while the responses to all types of mechanical stiumli were enhanced in 3/15 units. One cell was further activated by pinch and the another was not affected at all after induction of inflammation. 2) The sensitization of WDR cell was resulted from subcutaneous injection of mustard oil either inside or outside of the receptive field (RF), whereas the spontaneous activity increased only after mustard oil was injected inside of the RF. 3) In the animal with inflammation the responses of high threshold (HT) cell to noxious stimulus were not altered, while HT cell responded to such mechanical stimulus as pressure which was usually ineffective in normal animals. 4) After induction of inflammation, low threshold (LT) cell appeared to be converted to WDR cell, showing responses not only to brush but also to pressure and pinch. 5) The mustard oil-induced inflammation enhanced responses of WDR and HT cells to the thermal stimuli and also resulted in a pronounced after-discharge in WDR cells. 6) After subcutaneous injection of lidocaine, the increased background activity of WDR cells due to inflammation was almost completely abolished. 7) A subcutaneous injection of mustard oil inside of the RF invariably desensitized the dorsal horn cells which receive sensory inputs from the inflamed RF. From the results of Present study it was revealed that a neurogenic inflammation induced by mustard oil resulted in an enhancement of responses of cat dorsal horn cells to mechanical and thermal stimuli.

• The Korean Journal of Physiology and Pharmacology
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• v.4 no.1
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• pp.15-24
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• 2000

Although nociceptive informations are thought to be processed via different neural mechanisms depending on the types of stimuli, sufficient data have not been accumulated yet. We performed a series of experiments to elucidate the possible neural mechanisms as to chemical stimuli such as formalin, capsaicin and ATP. Single unit activity of wide dynamic range (WDR) neurons and high threshold cells were recorded extracellularly from the lumbosacral enlargement of cat spinal cord before and after chemical stimulation to its receptive field (RF). Each chemical substance - formalin $(20{\mu}l,\;4%),$ capsaicin (33 mM) or Mg-ATP (5 mM)- was injected intradermally into the RFs and then the changes in the spontaneous activity, mechanical threshold and responses to the peripheral mechanical stimuli were observed. In many cases, intradermal injection of formalin (5/11) and capsaicin (8/11) resulted in increase of the spontaneous activity with a biphasic pattern, whereas ATP (8/8) only showed initial responses. Time courses of the biphasic pattern, especially the late response, differed between formalin and capsaicin experiments. One hour after injection of each chemical (formalin, capsaicin, or ATP), the responses of the dorsal horn neurons to mechanical stimuli increased at large and the RFs were expended, suggesting development of hypersensitization (formalin 6/10, capsaicin 8/11, and ATP 15/19, respectively). These results are suggested that formalin stimulates peripheral nociceptor, local inflammation and involvement of central sensitization, capsaicin induces central sensitization as well as affects the peripheral C-polymodal nociceptors and neurogenic inflammation, and ATP directly stimulates peripheral nociceptors.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.31-37
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• 2021

In this paper proposed a feature fusion and spatial attention-based modified YOLOv4S for small and occluded detection. Conventional YOLOv4S is a lightweight network and lacks feature extraction capability compared to the method of the deep network. The proposed method first combines feature maps of different scales with feature fusion to enhance semantic and low-level information. In addition expanding the receptive field with dilated convolution, the detection accuracy for small and occluded objects was improved. Second by improving the conventional spatial information with spatial attention, the detection accuracy of objects classified and occluded between objects was improved. PASCAL VOC and COCO datasets were used for quantitative evaluation of the proposed method. The proposed method improved mAP by 2.7% in the PASCAL VOC dataset and 1.8% in the COCO dataset compared to the Conventional YOLOv4S.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.81-89
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• 2021

Under natural conditions, Apple detection has the problems of occlusion and small object detection difficulties. This paper proposes an improved model based on SSD. The SSD backbone network VGG16 is replaced with the ResNet50 network model, and the receptive field structure RFB structure is introduced. The RFB model amplifies the feature information of small objects and improves the detection accuracy of small objects. Combined with the attention mechanism (SE) to filter out the information that needs to be retained, the semantic information of the detection objectis enhanced. An improved SSD algorithm is trained on the VOC2007 data set. Compared with SSD, the improved algorithm has increased the accuracy of occlusion and small object detection by 3.4% and 3.9%. The algorithm has improved the false detection rate and missed detection rate. The improved algorithm proposed in this paper has higher efficiency.

• Korean Journal of Construction Engineering and Management
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• v.23 no.2
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• pp.54-64
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• 2022

Since the interest in big data is growing exponentially, various types of research and development in the field of big data have been conducted in the construction industry. Among various application areas, cost estimating can be a topic where the use of big data provides positive benefits. In order for firms to make efficient use of big data for estimating tasks, they need to establish a strategy based on the multifaceted analysis of internal and external environments. The objective of the study is to develop and propose a strategy of the use of big data for construction management(CM) firms' cost estimating tasks based on the SWOT analysis. Through the combined efforts of literature review, questionnaire survey, interviews and the SWOT analysis, the study suggests that CM firms need to maintain the current level of the receptive culture for the use of big data and expand incrementally information resources. It also proposes that they need to reinforce the weak areas including big data experts and practice infrastructure for improving the big data-based cost estimating.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2390-2406
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• 2022

Scene text recognition has important application value and attracted the interest of plenty of researchers. At present, many methods have achieved good results, but most of the existing approaches attempt to improve the performance of scene text recognition from the image level. They have a good effect on reading regular scene texts. However, there are still many obstacles to recognizing text on low-quality images such as curved, occlusion, and blur. This exacerbates the difficulty of feature extraction because the image quality is uneven. In addition, the results of model testing are highly dependent on training data, so there is still room for improvement in scene text recognition methods. In this work, we present a natural scene text recognizer to improve the recognition performance from the feature level, which contains feature representation and feature enhancement. In terms of feature representation, we propose an efficient feature extractor combined with Representative Batch Normalization and ResNet. It reduces the dependence of the model on training data and improves the feature representation ability of different instances. In terms of feature enhancement, we use a feature enhancement network to expand the receptive field of feature maps, so that feature maps contain rich feature information. Enhanced feature representation capability helps to improve the recognition performance of the model. We conducted experiments on 7 benchmarks, which shows that this method is highly competitive in recognizing both regular and irregular texts. The method achieved top1 recognition accuracy on four benchmarks of IC03, IC13, IC15, and SVTP.