• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.63-73
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• 2022

A more accurate understanding of the irrigation water supply is necessary for efficient agricultural water management. Although we measure water levels in an irrigation canal using ultrasonic water level gauges, some errors occur due to malfunctions or the surrounding environment. This study aims to apply CNN (Convolutional Neural Network) Deep-learning-based image classification and segmentation models to the irrigation canal's CCTV (Closed-Circuit Television) images. The CCTV images were acquired from the irrigation canal of the agricultural reservoir in Cheorwon-gun, Gangwon-do. We used the ResNet-50 model for the image classification model and the U-Net model for the image segmentation model. Using the Natural Breaks algorithm, we divided water level data into 2, 4, and 8 groups for image classification models. The classification models of 2, 4, and 8 groups showed the accuracy of 1.000, 0.987, and 0.634, respectively. The image segmentation model showed a Dice score of 0.998 and predicted water levels showed R² of 0.97 and MAE (Mean Absolute Error) of 0.02 m. The image classification models can be applied to the automatic gate-controller at four divisions of water levels. Also, the image segmentation model results can be applied to the alternative measurement for ultrasonic water gauges. We expect that the results of this study can provide a more scientific and efficient approach for agricultural water management.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.570-573
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• 2022

This paper presents the identification of void diameters for a cast-resin transformer using an artificial neural network (ANN) model. A PD signal was measured by the Rogowski coil sensor which has the planar and thin structures fabricated on a printed circuit board (PCB), and the PD electrode system was fabricated to simulate a PD defect by a void. In addition, void samples with different diameters were fabricated by injecting air in a cylindrical aluminum frame using a syringe during the epoxy curing process. To identify the diameter of void defects, PD characteristics such as the discharge magnitude, pulse count, and phase angle were extracted and back propagation algorithm (BPA) was designed using virtual instrument (VI) based on the Labview program. From the experimental results, the BPA algorithm proposed in this paper has over 90% accurate rate to identify the diameter of void defects and is expected to use reference data of maintenance and replacement of insulation for cast-resin transformers in the on-site PD measurement.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.388-389
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• 2022

Recently, AI (Artificial Intelligence) has been applied to various technologies such as automatic driving, robot and smart communication. Currently, AI system is developed by software-based method using tensor flow, and GPU (Graphic Processing Unit) is employed for processing unit. However, if software-based method employing GPU is used for AI applications, there is a problem that we can not change the internal circuit of processing unit. In this method, if high-level jobs are required for AI system, we need high-performance GPU, therefore, we have to change GPU or graphic card to perform the jobs. In this work, we developed a CNN-based FPGA (Field Programmable Gate Array) chip to solve this problem.

• The Korean Journal of Nuclear Medicine
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• v.39 no.6
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• pp.438-444
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• 2005

Purpose: Anhedonia has been proposed to be the result of a basic neurophysiologic dysfunction and a vulnerability marker that precede and contribute to the liability of developing schizophrenia. We hypothesized that anhedonia, as a construct reflecting the decreased capacity to experience pleasure, should be associated with decreased positive hedonic affect trait. This study examined the relationship between anhedonia and positive hedonic affect trait and searched for the brain legions which correlate with anhedonia in normal subjects. Materials and Methods: Using $^{18}F$-FDG PET scan, we investigated the brain activity of twenty one subjects during resting state. Questionnaires were administrated after the scan in order to assess the self-rated individual differences in physical/social anhedonia and positive/negative affect traits. Results: Negative correlation between physical anhedonia score and positive affect trait score was significant (Pearson coefficient =-0.440, p<0.05). The subjects physical and social anhedonia scores showed positive correlation with metabolic rates in the cerebellum and negative correlation with metabolic rates in the inferior temporal gyrus and middie frontal gyrus. In addition, the positive affect trait score positively correlated with various areas, most prominent with the inferior temporal gyrus. Conclusion: These results suggest that neural substrates, such as the inferior temporal gyrus and prefrontal-cerebellar circuit, which dysfunction has been proposed to be involved with the cognitive deficits of schizophrenia, may also play a significant role in the liability of affective deficits like anhedonia.

• Korean Journal of Biological Psychiatry
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• v.10 no.1
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• pp.62-69
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• 2003

Corticotropin-releasing factor(CRF) and neuropeptide Y(NPY) are known to play important roles in mediating stress responses and stress-related behavior. To elucidate the role of neuropeptides in response to the condition that had paired with traumatic event, we observed the changes of CRF and NPY by immunohistochemistry using a conditioned footshock paradigm. Male Sprague-Dawley rats were placed in a shuttle box and exposed to 20 pairings of a tone(< 70dB, 5sec) followed by a footshock(FS, 0.8mA, 1sec) over 60min. A second group was exposed to the tone-footshock pairings, returned to the homecage for 2days, and then reexposed to the test chamber and 20tones alone for 60min, prior to sacrifice. Control groups were : a) sacrificed without exposure to FS ; b) exposed to the tone-footshock pairings and then sacrificed two days later ; or c) exposed to the chamber and tones alone, returned to the homecage for 2days and then reexposed to the chamber and 20tones over 60min prior to sacrifice. CRF was increased in animals exposed to FS or the aversive condition(context and tone) that had paired to FS in bed nucleus of the stria terminalis (BNST) compared to the control. NPY was increased by FS in amygdala and PVN, but the condition previously associated with FS results in slight increase only in amygdala area. These results suggest that the BNST appears to be the mostly involved neural circuit in response to explicit cues previously paired with footshock. Moreover, this study raise the possibility that increased CRF peptide in the BNST in response to re-exposure to the aversive condition may underlie, in part, the experience of conditioned fear-related anxiety behavior.

• Korean Journal of Psychosomatic Medicine
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• v.9 no.1
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• pp.81-92
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• 2001

Stress has been linked to the pathophysiology and pathogenesis of various psychiatric illnesses. Over the past few years, our understanding of the brain and neuroendocrine systems that are linked to stress responses has increased enormously. This article reviews a series of animal and human studies to understand what are the central pathways by which stress is perceived, processed, and transduced into a neuroendocrine response. We focus on the limbic-hypothalamic-pituitary-adrenal(LHPA) axis and several neurotransmitter systems such as norepinephrine, CRF, serotonin, acetylcholine, and dopamine. LHPA stress circuit is a complex system with multiple control mechanisms which are altered in pathological states. CRF and related peptides in the central nervous system appear to enhance behavioral responses to stressors. Norepinephrine systems are also activated by stressors and cause the release of catecholamines from the autonomic nervous system. CRF-norepinephrine interaction makes a feed-forward system which may be important for an organism to mobilize not only the pituitary system but also the central nervous system, in response to environmental challenges. The interactions among several neurotransmitters and endocrine systems appear to play key roles in mediating various behavioral and psychological stress responses involving abnormal responses to stressors such as anxiety and affective disorders.

• Korean Journal of Veterinary Research
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• v.36 no.1
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• pp.39-49
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• 1996

The present study was performed to investigate the distribution of neuropeptide Y immunoreactivities in the corpus striatum of the Korean squirrels. The animals were perfused with 4%-paraformaldehyde and the brain was cut serially into $40{\mu}m$ thick coronal sections. Sections either were stained with cresyl violet or were stained immunohistochemically. The corpus striatum was divided into the caudate nucleus, putamen and globus pallidus. Anterior part. however, of the striatum was observed as the combined caudate-putamen. NPY immunoreactive (NPY-IR) neurons were medium-sized. The corpus striatum contained a low level of NPY-IR fibers, whose distribution appeared to be related to the immunoreactive perikarya. Large numbers of NPY-IR neurons in the caudate-putamen and caudate nucleus were expressed in medial and ventral parts. In the anterior part of the putamen NPY-IR neurons were scattered throughout the nucleus; in posterior part were found generally in the lateral and ventral parts. The density of NPY-IR fibers of the putamen were low, whose distribution appeared to be related to the perikarya. The globus pallidus contained NPY-IR fibers only in the lowest density. In brief, NPY-immunoreactivities in the corpus striatum are heterogenous in distribution. These findings may reflect innate characteristics of the specific neural circuit in the corpus striatum itself.

• Molecules and Cells
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• v.41 no.12
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• pp.1061-1071
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• 2018

From Xenopus embryo studies, the BMP4/Smad1-targeted gene circuit is a key signaling pathway for specifying the cell fate between the ectoderm and neuro-ectoderm as well as the ventral and dorsal mesoderm. In this context, several BMP4/Smad1 target transcriptional factors have been identified as repressors of the neuro-ectoderm. However, none of these direct target transcription factors in this pathway, including GATA1b, Msx1 and Ventx1.1 have yet been proven as direct repressors of early neuro-ectodermal gene expression. In order to demonstrate that Ventx1.1 is a direct repressor of neuro-ectoderm genes, a genome-wide Xenopus ChIP-Seq of Ventx1.1 was performed. In this study, we demonstrated that Ventx1.1 bound to the Ventx1.1 response cis-acting element 1 and 2 (VRE1 and VRE2) on the promoter for zic3, which is a key early neuro-ectoderm gene, and this Ventx1.1 binding led to repression of zic3 transcription. Site-directed mutagenesis of VRE1 and VRE2 within zic3 promoter completely abolished the repression caused by Ventx1.1. In addition, we found both the positive and negative regulation of zic3 promoter activity by FoxD5b and Xcad2, respectively, and that these occur through the VREs and via modulation of Ventx1.1 levels. Taken together, the results demonstrate that the BMP4/Smad1 target gene, Ventx1.1, is a direct repressor of neuro-ectodermal gene zic3 during early Xenopus embryogenesis.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.299-306
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• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

• Journal of Life Science
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• v.22 no.4
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• pp.499-507
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• 2012

Previous work has characterized myomodulin A (MMA, PMSMLRLamide) and myomodulin E (MME, GLQMLRLamide) purified from the central nervous systems of the sea hare, $Aplysia$ $Kurodai$, using the anterior byssus retractor muscle (ABRM) of the mussel, $Mytilus$ $edulis$. The amino acid sequences of MMA and MME were the same as those of the myomodulin family peptide found in other mollusks. In this study, we synthesized MME, its derivatives, and other neuropeptides to investigate the relationship between the structure and biological activity of MME. The primary structures of MME's derivatives, Des[$Gly^1$]-MME, Des[$Gly^1,Leu^2$]-MME, and Des[$Gly^1,Leu^2,Gln^3$]-MME, were LQMLRLamide, QMLRLamide, and MLRLamide, respectively. MMA and synthetic peptides were tested on ABRM in $M.$ $edulis$ as well as muscle preparations in $Achatina$ $fulica$. MME displayed an inhibitory effect on phasic contraction of the ABRM at $1{\times}10^{-9}$ M or higher. MME also had a relaxing effect on the catch-tension of AMRM at $1{\times}10^{-8}$ M. Both MMA and its analogs stimulated a contractile response on the crop and relaxed the catch-relaxing response on the penial retractor muscle of $A.$ $fulica$. These results suggest that MME and its analogs have modulatory effects on various muscles of mollusks. This study has also laid the groundwork for future neural and circuit modulation studies during animal behavioral changes.