• The Korean Journal of Pain
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• v.32 no.3
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• pp.168-177
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• 2019

Background: Brennan's rodent paw incision model has been extensively used for understanding mechanisms underlying postoperative pain in humans. However, alterations of physiological parameters like blood pressure and heart rate, or even feeding and drinking patterns after the incision have not been documented as yet. Moreover, though eicosanoids like prostaglandins and leukotrienes contribute to inflammation, tissue levels of these inflammatory mediators have never been studied. This work further investigates the antinociceptive effect of protein C after intra-wound administration. Methods: Separate groups of Sprague-Dawley rats were used for quantitation of cyclooxygenase (COX) activity and leukotriene B4 level by enzyme-linked immunosorbent assay, as well as estimation of cardiovascular parameters and feeding and drinking behavior after paw incision. In the next part, rats were subjected to incision and $10{\mu}g$ of protein C was locally administered by a micropipette. Both evoked and non-evoked pain parameters were then estimated. Results: COX, particularly COX-2 activity and leukotriene B4 levels increased after incision. Hemodynamic parameters were normal. Feeding and drinking were affected on days 1 and 3, and on day 1, respectively. Protein C attenuated non-evoked pain behavior alone up to day 2. Conclusions: Based upon current observations, Brennan's rodent paw incision model appears to exhibit a prolonged period of nociception similar to that after surgery, with minimal interference of physiological parameters. Protein C, which is likely converted to activated protein C in the wound, attenuated the guarding score, which probably represents pain at rest after surgery in humans.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.1
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• pp.1-9
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• 2019

In electric agricultural machine the gearbox is used to increase torque and lower the output speed of the motor shaft. The gearbox consists of several shafts, helical gears and spur gears works in series. Optimization plays an important role in gear design as reducing the weight or volume of a gear set will increase its service life and improve the bearing capacity. In this paper the basic design parameters for gear like shaft diameter and face width are considered as the input variables. The bending stress and material volume is considered as the objective function. ANSYS was used to investigate the bending stress when the variable was changed. Artificial Neural Network (ANN) was used to obtain the mathematical model of the system based on the bending stress behaviour. The ANN was used since the output system is nonlinear. The Genetic Algorithm (GA)　technique of optimization is used to obtain the optimized values of shaft diameter and face width on the pinion based on the ANN mathematical model and the results are compared as that obtained using the traditional method. The ANN and GA were performed using MATLAB. The simulation results were shown that the proposed algorithm was successfully calculated the value of shaft diameter and face width to obtain the minimal bending stress and material volume of the gearbox.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.201-207
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• 2023

In this paper, we propose an optimal model for mid to long-term price prediction of agricultural products using LGBM, MLP, LSTM, and GRU to compare and analyze the three strategies of the Multi-Step Time Series. The proposed model is designed to find the optimal combination between the models by selecting methods from various angles. Prior agricultural product price prediction studies have mainly adopted traditional econometric models such as ARIMA and LSTM-type models. In contrast, agricultural product price prediction studies related to Multi-Step Time Series were minimal. In this study, the experiment was conducted by dividing it into two periods according to the degree of volatility of agricultural product prices. As a result of the mid-to-long-term price prediction of three strategies, namely direct, hybrid, and multiple outputs, the hybrid approach showed relatively superior performance. This study academically and practically contributes to mid-to-long term daily price prediction by proposing an effective alternative.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.403-411
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• 2013

Horizontal construction projects such as oil and gas pipeline projects typically involve repetitive-work activities with the same crew and equipment from one end of the project to the other. Repetitive scheduling also known as linear scheduling is known to have superior schedule management capabilities specifically for such horizontal construction projects. This study discusses on expanding the capabilities of repetitive scheduling to account for the variance in production rates and visual representation by developing an automated alignment based linear scheduling program for applying temporal and spatial changes in production rates. The study outlines a framework to apply changes in productions rates when and where they will occur along the horizontal alignment of the project and illustrates the complexity of construction through the time-location chart through a new linear scheduling model, Linear Scheduling Model with Varying Production Rates (LSM_VPR). The program uses empirically derived production rate equations with appropriate variables as an input at the appropriate time and location based on actual 750 mile natural gas liquids pipeline project starting in Wyoming and terminating in the center of Kansas. The study showed that the changes in production rates due to time and location resulted in a close approximation of the actual progress of work as compared to the planned progress and can be modeled for use in predicting future linear construction projects. LSM_VPR allows the scheduler to develop schedule durations based on minimal project information. The model also allows the scheduler to analyze the impact of various routes or start dates for construction and the corresponding impact on the schedule. In addition, the graphical format lets the construction team to visualize the obstacles in the project when and where they occur due to a new feature called the Activity Performance Index (API). This index is used to shade the linear scheduling chart by time and location with the variation in color indicating the variance in predicted production rate from the desired production rate.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.9-18
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• 2024

Small streams, despite their rich ecosystems, face challenges in vegetation assessment due to the limitations of traditional, time-consuming methods. This study presents a groundbreaking approach, combining unmanned aerial vehicles(UAVs), convolutional neural networks(CNNs), and the vegetation differential vegetation index (VDVI), to revolutionize both assessment and management of stream vegetation. Focusing on Idong Stream in South Korea (2.7 km long, 2.34 km² basin area)with eight diverse revetment methods, we leveraged high-resolution RGB images captured by UAVs across five dates (July-December). These images trained a ResNeXt101 CNN model, achieving an impressive 89% accuracy in classifying vegetation cover(soil,water, and vegetation). This enabled detailed spatial and temporal analysis of vegetation distribution. Further, VDVI calculations on classified vegetation areas allowed assessment of vegetation vitality. Our key findings showcase the power of this approach:(a) TheCNN model generated highly accurate cover maps, facilitating precise monitoring of vegetation changes overtime and space. (b) August displayed the highest average VDVI(0.24), indicating peak vegetation growth crucial for stabilizing streambanks and resisting flow. (c) Different revetment methods impacted vegetation vitality. Fieldstone sections exhibited initial high vitality followed by decline due to leaf browning. Block-type sections and the control group showed a gradual decline after peak growth. Interestingly, the "H environment block" exhibited minimal change, suggesting potential benefits for specific ecological functions.(d) Despite initial differences, all sections converged in vegetation distribution trends after 15 years due to the influence of surrounding vegetation. This study demonstrates the immense potential of UAV-based remote sensing and CNNs for revolutionizing small-stream vegetation assessment and management. By providing high-resolution, temporally detailed data, this approach offers distinct advantages over traditional methods, ultimately benefiting both the environment and surrounding communities through informed decision-making for improved stream health and ecological conservation.

• Ocean and Polar Research
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• v.39 no.1
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• pp.13-21
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• 2017

Temporal changes in the number of zooplankton species are important information for understanding basic characteristics and species diversity in marine ecosystems. The aim of the present study was to estimate the optimal monitoring frequency (OMF) to guarantee and predict the minimum number of species occurrences for studies concerning marine ecosystems. The OMF is estimated using the temporal number of zooplankton species through bi-weekly monitoring of zooplankton species data according to operational taxonomic units in the Tongyoung coastal sea. The optimal model comprises two terms, a constant (optimal mean) and a cosine function with a one-year period. The confidence interval (CI) range of the model with monitoring frequency was estimated using a bootstrap method. The CI range was used as a reference to estimate the optimal monitoring frequency. In general, the minimum monitoring frequency (numbers per year) directly depends on the target (acceptable) estimation error. When the acceptable error (range of the CI) increases, the monitoring frequency decreases because the large acceptable error signals a rough estimation. If the acceptable error (unit: number value) of the number of the zooplankton species is set to 3, the minimum monitoring frequency (times per year) is 24. The residual distribution of the model followed a normal distribution. This model can be applied for the estimation of the minimal monitoring frequency that satisfies the target error bounds, as this model provides an estimation of the error of the zooplankton species numbers with monitoring frequencies.

• Journal of Internet Computing and Services
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• v.7 no.2
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• pp.23-35
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• 2006

This work presents o novel method which extract facial region und features from motion picture automatically and controls the 3D facial expression in real time. To txtract facial region and facial feature points from each color frame of motion pictures a new nonparametric skin color model is proposed rather than using parametric skin color model. Conventionally used parametric skin color models, which presents facial distribution as gaussian-type, have lack of robustness for varying lighting conditions. Thus it needs additional work to extract exact facial region from face images. To resolve the limitation of current skin color model, we exploit the Hue-Tint chrominance components and represent the skin chrominance distribution as a linear function, which can reduce error for detecting facial region. Moreover, the minimal facial feature positions detected by the proposed skin model are adjusted by using edge information of the detected facial region along with the proportions of the face. To produce the realistic facial expression, we adopt Water's linear muscle model and apply the extended version of Water's muscles to variation of the facial features of the 3D face. The experiments show that the proposed approach efficiently detects facial feature points and naturally controls the facial expression of the 3D face model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5B
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• pp.889-898
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• 2000

In order to support various broadband multimedia servies in the future, we designed a well balanced WDM backbone network. In Korean network traffic environment, six regional centers are selected, link capacities between the regional centers are estimated from the PDI traffic model, and the overall network configuration is designed for the all-optical backbone network. Also, we designed a basic configuration to be able to protect minimum communication capability against link failure. A simulation study is carried out to verify the desired performance of the designed WDM backbone network. Simulation results show that performance of the backbone network is well balanced to support various communication services in Korea in the mid 2000s

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.152-160
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• 2012

This paper proposes a frame-level rate control algorithm for low delay video applications to reduce the fluctuations in the bitrate. The proposed algorithm minimizes the bitrate fluctuations in two ways with minimal coding loss. First, the proposed rate control applies R-Q model to all frames including the first frame of every group of pictures (GOP) except for the first one of a sequence. Conventional rate control algorithms do not use any R-Q models for the first frame of each GOP and do not estimate the generated-bit. An unexpected output rate result from the first frame affects the remainder of the pictures in the rate control. Second, a rate-distortion (R-D) cost is calculated regardless of the hierarchical coding structure for low bitrate fluctuations because the hierarchical coding structure controls the output bitrate in rate distortion optimization (RDO) process. The experimental results show that the average variance of per-frame bits with the proposed algorithm can reduce by approximately 33.8% with a delta peak signal-to-noise ratio (PSNR) degradation of 1.4dB for a "low-delay B" coding structure and by approximately 35.7% with a delta-PSNR degradation of 1.3dB for a "low-delay P" coding structure, compared to HM 8.0 rate control.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.377-391
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• 1997

We consider the characterized curriculum of industrial engineering for training the excellent technician. We classified many kinds of jobs in the industry and information society and compared them with the curriculums of 13 junior colleges sampled randomly. Also we inquired the degree of relation of the technique qualification for graduates from industrial engineering to the current major subjects. For fostering the cultured individuals the community demands, we amended and looked into the current liberal arts course to supplement it. We analyzed the opinions of students, professors and experts from various circles through questionnaires, and then we set up the direction and the priority order for developing the curriculum for training the technician. According to the analyzed results, we presented the curriculum centering around customers and demanders and introduced it in detail. We are going to utilize developed curriculum, teaching methods by computers and practice methods step by step, and make expansion to industrial engineering of other colleges. Then we are planning to apply to the reeducation for graduates and the social education that contains the industrial human resources and the ordinary persons.