• Advances in Traditional Medicine
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• v.7 no.5
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• pp.459-465
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• 2008

The present study was undertaken to investigate the effect of in vivo administration of neem oil intra-peritoneally (i.p.) to mice bearing a progressively growing transplantable T cell lymphoma of spontaneous origin, designated as Daltons lymphoma (DL), on the tumor growth. Mice were administered various doses of neem oil mixed in groundnut oil, which was used as a diluting vehicle or for administration to control DL-bearing mice. Administration of neem oil resulted in an acceleration of tumor growth along with a reduction in the survival time of the tumor-bearing host. Neem oil administered DL-bearing mice showed an augmented apoptosis in splenocytes, bone marrow cells and thymocytes along with an inhibition in the anti-tumor functions of tumor-associated macrophages. Thus this study gives an altogether a novel information that neem oil instead of the popular belief of being anti-tumor and immunoaugmentary may in some tumor-bearing conditions, behave in an opposite way leading to an accelarated tumor progression along with a collapse of the host's anti-tumor machinery. These observations will thus have long lasting clinical significance, suggesting caution in use of neem oil for treatment of cancer.

• Journal of Korean Society for Quality Management
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• v.43 no.3
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• pp.221-238
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• 2015

Purpose: In this study, A reliability assurance model (or reliability program) is proposed to evaluate the reliability of an armed vehicle. The reliability assurance is performed through the reliability-centered activities during its life cycle of development/design, production, deployment, maintenance, and disposal. Methods: By reflecting the current situations of korea defense industry, a reliability assurance model is built up based on the benchmarking results of world leading companies' best practices in same fields. Results: The proposed reliability program of armed vehicles, which is based on the reliability program of ANSI/GEIA-STD 0009, uses DMAIC process of the six sigma methodology from design phase to testing and evaluation phase. Conclusion: This research is supposed to develop reliability program of armed vehicles by integrating DFSS, DFR and reliability growth process.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.10
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• pp.97-107
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• 2009

Recent technologies of the car are focused on improving vehicle's fuel efficiency and developing alternative energy sources. These technologies bring on the development of hybrid car. On the other hand, because of short driving distance, low efficiency of charging and high price, energy storage system need to improve the storage capability. It is very important to understand the existing technologies, grasp the existing patent and establish the technical target to improve the energy storage system. In this paper, technology trends of energy storage system of the hybrid car are analyzed. This study was based on the applied and registered patent in Korea, Japan, U.S.A and Europe until December 2008. The analyses are divided into two categories: a battery system and charging system of the hybrid car. The facts of the level of technology, trends of the R&D of leading companies, key patents, blank of the technology were analyzed. Finally the future R&D strategy of hybrid car are established.

• Korean Parent-Child Health Journal
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• v.10 no.1
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• pp.77-90
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• 2007

Purpose: Motor vehicle crashes are the leading cause of death among children younger than 14 years old. The purposes of this study were to 1) provide a basic overview of child safety seats, 2) review car seat safety usage and misuse, 3) suggest interventions to motivate the usage of child safety seats. Method: The design was a descriptive study with literature review. Previous studies were searched of PUBMED, ProQuest and KERIS. Result: Child safety seats and automobile safety belts protect children in a crash if they are used correctly, but if a child does not fit in the restraint correctly, it can lead to injury. A child safety seat should be used until the child correctly fits into an adult seat belt. Conclusion: To improve child passenger's safety, educational, legislational and environmental enforcements are needed: educational interventions to promote use of child safety seats, strengtened legislation to mandate use of child safety seats, establishment of public acquirements.

• Journal of the Korean Society of Safety
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• v.22 no.1 s.79
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• pp.61-66
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• 2007

Car crashes are the leading cause of death for persons of every age. Specially, human-related factor has been known to be the primary causal factor of such crashes than vehicle-and environmental-related factors. There are various studies to analyze driver's behavior and characteristics in driving for reducing the car crashes in many areas of car engineering, psychology, human factor, etc. However, there are almost no studies which analyze mainly the human errors in driving and estimate their probabilities in terms of human reliability analysis. This study estimates the probability of human error in driving, i.e. driver error probability. First, fifty driver errors are investigated through DBQ (Driver Behavior Questionnaire) revision and the error likelihoods in driving are collected which are judged by skillful drivers using revised DBQ. Next, these likelihoods are converted into driver error probabilities using the results that verbal probabilistic expressions are changed into quantitative probabilities. Using these probabilities we can improve the warning effects on drivers by indicating their driving error likelihoods quantitatively. We can also expect the reduction effects of car accident through controlling especially dangerous error groups which have higher probabilities. Like these, the results of this study can be used as the primary materials of safety education on drivers.

• Journal of the Korean Society of Safety
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• v.24 no.4
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• pp.104-110
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• 2009

In this driving simulation study, the impairing effects of various types of electronic devices usage(i. e., destination search by using in-vehicle navigation system, TV watching and dialing cellular phone) during driving on front-to-rear-end collision avoidance were investigated. Percentage of collisions, driving speeds when the drivers collided, and initial reaction time for collision avoidance were analyzed and compared as the dependent measures. The results indicated that (1) any types of electronic devices usage during driving induced more serious collision-related impairment than control condition where no additional task was required, and (2) in general, destination search task appeared to impair drivers collision avoidance performance more than the other task requirements in terms of percentage of collisions and initial reaction time for collision avoidance, but TV watching induced most serious collision impact. These results suggested that any types of electronic device usage could distract drivers attention from the primary task of driving, and be resulted in serious outcome in potentially risky situation of front-to-rear-end collision. In particular, mandatory use of eye-hand coordination and receiving feedback seemed to one of essential factor leading the drivers visual attentional distraction.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.719-731
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• 2021

This study proposes a two-stage hybrid classification model for crop classification using multi-temporal remote sensing images; the model combines feature embedding by using an autoencoder (AE) with a convolutional neural network (CNN) classifier to fully utilize features including informative temporal and spatial signatures. Long short-term memory (LSTM)-based AE (LAE) is fine-tuned using class label information to extract latent features that contain less noise and useful temporal signatures. The CNN classifier is then applied to effectively account for the spatial characteristics of the extracted latent features. A crop classification experiment with multi-temporal unmanned aerial vehicle images is conducted to illustrate the potential application of the proposed hybrid model. The classification performance of the proposed model is compared with various combinations of conventional deep learning models (CNN, LSTM, and convolutional LSTM) and different inputs (original multi-temporal images and features from stacked AE). From the crop classification experiment, the best classification accuracy was achieved by the proposed model that utilized the latent features by fine-tuned LAE as input for the CNN classifier. The latent features that contain useful temporal signatures and are less noisy could increase the class separability between crops with similar spectral signatures, thereby leading to superior classification accuracy. The experimental results demonstrate the importance of effective feature extraction and the potential of the proposed classification model for crop classification using multi-temporal remote sensing images.

• Journal of Drive and Control
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• v.19 no.1
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• pp.62-68
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• 2022

Considering the characteristics of industrial machines that lack vehicle-induced wind, forced convection by a cooling fan is mostly required. Therefore, numerical analysis of an engine room is usually performed to examine the cooling performance in the room. However, most engine rooms consist of a number of parts and components at specific positions, leading to high costs for numerical modeling and simulation. In this paper, a new methodology for three-dimensional computer-assisted design simplification was proposed, especially for the pile of components and parts at the engine room outlet. A porous media model and regression analysis were used to derive a meta-model for imitating the flow rate reduction at the outlet by the pile. The results showed that the fitted model was reasonable considering the coefficient of determination. The final numerical model of the engine room was then used to simulate the velocity distribution by changing the mass flow rate at the outlet. The results showed that both velocity distributions were significantly changed in each case and the meta-model was valid in imitating the flow rate reduction by some piles of components and parts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.1996-2015
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• 2023

High-definition (HD) maps can provide precise road information that enables an autonomous driving system to effectively navigate a vehicle. Recent research has focused on leveraging semantic segmentation to achieve automatic annotation of HD maps. However, the existing methods suffer from low recognition accuracy in automatic driving scenarios, leading to inefficient annotation processes. In this paper, we propose a novel semantic segmentation method for automatic HD map annotation. Our approach introduces a new encoder, known as the convolutional transformer hybrid encoder, to enhance the model's feature extraction capabilities. Additionally, we propose a multi-level fusion module that enables the model to aggregate different levels of detail and semantic information. Furthermore, we present a novel decoupled boundary joint decoder to improve the model's ability to handle the boundary between categories. To evaluate our method, we conducted experiments using the Bird's Eye View point cloud images dataset and Cityscapes dataset. Comparative analysis against stateof-the-art methods demonstrates that our model achieves the highest performance. Specifically, our model achieves an mIoU of 56.26%, surpassing the results of SegFormer with an mIoU of 1.47%. This innovative promises to significantly enhance the efficiency of HD map automatic annotation.

• The Journal of Economics, Marketing and Management
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• v.5 no.3
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• pp.1-11
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• 2017

E-infrastructural economy for ICT Living-Labs is a need for economic and cultural changes in various types of cars in accordance with the supply of the electric car. Depending on the number of cases by analyzing the supply and demand of electric vehicles among Korea and Northern Europe countries. it was indirectly proved that it makes economic growth. The research design is analyzed with the data and how to respond quickly to focus on the possibility of potential changes to the infrastructure realization and commercialization of government enterprises or electric cars through the ICT Living-Labs in Nordic countries. The data indicates that the leading commercialization emphasize on the development of the electric economic convergence and scalability for electric vehicle. When It shows the time of the infrastructure as ICT Living-Labs being delayed, it lowered growth target results for the development of the electric car industry in the future. All this is from the reason of opening the E-convergence economy over time. It is required that Korea should prepare E-convergence economy. Public regional energy should be present through the consistent selection of development for energy linking E-economy and E-trans distribution. Korea needs to be many difficulties in building the E- infrastructure for ICT Living-Labs. Unlike the Northern Europe it is to prepare the active support of both government and business. The role of the government discovers that the power generation through the quick selection of the industry, as well as to connect with the growth of the smart cities with the EVs industry.