• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5A
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• pp.551-555
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• 2009

This study is performed to apply a standard to evaluate fire protection assessment for tunnel structures when a fire breaks out in the road tunnel. Recently, a number of road tunnels have been rapidly increased and fire risk also multiplyed according to extend tunnel length, due to natural features and environmentally-friendly road construction in Korea. But we have not yet been prescribed appropriate time-temperature curve for tunnel fire. Therefore, we presented fire design model and investigated time-temperature curve proposed by a foreign country considering traffic, a kinds of vehicles which are a basis of heat rate. At the end, Hydrocarbon modified curve applied as design fire model by using numerical analysis and presented design fire model and examined the effects of tunnel structures.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.958-963
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• 2023

Lately, there has been increasing research on the prediction of motion performance using artificial intelligence for the safe design and operation of ships. However, compared to conventional ships, research on small fishing boats is insufficient. In this paper, we propose a model that estimates the motion response essential for calculating the motion performance of small fishing boats using a deep neural network. Hydrodynamic analysis was conducted on 15 small fishing boats, and a database was established. Environmental conditions and main particulars were applied as input data, and the response amplitude operators were utilized as the output data. The motion response predicted by the trained deep neural network model showed similar trends to the hydrodynamic analysis results. The results showed that the high-frequency motion responses were predicted well with a low error. Based on this study, we plan to extend existing research by incorporating the hull shape characteristics of fishing boats into a deep neural network model.

• Journal of the Korean association of regional geographers
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• v.3 no.2
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• pp.151-162
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• 1997

Although modern versions of the traditional Von $Th{\ddot{u}}nen$ theory have contributed to a description of spatial organization in agriculture, they did not incorporate the market mechanism as an integral part of location theory. This deficiency has been indicated and new mathematical structure has been proposed elsewhere by the author. The closed model, which simultaneously considered a basic principle of supply and demand, exposed a computational complexity. Based on the problem, this study attempts to extend market mechanism in order to consider the influence of city (market) size in agricultural location theory. To theoretically explore the economic relationship in a location theory, this study simplifies agricultural activity as just two activities in one-dimensional spatial economy. The problem has been solved by equating total supply and demand of agricultural products, and then by determining each agricultural price from the relationship. All of the mathematical problems have been arranged in matrix form. First, the traditional model and closed model have been compared by quantitative comparative statics which provides the sensitivity test for each model. The results have shown that the traditional model shows a relatively excessive change in land use, besides the deficiency of a constant agricultural price. Second, the effects of the size of market town and its population increase were examined, using the closed model. In this case, the price of agricultural product is increased, and the land use is extended outward. This proves that locational rent is related to the expansion of land use. Third, environmental uncertainty was associated with the closed model, in order to further consider the difference of farmers attitude in strategic perspective. In this study, two extreme attitudes, which reflects the maximum average expected returns and the maximum guaranteed returns, were examined in their land use and their effects on the prices of agricultural products. It was shown that the two farmers attitudes can be interconnected with location theory. Due to the exogenous data, the differences in the area of land use and total quantities of agricultural products were not clearly shown in this study. However, it was shown that the land use pattern is very different. That is, maximum guaranteed return model reveals a mixed land use pattern around the market town. Basically, this study shows some spatial and economic implications related to Von $Th{\ddot{u}}nen$ model.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1037-1052
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• 2019

We had developed in preceding study a classification model for the Korean pine and Larch with an accuracy of 98 percent using Hyperion and Sentinel-2 satellite images, texture information, and geometric information as the first step for tree species mapping in the inaccessible North Korea. Considering a share of major tree species in North Korea, the classification model needs to be expanded as it has a large share of Oak(29.5%), Pine (12.7%), Fir (8.2%), and as well as Larch (17.5%) and Korean pine (5.8%). In order to classify 5 major tree species, national forest type map of South Korea was used to build 11,039 training and 2,330 validation data. Sentinel-2 data was used to derive spectral information, and PlanetScope data was used to generate texture information. Geometric information was built from SRTM DEM data. As a machine learning algorithm, Random forest was used. As a result, the overall accuracy of classification was 80% with 0.80 kappa statistics. Based on the training data and the classification model constructed through this study, we will extend the application to Mt. Baekdu and North and South Goseong areas to confirm the applicability of tree species classification on the Korean Peninsula.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.479-485
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• 2006

The double gate(DG) MOSFET is a promising candidate to further extend the CMOS scaling and provide better control of short channel effect(SCE). DGMOSFETs, having ultra thin undoped Si channel for SCEs control, ale being validated for sub-20nm scaling. A novel analytical transport model for the subthreshold mode of DGMOSFETs is proposed in this paper. The model enables analysis of short channel effect such as the subthreshold swing(SS), the threshold voltage roil-off$({\Delta}V_{th})$ and the drain induced barrier lowering(DIBL). The proposed model includes the effects of thermionic emission and quantum tunneling of carriers through the source-drain barrier. An approximative solution of the 2D Poisson equation is used for the distribution of electric potential, and Wentzel-Kramers-Brillouin approximation is used for the tunneling probability. The new model is used to investigate the subthreshold characteristics of a double gate MOSFET having the gate length in the nanometer range $(5-20{\sim}nm)$ with ultra thin gate oxide and channel thickness. The model is verified by comparing the subthreshold swing and the threshold voltage roll-off with 2D numerical simulations. The proposed model is used to design contours for gate length, channel thickness, and gate oxide thickness.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.140-146
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• 2021

As the environment using intelligent IoT devices increases, various studies are underway to ensure the integrity of information sent and received from intelligent IoT devices. However, all IoT information generated in heterogeneous environments is not fully provided with reliable protocols and services. In this paper, we propose an intelligent-based multi-blockchain model that can extract only critical information among various information processed by intelligent IoT devices. In the proposed model, blockchain is used to ensure the integrity of IoT information sent and received from IoT devices. The proposed model uses the correlation index of the collected information to trust a large number of IoT information to extract only the information with a high correlation index and bind it with blockchain. This is because the collected information can be extended to the n-tier structure as well as guaranteed reliability. Furthermore, since the proposed model can give weight information to the collection information based on blockchain, similar information can be selected (or bound) according to priority. The proposed model is able to extend the collection information to the n-layer structure while maintaining the data processing cost processed in real time regardless of the number of IoT devices.

• Smart Media Journal
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• v.12 no.11
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• pp.48-56
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• 2023

The technology of Three-dimensional human posture estimation is used in sports, motion recognition, and special effects of video media. Among various methods for this, multi-view 3D human pose estimation is essential for precise estimation even in complex real-world environments. But Existing models for multi-view 3D human posture estimation have the disadvantage of high order of time complexity as they use 3D feature maps. This paper proposes a method to extend an existing monocular viewpoint multi-frame model based on Transformer with lower time complexity to 3D human posture estimation for multi-viewpoints. To expand to multi-viewpoints our proposed method first generates an 8-dimensional joint coordinate that connects 2-dimensional joint coordinates for 17 joints at 4-vieiwpoints acquired using the 2-dimensional human posture detector, CPN(Cascaded Pyramid Network). This paper then converts them into 17×32 data with patch embedding, and enters the data into a transformer model, finally. Consequently, the MLP(Multi-Layer Perceptron) block that outputs the 3D-human posture simultaneously updates the 3D human posture estimation for 4-viewpoints at every iteration. Compared to Zheng[5]'s method the number of model parameters of the proposed method was 48.9%, MPJPE(Mean Per Joint Position Error) was reduced by 20.6 mm (43.8%) and the average learning time per epoch was more than 20 times faster.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.503-514
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• 2003

In conventional development methodologies, requirements are considered to be not changing after analysis phase, and requirements specifications are used for the next step system design purpose. But in the real world, requirements can be changed and modified throughout the development life cycle according to end-user's more understanding about the target system, new IT technologies, changes of customer environment and market situation, and so on. So there needs a requirements change management process that can extend requirements management over the entire development life cycle and can support managing changes to the requirements after design phase. In this paper, a requirements change management process that can be integrated into conventional development methodologies is proposed to support the extension of requirements life cycle and managing changes to the requirements after design phase. This process was evaluated through an verification test with a widely used development methodology‘MaRMI’.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.7
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• pp.469-477
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• 2009

In mobile systems, energy efficiency is critical to extend battery life. Therefore, power consumption should be taken into account to develop software in addition to performance, Efficient software design in power and performance is possible if accurate power prediction is accomplished during the execution of software, In this paper, power estimation model is developed using statistical analysis, The proposed model analyzes processor behavior Quantitatively using the data of performance monitoring events and power consumption collected by executing various benchmark programs, And then representative hardware events on power consumption are selected using hierarchical clustering, The power prediction model is established by regression analysis in which the selected events are independent variables and power is a response variable, The proposed model is applied to a PXA320 mobile processor based on Intel XScale architecture and shows average estimation error within 4% of the actual measured power consumption of the processor.

• Journal of Energy Engineering
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• v.11 no.2
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• pp.166-177
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• 2002

The present study is described of the flame structure of one-dimensional, flat, premixed, laminar, coal-air flame with some addition of methane for the flame stability. A low pressure burner operating at a combustion pressure of 0.3 arm was employed in order to extend the reaction zone. Predicted results from the models considered in the present study are compared with experimental results. Comparisons are included gas temperatures, species concentrations, char analysis and measured burning velocity. Among the models, Model II $I^{*}$-d, which specified devolatilization rate constants and a char surface area factor S=4, resulted in good agreement within the present experimental ranges. The results of char analysis suggest that the extent of the reaction occurring on the panicle might be underestimated in the model so that the char surface area should be increased. A value of 4 for this factor was given by sensitivity analysis of change in char surface area. Again, model II $I^{*}$-d gave satisfactory predictions of burning velocities over most of the experimental range studied. It has been clearly shown that the particle diameter appreciably affects the rates of devolatilisation and char oxidation through the effects of thermal lag and volumetric reactive surface area, consequently laminar burning velocity.ity.