• Journal of Environmental Impact Assessment
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• v.14 no.6
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• pp.387-402
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• 2005

In this study, we tried to predict the change of future land-cover and relationships between land-cover change and geo-spatial information in the Gongju area by using fuzzy logic operation. Quantitative evaluation of prediction models was carried out using a prediction rate curve using. Based on the analysis of correlations between the geo-spatial information and land-cover change, the class with the highest correlation was extracted. Fuzzy operations were used to predict land-cover change and determine the land-cover prediction maps that were the most suitable. It was predicted that in urban areas, the urban expansion of old and new towns would occur centering on the Gem-river, and that urbanization of areas along the interchange and national roads would also expand. Among agricultural areas, areas adjacent to national roads connected to small tributaries of the Gem-river and neighboring areas would likely experience changes. Most of the forest areas are located in southeast and from this result we can guess why the wide chestnut-tree cultivation complex is located in these areas and the possibility of forest damage is very high. As a result of validation using the prediction rate curve, it was indicated that among fuzzy operators, the maximum fuzzy operator was the most suitable for analyzing land-cover change in urban and agricultural areas. Other fuzzy operators resulted in the similar prediction capabilities. However, in the prediction rate curve of integrated models for land-cover prediction in the forest areas, most fuzzy operators resulted in poorer prediction capabilities. Thus, it is necessary to apply new thematic maps or prediction models in connection with the effective prediction of changes in the forest areas.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.1-17
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• 2002

In this paper, we present our experiences in using symbolic model checker(SMV) to analyze a number of properties of RACE cache coherence protocol designed by ETRI(Electronics and Communications Research Institute) and to verify that RACE protocol satisfies important requirements. To investigate this, we specified the model of the RACE protocol as the input language of SMV and specified properties as a formula in temporal logic CTL. We successfully used the symbolic model checker to analyze a number of properties of RACE protocol. We verified that abnormal state/input combinations was not occurred and every possible request of processors was executed correctly We verified that RACE protocol satisfies liveness, safety and the property that any abnormal state/input combination was never occurred. Besides, We found some ambiguities of the specification and a case of starvation that the protocol designers could not expect before. By this verification experience, we show advantages of model checking method. And, we propose a new method to generate automatically test cases which are used in simulation and testing.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.37-47
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• 2016

The practical constraints on the commercial FPGAs which contain dedicated wide function multiplexers in their slice structure are incorporated with one of the most advanced FPGA mapping algorithms based on the AIG (And-Inverter Graph), one of the best logic representations in academia. As the first step of the mapping process, cuts are enumerated as intermediate structures. And then, the cuts which can be mapped to the multiplexers are recognized. Without any increased complexity, the delay and area of multiplexers as well as LUTs are calculated after checking the requirements for the tree construction such as symmetry and depth limit against dynamically changing mapping of neighboring nodes. Besides, the root positions of multiplexer trees are identified from the RTL code, and annotated to the AIG as AOs (Auxiliary Outputs). A new AIG embedding the multiplexer tree structures which are intentionally synthesized by Shannon expansion at the AOs, is overlapped with the optimized AIG. The lossless synthesis technique which employs FRAIG (Functionally Reduced AIG) is applied to this approach. The proposed approach and techniques are validated by implementing and applying them to two RISC processor examples, which yielded 13~30% area reduction, and up to 32% delay reduction. The research will be extended to take into account the constraints on the dedicated hardware for carry chains.

• Journal of the military operations research society of Korea
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• v.37 no.1
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• pp.87-97
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• 2011

In this paper, we propose a new close combat expert system to overcome the difference of combat damage assessments between combat units belong to their own model in Combined Arms Integrated Interoperability System(CAIIS) which will be deployed in the early future. When it happens to engage in a battle among combat units belong to their own model in CAIIS, the result of damage assessment is different severely. This is related to CAIIS's confidence and need to be overcome. We propose the expert system for close combat damage assessment with a decision tree. Simulation results show that the proposed expert system is valid well. Because the proposed expert system is made not as an independent system but as an inner module type of CAIIS, CAIIS will be simpler system than we expect. And we will hope to reduce the cost of CAIIS.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.53-59
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• 2008

Recently, vision-based hand gesture recognition techniques have been developed for assisting elderly and disabled people to control home appliances. Frequently occurred problems which lower the hand gesture recognition rate are due to the inter-person variation and intra-person variation. The recognition difficulty caused by inter-person variation can be handled by using user dependent model and model selection technique. And the recognition difficulty caused by intra-person variation can be handled by using fuzzy logic. In this paper, we propose multivariate fuzzy decision tree learning and classification method for a hand motion recognition system for multiple users. When a user starts to use the system, the most appropriate recognition model is selected and used for the user.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.11
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• pp.135-143
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• 1990

A new over-the-cell routing system is proposed in this paper. The proposed system efficiently reduces not only the channel density but also the routing density in cell region. Generally, the over-the-cell system consists of three phases. Namely, over-the-cell routing, terminal selection and channel routing. In this paper, to select the nets to be routed over the cells, weights are assigned on the intersection graph considering both the channel density and the intersection relations among other nets. When selected nets are blocked by feedthroughs or metal layers for internal logic, they are routed by maze algorithm. Also, in order to reduce channel density, the terminals to be routed in a channel are selected using the minimum weight spanning tree. Channel routing is carried out with a channel router of HAN-LACAD_G. The effectiveness of the over-the-cell routing system is shown by the experiments with benchmark data and its application to the gate array layout system.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.9-21
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• 2023

The recent conflict between Russia and Ukraine underscores the significant of military logistics support in modern warfare. Military logistics support is intricate and specialized, and traditionally centered on the mission-level operational analysis and functional models. Nevertheless, there is currently increasing demand for military logistics support even at the engagement level, especially for resupply using unmanned transport assets. In response to the demand, this study proposes a task model of the military logistics support for engagement-level analysis that relies on the logic of ammunition resupply below the battalion level. The model employs a decisions tree to establish the priority of resupply based on variables such as the enemy's level of threat and the remaining ammunition of the supported unit. The model's feasibility is demonstrated through a combat simulation using OneSAF.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.43-58
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• 2014

As the use of trading systems has increased rapidly, many researchers have become interested in developing effective stock market prediction models using artificial intelligence techniques. Stock market prediction involves multifaceted interactions between market-controlling factors and unknown random processes. A successful stock prediction model achieves the most accurate result from minimum input data with the least complex model. In this research, we develop a combination model of ${\pi}$-fuzzy logic and support vector machine (SVM) models, using a genetic algorithm to optimize the parameters of the SVM and ${\pi}$-fuzzy functions, as well as feature subset selection to improve the performance of stock market prediction. To evaluate the performance of our proposed model, we compare the performance of our model to other comparative models, including the logistic regression, multiple discriminant analysis, classification and regression tree, artificial neural network, SVM, and fuzzy SVM models, with the same data. The results show that our model outperforms all other comparative models in prediction accuracy as well as return on investment.

• Earthquakes and Structures
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• v.10 no.2
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• pp.389-408
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• 2016

Recently, seismic hazard analysis has become a very significant issue. New systems and available data have been also developed that could help scientists to explain the earthquakes phenomena and its physics. Scientists have begun to accept the role of uncertainty in earthquake issues and seismic hazard analysis. However, handling the existing uncertainty is still an important problem and lack of data causes difficulties in precisely quantifying uncertainty. Ground Motion Prediction Equation (GMPE) values are usually obtained in a statistical method: regression analysis. Each of these GMPEs uses the preliminary data of the selected earthquake. In this paper, a new fuzzy method was proposed to select suitable GMPE at every intensity (earthquake magnitude) and distance (site distance to fault) according to preliminary data aggregation in their area using ${\alpha}$ cut. The results showed that the use of this method as a GMPE could make a significant difference in probabilistic seismic hazard analysis (PSHA) results instead of selecting one equation or using logic tree. Also, a practical example of this new method was described in Iran as one of the world's earthquake-prone areas.

• Structural Engineering and Mechanics
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• v.32 no.4
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• pp.563-581
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• 2009

In this paper, the peak horizontal ground acceleration over the bedrock (PGA) is calculated by a probabilistic seismic hazard assessment (PSHA). For this reason, at first, all the occurred earthquakes in a radius of 200 km of Sanandaj city have been gathered. After elimination of the aftershocks and foreshocks, the main earthquakes were taken into consideration to calculate the seismic parameters (SP) by Kijko (2000) method. The seismotectonic model of the considered region and the seismic sources of the region have been modeled. In this research, Sanandaj and its vicinity has been meshed as an 8 (vertical lines) * 10 (horizontal lines) and the PGA is calculated for each point of the mesh using the logic tree method and the five attenuation relationships (AR) with different weighted coefficient. These calculations have been performed by the Poisson distribution of four hazard levels. Then by using it, four regional maps of the seismic hazard regions have been provided for Sanandaj and its vicinity. The results show that the maximum and minimum value of PGA for the return periods of 75, 225, 475, 2475 years are (0.114, 0.074) (0.157, 0.101), (0.189, 0.121) and (0.266, 0.170), respectively.