• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.3-8
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• 1999

Previous variable vocabulary speech recognition systems with context-independent acoustic modeling, could not represent the effect of neighboring phonemes. To solve this problem, we use allophone-based context-dependent acoustic model. This paper describes the method to improve acoustic model of the system effectively. Acoustic model is improved by using allophone clustering technique that uses entropy as a similarity measure and the optimal allophone model is generated by changing the number of allophones. We evaluate performance of the improved system by using Phonetically Optimized Words(POW) DB and PC commands(PC) DB. As a result, the allophone model composed of six hundreds allophones improved the recognition rate by 13% from the original context independent model m POW test DB.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.5
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• pp.1-10
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• 2007

In this paper, we proposed development of improved model reduction and design of common controller using reduction model. The Algorithm of improved model reduction considered the transient response and the steady-state response in response curve. The generalized controller is designed not only to ensure specified phase margin and iso-damping property also optimized smith-predictor controller about real model using reduction model. Simulation examples are given to show the better performance of the proposed method than convention methods.

• Structural Engineering and Mechanics
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• v.70 no.2
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• pp.209-219
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• 2019

By normalizing the internal hysteresis variable and eliminating the redundant parameter, the normalized Bouc-Wen model is considered to be an improved and more reasonable form of the Bouc-Wen model. In order to facilitate application and further research of the normalized Bouc-Wen model, some key aspects of the model need to be uncovered. In this paper, hysteresis characterization of the normalized Bouc-Wen model is first studied with respect to the model parameters, which reveals the influence of each model parameter to the shape of the hysteresis loops. The parameter identification scheme is then proposed based on an improved genetic algorithm (IGA), and verified by experimental test data. It is proved that the proposed method can be an efficacious tool for identification of the model parameters by matching the reconstructed hysteresis loops with the target hysteresis loops. Meanwhile, the IGA is shown to outperform the standard GA. Finally, a simplified identification method is proposed based on parameter sensitivity, which indicates that the efficiency of the identification process can be greatly enhanced while maintaining comparable accuracy if the low-sensitivity parameters are reasonably restricted to narrower ranges.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2075-2080
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• 2013

A Coolant core for Range Extender engine has been developed using CFD technique. Coolant by-pass has been added to the improved model to reduce temperature near and between exhaust valve. Due to the increased coolant flow-rate both around the second cylinder block and between exhaust valves, improved model shows no significant stagnant flow compared with base model. Finally, the improved model shows improved heat transfer coefficients near exhaust valves, and 5% reduced pressure-drop through the coolant core. Reduced pressure-drop may increase the fuel efficiency by reducing the load of a coolant pump.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.2
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• pp.97-102
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• 2020

To prevent vibration of a vehicle's interior parts due to external impacts, the vehicle should be designed to reduce vibration and increase rigidity. In this paper, we conducted a vehicle test in which the vibration characteristics of a seatbelt resulting from the impact of a person closing a car door were measured and analyzed. A correlation analysis was performed using the finite analysis method. Based on this, a sensitivity analysis was performed, and an improved model was designed. We compared the natural frequencies and mode shapes of the improved and the initial models, which confirmed that the natural frequency of the improved model was more than 10 Hz higher than that of the initial model. Moreover, the response frequency of the improved model was three times higher than the input frequency applied in the vehicle test.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.625-627
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• 2022

In the construction and development of modern industrial production technology, the traditional technology management mode is faced with many problems such as low qualification rates and high application costs. In the research, an improved workpiece defect detection method based on deep learning is proposed, which can control the application cost and improve the detection efficiency of irregular defects. Based on the research of the current situation of deep learning applications, this paper uses the improved Faster R-CNN network structure model as the core detection algorithm to automatically locate and classify the defect areas of the workpiece. Firstly, the robustness of the model was improved by appropriately changing the depth and the number of channels of the backbone network, and the hyperparameters of the improved model were adjusted. Then the deformable convolution is added to improve the detection ability of irregular defects. The final experimental results show that this method's average detection accuracy (mAP) is 4.5% higher than that of other methods. The model with anchor size and aspect ratio (65,129,257,519) and (0.2,0.5,1,1) has the highest defect recognition rate, and the detection accuracy reaches 93.88%.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.399-404
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• 2012

Evolutionary algorithms such as genetic algorithm (GA) have been proven their effectiveness when applying to the design of fuzzy models. However, it tends to suffer from computationally expensWive due to the slow convergence speed. In this study, we propose an approach to develop fuzzy models by means of an improved differential evolution (IDE) to overcome this limitation. The improved differential evolution (IDE) is realized by means of an orthogonal approach and differential evolution. With the invoking orthogonal method, the IDE can search the solution space more efficiently. In the design of fuzzy models, we concern two mechanisms, namely structure identification and parameter estimation. The structure identification is supported by the IDE and C-Means while the parameter estimation is realized via IDE and a standard least square error method. Experimental studies demonstrate that the proposed model leads to improved performance. The proposed model is also contrasted with the quality of some fuzzy models already reported in the literature.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.450-464
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• 2023

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.10
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• pp.2787-2796
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• 1994

The modeling of combustion process is an important part in an engine simulation program. In this study, calculated results using a conventional B-K model and the other model which is called GESIM were compared with experimentally measured data of a three-cylinder spark-ignition engine under wide range of operating conditions. The burn rates calculated from the combustion models were compared with the burn rate calculated from the one-zone heat release analysis that uses measured pressure data as an input data. As a result of the two models' comparison, the GESIM combustion model conformed to be closer to the data acquired from the experiment in wide operating ranges. The GESIM model has been improved by introducing a variable that considers the flame size, the area of flame conacting the piston surface into the model, based on the comparison between the experimental result and the calculated results. The improved combustion model predicts experimental results more precisely than that of GESIM combustion model.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1309-1323
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• 2020

Crowd evacuation simulation is an important research issue for designing reasonable building layouts and planning more effective evacuation routes. The social force model (SFM) is an important pedestrian movement model, and is widely used in crowd evacuation simulations. The model can effectively simulate crowd evacuation behaviors in a simple scene, but for a multi-obstacle scene, the model could result in some undesirable problems, such as pedestrian evacuation trajectory oscillation, pedestrian stagnation and poor evacuation routing. This paper analyzes the causes of these problems and proposes an improved SFM for complex multi-obstacle scenes. The new model adds navigation points and walking shortest route principles to the SFM. Based on the proposed model, a crowd evacuation simulation system is developed, and the crowd evacuation simulation was carried out in various scenes, including some with simple obstacles, as well as those with multi-obstacles. Experiments show that the pedestrians in the proposed model can effectively bypass obstacles and plan reasonable evacuation routes.