• Journal of Advanced Navigation Technology
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• v.15 no.6
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• pp.1187-1193
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• 2011

In this paper, proposed controller preventing compressor surge and reducing the acceleration time of the fuel flow control system for turbo-jet engine. Turbo-jet engine controller is designed by applying fuzzy PID control algorithm and high-gain observer. Observer is used to estimate to compressor rotation speed of turbo-jet engine. Result of fuzzy inference is used as the fuel flow control inputs for preventing compressor surge and flame-out in turbo-jet engine. The controller is designed to converge to the desired speed quickly and safely. Using MATLAB to perform computer simulations verified the performance of the proposed controller.

• The KIPS Transactions:PartD
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• v.11D no.7 s.96
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• pp.1527-1536
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• 2004

For using the knowledge of experts diversely and efficiently, it is very important that the system could represent the complex knowledge in well structured manner and also adapt well to the frequent schema changes. In this paper, we propose an efficient method for knowledge base management by using XML based templates. In our proposed method, to solve the inefficiency of management of many XML documents, we represent the complex knowledge on XML-based templates, and manage the templates structurally by using a meta-template that defines relationship among the templates. In order to show the effectiveness of our method, we developed a knowledge base to formulate an exercise prescription for a subject and an application program to classify the subject's fitness. The experimental study shows that XML-based templates provide a flexible, extensible and structured way of representing expert knowledge. The inference using XML-based templates can be controlled systematically and efficiently by using meta-template.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.201-204
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• 2003

At a consequence of WWW large popularity, the internet has suffered from various performance problems, such as network congestion and overloaded servers. These days, it is not uncommon to find servers refusing connections because they are overloaded. Web server performance has always been a key issue in the design and operation of on-line systems. With regard to Internet, performance is also critical, because users want fast and easy access to all objects (e.g., documents, graphics, audio, and video) available on the net. To solve this problem, a number of companies are exploring the benefits of having multiple geographically or locally distributed Internet sites. This requires a comprehensive scheme for traffic management, which includes the principle of an optimal load balancing of client requests across multiple clusters of real servers. This paper focuses on the performance analysis of Web server and we apply these results to load balancing in clustering web server. It also discusses the mam steps needed to carry out a WWW performance analysis effort and shows relations between the workload characteristics and system resource usage. Also, we will introduce an optimal load balancing algorithm base on the RTSM (Real-Time Server Monitor) and Fuzzy Inference Engine for the local status of a real server, and the benefits is provided with of the suggested method.

• Journal of the Korea Concrete Institute
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• v.14 no.6
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• pp.1022-1031
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• 2002

This paper presents efficient models for bridge structures using CART-ANFIS (classification and regression tree-adaptive neuro fuzzy inference system). A fuzzy decision tree partitions the input space of a data set into mutually exclusive regions, each region is assigned a label, a value, or an action to characterize its data points. Fuzzy decision trees used for classification problems are often called fuzzy classification trees, and each terminal node contains a label that indicates the predicted class of a given feature vector. In the same vein, decision trees used for regression problems are often called fuzzy regression trees, and the terminal node labels may be constants or equations that specify the predicted output value of a given input vector. Note that CART can select relevant inputs and do tree partitioning of the input space, while ANFIS refines the regression and makes it continuous and smooth everywhere. Thus it can be seen that CART and ANFIS are complementary and their combination constitutes a solid approach to fuzzy modeling.

• Convergence Security Journal
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• v.12 no.6
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• pp.85-92
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• 2012

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outliers, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical Process Control (SPC) can monitor the forecasting of software failure and there by contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of log Poission, log-linear and Parto distribution.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.5
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• pp.563-569
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• 2015

A chemical reaction occurring in CSTR (Continuous Stirred Tank Reactor) is significantly affected by the concentration, temperature, pressure, and reacting time of materials, and thus it has strong nonlinear and time-varying characteristics. Also, when an existing linear PID controller with fixed gain is used, the performance could deteriorate or could be unstable if the system parameters change due to the change in the operating point of CSTR. In this study, a technique for the design of a fuzzy PD plus I controller was proposed for the temperature control of a CSTR process. In the fuzzy PD plus I controller, a linear integral controller was added to a fuzzy PD controller in parallel, and the steady-state performance could be improved based on this. For the fuzzy membership function, a Gaussian type was used; for the fuzzy inference, the Max-Min method of Mamdani was used; and for the defuzzification, the center of gravity method was used. In addition, the saturation state of the actuator was also considered during controller design. The validity of the proposed method was examined by comparing the set-point tracking performance and the robustness to the parameter change with those of an adaptive controller and a nonlinear proportional-integral-differential controller.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1779-1785
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• 2018

In this paper, we propose an error correction method to improve the accuracy of human activity recognition using sensor event data obtained by smart devices such as wearable and smartphone. In the context awareness through the smart device, errors inevitably occur in sensing the necessary context information due to the characteristics of the device, which degrades the prediction performance. In order to solve this problem, we apply Kalman filter's error correction algorithm to compensate the signal values obtained from 3-axis acceleration sensor of smart device. As a result, it was possible to effectively eliminate the error generated in the process of the data which is detected and reported by the 3-axis acceleration sensor constituting the time series data through the Kalman filter. It is expected that this research will improve the performance of the real-time context-aware system to be developed in the future.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.5
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• pp.345-353
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• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do parameter inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision to market software, the conditional failure rate is an important variables. In this case, finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of polynomial hazard function.

• Geomechanics and Engineering
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• v.12 no.3
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• pp.441-464
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• 2017

The determination of the mixture parameters of stabilization has become a great concern in geotechnical applications. This paper presents an effort about the application of artificial intelligence (AI) techniques including radial basis neural network (RBNN), multi-layer perceptrons (MLP), generalized regression neural network (GRNN) and adaptive neuro-fuzzy inference system (ANFIS) in order to predict the unconfined compressive strength (UCS) of silty soil stabilized with bottom ash (BA), jute fiber (JF) and steel fiber (SF) under different freeze-thaw cycles (FTC). The dosages of the stabilizers and number of freeze-thaw cycles were employed as input (predictor) variables and the UCS values as output variable. For understanding the dominant parameter of the predictor variables on the UCS of stabilized soil, a sensitivity analysis has also been performed. The performance measures of root mean square error (RMSE), mean absolute error (MAE) and determination coefficient ($R^2$) were used for the evaluations of the prediction accuracy and applicability of the employed models. The results indicate that the predictions due to all AI techniques employed are significantly correlated with the measured UCS ($p{\leq}0.05$). They also perform better predictions than nonlinear regression (NLR) in terms of the performance measures. It is found from the model performances that RBNN approach within AI techniques yields the highest satisfactory results (RMSE = 55.4 kPa, MAE = 45.1 kPa, and $R^2=0.988$). The sensitivity analysis demonstrates that the JF inclusion within the input predictors is the most effective parameter on the UCS responses, followed by FTC.

• Journal of the Korean Society of Costume
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• v.62 no.4
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• pp.81-90
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• 2012

The contents of this study are as follows. First, an academic understanding has been achieved by exploring the theoretical concept "allegory", and a new theoretical approached methodology has been sought. Second, an analysis-index of fashion illustration cases has been suggested based on the allegory theory of Craig Owens. Third, in order to draw the characteristics of fashion illustration as viewed from the allegorical viewpoint and find out its feasibility, the case studies has been referred and the internal significance, external significance that combines different characteristics has been extracted. In regards to this study method, literature studies and case studies has been done in parallel with each other. This study was done in the following sequence: the establishment of the study system, the drawing of the allegory-associated concepts and the discovering the characteristics of aesthetic expressions. The results of this study on the expression characteristics of fashion illustration as viewed from the allegorical viewpoint of Craig Owens are as follows. First, the borrowing of image, which is a characteristic of allegory, contains the meaning of uncertainty in the fashion illustration as it expresses the image-synthesis and forms a completely different meaning as the fixed meaning is dissolved and it is utilized as a photo-montage technique. Second, the inference of pictogram is the mixture of linguistic medium and visual medium. Fashion illustration utilizes the characters and transmits the fashion information visually and immanently. It has the characteristic of making the information into pictograms and the internal significances of mutual-text with communication function. Third, the uniqueness of location in the fashion illustration has the special nature of utilized mediums as it is used for advertising or publicizing. The fashion illustration from the viewpoint of allegory has the impermanency of existing only for a limited time and reflects the coincidence that gives the meaning of utilized location according to the season trend. Fourth, the cross-breeding is expressed as the mixture of various materials in the fashion illustration. The expressions made by the mixture of media, such as the use of computer graphic programs mixed together with various materials showed the trend of diversity and genre dissolution.