• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.43 no.3
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• pp.1-10
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• 2011

Proportional.Integral.Derivative control schemes continue to provide the simplest and effective solutions to most of the control engineering applications today. However PID controller is poorly tuned in practice with most of the tuning done manually which is difficult and time consuming. This research comes up with a soft computing approach involving Genetic Algorithm, Evolutionary Programming, and Particle Swarm Optimization and Ant colony optimization. The proposed algorithm is used to tune the PID parameters and its performance has been compared with the conventional methods like Ziegler Nichols and Lambda method. The results obtained reflect that use of heuristic algorithm based controller improves the performance of process in terms of time domain specifications, set point tracking, and regulatory changes and also provides an optimum stability. This research addresses comparison of tuning of the PID controller using soft computing techniques on Machine Direction of basics weight control in pulp and paper industry. Compared to other conventional PID tuning methods, the result shows that better performance can be achieved with the soft computing based tuning method. The ability of the designed controller, in terms of tracking set point, is also compared and simulation results are shown.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_1
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• pp.485-497
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• 2007

By the rapid development of Information Communication Technology (ICT) and Geo-spatial Technology (GT) and the increased usage of spatial data for planning and infrastructure management, the National Geographic Information System (NGIS) for more efficient and effective utilization of spatial information has been developed by the central government in Korea since 1995. NGIS is the base of Spatial Data Infrastructure (SDI). SDI is developed as one of National Information Infrastructures (NII). Among the hierarchy of SDI, National Spatial Data Infrastructure (NSDI) has very important role in the success of SDI development. Many research articles show that the USA's NSDI initiatives, development strategy have been strongly influenced all over the world. In these viewpoints, to propose the future directions of Korean NGIS, the development of NSDI strategy of USA is reviewed by literature through published book and internet resources. The conclusions of this study are as follow: 1) top-down and bottom-up approach are needed for integrated data sharing and standardization. 2) the creative and evolutionary vision and strategy has to be suggested. 3) the training program and lecture material has to be developed and diffused to the users and providers of spatial data. 4) governance system has to be built for NSDI evaluation. 5) the formation of geo-spatial forum to discuss the spatial-related problems and make research agenda, etc.

• Korean Journal of Veterinary Research
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• v.53 no.3
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• pp.155-158
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• 2013

Paedomorphosis is the retention of juvenile morphology at maturity and is important in generating evolutionary change in domestic species and species in the wild. This preliminary study compared morphological characteristics of seven domestic cat pure breeds and felid species from around the world. An original procedure based on elliptical Fourier (EF) methods was applied to head lateral views of specimens and were assessed in order to analyse head profile. For comparative purposes three domestic kittens of different ages and three species of genus Lynx were also used. EF descriptors, allowed for the quantification of the head profile. Using the Fourier transform, reconstruction of the mean head profile revealed that there was a general shape difference between wild cats, domestic cats and kittens. Results suggested that variability in head profile differentiate quite well between adult cats and kittens, but domestic and wild cats appeared grouped into a similar cluster. The similarity between breeds can thus be attributed more to the general head profile than to flatness, i.e. to the general conformation rather than facial profile. Therefore, no effect of paedomorphism on the studied breeds can be undertaken. The present approach opens interesting ethnological perspectives for the aloidic characterisation for domestic breeds.

• Journal of KSNVE
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• v.3 no.4
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• pp.341-352
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• 1993

Although a frequency analysis by FFT algorithm has been widely used in the vibration community, this approach has somewhat limited features when an analysist want to see the details of frequency trends because FFT shows only energy contents along frequencies. So the concept of instantaneous frequency that represents the dominant frequency component at each time needs to be introduced. In this paper, to get the instantaneous frequency, two methods are used. Methods using Hilbert transform and evolutionary spectrum are those. One of the problems of estimating instantaneous frequency using Hilbert transform is that it is normally very sensitive to signal to noise ratio(SNR) because of the differentiation. Moving window is applied on the estimation of instantaneous frequency, and instantaneous frequency histogram are used to handle this problem and proved to be very effective. Computer simulations for various signals have been done to understand the characteristics of instantaneous frequency. The usefulness of signal analysis using instantaneous frequency was tested by three simple experiments, which were engine experiment, beam experiment, and car door experiment. The instantaneous frequency analysis is found to be a useful technique to analyze the signals that have time varying frequencies.

• Journal of Life Science
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• v.11 no.5
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• pp.400-404
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• 2001

A new human endogenous retroviral family (HERV-S) has recently been identified from human X chromosome. It is 6.7 kb in length and has a typical retroviral structure with LTR-gag-pol-env-LTR. Using the PCR and sequencing approach, we investigated LTR elements of the HERV-S family from a human genomic DNA. Four LTR elements (HSL-1, HSL-5, HSL-10, HSL-11) were identified and have a high degree of sequence similarity(96-99%) with that of the HERV-S. Phylogenetic analysis from the HERV-S family indicated that the LTR elements were mainly divided into 2- groups through evolutionary divergence in the primate evolution. Further investigation of the HERV-S LTR elements in primates may cast light on the integration timing into the primate genome and understanding of human evolution.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.4
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• pp.29-43
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• 2017

Innovation Cosystems are Conceptualized as Organizational Networks of Economic Actors, Technologies and Social Contexts that Interact for Knowledge Production, use, and Adaptation. This Paper Proposed a Conceptual Framework to Describe Value Co-creation of Organizational Networks Engaged in Technology Innovation. We Adopted Theory-Based Approach by Integrating the Perspective of Service-Dominant (S-D) Logic Into the Evolutionary Model of the Triple Helix. The Framework Gives a Plausible Explanation on how Actors Collaborate to Create Value in Dynamic Contexts of an Innovation Ecosystem. The Innovation Ecosystem can be Considered as a Composite of Sub-Ecosystems, Including Knowledge, Sectoral, and Business Ecosystems. When these Sub-Ecosystems are Recursively Transformed by Coordination of Functional Mechanisms that Serve Value Co-creation in the Innovation Process, the Innovation Ecosystem will be Re-Organized and Evolve. The case of the Digital Living Network Alliance (DLNA) was Examined to Demonstrate the Fundamental Mechanisms for Value Co-creation that was Described in the Framework. The case Study Indicates Features of Value Co-creation when Implementing Innovation in Organizational Networks.

• International Journal of Fluid Machinery and Systems
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• v.3 no.4
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• pp.352-359
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• 2010

In recent years, the market has shown increasing interest in pump-turbines. The prompt availability of pumped storage plants and the benefits to the power system achieved by peak lopping, providing reserve capacity, and rapid response in frequency control are providing a growing advantage. In this context, there is a need to develop pumpturbines that can reliably withstand dynamic operation modes, fast changes of discharge rate by adjusting the variable diffuser vanes, as well as fast changes from pumping to turbine operation. In the first part of the present study, various flow patterns linked to operation of a pump-turbine system are discussed. In this context, pump and turbine modes are presented separately and different load cases are shown in each operating mode. In order to create modern, competitive pump-turbine designs, this study further explains what design challenges should be considered in defining the geometry of a pump-turbine impeller. The second part of the paper describes an innovative, staggered approach to impeller development, applied to a low head pump-turbine project. The first level of the process consists of optimization strategies based on evolutionary algorithms together with 3D in-viscid flow analysis. In the next stage, the hydraulic behavior of both pump mode and turbine mode is evaluated by solving the full 3D Navier-Stokes equations in combination with a robust turbulence model. Finally, the progress in hydraulic design is demonstrated by model test results that show a significant improvement in hydraulic performance compared to an existing reference design.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.12
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• pp.1748-1755
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• 2015

A linear regression is widely used for prediction problem, but it is hard to manage an irregular nature of nonlinear system. Although nonlinear regression methods have been adopted, most of them are only fit to low and limited structure problem with small number of independent variables. However, real-world problem, such as weather prediction required complex nonlinear regression with large number of variables. GP(Genetic Programming) based evolutionary nonlinear regression method is an efficient approach to attach the challenging problem. This paper introduces the improvement of an GP based nonlinear regression method using ADF(Automatically Defined Function). It is believed ADFs allow the evolution of modular solutions and, consequently, improve the performance of the GP technique. The suggested ADF based GP nonlinear regression methods are compared with UM, MLR, and previous GP method for 3 days prediction of wind speed using MOS(Model Output Statistics) for partial South Korean regions. The UM and KLAPS data of 2007-2009, 2011-2013 years are used for experimentation.

• Industrial Engineering and Management Systems
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• v.12 no.2
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• pp.151-160
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• 2013

In the past decades, several algorithms based on evolutionary approaches have been proposed for solving job shop scheduling problems (JSP), which is well-known as one of the most difficult combinatorial optimization problems. Most of them have concentrated on finding optimal solutions of a single objective, i.e., makespan, or total weighted tardiness. However, real-world scheduling problems generally involve multiple objectives which must be considered simultaneously. This paper proposes an efficient particle swarm optimization based approach to find a Pareto front for multi-objective JSP. The objective is to simultaneously minimize makespan and total tardiness of jobs. The proposed algorithm employs an Elite group to store the updated non-dominated solutions found by the whole swarm and utilizes those solutions as the guidance for particle movement. A single swarm with a mixture of four groups of particles with different movement strategies is adopted to search for Pareto solutions. The performance of the proposed method is evaluated on a set of benchmark problems and compared with the results from the existing algorithms. The experimental results demonstrate that the proposed algorithm is capable of providing a set of diverse and high-quality non-dominated solutions.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.848-849
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• 2007

This paper presents an efficient approach for solving the economic dispatch (ED) problems with valve-point effects using differential evolution (DE). A DE, one of the evolutionary algorithms (EAs), is a novel optimization method capable of handling nonlinear, non-differentiable, and nonconvex functions. And an efficient constraints treatment method (CTM) is applied to handle the equality and inequality constraints. The resultant DE-CTM algorithm is very effective in solving the ED problems with nonconvex cost functions. To verify the superiority of the proposed method, a sample ED problem with valve-point effects is tested and its results are compared with those of previous works. The simulation results clearly show that the proposed DE-CTM algorithm outperforms other state-of-the-art algorithms in solving ED problems with valve-point effects