• Bulletin of the Korean Chemical Society
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• v.29 no.7
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• pp.1335-1343
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• 2008

Theoretical studies on the un-catalyzed and catalyzed aminations of ketene with $NH_3$ and $(NH_3)_2$, respectively, were studied using MP2 and hybrid density functional theory of B3LYP at the 6-31+G(d,p) and 6- 311+G(3df,2p) basis sets in the gas phase and in benzene and acetonitrile solvents. In the gas phase reaction, the un-catalyzed mechanism was the same as those previously reported by others. The catalyzed mechanism, however, was more complicated than expected requiring three transition states for the complete description of the C=O addition pathways. In the un-catalyzed amination, rate determining step was the breakdown of enol amide but in the catalyzed reaction, it was changed to the formation of enol amide, which was contradictory to the previous findings. Starting from the gas-phase structures, all structures were re-optimized using the CPCM method in solvent medium. In a high dielectric medium, acetonitrile, a zwitterions formed from the reaction of $CH_2$=C=O with $(NH_3)_2$, I(d), exists as a genuine minimum but other zwitterions, I(m) in acetonitrile and I(d) in benzene become unstable when ZPE corrected energies are used. Structural and energetic changes induced by solvation were considered in detail. Lowering of the activation energy by introducing additional $NH_3$ molecule amounted to ca. −20 $\sim$ −25 kcal/mol, which made catalyzed reaction more facile than un-catalyzed one.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.223-230
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• 2001

Since self-organizing map (SOM) preserves the topology of ordering in input spaces and trains itself by unsupervised algorithm, it is Llsed in many areas. However, SOM has a shortcoming: structure cannot be easily detcrmined without many trials-and-errors. Structure-adaptive self-orgnizing map (SASOM) which can adapt its structure as well as its weights overcome the shortcoming of self-organizing map: SASOM makes use of structure adaptation capability to place the nodes of prototype vectors into the pattern space accurately so as to make the decision boundmies as close to the class boundaries as possible. In this scheme, the initialization of weights of newly adapted nodes is important. This paper proposes a method which optimizes SASOM with genetic algorithm (GA) to determines the weight vector of newly split node. The leanling algorithm is a hybrid of unsupervised learning method and supervised learning method using LVQ algorithm. This proposed method not only shows higher performance than SASOM in terms of recognition rate and variation, but also preserves the topological order of input patterns well. Experiments with 2D pattern space data and handwritten digit database show that the proposed method is promising.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.470-477
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• 2015

This paper presents a new technique for generating an optimum synchronizable test sequence that can be applied in the distributed test architecture where both external synchronization and input/output operation costs are taken into consideration. The method defines a set of phases that constructs a tester-related digraph from a given finite state machine representation of a protocol specification such that a minimum cost tour of the digraph with intrinsically synchronizable transfer sequences can be used to generate an optimum synchronizable test sequence using synchronizable state identification sequences as the state recognition sequence for each state of the given finite state machine. This hybrid approach with a heuristic and optimization technique provides a simple and elegant solution to the synchronization problem that arises during the application of a predetermined test sequence in some protocol test architectures that utilize remote testers.

• Korean Journal of Optics and Photonics
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• v.22 no.6
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• pp.247-255
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• 2011

The optical performance of LLF(Lenticular Lens Film)-based backlight was studied by using optical simulation as functions of the aspect ratio and the refractive index of lenticular lenses. In order to perform reliable simulation, the BSDF(bi-directional scattering distribution function) of the scattering dots on the bottom surface of the light guide plate was obtained as a superposition of the Lambertian and the elliptic Gaussian distribution components by comparing the experimental results and the simulation for the luminance distribution on the light guide. Based on this approach, an appropriate BSDF of the scattering dots of the light guide was constructed. The resultant values of the optimized aspect ratio and the refractive were found to be 1.25 and 1.65, respectively. In spite of the hybrid aspects of LLF incorporating both diffusing and collimating functions, the optical performance, in particular the on-axis luminance of LLF-based backlight was inferior by about 20% compared to that of conventional backlights adopting one prism film. However, the combination of two lenticular lens films resulted in comparable luminance gain as well as smooth decrease in the luminance with the viewing angle without exhibiting any side lobes.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.138-143
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• 2006

This paper presents intelligent digital redesign method for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an . example to guarantee the stability and effectiveness of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.287-295
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• 2010

In this paper, we introduce a novel approach to optimization algorithm which is a distributed Mean field Genetic algorithm (MGA) implemented in MPI(Message Passing Interface) environments. Distributed MGA is a hybrid algorithm of Mean Field Annealing(MFA) and Simulated annealing-like Genetic Algorithm(SGA). The proposed distributed MGA combines the benefit of rapid convergence property of MFA and the effective genetic operations of SGA. The proposed distributed MGA is applied to the channel routing problem, which is an important issue in the automatic layout design of VLSI circuits. Our experimental results show that the composition of heuristic methods improves the performance over GA alone in terms of mean execution time. It is also proved that the proposed distributed algorithm maintains the convergence properties of sequential algorithm while it achieves almost linear speedup as the problem size increases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.943-948
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• 2018

In this paper, we propose a hybrid approach of combining $A^*$ and Genetic algorithm in the path search problem. In $A^*$, the cost from a start node to the intermediate node is optimized in principle but the path from that intermediate node to the goal node is generated and tested based on the cumulated cost and the next node in a priority queue is chosen to be tested. In that process, we adopt the genetic algorithm principle in that the group of nodes to generate the next node from an intermediate node is tested by its fitness function. Top two nodes are selected to use crossover or mutation operation to generate the next generation. If generated nodes are qualified, those nodes are inserted to the priority queue. The proposed method is compared with the original sequential selection and the random selection of the next searching path in $A^*$ algorithm and the result verifies the superiority of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5723-5743
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• 2018

The evolving internet-based services demand high-speed data transmission in conjunction with scalability. The next generation optical network has to exploit artificial intelligence and cognitive techniques to cope with the emerging requirements. This work proposes a novel way to solve the dynamic provisioning problem in optical network. The provisioning in optical network involves the computation of routes and the reservation of wavelenghs (Routing and Wavelength assignment-RWA). This is an extensively studied multi-objective optimization problem and its complexity is known to be NP-Complete. As the exact algorithms incurs more running time, the heuristic based approaches have been widely preferred to solve this problem. Recently the software-defined networking has impacted the way the optical pipes are configured and monitored. This work proposes the dynamic selection of path computation algorithms in response to the changing service requirements and network scenarios. A software-defined controller mechanism with a novel packet matching feature was proposed to dynamically match the traffic demands with the appropriate algorithm. A software-defined controller with Path Computation Element-PCE was created in the ONOS tool. A simulation study was performed with the case study of dynamic path establishment in ONOS-Open Network Operating System based software defined controller environment. A java based NOX controller was configured with a parent path computation element. The child path computation elements were configured with different path computation algorithms under the control of the parent path computation element. The use case of dynamic bulk path creation was considered. The algorithm selection method is compared with the existing single algorithm based method and the results are analyzed.

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.113-117
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• 2022

Additive manufacturing (AM, also known as 3D printing) technology is digitalized technology, making it easy to predict and manage quality and also, have design freedom ability. With these advantages, AM technology is applied to various industries. In particular, a method of manufacturing buildings and infrastructure with AM technology is being proposed to the construction industry. However, the application of AM technology is restricted due to problems such as insufficient history and quality of technology, lack of construction management methods, and certification of manufacturing products. Therefore, the manufacture of architectural products is implemented with indirect AM technology. In particular, it manufactures formwork using AM and injecting building materials to implement the architectural product. In this study, hybrid type material extrusion AM is used to manufacture large-sized formwork and implement building products. Moreover, we identify factors that can predict productivity and economic feasibility in the additive manufacturing process. As a result, design optimization results are proposed to reduce the production cost and time of architecture buildings.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1603-1611
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• 2021

As IMO environmental regulations are tightened, the need to establish a system that can reduce emissions is increasing, and for this purpose, various power control management systems have been studied and implemented as a new energy management system for ships. In this study, we design a control process through modeling for Bi-Directional Converter (BDC) application with bi-directional power flow to link batteries, which are energy storage devices, to conventional generator power systems, and propose mechanisms for batteries optimized for varying loads. This work models MATLAB/Simulink as a BDC and simulates current control and state of charge (SOC) optimization at the time of charging and discharging batteries according to load scenarios. Through this, the battery, power, and load were interlocked so that the generator operated on board could be operated in the optimal operation range, and power control management was performed to enable the generator to operate in the high fuel efficiency range.