• Journal of Korean Association for Spatial Structures
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• v.3 no.3 s.9
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• pp.67-74
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• 2003

The purpose of this study is to improve convergence speed of topology optimization procedure using the existing ESO method and to deal with topology decision of the truss structures according to a boundary condition, such as cantilever type. At the existing ESO topology optimization procedure for the truss structures, the adjustment of member sizes according to target stress has been executed by increasing or reducing a very small value from each member size. In this case, it takes too much iteration till convergence. Accordingly, it is practically hard to obtain optimum topology for a large scale structures. For that reason, it is necessary to improve convergence speed of ESO method more effectively. During the topology decision procedure, member sizes are adjusted by calculating approximate solution for member sizes corresponding to the target stress at every step, the new member sizes are adjusted by such method are applied in FEA procedure of next step.

• IE interfaces
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• v.16 no.spc
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• pp.14-20
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• 2003

This paper presents a multi-criteria decision model and Multi-Criteria Generic Algorithm(MCGA) approach to improve backbone topology by leveraging the Virtual Link(VL) system in an hierarchical Link-State(LS) routing domain. Given that the sound backbone topology structure has a great impact on the overall routing performance in an hierarchical LS domain, the importance of this research is evident. The proposed decision model is to find an optimal configuration of VLs that properly meets two-pronged engineering goals in installing and maintaining VLs: i.e., operational costs and network reliability. The experiment results clearly indicates that it is essential to the effective operations of hierarchical LS routing domain to consider not only engineering aspects but also specific benefits from systematical layout of VLs, thereby presenting the validity of the decision model and MCGA.

• The Journal of the Acoustical Society of Korea
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• v.21 no.2
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• pp.199-210
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• 2002

In this paper, we carried out the study on speech recognition using the KM-Net topology design algorithm based on decision tree state-clustering to improve the performance of acoustic models in speech recognition. The Korean has many allophonic and grammatical rules compared to other languages, so we investigate the allophonic variations, which defined the Korean phonetics, and construct the phoneme question set for phonetic decision tree. The basic idea of the HM-Net topology design algorithm is that it has the basic structure of SSS (Successive State Splitting) algorithm and split again the states of the context-dependent acoustic models pre-constructed. That is, it have generated. the phonetic decision tree using the phoneme question sets each the state of models, and have iteratively trained the state sequence of the context-dependent acoustic models using the PDT-SSS (Phonetic Decision Tree-based SSS) algorithm. To verify the effectiveness of the above algorithm we carried out the speech recognition experiments for 452 words of center for Korean language Engineering (KLE452) and 200 sentences of air flight reservation task (YNU200). Experimental results show that the recognition accuracy has progressively improved according to the number of states variations after perform the splitting of states in the phoneme, word and continuous speech recognition experiments respectively. Through the experiments, we have got the average 71.5%, 99.2% of the phoneme, word recognition accuracy when the state number is 2,000, respectively and the average 91.6% of the continuous speech recognition accuracy when the state number is 800. Also we haute carried out the word recognition experiments using the HTK (HMM Too1kit) which is performed the state tying, compared to share the parameters of the HM-Net topology design algorithm. In word recognition experiments, the HM-Net topology design algorithm has an average of 4.0% higher recognition accuracy than the context-dependent acoustic models generated by the HTK implying the effectiveness of it.

• The Transactions of the Korea Information Processing Society
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• v.2 no.5
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• pp.768-776
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• 1995

In a distributed computer system with star topology, the processing power of central node may be greater than that of peripheral nodes and the job arrival rate of each node may be different. The performance of load balancing may be very different according to the selection of sender criteria and receiver criteria for job transfer. But the optimal decision of sender and receiver criteria is very difficult in heterogeneous distributed computer systems. In this paper we propose effective destination decision policies using dynamic criteria such as mean job response time of a node and estimated response time of a job, instead of fixed threshold for dynamic load balancing.

• 한국정보통신설비학회:학술대회논문집
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• 2005.08a
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• pp.154-158
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• 2005

In this paper, we design optical receiver composed of CDR(clock and data recovery), SA(sense amp), TIA(transimpe dence amplifier), and decision circuit. The optical receiver can be classified to two main block, one is Deserializer composed of CDR and SA, another is PD receiver composed of preamplifier(샴), peak detector, etc. In this paper, we propose CDR using delayed data topology that could improve defects of existing CDR. The optical receiver that is proposed in this paper has the role of translation a 1.25 Gb/s optical signal to $10{\times}125 Mb/s$ array electric signals. This optical receiver is verified by simulator(hspice) using 0.35 um CMOS technology.

• The Journal of Information Technology
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• v.8 no.1
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• pp.51-56
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• 2005

The Back propagation algorithm is a very effective supervised training method for multi-layer feed forward neural networks. This paper studies the decision boundary formation based on the Back propagation algorithm. The discriminating powers of several neural network topology are also investigated against five manually created data sets. It is found that neural networks with multiple hidden layer perform better than single hidden layer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8C
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• pp.729-740
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• 2002

This paper studies the issues arising in the virtual topology reconfiguration phase of Multi-wavelength Routed Optical Networks. This reconfiguration process means to change the virtual topology in response to the changing traffic patterns in the higher layer. We formulate the optimal reconfiguration policy as a multi-stage decision-making problem to maximize the expected reward and cost function over an infinite horizon. Then we propose a new heuristic algorithm based on node-exchange to reconfigure the virtual topology to meet the traffic requirement. To counter the continual approximation problem brought by heuristic approach, we take the traffic prediction into consideration. We further propose a new heuristic reconfiguration algorithm called Prediction based Multi-stage Reconfiguration approach to realize the optimal reconfiguration policy based on predicted traffic. Simulation results show that our reconfiguration policy significantly outperforms the conventional one, while the required physical resources are limited.

• Steel and Composite Structures
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• v.19 no.2
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• pp.263-275
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• 2015

This study presents conceptual information of newly optimized shapes and connectivity of the so-called outrigger truss system for modern tall buildings that resists lateral loads induced by wind and earthquake forces. In practice, the outrigger truss consists of triangular or Vierendeel types to stiffen tall buildings, and the decision of outrigger design has been qualitatively achieved by only engineers' experience and intuition, including information of structural behaviors, although outrigger shapes and the member's connectivity absolutely affect building stiffness, the input of material, construction ability and so on. Therefore the design of outrigger trusses needs to be measured and determined according to scientific proofs like reliable optimal design tools. In this study, at first the shape and connectivity of an outrigger truss system are visually evaluated by using a conceptual design tool of the classical topology optimization method, and then are quantitatively investigated with respect to a structural safety as stiffness, an economical aspect as material quantity, and construction characteristics as the number of member connection. Numerical applications are studied to verify the effectiveness of the proposed design process to generate a new shape and connectivity of the outrigger for both static and dynamic responses.

• Spatial Information Research
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• v.2 no.2
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• pp.147-163
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• 1994

This paper presents three methods of generating the transportation network data out of the topological geographic database in the hope that the conversion of the geographic database file containing the topology to the conventional node-link type trans¬portation network file may facilitate the integration between transportation planning mod¬els and GIS by alleviating the inherent problems of both computing environments. One way of the proposed conversion method is to use the conversion software that allows the bi-directional conversion between the UTPS (Urban Transportation Planning System) type transportation planning model and GIS. The other two methods of data structure conversion approach directly transform the GIS's user-level topology into the transportation network data topology, and have been introduced with codes programmed with FORTRAN and AML (Arc Macro Language) of ARC/INFO. If used successfully, any approach would not only improve the efficiency of transportation planning process and the associated decision-making activities in it, but enhance the productivity of trans¬portation planning agencies.

• Advances in Computational Design
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• v.2 no.4
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• pp.313-331
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• 2017

In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.