• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.26-35
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• 2007

The vehicle of urban transit is a complex system that consists of various electric, electronic, and mechanical equipments, and the maintenance cost of this complex and large-scale system generally occupies sixty percent of the LCC (Life Cycle Cost). For reasonable establishing of maintenance strategies, safety security and cost limitation must be considered at the same time. The concept of system reliability has been introduced and optimized as the key of reasonable maintenance strategies. For optimization, three preceding studies were accomplished; standardizing a maintenance classification, constructing RBD (Reliability Block Diagram) of VVVF (Variable Voltage Variable Frequency) urban transit, and developing a web based reliability evaluation system. Historical maintenance data in terms of reliability index can be derived from the web based reliability evaluation system. In this paper, we propose applying inverse problem analysis method and hybrid neuro-genetic algorithm to system reliability optimization for using historical maintenance data in database of web based system. Feed-forward multi-layer neural networks trained by back propagation are used to find out the relationship between several component reliability (input) and system reliability (output) of structural system. The inverse problem can be formulated by using neural network. One of the neural network training algorithms, the back propagation algorithm, can attain stable and quick convergence during training process. Genetic algorithm is used to find the minimum square error.

• The Journal of Society for e-Business Studies
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• v.7 no.1
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• pp.87-106
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• 2002

The behavioral and dynamic implications of an ERP implementation/installation are, to say the least, not well understood. Getting the switches set to enable the ERP software to go live is becoming straightforward. The really difficult part is understanding all of the dynamic interactions that accrue as a consequence. Dynamic causal and connectionist models are employed to facilitate an understanding of the dynamics and to enable control of the information-enhanced processes to take place. The connectionist model ran be analyzing (behind the scenes) the information accesses and transfers and coming If some conclusions about strong linkages that are getting established and what the behavioral implications of those new linkages and information accesses we. Ultimately, the connectionist model will come to an understanding of the dynamic, behavioral implications of the larger ERP implementation/installation per se. The underlying connectionist model will determine information transfers and workflow. Once a map of these two infrastructures is determined by the model, it becomes a relatively easy job for an analyst to suggest improvements in both. Connectionist models start with analog object structures and then use learning to produce mechanisms for managerial problem diagnoses. These mechanisms are neural models with multiple-layer structures that support continuous input/output. Based on earlier work performed and published by the author[10][11], a Connectionist ReasOning and LEarning System(CROLES) is developed that mimics the real-world reasoning infrastructure. Coupled with an explanation subsystem, this system can provide explanations as to why a particular reasoning structure behaved the way it did. Such a system operates in the backgmund, observing what is happening as every information access, every information response coming from each and every intelligent node (whether natural or artificial) operating within the ERP infrastructure is recorded and encoded. The CROLES is also able to transfer all workflows and map these onto the decision-making nodes of the organization.

• Journal of the Korean Geophysical Society
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• v.9 no.1
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• pp.1-6
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• 2006

To remove ringing and increase vertical resolution of GRP data, signature deconvolution was applied to GPR data obtained using a 100 MHz antenna in the Soyang Lake. The signature was extracted through stacking reflection signals from the lake bottom. Results of this deterministic deconvolution was compared with those from the conventional Wienner method. Due to increased vertical resolution, both deconvolution methods are able to resolve three or more layers in an apparent single layer on the input data. However, identification of reflection boundaries from ringing is not easy due to poor definition in the output data of the Wienner filter. On the contrary, the signature deconvolution greatly enhances both vertical resolution and definition of reflection boundaries, showing detailed internal stratigraphic features of the three sedimentary layers. Since extraction of signature at various depths is possible, this deconvolution method can be appled effectively to unstationary GPR data.

• Journal of Korean Society of Water and Wastewater
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• v.25 no.6
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• pp.885-892
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• 2011

In this study, LCA(Life Cycle Assessment) on 'Saemangum CSO Project' was carried out to evaluate environmental impact which occurred during the construction and operation periods and the potential environmental impact reduction was analyzed by comparing production and reduction level of pollution loads. LCA was conducted out according to the procedure of ISO14040 which suggested Goal and Scope Definition, Life Cycle Inventory Analysis, Life Cycle Impact Assessment and Interpretation. In the Goal and Scope Definition, the functional unit was 1 m3 of CSO, the system boundary was construction and operation phases, and the operation period was 20 years. For the data collection and inventory analysis, input energies and materials from civil, architecture, mechanical and electric fields are collected from design sheet but the landscape architecture field is excepted. LCIA(Life Cycle Impact Assessment) was performed following the procedure of Eco-Labelling Type III under 6 categories which were resource depletion, eutrophication, global warming, ozone-layer destruction, and photochemical oxide formation. In the result of LCA, 83.4% of environmental impact occurred in the construction phase and 16.6% in the operation phase. Especially 78% of environmental impact occurred in civil works. The Global warming category showed the highest contribution level in the environmental impact categories. For the analysis on potential environmental impact reduction, the reduction and increased of environmental impact which occurred on construction and operation phases were compared. In the case of considering only the operation phase, the result of the comparison showed that 78% of environmental impact is reduced. On the other hand, when considering both the construction and operation phases, 50% of environmental impact is increase. Therefore, this study showed that eco-friendly material and construction method should be used for reduction of environmental impact during life cycle, and it is strongly necessary to develop technology and skills to reduce environmental impact such as renewable energies.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.2
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• pp.69-74
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• 2000

The bandwidth of microstrip slot antenna with T-shaped feed line was a wider than one of the conventional feeding structure. When the slot antenna with bi-directional radiator wants to radiate only one direction, the reflector must be set up seperately. But this antenna doesn't need set up reflector. And then we proposed to a new method of a directional slot radiator with a cross-shaped feedline including the reflector using 2-layers dielectric materials. It is calculated waves and electric field distribution in the time domain by using FDTD method. We also are calculated return loss, VSWR, input impedance, and radiation pattern in the frequency domain by Fourier transforming the time domain results, respectively. It was found that the bandwidth of this antenna changes as length($\I_s$) and width($\W_s$) of slot, length of the horizontal feedline($\I_d$), length of the vertical feedline($\I_u$) and offset sensitively. After optimizing the parameters of design, the maximum bandwidth was measured as 1,850MHz at the center frequency 2.5 GHz.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.40-48
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• 2007

This paper presents a novel texture segmentation method using multilayer perceptron (MLP) networks and Markov random fields in multiscale Bayesian framework. Multiscale wavelet coefficients are used as input for the neural networks. The output of the neural network is modeled as a posterior probability. Texture classification at each scale is performed by the posterior probabilities from MLP networks and MAP (maximum a posterior) classification. Then, in order to obtain the more improved segmentation result at the finest scale, our proposed method fuses the multiscale MAP classifications sequentially from coarse to fine scales. This process is done by computing the MAP classification given the classification at one scale and a priori knowledge regarding contextual information which is extracted from the adjacent coarser scale classification. In this fusion process, the MRF (Markov random field) prior distribution and Gibbs sampler are used, where the MRF model serves as the smoothness constraint and the Gibbs sampler acts as the MAP classifier. The proposed segmentation method shows better performance than texture segmentation using the HMT (Hidden Markov trees) model and HMTseg.

• Proceedings of the KIEE Conference
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• 1996.07c
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• pp.1968-1970
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• 1996

We investigate a surface-micromachined polysilicon microgyroscope, whose resonant frequencies are electrostatically-tunable after fabrication. The microgyroscope with two oscillation nudes has been designed so that the resonant frequency in the sensing mode is higher than that in the actuating mode. The microgyroscope has been fabricated by a 4-mask surface-micrormachining process, including the deep RIE of a $6{\mu}m$-thick LPCVD polycrystalline silicon layer. The resonant frequency in the sensing mode has been lowered to that in actuating mode through the adjustment of an inter-plate bias voltage; thereby achieving a frequency matching at 5.8kHz under the bias voltage of 2V in a reduced pressure of 0.1torr. For an input angular rate of $50^{\circ}/sec$, an output signal of 20mV has been measured from the tuned microgyroscope under an AC drive voltage of 2V with a DC bias voltage of 3V.

• Advances in Computational Design
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• v.3 no.3
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• pp.269-288
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• 2018

180 different 2D numerical analyses have been carried out to estimate the factor of safety (FOS) for rooted slopes. Four different types of vegetated coverage and a variety of slope geometry considering three types of soil have been evaluated in this study. The highly influenced parameters on the slope's FOS are determined. They have been chosen as the input parameters for developing a new practical relationship to estimate the FOS with an emphasis on the roots effects. The dependency of sliding mode and shape considering the soil and roots-type has been evaluated by using the numerical finite element model. It is observed that the inclination and height of the slope and the coverage type are the most important effective factors in FOS. While the soil strength parameters and its physical properties would be considered as the second major group that affects the FOS. Achieved results from the developed relationship have shown the acceptable estimation for the roots slope. The extracted R square from the proposed relationship considering nonlinear estimation has been achieved up to 0.85. As a further cross check, the achieved R square from a multi-layer neural network has also been observed to be around 0.92. The numerical verification considering different scenarios has been done in the current evaluation.

• The KIPS Transactions:PartA
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• v.15A no.1
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• pp.17-26
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• 2008

This paper proposes an efficient caching mechanism appropriate for the integrated RFID middleware which can integrate wireless sensor networks (WSNs) and RFID (radio frequency identification) systems. The operating environment of the integrated RFID middleware is expected to face the situations of a significant amount of data reading from RFID readers, constant stream data input from large numbers of autonomous sensor nodes, and queries from various applications to history data sensed before and stored in distributed storages. Consequently, an efficient middleware layer equipping with caching mechanism is inevitably necessary for low latency of request-response while processing both data stream from sensor networks and history data from distributed database. For this purpose, the proposed caching mechanism includes two optimization methods to reduce the overhead of data processing in RFID middleware based on the classical cache implementation polices. One is data stream cache (DSC) and the other is history data cache (HDC), according to the structure of data request. We conduct a number of simulation experiments under different parameters and the results show that the proposed caching mechanism contributes considerably to fast request-response times.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.535-538
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• 1990

The main problem in speech recognition is the enormous variability in acoustic signals due to complex but predictable contextual effects. Especially in plosive consonants it is very difficult to find invariant cue due to various contextual effects, but humans use these contextual effects as helpful information in plosive consonant recognition. In this paper we experimented on three artificial neural net models for the recognition of plosive consonants. Neural Net Model I used "Multi-layer Perceptron ". Model II used a variation of the "Self-organizing Feature Map Model". And Model III used "Interactive and Competitive Model" to experiment contextual effects. The recognition experiment was performed on 9 Korean plosive consonants. We used VCV speech chains for the experiment on contextual effects. The speech chain consists of Korean plosive consonants /g, d, b, K, T, P, k, t, p/ (/ㄱ, ㄷ, ㅂ, ㄲ, ㄸ, ㅃ, ㅋ, ㅌ, ㅍ/) and eight Korean monothongs. The inputs to Neural Net Models were several temporal cues - duration of the silence, transition and vot -, and the extent of the VC formant transitions to the presence of voicing energy during closure, burst intensity, presence of asperation, amount of low frequency energy present at voicing onset, and CV formant transition extent from the acoustic signals. Model I showed about 55 - 67 %, Model II showed about 60%, and Model III showed about 67% recognition rate.