• Bulletin of the Korean Mathematical Society
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• v.51 no.2
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• pp.519-530
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• 2014

Let (R,m) be a Noetherian local ring and M a finitely generated R-module. For an integer s > -1, we say that M is Cohen-Macaulay in dimension > s if every system of parameters of M is an M-sequence in dimension > s introduced by Brodmann-Nhan [1]. In this paper, we give some characterizations for Cohen-Macaulay modules in dimension > s in terms of the Noetherian dimension of the local cohomology modules $H^i_m(M)$, the polynomial type of M introduced by Cuong [5] and the multiplicity e($\underline{x}$;M) of M with respect to a system of parameters $\underline{x}$.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.10a
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• pp.195-200
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• 2007

We analyzed a sequence of multi-stage automatic cold forging processes composed of four axisymmetric processes followed by a non-axisymmetric process using rigid-plastic finite element based forging simulators. The forging sequence selected for an example involves a piercing process and a heading process accompanying folding or overlapping, which all make it difficult to simulate the processes. To reduce computational time and to enhance the solution reliability, only the non-symmetric process was analyzed by the three-dimensional approach after the axisymmetric processes were analyzed by the two-dimensional approach. It has been emphsized that this capability is very helpful in simulating the multi-stage automatic forging processes which are next to axisymmetric.

• Transactions of Materials Processing
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• v.17 no.3
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• pp.155-160
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• 2008

We analyzed a sequence of multi-stage automatic cold forging processes composed of four axisymmetric processes followed by a non-axisymmetric process using rigid-plastic finite element based forging simulators. The forging sequence selected for an example involves a piercing process and a heading process accompanying folding or overlapping, which all make it difficult to simulate the processes. To reduce computational time and to enhance the solution reliability, only the non-symmetric process was analyzed by the three-dimensional approach after the axisymmetric processes were analyzed by the two-dimensional approach. It has been emphsized that this capability is very helpful in simulating the multi-stage automatic forging processes which are next to axisymmetric or involve several axisymmetric processes.

• KSBB Journal
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• v.21 no.6 s.101
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• pp.451-455
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• 2006

An efficient pilot scale (10 ton) three-stage methane fermentation system to digest food waste has been developed in this laboratory. This system consisted of three stages: semianaerobic hydrolysis, anaerobic acidogenesis and strictly anaerobic methanogenesis. From the secondary acidogenesis reactor, a novel strain KA4 responsible for alcohol fermentation was isolated and characterized. The cell was oval and its dimension was $5.5-6.5{\times}3.5-4.5\;{\mu}m$. This strain was identified as Saccharomyces cerevisiae KA4 by 26S rDNA D1/D2 rDNA sequence. Optimal culture temperature was $30-35^{\circ}C$. Cells were tolerant to 5% (v/v) ethanol concentration, however, were inhibited significantly by higher ethanol concentration up to 7%. The strain could grow well up to 50% (w/v) initial glucose concentration in the YM liquid medium, however, optimal concentration for ethanol fermentation was 10%. It could produce ethanol in a broad initial pH range from 4 to 10, and optimal pH was 6. In this condition, the strain converted 10% glucose to 7.4% ethanol during 24 hr, and ethanol yield was estimated to be 2.87 moi EtOH/mol glucose.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.57-65
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• 2018

Conventional RF signal-based indoor localization techniques such as BLE or Wi-Fi based fingerprinting method show considerable localization errors even in small-scale indoor environments due to unstable received signal strength(RSS) of RF signals. Therefore, it is difficult to apply the existing RF-based fingerprinting techniques to large-scale indoor environments such as airports and department stores. In this paper, instead of RF signal we use the geomagnetic sensor signal for indoor localization, whose signal strength is more stable than RF RSS. Although similar geomagnetic field values exist in indoor space, an object movement would experience a unique sequence of the geomagnetic field signals as the movement continues. We use a deep neural network model called the recurrent neural network (RNN), which is effective in recognizing time-varying sequences of sensor data, to track the user's location and movement path. To evaluate the performance of the proposed geomagnetic field based indoor positioning system (IPS), we constructed a magnetic field map for a campus testbed of about $94m{\times}26$ dimension and trained RNN using various potential movement paths and their location data extracted from the magnetic field map. By adjusting various hyperparameters, we could achieve an average localization error of 1.20 meters in the testbed.