• KSBB Journal
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• v.7 no.4
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• pp.308-316
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• 1992

Two-stage continuous culture system has been studied intensively to maximize the productivity of a cloned gene product in unstable recombinant microorganism. As an effort to optimize the two-stage process, transient behavior of the second-stage was studied theoretically as well as experimentally using Escherichia coli Kl2$\delta$Hl$\delta$trp. A mathematical model describing the transient response to a step change in dilution rate was developed based on the assumption that the adaptation rate of cell growth is proportional to the available growth potential, which is defined as the difference in dilution rates between before and after shift-up. The kinetic parameters appearing in the model equations were the dimensionless step increase in growth rate($\alpha$) and the adaptation rate constant(k). These parameters were evaluated for various dilution rates and temperatures by washout method. This relatively simple adaptation model could predict the specific growth rate of the second-stage successfully. Advantage and disadvantage of the proposed model are also discussed.

• Journal of Microbiology and Biotechnology
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• v.2 no.2
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• pp.141-151
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• 1992

Physiological changes of the murine hybridoma cell line $S3H5/\gamma{2bA2}$ during adaptation to RPMI 1640 medium with 1%(v/v) fetal bovine serum were characterized in terms of cell growth, antibody production, morphology, and metabolic quotients. Cells adapted to 1% serum medium in T-flasks became sensitive to shear induced by mechanical agitation and required at least 5% serum in the medium or spent medium for cell growth in spinner flasks, while cells adapted to 10% serum medium in T-flasks could grow in 1% serum medium in spinner flasks. Consequently, long-term adaptation to low serum media may not give the expected growth enhancement. After adaptation to 1% serum medium, changes in cell morphology were observed. The cells in 10% serum medium were uniform and circular, while cells in 1% medium were irregularly shaped. The DNA contents, which were measured by flow cytometry, were almost constant among the cells in the range of 1% to 10%. Further, no significant changes in energy metabolism and specific monoclonal antibody production rate were observed among these cells.

• Journal of Environmental Impact Assessment
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• v.25 no.4
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• pp.296-306
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• 2016

There is a growing interest in establishing a regional climate change adaptation policy as the climate change impact in the region and local scale increases. This study focused on the analysis of 32 regions on its characteristics of local climate change adaptation plans. First, statistic program R was used for conducting cluster analysis based on the frequency and budgets of adaptation plan. Further, we analyzed damage frequency from newspapers regarding climate change impacts in eight categories which were caused by extreme weather events on 2,565 cases for 24 years. Lastly, the characteristics of climate change adaptation plan was compared with damage frequency patterns for evaluating the adequacy of climate change adaptation plan on each cluster. Four different clusters were created by cluster analysis. Most clusters clearly have their own characteristics on certain sectors. There was a high frequency of damage in 'disaster' and 'health' sectors. Climate change adaptation plan and budget also invested a lot on those sectors. However, when comparing the relative rate among regional governments, there was a difference between types of damage and climate change adaptation plan. We assumed that the difference could come from that each region established their adaptation plans based on not only the frequency of damage, but vulnerability assessment, and expert opinions as well. The result of study could contribute to policy making of climate change adaptation plan.

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.68-74
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• 2019

Along with the deeper architecture in the deep learning approaches, the need for the data becomes very big. In the real problem, to get huge data in some disciplines is very costly. Therefore, learning on limited data in the recent years turns to be a very appealing area. Meta-learning offers a new perspective to learn a model with this limitation. A state-of-the-art model that is made using a meta-learning framework, Meta-SGD, is proposed with a key idea of learning a hyperparameter or a learning rate of the fast adaptation stage in the outer update. However, this learning rate usually is set to be very small. In consequence, the objective function of SGD will give a little improvement to our weight parameters. In other words, the prior is being a key value of getting a good adaptation. As a goal of meta-learning approaches, learning using a single gradient step in the inner update may lead to a bad performance. Especially if the prior that we use is far from the expected one, or it works in the opposite way that it is very effective to adapt the model. By this reason, we propose to add a weight term to decrease, or increase in some conditions, the effect of this prior. The experiment on few-shot learning shows that emphasizing or weakening the prior can give better performance than using its original value.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4585-4603
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• 2015

Video streaming services make up a large proportion of Internet traffic on both fixed and mobile access throughout the world. Adaptive streaming allows for dynamical adaptation of the bitrate with varying network conditions, to guarantee the best user experience. Adaptive bitrate algorithms face a significant challenge in correctly estimating the throughput as it varies widely over time. In this paper, we first evaluate the throughput estimation techniques and show that the method that we have used offers stable response to throughput fluctuations while maintaining a stable playback buffer. Then, we propose an adaptive bitrate scheme that intelligently selects the video bitrates based on the estimated throughput and buffer occupancy. We show that the proposed scheme improves viewing experience by achieving a high video rate without taking unnecessary risks and by minimizing the frequency of changes in the video quality. Furthermore, we show that it offers a stable response to short-term fluctuations and responds swiftly to large fluctuations. We evaluate our algorithm for both constant bitrate (CBR) and variable bitrate (VBR) video content by taking into account the segment sizes and show that it significantly improves the quality of video streaming.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2144-2159
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• 2015

CISCO VNI predicted an average annual growth rate of 66% for mobile video traffic between 2014 and 2019 and accordingly much academic research related to video streaming has been initiated. In video streaming, Adaptive Bitrate (ABR) is a streaming technique in which a source video is stored on a server at variable encoding rates and each streaming user requests the most appropriate video encoding rate considering their channel capacity. However, these days, ABR related studies are only focusing on real-time rate adaptation omitting energy efficiency though it is one of the most important requirement for mobile devices, which may cause dissatisfaction for streaming users. In this paper, we propose an energy efficient prefetching based dynamic adaptive streaming technique by considering the limited characteristics of the batteries used in mobile devices, in order to reduce the energy waste and provide a similar level of service in terms of the average video rate compared to the latest ABR streaming technique which does not consider the energy consumption. The simulation results is showing that our proposed scheme saves 65~68% of energy at the average global mobile download speed compared to the latest high performance ABR algorithm while providing similar rate adaptation performance.

• KSBB Journal
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• v.16 no.6
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• pp.626-631
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• 2001

Lactobacilli have been considered to play important roles in the health of human vagina. They secrete inhibitory substances to prevent vaginal infection by pathogenic organisms. In a previous study, we have isolated several lactobacilli from Korean woman and one of them (KLB46) was selected and indentified as Lactobacillu crispatus which showed high antimicrobial activity. In this study. cold adaptation prior to subsequent stresses exposure was examined whether L. crispatus KLB46 maintain the viability better than the non-adapted calls under stresses. For pharmaceutical formulation, the lyophilization process is required where stresses such as freezing/thawing and dehydration are routinely applied. Formulated L. crispatus KLB46 can be used for ecological treatment of bacterial vaginosis. The response of cold-adapted cells to other environmental stresses such as acid, heat, ethanol, NaCl, and H$_2$O$_2$ was also examined. The results showed that cold-adapted cells maintained higher survival rate compared with the non-adapted cells (freezing-thawing. 3-folds; dehydration: 3-folds; acid, 3-folds; heat, 10-folds). However, we did net observe any positive effect of cold adaptation on other stresses such as ethanol, NaCl and H$_2$O$_2$. When chloramphenicol was added during cold adaptation, adaptation effect was abolished. This confirms that de novo protein synthesis is necessary during the adaptation process. Moreover, we have identified cold shock protein homolog that codes for a major cold shock protein by PCR amplification using degenerate primers.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.566-571
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• 2009

This paper proposes noise-robust fast speaker adaptation method based on the eigenvoice framework in various noisy environments. The proposed method is focused on de-noising and environment clustering. Since the de-noised adaptation DB still has residual noise in itself, environment clustering divides the noisy adaptation data into similar environments by a clustering method using the cepstral mean of non-speech segments as a feature vector. Then each adaptation data in the same cluster is used to build an environment-clustered speaker adapted (SA) model. After selecting multiple environmentally clustered SA models which are similar to test environment, the speaker adaptation based on an appropriate linear combination of clustered SA models is conducted. According to our experiments, we observe that the proposed method provides error rate reduction of $40{\sim}59%$ over baseline with speaker independent model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10B
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• pp.1150-1158
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• 2011

More than 100 Mbps rate is needed in the UBcN for a subscriber to receive broadband traffics with multi-channel like UDTV or 3DTV. Although the optical fiber is recently deployed for the FTTH, the UTP is the most widely used medium and will be used in UBcN age. Network providers may consider the 1000BASE-T or the vectorized VDSL if they adopts the UTP in the place where does not have optical fibers. But UTP should be expanded because 1000BASE-T and vectorized UTP needs 4 and 3 pairs cable, respectively while residential region has not exceeding 2 pair UTP cable. To solve the problem, we propose a 500BASE-T technology using 2 pairs UTP in this paper. The technology introduces a rate adaptation sublayer and a SERDES sublayer above and under the PCS, respectively. The rate adaptation sublayer is compatible for the GMII. Also, if we modify the SERDES sublayer, the technology can easily obtain 250BASE-T with 2 pairs UTP. We implement such functions with FPGA and analog board and verify the function of rate adaptation and symbol vector synchronization, and effective transmission rate by experiments. In particular, we show that link efficiency is increased by enable control in the rate adaptation sublayer.

• ETRI Journal
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• v.32 no.1
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• pp.160-162
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• 2010

For the acoustic models of embedded speech recognition systems, hidden Markov models (HMMs) are usually quantized and the original full space distributions are represented by combinations of a few quantized distribution prototypes. We propose a maximum likelihood objective function to train the quantized distribution prototypes. The experimental results show that the new training algorithm and the link structure adaptation scheme for the quantized HMMs reduce the word recognition error rate by 20.0%.