• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.51 no.12
• /
• pp.597-602
• /
• 2002

The restructuring of power industry is still going on all over the world for last several decades. Many kinds of restructuring model have been studied, proposed, and applied. Among those models, power pool is more popular than other. This paper assumes the power pool market structure having competitive generation sector, and a new method is presented to build a bidding strategy in that market. The utilities participating in the market have the perfect information of their cost and price functions, but they don't know which strategy to be chosen by others. To define one's strategy as a vector, we make utility's cost/price functions into discrete step functions. An utility knows only his own strategy, so he estimates the other's cost/price functions into discrete step functions. An utility knows only his own strategy, so he estimates the other's strategy using Nash equilibrium or stochastic methods. And he also has to forecast the system demand. According to this forecasting result, his payoffs can be changed. Considering these all conditions, we formulate a bidding game problem and apply noncooperative game theory to that problem for the optimal strategy or solution. Some restrictive assumption are added for simplification of solving process. A numerical example is given in Case Study to show essential features and concrete results of this approach.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.1A
• /
• pp.101-108
• /
• 2007

There nay be collisions among beacons from several full function devices in IEEE 802.15.4 sensor networks. These collision of beacons may cause devices to lose time synchronization, and thus be unable to association. To solve this problem, the IEEE 802.15.4b defines a new Post Beacon Period(PBP), but it does not still alleviate the beacon collision problem. In this paper, we propose two automatic beacon alignment schemes that a node itself can decide its beacon start time using its short address that has been assigned during association. We also simulate and investigate our proposed automatic beacon collision avoidance schemes using NS-2 simulator.

• Genomics & Informatics
• /
• v.8 no.2
• /
• pp.63-69
• /
• 2010

Monofunctional biosynthetic peptidoglycan transglycosylase (MBPT) catalyzes the formation of the glycan chain in bacterial cell walls from peptidoglycan subunits: N-acetylglucosamine (NAG) and acetylmuramic acid (NAM). Bifunctional glycosyltransferases such as the penicillin binding protein (PBP) have peptidoglycan glycosyltransferase (PGT) on their C terminal end which links together the peptidoglycan subunits while transpeptidase (TP) on the N terminal end cross-links the peptide moieties on the NAM monosaccharide of the peptide subunits to create the bacterial cell wall. The singular function of MBPT resembles the C terminal end of PBP as it too contains and utilizes a similar PGT domain. In this article we analyzed the infectious and non infectious protein sequences of MBPT from 31 different strains of bacteria using a variety of bioinformatic tools. Motif analysis, dot-plot comparison, and phylogenetic analysis identified a number of significant differences between infectious and non-infectious protein sequences. In this paper we have made an attempt to explain, analyze and discuss these differences from an evolutionary perspective. The results of our sequence analysis may open the door for utilizing MBPT as a new target to fight a variety of infectious bacteria.

• ETRI Journal
• /
• v.44 no.5
• /
• pp.733-745
• /
• 2022

In software-defined wireless networking (SDWN), the optimal routing technique is one of the effective solutions to improve its performance. This routing technique is done by many different methods, with the most common using integer linear programming problem (ILP), building optimal routing metrics. These methods often only focus on one routing objective, such as minimizing the packet blocking probability, minimizing end-to-end delay (EED), and maximizing network throughput. It is difficult to consider multiple objectives concurrently in a routing algorithm. In this paper, we investigate the application of machine learning to control routing in the SDWN. An intelligent routing algorithm is then proposed based on the machine learning to improve the network performance. The proposed algorithm can optimize multiple routing objectives. Our idea is to combine supervised learning (SL) and reinforcement learning (RL) methods to discover new routes. The SL is used to predict the performance metrics of the links, including EED quality of transmission (QoT), and packet blocking probability (PBP). The routing is done by the RL method. We use the Q-value in the fundamental equation of the RL to store the PBP, which is used for the aim of route selection. Concurrently, the learning rate coefficient is flexibly changed to determine the constraints of routing during learning. These constraints include QoT and EED. Our performance evaluations based on OMNeT++ have shown that the proposed algorithm has significantly improved the network performance in terms of the QoT, EED, packet delivery ratio, and network throughput compared with other well-known routing algorithms.

• Korean Chemical Engineering Research
• /
• v.50 no.4
• /
• pp.646-653
• /
• 2012

We studied the economic evaluations on Korea Institute of Energy Research (KIER)'s $CO_2$ capture process using dry sorbents, and compared the results with those of comparable technologies. Capital and operating costs of the $CO_2$ capture system for 500 MW coal fired power plant were estimated to determine the economic feasibility. LCOE (Levelized Cost of Energy) and $CO_2$ capture cost appeared 32.46$/MWh and 28.15$/ton$CO_2$, respectively. The internal rate of return (IRR), the net present values (NPV), and the payback period (PBP), were calculated by assuming several variables. As the result of calculation, IRR of KIER's $CO_2$ capture system was 15%, NPV was calculated 6,631,000$, and PBP was 5.93 years at $50/t$CO_2$ of CER price. Consequently, this process can compete with other comparative processes using dry sorbents.

• Journal of Food Hygiene and Safety
• /
• v.23 no.2
• /
• pp.121-128
• /
• 2008

The aim of this study was to develop a LightCycler-based real time PCR (LC-PCR) assay and to evaluate its diagnostic use for the detection of Staphylococcus aureus in raw milk samples. Following amplification of 113 bp of coa gene encoding an coagulase precursor specific for Staphylococcus aureus, melting curve and DNA sequencing analysis was performed to verify the specificity of the PCR products. Amplification of 209 bp gene encoding an altered penicillin-binding protein, PBP2a (mecA), melting curve analysis and DNA sequencing analysis was performed to verify methicillin resistance Staphylococcus aureus (MRSA). According to this study, 6 of 647 raw milk samples showed S. aureus positive and 2 of them showed a mecA positive and the detection limit was 10 fg of DNA. And we also isolated Staphylococcus chromogenes a causative agent of exudative epidermitis in pigs and cattle from 3 samples.

• Journal of Microbiology and Biotechnology
• /
• v.26 no.4
• /
• pp.784-789
• /
• 2016

We evaluated the synergistic antibacterial effect in combination with the chitosan-ferulic acid conjugate (CFA) and β-lactam antibiotics, such as ampicillin, penicillin, and oxacillin, against methicillin-resistant Staphylococcus aureus (MRSA) using fractional inhibitory concentration (FIC) indices. CFA clearly reversed the antibacterial activity of ampicillin, penicillin, and oxacillin against MRSA in the combination mode. Among these antibiotics, the combination of oxacillin-CFA resulted in a ΣFIC_min range of 0.250 and ΣFIC_max of 0.563, suggesting that the oxacillin-CFA combination resulted in an antibacterial synergy effect against MRSA. In addition, we determined that CFA inhibited the mRNA expression of gene mecA and the production of PBP2a, which is a key determinant for β-lactam antibiotic resistance, in a dose-dependent manner. Thus, the results obtained in this study supported the idea on the antibacterial action mechanism that oxacillin will restore the antibacterial activity against MRSA through the suppression of PBP2a production by CFA.

• Proceedings of the Korean Society of Applied Pharmacology
• /
• 1994.04a
• /
• pp.171-171
• /
• 1994

Cephem ring의 C-7위치에 aminothiazoly lmethoxyimino기를 가진 화합물들이 항균활성을 증가시키고, G(-)균의 외막투과성을 촉진시킬뿐 아니라 광범위항균 spectrum을 갖게 하고 $\beta$-lactamase에 안정하며 PBP(penicillin binding protein)에 대한 결합친화성을 증가시킨다는 보고에 따라 본 저자는 C-7위치에 cefotaxime구조와 같이 aminothiazolylmethoxyimino acetamido moiety를 고정시키고 항균활성을 증가시키기 위하여 약리활성이 기대되는 5-(substituted)-2H-tetrazole유도체들을 합성하여 C-3 위치에 도입시킨 새로운 화합물 7$\beta$-〔(z)-2-(2-aminothiazol-4-yl)-2_(methoxyimino)acetamido〕-3-〔5-(substituted)tetrazol-2-yl〕 methyl-3-cephem-4-carboxylic acid 유도체를 합성하여 B. subtilis ATCC 6633, M. luteus ATCC 1004, E. coli KCTC 1039, E. coli ESS, K. pncumonia KCTC 1560, P. aeruginosa IF0 13130, S. typhimurium KCTC 1925, S. typhimurium SL 1102, 및 C. albicans ATCC 10231 등의 균과 fungus에 대하여 기존의 cefotaxime과 cefazoline을 대조물질로 사용하여 항균력을 비교하였다. 이들 화합물들은 대체적으로 M. luteus ATCC 6633, E. coli ESS, S. typhimurium SL 1102 균에 대해서는 cefotaxime보다 항균력이 우수하였으나 P. aeruginosa IF0 13130에 대해서는 항균력이 저하되었고 cefazolin보다는 대체적으로 항균력이 우수하였다.

• Proceedings of the KIEE Conference
• /
• 2006.07a
• /
• pp.378-379
• /
• 2006

향후 나타날 가격 입찰방식 시장(Price-Bidding Generation Pool; PBP)에서는 발전사업자가 전략적으로 제출하는 비용특성에 의해 전력거래가 결정되기 때문에 상대기업의 비용특성을 정확히 안다는 것은 힘들다. 본 연구는 경쟁상황에서 상대사업자의 비용특성을 모르는 경우, 비용특성을 추정하고 추정을 통해 입찰전략을 결정하는 기법을 제안한다. 추정은 시장실적을 이용하여 이루어지며 이득을 최대화시킬 것이라 예상되는 입찰전략을 결정한다. 또한 정확성을 높이기 위해 평균이득 개념을 사용하여 추정을 시도한다.

• 한국HCI학회:학술대회논문집
• /
• 2007.02a
• /
• pp.256-261
• /
• 2007

본 논문은 이미지 완성(Image Completion)을 위한 근사적 에너지 최적화 알고리즘을 제안한다. 이미지 완성이란 이미지의 특정영역이 지워진 상태에서, 그 지워진 부분을 나머지 부분과 시각적으로 어울리도록 완성시키는 기법을 말한다. 본 논문에서 이미지 완성은 유사-확률적(pseudo-probabilistic) 시스템인 Markov Random Field로 모델링된다. MRF로 모델링된 이미지 완성 시스템에서 사후 확률(posterior probability)을 최대로 만드는 MAP(Maximum A Posterior) 문제는 결국 시스템의 전체 에너지를 낮추는 에너지 최적화 문제와 동일하다. 본 논문에서는 MRF의 최적화 알고리즘들 중에서 Belief Propagation 알고리즘을 이용한다. BP 알고리즘이 이미지 완성 분야에 적용될 때 다음 두 가지가 계산시간을 증가시키는 요인이 된다. 첫 번째는 완성시킬 영역이 넓어 MRF를 구성하는 정점의 수가 증가할 때이다. 두 번째는 비교할 후보 이미지 조각의 수가 증가할 때이다. 기존에 제안된 Priority-Belief Propagation 알고리즘은 우선순위가 높은 정점부터 메시지를 전파하고 불필요한 후보 이미지 조각의 수를 제거함으로써 이를 해결하였다. 하지만 우선순위를 정점에 할당하기 위한 최초 메시지 전파의 경우 Belief Propagation의 단점은 그대로 남아있다. 이를 개선하기 위해 본 논문에서는 이미지 완성을 위한 MRF 모델을 피라미드 구조와 같이 층위로 나누어 정점의 수를 줄이고, 계층적으로 메시지를 전파하여 시스템의 적합성(fitness)을 정교화 해나가는 Hierarchical Priority Belief Propagation 알고리즘을 제안한다.