• ALGAE
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• v.19 no.2
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• pp.145-148
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• 2004

As a result of the 2-year monthly monitoring of the phytoplankton community at 3 stations in Mankyeong Estuary, Korea, we learned that cyan bacterial species of the genus Anabaena occurred at most sampling points with huge salinity differences (0.1-32.5 psu). We isolated several clones of Anabaena spp. from the monitoring stations, and screen out two euryhaline and nitrogen-fixing Anabaena clones, CB-MAL21 and CB-MAL22. The two clones were grown under various environmental gradients such as temperature (20, 30, 35 and 40$^{\circ}C$), salinity (0, 2, 5, 15 and 30psu), and $PO_4^{3-}$-P concentration (0, 1.6, 8.0, 40 and 200 ${\mu}M$M). Growth of CB-MAL21 and CB-MAL22 was measured by daily monitoring of chlorophyll fluorescence from each experimental culture for more than three serial transfers. Both the two experimental clones did not grow at 0psu. Maximal growth rates of the two clones were markedly reduced at lower $PO_4^{3-}$-P concentrations showing negligible growth at 0 and 1.6 ${\mu}M$M. However, growth of CB-MAL21 was not affected by low $NO_3^--$ concentration in culture media, showing the nitrogen-fixing ability. Maximum biomass yields of the two clones decreased dramatically at 35 and 40$^{\circ}C$. Optimal growth conditions for the two experimental clones were determined to be 20-30$^{\circ}C$, 40 ${\mu}M$M $PO_4^{3-}$-P, and wide salinity range from 5.0 to over 30psu. Best growth of CB-MAL21 was shown at (20$^{\circ}C$-15psu), which is less saline and cooler condition than those (i.e., 30$^{\circ}C$-30psu) for the best growth of CB-MAL22. The euryhaline and nitrogen-fixing CB-MAL21 strain thus can be a candidate laboratory culture for the future cyan bacterial marine biotechnology in temperate coastal waters.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.49-55
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• 2007

Recently, with the IPTV services, e-learning, real-time broadcasting and e-contents, many application services need the multicasting routing protocol. In this paper, the performance of the algorithm to assign the rendezvous router (RP: rendezvous point) in the center-based multicasting mesh network is analyzed. The estimated distance to select RP in the candidate nodes is calculated, and the node minimizing the distance is selected as the optimal RP. We estimate the distance by using the maximum distance, average distance, and mean of the maximum and average distance between the RP and members. The performance of the algorithm is compared with the optimal algorithm of all enumeration. With the assumptions of mesh network and randomly positioned for sources and members, the simulations for different parameters are studied. From the simulation results, the performance deviation between the algorithm with minimum cost and optimal method is evaluated as 6.2% average.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.25-33
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• 2017

NOMA (Non-orthogonal multiple access) system becoming a strong candidate for 5G cellular system of its high spectral efficiency. This paper considers an optimal power allocation scheme to minimize the outage probability of a user relay based cooperative NOMA system. We first derive the outage probabilities of the relay user (RU) and the destination user (DU) with selection combining. Based on these probabilities, the outage probability of the cooperative NOMA system is obtained. The analytical results are verified by Monte Carlo simulation. It is noticed that the outage probability of cooperative NOMA system has a convex function, the optimum power allocation coefficient, which satisfied the minimum outage probability, is calculated. Numerical examples show that the optimal power allocation coefficient increases with the required capacity of DU. While the capacity of DU is fixed, we noticed that the increase of the required capacity of RU decreases the optimal power allocation coefficient.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3A
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• pp.217-224
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• 2010

In this paper, we propose a hard handover algorithm for a base station's self-optimization, one of the automatic operational technologies for the 3GPP LTE systems. The proposed algorithm simultaneously considers a mixed target sell selection method for optimal selection and a multiple parameter based active hysteresis method with the received signal strength from adjacent cells and the cell load information of the candidate target cells from information exchanges between eNBs through X2 interface. The active hysteresis method chooses optimal handover hysteresis value considering the costs of the various environmental parameters effect to handover performance. The algorithm works on the optimal target cell and the hysteresis value selections for a base station's automatic operational optimization of the LTE system with the gathered informaton effects to the handover performance. The simulation results show distinguished handover performances in terms of the most important performance indexes of handover, handover failure rate and load balancing.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.1
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• pp.57-70
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• 2004

Given a tree network on which each node has its own demand and also stands for a candidate location of a potential facility. such as plant or warehouse, the f-median problem on the network (PMPOT) is to select less than or equal to P number of facility locations so that the whole demand on a node is satisfied from only one facility and the total demand occurred on the network can be satisfied from those facilities with the minimum total cost, where the total cost Is the sum of transportation costs and the fixed costs of establishing facilities. Tamir(1996) developed an O(p n$^2$) algorithm for PMPOT which is known to be the best algorithm In terms of the time complexity, where n is the number of nodes in the network, but he didn't make any comments or explanation about implementation details for finding the optimal solution. In contrast to Tamir's work, Kariv and Hakimi(1979) developed O(p$^2$n$^2$) algorithm for PMPOT and presented O(n$^2$) algorithm for finding the optimal solution in detail. In this paper, we not only develop another O(p n$^2$) dynamic programming algorithm for PMPOT that is competitive to Tamir's algorithm in terms of the time complexity, but also present O(n) algorithm that is more efficient than kariv and Hakimi's algorithm in finding the optimal solution. finally, we implement our algorithm on a set of randomly generated problems and report the computational results.

• Microbiology and Biotechnology Letters
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• v.46 no.4
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• pp.377-389
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• 2018

In this study, a novel microalgal strain, Desmodesmus sp. KAERI-NJ5, was isolated, identified, and evaluated as a candidate for biodiesel feedstock. In a preliminary study, the effects of four general microalgal growth factors, including temperature, pH, light intensity, and concentration of nitrogen source ($KNO_3$), on the microalgal photoautotrophic growth were evaluated. With the exception of light intensity, the growth factors needed to be optimized for the microalgal biomass production. Optimization was done using response surface methodology. The optimal conditions for biomass production were pH 6.54, $27.66^{\circ}C$, and 0.52 g/l $KNO_3$. The biomass production at the optimal conditions was 1.55 g/l, which correlated well with the predicted value of 1.5 g/l. The total lipid and fatty acid methyl ester contents of the cells grown at the optimal conditions were 49% and 21.2% of cell dry weight, respectively. To increase the lipid content of the biomass, microalgae were challenged by nitrogen starvation. Enhancement of total lipid and fatty acid content up to 52.02% and 49%, respectively, were observed. Lipid analysis of the nitrogen-starved cells revealed that C16 and C18 species accounted for 95.9% of the total fatty acids. Among them, palmitic acid (46.17%) and oleic acid (39.43%) dominantly constituted the algal fatty acids. These results suggest Desmodesmus sp. KAERI-NJ5 as a promising feedstock for biodiesel production.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.171-176
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• 2004

Image matching is fundamental process in photogrammetry and computer vision to identify and to measure corresponding features on the multiple images. Uniqueness of the matching entities and robustness of the algorithm are the key issues that have influence on quality of the matching result. The optimal solution could be obtained by utilizing appropriate matching entities in the first place. In this study, candidate matching points were extracted by interest operator, and an area-based matching method was applied with characteristics of the gray value distribution as the matching entities. The characteristic information is based on the concept of "intrinsic image" (or parameter image). The information was utilized as additional and/or complementary matching entities. Matching on interest points with the characteristic information resulted in high quality of matching because matching windows were created with surrounding pixels of the interest points that contain distinct and unique features. The experiment shows that matching quality and reliability increase by exploiting interest operator, and the characteristic information has potential to be matching entity.

• Smart Structures and Systems
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• v.20 no.1
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• pp.1-10
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• 2017

Ionic Polymer Metal Composite (IPMC) is an electroactive polymer (EAP) and a promising candidate actuator for various potential applications mainly due to its flexible, low voltage/power requirements, small and compact design, and lack of moving parts. Although widely used in industry, this material requires accurate numerical models and knowledge of optimal control methods. This paper presents State-Dependent Riccati Equation (SDRE) approach as one of rapidly emerging methodologies for designing nonlinear controllers. Additionally, the present paper describes a novel method of Multi HGO Observer design. In the proposed design, the calculated position of the IPMC strip accurately tracks the target position, which is illustrated by the experiments. Numerical results and comparison with experimental data are presented and the effectiveness of the proposed control strategy is verified in experiments.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.1
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• pp.1-9
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• 2011

This paper presents a new method that can solve the integrated problem of combined location routing and inventory problem (CLRIP) efficiently. The CLRIP is used to establish facilities from several candidate depots, to find the optimal set of vehicle routes, and to determine the inventory policy in order to minimize the total system cost. We propose a mathematical model for the CLRIP with budget constrained. Because this model is a nonpolynomial (NP) problem, we propose a endosymbiotic evolutionary algorithm (EEA) which is a kind of symbiotic evolutionary algorithm (SEA). The heuristic method is used to obtaining the initial solutions for the EEA. The experimental results show that EEA perform very well compared to the existing heuristic methods with considering inventory control decisions.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.9-17
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• 1988

This vehicle scheduling problem with multiple depots and multiple vehicle types (VMM) is to determine the optimal vehicle routes to minimize the total travel costs. The object of this paper is to develope an exact algorithm for the VMM. In this paper the VMM is transformed into a mathematical model of the vehicle problem with multiple depots. Then an efficient branch and bound algorithm is developed to obtain an exact solution for this model. In order to enhance the efficiency, this algorithm emphasizes the follows; First, a heuristic algorithm is developed to get a good initial upper bound. Second, an primal-dual approach is used to solve subproblems which are called the quasi-assignment problem, formed by branching strategy is presented to reduce the number of the candidate subproblems.