• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.8
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• pp.484-489
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• 2004

When the energy resource available to a particular plant (be it coal, oil, gas, water, or nuclear fuel) is a limiting factor in the operation of the plant, the entire economic dispatch calculation must be done differently. Each economic dispatch calculation must account for what happened before and what will happen in the future. This paper presents a formulation and a solution method for the optimization problem with a fuel constraint in a competitive electricity market. Take-or- Pay (TOP) contract for an energy resource is the typical constraint as a limiting factor. Two approaches are proposed in this paper for modeling the dispatch calculation in a market mechanism. The approaches differ in the subject who considers and inserts the fuel-constraint into its optimization problem. Market operator and each power producer having a TOP contract are assumed as such subjects. The two approaches are compared from the viewpoint of profits. surplus. and social welfare on the basis of Nash Equilibrium.

• Journal of Microbiology and Biotechnology
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• v.26 no.8
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• pp.1428-1438
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• 2016

In the present work, Arthrobacter sp. 25, a lead-tolerant bacterium, was assayed to remove lead(II) from aqueous solution. The biosorption process was optimized by response surface methodology (RSM) based on the Box-Behnken design. The relationships between dependent and independent variables were quantitatively determined by second-order polynomial equation and 3D response surface plots. The biosorption mechanism was explored by characterization of the biosorbent before and after biosorption using atomic force microscopy (AFM), scanning electron microscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, and Fourier transform infrared spectroscopy. The results showed that the maximum adsorption capacity of 9.6 mg/g was obtained at the initial lead ion concentration of 108.79 mg/l, pH value of 5.75, and biosorbent dosage of 9.9 g/l (fresh weight), which was close to the theoretically expected value of 9.88 mg/g. Arthrobacter sp. 25 is an ellipsoidal-shaped bacterium covered with extracellular polymeric substances. The biosorption mechanism involved physical adsorption and microprecipitation as well as ion exchange, and functional groups such as phosphoryl, hydroxyl, amino, amide, carbonyl, and phosphate groups played vital roles in adsorption. The results indicate that Arthrobacter sp. 25 may be potentially used as a biosorbent for low-concentration lead(II) removal from wastewater.

• Korean Chemical Engineering Research
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• v.58 no.3
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• pp.346-355
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• 2020

This study proposed a new optimization-based decision model for an enterprise resource planning and production scheduling of a pharmaceutical intermediates manufacturing plant. To do this work, we first define the inflow and outflow information as well as the model structure, and develop an optimization model to minimize the production time (i.e., makespan) using a mixed integer linear programing (MILP). The unique feature of the proposed model is that the optimal process scheduling is established based on real-time resource logistics information using a radio frequency identification (RFID) technology, thereby theoretically requiring no material inventories. essential information for process operation, such as the required amount of raw materials and estimated arrival timing to manufacturing plant, is used as logistics constraints in the optimization model to yield the optimal manufacturing scheduling to satisfy final production demands. We illustrated the capability of the proposed decision model by applying the optimization model to two scheduling problems in a real pharmaceutical intermediates manufacturing process. As a result, the optimal production schedule and raw materials order timing were identified to minimize the makespan while satisfying all the product demands.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5701-5722
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• 2018

The continuous increase in the cost of energy production and concerns for environmental sustainability are leading research communities, governments and industries to amass efforts to reduce energy consumption and global $CO_2$ footprint. Players in the information and communication industry are keen on reducing the operational expenditures (OpEx) and maintaining the profitability of cellular networks. Meanwhile, network virtualization has been proposed in this regard as the main enabler for 5G mobile cellular networks. In this paper, we propose a generic framework of slice resource provisioning and customized physical resource allocation for energy-efficiency and quality of service optimization. In resource slicing, we consider user demand and population resources provisioning scheme aiming to satisfy quality of service (QoS). In customized physical resource allocation, we formulate this problem with an integer non-linear programming model, which is solved by a heuristic algorithm based on minimum vertex coverage. The proposed algorithm is compared with the existing approaches, without consideration of slice resource constraints via system-level simulations. From the perspective of infrastructure providers, traffic is scheduled over a limited number of active small-cell base stations (sc-BSs) that significantly reduce the system energy consumption and improve the system's spectral efficiency. From the perspective of virtual network operators and mobile users, the proposed approach can guarantee QoS for mobile users and improve user satisfaction.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.7
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• pp.219-230
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• 2014

In the cloud computing environment, cloud service users purchase and use the virtualized resources from cloud resource providers on a pay as you go manner. Typically, there are two billing plans for computing resource allocation adopted by large cloud resource providers such as Amazon, Gogrid, and Microsoft, on-demand and reserved plans. Reserved Virtual Machine(VM) instance is provided to users based on the lengthy allocation with the cheaper price than the one of on-demand VM instance which is based on shortly allocation. With the proper mixture allocation of reserved and on-demand VM corresponding to users' requests, cloud service providers are able to reduce the resource allocation cost. To do this, prior researches about VM allocation scheme have been focused on the optimization approach with the users' request prediction techniques. However, it is difficult to predict the expected demands exactly because there are various cloud service users and the their request patterns are heavily fluctuated in reality. Moreover, the previous optimization processing techniques might require unacceptable huge time so it is hard to apply them to the current cloud computing system. In this paper, we propose the cloud brokering system with the adaptive VM allocation schemes called A3R(Adaptive 3 Resource allocation schemes) that do not need any optimization processes and kinds of prediction techniques. By using A3R, the VM instances are allocated to users in response to their service demands adaptively. We demonstrate that our proposed schemes are able to reduce the resource use cost significantly while maintaining the acceptable Quality of Service(QoS) of cloud service users through the evaluation results.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.283-284
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• 2008

A cross-layer optimization is becoming a popular design methodology for the IP based next generation wireless network. We begin by investigating a cross-layer optimization scheme to enhance the system performance in wireless networks. By applying cross-layer optimization methodology to WiBro distributed network, the WiBro systems are expected to gain significant performance improvement and resource utilization enhanced. For further study we highlight some open challenges and new opportunities for cross-layer design.

• The Korean Journal of Pesticide Science
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• v.14 no.2
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• pp.138-147
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• 2010

Nematicidal activity against pine wood nematode, Bursaphelenchus xylophilus, was tested in the pot and field by the treatment of microbial formulation after media optimization. The optimized media composition was glycerol 10 g, soybean meal 10 g, NaCl 1 g, $CaCO_3$ 2 g, $K_2HPO_4$ 0.125 g per liter and microbial complex formulation was made with liquid and powder type. Most effective antibiotics against symbiotic microorganism with nematode, kanamycin, was added to the formulation. The control effects against pine wood nematodes were checked by pot test and field test. In the result of treatment by trunk injection, five times treatment was more effective than one time and the treatment with the formulation of concentrated culture supernatant was the most effective in the nematicidal activity showing below 10% mortality in pine tree.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.554-565
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• 2012

In this paper, we study a cross-layer and end-to-end optimization problem for the integrated wireless and wireline network that consists of one wireline core network and multiple wireless access networks. We consider joint end-to-end flow control/distribution at the transport and network layers and opportunistic scheduling at the data link and physical layers. We formulate a single stochastic optimization problem and solve it by using a dual approach and a stochastic sub-gradient algorithm. The developed algorithm can be implemented in a distributed way, vertically among communication layers and horizontally among all entities in the network, clearly showing what should be done at each layer and each entity and what parameters should be exchanged between layers and between entities. Numerical results show that our cross-layer and end-to-end optimization approach provides more efficient resource allocation than the conventional layered and separated optimization approach.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.123-123
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• 1993

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1157-1169
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• 2021

Modern graphics processor unit (GPU) architectures offer significant hardware resource enhancements for parallel computing. However, without software optimization, GPUs continuously exhibit hardware resource underutilization. In this paper, we indicate the need to alter different warp scheduler schemes during different kernel execution periods to improve resource utilization. Existing warp schedulers cannot be aware of the kernel progress to provide an effective scheduling policy. In addition, we identified the potential for improving resource utilization for multiple-warp-scheduler GPUs by sharing stalling warps with selected warp schedulers. To address the efficiency issue of the present GPU, we coordinated the kernel-aware warp scheduler and warp sharing mechanism (KAWS). The proposed warp scheduler acknowledges the execution progress of the running kernel to adapt to a more effective scheduling policy when the kernel progress attains a point of resource underutilization. Meanwhile, the warp-sharing mechanism distributes stalling warps to different warp schedulers wherein the execution pipeline unit is ready. Our design achieves performance that is on an average higher than that of the traditional warp scheduler by 7.97% and employs marginal additional hardware overhead.