• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.9
• /
• pp.4197-4219
• /
• 2017

Cloud computing is a new service to provide dynamic, scalable virtual resource services via the Internet. Cloud market is available to multiple cloud computing resource providers and users communicate with each other and participate in market transactions. However, since cloud computing is facing with more and more security issues, how to complete the allocation process effectively and securely become a problem urgently to be solved. In this paper, we firstly analyze the cloud resource allocation problem and propose a mathematic model based on combinatorial double auction. Secondly, we introduce a trust evaluation mechanism into our model and combine genetic algorithm with simulated annealing algorithm to increase the efficiency and security of cloud service. Finally, by doing the overall simulation, we prove that our model is highly effective in the allocation of cloud resources.

• Molecules and Cells
• /
• v.45 no.7
• /
• pp.444-453
• /
• 2022

Multivalent macromolecular interactions underlie dynamic regulation of diverse biological processes in ever-changing cellular states. These interactions often involve binding of multiple proteins to a linear lattice including intrinsically disordered proteins and the chromosomal DNA with many repeating recognition motifs. Quantitative understanding of such multivalent interactions on a linear lattice is crucial for exploring their unique regulatory potentials in the cellular processes. In this review, the distinctive molecular features of the linear lattice system are first discussed with a particular focus on the overlapping nature of potential protein binding sites within a lattice. Then, we introduce two general quantitative frameworks, combinatorial and conditional probability models, dealing with the overlap problem and relating the binding parameters to the experimentally measurable properties of the linear lattice-protein interactions. To this end, we present two specific examples where the quantitative models have been applied and further extended to provide biological insights into specific cellular processes. In the first case, the conditional probability model was extended to highlight the significant impact of nonspecific binding of transcription factors to the chromosomal DNA on gene-specific transcriptional activities. The second case presents the recently developed combinatorial models to unravel the complex organization of target protein binding sites within an intrinsically disordered region (IDR) of a nucleoporin. In particular, these models have suggested a unique function of IDRs as a molecular switch coupling distinct cellular processes. The quantitative models reviewed here are envisioned to further advance for dissection and functional studies of more complex systems including phase-separated biomolecular condensates.

• ETRI Journal
• /
• v.32 no.4
• /
• pp.634-637
• /
• 2010

This letter presents a model for a dynamic collaboration (DC) platform among cloud providers (CPs) that prevents adverse business impacts, cloud vendor lock-in and violation of service level agreements with consumers, and also offers collaborative cloud services to consumers. We consider two major challenges. The first challenge is to find an appropriate market model in order to enable the DC platform. The second is to select suitable collaborative partners to provide services. We propose a novel combinatorial auction-based cloud market model that enables a DC platform among CPs. We also propose a new promising multi-objective optimization model to quantitatively evaluate the partners. Simulation experiments were conducted to verify both of the proposed models.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1992.04b
• /
• pp.73-73
• /
• 1992

• Journal of Korean Institute of Industrial Engineers
• /
• v.42 no.6
• /
• pp.386-394
• /
• 2016

In this research, in order to optimize the multi-objective function effectively, we suggested the optimization model to maximize the total destruction of ground targets and minimize the total damage of aircrafts and cost of air munitions by using goal programming. To satisfy the various variables and constraints of this mathematical model, the concept of air strike package is applied. As a consequence, effective attack can be possible by identifying the prior ground targets more quickly. This study can contribute to maximize the ROK air force's combat power and preservation of high value air asset in the war.

• Journal of Educational Research in Mathematics
• /
• v.26 no.4
• /
• pp.635-662
• /
• 2016

Combinatorics, the basis of probabilistic thinking, is an important area of mathematics and closely linked with other subjects such as informatics and STEAM areas. But combinatorics is one of the most difficult units in school mathematics for leaning and teaching. This study, using the designed combinatorial models and executable expression, aims to analyzes the eye movement of graduate students when they translate the written combinatorial problems to the corresponding executable expression, and examines not only the understanding process of the written combinatorial sentences but also the degree of difficulties depending on the combinatorial semantic structures. The result of the study shows that there are two types of solving process the participants take when they solve the problems : one is to choose the right executable expression by comparing the sentence and the executable expression frequently. The other approach is to find the corresponding executable expression after they derive the suitable mental model by translating the combinatorial sentence. We found the cognitive processing patterns of the participants how they pay attention to words and numbers related to the essential informations hidden in the sentence. Also we found that the student's eyes rest upon the essential combinatorial sentences and executable expressions longer and they perform the complicated cognitive handling process such as comparing the written sentence with executable expressions when they try the problems whose meaning structure is rarely used in the school mathematics. The data of eye movement provide meaningful information for analyzing the cognitive process related to the solving process of the participants.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.45 no.6
• /
• pp.83-95
• /
• 2003

In this study, a new concept in a paddy consolidation project is introduced in that curved parallel terracing with contour-lined layout is adopted in sloping areas instead of conventional rectangular terracing. The contoured layout reduces earth-moving considerably compared to rectangular methods in consolidation projects. The objective of the paper is to develop a combinatorial optimization model using the network theory for the design of contour-lined plots which minimizes the volume of earth moving. The results showed that as the length of short side of plot is longer or the land slope is steeper, the volume of earth moving for land leveling increases. The developed optimization model is applied for three consolidated districts and the resulting optimal earth moving is compared with the volume of earth from the conventional method. The shorter is the minimum length of short side of a polt with increases the number of plots, the less is the volume of earth. As the minimum length of short side is 20 m for efficient field works by farm machinery, the volume of earth moving of optimal plot is less by 21.0∼27.1 % than that of the conventional consolidated plots.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.20 no.1
• /
• pp.63-81
• /
• 1995

This paper presents a model and algorithm for solving the multi-factor plant layout problem. The model can incorporate more than two factors that may be either quantitative or qualitative. The algorithm is based on simulated annealing, which has been successfully applied for the solution of combinatorial problems. A set of problems previously used by various authors is solved to demonstrate the effectiveness of the proposed methods. The results indicate that the proposed methods can yield good quality for each of eleven test problems.

• Management Science and Financial Engineering
• /
• v.18 no.2
• /
• pp.13-17
• /
• 2012

Set covering has widely been accepted as a staple tool for feature selection in data mining. We present a generalized version of this classical combinatorial optimization model to make it better suited for the purpose and propose a surrogate relaxation-based procedure for its meta-heuristic solution. Mathematically and also numerically with experiments on 25 set covering instances, we demonstrate the utility of the proposed model and the proposed solution method.

• Journal of KIISE:Computing Practices and Letters
• /
• v.15 no.12
• /
• pp.928-932
• /
• 2009

Most diseases are caused by complex processes of various factors. Although previous researches have tried to identify the causes of the disease, there are still lots of limitations to clarify the complex factors. Here, we present a disease classification model based on an evolutionary learning approach of combinatorial features using the data sets from the genetics and cohort studies. We implemented a system for finding the combinatorial risk factors and visualizing the results. Our results show that the proposed method not only improves classification accuracy but also identifies biologically meaningful sets of risk factors.