• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11A
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• pp.862-869
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• 2009

We propose a new adaptive K-best Sphere Decoding (SD) algorithm for Multiple Input Multiple Output (MIMO) systems where the number of survivor paths, K is changed based on the characteristics of path metrics which contain the instantaneous channel condition. In order to overcome a major drawback of Maximum Likelihood Detection (MLD) which exponentially increases the computational complexity with the number of transmit antennas, the conventional adaptive K-best SD algorithms which achieve near to MLD performance have been proposed. However, they still have redundant computation complexity since they only employ the channel fading gain as a channel condition indicator without instantaneous Signal to Noise Ratio (SNR) information. hi order to complement this drawback, the proposed algorithm use the characteristics of path metrics as a simple channel indicator. It is found that the ratio of the minimum path metric to the other path metrics reflects SNR information as well as channel fading gain. By adaptively changing K based on this ratio, the proposed algorithm more effectively reduce the computation complexity compared to the conventional K-best algorithms which achieve same performance.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.245-252
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• 2008

We present a classification algorithm based on ant colony system(ACS) for classifying digital images. The ACS has been recently emerged as a useful tool for the pattern recognition, image extraction, and edge detection. The classification algorithm of digital images is very important in the application areas of digital image coding, image analysis, and image recognition because it significantly influences the quality of images. The conventional procedures usually classify digital images with the fixed value for the associated parameters and it requires postprocessing. However, the proposed algorithm utilizing randomness of ants yields the stable and enhanced images even for processing the rapidly changing images. It is also expected that, due to this stability and flexibility of the present procedure, the digital images are stably classified for processing images with various noises and error signals arising from processing of the drastically fast moving images could be automatically compensated and minimized.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1845-1865
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• 2019

Current Internet is designed by lots of service providers with different objects and policies which make the direct deployment of radically new architecture and protocols on Internet nearly impossible without reaching a consensus among almost all of them. Network virtualization is proposed to fend off this ossification of Internet architecture and add diversity to the future Internet. As an important part of network virtualization, virtual network embedding (VNE) problem has received more and more attention. In order to solve the problems of large embedding cost, low acceptance ratio (AR) and environmental adaptability in VNE algorithms, cognitive method is introduced to improve the adaptability to the changing environment and a cognitive virtual network embedding algorithm based on weighted relative entropy (WRE-CVNE) is proposed in this paper. At first, the weighted relative entropy (WRE) method is proposed to select the suitable substrate nodes and paths in VNE. In WRE method, the ranking indicators and their weighting coefficients are selected to calculate the node importance and path importance. It is the basic of the WRE-CVNE. In virtual node embedding stage, the WRE method and breadth first search (BFS) algorithm are both used, and the node proximity is introduced into substrate node ranking to achieve the joint topology awareness. Finally, in virtual link embedding stage, the CPU resource balance degree, bandwidth resource balance degree and path hop counts are taken into account. The path importance is calculated based on the WRE method and the suitable substrate path is selected to reduce the resource fragmentation. Simulation results show that the proposed algorithm can significantly improve AR and the long-term average revenue to cost ratio (LTAR/CR) by adjusting the weighting coefficients in VNE stage according to the network environment. We also analyze the impact of weighting coefficient on the performance of the WRE-CVNE. In addition, the adaptability of the WRE-CVNE is researched in three different scenarios and the effectiveness and efficiency of the WRE-CVNE are demonstrated.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.347-353
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• 2019

Recent recommendation systems are developing toward the utilization of high-dimensional data. However, high-dimensional data can increase algorithm complexity by expanding dimensions and be lower the accuracy of recommended items. In addition, it can cause the problem of data sparsity and make it difficult to provide users with proper recommended items. This study proposed an algorithm that classify users' subjective data with objective criteria with fuzzy-AHP and make use of rules with repetitive patterns through fuzzy association rules. Trying to check how problems with high-dimensional data would be mitigated by the algorithm, we performed 5-fold cross validation according to the changing number of users. The results show that the algorithm-applied system recorded accuracy that was 12.5% higher than that of the fuzzy-AHP-applied system and mitigated the problem of data sparsity.

• Journal of Information Technology Services
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• v.17 no.4
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• pp.101-117
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• 2018

Companies are responding appropriately to the rapidly changing business environment and striving to lead those changes. As part of that, we are meeting our strategic goals through IT projects, which increase the number of simultaneous projects and the importance of project portfolio management for successful project execution. It also strives for efficient deployment of human resources that have the greatest impact on project portfolio management. In the early stages of project portfolio management, it is very important to establish a reasonable manpower plan and allocate performance personnel. This problem is a problem that can not be solved by linear programming because it is calculated through the standard deviation of the input ratio of professional manpower considering the uniformity of load allocated to the input development manpower and the importance of each project. In this study, genetic algorithm, one of the heuristic methods, was applied to solve this problem. As the objective function, we used the proper input ratio of projects, the input rate of specialist manpower for important projects, and the equal load of workload by manpower. Constraints were not able to input duplicate manpower, Was used as a condition. We also developed a program for efficient application of genetic algorithms and confirmed the execution results. In addition, the parameters of the genetic algorithm were variously changed and repeated test results were selected through the independent sample t test to select optimal parameters, and the improvement effect of about 31.2% was confirmed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1817-1825
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• 2021

Omnidirectional mobile robots can be mobile in any direction without changing the robot's direction, making them easy to apply in many applications and providing excellent maneuverability. Omnidirectional mobile robots have non-linear dynamic components such as friction, making them difficult to model accurately. In this paper, we linearize the mobile robot system using the mobile robot's inverse dynamics and integral sliding mode control method to remove these nonlinear components. And the position and velocity gains are optimized using a genetic algorithm to realize the optimal performance of the proposed system control method. As a result of the performance evaluation, the genetic algorithm's control method showed superior performance than the control method with an arbitrary gain. And the proposed inverse dynamic and integral sliding mode control method can be applied to other control methods. It can be beneficial for designing a linear control system.

• Annual Conference of KIPS
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• 2010.04a
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• pp.852-855
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• 2010

Tree type of Rule Case will be processed by the method that provide practical Rule Case to Rule Engine that is made with procedural language beforehand, then the Rule Engine according to the condition of the special Rule Case to return result in current Rule-Based System. There are two disadvantages in the method; the first is according to specific business rule after construct the Rule Engine when the business rule changing the Rule Engine also must be changed. The second is when Rule have many conditions the Rule Engine will become very complex and the speed of processing Rule Case will become very slow. In this paper, we will propose a simplified algorithm that according to the theory of ID Tree to produce Rules which be used in Rule-Based System. The algorithm can not only produce Rules but also make sure of satisfying change of business rule by execute the algorithm. Because it is not necessary to make a Rule Engine, we will anticipate effect of increasing speed and reducing cost from Rule-Based System of applying the algorithm.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.99-109
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• 2010

Existing research about automated wafer transport management strategy for semiconductor manufacturing equipment was mainly focused on dispatching rules which is optimized to specific system layout, process environment or transfer patterns. But these methods can cause problem as like requiring additional rules or changing whole transport management strategy when applied to new type of process or system. In addition, a lack of consideration for interconnectedness of the added rules can cause unexpected deadlock. In this study, in order to improve these problems, propose dynamic priority based transfer job decision making algorithm which is applicable with regardless of system lay out and transfer patterns. Also, extra rule handling part proposed to support special transfer requirement which is available without damage to generality for maintaining a consistent scheduling policies and minimize loss of stability due to expansion and lead to improve productivity at the same time. Simulation environment of Twin-slot type semiconductor equipment was built In order to measure performance and examine validity about proposed wafer scheduling algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1823-1840
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• 2023

In order to improve spectral efficiency and reduce power consumption for reconfigurable intelligent surface (RIS) assisted wireless communication systems, a joint design considering irregular RIS topology, RIS on-off switch, power allocation and phase adjustment is investigated in this paper. Firstly, a multi-dimensional variable joint optimization problem is established under multiple constraints, such as the minimum data requirement and power constraints, with the goal of maximizing the system energy efficiency. However, the proposed optimization problem is hard to be resolved due to its property of nonlinear nonconvex integer programming. Then, to tackle this issue, the problem is decomposed into four sub-problems: topology design, phase shift adjustment, power allocation and switch selection. In terms of topology design, Tabu search algorithm is introduced to select the components that play the main role. For RIS switch selection, greedy algorithm is used to turn off the RISs that play the secondary role. Finally, an iterative optimization algorithm with high data-rate and low power consumption is proposed. The simulation results show that the performance of the irregular RIS aided system with topology design and RIS selection is better than that of the fixed topology and the fix number of RISs. In addition, the proposed joint optimization algorithm can effectively improve the data rate and energy efficiency by changing the propagation environment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.927-933
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• 2006

The Variable Message Signs (VMS) are useful way to reduce the socio-economic costs due to the traffic congestions and delays by providing the information on traffic condition to drivers. This study provided a methodology to determine the locations of VMS's in terms of the minimization of the delay by applying the genetic algorithm. The optimal number of VMS's was also derived by the economic analysis based on the cost and the benefit. The simulation considered the variation of traffic volume, the frequency and duration of the incident, and the traffic conversion in order to reflect the real situation. I've made a scenario to consider traffic volume and incident, and it can undergo through changing different traffic volume and incident in time and days and seasons. And I've comprised two kinds of result, one is based on empirical studies, the other is based on Genetic Algorithm about optimal allocation VMS. This result of using optimal location VMS, reduce total travel time rather than preceding study based on normal location VMS and we can estimate optimal location VMS each one.