• Journal of Information Technology Services
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• v.17 no.2
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• pp.101-110
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• 2018

Analytic Hierarchy Process (AHP) is a systematic and objective decision method that stratifies multiple criteria to determine various evaluation factors' order of priority. Since AHP requires several stages of analysis with complicated attributes, they normally rely on computer programs for the execution of such analyses. However, the existing AHP analytic tools carry the inconvenience of having to repeatedly input massive amounts data generated in every stage. This repetitious data entry process results in prolonged analysis times and higher possibility of errors, leading to decreased reliability of the results. Thus, in this study, we develop an analytic tool that effectively simplifies the data entry process in AHP analysis, for the purpose of reducing analysis times and increasing the reliability of the results.

• Journal of the East Asian Society of Dietary Life
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• v.17 no.5
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• pp.727-737
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• 2007

The aims of this study was to suggest a new efficiency measurement indicator for evaluating the management efficiency of decision making units(DMUs) in the contract foodservice industry. The data envelopment analysis(DEA) model which considers multiple inputs and outputs and looking for benchmarks, was used to compare the productivity of DMUs. We considered sales, profits, and customer satisfaction as output variables and it adopted food cost, labor cost and administrative expense as input variables. The results of applying DEA revealed relatively efficient types of business and service types. The efficiency of school units was highest and the mired service type was the most efficient one. In this study the CCR model efficiency was analysed with profit and the customer satisfaction index by the matrix method. DEA efficiency was correlated with profit but there was no correlation between DEA efficiency and the customer satisfaction index.

• Journal of the Korean Home Economics Association
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• v.42 no.5
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• pp.107-126
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• 2004

As the information society matures, an analysis on possible outputs of internet usage is needed. Thus, this study was peformed in order to understand the utility cognition and negative outputs of internet users. The method used in this study was a web-based questionnaire that was administered to the internet users. Five hundred married men and women were analyzed with a factor and a multiple regression analysis. Results were as follows: First, many kinds of internet usages - information searching, internet shopping, electronic mail, instant messaging, and decision-making dependent on internet information - were differentiated with age. Second, the altitude about the internet was an important explanatory variable in the types of internet usage. Third, negative outputs of internet usage were great in terms of information resource management and unbalanced scheduling in daily time spent. Fourth, utility cognition was affected by qualitative elements on internet usage more than the quantitative ones.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.11
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• pp.522-531
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• 2001

Recently conventional artificial intelligence(AI) approaches have been employed to build action selectors for the autonomous mobile robot(AMR). However, in these approaches, the decision making process to choose an action from multiple competence modules is still an open question. Many researches have been focused on the reactive planning systems such as the biological immune system. In this paper, we attempt to construct an action selector for an AMR based on the artificial immune network and internet. The information from vision sensors is used for antibody. We propose a learning method for artificial immune network using evolutionary algorithm to produce antibody automatically. The internet environment for an AMR action selector shows the usefulness of the proposed learning artificial immune network application.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.212-220
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• 2007

This paper proposes a method of avoiding obstacles and tracking a moving object continuously and simultaneously by using new concepts of virtual tow point and fuzzy danger factor for differential wheeled mobile robots. Since differential wheeled mobile robot has smaller degree of freedom to control and are non-holonomic systems, there exist multiple solutions (trajectories) to control and reach a target position. The paper proposes 'fuzzy danger factor' for obstacles avoidance, 'virtual tow point' to solve non-holonomic object tracking control problem for unique solution and three kinds of fuzzy logic controller. The fuzzy logic controller is policy decision controller with fuzzy danger factor to decide which controller's result is more valuable when the mobile robot is tracking a moving object with obstacles to be avoided.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.285-286
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• 2006

H.264 provide good coding efficiency compared with existing video coding standards as H.263, MPEG-4, etc. However, H.264 require the increase of encoder complexity. In this paper, fast mode decision algorithm by skipping variable block size motion estimation and spatial-predictive coding, which occupies most encoder complexity, is proposed. Experimental results show that the proposed approach can save encoding time to 55% compared with the H.264 standard.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3345-3363
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• 2023

Developers often use cross-platform frameworks to create mobile apps that can run on multiple platforms with minimal code changes. However, these frameworks may not suit all the needs of a specific app, so developers may also use native APIs to add platform-specific features. This method eventually dilutes the advantages of cross-platform development methodology that aims to reduce development costs and time, and often leads to a decision to return back to the original native mobile development methodology. In this study, we explore a different approach: combining different cross-platform tools to develop a storybook mobile app that meets various requirements. We have demonstrated that integrating two cross-platform solutions can be used reliably to develop complex mobile applications. However, we also report that this approach can introduce unforeseen issues such as sandbox redundancy, unexpected functional burdens, and redundant permission requests. Despite these challenges, we believe that combining two cross-platform solutions can be applied to a variety of functional and performance requirements, enabling the development of more sophisticated mobile applications at lower costs and with shorter development timelines than traditional mobile app development methodologies.

• The KIPS Transactions:PartC
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• v.9C no.4
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• pp.459-466
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• 2002

This paper proposes a robust speaker identification algorithm based on the wavelet filter banks and multiple decision-making scheme. Since the proposed speaker identification algorithm has a structure performing the identification algorithm independently for each subband, the noise effect of an subband can be localized. Through this process, we can obtain more robust results for the environmental noises which generally have band limited frequency. In the experiments, the proposed method showed more 15∼60% improvement than the vector quantization method for the various noisy environments.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.644-654
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• 2024

After the Tohoku earthquake and tsunami (Japan, 2011), regulatory efforts to mitigate external hazards have increased both the safety requirements and the total capital cost of nuclear power plants (NPPs). In these circumstances, identifying not only disaster robustness but also cost-effective capacity setting of NPPs has become one of the most important tasks for the nuclear power industry. A few studies have been performed to relocate the seismic capacity of NPPs, yet the effects of multiple hazards have not been accounted for in NPP capacity optimization. The major challenges in extending this problem to the multihazard dimension are (1) the high computational costs for both multihazard risk quantification and system-level optimization and (2) the lack of capital cost databases of NPPs. To resolve these issues, this paper proposes an effective method that identifies the optimal multihazard capacity of NPPs using a multi-objective genetic algorithm and the two-stage direct quantification of fault trees using Monte Carlo simulation method, called the two-stage DQFM. Also, a capacity-based indirect capital cost measure is proposed. Such a proposed method enables NPP to achieve safety and cost-effectiveness against multi-hazard simultaneously within the computationally efficient platform. The proposed multihazard capacity optimization framework is demonstrated and tested with an earthquake-tsunami example.

• Journal of KIISE
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• v.43 no.12
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• pp.1365-1375
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• 2016

One of the most important capabilities for autonomous service robots working in living environments is to recognize and understand the correct context in dynamically changing environment. To generate high-level context knowledge for decision-making from multiple sensory data streams, many technical problems such as multi-modal sensory data fusion, uncertainty handling, symbolic knowledge grounding, time dependency, dynamics, and time-constrained spatio-temporal reasoning should be solved. Considering these problems, this paper proposes an effective dynamic context management and spatio-temporal reasoning method for intelligent service robots. In order to guarantee efficient context management and reasoning, our algorithm was designed to generate low-level context knowledge reactively for every input sensory or perception data, while postponing high-level context knowledge generation until it was demanded by the decision-making module. When high-level context knowledge is demanded, it is derived through backward spatio-temporal reasoning. In experiments with Turtlebot using Kinect visual sensor, the dynamic context management and spatio-temporal reasoning system based on the proposed method showed high performance.