• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.29-37
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• 2020

This research seeks to determine the influence of investment opportunity set (IOS); profitability (Return on Assets - ROA), liquidity, business risk and firm size on debt policy. We used 42 manufacturing companies registered on the Indonesian Stock Exchange (Bursa Efek Indonesia) as object research. We used purposive sampling method to determined samples, consider the period observation from 2012 to 2016, and produce 168 units analysis. Data analysis uses the multiple regressions with the SPSS tools. The results of the study found that companies' debt policies in Indonesia are negatively affected by the liquidity. Investment opportunity set (IOS) has negative effect on debt policy. Meanwhile, ROA, Return on Invested Capital (ROIC), and firm size of a company has no impact on debt policy. These findings indicate that Indonesian manufacture companies do not see the high investment opportunity set and profitability as a policy basis for increasing debt. Moreover, the high profitability also does not cause companies to increase their debt ratio. Our study indicates that Indonesian manufacture companies use internal funds to fund their investment. This finding is a concern for creditors, as they can now see the ability of the companies, and especially their performance, in determining their credit policies.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.163-168
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• 2002

The voting algorithm for action selection performs self-improvement by Reinforcement learning algorithm in the dynamic environment. The proposed voting algorithm improves the navigation of the robot by adapting the eligibility of the behaviors and determining the Command Set Generator (CGS). The Navigator that using a proposed voting algorithm corresponds to the CGS for giving the weight values and taking the reward values. It is necessary to decide which Command Set control the mobile robot at given time and to select among the candidate actions. The Command Set was learnt online by means as Q-learning. Action Selector compares Q-values of Navigator with Heterogeneous behaviors. Finally, real-world experimentation was carried out. Results show the good performance for the selection on command set as well as the convergence of Q-value.

• Journal of Environmental Impact Assessment
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• v.21 no.2
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• pp.247-254
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• 2012

This paper seeks for the set-up plan in the reasonable target area of environmental assessment. Domestically, the target area of environmental assessment is set up by the adjustment of opinion collection about the assessment scope result of an environmental factor. In a foreign country, the boundary of the target area for a development project is established with the environmental, economical, and social viewpoint based on the standard for significantly environmental impact. Based on the analysis of the present condition at home and abroad, the first set-up plan for the reasonable target area of environmental assessment is the preparation of the detailed term definition related to the target area of environmental assessment. The second is the arrangement of the judgement standard for significantly environmental impact. The quantitative assesment item can apply the present standard or regulation, and the qualitative assessment item can establish the standard based on factual and objective data. The last is the preparation of the reference material or the guideline for deciding the initial target area by the judgement standard and determining the final target area by opinion collection in the stage of scoping.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1627-1648
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• 2012

We propose an adaptive method for detecting plagiarized pairs from a large set of source code. This method is adaptive in that it uses an adaptive algorithm and it provides an adaptive threshold for determining plagiarism. Conventional algorithms are based on greedy string tiling or on local alignments of two code strings. However, most of them are not adaptive; they do not consider the characteristics of the program set, thereby causing a problem for a program set in which all the programs are inherently similar. We propose adaptive local alignment-a variant of local alignment that uses an adaptive similarity matrix. Each entry of this matrix is the logarithm of the probabilities of the keywords based on their frequency in a given program set. We also propose an adaptive threshold based on the local outlier factor (LOF), which represents the likelihood of an entity being an outlier. Experimental results indicate that our method is more sensitive than JPlag, which uses greedy string tiling for detecting plagiarism-suspected code pairs. Further, the adaptive threshold based on the LOF is shown to be effective, and the detection performance shows high sensitivity with negligible loss of specificity, compared with that using a fixed threshold.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3121-3143
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• 2019

Segmentation plays an important role in the field of image processing and computer vision. Intuitionistic fuzzy C-means (IFCM) clustering algorithm emerged as an effective technique for image segmentation in recent years. However, standard fuzzy C-means (FCM) and IFCM algorithms are sensitive to noise and initial cluster centers, and they ignore the spatial relationship of pixels. In view of these shortcomings, an improved algorithm based on IFCM is proposed in this paper. Firstly, we propose a modified non-membership function to generate intuitionistic fuzzy set and a method of determining initial clustering centers based on grayscale features, they highlight the effect of uncertainty in intuitionistic fuzzy set and improve the robustness to noise. Secondly, an improved nonlinear kernel function is proposed to map data into kernel space to measure the distance between data and the cluster centers more accurately. Thirdly, the local spatial-gray information measure is introduced, which considers membership degree, gray features and spatial position information at the same time. Finally, we propose a new measure of intuitionistic fuzzy entropy, it takes into account fuzziness and intuition of intuitionistic fuzzy set. The experimental results show that compared with other IFCM based algorithms, the proposed algorithm has better segmentation and clustering performance.

• Honam Mathematical Journal
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• v.31 no.3
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• pp.315-321
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• 2009

Erd$\"{o}$s posed the problem of determining the minimum number g(n) such that any set of g(n) points in general position in the plane contains an empty convex n-gon. In 1978, Harborth proved that g(5) = 10. We reprove the result in a geometric approach.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.634-639
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• 1998

A methodology based on the concept of variable string length GA(VGA) is developed for determining automatically the number of hyperplanes and their appropriate arrangement for modeling the class boundaries of a given training data set in RN. The genetic operators and fitness functionare newly defined to take care of the variability in chromosome length. Experimental results on different artificial and real life data sets are provided.

• Asia pacific journal of information systems
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• v.11 no.1
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• pp.61-73
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• 2001

Predicting a variable using other variables in a large data set is a very difficult task. It involves selecting variables to include in a model and determining the shape of the relationship between variables. Nonparametric regression such as smoothing splines and neural networks are widely-used methods for such a task. We propose an alternative method based on a genetic algorithm(GA) to solve this problem. We applied GA to regression splines, a nonparametric regression method, to estimate functional forms between variables. Using several simulated and real data, our technique is shown to outperform traditional nonparametric methods such as smoothing splines and neural networks.

• Journal of the Korean Operations Research and Management Science Society
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• v.3 no.2
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• pp.95-108
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• 1978

This paper discusses an application of mathematical programming techniques in the paper industry in determining optimal parent roll widths. Parent rolls are made from the reels produced at wide paper machines by slitting them to more manageable widths. The problem is finding a set of the slitting patterns that will minimize the trim loss involved in the sheeting operation. Two programming models, one linear and one mixed integer linear, are presented in this paper. Also presented are the computational experience, the model sensitivity, and the comparison of the optimal solutions with the simulated operational data.

• Korean Management Science Review
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• v.10 no.2
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• pp.79-91
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• 1993

Strategic decisions related to the design of a physical distribution system can be classified into three basic components : facility location, transportation, inventory decisions. In this research the interdependence of those decisions are expressed in a mathematical model such that the total relevant cost of the system is minimized. We suggested a heuristic technique for solving the model. In broad terms, our solution technique combines a heuristic method for determining which candidate DCs to open and an exact method for minimizing costs given a set of open DCs. And we also developed a decision supporting package for the design of a physical distribution system.