This study proposes a facility location model in consideration of spatial coverage and travel cost as an effort to make objective and effective decisions of natural gas filling stations. The proposed model is developed for fixed stations and consists of two stages. The first stage employs a heuristic algorithm to find a set of locations which satisfy the spatial coverage constraints determined by the maximum travel distance between the filling stations and bus depots. In the second stage, the optimal location of filling stations is determined based on the minimum travel cost estimated by using a modified transportation problem as well as the construction and maintenance costs of the filling stations. The applicability of the model is analyzed through finding the optimal location of filling stations for the city of Anyang, a typical medium-sized city in metropolitan Seoul, based on the demand of natural gas buses. This study is expected to help promote the spread of natural gas buses by providing a starting point of a objective and reasonable methodological perspective to address the filling station location problem.
Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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2015.05a
/
pp.116-119
/
2015
In this paper we propose an algorithm for environment monitoring using multiple mobile sensor (MS) nodes. Our focus is on maximizing sensing coverage of a group of MS nodes for monitoring a phenomenon in an unknown and open area over time. In the proposed algorithm, MS nodes are iteratively relocated to new positions at which a higher sensing coverage can be obtained. We formulated an integer linear programming (ILP) optimization problem to find the optimal positions for MS nodes with the objective of coverage maximization. The performance evaluation was performed to confirm that the proposed algorithm can enable MS nodes to relocate to high interest positions, and obtain a maximum sensing coverage.
The National Health Insurance Corporation has been retrieving from health care providers the payments made to them by insured patients as a result of the health care providers' arbitrary denial of coverage under the National Health Insurance, and has been disbursing such retrieved monies back to the patients, pursuant to Article 57, Sections 1 and 4 of the National Health Insurance Act. However, such practice is an application of the law that lacks legal exactitude. Another problem with such practice is that there is no legal provision under any laws or notices that expressly prohibits arbitrary denial of coverage. A legislative solution, therefore, is called for to address these issues.
Confidence interval estimators for proportions using normal approximation have been commonly used for coverage analysis of simulation output even though alternative approximate estimators of confidence intervals for proportions were proposed. This is -because the normal approximation was easier to use in practice than the other approximate estimators. Computing technology has no problem with dealing these alternative estimators. Recently, one of the approximation methods for coverage analysis which is based on arcsin transformation has been used for estimating proportion and for controlling the required precision in [12]. In this paper, we compare three approximate interval estimators, based on a normal distribution approximation, an arcsin transformation and an F-distribution approximation, of a single proportion. Three estimators were applied to sequential coverage analysis of steady-state means, in simulations of the M/M/1/$\infty$ and W/D/l/$\infty$ queueing systems on a single processor and multiple processors.
Journal of the Korea Society of Computer and Information
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v.24
no.4
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pp.169-176
/
2019
Wireless sensor networks are used to monitor and control areas in a variety of military and civilian areas such as battlefield surveillance, intrusion detection, disaster recovery, biological detection, and environmental monitoring. Since the sensor nodes are randomly placed in the area of interest, separation of the sensor network area may occur due to environmental obstacles or a sensor may not exist in some areas. Also, in the situation where the sensor node is placed in a non-relocatable place, some node may exhaust energy or physical hole of the sensor node may cause coverage hole. Coverage holes can affect the performance of the entire sensor network, such as reducing data reliability, changing network topologies, disconnecting data links, and degrading transmission load. It is possible to solve the problem that occurs in the coverage hole by finding a coverage hole in the sensor network and further arranging a new sensor node in the detected coverage hole. The existing coverage hole detection technique is based on the location of the sensor node, but it is inefficient to mount the GPS on the sensor node having limited resources, and performing other location information processing causes a lot of message transmission overhead. In this paper, we propose an Adjacent Matrix-based Hole Coverage Discovery(AMHCD) scheme based on connectivity of neighboring nodes. The method searches for whether the connectivity of the neighboring nodes constitutes a closed shape based on the adjacent matrix, and determines whether the node is an internal node or a boundary node. Therefore, the message overhead for the location information strokes does not occur and can be applied irrespective of the position information error.
Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.
Kim, Yeon Woo;Jung, Yong Sik;Kim, Wook Hwan;Min, Young Gi;Kim, Ki Woon;Lee, Kug Jong
Journal of Trauma and Injury
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v.18
no.1
/
pp.70-79
/
2005
Background: Abdominal compartment syndrome has multiple etiologies that are not only related to trauma but also any problem condition in the absence of abdominal injury. To determine whether prevention of the abdominal compartment syndrome after celiotomy for trauma victims justifies the use of temporary abdominal coverage with monofilament knitted polypropylene mesh (Malex mesh) in severely injured patients. Method: Medical records at the Ajou University Medical Center were reviewed for a 32-month period from May 1st, 2002 to December 31st, 2004. Twenty-nine consecutive patients requiring celiotomy who were survived until at the end of celiotomy received temporary abdominal coverage and staged abdominal repairs with Malex mesh. One of them was dissecting aortic aneurysm patient and the others were all trauma victims. Malex mesh prosthesis coverage was used in cases of abdominal compartment syndrome due to excessive fascial tension, severe bowel edema and retroperitoneal hemorrhage or edema followed by staged abdominal repairs. Result: Eighteen of twenty-nine patients were survived. Demographic characteristics, injury severity number of abdominal-pelvic bone injuries, mortality rate, complications, number of operations for permanent closure, required time for permanent closure showed no difference between man and women or child and adult. Except one dissecting aortic aneurysm patient, trauma cases showed $3.24{\pm}0.98$ injury sites. All cases that received temporary abdominal coverage and staged abdominal repairs did not show abdominal compartment syndrome. $10.08{\pm}5.85$ days and $2.27{\pm}0.82$ times of operation required making permanent abdominal closure after temporary abdominal coverage followed by staged abdominal repairs. Most of surviving patients have shown antibiotic-resistant organism and fungus infection. Patients who received permanent closure recovered from infectious problem completely. Conclusion: The use of Malex mesh for temporary abdominal coverage in severely injured patients undergoing celiotomy was effective treatment method.
In many security monitoring contexts, the performance or efficiency of surveillance sensors/networks based on a single sensor type may be limited by environmental conditions, like illumination change. It is well known that different modes of sensors can be complementary, compensating for failures or limitations of individual sensor types. From a location analysis and modeling perspective, a challenge is how to locate different modes of sensors to support security monitoring. A coverage-based optimization model is proposed as a way to simultaneously site k different sensor types. This model considers common coverage among different sensor types as well as overlapping coverage for individual sensor types. The developed model is used to site sensors in an urban area. Computational results show that common and overlapping coverage can be modeled simultaneously, and a rich set of solutions exists reflecting the tradeoff between common and overlapping coverage.
Backgrounds : To reduce the patients' economic burden of herbal decoctions use, in 2012, Korean government decided to implement the pilot project of herbal decoctions coverage in the National Health Insurance. Objectives : This study aimed to analyze the policy decision-making process for the pilot insurance project in 2012. Methods : Official documents, research papers, statistical reports, and news articles, etc. on the coverage of herbal decoctions were searched and collected. We used the Kingdon's Policy Stream Model to analyze how the policy of pilot project of herbal decoctions coverage was decided, and who were the main activists for the decision-making process. Results : Components to be included in the 'Problem stream' were the decline in the profits of Korean Medicine institutions, the contraction of the herbal decoctions use, and the fiscal surplus of National Health Insurance. In the 'Policy stream', there were several model studies for herbal decoctions coverage, and examples of herbal benefits in other social insurances. In the 'Political stream', there were the legislative initiatives by member of the National Assembly and the promotion of insurance coverage by the Association of Korean Medicine(AKOM), etc. Policy window for herbal decoctions coverage was opened by the combination of these three streams with the efforts of policy activists, such as the executives of AKOM, and policy researchers. Conclusions : The policy decision process for health insurance coverage of herbal decoctions was analyzed using Kingdon's model, and the analysis shows that the combination of political streams and entrepreneurs' competencies can be an important driving force in policy decision making.
Recently, in several countries including South Korea, the percentage of households having fixed telephones, which is often called the fixed telephone coverage rates, has decreased due to a rapid spread of mobile phones. It is generally assumed that the lower the rates of coverage, resulting in a major frame undercoverage problem, the greater the possibility of the bias. In this paper, we first take a look at the changes of coverage rates in both fixed telephones and mobile phones in South Korea and examine the coverage rates by sociodemographic characteristics of households. Also, we refer to a change in the level of fixed telephone noncoverage and the resulting problems in the situation. Second, we provide a comparison of the coverage rates for households for some European countries, the United States, Canada etc. Finally, we suggest further research to rise to our research environments increasingly troublesome, owing to the wide spread of mobile phones.
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