• Hip & pelvis
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• v.34 no.1
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• pp.56-61
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• 2022

Purpose: Histopathologic analysis of femoral head specimens following total hip arthroplasty (THA) is a routine practice that represents a significant use of health care resources. However, it occasionally results in discovery of undiagnosed hematopoietic malignancy and other discrepant diagnoses such as avascular necrosis. The purpose of this study was to determine the rate of discordant and discrepant diagnoses discovered from routine histopathological evaluation of femoral heads following THA and perform a cost analysis of this practice. Materials and Methods: A review of patients undergoing primary THA between 2004-2017 was conducted. A comparison of the surgeon's preoperative and postoperative diagnosis, and the histopathologic diagnosis was performed. In cases where the clinical and histopathology differed, a review determined whether this resulted in a change in clinical management. Medicare reimbursement and previously published cost data corrected for inflation were utilized for cost calculations. Results: A review of 2,134 procedures was performed. The pathologic diagnosis matched the postoperative diagnosis in 96.0% of cases. Eighty-three cases (4.0%) had a discrepant diagnosis where treatment was not substantially altered. There was one case of discordant diagnosis where lymphoma was diagnosed and subsequently treated. The cost per discrepant diagnosis was $141,880 and per discordant diagnosis was $1,669 when using 100% Medicare reimbursement and Current Procedural Terminology (CPT) code combination 88304+88311. Conclusion: Histopathologic analysis of femoral head specimens in THAs showed an association with high costs given the rarity of discordant diagnoses. Routine use of the practice should be at the discretion of individual hospitals with consideration for cost and utility thresholds.

• Korean Circulation Journal
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• v.54 no.8
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• pp.499-512
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• 2024

Background and Objectives: Arterial dissection during endovascular therapy rarely occurs but can be lethal. A fabric-based covered graft stents yield poor clinical outcomes. A novel balloon-expandable stent with biodegradable film graft for overcoming these issues was evaluated in a rabbit iliac artery model. Method: Eighteen rabbits with iliac artery dissections were induced by balloon over-inflation on angiography (Ellis type 2 or 3) and treated using the test device (3.0×24 mm). Subsequently, survived twelve animals underwent histologic examinations and micro-computed tomography (CT) at 0, 2, 4, and 8 weeks and 3, 6, 9, and 12 months and angiography at one-year. Results: There were no adverse cardiovascular events during the one-year. Early-stage histologic examination revealed complete sealing of disrupted vessels by the device, exhibiting mural hematoma, peri-stent red thrombi, and dense infiltration of inflammatory cells. Mid- and long-term histologic examination showed patent stents with neointimal hyperplasia over the stents (% area stenosis: 11.8 at 2 weeks, 26.1 at 1 month, 29.7 at 3 months, 49.2 at 9 months, and 51.0 at 1 year), along with mild peri-strut inflammatory response (Grade: 1-2 at mid-term and 0-1 at long-term). The graft film became scarcely visible after six months. Both CT and angiography revealed no instances of thrombotic occlusion or in-stent restenosis (% diameter stenosis: 5.7 at 2 weeks, 12.3 at 1 month, 14.2 at 3 months, 25.1 at 9 months, and 26.6 at 1 year). Conclusions: The novel balloon-expandable stent with a biodegradable film graft demonstrates feasibility in managing severe artery dissection and preventing lethal vascular events in animal model.

• Journal of Cerebrovascular and Endovascular Neurosurgery
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• v.26 no.2
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• pp.130-140
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• 2024

Objective: To assess whether local anesthetic infiltration could minimize the carotid baroreceptor reflex (CBR) which has an incidence after carotid artery stenting (CAS) that varies from 29% to 51%. Methods: This retrospective single-center study included 51 patients (mean age, 70.47 years) who underwent CAS for carotid stenosis. The groups included patients who underwent CAS for asymptomatic ischemic stroke (n=41) or symptomatic disease (n=10). Preprocedural percutaneous lidocaine injections (PPLIs) were administered to 70.6% and 5.9% of patients who underwent elective CAS and emergency CAS, respectively. Results: Among patients who received PPLIs, the mean degree of stenosis was 80.5% (95% confidence interval [CI]: ±10.74, 51-98%). The mean distance from the common carotid artery bifurcation to the most stenotic lesion (CSD) was 8.3 mm (95% CI: ±0.97, 6.3-10.2 mm); the mean angle between the internal carotid artery and common carotid artery (CCA) trunk (IAG) was 65.6° (95% CI: ±2.39, 61-70°). Among patients who did not receive PPLIs, the mean degree of stenosis was 84.0% (95% CI: ±8.96, 70-99%). The mean CSD was 5.9 mm (95% CI: ±1.83, 1.9-9.9 mm); the mean IAG was 60.4° (95% CI: ±4.41, 51-70°). The procedure time was longer in the PPLI group than in the no PPLI group (28.19 [n=39] vs. 18.88 [n=12] days) (P=0.057); the length of intensive care unit stay was shorter in the PPLI group (20.01 [n=36] vs. 28.10 [n=5] days) (P=0.132). Conclusions: Targeted PPLI administration to the carotid bulb decreased aberrant heart rates and blood pressure changes induced by carotid stent deployment and balloon inflation. As CBR sensitivity increases with decreasing distance to the stenotic lesion from the CCA bifurcation, PPLIs may help stabilize patients during procedures for stenotic lesions closer to the CCA.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

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.

• Journal of Korea Water Resources Association
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• v.57 no.8
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• pp.533-548
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• 2024

Due to climate change with extreme weather events, occurrences of unprecedented heavy rainfall have become more frequent. Since it is difficult to perfectly predict and prevent flood damages, the limitation of traditional prevention-centered approaches has come a issue. The concept of "resilience" has therefore been developed which emphasizes the ability to swiftly recover from damages to previous states or to even better conditions. In this study, we 1) developed a total of 20 domestic flood resilience indicators based on the 4R principles (Redundancy, Robustness, Rapidity, Resourcefulness), 2) conducted applicability evaluations targeting specific disaster-prone areas, and 3) assessed the importance of each indicator through Analytic Hierarchy Process (AHP) analysis with flood-related experts. To confirm the suitability of the developed flood resilience indicators, multicollinearity analysis was performed, and the results indicated that all 20 indicators had tolerance limits above 0.1 and Variance Inflation Factors (VIF) below 10, demonstrating suitability as factors. Furthermore, evaluations of proposed indicators were carried out targeting disaster-prone areas in 2022(21 areas), and AHP analysis was utilized to determine the relative importance of each indicator. The analysis revealed that the importance of each indicator was as follows: Robustness 0.46, Rapidity 0.22, Redundancy 0.17, and Resourcefulness 0.16, with Robustness exhibiting the highest importance. Regarding the sub-indicators that had the greatest influence on each 4R component, river embankment maintenance emerged as the most influential for Robustness, healthcare services for Rapidity, fiscal autonomy of local governments for Resourcefulness, and drainage facilities for Redundancy.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.11
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• pp.445-452
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• 2017

Electric pole is a supporting beam used for power transmission/distribution which accelerometer are used for measuring a external force. The meteorological condition has various effects on the external forces of electric pole. One of them is the elasticity change of the aerial wire. It is very important to perform modelling. The acceleration sensor is converted into a pitch and a roll angle. The meteorological condition has a high correlation between variables, and selecting significant explanatory variables for modeling may result in the problem of over-fitting. We constructed high deviance explained model considering multicollinearity using the Generalized Additive Model which is one of the machine learning methods. As a result of the Variation Inflation Factor Test, we selected and fitted the significant variable as temperature, precipitation, wind speed, wind direction, air pressure, dewpoint, hours of daylight and cloud cover. It was noted that the Hours of daylight, cloud cover and air pressure has high explained value in explonatory variable. The average coefficient of determination (R-Squared) of the Generalized Additive Model was 0.69. The constructed model can help to predict the influence on the external forces of electric pole, and contribute to the purpose of securing safety on utility pole.

• KDI Journal of Economic Policy
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• v.14 no.1
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• pp.191-212
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• 1992

This paper discusses the role of money in the process of capital accumulation where financial markets are impeded by contract enforcement problems in the context of overlapping generations framework. In particular, in less developed countries (LDCs) creditors may know little about the repayment capability of potential debtors due to incomplete information so that financial instruments other than money may not acceptable to them. In this paper the impediments to the operation of the private finanical markets are explicitly modelled. We argue that creditors cannot observe actual investment decisions made by the potential borrowers, and as a result, loan contracts may not be fully enforceable. Therefore, a laissez-faire regime may fail to provide the economy with the appropriate financial instruments. Under these circumstances, we introduce a government operated discount window (DW) that acts as an open market buyer of private debt. This theoretical structure represents the practice of governments of many LDCs to provide loans (typically at subsidized interest rates) to preferred borrowers either directly or indirectly through the commercial banking system. It is shown that the DW can substantially overcome impediments to trade which are caused by the credit market failure. An appropriate supply of the DW loan enables producers to purchase the resources they cannot obtain through direct transactions in the credit market. This result obtains even if the DW is subject to the same enforcement constraint that is responsible for the market failure. Thus, the DW intervention implies higher investment and output. However, the operation of the DW may cause inflation. Furthermore, the provision of cheap loans through the DW results in a worse income distribution. Therefore, there is room for welfare enhancing schemes that utilize the higher output to develop. We demonstrate that adequate lump sum taxes-cum-transfers along with the operation of the DW can support an allocation that is Pareto superior to the laissez-faire equilibrium allocation.

• Korean journal of communication and information
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• v.67
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• pp.88-118
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• 2014

This study attempted to clarify (1) the meaning of 'people's livelihood (Minsaeng, 民生)' conveyed by the newspapers in Korean society and the specific matter it refers to, and (2) consider the discourse formed by the newspapers and what does and does not change in that discourse over the passage of time. Editorials were classified and analyzed based on the framework of Fairclough's critical discourse analysis(CDA). It was clear, from the political perspective, that the discourse was respectively formed and changed for each administration. The discourse on 'people's livelihood' was critical and at the same time generally negative, because it dealt with the important social incidents or controversies of the time. The discourse on 'people's livelihood' related to the massive social streams of Korea's democratization and globalization process. Whereas the discourse on 'people's livelihood' in the 1990s, seen from an economic perspective, tried to resolve labor strikes, inflation rate, housing problem, and financial crisis. The discourse in the 2000s changed to issues ranging from economic growth and distribution to bi-polarization problem, job creation, abolishment of non-regular employments, etc. The meaning of 'people's livelihood' produced in the editorials of the major daily newspapers is different from the word's dictionary definition as 'the people's lives'.

• The Korean Journal of Financial Management
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• v.25 no.2
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• pp.1-31
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• 2008

Before the financial crisis in 1997, Korean bond markets had been those of corporate bonds with relatively high market yield. During the period, most of major institutional investors tend to utilize passive strategies such as buying and holding. After the crisis, however, they could not help choosing active bond management strategies because of lowed yield level and intensified competition among the financial institutions. This study is forced on the yield curve, which is the reflection of all information on the bond investment environments. The study also make analysis on the major economic and securities market factors and its structural relationship with the shape of the curve such as level, curvature and slope. For these purposes, an empirical model based on the Nelson-Siegel Model is estimated with the data during $1999{\sim}2006$. Out-of-sample forecasting is also made to test the usefulness of the estimated model. In addition, the dependent variables which are the estimates of level and slope are estimated on the macro variables and securities market variables. VAR and SUR models are used for the estimation. Estimation results show that level and slope of the yield curve are influenced by the target call rate change, exchange rate change rate, inflation rate. These results provide practical implications for the active managements in the overall treasury bond markets.

• Korean Journal of Construction Engineering and Management
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• v.5 no.6 s.22
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• pp.203-211
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• 2004

This study is the results to survey on the problems and improvable Policies for current escalation system in construction contracts, through a Delphi survey to experts. From the survey results, it is desirable to decide the fluctuation rate of construction cost, which is the requirement of escalation clause, on the basis of inflation rate or construction cost index. The desirable price fluctuation rate is proposed as a $3\%$ level. However, it is difficult for construction companies to cope with the sudden increase of material price in advance, arising from short-term shock factors such as exchange rate and international raw material's price. Accordingly escalation system for specified materials, as an exceptional mode, should be introduced. As a method to calculate the fluctuation rate, ARCA(adjustment rate for the categories of articles) is more desirable than ARI(adjustment rate for an index), because the ARCA can be more reflected the characteristics of each construction work.To rationalize the ARI method, it is needed to announce the wage index, material index and machinery expense index via detailed classification by construction types. Also, it is desirable to prescribe the bidding date as a starting date of the price change, rather than contact signing date. considering the price change can happen since the biddiilg stage.