Income Distribution and Public Transfers as Social Safety Nets in Korea

Using 5-year balanced household panel data, this paper shows that the inequality of per capita income in Korea aggravated during the financial crisis in 1998. The decomposition analysis of income inequality by factor component shows that the dominant positive effect on the income inequality is by the asset income. Next is the wage income, followed by the other income. Furthermore, this paper shows that social safety net programs were not yet in place during the initial period of the crisis. Public transfers were not effective social safety net devices and did not contribute in decreasing income inequality. Private transfers, on the other hand, were effective devices and narrowed the disparity in household income.

Implementation Of Automated Systems For Target Cost Management And Assessing Performance: A Case Study In A Global Automobile Component Company

We examine the implementation of automated systems for target cost management and assessing firm performance in global automobile component company. After financial crisis, companies need to make strategic decisions as fast as possible. However, global companies are difficult to make fast decisions because of taking time for sorting the internal data through oversea companies. Also there are difficult to build systems of cost management and assessment of performance achievement. In this study, as we explain elaborately about the automatic process of cost management and assessment of performance achievement systems in global automobile component companies, we provide practical implications of this benchmark case for other companies’ automated target cost management systems and assessing performance system’s innovations

Is Foreign Direct Investment Effective From The Perspective Of Tax Avoidance? An Analysis Of Tax Avoidance Through The International Transfer Pricing Behaviors Of Korean Corporations

This study examines whether multinational companies carry out tax avoidance through subsidiaries. An empirical analysis was conducted of 4,585 Korean firms from 2001 to 2010 by company and year. The results are as follows. First, MNCs that have become more internationally diversified through the establishment of overseas subsidiaries generally show a higher tendency to avoid tax. Thus, the analysis results show a positive correlation between globally diversified MNCs and corporate tax avoidance. This correlation is established due to the firms' active use of tax strategies (investment tax credits, tax cuts) applicable to the various countries in which they have expanded their businesses. Second, the analysis results showed that these firms actively avoided tax with overseas transfer pricing behaviors when compared to companies without overseas subsidiaries. Thus, the adjustment of sales prices and purchase value through actual transactions increased the propensity of the parent company to avoid tax.

Schwannomatosis of the tibial nerve

Schwannoma is the most common type of benign tumor arising from the sheaths of the peripheral nerves. It occurs as a solitary tumor in most cases, but when it appears in multiple forms, it is necessary to differentiate it from plexiform schwannoma, schwannomatosis, neurofibroma and malignant peripheral nerve tumors. The authors experienced schwannomatosis in the tibial nerve without the features of neurofibromatosis type 2, so here we present a case report and literature review

Construction and nonnegativity of sign idempotent sign pattern matrices

AbstractIn this paper, we modify Eschenbach’s algorithm for constructing sign idempotent sign pattern matrices so that it correctly constructs all of them. We find distinct classes of sign idempotent sign pattern matrices that are signature similar to an entrywise nonnegative sign pattern matrix. Additionally, if for a sign idempotent sign pattern matrix A there exists a signature matrix S such that SAS is nonnegative, we prove such S is unique up to multiplication by -1 if the signed digraph D(A) is not disconnected

Risk factors for delayed and non-union following transfibular ankle arthrodesis

Background: This study was to identify risk factors associated with delayed union and non-union in patients who underwent transfibular ankle arthrodesis.Methods: This study included 43 patients who underwent ankle arthrodesis using transfibular approach between January 2012 and September 2018 and were followed up for more than 12 months. The patients were divided into two groups according to delayed union or non-union. Group A included patients who had delayed union or non-union and Group B included patients without these complications. Variables that could contribute to non-union including etiologies, age, chronic renal failure, hypertension, diabetes, smoking, pre-operative talus bone quality, pre-operative angulation of the talus and fixation methods were evaluated.Results: The mean time to bone union was 12.7±7.25 weeks. Group A included 12 patients with 5 cases of non-union and 7 cases of delayed union and group B included 31 patients. Infection of the ankle joint (OR, 1.73; p=0.041) was risk factor for non-union and delayed union on the basis of multivariate analysis.Conclusions: We concluded that infection of the ankle joint is the most significant risk factor for delayed union and nonunion in our study. Careful attention should be paid preoperatively, intraoperatively and postoperatively to patients who have this risk factor to obtain a satisfactory surgical outcome

CropCat: Data Augmentation for Smoothing the Feature Distribution of EEG Signals

Brain-computer interface (BCI) is a communication system between humans and computers reflecting human intention without using a physical control device. Since deep learning is robust in extracting features from data, research on decoding electroencephalograms by applying deep learning has progressed in the BCI domain. However, the application of deep learning in the BCI domain has issues with a lack of data and overconfidence. To solve these issues, we proposed a novel data augmentation method, CropCat. CropCat consists of two versions, CropCat-spatial and CropCat-temporal. We designed our method by concatenating the cropped data after cropping the data, which have different labels in spatial and temporal axes. In addition, we adjusted the label based on the ratio of cropped length. As a result, the generated data from our proposed method assisted in revising the ambiguous decision boundary into apparent caused by a lack of data. Due to the effectiveness of the proposed method, the performance of the four EEG signal decoding models is improved in two motor imagery public datasets compared to when the proposed method is not applied. Hence, we demonstrate that generated data by CropCat smooths the feature distribution of EEG signals when training the model.Comment: 4 pages, 1 tabl

Effectiveness of vaccination and quarantine policies to curb the spread of COVID-19

A pandemic, the worldwide spread of a disease, can threaten human beings from the social as well as biological perspectives and paralyze existing living habits. To stave off the more devastating disaster and return to a normal life, people make tremendous efforts at multiscale levels from individual to worldwide: paying attention to hand hygiene, developing social policies such as wearing masks, social distancing, quarantine, and inventing vaccines and remedy. Regarding the current severe pandemic, namely the coronavirus disease 2019, we explore the spreading-suppression effect when adopting the aforementioned efforts. Especially the quarantine and vaccination are considered since they are representative primary treatments for block spreading and prevention at the government level. We establish a compartment model consisting of susceptible (S), vaccination (V), exposed (E), infected (I), quarantined (Q), and recovered (R) compartments, called SVEIQR model. We look into the infected cases in Seoul and consider three kinds of vaccines, Pfizer, Moderna, and AstraZeneca. The values of the relevant parameters are obtained from empirical data from Seoul and clinical data for vaccines and estimated by Bayesian inference. After confirming that our SVEIQR model is plausible, we test the various scenarios by adjusting the associated parameters with the quarantine and vaccination policies around the current values. The quantitative result obtained from our model could suggest a guideline for policy making on effective vaccination and social policies.Comment: 8 pages, 5 figure