We empirically analyze the impact of economic uncertainty due to the COVID-19 pandemic on the trading volume of each sector in the S&P 500 index. Wavelet coherence analysis is carried out using economic policy uncertainty data and the trading volume of each sector in the S&P 500 index from July 2004 to September 2020. Furthermore, we apply multifractal detrended fluctuation analysis to the trading volume series of all sectors. The wavelet coherence analysis shows that the COVID-19 pandemic has substantially influenced (...) trading volume in all sectors. However, the impact of the pandemic is different from that during the global financial crisis in some sectors, such as information technology, consumer discretionary, and communication services. Because of the lockdown taken to suppress COVID-19, increased remote working and remote learning are the main reasons for these results. Additionally, according to the MF-DFA analysis, the trading volume of all the sectors has clear multifractal characteristics, and they are all nonpersistent. Specifically, trading volumes of the real estate and materials sector are highly correlated, whereas the trading volumes of industry and information technology sectors are comparatively less correlated. (shrink)

In contemporary European policy discussion, “innovation“ is a term popularly used for finding responses to the pressure of global competition. In various forms of innovation, the accent is mainly given to technical and business innovation but less to social innovation. This article studies the issue of social innovation with reference to the local practice in Hangzhou city, which aims to strengthen the life quality of citizens in this city. These practices develop various forms of inter-sectoral collaboration, resulting in numerous “common (...) denominator subject“ (CDS) groups that are promoted by the local government. These practices follow the principles of cooperation and partnership, and thus develop a corporatist mechanism for urban development. Through discussion of these practices this article explores the nature and the features of these CDS groups, and evaluates its meaning for social innovation, local administration, life quality and social quality. (shrink)

To identify the common and specific structural basis of bipolar depression and unipolar depression is crucial for clinical diagnosis. In this study, a total of 85 participants, including 22 BD patients, 36 UD patients, and 27 healthy controls, were enrolled. A voxel-based morphology method was used to identify the common and specific changes of the gray matter volume to determine the structural basis. Significant differences in GMV were found among the three groups. Compared with healthy controls, UD patients showed decreased (...) GMV in the orbital part of the left inferior frontal gyrus, whereas BD patients showed decreased GMV in the orbital part of the left middle frontal gyrus. Compared with BD, UD patients have increased GMV in the left supramarginal gyrus and middle temporal gyrus. Our results revealed different structural changes in UD and BD patients suggesting BD and UD have different neurophysiological underpinnings. Our study contributes toward the biological determination of morphometric changes, which could help to discriminate between UD and BD. (shrink)

I. 왜 씨알인가 1. 씨알의 의미와 내용 2. 씨알사상과 씨알의 삶 3. 씨알사상의 시대적 의미 II. 씨알사상은 어떻게 생겨났는가 1. 동서문명의 만남 2. 씨알사상의 형성 3. 동서사상의 어울림 III. 내가 씨알이다 1. 주체의 철학 2. 스스로 함의 원리 3. 생각하는 백성이라야 산다 IV. 세계평화가 씨알에서 움튼다 1. 세계평화의 길 2. 반생명에서 생명친화로 3. 비폭력의 힘 V. 씨알은 세계통일로 나아간다 1. 세계통일을 위한 진통 2. 세계통일의 철학적 근거 3. 세계통일의 실천 VI. 씨알은 섬김으로 이끈다 1. 민주통일시대의 철학 2. 불타는 씨알생명 3. (...) 씨알의 삶과 섬기는 지도력 대담|21세기 씨알사상의 의미. (shrink)

철학계의 올림픽이라 할 세계철학대회가 2008년, 아시아권에서는 처음으로 서울에서 열렸다. 대회의 주제는 ‘동서 철학 전통의 만남과 융합’이었고, 유영모와 함석헌의 사상을 소개하는 특별분과가 열렸다. 다른 분과의 수강생은 서너 명에 불과했지만 유영모ᆞ함석헌 분과에는 800여 명이 몰리는 현상이 벌어졌고 이후 유럽과 일본에서는 씨알사상에 대한 본격적 연구가 시작되었다. 철학이 없어 더욱 불행했던 시기라고 하는 우리의 20세기는 유영모와 함석헌이라는 두 사상가를 숨겨 놓았다. 이 책은『다석일지』, 『다석강의』, 『뜻으로 본 한국역사』 등 두 거장의 저작에서 알짬을 뽑아 해설을 덧붙인 365일 묵상집이다. 우리말과 우리글로 철학을 한 두 사상가를 오랫동안 연구하고 (...) 글을 발표해 온 박재순 씨알사상연구소 소장이 해설을 붙였다. (shrink)

This study investigates the relationship among ethical philosophy, thinking style, and managerial ethical decision-making. Based on the premise that business ethics is a function of culture and time, we attempt to explore two important questions as to whether the national differences in managerial ethical philosophies remain over time and whether the relationship between thinking style and ethical decision-making is consistent across different national contexts. We conducted a survey on Korean managers’ ethical decision-making and thinking style and made a cross-cultural, cross-temporal (...) comparison with the results presented by previous studies that surveyed Korean and US managers with the same questionnaire at different points in time. Our analysis revealed that Korean managers have become more reliant on rule utilitarianism for ethical decision-making over the last two decades, which is dominantly used by US managers, corroborating our convergence hypothesis built on social contracts theory. However, as opposed to previous research, we found that managers with a balanced linear and nonlinear thinking style do not necessarily make more ethical decisions compared to those with a predominantly linear or nonlinear thinking style. This study contributes to international business ethics literature by presenting a theoretical framework that may explain the convergence of ethical philosophies employed by managers in different national contexts over time, and that the relationship between thinking style and managerial ethical decision-making may not be universal, but contingent on contextual factors. (shrink)

Eye-tracking technology has become a powerful tool for biomedical-related applications due to its simplicity of operation and low requirements on patient language skills. This study aims to use the machine-learning models and deep-learning networks to identify key features of eye movements in Alzheimer's Disease (AD) under specific visual tasks, thereby facilitating computer-aided diagnosis of AD. Firstly, a three-dimensional (3D) visuospatial memory task is designed to provide participants with visual stimuli while their eye-movement data are recorded and used to build an (...) eye-tracking dataset. Then, we propose a novel deep-learning-based model for identifying patients with Alzheimer's Disease (PwAD) and healthy controls (HCs) based on the collected eye-movement data. The proposed model utilizes a nested autoencoder network to extract the eye-movement features from the generated fixation heatmaps and a weight adaptive network layer for the feature fusion, which can preserve as much useful information as possible for the final binary classification. To fully verify the performance of the proposed model, we also design two types of models based on traditional machine-learning and typical deep-learning for comparison. Furthermore, we have also done ablation experiments to verify the effectiveness of each module of the proposed network. Finally, these models are evaluated by four-fold cross-validation on the built eye-tracking dataset. The proposed model shows 85% average accuracy in AD recognition, outperforming machine-learning methods and other typical deep-learning networks. (shrink)

Extreme events, which are usually characterized by generalized extreme value models, can exhibit long-term memory, whose impact needs to be quantified. It was known that extreme recurrence intervals can better characterize the significant influence of long-term memory than using the GEV model. Our statistical analyses based on time series datasets following the Lévy stable distribution confirm that the stretched exponential distribution can describe a wide spectrum of memory behavior transition from exponentially distributed intervals to power-law distributed ones, extending the previous (...) evaluation of the stretched exponential function using Gaussian/exponential distributed random data. Further deviation and discussion of a historical paradox are also provided, based on the theoretical analysis of the Bayesian law and the stretched exponential distribution. (shrink)

Face recognition is one of the core and challenging issues in computer vision field. Compared to computer vision, human visual system can identify a target from complex backgrounds quickly and accurately. This paper proposes a new network model deriving from Where-What Networks (WWNs), which can approximately simulate the information processing pathways (i.e., dorsal pathway and ventral pathway) of human visual cortex and recognize different types of faces with different locations and sizes in complex background. To enhance the recognition performance, synapse (...) maintenance mechanism and neuron regenesis mechanism are both introduced. Synapse maintenance is used to reduce the background interference while neuron regenesis mechanism is introduced to regulate the neuron resource dynamically to improve the network usage efficiency. Experiments have been conducted on human face images of 5 types, 11 sizes, and 225 locations in complex backgrounds. Experiment results demonstrate that the proposed WWN model can basically learn three concepts (type, location and size) simultaneously. The experiment results also show the advantages of the enhanced WWN-7 model for face recognition in comparison with several existing methods. (shrink)

Since the breakdown of the Bretton Woods system in the early 1970s, the foreign exchange market has become an important focus of both academic and practical research. There are many reasons why FX is important, but one of most important aspects is the determination of foreign investment values. Therefore, FX serves as the backbone of international investments and global trading. Additionally, because fluctuations in FX affect the value of imported and exported goods and services, such fluctuations have an important impact (...) on the economic competitiveness of multinational corporations and countries. Therefore, the volatility of FX rates is a major concern for scholars and practitioners. Forecasting FX volatility is a crucial financial problem that is attracting significant attention based on its diverse implications. Recently, various deep learning models based on artificial neural networks have been widely employed in finance and economics, particularly for forecasting volatility. The main goal of this study was to predict FX volatility effectively using ANN models. To this end, we propose a hybrid model that combines the long short-term memory and autoencoder models. These deep learning models are known to perform well in time-series prediction for forecasting FX volatility. Therefore, we expect that our approach will be suitable for FX volatility prediction because it combines the merits of these two models. Methodologically, we employ the Foreign Exchange Volatility Index as a measure of FX volatility. In particular, the three major FXVIX indices from 2010 to 2019 are considered, and we predict future prices using the proposed hybrid model. Our hybrid model utilizes an LSTM model as an encoder and decoder inside an autoencoder network. Additionally, we investigate FXVIX indices through subperiod analysis to examine how the proposed model’s forecasting performance is influenced by data distributions and outliers. Based on the empirical results, we can conclude that the proposed hybrid method, which we call the autoencoder-LSTM model, outperforms the traditional LSTM method. Additionally, the ability to learn the magnitude of data spread and singularities determines the accuracy of predictions made using deep learning models. In summary, this study established that FX volatility can be accurately predicted using a combination of deep learning models. Our findings have important implications for practitioners. Because forecasting volatility is an essential task for financial decision-making, this study will enable traders and policymakers to hedge or invest efficiently and make policy decisions based on volatility forecasting. (shrink)

v. Chʻamdoen na chʻatki -- v. 2 Sesang paro pogi.

Ben shu de zhu yao nei rong shi chan shu zhe xue de te shu de li lun xing zhi he du te de huo dong fang shi,Bing tong guo ju ti lun zheng zhe xue dui gou cheng si xiang de ji ben xin nian,Ji ben luo ji,Ji ben fang shi,Ji ben guan nian,Zhe xue li nian de qian ti pi pan,Zhan xian zhe xue fa zhan de zi wo pi pan de huo li he yong bu ku jie (...) de li lun kong jian. (shrink)

During the past decade, Si Xiao, Xianglong Zhang, Xiangcheng Sun and others have proposed a Confucian Philosophy of Family movement as a response to issues in contemporary China. These issues...