ECGadv: Generating Adversarial Electrocardiogram to Misguide Arrhythmia Classification System

Deep neural networks (DNNs)-powered Electrocardiogram (ECG) diagnosis systems recently achieve promising progress to take over tedious examinations by cardiologists. However, their vulnerability to adversarial attacks still lack comprehensive investigation. The existing attacks in image domain could not be directly applicable due to the distinct properties of ECGs in visualization and dynamic properties. Thus, this paper takes a step to thoroughly explore adversarial attacks on the DNN-powered ECG diagnosis system. We analyze the properties of ECGs to design effective attacks schemes under two attacks models respectively. Our results demonstrate the blind spots of DNN-powered diagnosis systems under adversarial attacks, which calls attention to adequate countermeasures.Comment: Accepted by AAAI 202

The Application of the “Three Accordance” Principles in the Translation of Foreign Publicity Texts: Taking the translation of Chinese leaders’ epidemic speech as examples

This paper takes the epidemic speech of Chinese leaders as the research object, analyzes the English translation of the epidemic speech of Chinese leaders in detail based on the “Three Accordance” Principles for External Publicity. The translation techniques of foreign publicity texts are discussed - comparing words with each other, turning images into meanings and adapting to local customs. These three techniques are used in order to show the strengths of China and avoid the prejudice and better publicize Chinese opinions and attitudes

Nonlinearity and efficiency dynamics of foreign exchange markets: evidence from multifractality and volatility of major exchange rates

This study investigates the efficiencies of the exchange markets for four major currencies—the euro (EUR), the pound (GBP), the Canadian dollar (CAD) and the Japanese yen (JPY)—from 2005 to 2019 by using multifractal detrended fluctuation analysis (MFDFA). This study also investigates the causes of these efficiencies. Significant multifractal properties are demonstrated by the four markets, and long-range correlation and fat-tail distribution properties are the main causes. We calculate and compare the multifractal degrees in three subsamples, which are classified based on their temporal relation to two economic events: the 2008 financial crisis and the announcement by the Federal Reserve of its withdrawal from the quantitative easing policy in 2014. Empirical results suggest that multifractal properties exist at different levels in the subsamples, thus showing that these events affect foreign exchange market efficiencies in terms of statistics and the fractal market. The JPY exchange market has the fewest multifractal properties, thus indicating that this exchange market has the highest market efficiency among these four exchange markets. The empirical results have implications for the nonlinear mechanism and efficiency in foreign exchange markets, which may help investors effectively manage market risks and benefit a stable global economy