scholarly journals Incorrect Data in Text, Table, and Figure Legend

JAMA ◽  
2019 ◽  
Vol 322 (19) ◽  
pp. 1925
Keyword(s):  
Universe ◽  
2021 ◽  
Vol 7 (5) ◽  
pp. 138
Author(s):  
Yuri I. Yermolaev ◽  
Irina G. Lodkina ◽  
Lidia A. Dremukhina ◽  
Michael Y. Yermolaev ◽  
Alexander A. Khokhlachev

One of the most promising methods of research in solar–terrestrial physics is the comparison of the responses of the magnetosphere–ionosphere–atmosphere system to various types of interplanetary disturbances (so-called “interplanetary drivers”). Numerous studies have shown that different types of drivers result in different reactions of the system for identical variations in the interplanetary magnetic field. In particular, the sheaths—compression regions before fast interplanetary CMEs (ICMEs)—have higher efficiency in terms of the generation of magnetic storms than ICMEs. The growing popularity of this method of research is accompanied by the growth of incorrect methodological approaches in such studies. These errors can be divided into four main classes: (i) using incorrect data with the identification of driver types published in other studies; (ii) using incorrect methods to identify the types of drivers and, as a result, misclassify the causes of magnetospheric-ionospheric disturbances; (iii) ignoring a frequent case with a complex, composite, nature of the driver (the presence of a sequence of several simple drivers) and matching the system response with only one of the drivers; for example, a magnetic storm is often generated by a sheath in front of ICME, although the authors consider these events to be a so-called “CME-induced” storm, rather than a “sheath-induced” storm; (iv) ignoring the compression regions before the fast CME in the case when there is no interplanetary shock (IS) in front of the compression region (“sheath without IS” or the so-called “lost driver”), although this type of driver generates about 10% of moderate and large magnetic storms. Possible ways of solving this problem are discussed.


JAMA ◽  
2015 ◽  
Vol 314 (24) ◽  
pp. 2693
Keyword(s):  

Author(s):  
Bisma Gulzar ◽  
Ankur Gupta

As IoT applications are pervasively deployed across multiple domains, the potential impact of their security vulnerabilities are also accentuated. Sensor nodes represent a critical security vulnerability in the IoT ecosystem as they are exposed to the environment and accessible to hackers. When compromised or manipulated, sensor nodes can transmit incorrect data which can have a damaging impact on the overall operation and effectiveness of the system. Researchers have addressed the security vulnerabilities in sensor nodes with several mechanisms being proposed to address them. This paper presents DAM (Detect, Avoid, Mitigate), a theoretical framework to evaluate the security threats and solutions for sensor security in IoT applications and deployments. The framework leads to the classification of sensor security threats and categorization of available solutions which can be used to either detect vulnerabilities and attacks, recover from them or completely avoid them. The proposed framework will be useful for evaluating sensor security in real-world IoT deployments in terms of potential threats and designing possible solution


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