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2D Materials ◽  
2021 ◽  
Author(s):  
Sung Ju Hong ◽  
Xiao Xiao ◽  
Dirk Wulferding ◽  
Christopher Belke ◽  
Peter Lemmens ◽  
...  
Keyword(s):  

2019 ◽  
Vol 7 (5) ◽  
pp. 337
Author(s):  
Zheng Fuchun ◽  
Chang Jianing ◽  
Zong Fei ◽  
Zhang Hao ◽  
Li Shengjun ◽  
...  
Keyword(s):  

2018 ◽  
Vol 11 (1) ◽  
pp. 14-22
Author(s):  
Rashesh Vaidya

The stochastic oscillator is one of the popular tools used by technical analysts. The tools are used mainly to find the overbought and oversold position in the stock market. The stochastic values are between 0-100 which helps to determine the market scenario. The two stochastic indicators are comprised of two lines namely; %K and %D. The investors using the short-term moving average follows %K and for long-term moving average for %D. Though, both are used for buy signal or sell signal by the investors. The basic concept is if, the value of %K is seen above %D, which reflects to sell position, which in context to Nepalese stock market, the scenario is seen during the month of June-July of every fiscal year. At the same time, momentum uses transaction signal or trade signal or the zero ‘0’ line to find the bearish or bullish trend of the market. The momentum of NEPSE index clearly pictures out the bullish and the bearish trend for a specific duration. If the momentum line touches the ‘zero line’, the NEPSE has changed its trend.


2018 ◽  
Vol 98 (24) ◽  
Author(s):  
Tao Hou ◽  
Guanghui Cheng ◽  
Wang-Kong Tse ◽  
Changgan Zeng ◽  
Zhenhua Qiao
Keyword(s):  

2018 ◽  
Vol 14 (2) ◽  
Author(s):  
Ke Wang ◽  
Tao Hou ◽  
Yafei Ren ◽  
Zhenhua Qiao
Keyword(s):  

2018 ◽  
Vol 8 (8) ◽  
pp. 1236 ◽  
Author(s):  
Iban Gómez ◽  
Ester Viteri ◽  
Jessica Montero ◽  
Mile Djurdjevic ◽  
Gerhard Huber

The aim of this work is to give an overview of existing methods and to introduce three new methods for the determination of the Dendrite Coherency Point (DCP) for AlSi10Mg alloys, as well as to compare the acquired values of DCP based on a thermal analysis and on the analysis of cooling curves working with only one thermocouple. Additionally, the impact of alloying and contaminant elements on the DCP will be also studied. The first two proposed methods employ the higher order derivatives of the cooling curves. The DCP was determined as the crossing point of the second and third derivative curves plotted versus time (method 1) or that of the temperature (method 2) with the zero line just after the maximum liquidus temperature. The third proposed method is based on the determination of the crossing point of the third solid fraction derivative curve with the zero line, corresponding to a minimum of the second derivative. A Taguchi design for the experiments was developed to study the DCP values in the AlSi10Mg alloy. The DCP temperature values of the test alloys were compared with the DCP temperatures predicted by the previous methods and the influence of the major and minor alloying elements and contaminants over the DCP. The new processes obtained a correlation factor r2 from 0.954 and 0.979 and a standard deviation from 1.84 to 2.6 °C. The obtained correlation values are higher or similar than those obtained using previous methods with an easier way to define the DCP, allowing for a better automation of the accuracy of DCP determination. The use of derivative curves plotted versus temperature employed in the last two proposed methods, where the test samples did not have an influence over the registration curves, is proposed to have a better accuracy than those of the previously described methods.


2017 ◽  
Vol 96 (15) ◽  
Author(s):  
Yafei Ren ◽  
Junjie Zeng ◽  
Ke Wang ◽  
Fuming Xu ◽  
Zhenhua Qiao
Keyword(s):  

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