With the advancement in the digital technologies, the internet has become major break-through and has been universally acceptable technology by the people of all the ages. They use the internet for the purpose of ente...
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Money laundering is a worrying term for every country’s economy these days. Leading economists of all major developed and developing economies are concerned to devise methods to prevent it. The economy of a country i...
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Scale-Free social network is universally popular among the users of almost all the ages. This scale-free network follows the Power Law that expresses the distribution of data in the form of body and tail. Tail can be ...
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This paper presents a novel method of improving image quality using meta-heuristic algorithms such as Bat Algorithm, Cuckoo Search Algorithm and Interior Search Algorithm by contrast enhancement method. The performanc...
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In this paper, High linearity low voltage Current Follower Transconductance Amplifier (CFTA) design has been proposed. The proposed circuit operates at ±0.6V symmetric supply voltage. The linearity of proposed CF...
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In this paper, optimum transistor sizing of clock-gated master slave flip-flops viz. Gated Master Slave Latch (GMSL) and clock-gated Transmission Gate Flip-flop (CG-TGFF) has been implemented for high performance base...
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Wind energy conversion systems have to handle the variations in the wind speed for efficient energy conversion. This paper presents an analysis made on the controller effectiveness system for pitch angle control of a ...
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This paper proposes implementation of a low power hybrid CMOS-Memristor Ring Oscillator (RO), with a higher randomness value compared to existing technologies. A comparison of conventional CMOS inverter, memristive lo...
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This paper presents a novel programmable Wien Bridge Oscillator (WBO) using hybrid CMOS-Memristor circuit to generate required frequency based on memristor programmability. The memristor consumes very small area at na...
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It is an important task in the agricultural domain to determine the stress levels in plants. Drought conditions can have an adverse effect on crop yield. Hyperspectral Imaging (HSI) combined with classical Machine Lea...
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It is an important task in the agricultural domain to determine the stress levels in plants. Drought conditions can have an adverse effect on crop yield. Hyperspectral Imaging (HSI) combined with classical Machine Learning algorithms are in current use to determine the stress levels. Every spectral band in an HSI does not contain useful information regarding the stress levels. For this reason, some vegetation indices are selected by agricultural researchers, based on reflectance ratios where a significant change in reflectance was observed because of stress. These indices do not always contain significant information because of changes in temperature, humidity or other atmospheric variations in different trials. There is no fixed set of vegetation indices which can be used to estimate stress levels accurately. In this paper, we demonstrated the working of Conditional Covariance Operator (CCM) which is used to select the most significant spectral bands from the collected Hyperspectral data itself. CCM is the most recent of the feature selection methods. This efficient feature selection method is used for the first time in this paper for plant stress analysis in rapid manner. It selects consistent discriminative spectral bands even when training examples per class are less than what other feature selection methods need. It can be seen that the Random Forest classifier model can classify the stress level into three categories (i) normal (ii) mild and (iii) severe stress with an accuracy of 99.7% when only 10 spectral bands are selected.
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