The annealing effect on the spectral and nonlinear optical (NLO) characteristics of ZnO thin films deposited on quartz substrates by sol-gel process is investigated. As the annealing temperature increases from 300–1050 °C, there is a decrease in the band gap, which indicates the changes of the interface of ZnO. ZnO is reported to show two emission bands, an ultraviolet (UV) emission band and another in the green region. The intensity of the UV peak remains the same while the intensity of the visible peak increases with increase in annealing temperature. The role of oxygen in ZnO thin films during the annealing process is important to the change in optical properties. The mechanism of the luminescence suggests that UV luminescence of ZnO thin films is related to the transition from conduction band edge to valence band, and green luminescence is caused by the transition from deep donor level to valence band due to oxygen vacancies. The NLO response of these samples is studied using nanosecond laser pulses at off-resonance wavelengths. The nonlinear absorption coefficient increases from 2.9×10−6 to 1.0×10−4 m/W when the annealing temperature is increased from 300 to 1050 °C, mainly due to the enhancement of interfacial state and exciton oscillator strength. The third order optical susceptibility χ(3) increases with increase in annealing temperature (T) within the range of our investigations. In the weak confinement regime, T2.4 dependence of χ(3) is obtained for ZnO thin films. The role of annealing temperature on the optical limiting response is also studied.
Machine tool chatter is an unfavorable phenomenon during metal cutting, which results in heavy vibration of cutting tool. With increase in depth of cut, the cutting regime changes from chatter-free cutting to one with chatter. In this paper, we propose the use of permutation entropy (PE), a conceptually simple and computationally fast measurement to detect the onset of chatter from the time series using sound signal recorded with a unidirectional microphone. PE can efficiently distinguish the regular and complex nature of any signal and extract information about the dynamics of the process by indicating sudden change in its value. Under situations where the data sets are huge and there is no time for preprocessing and fine-tuning, PE can effectively detect dynamical changes of the system. This makes PE an ideal choice for online detection of chatter, which is not possible with other conventional nonlinear methods. In the present study, the variation of PE under two cutting conditions is analyzed. Abrupt variation in the value of PE with increase in depth of cut indicates the onset of chatter vibrations. The results are verified using frequency spectra of the signals and the nonlinear measure, normalized coarse-grained information rate (NCIR).
The design and development of a fibre optic evanescent wave refractometer for the detection of trace amounts of paraffin oil and palm oil in coconut oil is presented. This sensor is based on a side-polished plastic optical fibre. At the sensing region, the cladding and a small portion of the core are removed and the fibre nicely polished. The sensing region is fabricated in such a manner that it sits perfectly within a bent mould. This bending of the sensing region enhances its sensitivity. The oil mixture of different mix ratios is introduced into the sensing region and we observed a sharp decrease in the output intensity. The observed variation in the intensity is found to be linear and the detection limit is 2% (by volume) paraffin oil/palm oil in coconut oil. The resolution of this refractometric sensor is of the order of 10 −3. Since coconut oil is consumed in large volumes as edible oil in south India, this fibre optic sensor finds great relevance for the detection of adulterants such as paraffin oil or palm oil which are readily miscible in coconut oil. The advantage of this type of sensor is that it is inexpensive and easy to set up. Another attraction of the side-polished fibre is that only a very small amount of analyte is needed and its response time is only 7 s.
In this paper, a time series complexity analysis of dense array electroencephalogram signals is carried out using the recently introduced Sample Entropy (SampEn) measure. This statistic quantifies the regularity in signals recorded from systems that can vary from the purely deterministic to purely stochastic realm. The present analysis is conducted with an objective of gaining insight into complexity variations related to changing brain dynamics for EEG recorded from the three cases of passive,eyes closed condition, a mental arithmetic task and the same mental task carried out after a physical exertion task. It is observed that the statistic is a robust quantifier of complexity suited for short physiological signals such as the EEG and it points to the specific brain regions that exhibit lowered complexity during the mental task state as compared to a passive, relaxed state. In the case of mental tasks carried out before and after the performance of a physical exercise, the statistic can detect the variations brought in by the intermediate fatigue inducing exercise period. This enhances its utility in detecting subtle changes in the brain state that can find wider scope for applications in EEG based brain studies.
This article deals with the complexity aspects of the recorded electroencephalogram (EEG) signal from male and female subjects. The analysis follows direct application of time series measures of global linear complexity and characterization of the embedded complexity in the signals using the nonlinear statistic of approximate entropy. The study reveals significant differences in complexity between the two sex groups during passive, no-task conditions, whereas no apparent variation exists during a mental task state. The detection of subtle changes as well as the ease in presenting a global picture of the complexity variation on the human cortical surface makes the nonlinear statistic a better marker of system complexity.
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