In this work, MoSe₂-WS₂ nanocomposites consisting of WS₂ nanoparticles covered with few MoSe₂ nanosheets were successfully developed via an easy hydrothermal synthesis method. Their nanostructure and photocatalytic hydrogen evolution (PHE) performance are investigated by a series of characterization techniques. The PHE rate of MoSe₂-WS₂ is evaluated under the white light LED irradiation. Under LED illumination, the highest PHE of MoSe₂-WS₂ nanocomposite is 1600.2 µmol g⁻¹ h⁻¹. When compared with pristine WS₂, the MoSe₂-WS₂ nanostructures demonstrated improved PHE rate, which is 10-fold higher than that of the pristine one. This work suggests that MoSe₂-WS₂ could be a promising photocatalyst candidate and might stimulate the further studies of other layered materials for energy conversion and storage.

Algorithms in Data mining are utilized to predict unrefined data into useful conventional information. This conservative information plays a vital role in the Health care industry. In this study we focus on the functionalities of diabetes prediction. In diabetes data we have the problem of data imbalance in predicting the accuracy. The Proposed tailored Firefly Algorithm along with Map reduce is used to augment the efficacy and precision of prediction. Comparison of Different bench mark algorithms with our new Extended Fire Fly is done and variety of classification methods are used with moto to increase the effectiveness. The new method helps to maximize the prediction of accuracy and reduces the time. The PIMA Indian Diabetic Dataset from UCI machine learning repository is utilized for our experiment results. Different metrics are used in order to prove the effectiveness.

Introduction: Sleep is important in humans, and it is affected by lifestyle changes. Improper sleep leads to serious physiological problems and disorders that occurs in human brain/scalp. These physiological changes and electrical activity of the human brain are recorded as electroencephalogram (EEG) signals. This paper describes the detection of a major sleep disorder \textit{i.e.}, sleep apnea (SA). Methods: In this paper, sleep apnea is measured using various artifacts taken from the subjects. The discrete wavelet transform (DWT) is used to extract characteristics from an electroencephalogram (EEG) signal and to detect sleep. This is used to determine whether a person has obstructive sleep apnea (OSA) or central sleep apnea (CSA). The wavelet technique is used to split the EEG signal into five frequency bands: delta, theta, alpha, beta, and gamma. Results: For these five frequency bands, the mean, standard deviation, variance, maximum, minimum, and energy are computed. Discussion: A sleep problem is detected based on these characteristics.

Ionosphere is the highest contributor of positional error in Global Navigation Satellite System (GNSS) owing to the trans-ionospheric signal delay, distortion and possible outage. Equatorial and Low latitudinal ionosphere experiences frequent perturbations in plasma density most of which is due to the presence of Equatorial Plasma Bubbles (EPBs). In order to improve positional and navigational precision of GNSS signals, EPBs must be identified and corrected. EPBs begin to manifest post-sunset and continue to thrive past midnight. This paper proposes a Rate of TEC Index (ROTI) based EPB identifier using single frequency GNSS receiver data. GNSS data has been collected from the archives of Scripps Orbit and Permanent Array Center (SOPAC). The raw data has been downloaded from the global continuous network station, IISC, located at Bangalore (13.0219°N, 77.5671°E) in Receiver Independent Exchange (RINEX) format. Analysis of EPB occurrence has been carried out for six consecutive years in the second half of the 24th solar cycle (2014-2019). The results show a clear surge in the number of EPBs identified in the course of equinoxes.

Hemoglobin plays a major role for the existence of the healthy human being it carries oxygen supply to every cell for its survival in the entire body. As its level varies from person to person between 12-17 grams per deciliter if very high or low cause diseases. Usually low hemoglobin cause anemia in many of the women during pregnancy. In the present article the hemoglobin measurement is done noninvasively using the photoplethysmography method at the fingertip by Infrared LED with a wavelength of (880 - 940) nm and Red LED with wavelength of 660nm. The empirical calculation of Hemoglobin estimation is carried indirectly through model of oxygen saturation in skin-tissuebone attenuation of the light on to the extremities. The analysis is supported by the Arduino IDE and MATLAB toolboxes for filtering the noise in signal and processing for target parameters. Further these real time parameters were sent to expertise to check for corrective ness and with the actual invasive methods for diagnosing its course of action. Internet of Things (IOT) technology to the outside world communication through Android mobile App.