A time series analysis can help to observe the behavior of the system and specify the system faults. In addition, it also helps to explain the various energy flows in the system and further aid in reducing the thermodynamic losses. The intelligent supervisory LabVIEW software can monitor the incoming data from the system by using Arduino microcontroller and calculates the important parameters. Energy, exergy, and anergy analysis present in this paper to investigate the system performance as well as its components. To accomplish this, a 4-ton vertical split air conditioner based on vapor compression refrigeration cycle charged with refrigerant R-22 was modified for experimental analysis. The results showed that during 540

Mechanical and thermal properties of composites, consisted of unsaturated polyester resin, reinforced by different kinds of natural materials (Orange peels and Date seeds) and industrial materials (carbon and silica) with particle size 98 µm were studied. Various weight ratios, 5, 10, and 15 wt. % of natural and industrial materials have been infused into polyester. Tensile, three-point bending and thermal conductivity tests were conducted for the unfilled polyester, natural and industrial composite to identify the weight ratio effect on the properties of materials. The results indicated that when the weight ratio for polyester with date seeds increased from 10% to 15%, the maximum Young’s modulus decreased by 54%. When the weight rat

In this study, multi-objective optimization of nanofluid aluminum oxide in a mixture of water and ethylene glycol (40:60) is studied. In order to reduce viscosity and increase thermal conductivity of nanofluids, NSGA-II algorithm is used to alter the temperature and volume fraction of nanoparticles. Neural network modeling of experimental data is used to obtain the values of viscosity and thermal conductivity on temperature and volume fraction of nanoparticles. In order to evaluate the optimization objective functions, neural network optimization is connected to NSGA-II algorithm and at any time assessment of the fitness function, the neural network model is called. Finally, Pareto Front and the corresponding optimum points are provided and

Complexes ofCo(ll),Cu(||),Ni(||),pt(|| ),and pd(||) with N3O-chelating Ligand Incorporating Azo and Shiff Base Moieties ;synthesis, spectroscopic ,Thermal Decomposition Theoretical

The present article discusses the synthesis of tetradentate Schiff base complexes formed by the condensation reaction of 2-hydroxy benzaldehyde and phthalohydrazide. The ligand (LH2) was detected using FT-IR spectra, 1H, 13C-NMR, UV-Vis spectroscopy, elemental microanalysis CHN, and mass spectrometry. The obtained solid complexes have been assessed using physicochemical and spectroscopic techniques, including UV-Vis, FT-IR, nuclear magnetic resonance (1H-NMR, 13C-NMR), mass spectrometry, thermal gravimetric analysis (TGA), and atomic absorption, in addition to complex conductivity and magnetic moment measurements. The infrared results demonstrated that ligands functioning as tetradentate ligands are chelated to metal ions via the ph

Objective: To identify causes of maternal death in Mizan Aman and Gebretsadik shawo general hospitals
Methodology: A case control study on 595 charts, 119 cases and 476 controls was conducted in Mizan
Aman & Gebretsadik shawo general hospitals. Data was analyzed by STATA 13.1. Propensity score
matching analysis was used to see causes of maternal death.
Results: Hemorrhage were the main direct causes of maternal death which accounts 47.9% (β =0.58
(95% CI (0.28,0.87)) in hospital but when projected to population based the sample (β =0.26 (95% CI
(0.22,0.31)). Followed by infection 36 (25.21%) (β = 0.50 (95% CI (0.08, 0.92)). when projected to
population based the sample PIH 7.6%) is significant cause (β = 0.16

Background: Measuring implant stability is an important issue in predicting treatment success. Dental implant stability is usually measured through resonance frequency analysis (RFA). Osstell® RFA devices can be used with transducers (Smartpeg™) that correspond to the implants used as well as with transducers designed for application with Penguin® RFA devices (Multipeg™). Aims: This study aims to assess the reliability of a MultiPeg™ transducer with an Osstell® device in measuring dental implant stability. Materials and Methods: Sixteen healthy participants who required dental implant treatment were enrolled in this study. Implant stability was measured by using an Osstell® device with two transducers, namely, Smartpeg™ and M

This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD