This paper presents an industrial monitoring system design using the Internet of Things (IoT). The gas sensor (MQ-5) captured information is posted into a data cloud. The sensor detects the leakage of gas under most atmospheric conditions. All the components are controlled by an Arduino (UNO-1) that acts as a central processor unit in the setup t. As soon as a gas leakage is detected by the sensor, the alarm is raised in the form of a buzzer. This alarm is supported by an LCD to display the location of leakage, alert the observer, and activate the exhaust fan in the particular section to extract leaked gas. The requirement of a gas detection system is not only to monitor continuously the surroundings but also to help prevent the gas leakage hence minimizing the chances of fire and damage.

Most complex physical phenomena are described by non-linear Burgers’ equations, which help us understand them better. This article uses the transformation and the fractional Taylor’s formula to find approximate solutions for non-linear fractional-order partial differential equations. Solving non-linear Burgers’ equations with the right starting data shows that the method utilized is correct and can be utilized. Based on the limit of the idea, a rapid convergence McLaurin series is used to obtain close series solutions for both models with less work and more accuracy. To see how time-Caputo fractional derivatives affect how the results of the above models behave, in three dimension figures are drawn. The results showed that the proposed method is an easy, flexible, and helpful way to solve and understand a wide range of non-linear physical models.

This paper considers a no-wait flow shop scheduling (NWFS) problem, where the objective is to minimise the total flowtime. We propose a genetic algorithm (GA) that is implemented in a spreadsheet environment. The GA functions as an add-in in the spreadsheet. It is demonstrated that with proposed approach any criteria can be optimised without modifying the GA routine or spreadsheet model. Furthermore, the proposed method for solving this class of problem is general purpose, as it can be easily customised by adding or removing jobs and machines. Several benchmark problems already published in the literature are used to demonstrate the problem-solving capability of the proposed approach. Benchmark problems set ranges from small (7-jobs, 7 machines) to large (100-jobs, 10-machines). The performance of the GA is compared with different meta-heuristic techniques used in earlier literature. Experimental analysis demonstrate that solutions obtained in this research offer equal quality as compared to algorithms already developed for NWFS problems.

This paper aims to theoretically study the concept of a photonic salinity and temperature sensor according to a deformed one-dimensional photonic structure. The fundamental capability of the proposed sensor is studied. Simultaneously we search to optimize the thickness of the structure and to get the maximum salinity and temperature sensitivity. The structure is constructed by alternating layers of TiO₂ and fused-silica P times. In the middle of the structure, a cavity containing seawater is inserted to measure its salinity and temperature. The transfer matrix method (TMM) is used to simulate the wave-transmittance spectra. It is shown that the quality factor (Q-factor) of the resonance peaks depends on the number (P) of layers. After that, the thickness of the layers is deformed by changing the deformation degree (h). The parameters P and h are optimized to get the maximal Q-factor with the minimal number of layers and structure thickness. The best sensitivity S_S of the proposed salinity sensor is 558.82 nm/RFIU with a detection limit of 0.0034 RFIU. In addition, the best sensitivity S_T of the designed temperature sensor is 600 nm/RFIU with a detection limit of 0.0005 RFIU.

Background: Grid-tied inverters play an efficient role in the integration of renewable energy resources with utility grids. Motivation: However, the interconnection between power converters and the grid has been seen to be responsible for various stability issues such as weak grid, and under weak grid conditions the injection of power to the grid becomes a challenging task due to continuously varying grid impedance affecting the stability margins as a result. Additionally, the grid impedance-related issues boost the voltage harmonics which further devalue its performance. These voltage harmonics propagate through the Phase-Locked Loop (PLL) circuit to the control unit of the inverter which in turn amplifies the low order harmonics of the inverter. Method: The aim of this research is to introduce a novel strategy that decreases the effect of grid impedance-variations on the performance and stability of an inverter. Hence, an adaptive hybrid mode control technique consisting of two parts is proposed in this research. The current regulator part is implemented in a synchronous reference frame for its gain and time parameters to improve the performance, stability, and response time. The adaptive harmonic compensators are implemented in a stationary reference frame for harmonic compensation purposes. This adaptive nature of harmonic compensator can effectively work in the case of frequency variation where the fixed value based harmonic compensator fails. Results: The adaptive harmonic compensators improve the performance by reducing total harmonic distortion (THD), reduce computation and improve stability when the grid has distorted voltage, variation in grid impedance and frequency. Impact and utility: Our results show that the system becomes less sensitive to grid impedance variations which makes the proposed technique very relevant to the stability performance applications.

Recent developments in textiles have led to the manufacturing of a variety of fabrics. These developments include spacer fabrics, embroidered fabrics, embedded sensors in fabrics, ECG vests, etc. Electronic components are also being knit within fabrics. The study used a configuration of thermocouples, based on the Seebeck effect, knitted into the main structure using a variety of yarn filaments. The knitted fabric was tested against temperature variation to examine how it affects the impedance of the knitted thermocouples. The testing procedure produced promising results, as it showed that certain combinations of knitting materials may result in positive and negative temperature coefficients of the fabric. The combination of the tested materials provides a guide to developing similar structures for thermoelectric sensor applications.