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To determine the distance, presence, or absence of the object by using a transmitter or photoelectric receiver the photoelectric device is used. The potential of a photovoltaic (PV) panel to produce power is roughly dependent on the intensity of sunlight falling on it. This study planned and constructed a dual-axis solar programmable logical controller (PLC) based automatic tracking system, as well as its management and signal conditioning. The suggested automated monitoring system regulates the elevation and orientation angles of solar panels to keep them transverse to the sun at all times. The capacity of the pouring source to right path the position of the sunlight is detracting for the proper functioning of warm excited lasers, which is an essential resource of absorbing light part of every 24 h. The current pursuing electronics, in another way, has poor strength and pursuing accuracy. To view the same issue, a photoelectric tracking system accompanying qual pivot is ingrained. The proposed system is based on the idiosyncratic multi quadrant photoelectric detector is implemented and a tracking scheme with a solar orbital method is included. The cosmic at fixed intervals monitoring device’s control design, in pair with the fine bringing into the harmony of the multi-one of four equal parts photoelectric indicator, substantially increases the effectiveness of the projected model. The pump source’s accurate positioning and tracking capabilities to the solar azimuth enable the pump source’s system reliability.

The problem of contamination in ceramic insulators was found to be frequent in power transmission lines and transformers. The key aim was to develop aquaphobic zirconium oxide (ZrO2) thin films using DC reactive magnetron sputtering over glass insulators to mitigate contamination problems. This was achieved by introducing O2 and Ar gas in the sputtering chamber, and three properties, namely, structural, optical, and aquaphobic, were inspected by changing the sputtering gas ratio (oxygen/argon). These properties were chosen based on comparison with the bulk ZrO2. These deposited ZrO2 samples were identified by X-ray diffractometer (XRD), atomic force microscopy (AFM), UV-Vis-NIR spectrophotometer, and contact angle goniometer (CAG). For all the samples, coatings were found to be limpid, clear, and aquaphobic. Coarseness (62.813 nm) and the contact angle made by water to the surface (107.45°) were found utmost as deposited at 0.25 oxygen/argon gas ratios. The transmittance and band gap were also found to be 90% and 5.33 eV, respectively, at this particular ratio.

Friction stir welding (FSW) was used to combine two different Al–Cu alloys, AA2618-T87 and Al–Mg alloy AA5086-H321 plates, and the characteristics of the procedure were adjusted using Taguchi L16 orthogonal experiments planned in advance. Consideration was given to a variety of factors including rotational and cross-sectional speeds, geometry, and the tool-to-pin-diameter ratio. The tensile strength of the joint was used to identify the best procedure parameters. Runs with the ideal settings confirmed the projected optimal tensile strength value. A wide range of process parameters can be used to generate high-quality joints, according to this study. According to the results of an analysis of variance, the most important factor in determining the soundness of a joint is the fraction of tool contact area to pin diameter, although pin shape and welding speed also have a major impact. During this examination, it was observed that the nugget region is dominated by material on the forward-moving side. Heat-affected zones with tensile failures occurred on the alloy 5086 side of the weldment.

The term blockchain is mainly regarded as the distributed transaction which is mainly comprised of different blocks, and each set tends to represent the data that are being associated with the previous blocks. The blockchain is mainly managed through peer-to-peer networks which comparatively involves in adhering to the protocol of authenticating various blocks to form the blockchain. The usage of blockchain technology has been increasingly used in different fields, and healthcare services are now using blockchain for better patient delivery, detecting disease, and other aspects. The scope of the proposed study is that this study has exploited the function of a blockchain-enabled big data network to support medical professionals in giving better treatment modalities and delivering better patient care. The application of a new generation of smart block chains such as Ethereum and NEM is now offering better services and features in creating blockchain-based healthcare data management and hence support healthcare centers, medical practitioners, nurses, radiologists, and patients for better healthcare management. The application of blockchain technology in big data networks supports adding more value as it results in enhanced data quality, accessibility, and support in creating better security and safety of data and information, which is highly essential in the medical industry. Blockchain technology enables big data technologies enabled in supporting medical practitioners in addressing various healthcare ailments; one of the major diseases impacting many people around the world is diabetes. Patients with such ailments tend to generate more data and information related to the disease and health-related aspects. Hence, this information requires being maintained and analyzed, so that superior healthcare services can be provided. This study is more involved in the investigation of blockchain technology through a big data network enabled in offering better care for elderly individuals who have been affected due to diabetes, the researchers propose to choose a questionnaire method to collect the data from nearly 169 respondents, and these data were then analyzed using SPSS data package. The analyst used percentage analysis, correlation analysis, and chi-square test to analyze the data which has been collated by the researchers. The results and discussion show in detail the major aspects of blockchain technology in supporting healthcare professionals for better diabetes care management for elderly individuals.

Big Data is rapidly gaining impetus and is attracting a community of researchers and organization from varying sectors due to its tremendous potential. Big Data is considered as a prospective raw material to acquire domain specific knowledge to gain insights related to management, planning, forecasting and security etc. Due to its inherent characteristics like capacity, swiftness, genuineness and diversity Big Data hampers the efficiency and effectiveness of search and leads to optimization problems. In this paper we explore the complexity imposed by big search spaces leading to optimization issues. In order to overcome the above mentioned issues we propose a hybrid algorithm for Big Data preprocessing ACO-clustering algorithm approach. The proposed algorithm can help to increase search speed by optimizing the process. As the proposed method using ant colony optimization with clustering algorithm it will also contribute to reducing pre-processing time and increasing analytical accuracy and efficiency.