The world’s energy consumption is outpacing supply due to population growth and technological advancements. For future energy demands, it is critical to progress toward a dependable, cost-effective, and sustainable renewable energy source. Solar energy, along with all other alternative energy sources, is a potential renewable resource to manage these enduring challenges in the energy crisis. Solar power generation is expanding globally as a result of growing energy demands and depleting fossil fuel reserves, which are presently the primary sources of power generation. In the realm of solar power generation, photovoltaic (PV) panels are used to convert solar radiation into energy. They are subjected to the constantly changing state of the environment, resulting in a wide range of defects. These defects should be discovered and remedied as soon as possible so that PV panels efficiency, endurance, and durability are not compromised. This paper focuses on five aspects, namely, (i) the various possible faults that occur in PV panels, (ii) the online/remote supervision of PV panels, (iii) the role of machine learning techniques in the fault diagnosis of PV panels, (iv) the various sensors used for different fault detections in PV panels, and (v) the benefits of fault identification in PV panels. Based on the investigated studies, recommendations for future research directions are suggested.

Over the past few years, natural fiber composites have been a strategy of rapid growth. The computational methods have become a significant tool for many researchers to design and analyze the mechanical properties of these composites. The mechanical properties such as rigidity, effects, bending, and tensile testing are carried out on natural fiber composites. The natural fiber composites were modeled by using some of the computation techniques. The developed convolutional neural network (CNN) is used to accurately predict the mechanical properties of these composites. The ground‐truth information is used for the training process attained from the finite element analyses below the plane stress statement. After completion of the training process, the developed design is authorized using the invisible data through the training. The optimum microstructural model is identified by a developed model embedded with a genetic algorithm (GA) optimizer. The optimizer converges to conformations with highly enhanced properties. The GA optimizer is used to improve the mechanical properties to have the soft elements in the area adjacent to the tip of the crack.

Several applications adapt the smart technologies to the existing versions to make the application more comfortable to its consumers, in which the technologies such as Internet of Things (IoT), Artificial Intelligence and so on. The adaptation of such technologies provides a huge support to the organizations and individuals to attain the commercial and non-commercial needs in good manner. The logic of Internet of Things provides a great support to automate the organizations, industries and even a residential buildings in proper way using such powerful technology advancements as well as it provides a way to the users to operate and monitor the respective place in global perception without any range restrictions. In this paper, the logic of Internet of Things is applied to the industrial automation needs and attain the benefits from that in correct manner. This is done with the abilities of Artificial Intelligence as well and the proposed logic is named as Artificial Intelligence Assisted Network Paradigm (AIANP). The proposed AIANP provides a huge support to automation industry to control and monitor the industrial environment without any security lackings and delay by means of associating the AI logic in its approach. This is achieved by means of associating the internet enabled services to the industry to operate the machineries accordingly. In literature lots of IoT based automation approaches are available but all are strucked up with certain limitations and lackings, so that a new approach is required to resolve the issues over conventional automation technologies. This paper provides a robust industrial automation abilities to the users to control and monitor the industry in proper way using proposed Artificial Intelligence Assisted Network Paradigm. And the resulting section provides the proper proof for the proposed approach efficiency and security effectiveness in graphical manner.

This article proposes a novel miniaturization single bit MEMS phase offset (shifter) using triangular Micro-electro mechanical system (MEMS) switches. The primary goal in the design of a single-bit switched delay line digital phase offset is to reduce the area of phase offset bits and the minimize the number of switches, which aids in the reduction of mechanical switching errors during the turn ON and OFF operation. The proposed phase shifter is simply based on a switched delay route and reference route configuration, which is connected with a gold connection sequence switch. The phase offset is built on 50 Ohm coplanar waveguide (CPW) configuration, which would generally be used in radio frequency (RF) MEMS systems. The RF and mechanical characteristics of the proposed switches were analyzed using Intellisuite software, and the finite element method was carried out in the HFSS software. The performance of the S 11 (return loss) and S 21 (insertion loss) of the miniaturized single bit phase shifter (22.5°) are 23 dB and 0.55 dB, respectively. The miniaturization phase offset is reduced by 30% by using three triangular SPST switches.

The automobile instrument is the indispensable item that is essential to keep the driver conversant of the process of the engineer and the other system. There are different parameters involved in the automobile instrument, which requires a different process involved in creating the automobile parameter. This research is designed to show the simulation development of injection molding and optimization of automobile instrument parameters using different optimization techniques. In this paper, Taguchi Orthogonal parameter design and particle swarm optimization (PSO) are used to measure the shrinkage volume rate and warpage amount rate. Most of the studies are designed to calculate the reduction and warpage for the gate location and glass material. The Taguchi orthogonal design contains five different parameters which are inversely proportional to each other. Hence, by optimizing those parameters, the injection molding procedure is passed out. In this research, the paper is designed to process the injection molding for the automobile instrument parameter using optimization techniques.

In the 21st Century, each and everyone needs a strong communication pathway to establish their transactions in both commercial and non-commercial manner. Wireless Communication technologies are the gateway to provide such facilities to the users to attain their communication needs in good way. Recently, mobile communication technologies provide a global connectivity to the users to achieve their connections in global manner without any intervention. Wireless Mobile Networks (WMN) provides such facility to the users to communicate between one and another. However, security concerns are always a question in the field of Wireless Communication. There are lots of researches has already done regarding the security enhancement features over the wireless mobile network industry, but all are strucked up with certain limitations such as failed to provide a robust support on high bandwidth requirements and implementation durability. This makes a Wireless Mobile Networks down and lots of hesitations to people mind to use such technology. This paper is intended to provide a robust communication protocol with enhanced security handling nature to attain best communication between users by using such Wireless Mobile Networks. The proposed approach is called as Novel Threat Management Scheme (NTMS), in which it is derived from the combination of two different conventional algorithms such as AODV and Data Hashing algorithms. By combining these two algorithms in a proper way the proposed NTMS is designed as well as once the communication begins by using the proposed algorithm the way of attacking is prohibited at rich level and attains a good communication abilities over WMN. The proposed algorithm assures the logic of security efficiency, data integrity level, access control abilities and bandwidth utilization level in good manner as well as the mentioned things are portrayed into the resulting section of this paper with proper specification.