A new perfect metamaterial absorber (PMA) with high fractional bandwidth (FBW) is examined and verified for solar energy harvesting. Solar cells based on perfect metamaterial give a chance to increase the efficiency of the system by intensifying the solar electromagnetic wave that incident on the device. The designed structure is mostly offered in the visible frequency range so as to exploit the solar’s energy efficiently. Parametric investigations with regard to the measurements of the design structure are fulfilled to characterize the absorber. The finite-difference time-domain (FDTD) method-based CST simulator was used to keep the pattern parameters and absorbance analysis. The metamaterial shows almost 99.96% and 99.60% perfect absorption at 523.84 THz and 674.12 THz resonance frequencies. Moreover, absorption’s FBW is studied, and 39.22% FBW is found. The results confirm that the designed PMA can attain very high absorption peak at two modes such as transverse electric (TE) and transverse magnetic (TM) mode. Other than the numerical outcomes demonstrated that the suggested configuration was also polarization angle insensitive. In addition, the change of absorbance of the structure has provided a new kind of sensor applications in these frequency ranges. Therefore, the suggested metamaterial absorber offers perfect absorption for visible frequency ranges and can be used for renewable solar energy harvesting applications.

Software defect identification (SDI) is a key part of improving the quality of software projects and lowering the risks that along with maintenance. It does identify the software defect causes that have not been reached yet to get sufficient results. On the other hand, many researchers have recently developed several models, including NN, ML, DL, advanced CNN, and LSTM, to enhance the effectiveness of defect prediction. Due to an insufficient dataset size, repeated investigations, and no longer appropriate baseline selection, the research on the CNN model was unable to produce reliable results. In addition, XAI a well-known explainability approach creates deep models in computer vision, as well as successfully handles the software defect prediction that is easy for humans to understand. To address these issues, firstly we have used SMOTE for preprocessing which was collected from the NASA repository; categorical and numerical data. Secondly, we have experimented with software defect prediction using 1D-CNN and 2D-CNN named lightweight CNN (LCNN). Subsequently, evaluation we have employed a 100-repetition holdout validation. For the cross-validation setup, we utilized the 1D-CNN model was $20\times 1$ , and for the 2D-CNN model, it was $4\times 5 \times 1$ . After that, the results of the experiment were compared and assessed in terms of accuracy, MSE, and AUC. The result shows that 2D-CNN shows 1.36% better contrast with 1D-CNN. Thirdly, we have conducted research on the identification of software defect features via LIME and SHAP in XAI stand as state-of-the-art techniques. However, we cannot use 2D-CNN because it involves more complex relationships, making it challenging to create transparent explanations. That is why we have realized that 1D-CNN will superior result to explain the root cause of software feature identifications. Finally, LIME provides accurate visualization of software defect features in contrast with SHAP, as well as it helps the stakeholders of the software industry easily find actual root causes of software defect identification.

Perfect metamaterial absorber (PMA) is an attractive optical wavelength absorber with potential solar energy and photovoltaic applications. Perfect metamaterials used as solar cells can improve efficiency by amplifying incident solar waves on the PMA. This study aims to assess a wide-band octagonal PMA for a visible wavelength spectrum. The proposed PMA consists of three layers: nickel, silicon dioxide, and nickel. Based on the simulations, polarisation-insensitive absorption transverse electric (TE) and transverse magnetic (TM) modes were achieved due to symmetry. The proposed PMA structure was subjected to computational simulation using a FIT-based CST simulator. The design structure was again confirmed using FEM-based HFSS to maintain pattern integrity and absorption analysis. The absorption rates of the absorber were estimated at 99.987% and 99.997% for 549.20 THz and 653.2 THz, respectively. The results indicated that the PMA could achieve high absorption peaks in TE and TM modes despite being insensitive to polarisation and the incident angle. Electric field and magnetic field analyses were performed to understand the absorption of the PMA for solar energy harvesting. In conclusion, the PMA possesses outstanding visible frequency absorption, making it a promising option.

A new compact octagonal shape perfect metamaterial absorber (PMA) design, numerical simulation, fabrication, and investigational verification of unit cell that is based on a simple structure are presented in this paper. The suggested structure comprised of three layers, in which interact to produce the plasmonic resonances. The finite-integration technique (FIT) based Computer Simulation Technology (CST) microwave electromagnetic simulator was utilized to examine the design parameters and conduct absorption analysis. The design structure exhibited peak absorption values as 99.64% and 99.95% at frequencies 8.08 GHz and 11.41 GHz, respectively. The absorption characteristics were analysed using the polarization angle of the structure, layer thickness, PMA with resistive load, and number of rings. An N5227A vector network analyser was used for the measurement. The measured results of the fabricated prototype were in good agreement with the simulation results. The suggested perfect absorber structure enables innumerable application aimed at X-band for applications like, defence, security, and stealth technology.