In this paper, an improved gradient-based optimizer (IGBO) is proposed with the target of improving the performance and accuracy of the algorithm for solving complex optimization and engineering problems. The proposed IGBO has the added features of adjusting the best solution by adding inertia weight, fast convergence rate with modified parameters, as well as avoiding the local optima using a novel functional operator (G). These features make it feasible for solving the majority of the nonlinear optimization problems which is quite hard to achieve with the original version of GBO. The effectiveness and scalability of IGBO are evaluated using well-known benchmark functions. Moreover, the performance of the proposed algorithm is statistically analyzed using ANOVA analysis, and Holm–Bonferroni test. In addition, IGBO was assessed by solving well-known real-world problems. The results of benchmark functions show that the IGBO is very competitive, and superior compared to its competitors in finding the optimal solutions with high convergence and coverage. The results of the studied real optimization problems prove the superiority of the proposed algorithm in solving real optimization problems with difficult and indefinite search domains.

There are many studies that focus on extracting harmonics from both DC and AC sides of grid-interfaced photovoltaic (PV) systems. Based on these studies, the paper introduces an efficient method depending on hybrid DC voltage, and an active and reactive power (DC-V PQ) control scheme in a single-stage three-phase grid-interfaced PV system. The proposed scheme is designed to regulate DC voltage to minimize power loss and energy share between the network reconfiguration and the utility grid. Moreover, the technique is more effective at dealing with uncertainty and has higher reliability under various operating scenarios. These operations are the insertion of linear load 1, nonlinear load, and linear load 2. Moreover, a novel objective function (OF) is developed to improve the dynamic response of the system. OF is coupled with a particle swarm optimization (PSO) algorithm and a gradient optimization (GBO) algorithm. The analysis and the comparative study prove the superiority of GBO with counterfeits algorithm.

The rapid growth of Consumer Internet of Things (CIoT) devices has significantly increased real-time multimedia data exchange, heightening vulnerability to attacks targeting audio, video, and image content. This paper introduces Multimedia Anomaly and Integrity Detection using Knowledge Distillation (MAID-KD), a lightweight multi-task framework that performs anomaly detection and integrity verification in CIoT environments. MAID-KD leverages a Transformer-based teacher model to extract rich spatio-temporal features from multimedia streams, while a compact CNN-LSTM student model optimized for edge deployment is trained through feature alignment, soft-target distillation, and variational projection. Experimental results demonstrate that MAID-KD achieves superior accuracy and F1-score compared to state-of-the-art baselines, while reducing model size and inference latency by over 60%. These results highlight MAID-KD’s ability to deliver scalable, privacy-preserving, and multimedia-aware security for CIoT devices such as smart surveillance systems, health-monitoring wearables, and connected home platforms.

In recent years, there is growth in acceptance to consume fewer fossil fuels globally and the manufacturing of electric vehicles (EVs) has become more popular. However, the increase in the number of systems connected to the grid that contain EVs with a huge power capacity leads to unstable working in the power system. To assess the stability of the electric charging station several control approaches in AC part and DC parts during charging mode and discharging modes are tested. African vulture optimization algorithm (AVOA) has been utilized to tune the system controllers (proportional integral derivative (PID)/tilt integral derivative (TID) controllers). The superiority of AVOA is confirmed by comparing the performance with the genetic algorithm (GA). Two objective functions have been used i.e. integral time absolute error (ITAE) and integral square time error (ISTE). AVOA-tuned TID controllers using ISTE were found to be the best to contain the frequency deviations. The results have shown of the AC part and DC part is within an acceptable limit recommended by IEEE standard. Further, maximum peak overshoot, undershoot, and settle time obtained by AVOA-tuned PID and TID controllers are found the best. Finally, the improvement of the performance index obtained by AVOA over its counterpart GA is confirmed.

In this paper, a compact design and new structure of bowtie antenna with dual-band characteristics for the 5G and public safety bands in intelligent transport systems (ITS) is presented. The antenna consists of a double-sided bowtie radiating patch with partial ground plane. A triangular complementary split-ring resonator (TCSRR) metamaterial (MTM) structure was etched on the radiating patch, to develop a dual band and a single notch band between 3.85 and 4.65 GHz. The proposed antenna had an overall size of 36 × 36 mm² and was fabricated using a FR4 substrate with a thickness and dielectric permittivity (ε_r) of 1.6 mm and 4.3, respectively. CST microwave studio software was used for the design of antenna. The measured frequency results show impedance bandwidths of 3.45–3.85 GHz and 4.65–5.4 GHz, for a voltage standing wave ratio (VSWR) less than 2. The proposed antenna operates at 3.5 GHz and 4.9 GHz, providing bandwidths of 400 MHz and 750 MHz, respectively, which cover the 5G and public safety bands. A prototype was fabricated and measured based upon optimal parameters, and the experimental results showed consistency with the simulation results. The proposed antenna provided a simulated/measured gain of 5.64 dBi/5 dBi and 4 dBi/3.7 dBi at 3.5 GHz and 4.9 GHz, respectively. The enhanced bandwidth and better gain results of the proposed antenna make it an ideal candidate for an ITS operating in the 5G and public safety bands.