Purpose: The notion of using a generative artificial intelligence (AI) engine for text composition has gained excessive popularity among students, educators and researchers, following the introduction of ChatGPT. However, this has added another dimension to the daunting task of verifying originality in academic writing. Consequently, the market for detecting artificially generated content has seen a mushroom growth of tools that claim to be more than 90% accurate in sensing artificially written content.Design/methodology/approach: This research evaluates the capabilities of some highly mentioned AI detection tools to separate reality from their hyperbolic claims. For this purpose, eight AI engines have been tested on four different types of data, which cover the different ways of using ChatGPT. These types are Original, Paraphrased by AI, 100% AI generated and 100% AI generated with Contextual Information. The AI index recorded by these tools against the datasets was evaluated as an indicator of their performance.Findings: The resulting figures of cumulative mean validate that these tools excel at identifying human generated content (1.71% AI content) and perform reasonably well in labelling AI generated content (76.85% AI content). However, they are perplexed by the scenarios where the content is either paraphrased by the AI (39.42% AI content) or generated by giving a precise context for the output (60.1% AI content).Originality/value: This paper evaluates different services for the detection of AI-generated content to verify academic integrity in research work and higher education and provides new insights into their performance.

The key issue in the practical implementation of the sliding mode (SM) control–based power inverter is the variable switching frequency. This variable switching frequency not only induces electromagnetic interference (EMI) noise, but also reduces the efficiency of the inverter, as the size of the inductor and capacitor does not alter in tandem with this variable frequency. In this context, fixed switching frequency–based SM control techniques are proposed; however, some of them are too complex, while others compromise the inherent properties of SM control. In this research, a fixed frequency SM controller is proposed, which is based on the novel low-pass filter extraction of the discontinuous control signal. This allows the technique to be implemented with fewer hardware components, thus reducing the complications of implementation, while maintaining the robustness and parametric invariance of SM control. A simulation-based comparison with an existing pulse width modulated (PWM) SM controller is presented as the benchmark. In comparison with the sigmoid function SM controller, an improvement of 50% in the settling time along with zero steady-state errors and a further 37% and 42% improvement in the undershoot and overshoot, respectively, is reported in the simulation. A hardware setup is established to validate the proposed technique, which substantiates the simulation results and its disturbance rejection properties.

Fuel cells guarantee ecological ways of electricity production by promising zero emissions. Proton exchange membrane fuel cells (PEMFCs) are considered one of the safest methods, with a low operating temperature and maximum conversion efficiency. In order to harness the full potential of PEMFC, it is imperative to ensure the membrane’s safety through appropriate control strategies. However, most of the strategies focus on fuel economy along with viable fuel cell life, but they do not assure constant output voltage characteristics. A comprehensive design to regulate and boost the output voltages of PEMFC under varying load conditions is addressed with dynamic integral sliding mode control (DISMC) by combining the properties of both the dynamic and integral SMC. The proposed system outperforms in robustness against parametric uncertainties and eliminates the reaching phase along with assured stability. A hardware test rig consisting of a portable PEMFC is connected to the power converter using the proposed technique that regulates voltage for varying loads and power conditions. The results are compared with a proportional integral (PI) based system. Both simulation and hardware results are provided to validate the proposed technique. The experimental results show improvements of $35.4\%$, $34\%$ and $50\%$ in the rise time, settling time and robustness, respectively.