This paper focuses on an effective control technique for enhancing the Maximum Power Point Tracking (MPPT) performance of a grid-connected DFIG-based wind power plant under continuously varying wind conditions. However, rapid fluctuations in wind speeds, uncertainties in parameters, and grid disturbances are key challenges to enhancing the MPPT performance capability. Considering these struggles, this study aims to model a modified dynamic DFIG-based wind turbine system and develop a hybrid Adaptive Neuro-Fuzzy Inference System (ANFIS) with a Proportional-Integral (PI) controller on the back-to-back converter at the rotor and grid sides. The actual limited ranges of wind speed and output power generation data of the Adama II wind power plant in Ethiopia are utilized as input and output variables for the ANFIS controller. The simulation results from the latest version of R2024a-MATLAB-Simulink software show that the proposed ANFIS-PI reached an MPPT of 2.22 MW compared to the FLC-PI controller attained 2.2 MW using the benchmark as the reference value of 1.561 MW in the PI controller, by improving the maximum power coefficient of 0.5504 compared to 0.5473 using the baseline as the reference value of 0.4109, respectively, at a rated wind speed of 12.5 m/s and an optimal pitch angle of 0°.
Context and motivation: With the rapid advancement of AI technologies, there is an increasing need to understand how AI can be effectively integrated into RE processes. In recent years, several studies have explored the potential and challenges of applying GenAI to support or even automate RE-related activities. Question/problem: Despite the existing body of knowledge on AI's potential for supporting RE activities, there is limited evidence on its practical applicability and limitations from an industry perspective. Principal ideas/results: To address this gap, we conducted a survey with RE practitioners in collaboration with the IREB Special Interest Group on AI RE. In addition to describing our research methodology and survey design, we present insights from our quantitative and qualitative data analyzes. These insights include practitioners' perspectives on current usage scenarios, concerns, experiences-both positive and negative-as well as training needs related to using GenAI in requirements elicitation, analysis, specification, validation, and management. Contribution: This study provides empirical evidence on the practical use of GenAI in RE, offering insights into its benefits, challenges, and training needs. The findings inform future research and industry strategies, guiding effective AI integration and skill development for improved RE processes and results.
The authors analyze the current requirements for the professional activities of engineering and pedagogical staff, identify their needs for the continuous development of educational communication and interaction skills in the educational environment, and determine the appropriate tools that form the basis of content and technologies for teacher training in this area. The proposed technologies are aimed at providing technical and pedagogical staff with tools and mechanisms for realizing the main goal of pedagogical communication in digital learning, which is to organize joint activities of the teacher and the student to increase and interpret information, develop a common view of the subject of study. Considering this, the authors divide communication areas into oral digital communication (active participation and independent organization of online conferences, webinars, webquests, online events, streams on social networks by students) and written digital communication (participation and independent implementation of joint work in Google docs, Google presentations, etc., the Canva service, work with online boards (Twiddla, MIRO, IDroo, Groupboard, etc.), written communication through social networks and learning services). A system of educational tasks has been developed, which, due to their level of complexity and distribution in time, contribute to the gradual development of engineering and pedagogical staff’s abilities of educational communication and interaction in the educational environment, and also allow them to improve their relevant abilities in further professional pedagogical activities.
IntroductionCouples living with dementia are at risk of experiencing a deterioration in relationship quality and may seek tools or guidance to sustain couplehood through challenging times. Music therapy interventions have shown potential to enhance closeness and well-being in couples. In this study, we aimed to explore the perspectives of music therapists conducting music interventions in the Randomised Controlled Trial (RCT) HOMESIDE, on the influence of the music therapy interventions on spousal relationship quality.MethodsWe adopted a qualitative interview study design and used a hermeneutic-phenomenological framework for analysis.ResultsData consisted of five interviews with music therapists voluntarily recruited from HOMESIDE. Through the analysis steps we identified three overarching themes: (1) Balancing changing roles and shifting emotions, (2) Resource-oriented facilitation for relationship quality, and (3) Enhancing and challenging relationship quality through music experiences. The results indicate that music and music therapy interventions may enhance activity, interaction, and closeness in couples, and spark enjoyment. Furthermore, potential risk factors were identified, such as triggering grief and increasing power imbalance in the couple through the interventions.DiscussionThe findings of this study support previous studies in showing the potential of music therapy interventions to positively influence relationship quality in couples living with dementia. The potential risk factors, however, are sparsely explored in the existing literature. Further studies should apply research designs that identify and explore such complexities, to facilitate the development of safe and supportive music therapy interventions for couples living with dementia.
To achieve climate protection goals, it is essential to adopt renewable energy sources. However, specific projects and measures for the generation and distribution of electricity and thermal energy often face local opposition due to noise emissions from the facilities. Shifting energy and heat production from large, remote facilities to decentralized generation units closer to urban or within residential areas may result in noise emissions that lead to conflicts with nearby residents. Based on a literature review, this study examines potential noise impacts associated with various renewable energy sources (e.g., wind turbines, geothermal systems, heat pumps, biogas plants) during both the construction and operational phases. For instance, in the case of wind turbines, aerodynamic noise generated by the rotor blades during operation is predominant, whereas geothermal systems can cause significant noise emissions during drilling activities. Against this backdrop, the paper identifies technical and planning measures (e.g., sound insulation, optimized facility placement) that can mitigate noise development. The findings of this study demonstrate that climate protection objectives and high standards for noise control can be achieved together. This requires adherence to established and well-known principles of noise protection in the design, planning, and construction of renewable energy facilities.
