Ercan Köse

Terrestrial animals perceive a wide range of frequencies, with auditory functions varying depending on the frequency. This study examines the auditory capabilities of terrestrial animals, focusing on hearing frequency ranges, hearing thresholds (in watts/cm²), and spontaneous otoacoustic emissions (SOAEs), which provide insights into auditory processing. Anatomical differences significantly influence hearing abilities. For instance, although mice have relatively small ears, they require higher intensity levels for auditory processing. The auditory thresholds of mice correspond to their ear anatomy, necessitating greater acoustic energy for hearing compared to many other terrestrial animals. A model was developed to illustrate how SOAEs contribute to the mouse’s auditory function. In biomimicry, these findings can inspire innovative technologies by replicating auditory mechanisms. For example, the energy conversion capabilities of auditory structures can enhance acoustic sensor efficiency. A detailed modeling study can further refine this concept by focusing on a specific species and incorporating numerous parameters based on empirical data. Future research should integrate ear modeling to improve our understanding of terrestrial animal communication and facilitate biomimetic applications. Such studies will contribute to advancements in auditory science and technology, leading to improved acoustic designs inspired by natural hearing mechanisms.

Education plays a critical role in equipping individuals with the knowledge, skills, and competencies necessary for success. However, traditional educational approaches often struggle to address the diverse learning paces, styles, and needs of students. This challenge is particularly pronounced in technical fields such as engineering, where personalized and adaptive learning methods are essential. This study proposes a novel approach leveraging closed-loop control systems to enhance the attainment of course learning outcomes. The proposed method is demonstrated through a case study on Circuit Analysis, a fundamental course in Electrical and Electronics Engineering. The study quantifies and systematically implements course learning outcomes using various assessment tools, including quizzes, exams, projects, and laboratory evaluations, all integrated into a closed-loop control framework. A numerical correlation is also established between course learning outcomes and broader program outcomes. Unlike traditional systems where assessment results are isolated, the proposed method incorporates adaptive mechanisms that adjust subsequent assessments and learning interventions based on earlier performance. This closed-loop approach enables personalized tracking of students' progress, tailored learning materials, and adaptive teaching strategies that address individual strengths and weaknesses. The findings indicate that closed-loop control systems can transform educational methodologies, offering a robust framework for personalized learning and maximizing students’ potential, particularly in technical disciplines. Furthermore, this approach aligns seamlessly with quality accreditation processes, making it applicable across a wide range of courses.

As Turkey’s energy demand surges due to industrialization, population growth, and economic development, precise forecasting of electricity demand has become crucial for ensuring energy security and facilitating sustainable planning. This study undertakes an analysis of Turkey’s current energy landscape and develops long-term electricity demand forecasts utilizing a diverse array of statistical and machine learning models, including linear regression, polynomial regression, and artificial neural networks (ANNs). By incorporating economic indicators, demographic trends, and historical consumption data, this research projects Turkey’s electricity demand up to 2045. Among the various influencing factors, industrial production stands out as the most significant driver. The findings offer strategic insights into infrastructure investments, the integration of renewable energy, and policies aimed at enhancing efficiency. This research presents a data-driven, policy-oriented framework to assist decision-makers in reducing import dependence while steering Turkey towards a sustainable energy transition.

In this study, mathematical modeling design based on Sound Transmission Loss measurement results of new acoustic material samples with natural content was carried out. Using the test samples in question, transfer function of acoustic materials based on electronic filter circuit design and a transition design method for the production of new acoustic materials by utilizing the transfer function is presented. Based on the experimental results of the test samples, it is the most suitable low-pass filter structure for the proposed design. In this study, active Sallen-Key low-pass filter structure is preferred and used. Sound Transmission Losses in dB (decibels) of acoustic samples were obtained experimentally for 500, 1000, 2000 and 4000 Hz. fundamental frequencies in the literature. Based on these data, transfer function simulation suppression gain results were obtained in TINA-TI program, active filter circuit designed, and MATLAB program. When the other results were compared in the experimental results, it was seen that very close values were obtained. It has been demonstrated that the proposed method can be used effectively in the design and examination of new acoustic materials.

Objective: The aim of the study is to develop new acoustic materials and panels that high sound transmission loss (STL), low carbon emissions, high sensitivity to human health, and also do not harm the indoor air quality. These materials are currently grown in Turkey and can be easily adopted in the industry. It has been comparatively analyzed that the developed materials can be alternatives to the synthetic materials on the market. Methods: In the experiment box similar to Alpha Cabin, which was designed and developed before, the STL values were obtained by conducting experiments in the frequency range 500–8000 Hz. with many natural and synthetic materials. In the study, low carbon emission natural materials with a STL of more than 30 dB were selected. Simulation: The experimentally measured samples were simulated in the acoustic module of the ANSYS program and compared with the results. Conclusion: The main purpose of choosing cones and walnut shells grown in our country is to contribute to the amount of oxygen in the atmosphere and green areas by increasing the cultivation of pine and walnut trees. In the tests of the samples, it was determined that the highest STL was 63.27 dB in the concave and egg-shaped sample, and 62.41 dB in the concave walnut shell and egg form. It is envisaged that the materials we obtained can be used in the sound insulation of machines and devices that produce 85 dB and above sound harmful to human health according to ILO and WHO standards.

In recent years, significant investments have been made for Solar Power Plants (SPP) plants in many countries. The installation costs of SPP plants are quite high. This situation increases the amortization period of investments. Lowering these costs during the installation phase will pave the way for more investments. One of the most important cost items of Solar Power Plants (SPP) is steel construction costs. In this study, it is aimed to reduce the cost by designing the best performance product by reducing the weight of C profiles, one of the steel constructions used during the installation of solar panels, with shape and topology methods. The results obtained show that shape and topological optimization can provide significant gains in terms of cost.

This work introduces an innovative approach that unites a PIDND²N² controller and the balanced arithmetic optimization algorithm (b-AOA) to enhance the stability of an automatic voltage regulator (AVR) system. The PIDND²N² controller, tailored for precision, stability, and responsiveness, mitigates the limitations of conventional methods. The b-AOA optimizer is obtained through the integration of pattern search and elite opposition-based learning strategies into the arithmetic optimization algorithm. This integration optimizes the controller parameters and the AVR system’s response, harmonizing exploration and exploitation. Extensive assessments, including evaluations on 23 classical benchmark functions, demonstrate the efficacy of the b-AOA. It consistently achieves accurate solutions, exhibits robustness in addressing a wide range of optimization problems, and stands out as a promising choice for various applications. In terms of the AVR system, comparative analyses highlight the superiority of the proposed approach in transient response characteristics, with the shortest rise and settling times and zero overshoot. Additionally, the b-AOA approach excels in frequency response, ensuring robust stability and a broader bandwidth. Furthermore, the proposed approach is compared with various state-of-the-art control methods for the AVR system, showcasing an impressive performance. These results underscore the significance of this work, setting a new benchmark for AVR control by advancing stability, responsiveness, and reliability in power systems.

This work introduces an innovative approach that unites a PIDND2N2 controller and the balanced arithmetic optimization algorithm (b-AOA) to enhance the stability of an automatic voltage regulator (AVR) system. The PIDND2N2 controller, tailored for precision, stability, and responsiveness, mitigates the limitations of conventional methods. The b-AOA optimizer is obtained through integration of pattern search and elite opposition-based learning strategies into the arithmetic optimization algorithm. This integration optimizes the controller parameters and the AVR system's response, harmonizing exploration and exploitation. Extensive assessments, including evaluations on 23 classical benchmark functions, demonstrate the efficacy of the b-AOA. It consistently achieves accurate solutions, exhibits robustness in addressing a wide range of optimization problems, and stands out as a promising choice for various applications. In terms of AVR system, comparative analyses highlight the superiority of the proposed approach in transient response characteristics, with the shortest rise and settling times and zero overshoot. Additionally, the b-AOA approach excels in frequency response, ensuring robust stability and a broader bandwidth. Furthermore, the proposed approach is compared with various state-of-the-art control methods for the AVR system, showcasing impressive performance. These important results underscore the significance of this work, setting a new benchmark for AVR control by advancing stability, responsiveness, and reliability in power systems.

Experimental criteria for sound insulation material recommendation and design have an important share in indoor acoustic control. Among these criteria, laboratories with devices such as impedance tubes, alpha cabins and reverberation rooms used to measure and analyze parameters such as sound transmission loss and sound absorption coefficient have been investigated. In literature, it has been observed that there are studies on acoustic materials and the tests applied to these materials, but the application is more limited. According to research data, an Alpha Cabin model system design that can be used to develop new types of acoustic sound materials has been proposed. In addition to the fact that a large number of experimental measurements can be performed at lower costs using the designed Alpha Cabin model system, many tests can be performed easily for different material designs in a very short time. To perform these tests, the Alpha Cabin system has been designed based on noise and sound insulation. For example, floating flooring, ribbed connection, and so on. Afterward, different insulation materials were used for insulation purposes and standards were achieved. The Alpha Cabin test system, which was designed and developed, overlaps the experimental and theoretical data for 500, 2000, and 4000 Hz when compared with the values of 29.1 dB for 500 Hz, 38.6 dB for 2000 Hz, and 49 dB for 4000 Hz measured in the Acoustic Facade Panel Test Room, and it has been observed that it can be used in the development of new sound insulation materials.