This study introduces the Quantum Becker Model (QBM), a novel quantum-classical hybrid framework that integrates rational choice theory with parameterized quantum neural networks. We created this model to better capture the complex, nonlinear cognitive dynamics that support corrupt decision-making in Indonesia, which conventional economic modeling approaches frequently fail to address. By representing individual choices as evolving qubit states modulated through rotation gates, the QBM naturally accounts for psychological superposition and abrupt behavioral shifts. We calibrated the model using empirical Indonesian data, including the 2024 Anti-Corruption Behavior Index (IPAK = 3.85), low detection probabilities, and sentencing records from 1,768 court decisions. Simulations revealed a near-total collapse of the cognitive state into the corrupt basis (offense probability 99.43 %) under current enforcement conditions. Analysis of the three-dimensional social loss landscape showed that increases in punishment severity yield little deterrence when the probability of apprehension remains low. Optimal policy configurations need significant improvements in detection capabilities rather than relying solely on harsher penalties. The QBM therefore provides policymakers with a robust computational tool for evaluating policy trade-offs and designing more effective, evidence-based anti-corruption strategies. Using quantum machine learning, law and economics, and computational public policy analysis, the proposed approach establishes a novel interdisciplinary connection. Its findings will contribute to quantum economics modeling theory as well as provide practical insights into designing more effective anti-corruption policies based on evidence.
A model rocket system serves as an excellent example of a mechatronic system, integrating mechanical, electrical, and control components. Computational Fluid Dynamics (CFD) plays a critical role in mechatronic system design by enabling the analysis and optimization of fluid interactions within these integrated systems. In rocket design, the accurate assessment of aerodynamic forces – thrust, weight, drag, and lift – is essential for optimizing performance. CFD analysis is employed to determine the drag coefficient (Cd) and lift coefficient (Cl), both of which contribute to improving the rocket's aerodynamic efficiency. CFD is a powerful tool for evaluating key aerodynamic parameters such as velocity, pressure, and temperature while also identifying and mitigating design flaws to enhance overall performance. This study examines the model rocket system from a mechatronic system design perspective, evaluating three different mesh structures in two- and three-dimensional CFD simulations to determine the most suitable configuration. The accuracy of the mesh depends on factors such as element size, quality metrics (skewness, orthogonal quality), and first-layer thickness. A well-refined mesh that adheres to these criteria significantly enhances the reliability of the simulation results, ensuring more precise aerodynamic analysis and performance optimization. The analysis results obtained in this study indicate that the rocket’s nose cone and the area around the wings are subjected to the highest forces, and that mechanical and structural improvements are needed in these areas.
One of the most important problems of electronic devices is heating. Especially high-performance processors and electronic cards can draw significant power and therefore reach critical temperatures. Heating can lead to functional loss or failure of devices. Sealed systems are used in many areas today. Sealing is defined as not allowing two substances, water and dust, into a closed space. The purpose of our thesis is to design a new cooling system related to the cooling of sealed electronic devices. External flow ventilation will be used as active cooling, and a heatsink structure will be used as passive cooling. Then, the efficiency of this new design will be analyzed using CFD method. By keeping the device at reasonable temperature values, a new design example will be created, especially for cooling sealed structures. Analysis studies have been conducted according to different ventilation channels. As a result of these studies, reference data on how much heat can be drawn by different fin structures will be obtained. These reference data are aimed to provide an approximate cooling capacity estimation in projects where sealing is required. The data obtained as a result of the study are compared and presented in tabular form.
To address the resonance peak issue of LCL (Inductor capacitor inductor) grid-connected inverters at the resonant frequency and reduce system losses caused by passive damping, this paper proposes a novel plug-in composite repetitive controller based on an active damping strategy utilizing a notch filter, along with detailed parameter design for the controller. Simulation results demonstrate that the notch filter-based repetitive controller maintains high gain at the fundamental frequency while exhibiting rapid gain attenuation at higher frequencies. Since the harmonic content of the inverter system is predominantly concentrated in the low-frequency range, the controller achieves excellent harmonic suppression performance within the low-frequency region. The low gain at high frequencies enhances system stability. Compared with conventional repetitive controllers, the proposed controller adopts a low-loss notch filter damping method, preserves the superior harmonic suppression capability (the grid current harmonic is reduced by 1.37 %), and improves system stability.
There is a growing interest in the area of human – robot interactions as the human – robot interactions plays an important role in the control design for the robot. The paper proposes a feedback torque control for a three degree of freedom model of an arm exoskeleton used for assisting user movement. Base on controlling the interaction torques in three joints of the robot to track the desired interaction torques, the feedback torque control is carried out to shape the impedance of the device. The optimal feedback torque control is carried out to minimize the total root mean square of human – robot interaction torques at three joints by using the Balancing Composite Motion Optimization.
