Design and Develop a Non-Invasive Pulmonary Vibration Device for Secretion Drainage in Pediatric Patients with Pneumonia

The study aimed to develop a non-invasive pulmonary vibration device, specifically tailored for pediatric patients, to address a range of pulmonary conditions. The device employs a PID control system to ensure consistent and precise vibrations. The primary contribution of this research is the successful development, testing, and implementation of this innovative device. Utilizing technical components such as an Arduino, a vibration DC motor, and an ADXL335 accelerometer, the device was engineered to deliver stable and continuous vibrations even when subjected to external pressures or interactions with the patient. Controllers, including P, PI, PD, and PID types, were rigorously compared. The Ziegler-Nichols tuning technique was applied for meticulous evaluation of vibration control specifically within the context of this non-invasive pulmonary vibration device. Our findings revealed that the PID controller displayed superior accuracy in vibration control compared to P, PI, and PD controllers. Clinical trials involving pediatric patients showed that the PID-controlled device achieved treatment outcomes comparable to conventional methods. The device's precise control of vibration strength provides an added benefit, making it a well-tolerated, non-invasive treatment option for various pulmonary conditions in pediatric patients. Future research is necessary to assess the long-term effectiveness of the device and to facilitate its integration into standard clinical practice. In summary, this study represents a significant advancement in pediatric pulmonary care, demonstrating the critical role that PID control systems adapted for non-invasive pulmonary vibration devices can play in enhancing treatment precision and outcomes

Comparative Study of Takagi-Sugeno-Kang and Madani Algorithms in Type-1 and Interval Type-2 Fuzzy Control for Self-Balancing Wheelchairs

This study examines the effectiveness of four different fuzzy logic controllers in self-balancing wheelchairs. The controllers under consideration are Type-1 Takagi-Sugeno-Kang (TSK) FLC, Interval Type-2 TSK FLC, Type-1 Mamdani FLC, and Interval Type-2 Mamdani FLC. A MATLAB-based simulation environment serves for the evaluation, focusing on key performance indicators like percentage overshoot, rise time, settling time, and displacement. Two testing methodologies were designed to simulate both ideal conditions and real-world hardware limitations. The simulations reveal distinct advantages for each controller type. For example, Type-1 TSK excels in minimizing overshoot but requires higher force. Interval Type-2 TSK shows the quickest settling times but needs the most force. Type-1 Mamdani has the fastest rise time with the lowest force requirement but experiences a higher percentage of overshoot. Interval Type-2 Mamdani offers balanced performance across all metrics. When a 2.7 N control input cap is imposed, Type-2 controllers prove notably more efficient in minimizing overshoot. These results offer valuable insights for future design and real-world application of self-balancing wheelchairs. Further studies are recommended for the empirical testing and refinement of these controllers, especially since the initial findings were limited to four-wheeled self-balancing robotic wheelchairs

Exploring ResNet-18 Estimation Design through Multiple Implementation Iterations and Techniques in Legacy Databases

In a rapidly evolving landscape where automated systems and database applications are increasingly crucial, there is a pressing need for precise and efficient object recognition methods. This study contributes to this burgeoning field by examining the ResNet-18 architecture, a proven deep learning model, in the context of fruit image classification. The research employs an elaborate experimental setup featuring a diverse fruit dataset that includes Rambutan, Mango, Santol, Mangosteen, and Guava. The efficacy of single versus multiple ResNet-18 models is compared, shedding light on their relative classification accuracy. A unique aspect of this study is the establishment of a 90% decision threshold, introduced to mitigate the risk of incorrect classification. Our statistical analysis reveals a significant performance advantage of multiple ResNet-18 models over single models, with an average improvement margin of 15%. This finding substantiates the study’s central hypothesis. The implemented 90% decision threshold is determined to play a pivotal role in augmenting the system’s overall accuracy by minimizing false positives. However, it’s worth noting that the increased computational complexity associated with deploying multiple models necessitates further scrutiny. In sum, this study provides a nuanced evaluation of single and multiple ResNet-18 models in the realm of fruit image classification, emphasizing their utility in practical, real-world applications. The research opens avenues for future exploration by refining these methodologies and investigating their applicability to broader object recognition tasks

Temperature Control of Heating Zone for Drying Process: Effect of Air Velocity Change

This paper proposes a temperature control technique to adjust air temperature in a heating zone for drying process. The controller design is achieved by using an internal model control (IMC) approach. When the IMC controller parameters were designed by calculating from an actual process transfer function estimated through an open-loop step response with input step change from 50% to 60% at a reference condition at air velocity of 1.20 m/s, the performance of temperature controller was experimentally tested by varying an air velocity between 1.32 m/s and 1.57 m/s, respectively. The experimental results showed that IMC controller had a high competency for controlling the drying temperature

Temperature Control of Heating Zone for Drying Process: Effect of Air Velocity Change

This paper proposes a temperature control technique to adjust air temperature in a heating zone for drying process. The controller design is achieved by using an internal model control (IMC) approach. When the IMC controller parameters were designed by calculating from an actual process transfer function estimated through an open-loop step response with input step change from 50% to 60% at a reference condition at air velocity of 1.20 m/s, the performance of temperature controller was experimentally tested by varying an air velocity between 1.32 m/s and 1.57 m/s, respectively. The experimental results showed that IMC controller had a high competency for controlling the drying temperature

Robotic Arm Design and Control Using MATLAB/Simulink

This research focuses on leveraging the capabilities of MATLAB/Simulink and Arduino microcontrollers to develop a control system for a robotic arm intended for medical and industrial applications. The arm's structural framework consists of three motors, each connected to adjustable resistors to form a comprehensive servo motor system. By integrating these hardware components with software solutions, the study aims to create a flexible, precise, and reliable automation system. The system's position and rotational control are executed through an Arduino microcontroller, which communicates with a computer running MATLAB/Simulink software. This configuration allows for real-time data processing and system adjustments. One of the study's key contributions is the utilization of Trajectory Control techniques, which govern the arm's movements through pre-defined paths, ensuring optimal efficiency and accuracy. Furthermore, the study introduces the use of a Smoothing Function to mitigate system over-shoot, thereby enhancing control precision. The research validates its methodologies through a series of tests. Results indicate that the robotic arm successfully navigates to predetermined positions with error magnitudes as low as 2.8587, 5.7340, and 4.4406 in the A, B, and C motor axes, respectively. These outcomes demonstrate the system's potential for high-precision tasks in medical and industrial settings

Advances in ethanol autothermal reforming

Fuel cell systems powered by bio-fuels such as ethanol are potential solutions to local, small scale electricity needs, especially in remote, off-grid locations. In recent years, many researchers around the world have studied the on-site autothermal reforming of ethanol to hydrogen, which can then be used in the fuel cell. However, a comprehensive review of those efforts has not been carried out. In this paper, a detailed literature review of experimental and numerical research is presented, with a focus on the catalysts, reactor design, and simulation and modelling efforts that sought to understand interactions among fluid flow, heat and mass transfer and chemical kinetics. Our review indicates that although considerable work has been carried out on the development of catalysts, relatively fewer studies report system level experiments and simulations that are necessary before these systems can be commercially deployed. Thereby, we also identify areas for further research in the area of ethanol autothtermal reforming.by Renika Baruah e.a