Intelligent Navigation of a Magnetic Microrobot with Model-Free Deep Reinforcement Learning in a Real-World Environment.

Microrobotics has opened new horizons for various applications, especially in medicine. However, it also witnessed challenges in achieving maximum optimal performance. One key challenge is the intelligent, autonomous, and precise navigation control of microrobots in fluid environments. The intelligence and autonomy in microrobot control, without the need for prior knowledge of the entire system, can offer significant opportunities in scenarios where their models are unavailable. In this study, two control systems based on model-free deep reinforcement learning were implemented to control the movement of a disk-shaped magnetic microrobot in a real-world environment. The training and results of an off-policy SAC algorithm and an on-policy TRPO algorithm revealed that the microrobot successfully learned the optimal path to reach random target positions. During training, the TRPO exhibited a higher sample efficiency and greater stability. The TRPO and SAC showed 100% and 97.5% success rates in reaching the targets in the evaluation phase, respectively. These findings offer basic insights into achieving intelligent and autonomous navigation control for microrobots to advance their capabilities for various applications.

Recent advances in ultrasound application as a novel technique in analysis, processing and quality control of fruits, juices and dairy products industries: A review.

Recently, ultrasound has been widely used in the researches in the food science and technology. Among the food materials, fruits, juices and dairy products are strongly sensitive to ultrasound-based techniques. In this review paper, applications of ultrasound in terms of high and low-power modes in processing, instrumentation and control of the industrial operations are studied in the fruit, juice and dairy sectors of the food science and technology by emphasizing the principles of these techniques and their physicochemical effects on the products. Also, a comprehensive analysis of these methods and important factors influencing their performance are presented, along with the advantages and the drawbacks of each ultrasound-assisted techniques. The solutions for better productivity of this technique would be presented and future trend of this technology would be outlined. By studying the latest researches and advances in the field of ultrasound applications, it has been confirmed that this technique can be helpful in accelerating processes, reducing energy requirements, increasing productivity, and producing better quality food materials in the fields of fruits, juices and dairy products. Notwithstanding, in order to solve the challenges ahead, and for potential applications of ultrasound technology, further researches need to be expanded in the areas mentioned. Also, with the advancement of technology, more advanced equipment, ultrasound transducers and instrumentations would be introduced that needs to be applied in this regard, to solve the current challenges.

Real-time color change monitoring of apple slices using image processing during intermittent microwave convective drying.

An intermittent microwave convective drying method combined with a real-time computer vision technique was employed to detect the effect of drying parameters on color properties of apple slices. The experiments were performed at air temperature of 40 to 80℃, air velocities of 1-2 m/s, microwave powers of 200-600 W, and pulse ratios (PRs) of 2-6. Drying rate and drying time varied from 0.014 to 0.000001 min-1 and 27 to 244 min, respectively. The normalized lightness values had ascending and descending parabolic trends with decrease in product moisture content. With descending dimensionless moisture content, redness, yellowness, color change, hue angle, and chroma were enlarged. The normalized redness values changed from -4 to 3. Models relating drying parameters with drying time, drying rate, and lightness were obtained and found to be significant (P < 0.01). Results indicated that microwave power and PRs had more influence on lightness and color change than other parameters.

Image analysis and green tea color change kinetics during thin-layer drying.

This study was conducted to investigate the effect of air temperature and air flow velocity on kinetics of color parameter changes during hot-air drying of green tea, to obtain the best model for hot-air drying of green tea, to apply a computer vision system and to study the color changes during drying. In the proposed computer vision system system, at first RGB values of the images were converted into XYZ values and then to Commission International d'Eclairage L*a*b* color coordinates. The obtained color parameters of L*, a* and b* were calibrated with Hunter-Lab colorimeter. These values were also used for calculation of the color difference, chroma, hue angle and browning index. The values of L* and b* decreased, while the values of a* and color difference (ΔE*ab ) increased during hot-air drying. Drying data were fitted to three kinetic models. Zero, first-order and fractional conversion models were utilized to describe the color changes of green tea. The suitability of fitness was determined using the coefficient of determination (R (2)) and root-mean-square error. Results showed that the fraction conversion model had more acceptable fitness than the other two models in most of color parameters.