More papers are written about Active Anti-roll bars (AARB) in automotive and mechanical field. These systems are usually designed for vehicles to change the roll stiffness of the vehicle, thus preventing a potential roll-over. In this present paper, the use of AARB will be analysed from two different perspectives in ride and handling. First, this paper proposed the basic vehicle dynamic modeling with four DOF (degree of freedom) on half car model are described that show, why and how it is possible to control the handling and ride comfort of the car, with the external forces on the front anti-roll bar. Basically, this paper is focused on understanding the vehicle dynamic behaviour under the influence and the effects of anti-roll bar mechanism. Simulated tests are presented, that shows how the characteristics of the body roll angle and roll rate responses by using MATLAB/SIMULINK software. By simulation analysis, the design model is validity and the performance under control of PID controller is achieved. Finally, some basic conclusions are drawn about the applicability of the possible control strategies will be investigated for such system in the future.

Experts have used ultrasound imaging to manually determine follicle count and perform measurements, especially in cases of polycystic ovary syndrome (PCOS). However, due to the laborious and error-prone process of manual diagnosis, researchers have explored and developed medical image processing techniques to help with diagnosing and monitoring PCOS. This study proposes a combination of Otsu’s thresholding with the Chan–Vese method to segment and identify follicles in the ovary with reference to ultrasound images marked by a medical practitioner. Otsu’s thresholding highlights the pixel intensities of the image and creates a binary mask for use with the Chan–Vese method to define the boundary of the follicles. The acquired results were compared between the classical Chan–Vese method and the proposed method. The performances of the methods were evaluated in terms of accuracy, Dice score, Jaccard index and sensitivity. In overall segmentation evaluation, the proposed method showed superior results compared to the classical Chan–Vese method. Among the calculated evaluation metrics, the sensitivity of the proposed method was superior, with an average of 0.74 ± 0.12. Meanwhile, the average sensitivity for the classical Chan–Vese method was 0.54 ± 0.14, which is 20.03% lower than the sensitivity of the proposed method. Moreover, the proposed method showed significantly improved Dice score (p = 0.011), Jaccard index (p = 0.008) and sensitivity (p = 0.0001). This study showed that the combination of Otsu’s thresholding and the Chan–Vese method enhanced the segmentation of ultrasound images.

This paper reports the use of a numerical solution of nanofluid flow. The boundary layer flow over a stretching sheet in combination of two nanofluids models is studied. The partial differential equation that governs this model was transformed into a nonlinear ordinary differential equation by using similarity variables, and the numerical results were obtained by applying the shooting technique. Copper (Cu) nanoparticles (water-based fluid) were used in this study. This paper presents and discusses all numerical results, including those for the local Sherwood number and the local Nusselt number. Additionally, the effects of the nanoparticle volume fraction, Brownian motion Nb, and thermophoresis Nt on the performance of heat transfer are discussed. The results show that the stretching sheet has a unique solution: as the nanoparticle volume fraction φ (φ = 0), Nt (Nt = 0.1), and Nb decrease, the rate of heat transfer increases. Furthermore, as φ (φ = 0) and Nb decrease, the rate of mass transfer increases. The data of the Nusselt and Sherwood numbers were tested using different statistical distributions, and it is found that both datasets fit the Weibull distribution for different values of Nt and rotating φ.

Polycystic Ovarian Syndrome (PCOS), is a condition of the ovary consisting numerous follicles. Accurate size and number of follicles detected are crucial for treatment. Hence the diagnosis of this condition is by measuring and calculating the size and number of follicles existed in the ovary. For diagnosis, ultrasound imaging has become an effective tool as it is non-invasive, inexpensive and portable. However, the presence of speckle noise in ultrasound imaging has caused an obstruction for manual diagnosis which are high time consumption and often produce errors. Thus, image segmentation for ultrasound imaging is critical to identify follicles for PCOS diagnosis and proper health treatment. This paper presents different methods proposed and applied in automated follicle identification for PCOS diagnosis by previous researchers. In this paper, the methods and performance evaluation are identified and compared. Finally, this paper also provided suggestions in developing methods for future research.

In recent years, Active Anti-Roll Bars (AARB) have become an important research direction aimed at improving vehicle comfort and lateral stability. Previous studies have indicated that asymmetric issues can occur when using reinforcement learning (RL) algorithms for active AARB, particularly when dealing with positive and negative lateral accelerations. This study explores an AARB control strategy that utilizes a 14-degree-of-freedom (14-DOF) vehicle model and an optimal reward function within the Deep Deterministic Policy Gradient (DDPG) algorithm to ensure symmetric responses to positive and negative accelerations. The simulation employs the DDPG algorithm, focusing primarily on the effects of different reward functions on training and output performance. Through training and analysis with seven distinct reward functions, the final results indicate that the actual output of the Reward_200 function outperforms the other reward functions. The generalization of the DDPG algorithm was validated through simulations using four different sets of parameters for step steer angle tests and sine wave input steer angle tests. In this simulation, DDPG effectively reduced the vehicle roll angle by approximately between 43.73% to 82.24%, with no significant asymmetric issues observed in positive and negative lateral accelerations.

This paper presents a current invention for monitoring the athletes' heart rate during training or exercise session. A bracelet with different color code of Light Emitting Diode (LED) is designed as a wrist heart rate monitor. This color-coding makes the heart rate easier to monitor and enabling the user to know their heart rate range at a certain moment. Our works investigate the used of Zigbee and ANT+ as a transmission medium from transmitter (chest strap) to receiver (bracelet). Different colors signify different ranges of heart rate. Preliminary result demonstrated that it is very helpful for athletes and coaches to monitor the fitness level of athletes and regulate their exercise training regime in a more effective and safer manner.