Potential of impact-based weight sensing of individual Chinese cabbage for real-time yield monitoring

Yield monitoring is one of the basic components of precision agriculture. It provides information on the spatial variability of yield in the field. The objective of this study was to estimate the weight of Chinese cabbage through impact force measurements using a weighing sensor. The sensor was installed to receive the impact of Cabbage as it dropped off an inclined conveyor. The investigated experimental variables were fall height, plate angle to the horizontal, and conveyor speed. The load cell was calibrated, with an R2 value of 0.96. The mean absolute percentage error (MAPE), root-mean-square error (RMSE), and correlation coefficient (R2) were the statistical indicators used to describe the accuracy of the estimates. The fall height had little effect on the precision of the yield sensor. The least sensing precision was 18.75%, observed at an angle of 30° with a conveyor speed of 0.05ms-1. The MAPE for cabbage weights were<3% at 40° and 0.2 ms−1 for both fall heights. The experiments showed the potential of measuring individual cabbage weights for yield estimation.

Axle Configuration and Weight Sensing for Moving Vehicles on Bridges Based on the Clustering and Gradient Method

Traffic information, including vehicle weight and axle spacing, is vital for bridge safety. The bridge weigh-in-motion (BWIM) system remotely estimates the axle weights of moving vehicles using the response measured from instrumented bridges. It has been proved more accurate and durable than the traditional pavement-based method. However, the main drawback of conventional BWIM algorithms is that they can only identify the axle weight and the information of axle configuration (the number of axles and axle spacing) is required to be determined using an extra device in advance of the weight identification procedure. Namely, dedicated sensors (pressure-sensitive sensors placed on the deck surface or under the soffit of a bridge) in addition to weighing sensors must be adopted for identifying the axle configuration, which significantly decreases the utility, feasibility, and economic efficiency of BWIM technology. In this study, a new iterative procedure simultaneously identifying axle spacing as well as axle weights and gross weights of vehicles is proposed. The novel method is based on k-means clustering and the gradient descent method. In this method, both the axle weight and the axle location are obtained by using the same global response of bridges; thus the axle detectors are no longer required, which makes it economical and easier to be implemented. Furthermore, the proposed optimization method has good computational efficiency and thus is practical for real-time application. Comprehensive numerical simulations and laboratory experiments based on scaled vehicle and bridge models were conducted to verify the proposed method. The identification results show that the proposed method has good accuracy and high computational efficiency in axle spacing and axle weight identification.

Multilayered Composites with Modulus Gradient for Enhanced Pressure—Temperature Sensing Performance

Highly sensitive and flexible composite sensors with pressure and temperature sensing abilities are of great importance in human motion monitoring, robotic skins, and automobile seats when checking the boarding status. Several studies have been conducted to improve the temperature-pressure sensitivity; however, they require a complex fabrication process for micro-nanostructures, which are material-dependent. Therefore, there is a need to develop the structural designs to improve the sensing abilities. Herein, we demonstrate a flexible composite with an enhanced pressure and temperature sensing performance. Its structural design consists of a multilayered composite construction with an elastic modulus gradient. Controlled stress concentration and distribution induced by a micropatterned structure between the layers improves its pressure and temperature sensing performance. The proposed composite sensor can monitor a wide range of pressure and temperature stimuli and also has potential applications as an automotive seat sensor for simultaneous human temperature detection and occupant weight sensing.

A body weight sensor regulates pre-pubertal growth via the somatotropic axis in male rats

In healthy conditions, prepubertal growth follows an individual specific growth channel. Growth hormone (GH) is undoubtedly the major regulator of growth. However, the homeostatic regulation to maintain the individual specific growth channel during growth is unclear. We recently hypothesized a body weight sensing homeostatic regulation of body weight during adulthood, the gravitostat. We now investigated if sensing of body weight also contributes to the strict homeostatic regulation to maintain the individual specific growth channel during prepubertal growth. To evaluate the effect of increased artificial loading on prepubertal growth, we implanted heavy (20% of body weight) or light (2% of the body weight) capsules into the abdomen of 26-day old male rats. The body growth, as determined by change in biological body weight and growth of the long bones and the axial skeleton, was reduced in rats bearing a heavy load compared to light load. Removal of the increased load resulted in a catch-up growth and a normalization of body weight. Loading decreased hypothalamic growth hormone releasing hormone mRNA, liver IGF-1 mRNA and serum IGF-1, suggesting that the reduced body growth was caused by a negative feed-back regulation on the somatotropic-axis and this notion was supported by the fact that increased loading did not reduce body growth in GH-treated rats. Based on these data, we propose the gravitostat hypothesis for the regulation of prepubertal growth. This states that there is a homeostatic regulation to maintain the individual specific growth channel via body weight sensing, regulating the somatotropic axis and explaining catch-up growth.

Revisiting the critical weight hypothesis for regulation of pubertal timing in boys

ABSTRACT Background Recent findings indicate that there is a body weight–sensing homeostatic regulation of body weight in postpubertal rodents and humans. It is possible that body weight sensing also might be involved in the regulation of pubertal timing. Although an early small study suggested that there is a critical body weight for pubertal timing in girls, most studies have focused on BMI and reported an inverse association between BMI and pubertal timing. Objectives In the present longitudinal well-powered cohort study, we revisited the critical weight hypothesis and tested if prepubertal body weight is a more robust inverse predictor of pubertal timing than prepubertal BMI in boys. Method We included men born during 1945–1961 (old cohort; n = 31,971) and men born during 1981–1996 (recent cohort; n = 1465) in the large BMI Epidemiology Study (BEST) Gothenburg (combined BEST cohort n = 33,436). Men with information on prepubertal body weight and BMI at 8 y of age and age at peak height velocity (PHV; an objective measure of pubertal timing) were included. Results Body weight explained more of the variance in age at PHV than BMI in both the old cohort and the recent cohort (combined cohort, body weight 6.3%, BMI 3.6%). Both body weight (β: −0.24 SD/SD increase in weight; 95% CI: −0.25, −0.23) and BMI (β: −0.18 SD/SD increase in BMI, 95% CI: −0.19, −0.17) were inversely associated with age at PHV but the association for body weight was significantly more pronounced than the association for BMI (P &lt; 0.001). Conclusions In conclusion, prepubertal body weight is a more robust inverse predictor of pubertal timing than prepubertal BMI in boys. We propose that body weight sensing constitutes a feedback mechanism to regulate pubertal timing.

DESIGN AND FABRICATION OF WEIGHT SENSING SYSTEM FOR PRODUCTION LINE

Most of industries in our area are still using old techniques to measure the quality of their products. These old ways of measuring the quality are not applicable for every product and the checking is only by random samples. This method may affect the company if more products are out of production tolerance. So, this project is to design and fabricate weight sensing system that can be used in a production line in which the system can accept a specific weight to go in production line and reject others. The idea of this project comes after seeing the effects of going out of weight tolerance for some products that require quality. So, this report will screen the previous works and technologies which are related to the topic in literature review chapter to get benefits from them and avoid mistakes. No specific literature was identified with complete design of automatic weight sensing system. Personal interaction with the Reem batteries and power appliances results in the generation of the idea for designing and developing light weight sensing system. This project has faced some challenges which are: To identify a sensor that is having more sensitivity for the light weight and the method to amplify its low signal. These challenges have been solved by searching from different sources to get the best weight sensor and the suitable amplifier.