Hybrid artificial genetic – neural network model to predict the transmission of vibration to the head during whole-body vibration training

In this work, Artificial Neural Network (ANN) modelling has been employed to investigate the effects of various factors on the biodynamic responses to vibration represented by the transmissibility and its phase. These factors include, height, weight, Body Mass Index (BMI), age, frequency and posture. Nine subjects stood on a vibrating plate and were exposed to vertical vibration at nine frequencies in the range 17-46 Hz while adopting four different standing postures; Bent Knee posture (BK), Locked Knee posture (LK), right foot to the Front and left foot to the Back posture (FB) and One Leg posture (OL). The accelerations of the vibrating plate and the head of the subjects were measured during the exposure to vibration in order to calculate the transmissibility between the vibrating plate and the head. Genetic Algorithm (GA) was used to choose ANN’s number of hidden layers and number of neurons in each layer to obtain the best performance for predicting the transmissibility. The GA compared the root mean square errors (RMSE) between the ANN outputs and the experimental outputs, and then choose the best results that could be achieved. The number of hidden layers and number of neurons tested in GA vary from one hidden layer to four hidden layers, and from one neuron per layer to one hundred neurons per layer. Several runs have been conducted to train and validate the ANN model. The results show that double hidden layer with 13 neurons in the first layer and 12 neurons in the second layer give the best candidate. The proposed model can be integrated with whole-body vibration machines in order to choose the suitable exposure based on the user’s characteristics

Electronic commerce logistics in developing countries : the case of online grocery shopping in Jordan

Online grocery shopping is one of the Internet business applications that received much attention in the last few years. Online grocery shopping has grown at a fast scale in the developed countries, where customers and retailers have benefited from it. However, this service remains in its infancy stage in developing countries. Groceries are one of the most difficult objects to sell online mainly, because of sensory and delivery issues. Online customers still worry about product quality, and they demand optimum logistical services, convenience, reliability and timely delivery service. Therefore, retailers have to respond to these expectations by developing convenient logistical services while keeping this process cost-efficient as much as possible. The main aim of this research is to design an e-commerce logistical decision support system for grocery retailers in Jordan as a case study of applying online grocery shopping in a developing country. Grocery retailers will be exposed to this model, and will be able to determine the most suitable logistical delivery system in the future. In order to achieve this aim, the designed system incorporates a web ordering system to collect customer orders, embedded map source (Google Maps) and a database system. The collected data then exported to one of the available routing and scheduling online solutions in order to identify, analyze and statistically compare the cost efficiencies of the available delivery alternatives. Moreover, two specially designed questionnaires were distributed among a group of customers and grocery retailers in Jordan, asking about their attitudes towards online grocery shopping and its delivery service. The results from analyzing the questionnaires data statistically were also used as input parameters for the designed system evaluation process. The findings from the questionnaires data statistical analysis indicated that Jordanian customers and retailers have positive attitudes towards online grocery shopping. The results also showed that customers and retailers have serious concerns towards the delivery service in Jordan. Customers are mainly worried about the availability of a suitable delivery service, while retailers are worried about the market size for the delivery service. The findings from implementing and statistically testing the proposed model over three delivery alternatives showed that there are differences between the mean values of the delivery alternatives among their key performance indicators (cost, distance and time). The questionnaire respondents indicated that they both prefer the pickup point service after home delivery for customers and after shop pickup for retailers. Depending on the level of investments that grocery retailers would like to implement and according to the experiment results, it could be concluded that pickup point solution is the best logistical strategy for retailers to start with.EThOS - Electronic Theses Online ServiceJerash Private University, JordanGBUnited Kingdo

Transforming farming with intelligence : smart vibration monitoring and alert system

ABSTRACT: During the evolution towards digital agriculture, the pivotal role of tractor riding necessitates a focus on improving operator performance and well-being. While most research has centered around vibration analysis, tangible solutions to control elevated vibration levels remain rare. The study aims to introduce an intelligent ThingSpeak-Enabled IoT (Internet of Things) solution that provides real-time monitoring and generates prompt warning alerts for tractor operators when vibrations exceed safe thresholds. The initial phase involved the real-time measurement of WBV (whole-body vibration) and SEAT (seat effective amplitude transmissibility). Following this, the secondary phase encompassed the analysis and validation of the system in cases where WBV and SEAT exceeded the recommended limits. The experimental design comprised 135 trials by systematically varying tractor ride parameters, including average speed (m/s), average depth (m), and pulling force (kN) levels. Daily vibration exposure response ranged from 0.43 m/s² to 0.87 m/s² with a mean exposure of 0.64 m/s², surpassing the EAV (exposure action value) threshold of 0.5 m/s². The SEAT values ranged between 91.37 and 133.08 with a mean of 108.35, that indicates insufficient seat isolation capacity, i.e., < 100. Statistically, the study ascertained a significant influence of average speed and average depth WBV and SEAT responses at a 5% significance level. It underscores the potential efficacy of altering speed and depth parameters to attenuate vibration exposure levels. Further, the effectiveness of the system was tested through the automatic transmission of warning alerts via emails, text messages, and flashing red LED light on the IoT system. This critical feature provides considerable utility for tractor operators to adjust ride settings, ensuring that the ride remains within safe vibration limits. Furthermore, adopting such an advanced warning system in tractor manufacturing signifies a pioneering step towards sustainably enhancing operator well-being

Postural stability when walking: Effect of the frequency and magnitude of lateral oscillatory motion

While walking on an instrumented treadmill, 20 subjects were perturbed by lateral sinusoidal oscillations representative of those encountered in transport: frequencies in the range 0.5-2 Hz and accelerations in the range 0.1-2.0 ms-2 r.m.s., corresponding to velocities in the range 0.032-0.16 ms-1 r.m.s. Postural stability was assessed from the self-reported probability of losing balance (i.e., perceived risk of falling) and the movements of the centre of pressure beneath the feet. With the same acceleration at all frequencies, the velocities and displacements of the oscillatory perturbations were greater with the lower frequency oscillations, and these caused greater postural instability. With the same velocity at all frequencies, postural instability was almost independent of the frequency of oscillation. Movements of the centre of pressure show that subjects attempted to compensate for the perturbations by increasing their step width and increasing their step rate