BACKGROUND Compared to standing posture, sitting decreases lumbar lordosis, increases low back muscle activity, disc pressure, and pressure on the ischium, which are associated with occupational LBP. A sitting device that reduces spinal load and low back muscle activities may help increase sitting comfort and reduce LBP risk. The objective of this study is to investigate the biomechanical effec...

Virtual Backbones (VBs) are expected to bring substantial benefits to routing in Wireless Sensor Networks (WSNs). Connected Dominating Sets (CDSs) based VBs are competitive approaches among the existing methods used to establish VBs in WSNs. Most existing works focus on constructing Minimum-sized CDSs (MCDSs). However, few works consider the load-balance factor. In this work, the size and the l...

Providing accurate load forecast to electric utility corporations is essential in order to reduce their operational costs and increase profits. Hence, training set selection is an important preprocessing step which has to be considered in practice in order to increase the accuracy of load forecasts. The usage of mutual information (MI) has been recently proposed in regression tasks, mostly for ...

This paper aims to assess the application of Support Vector Machine (SVM) regression in order to analysis flexible pavements. To this end, 10000 Four-layer flexible pavement sections consisted of asphalt concrete layer, granular base layer, granular subbase layer, and subgrade soil were analyzed under the effect of standard axle loading using multi-layered elastic theory and pavement critical r...

While many researchers believe that multimedia applications are best managed with hard, real-time scheduling mechanisms, models based on application-level adaptation with relaxed scheduling constraints are gaining acceptance. We analyze an existing video conferencing application that was designed without explicit support for CPU resource management , and propose modifications to its architectur...

Kernel-based methods, such as support vector regression (SVR), have demonstrated satisfactory performance in short-term load forecasting (STLF) application. However, the good performance of kernel-based method depends on the selection of an appropriate kernel function that fits the learning target, unsuitable kernel function or hyper-parameters setting may lead to significantly poor performance...