Abstract Seamless communication within and between cities allows for a tremendous increase in efficiencies, one of which is the way work can be done. When work no longer needs to be carried out only within the confines of the traditional office, it can then be done virtually and this research seeks to explore how communication influences the creation of smart economy through virtual work.... Seamless communication within and between cities allows for a tremendous increase in efficiencies, one of which is the way work can be done. When work no longer needs to be carried out only within the confines of the traditional office, it can then be done virtually and this research seeks to explore how communication influences the creation of smart economy through virtual work. This research therefore builds on prior smart cities and virtual work research to establish a framework for evaluating and explaining the relationship between smart communication and smart economy and established the link between connectivity/ communication to mobility, and further shows how the increase in connectivity increase virtual work which in turn leads to a smarter economy. The clear relationships established between virtual work and smart mobility and its mediating effect on the development of smart economy is very valuable for academic and practice. Read More Read Less

Abstract The purpose of this work is to contribute to the extended use of hybrid models to solve MRP issues dealing with stochastic demand over main stock-keeping units. The methodology development first apply SARIMA (Seasonal Autoregressive Integrated Moving Average Model), Long short term memory networks and Fb-prophet as forecasting methods to predict the demand for the master production schedule, next applies an integer programming... The purpose of this work is to contribute to the extended use of hybrid models to solve MRP issues dealing with stochastic demand over main stock-keeping units. The methodology development first apply SARIMA (Seasonal Autoregressive Integrated Moving Average Model), Long short term memory networks and Fb-prophet as forecasting methods to predict the demand for the master production schedule, next applies an integer programming model with JuMP (Julia Mathematical programming) for solving the MRP using the Lot for lot approach (L4L). The main contribution of this work is to show a way to solve dynamic demand problems over the Forecasting-MIP approach. Read More Read Less

Abstract Efficient representation of packet classifiers has become a significant challenge due to the rapid growth of data stored and processed in the forwarding, or routing, tables. In our work we propose two algorithms for reducing the size of forwarding tables both in length and width by the deletion of redundant bits and unreachable rules based on FCA analysis. We consider... Efficient representation of packet classifiers has become a significant challenge due to the rapid growth of data stored and processed in the forwarding, or routing, tables. In our work we propose two algorithms for reducing the size of forwarding tables both in length and width by the deletion of redundant bits and unreachable rules based on FCA analysis. We consider the task of transferring the forwarding packet to the correct destination as the task of multinomial classification. Thus, the process of reducing the forwarding table size corresponds to feature selection procedure with slight modifications. The presented techniques are based on closed descriptions and decision trees. The main challenge in applying decision trees to the task is processing the overlapping rules. To overcome this challenge we propose to employ concept- based hypotheses to delete unreachable actions assigned to the overlapping rules. The experiments were performed on data generated by the ClassBench software. The proposed approach results in significant decrease in bits in the forwarding tables as features. Read More Read Less