IoT device technology is currently developing rapidly, for example in smart home systems that have several features including lighting, surveillance security, temperature control, water sensors, and smart electricity. IoT device consists of smart electricity integrated with human action recognition using sensor vision are developed in this work. In smart electricity system, we build some relays controlled by smartphone applications and web-based platforms. We can control the relays and monitor the voltage, current, and power used from electricity appliances that are connected to our IoT device. In human action recognition, we use a single RGB camera to capture some human poses into spatiotemporal sequences to get data for training. There are six poses for testing scenario, these poses will be clustered using kNN (k-Nearest Neighbor) method. Each human action that is recognized will be connected to an IoT device for controlling the switching mode on the relays in smart electricity system. The result in this experiment shows that the system successfully reads every single posture with quite good accuracy performance using confusion matrix.
One problem in collaborative pickup delivery problem (PDP) was excessive outsourced jobs. It happened in many studies on the collaborative PDP. Besides, the revenue sharing in it was unclear although important. This work aimed to propose a novel collaborative PDP model which minimizes total travel distance while maintains low outsourced jobs. It proposed several contributions. First, it prioritized internal jobs first rather than full collaborative model. Second, it proposed new revenue sharing model. It adopted cluster-first route-second and mixed pickup and delivery. It was developed by combining the genetic algorithm and nearest distance algorithm where the genetic algorithm was used in the clustering process and the nearest distance was used in the routing process. The simulation result shows that the proposed model was better than the comparing models: (1) combined K-means and genetic algorithm model (KMGA) and (2) combined simulated annealing and last-in first-out (SNLIFO) model. When the number of orders was high (300 units), the total travel distance of the proposed model was 37 percent lower than the KMGA model and 30 percent lower than the SNLIFO model. In average, the outsourcing rate of the proposed model was 70 percent lower than the previous models.
Dengue fever is emerging tropical and subtropical disease caused by dengue virus infection. The vaccination should be done as a prevention of epidemic in population. The host-vector model are modified with consider a vaccination factor to prevent the occurrence of epidemic dengue in a population. An optimal vaccination strategy using non-linear objective function was proposed. The genetic algorithm programming techniques are combined with fourthorder Runge-Kutta method to construct the optimal vaccination. In this paper, the appropriate vaccination strategy by using the optimal minimum cost function which can reduce the number of epidemic was analyzed. The numerical simulation for some specific cases of vaccination strategy is shown
Dengue Hemorrhagic Fever (DHF) is a disease caused by Dengue virus infection. The main characteristic of the DHF is plasma leakage that leading to death. By modifying of the Navier Stokes equation, a mathematical model for blood flow conditions at the onset of plasma leakage are built. In this paper, three models of blood condition are reviewed by considering pressure variation i.e. blood flow with a constant pressure, blood flow with pressure pulsatile blood flow, and blood flow with systolic-diastolic pressure. The results indicate there are a difference in blood flux between healthy person and people who suffering DHF. In addition, plasma leakage in blood flow with constant pressure is affected by vessel radius, interference function, and blood viscosity. While the plasma leakage blood flow with pulsatile pressure and systole-diastole pressure are affected by the radius of vessel, interference function, blood viscosity, heart rate and blood density.
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