Wireless sensor network as a distribute database

Wireless sensor networks (WSN) have played a role in various fields. In-network data processing is one of the most important and challenging techniques as it affects the key features of WSNs, which are energy consumption, nodes life circles and network performance. In the form of in-network processing, an intermediate node or aggregator will fuse or aggregate sensor data, which are collected from a group of sensors before transferring to the base station. The advantage of this approach is to minimize the amount of information transferred due to lack of computational resources. This thesis introduces the development of a hybrid in-network data processing for WSNs to fulfil the WSNs constraints. An architecture for in-network data processing were proposed in clustering level, data compression level and data mining level. The Neighbour-aware Multipath Cluster Aggregation (NMCA) is designed in the clustering level, which combines cluster-based and multipath approaches to process different packet loss rates. The data compression schemes and Optimal Dynamic Huffman (ODH) algorithm compressed data in the cluster head for the compressed level. A semantic data mining for fire detection was designed for extracting information from the raw data by the semantic data-mining model is developed to improve data accuracy and extract the fire event in the simulation. A demo in-door location system with in-network data processing approach is built to test the performance of the energy reduction of our designed strategy. In conclusion, the added benefits that the technical work can provide for in-network data processing is discussed and specific contributions and future work are highlighted

Atomistic pseudopotential calculations of the optical properties of InAs/InP self-assembled quantum dots

We present a comprehensive study of the optical properties of InAs/InP self-assembled quantum dots (QDs) using an empirical pseudopotential method and configuration interaction treatment of the many-particle effects. The results are compared to those of InAs/GaAs QDs. The main results are: (i) The alignment of emission lines of neutral exciton, charged exciton and biexciton in InAs/InP QDs is quite different from that in InAs/GaAs QDs. (ii) The hidden correlation in InAs/InP QDs is 0.7 - 0.9 meV, smaller than that in InAs/GaAs QDs. (iii) The radiative lifetimes of neutral exciton, charged exciton and biexciton in InAs/InP QDs are about twice longer than those in InAs/GaAs QDs. (v) The phase diagrams of few electrons and holes in InAs/InP QDs differ greatly from those in InAs/GaAs QDs. The filling orders of electrons and holes are shown to obey the Hund's rule and Aufbau principle, and therefore the photoluminescence spectra of highly charged excitons are very different from those of InAs/GaAs QDs.Comment: 10 pages, 11 figure

SAFA : a semi-asynchronous protocol for fast federated learning with low overhead

Federated learning (FL) has attracted increasing attention as a promising approach to driving a vast number of end devices with artificial intelligence. However, it is very challenging to guarantee the efficiency of FL considering the unreliable nature of end devices while the cost of device-server communication cannot be neglected. In this paper, we propose SAFA, a semi-asynchronous FL protocol, to address the problems in federated learning such as low round efficiency and poor convergence rate in extreme conditions (e.g., clients dropping offline frequently). We introduce novel designs in the steps of model distribution, client selection and global aggregation to mitigate the impacts of stragglers, crashes and model staleness in order to boost efficiency and improve the quality of the global model. We have conducted extensive experiments with typical machine learning tasks. The results demonstrate that the proposed protocol is effective in terms of shortening federated round duration, reducing local resource wastage, and improving the accuracy of the global model at an acceptable communication cost

Terahertz scale microbunching instability driven by nonevaporable getter coating resistive-wall impedance

Non-evaporable getter (NEG) coating is widely required in the next generation of light sources and circular $e^+e^-$ colliders for small vacuum pipes to improve the vacuum level, which, however, also enhances the high-frequency resistive-wall impedance and often generates a resonator-like peak in the terahertz frequency region. In this paper, we will use the parameters of the planned Hefei Advanced Light Facility (HALF) storage ring to study the impact of NEG coating resistive-wall impedance on the longitudinal microwave instability via particle tracking simulation. Using different NEG coating parameters (resistivity and thickness) as examples, we find that the impedance with a narrow and strong peak in the high frequency region can cause micro-bunching instability, which has a low instability threshold current and contributes to a large energy spread widening above the threshold. In order to obtain a convergent simulation of the beam dynamics, one must properly resolve such a peak. The coating with a lower resistivity has a much less sharp peak in its impedance spectrum, which is helpful to suppress the micro-bunching instability and in return contributes to a weaker microwave instability

Numerical analysis of aerodynamic features of porosity-optimized wind barriers and running safety of train

A 2-D model-bridge with different porosity barriers is simulated with CFD to explore the windbreak mechanism. The accuracy of simulation is verified by a wind tunnel test. The porosity of the barriers is optimized by analyzing the aerodynamic features of the train-bridge system subjected to cross winds. It is found that wind velocity on the windward track changes greater than that on the leeward track. The train rolls towards the barrier when porosity is lower than 10 % and away from barrier when porosity is higher than 30 %, and the rolling moment is minimized when porosity is 30 %. The dynamic response of running train with and without wind barrier is compared, from which the windbreak effect of barrier is identified

PREDICTION PROGRAMMING OF THE WATER QUALITY AND ITS APPLICATION

This paper predicts the total phosphorus concentration in the water in the West Lake using a model of the convection and dispersion equation. The theory of the model is presented and predictions are made using a FORTRAN 77 program in a Dell 486 micro-computer. The results of numerical simulations are also discussed. The results presented in the paper have a practicable significance in controlling the environment of the water quality.Article信州大学理学部附属諏訪臨湖実験所報告 11: 99-108(1999)departmental bulletin pape