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In the actual control of the electronic throttle, the electronic throttle control system is affected by the return spring, friction, and gear clearance, and exhibits nonlinear characteristics and disturbance or parameter uncertainty caused by engine shake. It makes device design difficulties. In response to the above problems, a non-linear mathematical model of the electronic throttle is established, and a control algorithm based on the T-S model adaptive neural fuzzy inference system (ANFIS) is designed. The adaptive neural fuzzy inference system is used to optimize the input and output parameters. In Matlab / simulink, set up a simulation model to simulate the step signal, sinusoidal signal, disturbance and parameter perturbation. The simulation results show that the nonlinear position of the electronic throttle is the most obvious initial position (limping home position), ANFIS control strategy has better tracking effect; compared with conventional PID control, ANFIS control has better steady state, dynamic performance and anti-interference ability, and has stronger adaptability and robustness.

This paper present the industrial case study on quality improvement of the post reflow cleaning process in an assembly industry. Ceramic carrier boards are widely used in industrial fields due to their good thermal conductivity, strength and insulation. In order to reduce the terminal volume, flexible plates are also widely used. For the high quality industry application, a number of manufacturing related issues needed to be addressed. Of all Potential defects, the PCBA pollution is most critical defect which will affect the long term reliability. The ceramic board and FPC was assembly with Sn96.5Ag3Cu0.5 solder paste an orthogonal experimental design was conducted to understand the relationship among the washing temperature, washing solution and the cleanness level. From the experiment we got the optimal post-reflow process conditions for achieving highest quality cleaning status, which meet the requirements of IPC standard.

Issues related to Wireless Sensor Networks (WSNs) are inseparable part of concerns in Big Data, due to they can provide a large amount of real-time data to the processing units. A service-oriented wireless sensor network aims to manage the procedure for data-provision by considering the term "service" as a user-specified requirement. In another words, it provides a user-friendly interface for various users with a unified middleware for different types of nodes to access all services smoothly. In the low level framework, one of the major problems is how to automatically select minimum number of nodes, with high data accuracy, to access desired services in the environment. Scholars provide different solutions by magnifying some specific aspects of WSNs. Intelligent Water Drops Algorithm is a new population-based optimization approach under the inspiration of water drops following in rivers which can make optimal or near optimal paths to the lakes or seas. In this paper, IWD algorithm is improved to solve node-selection problem by considering each water drop as an agent which is responsible to find the minimum number of sensor nodes with high data accuracy. Then based on the information from all of the Intelligent Water Drops, a decision function can choose the best solution. Experimental results prove the effectiveness of our approach.

Limnoperna fortunei, the golden mussel, is a freshwater bivalve species native to the rivers and streams of China and Southeast Asia (Thailand, Korea, Laos, Cambodia, Vietnam, Indonesia), and has since become a major macrofouling pest. They also do harm to Japan, South America and other countries. They adhere to water intake facilities, resulting in major biofouling and environmental problems. Clogging of cooling water pipes has stopped raw water pumping to a water purification plant and caused the shutdown of a turbine dynamo-electric generator in a hydraulic power plant and also caused damage to all sorts of water supply systems inordinately. Substantial growth of L. fortunei is a new problem which seriously affected the water quality and water conditions in water supply system. A large number of L. fortunei not only reduced the flow area of the pipeline but also increased the pipe roughness, affecting the ability to water of the bar screen. While the respiration of L. fortunei dissolved oxygen in water, and their ammonia excretion and metabolism of nutrients caused deterioration of water quality.

The harm to raw water supply and treatment of Limnoperna fortunei is a new problem. It not only has influence on the ecosystem of water source and the water quality and resistance in the transmittion process, but also does harm to the facilities of water treatment. Through analysis of lots of literatures, the biological characters and damages of Limnoperna fortunei are summarized in this paper. Meanwhile, the author discusses the control technologies at home and abroad and makes suggestions on future study.

Congestion control algorithms of existing reliable multicast protocols are mainly derived from end-to-end model, which has high resource requirements and sometimes suppresses the package sending too much. Many-to-many reliable multicast requires efficient congestion control over a one-to-many model. It’s an important mechanism to use many-to-many multicast in LAN (Local Area Network) in distributed simulation. In this paper, a congestion control algorithm based on loss trend for many-to-many reliable multicast is proposed. It predicts future package loss of receivers on the analysis of historic loss and buffer variety, and then control the congestion by adjusting the sending rate in advance. This algorithm aims at the reliable multicast in LAN. The main idea of the algorithm is to lower the possibility of multicast package loss, and then the nodes can afford the cost of package recovery. It alleviates the congestion on the depression of package loss possibility by regulating the sending rate. Experiment results indicate that the algorithm can keep a high throughput of many-to-many reliable multicast with relatively real-time performance.