Earticle

When design lines in complex topography are a such as mountain areas, the selection of route schemes are usually restricted by the geological conditions because of complex terrain. According to the characters of line-selection design in complex topography areas of mountain areas, from the perspective of geological line selection, built the evaluation model of route schemes in complex geological area using the analytic hierarchy process and fuzzy optimization algorithm to solve the comprehensive evaluation problem having multilevel indices of line- selection multi-scheme from bottom to top and realized selection and decision of line schemes based on virtual geographic environments. Examples show that the established evaluation model reduced decision makers subjective influence on the results, made human-computer interaction content reduce to a minimum, and improved the accuracy and reliability of the decision.

This paper presents new mmWave-based cellular system as one of means to achieve the capacity requirement of 5G mobile communications. The base station of new system covers its service area with spot beams formed by many beamforming antennas, and one beam can be composed of multiple frequency allocation beam component carriers in which one broadband bandwidth is divided into multiple sub-bands at the millimeter frequency. The best feature of new cellular architecture is the multi-layered FA dynamic cell configuration and it means that one or more beam component carrier(s) can be grouped and then operated as one cell. The effect of this dynamic cell configuration is to avoid interference among cells via the association among multi-layered FAs and to imitate pseudo-small cells and pseudo-macro cell like 3GPP small cell enhancement architecture (user equipment in small cell enhancement architecture can use coverage layer (macro cell(s)) for mobility robustness and capacity layer (small cells) for capacity offering). In this paper, we design new system, its basic operation and evaluate its capacity to confirm the possibility as an alternative of 5G mobile communications.

According to the requirements for tower crane welding robots, precisely planning the welding trajectory is essential. The optimal model for the least-time trajectory planning for the robot is established by Bezier curve, which has the characteristic of sub-section processing. With the consideration of constraints such as joint angular velocity and acceleration, the specific operation steps of genetic algorithm (GA) optimization are presented. A weld seam trajectory example is then proposed, and the simulation of a robot’s trajectory planning is carried out. The result shows that the curve is smooth and steady, and can satisfy the requirements of tower crane welding operations. This method significantly reduces the motion time, and improves working efficiency.

This paper introduces the simple method of the mathematical modeling and simulation of current-voltage characteristics for photovoltaic panel. The aim of this modeling is to simply the nonlinear I-V model of photovoltaic panel to easily apply the model to the circuit simulators such as SPICE. So this paper is finding the parameters for the nonlinear I-V equations based on only the data such as open circuit voltage, short circuit current, voltage and current at Maximum power point and temperature coefficient for voltage and current at the nominal condition or the standard test condition which are obtained from manufacturer’s datasheet. The model in this paper is simple and has no iteration process during parameter calculation, which makes model complex and time consuming. This model can be suitable and powerful tools for circuit simulator and the modeling and simulation of the MPP tracker including solar panel.

To ensure the operation safety of landing signal officer (LSO) to pilot during carrier-based aircraft landing, the paper proposed a “LSO-pilot-aircraft” instruction associated with operation system. LSO guide mission, and design instruction associated with operation element is been analysed. The relationship and matching of “LSO-pilot-aircraft” system are exhibited by instruction associated with the operation model, and “instruction sending-operation responding-deviation correcting” process is realized based on LSO guidance instructions (original version), aircraft real-time flight states (boundary conditions) and pilot response operation (model output). Multiple loading conditions simulation results show that corrective strategies is in line with the actual situation of carrier-based aircraft landing.

In this paper we proposed a recovery and replacement algorithm mainly used to increase or strengthen the life of a sensor node when they complete the battery power. In generally wireless sensor network consists of lot of sensor nodes, hundred(s) or thousand(s) of nodes form a network to transfer the data from source node to sink node. The sensor node lose their battery power when it is used for long period of time, so it is difficult to recharge nodes of the sensor and also main in wireless sensor network is reduce the data loss, energy consumption and recovery and replace the effected nodes. So here we proposed a recovery and replacement algorithm which is a combination of genetic algorithm and grade diffusion algorithm. Here each node contains either two values those are binary values 0, 1. 1 means battery life greater than the threshold values otherwise it will be 0. This approach is better than existed algorithms, the number of faults decreases, reduces the data loss up to 98% and reduce energy consumption to 32%.

Response Surface Methodology(RSM) was successfully applied to a process simulator for optimization of Generalized Predictive Control(GPC) tuning parameters. Wireless experimental input/output data obtained from process simulator. GPC algorithm which is written in MATLAB is utilized to wireless temperature control experiments achieved by using MATLAB/Simulink program.The efficiency of the GPC is observed by calculating the integral of the square of the error (ISE) and the integral of the absolute value of the error (IAE) from experimental results which was optimized by the application of RSM. The three independent variables, which had been found the most effective variables on the GPC by screening experiments, were determined as NU, N2 and λ as minimum prediction horizon, maximum prediction horizon and control weighting, respectively. The quadratic models were developed through RSM in terms of related independent variables to describe the ISE and IAE as the two response. Based on statistic analysis, optimum GPC tuning parameters of NU (X1), N2 (X2) and λ (X3) for minimize the ISE were determined to be 1.7922, 1.9453 and 0.0642 and for minimize the IAE were determined to be 1.8880, 1.9752 and 0.0612, respectively. Calculated optimum points of GPC tuning parameters are close to based on ISE and IAE results. The data evaluated from the quadratic model were good agreement with those measured experimentally. The wireless temperature control is successfully applied to the process simulator and wireless control technique is proposed for various application areas.

Mini2440 domestic microprocessor is used as the hardware platform and DS18B20 temperature sensor driver is developed through embedded Linux systems. BOA technology, CGI technology and network communication technology is used to achieve the hardware remote control. Through analysis of the demand for system functions, to achieve an effective detection and collection on the ambient temperature. The outcome is writing a program to implement the corresponding function of temperature data collection and through network to show and feedback the data of temperature.

Data aggregation in wireless sensor network is the process of aggregating the data from multiple sensors to eliminate redundant transmissions. Data aggregation still suffers from some defects like network congestion or contention, sensor power consumption in transmission of redundant data packets due to spatio-time correlation of the neighbor sensors, and false data aggregation resulted from outlier data. To overcome these defects, we propose a data packet delivery approach from a reliable sensor to the cluster head when an event is occurred in the field of interest. We take advantage of cuckoo search (CS) algorithm as a nature-inspired metaheuristic algorithm to implement Single Node Selection (SNS) scenario for data packet delivery and we show the influence of data delivery mechanism of this scenario on the life time of the network. In Single Node Selection (SNS), cuckoo search optimization is used to find the sensor that is relatively close to the event to send a data packet holding the sensed raw data (without any modification) to the cluster head. Optimum data delivery route involves a single sensor that is relatively close to the event to send the recorded data. A comparison is made with respect to LEACH, E-LEACH protocols that show a superior advance of our approach over LEACH and E-LEACH protocols in energy consumption, network lifetime, and network throughput.