Advanced Materials Research Vols. 433-440

Abstract: Hand is a highly variable organ and hand features are easily affected by environmental factors. Considering the characteristics of hand gesture, a novel hand gesture recognition algorithm based on hybrid moments is presented. First, According to the color cue, the hand shape is available to extract from the complicated background, then the contour moment invariant and Fourier Descriptor are extracted and fused into a hybrid feature, finally the hybrid feature are put into the BP network to identity. The experimental results show that the method has better robustness and higher recognition rate.

Abstract: The P2P streaming media technology is popular and promising in recent years, to ensure the correctness of the identification method, and improve the identification rate and accuracy of the network traffic, this paper proposes a identification principle and algorithm of the P2P network traffic, and gives the overall structure of the system, Finally, puts up the system test environment. The experimental results show that the identification method of the network traffic proposed in this paper can effectively improve the identification rate and accuracy of the network traffic, the scheme has the value of further research and promotion.

Abstract: This paper presents an optimized FIR filter implementation by using the method of improving coefficient precision at reasonable cost. The comparable results of traditional fix-point implementation and the optimization method show that the high-precision FIR filter design method is universal and easy to implement. Plus the employment of multi-stage pipelining and parallel structure, FIR filter performs higher operating frequency. Let’s take a 32-order lowpass FIR filter as an example, original coefficients are generated on MATLAB, and translated into optimized coefficients according to the optimization method. The functional simulations verify the effective performance, while the synthesis is carried out to analyze the utilization of resources and maximum frequency.

Abstract: RFID (radio frequency identification) chips are usually called electronic volume label or radio frequency volume label. Now a new transponder is developed and it can accurately measure the surroundings pressure, temperature and humidity. Besides, it can complete the function of sensor by combining with RFID chips, which make the transponder can monitor the change of pressure, temperature and humidity and this information can be sent to reading device through RFID chip. This paper combines this technology and fire alarm system to prevent fires. This system connects RFID chips CC2430 sensor with each temperature sensor DS18b20. DS18b20 is placed in the area needed to be monitored according to certain order, and the single way is employed to connect every CC2430 module. The temperature sensor DS18b20 and its connection with CC2430 chips hardware are very practical and simple. We combine its address line, control line, and data line into one signal line which can be controlled individually and just needs CC2430 1 root I/O lines.

Abstract: In the process of constructing decision trees, the selecting criteria of classification attributes will directly affect the classification results. Here we presented the classification contribution function (CCF), a new concept based on rough sets theory, which is regarded as the criteria for choosing attributes in the core of attributes. The basic idea of CCF is using of discernibility matrix to determine attribute core (if there is no core, using its reduction). Then through the classification contribution function to determine core classification contribution value and employ the big value as node. Next employing the selected attribute ways to divide decision-making system and each value attribute can produce a subset. The experiments show that, being compared with the entropy based C4.5 and weighted mean roughness, our method can get simpler decision tree and improve the efficiency of classification.

Abstract: Short-term traffic flow forecasting has a high requirement for the responding time and accuracy of the forecasting method because the result is directly used for instant traffic inducing. Based on the introduction of the fuzzy neural network model for short-term traffic flow forecasting together with its detailed procedures, this paper adopt the particle swarm optimization algorithm to train the fuzzy neural network. Its global searching and optimization algorithm helps to overcome the shortcomings of the traditional fuzzy neural network, such as its low efficiency and “local optimum”. A case study is also given for the PSO algorithm to train the fuzzy neural network for traffic flow forecasting. The result shows that the average square error is 0.932 when the PSO algorithm is put to use for the network training, which is 3.926 when the PSO is not used. Thus result is more accurate and it requires less time for the training procedures. It proves this method is feasible and efficient.

Abstract: Cooperative spectrum sensing under network overhead constraints is studied. To protect the primary user well, the detection probability must exceed the predefined threshold. Based on the protection of the primary user, the constraints on optimal number of cognitive users are defined by weighting the detection performance and the usage efficiency in a target function. The analysis of the target function is given under energy fusion strategy in the fusion center. The simulation results show the validity of the constraints.

Abstract: The mobile internet is now in high-speed development as well as the trend of the convergence of mobile communication and Internet, which has brought a lot of new problems and challenges at the same time, especially security problems. The mobile Internet is flooded with unauthorized access, illegal traffic, bad-information transmission, thus resulting in great damage to the people's everyday life and work. This paper will analyze the performance and causes of security problems and introduce the technology for the mobile internet.

Abstract: A sensor network has many sensor nodes with limited energy. One of the important issues in these networks is the increase of the life time of the network. In this article, a clustering algorithm is introduced for wireless sensor networks that considering the parameters of distance and remaining energy of each node in the process of cluster head selection. The introduced algorithm is able to reduce the amount of consumed energy in the network. In this algorithm, the nodes that have more energy and less distance from the base station more probably will become cluster heads. Also, we use algorithm for finding the shortest path between cluster heads and base station. The results of simulation with the help of Matlab software show that the proposed algorithm increase the life time of the network compared with LEACH algorithm.

Abstract: In this paper, we will present an energy efficient clustering scheme in order to increase the wireless sensor network’s lifetime. In the proposed method all of the nodes are able to appear as cluster heads, in other words each node decides whether to act as a cluster head and aggregate data or to route the incoming data to a neighbor better suited for this role. The main goal of the proposed method is to eliminate the extensive overhead due to selection of the cluster head and the agreement on it. One of the characteristics of the proposed method is that it does not converge to a specific cluster head, so the balances the energy consumption in clusters which will result in increment the network’s lifetime. In addition the proposed method reduces the delay in the network and also maintains the load balance in a significant manner by selecting the optimal cluster head and optimal intra-cluster and outside-cluster paths.