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Thresholding is the simplest but most effecttive segmentation technique for image analysis. However, the computational complexity increases exponentially with the increase of threshold number in order to seek the most appropriate threshold values. Therefore, stochastic optimization algorithm are often used to overcome excessive computational problems, but the single optimization algorithm often falls into the local optimum. In general, hybrid algorithm is able to produce better performance. As a result, a parallel coupled mode(DE_GA in brief) of differential evolution algorithm (DE) and genetic algorithm (GA) is proposed for solving multi-threshold problem and The maximum variance is used as the fitness function. The experimental result displays that compared with a single algorithm, the results of the hybrid algorithm are relatively stable, which means that the parallel coupled DE_GA algorithm combined with Otsu might be an effect and practical image segmentation method.

Image enhancement based on Beta function is a widely used method for it is able to fit multiple transformation curves, which is a significant step for image analysis. The key step for the method is to find the appropriate parameters to determine the grayscale transformation function. However, it needs a lot of time to seek applicable parameters when enumeration is used and random optimization algorithms often have failures within a limited time and are prone to fall into the local optimum. In order to solve the problems a serial coupled mode of stochastic optimization algorithms is investigated in the paper. According to the model, the differential evolution algorithm and cuckoo search algorithm are tried in image enhancement through serial coupling mode and compared with the traditional optimization algorithm. The experimental results reveals that the proposed approach is feasible and the performance is more balanced, which has a good performance on the image enhancement.

Image segmentation is the indispensable part in the field of computer vision. There are tremendous methods for handling this task such as Otsu-thresholding and Fuzzy C-means (FCM). However, the segmentation results of the images are occasionally unsatisfactory due to the presence of noise. In this paper, two kinds of spatial information consisting of the relative position information and the intensity information of the neighborhood pixels in an image are taken into consideration in constructing the objective function in FCM. Moreover, Ant Lion Optimization, one of the recently proposed optimization algorithms is utilized to optimize the relevant index. Bioinspired ALO has the robust ability to find optimal parameters in search spaces. So the proposed approach to image segmentation based on Fuzzy C-Means (FCM) and Ant Lion Optimization (ALO) may alleviate this problem to a certain degree. A series of experimental validation has been implemented for demonstrating the performance of the proposed approach in the end of the paper.

A photonic crystal fiber (PCF) sensor based on spherical-shape structure cascaded with core-offset structure is proposed and fabricated. The sensor head is composed of PCF and spherical-shape structure cascaded with core-offset structure which are made by the single mode fiber. The temperature and refractive index(RI) are measured by the sensor. Experimental results show temperature sensitivity and refractive index sensitivity are 8.13pm/°C and 188.09nm/RIU, respectively. It can be widely applied in biological and medical sensing.

In this paper, an improved AODV - PWAODV (Piggyback and Weighted neighbor stability Ad hoc On-demand Distance Vector routing) protocol with lower route cost and smaller delay is presented. In the algorithm we introduce a piggyback mechanism and weighted neighbor stability algorithm. Essentially, the route cost can be reduced greatly by the use of piggyback mechanism and the link stability algorithm decreases the delay because of ensuring the robustness of the network topology. Finally, by comparison in the simulation via NS2, our newly-mentioned protocol could acquire better route cost and delay performances.

Based on the analysis of philosophy education status in the computer undergraduate education system, this article pointed the reasons for the unsuccessful teaching, then combined the lessons in practice, discussed the significance of the knowledge re-location of philosophy for the teachers and students, thus took the teaching practice, and achieved better results finally.

In the next generation mobile network, real-time multimedia applications need better network performance, such as lower handoff delay and packet loss rate. This paper proposes a new protocol named HBSIP, which is Hierarchical Bicasing based SIP. HBSIP is an improvement to the traditional mobile SIP, and the core idea is using the bicasting mechanism and hierarchical structure. Although HBSIP brings about additional network traffic load, in return it significantly enhances the network performance, including reducing handoff delay and packet loss rate. Due to the characters and performance of HBSIP, it is very suitable for the future seamless communication.