Advanced Materials Research Vols. 989-994

Abstract: This study focused on estimating chlorophyll concentration of rice using PROSPECT and support vector machine. The study site is located in West Lake sewage irrigation area of Changchun, Jiliin Province. Reflectance spectrual of rice were measured by ASD3 spectrometer, chlorophyll contents of rice were recorded with a portable chlorophyll meter SPAD-502. Support vector machines and PROSPECT model were adopted to construct hyperspectral models for predicting chlorophyll content. The results indicate that: the hyperspectral prediction model of rice chlorophyll content yields a maximum correlation coefficient of 0.8563, and achieves a smallest RMSE of 9.5106; and the prediction accuracy based on the first derivative spectrum is higher than on the original spectrum. Research of this paper provides a theoretical basis for large scale dynamic prediction of rice chlorophyll content in sewage irrigated area.

Abstract: The recommendation system based on collaborative filtering is one of the most popular recommendation mechanisms. However, with the continuous expansion of the system, several problems that traditional collaborative filtering recommendation algorithm (CF) faced such as cold startup, accuracy, and scalability are worsen. In order to address these issues, a distributed collaborative filtering recommendation model based on expand-vector (CF-EV) is proposed. Firstly, the eigenvector is expanded reasonably to get the expand-vector based on the expand-vector model, a new extension measure created in this paper. Then, the nearest neighbor user is found and a more accurate recommendation to the target user is given based on the calculation results. In addition, the further optimization makes it applied to the parallel computing framework successfully. Using the MovieLens dataset, the performance of CF-EV is compared with CF from both sides of recommendation precision and the speedup ratio. Through experimental results, CF-EV overcomes the problem of cold startup. Moreover, the accuracy and recall ratio has been doubled. With the increasing numbers of the computing nodes, the distributed implementation has linear speedup.

Abstract: This paper introduces PSO algorithm into ant colony optimization algorithm so that an improved ant colony optimization algorithm named ACA-PSO is proposed. The ACA-PSO algorithm can get more effective optimal solutions by using PSO algorithm to do crossover operation and mutation operation so as to avoid trapping in local optimum. Finally, the simulation experiment reflects that the ACA-PSO algorithm speeds the convergence up which is more suitable for resource scheduling in cloud computing.

Abstract: In this paper an improved chaos ant colony algorithm based on return optimization strategy, elite strategy and intersection removal strategy is proposed. The improved algorithm uses orthogonal method to cluster the target points, then adopt chaos technology to optimize initial solution of the ant colony to improve individual quality and chaos perturbation is utilized to avoid the search being trapped into local optimum solutions. The simulation results show that the improved algorithm has higher efficiency in finding optimal path and it is a novel method to solve traveling salesmen problem.

Abstract: In this paper,the authors briefly describe the development of cloud storage and give an improved cloud storage model. This paper proposes a scheduling algorithm based on Priority (SAP). According to the priority of data block ,the algorithm schedules on mastering the supply and demand of data block comprehensively and accurately, and solves the system's launch delay and the continuity of streaming media player.

Abstract: To solve the crosstalk noise question in deep-submicron technologies, a new spatial correlation model based on the distributed RC-π model is proposed in this paper. Quiet aggressor net and tree branch reduction techniques are introduced to the distributed RC-π model, and a new spatial correlation model of both Gaussian and non-Gaussian process variations among segments is created. Experimental results show that our method maintains the efficiency of past approaches, and significantly improves on their accuracy.

Abstract: The minimum lethal dose of the children and adults taking aminophylline tablets and severe poisoning is discussed in the paper. Linear differential equations and function image are both introduced to analysis timely rescue methods of the human during poisoning. Meanwhile, modeling is provided and the model solution is given. In the end, the simulation results showed the fatal time of the smallest dose and effective rescue when taking aminophylline poisoning.

Abstract: As for the problem of maneuvering target tracking in the clutter environment, this paper combines IMM with PHD and realizes it through approach of particle filter. This algorithm avoids the troublesome problem of data association, and takes advantage of probability hypothesis density (PHD) filter in tracking maneuvering targets and interacting multi-model (IMM) algorithm in the field of model switching effectively, in the clutter environment, the status of the targets can be estimated precisely and steadily. This paper compares the proposed filtering algorithm with the classical IMM algorithm in performance, and the simulation results show that, the improved filtering algorithm has good tracking performance and tracking accuracy.

Abstract: Professional skills are important to students who major in ideological and political education. They must be able to conduct the tasks required by the teaching of political activities. Evaluation of the student’s skills can offer a theoretical basis for measuring a ideological and political course, but an effective evaluation method is lacking. Therefore, an evaluation method based on the grey system theory is proposed in this article. First, the educational structure of the ideological and political education is discussed; second, the mathematical model of grey system theory is presented; and third, the structure of the professional skills evaluation model of students majoring in ideological and political education is presented. The evaluation index system, the results of which are drawn from a questionnaire distributed to 800 students, and the evaluation program, is put forward. A case study was carried out, the results of which show that the evaluation method outlined here can contribute to improving overall standards in the course.

Abstract: The paper presents a valid and efficient method to teach ideological and political education courses in linear regression analysis. It includes theory and practice parts, where interactive learning methodologies are created. It adopts case-study teaching, since this teaching method effectively integrates theoretical teaching and practical teaching. The lectures should be not an exhaustive review of regression methodology, but they should focus on how the regression models derived. Moreover, the teacher should pay more attention to the theoretical aspects of models rather than to their implementation using software. Students work in teams of three or four on a problem presented by teachers and choose relevant software to carry out their own projects. Feedback from students indicates that this method of teaching improves students' class attendance and greatly increases their interest in learning.