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How to deploy commodities for sale in different shelves in a supermarket in order to obtain better benefit for merchants with considering convenience for customers is an important topic in the retail area. In this paper, we present a new method for allocating commodity shelves in supermarket based on customers' shopping paths and transactions data mining. Therein, customers' shopping paths data can be obtained by shopping cart or basket, on which RFID (Radio Frequency Identification) tags located. And shopping transaction data can be obtained from POS (Point of Sales) machine. Through integrating and mining the frequent paths data and transactions data, See-Buy Rate, which refers to an approximate probability to purchase this commodity for customers when they see this commodity, can be calculated for each commodity. Based on See-Buy Rate, we build benefit optimization model to obtain the optimal allocating solution with considering the profit, sales volume, and purchase probability of the commodity. At last, one computation example is illustrated to show how to apply this method to practice.

In order to perfect criterion of CO concentration upper limit in the design of ventilation system for road tunnel, the influence of CO on person is analyzed, and the influence is judged by the COHb concentration made in human blood. On the basis of Coburn-Forster-Kane model, the relationship between CO concentration and COHb concentration in human blood is analyzed. Then the relationship between the time the vehicles passing through the tunnel and the CO concentration upper limit is obtained. The influence of altitude, ventilation type and traffic situation on the CO concentration upper limit is also analyzed here. Forming all these results in table, comparing with the CO concentration upper limit of criterion, it's clear that the longer the time requires passing through the tunnel, the higher the value is in criterion. The result can be used to guide design of ventilation system for road tunnel.

Random forest is an excellent ensemble learning method, which is composed of multiple decision trees grown on random input samples and splitting nodes on a random subset of features. Due to its good classification and generalization ability, random forest has achieved success in various domains. However, random forest will generate many noisy trees when it learns from the data set that has high dimension with many noise features. These noisy trees will affect the classification accuracy, and even make a wrong decision for new instances. In this paper, we present a new approach to solve this problem through weighting the trees according to their classification ability, which is named Trees Weighting Random Forest (TWRF). Here, Out-Of-Bag, which is the training data subset generated by Bagging and not involved in building decision tree, is used to evaluate the tree. For simplicity, we choose the accuracy as the index that notes tree’s classification ability and set it as the tree’s weight. Experiments show that TWRF has better performance than the original random forest and other traditional methods, such as C45, Naive Bayes and so on.

On the basis of the function and significance of performance evaluation of college political instructors, and by the principle of performance evaluation, the performance evaluation index system of the college political instructors was established in three aspects, including working philosophy, daily work and academic research, and the mismatch between performance evaluation index system of the political instructors and evaluation targets, the problems between static evaluation and dynamic evaluation of the instructors, and the problems between static assessment and dynamic adjustment of index are analyzed.

This paper investigates the housing price spatial diffusion within Wuhan city by using the quarterly data over the period 2001Q1 to 2009Q1. The Cointegration Test, Granger Causality Test and Generalized Impulse Response Function were employed. The results show that spatial interactions of urban region housing price take place. In the north of Yangtze River, the housing price of "core district" Jiangan has a significant influence on the Jianghan district, and then diffuse to the external districts. In the south of Yangtze River, the housing price of "core district" Wuchang works upon the external districts Hongshan, Qingshan. From the overall perspective of the city, the housing price of Jiangan, the "core district" in the north of Yangtze River, plays an promoting role in housing price of "core district" Wuchang, the "core district" in the south of Yangtze River.

How to select and justify college students scientific and technological innovation projects fairly is faced by colleges and universities currently, this paper used fuzzy mathematical methods, under the premise of the use of AHP to determine weights and established a multi-level fuzzy comprehensive evaluation model, it gave a better solution to assessing college students' scientific and technological projects with a wide range of practical and scalable.

This article describes the current situation of college students' organizations and explains the necessity to manage the college students' organizations in a scientific way. With the introduction of knowledge management, we have put forward a general model for knowledge management of the college students' organizations in terms of the three aspects: fundamental factors, basic and supporting activities. And we also put forward the "spring model" on the basis of the transformation of the knowledge.

As M-ary Orthogonal Code Spread-Spectrum Dispreading method is based on Maximum Correlation Rule, a false dispreading result will be computed out in the situation of false alarm. Moreover, this false result will be handed down to the following units, which of course causes a waste of resources. In this essay, a dispreading method based on confidence analysis is proposed, and the simulation results show that the computed confidence degree traces the SER very well, providing the succeeding units a good reference.