Applied Mechanics and Materials Vols. 513-517

Abstract: With the maturity of virtualization technology, the advantages of cloud computing have been gradually apparent with low cost, improvement of resource utilization, energy conservation of service consolidation and convenience of using. Cloud manufacturing provides a huge amount of services and there are kinds of user requirements and devices which are complicated and changeable. So it is necessary that the users quickly develop personalized products to meet their needs. With the popularity of smart phones and the development of 3G technology, the amount of information grows dramatically fast, which makes it a trend to extract information that users are interested in from the world of information, but traditional recommendation methods cant meet the need of people. Starting from information resource requirements of users in the cloud environment, this article discusses the application of cloud computing in personalized information services, analyzes the necessity and feasibility of the cloud computing technology applying to personalized services, proposes the personalized service idea based on cloud computing, and builds a model to introduce cloud computing and cloud service idea to the management and service, hoping to find the integrating point of the cloud computing technology applications in the personalized field.

Abstract: Electronic commerce recommender systems represent personalized services that want to predict users interest on information items. However, traditional recommendation system has suffered from its shortage in scalability as their calculation complexity increases quickly both in time and space when the number of the user and item in the rating database increases. Poor quality is also one challenge in electronic commerce recommender systems. The paper proposed an electronic commerce recommendation mechanism based on QoS and Bayesian model. And the proposed recommender method combining QoS and Bayesian can improve the accuracy of the electronic commerce recommendation system.

Abstract: Work integrated learning is the center of high vocational education. It is one of the most significant approaches to realize the training purpose of high level talent. At present, high vocational education faces one issue which is how to improve the specialty education level by work integrated learning and improve the initiative of students. In the paper, we begin with the teaching practice of compute multimedia technology, discuss how to create project studio system in specialty teaching and analyze the effect and prospects of this teaching model as well. The paper puts forward a notion about practice and reform on multimedia information specialty in higher vocational education, its emphasis includes: curriculum structure, curriculum evaluation manners, academic and practical instruction.

Abstract: Investigation of association relation for medical prescription appears as an essential part for the treatment of patient in clinical pharmacy. Not often, however occasionally, the pharmaceutical conflict that could possibly relate to unpredictable hazard to patient may occur. Therefore, clinical physicians apply specific software package embedded in HIS (Hospital Information System) to sensitively and instantly discover the potential danger from the electronic prescription. In some HIS systems or independent software packages, Apriori algorithm is applied in pharmaceutical conflict checking, however, the efficacy is encumbered due to the mechanism of the algorithm. The mentioned algorithm Apriori is a classical algorithm for association rules mining, it applies an iteration method called searching step by step, to explore K itemset by (K-1) itemset. Each time when it explores a K-itemset, Apriori algorithm must scan the whole database, which causes the obvious reduction of efficiency due to the requirement of constant database scanning. To solve this problem, an improved Apriori algorithm based on Linkedlist is applied. Due to the decrease of transactions number, the operating efficiency of the algorithm is enhanced during the process of K-itemsets exploration. In order to reduce the number of transactions, the database is transformed into a series LinkedLists which could allocate an element of L1 as header node. After being transformed, the whole database scanning could be skipped. Instead, the corresponding LinkedList is scanned to explore K-itemsets. The proposed method could filter the unrelated transactions during the generation of frequent itemsets. The experiment proves that the new algorithm could release better performance rather than original Apriori algorithm.

Abstract: Uighur web pages classification is meaningful for the Uighur information processing. In this paper, we propose a classification approach for Uighur web pages. It utilizes the combination of two methods to classify the Uighur web pages into the predefined classes. One is the classification method based on Column Navigator of web page. The other is the content classification method based on the classes feature dictionary. Based on the proposed approach, we design the classification system of Uighur web pages. The experimental results present that the system has better performance for Uighur web pages classification. It is useful and helpful for the construction of high-quality Uighur corpus, Uighur information retrieval as well as Uighur text mining.

Abstract: As an important form of Internet data, semi-structured data in data mining is an important fist conditions. And the data mining was designed to find and extract large database in the implied information of value. This paper first introduced the half structured data concept characteristic, based on the data from each of the half structural said, the data model two half-and-half structured data model are introduced, finally summarizes semi-structured data model and the relationship between the data model before difference [1].

Abstract: With the rapid development and widespread use of Internet, readers, especially scientific researchers, depend more on Internet than on traditional library services for necessary information. The Web access of libraries has begun to lay more emphasis on digital reference and consultation services. More importantly, this new type of service is becoming the focus of many scholars research at home and abroad. In this paper, we design a library digital resources management system based on the semantic Web technology, and analyze the access control model in our system by the semantic Web.

Abstract: An elderly people monitoring system based on 3-axis digital accelerometer ADXL345 and digital signal controller TMS320F28335 was designed based on 3-axis digital accelerometer ADXL345 and digital signal controller TMS320F28335. The human posture was collected from ADXL345 by the DSC28335. The FFT filtering algorithm was used to improve the detection accuracy. Then the exercise situation of the elderly people was calculated by using Pedometer algorithm. The fall information was calculated by analyzing the rate of acceleration change. The Beidou Satellite Navigation System was designed for collecting position data to protect the elderly people in different situation.

Abstract: Based on the integration of the genetic algorithm and particle swarm algorithm, a network congestion control method is proposed for path optimization, which takes the load balanced distribution function and the resource consumption function as optimization target and optimizes path under the condition of meeting a number of QoS metrics such as bandwidth, delay, expense. Aiming at avoidance of network congestion, the approach attempt to minimize the network resource consumption and balance the distribution of network load. Simulation results show that the method is effective and reliable.

Abstract: A new theory of infinite series is proposed in this paper, some new important theorems for function expansion and infinite series are also proposed. Unlike Taylors expansion, the expansion generated by a function is not the form of polynomials. In general, the performance of convergence is much better than that obtained by Taylor's Series. The new important theorems lay the foundation for the new theory of infinite series and applications. To describe the performance of the new results obtained in this paper, an example given in this paper shows that the region of convergence is much larger than that of Taylors series. The new infinite series can keep some important properties of original functions. Weight function neural networks are also used to training feedforward neural networks based on the new theory proposed in this paper.