Earticle

E-commerce as a new way of enterprise marketing ,it plays an important role in promoting small and medium enterprises to develop new markets, reduce production and management costs, improve productivity and so on. At the same time, the electronic commerce also helps small and medium enterprises to make full use of the flexible and quick advantages, and complete the upgrade of the flexible production .In this paper, we make a empirical analysis and try to find out the key factors that affect E-business performance in SMEs, the result shows that technical talents, leadership support, government policy, infrastructure and credit environment will have positive influence to E-business performance in enterprises.

In the field of Mobile Terminal (MT), Unity3D game engine has displayed outstanding rendering power and highly aggregated script editing function while in practice the network function of Unity3D has not been fully developed yet. This paper, based on the comparison with traditional network technology, proposed to invoke Java to create a WIFI Local Area Network (WLAN), in which Unity network view component and remote procedure call (RPC) are employed to synchronize data and images on both ends of the network, thus developing a Unity online game. Finally the author of this paper has designed an online Unity3D chess game based on Android mobile platform. The results indicate that the invocation of Java has made up the deficiency of Unity network while RPC, as a reliable, free and economical method in the network transmission displays great adaptability. The combination of Java and RPC has proved to be a simple but an effective way to develop mobile online game.

In last few decades, typical lithography based VLSI technology used to improve higher scale integration, low switching speed and low powered computing of semiconductor constituents. However, this trend meets severe challenges of tunneling, short-channel effects andleakage current. Quantum-dot Cellular Automata (QCA) is one of the promising substitutions to traditional semiconductor-based technology which proposed aunique scheme of information transmutation as well as computation.QCA hold the assurance of rapid speeds, higher switching frequency, highlyscalable feature and notably reduced sizes. In this paper, an efficient layout of fredkin gate is proposed based on QCA and CMOS technology which lessened total covered area, the number of cell and clock, latency timeand number of coplanar wire crossing compared with the earlier design also the VHSIC Hardware Description Language (VHDL) of proposed fredkin gate is presented. For simulating and confirming the proposed circuit QCADesigner and Microwindlite, familiar verification and simulation tools has been occupied. The proposed design has a promising prospective in the organizing of nanoscale low power exhausting information processing system and can stimulate complex digital applications in QCA.

As one of the most successful approaches to building recommender systems, collaborative filtering (CF) uses the known preferences of a group of users to make recommendations or predictions of the unknown preferences for other users. However, the open nature of collaborative filtering recommender systems allows attackers who inject biased profile data to have a significant impact on the recommendations produced. Shilling attacks against numeric ratings-based CF schemes have been extensively studied. To the best of our knowledge, there is rare study about how to attack binary ratings-based recommendation systems. Hence, shilling attacks strategies against binary ratings-based recommendation algorithms need to be further investigated. The empirical results obtained from Movielens dataset show that the segment attack, which is easy to mount, affects strongly against BU-CF algorithm and BI-CF algorithm, and the attack size and the filler size don’t have the same sensitivity in attack effect.

Sensors play a major role in an automated manufacturing system. They are used for getting information from manufacturing operations and processes that are being performed. They are also used for making decisions about the operations being conducted. The purpose of sensors is to inspect and monitor the work-in-progress interface with the manufacturing equipment. In manufacturing industries the multi-operation machine like VMC (Vertical machining center) and HMC (Horizontal machining center) are the major part. It is used to improve the high productivity, high quality and high accuracy of the product. But the CNC machine has some drawbacks like high initial investment, high maintenance and skilled labor wants to operate the machine. To overcome these problems, this paper proposes a low cost automatic multi-operation machine. It performs basic machining operations like drilling, tapping and boring using low cost color sensors (LDR and LEDs). In this system color sensors are the main part to determine the machining operations based on the usage of color LEDs. If LDR detects the color LED the machining operation will take places, the machining operation and job clamping operation are achieved by pneumatic system. All these operations are carried out in a sequence by pre-programming the Programmable Logic Controller.

In this paper, a novel prediction method for box-office is proposed based on the rough set data processing function and support vector machine (SVM) classification mechanism. The front-end processor, optimizes the input variables by attribute reduction, in order to improve the performance of classifier. Then, in view of the lack of guidance of scientific theory problem of domestic movie box office prediction, the classifier for the box-office prediction, the influence factors of the box office revenue as the input variables, the box-office income categories as output variables, data preprocessing and training test. Results show that the classifier can effectively solve the box office prediction problem, the results of the multilayer perceptron is better than that of Ramesh S. and Dursun D. using the prediction method, and the prediction error is less than 10%, to meet the requirements of the film market, show the powerful classification ability.

In this paper, the iterative learning control (ILC) scheme combined with the backstepping controller is applied to the Wiener system, which is a typical nonlinear and non-Lipschitz one. The ILC scheme as a feed forward control can improve the convergence speed, and the perfect tracking can be achieved as the system is repeatable. The backstepping control is a feedback control which improves the robustness of the control system, especially for the existence of non-repeatable noises. The backstepping part also guarantees the asymptotic stability, which further improves the convergence speed. The design of backstepping controller is based on the error information in the current control process, and the Lyapunov method. The convergence condition is achieved and the convergence speed is analyzed as well. It can be seen that the combination of ILC scheme and backstepping method can improve the system performance to a large extant. Numerical simulations validate the above conclusions.

Cloud computing platforms are complex system, which consist of a lot of software working together. Because of software defects, cloud computing platforms may has performance anomaly during runtime. In this paper, a data-driven anomaly detection method is proposed to monitor runtime performance for cloud computing platforms. The proposed method can not only detect the performance anomaly of cloud computing platforms during runtime, but also find out which performance metric results in the anomaly. A series of experiments are conducted on a real private cloud computing platform based on OpenStack and experimental results show the proposed method is better than previous anomaly detection methods for cloud computing platforms.