Earticle

The OADM based on DWDM technology is moving the telecommunications industry significantly closer to the development of optical networks. The OADM can be placed between two end terminals along any route and be substituted for an optical amplifier. Commercially available OADMs allow carriers to drop and/or add up to multi channels between DWDM terminals. By deploying an OADM instead of an optical amplifier, service providers can gain flexibility to distribute revenue–generating traffic and reduce costs associated with deploying end terminals at low traffic areas along a route. The OADM is especially well-suited for meshed or branched network configurations, as well as for ring architectures used to enhance survivability. Moreover, An optical add/drop multiplexer with tunable bandwidth offers several potential advantages, including optical performance monitoring and dynamic bandwidth allocation. This paper has proposed OADM for high transmission bit rates and products in next generation optical communication networks based on dense wavelength division multiplexing for different fiber link lengths at room temperature for best performance efficiency.

We present interference analysis from Non-communication device which is used in many applications such as factory, home and hospital into Global Positioning System (GPS) Service. GPS service is used to detect location for car driving and safety of life. Nowadays, non-communication devices are increased rapidly. Therefore, in case that non-communication device and GPS receiver are operated in closed each other, GPS receiver can be affected from interference of non-communication device. In regarding with interference problem, this paper suggested the reasonable isolation distance between non-communication device and GPS receiver in order to guarantee good performance of GPS service.

There are many problems with applying the machine learning technique, which is widely used in the conventional healthcare field, during the mobile u-health service analysis step. First, research on the mobile u-health service is just beginning, and there are very few cases where the existing techniques have been applied in the mobile u-health service environment. Second, since the machine learning technique requires a long learning period, it is not suitable for application in the mobile u-health service environment, which requires real-time disease management. Third, the various machine learning techniques that have been proposed until now do not include a way to assign the weight factors to the disease-related variables, and thus its use as a personalized disease prediction system is somewhat limited. This paper proposes PCADP, which is an ontology-based personalized disease prediction method, to solve such problems and to interpret the bio data analysis of the mobile u-health service system as a process. Moreover, the mobile u-health service ontology framework was modeled as a semantics type in order to meaningfully express the mobile u-health data and service statement based on PCADP. To validate the performance and efficiency of the PCADP technique proposed in this paper, the 5-cross validation method was used to measure the accuracy of the prediction. The validation of PCADP using a virtual disease group verified that the technique proposed in this paper shows much greater accuracy compared to existing methods. Moreover, the PCADP prediction method improved the flexibility and real-time attributes, which are the essential elements of any diagnosis technique in the mobile u-health environment, and showed efficiency in the continuous improvement of the monitoring and system of the diagnosis process.

It has been accepted that a graph can represent any document with minimum loss of information. In this article we are going to put forward some new standards of graph representation and graph distance measure for web documents. With the proposed enhanced method of graph representation and distance measure we would be able to hold more information than usual and hence classify them more efficiently.

We present a simple web search engine for indexing and searching html documents using python programming language. Because python is well known for its simple syntax and strong support for main operating systems, we hope it will be beneficial for learning information retrieval techniques, especially web search engine technology.