This paper presents a software risk prediction tool for risk analysis during the development of a software product. The term "Risk" refers to a problem that can threaten the success of the software project but has not happened yet. Risks are uncertain. The main objective of each organization is to provide very high quality software to their customers. The term "Quality" is a value to the person. But there is a long list of software risks that can have adverse impact on the quality of the software. It is necessary to address all the risks; otherwise, they may lead to undesireable results. Fuzzy Cognitive Maps (FCMs) describe different concepts with different aspects of the behaviour of complex systems. A software tool based upon FCM has been developed for assessing software risks. This paper describes the reasoning behind the focus on risk management during the software development process and its importance in delivering high quality software by assessing software risks during the development process using fuzzy cognitive maps.

An artificial intelligence system is capable of elucidating and representing knowledge along with storing and manipulating data.Knowledge could be a collection of facts and principles build up by human. It is the refined form of information. Knowledge representation is to represent knowledge in a manner that facilitates the power to draw conclusions from knowledge. Knowledge representation is a good approach as conventional procedural code is not the best way to use for solving complex problems. Frames, Semantic Nets, Systems Architecture, Rules, and Ontology are its techniques to represent knowledge. Forward and backward chaining are the two main methods of reasoning used in an inference engine. It is a very common approach for "expert systems", business and systems. This paper focus on the concept of knowledge representation in artificial intelligence and the elaborating the comparison of forward and backward chaining.

Telecommunications and data networking fields are being changed by the use of wireless networks proving flexibility and mobility of clients as well as servers. This also provides the ability of extension of applications in many diverse areas. In this work, we are evaluating performance of 802.11 WLAN scenarios in Opnet Modeler 14.5. Throughput of the WLAN is evaluated in the presence of high priority traffic as well as low priority traffic, generating data simultaneously. Results are shown in detail with the help of graphs.

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