Smart world needs intelligent system for effective and timely decision making. This is achieved only through a knowledge based system with functional knowledge representation units. In this paper, two models are proposed for representing knowledge. This process involves in getting the data and placing the information in the correct location. Logical notations are used for taking the clauses and graph is used for putting the entities. In Model one, the data is translated into logical statements using predicate logics, later the knowledge is stored in conceptual graph and retrieved. Whereas in Model two, the given information is translated using First Order Logic (FOL), by applying description logic concept rules are defined and as a result reasoning is done. Storage is done by using concept-relation graph. The main aims of our models are to have easy and simple access over the information. These models return the required exact answer, for the higher order query posted by the end user to the intelligent system.

Organizational Training and Learning are among the 22 key process areas in CMM. These two processes are subject for improvement based on its framework and execution. In this paper, we have worked on project-based frameworks for organizational training and learning and have attempted to validate them in the software developmental organizations and in an institution teaching software engineering.
The empirical validation is carried out with those case studies and significant results are obtained in assessing the improvement in the two process areas. Moreover, this work is also extended to accommodate improvement in the regular conventional OTL processes.