By means of data mining techniques, we can exploit furtive and precious information through medicine data bases. Because of huge amount of this information, study and analyses are too difficult. We want some methods to exploring through data and extract valuable information which can be used in the future similar cases. One of these cases is accouchement. The mechanism of accouchement is a natural and spontaneous process without the need to any intervention. In some conditions, maybe mother, baby or both of them are in hazard and need help and support. This help is provided by Caesarian Section which saves mother and baby. Nevertheless, we need to know when we should use surgery. This study explains utilization of medical data mining in determination of medical operation methods. We render this with accumulating 80 pregnant women information. The results show that decision tree algorithm designed for this case study generates correct prediction for more than 86.25% tests cases
Dynamic travelling salesman problem (DTSP) is one of the optimization issues which it is not solvable with classical methods. To solve this problem, various solutions in the literature can be seen that each has advantages and disadvantages. Genetic Algorithm (GA) and Ant Colony Optimization (ACO) have been good to solve the DTSP. In this paper, we highlight a new algorithm by combining genetic and ACO which gives us a better solution for DTSP. In hybrid algorithm, suitability of algorithm and travelled distance for DTSP has been considered. Obtained results suggest that Hybrid algorithm does not establish easily in the local optimum and possesses a good speed in convergence for comprehensive answer.
All existing methods for Developing Software Systems, most insist on a separate system to keep the components together till they have been had the least overlapping. But these methods in the management system those have some parts and are using use case, and involved in the other parts of the systems, are inefficient. With arriving the Aspect-Oriented Programming, programmers were able to Implement the overcome some of these requirements and Implement them in a separate unit, but there are still some of the analysis requirements and design, because of the wrong analysis and design they cannot be implemented as a measure. In this article we want to prominent the phase of analysis and design of this work using the Aspect-Oriented Software, in order to implement them in the Implementation phase as a cupon.
The N×N queen's puzzle is the problem of placing N chess queen on an N×N chess board so that no two queens attack each other. This approach is a classical problem in the artificial intelligence area. A solution requires that no two queens share the same row, column or diagonal. These problems for computer scientists present practical solution to many useful applications and have become an important issue. In this paper we proposed new resolution for solving nQueens used combination of depth firs search (DFS) and breathe first search (BFS) techniques. The proposed algorithm act based on placing queens on chess board directly. This is possible by regular pattern on the basis of the work law of minister.The results show that performance and run time in this approach better then back tracking methods and hill climbing modes.
Multiagent Systems Engineering (MaSE) Methodology is one of old object-oriented methodology which supports the development process and is established based on the development of the object-oriented software engineering methods and their adjustment with the agent view. Some characteristics of the agent like autonomy, creativity and preactivated are not paid attention. The agents are supposed as simple software processes which cooperate to obtain a certain goal. There are two basic phases in MaSE: analysis and design. The analysis phase concentrates on specializing the agent's roles, their duties and interactions. In design phase, matters such as diagrams and conversations class are introduced. The all steps in MaSE are implemented by graphic tools, agent Tool. This tool (agent Tool) covers all the steps of MaSE methodology design and analysis. In this article, we have covered the MaSE methodology based on a practical experience. The reason of choosing the chain store system is that it has the necessary characteristics like customer and seller autonomic agent technology and it is easier to identify and understand the analysis and design steps.
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