The city routing issue is the problem to find a shortest tour of minimum length on a fully connected graph. Various Natureinspired algorithms have been proposed towards this problem. This paper proposes an application of Particle Swarm Optimization for this Issue. Results are achieved with the concept of Swap Operator and Sequence of Swap.

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<p><span id="docs-internal-guid-12eaaa5f-7fff-c428-95bf-97a7381b2976"><span>Breast cancer is the most driving reason for death in women in both developed and developing nations. For the plan of effective classification of a system, the selection of features method must be used to decrease irregularity part in mammogram images. The proposed approach is used to crop the region of interests (ROIs) manually. Based on that number of features are extracted. In this proposed method a novel hybrid optimum feature selection (HOFS) method is used to find out the significant features to reach maximum accuracy for this classification. A number of selected features is applied to train the neural network. In this proposed method accessible informational index from the mini–mammographic image analysis society (MIAS) database was used. The classification of this mammogram database involved a neural networks classifier which attained an accuracy of 99.7% with a sensitivity of 99.5%, and specificity of 100% as the area under the curve (AUC) is 0.9975 and matthew’s correlation coefficient (MCC) represents a binary class value which reached the value of 0.9931. It can be useful in a computer-aided diagnosis system (CAD) framework to help the radiologist in analyzing breast cancer. Results achieved with the proposed method are better compared to recent work.</span></span></p>

<p class="Abstracttext"><span>Wireless sensor network will be the most dominating field in future era. There are certain issues which wireless sensor network suffers from. The main concern with wireless sensor network is limited energy which directly impact on network lifetime. In this paper we modify the cluster selection procedure of MODLEACH. MODLEACH protocol use threshold value for selecting cluster head. Once a cluster head is selected, it retains its position until it bypasses the threshold limit. In Basic LEACH, it does not use any threshold value but it randomly selects cluster head from the available nodes. We combine the probabilistic nature of LEACH to select the cluster head and threshold base selection of cluster head of MODLEACH. We also apply proposed modification in EAMMH protocol. Our main focus is on the enhancement of network lifetime, and we got significant improvement in network lifetime.</span></p>

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