The applications of wireless sensor networks became more usable in daily life. In spite of many proposed techniques and methods, energy efficient routing in WSN is still an open issue. In this paper we made an attempt to give one of the solution for this problem in vehicle tracking system based on the vehicle sensor nodes. We studied many existing works, were failed in handling location and energy efficient routing of vehicle tracking properly. We proposed an algorithm which handles clustering and location at time and improves the performance of the system. This algorithm uses the fundamentals of LEACH, CLAEER and mean shifted algorithm. We conducted a sequence of experiments and our algorithm EECLA (Clustering and Localization Techniques to Improve Energy Efficient Routing in Wireless Sensor Networks) has given better results than the existed one with more accuracy.

Due to increase of usage of wireless sensor networks (WSN) for various purposes leads to a required technology in the present world. Many applications are running with the concepts of WSN now, among that vehicle tracking is one which became prominent in security purposes. In our previous works we proposed an algorithm called EECAL (Energy Efficient Clustering Algorithm and Localization) to improve accuracy and performed well. But are not focused more on continuous tracking of a vehicle in better aspects. In this paper we proposed and refined the same algorithm as per the requirement. Detection and tracking of a vehicle when they are in larges areas is an issue. We mainly focused on proximity graphs and spatial interpolation techniques for getting exact boundaries. Other aspect of our work is to reduce consumption of energy which increases the life time of the network. Performance of system when in active state is another issue can be fixed by setting of peer nodes in communication. We made an attempt to compare our results with the existed works and felt much better our work. For handling localization, we used genetic algorithm which handled good of residual energy, fitness of the network in various aspects. At end we performed a simulation task that proved proposed algorithms performed well and experimental analysis gave us faith by getting less localization error factor.

The main objective of any technology is to give good service, availability and reliability to the end user along with protection and cost feasibility. Cloud computing is one of such technology which can be pay-as-you-go model. Computational resources and backup resources are the one of the issues. When multiple Physical Machines (PM) interacting to cloud to have respective services there may be a chances of failures that spoils the guaranteed services by the providers. In this paper we tried to elaborate these issues by developing a prototype cloud model for failure recovery management with the information of backup resource allocation strategy. We proposed an advanced open stack method based on BRAS. We also conducted a survey on BRAS to give better model. In this paper we focussed more on availability analytical model how its work for BRAS. We also covered some of case studies with yielding results for better understanding of the model. However one of the essential pitfalls in cloud computing is related to optimizing the property being allocated. Because of the distinctiveness of the model, useful resource allocation is achieved with the aim of minimizing the prices associated with it. The specific traumatic conditions of useful resource allocation are meeting customer desires and application requirements.

Thyroid disease is one of the most common diseases among the female Population in Bangladesh. Hypothyroid is a common variation of thyroid disease. It is clearly visible that hypothyroid disease is mostly seen in female patients. Most people are not aware of that disease as a result of which, it is rapidly turning into a critical disease. It is very much important to detect it in the primary stage so that doctors can provide better medication to keep itself turning into a serious matter. Predicting disease in machine learning is a difficult task. Machine learning plays an important role in predicting diseases. Again distinct Predicting techniques have facilitated this process analysis and assumption of diseases. There are two types of thyroid diseases namely Hyperthyroid and Hypothyroid. Here, in this paper, we have attempted to predict hypothyroid in the primary stage. To do so, we have mainly used classification algorithms named Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), Logistic Regression (LR) and Naive Bayes (NB). By observing the results, we could extrapolate that our Trained (Structured) Dataset provide’s an (approx.) 97.05% accuracy for Random Forest (Bagging) classification algorithm.

Cloud computing became a huge servicing platform to many domains for organizational growth. Virtualization, autonomic, utility computing and service oriented architecture made cloud computing robust. One of the major contributions of cloud computing to the health care systems is prominent one. In this paper we propose a framework that depicts various security and performance issues related to health care domain with the support of cloud computing. Beginning with a device of well known statistics protection the board procedures got from norms of the ISO 27000 own family the principle statistics protection tactics for medical care associations utilising distributed computing could be diagnosed thinking about the number one risks with admire to allotted computing and the sort of facts treated. The distinguished cycles will help a well being with worrying association utilising distributed computing to zero in on the most significant isms methods and lay out and work them at a becoming degree of development thinking about restricted property. We examine dangers and emergencies for medical care suppliers and talk about the effect of distributed computing in such situations. The research is led in an all encompassing manner, considering hierarchical and human angles, medical, it-associated, and utilities-associated takes a chance in addition to joining the angle on the overall gamble the executives. We ruin down risks and emergencies for medical care suppliers and study the impact of dispensed computing in such situations. The research is directed in a complete manner, thinking about hierarchical and human viewpoints, scientific, it-associated, and utilities-associated gambles as well as consolidating the angle on the general gamble the board. On this paper, we assessment about the unique types of problems and problems related with distributed computing in particular execution troubles and disbursed garage protection troubles.