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In today's life, biomedical field reach at higher level because of highest development in portable devices and the equipment which are being helping the patients in monitoring and controlling different disease at different stages. But in many work environments, the worker has lot pressure and continuous movement on daily basis which tends to foot related diseases as getting exact details about the foot movement throughout the daily work routine is not possible. In available treatment options in such conditions, they are recommended to employ the compression therapy delivered by bandage, medical-grade stockings, or pneumatic compression devices. As a result of this the patients may suffer from painful period which may cause amputation also especially in case of sensory neuropathy.While these forms of therapy can produce the slight improvements, still it is costly solution and patient remain an issues related to rehabilitation. As alternate of this need the wearable, wireless, portable health monitoring system have recently introduce as a low-cost solution for supervision of foot health condition monitoring. The proposed system is to design and implementation of wearable device for foot for diabetic person for disease monitoring where the system will be capable to detect the level of foot ulcers related issues along with daily exercise level monitoring.

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Globally terrorism continues to destroy the lives of people. To identify the terrorist amongst the other people is very difficult rather impossible. This exploratory study aims at investigating the effects of terrorism to recognize emotions. The current paper presents a view-based approach to the representation and recognition of human facial expression. In the designing of facial expression recognition (FER) system, Authors can take advantage of the resources and developed the algorithms for the system. The system divides into 3 modules, i.e. Preprocessing, Feature Extraction and Classification. The basis of the representation is a temporal template where the features are used typically based on local spatial position or displacement of specific points and regions of the face. In this paper, five different facial expressions were considered. Extracting the features, firstly logarithmic Gabor filters were applied. Then the Optimal subsets of features were selected for each expression. The classification tasks were performed using the Neural Network. Secondly, this study indicates that the YALE database contains expressers that expressed expressions.

The bio-inspired computation algorithms are the excellent tools for global optimization. These algorithms are very easy to understand and simple to implement. These algorithms especially dominate the classical optimization methods. Particle Swarm Optimization (PSO) is a global optimization algorithm that originally took its inspiration from the biological examples by swarming, flocking and herding phenomena in vertebrates. This paper presents facial emotion recognition system using PSO for different video clips with different cameras, at different distances and light intensity changes. The analysis is done for recognizing "Happy" emotion from other emotions. The comparison of facial emotion recognition system using other techniques and PSO is done. It is found that PSO has better results over other techniques in terms of accuracy and time required.