Mobility of people has significantly increased. Daily and occasional trips consume a significant time in our whole life span. A comfortable and safe travel is prime need of any individual. Noise is an important parameter which defines the quality of life. Vehicular noise not only affects the outer environment of the vehicle but it also causes discomfort for the occupants travelling inside the vehicle. Noise reduction during journey is an important aspect for a comfortable travel. We are constantly exposed to various types of noise generated from vibrations. These vibrations produce longitudinal waves which are intercepted by our ear. Sensitivity of our auditory system depends on various factors, and age of individual is an important parameter. Apart from this the exposure of noise during lifetime is important criteria for long term auditory functions. Exposure of noise during travel is gaining significant importance as it decides our comfort level, and sleep duration. In this paper we examine the noise pressure level (dBA) during travel through filed data collection. The trips discussed are on road, rail and air.
The diagnosis of clinical data is a major issue in the automation system. The automation system increases the efficiency and reliability of prediction of symptoms. In this paper presents the review of different technique used for the process of analysis. Now a days various authors used the data mining technique in the combination of neural network and fuzzy system. The behavious of fuzzy system increases the efficeny of automation systems. The fuzzy based systems only supported comprative analysis. Some others are used neuro-fuzzy systems for the prediction of clinical data analysis.
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