Abstract. The Word "Biorhythm" is derived from the Greek word "Bios" which means life and "Rhythm" which means flowing with a regular movement. Biorhythm theory uses mostly scientific methods to chart the rhythms or cycles that affect the internal functioning of the body and of human behavior. This is particularly applicable to the physical, emotional and intellectual or mental abilities. Biorhythm theory states that, at the moment of birth three statistical cycles are initiated and these will recur consistently throughout life. This chapter proposes an investigation of the reasons for human error as a contributing factor in flying accidents. Physical factors such as man machine interactions involved in flying mistakes and a taxonomic approach to errors has been proposed in this chapter, in order to avoid accidents. This chapter presents a new methodology based on a probabilistic approach for biorhythmic analysis in an attempt to prevent aviation accidents. The methodology has been developed using a Gaussian distribution technique for evaluation of the aviation system reliability considering the biorhythmic effects on the pilot. Normal distributed data from the US air force were tested and analyzed. These were based on the performance ability of pilots and the peak demand of the performance using a Gaussian distribution approach. Validation of an aircraft accident due to biorhythm is explained in this chapter with consideration of the peak performance demand and differing standard deviations in the performance ability of each pilot. A new curve named the Incident -Duration Curve has been introduced. This is based on a biorhythmic analysis of Indian and US air force data. The area under normal distribution curve of the US air force data represents the successful performance ability zone * Corresponding author. 208 R.K. Saket, S.P. Kaushik, and G. Singh of the Pilot. The accident zone is the area of operation during which the Performance Demand exceeds the Performance Ability of the particular aircraft pilot. Operation within the zone of the normal distribution curve is successful owing to ability and fitness of the particular pilot. Failure probabilities considering Peak Performance Demand and pilot's ability have been evaluated using a Gaussian distribution approach. A Safety Factor Concept is also given in this chapter. This has been done so as to include biorhythmic analysis in the attempt to avoid aviation accidents. A Stepped Incident-Duration Curve has been utilized in order to evaluate the particular pilot's reliability when using the system. The complete aviation system was evaluated by using Simpson's 1/3 rd rule.

The aim of this paper was to estimate the number of defects in software and remove them successfully. This paper incorporates Weibull distribution approach along with inflection S-shaped Software Reliability Growth Models (SRGM). In this combination two parameter Weibull distribution methodology is used. Relative Prediction Error (RPE) is calculated to predict the validity criterion of the developed model. Experimental results on actual data from five data sets are compared with two other existing models, which expose that the proposed software reliability growth model predicts better estimation to remove the defects. This paper presents best software reliability growth model with including feature of both Weibull distribution and inflection S-shaped SRGM to estimate the defects of software system, and provide help to researchers and software industries to develop highly reliable software products. Ó 2015 Production and hosting by Elsevier B.V. on behalf of Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

This paper presents a new methodology, based on the probabilistic approach, for biorhythmic analysis to prevent aviation accidents. The methodology has been developed using the Gaussian distribution technique for reliability evaluation of the aviation system, keeping in mind the biorhythmic effects of the pilot. The normal distributed data of the US Air Force were tested and analysed based on the performance ability of pilot and the peak demand of the performance. The accident zone is that area of operation during which the performance demand exceeds the performance ability of the aircraft pilot. Failure probabilities, considering peak performance demand and the pilot's ability, have been evaluated using the Gaussian distribution approach. The safety factor concept has also been presented in this paper for biorhythmic analysis to prevent aviation accidents. The stepped incident-duration curve has been utilised to evaluate the pilot's reliability on the aviation system using Simpson's 1/3rd rule.

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