In this paper, we presented the architecture and basic learning process underlying ANFIS (adaptive-network-based fuzzy inference system) which is a fuzzy inference system implemented in the framework of adaptive networks. Soft computing approaches including artificial neural networks and fuzzy inference have been used widely to model expert behavior. Using given input/output data values, the proposed ANFIS can construct mapping based on both human knowledge (in the form of fuzzy if-then rules) and hybrid learning algorithm. In modeling and simulation, the ANFIS strategy is employed to model nonlinear functions, to control one of the most important parameters of the induction machine and predict a chaotic time series, all yielding more effective, faster response or settling times.

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In order to cope with real-world problems more effectively, we tend to design a decision support system for tuberculosis bacterium class identification. In this paper, we are concerned to propose a fuzzy diagnosability approach, which takes value between {0, 1} and based on observability of events, we formalized the construction of diagnoses that are used to perform diagnosis. In particular, we present a framework of the fuzzy expert system; discuss the suitability of artificial intelligence as a novel soft paradigm and reviews work from the literature for the development of a medical diagnostic system. The newly proposed approach allows us to deal with problems of diagnosability for both crisp and fuzzy value of input data. Accuracy analysis of designed decision support system based on demographic data was done by comparing expert knowledge and system generated response. This basic emblematic approach using fuzzy inference system is presented that describes a technique to forecast the existence of bacterium and provides support platform to pulmonary researchers in identifying the ailment effectively. KEYWORDSExpert system, fuzzy diagnosability, rulebased method, MATLAB, Tuberculosis (TB).

Spur dikes are river training structures that have been extensively used worldwide for towards enhancing flood control and the stability of embankments and riverbanks.However, scour around spur dikes can be a major problem affecting their stability and hydraulic performance. The precise computation of temporal scour depth at spur dikes is very important for the design of economical and safe spur dikes. This study focuses on experimentally assessing the temporal variation of scour depth around a vertical wall spur dike and identifying the parameters, which mostly influence spur dike performance for a channel bed surface comprised of sand-gravel mixtures. In the current study, the authors did physical experiments in a flume based study to obtain new data, aimed at deriving a new predictive model for spur dike scour and comparing its performance to others found in the literature. It was found that the dimensionless temporal scour depth variation increases with an increase in (i) the threshold velocity ratio, (ii) the densimetric Froude number of the bed surface sediment mixture, (iii) the flow shallowness (defined as the ratio of the approach flow depth, y, to the spur dike's transverse length, l), and (iv) the flow depth-particle size ratio. It is also concluded that the temporal scour depth variation in the sediment mixture is influenced by the non-uniformity of sediment and decreases with an increase in the non-uniformity of the sediment mixture. A new mathematical model is derived for the estimation of temporal scour depths in sand-gravel sediment mixtures. The proposed equation has been calibrated and validated with the experimental data, demonstrating a good predictive capacity for the estimation of temporal scour depth evolution.

This paper aims to analyze the turbulent structure of flows over beds undergoing downward seepage under clear-water conditions. Laboratory experiments in this regard were carried out in a straight rectangular channel that was 17.20 m long and 1.00 m wide. A sandy bed with median grain size d50 = 0.50 mm and sediment gradation σg = 1.65 (i.e., slightly non-uniform sediment) was used for the channel bed. The 3D instantaneous velocities of water were measured with an Acoustic Doppler Velocimeter (ADV) at the working test section. In the vicinity of the bed surface with seepage, measurements revealed that the flow longitudinal velocities (i.e., velocities in x direction) were higher than those in the case of a bed without seepage. Moreover, the variations inthe Reynolds shear stresses increased for the bed with seepage, indicating a higher exchange of flow energy towards the boundary and vice versa. Therefore, it was found that seepage processes influence the turbulence intensity, with a prominent magnitude in the streamwise and vertical directions. The paper also focuses on the third-order moment (skewness) and the kurtosis of velocity fluctuations and the governance of sweep events within the near-bed flow in cases where seepage was observed.

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