Requirement engineering is the first phase of software engineering. In requirement engineering, the first phase is requirement elicitation (RE), which is the most critical and error-prone activity. In this phase, the requirements are extracted from various sources; after extraction, they are analyzed and documented for a specific purpose of software development. In RE, process requirements from stakeholders are gathered, upon which the entire software product failure and success are dependent. In order to accomplish the goal of requirement elicitation, various techniques are used. However, the selection of these techniques is a very challenging task, as one technique may suit a situation but may not be suited for other situations. Besides this, project attributes such as documentation culture of organization, degree of relationship among stakeholders, and familiarity to domain also have a great impact on the process of technique selection. The reason is that there is no empirical value of the techniques that provide help in techniques selection to analyze the basis software project attributes. This study proposed the analytic network process, which is one of the multicriteria decision making processes for the elicitation technique selection process with respect to criterion attributes of project. The motivation toward the use of the ANP approach for the selection of requirement selection technique is that there are dependencies existing among attributes of the project elements. So, the ANP approach is capable of dealing with such situations where dependencies and complexity occur. Results of the proposed study demonstrate that the technique helps in complex situations where decision making is difficult based on the alternatives.

The semiclassical hydrodynamic model is used to study the effect of electron exchange-correlation potential, quantum Bohm term, and degenerate pressure on the dynamics of dust ion acoustic waves by following the two-fluid theory in collisional, unmagnetized dusty plasma. For linear analysis, the dispersion relation modified by the exchange-correlation coefficient is derived. For nonlinear analysis, the standard perturbative approach is used to derive a deformed Korteweg–deVries equation with a linear damping term for finite amplitude waves. The analytical and numerical investigations in the presence of low collisional frequencies reveal the existence of compressive dissipative solitons. Considering the dense astrophysical objects, the dissipative compressive solitons are numerically investigated with the effect of different plasma parameters including collisions and exchange-correlation potential.

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Epicardial fat may play an important role in the pathogenesis of coronary artery disease (CAD). We investigated the relationship between coronary artery ectasia (CAE) and epicardial fat volume (EFV). This retrospective study included 506 patients with CAE (group 1), 500 with CAD (group 2), and 500 patients with normal coronaries as controls (group 3). The pericardium was traced manually from the edge of the pulmonary trunk to the last measured by computed tomography slice containing images of the heart to obtain a region of interest. EFV was significantly higher in patients with CAD than in those with CAE (87.94 ± 22.18 vs 61.33 ± 12.75 mL; P < .001). Patients with normal coronaries had EFV of 56.62 ± 9.82 mL. Multivariate logistic regression analysis showed that male gender [Odds ratio (OR) (95% confidence interval (CI)): 1.220 (1.015–1.682), P = .042], diabetes [OR (95% CI): 1.036 (1.008–1.057); P = .002], and smoking [OR (95% CI): 3.043 (1.022–9.462); P = .005] were significantly associated with CAE. The receiver operating characteristic (ROC) curve showed that EFV had strongest diagnostic value for detecting CAD rather than CAE [AUC .502 P = .074 (95% CI: .311–.784)]. This study demonstrated that EFV is an independent predictor for CAE and CAD. However, sensitivity and specificity for detecting CAE is low when compared with CAD.

Nanofluids play a prominent role in the development of various electronic structures and technological devices. Herein, we devise new and efficient techniques for overcoming the problems faced by the base fluids. This article describes water-based carbon nanotubes, including two major types of single-wall carbon nanotubes (SWCNT) and multi-wall carbon nanotubes (MWCNT). A mathematical model is considered for unsteady three-dimensional CNTs nanofluids flow with a uniform magnetic field between two revolving disks. The basic equations of the modeled flow problem are solved by the BVPh 2.0 package which is implemented using the Optimal Homotopy Analysis Method (OHAM). It has been observed that by stretching the top disk while keeping the lower disk stationary, the rotation aspect is reduced, whilst radial velocity near the top disk significantly increases. Moreover, The higher the values of unsteadiness parameter, the more accurate the temperature profile.