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WTM (Wind Turbine Micrositing) has been an important topic of discussion in recent times. A number of Evolutionary Algorithms have been applied to the WTM problem. The DEA (Differential Evolution Algorithm) is used for a bi-constrained optimization for getting maximum power production at the least cost from a 2x2 km space. It is shown that the DEA performs comparably to the GA (Genetic Algorithms) for wind farm optimization. The optimal configuration obtained enlists the number of turbines, the cost of power generated as well as the power produced. Moreover, this study is augmented by comparison with past approaches by using the GA for the same purpose.

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In this work, the numerical data related to wind turbine micrositing problem is presented. The data is acquired using the differential evolution algorithm (DEA) at different wind speeds. The data obtained through DEA include total dissipated power, cost per installation of unit turbine, and the efficiency of algorithm after installation of any particular number turbines; and are depicted versus number of turbines. The data provided in this paper can be used directly without having to spend weeks of computational time to simulate the results; and can readily be used for comparison with other existing (Massan et al. [1] and Rajper et al. [2], etc.) and forthcoming algorithms in future.

3C Tecnología. Glosas de innovación aplicadas a la pyme.

This work focuses on taking the research from impact factor to impact which means that it would propose the best interventions required at both public and private sector universities to improve the research scenario in times of emergency. The timing of this work coincides with the current corona virus pandemic and it encompasses the best practices for such an era in modern times. It proposes the requisite revamping and careful reworking of the university towards becoming a research enabler for the students at a time of crisis.This article analyzes the effects of the Coronavirus disease on the researchers who must maintain social distance during confinement at the university and yet be able to carry out meaningful research by utilizing videoconferencing and other facilities.

The Colebrook's equation is considered as an empirical model to accurately compute the Darcy friction factor in pipes under fully-developed turbulent flow. Due to non-linearity and implicitness of the Colebrook's equation, one needs to use numerical methods to acquire reasonably good approximation to the true friction factor values. However, such idea is not preferred by practitioners as it demands use of computers – also more computational time and effort. To overcome this, explicit equations that can describe Darcy friction factor directly in terms of the Reynolds number and relative roughness are essential. Using Fixed point iteration method in the MATLAB software, we have developed a 16 decimal places' accurate friction factor database for the Darcy friction factor for a 1000 by 1000 mesh of Reynolds number and relative roughness values. The accurate dataset described in this work will serve to be basis for the construction of new and more reliable explicit equations using regression modeling, artificial intelligence techniques and other soft computing methods.

Interconnectivity of smart devices such as mobile technology adoption in healthcare holds humongous impacts. Yet, medical professionals are reluctant to reap potential benefits of technology and the reason behind this phenomenon is ambiguous. This study aims to highlight current critical conditions in public healthcare hospitals in Pakistan, and how IoT will add value in healthcare services effectiveness through mobile computing and also to indicate current concepts that may add value in over-all smart healthcare system. According to available information, study to on AI enabled M-IoT network-based healthcare system specially in developing countries to address healthcare problems are rarely known. This study empirically analyzed the factors that influence IoT based smart healthcare devices adoption in Pakistan. In understand the phenomenon, Partial Least Square Equation Model (PLS SEM) was used to understand the relational influence of performance expectance, effort expectance, and social influence over behavior to use through intention to use the technology supported by Unified Theory of Acceptance Technology (UTAUT) assumptions. The results show that clinicians are reluctant to use technology though the results also reveal that same clinicians have positive influence of performance and effort expectations on their intention to use technology that leads the actual behavior of using the technology. Though, this research is among few to beacon upon urgent focus of public healthcare management in developing countries. Yet, new research is lacking far behind to facilitate methods to opt for M-IoT healthcare devices powered by AI.