Simple non-invasive dental treatment can have a positive effect on appearance-related satisfaction. The use of child-centred approaches offers an invaluable insight into patient perspectives.

Deep knowledge of how radio waves behave in a practical wireless channel is required for effective planning and deployment of radio access networks in urban environments. Empirical propagation models are popular for their simplicity, but they are prone to introduce high prediction errors. Different heuristic methods and geospatial approaches have been developed to further reduce path loss prediction error. However, the efficacy of these new techniques in built-up areas should be experimentally verified. In this paper, the efficiencies of empirical, heuristic, and geospatial methods for signal fading predictions in the very high frequency (VHF) and ultra-high frequency (UHF) bands in typical urban environments are evaluated and analyzed. Electromagnetic field strength measurements are performed at different test locations within four selected cities in Nigeria. The data collected are used to develop path loss models based on artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and Kriging techniques. The prediction results of the developed models are compared with those of selected empirical models and field measured data. Apart from Egli and ECC-33, the root mean squared error (RMSE) produced by all other models under investigation are considered acceptable. Specifically, the ANN and ANFIS models yielded the lowest prediction errors. However, the empirical models have the lowest standard deviation errors across all the bands. The findings of this study will help radio network engineers to achieve efficient radio coverage estimation; determine the optimal base station location; make a proper frequency allocation; select the most suitable antenna; and perform interference feasibility studies.INDEX TERMS ANFIS, artificial neural networks, backpropagation, path loss, Kriging, radio propagation. I. INTRODUCTIONA study of the characteristics of radio waves in different propagation environments is needed for an effective network planning, and for the deployment of wireless communication systems [1], [2]. The magnitude and direction of electromagnetic waves in a practical wireless channel is usuallyThe associate editor coordinating the review of this manuscript and approving it for publication was Mauro Tucci.random and highly unpredictable [3]. Meanwhile, a good understanding of this phenomenon is needed to guarantee good Quality of Service (QoS) and high data transmission rate in radio access networks.The efficiency of a wireless communication system depends on the physical constituents of the propagation environment. The presence of buildings, mountains, bill boards, foliage, vehicles and other physical objects in a practical propagation environment usually obstructs the direct

Access to quality healthcare is a major problem in Sub-Saharan Africa with a doctor-to-patient ratio as high as 1:50,000, which is far above the recommended ratio by the World Health Organization (WHO) which is 1:600. This has been aggravated by the lack of access to critical infrastructures such as the health care facilities, roads, electricity, and many other factors. Even if these infrastructures are provided, the number of medical practitioners to cater for the growing population of these countries is not sufficient. In this article, how information and communication technology (ICT) can be used to drive a sustainable health care delivery system through the introduction and promotion of Virtual Clinics and various health information systems such as mobile health and electronic health record systems into the healthcare industry in Sub-Saharan Africa is presented. Furthermore, the article suggests ways of attaining successful implementation of telemedicine applications /services and remote health care facilities in Africa.

An optimization model for the design of a hybrid renewable energy microgrid supplying an isolated load has been developed. This is achieved in two steps. The first step developed a linear programming model that uses the average pattern of demand, wind, and solar energy to determine the optimal configuration. The second step used a clustering algorithm to investigate the methods of improving the reliability of the system. These include increasing the storage capacity and increasing the rated power of the wind energy conversion system (WECS) or solar energy conversion system (SECS). The results have shown that increasing the capacity of storage is the most economical way of improving the reliability of the system. The model has been verified through applications to a test microgrid of common size. The results have shown a 70% reduction in gas emissions and an 80% reduction in energy costs.

In this paper, statistical analysis is carried out to determine the accurate frequency distribution that fits wind speed data. The frequency distributions used include Weibull, Rayleigh and Gamma distribution functions. The performances of the probability distributions are based on the error evaluations between the predicted and the theoretical wind power densities of the site. The Results show that Weibull distribution modelled the wind speed better compared to other distribution functions. According to the European Wind Energy Association, most of the sites are suitable for the generation of electrical energy. Also, the results have shown that Jos, Kano and Minna fall in class 4 and therefore suitable for both off grid and grid connected modes. In addition, the effects of c and k parameters on the probability distribution functions have been presented.