The selection of an entry-level music librarian: The analytic hierarchy process (AHP) as a new model

This paper aims to present how to select the best entry-level music librarian by using the Analytic Hierarchy Process technique. The reason why we used this technique is due to the fact that it helps the decision makers easily calculate ‘the importance weights of professional criteria’ and ‘the extent to which the candidates meet the professional criteria’ to come to a final decision on each candidate. With this purpose, we firstly described 7 professional criteria (a1, a2, a3,…, a7) that must be met by 3 entry-level music librarian candidates. Secondly, we decided each candidate’s performance score representing the extent to which each candidate meets these criteria. For this, we used both a 9-point scale for pairwise comparisons and Saaty’s eigenvector method. Thirdly, we assigned the importance weights to the required criteria. Fourthly, we performed the consistency test to measure the consistencies of our calculations with the aid of the consistency ratio (CR). Fifthly, we obtained the final performance scores of each candidate as the candidate 1= 0,464, the candidate 2= 0, 296, and the candidate 3= 0, 240. Finally, we selected the candidate 1 who earned the highest score (0,464) in total as the best entry-level music libraria

GIS-Based Site Suitability Analysis for Wind and Solar Photovoltaics Energy Plants in Central North Region, Namibia

Increasing urbanisation and population growth are making it difficult for governments to achieve sustainable development. Provision of clean energy is among the seventeen sustainable development goals, as it reduces reliance on fossil fuels. In recent years, Namibia has rapidly increased her reliance on sustainable energy. The renewable energy sources (RESs), including wind and solar energy, can be described as clean sources which have lesser negative environmental impact compared to conventional energy sources. Amongst the pressing challenges today is finding solutions on efficient solar and wind energy production. It is imperative to work out the optimum location of RESs before installing them. This can significantly improve performance and establishes the foundation for studying both solar and wind power in a site selection problem. This study aims to determine potential locations for wind and solar photovoltaic (PV) energy plants installation using one of the multi-criteria decision-making (MCDM) methods, the analytical hierarchy process (AHP), and a geographic information system (GIS) within the Central North Regional Electricity Distributor (CENORED) supply area. Combining GIS with MCDM results in a powerful technique for selecting potential sites, since GIS provides effective analysis, manipulation, and visualization of geospatial data, whereas MCDM provides consistent weighing of criteria. In the evaluations of the location: topographical, environmental, climatic and regulations constraints were considered as factors that may facilitate or hinder the deployment of solarwind energy power plants. For solar PV energy plant, the highest potential areas are in the north-west, south-west and study area's southern regions, whereas for the wind power plant, only the northwest part is a highly suitable location for wind energy plants installation. These findings can be used to determine most favourable location of interest for solar PV and wind power plant development or to support the integration of electrical grid expansion and off-grid electrification strategies

Methodology for avionics integration optimisation

Every state-of-art aircraft has a complex distributed systems of avionics Line Replaceable Units/Modules (LRUs/LRMs), networked by several data buses. These LRUs are becoming more complex because of the increasing number of new avionics functions need to be integrated in an avionics LRU. The evolution of avionics data buses and architectures have moved from distributed analogue and federated architecture to digital Integrated Modular Avionics (IMA). IMA architecture allows suppliers to develop their own LRUs/LRMs capable of specific features that can then be offered to Original Equipment Manufacturers (OEMs) as Commercial-Off-The-Shelf (COTS) products. In the meantime, the aerospace industry has been investigating new solutions to develop smaller, lighter and more capable avionics LRUs to be integrated into avionics architecture. Moreover, the complexity of the overall avionics architecture and its impact on cable length, weight, power consumption, reliability and maintainability of avionics systems encouraged manufacturers to incorporate efficient avionics architectures in their aircraft design process. However, manual design cannot concurrently fulfil the complexity and interconnectivity of system requirements and optimality. Thus, developing computer-aided design (CAD), Model Based System Engineering (MBSE) tools and mathematical modelling for optimisation of IMA architecture has become an active research area in avionics systems integration. In this thesis, a general method and tool are developed for optimisation of avionics architecture and improving its operational capability. The tool has three main parts including a database of avionics LRUs, mathematical modelling of the architectures and optimisation algorithms. The developed avionics database includes avionics LRUs with their technical specifications and operational capabilities for each avionics function. A MCDM method, SAW, is used to quantify and rank each avionics LRU’s operational capability. Based on the existing avionics LRUs in the database and aircraft level avionics requirements two avionics architectures are proposed i.e. AFCS architecture (SSA) and avionics architecture (LSA). The proposed avionics architectures are then modelled using mathematical programming. Further, the allocation of avionics LRUs to avionics architecture and mapping the avionics LRUs to their installation locations are defined as an assignment problem in Integer Programming (IP) format. The defined avionics architecture optimisation problem is to optimise avionics architecture in terms of mass, volume, power consumption, MTBF and operational capability. The problems are solved as both single-objective and multi-objective optimisation using the branch-and-bound algorithm, weighted sum method and Particle Swarm Optimisation (PSO) algorithm. Finally, the tool provides a semi-automatic optimisation of avionics architecture. This helps avionics system architects to investigate and evaluate various architectures in the early stage of design from an LRU perspective. It can also be used to upgrade a legacy avionics architecture.Aerospac