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The purpose of the paper is to define the best deployment alternatives for a public protection and disaster relief (PPDR) mobile network service – the implementation alternatives being either a dedicated network, a commercial network or a hybrid of the two network types. The selection criteria are based on the social benefits that the PPDR mobile service is expected to bring to society. The critical parameters are population density and service availability, which both directly relate to the socioeconomic benefits achieved by providing broadband (BB) mobile services in various demographic areas.

A causal loop model has been developed to define the socioeconomic benefits of the PPDR network, the parameters being population density, service availability, socioeconomic value of the service and the costs of the network. The network solution alternatives are studied using the Finnish PPDR network as a reference – analysing various areas of the country with differing population densities from remote, rural and more densely populated suburban and urban areas.

Socioeconomic value is a common measure for assessing the value of governmental investments; population density has a strong impact on the optimum deployment alternatives as the socioeconomic value is directly proportional to this variable. The flat nationwide fee of the mobile users means that the users are subsidised in sparsely populated areas – and overcharged in densely populated areas. This is the main reason why the commercial network seems to be most feasible in rural areas, whereas the dedicated network works best in urban areas. Based on the case study, the commercial network is most preferable up to the point when the population density reaches 50-125 persons/km². After that point, the dedicated network becomes more appropriate. Proposals are being made to improve the availability of the commercial networks enabling them to serve as a PPDR network: ensuring priority functionality and a protected power supply; allowing PPDR subscribers the exclusive use of one of the 700 MHz spectrum bands in restricted, critical areas; and extending use of the existing narrowband PPDR network in areas where communication availability is crucial.

On the one hand, the financing of BB PPDR mobile networks is an unresolved issue in many countries. On the other hand, the ability of commercial BB networks to provide better quality of service is improving, making viable the alternative to subscribe for radio service from a commercial operator. Therefore, the feasibility study on how to provide an optimum mobile BB service for PPDR organisations is of real value at this time.

Optimization involves changing the input parameters of a process that is experimented with different conditions to obtain the maximum or minimum result. Increasing interest is shown by antenna researchers in finding the optimum solution for designing complex antenna arrays which are possible by optimization techniques.

Design of antenna array is a significant electro-magnetic problem of optimization in the current era. The philosophy of optimization is to find the best solution among several available alternatives. In an antenna array, energy is wasted due to side lobe levels which can be reduced by various optimization techniques. Currently, developing optimization techniques applicable for various types of antenna arrays is focused on by researchers.

In the paper, different optimization algorithms for reducing the side lobe level of the antenna array are presented. Specifically, genetic algorithm (GA), particle swarm optimization (PSO), ant colony optimization (ACO), cuckoo search algorithm (CSA), invasive weed optimization (IWO), whale optimization algorithm (WOA), fruitfly optimization algorithm (FOA), firefly algorithm (FA), cat swarm optimization (CSO), dragonfly algorithm (DA), enhanced firefly algorithm (EFA) and bat flower pollinator (BFP) are the most popular optimization techniques. Various metrics such as gain enhancement, reduction of side lobe, speed of convergence and the directivity of these algorithms are discussed. Faster convergence is provided by the GA which is used for genetic operator randomization. GA provides improved efficiency of computation with the extreme optimal result as well as outperforming other algorithms of optimization in finding the best solution.

The originality of the paper includes a study that reveals the usage of the different antennas and their importance in various applications.

Nowadays, communications, products, services and costs are customized through the internet technology. The main theory to continue competitiveness in the organizations is customer relationship management (CRM). CRM enables organizations to efficiently interact with customers and gather, store and examine their data for providing a complete view of them. On the other hand, the subject of cloud computing has increasingly become the bridge for the success of the CRM implementation. Therefore, this study aims to investigate the impact of cloud computing (new cloud facility, knowledge of information technology (IT), cloud security and cost) on the success of CRM systems.

The model and the questioners-based data are analyzed using the Smart PLS 3.0. The data were gathered based on 80 employees of three main agricultural companies in Iran.

The obtained results have indicated that all of the considered factors, new cloud facilities, knowledge of IT, cloud security and cost, play an important role in CRM systems’ success. Also, the evaluation and examination of the consistency and validity of the model are performed through the structural equation model.

First, the authors have conducted a study in a single region. It cannot be guaranteed that the results can be generalized to other regions. Second, for this cross-sectional study, the research design was conducted that showed constant relationships between variables. The research done for this study is cross-sectional. Third, because of time and financial restrictions, the authors have gathered data using a sample from a single location.

Proposing a new model for investigating of the impact of cloud computing (new cloud facility, knowledge of Information Technology (IT), cloud security and cost) on the success of CRM systems is the main originality of this paper.