A Distributed Approach for Networked Flying Platform Association with Small Cells in 5G+ Networks

The densification of small-cell base stations in a 5G architecture is a promising approach to enhance the coverage area and facilitate the ever increasing capacity demand of end users. However, the bottleneck is an intelligent management of a backhaul/fronthaul network for these small-cell base stations. This involves efficient association and placement of the backhaul hubs that connects these small-cells with the core network. Terrestrial hubs suffer from an inefficient non line of sight link limitations and unavailability of a proper infrastructure in an urban area. Seeing the popularity of flying platforms, we employ here an idea of using networked flying platform (NFP) such as unmanned aerial vehicles (UAVs), drones, unmanned balloons flying at different altitudes, as aerial backhaul hubs. The association problem of these NFP-hubs and small-cell base stations is formulated considering backhaul link and NFP related limitations such as maximum number of supported links and bandwidth. Then, this paper presents an efficient and distributed solution of the designed problem, which performs a greedy search in order to maximize the sum rate of the overall network. A favorable performance is observed via a numerical comparison of our proposed method with optimal exhaustive search algorithm in terms of sum rate and run-time speed.Comment: Submitted to IEEE GLOBECOM 2017, 7 pages and 4 figure

ARTIFICIAL INTELLIGENCE (AI) BASED CONTRACTS PROCUREMENT: EXAMINING THE INFLUENCE OF BIG DATA, MACHINE LEARNING, INTERNET OF THINGS, EMPLOYEE SKILLS & RESOURCES AND LEADERSHIP ON PROCUREMENT COST REDUCTION

AI is not a single technology but a collection of diverse, powerful technologies that simulate human intelligence and invest in the power of the digital brain. Using AI techniques, big data analytics can be utilized to discover patterns and a wealth of knowledge. Consequently, this study aims to examine the impact of big data, machine learning, personnel, IoT skills, and artificial intelligence in procurement contracts that impact cost savings and improve enterprise performance and productivity by automating previously labor-intensive processes or tasks. One hundred fifty employees from the procurement department of Saudi Organizations were surveyed to collect data. The study's findings demonstrated the importance of big data analytics, the Internet of Things, and digital skills for employees. On the other hand, (machine learning and autonomous driving) had no significant impact on cost reduction

Heat and mass transfer analysis of MHD nanofluid flow in a rotating channel with slip effects

An investigation has been carried out to present the hydro-magnetic three-dimensional flow of a nanofluid in a rotating channel. Simultaneous effects of energy and concentration of the nanoparticles have been considered and discussed. Velocity, thermal and concentration slip conditions are utilized in order to make the analysis more interesting. Brownian motion and thermophoresis effects are analyzed in order to discuss the nanofluids for the rotating flow situations. The mathematical modeling is performed for the laws of conservation of mass, momentum, energy and mass fraction profiles. The computations are made numerical and the obtained results are presented graphically and numerically in details

Rheology of the Cu-H2O nanofluid in porous channel with heat transfer: multiple solutions

Dynamics of nanofluid comprising a base fluid (water) with copper (Cu) nanoparticles have been considered in channel with porous walls under magnetic field influence. The channel walls are considered to be permeable in order to analyze the wall mass transfer phenomenon. Relevant mathematical modelling has been performed and the derived PDEs are converted into coupled nonlinear ODEs by using suitable transformations. Computations have been made numerically by employing the shooting technique. It is noted that multiple solutions occur for the variation of suction Reynolds number, solid volume fraction and magnetic parameters which are interpreted in detail

Association of networked flying platforms with small cells for network centric 5G+ C-RAN

5G+ systems expect enhancement in data rate and coverage area under limited power constraint. Such requirements can be fulfilled by the densification of small cells (SCs). However, a major challenge is the management of fronthaul links connected with an ultra dense network of SCs. A cost effective and scalable idea of using network flying platforms (NFPs) is employed here, where the NFPs are used as fronthaul hubs that connect the SCs to the core network. The association problem of NFPs and SCs is formulated considering a number of practical constraints such as backhaul data rate limit, maximum supported links and bandwidth by NFPs and quality of service requirement of the system. The network centric case of the system is considered that aims to maximize the number of associated SCs without any biasing, i.e., no preference for high priority SCs. Then, two new efficient greedy algorithms are designed to solve the presented association problem. Numerical results show a favorable performance of our proposed methods in comparison to exhaustive search.Comment: Submitted to IEEE PIMRC 2017, 7 pages and 5 figure

A Novel Feature Extraction and Fault Detection Technique for the Intelligent Fault Identification of Water Pump Bearings

The reliable and cost-effective condition monitoring of the bearings installed in water pumps is a real challenge in the industry. This paper presents a novel strong feature selection and extraction algorithm (SFSEA) to extract fault-related features from the instantaneous power spectrum (IPS). The three features extracted from the IPS using the SFSEA are fed to an extreme gradient boosting (XBG) classifier to reliably detect and classify the minor bearing faults. The experiments performed on a lab-scale test setup demonstrated classification accuracy up to 100%, which is better than the previously reported fault classification accuracies and indicates the effectiveness of the proposed method

Islamic capitalism: an approaching truth or an expectant panorama for Islamic finance – a case of Pakistan and Malaysia

The investigation of future capitalism in the wake of Islam is rather complicated. The difference of interests and difference of opinions between secular scholars and fiqh scholars can stymie the progress of innovation. Nevertheless, a harmony between their intellectual views can prove to be a boon for encouraging Islamic financial elements. This paper scrutinizes an alternative capitalist structure as one of the basic and fundamental key elements for Islamic finance. In this study, interview-based multi case-study method is used, which is based on qualitative approach. This study concludes that Islam promotes the concept of risk sharing in trading and other financial activities, which may lead to lessen the burden on an individual. However, external factors are playing major roles in both of the countries as conventional system is very strong around the globe

The process of risk management: sketching the providers of Islamic micro- finance

With the assistance of using comparative analysis and interviews, we have formulated study on two discreet types of Islamic microfinance institutions: Non-government organizations & Commercial financial institutions. This has relatively been done with the help of taking into consideration the systematic disbursement and repayment methods. Conclusively, both of the companies were susceptible to Shariah risk, operational risk and credit risk. Furthermore, company B has a well renowned goodwill in the market therefore, it is prone to reputational risk as well