Reviews

Microwave propagation in dust storms has become an active research field. Dust particles’ permittivity property is an important component with its applications in microwave signal propagation. Permittivity values, determined using different techniques and methods, usually serve as input variables to computation of electromagnetic scattering. They are also used to determine propagation impairments such as microwave attenuation, phase rotation, cross polarization, antenna’s accretion and beam shift effects thereby making accurate knowledge of dust permittivity in the microwave frequency range very important. This paper has investigated and presented a review of some related works on the permittivity of dust particles. The current state of knowledge of dust particles permittivity is presented by examining the variety of techniques and methods, their strengths and limitations. The permittivity properties of dust samples are a function of frequency, moisture content and chemical composition. Identical chemical composition of dust sample gives identical permittivity, while different chemical compositions give a different permittivity property. Furthermore, gaps in knowledge that need to be covered are identified and the projected path and outlook of dust particle’s permittivity property is also presented.

Exploratory data analysis (EDA) is often a necessary task in uncovering hidden patterns, detecting outliers, and identifying important variables and any anomalies in data. Furthermore, the approach can be used to gain insights by modelling the dataset through graphical representations. In this paper, we propose an exploratory framework for analysing a road traffic accidents real-life dataset using graphical representations and incorporating dimensionality reduction methods. Both Principal component and Linear discriminant analyses are performed on the dataset and the resulting performance metrics reveal some comprehensive insights of the road traffic accident patterns. The investigation also revealed which road traffic factors contribute more significantly to the events. Classification results were generated after applying the dimensionality reduction methods to the dataset and show that the application of Linear discriminant analysis dimensionality reduction together with Naïve Bayes classification performed better as compared to the other approaches for the dataset.

Ghana currently has no future energy strategic plan or framework for its generation system apart from the Energy Policy developed by the Energy Commission (EC). The EC based its research on the year 2000 parameters and estimated the energy system up to 2020, which cannot entirely address the current challenges facing the energy sector. The main objective of this paper is to develop an integrated energy planning (IEP) framework for Ghana as a guideline for addressing energy challenges, to promote energy efficiency in both demand and transmission, CO ₂ emissions reduction, and the utilization of renewable energy sources (RES). The methods used are content analysis, multiple case study, and procedure for IEP framework development. The primary computer tool used for the analysis and future energy projections was Long-range Energy Alternative Planning. The demand forecast was performed using key input parameters, including Gross Domestic Product, population change and urbanization. The overall results of this study suggest 40% of non-conventional renewable energy resources into the country’s energy mix, proposed energy efficiency promotion in both demand and transmission, and the utilization of RES integration to save the nation up to about 40% CO ₂ emissions reduction. The paper recommends strategies to reduce losses in the transmission and distribution systems of Ghana. The paper again recommends the revenues accrued from the carbon tax for maintenance work on the existing equipment, and finally, an integrated energy planning framework was developed to serve as a roadmap for Ghana’s energy sector up to the year 2050.

Several heterogeneous, intelligent, and distributed devices can be connected to interact with one another over the Internet in what is termed internet of things (IoT). Also, the concept of IoT can be exploited in the industrial environment for enhancing the production of goods and services and for mitigating the risk of disaster occurrences. This application of IoT for enhancing industrial production is known as industrial IoT (IIoT). Emergent configuration (EC) is a technology that can be adopted to enhance the operation and collaboration of IoT connected devices in order to improve the efficiency of the connected IoT systems for maximum user satisfaction. To meet user goals, the connected devices are required to cooperate with one another in an adaptive, interoperable, and homogeneous manner. In this paper, a survey of the concept of IoT is presented in addition to a review of IIoT systems. The application of ubiquitous computing-aided software define networking (SDN)-based EC architecture is propounded for enhancing the throughput of oil and gas production in the maritime ecosystems by managing the exploration process especially in emergency situations that involve anthropogenic oil and gas spillages.

Ijiga, O.E.; Malekian, R.; Chude-Okonkwo, U.A.K. Enabling Emergent Configurations in the Industrial Internet of Things for Oil and Gas Explorations: A Survey. Electronics 2020, 9, 1306. https://doi.org/10.3390/electronics9081306