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Sourcing for an alternative to the liquid electrolyte in dye-sensitized solar cells (DSSCs) have been the subject of interest in the photovoltaic horizon. Herein, we reported by means of simulation, the performance of dye-sensitized solar cell by replacing the liquid electrolyte with a copper (I) thiocyanate (CuSCN) hole conductor. The study was carried out using Solar Capacitance Simulation Software (SCAPS) which is based on poisson and continuity equations. The simulation was done based on an n-i-p proposed architecture of FTO/TiO2/N719/CuSCN/Pt. The result of the initial device gave a Power Conversion Efficiency (PCE), Fill Factor (FF), Short Circuit Current Density (Jsc) and Open Circuit Voltage (Voc) of 5.71 %, 78.32 %, 6.23 mAcm-2, and 1.17 V. After optimizing input parameters to obtain 1×109 cm-2 for CuSCN/N719 interface defect density, 280 K for temperature, 1.0 μm for N719 dye thickness, 0.4 μm for TiO2 thickness, Pt for metal back contact, and 0.2 μm for CuSCN thickness, the overall device performance of 7.379 % for PCE, 77.983 % for FF, 7.185 mAcm-2 for Jsc and 1.317 V for Voc were obtained. When compared with the initial device, the optimized results showed an enhanced performance of ~ 1.29 times, 1.15 times, and 1.13 times in PCE, Jsc, and Voc over the initial device. The results obtained are encouraging and the findings will serve as a baseline to researchers involved in the fabrication of novel high-performance solid-state DSSCs to realize its appealing nature for industry scalability.

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The application of machine learning algorithms to the detection of fraudulent credit card transactions is a challenging problem domain due to the high imbalance in the datasets and confidentiality of financial data. This implies that legitimate transactions make up a high majority of the datasets such that a weak model with 99% accuracy and faulty predictions may still be assessed as high-performing. To build optimal models, four techniques were used in this research to sample the datasets including the baseline train test split method, the class weighted hyperparameter approach, and the undersampling and oversampling techniques. Three machine learning algorithms were implemented for the development of the models including the Random Forest, XGBoost and TensorFlow Deep Neural Network (DNN). Our observation is that the DNN is more efficient than the other 2 algorithms in modelling the under-sampled dataset while overall, the three algorithms had a better performance in the oversampling technique than in the undersampling technique. However, the Random Forest performed better than the other algorithms in the baseline approach. After comparing our results with some existing state-of-the-art works, we achieved an improved performance using real-world datasets.

Subsequent to the launch of the first Nigerian satellite into space in September 2003, the National Space Research and Development Agency (NASRDA), Abuja, Nigeria, has demonstrated a peaceful use of outer space through the commercial, educational, humanitarian and governmental applications of its four satellites successfully launched so far. The nation has also maintained a sustainable national development since achieving this feat by joining other nations in space operations. The satellite operations are carried out indigenously by Nigerian Engineers and Scientist from the Mission Control Ground Station (MCGS), Abuja, Nigeria. Consequently, three remote sensing satellites; NigeriaSat-1, NigeriaSat-X and NigeriaSat-2 and one communications satellite; NIGCOMSAT-1R, have answered numerous questions on the status of space operations and the peaceful use of outer space. With the successful completion of its mission lifetime, NigeriaSat-1 was de-orbited after about nine years of useful and peaceful satellite operations. During its mission lifetime, it responded to both local and international disasters while in the Disaster Monitoring Constellation (DMC) including sustainable development campaigns initiated jointly or individually for satellites in the constellation such as Hurricane Katrina and the development of a national resource inventory showing land-use/land cover mapping at 1:50,000 etc. In continuation of this recorded achievements, NigeriaSat-X and NigeriaSat-2 which are advanced Earth Observation (EO) micro-satellites equipped with enhanced imaging performance for improved capability and applications have equally witnessed improved satellite operations from the Abuja MCGS. Also, NIGCOMSAT-1R has been applied in tele-medicine and tele-conferencing, data transfer, internet services, e-library etc.In the course of our satellite operations, useful lessons have been learnt in the management and operations of more than one satellite from a single ground-station for the remote sensing satellites. Therefore, in this paper, we review and share our operational experiences, achievements and future direction on our quest into space for sustainable development through the use of our remote sensing and communications satellites.