Image edge detection is a process of locating the edge of an image which is important in finding the approximate absolute gradient magnitude at each point I of an input grayscale image. The problem of getting an appropriate absolute gradient magnitude for edges lies in the method used. The Sobel operator performs a 2-D spatial gradient measurement on images. Transferring a 2-D pixel array into statistically uncorrelated data set enhances the removal of redundant data, as a result, reduction of the amount of data is required to represent a digital image. The Sobel edge detector uses a pair of 3 x 3 convolution masks, one estimating gradient in the x-direction and the other estimating gradient in y-direction. The Sobel detector is incredibly sensitive to noise in pictures, it effectively highlight them as edges. Hence, Sobel operator is recommended in massive data communication found in data transfer.

Security breaches have been observed in different dimensions in mobile payment system. The violation of user's privacy is a common phenomenon in mobile payment transactions. This study presents an improved security scheme for a mobile payment system using elliptic curve cryptography over a binary field with International Mobile Equipment Identity to ensure higher security. The scheme uses a payment gateway for registration and maps all input text to elliptic curve points using ASCII values. Payment details are stored on the gateway, which is encrypted but decrypted only with merchant's decryption key. The proposed scheme was evaluated in terms of key size, security strength, computational power, memory capacity, encryption and decryption time and mobile phone battery. The result shows that the scheme provides integrity, confidentiality and privacy. The result also shows that the proposed scheme is time-efficient and computationally inexpensive for resourceconstrained environment like mobile payment system.

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The outbreak of coronavirus pandemic has led to different regulations and changed the usual way of doing things. Considering the level of technology in Africa society before the outbreak of the epidemic many activities, including classroom teaching and learning were affected. This paper examines virtual learn-ing as an unavoidable pedagogical model for learning during the COVID-19 pandemic. A cross-sectional study was conducted by adopting the Technology Acceptance Model. Data were obtained from an online survey of 543 respondents and analyzed. Regression of Partial Least Squares (PLS) was used for modeling and hypothesis testing. The results revealed that perceived usefulness, perceived ease of use, regulatory compliance, and implementation context significantly affect educators' and learners' attitudes towards adopting virtual learning for learning. Subsequently, regulatory compliance had the most substantial influence on educators' and learners' attitudes towards adopting virtual learning for learning during the COVID-19 outbreak. This study established that the adoption of virtual learning has enhanced learning during the coronavirus pandemic lock-down, and the process would also continue after the pandemic. Virtual learning has provided the classroom experience for learners and educators.

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