Information and communication Technology (ICT) is basically making use of ICT tool to store and retrieves information. It plays an important role in growing and maintaining country's economic growth. Currently, the old system of classroom teaching and learning of ICT is changing and students in Ghana are becoming more technology oriented. Therefore, in this changing learning environment, it's important one thinks of the latest technologies to incorporate in the teaching and learning of ICT. One of the latest technologies prevailing nowadays is cloud computing. By sharing IT services as platform-based, software-based and infrastructure-based in the cloud, educational institutions in Ghana can now out-source non-core services and better concentrate on offering students, teachers, faculty and other staff the essential tools to help them succeed.
This paper presents a digital image watermarking scheme in the frequency domain for colour images. The algorithm was developed using the digital wavelet transform together with fractal encryption. A host image was first transformed into a frequency domain using the discrete wavelet transform after which a binary watermark was permuted and encrypted with a fractal generated from the watermark and a random key. The encrypted watermark is then embedded into the host image in the frequency domain to form a watermarked image. The algorithm's performance was examined based on the image quality of the watermarked image using peak signal to noise ratio. A perceptual metrics called the structural similarity index metric was further used to examine the structural similarity of the watermarked image and the extracted watermark. Again, the normalised cross-correlation was introduced to further assess the robustness of the algorithm. Our algorithm produced a peak signal to noise ratio of 51.1382dB and a structural similarity index of 0.9999 when tested on colour images of Lena, baboon and pepper indicating the quality of the watermarked images produced and hence indicates a higher imperceptibility of the proposed algorithm. The extracted watermark also had a structural similarity of 1 and a normalised cross correlation of 1 indicating a perfect similarity between the original watermark and the extracted watermark hence shows a higher performance of the proposed algorithm. The algorithm also showed a very good level of robustness when various attacks such as Gaussian noise, Poisson noise, salt and pepper noise, speckle noise and filtering were applied.
Contact tracing has become one of the most useful tools for fighting the novel Corona Virus (COVID-19) pandemic worldwide. The underlining philosophy of contact tracing is determining people who have been in contact with infected persons and thus isolate them from becoming agents of onward transmission of the virus. Slow tracing of contacts and inconsistent or inaccurate information provided by patients usually leads to the spread of the virus along a trajectory at the healthcare systems' blindside. This has led to the proposal of app-based contact tracing solutions. This paper proposes an SQL-based framework that transforms simple interaction data entries into interaction graphs and applies graph theory to prioritize the contact tracing process. The framework returns nodes or individual IDs together with values called Risk_Points to enable individuals' selection for isolation and treatment. Results on simulated data show that the proposed framework can help slow the virus's rate of transmission.
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