Although spreadsheets have been around for over thirty years, we are only just realising their importance. Most companies use spreadsheets in their decision-making processes, but rarely employ any form of testing. This paper shows how an "all-uses" test adequacy technique can be integrated into Microsoft's Excel. The modular technique adopted makes the implementation spreadsheet package independent. It also includes a user interface, to assist developers specify test cases and a technique for recording test cases and session information.

The aim of this research is to propose an extended mean value cloning algorithm with automatic trimap generation and accurate alpha matting. This implementation improves the visualization accuracy of the merged video by reducing the discolored and smudging artefacts of the remote surgeon’s boundary. It also makes the merge robust for the illumination changes by taking less processing time in real time surgery. The proposed system uses automatic trimap generation from the source video for accurate foreground extraction. Extended mean value cloning with gradient mixing is then applied for the cloning with optimized alpha matting for accurate and realistic video composition. The proposed system improved the visualization accuracy by providing almost 99.7% visibility of the pixels compared to the state-of-the-art solution, which provides 99.1% visibility of pixels. The overlay error was reduced from 0.93 mm to 0.63 mm. The processing time was also reduced. The proposed solution processe...

Background and Aim: Health care monitoring is increasing day by day as peoples are more concerned with their health these days. Everyone needs a convenient way to be fit these days and will increase more day by day in the future. Limitations in the interoperability of the devices, power consumption of devices and accuracy of data are the major challenge in this field of research. This research aims to provide integration of cloud and IoT together for the management and provision of sensors using cloud technology together leveraging the web application to manage the sensor data, web-based system for monitoring and cloud-based storage for the historical use of data. Methodology: In this paper, we propose Data, Data processing and transmission, Monitoring, and Visualization as four main components and define our taxonomy as DPMV (Data, Processing, Monitoring and Visualization) required for Cloud-IoT healthcare monitoring system. We proposed this component to make the system working systematically. A Cloud-IoT healthcare monitoring system will help doctors or caretakers to provide effective medical diagnosis and prevention of disease in the early stage with the help of combining cutting edge technologies. This system will also provide alert through an alert generation mechanism in emergency cases and also sends messages regarding alerts. Results: We have evaluated the Cloud-IoT healthcare monitoring system based on its data accuracy and system performance. We demonstrate the utility of the Cloud-IoT healthcare monitoring system by defining the classification table of the previous 25 state-of-art journal papers in the domain of monitoring for elderly people. Conclusion: Finally, our classification shows that readers will be able to know the benefits of using Cloud-IoT in the healthcare field. Also, Reader will be able to understand future gaps, classification of works and evaluation/validation of 25 literature reviews.

Health care monitoring is increasing day by day as peoples are more concerned with their health these days. Everyone needs a convenient way to be fit these days and will increase more day by day in the future. Limitations in the interoperability of the devices, power consumption of devices and accuracy of data are the major challenge in this field of research. This research aims to provide integration of cloud and IoT together for the management and provision of sensors using cloud technology together leveraging the web application to manage the sensor data, web-based system for monitoring and cloud-based storage for the historical use of data. Methodology: In this paper, we propose Data, Data processing and transmission, Monitoring, and Visualization as four main components and define our taxonomy as DPMV (Data, Processing, Monitoring and Visualization) required for Cloud-IoT healthcare monitoring system. We proposed this component to make the system working systematically. A Cloud-IoT healthcare monitoring system will help doctors or caretakers to provide effective medical diagnosis and prevention of disease in the early stage with the help of combining cutting edge technologies. This system will also provide alert through an alert generation mechanism in emergency cases and also sends messages regarding alerts. Results: We have evaluated the Cloud-IoT healthcare monitoring system based on its data accuracy and system performance. We demonstrate the utility of the Cloud-IoT healthcare monitoring system by defining the classification table of the previous 25 stateof-art journal papers in the domain of monitoring for elderly people. Conclusion: Finally, our classification shows that readers will be able to know the benefits of using Cloud-IoT in the healthcare field. Also, Reader will be able to understand future gaps, classification of works and evaluation/validation of 25 literature reviews.

Results of a study to determine if patients attending sexually transmitted diseases (STD) clinics are at high risk to human immunodeficiency virus (HIV) infection are presented. The 206 patients who attended the STD clinic at the Maiduguri General Hospital consisted of 200 males ...