Traditionally, a system of survey activities is often conducted as a separate process, apart from the target system, which includes explicit invitations to a predefined or randomly selected group of users, collection of data from submitted forms and compilation into various analytical reports for decision making. Such a process is expensive and time consuming. Also, since traditional surveys are often conducted after the system usage, the users' experiences with the system become somewhat detached in responding to survey invitations at a later time, causing the concentrations and interests to decrease during this period. So it is likely that they may overlook some vital areas in survey questionnaires where it is most expected for them to respond with pragmatic thoughts within the context of the system environment; thus, straying away from the actual purpose of the survey. To eliminate these difficulties, the integration capabilities of any computer-based system can be carefully utilized for accumulating system usage data, workflow path traversal, calculating various feature ranks, as well as lightweight feedbacks at users' own will while they are using the system. In addition, displaying significant real-time system usage statistics, as well as historical data at relevant areas in the system workflow enables the users to be more aware of the dynamicity of the system components, which implicitly encourages them to drop few responses to very simple questions while traversing through the system. In this paper, we propose a framework for an integrated survey mechanism for computer-based systems that is able to serve most of the purposes of conducting manual surveys for the assessment of the system itself, as well as its users.

Long term evolutionary needs for a system to be able to meet new and emerging requirements are often left unnoticed, since the complete picture is not apparently visible at the time of analysis. Therefore, over a long period of time, many of these systems become obsolete, because their lifecycles cannot be extended or are very expensive to re-engineer into a reusable system that could actually meet the new requirements. To overcome such difficulties, we present a methodology to build a wrapper-system based on the iterative Object-Process Modeling scheme. The purpose of the wrapper-system is to coordinate three stages of iteration: first, to collect the evolving factors from the system behavior; second, to update system state, and third, to apply necessary changes to the system to meet new requirements. Based on our analyses of the system usage activity logs and detailed update-request history of several projects over two to three years of time, we show that this iterative scheme can be effectively applied for architecting evolvable systems with longer life expectancy.

Automated surveillance systems have drawn much attention recently. For a surveillance system to operate and obtain credible sensing of a scenario, visual analysis is the most critical aspect. With an increasing expectation of acceptable outcomes from surveillance systems, light weight but fast visual analyses for producing authentic results are being greatly emphasized. In this paper, we present a new approach for detecting fast scene change in the sequentially captured photographs of a focused location. The system considers the images in RGB color format and analyzes all 3 color layers. In this method, the color value histograms of the images were compared to each other using a statistical procedure called ANOVA. We devised an approach that approximately identifies the locality of change in the scene. Various experimental outcomes based on this visual computation process have also been provided in this paper.

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