Volatile Data of a computer is a temporary and they are created when a computer system is running aka in operational condition. They are removed immediately when the system powered off. It is stored on the Random Access Memory (RAM) and other temporary storage units such as Registars of the Computer and not in the main storage partitions of Hard Drives. It could be emails related information, chats or browser history, running processes related information, unsaved data, clipboard contents etc. The analysis of volatile memory for extracting forensic artifacts is called Memory Forensic. Volatile Memory contains the most valuable information about running programs and instructions including running system processes, kernel drivers, loaded modules, executed commands, executable paths, active Network Connections, etc.

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This paper deals with the problem of modelling sub-county areas that are so small that county level forecasts cannot be used for policy purposes. Starting from a simple specification that relates demand for local goods and services to local and non-local income, a system of equations is developed that can be used as a satellite to a county model to forecast impacts of economic events at the town level. Regression coefficients for the equations are estimated using data at the one-digit SIC code level for a pooled sample of towns in Massachusetts. Model validation tests are reported. An example of an application is provided by simulating impacts of 500 new manufacturing jobs in a town within a county. Our approach yields simulation and forecasting results for both the town and the county. MALL AREA MODELLING HAS BEEN a topic of interest in S regional analysis for quite a long time. Economic base theory, which stipulates that a region's wealth increases when its resources are devoted to activities of greatest economic gain and the surplus is exported, has been used to estimate employment multipliers at various geographical levels (Tiebout 1962, Garrison 1972. Although the economic base model is an attractive planning tool for communities with low budgets and scarce data,