An Approach to Analyze Physical Memory Image File of Mac OS X

Memory analysis is one of the key techniques in computer live forensics. Especially,the analysis of a Mac OS X operating system's memory image file plays an important role in identifying the running status of an apple computer. However,how to analyze the image file without using extra"mach-kernel"file is one of the unsolved difficulties. In this paper,we firstly compare several approaches for physical memory acquisition and analyze the effects of each approach on physical memory. Then,we discuss the traditional methods for the physical memory file analysis of Mac OS X. A novel physical memory image file analysis approach without using extra"mach-kernel"file is proposed base on the discussion. We verify the performance of the new approach on Mac OS X 10. 8. 2. The experimental results show that the proposed approach is simpler and more practical than previous ones.

Physical informed memory networks for solving PDEs:implementation and applications

With the advent of physics informed neural networks(PINNs),deep learning has gained interest for solving nonlinear partial differential equations(PDEs)in recent years.In this paper,physics informed memory networks(PIMNs)are proposed as a new approach to solving PDEs by using physical laws and dynamic behavior of PDEs.Unlike the fully connected structure of the PINNs,the PIMNs construct the long-term dependence of the dynamics behavior with the help of the long short-term memory network.Meanwhile,the PDEs residuals are approximated using difference schemes in the form of convolution filter,which avoids information loss at the neighborhood of the sampling points.Finally,the performance of the PIMNs is assessed by solving the Kd V equation and the nonlinear Schr?dinger equation,and the effects of difference schemes,boundary conditions,network structure and mesh size on the solutions are discussed.Experiments show that the PIMNs are insensitive to boundary conditions and have excellent solution accuracy even with only the initial conditions.

Exercise preconditioning exhibits neuroprotective effects on hippocampal CA1 neuronal damage after cerebral ischemia

Recent evidence has suggested the neuroprotective effects of physical exercise on cerebral ischemic injury. However, the role of physical exercise in cerebral ischemia-induced hippocampal damage remains controversial. The aim of the present study was to evaluate the effects of pre-ischemia treadmill training on hippocampal CA1 neuronal damage after cerebral ischemia. Male adult rats were randomly divided into control, ischemia and exercise ＋ ischemia groups. In the exercise ＋ ischemia group, rats were subjected to running on a treadmill in a designated time schedule（5 days per week for 4 weeks）. Then rats underwent cerebral ischemia induction th rough occlusion of common carotids followed by reperfusion. At 4 days after cerebral ischemia, rat learning and memory abilities were evaluated using passive avoidance memory test and rat hippocampal neuronal damage was detected using Nissl and TUNEL staining. Pre-ischemic exercise significantly reduced the number of TUNEL-positive cells and necrotic cell death in the hippocampal CA1 region as compared to the ischemia group. Moreover, pre-ischemic exercise significantly prevented ischemia-induced memory dysfunction. Pre-ischemic exercise mighct prevent memory deficits after cerebral ischemia through rescuing hippocampal CA1 neurons from ischemia-induced degeneration.

Study on Preventive Software Rejuvenation Policy for Two Kinds of Bugs

A new preventive software rejuvenation policy is proposed in this paper. This technique is implemented when additive consumption of physical memory has reached some level. Using the theory of cumulative damage process, two models are given for two kinds of bugs. For the first model, aging-related bug is considered only and consumption of physical memory could be known by tests made at periodic times, optimal preventive rejuvenation policy is analytically derived and numerical example is given. As an extended preventive software rejuvenation policy, Heisenbug and aging-related bug are considered meanwhile in the second model.