مجله علوم و فناوری های پدافند نوین
سال چهارم شماره 1 (پیاپی 11، بهار 1392)

In the present paper, a new adaptive steganographic method has been proposed to embed secret data in an image. Proposed method allows the user to set algorithm parameters in a way that reducing the distortion resulted from stegnanography in the image in spite of embedding secret data in all pixels of image, considering size of secret data required for sending to destination. These parameters can be also used as a secret steganographic key. In this method, considering the human vision system, more secrete data bits are embedded in edged areas of image than in its smooth ones. In the proposed method, blocks are classified into different groups based on the extent of local complexity of pixels, and the capacity of each group is determined by total size of secret data. This method is also resistant to statistical and histogram steganalysis attack.

Shelters and underground spaces are among the options to come out from the crisis situation in natural and military disasters. In recent years, from the passive defense viewpoint, buried structures have been considered as safe structures against the air and missile attacks. From this perspective, these structures are a part of the main facilities in peacetime and are important factors to save lives in the event of a natural disaster and during the wars. In this study, the effects of grouting around a tunnel to reduce the impact of blast loads on the tunnel structure is evaluated by the numerical modeling software FLAC 2D, in a part of line 7 of the Tehran subway. Intended specifications for the soil around the tunnel, are the results of uniaxial compression tests conducted on some soil samples made from the Tehran alluvial type C. Finally by carrying out an interpolation in the MATLAB software, two equations have been derived to predict displacement and stresses of the tunnel lining (due to the various parameters of the soil, tunnel and bomb) in order to use in the initial stages of tunnel designing for this purpose.

Anomaly detection refers to the problem of finding patterns in data that do not conform to expected behavior. Development of advanced anomaly detection and failure diagnosis technologies for satellite launch vehicle (SLV) is a quite significant issue in the aerospace industry, because the space environment is harsh, distant and uncertain.Current SLV health monitoring and fault diagnosis practices involve around-the-clock limit-checking or simple trend analysis using text or graphical displays on large amount of telemetry data. This procedure, which requires large numbers of human experts, is of course cumbersome and time-consuming. Furthermore, humans are not always able to recognize anomalous situations. In this paper, a systematic and transparent diagnostic methodology will be proposed and developed within intelligent anomaly detectioon framework for SLV health monitoring. Experimental results show that the proposed method is capable of characterizing and monitoring interactions between multiple spacecraft parameters and can provide additional insight and valuable decision support for controllers and engineers.