The paper provides a pre-stage of any data hiding method hiding message data in media data and a data extraction
method of extracting the hidden data, wherein message data is dispersively hidden in digital media data, such as images,
to prevent a third person from forging/modifying the message data easily. More specifically, the technique relates to a
data hiding method in which media data is expressed as a media array while message data is expressed as a message
array so that the array elements of the message array can be dispersively hidden in the media array randomly by
scrambling order of particular array element of the media array based on a private key. It needs to declare that the
proposed strategy aims only to enhance the watermark security. It is not used to improve the robustness of watermark.
This paper proposes a new method to enhance digital media protection over the internet. The major obstacle while developing a Digital Rights Management (DRM) system is the lack of available trusted viewers. Using the newly proposed method, the digital content is decrypted only when the client machine is under controlling and monitoring of the server. The client-side and server-side program works together to ensure the safety of the system. Any malicious action once detected, the server can order the client-side management program to close the digital media immediately.
A technique for high capacity data hiding in MPEG-2 streams is presented. The objective is to maximise the payload while keeping robustness and simplicity. Ancillary data is embedded in the host signal by modulating the quantized block DCT coefficients of I frames. To achieve robustness, each information bit is embedded in more than one DCT coefficient within each intra coded block. The extraction process is blind. Thus, the presented technique is suitable for side information delivery. The scheme is less complex than a complete decoding process followed by watermarking in the pixel domain and reencoding. Selected results of computer simulations are also reported
Immunoglobulin M (IgM) autoantibodies, as the early appearing antibodies in humoral immunity when stimulated by antigens, might be excellent biomarkers for the early detection of lung cancer (LC). We aimed to develop a multi-analyte integrative model combining IgM autoantibodies and a traditional tumor biomarker that could be a valuable and powerful auxiliary diagnostic tool and might improve the accuracy of early detection of lung adenocarcinoma (LUAD). A customized protein array based on cancer driver genes was constructed and applied in the discovery cohort consisting of 68 LUAD patients and 68 normal controls (NCs); 31 differentially expressed IgM autoantibodies were identified. The top 5 candidate IgM autoantibodies [based on the area under the receiver operating characteristic curve (AUC) ranking], namely, TSHR, ERBB2, survivin, PIK3CA, and JAK2, were validated in the validation cohort using enzyme-linked immunosorbent assay (ELISA), which included 147 LUAD samples, 72 lung squamous cell carcinoma (LUSC) samples, 44 small cell lung carcinoma (SCLC) samples, and 147 NCs. These indicators presented diagnostic capacity for LUAD, with AUCs of 0.599, 0.613, 0.579, 0.601, and 0.633, respectively ( p < 0.05). However, none of them showed a significant difference between the SCLC and NC groups, and only the IgM autoantibody against JAK2 showed a higher expression in LUSC than in NC ( p = 0.046). Through logistic regression analysis, with the five IgM autoantibodies and carcinoembryonic antigen (CEA), one diagnostic model was constructed for LUAD. The model yielded an AUC of 0.827 (sensitivity = 56.63%, specificity = 93.98%). The diagnostic efficiency was superior to that of either CEA (AUC = 0.692) or IgM autoantibodies alone (AUC = 0.698). Notably, the accuracy of this model in early-stage LUAD reached 83.02%. In conclusion, we discovered and identified five novel IgM indicators and developed a multi-analyte model combining IgM autoantibodies and CEA, which could be a valuable and powerful auxiliary diagnostic tool and might improve the accuracy of early detection of LUAD.
Digital rights management systems (DRMs) tend to solve two issues in rights protection of digital contents-access control and usage control. Access control concerns about how users access the contents, while usage control focuses on how users use it. In this paper, we present the key techniques to overcome the difficulties in implementation of a compatible and transparent-to-user DRM system on Linux platform. These techniques include hardware fingerprint encryption (HFE), Linux systemcall redirection and Windows inspection under XWindows system. Experiments with rendering programs such as OpenOffice-Writer (for doc file), OpenOffice-Express (for ppt file), gedit (for txt file), evince (for pdf file) and eog (for jpg file) have been carried out. The results shows that our techniques successfully solve the access control and usage control in DRM.
English writing is one of the most important but difficult part in College English Teaching. The development of computer and network has brought a good chance for the teaching reform. Making explorations into the necessity of autonomous learning of college English writing assisted by computer and network enables college English teachers and students to realize its importance and necessity and make full use of computer and network to assist autonomous learning of college English writing, thus improving students' English writing ability.
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