LEADER 01998nam 2200397 450 001 9910674393303321 005 20230629092132.0 035 $a(CKB)5400000000043753 035 $a(NjHacI)995400000000043753 035 $a(EXLCZ)995400000000043753 100 $a20230629d2022 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData Hiding and Its Applications $eDigital Watermarking and Steganography /$fDavid Megi?as, Wojciech Mazurczyk, Minoru Kuribayashi 210 1$aBasel :$cMDPI - Multidisciplinary Digital Publishing Institute,$d2022. 215 $a1 online resource (234 pages) 311 $a3-0365-2936-5 330 $aData hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others. 517 $aData Hiding and Its Applications 606 $aComputer security 606 $aComputer security$xManagement 615 0$aComputer security. 615 0$aComputer security$xManagement. 676 $a005.8 700 $aMegi?as$b David$01369484 702 $aMazurczyk$b Wojciech 702 $aKuribayashi$b Minoru 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910674393303321 996 $aData Hiding and Its Applications$93395616 997 $aUNINA LEADER 02774nam 22003973 450 001 9910583352603321 005 20240506010230.0 010 $a0-08-101171-7 035 $a(CKB)3710000001410819 035 $a(MiAaPQ)EBC4884394 035 $a(EXLCZ)993710000001410819 100 $a20210428d2017 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBiostatistics and Computer-Based Analysis of Health Data Using SAS 210 1$aSan Diego :$cElsevier,$d2017. 210 4$dİ2017. 215 $a1 online resource (176 pages) 311 $a1-78548-111-8 327 $aFront Cover -- Biostatistics and Computer-based Analysis of Health Data using SAS -- Copyright -- Contents -- Introduction -- 1. Language Elements -- 1.1. Introduction to the SAS language -- 1.2. Creating and managing SAS tables -- 1.3. Key points to remember -- 1.4. Further information -- 1.5. Applications -- 2. Simple Descriptive Statistics -- 2.1. Univariate descriptive statistics: Estimation -- 2.2. Bivariate descriptive statistics -- 2.3. Key points to remember -- 2.4. Further information -- 2.5. Applications -- 3. Measures of Association, Comparison of Means or Proportions -- 3.1. Comparison of two means -- 3.2. Comparisons of two proportions with independent samples -- 3.3. Measures of association in a contingency table -- 3.4. Comparisons of several means -- 3.5. Key points to remember -- 3.6. Further information -- 3.7. Applications -- 4. Correlation, Linear Regression -- 4.1. Linear correlation -- 4.2. Linear regression -- 4.3. Key points to remember -- 4.4. Further information -- 4.5. Applications -- 5. Logistic Regression -- 5.1. Logistic regression -- 5.2. Key points to remember -- 5.3. Further information -- 5.4. Applications -- 6. Survival Curves, Cox Regression -- 6.1. Survival curves -- 6.2. Cox regression -- 6.3. Key points to remember -- 6.4. Further information -- 6.5. Applications -- Appendices -- Appendix A: Introduction to SAS Studio -- A.1. Dialogue with Dylan to install SAS Studio -- A.2. Comments -- Appendix B: Introduction to SAS Macro -- B.1. Simple examples of SAS/MACRO programs -- B.2. Comments -- Appendix C: Introduction to SAS IML -- C.1. Example of a SAS/IML program -- C.2. Comments -- Bibliography -- Index -- Back Cover. 606 $aBiometry 615 0$aBiometry. 676 $a570.1/5195 676 $a570.15195 700 $aLalanne$b Christophe$0873622 701 $aMesbah$b Mounir$01656355 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910583352603321 996 $aBiostatistics and Computer-Based Analysis of Health Data Using SAS$94173904 997 $aUNINA