LEADER 02176nam 2200493 450 001 9910797625703321 005 20231015011527.0 010 $a1-4438-8399-9 035 $a(CKB)3710000000485908 035 $a(EBL)4534871 035 $a(MiAaPQ)EBC4534871 035 $a(Au-PeEL)EBL4534871 035 $a(CaPaEBR)ebr11215884 035 $a(CaONFJC)MIL838952 035 $a(OCoLC)924631885 035 $a(EXLCZ)993710000000485908 100 $a20160619h20152015 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 00$aEnglish for academic purposes $eapproaches and implications /$fedited by Paul Thompson and Giuliana Diani 210 1$aNewcastle upon Tyne, England :$cCambridge Scholars Publishing,$d2015. 210 4$dİ2015 215 $a1 online resource (357 p.) 300 $aDescription based upon print version of record. 311 $a1-4438-7439-6 320 $aIncludes bibliographical references and index. 330 $aThe analysis of academic genres and the use of corpus resources, methods and analytical tools are now central to a great deal of research into English for Academic Purposes (EAP). 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Nagar 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2023. 215 $a1 online resource (114 pages) 225 1 $aSpringerBriefs in Computational Intelligence,$x2625-3712 311 08$a981-19-9721-7 327 $aIntroduction -- Sine Cosine Algorithm -- Sine Cosine Algorithm for Multi-Objective Optimization -- Sine Cosine Algorithm for Discrete Optimization Problems -- Advancements in the Sine Cosine Algorithm -- Conclusion and Further Research Directions. 330 $aThis open access book serves as a compact source of information on sine cosine algorithm (SCA) and a foundation for developing and advancing SCA and its applications. SCA is an easy, user-friendly, and strong candidate in the field of metaheuristics algorithms. Despite being a relatively new metaheuristic algorithm, it has achieved widespread acceptance among researchers due to its easy implementation and robust optimization capabilities. 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