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"This book introduces audio watermarking methods in transform domain based on matrix decomposition for copyright protection. Chapter 1 discusses the application and properties of digital watermarking. Chapter 2 proposes a blind lifting wavelet transform (LWT) based watermarking method using fast Walsh Hadamard transform (FWHT) and singular value decomposition (SVD) for audio copyright protection. Chapter 3 presents a blind audio watermarking method based on LWT and QR decomposition (QRD) for audio copyright protection. Chapter 4 introduces an audio watermarking algorithm based on FWHT and LU decomposition (LUD). Chapter 5 proposes an audio watermarking method based on LWT and Schur decomposition (SD). Chapter 6 explains in details on the challenges and future trends of audio watermarking in various application areas."

"This state-of-the-art survey offers a renewed and refreshing focus on the progress in evolutionary computation, in neural networks, and in fuzzy systems. The book presents the expertise and experiences of leading researchers spanning a diverse spectrum of computational intelligence in these areas. The result is a balanced contribution to the research area of computational intelligence that should serve the community not only as a survey and a reference, but also as an inspiration for the future advancement of the state of the art of the field. The 13 selected chapters originate from lectures and presentations given at the IEEE World Congress on Computational Intelligence, WCCI 2012, held in Brisbane, Australia, in June 2012."

"Non-linear aeroacoustic modeling approach is used to estimate the important fine-structure speech events, which are not revealed by the short time Fourier transform (STFT). This book includes advanced topics in non-linear estimation and modeling techniques along with their applications to speaker recognition."

"Natural Language Generation (NLG) merupakan salah satu topik dalam bidang Natural Language Processing (NLP) yang hingga sekarang penelitiannya masih banyak dilakukan. Tugas dari NLG adalah menghasilkan bahasa natural (manusia) dari data non-linguistik. Secara umum, sistem NLG melibatkan tahapan-tahapan utama yaitu document planning, microplanning, dan surface realisation. Penelitian yang dilakukan adalah mengembangkan sistem NLG yang menggunakan konsep inference dalam prosesnya menghasilkan dokumen. Selain itu sistem juga diharapkan mampu memanfaatkan informasi yang sifatnya historis dalam proses menghasilkan dokumen tersebut. Pengembangan terutama dilakukan pada subbagian perencanaan (document planning dan microplanning) dengan domain yang dipilih adalah sepak bola. Implementasi dilakukan dengan menggunakan prolog. Prolog dipilih karena sangat cocok digunakan untuk proses inference. Evaluasi sistem dilakukan dengan cara melakukan pengujian unit untuk setiap komponen, terutama komponen yang melakukan inference. Hasilnya menunjukkan bahwa sistem berjalan sebagaimana mestinya yaitu mengeluarkan output yang benar sesuai dengan permintaan pada input (query). Selain itu, dilakukan juga evaluasi oleh manusia dengan cara menyebarkan kuesioner penilaian terhadap laporan yang dihasilkan oleh sistem NLG dibandingkan dengan laporan hasil buatan manusia. Hasilnya menunjukkan bahwa laporan buatan manusia masih lebih baik, namun laporan hasil dari sistem juga memperoleh penilaian yang cukup baik.

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Natural Language Generation (NLG) is one of the topics in the field of Natural Language Processing (NLP), which until now is still a lot of research done. Task of NLG is to generate natural (human) language from non-linguistic data. In general, the NLG system involves main phases namely document planning, microplanning, and surface realisation.

This research is to develop NLG system which uses the concept of inference in the process of generating document. Furthermore, the system also expected to use historical information in the process of producing the document. Development is mainly on planning phase (document planning and microplanning) with selected domain is football. Implementation is done by using prolog. Prolog selected because it is suitable for inference process. Evaluation of the system is done by doing a unit testing for each component, especially for component which perform inference.

The result shows that the system is running as it should be that is gives correct output according to the request on the input (query). In addition, the evaluation was also conducted by distributing questionnaires to compare the reports generated by the NLG system with man-made reports. The results show that man-made report is still better, but the report generated by the NLG system also obtain a fairly good assessment."

"The two volume set LNCS 7491 and 7492 constitutes the refereed proceedings of the 12th International Conference on Parallel Problem Solving from Nature, PPSN 2012, held in Taormina, Sicily, Italy, in September 2012. The total of 105 revised full papers were carefully reviewed and selected from 226 submissions. The meeting began with 5 workshops which offered an ideal opportunity to explore specific topics in evolutionary computation, bio-inspired computing and metaheuristics. PPSN 2012 also included 8 tutorials. The papers are organized in topical sections on evolutionary computation, machine learning, classifier systems, image processing, experimental analysis, encoding, EDA, GP; multiobjective optimization, swarm intelligence, collective behavior, coevolution and robotics, memetic algorithms, hybridized techniques, meta and hyperheuristics, and applications."

"The two volume set LNCS 7491 and 7492 constitutes the refereed proceedings of the 12th International Conference on Parallel Problem Solving from Nature, PPSN 2012, held in Taormina, Sicily, Italy, in September 2012. The total of 105 revised full papers were carefully reviewed and selected from 226 submissions. The meeting began with 6 workshops which offered an ideal opportunity to explore specific topics in evolutionary computation, bio-inspired computing and metaheuristics. PPSN 2012 also included 8 tutorials. The papers are organized in topical sections on evolutionary computation, machine learning, classifier systems, image processing, experimental analysis, encoding, EDA, GP, multiobjective optimization, swarm intelligence, collective behavior, coevolution and robotics, memetic algorithms, hybridized techniques, meta and hyperheuristics, and applications."