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Scientific Style and Format: The CSE Manual for Authors, Editors, and Publishers by 
Publication Manual of the American Psychological Association (Seventh ed.)
The Publication Manual of the American Psychological Association, Seventh Edition is the official source for APA Style. With millions of copies sold worldwide in multiple languages, it is the style manual of choice for writers, researchers, editors, students, and educators in the social and behavioral sciences, natural sciences, nursing, communications, education, business, engineering, and other fields. Known for its authoritative, easy-to-use reference and citation system, the Publication Manual also offers guidance on choosing the headings, tables, figures, language, and tone that will result in powerful, concise, and elegant scholarly communication. It guides users through the scholarly writing process--from the ethics of authorship to reporting research through publication. The seventh edition is an indispensable resource for students and professionals to achieve excellence in writing and make an impact with their work. The seventh edition has been thoroughly revised and updated to reflect best practices in scholarly writing and publishing. All formats are in full color, with a new tabbed spiral version Improved ease of navigation, with many additional numbered sections to help users quickly locate answers to their questions Resources for students on writing and formatting annotated bibliographies, response papers, and other paper types as well as guidelines on citing course materials Dedicated chapter for new users of APA Style covering paper elements and format, including sample papers for both professional authors and student writers New chapter on journal article reporting standards that includes updates to reporting standards for quantitative research and the first-ever qualitative and mixed methods reporting standards in APA Style New chapter on bias-free language guidelines for writing about people with respect and inclusivity in areas including age, disability, gender, participation in research, race and ethnicity, sexual orientation, socioeconomic status, and intersectionality More than 100 new reference examples covering periodicals, books, audiovisual media, social media, webpages and websites, and legal resources More than 40 new sample tables and figures Expanded guidance on ethical writing and publishing practices, including how to ensure the appropriate level of citation, avoid plagiarism and self-plagiarism, and navigate the publication process Guidelines that support accessibility for all users, including simplified reference, in-text citation, and heading formats as well as additional font options
This book provides comprehensive coverage of verification and debugging techniques for embedded software, which is frequently used in safety critical applications (e.g., automotive), where failures are unacceptable. Since the verification of complex systems needs to encompass the verification of both hardware and embedded software modules, this book focuses on verification and debugging approaches for embedded software with hardware dependencies. Coverage includes the entire flow of design, verification and debugging of embedded software and all key approaches to debugging, dynamic, static, and hybrid verification. This book discusses the current, industrial embedded software verification flow, as well as emerging trends with focus on formal and hybrid verification and debugging approaches.
This book describes various methods and recent advances in predictive computing and information security. It highlights various predictive application scenarios to discuss these breakthroughs in real-world settings. Further, it addresses state-of-art techniques and the design, development and innovative use of technologies for enhancing predictive computing and information security. Coverage also includes the frameworks for eTransportation and eHealth, security techniques, and algorithms for predictive computing and information security based on Internet-of-Things and Cloud computing. As such, the book offers a valuable resource for graduate students and researchers interested in exploring predictive modeling techniques and architectures to solve information security, privacy and protection issues in future communication.
In this book, anew method for hybrid intelligent systems is proposed. The proposed method isbased on a granular computing approach applied in two levels. The techniquesused and combined in the proposed method are modular neural networks (MNNs)with a Granular Computing (GrC) approach, thus resulting in a new concept ofMNNs; modular granular neural networks (MGNNs). In addition fuzzy logic (FL)and hierarchical genetic algorithms (HGAs) are techniques used in this researchwork to improve results. These techniques are chosen because in other workshave demonstrated to be a good option, and in the case of MNNs and HGAs, thesetechniques allow to improve the results obtained than with their conventionalversions; respectively artificial neural networks and genetic algorithms.
This book presents methods to improve information security for protected communication. It combines and applies interdisciplinary scientific engineering concepts, including cryptography, chaos theory, nonlinear and singular optics, radio-electronics and self-changing artificial systems. It also introduces additional ways to improve information security using optical vortices as information carriers and self-controlled nonlinearity, with nonlinearity playing a key "evolving" role. The proposed solutions allow the universal phenomenon of deterministic chaos to be discussed in the context of information security problems on the basis of examples of both electronic and optical systems. Further, the book presents the vortex detector and communication systems and describes mathematical models of the chaos oscillator as a coder in the synchronous chaotic communication and appropriate decoders, demonstrating their efficiency both analytically and experimentally. Lastly it discusses the cryptologic features of analyzed systems and suggests a series of new structures for confident communication.
This volume provides an overview of the field of Hybrid Machine Translation (MT) and presents some of the latest research conducted by linguists and practitioners from different multidisciplinary areas. Nowadays, most important developments in MT are achieved by combining data-driven and rule-based techniques. These combinations typically involve hybridization of different traditional paradigms, such as the introduction of linguistic knowledge into statistical approaches to MT, the incorporation of data-driven components into rule-based approaches, or statistical and rule-based pre- and post-processing for both types of MT architectures. The book is of interest primarily to MT specialists, but also - in the wider fields of Computational Linguistics, Machine Learning and Data Mining - to translators and managers of translation companies and departments who are interested in recent developments concerning automated translation tools.
