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                <text>This open access book covers the most cutting-edge and hot research topics and fields of post-quantum cryptography. The main purpose of this book is to focus on the computational complexity theory of lattice ciphers, especially the reduction principle of Ajtai, in order to fill the gap that post-quantum ciphers focus on the implementation of encryption and decryption algorithms, but the theoretical proof is insufficient. In Chapter 3, Chapter 4, and Chapter 6, the author introduces the theory and technology of LWE distribution, LWE ciphers, and homomorphic encryption in detail. When using random analysis tools, there is a problem of "ambiguity" in both definition and algorithm. The greatest feature of this book is its use of probability distribution to carry out rigorous mathematical definitions and mathematical demonstrations for various unclear or imprecise expressions, so as to make it a rigorous theoretical system for classroom teaching and dissemination. Chapters 5 and 7 further expand and improve the theory of cyclic lattices, ideal lattices, and generalized NTRU cryptography.&#13;
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                <text>This open access book systematically explores the statistical characteristics of cryptographic systems, the computational complexity theory of cryptographic algorithms, and the mathematical principles behind various encryption and decryption algorithms. The theory stems from technology. Based on Shannon's information theory, this book systematically introduces the information theory, statistical characteristics, and computational complexity theory of public key cryptography, focusing on the three main algorithms of public key cryptography: RSA, discrete logarithm, and elliptic curve cryptosystem. It aims to indicate what it is and why it is. It systematically simplifies and combs the theory and technology of lattice cryptography, which is the greatest feature of this book.&#13;
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                <text>Ruopeng An, Michael A. Lindsey</text>
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                <text>This open access book is a comprehensive examination of how artificial intelligence (AI) is transforming the field of social work across practice, education, and research. This topic is particularly important to the field at this time due to the rapid integration of AI technologies into societal structures and the increasing demand for social services that are efficient, effective, and ethically sound. The book provides timely insights into how AI can be harnessed to address complex social issues while maintaining the core values of social work. It emphasizes the critical need for professionals to understand and navigate the ethical implications of AI, ensuring that technological advancements serve to enhance, rather than compromise, human well-being.&#13;
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Organized into five parts, the book begins with a foundational overview in Part I, introducing the role of AI in transforming social work. Part II explores AI applications responding to social needs, covering critical areas such as poverty, child welfare, health care, mental health, substance abuse, support for older adults, communities at risk, criminal justice, and human trafficking prevention. Part III delves into AI's impact on social justice in changing contexts, including advocacy, environmental challenges, the evolving workplace, and international issues. Part IV focuses on AI in social work education and research, highlighting how AI tools enhance learning and scholarly inquiry. Part V addresses ethical considerations and future directions, discussing challenges, governance, and strategies for building AI literacy, culminating in a conclusion that outlines opportunities for AI in social work.&#13;
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Artificial Intelligence in Social Work: Bridging Technology and Humanity equips social work practitioners, educators, researchers, and students with a deep understanding of AI's capabilities and implications within various social work domains. The book offers practical guidance on integrating AI into various aspects of social work practice, enhancing service delivery, and improving client outcomes. For educators and students, it provides a framework for incorporating AI literacy into social work curricula, preparing the next generation of professionals for a technologically advanced landscape. Researchers benefit from insights into innovative methodologies that leverage AI for more robust and impactful studies. By intertwining technological advancements with the human-centric values of social work, the book underscores the necessity of balancing innovation with compassion and ethical responsibility.</text>
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                <text>Artificial Intelligence</text>
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                <text>2026</text>
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                <text>This work is licensed under a Creative Commons Attribution 4.0 International License</text>
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                <text>English</text>
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