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Articulating the World: Conceptual Understanding and the Scientific Image
by Joseph RouseNaturalism as a guiding philosophy for modern science both disavows any appeal to the supernatural or anything else transcendent to nature, and repudiates any philosophical or religious authority over the workings and conclusions of the sciences. A longstanding paradox within naturalism, however, has been the status of scientific knowledge itself, which seems, at first glance, to be something that transcends and is therefore impossible to conceptualize within scientific naturalism itself. In Articulating the World, Joseph Rouse argues that the most pressing challenge for advocates of naturalism today is precisely this: to understand how to make sense of a scientific conception of nature as itself part of nature, scientifically understood. Drawing upon recent developments in evolutionary biology and the philosophy of science, Rouse defends naturalism in response to this challenge by revising both how we understand our scientific conception of the world and how we situate ourselves within it.
Artificial Assemblies with Cooperative DNA Recognition (Springer Theses)
by Zutao YUThis book presents three types of synthetically cooperative DNA recognizing assemblies, in order to advance the development of programmable DNA-binding pyrrole–imidazole polyamides (PIPs). PIPs represent the best-characterized class of small molecule DNA binders that can be modified to bind with any predetermined DNA sequence and regulate gene expression patterns in a transgene-free and cost-effective manner. PIPs are characterized by their small molecular size, high binding affinity, programmability, sequence selectivity, and moderate cell permeability. In recent years, there have been numerous novel studies on the applications of these biological tools; this research is thoroughly reviewed in the first chapter. There are several critical issues, however, that impede the further broad study of PIPs, which greatly concern the author. For instance, the short PIP version has an excessively hi^10 bp; this significantly decreases cell permeability. Moreover, the conventional binding strategy for PIP design cannot apply to flexible DNA binding—for example, the DNA-binding mode of a transcription factor pair. In this book, the author describes the development of three kinds of cooperative DNA-binding systems that help resolve the current highly problematic issues concerning PIPs. These three systems offer a range of significant advantages, such as favorable sequence selectivity, long recognition sequence, higher binding affinity, and a flexible gap distance. Released at a critical juncture in the application of PIPs, this book will greatly facilitate their use as therapeutic drugs in the treatment of cancer and hereditary diseases, and in regenerative medicine.
Artificial Cognitive Systems: A Primer
by David VernonA concise introduction to a complex field, bringing together recent work in cognitive science and cognitive robotics to offer a solid grounding on key issues. <p><p> This book offers a concise and accessible introduction to the emerging field of artificial cognitive systems. Cognition, both natural and artificial, is about anticipating the need for action and developing the capacity to predict the outcome of those actions. Drawing on artificial intelligence, developmental psychology, and cognitive neuroscience, the field of artificial cognitive systems has as its ultimate goal the creation of computer-based systems that can interact with humans and serve society in a variety of ways. This primer brings together recent work in cognitive science and cognitive robotics to offer readers a solid grounding on key issues. <p><p> The book first develops a working definition of cognitive systems―broad enough to encompass multiple views of the subject and deep enough to help in the formulation of theories and models. It surveys the cognitivist, emergent, and hybrid paradigms of cognitive science and discusses cognitive architectures derived from them. It then turns to the key issues, with chapters devoted to autonomy, embodiment, learning and development, memory and prospection, knowledge and representation, and social cognition. Ideas are introduced in an intuitive, natural order, with an emphasis on the relationships among ideas and building to an overview of the field. The main text is straightforward and succinct; sidenotes drill deeper on specific topics and provide contextual links to further reading.
Artificial DNA: Methods and Applications
by Yury E. Khudyakov Howard A. FieldsCombining elements of biochemistry, molecular biology, and immunology, artificial DNA can be employed in a number of scientific disciplines. Some of the varied applications include site-specific mutagenesis, hybridization, amplification, protein engineering, anti-sense technology, DNA vaccines, protein vaccines, recombinant antibodies, screening fo
Artificial Economics and Self Organization: Agent-Based Approaches to Economics and Social Systems (Lecture Notes in Economics and Mathematical Systems #669)
by Stephan Leitner Friederike WallThis volume presents recent advances in the dynamic field of Artificial Economics and its various applications. Artificial Economics provides a structured approach to model and investigate economic and social systems. In particular, this approach is based on the use of agent-based simulations and further computational techniques. The main aim is to analyze the outcomes at the overall systems' level as results from the agents' behavior at the micro-level. These emergent characteristics of complex economic and social systems can neither be foreseen nor are they intended. The emergence rather makes these systems function. Artificial Economics especially facilitates the investigation of this emergent systems' behavior.
Artificial Gauge Fields with Ultracold Atoms in Optical Lattices (Springer Theses)
by Monika AidelsburgerThis work reports on the generation of artificial magnetic fields with ultracold atoms in optical lattices using laser-assisted tunneling, as well as on the first Chern-number measurement in a non-electronic system. It starts with an introduction to the Hofstadter model, which describes the dynamics of charged particles on a square lattice subjected to strong magnetic fields. This model exhibits energy bands with non-zero topological invariants called Chern numbers, a property that is at the origin of the quantum Hall effect. The main part of the work discusses the realization of analog systems with ultracold neutral atoms using laser-assisted-tunneling techniques both from a theoretical and experimental point of view. Staggered, homogeneous and spin-dependent flux distributions are generated and characterized using two-dimensional optical super-lattice potentials. Additionally their topological properties are studied via the observation of bulk topological currents. The experimental techniques presented here offer a unique setting for studying topologically non-trivial systems with ultracold atoms.
Artificial General Intelligence: Smart Applications and Sustainable Technologies (Advanced Technologies and Societal Change)
by Keshav Kaushik Inam Ullah Khan Salma El HajjamiThis book highlights a collection of state-of-the-art research on Safe Artificial General Intelligence (AGI), highlighting the crucial role of cybersecurity, smart applications, and sustainable technologies in ensuring a secure AI future. It illustrates the latest trends in AI safety, exploring the potential risks and dangers associated with AGI development and ways to prevent unintended consequences. The book discusses the convergence of various fields, such as AI, cybersecurity, smart applications, and sustainable technologies, by providing an overview of theoretical, practical, and simulation concepts of AGI. It also displays solutions that will help mitigate the risks and ensure the responsible and ethical development of AGI. It provides insights and perspectives from experts in these fields and offers a comprehensive guide to understanding the challenges and opportunities associated with the development of safe and secure AGI. The book includes chapters on various topics related to AGI security, including the ethical and legal aspects of AGI development, the role of explainability in ensuring transparency and accountability, the use of machine learning for intrusion detection and prevention, and the application of smart technologies for securing AGI systems. Additionally, it explores the impact of sustainable technologies on AGI security, such as the use of renewable energy sources to power AGI systems and the development of eco-friendly hardware. This book is a valuable source for researchers, students, and practitioners interested in the fields of artificial general intelligence, cybersecurity, smart applications, and sustainable technologies.
Artificial Intelligence (Forensic Science in Focus)
by Katrin Franke Zeno GeradtsARTIFICIAL INTELLIGENCE (AI) IN FORENSIC SCIENCES Foundational text for teaching and learning within the field of Artificial Intelligence (AI) as it applies to forensic science Artificial Intelligence (AI) in Forensic Sciences presents an overview of the state-of-the-art applications of Artificial Intelligence within Forensic Science, covering issues with validation and new crimes that use AI; issues with triage, preselection, identification, argumentation and explain ability; demonstrating uses of AI in forensic science; and providing discussions on bias when using AI. The text discusses the challenges for the legal presentation of AI data and interpretation and offers solutions to this problem while addressing broader practical and emerging issues in a growing area of interest in forensics. It builds on key developing areas of focus in academic and government research, providing an authoritative and well-researched perspective. Compiled by two highly qualified editors with significant experience in the field, and part of the Wiley — AAFS series ‘Forensic Science in Focus’, Artificial Intelligence (AI) in Forensic Sciences includes information on: Cyber IoT, fundamentals on AI in forensic science, speaker and facial comparison, and deepfake detection Digital-based evidence creation, 3D and AI, interoperability of standards, and forensic audio and speech analysis Text analysis, video and multimedia analytics, reliability, privacy, network forensics, intelligence operations, argumentation support in court, and case applications Identification of genetic markers, current state and federal legislation with regards to AI, and forensics and fingerprint analysis Providing comprehensive coverage of the subject, Artificial Intelligence (AI) in Forensic Sciences is an essential advanced text for final year undergraduates and master’s students in forensic science, as well as universities teaching forensics (police, IT security, digital science and engineering), forensic product vendors and governmental and cyber security agencies.
Artificial Intelligence Applications for Health Care
by Anil Kumar Mitul Kumar Ahirwal Narendra D. LondheThis book takes an interdisciplinary approach by covering topics on health care and artificial intelligence. Data sets related to biomedical signals (ECG, EEG, EMG) and images (X-rays, MRI, CT) are explored, analyzed, and processed through different computation intelligence methods. Applications of computational intelligence techniques like artificial and deep neural networks, swarm optimization, expert systems, decision support systems, clustering, and classification techniques on medial datasets are explained. Survey of medical signals, medial images, and computation intelligence methods are also provided in this book. Key Features Covers computational Intelligence techniques like artificial neural networks, deep neural networks, and optimization algorithms for Healthcare systems Provides easy understanding for concepts like signal and image filtering techniques Includes discussion over data preprocessing and classification problems Details studies with medical signal (ECG, EEG, EMG) and image (X-ray, FMRI, CT) datasets Describes evolution parameters such as accuracy, precision, and recall etc. This book is aimed at researchers and graduate students in medical signal and image processing, machine and deep learning, and healthcare technologies.
Artificial Intelligence Applications in Electrical Transmission and Distribution Systems Protection
by Almoataz Y. AbdelazizArtificial intelligence (AI) can successfully help in solving real-world problems in power transmission and distribution systems because AI-based schemes are fast, adaptive, and robust and are applicable without any knowledge of the system parameters. This book considers the application of AI methods for the protection of different types and topologies of transmission and distribution lines. It explains the latest pattern-recognition-based methods as applicable to detection, classification, and location of a fault in the transmission and distribution lines, and to manage smart power systems including all the pertinent aspects. FEATURES Provides essential insight on uses of different AI techniques for pattern recognition, classification, prediction, and estimation, exclusive to power system protection issues Presents an introduction to enhanced electricity system analysis using decision-making tools Covers AI applications in different protective relaying functions Discusses issues and challenges in the protection of transmission and distribution systems Includes a dedicated chapter on case studies and applications This book is aimed at graduate students, researchers, and professionals in electrical power system protection, stability, and smart grids.
Artificial Intelligence Applications in a Pandemic: COVID-19 (Smart and Intelligent Computing in Engineering)
by Salah-Ddine KritCOVID-19, a novel coronavirus pandemic has disrupted our society in many ways. Digital healthcare innovations are required more than ever before as we come across myriad challenges during this pandemic. Scientists and developers are learning and finding a way to use artificial intelligence applications and natural language processing to comprehend and tackle this disease. AI technologies are playing an important role in the response to the COVID-19 pandemic. Experts are using all possible tools to study the virus, diagnose individuals, and analyze the public health impacts. This book is a collection of some of the leading efforts related to AI and COVID-19 focused on finding how AI can be helpful in monitoring the situation from early warnings, swift emergency responses, and critical decision-making. It discusses the use of machine learning and how it may help to reduce the impacts of this pandemic in conjunction with all other research and strategies going on. The book serves as a technical resource of data analytics and AI applications in tracking infectious diseases. It will serve academics, students, data scientists, medical practitioners, and anybody managing a global pandemic. Features: Directs the attention to the smart digital healthcare system in this COVID-19 pandemic. Simulates novel investigations and how they will be beneficial in understanding the pandemic. Presents the latest ideas developed for data scientists, doctors, engineers, and economists. Analyses the various issues related to computing, AI apps, big data analytic techniques, and predictive scientific skill gaps. Explains some interesting and diverse types of challenges and data-driven healthcare applications.
Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing
by Ram Bilas Pachori Rajesh Kumar TripathyThe book provides details regarding the application of various signal processing and artificial intelligence-based methods for electroencephalography data analysis. It will help readers in understanding the use of electroencephalography signals for different neural information processing and cognitive neuroscience applications. The book: Covers topics related to the application of signal processing and machine learning-based techniques for the analysis and classification of electroencephalography signals Presents automated methods for detection of neurological disorders and other applications such as cognitive task recognition, and brain-computer interface Highlights the latest machine learning and deep learning methods for neural signal processing Discusses mathematical details for the signal processing and machine learning algorithms applied for electroencephalography data analysis Showcases the detection of dementia from electroencephalography signals using signal processing and machine learning-based techniques It is primarily written for senior undergraduates, graduate students, and researchers in the fields of electrical engineering, electronics and communications engineering, and biomedical engineering.
Artificial Intelligence Models for the Dark Universe: Forays in Mathematical Cosmology
by Ariel FernándezThe dark universe contains matter and energy unidentifiable with current physical models, accounting for 95% of all the matter and energetic equivalent in the universe. The enormous surplus brings up daunting enigmas, such as the cosmological constant problem and the apparent distortions in the dynamics of deep space, and so coming to grips with the invisible universe has become a scientific imperative.This book addresses this need, reckoning that no cogent physical model of the dark universe can be implemented without first addressing the metaphysical hurdles along the way. The foremost problem is identifying the topology of the universe which, as argued in the book, is highly relevant to unveil the secrets of the dark universe.Artificial Intelligence (AI) is a valuable tool in this effort since it can reconcile conflicting data from deep space with the extant laws of physics by building models to decipher the dark universe. This book explores the applications of AI and how it can be used to embark on a metaphysical quest to identify the topology of the universe as a prerequisite to implement a physical model of the dark sector that enables a meaningful extrapolation into the visibile sector.The book is intended for a broad readership, but a background in college-level physics and computer science is essential. The book will be a valuable guide for graduate students as well as researchers in physics, astrophysics, and computer science focusing on AI applications to elucidate the nature of the dark universe.Key Features:· Provides readers with an intellectual toolbox to understand physical arguments on dark matter and energy.· Up to date with the latest cutting-edge research.· Authored by an expert on artificial intelligence and mathematical physics.
Artificial Intelligence Revolution: How AI Will Change our Society, Economy, and Culture
by Robin LiThe co-founder of Baidu explains how AI will transform human livelihood, from our economy and financial systems down to our daily lives. Written by Baidu cofounder Robin Li and prefaced by award-winning sci-fi writer Cixin Liu (author of The Three-Body Problem), Artificial Intelligence Revolution introduces Baidu&’s teams of top scientists and management as pioneers of movement toward AI. The book covers many of the latest AI-related ideas and technological developments, such as: Computational abilityBig data resourcesSetting the basic standards of AI in research and developmentAn introduction to the &“super brain&”Intelligent manufacturingDeep learningL4 automated vehiclesSmart finance The book describes the emergence of a &“smart&” society powered by technology and reflects on the challenges humanity is about to face. Li covers the most pressing AI-related ideas and technological developments, including: Will artificial intelligence replace human workers, and in what sectors of the economy? How will it affect healthcare and finance? How will daily human life change? Robin Li&’s Artificial Intelligence Revolution addresses these questions and more from the perspective of a pioneer of AI development. It's a must-read for anyone concerned about the emergence of a &“smart&” society powered by technology and the challenges humanity is about to face.
Artificial Intelligence Revolutionizing Cancer Care: Precision Diagnosis and Patient-Centric Healthcare (Future Generation Information Systems)
by Suman Kumar Swarnkar Gurpreet Singh Chhabra Abhishek Guru Harshitha Raghavan DevarajanIn the ever-evolving landscape of cancer treatment, the fusion of artificial intelligence (AI) with medical science marks a groundbreaking shift toward more precise, efficient, and personalized healthcare. Artificial Intelligence Revolutionizing Cancer Care: Precision Diagnosis and Patient-Centric Healthcare delves into the transformative power of AI, offering a comprehensive exploration of its role in enhancing cancer diagnosis, treatment, and patient management. This edited volume brings together leading experts and researchers who illuminate the latest advancements in AI technologies applied to oncology. From machine learning algorithms that predict cancer progression to sophisticated imaging techniques that improve diagnostic accuracy, this book covers a spectrum of innovations reshaping cancer care. Key highlights include precision diagnosis, uncovering how AI-driven tools are revolutionizing the early detection and accurate classification of various cancer types, leading to better patient outcomes; patient-centric approaches, exploring the shift toward personalized medicine, where AI tailors treatment protocols to individual patient profiles, ensuring more effective and targeted therapies; and ethical and practical considerations, gaining insights into the ethical, practical, and regulatory challenges of integrating AI in healthcare, emphasizing the need for patient privacy and data security. Additionally, the book looks ahead to the potential future applications of AI in oncology, including predictive analytics, robotic surgery, and beyond. Artificial Intelligence Revolutionizing Cancer Care is an essential resource for medical professionals, researchers, and students seeking to understand the intersection of AI and oncology. It offers a visionary perspective on how cutting-edge technology is poised to enhance patient care and transform the fight against cancer.This book focuses on the critical intersection of artificial intelligence and cancer diagnosis within the healthcare sector emphasizes the real-world impact of artificial intelligence in improving cancer detection, treatment, and overall patient care covers artificial intelligence algorithms, machine learning techniques, medical image analysis, predictive modeling, and patient care applications explores how artificial intelligence technologies enhance the patient’s experience, resulting in better outcomes and reduced healthcare disparities provides readers with an understanding of the mathematics underpinning machine learning models, including decision trees, support vector machines, and deep neural networks It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, biomedical engineering, and information technology.
Artificial Intelligence Security and Privacy: First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, Guangzhou, China, December 3–5, 2023, Proceedings, Part I (Lecture Notes in Computer Science #14509)
by Jin Li Moncef Gabbouj Jaideep VaidyaThis two-volume set LNCS 14509-14510, constitutes the refereed proceedings of the First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, held in Guangzhou, China, during December 3–5, 2023.The 40 regular papers and 23 workshop papers presented in this two-volume set were carefully reviewed and selected from 115 submissions.Topics of interest include, e.g., attacks and defence on AI systems; adversarial learning; privacy-preserving data mining; differential privacy; trustworthy AI; AI fairness; AI interpretability; cryptography for AI; security applications.
Artificial Intelligence Security and Privacy: First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, Guangzhou, China, December 3–5, 2023, Proceedings, Part II (Lecture Notes in Computer Science #14510)
by Jin Li Moncef Gabbouj Jaideep VaidyaThis two-volume set LNCS 14509-14510, constitutes the refereed proceedings of the First International Conference on Artificial Intelligence Security and Privacy, AIS&P 2023, held in Guangzhou, China, during December 3–5, 2023.The 40 regular papers and 23 workshop papers presented in this two-volume set were carefully reviewed and selected from 115 submissions. Topics of interest include, e.g., attacks and defence on AI systems; adversarial learning; privacy-preserving data mining; differential privacy; trustworthy AI; AI fairness; AI interpretability; cryptography for AI; security applications.
Artificial Intelligence Security and Privacy: Second International Conference, AIS&P 2024, Guangzhou, China, December 6-7, 2024, Proceedings (Lecture Notes in Computer Science #15399)
by Fangguo Zhang Hongyang Yan Weiwei LinThis book constitutes the refereed proceedings of the Second International Conference on Artificial Intelligence Security and Privacy, AIS&P 2024, held in Guangzhou, China, during December 6-7, 2024. The 14 full papers included in this book were carefully reviewed and selected from 47 submissions. The papers help to researchers to exchange latest research progress in all areas such as artificial intelligence, security and privacy, and their applications.
Artificial Intelligence Techniques for Sustainable Development (Smart Engineering Systems: Design and Applications)
by Suman Lata Tripathi Kanav Dhir Deepika Ghai Kirti RawalHow can the efficiency of the algorithms be increased with a lesser number of computations as well as optimized with the resources for cost-effective solutions? Artificial Intelligence Techniques for Sustainable Development provides an answer. Further, it discusses important concepts such as green communication network design and implementation for the Internet of Things ecosystem, green computing in network security, and artificial intelligence models for remote sensing applications.Key features: Presents the latest tools and techniques in developing solutions intended for resource utilization, energy efficiency, and human and environmental health Highlights the advancement in electronics and communication technology for green applications Covers smart energy harvesting/charging and power management techniques using machine learning Explains green communication network design and implementation for the Internet of Things ecosystem, and green computing in network security Illustrates prediction models for carbon emission and sequestration, environmental health, and climate change The book is aimed at senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics, and communications engineering, computer science and engineering, environmental engineering, and biomedical engineering.
Artificial Intelligence Techniques in Smart Agriculture
by Sanjeev Jain Siddharth Singh Chouhan Uday Pratap Singh Akash SaxenaThis edited volume explores the integration of artificial intelligence to improve crop production. It addresses the critical need for intelligent crop management in light of the world's escalating population. Encompassing a spectrum of technologies, including computer vision, image processing, soft computing, machine learning, and deep learning, the book explores advancements in decision-making systems. It integrates data science methodologies, Internet of Things, wireless communications, and a range of sensors and actuators to provide precise, timely, and cost-effective solutions to agricultural challenges, ultimately enhancing both the quality and quantity of crop yields. The book empowers its audience to direct their efforts towards designing models and prototypes that benefit society and the environment, making it an indispensable resource for those eager to shape the future of intelligent agriculture. It serves as a comprehensive guide for students, scholars, and academicians keen on delving into the transformative field of artificial intelligence in agriculture. Researchers, scientists, and field experts will find invaluable insights to guide their exploration and contribution to this domain.
Artificial Intelligence Technologies for Computational Biology
by Ranjeet Kumar Rout Saiyed Umer Sabha Sheikh Amrit Lal SangalThis text emphasizes the importance of artificial intelligence techniques in the field of biological computation. It also discusses fundamental principles that can be applied beyond bio-inspired computing.It comprehensively covers important topics including data integration, data mining, machine learning, genetic algorithms, evolutionary computation, evolved neural networks, nature-inspired algorithms, and protein structure alignment. The text covers the application of evolutionary computations for fractal visualization of sequence data, artificial intelligence, and automatic image interpretation in modern biological systems.The text is primarily written for graduate students and academic researchers in areas of electrical engineering, electronics engineering, computer engineering, and computational biology.This book:• Covers algorithms in the fields of artificial intelligence, and machine learning useful in biological data analysis.• Discusses comprehensively artificial intelligence and automatic image interpretation in modern biological systems.• Presents the application of evolutionary computations for fractal visualization of sequence data.• Explores the use of genetic algorithms for pair-wise and multiple sequence alignments.• Examines the roles of efficient computational techniques in biology.
Artificial Intelligence Technology in Healthcare: Security and Privacy Issues (Advances in Smart Healthcare Technologies)
by Neha Sharma Deepak Sinwar Durgesh SrivastavaArtificial Intelligence Technology in Healthcare: Security and Privacy Issues focuses on current issues with patients’ privacy and data security including data breaches in healthcare organizations, unauthorized access to patients’ information, and medical identity theft. It explains recent breakthroughs and problems in deep learning security and privacy issues, emphasizing current state-of-the-art methods, methodologies, implementation, attacks, and countermeasures. It examines the issues related to developing artifiicial intelligence (AI)-based security mechanisms which can gather or share data across several healthcare applications securely and privately. Features: Combines multiple technologies (i.e., Internet of Things [IoT], Federated Computing, and AI) for managing and securing smart healthcare systems. Includes state-of-the-art machine learning, deep learning techniques for predictive analysis, and fog and edge computing-based real-time health monitoring. Covers how to diagnose critical diseases from medical imaging using advanced deep learning-based approaches. Focuses on latest research on privacy, security, and threat detection on COVID-19 through IoT. Illustrates initiatives for research in smart computing for advanced healthcare management systems. This book is aimed at researchers and graduate students in bioengineering, artificial intelligence, and computer engineering.
Artificial Intelligence and Advanced Analytics for Food Security
by Chandrasekar VuppalapatiClimate change, increasing population, food-versus-fuel economics, pandemics, etc. pose a threat to food security to unprecedented levels. It has fallen upon the practitioners of agriculture and technologists of the world to innovate and become more productive to address the multi-pronged food security challenges. Agricultural innovation is key to managing food security concerns. The infusion of data science, artificial intelligence (AI), advanced analytics, satellites data, geospatial data, climatology, sensor technologies, and climate modeling with traditional agricultural practices such as soil engineering, fertilizers use, and agronomy are some of the best ways to achieve this. Data science helps farmers to unravel patterns in fertilizer pricing, equipment usage, transportation and storage costs, yield per hectare, and weather trends to better plan and spend resources. AI enables farmers to learn from fellow farmers to apply best techniques that are transferred learning from AI to improve agricultural productivity and to achieve financial sustainability. Sensor technologies play an important role in getting real-time farm field data and provide feedback loops to improve overall agricultural practices and can yield huge productivity gains. Advanced Analytics modeling is essential software technique that codifies farmers’ tacit knowledge such as better seed per soil, better feed for dairy cattle breed, or production practices to match weather pattern that was acquired over years of their hard work to share with worldwide farmers to improve overall production efficiencies, the best antidote to food security issue. In addition to the paradigm shift, economic sustainability of small farms is a major enabler of food security. The book reviews all these technological advances and proposes macroeconomic pricing models that data mines macroeconomic signals and the influence of global economic trends on small farm sustainability to provide actionable insights to farmers to avert any financial disasters due to recurrent economic crises.
Artificial Intelligence and Biological Sciences
by P. V. MohananAdvancements of AI in medical and biological sciences have opened new ways for drug development. Novel therapeutic molecules and their target action can be easily predicted and can be modified. AI helps in disease detection and diagnosis faster. The breakthrough of AI is made especially in the area of personalized precision medicine, host-pathogen interaction and predictive epidemiology. These approaches could help in faster decision-making with minimal errors that can improve risk analysis, especially disease diagnosis and selecting treatment strategy. In agricultural practices, an exact combination of fertilizers, pesticides, herbicides, soil management, water requirement analysis, yield prediction and overall crop management can be modified by implementing AI interventions. AI could provide a better improvement in agriculture, medical research, pharmaceuticals and bio-based industries for a sustainable life.The key features of this book are: AI in medical Sciences, biotechnology and drug discovery; Application of AI in Digital Pathology, cytology and bioinformatics; Overview of AI, Machine Learning and Deep Learning; Impact of Artificial Intelligence in Society; Artificial Intelligence in Pharmacovigilance; and Ethics in Artificial Intelligence. The volume aims to comprehensively cover the application of AI in biological sciences. It is a collection of contributions from different authors who have several years of experience in their specific areas. The book will be useful for pharma companies, CROs, product developers, students, researchers, academicians, policymakers and practitioners.
Artificial Intelligence and Blockchain in Digital Forensics (River Publishers Series in Digital Security and Forensics)
by P. Karthikeyan Hari Mohan Pandey Velliangiri SarveshwaranDigital forensics is the science of detecting evidence from digital media like a computer, smartphone, server, or network. It provides the forensic team with the most beneficial methods to solve confused digital-related cases. AI and blockchain can be applied to solve online predatory chat cases and photo forensics cases, provide network service evidence, custody of digital files in forensic medicine, and identify roots of data scavenging. The increased use of PCs and extensive use of internet access, have meant easy availability of hacking tools. Over the past two decades, improvements in the information technology landscape have made the collection, preservation, and analysis of digital evidence extremely important. The traditional tools for solving cybercrimes and preparing court cases are making investigations difficult. We can use AI and blockchain design frameworks to make the digital forensic process efficient and straightforward. AI features help determine the contents of a picture, detect spam email messages and recognize swatches of hard drives that could contain suspicious files. Blockchain-based lawful evidence management schemes can supervise the entire evidence flow of all of the court data. This book provides a wide-ranging overview of how AI and blockchain can be used to solve problems in digital forensics using advanced tools and applications available on the market.