Acoustic and Linguistic Analysis in Neurological and Psychiatric Disorders
This book explores the use of speech and language analysis for evaluating and monitoring Major Depression Disorder (MDD), Alzheimer's Disease (AD), and Parkinson's Disease (PD). By combining acoustic and linguistic features with machine learning, it addresses challenges in diagnosis and symptom overlap while aiming to improve therapy outcomes and patient monitoring. For MDD, the study analyzes therapy effectiveness by evaluating speech descriptors' impact on therapy, changes in emotional and speech patterns, and neural embeddings' suitability for tracking depression levels using contrastive learning. In AD, it applies automatic speech analysis to classify the disease, predict cognitive states, and detect pre-clinical stages. This includes AD classification using acoustic, emotional, and linguistic features; cognitive state prediction aligned with clinical assessments; and detection of pre-clinical stages linked to the PSEN1 mutation. For PD, speech analysis focuses on classifying and predicting neurological and motor states, incorporating spectral-based representation learning for disease severity prediction and identifying depression through emotional speech analysis. The book also examines biases in data collection and emphasizes the need for robust, multilingual models to enable cross-language feature transferability. Findings demonstrate the potential of speech and language analysis to support diagnosis and monitor treatment across neurological and psychiatric disorders.
Structural, Syntactic, and Statistical Pattern Recognition
This book constitutes the proceedings of the Joint IAPR International Workshops on Structural, Syntactic, and Statistical Pattern Recognition, S+SSPR 2024, which took place in Venice, Italy, during September 9-11, 2024. The 19 full papers presented in this volume were carefully reviewed and selected from 27 submissions. The proceedings focus on pattern recognition, including classification and clustering, deep learning, structural matching and graph-theoretic methods, and multimedia analysis and understanding.
Supercomputing
The two-volume set LNCS 15406 and 15407 constitutes the refereed proceedings of the 10th Russian Supercomputing Days International Conference, RuSCDays 2024, held in Moscow, Russia, during September 2024. The 43 full papers presented in these two volumes were carefully reviewed and selected from 95 submissions. The papers are organized in the following topical sections: Part I: Supercomputer Simulation; HPC, BigData, AI: Algorithms, Technologies, Evaluation Part II: Distributed Computing; HPC Education.
Advances in Differential and Difference Equations and Their Applications
This Special Issue presents a collection of articles that highlight the significant progress in the study of differential and difference equations. These contributions cover a wide range of topics, from boundary value problems and the asymptotic behavior of solutions to complex mathematical models and the application of fractional and difference equations in various scientific and engineering fields.Differential equations are a core mathematical tool for modeling dynamic systems in a diverse range of areas, such as physics, biology, economics, and engineering. Likewise, difference equations provide discrete counterparts to continuous models, which are crucial in understanding phenomena occurring in digital systems and various computational models. The papers presented in this Special Issue reflect the latest theoretical advancements and applications in these important research areas.
Professional Penetration Testing
Professional Penetration Testing: Creating and Learning in a Hacking Lab, Third Edition walks the reader through the entire process of setting up and running a pen test lab. Penetration testing--the act of testing a computer network to find security vulnerabilities before they are maliciously exploited--is a crucial component of information security in any organization. Chapters cover planning, metrics, and methodologies, the details of running a pen test, including identifying and verifying vulnerabilities, and archiving, reporting and management practices. The material presented will be useful to beginners through advanced practitioners. Here, author Thomas Wilhelm has delivered penetration testing training to countless security professionals, and now through the pages of this book, the reader can benefit from his years of experience as a professional penetration tester and educator. After reading this book, the reader will be able to create a personal penetration test lab that can deal with real-world vulnerability scenarios. "...this is a detailed and thorough examination of both the technicalities and the business of pen-testing, and an excellent starting point for anyone getting into the field." -Network Security
Supercomputing
The two-volume set LNCS 15406 and 15407 constitutes the refereed proceedings of the 10th Russian Supercomputing Days International Conference, RuSCDays 2024, held in Moscow, Russia, during September 2024. The 43 full papers presented in these two volumes were carefully reviewed and selected from 95 submissions. The papers are organized in the following topical sections: Part I: Supercomputer Simulation; HPC, BigData, AI: Algorithms, Technologies, Evaluation Part II: Distributed Computing; HPC Education.
Artificial Intelligence Logic and Applications
This book constitutes the proceedings of the 4th International Conference on Artificial Intelligence Logic and Applications, AILA 2024, held in Lanzhou, China, during August 10-11, 2024. The 16 full papers and the 11 short papers included in this volume were carefully reviewed and selected from 45 submissions. The papers cover the following topics: AI logic foundation; AI logic reasoning; AI logic applications.
Study of Vulnerability to Data Collection by the Phishing Scam Technique
Embedded Computer Systems: Architectures, Modeling, and Simulation
The two-volume set LNCS 15226 and 15227 constitutes the refereed proceedings of the 24th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2024, held in Samos, Greece, during June 29-July 4, 2024. The 24 full papers, 10 full papers in 2 special sessions and 4 poster session included in this book were carefully reviewed and selected from 57 submissions. This SAMOS 2024 covers the topics systems themselves - through their applications; architectures; and underlying processors - or methods created to automate their design.
Embedded Computer Systems: Architectures, Modeling, and Simulation
The two-volume set LNCS 15226 and 15227 constitutes the refereed proceedings of the 24th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2024, held in Samos, Greece, during June 29-July 4, 2024. The 24 full papers, 10 invited full papers and 4 poster papers included in the proceedings were carefully reviewed and selected from 57 submissions. They deal with embedded computer systems focusing on their applications; architectures; and underlying processors, as well as methods created to automate their design.
Application of Various Hydrological Modeling Techniques and Methods in River Basin Management
Hydrological models, ranging from conceptual to fully distributed frameworks, are essential for understanding and addressing water resource challenges. They offer innovative solutions to stabilize water balances and tackle pressing environmental issues such as droughts, floods, and water scarcity. Complementing these traditional methods, machine learning algorithms (MLAs) have proven highly effective in simulating complex hydrological processes, enabling improved predictions for flood forecasting, drought management, crop modeling, and freshwater allocation. This Special Issue of Water delves into cutting-edge advancements in hydrological modeling, highlighting the integration of remote sensing data and the application of MLAs to enhance the accuracy and efficiency of water resource management. From adapting novel machine learning techniques to assessing water balance components, the research in this collection addresses the critical challenges that are faced by watersheds worldwide. Featuring innovative approaches and practical applications, this Special Issue is an invaluable resource for researchers, practitioners, and policy-makers who are dedicated to advancing hydrological science and fostering sustainable water management solutions.
Human Power
The book challenges the view of technological determinism that portrays humans as powerless and flawed, and instead suggests that we need to reposition the different kinds of human power in technology politics and governance.
Prefabricated and Modular Steel Structures
Prefabricated steel structures permit a large portion of the building to be manufactured in a factory, making it environmentally friendly and highly efficient. The modularized production of buildings has attracted extensive interest from engineers in recent years with growing environmental impact and increasing labor costs for traditional on-site construction. A steel-based module is the ideal structural form for modular construction, owing to its flexibility in architectural design, long span, lightweight, and convenience in connection.This reprint focuses on the cutting-edge research progress in prefabricated and modular steel structures. The topics of this reprint include development and application of different types of prefabricated steel structures, mechanical behavior and design of prefabricated modularized steel structures, and so on.
Intelligent Safety Monitoring and Prevention Process in Coal Mines
This Special Issue collects research papers relating to advances in intelligent safety monitoring and prevention in coal mines. The content covers the safety technology research of coal mine disaster mechanism and risk identification, coal mine disaster multi-information intelligent early warning, coal mine disaster prevention mechanisms, and their intelligent prevention and control. The findings highlight the critical role of technology in protecting workers' lives and ensuring the sustainability of coal mine operations. Our aim is to explore how advanced technologies can effectively reduce risks, prevent accidents, and improve overall safety management in the coal mining industry. We are committed to improving the safety of coal mine operations by identifying and mitigating potential hazards through intelligent monitoring systems. Promoting the safe and efficient, green development, and clean and efficient utilization of coal resources is the only way for the development of the coal industry, and it is also one of the important guarantees for achieving the goal of carbon peak and carbon neutrality. In order to achieve the goal of the safe and efficient mining of coal resources, the intelligence levels of coal mines must be improved. We have deeply studied the intelligent monitoring, early warning, and prevention of coal mine disasters, and contributed our strength to realize the intelligent control of the whole process of mine safety risks and ensure coal mine energy security and green mining.
Data-Driven Intelligent Modeling and Optimization Algorithms for Industrial Processes
The aim of this Special Issue is to explore the multifaceted aspects of data-driven intelligent modeling and optimization algorithms for industrial processes. The main goals are to harness the power of data to improve control, decision making, and parameter optimization and to drive industrial systems to unprecedented levels of efficiency, reliability, and adaptability. Research areas within this scope include data-driven modeling, intelligent data representation, integrated/hybrid modeling, machine learning and optimization, advanced machine learning algorithms, hybrid models with optimization algorithms, adaptive learning algorithms, intelligent process monitoring, real-time data monitoring and analysis, soft sensing technologies, operation mode perception and recognition, decision support systems, intelligent decision support systems, the integration of optimization algorithms, and human-machine collaboration for improved decision making. These powerful intelligent algorithms use data for control, decision making, and parameter optimization, driving industrial systems to unprecedented levels of efficiency, reliability, and adaptability. By sharing their practice and insights in the development and application of these new technologies, the authors of the articles in this Reprint have demonstrated the value of data-driven intelligent modeling and optimization algorithms for industrial processes, providing readers with valuable ideological inspiration in the field.
Information-Theoretic Methods in Deep Learning
The rapid development of deep learning has led to groundbreaking advancements across various fields, from computer vision to natural language processing and beyond. Information theory, as a mathematical foundation for understanding data representation, learning, and communication, has emerged as a powerful tool in advancing deep learning methods. This Special Issue, "Information-Theoretic Methods in Deep Learning: Theory and Applications", presents cutting-edge research that bridges the gap between information theory and deep learning. It covers theoretical developments, innovative methodologies, and practical applications, offering new insights into the optimization, generalization, and interpretability of deep learning models. The collection includes contributions on: Theoretical frameworks combining information theory with deep learning architectures; Entropy-based and information bottleneck methods for model compression and generalization; Mutual information estimation for feature selection and representation learning; Applications of information-theoretic principles in natural language processing, computer vision, and neural network optimization.
Introduction to Bioinformatics and Clinical Scientific Computing
This textbook provides an introduction to computer science theory, informatics best practice, and the standards and legislation that apply to computing in a healthcare environment.
Nonlinear Systems
Open Mathematics is a challenging notion for theoretical modeling, technical analysis, and numerical simulation in the fields of physics and mathematics, among others, as highly correlated nonlinear phenomena, evolving over a large range of time and length scales, control the underlying systems and processes in their spatiotemporal evolution. Indeed, available data, be they physical, biological, or financial, and technologically complex systems and stochastic systems, such as mechanical or electronic devices, can be managed from the same conceptual approach, both analytically and through computer simulation, using effective nonlinear dynamics methods.The aim of this Special Issue is to highlight papers that show the dynamics, control, optimization, and applications of nonlinear systems. This has recently become an increasingly popular subject, with impressive growth concerning applications in engineering, economics, biology, and medicine, and can be considered a veritable contribution to the literature. Original papers relating to the objective presented above are especially welcome subjects.Potential topics include, but are not limited to, the following: Stability analysis of discrete and continuous dynamical systems; Nonlinear dynamics in biological complex systems; Stability and stabilization of stochastic systems; Mathematical models in statistics and probability; Synchronization of oscillators and chaotic systems; Optimization methods of complex systems; Reliability modeling and system optimization; Computation and control over networked systems.
AI-Driven Network Security and Privacy
The security technology of new information technologies in scenarios such as smart life, smart cities, smart networks, etc., and the promotion and enhancement of the development of network security are mainly included here. New-generation network attacks and defense technology, new secure cryptographic algorithms, data security and privacy protection technology, network and communication security protocol, security analysis, and the evaluation of new application scenarios are discussed.
