Xiaodong Li – författare

This book offers a comprehensive exploration of brain tumors, beginning with a foundational understanding of their pathophysiology and extending through the latest advancements in diagnosis and treatment. The chapters examine the underlying mechanisms that drive the development and progression of brain tumors and present a detailed analysis of the incidence, distribution, and potential risk factors associated with brain tumors. The book explores the intricate relationship between brain tumors and visual disorders, and reviews the critical role of advanced imaging technologies in diagnosing brain tumors, evaluating the strengths and limitations of various modalities such as MRI and PET scans. Additionally, the book evaluates the effectiveness and precision of radiosurgery in targeting brain tumors, discussing its benefits and challenges in the context of non-invasive cancer treatment. The chapters also introduce us to antisense oligonucleotides as a novel therapeutic strategy, outlining their mechanism of action and potential to silence cancer-driving genes. The book highlights the latest developments in nanotechnology for brain tumor diagnosis, emphasizing the use of nanomaterials to enhance imaging quality and specificity.Key Features:Provides a thorough exploration of brain tumors, from basic pathophysiology to advanced treatment optionsPresents detailed analyses of the incidence, distribution, and potential risk factors associated with brain tumorsDiscusses the critical role of imaging technologies, including MRI and PET scans, in the diagnosis of brain tumorsIntroduces novel therapeutic strategies such as radiosurgery and antisense oligonucleotides for targeting brain tumorsExamines strategies to overcome the blood–brain barrier for effective drug deliveryToward the end, the book covers challenges of and strategies for delivering therapeutic agents across the blood–brain barrier and discusses phytochemicals in brain tumor treatment. This book serves as a useful source for researchers and students in oncology and neuroscience.

This book constitutes the proceedings of the 31st Australasian Joint Conference on Artificial Intelligence, AI 2018, held in Wellington, New Zealand, in December 2018.The 50 full and 26 short papers presented in this volume were carefully reviewed and selected from 125 submissions. The paper were organized in topical sections named: agents, games and robotics; AI applications and innovations; computer vision; constraints and search; evolutionary computation; knowledge representation and reasoning; machine learning and data mining; planning and scheduling; and text mining and NLP.

This book presents the latest trends and developments in multimodal optimization and niching techniques. Most existing optimization methods are designed for locating a single global solution. However, in real-world settings, many problems are “multimodal” by nature, i.e., multiple satisfactory solutions exist. It may be desirable to locate several such solutions before deciding which one to use. Multimodal optimization has been the subject of intense study in the field of population-based meta-heuristic algorithms, e.g., evolutionary algorithms (EAs), for the past few decades. These multimodal optimization techniques are commonly referred to as “niching” methods, because of the nature-inspired “niching” effect that is induced to the solution population targeting at multiple optima. Many niching methods have been developed in the EA community. Some classic examples include crowding, fitness sharing, clearing, derating, restricted tournament selection, speciation, etc.Nevertheless, applying these niching methods to real-world multimodal problems often encounters significant challenges.To facilitate the advance of niching methods in facing these challenges, this edited book highlights the latest developments in niching methods. The included chapters touch on algorithmic improvements and developments, representation, and visualization issues, as well as new research directions, such as preference incorporation in decision making and new application areas. This edited book is a first of this kind specifically on the topic of niching techniques.This book will serve as a valuable reference book both for researchers and practitioners. Although chapters are written in a mutually independent way, Chapter 1 will help novice readers get an overview of the field. It describes the development of the field and its current state and provides a comparative analysis of the IEEE CEC and ACM GECCO niching competitions of recent years, followed by a collection of open research questions and possible research directions that may be tackled in the future.

This book presents the latest trends and developments in multimodal optimization and niching techniques. Most existing optimization methods are designed for locating a single global solution. However, in real-world settings, many problems are “multimodal” by nature, i.e., multiple satisfactory solutions exist. It may be desirable to locate several such solutions before deciding which one to use. Multimodal optimization has been the subject of intense study in the field of population-based meta-heuristic algorithms, e.g., evolutionary algorithms (EAs), for the past few decades. These multimodal optimization techniques are commonly referred to as “niching” methods, because of the nature-inspired “niching” effect that is induced to the solution population targeting at multiple optima. Many niching methods have been developed in the EA community. Some classic examples include crowding, fitness sharing, clearing, derating, restricted tournament selection, speciation, etc.Nevertheless, applying these niching methods to real-world multimodal problems often encounters significant challenges.To facilitate the advance of niching methods in facing these challenges, this edited book highlights the latest developments in niching methods. The included chapters touch on algorithmic improvements and developments, representation, and visualization issues, as well as new research directions, such as preference incorporation in decision making and new application areas. This edited book is a first of this kind specifically on the topic of niching techniques.This book will serve as a valuable reference book both for researchers and practitioners. Although chapters are written in a mutually independent way, Chapter 1 will help novice readers get an overview of the field. It describes the development of the field and its current state and provides a comparative analysis of the IEEE CEC and ACM GECCO niching competitions of recent years, followed by a collection of open research questions and possible research directions that may be tackled in the future.

This volume constitutes the proceedings of the 10th International Conference on Simulated Evolution and Learning, SEAL 2012, held in Dunedin, New Zealand, in December 2014. The 42 full papers and 29 short papers presented were carefully reviewed and selected from 109 submissions. The papers are organized in topical sections on evolutionary optimization; evolutionary multi-objective optimization; evolutionary machine learning; theoretical developments; evolutionary feature reduction; evolutionary scheduling and combinatorial optimization; real world applications and evolutionary image analysis.

This bookconstitutes the proceedings of the Second Australasian Conference on ArtificialLife and Computational Intelligence, ACALCI 2016, held in Canberra, ACT,Australia, in February 2016. The 30 fullpapers presented in this volume were carefully reviewed and selected from 41submissions.

This book constitutes the proceedings of the 10th International Conference on Swarm Intelligence, ANTS 2016, held in Brussels, Belgium, in September 2016. The 18 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 47 submissions.

This book constitutes the refereed proceedings of the Third Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2017, held in Geelong, VIC, Australia, in January/February 2017. They were organized in topical sections named: artificial life and computational intelligence and optimization algorithms and applications.

This book constitutes the refereed proceedings of the 30th Australasian Joint Conference on Artificial Intelligence, AI 2017, held in Melbourne, VIC, Australia, in August 2017.

This book constitutes the refereed proceedings of the 11th International Conference on Simulated Evolution and Learning, SEAL 2017, held in Shenzhen, China, in November 2017. They were organized in topical sections named: evolutionary optimisation; evolutionary multiobjective optimisation; evolutionary machine learning;

This book constitutes the refereed proceedings of the 6th International Conference on Simulated Evolution and Learning, SEAL 2006, held in Hefei, China in October 2006. The 117 revised full papers presented were carefully reviewed and selected from 420 submissions.

This LNCS volume contains the papers presented at SEAL 2008, the 7th Int- nationalConference on Simulated Evolutionand Learning,held December 7–10, 2008, in Melbourne, Australia. SEAL is a prestigious international conference series in evolutionary computation and learning. This biennial event was ?rst held in Seoul, Korea, in 1996, and then in Canberra, Australia (1998), Nagoya, Japan (2000), Singapore (2002), Busan, Korea (2004), and Hefei, China (2006). SEAL 2008 received 140 paper submissions from more than 30 countries. After a rigorous peer-review process involving at least 3 reviews for each paper (i.e., over 420 reviews in total), the best 65 papers were selected to be presented at the conference and included in this volume, resulting in an acceptance rate of about 46%. The papers included in this volume cover a wide range of topics in simulated evolution and learning: from evolutionarylearning to evolutionary optimization, from hybrid systems to adaptive systems, from theoretical issues to real-world applications. They represent some of the latest and best research in simulated evolution and learning in the world.

This book constitutes the refereed proceedings of the 22nd Australasian Joint Conference on Artificial Intelligence, AI 2009, held in Melbourne, Australia, in December 2009. The 68 revised full papers presented were carefully reviewed and selected from 174 submissions. The papers are organized in topical sections on agents; AI applications; computer vision and image processing; data mining and statistical learning; evolutionary computing; game playing; knowledge representation and reasoning; natural language and speech processing; soft computing; and user modelling.

COVID-19 is a severe and complex epidemic ravaging many countries. Traditional Chinese medicine (TCM) has accumulated rich experience and achieved outstanding effects in its struggle against epidemics for thousands of years. As an essential intervention means for prevention and control of COVID-19, TCM boasts significant effects in relieving fever symptoms, slowing down disease progression, preventing disease transformation, reducing hormone dosage, and alleviating complications. Establishing and improving the emergency supply service mode of Chinese medicine in response to public health emergencies, and scientifically managing and allocating Chinese medicine medical resources are conducive to establishing a green channel for the emergency supply of Chinese medicine in response to major public health emergencies.This book focuses on the four oral Chinese patent medicines used in the clinical treatment period based on the Guidelines for the Diagnosis and Treatment of COVID-19 by the National Health Commission and National Administration of Traditional Chinese Medicine of China.This work is not only an important part of the theoretical system of TCM treatment based on syndrome differentiation but also an effective way to promote an even deeper integration of clinical pharmaceutical service and clinical medical practice.

This book introduces readers to using the simple but effective Zhang-gradient (ZG) method to solve tracking-control problems concerning various nonlinear systems, while also highlighting the applications of the ZG method to tracking control for practical systems, e.g.

This book introduces readers to using the simple but effective Zhang-gradient (ZG) method to solve tracking-control problems concerning various nonlinear systems, while also highlighting the applications of the ZG method to tracking control for practical systems, e.g.

This book introduces the current state of research on dark energy. It consists of three parts. The first part is for preliminary knowledge, including general relativity, modern cosmology, etc. The second part reviews major theoretical ideas and models of dark energy. The third part reviews some observational and numerical works. The aim of this book is to provide a sufficient level of understanding of dark energy problems, so that the reader can both get familiar with this area quickly and also be prepared to tackle the scientific literature on this subject. It will be useful for graduate students and researchers who are interested in dark energy.

This two-volume set LNCS 15512-15513 constitutes the proceedings of the 13th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2025, held in Canberra, ACT, Australia, in March 2025.The 38 full papers and 2 extended abstracts presented in this book were carefully reviewed and selected from 63 submissions. The papers are divided into the following topical sections:Part I : Algorithm design; Benchmarking; Applications.Part II : Algorithm analysis; Surrogates and machine learning; Multi-criteria decision support.