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The demand for advance telecommunication services has increased dramatically over the last few years. This has led to technological changes with revolutionized engineering strategies to optimize network construction and operation. Telecommunication networks integrate with a wide range of technologies, including optical amplifiers, software architectures for network control and management, abstract algebra required to design error correction codes, and network modeling. This book presents research contributions towards new techniques, concepts, analysis of the telecom market's evolving trends, and infrastructure to provide integrated voice, data, and video communications services that are critical to the operation and competitiveness of companies, governments, and other organizations.
TheInternetisamassiveglobalnetworkofover700millionusersanditisadding users at the rate of 300,000 per day. This large, distributed, and everchanging network poses a challenge to researchers: How does one study, model, or und- stand such a decentralized, constantly evolving entity? Research in large-scale networks seeks to address this question, and the unique nature of these networks calls for a range of techniques from a host of disciplines. The workshop Com- natorial and Algorithmic Aspects of Networking and the Internet (CAAN 2004) provided a forum for the exchange of ideas on these topics. The primary goals of the workshop were to bring together a diverse cro- section of researchers in an already scattered and distinct community and also to provide a snapshot of the cutting-edge research in this?eld. We succeeded in these goals: among the participants were mathematicians, computer scientists in theory and algorithms, computer scientists in networks, physicists, and en- neers, as well as researchers from Europe and North America, participants from industry and academia, students, and established researchers; and among the papers were some new and surprising results as well as some introductions to the foundations of the?eld. Theworkshopprogramfeatured12peer-reviewedpapersbracketedbytwoho- longinvitedsurveytalks anopeningtalkbyAshishGoelandaclosingtalkby- dreiBroder. TopicscoveredbythetalksrangedfromtheWebgraphtogametheory tostringmatching, allinthecontextoflarge-scalenetworks. Thisvolumecollects togetherthetalksdeliveredattheworkshopalongwithanumberofsurveyarticles toroundoutthepresentationandgiveacomprehensiveintroductiontothetopic.
This book explores outcome modeling in cancer from a data-centric perspective to enable a better understanding of complex treatment response, to guide the design of advanced clinical trials, and to aid personalized patient care and improve their quality of life. It contains coverage of the relevant data sources available for model construction (panomics), ranging from clinical or preclinical resources to basic patient and treatment characteristics, medical imaging (radiomics), and molecular biological markers such as those involved in genomics, proteomics and metabolomics. It also includes discussions on the varying methodologies for predictive model building with analytical and data-driven approaches. This book is primarily intended to act as a tutorial for newcomers to the field of outcome modeling, as it includes in-depth how-to recipes on modeling artistry while providing sufficient instruction on how such models can approximate the physical and biological realities of clinical treatment. The book will also be of value to seasoned practitioners as a reference on the varying aspects of outcome modeling and their current applications. Features: Covers top-down approaches applying statistical, machine learning, and big data analytics and bottom-up approaches using first principles and multi-scale techniques, including numerical simulations based on Monte Carlo and automata techniques Provides an overview of the available software tools and resources for outcome model development and evaluation, and includes hands-on detailed examples throughout Presents a diverse selection of the common applications of outcome modeling in a wide variety of areas: treatment planning in radiotherapy, chemotherapy and immunotherapy, utility-based and biomarker applications, particle therapy modeling, oncological surgery, and the design of adaptive and SMART clinical trials
The human brain is extraordinary complex and yet its origin is a simple tubular structure. Rapid and dramatic structural growth takes place during the fetal and perinatal period. By the time of birth, a repertoire of major cortical, subcortical and white matter structures resembling the adult pattern has emerged, however there are continued maturational changes of the gray matter and white matter throughout childhood and adolescence and into adulthood. The maturation of neuronal structures provides the neuroanatomical basis for the acquisition and refinement of cognitive functions during postnatal development. Histological imaging has been traditionally dominant in understanding neuroanatomy of early brain development and still plays an unparalleled role in this field. Modern magnetic resonance imaging (MRI) techniques including diffusion MRI, as noninvasive tools readily applied to in vivo brains, have become an important complementary approach in revealing the detailed brain anatomy, including the structural connectivity between brain regions. In this research topic, we presented the most recent investigations on understanding the neuroanatomy and connectivity of human brain development using both histology and MRI. Modern advances in mapping normal developmental brain anatomy and connectivity should elucidate many neurodevelopmental disorders, ranging from rare congenital malformations to common disorders such as autism and attention deficit hyperactivity disorder (ADHD), which is a prerequisite for better diagnosis and treatment of these currently poorly understood diseases.