الصفحة 39
الصفحة 39
Macrophytes in Aquatic Ecosystems : from Biology to Management ; Proceedings of the 11th International Symposium on Aquatic Weeds, European Weed Research Society
Macrophytes and macrophytes ecology have gained an added importance with the introduction of, and legal requirement to implement, the European Water Framework Directive. This reflects the valuable role that aquatic plant communities play in assessing the ecological status of water bodies. Significant changes in the status and general abundance of these communities has been recorded in the last three decades, consequent on such factors as global warming and, increasingly, on the spread of aggressive alien species. These changes have been most felt in those waters that are exploited for amenity and recreational pursuits. The increased biomass of aquatic vegetation in water bodies has adversely impacted on leisure use of these systems but has also impacted on their use for agricultural, flood relief, municipal and domestic purposes. The loss to national economies resulting from this excessive plant biomass has been appreciable and has put pressure on water managers to develop weed control procedures that are efficient, environmentally sensitive and cost-effective.
Macro-Engineering : A Challenge for the Future
Macro-engineering involves the large-scale modification and manipulation of natural systems for the benefit of mankind. The primary goals of some Earth-based macroprojects described in this book are power production, land reclamation, food production, climate change, environment, water, transport and coastal protection. Other Earth or space projects considered here have a more futuristic ring, but our present-day technical skill makes their realization possible. Earth-based macroprojects usually combine different aspects and aims. They have a major impact on the ecology of a region and the inhabitants' means of living (like tourism, fishing, shipping). Its effects may be felt worldwide, like the rise in global sea level after the damming and evaporation of large ocean gulfs for power production, or the change in climate following the regional reduction of solar insolation.
Machine Learning in Computer Vision
The goal of this book is to address the use of several important machine learning techniques into computer vision applications. An innovative combination of computer vision and machine learning techniques has the promise of advancing the field of computer vision, which contributes to better understanding of complex real-world applications. The effective usage of machine learning technology in real-world computer vision problems requires understanding the domain of application, abstraction of a learning problem from a given computer vision task, and the selection of appropriate representations for the learnable (input) and learned (internal) entities of the system. In this book, we address all these important aspects from a new perspective: that the key element in the current computer revolution is the use of machine learning to capture the variations in visual appearance, rather than having the designer of the model accomplish this. As a bonus, models learned from large datasets are likely to be more robust and more realistic than the brittle all-design models.
Machine Learning and Probabilistic Graphical Models for Decision Support Systems
Presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.
Machine learning and its application to reacting flows: ml and combustion
These two fields, ML and turbulent combustion, have large body of work and knowledge on their own, and this book brings them together and explain the complexities and challenges involved in applying ML techniques to simulate and study reacting flows. This is important as to the world’s total primary energy supply (TPES), since more than 90% of this supply is through combustion technologies and the non-negligible effects of combustion on environment. Although alternative technologies based on renewable energies are coming up, their shares for the TPES is are less than 5% currently and one needs a complete paradigm shift to replace combustion sources. The book covers the current state of the art in these two topics and outlines the challenges involved, merits and drawbacks of using ML for turbulent combustion simulations including avenues which can be explored to overcome the challenges.
Machine Learning and Data Mining in Pattern Recognition ; 4th International Conference, MLDM 2005, Leipzig, Germany, July 9-11, 2005, Proceedings
Today, artificial intelligence deals with large amounts of data and knowledge and finds new information using machine learning and data mining. Machine learning and data mining are irreplaceable subjects and tools for the theory of pattern recognition and in applications of pattern recognition such as bioinformatics and data retrieval. This was the fourth edition of MLDM in Pattern Recognition which is the main event of Technical Committee 17 of the International Association for Pattern Recognition; it started out as a workshop and continued as a conference in 2003. Today, there are many international meetings which are titled “machine learning” and “data mining”, whose topics are text mining, knowledge discovery, and applications. This meeting from the first focused on aspects of machine learning and data mining in pattern recognition problems. We planned to reorganize classical and well-established pattern recognition paradigms from the viewpoints of machine learning and data mining. Though it was a challenging program in the late 1990s, the idea has inspired new starting points in pattern recognition and effects in other areas such as cognitive computer vision.
Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks
Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.
Lymphocyte Signal Transduction
Signal transduction through leukocyte receptors involves a variety of signaling molecules including kinases, phosphatases, adaptor proteins, small GTPases GTP exchange factors, membrane phospholipids as well as others. These signal transducers, regulated by inter- and intra-molecular interactions, as well as by various post-translational modifications, lead to the activation of transcription factors that mediate cellular differentiation and growth, effector cell functions, and apoptotic cell death. Several investigators from various parts of the world convened at the 3rd Lymphocyte Signal Transduction Workshop in Crete, Greece from May 27 to June 1, 2005 to discuss their most recent findings in leukocyte signaling. This volume represents a collection of topics discussed during the conference.
Low-Frequency Noise in Advanced MOS Devices
Low-Frequency Noise in Advanced CMOS Devices begins with an introduction to noise, describing the fundamental noise sources and basic circuit analysis. The characterization of low-frequency noise is discussed in detail and useful practical advice is given. The various theoretical and compact low-frequency (1/f) noise models in MOS transistors are treated extensively providing an in-depth understanding of the low-frequency noise mechanisms and the potential sources of the noise in MOS transistors. Advanced CMOS technology including nanometer scaled devices, strained Si, SiGe, SOI, high-k gate dielectrics, multiple gates and metal gates are discussed from a low-frequency noise point of view. Some of the most recent publications and conference presentations are included in order to give the very latest view on the topics. The book ends with an introduction to noise in analog/RF circuits and describes how the low-frequency noise can affect these circuits.
Low-Dose Radiation Effects on Animals and Ecosystems : Long-Term Study on the Fukushima Nuclear Accident
Brings together the works of radiation biologists and ecologists to provide reliable radioecology data and gives insight into future radioprotection. The book examines the environmental pollution and radiation exposure, and contains valuable data from abandoned livestock in the ex-evacuation zone and from wild animals including invertebrates and vertebrates, aqueous and terrestrial animals, and plants that are subjected to long-term exposure in the area still affected by radiation. It also analyzes dose evaluation, and offers new perspectives gained from the accident, as well as an overview for future studies to promote radioprotection of humans and the ecosystem.
Low-Dimensional Molecular Metals
Assimilating new research in the field of low-dimensional metals, this monograph provides a detailed overview of the current status of research on quasi-one- and two-dimensional molecular metals, describing normal-state properties, magnetic field effects, superconductivity, and the phenomena of interacting p and d electrons. It will be useful not only for frontier researchers with a broad interest in low-dimensional electronic and magnetic properties, but also for graduate students of solid-state physics and chemistry with some background knowledge of solid-state physics. It includes a number of fundamental and novel findings relating to the characteristics of these low-dimensional metals, which in future are likely to become standard material in textbooks on solid-state physics.
Low-Cost Country Sourcing : Trends and Implications
Globalization has induced immense cost pressure in most industries. In combination with the economic downturn after the turn of the century, companies are increasingly looking for new ways of reducing costs and increasing shareholder value. From this perspective, low-cost country sourcing has proved to be an effective means to realize cost-saving targets. Although many external key success factors have been identified, relatively little is known about intra-firm factors that can influence the outcome of low-cost country sourcing initiatives.
Loss and Damage from Climate Change : Concepts, Methods and Policy Options
Provides an authoritative insight on the Loss and Damage discourse by highlighting state-of-the-art research and policy linked to this discourse and articulating its multiple concepts, principles and methods. Written by leading researchers and practitioners, it identifies practical and evidence-based policy options to inform the discourse and climate negotiations. With climate-related risks on the rise and impacts being felt around the globe has come the recognition that climate mitigation and adaptation may not be enough to manage the effects from anthropogenic climate change.
Longs COVID-19 patients
Nearly 250 million people around the world have recovered from Covid-19. But here, the word "recovered" refers only to the acute phase of the illness. Approximately 10 and 40 percent of Covid patients continue to experience symptoms several weeks to months after falling sick, a nebulous condition now referred to as post-Covid condition, or long Covid. In long Covid, we are witnessing the emergence of a legitimate new illness, officially recognized by the World Health Organization's International Classification of Diseases...
Logistics Outsourcing Relationships : Measurement, Antecedents, and Effects of Logistics Outsourcing Performance
In recent years, logistics outsourcing has gained increasing importance and today is used by a large number of firms across virtually all industries worldwide. Logistics service providers have developed a wide array of services that are utilized to improve logistics processes - and mainly to cut costs.This book uses state-of-the-art scientific methods to reveal that most firms currently do not realize the full potential of logistics outsourcing. It shows the complexity of outsourcing performance and that its true drivers lie in the relationship between service providers and their customers. Through the results of a large-scale empirical survey, the book also emphasizes the importance of a firm's approach towards outsourcing: solely striving for cost reductions may be a dead end, while the often overlooked increased logistics service levels are equally important for boosting logistics performance. In the light of current outsourcing practices, this indicates substantial room for improvement for most firms.
Local anesthesia in dentistry : A locoregional approach
Provides comprehensive coverage of all aspects of local anesthetics, including anatomic considerations, pharmacology, armamentarium, injection techniques, indications, contraindications, complications, novel anesthetics formulations, and more.
Local anesthesia for the dental hygienist
Provides complete instructions for the safe and effective administration of local anesthesia. Written by noted dental hygiene educator Demetra Logothetis, the first edition won a 2012 PROSE Honorable Mention award. This edition adds a new chapter on children and adolescent patients, plus new coverage of anesthetic agents and advanced techniques.
Local Anaesthesia in Dentistry
A comprehensive guide to the use of local anaesthesia in dentistry that will meet the needs of both students and dental practitioners. It provides the reader with ample background information on the origin of pain and the pharmacology of anaesthetics, and describes the anatomy of the trigeminal nerve in detail. Subsequent chapters cover key are as such as general practical aspects, local anesthaesia in the upper and the lower jaw, the use of local anaesthetics in children, local and systematic complications, and the prevention of side effects. Patients at particular risk of adverse effects are identified and attention drawn to significant legal aspects.
Load balancing using SDN
Software-Defined Network (SDN) is considered a breakthrough to the global network. It plays an important role in performance improvement and network optimization. SDN is a new mechanism for managing and designing networks rather than the current traditional network system which does not afford more services and higher data rates; therefore, we analyze the effect of applying load balancing techniques and its importance in different SDN environments. In this paper, we propose a dynamic server load balancing technique in SDN architecture. Hence, we implement a server Connection-based load balancing technique and evaluate its performance with a static Round-robin and Random-based in both mininet emulation environment and OpenFlow-enabled switch using Ryu OpenFlow controller.
Liquid separations with membranes : An introduction to barrier interference
On the level of a textbook a self-consistent approach to liquid separations with membranes is presented, contrasting equilibrium separations with the rate-controlling effects of barrier interference on mass transfer. As a corollary objective, an effort is made to observe context, factual and historical, when introducing concepts and applications of membrane separation science. Ordering principle is the formal structure of mass transfer across barriers, being construed of a driving force (allocated to the condition of the mixtures to be separated) and a barrier permeability (holding the keys to membrane selectivity). The membranes, by this approach, appear by way of the mass transport demands which they are to meet, or else by way of the separation effects which they inspire.
