The book shows how eastern and western perspectives and conceptions can be used to addresses recent topics laying at the crossroad between philosophy and cognitive science. It reports on new points of view and conceptions discussed during the International Conference on Philosophy and Cognitive Science (PCS2013), held at the Sun Yat-sen University, in Guangzhou, China, and the 2013 Workshop on Abductive Visual Cognition, which took place at KAIST, in Deajeon, South Korea. The book emphasizes an ever-growing cultural exchange between academics and intellectuals coming from different fields. It juxtaposes research works investigating new facets on key issues between philosophy and cognitive science, such as the role of models and causal representations in science; the status of theoretical concepts and quantum principles; abductive cognition, vision, and visualization in science from an eco-cognitive perspective. Further topics are: ignorance immunization in reasoning; moral cognition, violence, and epistemology; and models and biomorphism. The book, which presents a unique and timely account of the current state-of-the art on various aspects in philosophy and cognitive science, is expected to inspire philosophers, cognitive scientists and social scientists, and to generate fruitful exchanges and collaboration among them.

Between Certainty & Uncertainty is a one-of a-kind short course on statistics for students, engineers and researchers. It is a fascinating introduction to statistics and probability with notes on historical origins and 80 illustrative numerical examples organized in the five units:

. Chapter 1 "Descriptive Statistics" Compressing small samples, basic averages - mean and variance, their main properties including God s proof; linear transformations and "z-scored" statistics .

. Chapter 2 "Grouped data" Udny Yule s concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles.

. Chapter 3 "Regression and correlation" Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right? Houbolt s cloud. What in fact measures the correlation coefficient?

. Chapter 4 "Binomial distribution" Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal s Arithmetical Triangle. Bernoulli s or Poisson Trials? John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli s Weak Law of Large Numbers and others.

. Chapter 5 "Normal distribution and binomial heritage" Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace.

. Chapter 1 "Descriptive Statistics" Compressing small samples, basic averages - mean and variance, their main properties including God s proof; linear transformations and "z-scored" statistics .

. Chapter 2 "Grouped data" Udny Yule s concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles.

. Chapter 3 "Regression and correlation" Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right? Houbolt s cloud. What in fact measures the correlation coefficient?

. Chapter 4 "Binomial distribution" Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal s Arithmetical Triangle. Bernoulli s or Poisson Trials? John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli s Weak Law of Large Numbers and others.

. Chapter 5 "Normal distribution and binomial heritage" Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace.

. Chapter 5 "Normal distribution and binomial heritage" Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace.

"

This book discusses topics related to bioinformatics, statistics, and machine learning, presenting the latest research in various areas of bioinformatics. It also highlights the role of computing and machine learning in knowledge extraction from biological data, and how this knowledge can be applied in fields such as drug design, health supplements, gene therapy, proteomics and agriculture.

The book conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in financial systems when these are described in the form of nonlinear ordinary differential equations. It then addresses problems associated with the control and estimation of financial systems governed by partial differential equations (e.g. the Black-Scholes partial differential equation (PDE) and its variants). Lastly it an offers optimal solution to the problem of statistical validation of computational models and tools used to support financial engineers in decision making. The application of state-space models in financial engineering means that the heuristics and empirical methods currently in use in decision-making procedures for finance can be eliminated. It also allows methods of fault-free performance and optimality in the management of assets and capitals and methods assuring stability in the functioning of financial systems to be established. Covering the following key areas of financial engineering: (i) control and stabilization of financial systems dynamics, (ii) state estimation and forecasting, and (iii) statistical validation of decision-making tools, the book can be used for teaching undergraduate or postgraduate courses in financial engineering. It is also a useful resource for the engineering and computer science community

This book presents a collection of research findings and proposals on computer science and computer engineering, introducing readers to essential concepts, theories, and applications. It also shares perspectives on how cutting-edge and established methodologies and techniques can be used to obtain new and interesting results. Each chapter focuses on a specific aspect of computer science or computer engineering, such as: software engineering, complex systems, computational intelligence, embedded systems, and systems engineering. As such, the book will bring students and professionals alike up to date on key advances in these areas.

Call Admission Control (CAC) and Dynamic Channel Assignments (DCA) are important decision-making problems in mobile cellular communication systems. Current research in mobile communication considers them as two independent problems, although the former greatly depends on the resulting free channels obtained as the outcome of the latter. This book provides a solution to the CAC problem, considering DCA as an integral part of decision-making for call admission. Further, current technical resources ignore movement issues of mobile stations and fluctuation in network load (incoming calls) in the control strategy used for call admission. In addition, the present techniques on call admission offers solution globally for the entire network, instead of considering the cells independently. CAC here has been formulated by two alternative approaches. The first approach aimed at handling the uncertainty in the CAC problem by employing fuzzy comparators. The second approach is concerned with formulation of CAC as an optimization problem to minimize call drop, satisfying a set of constraints on feasibility and availability of channels, hotness of cells, and velocity and angular displacement of mobile stations. Evolutionary techniques, including Genetic Algorithm and Biogeography Based Optimization, have been employed to solve the optimization problems. The proposed approaches outperform traditional methods with respect to grade and quality of services.

This book presents recent applications and approaches as well as challenges in digital forensic science. One of the evolving challenges that is covered in the book is the cloud forensic analysis which applies the digital forensic science over the cloud computing paradigm for conducting either live or static investigations within the cloud environment. The book also covers the theme of multimedia forensics and watermarking in the area of information security. That includes highlights on intelligence techniques designed for detecting significant changes in image and video sequences. Moreover, the theme proposes recent robust and computationally efficient digital watermarking techniques. The last part of the book provides several digital forensics related applications, including areas such as evidence acquisition enhancement, evidence evaluation, cryptography, and finally, live investigation through the importance of reconstructing the botnet attack scenario to show the malicious activities and files as evidences to be presented in a court.

This book contains an edited selection of the papers accepted for presentation and discussion at the first International Symposium on Qualitative Research (ISQR2016), held in Porto, Portugal, July 12th-14th, 2016. The book and the symposium features the four main application fields Education, Health, Social Sciences and Engineering and Technology and seven main subjects: Rationale and Paradigms of Qualitative Research (theoretical studies, critical reflection about epistemological dimensions, ontological and axiological); Systematization of approaches with Qualitative Studies (literature review, integrating results, aggregation studies, meta -analysis, meta- analysis of qualitative meta- synthesis, meta- ethnography); Qualitative and Mixed Methods Research (emphasis in research processes that build on mixed methodologies but with priority to qualitative approaches); Data Analysis Types (content analysis , discourse analysis , thematic analysis , narrative analysis , etc.); Innovative processes of Qualitative Data Analysis (design analysis, articulation and triangulation of different sources of data - images, audio, video); Qualitative Research in Web Context (eResearch, virtual ethnography, interaction analysis , latent corpus on the internet, etc.); Qualitative Analysis with Support of Specific Software (usability studies, user experience, the impact of software on the quality of research.

This paper collection is the second volume of the LNMOB series on Road Vehicle Automation. The book contains a comprehensive review of current technical, socio-economic, and legal perspectives written by experts coming from public authorities, companies and universities in the U.S., Europe and Japan. It originates from the Automated Vehicle Symposium 2014, which was jointly organized by the Association for Unmanned Vehicle Systems International (AUVSI) and the Transportation Research Board (TRB) in Burlingame, CA, in July 2014. The contributions discuss the challenges arising from the integration of highly automated and self-driving vehicles into the transportation system, with a focus on human factors and different deployment scenarios. This book is an indispensable source of information for academic researchers, industrial engineers, and policy makers interested in the topic of road vehicle automation.

This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics. Accordingly, there is a pressing need for novel and innovative algorithms to help us find effective solutions in industrial application areas such as media, healthcare, travel, finance, and retail. In all of these areas, data is the crucial parameter, and the main key to unlocking the value of industry. The book presents a range of intelligent algorithms that can be used to filter useful information in the above-mentioned application areas and efficiently solve particular problems. Its main objective is to raise awareness for this important field among students, researchers, and industrial practitioners.

This book explores the inputs with regard to individuals and companies who have developed technologies and innovative solutions, bioinformatics, datasets, apps for diagnosis, etc., that can be leveraged for strengthening the fight against coronavirus. It focuses on technology solutions to stop Covid-19 outbreak and mitigate the risk. The book contains innovative ideas from active researchers who are presently working to find solutions, and they give insights to other researchers to explore the innovative methods and predictive modeling techniques. The novel applications and techniques of established technologies like artificial intelligence (AI), Internet of things (IoT), big data, computer vision and machine learning are discussed to fight the spread of this disease, Covid-19. This pandemic has triggered an unprecedented demand for digital health technology solutions and unleashing information technology to win over this pandemic.

The theme of this book is the self-generation of information by the self-modification of systems. The author explains why biological and cognitive processes exhibit identity changes in the mathematical and logical sense. This concept is the basis of a new organizational principle which utilizes shifts of the internal semantic relations in systems. There are mathematical discussions of various classes of systems (Turing machines, input-output systems, synergetic systems, non-linear dynamics etc), which are contrasted with the author's new principle. The most important implications of this include a new conception on the nature of information and which also provides a new and coherent conceptual view of a wide class of natural systems. This book merits the attention of all philosophers and scientists concerned with the way we create reality in our mathematical representations of the world and the connection those representations have with the way things really are.

This book contains selected papers from the 9th International Conference on Information Science and Applications (ICISA 2018) and provides a snapshot of the latest issues encountered in technical convergence and convergences of security technology. It explores how information science is core to most current research, industrial and commercial activities and consists of contributions covering topics including Ubiquitous Computing, Networks and Information Systems, Multimedia and Visualization, Middleware and Operating Systems, Security and Privacy, Data Mining and Artificial Intelligence, Software Engineering, and Web Technology. The proceedings introduce the most recent information technology and ideas, applications and problems related to technology convergence, illustrated through case studies, and reviews converging existing security techniques. Through this volume, readers will gain an understanding of the current state-of-the-art information strategies and technologies of convergence security. The intended readership includes researchers in academia, industry and other research institutes focusing on information science and technology.

Creating Knowledge Based Organizations brings together high quality concepts closely related to organizational learning, knowledge workers, intellectual capital, virtual teams and will include the methodologies, systems and approaches needed to create and manager knowledge-based organizations of the 21st Century.

This book provides an opportunity for investigators, government officials, systems scientists, strategists, assurance researchers, owners, operators and maintainers of large, complex and advanced systems and infrastructures to update their knowledge with the state of best practice in the challenging domains whilst networking with the leading representatives, researchers and solution providers. Drawing on 12 years of successful events on information security, digital forensics and cyber-crime, the 13th ICGS3-20 conference aims to provide attendees with an information-packed agenda with representatives from across the industry and the globe. The challenges of complexity, rapid pace of change and risk/opportunity issues associated with modern products, systems, special events and infrastructures. In an era of unprecedented volatile, political and economic environment across the world, computer-based systems face ever more increasing challenges, disputes and responsibilities, and whilst the Internet has created a global platform for the exchange of ideas, goods and services, it has also created boundless opportunities for cyber-crime. As an increasing number of large organizations and individuals use the Internet and its satellite mobile technologies, they are increasingly vulnerable to cyber-crime threats. It is therefore paramount that the security industry raises its game to combat these threats. Whilst there is a huge adoption of technology and smart home devices, comparably, there is a rise of threat vector in the abuse of the technology in domestic violence inflicted through IoT too. All these are an issue of global importance as law enforcement agencies all over the world are struggling to cope.

This book presents an Intelligent Control Architecture (ICA) to enable multiple collaborating marine vehicles to autonomously carry out underwater intervention missions. The presented ICA is generic in nature but aimed at a case study where a marine surface craft and an underwater vehicle are required to work cooperatively. It is shown that they are capable of cooperating autonomously towards the execution of complex activities since they have different but complementary capabilities. The ICA implementation is verified in simulation, and validated in trials by means of a team of autonomous marine robots. This book also presents architectural details and evaluation scenarios of the ICA, results of simulations and trials from different maritime operations, and future research directions.

This book features a collection of high-quality, peer-reviewed research papers presented at the 7th International Conference on Innovations in Computer Science & Engineering (ICICSE 2019), held at Guru Nanak Institutions, Hyderabad, India, on 16-17 August 2019. Written by researchers from academia and industry, the book discusses a wide variety of industrial, engineering, and scientific applications of the emerging techniques in the field of computer science.

This book is dedicated to the theory and applications of Intelligent Systems. Research and development in the Intelligent Systems area is growing rapidly due to many successful applications of these new techniques in very diverse problems. Intelligent Systems and Techniques covers many fields such as neural networks, (adaptive) fuzzy logic, evolutionary computing and their hybrids and derivatives. This book aims to provide highlights of the current research in the Intelligent Systems area. It consists of research papers in the fields of neural networks, fuzzy logic, genetic algorithms and evolutionary computing, knowledge acquisition and knowledge discovery, intelligent agents, image processing, robotics and automation, speech recognition, signal processing and control, data mining and information retrieval, case-based reasoning and clustering.

This book primarily addresses Intelligent Information Systems (IIS) and the integration of artificial intelligence, intelligent systems and technologies, database technologies and information systems methodologies to create the next generation of information systems. It includes original and state-of-the-art research on theoretical and practical advances in IIS, system architectures, tools and techniques, as well as "success stories" in intelligent information systems. Intended as an interdisciplinary forum in which scientists and professionals could share their research results and report on new developments and advances in intelligent information systems, technologies and related areas - as well as their applications - , it offers a valuable resource for researchers and practitioners alike.

This book introduces Industrial AI in multiple dimensions. Industrial AI is a systematic discipline which focuses on developing, validating and deploying various machine learning algorithms for industrial applications with sustainable performance. Combined with the state-of-the-art sensing, communication and big data analytics platforms, a systematic Industrial AI methodology will allow integration of physical systems with computational models. The concept of Industrial AI is in infancy stage and may encompass the collective use of technologies such as Internet of Things, Cyber-Physical Systems and Big Data Analytics under the Industry 4.0 initiative where embedded computing devices, smart objects and the physical environment interact with each other to reach intended goals. A broad range of Industries including automotive, aerospace, healthcare, semiconductors, energy, transportation, mining, construction, and industrial automation could harness the power of Industrial AI to gain insights into the invisible relationship of the operation conditions and further use that insight to optimize their uptime, productivity and efficiency of their operations. In terms of predictive maintenance, Industrial AI can detect incipient changes in the system and predict the remains useful life and further to optimize maintenance tasks to avoid disruption to operations.

This book presents a study in knowledge discovery in data with knowledge understood as a set of relations among objects and their properties. Relations in this case are implicative decision rules and the paradigm in which they are induced is that of computing with granules defined by rough inclusions, the latter introduced and studied within rough mereology, the fuzzified version of mereology. In this book basic classes of rough inclusions are defined and based on them methods for inducing granular structures from data are highlighted. The resulting granular structures are subjected to classifying algorithms, notably k-nearest neighbors and bayesian classifiers. Experimental results are given in detail both in tabular and visualized form for fourteen data sets from UCI data repository. A striking feature of granular classifiers obtained by this approach is that preserving the accuracy of them on original data, they reduce substantially the size of the granulated data set as well as the set of granular decision rules. This feature makes the presented approach attractive in cases where a small number of rules providing a high classification accuracy is desirable. As basic algorithms used throughout the text are explained and illustrated with hand examples, the book may also serve as a textbook.

This book provides a self-study program on how mathematics, computer science and science can be usefully and seamlessly intertwined. Learning to use ideas from mathematics and computation is essential for understanding approaches to cognitive and biological science. As such the book covers calculus on one variable and two variables and works through a number of interesting first-order ODE models. It clearly uses MatLab in computational exercises where the models cannot be solved by hand, and also helps readers to understand that approximations cause errors - a fact that must always be kept in mind.

This book provides a comprehensive review and in-depth study on efficient beamforming design and rigorous performance analysis in mmWave networks, covering beam alignment, beamforming training and beamforming-aided caching. Due to significant beam alignment latency between the transmitter and the receiver in existing mmWave systems, this book proposes a machine learning based beam alignment algorithm for mmWave networks to determine the optimal beam pair with a low latency. Then, to analyze and enhance the performance of beamforming training (BFT) protocol in 802.11ad mmWave networks, an analytical model is presented to evaluate the performance of BFT protocol and an enhancement scheme is proposed to improve its performance in high user density scenarios. Furthermore, it investigates the beamforming-aided caching problem in mmWave networks, and proposes a device-to-device assisted cooperative edge caching to alleviate backhaul congestion and reduce content retrieval delay. This book concludes with future research directions in the related fields of study. The presented beamforming designs and the corresponding research results covered in this book, provides valuable insights for practical mmWave network deployment and motivate new ideas for future mmWave networking. This book targets researchers working in the fields of mmWave networks, beamforming design, and resource management as well as graduate students studying the areas of electrical engineering, computing engineering and computer science. Professionals in industry who work in this field will find this book useful as a reference.

This book is concerned with recent advances in fitness landscapes. The concept of fitness landscapes originates from theoretical biology and refers to a framework for analysing and visualizing the relationships between genotypes, phenotypes and fitness. These relationships lay at the centre of attempts to mathematically describe evolutionary processes and evolutionary dynamics.

The book addresses recent advances in the understanding of fitness landscapes in evolutionary biology and evolutionary computation. In the volume, experts in the field of fitness landscapes present these findings in an integrated way to make it accessible to a number of audiences: senior undergraduate and graduate students in computer science, theoretical biology, physics, applied mathematics and engineering, but also researcher looking for a reference or/and entry point into using fitness landscapes for analysing algorithms. Also practitioners wanting to employ fitness landscape techniques for evaluating bio- and nature-inspired computing algorithms can find valuable material in the book. For teaching proposes, the book could also be used as a reference handbook.

This book covers the further advances in the field of the Internet of things, biomedical engineering and cyber physical system with recent applications. It is covering the various real-time, offline applications, and case studies in the field of recent technologies and case studies of the Internet of things, biomedical engineering and cyber physical system with recent technology trends. In the twenty-first century, the automation and management of data are vital, in that, the role of the Internet of things proving the potential support. The book is consisting the excellent work of researchers and academician who are working in the domain of emerging technologies, e.g., Internet of things, biomedical engineering and cyber physical system. The chapters cover the major achievements by solving and suggesting many unsolved problems, which am sure to be going to prove a strong support in industries towards automation goal using of the Internet of things, biomedical engineering and cyber physical system.