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• Introduction
• Belkin Model
• Ingwersen Model
• Ellis Model
• Kuhlthau Model
• Wilson Model
• Dervin Model
• Byström Model
• Cruz Model
• References
• Index.

"In our lives, we need information continuously to carry out tasks of any kind (personal, academic, and professional). Depending on the context in which we find ourselves and the time available to carry out the task, emotions such as uncertainty and stress can present in the search process. But the important thing is that when we know the search process, the uncertainty and stress are minimized. In this context, the author investigates existing studies on the search and retrieval of information from the user's perspective. The study turned out to be very complex for two reasons: 1. Scientific literature is widely dispersed in different articles and academic books, even if it was the same search and information retrieval model. 2. Sources are not accessible to all people. As a consequence, the author plans to disseminate the results of this research with the aim of facilitating knowledge and understanding of anyone interested in entering the information search and retrieval process. With the collaboration of Nova Science Publishers, we find ourselves before an affordable, simple, and manageable book. Chapters 1 to 7 outline the search and information retrieval models of the following authors: Belkin, Ingwersen, Ellis, Kuhlthau, Wilson, Dervin, and Byström. In Chapter 8, the author presents her own model for searching and retrieving information. This model is formed by some elements previously seen from the other authors, but also by other novel ones such as the organisation. This is due to the fact that some of the tasks carried out with greater frequency and complexity are those that intervene in our professional tasks, in which scientific studies confirm that an effective organisation cannot be conceived without efficient information management"-- Provided by publisher.

"In the past few years, considerable interest has been shown and relevant resources have been devoted to the design, development and operation of autonomous aerial, underwater, and sea surface vehicles. The possibility of removing human pilots from danger and the size and cost advantages of autonomous vehicles are indeed attractive, but often have to be compared with the performance that can be attained by human-piloted vehicles, in terms of mission capabilities, efficiency and flexibility. The operation of an autonomous vehicle in an unknown, dynamic and potentially hostile environment is a very complex problem, especially when the autonomous vehicle is required to use its full maneuvering capabilities and to react in real time to changes in the operational environment. A common way of dealing with highly complex systems is via a hierarchical decomposition of the activities to be performed by the autonomous vehicles. However, only limited results can be obtained with this method. Another method is to design a hybrid control system that offers safety and performance guarantees by use of neural control technique. Neural networks appear to offer a new, promising direction toward better understanding of the most difficult control problems that have previously been very difficult or impossible to solve. This book provides basic approaches for the modeling and simulation of neural control systems using the MATLAB/Simulink environment for various types of vehicles, emphasizing realistic dynamics with numerous examples. These types of vehicles include experimental aircraft, self-guided missiles, unmanned miniature helicopters, autonomous underwater vehicles, and more"-- Provided by publisher.

• Introduction to support vector machines / Pooja Saigal, PhD, Vivekananda School of Information Technology, Vivekananda Institute of Professional Studies, New Delhi, India
• Journey of support vector machines : from maximum-margin hyperplane to a pair of non-parallel hyperplanes / Pooja Saigal, PhD, Vivekananda School of Information Technology, Vivekananda Institute of Professional Studies, New Delhi, India
• Power spectrum entropy-based support vector machine for quantitative diagnosis of rotor vibration process faults / Cheng-Wei Fei, Department of Aeronautics and Astronautics, Fudan University, Shanghai, China.

"Support Vector Machines: Evolution and Applications reviews the basics of Support Vector Machines (SVM), their evolution and applications in diverse fields. SVM is an efficient supervised learning approach popularly used for pattern recognition, medical image classification, face recognition and various other applications. In the last 25 years, a lot of research has been carried out to extend the use of SVM to a variety of domains. This book is an attempt to present the description of a conventional SVM, along with discussion of its different versions and recent application areas. The first chapter of this book introduces SVM and presents the optimization problems for a conventional SVM. Another chapter discusses the journey of SVM over a period of more than two decades. SVM is proposed as a separating hyperplane classifier that partitions the data belonging to two classes. Later on, various versions of SVM are proposed that obtain two hyperplanes instead of one. A few of these variants of SVM are discussed in this book. The major part of this book discusses some interesting applications of SVM in areas like quantitative diagnosis of rotor vibration process faults through power spectrum entropy-based SVM, hardware architectures of SVM applied in pattern recognition systems, speaker recognition using SVM, classification of iron ore in mines and simultaneous prediction of the density and viscosity for the ternary system water- ethanol-ethylene glycol ionic liquids. The latter part of the book is dedicated to various approaches for the extension of SVM and similar classifiers to a multi-category framework, so that they can be used for the classification of data with more than two classes"-- Provided by publisher

• Preface
• Modelling of Leader-Follower Formations
• 1st-Order Sliding Mode-Based Formation Design
• Coordinated Formation via an Adaptive-Gain 2nd-Order Sliding Mode Method
• Integral Sliding Mode-Based Formation Maneuvers of Multi-Agent Robots
• Leader-Following Formation Control of Multiple Agents via Derivative and Integral Terminal Sliding Mode
• Extreme Learning Machine-Based Sliding Mode Formation Maneuvers for Multi-Robot Systems
• Formation Design of Multiple Agents with Uncertainties by Integral Sliding Mode
• A Fuzzy Logic-Based Adaptive Strictly Negative-Imaginary Formation Controller for Multi-Quadrotor Systems
• Index.
• (source: Nielsen Book Data)

Formation control is one of the most challenging problems in cooperative multi-robots. It is defined as a coordination of a group of robots to get into and to maintain a formation with a certain shape. The formation control problem has drawn significant attention for many years, and now it is well understood and tends to be mature. This control problem is originated from biological inspires such as flocking and schooling. Its classification includes formation shape generation, formation reconfiguration and selection, formation tracking, and role assignment in formation. It also has potential applications in search and rescue missions, forest fire detection and surveillance, etc. It can be extended to many real-world systems, autonomous robots, such as underwater vehicles, unmanned aerial vehicles, mobile sensor networks, rectangular agents, nonholonomic mobile robots, to name but a few. Apparently, the book cannot include all research topics. The editor and the authors wish that it could reveal some tendencies on this research field and benefit readers. In this book, different aspects of formation control are explored. Chapters includes some new tendencies and developments in research on several formation methods of multi-robot systems, that is, the 1st-order sliding mode control, the 2nd-order sliding mode control, the integral sliding mode control, the terminal sliding mode control, the sliding model control of multi-agents and the fuzzy-based formation control of multiple quadrotor systems.
(source: Nielsen Book Data)

• Intro
• Contents
• Preface
• Chapter 1
• Data Center Optimization: Agencies Need to Address Challenges and Improve Progress to Achieve Cost Savings Goal(
• Why GAO Did This Study
• What GAO Recommends
• What GAO Found
• Abbreviations
• Background
• OMB and the Federal CIO Established FDCCI
• IT Acquisition Reform Law Enhanced Data Center Consolidation and Optimization Efforts
• OMB Established DCOI
• GAO Has Reported and Testified on Issues Related to Consolidating and Optimizing Data Centers

• Agencies Are Reporting Limited Progress against OMB's Data Center Optimization Targets
• Most Agencies Are Not Planning to Meet OMB's Fiscal Year 2018 Optimization Targets
• Agencies Reported Successes and Challenges in Optimizing Data Centers
• Agencies Identified the Use of Optimization Technologies and Improved Energy Efficiency as the Most Reported Successes
• Approximately Two-Thirds of Agencies Reported That Implementing Virtualization Technologies Improved Their Data Center Optimization Efforts

• About Half of the Agencies Reported That Migrating IT Applications and Services to Cloud Computing Solutions Increased Optimization Progress
• Five Agencies Reported Success in Increasing Energy Efficiency to Optimize Their Data Centers
• Agencies Reported Operational, Technical, and Financial Challenges in Optimizing Their Data Centers
• Operational Challenges
• Technical Challenges
• Financial Challenges
• Most Agencies Still Cannot Effectively Measure Server Utilization
• Conclusion
• Matter for Congressional Consideration
• Recommendations for Executive Action

• Agency Comments and Our Evaluation
• List of Committees
• Appendix I: Objectives, Scope, and Methodology
• Appendix II: Comments from the Department of Commerce
• Appendix III: Comments from the Department of Defense
• Appendix IV: Comments from the Department of Energy
• Appendix V: Comments from the Department of Health and Human Services
• Appendix VI: Comments from the Department of Homeland Security
• Appendix VII: Comments from the Department of the Interior
• Appendix VIII: Comments from the Department of Labor
• Appendix IX: Comments from the Department of State

• Appendix X: Comments from the Department of Veterans Affairs
• Appendix XI: Comments from the Environmental Protection Agency
• Appendix XII: Comments from the General Services Administration
• Appendix XIII: Comments from the Nuclear Regulatory Commission
• Appendix XIV: Comments from the Office of Personnel Management
• Appendix XV: Comments from the Department of Housing and Urban Development
• Appendix XVI: Comments from the Social Security Administration
• Appendix XVII: GAO Contact and Staff Acknowledgments
• GAO Contact
• Staff Acknowledgments
• Chapter 2

• Preface
• Enterprise Architecture Alignment
• Enterprise Architecture Knowledge Transfer and Organizational Empowerment
• Application of SOA with Cloud Computing
• Microservice Architecture
• Index.
• (source: Nielsen Book Data)

An enterprise architecture is an instrument that focuses on coherence between business processes, information distribution, and technology infrastructure of an organization. In this compilation, the authors begin by creating and subsequently discussing an artifact that provides architects with the capability of monitoring validity within ArchiMate enterprise architecture models. Next, it is suggested that business specialists and enterprise architects can benefit from collocated training, and that training activities in enterprise architecture are both one-off training and recurring training, where the latter is providing a community of practice. The authors consider ideas that may make it easier for organizations to realize the potential benefits of service-oriented architectures and cloud computing, as one of the challenges for software engineers today is keeping up with the rapid changes in technology. The major features underlying microservice architecture are examined, particularly the advantages and the disadvantages of their technologies and implementation. This analysis also highlights the major capabilities of microservices in driving future advances in the software and hardware industries.
(source: Nielsen Book Data)

• Preface
• Analysis and Design of Oil Pipeline Leaks Monitoring System Using LoRa and IoT Network
• LoRaWAN: A Communication Protocol for IoT Agriculture Applications
• Industrial Hazard Prevention Using Xbee and IoT
• Essential Aspects of Day to Day Life and Its Influence on Industry 4.0
• Wireless Personal Area Network-Based Waste Monitoring System Using XBee and IoT
• Role of Fire Safety Engineering Methods and Devices in Present Scenario: A Review
• Mobile Platform Localization in Indoor/Outdoor Techniques: A Review
• Smart Water Management System Using Pi
• The Importance of Internet of Things (IoT): Applications and Security Challenges
• IoT in Fire Safety-An Exciting Future for Smart Building and Cities
• Index.
• (source: Nielsen Book Data)

The concept of Industry 4.0 includes both Internet of Things (IoT) structure and the local networks which need to carry the real-time tasks. The LoRa technology can be implemented for industrial wireless networks to control sensors and actuators of the Industry 4.0 era. This book aims to explore the methods and systems to implement LoRa network for Industry 4.0. The book comprises of ten chapters. Chapter 1 explains the monitoring of pipeline leaks, which play a prominent role in crude oil industry. To achieve the best solution and more protection of the environment, possible combinations of various technologies are discussed. Chapter 2 illustrates the low power wide area networks. A survey of recent published articles has been included on Low Power Wide Area networks and their applications. Chapter 3 discusses industrial hazards. It explores the various technical algorithms comprising of various equipments able to monitor environmental parameters by sensing through different pre-installed nodes deployed at specific positions. Chapter 4 deals with smart agriculture with an emphasis on guaranteed nourishment, effects of environmental changes on agribusiness along with lighting and smart parking issues. Chapter 5proposed an XBEee and IoT based architecture for the monitoring the garbage bins wirelessly. Here the XBee based sensor, which is placed in the garbage bin, initiates the function of our architecture and sends the status of the garbage bin to the local sever. Chapter 6 identifies various areas where fire safety technology upgradation is required. The importance of wireless sensor networks as the one of the efficient methods for fire safety systems is also highlighted. Chapter 7 reports a review of research work related to the RSSI. RSSI is concluded as a very good indoor localization approach. Chapter 8 explores the problem of measuring the depth and flow of water in large water body or water pipe. A solution is proposed which will reduce the chance of human error and make pace for intelligent cities. Chapter 9 discusses the cyber security in manufacturing and related industries. It explores the nature of the data, topologies of IoT devices, and complexities of threat management and ensuring compliance. Chapter 10 addresses the importance of fire safety in smart city and building along with the role of IoT for meeting the requirement. Editors are thankful to all the contributors and publisher for their support.
(source: Nielsen Book Data)

• Preface
• Artificial Neural Networks, Concept, Application and Types
• Emotion Recognition from Facial Expressions Using Artificial Neural Networks: A Review
• Dipole Mode Index Prediction with Artificial Neural Networks
• Efficacy of Artificial Neural Networks in Differentiating Breast Cancers in Digital Mammography
• Supervised Adjustment of Synaptic Plasticity in Spiking Neural Networks
• A Review on Intelligent Decision Support Systems and a Case Study: Prediction of Cryptocurrency Prices with Neural Networks
• Index.
• (source: Nielsen Book Data)

With respect to the ever-increasing developments in artificial intelligence and artificial neural network applications in different scopes such as medicine, biology, history, military industries, recognition science, space, machine learning and etc., the book first presents a comprehensive investigation of artificial neural networks. Next, the authors focus on studies carried out with the artificial neural network approach on the emotion recognition from 2D facial expressions between 2009 and 2019. The major objective of this study is to review, identify, evaluate and analyze the performance of artificial neural network models in emotion recognition applications. This compilation also proposes a simple nonlinear approach for dipole mode index prediction where past values of dipole mode index were used as inputs, and future values were predicted by artificial neural networks. The study was also conducted for seasonal dipole mode index prediction because the dipole mode index is more prominent in the Sep-Oct-Nov season. A subsequent study focuses on how mammography has a high false negative and false positive rate. As such, computer-aided diagnosis systems have been commercialized to help in micro-calcification detection and malignancy differentiation. Yet, little has been explored in differentiating breast cancers with artificial neural networks, one example of computer-aided diagnosis systems. The authors aim to bridge this gap in research. The penultimate chapter reviews the general conditions under which synaptic plasticity most effectively takes place to support the supervised learning of a precise temporal code. Then, the accuracy of each plasticity rule with respect to its temporal encoding precision is examined, and the maximum number of input patterns it can memorize using the precise timings of individual spikes as an indicator of storage capacity in different control and recognition tasks is explored. In closing, a case study is presented centered on an intelligent decision support system that is built on a neural network model based on the Encog machine learning framework to predict cryptocurrency close prices.
(source: Nielsen Book Data)

The 21st century has marked the arrival of new digital technologies that transform the way enterprises operate and people live their lives. From social media sites and smartphone technology to video streaming and cloud computing, there has been a bevy of new applications that are impacting society and business seemingly on a daily basis. Considering technology and networking is a constantly changing field, some of its aspects need to be changed to conform to newly set trends. Even though prior network management frameworks have proved efficient in the past years, change is inevitable. More and more people use the internet and more scalable network management architecture needs to be developed. In that respect, the telecommunication industry has seen tremendous growth accompanied by various challenges. Ideally, the expectations of all these include the quality of service and customer services as well as mitigating any threats that are affecting the service providers. With many opportunities being granted, telecommunication has a wide range of emerging content. For instance, there is the exponential growth of the Internet of Things devices and 5G network data, and the acceleration of cloud-based network adoption. More so, there are smart cities, mobile broadband, massive connectivity, artificial intelligence, and automation. Moving on to trends in big data, the development of the Internet of Things has brought into the picture countless innovative sources of big data. Cloud computing has served as one of the biggest trends in the last ten years and fog computing exhibits greater prospects. Cloud computing is changing the way we access applications and hardware as well as the business and healthcare environments. Even though there is presently a considerable amount of work underway at cloud data centers, the fog computing trend is bound to change things. Many of the important and disruptive IoT trends are taking place in the industrial setting in terms of transport, manufacturing, and utilities. In terms of smart living, turning regular homes into smart homes is a developing trend that is progressively getting bigger every single day. Automation and pervasive networks emerge from the combination of virtualization, IoT, densification, and 5G to replace today's atomistic networks. All of these trends are coined from the dynamism that is witnessed in computerized systems that have the unending need to offer improved and more efficient services. In this book, the author has discussed the future roadmap of telecommunications and the major disruptions that will drive the most change in this industry. The focus of this book concerns the cloud, fog and edge computing with their benefits, and challenges.
(source: Nielsen Book Data)

• Real time communication characteristics with the Timed-Token MAC Protocol
• Analysis and evaluation of real-time communication using Profibus networks
• Performance analysis of data communicationn with its improvement in FF Fieldbus
• Transmission and scheduling of time critical data with World FIP Fieldbus in industrial application
• Analysis and evaluation of communication performance for CAN Fieldbus.

This book provides comprehensive research on the communication performance of a real time industrial fieldbus. Several important topics were investigated, such as how to ensure the transmission of real-time messages within a maximum bound time along the industrial fieldbus mentioned in this book. Profibus, FF, WorldFIP and CAN are all well-proved solutions for real-time communication systems, based on a simplified timed token (TT) protocol and bus scheduling. The following subjects dealing with the real-time communication performance of an industrial fieldbus were investigated and studied in this book. Features: 1) Concept and essentiality of timed-token MAC protocol with the effect of its parameter in real-time characteristics; 2) MAC mechanism in Profibus, timing analysis, optimization of acyclic bandwidth allocation, and the approaches to guarantee the real-time behaviour of the Profibus protocol; 3) Principles of acyclic data communication, and analysis of the delay performance of time-critical and time-available data in FF fieldbus data link layer token-passing service; 4) Communication models in WorldFIP network, Producer/Distributor/Consumer concept, response time analysis for sporadic traffic and investigation of the worst-case response time issues; 5) Communication mechanism in CAN fieldbus with its performance analysis and evaluation in real-time applications. The academic level of this book is relatively high and professional. It is suitable as a reference for university graduates, lecturers and researchers.
(source: Nielsen Book Data)

• Preface; Applications of Artificial Neural Networks in Chemical Engineering; Abstract; Artificial Neural Networks; Artificial and Biological Neural Networks; Biological Neuron; Analogy between Artificial and Biological Neurons; Artificial Neuron; Perceptrons; Comparison of the Biological and Artificial Neural Networks; Learning; Division of Artificial Neural Networks; Application of ANN; The Application of ANN in Chemical Engineering; Application of Artificial Neural Networks in Pharmaceutical Research; Application of Artificial Neural Network for Extraction Processes.

• Application of Artificial Neural Network for Adsorption ProcessesApplication of Artificial Neural Networks; in Chemistry; Conclusion; Acknowledgments; References; Biographical Sketch; Applications of Artificial Neural Networks in Chemistry and Chemical Engineering; Abstract; Introduction; Applications of Artificial Neural Networks in Chemical Engineering; Lengthy Response or Unavailability of Physical Sensors; Multipurpose Processes; Advanced Control, Faults Detection and Diagnosis, and Safety; Applications of Artificial Neural Networks in Chemical and Related Areas; Data Reduction.

• Overlapped Signal ResolutionExperimental Design and Response Surface; Modeling; Pattern Recognition; Multivariate Calibration Method; Conclusion; Acknowledgments; References; Applications of Artificial Neural Networks to Energy and Buildings; Abstract; Foreword; Feedforward Neural Network: Learning Process; Analysis of the Artificial Neural Network Applications in Energy and Buildings; Artificial Neural Network Applications; Buildings and Energy Plants; Renewable Energy Sources; Indoor Thermal Conditions; Outdoor Conditions; Other Applications; Conclusion; References.

• Applications of Artificial Neural Network to Predict Biodiesel Fuel Properties from Fatty Acid ConstituentsAbstract;
• 1. Introduction;
• 2. Materials and Methods; 2
• .1. Data Collection and Selection; 2
• .2. Modification of Fatty Acids; 2
• .3. ANN Components and Architecture; 2
• .4. ANN Modelling; 2.4
• .1. Modeled Parameters; 2.4
• .2. ANN Training;
• 3. Result and Discussion; 3
• .1. Cetane Number Prediction; 3
• .2. Kinematic Viscosity Prediction; 3
• .3. Flash Point Prediction; 3
• .4. Density Prediction; Appendix; References; Applications of ANN Methods for Solar Radiation Estimation; Abstract;
• 1. Introduction.

• 2. Meteorological Data Bas
• e3. Artificial Neural Network (ANN);
• 4. Accuracy Estimation;
• 5. First Study: Determination of Horizontal Global Solar Irradiation from Other Meteorological Data;
• 6. Second Study: Conversion of Horizontal Global Solar Irradiation into Tilted One; Conclusion; Acknowledgement; References; Biographical Sketches; The Use of In Silico Methods to Design and Evaluate Skin UV Filters; Abstract; Introduction; Artificial Neural Networks (ANNs); Data Selection; External Model Validation; Conclusion; References.

This current book provides new research on artificial neural networks (ANNs). Topics discussed include the application of ANNs in chemistry and chemical engineering fields; the application of ANNs in the prediction of biodiesel fuel properties from fatty acid constituents; the use of ANNs for solar radiation estimation; the use of in silico methods to design and evaluate skin UV filters; a practical model based on the multilayer perceptron neural network (MLP) approach to predict the milling tool flank wear in a regular cut, as well as entry cut and exit cut, of a milling tool; parameter extraction of small-signal and noise models of microwave transistors based on ANNs; and the application of ANNs to deep-learning and predictive analysis in semantic TCM telemedicine systems.
(source: Nielsen Book Data)

• Preface
• Secure Data Transmission via Synchronization of Chaotic Systems
• The Synchronization of an Uncertain Fractional-Order Chaotic System & Its Application in Secure Communications
• Linked Data Structures
• Sensor Data Collection, Secure Transmission & Distributed Processing in the SCADA System
• Index.
• (source: Nielsen Book Data)

The recent advances in computer networks and the widespread use of the Internet, together with other developments in telecommunications technology have made it possible to send messages and exchange information around the whole world. The high variety and the large amount of data exchanged across communication networks have increased over the last few years. This means the threat of interception during data transmission has become a major concern. Important research aimed at designing algorithms to help prevent interception and enhance data security is currently of primary relevance. This advanced technology requires new and efficient encryption methodologies. These algorithms can assure security for fast evolving communication and storage applications that must be secured against intrusion threats, which unfortunately are increasing in sophistication and frequency. This book analyses new research on the technology and applications of data structures and data transmission.
(source: Nielsen Book Data)

• Historical review of configuration software and WorldFIP Fieldbus technology
• IEC 61131-3 norm
• Design of function block diagram configurator for WorldFIP fieldbus control system
• Review and prospect.

Since the beginning of the 1980s, configuration software has developed and evolved. It should be said that configuration software, as a kind of application software, rose with the development of personal computers. The development of configuration software is closely related to the development of the industrial control system. With the rapid development of modern industries, the production process continues to expand in scale, and its complexity is increasing. The process of industrial production is now being transformed from labour intensive, equipment intensive, and information intensive to a more knowledge intensive fashion. Configuration software as a product appeared in the early 80s, and was widely used in the late 80s. But before the mid-90s, the configuration software application was not universal. With the applications of industrial control systems widely used around the world, in the face of larger and more complex control systems, users have become gradually more aware of original host computer programming. This mode is time-consuming. The loss outweighs the gains. At the same time, MIS (management information systems) and CIMS (computer integrated manufacturing systems), and a large number of applications require an industrial site for enterprise production, management, and decision-making to provide more detailed and in-depth data in order to optimize the production and operation of enterprises in all aspects.
(source: Nielsen Book Data)

• Genetic algorithms : a tool for optimizing intensified distillation sequences / Fernando Israel Gómez-Castro, Claudia Gutiérrez-Antonio, Abel Briones-Ramírez and Juan Gabriel Segovia-Hernández
• The optimization of a genetic algorithm for unmanned aerial vehicle path planning / Parvathy Rajendran and KaiYit Kok
• Calibration of the numerical model of a telecommunications tower based on genetic algorithms / Diogo Ribeiro, Jorge Leite, Rafael de Pauli, Vinicius Alves, Bruno Costa and Rui Calçada
• Application of a genetic algorithm in calibration of traffic microsimulation models / Orazio Giuffrè, Anna Granà, Raffaele Mauro, Antonino Sferlazza and Maria Luisa Tumminello.

• Preface
• Knowledge is Power
• Fuzzy Logic Concept
• Neural Network Concept
• Structured & Unstructured Data Processing
• Artificial Intelligence Systems & Robots of Tomorrow
• Computational Neuroscience
• Cable & Compartmental Models of Dendritic Trees
• Dynamics of Cerebral Cortical Networks
• Neural Networks & Fuzzy Logic Systems
• The Extraordinary Future of Artificial Intelligence
• Appendix. Fluorescence Microscopy
• Index.
• (source: Nielsen Book Data)

With today's growing and overloading volume of information, it is becoming tremendously difficult to analyse the huge amounts of data that contain this information. It makes it very strenuous and inconvenient to introduce an appropriate methodology of decision-making fast enough to the point that it can be considered as real-time. The demand for real-time processing information and related data -- both structured and unstructured -- is on the rise and consequently makes it harder and harder to implement correct decision making at the enterprise level to keep the organisation robust and resilient against either manmade threats or natural disasters. Neural networking and fuzzy systems combined show how an artificial intelligence (AI) can be driven, by these combinations as a trainable system that is more dynamic than static when it comes to machine and deep learning language to deal with both adversary and friendly events in real-time. Dynamic systems of AI that are built around such an innovative approach allows the robots of the future to be more adaptive with mechanisms such as principle adoption, self-organisation, and the convergence of global stability from the viewpoint of business and intelligence security needed in today's cyber world. To deal with uncertainty, vagueness, and imprecision, Lofti A Zadeh introduced fuzzy sets and fuzzy logic. In the present book, fuzzy classification is applied to extend portfolio analysis, scoring methods, customer segmentation and performance measurement, and thus improves managerial decisions. As an integral part of the book, case studies show how fuzzy classification -- with its query facilities -- can extend customer equity, enable mass customisation, and refine marketing campaigns. This book shows interoperability between the two sciences/techniques show how: 1) To utilise fuzzy theory of the first and second kind to an adaptive control; and 2) how to invent a structured fuzzy system and robots of future, with unsupervised neural network techniques to face an unstructured world of big data and unpredictable global events all in real-time. An important aspect of this approach is to examine biological neural systems and study how artificial neural networks are, how they are based on them, and how they are driven by them as well. Key areas discussed include: 1) Structural diversity; 2) temporal lobe; 3) origins of artificial neural systems; 4) brain structure and function; 5) biological nerve cells; 6) synapses; 7) random and fixed positions in the brain's neural networks; and 8) how biological systems really compare to computational neural networks. The book is designed to be appropriate for courses in engineering, computer science, mathematics, psychology and biology.
(source: Nielsen Book Data)

• Identification issues in pattern analysis / Darko Brodić, Alessia Amelio and Zoran N. Milivojević
• Cheiloscopy and human identification : a review / Inês Morais Caldas, Alexandra Teixeira and Daniel Pérez-Mongiovi
• Palatoscopy in human identification : a review / Susana Braga, Maria Lurdes Pereira, Benedita Sampaio-Maia and Inês Morais Caldas
• Variable-scale-based pattern analysis for time series of wind speed, atmospheric pressure, and atmospheric temperature / Cristian Suteanu.

This book reviews methods, applications and challenges of pattern analysis. Chapter One addresses the identification problem of the printed medieval documents origin. The authors of Chapter Two perform a review on current cheiloscopic techniques, addressing the study methodology and usefulness of lip print patterns study. Chapter Three examines theoretical bases of human identification using palatal rugae pattern, and addresses the study methodology and techniques, potentialities and future usefulness of palatal rugae patterns. Chapter Four focuses on variable-scale-based pattern analysis for time series of wind speed, atmospheric pressure, and atmospheric temperature.
(source: Nielsen Book Data)