Weak Knowledge

Many of us view the world of science as a firm bastion of knowledge, with each new discovery and further illumination adding to an unshakable foundation of natural truths. Weak Knowledge aims to rattle our faith, not in core certainties of scientific findings but in their strength as accessible resources. The authors show how, throughout history, many bodies of research have become precarious due to a host of factors. These factors have included cultural or social disinterest, feeble empirical evidence or theoretical justifications, and a lack of practical applications in a given field's findings. This book brings together cases from a range of historical periods and disciplines, ranging from personal medicine to climatology, to illuminate the specific forms, functions, and dynamics of so-called "weak" bodies of knowledge.

These proceedings represent the work of contributors to the 17th International Conference on Intellectual Capital, Knowledge Management & Organisational Learning (ICICKM 2020), hosted by ACI and the University of Toronto, Canada on 15-16 October 2020. The Conference Chairs are Dr. Anthony Wensley, from the University of Toronto and Dr. Max Evans, from McGill University. The Programme Chair is Dr. Ilja Frissen from McGill University.

Exciting new developments in risk assessment and management Risk assessment and management is fundamentally founded on the knowledge available on the system or process under consideration. While this may be self-evident to the laymen, thought leaders within the risk community have come to recognize and emphasize the need to explicitly incorporate knowledge (K) in a systematic, rigorous, and transparent framework for describing and modeling risk. Featuring contributions by an international team of researchers and respected practitioners in the field, this book explores the latest developments in the ongoing effort to use risk assessment as a means for characterizing knowledge and/or lack of knowledge about a system or process of interest. By offering a fresh perspective on risk assessment and management, the book represents a significant contribution to the development of a sturdier foundation for the practice of risk assessment and for risk-informed decision making. How should K be described and evaluated in risk assessment? How can it be reflected and taken into account in formulating risk management strategies? With the help of numerous case studies and real-world examples, this book answers these and other critical questions at the heart of modern risk assessment, while identifying many practical challenges associated with this explicit framework. This book, written by international scholars and leaders in the field, and edited to make coverage both conceptually advanced and highly accessible: Offers a systematic, rigorous and transparent perspective and framework on risk assessment and management, explicitly strengthening the links between knowledge and risk Clearly and concisely introduces the key risk concepts at the foundation of risk assessment and management Features numerous cases and real-world examples, many of which focused on various engineering applications across an array of industries Knowledge of Risk Assessment and Management is a must-read for risk assessment and management professionals, as well as graduate students, researchers and educators in the field. It is also of interest to policy makers and business people who are eager to gain a better understanding of the foundations and boundaries of risk assessment, and how its outcomes should be used for decision-making.

Knowledge when properly leveraged and harnessed contributes to effective organizational performance. How much an organization benefits from knowledge would depend on how well knowledge has been managed. There have been challenges to implementing knowledge management in today’s dramatically different world from before. This comprehensive reference work is a timely guide to understanding knowledge management. The book covers key themes of knowledge management which includes the basic framework of knowledge management and helps readers to understand the state of art of knowledge management both from the aspects of theory and practice, from the perspectives of strategy, organization, resources, as well as institution and organizational culture. This reference work reflects the increasingly important role of both philosophy and digital technologies in knowledge management research and practice. This handbook will be an essential resource for knowledge management scholars, researchers and graduate students.

An in-depth exploration of the nature of language, knowledge and pedagogy, providing a progressive analysis of knowledge structures at work in educations institutions.

Knowledge Mining Using Intelligent Agents explores the concept of knowledge discovery processes and enhances decision-making capability through the use of intelligent agents like ants, termites and honey bees. In order to provide readers with an integrated set of concepts and techniques for understanding knowledge discovery and its practical utility, this book blends two distinct disciplines — data mining and knowledge discovery process, and intelligent agents-based computing (swarm intelligence and computational intelligence). For the more advanced reader, researchers, and decision/policy-makers are given an insight into emerging technologies and their possible hybridization, which can be used for activities like dredging, capturing, distributions and the utilization of knowledge in their domain of interest (i.e. business, policy-making, etc.). By studying the behavior of swarm intelligence, this book aims to integrate the computational intelligence paradigm and intelligent distributed agents architecture to optimize various engineering problems and efficiently represent knowledge from the large gamut of data. Contents: Theoretical Foundations of Knowledge Mining and Intelligent Agent (S Dehuri & S-B Cho)The Use of Evolutionary Computation in Knowledge Discovery: The Example of Intrusion Detection Systems (S X Wu & W Banzhaf)Evolution of Neural Network and Polynomial Network (B B Misra et al.)Design of Alloy Steels Using Multi-Objective Optimization (M Chen et a.)An Extended Bayesian/HAPSO Intelligent Method in Intrusion Detection System (S Dehuri & S Tripathy)Mining Knowledge from Network Intrusion Data Using Data Mining Techniques (M Panda & M R Patra)Particle Swarm Optimization for Multi-Objective Optimal Operational Planning of Energy Plants (Y Fukuyama et al.)Soft Computing for Feature Selection (A K Jagadev et al.)Optimized Polynomial Fuzzy Swarm Net for Classification (B B Misra et al.)Software Testing Using Genetic Algorithms (M Ray & D P Mohapatra) Readership: Researchers and professionals in the knowledge discovery industry. Keywords:Intelligent Agent;Knowledge Mining;Data Mining;Knowledge Discovery;Computational Intelligence;Swarm Intelligence;Evolutionary ComputationKey Features:Addresses the various issues/problems of knowledge discovery, data mining tasks and the various design challenges by the use of different intelligent agents technologiesCovers new and unique intelligent agents techniques (computational intelligence + swarm intelligence) for knowledge discovery in databases and data mining to solve the tasks of different phases of knowledge discoveryHighlights data pre-processing for knowledge mining and post-processing of knowledge that is ignored by most of the authorsConsists of a collection of well-organized chapters written by prospective authors who are actively engaged in this active area of research

A pedagogical approach to the principles and architecture of knowledge management in organizations This textbook is based on a graduate course taught at Stevens Institute of Technology. It focuses on the design and management of today's complex K organizations. A K organization is any company that generates and applies knowledge. The text takes existing ideas from organizational design and knowledge management to enhance and elevate each through harmonization with concepts from other disciplines. The authors—noted experts in the field—concentrate on both micro- and macro design and their interrelationships at individual, group, work, and organizational levels. A key feature of the textbook is an incisive discussion of the cultural, practice, and social aspects of knowledge management. The text explores the processes, tools, and infrastructures by which an organization can continuously improve, maintain, and exploit all elements of its knowledge base that are most relevant to achieve its strategic goals. The book seamlessly intertwines the disciplines of organizational design and knowledge management and offers extensive discussions, illustrative examples, student exercises, and visualizations. The following major topics are addressed: Knowledge management, intellectual capital, and knowledge systems Organizational design, behavior, and architecture Organizational strategy, change, and development Leadership and innovation Organizational culture and learning Social networking, communications, and collaboration Strategic human resources; e.g., hiring K workers and performance reviews Knowledge science, thinking, and creativity Philosophy of knowledge and information Information, knowledge, social, strategy, and contract continuums Information management and intelligent systems; e.g., business intelligence, big data, and cognitive systems Designing Knowledge Organizations takes an interdisciplinary and original approach to assess and synthesize the disciplines of knowledge management and organizational design, drawing upon conceptual underpinnings and practical experiences in these and related areas.