Knowledge Labor Measurement (Theory and Application)

Author: Liu Gang
Publisher:
Publishing Time: Not available
Features: This book consists of eight chapters. The preface outlines knowledge and knowledge labor, proposes the content and framework of the research in this book, and provides the chapter arrangement.
1. Overview of Labor Measurement Theory: This chapter explains the concept of labor measurement, its scales, principles, significance, and basic methods.
2. Theoretical Basis of Knowledge Labor Measurement: This chapter introduces the fundamental theories of fuzzy set theory, including basic concepts, operations of fuzzy sets, membership functions, fuzzy logic and reasoning, and fuzzy comprehensive evaluation. It also summarizes the basic content of knowledge engineering, primarily discussing knowledge representation methods such as predicate logic, production rules, semantic web, characteristic tables, direct or analogical methods, and fuzzy knowledge representation. Additionally, it analyzes artificial neural network models, learning rules, architectures, and applications.
3. Analysis of Knowledge Labor Measurement Theory: This chapter examines knowledge labor and its fundamental characteristics, compares and contrasts knowledge labor with mental labor, and discusses the current status and challenges of knowledge labor measurement. Based on this, it studies the process of knowledge labor and its three key characteristics, proposing the basic ideas of process-oriented, knowledge-quantity-based and object-oriented, knowledge-processing-based knowledge labor measurement.
4. Methods of Knowledge Labor Measurement: Based on the theory of knowledge labor measurement, this chapter introduces the principles of tree diagrams, fuzzy set theory, and neural network methods to establish a process-oriented, knowledge-quantity-based labor measurement method. It also applies fuzzy logic for knowledge representation and neural network knowledge processing methods to establish an object-oriented, knowledge-processing-based labor measurement method.
5. Application of Knowledge Labor Measurement Theory and Methods—Engineering Design Labor Measurement Model: This chapter studies the knowledge quantity in engineering design processes, focusing on the decomposition and expansion of engineering design processes and their knowledge quantity. It establishes a process-oriented, knowledge-quantity-based engineering design labor measurement model. It also investigates the fuzzy knowledge representation structure model of engineering design objects and applies neural network knowledge processing methods to establish an object-oriented, knowledge-processing-based engineering design labor measurement model.
6. Application Examples of Engineering Design Labor Measurement Models: Taking the design of shrimp grading machines and chairs as examples, this chapter provides an analysis of the application of both the process-oriented, knowledge-quantity-based and object-oriented, knowledge-processing-based engineering design labor measurement models.
7. Knowledge Labor Measurement System: This chapter presents the design philosophy of the measurement system and its composition and structure. It studies the structural framework and data flow diagrams of the sample acquisition subsystem, measurement model subsystem, model database subsystem, and measurement subsystem.
8. Conclusion: This chapter compares and analyzes the characteristics of the two knowledge labor measurement theories and methods, offering prospects for further research.