The logic theory machine--A complex information processing system

Allen Newell and Herbert A. Simon. The logic theory machine. A complex information processing system. Institute of Radio Engineers, Transactions on information theory, vol. IT-2 no. 3 (1956), pp. 61–79. - Volume 22 Issue 3

“Garbage in, garbage out” is a familiar phrase from the field of computer science. The concept surrounding the phrase is simple. Despite the most complex information processing systems, computers will unquestioningly process the most ridiculous of input data, “garbage in,” and produce ridiculous output, “garbage out.” Commonly used in other fields, including laboratory medicine, this phrase serves as an important reminder that in the context of healthcare, inaccurate data input—garbage in—leads to misleading results—garbage out. So before the laboratory can perform testing it is imperative that inherent, pre-analytical issues are understood and identified. This chapter focuses on specimen integrity in the pre-analytical phase of testing and discusses how the laboratory strives to link the quality of incoming specimens to quality results.

Parallel Image Compression with JPEG for Multimedia Applications

This talk will trace the growing influence of fundamental ideas from computer science on the nature of research in a number of scientific fields. There is a growing awareness that information processing lies at the heart of the processes studied in fields as diverse as quantum mechanics, statistical physics, nanotechnology, neuroscience, linguistics, economics and sociology. Increasingly, mathematical models in these fields are expressed in algorithmic languages and describe algorithmic processes. The speaker will briefly describe connections between quantum computing and the foundations of quantum mechanics, and between statistical mechanics and phase transitions in computation. He will indicate how the growth of the Web has created new phenomena to be investigated by sociologists and economists. He will then focus in greater detail on computational molecular biology, where the view of living cells as complex information processing systems has become the dominant paradigm, and will discuss specific algorithmic problems arising in the sequencing of genomes, the comparative analysis of the resulting genomic sequences, the modeling of networks of interacting proteins, and the associations between genetic variation and disease.

ABSTRACTOver the past several years, numerous industries have increased their adoption of the systems modeling language (SysML®) and model‐based systems engineering (MBSE) as a core practice within their engineering lifecycles. However, the introduction of SysML and MBSE methodologies has not yet yielded many of the originally envisioned benefits. System models are becoming larger and more complex and many large MBSE projects continue to experience problems with model integration, repository performance, and model lifecycle management. The root cause is the failure to recognize the MBSE digital environment as a complex engineering information processing system that requires the same rigor and development processes as the system‐of‐interest (SoI) it is designing. This article describes how three future of systems engineering (FuSE) agility foundation concepts (system of innovation, effective stakeholder engagement, and continuous integration) directly address some of the problems seen in adoption, deployment, and sustainment of the MBSE digital environment as an SoI.

Artificial neural networks arise from the research of the configuration and function of the brain. As pointed out in [79], the brain can be regarded as a complex nonlinear parallel information processing system with a concept of neuron as a basic functional unit.

This paper is a case study in problem solving, representing part of a program of research on complex information-processing systems. We have specified a system for finding proofs of theorems in elementary symbolic logic, and by programming a computer to these specifications, have obtained empirical data on the problem-solving process in elementary logic. The program is called the Logic Theory Machine (LT); it was devised to learn how it is possible to solve difficult problems such as proving mathematical theorems, discovering scientific laws from data, playing chess, or understanding the meaning of English prose.

This paper does not deal with the topic of ‘the generosity of artificial languages from an Asian or a comparative perspective’. Rather, it is concerned with a particular case taken from a development in the Western tradition, when in the wake of the rise of formal logic at the end of the nineteenth and the beginning of the twentieth century people in philosophy and later in linguistics started to use formal languages in the study of the semantics of natural languages. This undertaking rests on certain philosophical assumptions and instantiates a particular methodology, that we want to examine critically. However, that in itself is still too broad a topic for a single paper, so we will focus on a particular aspect, viz., the distinction between grammatical form and logical form and the crucial role it plays in how the relationship between natural languages and formal languages is understood in this tradition. We will uncover two basic assumptions that underlie the standard view on the distinction between grammatical form and logical form, and discuss how they have contributed to the shaping of a particular methodology and a particular view on the status of semantics as a discipline. But before we turn to the topic at hand, a few more words on the general nature of the investigation are in order. Its general aim is to find out how semantics constructs its object, i.e., we are interested in what semanticists view as the proper object of study, how they think this object can best be approached, and how they view the relations between their own undertaking and neighbouring disciplines that deal with related, or even the same kind of phenomena, such as cognitive psychology, cognitive neuroscience, philosophy, anthropology. The background assumption is that, much like in other disciplines, semantics, too, does not have its object of investigation cut out for itself by nature, but constructs it in a complex process that involves empirical elements (‘facts’ being already too dangerous a term), philosophical assumptions, and borrowings

This paper addresses the critical issue of developing complex information processing systems for metro electric depots using modern methods of railway automation and telemechanics. The study proposes a structured approach based on object-oriented analysis, which provides a robust framework for modeling and optimizing the intricate operational environment of a metro depot. The core of this methodology lies in defining key system components as interconnected objects, thereby facilitating a clear decomposition of the problem into manageable parts. The research develops formal information models, including a state machine for rolling stock, to represent wagon movements and transitions between states such as at rest, under inspection, or under repair. This approach is crucial for overcoming terminological ambiguities and ensuring a consistent understanding of operational processes. A multi-level, component-hierarchical structural diagram of the system is presented, which is designed to integrate various hardware and software elements. This architecture is composed of a field level with sensors and diagnostic complexes, a data collection and processing level with processors and controllers, a central information processing hub with servers and data analysis software, and a user interface level for seamless human-system interaction. This design is aligned with modern SCADA principles, ensuring modularity, scalability, and remote management capabilities. Furthermore, the article formulates fundamental principles for automating data collection and processing. This includes a shift from traditional scheduled maintenance to a more efficient condition-based monitoring approach, enabling maintenance and repairs to be performed only when necessary, based on real-time diagnostic data. The system incorporates automated wagon identification technologies, suh as RFID and video recognition, for accurate tracking of rolling stock within the depot. It also advocates for the implementation of electronic document management to optimize workflows, reduce paperwork, and enhance process transparency. The ultimate goal is to minimize human error and the impact of the human factor, which is a major source of risk in railway operations, thereby significantly improving the safety, reliability, and cost-effectiveness of metro electric depot management.

The purpose of any social discipline is to understand the society through their theoretical perspectives. Human communication as a social science is also without exception, its purpose is to explain the society by means of inspecting the social information as well as the contents and extensions during the operation of social information system. Social together with its system are complex and comprehensive by nature, which determines human communication existing itself as a comprehensive science with multiple theories, aspects and perspectives. It is reasonable to study with the help of related theories of other subjects in facing concrete research issues and when the existing theories lack enough power to give an explanation. Interpersonal human communication is an important part in human life, the human communication study about is rather few, however. This paper is about to solve this problem, for current human communication cannot explain the barriers occurred in the interpersonal human communication. To deal with such issue that often happens in social life, the author is appeal to information system theories to explain that the trajectory of information changes in the course of human communication could cause barriers.

Linguistic Geometry for autonomous navigation

ASTRAL is a formal specification language for realtime systems. It is intended to support formal software development, and therefore has been formally defined. In ASTRAL a realtime system is modeled by a collection of state machine specifications and a single global specification. This paper focuses on extending the ASTRAL methodology to allow the composition of ASTRAL system specifications into specifications of larger and more complex systems. The ASTRAL language includes structuring mechanisms that allow one to build modularized specifications of complex systems with layering. In this paper we concentrate on how to combine these complex system specifications into specifications of even more complex realtime systems. This is accomplished by adding a COMPOSE section to the language that provides the needed information to combine two or more ASTRAL specifications into a single new one. In this paper we also introduce the necessary proof obligations to assure that the assumptions of each of the components of the larger system are satisfied by the other components of the system that replace the previous external environment. We also discuss how some exported transitions become internal transitions of the new system. A telephony example with local central controls that interface to long distance units is used to motivate the extensions.

The complexity of problems facing society continues to grow, and decision-makers and problem-solvers are finding many of today's emerging problems to be beyond their capability to adequately address. There is agreement in the literature that problems of this nature are complex system problems, inextricably linked to some highly complex system of systems. Establishing a clear understanding of the specific complex system context is fundamental to the process of understanding and analyzing complex systems and complex system problems across all of the different systems-based disciplines. While complex system context is widely referred to in systems literature, there is no clear characterization of exactly what system context is, making this foundational system concept ambiguous. This research addressed this gap in the systems body of knowledge by providing the needed detail and clarity to the concept of complex system context. A rigorous research methodology, employing the grounded theory method, was used to analyze data collected through a series of semi-structured interviews conducted with individuals reflecting a wide range of systems education and practical experience. Two research questions were identified as integral to increasing the understanding of context within complex systems. (1) What are the constituent elements of complex system context, and what attributes and dimensions characterize these elements? (2) What systems-based framework can be developed for constructing and articulating complex system context? Using the grounded theory method, a theory of system context was constructed, adding to the systems body of knowledge and substantiating a comprehensive and unambiguous theoretical construct for system context within complex systems. Then, based on this theory, a conceptual model to articulate and capture system-specific complex system context was developed---the Complex System Contextual Framework (CSCF). The CSCF shows significant promise for contribution to systems practitioners by supporting the future development of tools to help practitioners capture system context as a part of complex system problem formulation. The research also made a contribution in the area of research methodologies by furthering the use of the grounded theory method in the engineering management and systems engineering domain, an area where its application has been very limited.

Regional complex system simulation optimization through linking governance and environment performance: A case study of water environmental carrying capacity based on the SDES model

In complex systems, multiple aspects interact and influence each other. A vast number of entities are present in the system. Traditional modeling and simulation techniques fail to capture interactions between loosely coupled aspects of a complex distributed system. The objective of this work is to extend a Holonic methodology by using a formal specification language based on two formalisms: Generalized Stochastic Petri Net (GSPN) and Z language. Such a specification style facilitates the modeling of organizations and the interactions between them with both reactive and functional aspects. We illustrate the suitability of our generic approach by applying it to a Distributed Industrial Maintenance Company.