Research on Advanced Knowledge Bases for Proactive Trouble Prevention in Complex Systems

A knowledge-based approach to the evaluation of fault trees

Wildfire is indiscriminate in its impacts, affecting communities, ecosystems, and landscapes regardless of borders or distinctions. As a social-ecological disturbance, wildfire embodies complex, interdependent interactions between humans and the natural environment and poses significant challenges for management. From residential properties to public lands, human-wildfire interactions occur along a continuum from dense urban centers to natural landscapes. There is an urgent need to better understand these dynamics, especially in the context of growing human pressures on natural systems, shifting wildfire activity, and climate change, which can amplify human exposure to wildfire risks. Focusing on the western United States, this research examines key aspects of human-wildfire interactions to advance proactive fire prevention and risk reduction strategies. Land use and land cover maps can be a useful tool for informing decision-making and improving hazard response and mitigation efforts, such as in the context of wildfires, but some existing maps are limited in their ability to identify building types. Chapter One leveraged remote sensing technologies and cloud computing to produce annually resolved maps of built infrastructure across the Snake River Plain in southern Idaho. We demonstrate that finer resolution maps that distinguish between residential and other infrastructure types can be generated from freely available remote sensing imagery and open source software that leverages data fusion with multispectral and radar imagery. Improved infrastructure maps advance our understanding of the wildland-urban interface (WUI), a prevailing term to describe areas where human and natural fire-prone systems meet and intermingle. However, the WUI concept has no unanimous definition, and methodologies for WUI mapping are highly varied. In Chapter Two, a critical review of the WUI concept, we demonstrate that the definition of the WUI profoundly shapes how it is mapped and interpreted, with implications for wildfire risk assessment, resource allocation, decision making and policy development. We emphasize the importance of adopting WUI definitions and methodologies that are flexible, tailored to local challenges, focus on proactive fire prevention, and involve collaboration between researchers and practitioners. WUI landscapes can be diverse, but human presence and proximity to vegetated lands is a consistent characteristic. A nexus for human-wildfire interactions, WUI spaces have drawn attention to the ways human behaviors contribute to, mitigate, and prevent wildfires. This focus has grown as human activity is increasingly recognized as a key driver of shifting wildfire patterns across the US. Less attention, however, has been directed towards areas adjacent to the WUI, such as public lands, where people engage in recreational activities. Chapter Three employed a multi-scale approach to explore wildfire ignition sources and patterns on public lands managed under the Bureau of Land Management National Conservation Lands system. We reveal that wildfire occurrences on these lands have increased, irrespective of whether the ignition cause is natural or anthropogenic. Further, natural ignitions dominate in most areas. However, the Morley Nelson Snake River Birds of Prey National Conservation Area, southern Idaho, emerged as hotspot for human-caused ignitions, particularly due to firearms, explosives use, equipment and vehicle use. National ignition patterns show higher natural ignitions in the non-coastal western US, but our findings highlight this area as a notable anomaly. This offers valuable insights into potential future conditions on other public lands, underscoring the need for targeted outreach, stronger regulatory measures, and improved fire-cause reporting standards to reduce human-caused ignitions. Collectively, this work advances our understanding of human-wildfire interactions both quantitatively and qualitatively. By prioritizing accurate, reliable data - from land use and land cover mapping to ignition source attribution - this research provides a foundation for more effective fire prevention strategies, targeted education and outreach efforts, and efforts to reduce human exposure to wildfire risk in an era of intensifying fire activity. Furthermore, by critically examining how such data can be used to define targeted areas and inform decision-making, this research advances knowledge of how data can be responsibly leveraged to shape more effective and equitable wildfire management practices.

Pragmatic Trials and Improving Long-Term Care: Recommendations From a National Institutes of Health Conference.

Sugar surfactants — aggregation, interfacial, and adsorption phenomena

Despite the wealth of information available on phase equilibria of oxide systems, there remain many gaps and inconsistencies in the knowledge base. From an industry perspective, there is an ongoing need to adequately describe the phase chemistry of slag systems in order to optimise process performance and improve productivity. Since this chemical behaviour cannot be predicted from first principles it follows, there is also an ongoing need for accurate experimental data. The advancements made in recent years in the capabilities of sophisticated analytical and measurement equipment have made it possible to develop new experimental techniques for the direct determination of phase equilibria in low order and complex multicomponent slag systems. In addition, the development of powerful computer modelling tools makes it possible to provide more comprehensive descriptions of the phase chemistry, to present the information in a range of perspectives, and to critically analyse the various types of related thermodynamic and structural information available. This review provides an overview of the types of information that can be used to determine phase equilibria in slag systems, analyses the influence of uncertainty and the relative importance of these types of data, and describes the advantages and limitations of the various experimental techniques that can be employed to obtain this information. Examples of recent studies are provided that demonstrate how an integrated approach to the determination of phase equilibria in complex systems, involving the use of targeted experimental studies and systematic thermodynamic model development, can lead to a better utilisation of the current research capabilities and resources, and more accurate descriptions of these systems.

Knowledge representation in expert systems for process control

System vulnerability is a major cause of failures in complex systems. Relevancy analysis and ranking of vulnerability are important for system administrative work. Our research roadmap is to define a framework for prioritizing vulnerabilities based on relevancy gleaned on online information. In order to do that a systematic representation of knowledge is needed. In this paper, the relationship between lifecycle and characteristic of vulnerability-related information are defined and used in building the Vulnerability Lifecycle Ontology (VLO). VLO is further enriched by standardized naming scheme, vulnerability database, taxonomy, and related documents from the Internet. VLO will be used as the knowledge base in the vulnerability relevancy framework.

Chapter 10 - Fundamentals of Nonlinear Dynamics

The capability to provide a platform for flexible business services in the Air Traffic Management (ATM) domain is both a major success factor for the ATM industry and a challenge to integrate a large number of complex and heterogeneous information systems. Most of the system knowledge needed for integration is not available explicitly in machine-understandable form, resulting in time-consuming and error-prone human tasks.In this paper we propose a knowledge-based ap-proach, Semantically-Enabled Externalization of Knowledge for the ATM domain (SEEK-ATM), which explicitly models a) expert knowledge on specific heterogeneous systems and integration requirements; and b) allows mapping of the specific knowledge to the general ATM problem domain knowledge for semantic integration. The domain-specific modeling enables a) to verify the integration knowledge base as requirements specification for later design of technical systems integration and b) to provide an API to the prob-lem space knowledge to facilitate tool support for efficient and effective systems integration. Based on an industry case study, we evaluate effects of the proposed SEEK-ATM approach in comparison to traditional system integration approaches in the ATM domain.

The development of effective and dependable methods for drilling through theso-called "heaving-shale" horizons, particularly in the Gulf Coastarea, is believed to comprise a major contribution to drilling technology, andto the task of finding and developing our undiscovered oil pools. Manymechanical remedies have been proposed and are in use in troublesome areas forcombating heaving shale. However, in conducting a research program it wasconcluded that the physical and chemical properties of shales should beinvestigated, and the effect of added chemicals on such properties determined.As a preliminary step, the effect of chemicals on bentonitic suspensions wasdetermined in accordance with recent contributions in the field of ceramics.The most plausible theoretical explanations for the behavior of the clayminerals involved are offered in the paper that follows. It is hoped thatsubsequent investigation of actual shale from troublesome wells will be aidedby the initial work done on bentonitic suspensions of known composition. Introduction Formations variously designated as "heaving shale," "sloughingshale" and "caving shale" impede and may even preclude drilling ofoil wells, particularly in certain parts of the Gulf Coast. In a previous paperit has been stated that the development of effective and dependable methods fordrilling through these troublesome beds is believed to comprise a majorcontribution to drilling technology, and to the task of finding and developingour undiscovered oil pools. Since the attack on the heaving-shale problem by mechanical means wasprincipally a matter of field investigation, it was concluded that a researchprogram should be concerned with the physical and chemical properties ofheaving shales, and the effect of added chemicals on such properties. It wasrealized that a study of shales required an advanced knowledge of the behaviorof the individual clay minerals. A thorough review of the literature led theauthors to the conclusion that very recent contributions in the field ofceramics furnished the most plausible theoretical explanations for the behaviorof clay minerals. Accordingly, these fundamental ideas will be used in anattempt to explain the behavior of more complex systems whose composition andreplaceable ions are known. T.P. 1401

Review: 84 refs.

Natural and intuitive interaction between users and complex systems is a crucial research topic in human‐computer interaction. A major direction is the definition and implementation of systems with natural language understanding capabilities. The interaction in natural language is often performed by means of systems called chatbots. A chatbot is a conversational agent with a proper knowledge base able to interact with users. Chatbots appearance can be very sophisticated with 3D avatars and speech processing modules. However the interaction between the system and the user is only performed through textual areas for inputs and replies. An interaction able to add to natural language also graphical widgets could be more effective. On the other side, a graphical interaction involving also the natural language can increase the comfort of the user instead of using only graphical widgets. In many applications multi‐modal communication must be preferred when the user and the system have a tight and complex interaction. Typical examples are cultural heritages applications (intelligent museum guides, picture browsing) or systems providing the user with integrated information taken from different and heterogenous sources as in the case of the iGoogle™ interface. We propose to mix the two modalities (verbal and graphical) to build systems with a reconfigurable interface, which is able to change with respect to the particular application context. The result of this proposal is the Graphical Artificial Intelligence Markup Language (GAIML) an extension of AIML allowing merging both interaction modalities. In this context a suitable chatbot system called Graphbot is presented to support this language. With this language is possible to define personalized interface patterns that are the most suitable ones in relation to the data types exchanged between the user and the system according to the context of the dialogue.

Interactions between software components play a major role in the achievement of goals in complex systems, such as platooning System-of-Systems (SoS). A platooning SoS groups vehicles in order to increase their fuel efficiency and alleviates traffic congestion by enabling driving in close proximity using operation protocols. In a platooning SoS, the execution of typical operations, such as Leave or Merge, consists of 20 micro-operations on average. Owing to this overabundance of sub-operations, interaction failures in a specific operation sequence can occur in an SoS execution. Further, analyzing the root cause of such failures is highly time-consuming, due to the density of the constituent interactions. Existing techniques suffer from two limitations: (1) The majority of the root cause analysis techniques are not capable of isolating faulty interaction sequences, because they do not directly utilize interaction data; (2) The majority of the fault diagnosis techniques assume the preexamined fault knowledge base, which needs too high cost due to limited knowledge in an SoS. To effectively analyze interaction failures in an SoS, we propose a pattern-based faulty interaction analysis technique. To this end, an interaction model is first defined for an SoS, followed by the proposal of a suspicious interaction pattern mining algorithm. During the case study using a platooning simulator, the technique automatically abstracts interaction data from logs and extracts faulty interaction patterns, thereby enabling the identification of seven new unreported interaction failure scenarios. The conclusions of this study can enrich the general fault knowledge base for platooning SoS.

Network intrusion detection systems identify malicious connections and thus help protect networks from attacks. Various data-driven approaches have been used in the development of network intrusion detection systems, which usually lead to either very complex systems or poor generalization ability due to the complexity of this challenge. This paper proposes a data-driven network intrusion detection system using fuzzy interpolation in an effort to address the aforementioned limitations. In particular, the developed system equipped with a sparse rule base not only guarantees the online performance of intrusion detection, but also allows the generation of security alerts from situations which are not directly covered by the existing knowledge base. The proposed system has been applied to a well-known data set for system validation and evaluation with competitive results generated.

Construction of a Knowledge Base for Simulation and Control of Large Scale and Complex Systems. Applications was published in Systems Analysis and Simulation 1988, I: Theory and Foundations. Proceedings of the International Symposium held in Berlin (GDR), September 12–16, 1988 on page 387.