Literatura académica sobre el tema "Causality diagram"

Because of the frequent occurrence of injury accident in the sports curriculum, the security of physical education cannot be ignored. So, this paper analyzes the factors of injury accident in physical education teaching process and proposes prevention measures. The establishment of security system in physical education is an urgent problem. This paper studies the causes and countermeasures of sports injury accidents based on two methods: causality diagram and analytic hierarchy process. The first section introduces the principles of causality diagram and hierarchical analysis in detail. The second part of the article establishes mathematical model of the analysis method. The part three of the text investigates and analyzes the accident status and prevention measures of 100 primary schools and universities in Heilongjiang province in the form of literature researches and questionnaires. It also proposes weight coefficients and causality diagrams of Sports Injury Accidents using causal analysis theory. It converts causal diagram into a hierarchical model using the analytic hierarchy process AHP.

Recent global trends in electric vehicles (EV) triggered Indonesia to participate in battery industry development. Rich in geological resources, the government promotes various capital-intensive industries that process raw mining commodities, particularly limonite nickel ore, to support the EV industry in Indonesia. Inarguably, financial support is needed from various financial institutions and investors. On the contrary, the mining industry is closely related to environmental issues that attract the attention of financial institutions and investors. Therefore, understanding the relationship between “sustainability” and “financing activity” is essential, as it may not only practically guide the business to re-examine their environmental, social, and governance (ESG) initiatives but also extend the literature review on these matters. Therefore, this paper aims to describe the system through the Causal Loop Diagram (CLD) formed by ESG factors related to the financing process in mining companies in Indonesia. The research method used in this paper is developing causal loop diagrams from primary data and literature reviews. The CLD is constructed through a literature review and confirmed by an expert from the mining company. The result explains the causal loop between sustainability and financing. Improving ESG performance will increase financial support from global investors and financial institutions. To support practice and concept sustainability in Indonesia, the government should encourage mining companies to increase local partnerships and CSR Allocation as it will support the company's financing activity and trigger community improvement. Creating a supporting environment to attract global investors to finance the mining company in Indonesia is also necessary. Keywords: Causal Loop Diagram, ESG Performance, Financial Performance, Mining Industry, Sustainability JEL : M14, Q01, G32

In order to obtain the effective network intrusion alarm information, and reveal the intention of attackers, an intrusion scenario dynamic correlation algorithm is proposed based on single value causality diagram. According to the composition principle of single value causality diagram, the key factors of the cause and effect diagram are defined. By relating the alarm information of intrusion detection system, attack scenarios are constructed based on cause and effect diagram, and dynamic correction is conduct. Based on the MIT Lincoln laboratory data sets, the correlation test is done using the above attack scenario correlation algorithm. Test results show that the reconstruction of attack scenarios and actual condition have very good consistency, proving that the proposed correlation algorithm can correctly reflect the real hacker intrusion process. The research of this paper provides effective help for the security administrator to implement effective management measures.

With the rapidly growing economy, the energy demand increases greatly. Due to energy distribution imbalance in the space, part of the areas lack of energy resources, relying on energy call to ensure energy security. In this paper, first of all, we put forward the steps of comparatively studying different modes of energy transmission with system dynamics model and carry out a causal analysis. Then we analyze the causality among model variables. Finally, we draft a causality diagram of model elements. Based on this, we establish quantitative relations among variables and draft a system flow diagram.

Universal Causality is a mathematical framework based on higher-order category theory, which generalizes previous approaches based on directed graphs and regular categories. We present a hierarchical framework called UCLA (Universal Causality Layered Architecture), where at the top-most level, causal interventions are modeled as a higher-order category over simplicial sets and objects. Simplicial sets are contravariant functors from the category of ordinal numbers Δ into sets, and whose morphisms are order-preserving injections and surjections over finite ordered sets. Non-random interventions on causal structures are modeled as face operators that map n-simplices into lower-level simplices. At the second layer, causal models are defined as a category, for example defining the schema of a relational causal model or a symmetric monoidal category representation of DAG models. The third layer corresponds to the data layer in causal inference, where each causal object is mapped functorially into a set of instances using the category of sets and functions between sets. The fourth homotopy layer defines ways of abstractly characterizing causal models in terms of homotopy colimits, defined in terms of the nerve of a category, a functor that converts a causal (category) model into a simplicial object. Each functor between layers is characterized by a universal arrow, which define universal elements and representations through the Yoneda Lemma, and induces a Grothendieck category of elements that enables combining formal causal models with data instances, and is related to the notion of ground graphs in relational causal models. Causal inference between layers is defined as a lifting problem, a commutative diagram whose objects are categories, and whose morphisms are functors that are characterized as different types of fibrations. We illustrate UCLA using a variety of representations, including causal relational models, symmetric monoidal categorical variants of DAG models, and non-graphical representations, such as integer-valued multisets and separoids, and measure-theoretic and topological models.

This article analysis QC group activity common method, including permutation diagram, causality diagram, countermeasure table, and discussion methods---brainstorming method. It grasp the design process and the actual value, point out the direction and laid a solid foundation for work of QC group activities in the enterprise effectively. It also create broad platform for innovation of enterprise product quality and increase of team cohesion.

Under the new wave of scientific and technological revolution, the construction industry finds itself with a critical need to alter the traditional and outdated production mode through technological innovation in order to realize industry transformation and move towards a new era characterized by digitalization, informatization, and intelligence. As intelligent construction is the indispensable pathway for the transformation and upgrading of the construction industry, it is of great significance to conduct in-depth research on its evaluation indicators and causality. This paper adopts the system dynamics method, based on the overall structure of intelligent construction, extracts the causality chain and causal feedback loop of intelligent construction, and presents a causality diagram and system dynamics diagram to build a robust system dynamics model for intelligent construction. On this basis, an evaluation index system for intelligent construction is constructed from the five dimensions—investment, design, construction, operation, and environment—for a holistic assessment of the current state of intelligent construction. The research aims to provide a valuable reference for professionals focusing on intelligent construction and the broader development of the industry.