Modeling System Events and Negative Events Using Thinging Machines Based on Lupascian Logic

This paper is an exploration of the ontological foundations of conceptual modeling that addresses the concept of events and related notions. Development models that convey how things change over space and time demand continued attention in systems and software engineering. In this context, foundational matters in modeling systems include the definition of an event, the types of events, and the kinds of relationships that can be recognized among events. Although a broad spectrum of research of such issues exists in various fields of study, events have extensive applicability in computing (e.g., event-driven programming, architecture, data modeling, automation, and surveillance). While these computing notions are diverse, their event-based nature lets us apply many of the same software engineering techniques to all of them. In this paper, the focus is on addressing the dynamic concepts of system events and negative events. Specifically, we concentrate on what computer scientists would refer to as an event grammar and event calculus. Analyzing the concept of event would further the understanding of the event notion and provide a sound foundation for improving the theory and practice of conceptual modeling. An event in computer science has many definitions (e.g., anything that happens, changes in the properties of objects, and the occurrence of and transition between states). This paper is based upon a different conceptualization using thinging machines and Lupascian logic to define negative events. An event is defined as a time penetrated domain s region, which is described in terms of things and five-action machines. Accordingly, samples from event grammar and event calculus are remodeled and analyzed in terms of this definition. The results point to an enriched modeling technique with an enhanced conceptualization of events that can benefit behavior modeling in systems.Comment: 12 pages, 29 figure

Antithesis of Object Orientation: Occurrence-Only Modeling Applied in Engineering and Medicine

This paper has a dual character, combining a philosophical ontological exploration with a conceptual modeling approach in systems and software engineering. Such duality is already practiced in software engineering, in which the current dominant modeling thesis is object orientation. This work embraces an anti-thesis that centers solely on the process rather than emphasizing the object. The approach is called occurrence-only modeling, in which an occurrence means an event or process where a process is defined as an orchestrated net of events that form a semantical whole. In contrast to object orientation, in this occurrence-only modeling objects are nothing more than long events. We apply this paradigm to (1) a UML/BPMN inventory system in simulation engineering and (2) an event-based system that represents medical occurrences that occur on a timeline. The aim of such a venture is to enhance the field of conceptual modeling by adding yet a new alternative methodology and clarifying differences among approaches. Conceptual modeling s importance has been recognized in many research areas. An active research community in simulation engineering demonstrates the growing interest in conceptual modeling. In the clinical domains, temporal information elucidates the occurrence of medical events (e.g., visits, laboratory tests). These applications give an opportunity to propose a new approach that includes (a) a Stoic ontology that has two types of being, existence and subsistence; (b) Thinging machines that limit activities to five generic actions; and (c) Lupascian logic, which handles negative events. With such a study, we aim to substantiate the assertion that the occurrence only approach is a genuine philosophical base for conceptual modeling. The results in this paper seem to support such a claim.Comment: 13 pages, 16 figure

Why are events important and how to compute them in geospatial research?

Geospatial research has long centered around objects. While attention to events is growing rapidly, events remain objectified in spatial databases. This paper aims to highlight the importance of events in scientific inquiries and overview general event-based approaches to data modeling and computing. As machine learning algorithms and big data become popular in geospatial research, many studies appear to be the products of convenience with readily adaptable data and codes rather than curiosity. By asking why events are important and how to compute events in geospatial research, the author intends to provoke thinking into the rationale and conceptual basis of event-based modeling and to emphasize the epistemological role of events in geospatial information science. Events are essential to understanding the world and communicating the understanding, events provide points of entry for knowledge inquiries and the inquiry processes, and events mediate objects and scaffold causality. We compute events to improve understanding, but event computing and computability depend on event representation. The paper briefly reviews event-based data models in spatial databases and methods to compute events for site understanding and prediction, for spatial impact assessment, and for discovering events\u27 dynamic structures. Concluding remarks summarize key arguments and comment on opportunities to extend event computability

Business Process Simulation: Transformation of BPMN 2.0 to Discrete Event System Specification

Theoretical modeling is a complicated characteristic of a simulation study that straight affects the quality and effectiveness of simulation projects. This paper presents a model to model transformation from a conceptual modeling language to a simulation model specification. BPMN (Business Process Model and Notation) is worn for theoretical modeling and DEVS (Discrete Event System Specification) is elected for simulation model requirement. Simulation is a dynamic feature of MDSE and which explains the need of coherent M&S formalisms for simulation activities.Accordingly, this paper presents the simulation of service systems based on DEVS models. It defines a transformation approach of BPMN models into DEVS simulation models based on the metamodel approach, and describes the enrichment of obtained DEVS models through performance indicators (time and costs)

Event-entity-relationship modeling in data warehouse environments

We use the event-entity-relationship model (EVER) to illustrate the use of entity-based modeling languages for conceptual schema design in data warehouse environments. EVER is a general-purpose information modeling language that supports the specification of both general schema structures and multi-dimensional schemes that are customized to serve specific information needs. EVER is based on an event concept that is very well suited for multi-dimensional modeling because measurement data often represent events in multi-dimensional databases

Ontology mapping of business process modeling based on formal temporal logic

A business process is the combination of a set of activities with logical order and dependence, whose objective is to produce a desired goal. Business process modeling (BPM) using knowledge of the available process modeling techniques enable a common understanding and analysis of a business process. Industry and academics use informal and formal methods respectively to represent business processes (BP), having the main objective to support an organization. Despite both are aiming at BPM but the methods used are quite different in their semantics. While carrying out literature research, it has been found that there is no general representation of business process modeling is available that is expressive than the commercial modeling tools and techniques. Therefore, it is primarily conceived to provide an ontology mapping of modeling terms of Business Process Modeling Notation (BPMN), Unified Modeling Language (UML) Activity Diagrams (AD) and Event Driven Process Chains (EPC) to temporal logic. Being a formal system, first order logic assists in thorough understanding of process modeling and its application. However, our contribution is to devise a versatile conceptual categorization of modeling terms/constructs and also formalizing them, based on well accepted business notions, such as action, event, process, sub-process, connector and flow. It is demonstrated that the new categorization of modeling terms mapped to formal temporal logic, provides the expressive power to subsume business process modeling techniques i.e. BPMN, UML AD and EPC

Post-event visits as the sources of marketing strategy sustainability: a conceptual model approach

While extant literature has mainly concentrated on contemporaneous event tourism marketing (i.e., on visiting the city during or around the event) and on intentions to revisit after the event's completion, this research investigates the impact of the event on the decisions of potential tourists/visitors who have never visited the host city and want to visit it after the event's completion. Research in this area, especially in those emerging markets where event marketing is developing rapidly, is limited. In order to address the issues raised, a conceptual model is proposed. This model is based on a multivariate research approach, examining the interrelationships between event image, destination image, participants’ perceived satisfaction with the event and intentions to visit, under the context of non-repeat event marketing. Five hypotheses postulating these interrelationships were tested using structural equation modeling. A “non-repeat” event, the National Games, the biggest traditional sports event in China, was chosen to test this model. Selfadministered questionnaires were used to collect data relating to a period of two months after the event's completion. The findings show that the sustainability of event marketing strategy can be achieved through the post-event visit to the host city. First published online: 15 Jan 201

In-Depth Behavior Modeling of Transportation Networks: Description and Preliminary Results of a Subway Network Model

This paper describes the conceptual ideas behind a computer-aided microsimulation model combining agent-based modeling and discrete event simulation in order to reproduce the complex behavior of a fictitious subway system. Such a model allows passengers to be both active and passive agents behaving according to the model rules, and also affecting them in return, for more realistic results. Decision support in this network can be approached from both the passenger and the network operator perspective, by correctly predicting ridership and system delays. Preliminary results are presented, together with some of the challenges faced throughout the development process