Visual and persistence behavior modeling for DEVS in CoSMoS

Modelling the testing system brings the idea of model driven into testing field. Reusing testing resources is the core of the model, which effectively shortens the testing cycle. When the testing requirements or design specifications of the system under test (SUT) are changed, the testing system designers can adapt the change by adjusting the testing model. Based on the definition of the meta-model in this paper, the testing system model and instance data editor have been established by GMF (Graphical Modelling Framework) based on the mode driven development method. It realizes the visual modelling and the automatic generation of a part of code. In this paper, the situation of GMF is firstly introduced. Then it describes the process of designing and developing the visual modelling and the method of researching the visual modelling and automatically generating a part of code of the testing system in detail. At last, it presents the process and results of visual modelling by a website.

Visual environments for the modelling and simulation of complex, software-intensive systems are increasingly popular. While visual languages have many advantages, they may not be appropriate to render all details of a Discrete EVent system Specification (DEVS) model. Textual may be more appropriate, both to completely describe all details of a DEVS model (i.e., the content of transition and output functions), and to make the specification independent of the implementation platform (i.e., simulation implementation language). In this paper, we propose two textual notations that are used as part of an integrated modelling and simulation environment for the Parallel DEVS formalism. Both notations allow the specification of DEVS functions by means of neutral action code. DEVSPro uses Python-like textual syntax and supports the full power of Parallel DEVS. From this neutral specification, simulator-specific code is synthesized. DEVSLang supports blended textual/visual modelling. It is more restricted in expressiveness to match the limited expressiveness of visual notations. For example, the sequential states in an Atomic model must be explicitly enumerated. Visual DEVSLang models are transformed to their textual form in order to carry out syntactic and semantic checks. Possible detected errors are fed back to the visual modelling environment allowing the modeller to make changes directly in the source model. DEVSLang models are further translated automatically to DEVSPro models to allow for possible combination with DEVSPro models and subsequent analysis and simulation.

Computer simulations and behavioral modeling are becoming increasingly important in product development processes. Simulations can result in better decisions in less time by providing the designers with greater understanding of the product’s behavior. However, behavior model creators (i.e. analysts) and behavior model users (i.e. designers) often do not have the same level of understanding of the model, thus limiting the reuse of a model. Our goal in this research is to develop a clean interface that reduces the knowledge gap between engineering design and analysis by facilitating reuse of behavioral models. To achieve a higher level of reuse in the product design process, we propose a meta-data representation for formally characterizing behavioral models. The meta-data representation captures the assumptions, limitations, accuracy, and context of engineering behavioral models. Based on this knowledge representation, a proof-of-concept repository is implemented for archiving and exchanging reusable behavioral models. The knowledge representation and implementation is illustrated with a simple cantilever beam example.

It is increasingly crucial to build behavioral models with human physiological characteristics in complex scenes. Traditional methods are based on domain expert and computer-based knowledge discovery. This paper innovatively proposes a way of data acquisition that used pilot brain physiological signals for behavior modeling to solve the multiple flight sub-tasks classification. EEG pre-processing procedures based on data mining methods are proposed. Wavelet analysis and K-means algorithms are designed for feature extraction and optimization, respectively. The combination of quantitative and determinable modeling is adopted, which can help to understand the pilot behavior more accurately. Multiple sequence network coding scheme is used for quantitative physiological behavior model. Simultaneously, we proposed random forest algorithm to train a determinable behavioral decision model and grid search optimization should be required for hyper-parameter optimization. Results show that the alpha wavelet plays a significant role in behavioral decision-making. RF-GSO-Kmeans modeling obtain classification accuracy, precision, recall and f1-score indexes are 82.39%, 86.02%, 85.13%, and 85.22%. This will give important clues for future developments of behavioral model of robust and bionic characteristics combined physiological information and domain experts’ methods.

In this study, a functional and behavioral representation model for collaboration in product development is developed to represent assembly-related product knowledge, including its geometry, spatial relationships, function and behavior, which will be used to create a knowledge representation scheme to capture, store, and retrieve product knowledge. In this model, the function, behavior and artifact information is interrelated based on assembly associations. Functional and behavioral inputs and outputs are defined based on the spatial relationships in the assembly, as well as on the geometry of the product. The functional associations among artifacts define the “Behavior Model” with engineering formulas and physical rules. “Behavior Models” then define the behavior of the artifact. Behavior has four different forms for different phases in life cycle: (1) Intended Behavior in the conceptual design phase, (2) Estimated Behavior in the design phase, (3) Observed Behavior in the operation stage, and (4) Evaluated Behavior in the design and operation phases. When an unintended event (behavior) occurs, an additional function can be added to eliminate that effect. As a result, the functional and behavioral model is updated dynamically.

To make the creation of models under EDEVS (Event-Scheduling based Discrete Event System Specification) quick and easy, a graphical modeling framework, VISICOM (Visible Component Modeling Framework), is presented. Two primary elements of the framework are discussed: atomic model editor and coupled model editor. In atomic model editor, new EDEVS atomic models are created by dragging building blocks into the canvas and filling in parameters, so that the modeler need not be a sophisticated programmer. In coupled model editor, new EDEVS coupled models are built by dragging existing EDEVS models into the canvas, setting their configurable parameters and connecting their input and output ports.

Aiming at the inefficient design of virtual character behavior in traditional digital movies, this paper proposes to construct a virtual character behavior and control model. The virtual character’s behavior is constructed using a behavior tree, and perception and decision-making behavior models are created to optimize the visual perception of the virtual character. After the behavioral modeling is completed, the action controller is used to generate the character’s behavioral actions, combined with the physical dynamics method to capture the character’s trajectory, and the feedback control theory is applied to output the character’s joint rotation data information to realize the behavioral control of the virtual character. In the digital movie scene design of firefighters fighting and rescuing, the acquisition and execution time of a single behavioral modeling sample of this paper’s virtual character behavioral modeling method is 0.01s~0.03s, and the maximum running iteration time is 63.83s, which is faster than the agent-based behavioral modeling method. Compared to the traditional virtual character behavioral control method, which has an offset of more than 4mm, the virtual character firefighter generated in this paper has an offset of less than 0.3mm, which provides better control accuracy.

The article reveals the theoretical and applied principles of forming organizational behavior models in the conditions of the transformational economy of Ukraine. Given the challenges of the modern environment - war, economic instability, digitalization, changing consumer priorities - the issue of choosing and adapting an appropriate behavioral model for an enterprise becomes particularly important. The behavioral model of an organization is considered as a system of interrelated management decisions that shape the enterprise's response to external and internal changes.The work systematizes the main types of behavioral models: strategic, innovative, entrepreneurial, organizational, informational, market, competitive, and socially responsible. Particular attention is paid to examples of Ukrainian enterprises that effectively combine several management models under martial law. Statistical data for 2024 is analyzed, demonstrating the connection between an organization's adaptive behavior and its performance, competitiveness, and sustainability in the market. An approach to choosing a behavioral model is proposed, taking into account the level of organizational order, strategic priorities, and expectations of target groups. It is emphasized that the effective behavior of an enterprise is formed on the basis of a combination of rational economic mechanisms and behavioral attitudes of management subjects. It was also noted that in reality, behavioral models are combined by enterprises, which creates a certain synergy and improves the performance of the enterprise, organization, etc. The result of combining behavioral models of organizations can be: «Strategic + Innovative model» - a combination of the strategic vision of the long-term goals of the enterprise with active implementation of innovative solutions; «Information + Competitive Model» - the use of analytical tools contributes to a deeper understanding of the market, customer and competitor behavior; «Socially Responsible + Market Model» takes into account market needs and implements CSR strategies that can form a positive brand, strengthen consumer loyalty and increase market share; «Entrepreneurial + Organizational Model» combines initiative, flexibility and risk-taking with a clear internal structure and discipline, allowing you to create an environment in which innovations are implemented effectively and managed; "Innovative + Socially Responsible + Informational" combines three times and creates a high-tech, open and socially oriented. The results of the study have practical significance for business leaders, analysts, economists, and scholars who study issues of adaptive management, organizational behavior, and economic security in conditions of instability.

We present an evaluation of the Graphical Modeling Framework (GMF) based on our experiences in developing an editor for the risk modeling language CORAS using GMF. Our main hypothesis is that GMF shortens development time and results in more reliable and maintainable systems than alternative approaches which are not based on code generation. We conclude that the hypothesis is true, but that the answer is not as clear cut as we initially believed, and that there is still a large potential for improvement.

In this paper, we describe a new multi-mode telestimulation system for brain-microstimulation for the navigation of a robo-pigeon, a new type of bio-robot based on Brain-Computer Interface (BCI) techniques. The multi-mode telestimulation system overcomes neuron adaptation that was a key shortcoming of the previous single-mode stimulation by the use of non-steady TTL biphasic pulses accomplished by randomly alternating pulse modes. To improve efficiency, a new behavior model ("virtual fear") is proposed and applied to the robo-pigeon. Unlike the previous "virtual reward" model, the "virtual fear" behavior model does not require special training. The performance and effectiveness of the system to alleviate the adaptation of neurons was verified by a robo-pigeon navigation test, simultaneously confirming the practicality of the "virtual fear" behavioral model.

Visual workflow modeling is the most critical step of workflow application technology. In this paper, we realize a Visual Workflow Modeling tool using the Graphical Modeling Framework to separate the model, view and control, and by being taped to the Eclipse plugins pattern. By experimenting, the instrument can effectively support the business process modeling based on the workflow system, and this prototype tool lays the foundation for further development of simulation and verification tools.

The article shows that the development of the economy today clearly demonstrates the limitations of classical management theories, which are based on the rationality of decision-making, the provision of the subject of decision-making with full information about possible alternative options, as well as a clear understanding of the consequences of each of the possible alternatives. The difference between the algorithmic model (which involves the subject performing a certain sequence of actions, which is not necessarily understood, with a predicted result) and the heuristic behavioral model (which offers the subject a sequence of actions that is understandable to the subject without a guaranteed result) is shown. Features of classical, behavioral and irrational behavior models are also demonstrated. Information is provided on the most common heuristic methods of scientific research, which are: brainstorming (involves group thinking with the search for an optimal solution); method of multidimensional matrices (combination of individual elements of the research object based on chance); inversion method (finding a solution through the analysis of opposite characteristics). It was concluded that given the limitations of the theory of rational choice, decision-making processes are complicated by the vagueness of the criteria by which decisions are made. That is, it is increasingly possible to see atypicality in the identification of such criteria, which is complicated by cognitive biases that are formed in the decision-making subject. Regulation of behavioral models of economic subjects is a complex task, which involves the creation of such an institutional framework, which will take into account the peculiarities of the tendency to irrationality, cognitive limitations and prejudices. It was found that the top-level managers are increasingly using the tools of the so-called "pushing" of the managed system, which can be implemented according to several conventional versions: asymmetric paternalism, light paternalism, and libertarian paternalism.

Precise modeling with UML and OCL traditionally focuses on structural model features like class invariants. OCL also allows the developer to handle behavioral aspects in form of operation pre- and postconditions. However, behavioral UML models like statecharts have rarely been integrated into UML and OCL modeling tools. This paper discusses an approach that combines precise structure and behavior modeling: Class diagrams together with class invariants restrict the model structure and protocol state machines constrain the model behavior. Protocol state machines can take advantage of OCL in form of OCL state invariants and OCL guards and postconditions for state transitions. Protocol state machines can cover complete object lifecycles in contrast to operation pre- and postconditions which only affect single operation calls. The paper reports on the chosen UML language features and their implementation in a UML and OCL validation and verification tool.KeywordsStructure modelingBehavior modelingUMLOCLProtocol state machineState invariantGuardTransition postcondition

Periodontal disease is a significant global health burden affecting half of the world's population. Given that plaque and inflammation control are essential to the attainment of periodontal health, recent trends in preventive dentistry have focused on the use of behavioral models to understand patient psychology and promote self-care and treatment compliance. In addition to their uses in classifying, explaining and predicting oral hygiene practices, behavioral models have been adopted in the design of oral hygiene interventions from individual to population levels. Despite the growing focus on behavioral modification in dentistry, the currently available evidence in the field of periodontology is scarce, and interventions have primarily measured changes in patient beliefs or performance in oral hygiene behaviors. Few studies have measured their impact on clinical outcomes, such as plaque levels, gingival bleeding and periodontal pocket reduction, which serve as indicators of the patient's disease status and quality of oral self-care. The present narrative review aims to summarize selected literature on the use of behavioral models to improve periodontal outcomes. A search was performed on existing behavioral models used to guide dental interventions to identify their use in interventions measuring periodontal parameters. The main models were identified and subsequently grouped by their underlying theoretical area of focus: patient beliefs (health belief model and cognitive behavioral principles); stages of readiness to change (precaution adoption process model and transtheoretical model); planning behavioral change (health action process approach model, theory of planned behavior and client self-care commitment model); and self-monitoring (self-regulation theory). Key constructs of each model and the findings of associated interventions were described. The COM-B model, a newer behavioral change system that has been increasingly used to guide interventions and policy changes, is discussed with reference to its use in oral health settings. Within the limitations of the available evidence, interventions addressing patient beliefs, motivation, intention and self-regulation could lead to improved outcomes in periodontal health. Direct comparisons between interventions could not be made due to differences in protocol design, research populations and follow-up periods. The conclusions of this review assist clinicians with implementing psychological interventions for oral hygiene promotion and highlight the need for additional studies on the clinical effects of behavioral model-based interventions.

Analysis and classification of context-based malware behavior