Represent System Behavior Research Articles

Application of the ANFIS Method to Predict Satisfaction with Facilities and Infrastructure

Facilities and infrastructure are all movable or immovable objects or objects that are used to support every aspect of human life. Students, lecturers and office workers at least spend about half of their active hours at work. Therefore it is very important to pay attention to the high level of comfort, security, completeness in a building. There fore we need a way to predict satisfaction with facilities and infrastructure. To provide solutions to existing problems, the authors create applications that can predict the satisfaction of facilities and infrastructure. In this article, a satisfaction prediction approach based on a data-driven technique, representing system behavior using the Takagi-Sugeno model is developed. The Adaptive Neuro Fuzzy Inference System method is used to build a predictive model. The research was conducted by interview, observation and literature study. Data were taken from 92 respondents consisting of lecturers, students, and staff/employees in the research area. The test results using this method showed satisfactory results, indicating a success rate with an accuracy of 97.2%.

Transforming Software Requirements into Test Cases via Model Transformation

Executable test cases originate at the onset of testing as abstract requirements that represent system behavior. Their manual development is time-consuming, susceptible to errors, and expensive. Translating system requirements into behavioral models and then transforming them into a scripting language has the potential to automate their conversion into executable tests. Ideally, an effective testing process should start as early as possible, refine the use cases with ample details, and facilitate the creation of test cases.We propose a methodology that enables automation in converting functional requirements into executable test cases via model transformation. The proposed testing process starts with capturing system behavior in the form of visual use cases, using a domain-specific language, defining transformation rules, and ultimately transforming the use cases into executable tests.

Fast Design Space Exploration of Nonlinear Systems: Part I

System design tools are often only available as input–output blackboxes: for a given design as input, they compute an output representing system behavior. Blackboxes are intended to be run in the forward direction. This article presents a new method of solving the “inverse design problem,” namely, given requirements or constraints on output, find an input that also optimizes an objective function. This problem is challenging for several reasons. First, blackboxes are not designed to be run in reverse. Second, inputs and outputs can be discrete and continuous. Third, finding designs concurrently satisfying a set of requirements is hard because designs satisfying individual requirements may conflict with each other. Fourth, blackbox evaluations can be expensive. Finally, evaluations can sometimes fail to produce an output due to nonconvergence of underlying numerical algorithms. This article presents CNMA, a new method of solving the inverse problem that overcomes these challenges. CNMA tries to sample only the part of the design space relevant to solving the inverse problem, leveraging the power of neural networks, mixed-integer linear programs, and a new learning-from-failure feedback loop. This article also presents a parallel version of CNMA that improves the efficiency and quality of solutions over the sequential version and tries to steer it away from local optima. CNMA’s performance is evaluated against conventional optimization methods for seven nonlinear design problems of 8 (two problems), 10, 15, 36 and 60 real-valued dimensions and one with 186 binary dimensions. Conventional methods evaluated are stable, off-the-shelf implementations of the Bayesian optimization with the Gaussian Processes, Nelder–Mead, and Random Search. The first two do not even produce a solution for problems that are high dimensional, having both discrete and continuous variables or whose blackboxes fail to return values for some inputs. CNMA produces solutions for all problems. When conventional methods do produce solutions, CNMA improves upon their performance by 1%–87%.

Using activity time windows and logical representation to reduce the complexity of biological network models: G1/S checkpoint pathway with DNA damage

Biological systems are difficult to understand complex systems. Scientists continue to create models to simulate biological systems but these models are complex too; for this reason, new reduction methods to simplify complex biological models into simpler ones are increasingly needed. In this paper, we present a way of reducing complex quantitative (continuous) models into logical models based on time windows of system activity and logical (Boolean) models. Time windows were used to define slow and fast activity areas. We use the proposed approach to reduce a continuous ODE model into a logical model describing the G1/S checkpoint with and without DNA damage as a case study. We show that the temporal unfolding of this signalling system can be broken down into three time windows where only two display high level of activity and the other shows little or no activity. The two active windows represent a cell committing to cell cycle and making the G1/S transition, respectively, the two most important high level functions of cell cycle in the G1 phase. Therefore, we developed two models to represent these time windows to reduce time complexity and used Boolean approach to reduce interaction complexity in the ODE model in the respective time windows. The developed reduced models correctly produced the commitment to cell cycle and G1/S transfer through the expected behavior of signalling molecules involved in these processes. As most biological models have a large number of fast reactions and a relatively smaller number of slow reactions, we believe that the proposed approach could be suitable for representing many, if not all biological signalling networks. The approach presented in this study greatly helps in simplifying complex continuous models (ODE models) into simpler models. Moreover, it will also assist scientists build models concentrating on understanding and representing system behavior rather than setting values for a large number of kinetic parameters.

Combining genetic algorithm and pairwise testing for optimised test generation from UML ADs

Unified modelling language (UML) activity diagram (AD) is used to represent system behaviour abstractly and is used by testers to generate test cases and test data. During the design of test cases, AD with concurrent activities may lead to a large number of paths, and it may not always be possible to test all execution paths. Research on deriving test cases from AD having concurrent activities has focused on conventional search techniques such as breadth-first search and depth-first search which has been found to be inefficient in such cases. To overcome this drawback, the authors propose a method using pairwise testing and genetic algorithm to derive a reduced number of test cases in AD with concurrent activities. Experiments conducted on various real-life concurrent systems show that the proposed technique generates a reduced number of test cases compared with existing methods.

A dynamic model for the evolution of the next generation Internet: Implications for network policies

Abstract This paper studies the deployment of next generation Internet, which will serve as crucial infrastructure for basic network services for social connections as well as premium network services. Service productions and consumptions take different forms across these service types. For example, their network externalities are one of the distinct characteristics of social connections, while premium network services contribute to investment in network assets beyond a base level, resulting in extra capital stock. This multifaceted nature of the next generation Internet raises policy issues regarding network investment and net neutrality. This study aims at developing a dynamic model with a representative user whose preferences are differentiated by service types. The fraction of usage of social connections and the level of the extra capital stock are state variables representing system behavior. My analyses identify not only interior but also boundary equilibria under various scenarios about the relationships between the relative productivity and cost of social connectedness and premium network services. The policy implications from the analysis include the effects of rapid technological development on network obsolescence, which may tip the market in favor of social connections. Net neutrality may lead to unintended consequences though, due to its effects on the sources for network investment.

Gaussian process for 6-DoF rigid motions

Data-driven modeling approaches receive significant attention in robotics as they are capable of representing system behavior to which first-order principles cannot be employed. Modeling of human motions, based on observations is one of the many application areas. So far, however, the available probabilistic approaches cannot handle dynamics evolving in the space of rigid motions, as rotations are not appropriately considered. In this article, we present a mathematical framework for Gaussian process modeling, where the valid input domain is generalized to full rigid motions, namely the special Euclidean group SE(3). The kernel functions inside the Gaussian process are modified to exploit properties of the input data representation by dual quaternions. We further prove that the presented covariance functions maintain the Gaussian process properties. The correctness and accuracy of our approach is validated on simulated and real human motion data. We analyze the estimation performance of the novel Gaussian process framework in comparison to state of the art techniques, and show significantly improved model behavior of rigid motions.

Fault Tolerant Control Using Gaussian Processes and Model Predictive Control

Abstract Essential ingredients for fault-tolerant control are the ability to represent system behaviour following the occurrence of a fault, and the ability to exploit this representation for deciding control actions. Gaussian processes seem to be very promising candidates for the first of these, and model predictive control has a proven capability for the second. We therefore propose to use the two together to obtain fault-tolerant control functionality. Our proposal is illustrated by several reasonably realistic examples drawn from flight control.

An exploratory study of disaggregated clearing functions for production systems with multiple products

Clearing functions (CFs) have shown considerable promise for representing production capacity in production planning models due to their ability to capture the non-linear relationships between throughput, order releases and lead times. Most CFs developed to date use the total work in progress of all products, in units of processing time, as the state variable. In this paper, we investigate CFs for multi-product systems where the overall throughput of the system is affected by the product mix. We show that the aggregate work in process (WIP) variable used in the previous CF literature may lead to inaccurate estimates of expected throughput for individual products. To address this issue, we explore the use of multi-dimensional CFs (MDCFs) that use an extended definition of resource state based on the disaggregated WIP levels for individual products. Several new functional forms for MDCFs are postulated for single machine multi-product systems and their ability to represent system behaviour is assessed using simulation experiments. Results reveal that MDCFs are better able to predict system performance in the presence of mix-dependent capacity losses. We also discuss the extension of the MDCF approach to multi-stage production systems.

Sheet metal forming limits under stretch-bending with anisotropic hardening

One of the important failure criteria of press operations in industry for forming simulations is the Forming Limit Diagram (FLD). The complex loading effects on FLD, in particular the localized necking phenomenon under stretch-bending condition, have not been fully investigated and well understood. In practical sheet metal applications, the deformation is invariably three dimensional with a combination of stretching and bending. For most sheet materials under these complex loading processes used in industry, strong Bauschinger effect is observed, and the material hardening behavior tends to be anisotropic. This study aims to understand and evaluate such anisotropic hardening effect on the forming limit prediction under stretch-bending condition. The extended through-thickness Marciniak–Kuczynski (M–K) analysis is incorporated with Yoshida–Uemori (YU) two-surface kinematic hardening constitutive model, which has a more accurate description of the reverse loading behavior than that of the conventional isotropic hardening model. The material parameters used in this paper for YU model are calibrated with the experimental data from uniaxial large-strain tension-compression cyclic test. Both the isotropic hardening and YU kinematic hardening models with Hill'48 yield surface are employed in the analysis for the purpose of comparison. The Forming Limit Average Stress Diagram (FLASD) under stretch-bending condition is proposed to extend the understanding of Forming Limit Stress Diagram (FLSD) from in-plane to out-of-plane deformations. The “bending-ratio-dependent” phenomenon in forming limit diagram is predicted and observed in both stress/strain space with the proposed method. It suggests that the individual stress/strain state cannot represent system behavior. Forming limits under stretch-bending is suggested as an occurrence of system instability, not individual material instability. The system behavior of sheet metal deformation is reinforced as critical to the understanding of necking instability in stretch bending processes. The analysis shows that the Bauschinger effect provides positive effect in delaying the necking instability, predicting higher formability for sheet metals under stretch-bending. The insight obtained in this paper provides further understanding of the localized necking phenomenon under stretch-bending condition.

A proposal for extending UML-B to support a conceptual model

UML-B is a development process framework for Event-B based on a "UML-like" graphical formal notation that provides support for object-oriented modelling concepts, in particular, for class and state machine diagrams. However, this methodology has a gap for mapping requirements to formal specifications. To overcome this issue, we present a proposal for extending UML-B to support a conceptual model to provide an easier starting point for the actual development process. More precisely, we propose two diagrams to facilitate the passing from requirements to the initial formal model: a first one to represent system behavior based on UML 2 interaction overview diagram (IOD) and a second one for system structure based on boundary-control-entity stereotyped class diagram (BCE). We show how to translate the former into an Event-B specification and explain how to link the latter to the original UML-B using a simple ATM example as proof of concept.

Gypsies in the palace: experimentalist's view on the use of 3‐D physics‐based simulation of hillslope hydrological response

AbstractAs a fundamental unit of the landscape, hillslopes are studied for their retention and release of water and nutrients across a wide range of ecosystems. The understanding of these near‐surface processes is relevant to issues of runoff generation, groundwater–surface water interactions, catchment export of nutrients, dissolved organic carbon, contaminants (e.g. mercury) and ultimately surface water health. We develop a 3‐D physics‐based representation of the Panola Mountain Research Watershed experimental hillslope using the TOUGH2 sub‐surface flow and transport simulator. A recent investigation of sub‐surface flow within this experimental hillslope has generated important knowledge of threshold rainfall‐runoff response and its relation to patterns of transient water table development. This work has identified components of the 3‐D sub‐surface, such as bedrock topography, that contribute to changing connectivity in saturated zones and the generation of sub‐surface stormflow. Here, we test the ability of a 3‐D hillslope model (both calibrated and uncalibrated) to simulate forested hillslope rainfall‐runoff response and internal transient sub‐surface stormflow dynamics. We also provide a transparent illustration of physics‐based model development, issues of parameterization, examples of model rejection and usefulness of data types (e.g. runoff, mean soil moisture and transient water table depth) to the model enterprise. Our simulations show the inability of an uncalibrated model based on laboratory and field characterization of soil properties and topography to successfully simulate the integrated hydrological response or the distributed water table within the soil profile. Although not an uncommon result, the failure of the field‐based characterized model to represent system behaviour is an important challenge that continues to vex scientists at many scales. We focus our attention particularly on examining the influence of bedrock permeability, soil anisotropy and drainable porosity on the development of patterns of transient groundwater and sub‐surface flow. Internal dynamics of transient water table development prove to be essential in determining appropriate model parameterization. Copyright © 2010 John Wiley & Sons, Ltd.

Review of Recent Patents Related to Graphical Embedded Programming

This paper summarizes recent patents related to the use of graphical programming languages for the development of embedded computing applications. Patents in three specific areas of application are described in the paper. The first set of patents relates to general aspects of using graphical programming for applications targeted to embedded devices. The second area relates to the use of graphical programming environments to enable representations of system behavior using domain-specific “models of computation.” These models of computation may include control block diagrams, statecharts, textual math, etc. The third application area is the use of a graphical programming language to represent system behavior that may be targeted to any of a plurality of different embedded devices. In this case, the system behavior is abstracted to a general form and is not written in a manner that is specific to a particular device. Finally, the current and future developments in the field are briefly discussed. Keywords: Graphical programming, embedded programming, embedded computing, statechart, finite state machine, hardware description language (HDL), field-programmable gate array (FPGA), microprocessor, digital signal processor (DSP), real-time

The use of metamodeling for VoIP over WiFi capacity evaluation [Transactions Letters

The increasing popularity of wireless fidelity (Wi-Fi) networks at home, in public areas and in the enterprise motivates extensive modeling and analysis of their performance measures, such as network capacity and quality of service (QoS) capabilities. Some of the easier performance problems can be solved by analytical modeling methods, but most of the complicated ones, involving several design parameters from multiple layers, can only be answered through simulation studies that are typically implicit and less suitable for design and optimization. Hence, we believe it is crucial to obtain explicit mathematic models, that are effective in representing system behavior and a basis for performance optimization. Here, we first advocate the application of formal empirical modeling techniques to performance studies of Wi-Fi networks, in order to find usable, if approximate, closed-form mathematical models. Subsequently, by applying these metamodeling techniques, we perform a case study with very useful results: our VoWiFi (voice over Wi-Fi) admission capacity metamodel gives a much tighter bound than those existing in the literature and leads to a more effective admission control scheme. Our work, therefore, points out a new direction for future performance studies of Wi-Fi networks.

Coupling structural and functional models for interaction design

Model-based interaction design is a promising approach to the problem of building sophisticated interactive systems. Although many models and model-based design methods have been proposed, in practice their effectiveness has tended to be limited to solving fragmented design problems. One factor that has diminished the effectiveness of previous approaches has been their inability to integrate the various models used for different aspects of the overall design problem. This paper proposes a novel approach for combining a structural model and a functional model for complicated interaction design. Formal correspondence between the models is defined and a conversion process to transform from one model to the other and vice versa is introduced. The functional model, OCD, is an efficient technique for representing task procedures, while the structural model, statechart, is well suited to representing system behavior. The usability needs and system requirements are introduced into the design process through either representation. Then, the constraints formed by a decision in a model can be seen by the designer in the other model through transformation. The possibility of automatic conversion between the models warrants the consistence between the models through the design process even when the models should continually evolve.

Metaphorical representation in collaborative software engineering

Finding a useful abstract representation is fundamental to solving many difficult problems in software engineering. In order to better understand how representations are actually used in key collaborative software engineering tasks, this empirical study examined all of the spoken representations of software behavior in 9 domain analysis sessions. It found that about 70% of them were metaphorical, representing system behavior as physical movement of objects, as perceptual processes, or in anthropomorphic terms ascribing beliefs and desires to the system. The pattern of use of these representations indicates 1) that they were not merely temporary placeholders, but rather their use persisted even when a specialized and more formal vocabulary had been developed, and 2) the metaphoric descriptions appear to reflect actual use of metaphor, rather than just a choice of vocabulary. The use of metaphor is explained in terms of how well they serve human cognitive abilities and collaborative needs. The predominance of metaphorical representations in synchronous collaborative sessions raises important issues about the possible misleading effects of metaphorical thinking. It also raises questions about the compatibility of the spoken representations with other representations (e.g., diagrams, specification languages) that trigger, and capture the results of, the verbal collaborative work.

Results of the Application of a Linguistic Approach to Object-Oriented Analysis

In this paper, we present a linguistic approach in order to achieve the object oriented analysis (OOA) process in a systematic way. The approach is based on the definition of a formal correspondence between a subset of structures from linguistic world, called linguistic patterns, and a subset of structures from conceptual world, called conceptual patterns. This correspondence provides a solid basis in order to develop the conceptual models that represent the problem and its solution. One conceptual model will be used to represent the static part of the system, and another will represent system behavior.