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Polymer-plugging agents are widely employed in profile control and water-plugging measures, serving as a crucial component for efficient reservoir development. However, quantitatively monitoring the emplacement depth of polymer-plugging agents in low-permeability and high-permeability layers remains a challenging bottleneck. Presently, insufficient attention on shear thinning, a critical rheological property for water shut-off and profile control, has limited our understanding of polymer distribution laws. In this study, polymer shear-thinning experiments are firstly conducted to explore polymer variations with flow rate. The novelty of the research is that varying polymer viscosity is implemented instead of the fixed-fluid viscosity that is conventionally used. The fitted correlation is then integrated into the 2D and 3D heterogeneous numerical models for simulations, and a multivariate nonlinear regression analysis is performed based on the simulation results. The results show that lower polymer emplacement depth ratios corresponded to higher viscosity loss rates under the same flow rate. An increase in the initial permeability ratio corresponds to a decrease in the emplacement ratio, along with a reduction in the fraction of the plugging agent penetrating the low permeability formations. The model was applied to the Kunan Oilfield and demonstrated a polymer reduction of approximately 3000 tons compared to traditional methods. Despite the slightly complex nature of the multivariate nonlinear mathematical model, it presents clear advantages in controlling plugging agent distribution and estimating dosage, laying good theoretical ground for the effective and efficient recovery of subsurface resources. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Southeast University (English Edition) is the property of Journal of Southeast University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Developing distributed real-time systems is a complex task that has historically entailed specialized handcraft. In this paper, we propose a retrospective on the (r)evolutionary changes that led to the transition from low-level programming to industrial full-fledged model-based development embodied by the Rubus Component Model and its tool-ecosystem. We focus on the needs, challenges, and solutions of a 15-year-long evolution journey of a software development approach that has gone from low-level and manual programming to a highly automated environment offering modeling, analysis, and development of vehicular software systems with multi-criticality for deployment on single- and multi-core platforms. [ABSTRACT FROM AUTHOR]

The stability of geogrid-reinforced soil structure is closely related to the interface characteristics between geogrid and soil. However, the creep behavior of the soil–geogrid interface is still unrevealed. In this study, using a modified stress-controlled pullout device, influence of the normal pressure, dry density, and water content on creep behavior of interface of compacted loess and high-density polyethylene (HDPE) geogrid is investigated. A three-parameter empirical model and a Merchant element model were established through fitting analysis. Analysis results show that the normal pressure, dry density, and water content have significant effects on the creep shear displacement of the reinforced soil interface. Under the same pullout level, creep displacement of the interface increases with the increase of water content and decreases with the increase of dry density and normal pressure. Both the three-parameter empirical model and Merchant element model can describe the creep characteristics of the reinforced soil interface. The Merchant model is more accurate in the early stage, while the three-parameter empirical model is more suitable for predicting the long-term creep deformation of the interface of compacted loess and geogrid. [ABSTRACT FROM AUTHOR]

Proton exchange membrane fuel cell system has been proposed as an alternative to the internal combustion engine due to its clean and high efficiency. Analysis of the coupling effects among components is critical to improve the design of the fuel cell system and shorten the development cycle. In this paper, the steady-state modeling of a fuel cell system is developed, focusing on the coupling effects between various components and the influence of operating conditions on the internal parameters. Firstly, the model of each component is established based on the mechanism or experience, and the boundary conditions of each component model are defined. Then, the component models are integrated into a system model, and the operation parameters of the system are solved by an iterative method. The operation conditions at different ambient temperatures are simulated and the results are discussed. It is indicated that a higher ambient temperature will significantly increase auxiliary power consumption and decrease system efficiency. The steady-state model proposed in this paper predicts the operation parameters of the system, which is helpful to reduce the development cost.

The stability of geogrid-reinforced soil structure is closely related to the interface characteristics between geogrid and soil. However, the creep behavior of the soil–geogrid interface is still unrevealed. In this study, using a modified stress-controlled pullout device, influence of the normal pressure, dry density, and water content on creep behavior of interface of compacted loess and high-density polyethylene (HDPE) geogrid is investigated. A three-parameter empirical model and a Merchant element model were established through fitting analysis. Analysis results show that the normal pressure, dry density, and water content have significant effects on the creep shear displacement of the reinforced soil interface. Under the same pullout level, creep displacement of the interface increases with the increase of water content and decreases with the increase of dry density and normal pressure. Both the three-parameter empirical model and Merchant element model can describe the creep characteristics of the reinforced soil interface. The Merchant model is more accurate in the early stage, while the three-parameter empirical model is more suitable for predicting the long-term creep deformation of the interface of compacted loess and geogrid.

Emotions are an inseparable part of human nature affecting our behavior in response to the outside world. Although most empirical studies have been dominated by two theoretical models including discrete categories of emotion and dichotomous dimensions, results from neuroscience approaches suggest a multi-processes mechanism underpinning emotional experience with a large overlap across different emotions. While these findings are consistent with the influential theories of emotion in psychology that emphasize a role for multiple component processes to generate emotion episodes, few studies have systematically investigated the relationship between discrete emotions and a full componential view. This article applies a componential framework with a data-driven approach to characterize emotional experiences evoked during movie watching. The results suggest that differences between various emotions can be captured by a few (at least 6) latent dimensions, each defined by features associated with component processes, including appraisal, expression, physiology, motivation, and feeling. In addition, the link between discrete emotions and component model is explored and results show that a componential model with a limited number of descriptors is still able to predict the level of experienced discrete emotion(s) to a satisfactory level. Finally, as appraisals may vary according to individual dispositions and biases, we also study the relationship between personality traits and emotions in our computational framework and show that the role of personality on discrete emotion differences can be better justified using the component model. [ABSTRACT FROM AUTHOR]

The Component Process Model is a well-established framework describing an emotion as a dynamic process with five highly interrelated components: cognitive appraisal, expression, motivation, physiology and feeling. Yet, few empirical studies have systematically investigated discrete emotions through this full multi-componential view. We therefore elicited various emotions during movie watching and measured their manifestations across these components. Our goal was to investigate the relationship between physiological measures and the theoretically defined components, as well as to determine whether discrete emotions could be predicted from the multicomponent response patterns. By deploying a data-driven computational approach based on multivariate pattern classification, our results suggest that physiological features are encoded within each component, supporting the hypothesis of a synchronized recruitment during an emotion episode. Overall, while emotion prediction was higher when classifiers were trained with all five components, a model without physiology features did not significantly reduce the performance. The findings therefore support a description of emotion as a multicomponent process, in which emotion recognition requires the integration of all the components. However, they also indicate that physiology per se is the least significant predictor for emotion classification among these five components.

Construction of Cyber-Physical Systems (CPS) by reusing or composing existing components (sub-systems) is the emerging need in software based system development. For software development, a number of paradigms exists to deal with the reusability at different levels. Component-based development (CBD) represents a paradigm shift in software development for its emphasis on development for/with reuse. Software composition mechanisms are the essence of this paradigm. In general, a software system in CBD is comprised of two kinds of elements: computation and communication. Defining/creating these elements in a generic way and for system construction allowing these elements to be customised in specific to the system needs can increase the level of reusability. In this paper, for a development paradigm (referred to as EX-MAN in CBD) for CPS construction, we focus on software elements dealing with the communications elements (referred to as connectors) among the computational elements. We define constraints (written in our proposed flow constraint language (FCL)) as a property for coordination by the exogenous connectors to customise the behaviour of connectors for system construction. In this paper, the semantics of FCL constraints for a sample exogenous connector is described for system construction/execution. In order to verify the operational semantics of FCL constraints of this exogenous connector, we use Coloured Petri Nets (in CPN tools) to model and simulate the connectors with constraints. Exogenous connectors are implemented in a tool exogenous composition framework (ECF) for system construction.

In the current era of systems biology research, there is a need for the integrative analysis of binary and quantitative genomics data sets measured on the same objects. One standard tool of exploring the underlying dependence structure present in multiple quantitative data sets is the simultaneous component analysis (SCA) model. However, it does not have any provisions when a part of the data are binary. To this end, we propose the generalized SCA (GSCA) model, which takes into account the distinct mathematical properties of binary and quantitative measurements in the maximum likelihood framework. Like in the SCA model, a common low‐dimensional subspace is assumed to represent the shared information between these two distinct types of measurements. To achieve a low rank solution, we propose to use a concave variant of the nuclear norm penalty. An efficient majorization algorithm is developed to fit this model with different concave penalties. Realistic simulations (low signal‐to‐noise ratio and highly imbalanced binary data) are used to evaluate the performance of the proposed model in recovering the underlying structure. Also, a missing value based cross‐validation procedure is implemented for model selection. We illustrate the usefulness of the GSCA model for exploratory data analysis of quantitative gene expression and binary copy number aberration measurements obtained from the GDSC1000 data sets. For the integrative analysis of binary and quantitative data sets, we propose the generalized simultaneous component analysis model. A common low‐dimensional subspace is assumed to represent the shared information between these two distinct types of measurements. To achieve a low‐rank solution, we propose to use a concave variant of the nuclear norm penalty. Efficient algorithms are developed. The model is validated by realistic simulations, and its usefulness is illustrated by the analysis of the GDSC1000 data sets. [ABSTRACT FROM AUTHOR]

After years of development, the complexity of the biological sequence alignment algorithm is gradually increasing, and the lack of high abstract level domain research leads to the complexity of its algorithm development and improvement. By applying the idea of software components to the design and development of algorithms, the development efficiency and reliability of biological sequence alignment algorithms can be effectively improved. The component assembly platform applies related assembly technology, which simplifies the operation difficulty of component assembly and facilitates the maintenance and optimization of the algorithm. At the same time, a friendly visual interface is used to intuitively complete the assembly of algorithm components, and an executable sequence alignment algorithm program is obtained, which can directly carry out alignment computing.

Copyright of Journal of National University of Defense Technology / Guofang Keji Daxue Xuebao is the property of NUDT Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper introduces a novel model-driven methodology for the software development of real-time distributed vehicular embedded systems on single- and multi-core platforms. The proposed methodology discloses the opportunity of improving the cost-efficiency of the development process by providing automated support to identify viable design solutions with respect to selected non-functional requirements. To this end, it leverages the interplay of modeling languages for the vehicular domain whose integration is achieved by a suite of model transformations. An instantiation of the methodology is discussed for timing requirements, which are among the most critical ones for vehicular systems. To support the design of temporally correct systems, cooperation between EAST-ADL and the Rubus component model is opportunely built-up by means of model transformations, enabling timing-aware design and model-based timing analysis of the system. The applicability of the methodology is demonstrated as the proof of concepts on industrial use cases performed in cooperation with our industrial partners.

Forecasting Photovoltaic (PV) energy production, based on the last weather and power data only, can obtain acceptable prediction accuracy in short-time horizons. Numerical Weather Prediction (NWP) systems usually produce free forecasts of the local cloud amount each 6 h. These are considerably delayed by several hours and do not provide sufficient quality. A Differential Polynomial Neural Network (D-PNN) is a recent unconventional soft-computing technique that can model complex weather patterns. D-PNN expands the n-variable kth order Partial Differential Equation (PDE) into selected two-variable node PDEs of the first or second order. Their derivatives are easy to convert into the Laplace transforms and substitute using Operator Calculus (OC). D-PNN proves two-input nodes to insert their PDE components into its gradually expanded sum model. Its PDE representation allows for the variability and uncertainty of specific patterns in the surface layer. The proposed all-day single-model and intra-day several-step PV prediction schemes are compared and interpreted with differential and stochastic machine learning. The statistical models are evolved for the specific data time delay to predict the PV output in complete day sequences or specific hours. Spatial data from a larger territory and the initially recognized daily periods enable models to compute accurate predictions each day and compensate for unexpected pattern variations and different initial conditions. The optimal data samples, determined by the particular time shifts between the model inputs and output, are trained to predict the Clear Sky Index in the defined horizon.

Copyright of Chinese Journal of Explosives & Propellants is the property of Chinese Journal of Explosives & Propellants Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Explosives & Propellants is the property of Chinese Journal of Explosives & Propellants Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Component-based software development (CBSD) is widely utilized to develop open CNC applications. It aims to build an open CNC application by composing a set of components, each implementing specific CNC sub-domain logic. Components conform to a certain component model to keep conformant interactive behaviors. Due to there is no standard granularity to decompose CNC domain and no general component model, as well as seldom consider extra-functional properties, components are heterogeneous. Moreover, they have a direct dependency rather than depending on abstractions. In a nutshell, there are many open-source CNC applications built by heterogeneous and tightly coupled components. They can implement CNC functionality but are good at functional extension and reconfiguration. In this paper, we apply CBSD and dependency inversion principle to develop a novel open CNC application which allows customizing CNC functionality. Specifically, a new granularity to decompose CNC domain is proposed. A special sub-domain is designed to encapsulate the execution logic of other sub-domains at an abstract level and instantiate concrete implementation details at runtime according to configuration. The functional properties of sub-domains are exposed via abstractions. Therefore, as long as re-writing the execution logic and configuring corresponding implementation details, CNC functionality can be extended or reconfigured. A prototype and several components have been developed to test the performance of the application. [ABSTRACT FROM AUTHOR]

The development of open CNC systems is a popular topic in the past three decades. From the perspective of software engineering, most open CNC prototypes are developed based on the component-based software development (CBSD) approach. That is, they are constructed by composing functional or logical components. This paper retrospects the development of CBSD-based open CNC systems. These systems are analyzed from three aspects. For the component granularity aspect, CNC domain analysis and component reusability are discussed. For the component model aspect, component models used in open CNC systems are summarized, illustrated, and discussed. Likewise, for the software architecture aspect, architecture styles are summarized, described, and analyzed. But due to the diversity and platform dependency of component models, there is no widely accepted platform that can collect and execute heterogeneous CNC components. Service is an evolution of components. It makes a traditional component to be platform-independent and supports communication via message. Thus, a service-oriented architecture (SOA)-based universal open CNC platform is an attractive development trend of diverse CBSD-based open CNC systems. And its development is similar to the development of the CBSD-based system, but more complicated because it contains more domain logic. Therefore, this paper provides a technical foundation for developing SOA-based open CNC platform which is a part of novel automation patterns, such as cloud manufacturing and cyber-physical production system. [ABSTRACT FROM AUTHOR]

In software engineering, composition is the way to reuse existing work. In component-based development (CBD), a number of component models are defined with an emphasis on composition mechanisms for components. With respect to components, current component models can be categorised into three main groups where components are: (i) objects, (ii) architectural units and (iii) encapsulated components. This paper presents a comparison of system construction in these three categories of component models and concludes selecting the X-MAN component model (X-MAN) from the third category for its edge over other models because of its exogenous composition connectors. However, because of the limitations of X-MAN, the use of this component model at a wider scale is hindered. In this paper, we propose extended X-MAN component model (EX-MAN) which addresses the limitations of X-MAN. To demonstrate the EX-MAN semantics for system construction, we have developed a tool exogenous composition framework (ECF). We have described the concepts used in our work using a trivial bank example. To evaluate the feasibility of EX-MAN for system construction, using ECF (a related tool we have developed), we constructed the trivial bank example and also a more complex system, CoCoME, example. [ABSTRACT FROM AUTHOR]

Smartphone use has increased markedly over the past decade and recent research has demonstrated that a small minority of users experience problematic consequences, which in extreme cases have been contextualized as an addiction. To date, most research have been quantitative and survey-based. This study qualitatively examined the components model of addiction for both "addicted" and "non-addicted" users. A screening tool comprising 10 dichotomous items was administered to 40 college students. Of these, six addicted and six non-addicted participants were identified on the basis of their score on the screening tool and were asked to participate in a semi-structured interview. The interview questions were based on the components model of addiction comprising six domains (i.e., salience, withdrawal, conflict, relapse and reinstatement, tolerance, and mood modification). Directed content analysis was used to analyze the transcribed data and subthemes as well as emerging themes for the study as a whole were established. There was some evidence of demarcation between smartphone addicts on the dimensions of salience, tolerance, withdrawal, and conflict. Mood modification was not much different in either group, and no participant reported relapse. The non-addicted group had much greater control over their smartphone usage than the addicted group on four (of six) aforementioned dimensions of behavioral addiction. Consequently, the main findings of this study provided good support for the components model of behavioral addiction. [ABSTRACT FROM AUTHOR]

This paper presents a semantics-based dynamic service composition architecture that composes an application through combining distributed components based on the semantics of the components. This architecture consists of a component model called Component Service Model with Semantics (CoSMoS), a middleware called Component Runtime Environment (CoRE), and a service composition mechanism called Semantic Graph based Service Composition (SeGSeC). CoSMoS represents the semantics of components. CoRE provides interfaces to discover and access components modeled by CoSMoS. SeGSeC composes an application by discovering components through CoRE, and synthesizing a workflow of the application based on the semantics of the components modeled by CoSMoS. This paper describes the latest design of the semantics-based dynamic service composition architecture, and also illustrates the implementation of the architecture based on the Web Service standards, i.e. WSDL, RDF, SOAP, and UDDL The Web Service based implementation of the architecture allows existing Web Services to migrate onto the architecture without reimplementation. It also simplifies the development and deployment of a new Web Service on the architecture by automatically generating the necessary description files (i.e. WSDL and RDF files) of the Web Service from its runtime binary (i.e. a Java class file).

Complex services may be dynamically composed through combining distributed components on demand (i.e., when requested by a user) in order to provide new services without preinstallation. Several systems have been proposed to dynamically compose services. However, they require users to request services in a manner that is not intuitive to the users. In order to allow a user to request a service in an intuitive form (e.g., using a natural language), this paper proposes a semantics-based service composition architecture. The proposed architecture obtains the semantics of the service requested in an intuitive form, and dynamically composes the requested service based on the semantics of the service. To compose a service based on its semantics, the proposed architecture supports semantic representation of components [through a component model named Component Service Model with Semantics (CoSMoS)], discovers components required to compose a service [through a middleware named Component Runtime Environment (CoRE)], and composes the requested service based on its semantics and the semantics of the discovered components [through a service composition mechanism named Semantic Graph-Based Service Composition (SeGSeC)]. This paper presents the design, implementation and empirical evaluation of the proposed architecture.

The concept of communicative competence has been the essence of numerous studies for over 50 years. Despite this, it still represents an attractive topic of research for many professionals both due to its importance and because of multiple confusions created by various interpretations of its meanings. The aim of this article is to throw light on some theoretical aspects that apply to the communicative competence, its components as approached in several models as well as teachers’ role and responsibility in its holistic development through selecting adapting and offering relevant educational materials.

Cyber-physical systems reconfigure the structure of their software architecture, e.g., to avoid hazardous situations and to optimize operational conditions like their energy consumption. These reconfigurations have to be safe so that the systems protect their users or environment against harmful conditions or events while changing their structure. As software architectures are typically built on components, reconfiguration actions need to take into account the component structure. This structure should support vertical composition to enable hierarchically encapsulated components. While many reconfiguration approaches for cyber-physical and embedded real-time systems allow the use of hierarchically embedded components, i.e., vertical composition, none of them offers a modeling and verification solution to take hierarchical composition, i.e., encapsulation, into account thus limiting reuse and compositional verification. In this paper, we present an extension to our existing modeling language, MECHATRONICUML, to enable safe hierarchical reconfigurations. The three extensions are (a) an adapted variant of the 2-phase-commit protocol to initiate reconfigurations that maintain component encapsulation, (b) the integration of feedback controllers during reconfiguration, and (c) a verification approach based on (timed) model checking for instances of our model. We illustrate our approach on a case study in the area of smart railway systems by showing two different use cases of our approach. We show that using our approach the systems can be easily designed to reconfigure safely. [ABSTRACT FROM AUTHOR]

The collective use of several models and tools at various abstraction levels and phases during the development of vehicular distributed embedded systems poses many challenges. Within this context, this paper targets the challenges that are concerned with the unambiguous refinement of timing requirements, constraints and other timing information among various abstraction levels. Such information is required by the end-to-end timing analysis engines to provide pre-run-time verification about the predictability of these systems. The paper proposes an approach to represent and refine such information among various abstraction levels. As a proof of concept, the approach provides a representation of the timing information at the higher levels using the models that are developed with EAST-ADL and Timing Augmented Description Language. The approach then refines the timing information for the lower abstraction levels. The approach exploits the Rubus Component Model at the lower level to represent the timing information that cannot be clearly specified at the higher levels, such as trigger paths in distributed chains. A vehicular-application case study is conducted to show the applicability of the proposed approach. [ABSTRACT FROM AUTHOR]

The availability of smart and intelligent sensors has changed the monitoring, control and maintenance of a conventional and advanced cyber-physical system used in public or private sectors of a society. For example, internet of things (IoT)-based health, agricultural and weather management systems. With the emergence of such sensors, along with the new ways to communicate or coordinate with them, we need to analyze and optimize the system construction processes. In this paper, to address the issue of scalability for bigger and complex systems based on sensors, we redefine an incremental construction process with an emphasis on behavior preservation and study the effectiveness of the use of software component models from the component-based development domain. In this paper, to deal with the issue of scalability, we investigate component-based development approaches with respect to our defined process and propose a taxonomy of component models with respect to component/system behavior. Moreover, based on the outcome of our analysis, we recommend the EX-MAN component model as the most suitable approach. We investigate incremental construction in the context of the three main categories of current component models, namely models where components are: (i) objects, (ii) architectural units and (iii) encapsulated components. Furthermore, to evaluate our defined process and selection of EX-MAN, we designed three examples of systems using our proposed process in EX-MAN component model.

The paper is focussed on partition walls assembled from hollow glass blocks. These blocks gained popularity recently because of new development: new decors, wide range of colours, variable surface finishing and wide range of accessories make it attractive for architects. In addition, improvements in acoustic and thermal properties, improved fire resistance and further innovations lead to new applications. The traditional method of assembling is based on using of cement mortar and steel reinforcement leading in kind of reinforcement concrete structure. However, the growing popularity demands new, easier and faster installation methods as is the Vitralock system. It consists of two plastic elements and steel reinforcement. The elements are easily assembled, there is no need for special tools and skills. The performance of the system needs to be verified and reliable design model and application rules need to be prepared. Extensive test programme was carried out at Czech technical University in Prague. It include full-scale test of the wall loaded by horizontal load to evaluate the overall performance. The test is briefly described in the paper. In addition, component tests were performed to obtain properties of several parts of the system. These tests allow to build component finite element model which can be used to predict the response of the wall. Detailed description of these tests and basic information about the model is included here.