Social insect colony as a biological regulatory system: modelling information flow in dominance networks

Social insects provide an excellent platform to investigate flow of information in regulatory systems since their successful social organization is essentially achieved by effective information transfer through complex connectivity patterns among the colony members. Network representation of such behavioural interactions offers a powerful tool for structural as well as dynamical analysis of the underlying regulatory systems. In this paper, we focus on the dominance interaction networks in the tropical social wasp Ropalidia marginata—a species where behavioural observations indicate that such interactions are principally responsible for the transfer of information between individuals about their colony needs, resulting in a regulation of their own activities. Our research reveals that the dominance networks of R. marginata are structurally similar to a class of naturally evolved information processing networks, a fact confirmed also by the predominance of a specific substructure—the ‘feed-forward loop’—a key functional component in many other information transfer networks. The dynamical analysis through Boolean modelling confirms that the networks are sufficiently stable under small fluctuations and yet capable of more efficient information transfer compared to their randomized counterparts. Our results suggest the involvement of a common structural design principle in different biological regulatory systems and a possible similarity with respect to the effect of selection on the organization levels of such systems. The findings are also consistent with the hypothesis that dominance behaviour has been shaped by natural selection to co-opt the information transfer process in such social insect species, in addition to its primal function of mediation of reproductive competition in the colony.     

An integrated module partition approach for complex products and systems based on weighted complex networks

The modularisation strategy can dramatically shorten the lead time and reduce the cost of complex products and systems (CoPS) development. Module partition is the basis of the modularisation. Because of the high technical content and multi-dimensional complexity of CoPS, the existing module partition approach cannot identify the module of CoPS effectively and efficiently. The complex network is introduced to visually represent the CoPS as their topological structures are very similar. The weights of the edges in the weighted complex network (WCN) are brought to illustrate the correlation strengths among components. An integrated approach is proposed in this article by modelling the CoPS module partition problem as the community detection problem of WCN. Firstly, the CoPS component-WCN is constructed and transformed to a multi-graph. Secondly, the modified GN algorithm is adopted to establish the community detection, namely module partition of CoPS. Finally, a module partition case example of a large tonnage crawler crane expounds that the proposed approach is effective and systematic to solve the CoPS module partition problem.     

New stage in the metrological provision for sensors

It is shown that traditional methods of metrological provision for critical sensors do not provide the required level of confidence for measurement results and economic efficiency. The desirability of changing to automatic monitoring of the metrological precision of sensors during operation is substantiated and requirements for the metrological procedures that are necessary are determined. __________ Translated from Izmeritel’naya Tekhnika, No. 3. pp. 69–73, March, 2007.     

Diagnostic system for identification of accident scenarios in nuclear power plants using artificial neural networks

This paper presents the work carried out towards developing a diagnostic system for the identification of accident scenarios in 220 MWe Indian PHWRs. The objective of this study is to develop a methodology based on artificial neural networks (ANNs), which assists in identifying a transient quickly and suggests the operator to initiate the corrective actions during abnormal operations of the reactor. An operator support system, known as symptom-based diagnostic system (SBDS), has been developed using ANN that diagnoses the transients based on reactor process parameters, and continuously displays the status of the reactor. As a pilot study, the large break loss of coolant accident (LOCA) with and without the emergency core cooling system (ECCS) in reactor headers has been considered. Several break scenarios of large break LOCA have been analyzed. The time-dependent transient data have been generated using the RELAP5 thermal hydraulic code assuming an equilibrium core, which conforms to a realistic estimation. The diagnostic results obtained from the ANN study are satisfactory. These results have been incorporated in the SBDS software for operator assistance. A few important outputs of the SBDS have been discussed in this paper.     

An integrated architecture for implementing extended producer responsibility in the context of Industry 4.0

Extended producer responsibility (EPR) is a regulatory measure to enforce the life cycle management of electrical and electronic equipment, however, the implementation of EPR programmes is not as effective as expected. In the face of the fourth industrial revolution that commonly labelled as ‘Industry 4.0,’ this paper proposes an integrated architecture to achieve effective and efficient EPR from the manufacturer perspective, and attention is specifically paid on promoting information sharing. On the basis of the selected case study, a smart refrigerator plant of Haier, the architecture integrates information systems and facilitates life cycle management. Particularly, eco-design and end-of-life disposal, the two lasting problems in the current practises of implementing EPR, can be enforced based on product modularisation and high level of information availability that provided by the architecture. The outcomes of this study provide a valuable reference for other sectors that involve EPR or product life cycle management.     

An integrated fuzzy approach for information technology planning in collaborative product development

Collaborative product development (CPD) processes are generally based on technological infrastructures. Various information technologies (IT) are proposed every day to facilitate collaboration, integration, co-design and co-development processes. In this highly uncertain environment, a systematic methodology is essential to plan the IT infrastructure needed to start and maintain a collaborative process. This study offers an integrated IT planning methodology combining fuzzy quality function deployment, fuzzy axiomatic design and fuzzy rule-based systems. The methodology is tested in a CPD case and the outcome presents an improvement path for IT for each of the collaborative parties.     

Numerical solution of an inverse diffusion problem for the moisture transfer coefficient in a porous material

On the basis of the solution of a nonlinear diffusion equation with initial and boundary conditions, a transfer coefficient of moisture in a sample of a porous material is found by minimization of a functional, which expresses error of the calculated profile of moisture concentration in well defined time moments from their experimental values for the defined moisture transfer coefficient. In this case the transfer coefficient as opposed to previous studies is found as a sum of a power function and an exponential function of the moisture concentration. The exponent of the power function depends on time. Thus, a more accurate coincidence of the calculated profiles of the moisture concentration to their experimental profiles is gained in comparison to the investigations performed by other authors. The exponential term provides a good coincidence of the mentioned profiles for big times nearby the boundary of the sample, where the moisture evaporation to the atmosphere takes place.     

New methods and technologies for the identification of optical measurements performed by video cameras with degeneration in the arrangement of test objects in the plane

New methods and technologies for the identification of optical measurements for video cameras in cases where the spatial arrangement of the test objects (test objects) in the plane becomes degenerate are considered. Moscow, Russia. Translated from Izmeritel’naya Tekhnika, No. 5, pp. 23–29, May, 2008.     

Spatial regression analysis of NOx and O3 concentrations in Madrid urban area using Radial Basis Function networks

This paper discusses the performance of Radial Basis Function networks (RBF) in a problem of spatial regression of pollutants in Madrid. Specifically, the spatial regression of NO_x and O₃ is considered, in such a way that, starting from a set of measuring points provided by the air quality monitoring network of Madrid, the complete surface of the pollutants in the city is obtained. This pollutant surface can be used as an initial step for modeling intra-urban pollution using land-use regression techniques for example. Also, different works has used a pollutant surface to study the patterns of pollution in different cities in the world and also to establish their air monitoring networks under mathematical criteria. The paper is focussed in analyzing the performance of RBF networks to obtain this first pollutant surface, so different RBF training algorithms are tested in this paper. Specifically, evolutionary-based RBF training algorithms are described, and compared with classical training algorithms for RBF networks with Gaussian kernels. The inclusion of meteorological variables in the RBF networks are also discussed in the paper. The experimental part of the article studies real results of the application of RBF networks to obtain a first pollutant surface of NO_x and O₃, using the data of the air pollution monitoring network of Madrid and the meteorological network of the city.