Set Of Interconnected Modules Research Articles

Development of the information system for navigation in modern university campus

According to the aims, the paper highlights algorithmic, interface and technological solutions for the development of the information system for navigation in university campus. In the process of searching for algorithmic and interface solutions, the peculiarities of the scientific and applied problem of indoor navigation were analyzed, as well as the capabilities of selected analogues of navigation systems implementing similar functions of this subject domain were evaluated. It was concluded that the analyzed analogues, despite their significant functionality, have the set of limitations. The specification of functional and non-functional requirements for the university navigation system was carried out, its architecture was defined as a set of interconnected modules, for the implementation of which appropriate interface and algorithmic solutions were elaborated and covered. The main stages of design and development of the university navigation system in the context of the elaborated solutions are highlighted. The functionality of the implemented system is characterized. It was established that during the design it was possible to overcome the main limitations inherent in similar systems implementing indoor navigation. The results of the system implementation in the educational practice of a national university are highlighted. Feedback from users received during the approbation testified the feasibility of developing and using the information system for navigation in university campus. The prospects for further work are formulated.

Modular interdependency analysis for water distribution systems

Complexity in water distribution systems (WDSs) poses a challenge for analysis and management of the systems. To reduce the complexity, the recent development of complex network science provides a system decomposition technique that converts a complex WDS with a large number of components into a simple system with a set of interconnected modules. Each module is a subsystem with stronger internal connections than external connections. Thus far, the topological features of the modular structure in WDS have been extensively studied but not the behavioural features, e.g. the hydraulic interdependencies among modules. Therefore, this paper aims to quantitatively measure and graphically visualize the module interdependency in WDSs, which helps understanding the behavioural complexity of WDSs and thus various WDS analyses, such as pipe maintenance, model calibration, rehabilitation, and District Metered Areas planning. Specifically, this study first identifies the WDS's modular structure then measures how changes in the state of one module (i.e. any single pipe failure or perturbed demand within each module) affect the state of another module. Modular interdependencies are summarized in an interdependency matrix and visualized by the digraph. Four real-world systems are analysed, and three of them shows low interdependencies among most of the modules and there are only a few critical modules whose status changes will substantially affect a number of other modules. Hence, highly interconnected topologies may not result in strong and complex module interdependency, which is a fact that simplifies several WDS analysis for practical applications as discussed in this paper.

Models of technological integration development

Issues of scientific and technological development of the economy, increasing its competitiveness, including various aspects of technological integration, are the subject of foreign and domestic research. At the same time, technological integration is considered as a key direction of the new industrial and scientific-technical policy, as a means of transition to the digital economy, to production processes with higher added value, as a means of establishing a constructive dialogue between industrial enterprises and science. The reason for this is, on the one hand, the relative novelty of this economic phenomenon, and, on the other, the lack of theoretical and methodological tools for modelling the development of technological integration. The purpose of the article is to study the problems of modelling the development of technological integration in the context of priority scientific and technological development of the Russian economy. The article uses a wide range of general scientific methods: analysis and synthesis, grouping, typing, modelling, economicstatistical and graphical. The main methodological approaches used in the article are: structural-functional, instrumental and process approaches, which are reflected in the scientific and practical material of the general theory of systems, the theory of organization. The theoretical results of the study are the disclosure of the organizational model for the development of technological integration as a dynamic set of interconnected modules: management and coordination; structure; processes; resources designated to achieve the strategic objectives of technology integration participants. Classification characteristics of technological integration development processes have been identified and theoretically justified. The applied result is a specialized modelling tool based on a combination of a standardized approach and improved design quality with the ability to test simulated processes and the presence of stable feedback with all participants in technological integration. The process model of technological integration development was argued, its decomposition was carried out, which allows distinguishing the main, supporting and regulatory processes of participants in technological integration. The combination of these models facilitates the management of these processes in order to maximize the efficiency of the modern economy. An organizational and economic mechanism for modelling the development of technological integration is proposed, which allows the use of operational monitoring, due to the vector orientation of which it becomes possible to promptly carry out regular adjustments of key parameters of assessing the impact of technological integration on the results of technological development in national economies.

Distributed First Order Logic

Distributed First Order Logic (DFOL) has been introduced more than ten years ago with the purpose of formalising distributed knowledge-based systems, where knowledge about heterogeneous domains is scattered into a set of interconnected modules. DFOL formalises the knowledge contained in each module by means of first-order theories, and the interconnections between modules by means of special inference rules called bridge rules. Despite their restricted form in the original DFOL formulation, bridge rules have influenced several works in the areas of heterogeneous knowledge integration, modular knowledge representation, and schema/ontology matching. This, in turn, has fostered extensions and modifications of the original DFOL that have never been systematically described and published. This paper tackles the lack of a comprehensive description of DFOL by providing a systematic account of a completely revised and extended version of the logic, together with a sound and complete axiomatisation of a general form of bridge rules based on Natural Deduction. The resulting DFOL framework is then proposed as a clear formal tool for the representation of and reasoning about distributed knowledge and bridge rules.

Of Mice and Meth

This article describes an innovative neuropsychopharmacology laboratory that can be incorporated into any research methods class. The lab consists of a set of interconnected modules centered on observations of methamphetamine-induced behavioral changes in mice and is designed to provide students with an opportunity to acquire basic skills necessary for conducting research. To assess the practical utility of this new laboratory, an empirical study was conducted to determine whether different formats of the lab produce similar learning gains. The results suggest that both the live and the media-based variations of this lab are similarly effective. Thus, to facilitate the adoption of the lab, especially in its media-based format, all necessary materials are made available on a dedicated website.

An integer programming formulation to identify the sparse network architecture governing differentiation of embryonic stem cells

Primary purpose of modeling gene regulatory networks for developmental process is to reveal pathways governing the cellular differentiation to specific phenotypes. Knowledge of differentiation network will enable generation of desired cell fates by careful alteration of the governing network by adequate manipulation of cellular environment. We have developed a novel integer programming-based approach to reconstruct the underlying regulatory architecture of differentiating embryonic stem cells from discrete temporal gene expression data. The network reconstruction problem is formulated using inherent features of biological networks: (i) that of cascade architecture which enables treatment of the entire complex network as a set of interconnected modules and (ii) that of sparsity of interconnection between the transcription factors. The developed framework is applied to the system of embryonic stem cells differentiating towards pancreatic lineage. Experimentally determined expression profile dynamics of relevant transcription factors serve as the input to the network identification algorithm. The developed formulation accurately captures many of the known regulatory modes involved in pancreatic differentiation. The predictive capacity of the model is tested by simulating an in silico potential pathway of subsequent differentiation. The predicted pathway is experimentally verified by concurrent differentiation experiments. Experimental results agree well with model predictions, thereby illustrating the predictive accuracy of the proposed algorithm. ipb1@pitt.edu Supplementary data are available at Bioinformatics online.

Architectural energy optimization by bus splitting

This paper proposes split shared-bus architecture to reduce the energy dissipation for global data exchange among a set of interconnected modules. The bus splitting problem for minimum energy is formulated as a minimum-exchange bus split problem, which is shown to be NP-complete. The problem is solved heuristically by using a maximum-weight matching algorithm and combinatorial search. Experimental results show that the energy saving of split-bus architecture compared to monolithic-bus architecture varies from 16% to 50%, depending on the characteristics of the data transfer among the modules and the configuration of the split-bus. The proposed split-bus architecture can be extended to multiway split-bus architecture when large numbers of modules are to be connected.

A modular neural network approach to fault diagnosis

Certain real-world applications present serious challenges to conventional neural-network design procedures. Blindly trying to train huge networks may lead to unsatisfactory results and wrong conclusions about the type of problems that can be tackled using that technology. In this paper a modular solution to power systems alarm handling and fault diagnosis is described that overcomes the limitations of "toy" alternatives constrained to small and fixed-topology electrical networks. In contrast to monolithic diagnosis systems, the neural-network-based approach presented here accomplishes the scalability and dynamic adaptability requirements of the application. Mapping the power grid onto a set of interconnected modules that model the functional behavior of electrical equipment provides the flexibility and speed demanded by the problem. After a preliminary generation of candidate fault locations, competition among hypotheses results in a fully justified diagnosis that may include simultaneous faults. The way in which the neural system is conceived allows for a natural parallel implementation.

Fault analysis with modular neural networks

Automatic fault diagnosis in power systems presents real challenges to computing technologies. As an alternative approach to expert systems, several neural network solutions have been proposed recently. In this paper a modular, neural network-based solution to power systems alarm handling and fault diagnosis is described that overcomes the limitations of ‘toy’ alternatives constrained to small and fixed-topology electrical networks. In contrast to monolithical diagnosis systems, the neural network-based approach presented here fulfills the scalability and dynamic adaptability requirements of the application. Mapping the power grid onto a set of interconnected modules that model the functional behaviour of electrical equipment provides the flexibility and speed demanded by the problem. The way in which the neural system is conceived allows full scalability to real-size power systems.

Human physiology: Improving students' achievements through intelligent studyware

A studyware comprising a set of interconnected modules on human physiology has been developed and used to improve undergraduate students' achievements. Using the study modules, students can engage in active learning and enhance their spatial and problemsolving abilities, while the system monitors their responses and reacts accordingly. Examples from the Brain and Heart modules of the Human Physiology studyware are presented. The results of the study showed that although students' final grades were correlated with their previous biology course grades, the scores of those students who used the optional computer laboratory sessions were enhanced over those who did not use the studyware.