Sensor placement for fault location identification in water networks: A minimum test cover approach

This paper focuses on the optimal sensor placement problem for the identification of pipe failure locations in large-scale urban water systems. The problem involves selecting the minimum number of sensors such that every pipe failure can be uniquely localized. This problem can be viewed as a minimum test cover (MTC) problem, which is NP-hard. We consider two approaches to obtain approximate solutions to this problem. In the first approach, we transform the MTC problem to a minimum set cover (MSC) problem and use the greedy algorithm that exploits the submodularity property of the MSC problem to compute the solution to the MTC problem. In the second approach, we develop a new \textit{augmented greedy} algorithm for solving the MTC problem. This approach does not require the transformation of the MTC to MSC. Our augmented greedy algorithm provides in a significant computational improvement while guaranteeing the same approximation ratio as the first approach. We propose several metrics to evaluate the performance of the sensor placement designs. Finally, we present detailed computational experiments for a number of real water distribution networks

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Resilience markers for safer systems and organisations

If computer systems are to be designed to foster resilient performance it is important to be able to identify contributors to resilience. The emerging practice of Resilience Engineering has identified that people are still a primary source of resilience, and that the design of distributed systems should provide ways of helping people and organisations to cope with complexity. Although resilience has been identified as a desired property, researchers and practitioners do not have a clear understanding of what manifestations of resilience look like. This paper discusses some examples of strategies that people can adopt that improve the resilience of a system. Critically, analysis reveals that the generation of these strategies is only possible if the system facilitates them. As an example, this paper discusses practices, such as reflection, that are known to encourage resilient behavior in people. Reflection allows systems to better prepare for oncoming demands. We show that contributors to the practice of reflection manifest themselves at different levels of abstraction: from individual strategies to practices in, for example, control room environments. The analysis of interaction at these levels enables resilient properties of a system to be ‘seen’, so that systems can be designed to explicitly support them. We then present an analysis of resilience at an organisational level within the nuclear domain. This highlights some of the challenges facing the Resilience Engineering approach and the need for using a collective language to articulate knowledge of resilient practices across domains

Targeted consultancy services as an instrument for the development of rural SMEs - a brazilian case

One of the problems that policy makers face in the process of development in many countries is the inequality between the periphery and the metropolis center. The periphery has difficulties making the structural adjustments needed to fit in the national growth, leading to growing unemployment rates, regional gaps and continuous migration to the big metropolis. One of the sectors that has a difficulty making the transition is the small business sector. Amongst the reasons is in-adequate skills and information of the business management and in some cases a lack of awareness to the importance of these fields in the potential growth to the business. In addition the government support systems for small businesses do not give an adequate response. Support programs for small businesses are mostly provided within the urban sector, and are not adapted to the needs of the rural sector. The outcome is that although there is a "potential" need among small businesses in the interior for business consultant's services and in-spite of there being a wide range system of support for small businesses at the national level, their access to such services is limited. As a consequence of the potential demand that doesn't come into expression in the existing structure and of a national supply of these services that does not meet the needs of this sector, the gaps between the rural area and the urban central area grows. Our hypothesis is that an effort to establish a link between the unexpressed demand and the inappropriate supply of services to small-scale businesses in the rural area may contribute to economic growth. We test this hypothesis by using a program that was launched in the state of Ceara, Brazil, that is set to aim at both the demand and supply, focusing on a specific population: non-agricultural businesses in the rural region. The program is intended in the first stage to create awareness in the business community to the potential for business development and to encourage their demand for such services. The program offers consultancy services suited to the special needs of businesses in the non-metropolitan region adopting a reach-out approach. The program is part of the San Jose Project directed by the Secretary of Rural Development of the State of Ceara, that is aimed to bring a reduction in poverty in rural poor areas. The first stage of the research is to identify the potential of demand for consulting services and identifying the main areas in which the consulting is needed. A questionnaire was applied to 224 entrepreneurs in three selected areas. The findings show that about all the entrepreneurs are interested in receiving the consulting services. 90% of them evaluated that they had a growth potential. The factors that they point out as main constraints are, in order: physical infrastructures (65%), marketing (60%), capital returns (52%) problems in management and labor force (37%) and administration problems (35%). The second stage of the research was focused on 140 entrepreneurs who responded to a few basic criteria and were entitled to receive basic consulting services, of up to 15 hours. At this stage the marketing turned up as a main problem, especially for businesses that are in a process of transition from local to national markets. The findings show also that the support system that provides the consultancy services needs to go through a process of adaptation. One important difficulty of the system is to switch from internal advisers to external ones who specialize in the field.

Internal combustion engine sensor network analysis using graph modeling

In recent years there has been a rapid development in technologies for smart monitoring applied to many different areas (e.g. building automation, photovoltaic systems, etc.). An intelligent monitoring system employs multiple sensors distributed within a network to extract useful information for decision-making. The management and the analysis of the raw data derived from the sensor network includes a number of specific challenges still unresolved, related to the different communication standards, the heterogeneous structure and the huge volume of data. In this paper we propose to apply a method based on complex network theory, to evaluate the performance of an Internal Combustion Engine. Data are gathered from the OBD sensor subset and from the emission analyzer. The method provides for the graph modeling of the sensor network, where the nodes are represented by the sensors and the edge are evaluated with non-linear statistical correlation functions applied to the time series pairs. The resulting functional graph is then analyzed with the topological metrics of the network, to define characteristic proprieties representing useful indicator for the maintenance and diagnosis

MISSED: an environment for mixed-signal microsystem testing and diagnosis

A tight link between design and test data is proposed for speeding up test-pattern generation and diagnosis during mixed-signal prototype verification. Test requirements are already incorporated at the behavioral level and specified with increased detail at lower hierarchical levels. A strict distinction between generic routines and implementation data makes reuse of software possible. A testability-analysis tool and test and DFT libraries support the designer to guarantee testability. Hierarchical backtrace procedures in combination with an expert system and fault libraries assist the designer during mixed-signal chip debuggin