Revealing Casual Pathways to Sustainable Water Service Delivering Using fsQCA

This study aimed to build on theory and practice regarding the combinations of conditions that influence water service sustainability when external partners are involved. The study investigates 26 well projects that have been implemented in developing countries with the assistance of Engineers Without Borders-USA (EWB-USA). Using past literature on sustainable water service delivery in developing communities, emergent coding techniques with project documents, and surveys with EWB-USA team members, this study identifies a set of project conditions to conduct fuzzy-set Qualitative Comparative Analysis (fsQCA). Findings show that the presence of a water committee cannot alone account for project sustainability. Additional conditions, such as technology and construction processes, project governance, and community engagement practices must also be considered for project sustainability. The relationship between construction quality and financial sustainability is also discussed. Overall, the findings from this research contribute to sector theory and reveal distinct pathways towards sustainable water services. These findings informed recommendations for EWB-USA well project implementation and management, and demonstrate the utility of fsQCA as a tool to navigate the complexities of water service delivery by external partners and improve understanding to increase water service sustainability

An Architectural Approach to Ensuring Consistency in Hierarchical Execution

Hierarchical task decomposition is a method used in many agent systems to organize agent knowledge. This work shows how the combination of a hierarchy and persistent assertions of knowledge can lead to difficulty in maintaining logical consistency in asserted knowledge. We explore the problematic consequences of persistent assumptions in the reasoning process and introduce novel potential solutions. Having implemented one of the possible solutions, Dynamic Hierarchical Justification, its effectiveness is demonstrated with an empirical analysis

Predicting and Evaluating Software Model Growth in the Automotive Industry

The size of a software artifact influences the software quality and impacts the development process. In industry, when software size exceeds certain thresholds, memory errors accumulate and development tools might not be able to cope anymore, resulting in a lengthy program start up times, failing builds, or memory problems at unpredictable times. Thus, foreseeing critical growth in software modules meets a high demand in industrial practice. Predicting the time when the size grows to the level where maintenance is needed prevents unexpected efforts and helps to spot problematic artifacts before they become critical. Although the amount of prediction approaches in literature is vast, it is unclear how well they fit with prerequisites and expectations from practice. In this paper, we perform an industrial case study at an automotive manufacturer to explore applicability and usability of prediction approaches in practice. In a first step, we collect the most relevant prediction approaches from literature, including both, approaches using statistics and machine learning. Furthermore, we elicit expectations towards predictions from practitioners using a survey and stakeholder workshops. At the same time, we measure software size of 48 software artifacts by mining four years of revision history, resulting in 4,547 data points. In the last step, we assess the applicability of state-of-the-art prediction approaches using the collected data by systematically analyzing how well they fulfill the practitioners' expectations. Our main contribution is a comparison of commonly used prediction approaches in a real world industrial setting while considering stakeholder expectations. We show that the approaches provide significantly different results regarding prediction accuracy and that the statistical approaches fit our data best

Forms and processes of information systems evolution

The way in which software evolves over time has been much studied and is now fairly well-understood. What has been less thoroughly studied are the processes by which information systems – containing software as one component, but also with significant human and organisational aspects – evolve. In many organisations, few information systems are built at all from scratch, but rather are modified from or built on top of existing ones or bolted together from third-party components. In practice, the old division between design, implementation and maintenance has largely disappeared. In this paper, I discuss the nature of IS evolution. I make a distinction between planned (intentional and strategic) evolution, for which we can formulate a clear process; and unplanned (emergent and externally-driven) evolution, where we can simply study the dynamics of the process and be ready for events

Renewable energy in remote communities

This article is the result of a competitively tendered University-funded project, this brings together two major Government Policy areas: sustainable communities and use of carbon fuels, and is aimed at influencing the policy debate on the difficulties of linking remote communities to renewable energy production because of poor distribution networks. Linkage with the Sustainable Communities agenda is an essential ingredient, as the proposal is that the renewable energy technologies will be installed and maintained by the communities themselves

Project scheduling under uncertainty using fuzzy modelling and solving techniques

In the real world, projects are subject to numerous uncertainties at different levels of planning. Fuzzy project scheduling is one of the approaches that deal with uncertainties in project scheduling problem. In this paper, we provide a new technique that keeps uncertainty at all steps of the modelling and solving procedure by considering a fuzzy modelling of the workload inspired from the fuzzy/possibilistic approach. Based on this modelling, two project scheduling techniques, Resource Constrained Scheduling and Resource Leveling, are considered and generalized to handle fuzzy parameters. We refer to these problems as the Fuzzy Resource Constrained Project Scheduling Problem (FRCPSP) and the Fuzzy Resource Leveling Problem (FRLP). A Greedy Algorithm and a Genetic Algorithm are provided to solve FRCPSP and FRLP respectively, and are applied to civil helicopter maintenance within the framework of a French industrial project called Helimaintenance

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

A beginner's guide to belief revision and truth maintenance systems

This brief note is intended to familiarize the non-TMS audience with some of the basic ideas surrounding classic TMS's (truth maintenance systems), namely the justification-based TMS and the assumption-based TMS. Topics of further interest include the relation between non-monotonic logics and TMS's, efficiency and search issues, complexity concerns, as well as the variety of TMS systems that have surfaced in the past decade or so. These include probabilistic-based TMS systems, fuzzy TMS systems, tri-valued belief systems, and so on