Reviewing qualitative research approaches in the context of critical infrastructure resilience

Modern societies are increasingly dependent on the proper functioning of critical infrastructures (CIs). CIs produce and distribute essential goods or services, as for power transmission systems, water treatment and distribution infrastructures, transportation systems, communication networks, nuclear power plants, and information technologies. Being resilient becomes a key property for CIs, which are constantly exposed to threats that can undermine safety, security, and business continuity. Nowadays, a variety of approaches exist in the context of CIs’ resilience research. This paper provides a state-of-the-art review on the approaches that have a complete qualitative dimension, or that can be used as entry points for semi-quantitative analyses. The study aims to uncover the usage of qualitative research methods through a systematic review based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). The paper identifies four principal dimensions of resilience referred to CIs (i.e., techno-centric, organisational, community, and urban) and discusses the related qualitative methods. Besides many studies being focused on energy and transportation systems, the literature review allows to observe that interviews and questionnaires are most frequently used to gather qualitative data, besides a high percentage of mixed-method research. The article aims to provide a synthesis of literature on qualitative methods used for resilience research in the domain of CIs, detailing lessons learned from such approaches to shed lights on best practices and identify possible future research directions

Foreign direct investments distribution in the Russian Federation: do spatial effects matter?

In this paper we explore the hypothesis of spatial effects in the distribution of Foreign Direct Investments (FDI) across Russian regions. We make use of a model, which describes FDI inflows as resulting from an agglomeration effect (the level of FDI in a given region depends positively on the level of FDI received by the regions in its neighbourhood) and remoteness effect (the distance of each Russian regions from the most important outflows countries). Considering a panel of 68 Russian regions over the period 2000-2004 we find that the two effects play a significant role in determining FDI inflows towards Russia. The two effects are also robust to the inclusion of other widely used explanatory variables impacting the level of FDI towards countries or regions (e.g. surrounding market potential, infrastructures, investment climate)

Benchmarking Image Processing Algorithms for Unmanned Aerial System-Assisted Crack Detection in Concrete Structures

This paper summarizes the results of traditional image processing algorithms for detection of defects in concrete using images taken by Unmanned Aerial Systems (UASs). Such algorithms are useful for improving the accuracy of crack detection during autonomous inspection of bridges and other structures, and they have yet to be compared and evaluated on a dataset of concrete images taken by UAS. The authors created a generic image processing algorithm for crack detection, which included the major steps of filter design, edge detection, image enhancement, and segmentation, designed to uniformly compare dierent edge detectors. Edge detection was carried out by six filters in the spatial (Roberts, Prewitt, Sobel, and Laplacian of Gaussian) and frequency (Butterworth and Gaussian) domains. These algorithms were applied to fifty images each of defected and sound concrete. Performances of the six filters were compared in terms of accuracy, precision, minimum detectable crack width, computational time, and noise-to-signal ratio. In general, frequency domain techniques were slower than spatial domain methods because of the computational intensity of the Fourier and inverse Fourier transformations used to move between spatial and frequency domains. Frequency domain methods also produced noisier images than spatial domain methods. Crack detection in the spatial domain using the Laplacian of Gaussian filter proved to be the fastest, most accurate, and most precise method, and it resulted in the finest detectable crack width. The Laplacian of Gaussian filter in spatial domain is recommended for future applications of real-time crack detection using UAS

Environmental performance of rainwater harvesting strategies in Mediterranean buildings

Purpose: The rapid urbanization and the constant expansion of urban areas during the last decades have locally led to increasing water shortage. Rainwater harvesting (RWH) systems have the potential to be an important contributor to urban water self-sufficiency. The goal of this study was to select an environmentally optimal RWH strategy in newly constructed residential buildings linked to rainwater demand for laundry under Mediterranean climatic conditions, without accounting for water from the mains. Methods: Different strategies were environmentally assessed for the design and use of RWH infrastructures in residential apartment blocks in Mediterranean climates. The harvested rainwater was used for laundry in all strategies. These strategies accounted for (i) tank location (i.e., tank distributed over the roof and underground tank), (ii) building height considering the number of stories (i.e., 6, 9, 12, and 15), and (iii) distribution strategy (i.e., shared laundry, supply to the nearest apartments, and distribution throughout the building). The RWH systems consisted of the catchment, storage, and distribution stages, and the structural and hydraulic calculations were based on Mediterranean conditions. The quantification of the environmental performance of each strategy (e.g., CO2eq. emissions) was performed in accordance with the life cycle assessment methodology. Results and discussion: According to the environmental assessment, the tank location and distribution strategy chosen were the most important variables in the optimization of RWH systems. Roof tank strategies present fewer impacts than their underground tank equivalents because they enhance energy and material savings, and their reinforcement requirements can be accounted for within the safety factors of the building structure without the tank. Among roof tanks and depending on the height, a distribution strategy that concentrates demand in a laundry room was the preferable option, resulting in reductions from 25 to 54 % in most of the selected impact categories compared to distribution throughout the building. Conclusions: These results may set new urban planning standards for the design and construction of buildings from the perspective of sustainable water management. In this sense, a behavioral change regarding demand should be promoted in compact, dense urban settlements.Peer ReviewedPostprint (author's final draft

Vulnerability reduction of infrastructure reconstruction projects

Various infrastructure segments of numerous countries have been repeatedly subjected to natural and man-made disasters. The potential reason of damaging infrastructure facilities and their services is resultant disaster risks due to natural or man-made hazards connect with vulnerable infrastructure facilities and vulnerable communities. The simplest way to prevent or mitigate disaster losses is addressing vulnerabilities. The main study based on which this paper was compiled aimed at exploring and investigating the vulnerabilities of infrastructures and communities benefited from infrastructures and possible solutions to overcome them. This paper presents the literature review conducted on vulnerabilities of infrastructures and empirical evidence collated on best possible DRR strategies to overcome such vulnerabilities of infrastructures. The main study was conducted using case study strategy and the expert interviews. This paper is entirely based on the data collated from the expert interviews conducted in Sri Lanka and United Kingdom. The expert interviews discovered various DRR strategies to overcome the vulnerabilities of the infrastructure project

Enhancing Infrastructure Resilience Under Conditions of Incomplete Knowledge of Interdependencies

Today’s infrastructures — such as road, rail, gas, electricity and ICT — are highly interdependent, and may best be viewed as multi-infrastructure systems. A key challenge in seeking to enhance the resilience of multi-infrastructure systems in practice relates to the fact that many interdependencies may be unknown to the operators of these infrastructures. How can we foster infrastructure resilience lacking complete knowledge of interdependencies? In addressing this question, we conceptualize the situation of a hypothetical infrastructure operator faced with incomplete knowledge of the interdependencies to which his infrastructure is exposed. Using a computer model which explicitly represents failure propagations and cascades within a multi-infrastructure system, we seek to identify robust investment strategies on the part of the operator to enhance infrastructure resilience. Our results show that a strategy of constructing redundant interdependencies may be the most robust option for a financially constrained infrastructure operator. These results are specific to the infrastructure configuration tested. However, the developed model may be tailored to the conditions of real-world infrastructure operators faced with a similar dilemma, ultimately helping to foster resilient infrastructures in an uncertain world

Survey and Analysis of Production Distributed Computing Infrastructures

This report has two objectives. First, we describe a set of the production distributed infrastructures currently available, so that the reader has a basic understanding of them. This includes explaining why each infrastructure was created and made available and how it has succeeded and failed. The set is not complete, but we believe it is representative. Second, we describe the infrastructures in terms of their use, which is a combination of how they were designed to be used and how users have found ways to use them. Applications are often designed and created with specific infrastructures in mind, with both an appreciation of the existing capabilities provided by those infrastructures and an anticipation of their future capabilities. Here, the infrastructures we discuss were often designed and created with specific applications in mind, or at least specific types of applications. The reader should understand how the interplay between the infrastructure providers and the users leads to such usages, which we call usage modalities. These usage modalities are really abstractions that exist between the infrastructures and the applications; they influence the infrastructures by representing the applications, and they influence the ap- plications by representing the infrastructures

Closing the technology gap?

This paper focuses on the dimensions shaping the dynamics of technology. We present a model where the knowledge stock of a country grows over time as a function of three main factors: its innovation intensity, its technological infrastructures and its human capital. The latter two variables contribute to determine the absorptive capacity of a country as well as its innovative ability. Based on this theoretical framework, we carry out an empirical analysis that investigates the dynamics of technology in a large sample of developed and developing economies in the last two-decade period, and studies its relationships with the growth of income per capita in a dynamic panel model setting. The results indicate that the cross-country distributions of technological infrastructures and human capital have experienced a process of convergence, whereas the innovative intensity is characterized by increasing polarization between rich and poor economies. Thus, while the conditions for catching up have generally improved, the increasing innovation gap represents a major factor behind the observed differences in income per capita.Growth and development; technology gap; absorptive capacity; innovation; polarization; twin-peaks