Opportunities and challenges for multicriteria assessment of food system sustainability

The focus of the Special Feature on “Multicriteria assessment of food system sustainability” is on the complex challenges of making and communicating overall assessments of food systems sustainability based on multiple and varied criteria. Four papers concern the choice and development of appropriate tools for making multicriteria sustainability assessments that handle built-in methodological conflicts and trade-offs between different assessment objectives. They underscore the value of linking diverse methods and tools, or nesting and stepping their deployment, to help build resilience and sustainability. They conclude that there is no one tool, one framework, or one indicator set that is appropriate for the different purposes and contexts of sustainability assessment. The process of creating the assessment framework also emerges as important: if the key stakeholders are not given a responsible and full role in the development of any assessment tool, it is less likely to be fit for their purpose and they are unlikely to take ownership or have confidence in it. Six other papers reflect on more fundamental considerations of how assessments are based in different scientific perspectives and on the role of values, motivation, and trust in relation to assessments in the development of more sustainable food systems. They recommend a radical break with the tradition of conducting multicriteria assessment from one hegemonic perspective to considering multiple perspectives. Collectively the contributions to this Special Feature identify three main challenges for improved multicriteria assessment of food system sustainability: (i) how to balance different types of knowledge to avoid that the most well-known, precise, or easiest to measure dimensions of sustainability gets the most weight; (ii) how to expose the values in assessment tools and choices to allow evaluation of how they relate to the ethical principles of sustainable food systems, to societal goals, and to the interests of different stakeholders; and (iii) how to enable communication in such a way that the assessments can effectively contribute to the development of more sustainable food systems by facilitating a mutual learning process between researchers and stakeholders. The wider question of how to get from assessment to transformation goes across all three challenges. We strongly recommend future research on the strengths, weaknesses, and complementarities of taking a values-based rather than a performance-based approach to promoting the resilience and sustainability of coupled ecological, economic, and social systems for ensuring food security and agroecosystem health in the coming millennium

Integrated assessment and valuation of ecosystem services - Guidelines and experiences

EU FP7 OpenNESS project deliverable D33 & D4

A GIS-based multi-criteria evaluation framework for uncertainty reduction in earthquake disaster management using granular computing

One of the most important steps in earthquake disaster management is the prediction of probable damages which is called earthquake vulnerability assessment. Earthquake vulnerability assessment is a multicriteria problem and a number of multi-criteria decision making models have been proposed for the problem. Two main sources of uncertainty including uncertainty associated with experts‘ point of views and the one associated with attribute values exist in the earthquake vulnerability assessment problem. If the uncertainty in these two sources is not handled properly the resulted seismic vulnerability map will be unreliable. The main objective of this research is to propose a reliable model for earthquake vulnerability assessment which is able to manage the uncertainty associated with the experts‘ opinions. Granular Computing (GrC) is able to extract a set of if-then rules with minimum incompatibility from an information table. An integration of Dempster-Shafer Theory (DST) and GrC is applied in the current research to minimize the entropy in experts‘ opinions. The accuracy of the model based on the integration of the DST and GrC is 83%, while the accuracy of the single-expert model is 62% which indicates the importance of uncertainty management in seismic vulnerability assessment problem. Due to limited accessibility to current data, only six criteria are used in this model. However, the model is able to take into account both qualitative and quantitative criteria

Risk Assessment Framework for Evaluation of Cybersecurity Threats and Vulnerabilities in Medical Devices

Medical devices are vulnerable to cybersecurity exploitation and, while they can provide improvements to clinical care, they can put healthcare organizations and their patients at risk of adverse impacts. Evidence has shown that the proliferation of devices on medical networks present cybersecurity challenges for healthcare organizations due to their lack of built-in cybersecurity controls and the inability for organizations to implement security controls on them. The negative impacts of cybersecurity exploitation in healthcare can include the loss of patient confidentiality, risk to patient safety, negative financial consequences for the organization, and loss of business reputation. Assessing the risk of vulnerabilities and threats to medical devices can inform healthcare organizations toward prioritization of resources to reduce risk most effectively. In this research, we build upon a database-driven approach to risk assessment that is based on the elements of threat, vulnerability, asset, and control (TVA-C). We contribute a novel framework for the cybersecurity risk assessment of medical devices. Using a series of papers, we answer questions related to the risk assessment of networked medical devices. We first conducted a case study empirical analysis that determined the scope of security vulnerabilities in a typical computerized medical environment. We then created a cybersecurity risk framework to identify threats and vulnerabilities to medical devices and produce a quantified risk assessment. These results supported actionable decision making at managerial and operational levels of a typical healthcare organization. Finally, we applied the framework using a data set of medical devices received from a partnering healthcare organization. We compare the assessment results of our framework to a commercial risk assessment vulnerability management system used to analyze the same assets. The study also compares our framework results to the NIST Common Vulnerability Scoring System (CVSS) scores related to identified vulnerabilities reported through the Common Vulnerability and Exposure (CVE) program. As a result of these studies, we recognize several contributions to the area of healthcare cybersecurity. To begin with, we provide the first comprehensive vulnerability assessment of a robotic surgical environment, using a da Vinci surgical robot along with its supporting computing assets. This assessment supports the assertion that networked computer environments are at risk of being compromised in healthcare facilities. Next, our framework, known as MedDevRisk, provides a novel method for risk quantification. In addition, our assessment approach uniquely considers the assets that are of value to a medical organization, going beyond the medical device itself. Finally, our incorporation of risk scenarios into the framework represents a novel approach to medical device risk assessment, which was synthesized from other well-known standards. To our knowledge, our research is the first to apply a quantified assessment framework to the problem area of healthcare cybersecurity and medical networked devices. We would conclude that a reduction in the uncertainty about the riskiness of the cybersecurity status of medical devices can be achieved using this framework

Partner selection in green supply chains using PSO – a practical approach

Partner selection is crucial to green supply chain management as the focal firm is responsible for the environmental performance of the whole supply chain. The construction of appropriate selection criteria is an essential, but often neglected pre-requisite in the partner selection process. This paper proposes a three-stage model that combines Dempster-Shafer belief acceptability theory and particle swarm optimization technique for the first time in this application. This enables optimization of both effectiveness, in its consideration of the inter-dependence of a broad range of quantitative and qualitative selection criteria, and efficiency in its use of scarce resources during the criteria construction process to be achieved simultaneously. This also enables both operational and strategic attributes can be selected at different levels of hierarchy criteria in different decision-making environments. The practical efficacy of the model is demonstrated by an application in Company ABC, a large Chinese electronic equipment and instrument manufacturer

The posterity of Zadeh's 50-year-old paper: A retrospective in 101 Easy Pieces – and a Few More

International audienceThis article was commissioned by the 22nd IEEE International Conference of Fuzzy Systems (FUZZ-IEEE) to celebrate the 50th Anniversary of Lotfi Zadeh's seminal 1965 paper on fuzzy sets. In addition to Lotfi's original paper, this note itemizes 100 citations of books and papers deemed “important (significant, seminal, etc.)” by 20 of the 21 living IEEE CIS Fuzzy Systems pioneers. Each of the 20 contributors supplied 5 citations, and Lotfi's paper makes the overall list a tidy 101, as in “Fuzzy Sets 101”. This note is not a survey in any real sense of the word, but the contributors did offer short remarks to indicate the reason for inclusion (e.g., historical, topical, seminal, etc.) of each citation. Citation statistics are easy to find and notoriously erroneous, so we refrain from reporting them - almost. The exception is that according to Google scholar on April 9, 2015, Lotfi's 1965 paper has been cited 55,479 times

Decision making for risk evaluation: integration of prospect theory with failure modes and effects analysis (FMEA)

The aim of the present study is to overcome some of the limitations of the FMEA method by presenting a theoretical base for considering risk evaluation into its assessment methodology and proposing an approach for its implementation. Fuzzy AHP is used to calculate the weights of the likelihood of occurrence (O), severity (S) and difficulty of detection (D). Additionally, the Prospect Theory-based TODIM method was integrated with fuzzy logic. Thus, fuzzy TODIM was employed to calculate the ranking of potential failure modes according to their RPNs. In order to verify the results of the study, in-depth interviews were conducted with the participation of industry experts. The results are very much in line with Prospect Theory. Therefore, practitioners may apply the proposed method to FMEA. The most crucial failure mode for a firm’s attention is furnace failure followed by generator failure, crane failure, tank failure, kettle failure, dryer failure, and operator failure, respectively. The originality of this paper consists in integrating Prospect Theory with the FMEA method in order to overcome the limitations naturally inherent in the calculation of the FMEA’s Risk Priority Numbers (RPNs).N/