An analytic framework to assess organizational resilience

Background: Resilience Engineering is a paradigm for safety management that focuses on coping with complexity to achieve success, even considering several conflicting goals. Modern socio-technical systems have to be resilient to comply with the variability of everyday activities, the tight-coupled and underspecified nature of work and the nonlinear interactions among agents. At organizational level, resilience can be described as a combination of four cornerstones: monitoring, responding, learning and anticipating. Methods: Starting from these four categories, this paper aims at defining a semi-quantitative analytic framework to measure organizational resilience in complex socio-technical systems, combining the Resilience Analysis Grid (RAG) and the Analytic Hierarchy Process (AHP). Results: This paper presents an approach for defining resilience abilities of an organization, creating a structured domain-dependent framework to define a resilience profile at different levels of abstraction, to identify weaknesses and strengths of the system and thus potential actions to increase system’s adaptive capacity. An illustrative example in an anaesthesia department clarifies the outcomes of the approach. Conclusions: The outcome of the RAG, i.e. a weighted set of probing questions, can be used in different domains, as a support tool in a wider Safety-II oriented managerial action to bring safety management into the core business of the organization

Trespassing the Boundaries: Labeling Temporal Bounds for Object Interactions in Egocentric Video

Manual annotations of temporal bounds for object interactions (i.e. start and end times) are typical training input to recognition, localization and detection algorithms. For three publicly available egocentric datasets, we uncover inconsistencies in ground truth temporal bounds within and across annotators and datasets. We systematically assess the robustness of state-of-the-art approaches to changes in labeled temporal bounds, for object interaction recognition. As boundaries are trespassed, a drop of up to 10% is observed for both Improved Dense Trajectories and Two-Stream Convolutional Neural Network. We demonstrate that such disagreement stems from a limited understanding of the distinct phases of an action, and propose annotating based on the Rubicon Boundaries, inspired by a similarly named cognitive model, for consistent temporal bounds of object interactions. Evaluated on a public dataset, we report a 4% increase in overall accuracy, and an increase in accuracy for 55% of classes when Rubicon Boundaries are used for temporal annotations.Comment: ICCV 201

Decision support model for the selection of asphalt wearing courses in highly trafficked roads

The suitable choice of the materials forming the wearing course of highly trafficked roads is a delicate task because of their direct interaction with vehicles. Furthermore, modern roads must be planned according to sustainable development goals, which is complex because some of these might be in conflict. Under this premise, this paper develops a multi-criteria decision support model based on the analytic hierarchy process and the technique for order of preference by similarity to ideal solution to facilitate the selection of wearing courses in European countries. Variables were modelled using either fuzzy logic or Monte Carlo methods, depending on their nature. The views of a panel of experts on the problem were collected and processed using the generalized reduced gradient algorithm and a distance-based aggregation approach. The results showed a clear preponderance by stone mastic asphalt over the remaining alternatives in different scenarios evaluated through sensitivity analysis. The research leading to these results was framed in the European FP7 Project DURABROADS (No. 605404).The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under Grant Agreement No. 605404

FixMiner: Mining Relevant Fix Patterns for Automated Program Repair

Patching is a common activity in software development. It is generally performed on a source code base to address bugs or add new functionalities. In this context, given the recurrence of bugs across projects, the associated similar patches can be leveraged to extract generic fix actions. While the literature includes various approaches leveraging similarity among patches to guide program repair, these approaches often do not yield fix patterns that are tractable and reusable as actionable input to APR systems. In this paper, we propose a systematic and automated approach to mining relevant and actionable fix patterns based on an iterative clustering strategy applied to atomic changes within patches. The goal of FixMiner is thus to infer separate and reusable fix patterns that can be leveraged in other patch generation systems. Our technique, FixMiner, leverages Rich Edit Script which is a specialized tree structure of the edit scripts that captures the AST-level context of the code changes. FixMiner uses different tree representations of Rich Edit Scripts for each round of clustering to identify similar changes. These are abstract syntax trees, edit actions trees, and code context trees. We have evaluated FixMiner on thousands of software patches collected from open source projects. Preliminary results show that we are able to mine accurate patterns, efficiently exploiting change information in Rich Edit Scripts. We further integrated the mined patterns to an automated program repair prototype, PARFixMiner, with which we are able to correctly fix 26 bugs of the Defects4J benchmark. Beyond this quantitative performance, we show that the mined fix patterns are sufficiently relevant to produce patches with a high probability of correctness: 81% of PARFixMiner's generated plausible patches are correct.Comment: 31 pages, 11 figure

MBNQA criteria in education: Assigning weights from a Malaysian perspective and proposition of an alternative evaluation scheme

In order to improve quality and productivity among American companies, Malcolm Baldrige National Quality Award (MBNQA) was launched by the National Institute of Standards and Technology (NIST) under the Department of Commerce of US government in 1987. Over the years, the award has been proved to be effective in improving companies’ market share, customer satisfaction, employee morals and also profitability. MBNQA has been a ‘role model’ in developing national quality award for many other countries in the world. Furthermore, for organizational self-assessment, the criteria framework of MBNQA has been in use throughout the world. Presently, the award is offered in three categories: Business, Education, and Health-care. The present paper is concerned with MBNQA in Education. NIST has developed a comprehensive set of criteria to be fulfilled in order to be eligible to win the award. However, in the existing literature, it is not clear how the weights are assigned to the criteria and subcriteria. The present paper uses analytic hierarchy process (AHP) to reassign criteria weights from a Malaysian perspective. Furthermore, the paper points out the fallacy of the present evaluation scheme and proposes an alternative one based upon the absolute measurement procedure of AHP. The modified scheme is expected to enhance the fairness in evaluation of the award aspirants. The paper also shares the experiences gathered in data collection using AHP.Malcolm Baldrige national quality award, total quality management, analytic hierarchy process, evaluation

Is it time to withdraw from china?

This research cross-employs the Social Cognitive Theory (SCT) and three major labor theories comprised of Maslow’s theory, Alderfer’s theory and Herzberg’s theory with Multiple Criteria Decision Making (MCDM) consisting of Factor Analysis (FA), Analytical Network Process (“ANP”), Fuzzy Analytical Network Process (FANP) and Grey Relation Analysis (GRA) to evaluate the four types of innovative investment strategies in China after the Domino Effect of the China’s Labor Revolution. The most contributed conclusion is that the “change of original business at the raising compensation policy” (CBRCP) is the best choice for Taiwanese manufacturers operating in China because it is the highest scores of three assessed measurements in the CBRCP. This conclusion further indicates that manufacturing enterprises have little leverage, in the interim, but to increase employment compensation and benefits to satisfy the demands from the ongoing Chinese labor revolution even though it brings about an incremental expenditure in their manufacturing costs. Therefore, the next step beyond this research is to collect additional empirical macroeconomic data to develop a more comprehensive evaluation model that takes into consideration a more in-depth vertical measurement and horizontal assessment methodologies for developing added comprehensive and effective managerial strategies for surviving in this momentous, dynamically-changing and lower-profit Chinese manufacturing market.China labor revolution; Maslow theory; Alderfer theory and Herzberg theory; Multiple criteria decision making

Are Students Competent? Methods of Assessing Bachelor of Social Work Student Competence

Higher educational institutions must demonstrate that their Bachelor of Social Work (BSW) students are competent prior to graduation. There are conflicting studies regarding the reliability of field instructor, faculty, and students’ self-assessment. The purpose of this study was to examine the consistency of how field instructors, faculty, and students assessed the same students’ social work competence across three academic years. This quantitative research study examined historical data from one Midwestern University where students, faculty, and field instructors rated students’ competence in the last semester of their senior year using the Council on Social Work Education’s (CSWE) 13 core competencies (2.1.1-2.1.10d). Data analysis included descriptive statistics, 39 Kruskal-Wallis H tests, 13 Friedman’s test, Bonferroni correction, and a False Discovery Rate, due to the large number of statistical tests conducted using the same data set. The field instructor and faculty sample were similar (n = 83); however, the sample for student self-assessment was n = 45. Findings indicated that faculty assessment of students’ social work 13 core competencies was the most inconsistent across three academic years, whereas field instructors’ assessment was the most consistent. When comparing how faculty, field instructors, and students assessed the same students, finding indicated that faculty and field instructors were more closely aligned than students and field instructors and students rated their own social work competence higher than faculty on two core competencies and higher than field instructors on four core competencies