Cyber risk at the edge: Current and future trends on cyber risk analytics and artificial intelligence in the industrial internet of things and industry 4.0 supply chains

Digital technologies have changed the way supply chain operations are structured. In this article, we conduct systematic syntheses of literature on the impact of new technologies on supply chains and the related cyber risks. A taxonomic/cladistic approach is used for the evaluations of progress in the area of supply chain integration in the Industrial Internet of Things and Industry 4.0, with a specific focus on the mitigation of cyber risks. An analytical framework is presented, based on a critical assessment with respect to issues related to new types of cyber risk and the integration of supply chains with new technologies. This paper identifies a dynamic and self-adapting supply chain system supported with Artificial Intelligence and Machine Learning (AI/ML) and real-time intelligence for predictive cyber risk analytics. The system is integrated into a cognition engine that enables predictive cyber risk analytics with real-time intelligence from IoT networks at the edge. This enhances capacities and assist in the creation of a comprehensive understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when AI/ML technologies are migrated to the periphery of IoT networks

Proceedings of SAT Competition 2020 : Solver and Benchmark Descriptions

Non peer reviewe

An ontology-based approach to knowledge representation for Computer-Aided Control System Design

P. 107-125Different approaches have been used in order to represent and build control engineering concepts for the computer. Software applications for these fields are becoming more and more demanding each day, and new representation schemas are continuously being developed. This paper describes a study of the use of knowledge models represented in ontologies for building Computer Aided Control Systems Design (CACSD) tools. The use of this approach allows the construction of formal conceptual structures that can be stated independently of any software application and be used in many different ones. In order to show the advantages of this approach, an ontology and an application have been built for the domain of design of lead/lag controllers with the root locus method, presenting the results and benefits found

ModelVars2SPL : an automated approach to reengineer model variants into software product lines

Orientadora : Profª. Drª. Silvia R. VergilioCoorientador : Prof Dr. Roberto E. Lopez-HerrejonTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa: Curitiba, 11/04/2017Inclui referências : f. 74-82Área de concentração : Ciência da computaçãoResumo: Linhas de Produto de Software (LPSs) são famílias de sistemas de software relacionados que são desenvolvidos para um segmento de mercado ou domínio. Comumente, LPSs surgem de um conjunto de variantes existentes, quando a manutenção e/ou evolução individuais tornam-se complexas. Contudo, as abordagens encontradas na literatura para extração de LPS a partir de variantes existentes não dão suporte a modelos de projeto, são parcialmente automatizadas, ou não refletem restrições de domínio em termos de combinação de características. Para lidar com estas limitações, o objetivo deste trabalho é apresentar uma abordagem automatizada para fazer a reengenharia de variantes de modelos em uma LPS, chamada ModelVars2SPL (Variantes de Modelos para Linha de Produto de Software, do Inglês Model Variants to Software Product Line). A entrada para a abordagem é um conjunto de diagramas de classe Linguagem de Modelagem Unificada (UML) e uma lista de características que estes implementam. Todo o processo de reengenharia é coberto, e a saída inclui (i) um Modelo de Características, que representa a combinação de características das variantes de entrada, e (ii) uma Arquitetura de Linha de Produto, que representa uma arquitetura global com características anotadas. O processo de reengenharia da ModelVars2SPL é composto por quatro passos, sendo dois deles apoiados em técnicas baseadas em busca, e os dois outros baseados em algoritmos determinísticos. Não existe a necessidade de especialistas humanos para obter soluções. Para avaliar a abordagem proposta, foi conduzido um experimento para aferir a qualidade das soluções obtidas. A qualidade dos Modelos de Características e das Arquiteturas de Linha de Produto foi medida considerando-se o quão bem as variantes de entrada foram representadas. Além disso, a qualidade das saídas em cada passo da abordagem foi avaliada levando-se em consideração os objetivos do processo de reengenharia. Para a experimentação utilizaram-se dez estudos de caso representando dois cenários diferentes. Os resultados da avaliação mostram que a abordagem consegue obter soluções com alto grau de corretude em termos de representação das variantes de entrada, e que as saídas dos passos estão de acordo com as fases do processo de reengenharia. Com base em um exemplo de uso de uma solução mostra-se como os artefatos de LPS obtidos facilitam a atividade de manutenção. Palavras-chave: Reúso, Reengenharia, Linha de Produto de Software, Extração de LPS, Engenharia de Software Baseada em Busca.Abstract: Software Product Lines (SPLs) are families of related software systems developed for specific market segments or domains. SPLs commonly emerge from sets of existing variants when their individual maintenance and/or evolution become complex. However, current approaches for SPL extraction from existing variants do not support design models, are partially automated, or do not reflect domain constraints in terms of feature combinations. To tackle these limitations, the goal of this work is to present an automated approach to reengineer model variants into an SPL, called ModelVars2SPL (Model Variants to Software Product Line). The input of the approach is a set of Unified Modeling Language (UML) class diagrams and the list of features they implement. All the reengineering process is covered, and the output includes (i) a Feature Model, which represents the combinations of features of the input variants, and (ii) a Product Line Architecture, which represents a global architecture with feature-related annotations. The reengineering process of ModelVars2SPL is composed of four steps, two of them rely on searchbased techniques and the others are based on deterministic algorithms. There is no need for human experts for obtaining solutions. We conducted an experiment to evaluate the quality of the solutions obtained with the proposed approach. The quality of the FMs and PLAs was measured by considering how well these artifacts represent the input variants. Furthermore, we evaluate the quality of the outputs in each step of the approach taking into account the goals of the reengineering process. For the experimentation we used ten case studies representing two di_erent scenarios. The results of the evaluation show that the approach can obtain solutions with high degree of correctness in terms of representing the input variants, and that the outputs of the steps are in accordance to the phases of the reengineering process. Based on an example of use we show how the obtained FM and PLA make easier the maintenance activity. Keywords: Reuse, Reengineering, Software Product Line, SPL extraction, Search-Based Software Engineering

Development of a Three-Dimensional Bioprinter with Inline Light Activation for Bone Tissue Engineering

Bioprinting offers exciting possibilities for tissue engineering related to tissue and organ failure due to trauma, disease, or aging. This is of substantial societal value as the world populace mean age rises. Current needs for tissue and organ repair far exceed availability. A strategy being explored to counter this imbalance is the single step fabrication of cellular constructs. This paper explores various bioprinting techniques and suggests a custom design for a cost-effective, low-maintenance bioprinting platform for academic research. The platform functionality was validated via two-dimensional image transfer and simple three-dimensional geometries

TreeSketchNet: From Sketch To 3D Tree Parameters Generation

3D modeling of non-linear objects from stylized sketches is a challenge even for experts in Computer Graphics (CG). The extrapolation of objects parameters from a stylized sketch is a very complex and cumbersome task. In the present study, we propose a broker system that mediates between the modeler and the 3D modelling software and can transform a stylized sketch of a tree into a complete 3D model. The input sketches do not need to be accurate or detailed, and only need to represent a rudimentary outline of the tree that the modeler wishes to 3D-model. Our approach is based on a well-defined Deep Neural Network (DNN) architecture, we called TreeSketchNet (TSN), based on convolutions and able to generate Weber and Penn parameters that can be interpreted by the modelling software to generate a 3D model of a tree starting from a simple sketch. The training dataset consists of Synthetically-Generated \revision{(SG)} sketches that are associated with Weber-Penn parameters generated by a dedicated Blender modelling software add-on. The accuracy of the proposed method is demonstrated by testing the TSN with both synthetic and hand-made sketches. Finally, we provide a qualitative analysis of our results, by evaluating the coherence of the predicted parameters with several distinguishing features

Critical engineering pedagogy: curricular peer mentoring as a case study for change in the Canadian neoliberal university

This research explores themes of pedagogy, change, and agency within education systems, by examining the possibility of changing a pedagogical discourse within an undergraduate engineering program through critical pedagogy. Changing that discourse is necessary because engineering, as engineers themselves acknowledge, cannot remain an exclusionary space given its crucial role in shaping our postmodern world. This world is full of tensions: it is defined by a pervasive neoliberalism that values technical knowledge for its commercial utility; however, it also values human rights, social responsibility, and environmental stewardship. If engineering education only focuses on training students to solve technical problems, it risks producing engineering professionals who are unwilling to reflect on, and lack the agency to address, the effects of engineering on individuals, society, and the environment. To address these concerns, this study piloted a peer-based learning program that ran in an undergraduate engineering program at a Canadian university for one semester, returning rich qualitative data on implementing a change process within engineering education. The pilot program was informed by critical pedagogy, and attempted to introduce a specific model of undergraduate peer mentoring, known as curricular peer mentoring, within engineering education to question exclusionary discourses. Therefore, the pilot program primarily acted as a case study into implementing a pedagogical change within engineering education at a program and faculty-level. However, the case study was also used to assess whether introducing curricular peer mentoring within university education generally might produce graduates who are critical thinkers, and able to engage in the academic, professional, and civic discourses within and beyond their chosen fields of study and practice. This is a pressing issue of contemporary university education, for as we enter the ‗Post-Truth Era‖ there is an urgent need to train university graduates to think critically, so they can effectively evaluate social, political, and economic discourses. Finally, as the wider university continues to be impacted by a neoliberal agenda that curtails their agency and shapes their pedagogies, research, and organizational structures, they too must change. The pilot program also provided an exploration of a change process that challenges that neoliberal discourse, while at the same time existing within it

Evolution, testing and configuration of variability intensive systems

Tesis descargada desde ResearchGateOne of the key characteristics of software is its ability to be adapted and configured to different scenarios. Recently, software variability has been studied as a first-class concept in different domains ranging from software product lines to pervasive systems. Variability is the ability of a software product to vary depending on different circumstances. Variability intensive systems are those software products where variability management is a core engineering activity. The varying parts of those systems are commonly modeled by us- ing different variability model flavors, being feature modeling one of the most common ones. Feature models were first introduced by Kang et al. back in 1990 and are a compact representation of a set of configurations in a variability intensive system. The large number of configurations that a feature model can encode makes the manual analysis of feature models an error prone and costly task. Then, computer-aided mechanisms appeared as a solution to extract useful information from feature models. This process of extracting information from feature models is known as ¿Automated Analysis of Feature models¿ that has been one of the main areas of research in the last years where more than thirty analysis operations have been proposed.Premio Extraordinario de Doctorado U