A document management methodology based on similarity contents

The advent of the WWW and distributed information systems have made it possible to share documents between different users and organisations. However, this has created many problems related to the security, accessibility, right and most importantly the consistency of documents. It is important that the people involved in the documents management process have access to the most up-to-date version of documents, retrieve the correct documents and should be able to update the documents repository in such a way that his or her document are known to others. In this paper we propose a method for organising, storing and retrieving documents based on similarity contents. The method uses techniques based on information retrieval, document indexation and term extraction and indexing. This methodology is developed for the E-Cognos project which aims at developing tools for the management and sharing of documents in the construction domain

Development of a BIM-based simulator for workspace management in construction

openNei cantieri edili, quali contesti altamente dinamici, lo spazio richiesto dalle attività muta continuamente evidenziando la necessità di considerarlo come una risorsa limitata. Ad oggi, le aree di lavoro non sono efficacemente gestite né dalle tecniche tradizionali di pianificazione né dagli strumenti 4D più avanzati. I manager del processo costruttivo sono costretti a condurre considerazioni spaziali manualmente sulla base di schizzi 2D. Tale approccio è altamente dispendioso e soggetto ad errori; inoltre, come dimostrano le statistiche, è una delle principali cause di infortuni e riduzione della produttività. Questa tesi di dottorato affronta il problema della gestione delle aree di lavoro, proponendo un approccio che integra la fase di pianificazione con la verifica delle interferenze, condotta da un simulatore spaziale sviluppato in un motore grafico. Tale simulatore, acquisiti il modello BIM ed il cronoprogramma, individua eventuali conflitti spaziali quale risultato di computazioni geometriche e simulazioni fisiche. La criticità dei conflitti viene stimata mediante inferenza Bayesiana al fine di escludere scenari trascurabili. Successivamente, i manager del processo costruttivo, consapevoli dei possibili conflitti spaziali futuri, modificano o confermano il cronoprogramma. Questo approccio può essere applicato per identificare i conflitti spaziali sia durante la fase di pianificazione che quella di esecuzione dei lavori. In questa tesi, il simulatore spaziale proposto è stato validato con riferimento alla fase di pianificazione dei lavori di un edificio reale. I risultati hanno dimostrato la sua capacità di identificare non solo un maggior numero di conflitti, rispetto agli strumenti dello stato dell’arte, ma anche di stimare il relativo livello di criticità evitando sovrastime. In futuro, l’approccio proposto in questa tesi, adattato con minime integrazioni, potrà essere applicato a runtime per aggiornare il cronoprogramma durante l’esecuzione dei lavori.In the AEC industry, construction sites are very dynamic operating environments. Activities workspace demand continuously changes across space demanding and time, stressing the need to consider the space as a limited and renewable resource. This issue has not been fully handled yet, neither by traditional scheduling techniques nor by more advanced 4D tools. For these reasons, construction management teams usually carry out manually spatial considerations based on 2D sketches. This approach, especially in big construction projects, is highly time-demanding and error-prone causing, as demonstrated by statistics, injuries, and productivity slowdown. To cover these gaps, this study proposes a workspace management framework that integrates the work scheduling phase with spatial analysis, carried out by a spatial conflict simulator developed using a serious game engine. The simulator, given the BIM model and the construction work schedule, can detect eventual spatial interferences based on geometric computations and physics simulations. The detected conflicts are then judged applying Bayesian inference to filter non-critical scenarios and avoid overestimation. Afterwards, the construction management team, made aware of likely future spatial issues, can adjust or confirm the work schedule. This approach can provide a valuable contribution in detecting spatial conflicts during both the construction planning phase and works execution. In this study, the proposed spatial conflict simulator has been validated on the planning phase of a real use case, demonstrating its capability to not only detect an increased number of spatial issues, compared to the state-of-the-art tools, but also to esteem related criticality levels and avoid overestimations. In the future, the proposed approach, adapted with minor changes, can be applied at runtime for proactively refining the work schedule during works execution.INGEGNERIA CIVILE, AMBIENTALE, EDILE E ARCHITETTURAopenMessi, Leonard

Tools and Processes for enhanced Product Customization

O fornecimento de um sistema personalizável permite que clientes e parceiros expandam as funcionalidades do produto para abranger as suas necessidades e os seus objetivos específicos. Mas as alterações ou adições de funcionalidades ao sistema-base requerem um profundo conhecimento da sua estrutura e do seu funcionamento, assim como competências técnicas que garantam alterações totalmente funcionais. Com o intuito de minimizar as dificuldades inerentes ao processo de desenvolvimento e teste destas customizações, os fornecedores de software disponibilizam ferramentas e documentação de suporte.O principal foco do presente trabalho consiste na análise de projetos de customização, suas ferramentas e documentação de suporte ao desenvolvimento, para a resolução ou minimização das dificuldades e problemas do processo de customização. Através da definição de uma estratégia de suporte à customização que propõe a extracção de conhecimento como forma de documentação orientada pelos conceitos dos Collective Knowledge Systems. E uma ferramenta que aumenta a simplicidade e a fiabilidade do processo apresentando de uma forma intuitiva ao utilizador a análise do código produzida pelo compilador.O presente trabalho contempla ainda a implementação dessa estratégia de suporte ao processo de customização do Manufacturing Execution System (MES) da Critical Manufacturing (CMF), com vista a validar a sua eficácia.O Critical Manufacturing MES é um sistema de informação personalizável que realiza a gestão das operações em ambientes avançados de fabricação garantindo um elevado desempenho e competitividade. A CMF garante a personalização do sistema para corresponder aos requisitos dos clientes e parceiros, mas a complexidade inerente à oferta de um sistema completo e competitivo implica uma estratégia de apoio à customização que garanta um processo simples, rápido e fiável.Os resultados esperados para o presente trabalho, e consequentes da definição de uma estratégia de apoio à customização de software são: (1) uma ferramenta e documentação de apoio que orientem os clientes e parceiros no seu processo de customização e (2), um aumento da confiança e eficiência dos clientes e parceiros no desenvolvimento das suas personalizações através de um processo mais rápido e fiável. A estratégia de apoio à customização definida procura ser a mais abrangente e genérica possível de forma a facilitar a sua adoção por outras entidades.Providing a customizable system allows customers and partners to expand product functionality to meet their specific needs and goals. But the changes or additions of functionalities to the base system require a deep knowledge of its structure and functionality, as well as technical skills that ensure fully functional modifications. In order to minimize the inherent difficulties of the development and testing process of these customizations, software suppliers provide support tools and documentation.The main focus of the present work is the analysis of customization projects, their support tools and documentation, to solve or minimize the customization process difficulties and problems. Through the definition of a customization support strategy that proposes knowledge extraction as a kind of documentation guided by the Collective Knowledge Systems concepts. And a tool that improves the process simplicity and reliability due to displaying intuitively the compilers code analysis to the user. The present work also covers the implementation of this support strategy to the process of customization of the Manufacturing Execution System (MES) of Critical Manufacturing (CMF), in order to validate its effectiveness.Critical Manufacturing MES is a customizable information system that performs operations management in advanced manufacturing environments while ensuring high performance and competitiveness. CMF provides system customizations to meet customer and partner requirements, but the inherent complexity in offering a complete and competitive system implies a customization support strategy that ensures a simple, fast and reliable process.The expected results for the present work, and following the definition of a software customization support strategy are: (1) a tool and documentation that support and guide customers and partners in their customization process, and (2) an increase in the confidence and efficiency of customers and partners on the development of their customizations through a more rapid and efficient process. The customization support strategy seeks to be as comprehensive and generic as possible to facilitate its adoption by other entities

A road map for applied data sciences supporting sustainability in advanced manufacturing: the information quality dimensions

Abstract Data science is a multidisciplinary blend of data inference, algorithm development, and technology in order to solve analytically complex problems. Sustainability is a critical asset of a manufacturing enterprise. It enables a business to differentiate itself from competitors and to compete efficiently and effectively to the best of its ability. This paper is a review of data analytics, and how it supports advanced manufacturing with an emphasis on sustainability. The objective is to present a context for a roadmap for applied data science addressing such analytic challenges. We start with a general introduction to advanced manufacturing and trends in modern analytics tools and technology. We then list challenges of analytics supporting advanced manufacturing and sustainability aspects. The information quality (InfoQ) framework is proposed as a backbone to evaluate the analytics needed in advanced manufacturing. The eight InfoQ dimensions are: 1) Data Resolution, 2) Data Structure, 3) Data Integration, 4) Temporal Relevance, 5) Chronology of Data and Goal, 6) Generalizability, 7) Operationalization and 8) Communication. These dimensions provide a classification of advanced manufacturing analytics domains. The paper provides a roadmap for the development of applied analytic techniques supporting advanced manufacturing and sustainability. The objective is to motivate researchers, practitioners and industrialists to support such a roadmap

The incidence of nominal and real wage rigidity : An individual-based sectoral approach

This paper presents estimates based on individual data on downward nominal and real wage rigidities for thirteen sectors in Belgium, Denmark, Spain and Portugal. Our methodology follows the approach recently developed for the International Wage Flexibility Project, whereby resistance to nominal and real wage cuts is measured through departures of observed individual wage-change histograms from an estimated counterfactual wage-change distribution that would have prevailed in the absence of any rigidity. We evaluate the role of worker and firm characteristics in shaping wage rigidities. We also confront our estimates of wage rigidities with structural features of the labour markets studied, such as the wage bargaining level, variable pay policy and the degree of product market competition. We find that the use of firm-level collective agreements in countries with rather centralised wage formation reduces the degree of real wage rigidity. This finding suggests that some degree of decentralisation within centralised countries allows firms to adjust wages downwards, when business conditions take a turn for the worsewage rigidity, wage-bargaining institutions

An Approach to Data Analysis in 5G Networks

5G networks expect to provide significant advances in network management compared to traditional mobile infrastructures by leveraging intelligence capabilities such as data analysis, prediction, pattern recognition and artificial intelligence. The key idea behind these actions is to facilitate the decision-making process in order to solve or mitigate common network problems in a dynamic and proactive way. In this context, this paper presents the design of Self-Organized Network Management in Virtualized and Software Defined Networks (SELFNET) Analyzer Module, which main objective is to identify suspicious or unexpected situations based on metrics provided by different network components and sensors. The SELFNET Analyzer Module provides a modular architecture driven by use cases where analytic functions can be easily extended. This paper also proposes the data specification to define the data inputs to be taking into account in diagnosis process. This data specification has been implemented with different use cases within SELFNET Project, proving its effectiveness.Depto. de Ingeniería de Software e Inteligencia Artificial (ISIA)Fac. de InformáticaTRUEUnión Europea. Horizonte 2020pu

Developing a diagnostic heuristic for integrated sugarcane supply and processing systems.

Doctoral Degrees. University of KwaZulu-Natal, Pietermaritzburg.Innovation is a valuable asset that gives supply chains a competitive edge. Moreover, the adoption of innovative research recommendations in agricultural value chains and integrated sugarcane supply and processing systems (ISSPS) in particular has been relatively slow when compared with other industries such as electronics and automotive. The slow adoption is attributed to the complex, multidimensional nature of ISSPS and the perceived lack of a holistic approach when dealing with certain issues. Most of the interventions into ISSPS often view the system as characterised by tame problems hence, the widespread application of traditional operations research approaches. Integrated sugarcane supply and processing systems are, nonetheless, also characterised by wicked problems. Interventions into such contexts should therefore, embrace tame and/or wicked issues. Systemic approaches are important and have in the past identified several system-scale opportunities within ISSPS. Such interventions are multidisciplinary and employ a range of methodologies spanning across paradigms. The large number of methodologies available, however, makes choosing the right method or a combination thereof difficult. In this context, a novel overarching diagnostic heuristic for ISSPS was developed in this research. The heuristic will be used todiagnose relatively small, but pertinent ISSPS constraints and opportunities. The heuristic includes a causal model that determines and ranks linkages between the many domains that govern integrated agricultural supply and processing systems (IASPS) viz. biophysical, collaboration, culture, economics, environment, future strategy, information sharing, political forces, and structures. Furthermore, a diagnostic toolkit based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was developed. The toolkit comprises a diagnostic criteria and a suite of systemic tools. The toolkit, in addition, determines thesuitability of each tool to diagnose any of the IASPS domains. Overall, the diagnostic criteria include accessibility, interactiveness, transparency, iterativeness, feedback, cause-and-effect logic, and time delays. The tools considered for the toolkit were current reality trees, fuzzy cognitive maps (FCMs), network analysis approaches, rich pictures (RP), stock and flow diagrams, cause and effect diagrams (CEDs), and causal loop diagrams (CLDs). Results from the causal model indicate that collaboration, structure and information sharing had a high direct leverage over the other domains as these were associated with a larger number of linkages. Collaboration and structure further provided dynamic leverage as these were also part of feedback loops. Political forces and the culture domain in contrast, provided lowleverage as these domains were only directly linked to collaboration. It was further revealed that each tool provides a different facet to complexity hence, the need for methodological pluralism. All the tools except RP could be applied, to a certain extent, across both appreciation and analysis criteria. Rich pictures do not have causal analysis capabilities viz. cause-and-effect logic, time delays and feedback. Stock and flow diagrams and CLDs conversely, met all criteria. All the diagnostic tools in the toolkit could be used across all the system domains except for FCMs. Fuzzy cognitive maps are explicitly subjective and their contribution lies outside the objective world. Caution should therefore be practiced when FCMs areapplied within the biophysical domain. The heuristic is only an aid to decision making. The decision to select a tool or a combination thereof remains with the user(s). Even though the heuristic was demonstrated at Mhlume sugarcane milling area, it is recommended that other areas be considered for future research. The heuristic itself should continuously be updated with criteria, tools and other domain dimensions

Electricity Transmission Pricing and Performance-Based Regulation

Performance-based regulation (PBR) is influenced by the Bayesian and non-Bayesian incentive mechanisms. While Bayesian incentives are impractical, the insights from their properties can be combined with practical non-Bayesian mechanisms for application to transmission pricing. This combination suggests an approach based on the distinction between ultra-short, short and long periods. Ultra-short periods are marked by real-time pricing of point-to-point transmission services. Pricing in short periods involves fixed fees and adjustments via price-cap formulas or profit sharing. Productivity-enhancing incentives have to be tempered by long-term commitment considerations, so that profit sharing may dominate pure price caps. Investment incentives require long-term adjustments based on rate-of-return regulation with a “used and useful” criterion.

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future