Chemical laboratories 4.0: A two-stage machine learning system for predicting the arrival of samples

This paper presents a two-stage Machine Learning (ML) model to predict the arrival time of In-Process Control (IPC) samples at the quality testing laboratories of a chemical company. The model was developed using three iterations of the CRoss-Industry Standard Process for Data Mining (CRISP-DM) methodology, each focusing on a different regression approach. To reduce the ML analyst effort, an Automated Machine Learning (AutoML) was adopted during the modeling stage of CRISP-DM. The AutoML was set to select the best among six distinct state-of-the-art regression algorithms. Using recent real-world data, the three main regression approaches were compared, showing that the proposed two-stage ML model is competitive and provides interesting predictions to support the laboratory management decisions (e.g., preparation of testing instruments). In particular, the proposed method can accurately predict 70% of the examples under a tolerance of 4 time units.This work has been supported by FCT – Funda ̧c ̃ao para a Ciˆencia e Tecnologiawithin the R&D Units Project Scope: UIDB/00319/2020. The authors also wishto thank the chemical company staff involved with this project for providing thedata and also the valuable domain feedback

Possibilistic interorganizationalworkflow net for the recovery problem concerning communication failures

In this paper, an approach based on interorganizational WorkFlow nets and on possibilistic Petri nets is proposed to deal with communication failures in business processes. Routing patterns and communication protocols existing in business processes are modeled by interorganizational WorkFlow nets. Possibilistic Petri nets with uncertainty on the marking and on the transition firing are considered to express in a more realistic way the uncertainty attached to communication failures. Combining both formalisms, a kind of possibilistic interorganizational WorkFlow net is obtained. An example of communication failure at a process monitoring level that precedes the presentation of a paper at a conference is presented

A decade of Portuguese research in e-government: Evolution, current standing, and ways forward

In this paper, we present an investigation of the Portuguese research on e-government. Bibliometric techniques are used to explore all the documents published by researchers affiliated to Portuguese institutions from 2005 to 2014 and listed in the Scopus® database. Research production, impact, source types, language used, subject areas, topics, scopes, methods, authors, institutions, networks, and international cooperation are analysed and discussed. We conclude that so that Portuguese research on e-government can evolve, more researchers should be involved, international cooperation should be developed, and more attention should be given to the study of the reasons behind the very good results of the country in the provision of e-government services, as measured by the international rankings. By establishing the evolution and current standing of e-government research in Portugal and exploring the ways forward, our conclusions may prove useful to e-government researchers, research managers, and research policy makers. © Copyright 2016 Inderscience Enterprises Ltd

A Comparative Study of Two Egocentric-based User Profiling Algorithms Experiment in Delicious

With the growing amount of social media contents, the user needs more accurate information that reflects his interests. We focus on deriving user’s profile and especially user’s interests, which are key elements to improve adaptive mechanisms in information systems (e.g. recommendation, customization). In this paper, we are interested in studying two approaches of user’s profile derivation from egocentric networks: individual-based approach and community-based approach. As these approaches have been previously applied in a co-author network and have shown their efficiency, we are interested in comparing them in the context of social annotations or tags. The motivation to use tagging information is that tags are proved relevant by many researches to describe user’s interests. The evaluation in Delicious social databases shows that the individual-based approach performs well when the semantic weight of user’s interests is taken more in consideration and the community-based approach perf orms better in the opposite case. We also take into consideration the dynamic of social tagging networks. To study the influence of time in the efficiency of the two user’s profile derivation approaches, we have applied a time-awareness method in our comparative study. The evaluation in Delicious demonstrates the importance of taking into account the dynamic of social tagging networks to improve effectiveness of the tag-based user profiling approaches

Predicting multiple domain queue waiting time via machine learning

This paper describes an implementation of the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology for a demonstrative case of human queue waiting time prediction. We collaborated with a multiple domain (e.g., bank, pharmacies) ticket management service software development company, aiming to study a Machine Learning (ML) approach to estimate queue waiting time. A large multiple domain database was analyzed, which included millions of records related with two time periods (one year, for the modeling experiments; and two year, for a deployment simulation). The data was first preprocessed (including data cleaning and feature engineering tasks) and then modeled by exploring five state-of-the-art ML regression algorithms and four input attribute selections (including newly engineered features). Furthermore, the ML approaches were compared with the estimation method currently adopted by the analyzed company. The computational experiments assumed two main validation procedures, a standard cross-validation and a Rolling Window scheme. Overall, competitive and quality results were obtained by an Automated ML (AutoML) algorithm fed with newly engineered features. Indeed, the proposed AutoML model produces a small error (from 5 to 7 min), while requiring a reasonable computational effort. Finally, an eXplainable Artificial Intelligence (XAI) approach was applied to a trained AutoML model, demonstrating the extraction of useful explanatory knowledge for this domain.This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the R &D Units Project Scope: UIDB/00319/2020 and the project “QOMPASS .: Solução de Gestão de Serviços de Atendimento multi-entidade, multi-serviço e multi-idioma” within the Project Scope NORTE-01-0247-FEDER-038462

The Organisational Impact of Implementing Integrated IS in HE institutions: a case study from a UK University

This paper explores the implementation process of integrated Information Systems (IS) in Higher Education (HE) institutions. This is achieved through the analysis of a HE institution’s strategy during the implementation process of the integrated IS and the impact that the new system had on the working practices of the HE institution. Through the use of interviews, the research indicates that there has been a growth of alternative power bases within the university, new roles and responsibilities for administrative staff and a different working environment for academics

An environment to support negotiation and contracting in collaborative networks

During the last years, manufacturing and service industries faced a global change in the production paradigm. They have to continuously adapt their operating principles in reaction to new business or collaboration opportunities, where a natural reaction is a shift to a new business paradigm with the creation of strategic alliances for product or services development, but also for innovative and emergent business services design. On one hand, the process of creating such alliances can be rather simple if organizations share the same geographical and cultural context. But on the other hand, considering different conditions, there might be a low success rate in the creation of successful consortia. One known reason for such low rate are the delays resulting from negotiations in the establishment of collaboration commitments, represented by contracts or agreements, which are crucial in the creation of such alliances. The collaborative networks discipline covers the study of networks of organizations specially when supported by computer networks. This thesis contributes with research in this field describing the creation process of virtual organizations, and proposing a negotiation support environment to help participants in the negotiation of the consortia creation process and in the co-design of new business services. A negotiation support environment is therefore proposed and described with its main requirements, adopted negotiation protocol, conceptual architecture, models, and software environment. To demonstrate the feasibility of the implementation of the proposed systems, a proof-ofconcept software prototype was implemented and tested using some specific scenarios. This thesis work has been validated adopting a methodology that includes: (i) validation in the research community; (ii) validation in a solar industry network; and (iii) validation by comparison analysis

Analyse du comportement d'annotation du réseau social d'un utilisateur pour la détection des intérêts - Application sur Delicious

International audienceL’utilisateur social est caractérisé par son activité sociale comme le partage d’informations et l’établissement de relations avec d’autres utilisateurs. Avec l’évolution du contenu social, l’utilisateur a besoin d’informations plus précises qui reflètent ses intérêts. Nous nous concentrons sur la détection des intérêts de l’utilisateur qui sont des éléments clés pour améliorer l’adaptation (recommandation, personnalisation, etc.). L’originalité de notre approche est basée sur la proposition d’une nouvelle technique de détection des intérêts qui analyse le réseau des relations d’un utilisateur et aussi la précision de leurs comportements d’annotation dans le but de sélectionner les tags qui reflètent réellement le contenu des ressources. L’approche proposée a été testée et évaluée sur la base de données sociales Delicious. Pour l’évaluation, nous comparons le résultat issu de notre approche utilisant le comportement d’annotation des personnes proches (le réseau égocentrique ou les communautés) avec les informations connues de l’utilisateur (son profil). Une évaluation comparative avec une approche classique (basée sur les tags) de détection des intérêts montre que l’approche proposée fournit de meilleurs résultats

Opinion Mining for Software Development: A Systematic Literature Review

Opinion mining, sometimes referred to as sentiment analysis, has gained increasing attention in software engineering (SE) studies. SE researchers have applied opinion mining techniques in various contexts, such as identifying developers’ emotions expressed in code comments and extracting users’ critics toward mobile apps. Given the large amount of relevant studies available, it can take considerable time for researchers and developers to figure out which approaches they can adopt in their own studies and what perils these approaches entail. We conducted a systematic literature review involving 185 papers. More specifically, we present 1) well-defined categories of opinion mining-related software development activities, 2) available opinion mining approaches, whether they are evaluated when adopted in other studies, and how their performance is compared, 3) available datasets for performance evaluation and tool customization, and 4) concerns or limitations SE researchers might need to take into account when applying/customizing these opinion mining techniques. The results of our study serve as references to choose suitable opinion mining tools for software development activities, and provide critical insights for the further development of opinion mining techniques in the SE domain

Extensibility of Enterprise Modelling Languages

Die Arbeit adressiert insgesamt drei Forschungsschwerpunkte. Der erste Schwerpunkt setzt sich mit zu entwickelnden BPMN-Erweiterungen auseinander und stellt deren methodische Implikationen im Rahmen der bestehenden Sprachstandards dar. Dies umfasst zum einen ganz konkrete Spracherweiterungen wie z. B. BPMN4CP, eine BPMN-Erweiterung zur multi-perspektivischen Modellierung von klinischen Behandlungspfaden. Zum anderen betrifft dieser Teil auch modellierungsmethodische Konsequenzen, um parallel sowohl die zugrunde liegende Sprache (d. h. das BPMN-Metamodell) als auch die Methode zur Erweiterungsentwicklung zu verbessern und somit den festgestellten Unzulänglichkeiten zu begegnen. Der zweite Schwerpunkt adressiert die Untersuchung von sprachunabhängigen Fragen der Erweiterbarkeit, welche sich entweder während der Bearbeitung des ersten Teils ergeben haben oder aus dessen Ergebnissen induktiv geschlossen wurden. Der Forschungsschwerpunkt fokussiert dabei insbesondere eine Konsolidierung bestehender Terminologien, die Beschreibung generisch anwendbarer Erweiterungsmechanismen sowie die nutzerorientierte Analyse eines potentiellen Erweiterungsbedarfs. Dieser Teil bereitet somit die Entwicklung einer generischen Erweiterungsmethode grundlegend vor. Hierzu zählt auch die fundamentale Auseinandersetzung mit Unternehmensmodellierungssprachen generell, da nur eine ganzheitliche, widerspruchsfreie und integrierte Sprachdefinition Erweiterungen überhaupt ermöglichen und gelingen lassen kann. Dies betrifft beispielsweise die Spezifikation der intendierten Semantik einer Sprache