French/English abstract: Les systèmes d’aide à la prise de décision jouent un rôle important dans la pratique juridique aux Pays-Bas. Divers organismes gouvernementaux utilisent de tels systèmes automatisés pour la prise de décisions juridiques (de masse). Les départements juridiques, les cabinets d’avocats, les éditeurs juridiques et d’autres organismes ont de plus en plus recours à ces outils pour appuyer et améliorer les services d’aide juridique aux particuliers et aux entreprises. Ces outils permettent d’améliorer l’efficacité des processus et des services juridiques, mais ils peuvent aussi avoir d’importants effets préjudiciables sur les droits des personnes ou sur la qualité juridique des services produits, en particulier lorsqu’il n’existe pas de processus de conception minutieux et transparent. Cet article donne un aperçu de l’utilisation de ces systèmes dans la pratique juridique néerlandaise, discute de leurs avantages, pièges et défis, puis il identifie certaines questions de recherche pour le futur.---Rule-based systems for decision support and decision-making play an important role in Dutch legal practice. Government agencies use rule-based systems for (mass) legal decision-making. Legal departments, law firms, legal publishers and various other organizations increasingly use rule-basedsystems to support and improve the provision of legal aid to private individuals and corporate clients. Rule-based systems can improve efficiency of legal processes and services, but can also have important detrimental effects on the rights of individuals or legal quality, especially when there is no careful and transparent design process. This article provides an overview of the use of these systems in Dutch legal practice, discusses benefits, pitfallsand challenges and identifies questions for future research.
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Author supplied: "Abstract—Software architecture compliance checking (SACC) is an approach to monitor the consistency between the intended and the implemented architecture. In case of static SACC, the focus is mainly on the detection of dependencies that violate architectural relation rules. Interpretation of reported violations may be cumbersome, since the violations need to be connected to architectural resolutions and targeted qualities such as maintainability and portability. This paper describes an SACC case study which shows that inclusion of different types of rules in the SACC process enhances reasoning on architecture violations, especially if a rule type is related to specific architectural pattern. The SACC is performed with HUSACCT, an SACC-tool that provides rich sets of module and rule types in support of patterns such as layers, facade, and gateway. The case system is a governmental system developed in C#, which follows the .NET common application architecture. Even though the system appeared to be well-structured, the SACC revealed that 10 of the 17 architectural rules were violated."
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Agile software development has evolved into an increasingly mature software development approach and has been applied successfully in many software vendors’ development departments. In this position paper, we address the broader agile service development. Based on method engineering principles we define a framework that conceptualizes an operational way of working for the development of services, emphatically taking into account agility. As a first level of agility, the framework contains situational project factors that influence the choice of method fragments; secondly, increased agility is proposed by describing and operationalizing these method fragments not as imperative steps or activities, but instead by means of sets of minimally specified, declarative rules that determine the context and constraints within which goals are to be reached. This approach borrows concepts from rules management, organizational patterns, and game design theory. Keywordsmethod engineering–agile service development–business rules–business rules management–product management–game design
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The Heating Ventilation and Air Conditioning (HVAC) sector is responsible for a large part of the total worldwide energy consumption, a significant part of which is caused by incorrect operation of controls and maintenance. HVAC systems are becoming increasingly complex, especially due to multi-commodity energy sources, and as a result, the chance of failures in systems and controls will increase. Therefore, systems that diagnose energy performance are of paramount importance. However, despite much research on Fault Detection and Diagnosis (FDD) methods for HVAC systems, they are rarely applied. One major reason is that proposed methods are different from the approaches taken by HVAC designers who employ process and instrumentation diagrams (P&IDs). This led to the following main research question: Which FDD architecture is suitable for HVAC systems in general to support the set up and implementation of FDD methods, including energy performance diagnosis? First, an energy performance FDD architecture based on information embedded in P&IDs was elaborated. The new FDD method, called the 4S3F method, combines systems theory with data analysis. In the 4S3F method, the detection and diagnosis phases are separated. The symptoms and faults are classified into 4 types of symptoms (deviations from balance equations, operating states (OS) and energy performance (EP), and additional information) and 3 types of faults (component, control and model faults). Second, the 4S3F method has been tested in four case studies. In the first case study, the symptom detection part was tested using historical Building Management System (BMS) data for a whole year: the combined heat and power plant of the THUAS (The Hague University of Applied Sciences) building in Delft, including an aquifer thermal energy storage (ATES) system, a heat pump, a gas boiler and hot and cold water hydronic systems. This case study showed that balance, EP and OS symptoms can be extracted from the P&ID and the presence of symptoms detected. In the second case study, a proof of principle of the fault diagnosis part of the 4S3F method was successfully performed on the same HVAC system extracting possible component and control faults from the P&ID. A Bayesian Network diagnostic, which mimics the way of diagnosis by HVAC engineers, was applied to identify the probability of all possible faults by interpreting the symptoms. The diagnostic Bayesian network (DBN) was set up in accordance with the P&ID, i.e., with the same structure. Energy savings from fault corrections were estimated to be up to 25% of the primary energy consumption, while the HVAC system was initially considered to have an excellent performance. In the third case study, a demand-driven ventilation system (DCV) was analysed. The analysis showed that the 4S3F method works also to identify faults on an air ventilation system.
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In this paper we present the results of an international comparative research conducted through a special web survey, i.e. an online 'game' to rate and classify Critical Success Factors (CFSs) for BPMS implementations. The survey was completed by 39 respondents from 11 different countries. Central to the research was the question how BPM-systems success factors are perceived by professionals from different countries (i.e. cultural backgrounds) and how this is related to other characteristics such as their level of experience within the BPM domain. The respondents judged a total of 55 factors in two ways: (1) by allocating them to one of the five domains of BPMS implementation, and (2) by ranking their importance for BPMS implementations. Significant differences were found between respondents from Northern European versus Anglo-American countries, and between respondents with different levels of experience with BPMS implementations.
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Author supplied: "Abstract—Software architecture compliance checking (SACC) is an approach to monitor the consistency between the intended and the implemented architecture. In case of static SACC, the focus is mainly on the detection of dependencies that violate architectural relation rules. Interpretation of reported violations may be cumbersome, since the violations need to be connected to architectural resolutions and targeted qualities such as maintainability and portability. This paper describes an SACC case study which shows that inclusion of different types of rules in the SACC process enhances reasoning on architecture violations, especially if a rule type is related to specific architectural pattern. The SACC is performed with HUSACCT, an SACC-tool that provides rich sets of module and rule types in support of patterns such as layers, facade, and gateway. The case system is a governmental system developed in C#, which follows the .NET common application architecture. Even though the system appeared to be well-structured, the SACC revealed that 10 of the 17 architectural rules were violated." http://ieeexplore.ieee.org/document/7484100/ http://dx.doi.org/10.1109/QRASA.2016.7
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This study explores how households interact with smart systems for energy usage, providing insights into the field's trends, themes and evolution through a bibliometric analysis of 547 relevant literature from 2015 to 2025. Our findings discover: (1) Research activity has grown over the past decade, with leading journals recognizing several productive authors. Increased collaboration and interdisciplinary work are expected to expand; (2) Key research hotspots, identified through keyword co-occurrence, with two (exploration and development) stages, highlighting the interplay between technological, economic, environmental, and behavioral factors within the field; (3) Future research should place greater emphasis on understanding how emerging technologies interact with human, with a deeper understanding of users. Beyond the individual perspective, social dimensions also demand investigation. Finally, research should also aim to support policy development. To conclude, this study contributes to a broader perspective of this topic and highlights directions for future research development.
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Current methods for energy diagnosis in heating, ventilation and air conditioning (HVAC) systems are not consistent with process and instrumentation diagrams (P&IDs) as used by engineers to design and operate these systems, leading to very limited application of energy performance diagnosis in practice. In a previous paper, a generic reference architecture – hereafter referred to as the 4S3F (four symptoms and three faults) framework – was developed. Because it is closely related to the way HVAC experts diagnose problems in HVAC installations, 4S3F largely overcomes the problem of limited application. The present article addresses the fault diagnosis process using automated fault identification (AFI) based on symptoms detected with a diagnostic Bayesian network (DBN). It demonstrates that possible faults can be extracted from P&IDs at different levels and that P&IDs form the basis for setting up effective DBNs. The process was applied to real sensor data for a whole year. In a case study for a thermal energy plant, control faults were successfully isolated using balance, energy performance and operational state symptoms. Correction of the isolated faults led to annual primary energy savings of 25%. An analysis showed that the values of set probabilities in the DBN model are not outcome-sensitive. Link to the formal publication via its DOI https://doi.org/10.1016/j.enbuild.2020.110289
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The maturing field of Wireless Sensor Networks (WSN) results in long-lived deployments that produce large amounts of sensor data. Lightweight online on-mote processing may improve the usage of their limited resources, such as energy, by transmitting only unexpected sensor data (anomalies). We detect anomalies by analyzing sensor reading predictions from a linear model. We use Recursive Least Squares (RLS) to estimate the model parameters, because for large datasets the standard Linear Least Squares Estimation (LLSE) is not resource friendly. We evaluate the use of fixed-point RLS with adaptive thresholding, and its application to anomaly detection in embedded systems. We present an extensive experimental campaign on generated and real-world datasets, with floating-point RLS, LLSE, and a rule-based method as benchmarks. The methods are evaluated on prediction accuracy of the models, and on detection of anomalies, which are injected in the generated dataset. The experimental results show that the proposed algorithm is comparable, in terms of prediction accuracy and detection performance, to the other LS methods. However, fixed-point RLS is efficiently implementable in embedded devices. The presented method enables online on-mote anomaly detection with results comparable to offline LS methods. © 2013 IEEE.
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This paper investigates how management accounting and control systems (operationalized by using Simons’ (1995a) levers of control framework) can be used as devices to support public value creation and as such it contributes to the literature on public value accounting. Using a mixed methods case study approach, including documentary analysis and semi-structured interviews, we found diverging uses of control systems in the Dutch university of applied sciences we investigated. While belief and interactive control systems are used intensively for strategy change and implementation, diagnostic controls were used mainly at the decentral level and seen as devices to make sure that operational and financial boundaries were not crossed. Therefore, belief and interactive control systems lay the foundation for the implementation of a new strategy, in which concepts of public value play a large role, using diagnostic controls to constrain actions at the operational level. We also found that whereas the institution wanted to have interaction with the external stakeholders, in daily practice this takes place only at the phase of strategy formulation, but not in the phase of intermediate strategy evaluation.
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