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Business process variability is an active research area in the field of business process management and deals with variations and commonalities among processes of a given process family. Many theoretical approaches have been suggested in the last years; however, practical implementations are rare and limited in their functionality. In this paper, we propose a new approach for business process variability...
Agent-based Modeling (ABM) has become quite popular to the simulation community for its usability and wide area of applicability. However, speed is not usually a trait that ABM tools are characterized of attaining. This paper presents HLogo, a parallel variant of the NetLogo ABM framework, that seeks to increase the performance of ABM by utilizing Software Transactional Memory and multi-core CPUs,...
The platform we're proposing will be the main actor of the upcoming paradigm shift from representative governance to self governance, the architecture, functionality and interface of the platform was modelled after the human anatomy. Human decision making efficiency is dependent upon the governance system of the deciding agents and the roles they play. Aligning the context in which a decision impacting...
Word embedding in the NLP area has attracted increasing attention in recent years. The continuous bag-of-words model (CBOW) and the continuous Skip-gram model (Skip-gram) have been developed to learn distributed representations of words from a large amount of unlabeled text data. In this paper, we explore the idea of integrating extra knowledge to the CBOW and Skip-gram models and applying the new...
A key open question in the area of software modeling is which costs and benefits it brings to software development and maintenance. For answering this question, better empirical studies into software modeling are needed. In this paper I focus on what I believe are the pitfalls in- and prospects for such types of studies. This paper is an abstract for an invited keynote at the Modeling in Software...
This article studies the relation between the minimality properties of two different types of models encountered in the context of linear time-invariant (LTI) sampled-data systems with aperiodic sampling. More precisely, we consider the problem of determining the relationship between the minimality of a continuous-time LTI state-space (SS) representation and the minimality of the discrete-time linear...
Software testing plays a major role for engineering future systems that become more and more ubiquitous and also more critical for every days life. In order to fulfill the high demand, test automation is needed as a keystone. However, test automation, as it is used today, is counting on scripting and capture-and-replay and is not able to keep up with autonomous and intelligent systems. Therefore,...
The evolution of the economy, competition, development of new technologies and globalization explain the blooming of inter-organizations cooperation. The interorganizations cooperation represents a new opportunity to answer to complex challenges that a single organization can't face alone. Cloud Computing is an emerging computation paradigm in information technology and networking. Most recently business...
Recent advances in sensor technologies and instrumentation have led to an extraordinary growth of data sources and streaming applications. A wide variety of devices, from smart phones to dedicated sensors, have the capability of collecting and streaming data at unprecedented rates. Typical applications include smart cities & built environments for instance, where sensor-based infrastructures continue...
Social context is important to a variety of significant applications such as business intelligence, public security and epidemic. For example, companies can refine the advertisement strategy by targeting the influential people within the social group. Social context modelling and recognition is an emerging research area which aims to infer the information that characterizes multiple users such as...
This paper is about extended application of virtual engineering principles, methodologies, and systems as a possible answer to urgent need for integrated industrial, research, and higher educational programs and processes. One of the motivations is the changed world of engineering which requires quick utilization of new findings as new context. At the same time, development of virtual engineering...
In this work we apply a fully differentiable Recurrent Model of Visual Attention to unconstrained real-world images. We propose a deep recurrent attention model and show that it can successfully learn to jointly localize and classify objects. We evaluate our model on multiple digit images generated from MNIST data, Google Street View images, and a fine-grained recognition dataset of 200 bird species,...
Provenance data is a type of metadata that computer scientists argue can support trustworthy and reliable replication of scientific results. From its origins in scientific workflow systems and database theory, and with concurrent interest from the ecological informatics community, a standard data model (PROV) and extensions for DataONE (ProvONE) have led to initial implementations in several tools...
A case study on climate models intercomparison data analysis addressing several classes of multi-model experiments is being implemented in the context of the EU H2020 INDIGO-DataCloud project. Such experiments require the availability of large amount of data (multi-terabyte order) related to the output of several climate models simulations as well as the exploitation of scientific data management...
Simulation experiments are not conducted in a vacuum. They are performed to address specific research questions that require evaluation of testable hypotheses. However, the connections among goals, hypotheses, and experiments are often characterized in an ad hoc manner. In this paper, we examine symbiotic dependencies among goals, hypotheses, and experiments within the context of computational discovery...
Processes in hospitals or in other healthcare institutions are usually analyzed and optimized isolated for enclosed organizations like single hospital wards or certain clinical pathways. However, many workflows should be considered in a broader scope in order to better represent the reality, i.e., in combination with other processes and in contexts of macro structures. Therefore, an integrated view...
A variety of topics at the undergraduate level of science and engineering require learners to apply Hypothetico-Deductive Reasoning (HDR). HDR involves forming hypotheses, designing experiments to test the hypotheses, predicting the outcomes of the experiments, conducting the experiments to observe the outcomes and comparing the predicted and observed outcomes. HDR skill is important for core practices...
Are hybrid simulation models always beneficial? When should one modeling paradigm be used more than another? How does one know the right balance has been reached between different simulation techniques for the system under investigation? We illustrate selected insights into hybrid simulation through the use of a discrete event simulation (DES) model and a hybrid DES agent based model (ABM) of the...
The aim of this paper is to analyze available maturity models in the context of assessment of the maturity of IT systems that support communication processes in HCM. The paper presents theoretical issues connected with the evolution of information systems in context of support Human Capital Management (HCM) in a modern organization. Selected problems connected with assessment of maturity were presented,...
Driving in developing cities presents numerous challenges. Traffic congestion and traffic accidents are the most visible challenges which are caused by different underlying factors. Two chief factors are poorly planned and maintained roadway infrastructure and the decisions made by the drivers. Drivers are constantly forced to negotiate road hazards, like potholes, unlabeled speed bumps as well as...
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