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Due to the number of cloud providers, as well as the extensive collection of services, cloud computing provides very flexible environments, where resources and services can be provisioned and released on demand. However, reconfiguration and adaptation mechanisms in cloud environments are very heterogeneous and often exhibit complex constraints. For example, when reconfiguring a cloud system, a set...
This paper puts forward a knowledge push method which is based on multidimensional hierarchical context model for general business process, and constructs a multi-dimensional hierarchical model of business process and a context driven knowledge resource database model, which emphasizes the mapping relation between knowledge and the knowledge context. On this basis, a framework of the knowledge push...
Convolutional Neural Networks (CNNs) have recently demonstrated a superior performance in computer vision applications; including image retrieval. This paper introduces a bilinear CNN-based model for the first time in the context of Content-Based Image Retrieval (CBIR). The proposed architecture consists of two feature extractors using a pre-trained deep CNN model fine-tuned for image retrieval task...
Most literature in conceptual modelling focuses on the development of models. However, models, once created, must be used, which requires that the model is as usable as possible. Often, usage scenarios for a model are only vaguely clear at model creation time, so model usability should be considered as a relevant problem, especially in relation to conformance (creating instance models that conform...
Structuring content has a positive effect on students' metacognitive skills. Our work in designing content is to approach the use of gaze tracking techniques in adaptive learning strategy that implicates structuring a learning content that will insure the adaptability in real time, taking into account the profile of each learner in the learning process. We present in this paper a learning content...
Mining frequent patterns is a crucial task in data mining. Most of the existing frequent pattern mining methods find the complete set of frequent patterns from a given dataset. However, in real-life scenarios we often need to predict the future frequent patterns for different tasks such as business policy making, web page recommendation, stock-market behavior and road traffic analysis. Predicting...
Thanks to a remarkably great ability to show amusement and engagement, laughter is one of the most important social markers in human interactions. Laughing together can actually help to set up a positive atmosphere and favors the creation of new relationships. This paper presents a data collection of social interaction dialogs involving humor between a human participant and a robot. In this work,...
Self-adaptive systems overcome many of the limitations of human supervision in complex software-intensive systems by endowing them with the ability to automatically adapt their structure and behavior in the presence of runtime changes. However, adaptation in some classes of systems (e.g., Safety-critical) can benefit by receiving information from humans (e.g., Acting as sophisticated sensors, decision-makers),...
A Dynamic Software Product Line (DSPL) is a widely used approach to handle variability at runtime, e.g., By activating or deactivating features to adapt the running configuration. With the emergence of highly configurable and evolvable systems, DSPLs have to cope with the evolution of their structural variability, i.e., The Feature Model (FM) used to derive the configuration. So far, little is known...
This paper describes a theoretical approach to implement human error identification services for antifragile systems. The services provide data analysis and maintain a human error database that is fed and used by multiple software systems. Thus, systems take advantage of the shared human error database by integrating its knowledge into their own antifragile strategy to self-adjust data policies and...
This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players' profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions...
Variability represents an important challenge in multi-tenant SaaS applications. In fact, even if multi-tenancy realizes SaaS providers dream of having a single maintained software instance serving multiple customers (tenants) for common functionality, variations in tenants needs and their specific requirements at many places of the application bring providers back to the real world. They face an...
Modern applications are increasingly dynamic and heterogeneous and their lifecycle is more and more governed by autonomic managers that are also getting more and more complex. The purpose of this paper is to present a service-oriented framework that facilitates the development and management of dynamically extensible autonomic managers. More precisely, we propose an architecture based on the opportunistic...
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