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Aiming to keep under control a particular system or environment or to ensure that it works as expected there is a need to know what-when-why happens there. Various conditions and environmental factors can lead to errors, unexpected behavior or loss of control. To pursue these factors manually is time consuming, error prone, slow and usually quite expensive. Monitoring is quite complex and challenging...
This paper introduces a methodology to design a Context-aware Adaptive System based on a layered software architecture. The model of the context awareness multi-modal traffic management takes into account the context parameters in order to adapt dynamically the decisions (choice of the best transportation route). The efficiency of the proposed technique is validated through a case study including...
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...
Sexual harassment at workplace has been a criticalchallenge for women, especially in the service sector due to oddworking hours. Companies and Government on their part havetaken up measures to protect women employees but theproblem seems persistent. To address this, we have designed aregulatory solution based on operant conditioning. Operantconditioning argues that people's behaviors are primarilycontrolled...
In state-of-the-art Software Transactional Memory (STM) systems, threads carry out the execution of transactions as non-interruptible tasks. Hence, a thread can react to the injection of a higher priority transactional task and take care of its processing only at the end of the currently executed transaction. In this article we pursue a paradigm shift where the execution of an in-memory transaction...
We present an original concept for patch generation: we propose to do it directly in production. Our idea is to generate patches on-the-fly based on automated analysis of the failure context. By doing this in production, the repair process has complete access to the system state at the point of failure. We propose to perform live regression testing of the generated patches directly on the production...
Temporal Pooling (TP) is a recent technique for processing temporal events by forming declarative representations of the complete sequences. In this paper, we examine and extend the functionality of the existing TP algorithm from the Hierarchical Temporal Memory (HTM) framework and introduce the Self-Organising Temporal Pooling (SOTP) architecture. The SOTP draws together the Merge Self-Organising...
Nowadays, developing effective techniques able to deal with data coming from structured domains is becoming crucial. In this context kernel methods are the state-of-the-art tool widely adopted in real-world applications that involve learning on structured data. Contrarily, when one has to deal with unstructured domains, deep learning methods represent a competitive, or even better, choice. In this...
The new challenges in the smart city context are mainly related to the stimulation of the city users towards taking more sustainable behaviors, in mobility and energy. The state of the art in this case is mainly focused on classical smart city solution for informing the city users and or for engaging them with specific wired rules toward virtuous models. And not using flexible languages and predictive...
Episodic memory which can store and recall episodes has been modeled by various research. Those models focus on encoding and retrieving the same sequence of events of episodes. In this paper, we propose context preference-based deep adaptive resonance theory (CPD-ART). CPD-ART uses a new approach in encoding and retrieving a temporal sequence of events considering subjects, preference criteria such...
The development of Fog Computing technology is crucial to address the challenges to come with the mass adoption of Internet Of Things technology, where the generation of data tends to grow at an unprecedented pace. The technology brings computing power to the surrounds of devices, to offer local processing, filtering, storage and analysis of data and control over actuators. Orchestration is a requirement...
The abstraction tasks are challenging for multi-modal sequences as they require a deeper semantic understanding and a novel text generation for the data. Although the recurrent neural networks (RNN) can be used to model the context of the time-sequences, in most cases the long-term dependencies of multi-modal data make the back-propagation through time training of RNN tend to vanish in the time domain...
We describe an integration of the CHiLL compiler with OpenTuner to reduce the programmer burden in using autotuning. We use as a case study optimizing the smooth operator and its associated stencil computations in the context of Geometric Multigrid (GMG), a hierarchical linear solver that operates in multiple grid resolutions (levels). Smooth is the most performance-critical operation that runs multiple...
Software Defined Networking (SDN) and analogous approaches to different domains like storage, compute and security have emerged as promising paradigms for controlling and managing many different types of distributed systems. In this paper, we examine the application of software defined concepts to coalition operations. Specifically, we propose the concept of Software Defined Coalitions (SDC), a mechanism...
Word embeddings are a low-dimensional vector representation of words that incorporates context. TWo popular methods are word2vec and global vectors (GloVe). Word2vec is a single-hidden layer feedforward neural network (SLFN) that has an auto-encoder influence for computing a word context matrix using backpropagation for training. GloVe computes the word context matrix first then performs matrix factorization...
During face-to-face interactions, people naturally integrate nonverbal behaviors such as facial expressions and body postures as part of the conversation to infer the communicative intent or emotional state of their interlocutor. The interpretation of these nonverbal behaviors will often be contextualized by interactional cues such as the previous spoken question, the general discussion topic or the...
We explore a reference monitor (RM) design which borrows from the Flask security architecture. Our RM design goal is to achieve complete mediation by checking and verifying the authority and authenticity of every access to every system object. Access decisions are administered by a security logic server implemented as an extension of the peripheral bus. Initial results show a minimal increase in resource...
Cervical nuclei carry substantial diagnostic information for cervical cancer. Therefore, in automation-assisted reading of cervical cytology, automated and accurate segmentation of nuclei is essential. This paper proposes a novel approach for segmentation of cervical nuclei that combines fully convolutional networks (FCN) and graph-based approach (FCNG). FCN is trained to learn the nucleus high-level...
Software architecting is about making decisions that have system-wide impact and that shape software product and process alike. While researchers and practitioners have tried to define and scope the role of the architect, social and organizational impacts on the architect and the architecting process are often neglected. The SODA workshop focuses on the social and organizational dimensions in which...
MGDIS SA is a software editing company that underwent a major strategic and technical change during the past three years, investing 17 300 man. Days rewriting its core business software from monolithic architecture to a Web Oriented Architecture using microservices. The paper presents technical lessons learned during and from this migration by addressing three crucial questions for a successful context-adapted...
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