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Currently, Decision support systems in dynamic and complex environment involves the use of visual data mining technology for interactive data analysis and visualization. This paper presents a new architecture for designing such systems. The envisaged architecture based on the Multi-Agent System to improve coordination and communication between the different system modules to generate the appropriate...
Architectural Technical Debt has recently received the attention of the scientific community, as a suitable metaphor for describing sub-optimal architectural solutions having short-term benefits but causing a long-term negative impact. We study such phenomenon in the context of Volvo Car Group, where the development of modern cars includes complex systems with mechanical components, electronics and...
The automated formation of the interactive task for the computer aided training means is studied in the article. This problem is of current importance since there is a necessity to create an instrumental tool that would give an opportunity to realize different types of the testing and training tasks on basis of the interactive technologies in the modern stage of the computer training system development...
Naturally every individual is unique. Thus, learning process in every learner is also different. On the other hand, education requires every learner to achieve a certain standard of competency. Standards are made to ensure all learners meet the defined learning outcome. In order to help learner achieve the targeted competency based on their own pace and way of learning, we propose personalized e-learning...
This work develops the implementation of a software application that allows the management of digital medical records of populations of children and youths who are under criminal processes. This application allows the registration of clinical, mental and family environmental events that occur during the stay of patients in this kind of health care institutions. Based on local current legislation and...
The use of emotional states for Human-Robot Interaction (HRI) has attracted considerable attention in recent years. One of the most challenging tasks is to recognize the spontaneous expression of emotions, especially in an HRI scenario. Every person has a different way to express emotions, and this is aggravated by the complexity of interaction with different subjects, multimodal information and different...
Many techniques have been proposed in the literature to support architecture definition, conformance, and analysis. However, there is a lack of adoption of such techniques by the industry. Previous work have analyzed this poor support. Specifically, former approaches lack proper analysis techniques (e.g., detection of architectural inconsistencies), and they do not provide extension and addition of...
This paper describes a whole new framework to quickly develop dynamic visual servoing systems embedded in an FPGA. Parallel design of the algorithms increases the precision of this kind of controllers, whereas minimizes the response time. Embedding dynamic visual servoing algorithms converts these systems into real-time systems. Additionally, an optimal control framework to dynamically visual control...
Existing high-level, source-to-source compilers can accept input programs in a high-level language (e.g., C) and perform complex automatic parallelization and other mappings using various optimizations. These optimizations often require trade-offs and can benefit from the user's involvement in the process. However, because of the inherent complexity, the barrier to entry for new users of these high-level...
The former 25th Ephorate of Byzantine Antiquities in Greece has long been engaged in the research of medieval fortified architecture and in tailoring of restoration and promotion projects for particular monuments. “Digital Enhancement of Argolid, Arcadia and Corinthia castles” is an ongoing project, currently carried out under the jurisdiction of the newly established Argolid Ephorate of Antiquities...
Cloud monitoring has become a key tool for organizations to ensure that their critical processes are being effectively managed in a private cloud infrastructure. A cloud monitoring tool should include complex tasks such as information extraction, management and planning of alerts in order to keep the service up during failures. However, current available solutions for private clouds only support some...
The problem of development of system for monitoring renewable energy sources (RES) in the Republic of Kazakhstan is discussed. New information and communication technologies (ICT) become the technological basis for large scale monitoring. Wireless sensor networks, inter-machine communication system (Machine-to-Machine — M2M), broadband networks based on new communication protocols, machine learning...
We provide a computational model showing how turn-taking behaviors can self-organize out of sensorimotor interactions between vocalizing agents. Recent hypotheses propose that turn-taking behaviors in certain primate species emerge from a need to maintain vocal contact in a group (e.g. in dense environments preventing visual contact). In this context, vocalizations can convey information about the...
In this paper, we propose a monocular vision system for autonomous obstacle avoidance and simultaneous stabilization of dynamic bipedal walking using the Aldebaran Nao robot. In particular, we address the case where erroneous bipedal locomotion causes the robot to drift away from a planned trajectory over time. To eliminate drifting, we use hybrid control patterns. This results in an efficient, self-correcting...
Event recognition from still images is of great importance for image understanding. However, compared with event recognition in videos, there are much fewer research works on event recognition in images. This paper addresses the issue of event recognition from images and proposes an effective method with deep neural networks. Specifically, we design a new architecture, called Object-Scene Convolutional...
Multilabel image annotation is one of the most important open problems in computer vision field. Unlike existing works that usually use conventional visual features to annotate images, features based on deep learning have shown potential to achieve outstanding performance. In this work, we propose a multimodal deep learning framework, which aims to optimally integrate multiple deep neural networks...
The interacting visual maps (IVM) algorithm introduced in [1] is able to perform the joint approximate inference of several visual quantities such as optic-flow, gray-level intensities and ego-motion, using a sparse input coming from a neuromorphic dynamic vision sensor (DVS). We show that features of the model such as the intrinsic parallelism and distributed nature of its computation make it a natural...
Humans can easily memorize images of places and labels (road names, addresses, etc.) associated with them, as well as trajectories defined by sequences of images and corresponding positions. Later, they are able to remember places' labels and relative positions when seeing the same images again. In this work, we present an image-based mapping, global localization and position tracking system based...
Source code and models of a software system, like architectural views, tend to evolve separately and drift apart over time. Previous research has shown that it is possible to effectively relate them through a reflex ion model, defined as a "summarization of a software system from the viewpoint of a particular high-level model"'. While effective, the process of constructing and analyzing...
Saccades are fast eye movements that allow humans and robots to bring the visual target in the center of the visual field. Saccades are open loop with respect to the vision system, thus their execution require a precise knowledge of the internal model of the oculomotor system. In this work, we modeled the saccade control, taking inspiration from the recurrent loops between the cerebellum and the brainstem...
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