The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
More and more modern applications make use of natural language data, e. g. Information Extraction (IE) or Question Answering (QA) systems. Those application require preprocessing through Natural Language Processing (NLP) pipelines, and the output quality of these applications depends on the output quality of NLP pipelines. If NLP pipelines are applied in different domains, the output quality decreases...
Detecting events on time series data generated by sensors has received a great amount of attention with increasingly deployment of variable sensors. In this paper, we propose a novel framework for classifying events upon sensors data called BEC. Given long raw time series and event labels on fuzzy time points, BEC extracts burst-based features to represent the events. There are mainly two important...
This visual paper aims at proposing a framework for detecting depression in cancer patients using prosodic and statistical features extracted by speech, while chatting with a virtual coach.
In the process of training the professional competences of the students who will become teachers, the pedagogical practice coordinator in the university (tutor) has a key role in the years of initial training for these students' didactic career. The pedagogical practice coordinator in the university has to have counselling psycho-pedagogical competences for the future teachers in order to sustain...
Control and monitoring of asthma progress is highly important for patient's quality of life and healthcare management. Emerging tools for self-management of various chronic diseases have the potential to support personalized patient guidance. This work presents the design aspects of the myAirCoach decision support system, with focus on the assessment of three machine learning approaches as support...
Robotic-assisted technology has given the researchers new opportunities to augment traditional physical rehabilitation with technologically advanced devices. The goal is to leverage robotic technology to improve the efficacy of physical therapy and expedite the recovery period of patients. Robotic systems can take on an important role in physical therapy - assisting, guiding, and motivating patients...
In recent times food safety has drawn upsurge of academic and commercial concerns. In supply chain area, with the rapid growth of internet technologies, a lot of emerging technologies have been applied in traceability systems. However, to date, nearly all of these systems are centralized which are monopolistic, asymmetric and opaque that could result in the trust problem, such as fraud, corruption,...
This work presents initial findings of a research project aimed at designing an assistance system able to improve driver ability and reduce accident risk. The proposed system is an innovative Advanced Driver Assistance System based on the integration of two main components: a training procedure based on precision teaching, and a control equipment monitoring driver behavior and providing feedbacks...
Nowadays, systems providing user-oriented services often demonstrate periodic patterns due to the repetitive behaviors from people's daily routines. The monitoring data of such systems are time series of observations that record observed system status at sampled times during each day. The periodic feature and multidimensional character of such monitoring data can be well utilized by anomaly detection...
We propose a Least Squares Estimation procedure for estimating the admittance matrix of multi-bus DC MicroGrids (MGs). In the proposed solution, the generators simultaneously inject training signals in the form of small deterministic perturbations of the primary droop control parameters and measure the related steady state deviations of the bus voltage. When the training signals meet sufficient excitation...
Fault diagnosis constitutes a problem in electric power systems with relevant economic impact for operators and stakeholders. Artificial neural networks have been proposed in the literature to deal with this problem in a significant number of applications. However, most proposals are based in ad-hoc structure specification and model regularization, which compromises the direct application of the algorithms...
Identifying anomalous events in the network is one of the vital functions in enterprises, ISPs, and datacenters to protect the internal resources. With its importance, there has been a substantial body of work for network anomaly detection using supervised and unsupervised machine learning techniques with their own strengths and weaknesses. In this work, we take advantage of the both worlds of unsupervised...
The aim of active and assisted living (AAL) is to develop tools to assist the elderly people in the ageing status. Human posture recognition algorithms can help monitor aged people in home environments. Different types of sensors can be used for such a task. A case in point is the RGBD sensors, which are cost-effective and provide rich information about the environment. This work aims to propose a...
The article is devoted to the development of the decision support system for the classification of allergic pollen types based on fuzzy expert data of their features on the microscope images and the improvement of the identification method of this system. The genetic algorithm of the classifier training has been improved taking into account the spatial-temporal features of the distribution of pollen...
The objective of this paper is to extend the applicability of the GLR method to a wide range of practical systems. Most real systems are nonlinear, multivariate, and are best represented by input-output type of models. Kernel partial least squares (KPLS) models have been widely used to represent such systems. Therefore, in this paper, kernel PLS-based GLR method will be utilized in practice to improve...
Attacks in Wireless Sensor Networks (WSNs) aim in limiting or even eliminating the ability of the network to perform its expected function. WSNs are networks with limited resources and often deployed in uncontrollable environments that an intruder can easily access. WSN attacks target specific network layer's vulnerabilities but normally affect other layers as well. Local sensor activity at multiple...
In order to enhance and/or improve recovery after stroke, rehabilitation needs to start early and be monitored by continuous and recurrent long-term interventions in the clinic and home setting. The elderly is a high risk stroke group with advancing age, resulting in increasing demand of strengthened resource of hospitals and physiotherapist. The residential rehabilitation for stroke patients would...
The accelerating development of information and communication technologies have an eminent influence on contemporary society. As a result, we have an opportunity to increase our effectiveness. However, there is a drawback. Contemporary systems becoming much more interconnected and opened. However, it negatively affects cyber security of Supervisory Control and Data Acquisition (SCADA) systems. Therefore,...
An integral part of modem day health-care is monitoring the physical activities of human beings. In this paper, we deal with automatic recognition of some daily activities based on signals measured using easily-available smart phones. We present a neural-network based methodology to classify these signals. In contrast to typical conventional techniques we use sequential processing of signals and circumvent...
Early isolation of small faults is an important issue in the literature of fault diagnosis. In this paper, for a class of nonlinear lipschitz systems with output measurements, an approach for rapid isolation of small oscillation faults is presented. By utilizing the knowledge obtained through the deterministic learning, a bank of estimators is constructed for the training normal mode and oscillation...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.