Search results for "computer.software_genre"
showing 10 items of 3858 documents
Using ‘Ambient Intelligence’ for Compensating Intellectual Difficulties of People with Severe Learning Difficulties and/or Autistic Spectrum Disorders
2004
This paper describes a set of services and software created so that what is called ‘ambient intelligence’ would compensate for the ‘intellectual difficulties’ that people from this collective have. Existing concepts and standards of ambient intelligence are strongly reinforced through the use of the exact current user’s position as a key factor to calculate how the ‘digital home’ or any ‘digital environment’ behaves at every moment. This will be obtained using both Wi-Fi personal locators (embedded in necklaces or bracelets) and Wi-Fi communication from the PDA. This mix, together with individual capabilities and preferences, makes the development of a wide range of services possible when c…
Sensor Mining for User Behavior Profiling in Intelligent Environments
2011
The proposed system exploits sensor mining methodologies to profile user behaviors patterns in an intelligent workplace. The work is based in the assumption that users’ habit profiles are implicitly described by sensory data, which explicitly show the consequences of users’ actions over the environment state. Sensor data are analyzed in order to infer relationships of interest between environmental variables and the user, detecting in this way behavior profiles. The system is designed for a workplace equipped in the context of Sensor9k, a project carried out at the Department of Computer Science of Palermo University.
The Intelligent e-Therapy system: a new paradigm for telepsychology and cybertherapy
2009
ABSTRACT One of the main drawbacks of computer-assisted psychology tools developed up to now is related to the real time customisation and adaptation of the content to each patient depending on his/her activity. In this paper we propose a new approach for mental e-health treatments named Intelligent e-Therapy (eIT) with capabilities for ambient intelligence and ubiquitous computing. From a technical point of view, an eIT system is based on four fundamental axes: ambient intelligence for capturing physiological, psychological and contextual information of the patient; persuasive computing for changing/reinforcing behaviours; ubiquitous computing for using the system at any place, and at any …
Exploring the validity of the long term data record V4 database for land surface monitoring
2015
The last (and final) version of the Long Term Data Record (LTDR) — Version 4 — has been released recently by NASA. This database includes daily information for all AVHRR (Advanced Very High Resolution Radiometer) channels, as well as ancillary data, since July 1981 up to present. This database is the longest available record of remotely sensed data useful for land surface monitoring, since it allows the estimation of vegetation indices at daily resolution, as well as the daily estimation of land surface temperature (LST). Here, we analyze the fitness of this database for land surface monitoring. To that end, we first estimated NDVI (Normalized Difference Vegetation Index), LST, as well as e…
Machine Learning-Based Classification of Vector Vortex Beams.
2020
Structured light is attracting significant attention for its diverse applications in both classical and quantum optics. The so-called vector vortex beams display peculiar properties in both contexts due to the non-trivial correlations between optical polarization and orbital angular momentum. Here we demonstrate a new, flexible experimental approach to the classification of vortex vector beams. We first describe a platform for generating arbitrary complex vector vortex beams inspired to photonic quantum walks. We then exploit recent machine learning methods -- namely convolutional neural networks and principal component analysis -- to recognize and classify specific polarization patterns. O…
Mitigating DDoS using weight‐based geographical clustering
2020
Distributed denial of service (DDoS) attacks have for the last two decades been among the greatest threats facing the internet infrastructure. Mitigating DDoS attacks is a particularly challenging task as an attacker tries to conceal a huge amount of traffic inside a legitimate traffic flow. This article proposes to use data mining approaches to find unique hidden data structures which are able to characterize the normal traffic flow. This will serve as a mean for filtering illegitimate traffic under DDoS attacks. In this endeavor, we devise three algorithms built on previously uncharted areas within mitigation techniques where clustering techniques are used to create geographical clusters …
Comparative study to predict toxic modes of action of phenols from molecular structures.
2013
Quantitative structure-activity relationship models for the prediction of mode of toxic action (MOA) of 221 phenols to the ciliated protozoan Tetrahymena pyriformis using atom-based quadratic indices are reported. The phenols represent a variety of MOAs including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles and soft electrophiles. Linear discriminant analysis (LDA), and four machine learning techniques (ML), namely k-nearest neighbours (k-NN), support vector machine (SVM), classification trees (CTs) and artificial neural networks (ANNs), have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. M…
Identifying technical, physiological, tactical and psychological characteristics that contribute to career progression in soccer
2016
This study sought to examine which technical, physiological, tactical and psychological characteristics at age 15 years contribute to successful soccer performance at age 19 years. Participants were male soccer players ( n = 114; mean age 15.4 ± 0.3 years), divided into elite and sub-elite groups based on their performance level at age 19 years. Technical, physiological, tactical and psychological characteristics were recorded when players were 15-year olds. Binary logistic regression analysis showed that performance level at age 19 was clearly associated with technical skills of passing and centering as well as agility and motivation levels recorded at age 15 years. These results extend o…
Sequential Mining Classification
2017
Sequential pattern mining is a data mining technique that aims to extract and analyze frequent subsequences from sequences of events or items with time constraint. Sequence data mining was introduced in 1995 with the well-known Apriori algorithm. The algorithm studied the transactions through time, in order to extract frequent patterns from the sequences of products related to a customer. Later, this technique became useful in many applications: DNA researches, medical diagnosis and prevention, telecommunications, etc. GSP, SPAM, SPADE, PrefixSPan and other advanced algorithms followed. View the evolution of data mining techniques based on sequential data, this paper discusses the multiple …
Medical Data Mining for Heart Diseases and the Future of Sequential Mining in Medical Field
2018
Data Mining in general is the act of extracting interesting patterns and discovering non-trivial knowledge from a large amount of data. Medical data mining can be used to understand the events happened in the past, i.e. studying a patients vital signs to understand his complications and discover why he has died, or to predict the future by analyzing the events that had happened. In this chapter we are presenting an overview on studies that use data mining to predict heart failure and heart diseases classes. We will also focus on one of the trendiest data-mining field, namely the Sequential Mining, which is a very promising paradigm. Due to its important results in many fields, this chapter …