Search results for "Bayesian [statistical analysis]"
showing 10 items of 299 documents
A Context-Aware System for Ambient Assisted Living
2017
In the near future, the world's population will be characterized by an increasing average age, and consequently, the number of people requiring for a special household assistance will dramatically rise. In this scenario, smart homes will significantly help users to increase their quality of life, while maintaining a great level of autonomy. This paper presents a system for Ambient Assisted Living (AAL) capable of understanding context and user's behavior by exploiting data gathered by a pervasive sensor network. The knowledge inferred by adopting a Bayesian knowledge extraction approach is exploited to disambiguate the collected observations, making the AAL system able to detect and predict…
An Ambient Intelligence System for Assisted Living
2017
Nowadays, the population's average age is constantly increasing, and thus the need for specialized home assistance is on the rise. Smart homes especially tailored to meet elderly and disabled people's needs can help them maintaining their autonomy, whilst ensuring their safety and well-being. This paper proposes a complete context-aware system for Ambient Assisted Living (AAL), which infers user's actions and context, analyzing its past and current behavior to detect anomalies and prevent possible emergencies. The proposed system exploits Dynamic Bayesian Networks to merge raw data coming from heterogeneous sensors and infer user's behavior and health conditions. A rule-based reasoner is ab…
On using novel “Anti-Bayesian” techniques for the classification of dynamical data streams
2017
The classification of dynamical data streams is among the most complex problems encountered in classification. This is, firstly, because the distribution of the data streams is non-stationary, and it changes without any prior “warning”. Secondly, the manner in which it changes is also unknown. Thirdly, and more interestingly, the model operates with the assumption that the correct classes of previously-classified patterns become available at a juncture after their appearance. This paper pioneers the use of unreported novel schemes that can classify such dynamical data streams by invoking the recently-introduced “Anti-Bayesian” (AB) techniques. Contrary to the Bayesian paradigm, that compare…
Inference and prediction in bulk arrival queues and queues with service in stages
1998
This paper deals with the statistical analysis from a Bayesian point of view, of bulk arrival queues where the batch size is considered as a fixed constant. The focus is on prediction of the usual measures of performance of the system in the steady state. The probability generating function of the posterior predictive distribution of the number of customers in the system and the Laplace transform of the posterior predictive distribution of the waiting time in the system are obtained. Numerical inversion of these transforms is considered. Inference and prediction of its equivalent single queue with service in stages is also discussed.
The Ghost of the Hawk: Top Predator Shaping Bird Communities in Space and Time
2021
Despite the wide recognition that strongly interacting species can influence distributions of other species, species interactions are often disregarded when assessing or projecting biodiversity distributions. In particular, it remains largely uncharted the extent to which the disappearance of a keystone species cast repercussions in the species composition of future communities. We tested whether an avian top predator can exert both positive and negative effects on spatial distribution of other species, and if these effects persist even after the predator disappeared. We acquired bird count data at different distances from occupied and non-occupied nests of Northern goshawks Accipiter genti…
Seeking the Holy Grail: robust chronologies from archaeology and radiocarbon dating combined
2018
The strengths of formal Bayesian chronological modelling are restated, combining as it does knowledge of the archaeology with the radiocarbon dating of carefully chosen samples of known taphonomy in association with diagnostic material culture. The risks of dating bone samples are reviewed, along with a brief history of the development of approaches to the radiocarbon dating of bone. In reply to Strien (2017), selected topics concerned with the emergence and aftermath of the LBK are discussed, as well as the early Vinča, Ražište and Hinkelstein sequences. The need for rigour in an approach which combines archaeology and radiocarbon dating is underlined.
A Bayesian approach to assess data from radionuclide activity analyses in environmental samples
2007
A Bayesian statistical approach is introduced to assess experimental data from the analyses of radionuclide activity concentration in environmental samples (low activities). A theoretical model has been developed that allows the use of known prior information about the value of the measurand (activity), together with the experimental value determined through the measurement. The model has been applied to data of the Inter-laboratory Proficiency Test organised periodically among Spanish environmental radioactivity laboratories that are producing the radiochemical results for the Spanish radioactive monitoring network. A global improvement of laboratories performance is produced when this pri…
Bayesian Modelling of Confusability of Phoneme-Grapheme Connections
2007
Deficiencies in the ability to map letters to sounds are currently considered to be the most likely early signs of dyslexia. This has motivated the use of Literate, a computer game for training this skill, in several Finnish schools and households as a tool in the early prevention of reading disability. In this paper, we present a Bayesian model that uses a student's performance in a game like Literate to infer which phoneme-grapheme connections student currently confuses with each other. This information can be used to adapt the game to a particular student's skills as well as to provide information about the student's learning progress to their parents and teachers. We apply our model to …
The Algorithm of a Game-Based System in the Relation between an Operator and a Technical Object in Management of E-Commerce Logistics Processes with …
2021
Machine learning (ML) is applied in various logistic processes utilizing innovative techniques (e.g., the use of drones for automated delivery in e-commerce). Early challenges showed the insufficient drones’ steering capacity and cognitive gap related to the lack of theoretical foundation for controlling algorithms. The aim of this paper is to present a game-based algorithm of controlling behaviours in the relation between an operator (OP) and a technical object (TO), based on the assumption that the game is logistics-oriented and the algorithm is to support ML applied in e-commerce optimization management. Algebraic methods, including matrices, Lagrange functions, systems of differential e…
Assessment of building energy modelling studies to meet the requirements of the new Energy Performance of Buildings Directive
2020
Abstract The cost optimal method (COM) as applied in the Energy Performance of Buildings Directive (EPBD) uses “non-calibrated deterministic reference buildings (RBs)”. Such RBs are defined with single envelope and equipment parameter values, for which calibration with actual building stock energy performance (EP) is not undertaken. Thus, it is not possible to visualise the effect of uncertainties or diversity in the input parameters on cost-optimal level benchmarks and to verify the choice of RBs. The paper proposes an update to the COM via use of “Probabilistic Bayesian calibrated RBs” to handle uncertainties and produce more realistic cost optimal levels to support policy makers in devis…