Search results for "Data-driven"
showing 10 items of 59 documents
Wi-Dia: Data-Driven Wireless Diagnostic Using Context Recognition
2018
The recent densification of Wi-Fi networks is exacerbating the effects of well-known pathologies including hidden nodes and flow starvation. This paper provides an automatic diagnostic tool for detecting the source roots of performance impairments by recognizing the wireless operating context. Our tool for Wi-Fi diagnostic, named Wi-Dia, exploits machine learning methods and uses features related to network topology and channel utilization, without impact on regular network operations and working in real-time. Real-time per-link Wi-Fi diagnosis enables recovering actions for context-specific treatments. Wi-Dia classifier recognizes different classes of interference; it is jointly trained us…
An evaluation of recent local image descriptors for real-world applications of image matching
2019
This paper discusses and compares the best and most recent local descriptors, evaluating them on increasingly complex image matching tasks, encompassing planar and non-planar scenarios under severe viewpoint changes. This evaluation, aimed at assessing descriptor suitability for real-world applications, leverages the concept of approximated overlap error as a means to naturally extend to non-planar scenes the standard metric used for planar scenes. According to the evaluation results, most descriptors exhibit a gradual performance degradation in the transition from planar to non-planar scenes. The best descriptors are those capable of capturing well not only the local image context, but als…
Tests for Differentiation in Gene Expression Using a Data-Driven Order or Weights for Hypotheses
2005
In the analysis of gene expression by microarrays there are usually few subjects, but high-dimensional data. By means of techniques, such as the theory of spherical tests or with suitable permutation tests, it is possible to sort the endpoints or to give weights to them according to specific criteria determined by the data while controlling the multiple type I error rate. The procedures developed so far are based on a sequential analysis of weighted p-values (corresponding to the endpoints), including the most extreme situation of weighting leading to a complete order of p-values. When the data for the endpoints have approximately equal variances, these procedures show good power properties…
Examining the Impact of ICT on Sustainable Development: A Data-Driven Narrative
2021
Considering the challenges of sustainable development and the mixed prescriptions being offered by the use of digital technologies, we present a data-driven narrative of how ICT development impacts the sustainable growth of economies. The analysis is based on historical panel data from 39 economies across the developed and developing economies. The industry-standard CRISP-DM methodology was applied as it is flexible, robust, and offers a practical approach for data analytics. The findings reveal that there are differentiated outcomes in terms of sustainable growth among high-income and low-income economies. This poses legitimate questions as to whether low-income economies will be able to m…
Data-Driven Adaptive Observer for Fault Diagnosis
2012
Published version of an article from the journal: Mathematical Problems in Engineering. Also available from the publisher:http://dx.doi.org/10.1155/2012/832836 This paper presents an approach for data-driven design of fault diagnosis system. The proposed fault diagnosis scheme consists of an adaptive residual generator and a bank of isolation observers, whose parameters are directly identified from the process data without identification of complete process model. To deal with normal variations in the process, the parameters of residual generator are online updated by standard adaptive technique to achieve reliable fault detection performance. After a fault is successfully detected, the iso…
Organizāciju cilvēkresursu analītikas attīstības līmenis Eiropā
2018
Cilvēkresursu analītika, kas operē ar datiem lēmumu pieņemšanas procesos, visā pasaulē kļuva par aktuālu tematu. Bakalaura darba mērķis ir izpētīt Eiropas cilvēkresursu analītikas attīstības līmeni un sniegt ieteikumus organizācijām, cilvēkresursu speciālistiem un akadēmiskām iestādēm, lai veiksmīgi ievest cilvēkresursu analītiku. Pētījuma pamatā ir kvalitatīvi dati, kuri tika iegūti intervējot četrus cilvēkresursu speciālistus. Secināts, ka ir būtiska vajadzība pēc cilvēkresursu analītikas un intervētiem organizāciju pārstāvjiem šī tēma ir pazīstama. Galvenais izaicinājums ir saistīts ar profesionālo prasmju trūkumu, tomēr nākotnei cilvēkresursu analītikas cerības ir pozitīvas.
An atlas- and data-driven approach to initializing reaction-diffusion systems in computer cardiac electrophysiology
2016
The cardiac electrophysiology (EP) problem is governed by a nonlinear anisotropic reaction-diffusion system with a very rapidly varying reaction term associated with the transmembrane cell current. The nonlinearity associated with the cell models requires a stabilization process before any simulation is performed. More importantly, when used in a 3-dimensional (3D) anatomy, it is not sufficient to perform this stabilization on the basis of isolated cells only, since the coupling of the different cells through the tissue greatly modulates the dynamics of the system. Therefore, stabilization of the system must be performed on the entire 3D model. This work develops a novel procedure for the i…
Mixed Driven Refinement Design of Multidimensional Models based on Agglomerative Hierarchical Clustering
2015
20 pages; International audience; Data warehouses (DW) and OLAP systems are business intelligence technologies allowing the on-line analysis of huge volume of data according to users' needs. The success of DW projects essentially depends on the design phase where functional requirements meet data sources (mixed design methodology) (Phipps and Davis, 2002). However, when dealing with complex applications existing design methodologies seem inefficient since decision-makers define functional requirements that cannot be deduced from data sources (data driven approach) and/or they have not sufficient application domain knowledge (user driven approach) (Sautot et al., 2014b). Therefore, in this p…
Sub-symbolic Mapping of Cyc Microtheories in Data-Driven “Conceptual” Spaces
2007
The presented work aims to combine statistical and cognitive-oriented approaches with symbolic ones so that a conceptual similarity relationship layer can be added to a Cyc KB microtheory. Given a specific microtheory, a LSA-inspired conceptual space is inferred from a corpus of texts created using both ad hoc extracted pages from the Wikipedia repository and the built-in comments about the concepts of the specific Cyc microtheory. Each concept is projected in the conceptual space and the desired layer of subsymbolic relationships between concepts is created. This procedure can help a user in finding the concepts that are "sub-symbolically conceptually related" to a new concept that he want…
Barriers to Data-Driven Decision-Making Among Online Retailers
2022
This study investigates the barriers to data-driven decision-making among online retailers. The study seeks to deepen the previous knowledge by considering data-driven decision-making as a process and identifying the critical obstacles within its different (6) stages. Qualitative interview data (N=10) collected from Finnish e-commerce professionals are analyzed. The findings show that barriers to data-driven decision-making occur at all stages during the decision-making process. The barriers are mostly related to the employees’ and the management’s expertise in collecting, organizing, analyzing, summarizing, synthesizing, and prioritizing data. In addition, attitudinal, technical, and strat…