Search results for "Data modeling"
showing 10 items of 112 documents
Combining Auto-Encoder with LSTM for WiFi-Based Fingerprint Positioning
2021
Although indoor positioning has long been investigated by various means, its accuracy remains concern. Several recent studies have applied machine learning algorithms to explore wireless fidelity (WiFi)-based positioning. In this paper, we propose a novel deep learning model which concatenates an auto-encoder with a long short term memory (LSTM) network for the purpose of WiFi fingerprint positioning. We first employ an auto-encoder to extract representative latent codes of fingerprints. Such an extraction is proven to be more reliable than simply using a deep neural network to extract representative features since a latent code can be reverted back to its original input. Then, a sequence o…
Downstream Services for Rice Crop Monitoring in Europe: From Regional to Local Scale
2017
The ERMES agromonitoring system for rice cultivations integrates EO data at different resolutions, crop models, and user-provided in situ data in a unified system, which drives two operational downstream services for rice monitoring. The first is aimed at providing information concerning the behavior of the current season at regional/rice district scale, while the second is dedicated to provide farmers with field-scale data useful to support more efficient and environmentally friendly crop practices. In this contribution, we describe the main characteristics of the system, in terms of overall architecture, technological solutions adopted, characteristics of the developed products, and funct…
Database Versioning 2.0, a Transparent SQL Approach Used in Quantitative Management and Decision Making
2015
Abstract Managerial decisions are based on accurate information and in today's time raw data is produced even with a stroke of a key. Regardless of the data creating process one needs to know how the information was extracted and which pool of data was used. One important factor is time therefore we need to structure it in layers of data history in such a way that it can be analyzed, (post)process, in order to be able to retrieve valuable information. The simplest way is to use a Database Management System (DBMS), but even with such a management system we face the issue of making it a self-contained database on each version of data added. Our proposed system, a continuation of previous work…
Making Every "Point" Count: Identifying the Key Determinants of Team Success in Elite Men’s Wheelchair Basketball
2019
Wheelchair basketball coaches and researchers have typically relied on box score data and the Comprehensive Basketball Grading System to inform practice, however, these data do not acknowledge how the dynamic perspectives of teams change, vary and adapt during possessions in relation to the outcome of a game. Therefore, this study aimed to identify the key dynamic variables associated with team success in elite men’s wheelchair basketball and explore the impact of each key dynamic variable upon the outcome of performance through the use of binary logistic regression modelling. The valid and reliable template developed by Francis, Owen and Peters (2019) was used to analyse video footage in S…
Monitoring the Morphology of M87* in 2009-2017 with the Event Horizon Telescope
2020
All authors: Wielgus, Maciek; Akiyama, Kazunori; Blackburn, Lindy; Chan, Chi-kwan; Dexter, Jason; Doeleman, Sheperd S.; Fish, Vincent L.; Issaoun, Sara; Johnson, Michael D.; Krichbaum, Thomas P.; Lu, Ru-Sen; Pesce, Dominic W.; Wong, George N.; Bower, Geoffrey C.; Broderick, Avery E.; Chael, Andrew; Chatterjee, Koushik; Gammie, Charles F.; Georgiev, Boris; Hada, Kazuhiro Loinard, Laurent; Markoff, Sera; Marrone, Daniel P.; Plambeck, Richard; Weintroub, Jonathan; Dexter, Matthew; MacMahon, David H. E.; Wright, Melvyn; Alberdi, Antxon; Alef, Walter; Asada, Keiichi; Azulay, Rebecca; Baczko, Anne-Kathrin; Ball, David; Baloković, Mislav; Barausse, Enrico; Barrett, John; Bintley, Dan; Boland, Wilf…
Information Systems Students’ Impressions on Learning Modeling Enterprise Architectures
2020
This Full Research Paper presents enterprise architecture (EA) modeling tools utilized in an educational context. EA is a well-known and a commonly used approach for organizational development aiming to improve the alignment of business operations and information technology. This high level design of information technology (IT) driven business operations lays the foundations on lower level technical activities such as the design and implementation of application programs and features, system boundary interfaces, database distribution and data pipes, and system recovery. Organizations’ architectures are made visible by creating EA artefacts, such as business process diagrams, data models and…
Domain-Specific Characteristics of Data Quality
2017
The research discusses the issue how to describe data quality and what should be taken into account when developing an universal data quality management solution. The proposed approach is to create quality specifications for each kind of data objects and to make them executable. The specification can be executed step-by-step according to business process descriptions, ensuring the gradual accumulation of data in the database and data quality checking according to the specific use case. The described approach can be applied to check the completeness, accuracy, timeliness and consistency of accumulated data.
Managing Multi-center Flow Cytometry Data for Immune Monitoring.
2014
With the recent results of promising cancer vaccines and immunotherapy 1 – 5 , immune monitoring has become increasingly relevant for measuring treatment-induced effects on T cells, and an essential tool for shedding light on the mechanisms responsible for a successful treatment. Flow cytometry is the canonical multi-parameter assay for the fine characterization of single cells in solution, and is ubiquitously used in pre-clinical tumor immunology and in cancer immunotherapy trials. Current state-of-the-art polychromatic flow cytometry involves multi-step, multi-reagent assays followed by sample acquisition on sophisticated instruments capable of capturing up to 20 parameters per cell at a…
Improvement of Temperature Based ANN Models for ETo Prediction in Coastal Locations by Means of Preliminary Models and Exogenous Data
2008
This paper reports the application of artificial neural networks for estimating reference evapotranspiration (ETo) as a function of local maximum and minimum air temperatures and exogenous relative humidity and evapotranspiration in twelve coastal locations of the autonomous Valencia region, Spain. The Penman-Monteith model for ETo prediction, as been proposed by the Food and Agriculture Organization of the United Nations (FAO) as the standard method for ETo forecast, has been used to provide the ANN targets. The number of stations where reliable climatic data are available for the application of the Penman-Monteith equation is limited. Thus, the development of more precise predicting tools…
Executable Data Quality Models
2017
The paper discusses an external solution for data quality management in information systems. In contradiction to traditional data quality assurance methods, the proposed approach provides the usage of a domain specific language (DSL) for description data quality models. Data quality models consists of graphical diagrams, which elements contain requirements for data object's values and procedures for data object's analysis. The DSL interpreter makes the data quality model executable therefore ensuring measurement and improving of data quality. The described approach can be applied: (1) to check the completeness, accuracy and consistency of accumulated data; (2) to support data migration in c…