scholarly journals Definition of an FHIR-based multiprotocol IoT home gateway to support the dynamic plug of new devices within instrumented environments

2021 ◽  
Author(s):  
Paolo Zampognaro ◽  
Giovanni Paragliola ◽  
Vincenzo Falanga
Keyword(s):  
Medical Devices ◽  
Semantic Annotation ◽  
Health Resources ◽  
Data Retrieval ◽  
Original Data ◽  
Seamless Integration ◽  
Data Format ◽  
Continuous Growth ◽  
Home Gateway ◽  
Mobile Phone Technology

AbstractInternet of Things (IoT) technologies have become a milestone advancement in the digital healthcare domain, since the number of IoT medical devices is grown exponentially, and it is now anticipated that by 2020, there will be over 161 million of them connected worldwide. Therefore, in an era of continuous growth, IoT healthcare faces various challenges, such as the collection over multiple protocols (e.g. Bluetooth, MQTT, CoAP, ZigBEE, etc.) the interpretation, as well as the harmonization of the data format that derive from the existing huge amounts of heterogeneous IoT medical devices. In this respect, this study aims at proposing an advanced Home Gateway architecture that offers a unique data collection module, supporting direct data acquisition over multiple protocols (i.e.BLE, MQTT) and indirect data retrieval from cloud health services (i.e. GoogleFit). Moreover, the solution propose a mechanism to automatically convert the original data format, carried over BLE, in HL7 FHIR by exploiting device capabilities semantic annotation implemented by means of FHIR resource as well. The adoption of such annotation enables the dynamic plug of new sensors within the instrumented environment without the need to stop and adapt the gateway. This simplifies the dynamic devices landscape customization requested by the several telemedicine applications contexts (e.g. CVD, Diabetes) and demonstrate, for the first time, a concrete example of using the FHIR standard not only (as usual) for health resources representation and storage but also as instrument to enable seamless integration of IoT devices. The proposed solution also relies on mobile phone technology which is widely adopted aiming at reducing any obstacle for a larger adoption.

Pillars of Ontology Treatment in the Medical Domain

2009 ◽  
Vol 11 (4) ◽  
pp. 47-73 ◽  
Author(s):  
Daniel Sonntag ◽  
Pinar Wennerberg ◽  
Paul Buitelaar ◽  
Sonja Zillner
Keyword(s):  
Large Scale ◽  
Knowledge Engineering ◽  
Semantic Annotation ◽  
Image Data ◽  
Clinical Decision ◽  
Direct Access ◽  
Seamless Integration ◽  
Data Repositories ◽  
Semantic Image Retrieval ◽  
Medical Domain

In this chapter the authors describe the three pillars of ontology treatment in the medical domain in a comprehensive case study within the large-scale THESEUS MEDICO project. MEDICO addresses the need for advanced semantic technologies in medical image and patient data search. The objective is to enable a seamless integration of medical images and different user applications by providing direct access to image semantics. Semantic image retrieval should provide the basis for the help in clinical decision support and computer aided diagnosis. During the course of lymphoma diagnosis and continual treatment, image data is produced several times using different image modalities. After semantic annotation, the images need to be integrated with medical (textual) data repositories and ontologies. They build upon the three pillars of knowledge engineering, ontology mediation and alignment, and ontology population and learning to achieve the objectives of the MEDICO project.

Pillars of Ontology Treatment in the Medical Domain

2011 ◽  
pp. 162-186 ◽  
Author(s):  
Daniel Sonntag ◽  
Pinar Wennerberg ◽  
Paul Buitelaar ◽  
Sonja Zillner
Keyword(s):  
Large Scale ◽  
Knowledge Engineering ◽  
Semantic Annotation ◽  
Image Data ◽  
Clinical Decision ◽  
Direct Access ◽  
Seamless Integration ◽  
Data Repositories ◽  
Semantic Image Retrieval ◽  
Medical Domain

In this chapter the authors describe the three pillars of ontology treatment in the medical domain in a comprehensive case study within the large-scale THESEUS MEDICO project. MEDICO addresses the need for advanced semantic technologies in medical image and patient data search. The objective is to enable a seamless integration of medical images and different user applications by providing direct access to image semantics. Semantic image retrieval should provide the basis for the help in clinical decision support and computer aided diagnosis. During the course of lymphoma diagnosis and continual treatment, image data is produced several times using different image modalities. After semantic annotation, the images need to be integrated with medical (textual) data repositories and ontologies. They build upon the three pillars of knowledge engineering, ontology mediation and alignment, and ontology population and learning to achieve the objectives of the MEDICO project.

scholarly journals Web-Based Presence Application Development at Pontianak State Polytechnic

ELKHA ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 63
Author(s):  
Hendro Cahyono ◽  
Hasan Hasan ◽  
Lindung Siswanto ◽  
M. Ridhwan Sufandi
Keyword(s):  
Information System ◽  
Data Collection ◽  
Employee Performance ◽  
Data Retrieval ◽  
Application Development ◽  
Process Data ◽  
Web Based ◽  
Mobile Phone Technology ◽  
Presence Data ◽  
Waterfall Model

The employees' presence is an important factor for an institution, which is relate to discipline and has an impact on the employee's performance.  Therefore, it is necessary to have specific data collection to record presence, absenteeism, and work activities that has done every day so that employee performance record in real-time and proper. There are many ways that can be done to achieve a good presence information system, one of them is using computer and mobile phone technology which is implemented with a website-based presence application. At the Pontianak State Polytechnic, finger print machine used in the presence process system, but it is still lack in efficiency and effectiveness in data collection, data retrieval as well as data recap calculations, which require a relatively long time. Besides, the bigger risk of error and loss of presence data.  Based on problems, a Web-Based Presence Application Development Information System created at the Pontianak State Polytechnic. The research method used in data collection, which includes research methods, interviews and literature. While software development uses a waterfall model which includes requirements analysis, design, coding, testing and implementation. This web-based presence application can provide convenience in the employee presence process, data search and presence recap calculations, and minimize loss and errors in recording employee presence data. Based on web-based presence application testing and evaluation to thirty-four employees of Pontianak State Polytechnic, it stated that the web-based presence application is suitable for used by all employees of Pontianak State Polytechnic.

Target-oriented waveform redatuming and high-resolution inversion: Role of the overburden

Geophysics ◽  
2020 ◽  
Vol 85 (6) ◽  
pp. R525-R536 ◽  
Author(s):  
Qiang Guo ◽  
Tariq Alkhalifah
Keyword(s):  
High Resolution ◽  
Waveform Inversion ◽  
Model Space ◽  
Data Retrieval ◽  
Original Data ◽  
Fine Grid ◽  
Data Set ◽  
High Frequencies ◽  
Full Band ◽  
Virtual Data

Target-oriented inversion (TOI) is an approach aimed at enhancing the ability of full-waveform inversion (FWI) to achieve a high-resolution delineation of a reservoir. FWI has demonstrated its potential to address the challenge of imaging complex structures on a considerable number of field data applications. Nevertheless, it is still impractical costwise to implement FWI with the full band of seismic data because, in this case, we need to discretize the whole subsurface model space with a fine grid to handle the high frequencies and satisfy the interpretation of, for example, reservoir-scale features. Redatuming techniques enable us to obtain a virtual data set at the target level from the original data acquisition that is most commonly deployed on the earth’s surface. The virtual data set can help us apply a high-resolution FWI to the target region, which often occupies a small area of the entire model space. To analyze such a redatuming process, we need to estimate an overburden model that can accurately describe the kinematics and dynamics of the wave propagation. Fortunately, our virtual data retrieval can rely on the overburden estimation with relatively low resolution, because the high-frequency multiple scattering has a limited effect on the deep part and on the corresponding virtual data. Therefore, we start with macro-overburden models that contain reasonably accurate kinematics, and we then apply FWI on the overburden with only low-frequency data. The resulting model is used to implement a least-squares waveform redatuming using the full band. The Marmousi model and Chevron 2014 benchmark data set are used to demonstrate the effectiveness of our strategy, which results in the high-resolution inversion of the target areas. Our TOI workflow leads to an obvious boost in efficiency and reduces the memory requirement because the finer grid needed for the high frequencies is only adopted for the redatuming and the TOI.

The KnowledgeStore

2015 ◽  
Vol 11 (2) ◽  
pp. 1-35 ◽  
Author(s):  
Francesco Corcoglioniti ◽  
Marco Rospocher ◽  
Roldano Cattoni ◽  
Bernardo Magnini ◽  
Luciano Serafini
Keyword(s):  
Fault Tolerant ◽  
Storage System ◽  
Open Data ◽  
Data Retrieval ◽  
Lessons Learned ◽  
Concept Design ◽  
Seamless Integration ◽  
Design Function ◽  
Structured Information ◽  
Eu Project

Although the quantity of structured information on the Web and within organizations is increasing, the majority of information remains available only in unstructured form. While different in form, both unstructured and structured information sources provide information about entities in the world and their properties and relations; still, frameworks for their seamless integration have not been deeply investigated. In this paper the authors describe the KnowledgeStore, a scalable, fault-tolerant, and Semantic Web grounded open-source storage system for interlinking structured and unstructured data. They present the concept, design, function and implementation of the system, and report on its concrete usage in three application scenarios within the NewsReader EU project, where it stores and supports the querying of millions of news articles interlinked with millions of RDF triples extracted from text and imported from Linked Open Data sources. The authors report on data population and data retrieval performances of the system measured through a number of experiments, and they also discuss the practical issues and lessons learned from these experiences.

scholarly journals POINT-BASED MORPHOLOGICAL OPENING WITH INPUT DATA RETRIEVAL

2021 ◽  
Vol VIII-4/W2-2021 ◽  
pp. 53-58
Author(s):  
J. Balado ◽  
P. van Oosterom ◽  
L. Díaz-Vilariño ◽  
H. Lorenzo
Keyword(s):  
Point Cloud ◽  
Real Data ◽  
Data Retrieval ◽  
Original Data ◽  
Traffic Sign ◽  
Cloud Data ◽  
Structuring Element ◽  
Complex Process ◽  
Working Principle ◽  
Morphological Opening

Abstract. Mathematical morphology is a technique recently applied directly for point cloud data. Its working principle is based on the removal and addition of points from an auxiliary point cloud that acts as a structuring element. However, in certain applications within a more complex process, these changes to the original data represent an unacceptable loss of information. The aim of this work is to provide a modification of the morphological opening to retain original points and attributes. The proposed amendment involved in the morphological opening: erosion followed by dilatation. In morphological erosion, the new eroded points are retained. In morphological dilation, the structuring element does not add its points directly, but uses the point positions to search through the previously eroded points and retrieve them for the dilated point cloud. The modification was tested on synthetic and real data, showing a correct performance at the morphological level, and preserving the precision of the original points and their attributes. Furthermore, the conservation is shown to be very relevant in two possible applications such as traffic sign segmentation and occluded edge detection.

scholarly journals IoT in Healthcare: Achieving Interoperability of High-Quality Data Acquired by IoT Medical Devices

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 1978 ◽  
Author(s):  
Argyro Mavrogiorgou ◽  
Athanasios Kiourtis ◽  
Konstantinos Perakis ◽  
Stamatios Pitsios ◽  
Dimosthenis Kyriazis
Keyword(s):  
Data Quality ◽  
Medical Devices ◽  
Holistic Approach ◽  
Quality Data ◽  
Quality Estimation ◽  
High Quality ◽  
Data Interoperability ◽  
High Quality Data ◽  
Continuous Growth

It is an undeniable fact that Internet of Things (IoT) technologies have become a milestone advancement in the digital healthcare domain, since the number of IoT medical devices is grown exponentially, and it is now anticipated that by 2020 there will be over 161 million of them connected worldwide. Therefore, in an era of continuous growth, IoT healthcare faces various challenges, such as the collection, the quality estimation, as well as the interpretation and the harmonization of the data that derive from the existing huge amounts of heterogeneous IoT medical devices. Even though various approaches have been developed so far for solving each one of these challenges, none of these proposes a holistic approach for successfully achieving data interoperability between high-quality data that derive from heterogeneous devices. For that reason, in this manuscript a mechanism is produced for effectively addressing the intersection of these challenges. Through this mechanism, initially, the collection of the different devices’ datasets occurs, followed by the cleaning of them. In sequel, the produced cleaning results are used in order to capture the levels of the overall data quality of each dataset, in combination with the measurements of the availability of each device that produced each dataset, and the reliability of it. Consequently, only the high-quality data is kept and translated into a common format, being able to be used for further utilization. The proposed mechanism is evaluated through a specific scenario, producing reliable results, achieving data interoperability of 100% accuracy, and data quality of more than 90% accuracy.

The KnowledgeStore

2018 ◽  
pp. 686-721
Author(s):  
Francesco Corcoglioniti ◽  
Marco Rospocher ◽  
Roldano Cattoni ◽  
Bernardo Magnini ◽  
Luciano Serafini
Keyword(s):  
Fault Tolerant ◽  
Storage System ◽  
Open Data ◽  
Data Retrieval ◽  
Lessons Learned ◽  
Concept Design ◽  
Seamless Integration ◽  
Design Function ◽  
Structured Information ◽  
Eu Project

Although the quantity of structured information on the Web and within organizations is increasing, the majority of information remains available only in unstructured form. While different in form, both unstructured and structured information sources provide information about entities in the world and their properties and relations; still, frameworks for their seamless integration have not been deeply investigated. In this paper the authors describe the KnowledgeStore, a scalable, fault-tolerant, and Semantic Web grounded open-source storage system for interlinking structured and unstructured data. They present the concept, design, function and implementation of the system, and report on its concrete usage in three application scenarios within the NewsReader EU project, where it stores and supports the querying of millions of news articles interlinked with millions of RDF triples extracted from text and imported from Linked Open Data sources. The authors report on data population and data retrieval performances of the system measured through a number of experiments, and they also discuss the practical issues and lessons learned from these experiences.

Rotational Characteristics of the Green Solar Corona: 1947-1991

1994 ◽  
Vol 144 ◽  
pp. 139-141 ◽  
Author(s):  
J. Rybák ◽  
V. Rušin ◽  
M. Rybanský
Keyword(s):  
Solar Corona ◽  
World Wide ◽  
Rotation Period ◽  
Original Data ◽  
Coronal Emission ◽  
Time Intervals ◽  
Data Set ◽  
The World ◽  
Coronal Emission Line ◽  
Homogeneous Data

AbstractFe XIV 530.3 nm coronal emission line observations have been used for the estimation of the green solar corona rotation. A homogeneous data set, created from measurements of the world-wide coronagraphic network, has been examined with a help of correlation analysis to reveal the averaged synodic rotation period as a function of latitude and time over the epoch from 1947 to 1991.The values of the synodic rotation period obtained for this epoch for the whole range of latitudes and a latitude band ±30° are 27.52±0.12 days and 26.95±0.21 days, resp. A differential rotation of green solar corona, with local period maxima around ±60° and minimum of the rotation period at the equator, was confirmed. No clear cyclic variation of the rotation has been found for examinated epoch but some monotonic trends for some time intervals are presented.A detailed investigation of the original data and their correlation functions has shown that an existence of sufficiently reliable tracers is not evident for the whole set of examinated data. This should be taken into account in future more precise estimations of the green corona rotation period.

Sign in / Sign up

Export Citation Format

Share Document