scholarly journals Enabling Agile Clinical and Translational Data Warehousing: Platform Development and Evaluation

10.2196/15918 ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. e15918
Author(s):  
Helmut Spengler ◽  
Claudia Lang ◽  
Tanmaya Mahapatra ◽  
Ingrid Gatz ◽  
Klaus A Kuhn ◽  
...  
Keyword(s):  
Laboratory Data ◽  
Data Representation ◽  
Heterogeneous Data ◽  
Use Cases ◽  
Iterative Refinement ◽  
Cloud Infrastructure ◽  
Specific Domain ◽  
Wide Range ◽  
Data Loading ◽  
Time Required

Background Modern data-driven medical research provides new insights into the development and course of diseases and enables novel methods of clinical decision support. Clinical and translational data warehouses, such as Informatics for Integrating Biology and the Bedside (i2b2) and tranSMART, are important infrastructure components that provide users with unified access to the large heterogeneous data sets needed to realize this and support use cases such as cohort selection, hypothesis generation, and ad hoc data analysis. Objective Often, different warehousing platforms are needed to support different use cases and different types of data. Moreover, to achieve an optimal data representation within the target systems, specific domain knowledge is needed when designing data-loading processes. Consequently, informaticians need to work closely with clinicians and researchers in short iterations. This is a challenging task as installing and maintaining warehousing platforms can be complex and time consuming. Furthermore, data loading typically requires significant effort in terms of data preprocessing, cleansing, and restructuring. The platform described in this study aims to address these challenges. Methods We formulated system requirements to achieve agility in terms of platform management and data loading. The derived system architecture includes a cloud infrastructure with unified management interfaces for multiple warehouse platforms and a data-loading pipeline with a declarative configuration paradigm and meta-loading approach. The latter compiles data and configuration files into forms required by existing loading tools, thereby automating a wide range of data restructuring and cleansing tasks. We demonstrated the fulfillment of the requirements and the originality of our approach by an experimental evaluation and a comparison with previous work. Results The platform supports both i2b2 and tranSMART with built-in security. Our experiments showed that the loading pipeline accepts input data that cannot be loaded with existing tools without preprocessing. Moreover, it lowered efforts significantly, reducing the size of configuration files required by factors of up to 22 for tranSMART and 1135 for i2b2. The time required to perform the compilation process was roughly equivalent to the time required for actual data loading. Comparison with other tools showed that our solution was the only tool fulfilling all requirements. Conclusions Our platform significantly reduces the efforts required for managing clinical and translational warehouses and for loading data in various formats and structures, such as complex entity-attribute-value structures often found in laboratory data. Moreover, it facilitates the iterative refinement of data representations in the target platforms, as the required configuration files are very compact. The quantitative measurements presented are consistent with our experiences of significantly reduced efforts for building warehousing platforms in close cooperation with medical researchers. Both the cloud-based hosting infrastructure and the data-loading pipeline are available to the community as open source software with comprehensive documentation.

scholarly journals Enabling Agile Clinical and Translational Data Warehousing: Platform Development and Evaluation (Preprint)

2019 ◽  
Author(s):  
Helmut Spengler ◽  
Claudia Lang ◽  
Tanmaya Mahapatra ◽  
Ingrid Gatz ◽  
Klaus A Kuhn ◽  
...  
Keyword(s):  
Laboratory Data ◽  
Data Representation ◽  
Heterogeneous Data ◽  
Use Cases ◽  
Iterative Refinement ◽  
Cloud Infrastructure ◽  
Specific Domain ◽  
Wide Range ◽  
Data Loading ◽  
Time Required

BACKGROUND Modern data-driven medical research provides new insights into the development and course of diseases and enables novel methods of clinical decision support. Clinical and translational data warehouses, such as Informatics for Integrating Biology and the Bedside (i2b2) and tranSMART, are important infrastructure components that provide users with unified access to the large heterogeneous data sets needed to realize this and support use cases such as cohort selection, hypothesis generation, and ad hoc data analysis. OBJECTIVE Often, different warehousing platforms are needed to support different use cases and different types of data. Moreover, to achieve an optimal data representation within the target systems, specific domain knowledge is needed when designing data-loading processes. Consequently, informaticians need to work closely with clinicians and researchers in short iterations. This is a challenging task as installing and maintaining warehousing platforms can be complex and time consuming. Furthermore, data loading typically requires significant effort in terms of data preprocessing, cleansing, and restructuring. The platform described in this study aims to address these challenges. METHODS We formulated system requirements to achieve agility in terms of platform management and data loading. The derived system architecture includes a cloud infrastructure with unified management interfaces for multiple warehouse platforms and a data-loading pipeline with a declarative configuration paradigm and meta-loading approach. The latter compiles data and configuration files into forms required by existing loading tools, thereby automating a wide range of data restructuring and cleansing tasks. We demonstrated the fulfillment of the requirements and the originality of our approach by an experimental evaluation and a comparison with previous work. RESULTS The platform supports both i2b2 and tranSMART with built-in security. Our experiments showed that the loading pipeline accepts input data that cannot be loaded with existing tools without preprocessing. Moreover, it lowered efforts significantly, reducing the size of configuration files required by factors of up to 22 for tranSMART and 1135 for i2b2. The time required to perform the compilation process was roughly equivalent to the time required for actual data loading. Comparison with other tools showed that our solution was the only tool fulfilling all requirements. CONCLUSIONS Our platform significantly reduces the efforts required for managing clinical and translational warehouses and for loading data in various formats and structures, such as complex entity-attribute-value structures often found in laboratory data. Moreover, it facilitates the iterative refinement of data representations in the target platforms, as the required configuration files are very compact. The quantitative measurements presented are consistent with our experiences of significantly reduced efforts for building warehousing platforms in close cooperation with medical researchers. Both the cloud-based hosting infrastructure and the data-loading pipeline are available to the community as open source software with comprehensive documentation. CLINICALTRIAL

Microwaves: Application in Electron Microscopy

1990 ◽  
Vol 48 (3) ◽  
pp. 140-141
Author(s):  
Anthony S-Y Leong ◽  
David W Gove
Keyword(s):  
Electron Microscopy ◽  
Light Microscopy ◽  
Chemical Reactions ◽  
Electromagnetic Waves ◽  
Tissue Fixation ◽  
Primary Method ◽  
Dipolar Molecules ◽  
Wide Range ◽  
Time Required ◽  
Cryostat Sections

Microwaves (MW) are electromagnetic waves which are commonly generated at a frequency of 2.45 GHz. When dipolar molecules such as water, the polar side chains of proteins and other molecules with an uneven distribution of electrical charge are exposed to such non-ionizing radiation, they oscillate through 180° at a rate of 2,450 million cycles/s. This rapid kinetic movement results in accelerated chemical reactions and produces instantaneous heat. MWs have recently been applied to a wide range of procedures for light microscopy. MWs generated by domestic ovens have been used as a primary method of tissue fixation, it has been applied to the various stages of tissue processing as well as to a wide variety of staining procedures. This use of MWs has not only resulted in drastic reductions in the time required for tissue fixation, processing and staining, but have also produced better cytologic images in cryostat sections, and more importantly, have resulted in better preservation of cellular antigens.

TIME TO THE END OF PRIMARY CONSOLIDATION (EOP) OF SOFT CLAYEY SOILS: CONCERNING THE EFFECT OF ATTERBERG’S LIMIT AND CYCLIC LOADING HISTORY

2019 ◽  
Vol 128 (2B) ◽  
pp. 29-41
Author(s):  
Trần Thanh Nhàn
Keyword(s):  
Cyclic Loading ◽  
Pore Water ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Clayey Soils ◽  
Loading History ◽  
Cyclic Shear ◽  
Wide Range ◽  
Primary Consolidation ◽  
Time Required

In order to observe the end of primary consolidation (EOP) of cohesive soils with and without subjecting to cyclic loading, reconstituted specimens of clayey soils at various Atterberg’s limits were used for oedometer test at different loading increments and undrained cyclic shear test followed by drainage with various cyclic shear directions and a wide range of shear strain amplitudes. The pore water pressure and settlement of the soils were measured with time and the time to EOP was then determined by different methods. It is shown from observed results that the time to EOP determined by 3-t method agrees well with the time required for full dissipation of the pore water pressure and being considerably larger than those determined by Log Time method. These observations were then further evaluated in connection with effects of the Atterberg’s limit and the cyclic loading history.

scholarly journals Automatic Hip Detection in Anteroposterior Pelvic Radiographs—A Labelless Practical Framework

2021 ◽  
Vol 11 (6) ◽  
pp. 522
Author(s):  
Feng-Yu Liu ◽  
Chih-Chi Chen ◽  
Chi-Tung Cheng ◽  
Cheng-Ta Wu ◽  
Chih-Po Hsu ◽  
...  
Keyword(s):  
Medical Image ◽  
Image Annotation ◽  
Region Of Interest ◽  
Confidence Score ◽  
Heterogeneous Data ◽  
Single Shot ◽  
Hip Joints ◽  
Pelvic Radiographs ◽  
Wide Range ◽  
Average Confidence

Automated detection of the region of interest (ROI) is a critical step in the two-step classification system in several medical image applications. However, key information such as model parameter selection, image annotation rules, and ROI confidence score are essential but usually not reported. In this study, we proposed a practical framework of ROI detection by analyzing hip joints seen on 7399 anteroposterior pelvic radiographs (PXR) from three diverse sources. We presented a deep learning-based ROI detection framework utilizing a single-shot multi-box detector with a customized head structure based on the characteristics of the obtained datasets. Our method achieved average intersection over union (IoU) = 0.8115, average confidence = 0.9812, and average precision with threshold IoU = 0.5 (AP50) = 0.9901 in the independent testing set, suggesting that the detected hip regions appropriately covered the main features of the hip joints. The proposed approach featured flexible loose-fitting labeling, customized model design, and heterogeneous data testing. We demonstrated the feasibility of training a robust hip region detector for PXRs. This practical framework has a promising potential for a wide range of medical image applications.

scholarly journals Relative Total Variation Structure Analysis-Based Fusion Method for Hyperspectral and LiDAR Data Classification

2021 ◽  
Vol 13 (6) ◽  
pp. 1143
Author(s):  
Yinghui Quan ◽  
Yingping Tong ◽  
Wei Feng ◽  
Gabriel Dauphin ◽  
Wenjiang Huang ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Total Variation ◽  
Structure Analysis ◽  
Hyperspectral Image ◽  
Gabor Filter ◽  
Heterogeneous Data ◽  
Lidar Data ◽  
Fusion Method ◽  
Wide Range ◽  
Relative Total Variation

The fusion of the hyperspectral image (HSI) and the light detecting and ranging (LiDAR) data has a wide range of applications. This paper proposes a novel feature fusion method for urban area classification, namely the relative total variation structure analysis (RTVSA), to combine various features derived from HSI and LiDAR data. In the feature extraction stage, a variety of high-performance methods including the extended multi-attribute profile, Gabor filter, and local binary pattern are used to extract the features of the input data. The relative total variation is then applied to remove useless texture information of the processed data. Finally, nonparametric weighted feature extraction is adopted to reduce the dimensions. Random forest and convolutional neural networks are utilized to evaluate the fusion images. Experiments conducted on two urban Houston University datasets (including Houston 2012 and the training portion of Houston 2017) demonstrate that the proposed method can extract the structural correlation from heterogeneous data, withstand a noise well, and improve the land cover classification accuracy.

scholarly journals Prototype Design and Experimental Evaluation of Autonomous Collaborative Communication System for Emerging Maritime Use Cases

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3871
Author(s):  
Jiri Pokorny ◽  
Khanh Ma ◽  
Salwa Saafi ◽  
Jakub Frolka ◽  
Jose Villa ◽  
...  
Keyword(s):  
Communication System ◽  
Autonomous Vehicles ◽  
High Speed ◽  
High Capacity ◽  
Workplace Safety ◽  
Unmanned Vehicles ◽  
Use Cases ◽  
Automated Systems ◽  
Collaborative Communication ◽  
Wide Range

Automated systems have been seamlessly integrated into several industries as part of their industrial automation processes. Employing automated systems, such as autonomous vehicles, allows industries to increase productivity, benefit from a wide range of technologies and capabilities, and improve workplace safety. So far, most of the existing systems consider utilizing one type of autonomous vehicle. In this work, we propose a collaboration of different types of unmanned vehicles in maritime offshore scenarios. Providing high capacity, extended coverage, and better quality of services, autonomous collaborative systems can enable emerging maritime use cases, such as remote monitoring and navigation assistance. Motivated by these potential benefits, we propose the deployment of an Unmanned Surface Vehicle (USV) and an Unmanned Aerial Vehicle (UAV) in an autonomous collaborative communication system. Specifically, we design high-speed, directional communication links between a terrestrial control station and the two unmanned vehicles. Using measurement and simulation results, we evaluate the performance of the designed links in different communication scenarios and we show the benefits of employing multiple autonomous vehicles in the proposed communication system.

Analysis and Reduction of the Waste in the Work Process Using Time Study Analysis: A Case Study

2014 ◽  
Vol 660 ◽  
pp. 971-975 ◽  
Author(s):  
Mohd Norzaim bin Che Ani ◽  
Siti Aisyah Binti Abdul Hamid
Keyword(s):  
Cycle Time ◽  
Lean Manufacturing ◽  
Value Added ◽  
Time Study ◽  
Study Approach ◽  
Root Cause ◽  
Wide Range ◽  
Unit Of Work ◽  
Time Required ◽  
The Impact

Time study is the process of observation which concerned with the determination of the amount of time required to perform a unit of work involves of internal, external and machine time elements. Originally, time study was first starting to be used in Europe since 1760s in manufacturing fields. It is the flexible technique in lean manufacturing and suitable for a wide range of situations. Time study approach that enable of reducing or minimizing ‘non-value added activities’ in the process cycle time which contribute to bottleneck time. The impact on improving process cycle time for organization that it was increasing the productivity and reduce cost. This project paper focusing on time study at selected processes with bottleneck time and identify the possible root cause which was contribute to high time required to perform a unit of work.

scholarly journals SAPHYR: Swiss Atlas of Physical Properties of Rocks: the continental crust in a database

2021 ◽  
Vol 114 (1) ◽  
Author(s):  
Alba Zappone ◽  
Eduard Kissling
Keyword(s):  
Physical Properties ◽  
Laboratory Data ◽  
Rock Physics ◽  
Resource Planning ◽  
Data Representation ◽  
Common People ◽  
Rock Types ◽  
Gis Tools ◽  
Porosity And Permeability ◽  
Thermal And Electrical Properties

AbstractThe Swiss Atlas of Physical Properties of Rocks (SAPHYR) project aims at centralize, uniform, and digitize dispersed and often hardly accessible laboratory data on physical properties of rocks from Switzerland and surrounding regions. The goal of SAPHYR is to make the quality-controlled and homogenized data digitally accessible to an open public, including industrial, engineering, land and resource planning companies as well as governmental and academic institutions, or simply common people interested in rock physics. The physical properties, derived from pre-existing literature or newly measured, are density, porosity and permeability as well as seismic, magnetic, thermal and electrical properties. The data were collected on samples either from outcrops or from tunnels and boreholes. At present, data from literature have been collected extensively for density, porosity, seismic and thermal properties. In the past years, effort has been placed especially on collecting samples and measuring the physical properties of rock types that were poorly documented in literature. A workflow for quality control on reliability and completeness of the data was established. We made the attempt to quantify the variability and the uncertainty of the data. The database has been recently transferred to the Federal Office of Topography swisstopo with the aim to develop the necessary tools to query the database and open it to the public. Laboratory measurements are continuously collected, therefore the database is ongoing and in continuous development. The spatial distribution of the physical properties can be visualized as maps using simple GIS tools. Here the distribution of bulk density and velocity at room conditions are presented as examples of data representation; the methodology to produce these maps is described in detail. Moreover we also present an exemplification of the use of specific datasets, for which pressure and temperatures derivatives are available, to develop crustal models.

scholarly journals Infection Prevention Time Required for Construction and Design at a Large Tertiary-Care Hospital, 2019

2020 ◽  
Vol 41 (S1) ◽  
pp. s69-s70
Author(s):  
Angie Dains ◽  
Michael Edmond ◽  
Daniel Diekema ◽  
Stephanie Holley ◽  
Oluchi Abosi ◽  
...  
Keyword(s):  
Infection Control ◽  
Patient Care ◽  
Construction Projects ◽  
Small Scale ◽  
Care Hospital ◽  
Class Iii ◽  
Construction Sites ◽  
Wide Range ◽  
Time Required ◽  
Class Iv

Background: Including infection preventionists (IPs) in hospital design, construction, and renovation projects is important. According to the Joint Commission, “Infection control oversights during building design or renovations commonly result in regulatory problems, millions lost and even patient deaths.” We evaluated the number of active major construction projects at our 800-bed hospital with 6.0 IP FTEs and the IP time required for oversight. Methods: We reviewed construction records from October 2018 through October 2019. We classified projects as active if any construction occurred during the study period. We describe the types of projects: inpatient, outpatient, non–patient care, and the potential impact to patient health through infection control risk assessments (ICRA). ICRAs were classified as class I (non–patient-care area and minimal construction activity), class II (patients are not likely to be in the area and work is small scale), class III (patient care area and work requires demolition that generates dust), and class IV (any area requiring environmental precautions). We calculated the time spent visiting construction sites and in design meetings. Results: During October 2018–October 2019, there were 51 active construction projects with an average of 15 active sites per week. These sites included a wide range of projects from a new bone marrow transplant unit, labor and delivery expansion and renovation, space conversion to an inpatient unit to a project for multiple air handler replacements. All 51 projects were classified as class III or class IV. We visited, on average, 4 construction sites each week for 30 minutes per site, leaving 11 sites unobserved due to time constraints. We spent an average of 120 minutes weekly, but 450 minutes would have been required to observe all 15 sites. Yearly, the required hours to observe these active construction sites once weekly would be 390 hours. In addition to the observational hours, 124 hours were spent in design meetings alone, not considering the preparation time and follow-up required for these meetings. Conclusions: In a large academic medical center, IPs had time available to visit only a quarter of active projects on an ongoing basis. Increasing dedicated IP time in construction projects is essential to mitigating infection control risks in large hospitals.Funding: NoneDisclosures: None

GOVERNMENT REGULATIONS OF THE USING CLOUD SERVICES

2022 ◽  
Author(s):  
Olexander Melnikov ◽  
◽  
Konstantin Petrov ◽  
Igor Kobzev ◽  
Viktor Kosenko ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Government Agencies ◽  
Remote Work ◽  
Cloud Infrastructure ◽  
Wide Range ◽  
Technological Base

The article considers the development and implementation of cloud services in the work of government agencies. The classification of the choice of cloud service providers is offered, which can serve as a basis for decision making. The basics of cloud computing technology are analyzed. The COVID-19 pandemic has identified the benefits of cloud services in remote work Government agencies at all levels need to move to cloud infrastructure. Analyze the prospects of cloud computing in Ukraine as the basis of e-governance in development. This is necessary for the rapid provision of quality services, flexible, large-scale and economical technological base. The transfer of electronic information interaction in the cloud makes it possible to attract a wide range of users with relatively low material costs. Automation of processes and their transfer to the cloud environment make it possible to speed up the process of providing services, as well as provide citizens with minimal time to obtain certain information. The article also lists the risks that exist in the transition to cloud services and the shortcomings that may arise in the process of using them.

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