Standard Interface Research Articles

Open Geospatial System for LUCAS In Situ Data Harmonization and Distribution

The use of in situ references in Earth observation monitoring is a fundamental need. LUCAS (Land Use and Coverage Area frame Survey) is an activity that has performed repeated in situ surveys over Europe every three years since 2006. The dataset is unique in many aspects; however it is currently not available through a standardized interface, machine-to-machine. Moreover, the evolution of the surveys limits the performance of change analysis using the dataset. Our objective was to develop an open-source system to fill these gaps. This paper presents a developed system solution for the LUCAS in situ data harmonization and distribution. We have designed a multi-layer client-server system that may be integrated into end-to-end workflows. It provides data through an OGC (Open Geospatial Consortium) compliant interface. Moreover, a geospatial user may integrate the data through a Python API (Application Programming Interface) to ease the use in workflows with spatial, temporal, attribute, and thematic filters. Furthermore, we have implemented a QGIS plugin to retrieve the spatial and temporal subsets of the data interactively. In addition, the Python API includes methods for managing thematic information. The system provides enhanced functionality which is demonstrated in two use cases.

Standardize or Let a Thousand Flowers Bloom? Interface Design Coordination between Software Platforms and Hosted Apps

Software platform ecosystems are emerging as a dominant model for IT-based services. To accelerate third-party development, platform owners often waive restrictions on app user interfaces to provide app developers with more autonomy in interface design. The literature has indicated, however, that standardized interface design across products is a strategic necessity for firms to introduce and manage their product lines, suggesting that platform owners should not waive restrictions on app user interfaces. This tension between the two approaches raises a crucial research question: Does standardized interface design used by apps and their host platform benefit the platform and apps that it hosts? Specifically, does the coordinated design approach enhance or hinder usage between the platform and apps such that apps attract usage from their host platform and vice versa? Drawing on the theory of basic Gestalts, we theorize the three interface design properties of interface similarity, embeddedness, and synchrony, and extend the theory to investigate how these properties help both apps and their host platform attract each other’s users, thus reflecting derivative usage between them. We performed a randomized field experiment to test the proposed hypotheses. The results reveal that interface similarity, embeddedness, and synchrony of the app-platform interface design strengthen users’ grouping perception of the platform and its apps, thus enhancing platform-to-app forward derivative usage. Contrary to our expectations, we found that this strengthened grouping perception does not improve the app-to-platform backward derivative usage. These findings have crucial implications for the value of interface design in software platform ecosystems.

Service-oriented Device Connectivity interface for a situation recognition system in the OR

PurposeContext awareness in the operating room (OR) is important to realize targeted assistance to support actors during surgery. A situation recognition system (SRS) is used to interpret intraoperative events and derive an intraoperative situation from these. To achieve a modular system architecture, it is desirable to de-couple the SRS from other system components. This leads to the need of an interface between such an SRS and context-aware systems (CAS). This work aims to provide an open standardized interface to enable loose coupling of the SRS with varying CAS to allow vendor-independent device orchestrations.MethodsA requirements analysis investigated limiting factors that currently prevent the integration of CAS in today's ORs. These elicited requirements enabled the selection of a suitable base architecture. We examined how to specify this architecture with the constraints of an interoperability standard. The resulting middleware was integrated into a prototypic SRS and our system for intraoperative support, the OR-Pad, as exemplary CAS for evaluating whether our solution can enable context-aware assistance during simulated orthopedical interventions.ResultsThe emerging Service-oriented Device Connectivity (SDC) standard series was selected to specify and implement a middleware for providing the interpreted contextual information while the SRS and CAS are loosely coupled. The results were verified within a proof of concept study using the OR-Pad demonstration scenario. The fulfillment of the CAS’ requirements to act context-aware, conformity to the SDC standard series, and the effort for integrating the middleware in individual systems were evaluated. The semantically unambiguous encoding of contextual information depends on the further standardization process of the SDC nomenclature. The discussion of the validity of these results proved the applicability and transferability of the middleware.ConclusionThe specified and implemented SDC-based middleware shows the feasibility of loose coupling an SRS with unknown CAS to realize context-aware assistance in the OR.

An autonomous lunar geophysical experiment package (ALGEP) for future space missions

Geophysical observations will provide key information about the inner structure of the planets and satellites and understanding the internal structure is a strong constraint on the bulk composition and thermal evolution of these bodies. Thus, geophysical observations are a key to uncovering the origin and evolution of the Moon. In this article, we propose the development of an autonomous lunar geophysical experiment package, composed of a suite of instruments and a central station with standardized interface, which can be installed on various future lunar missions. By fixing the interface between instruments and the central station, it would be possible to easily configure an appropriate experiment package for different missions. We describe here a series of geophysical instruments that may be included as part of the geophysical package: a seismometer, a magnetometer, a heat flow probe, and a laser reflector. These instruments will provide mechanical, thermal, and geodetic parameters of the Moon that are strongly related to the internal structure. We discuss the functionality required for future geophysical observations of the Moon, including the development of the central station that will be used commonly by different payloads.

Can the Standard Configuration of a Cardiac Monitor Lead to Medical Errors under a Stress Induction?

The essential factor that enables medical patient monitoring is the vital signs monitor, whereas the key in communication with the monitor is the user interface. The way the data display on the monitors is standard, and it is often not changed; however, vital signs monitors are now configurable. Not all the data have to be displayed concurrently; not all data are necessary at a given moment. There arises a question: is the standard monitor configuration sufficient, or can it lead to mistakes related to delays in perceiving parameter changes? Some researchers argue that mistakes in life-saving activities is not mainly due to medical mistakes but due to poorly designed patient life monitor interfaces, among other reasons. In addition, it should be emphasized that the activity that saves the patient’s life is accompanied by stress, which is often caused by the chaos occurring in the hospital emergency department. This raises the following question: is the standard user interface, which they are used to, still effective under stress conditions? Therefore, our primary consideration is the measure of reaction speed of medical staff, which means the perception of the changes of vital signs on the patient’s monitor, for stress and stressless situations. The paper attempts to test the thesis of the importance of the medical interface and its relation to medical mistakes, extending it with knowledge about the difference in speed of making decisions by the medical staff with regard to the stress stimulus.

A mm-Wave 5G System Architecture With Enhanced-Gain Antenna Solution

A millimeter-wave (mm-wave) system architecture with enhanced-gain antenna solution is proposed for fifth-generation (5G) wireless communications. To enhance the antenna gain, the surface wave currents are converted to constructive far-field radiations through a novel two-stage metallic and dielectric rings. By applying low-profile dielectric ring, the electric near-field distributions of the grounded quarter-wavelength metallic ring are modified to create radiation apertures with appropriate polarization and orientation. The mutual coupling between transmit/receive antennas and cross polarizations is reduced by 7 and 5 dB, respectively, and the gain is enhanced over 4 dB. Low-loss mm-wave transitions are implemented in a standard FR-4 printed circuit board and in an interposer substrate to integrate the active antenna with the rest of the wireless system on a compact universal serial bus (USB)-interface platform. To evaluate the interposer package and define the output power of the embedded 60-GHz RF IC, an evaluation module with a standard WR-15 waveguide interface is designed and implemented. A prototype of the architecture, which is entirely realized using low-cost organic substrates, is presented and evaluated by experiments. Excellent correlations are achieved between simulations and measurements, demonstrating more than 25 dBm of equivalent isotropically radiated power (EIRP) over the unlicensed 60-GHz frequency band.

Self-powered SECE piezoelectric energy harvesting induced by shock excitations for sensor supply

The article studies the piezoelectric frequency up-converted energy harvester endowed with an SP-SECE (self-powered synchronized electric charge extraction) interface circuit. The harvester device comprises a piezoelectric cantilever beam whose tip magnet is impulsively excited by another magnet fixed on a rotating plate. Energy is therefore harvested by resonant vibration of a beam excited at certain discrete driving frequencies. Three aspects are discussed here, including the frequency up-conversion for conditionally resonant power, electrically induced damping for matching impedance and reducing power ripples, and SP-SECE’s implementation for power extraction under shock excitations. Precisely, a theoretical model based on the Fourier decomposition of magnetic force is developed for realizing the phenomenon of frequency up-conversion. The SECE electrically induced damping is derived by considering the conversion of energy to electricity in analogy to the dissipation process of a linear mechanical damper. In addition, a novel electronic breaker is implemented for reducing the switching delay effect and enhancing the range of operating voltage. Finally, two experiments are prepared for performance evaluation. The results show the good agreement between the theoretical predictions and the experimental observations. Further, the first one with parameters close to the impedance matching criterion confirms the SECE power outperforms that based on the standard interface. The second one with the SECE electrically induced damping larger than the mechanical damping, the power ripples observed in the SECE case are much more suppressed than that based on the standard interface. Thus, the properties of load-independence and low power fluctuations make the SECE-based frequency up-converted harvester superior in powering sensor nodes operated at around 2–5 volt.

Modular hydronic subsystem models for testing and improving control algorithms of air-handling units

To reduce the energy consumption of building energy systems, efficient and well-tuned control strategies are needed. However, developing and benchmarking control strategies is a challenging task. Here, simulation-based controller tuning and testing is beneficial and more cost-efficient compared to experiments. However, generating a model for this purpose is time-consuming and profound expert knowledge is needed. An approach to reduce the modeling effort is to divide the overall system into frequently used subsystems and develop one model for each type of subsystem. In this paper, we present modular models for frequently used hydronic subsystems in air-handling units (AHU). The models are implemented in the modeling language Modelica with a high level of detail and provide a standardized connection interface to different controller models for testing and tuning. The developed subsystem models are validated using measured data of a real-world air-handling unit. The results show that the models have nearly the same static and dynamic behavior as the real system. The mean absolute percentage error (MAPE) between the simulation and measured data is in the range of 0.14% to 11.3% for all compared sensor values. In two case studies, the usage of the models for controller testing and tuning is demonstrated: the first case study deals with the tuning of a PI controller, and in the second case study we compare two control strategies regarding the control quality and energy consumption.

Discrete analysis of Schwarz waveform relaxation for a diffusion reaction problem with discontinuous coefficients

In this paper, we investigate the effect of the space and time discretisation on the convergence properties of Schwarz Waveform Relaxation (SWR) algorithms. We consider a reaction-diffusion problem with discontinuous coefficients discretised on two non-overlapping domains with several numerical schemes (in space and time). A methodology to determine the rate of convergence of the classical SWR method with standard interface conditions (Dirichlet-Neumann or Robin-Robin) accounting for discretisation errors is presented. We discuss how such convergence rates differ from the ones derived at a continuous level (i.e. assuming an exact discrete representation of the continuous problem). In this work we consider a second-order finite difference scheme and a finite volume scheme based on quadratic spline reconstruction in space, combined with either a simple backward Euler scheme or a two-step “Padé” scheme (resembling a Diagonally Implicit Runge Kutta scheme) in time. We prove those combinations of space-time schemes to be unconditionally stable on bounded domains. We illustrate the relevance of our analysis with specifically designed numerical experiments.

Workflow Integration of Research AI Tools into a Hospital Radiology Rapid Prototyping Environment.

The field of artificial intelligence (AI) in medical imaging is undergoing explosive growth, and Radiology is a prime target for innovation. The American College of Radiology Data Science Institute has identified more than 240 specific use cases where AI could be used to improve clinical practice. In this context, thousands of potential methods are developed by research labs and industry innovators. Deploying AI tools within a clinical enterprise, even on limited retrospective evaluation, is complicated by security and privacy concerns. Thus, innovation must be weighed against the substantive resources required for local clinical evaluation. To reduce barriers to AI validation while maintaining rigorous security and privacy standards, we developed the AI Imaging Incubator. The AI Imaging Incubator serves as a DICOM storage destination within a clinical enterprise where images can be directed for novel research evaluation under Institutional Review Board approval. AI Imaging Incubator is controlled by a secure HIPAA-compliant front end and provides access to a menu of AI procedures captured within network-isolated containers. Results are served via a secure website that supports research and clinical data formats. Deployment of new AI approaches within this system is streamlined through a standardized application programming interface. This manuscript presents case studies of the AI Imaging Incubator applied to randomizing lung biopsies on chest CT, liver fat assessment on abdomen CT, and brain volumetry on head MRI.

Resolving isobaric interferences in direct infusion tandem mass spectrometry.

RationaleThe co‐fragmentation of precursors in direct infusion (DI) tandem high‐resolution mass spectrometry (HRMS) can complicate the fragment spectra and consequently lead to false hits during compound identification.MethodsThe method herein described, termed IQAROS (incremental quadrupole acquisition to resolve overlapping spectra), modulates the intensities of precursors and fragments by stepwise movement of the quadrupole isolation window over the mass‐to‐charge (m/z) range of the precursors. The modulated signals are then deconvoluted by a linear regression model to reconstruct the fragment spectra with less interference. The hardware to demonstrate the use of IQAROS was an orbitrap with electrospray ionization (ESI) or secondary electrospray ionization (SESI), although the method can also be applied to other ionization techniques or mass analyzers.ResultsAssessing the performance of IQAROS with isobaric standards revealed that the reconstructed fragment spectra match with spectra acquired from the pure standards and that more compounds were correctly identified compared with the classical approach with the quadrupole centered at the m/z value of the precursor of interest. Moreover, the strength of IQAROS is exemplified by the identification of two isobaric biomarkers directly from a breath sample with SESI‐HRMS.ConclusionsWith IQAROS, cleaner fragment spectra of co‐fragmenting isobars during DI‐HRMS analysis can be obtained. IQAROS can easily be set up by the standard graphical user interface of the instrument. Therefore, it facilitates the characterization of features of interest in samples analyzed by DI‐HRMS, for example, in high‐throughput or real‐time metabolomics.

Systems Modeling Language (SysML v2) Support for Digital Engineering

ABSTRACTThe OMG Systems Modeling Language™ (SysML®) was adopted in 2006 and has been used by many organizations to support their efforts to transition to a model‐based systems engineering (MBSE) approach. SysML v2 is the next generation Systems Modeling Language and is intended to address many of the limitations of SysML v1. This paper highlights how the SysML v2 language and the new standard Application Programming Interface (API) can enable MBSE and digital engineering.SysML v2 is being developed by the SysML v2 Submission Team (SST) in response to requirements issued by the Object Management Group (OMG). The final submission to the OMG is planned for 2022. The draft SysML v2 specifications and the open‐source SysML v2 pilot implementation can be found at https://github.com/Systems-Modeling.

Research and Implementation of Embedded Real-time Target Detection Algorithm Based on Deep Learning

In view of the poor detection effect and low robustness of traditional target detection algorithms, this paper studies target detection algorithms based on deep learning, and designs an embedded real-time target detection evaluation board based on AI chip. It is realized that most of the common deep convolutional neural network models represented by YOLOv3 can be transplanted to the board. Although there is a certain accuracy loss within the acceptable range, this implementation achieves a faster speed to meet the needs of real-time detection. Meanwhile, a complete set of video component calling and network transmission schemes are proposed. By designing a unified standard interface accessed to the program framework, the implementation board can be flexibly extended to meet the needs of various artificial intelligence applications.

Conformance evaluation of the top‐100 Ethereum token smart contracts with Ethereum Request for Comment‐20 functional specifications

This study is an attempt to evaluate the compliance problem regarding the current status of the establishment of agreed-upon interfaces for tokens, which are the most important type of applications of the Ethereum blockchain. The authors analysed the existing application programming interface standard interface called Ethereum Request for Comment 20 (ERC-20), proposed functional ERC-20 specifications, and evaluated the real-world token smart contracts that have been deployed and used for transactions on a blockchain. For the evaluation, the authors developed an automatic tool with a test suite based on the proposed functional specifications. The authors' experiment revealed that no top-100 market capitalization token smart contracts turned out to agree perfectly based on the functional specifications. In addition, the authors found the de facto standard behaviour deduced through testing with the functional specifications and suggested a possible countermeasure for the compliance problem in dealing with multiple tokens together.

CSDMS: a community platform for numerical modeling of Earth surface processes

Abstract. Computational modeling occupies a unique niche in Earth and environmental sciences. Models serve not just as scientific technology and infrastructure but also as digital containers of the scientific community's understanding of the natural world. As this understanding improves, so too must the associated software. This dual nature – models as both infrastructure and hypotheses – means that modeling software must be designed to evolve continually as geoscientific knowledge itself evolves. Here we describe design principles, protocols, and tools developed by the Community Surface Dynamics Modeling System (CSDMS) to promote a flexible, interoperable, and ever-improving research software ecosystem. These include a community repository for model sharing and metadata, interface and ontology standards for model interoperability, language-bridging tools, a modular programming library for model construction, modular software components for data access, and a Python-based execution and model-coupling framework. Methods of community support and engagement that help create a community-centered software ecosystem are also discussed.

GloMPO (Globally Managed Parallel Optimization): a tool for expensive, black-box optimizations, application to ReaxFF reparameterizations

In this work we explore the properties which make many real-life global optimization problems extremely difficult to handle, and some of the common techniques used in literature to address them. We then introduce a general optimization management tool called GloMPO (Globally Managed Parallel Optimization) to help address some of the challenges faced by practitioners. GloMPO manages and shares information between traditional optimization algorithms run in parallel. We hope that GloMPO will be a flexible framework which allows for customization and hybridization of various optimization ideas, while also providing a substitute for human interventions and decisions which are a common feature of optimization processes of hard problems. GloMPO is shown to produce lower minima than traditional optimization approaches on global optimization test functions, the Lennard-Jones cluster problem, and ReaxFF reparameterizations. The novel feature of forced optimizer termination was shown to find better minima than normal optimization. GloMPO is also shown to provide qualitative benefits such a identifying degenerate minima, and providing a standardized interface and workflow manager.

Effect of Test Interface on Respiratory Muscle Activity and Pulmonary Function During Respiratory Testing in Healthy Adults: A Pilot Study.

The mouthpiece is the standard interface for spirometry tests. Although the use of a mouthpiece can be challenging for patients with orofacial weakness, maintaining a proper seal with a facemask can be an issue for healthy individuals during forceful efforts. We compared respiratory muscle activity and tests using a mouthpiece and facemask in healthy adults to investigate whether they can be used interchangeably. In this observational study, subjects (n=12) completed forced vital capacity, maximal respiratory pressure, and peak cough flow with a mouthpiece and facemask. Root mean square values of the genioglossus, diaphragm, scalene, and sternocleidomastoid were compared between conditions. When switching from a mouthpiece to a facemask, significantly higher values were seen for peak cough flow (average bias= -54.36 L/min, p<0.05) and the difference seen with MEP and MIP were clinically significant (average bias: MEP=27.33, MIP=-5.2). Additionally, submental activity was significantly greater when MIP was conducted with a mouthpiece. No significant differences were seen in respiratory muscle activity during resting breathing or spirometry. There are clinically significant differences with cough and MEP tests and neck muscles are activated differently based on interface. Considering the small sample size, our findings suggest a facemask may be used to complete some PFTs.

How can we Develop a Standard Interface that easily Integrates with Hl7, boosting EHR Interoperability?

Background: It appears that a systematic strategy that includes the basic underpinnings of health care, from systems and technologies to clinical understanding and workflow processes, is required to achieve the next great leap in improving quality and safety. To make meaningful progress, health-care systems integration is essential. However, to provide interoperability in EHR, systems must support all versions of HL7.Software companies and healthcare organisations are still having trouble integrating HL7 with multiple interfaces. Thus, a standard interface or platform is required that easily integrates with HL7 boosting EHR interoperability. Methods: Basic Modelling Interface (BMI) interoperability standards will be the focus of this research. The research plan proposes a qualitative research approach that includes clinicians’ interview and a panel discussion to characterise the information flow models. Qualitative research using a thematic analysis of semi structured interviews will be conducted in the proposed research plan. Results: Gaining the HL7 standard is insufficient for integrating EHR with diverse apps or software in use, thus clinicians' willingness to adopt a common interface is critical. Medical practitioners and software vendors agreement required to develop an API that tackles HL7 integration issues and EHR interoperability. Planning techniques for dealing with HL7 issues and doing coordinated testing can help identify and install HL7 standard interfaces successfully. Conclusions: The proposed research plan will help us to create a standard interface for HL7 integration which will benefit clinicians, healthcare professionals, and groups such as patients, healthcare authorities, and EHR vendors. Lastly, reducing or eliminating healthcare concerns will help the economy, ecosystem, and society in both concrete and qualitative ways.

Technical considerations regarding the modelling and implementation of a Web Dynpro application

Developed by SAP (System Application and Products) concern, the new Dynpro Web technology aims to create scalable business applications that comply with standardized user interface principles. This paper highlights how a Web Dynpro application consisting of several components can be modeled and implemented in the ABAP (Advanced Business Application Programming) language using a component binding technique based on the concept of MVC (Modell-View-Controller). All these aspects are presented through a case study, developed and implemented on the SAP NetWeaver integration platform version 7.0.

DeepImageTranslator: A free, user-friendly graphical interface for image translation using deep-learning and its applications in 3D CT image analysis.

The advent of deep-learning has set new standards in an array of image translation applications. At present, the use of these methods often requires computer programming experience. Non-commercial programs with graphical interface usually do not allow users to fully customize their deep-learning pipeline. Therefore, our primary objective is to provide a simple graphical interface that allows researchers with no programming experience to easily create, train, and evaluate custom deep-learning models for image translation. We also aimed to test the applicability of our tool in CT image semantic segmentation and noise reduction. DeepImageTranslator was implemented using the Tkinter library, the standard Python interface to the Tk graphical user interface toolkit; backend computations were implemented using data augmentation packages such as Pillow, Numpy, OpenCV, Augmentor, Tensorflow, and Keras libraries. Convolutional neural networks (CNNs) were trained using DeepImageTranslator. The effects of data augmentation, deep-supervision, and sample size on model accuracy were also systematically assessed. The DeepImageTranslator a simple tool that allows users to customize all aspects of their deep-learning pipeline, including the CNN, training optimizer, loss function, and the types of training image augmentation scheme. We showed that DeepImageTranslator can be used to achieve state-of-the-art accuracy and generalizability in semantic segmentation and noise reduction. Highly accurate 3D segmentation models for body composition can be obtained using training sample sizes as small as 17 images. In conclusion, an open-source deep-learning tool for accurate image translation with a user-friendly graphical interface was presented and evaluated. This standalone software can be downloaded at: https://sourceforge.net/projects/deepimagetranslator/.