Access Interface Research Articles

SPADA: A Toolbox of Designing Soft Pneumatic Actuators for Shape Matching Based on Surrogate Modeling.

Soft pneumatic actuators (SPAs) produce motions for soft robots with simple pressure input, however, they require to be appropriately designed to fit the target application. Available design methods employ kinematic models and optimization to estimate the actuator response and the optimal design parameters to achieve a target actuator's shape. Within SPAs, bellow SPAs excel in rapid prototyping and large deformation, yet their kinematic models often lack accuracy due to the geometry complexity and the material nonlinearity. Furthermore, existing shape-matching algorithms are not providing an end-to-end solution from the desired shape to the actuator. In addition, despite the availability of computational design pipelines, an accessible and user-friendly toolbox for direct application remains elusive. This article addresses these challenges, offering an end-to-end shape-matching design framework for bellow SPAs to streamline the design process, and the open-source toolbox SPADA (Soft Pneumatic Actuator Design frAmework) implementing the framework with a graphic user interface for easy access. It provides a kinematic model grounded on a modular design to improve accuracy, finite element method (FEM) simulations, and piecewise constant curvature (PCC) approximation. An artificial neural network-trained surrogate model, based on FEM simulation data, is trained for fast computation in optimization. A shape-matching algorithm, merging three-dimensional (3D) PCC segmentation and a surrogate model-based genetic algorithm, identifies optimal actuator design parameters for desired shapes. The toolbox, implementing the proposed design framework, has proven its end-to-end capability in designing actuators to precisely match two-dimensional shapes with root-mean-squared-errors of 4.16, 2.70, and 2.51 mm, and demonstrating its potential by designing a 3D deformable actuator.

ZOSPy, a python package for ray tracing simulations

Aims/Purpose: Ray tracing simulations with optical models of the eye are used for a wide range of applications, such as designing intra‐ocular lenses. These simulations are often performed in OpticStudio (Ansys/Zemax), a piece of software with powerful analytical tools. However, OpticStudio largely relies on manual user interaction, limiting its ability to analyse a large number of eyes. While OpticStudio has an Application Programming Interface (the ZOS‐API) that allows for automation, using this API requires in‐depth programming knowledge. Thus, we developed ZOSPy, an open source library that provides an accessible interface to the ZOS‐API which allows users to directly focus on the optical modelling and analyses.Methods: ZOSPy is a python‐based wrapper around the official ZOS‐API, which provides full access to the API and enables full control of OpticStudio. In addition, we facilitated the usage of the API by simplifying initiation of the API connection, adding functions that fully wrap analyses and including auto‐completion in Python. Finally, it provides unit‐tests that enable validation of different OpticStudio versions.Results: ZOSPy has been used to facilitate ray tracing in several studies. One study used ZOSPy to assess the relation between the anatomy and Negative Dysphotopsia. by determining retinal illumination profiles and [1] In another study, ZOSPy was used to show that the extent of an intra‐ocular tumour can be erroneously overestimated by transillumination during surgery [2].Conclusions: ZOSPy allows users to omit complex coding and directly focus on optical modelling and analyses, which reduces the threshold for using ray tracing simulation in (ophthalmic) research.

Data Lakes: A Survey of Functions and Systems

Data lakes are becoming increasingly prevalent for big data management and data analytics. In contrast to traditional ‘schema-on-write’ approaches such as data warehouses, data lakes are repositories storing raw data in its original formats and providing a common access interface. Despite the strong interest raised from both academia and industry, there is a large body of ambiguity regarding the definition, functions and available technologies for data lakes. A complete, coherent picture of data lake challenges and solutions is still missing. This survey reviews the development, architectures, and systems of data lakes. We provide a comprehensive overview of research questions for designing and building data lakes. We classify the existing approaches and systems based on their provided functions for data lakes, which makes this survey a useful technical reference for designing, implementing and deploying data lakes. We hope that the thorough comparison of existing solutions and the discussion of open research challenges in this survey will motivate the future development of data lake research and practice.

Quality assurance framework for rapid automatic analysis deployment in medical imaging

PurposeAutomatic image analysis algorithms have an increasing role in clinical quality assurance (QA) in medical imaging. Although the implementation of QA calculation algorithms may be straightforward at the development level, actual deployment of a new method to clinical routine may require substantial additional effort from supporting services. We sought to develop a multimodal system that enables rapid implementation of new QA analysis methods in clinical practice. MethodsThe QA system was built using freely available open-source software libraries. The included features were results database, database interface, interactive user interface, e-mail error dispatcher, data processing backend, and DICOM server. An in-house database interface was built, providing the developers of analyses with simple access to the results database. An open-source DICOM server was used for image traffic and automatic initiation of modality-specific QA image analyses. ResultsThe QA framework enabled rapid adaptation of new analysis methods to automatic image processing workflows. The system provided online data review via an easily accessible user interface. In case of deviations, the system supported simultaneous review of the results for the user and QA expert to trigger corrective actions. In particular, embedded error thresholds, trend analyses, and error-feedback channels were provided to facilitate continuous monitoring and to enable pre-emptive corrective actions. ConclusionAn effective and novel QA framework incorporating easy adaptation and scalability to automated image analysis methods was developed. The framework provides an efficient and responsive web-based tool to manage the normal operation, trends, errors, and abnormalities in medical image quality.

NEP+: A Human-Centered Framework for Inclusive Human-Machine Interaction Development.

This article presents the Network Empower and Prototyping Platform (NEP+), a flexible framework purposefully crafted to simplify the process of interactive application development, catering to both technical and non-technical users. The name "NEP+" encapsulates the platform's dual mission: to empower the network-related capabilities of ZeroMQ and to provide software tools and interfaces for prototyping and integration. NEP+ accomplishes this through a comprehensive quality model and an integrated software ecosystem encompassing middleware, user-friendly graphical interfaces, a command-line tool, and an accessible end-user programming interface. This article primarily focuses on presenting the proposed quality model and software architecture, illustrating how they can empower developers to craft cross-platform, accessible, and user-friendly interfaces for various applications, with a particular emphasis on robotics and the Internet of Things (IoT). Additionally, we provide practical insights into the applicability of NEP+ by briefly presenting real-world user cases where human-centered projects have successfully utilized NEP+ to develop robotics systems. To further emphasize the suitability of NEP+ tools and interfaces for developer use, we conduct a pilot study that delves into usability and workload assessment. The outcomes of this study highlight the user-friendly features of NEP+ tools, along with their ease of adoption and cross-platform capabilities. The novelty of NEP+ fundamentally lies in its holistic approach, acting as a bridge across diverse user groups, fostering inclusivity, and promoting collaboration.

QLTI-08. THE COLUMBIA NEURO-ONCOLOGY RESEARCH DASHBOARD: A WEB-BASED TOOL TO ASSESS CLINICAL TRIAL RECRUITMENT AND ACCRUAL METRICS

Abstract BACKGROUND Insufficient trial participation is a recognized barrier to drug development. Research has focused on patient and physician-associated factors, yet few institutions assess the impact of trial availability, referral patterns, and patient eligibility. Screening logs provide a rough estimate of candidate pools but tell us nothing about patients who are not screened, let alone why. To better understand site-specific barriers and effectively assess efforts to overcome them, real-time, data-driven metrics are essential. METHODS To address this need, we created The Columbia Neuro-Oncology Clinical Research Dashboard (CRD), a web-based tool designed to capture all patients presenting to our faculty practice with newly diagnosed or recurrent CNS tumors and track their participation -- or lack thereof -- in interventional trials. From 7/2022 - 9/2022, we experimented with several iterations of the CRD, adjusting the platform and variables in response to user feedback. To pilot the final design, we started with a limited sample of high-grade glioma patients seen at Columbia University Irving Medical Center's Neuro-Oncology Faculty Practice from 9/1/2022 - 1/1/2023. During this period, 62 patients were tracked, allowing for further refinements to improve functionality and data capture. When populated, the CRD was easily queried for important quality improvement metrics including accrual rates, time from presentation to study initiation and grounds for screen failure. It also captured the percentage of patients who were not offered a trial and the cited reasons. Inclusion of demographics and referral patterns provided additional dimensions to the data. NEXT STEPS: The CRD has met its preliminary aims. It provides a user friendly and accessible interface for data capture. With appropriate staffing and implementation processes in place, it has real potential to inform our efforts to improve patient accrual and diversity with real-time metrics. Subsequent efforts will focus on these aspects of the project.

Getting it Together: Combining information about archaeological sites and artefacts in ARIADNE

This article discusses the situation that exists in several European countries, whereby information about archaeological sites and monuments, and that about finds recorded by members of the public (primarily via metal detecting), is held in entirely separate databases. This prevents heritage management decisions being taken with full awareness of known archaeology, and makes research that seeks to draw on multiple information resources difficult. The article demonstrates how the European ARIADNE e-infrastructure has facilitated the integration of large-scale artefact and site information. Over one million records from the British Museum Portable Antiquities Scheme database and over one million records for English sites, monuments, and grey literature have been integrated in an open access interface for the first time, permitting entirely new research questions to be addressed.

DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research.

The exponential growth in scholarly publications necessitates advanced tools for efficient article retrieval, especially in interdisciplinary fields where diverse terminologies are used to describe similar research. Traditional keyword-based search engines often fall short in assisting users who may not be familiar with specific terminologies. To address this, we present a knowledge graph based paper search engine for biomedical research to enhance the user experience in discovering relevant queries and articles. The system, dubbed DiscoverPath, employs Named Entity Recognition (NER) and part-of-speech (POS) tagging to extract terminologies and relationships from article abstracts to create a KG. To reduce information overload, DiscoverPath presents users with a focused subgraph containing the queried entity and its neighboring nodes and incorporates a query recommendation system enabling users to iteratively refine their queries. The system is equipped with an accessible Graphical User Interface that provides an intuitive visualization of the KG, query recommendations, and detailed article information, enabling efficient article retrieval, thus fostering interdisciplinary knowledge exploration. DiscoverPath is open-sourced at https://github.com/ynchuang/DiscoverPath with a demo video at Youtube.

BatTool: projecting bat populations facing multiple stressors using a demographic model

Bats provide ecologically and agriculturally important ecosystem services but are currently experiencing population declines caused by multiple environmental stressors, including mortality from white-nose syndrome and wind energy development. Analyses of the current and future health and viability of these species may support conservation management decision making. Demographic modeling provides a quantitative tool for decision makers and conservation managers to make more informed decisions, but widespread adoption of these tools can be limited because of the complexity of the mathematical, statistical, and computational components involved in implementing these models. In this work, we provide an exposition of the BatTool R package, detailing the primary components of the matrix projection model, a publicly accessible graphical user interface (https://rconnect.usgs.gov/battool) facilitating user-defined scenario analyses, and its intended uses and limitations (Wiens et al., US Geol Surv Data Release 2022; Wiens et al., US Geol Surv Softw Release 2022). We present a case study involving wind energy permitting, weighing the effects of potential mortality caused by a hypothetical wind energy facility on the projected abundance of four imperiled bat species in the Midwestern United States.

Organization of Distance Learning in Google Meet in Modern Conditions

The aim of the article is to analyze the key aspects of distance learning organization on the Google Meet platform through the prism of modern digital educational trends and globalization challenges. The study is based on pedagogical knowledge theoretical methods (analysis and synthesis), dialectical and systematic method, as well as on the SWOT-analysis opportunities. In results it is underscored several key strengths, including user-friendly features, robust security measures backed by Google Corporation, an accessible interface, and valuable functionalities such as the digital whiteboard application that empowers educators to illustrate educational content and live subtitles that enhance inclusivity. However, it is worth noting that Google Meet's compatibility issues with certain devices pose potential challenges in educational settings. Addressing these limitations presents an opportunity to ensure the continued effectiveness of Google Meet as the primary digital conduit for distance learning. The scientific novelty of the study reveals that the platform offers distinct advantages and notable drawbacks, all of which merit careful consideration when planning educational activities. For example, vulnerabilities are the difficulties in launching on certain mobile devices, the limitation of the free version. The conclusions summarize the results of the research and note that the important advantages of the service are the support of the Google Corporation, the accessibility of the interface and the convenience of using digital tools. It is proposed to further develop the integration of the service with the company's products.

BSEMS-A Blockchain-Based Smart Energy Measurement System.

The modern world's increasing reliance on automated systems for everyday tasks has resulted in a corresponding rise in power consumption. The demand is further augmented by increased sales of electric vehicles, smart cities, smart transportation, etc. This growing dependence underscores the critical necessity for a robust smart energy measurement and management system to ensure a continuous and efficient power supply. However, implementing such a system presents a set of challenges, particularly concerning the transparency, security, and trustworthiness of data storage and retrieval. Blockchain technology offers an innovative solution in the form of a distributed ledger, which guarantees secure and transparent transaction storage and retrieval. This research introduces a blockchain-based system, utilising Hyperledger Fabric and smart contracts, designed for the secure storage and retrieval of consumers' energy consumption data. Finally, a user-friendly web portal was designed and developed using the node.js framework, offering an accessible and intuitive interface to monitor and manage energy consumption effectively.

MANGEM: A web app for multimodal analysis of neuronal gene expression, electrophysiology, and morphology

Single-cell techniques like Patch-seq have enabled the acquisition of multimodal data from individual neuronal cells, offering systematic insights into neuronal functions. However, these data can be heterogeneous and noisy. To address this, machine learning methods have been used to align cells from different modalities onto a low-dimensional latent space, revealing multimodal cell clusters. The use of those methods can be challenging without computational expertise or suitable computing infrastructure for computationally expensive methods. To address this, we developed a cloud-based web application, MANGEM (multimodal analysis of neuronal gene expression, electrophysiology, and morphology). MANGEM provides a step-by-step accessible and user-friendly interface to machine learning alignment methods of neuronal multimodal data. It can run asynchronously for large-scale data alignment, provide users with various downstream analyses of aligned cells, and visualize the analytic results. We demonstrated the usage of MANGEM by aligning multimodal data of neuronal cells in the mouse visual cortex.

Pre‐trained language models: What do they know?

AbstractLarge language models (LLMs) have substantially pushed artificial intelligence (AI) research and applications in the last few years. They are currently able to achieve high effectiveness in different natural language processing (NLP) tasks, such as machine translation, named entity recognition, text classification, question answering, or text summarization. Recently, significant attention has been drawn to OpenAI's GPT models' capabilities and extremely accessible interface. LLMs are nowadays routinely used and studied for downstream tasks and specific applications with great success, pushing forward the state of the art in almost all of them. However, they also exhibit impressive inference capabilities when used off the shelf without further training. In this paper, we aim to study the behavior of pre‐trained language models (PLMs) in some inference tasks they were not initially trained for. Therefore, we focus our attention on very recent research works related to the inference capabilities of PLMs in some selected tasks such as factual probing and common‐sense reasoning. We highlight relevant achievements made by these models, as well as some of their current limitations that open opportunities for further research.This article is categorized under: Fundamental Concepts of Data and Knowledge > Key Design Issues in Data Mining Technologies > Artificial Intelligence

Internet of things enabled parking management system using long range wide area network for smart city

As the Internet of Things (IoT) evolves, it paves the way for vital smart city applications, with the Smart Parking Management System (SPMS) standing as a prime example. This research introduces a novel IoT-driven SPMS that leverages Long Range Wide Area Network (LoRaWAN) technology, termed as IoT-SPMS-LoRaWAN, to surmount typical restrictions related to communication range, energy usage, and implementation cost seen in traditional systems. IoT-SPMS-LoRaWAN features intelligent sensing nodes that incorporate an Arduino UNO microcontroller and two sensors—a triaxial magnetic sensor and a waterproof ultrasonic sensor. These components collaboratively detect vehicle occupancy and transmit this data to the server via a LoRaWAN gateway. Notably, the integration of LoRa technology enables extensive network coverage and energy efficiency. Users are provided with real-time updates on parking availability via the accessible AllThingsTalk Maker graphical user interface. Additionally, the system operates independently, sustained by a solar-powered rechargeable battery. Practical testing of IoT-SPMS-LoRaWAN under various scenarios validates its merits in terms of functionality, ease of use, reliable data transmission, and precision. Its urban implementation is expected to alleviate traffic congestion, optimize parking utilization, and elevate awareness about available parking spaces among users. Primarily, this study enriches the realm of smart city solutions by enhancing the efficiency of parking management and user experience via IoT.

Modelling of Pollutant Transport in Yamuna River from the Najafgarh Drain, NCT Delhi Using Matlab Software

When the river Yamuna leaves the National Capital Territory of Delhi, its situation further deteriorates. Despite accounting for only 1% of the river’s overall catchment area, this region is responsible for more than half of the pollutants discovered in the Yamuna. The river Yamuna, on the other hand, is Delhi’s only natural resource for maintaining all forms of life. The Yamuna River is currently experiencing a significant level of pollution problem, and in order to control pollution in the Yamuna River, continual analysis is essential. The Yamuna River is contaminated by the discharge of untreated municipal sewage and industrial effluent through seven major drains: Najafgarh, Yamunapur, Sen Nursing Home, Barathpula, Maharani Bagh, Kalkaji, and Tuglakabad. In terms of people and chemicals, continuous sampling takes time and money. The primary objective of this study is to analyse the wastewater samples collected by sub-drains and STP’s to predict the pollutant transportation in river Yamuna from Najafgarh Drain. The study focusses on the only pollutant, i.e., Biochemical Oxygen Demand from the starting point to after the confluence of Najafgarh Drain into river Yamuna. The prediction is to be done by using MATLAB software. This study would help to identify the main sources of sub-drains which are polluting Najafgarh Drain and eventually the river Yamuna. This shows how MATLAB may be used to calculate the pollution load caused by organic waste in the Yamuna River as it flows through Delhi, India’s National Capital Territory. The model numerically solves a series of differential equations to simulate the dissolved oxygen and biochemical oxygen demand parameters in two dimensions. MATLAB is an interactive programming language that may be used to develop algorithms, graphics, and user interfaces in other computer languages. MATLAB helps estimate future water quality using present data, which saves time, labour, and other costs associated with the continuous study. There are various software programmes available in the market for predicting river water quality, however, MATLAB GUI provides an accessible and convenient user interface (Graphical User Interface).

Use of carbon-13 NMR to identify known natural products by querying a nuclear magnetic resonance database-An assessment.

The quick identification of known organic low molecular weight compounds, also known as structural dereplication, is a highly important task in the chemical profiling of natural resource extracts. To that end, a method that relies on carbon-13 nuclear magnetic resonance (NMR) spectroscopy, elaborated in earlier works of the author's research group, requires the availability of a dedicated database that establishes relationships between chemical structures, biological and chemical taxonomy, and spectroscopy. The construction of such a database, called acd_lotus, was reported earlier, and its usefulness was illustrated by only three examples. This article presents the results of structure searches carried out starting from 58 carbon-13 NMR data sets recorded on compounds selected in the metabolomics section of the biological magnetic resonance bank (BMRB). Two compound retrieval methods were employed. The first one involves searching in the acd_lotus database using commercial software. The second one operates through the freely accessible web interface of the nmrshiftdb2 database, which includes the compounds present in acd_lotus and many others. The two structural dereplication methods have proved to be efficient and can be used together in a complementary way.

Exploring user reviews to identify accessibility problems in applications for autistic users

The Google Play Store provides various user reviews that can provide information about user experience, usability, and accessibility. Despite multiple studies addressing these reviews’ importance and contributions to improving interactive systems, accessibility for users with Autism Spectrum Disorder (ASD) is still little discussed in this context. Considering the potential of user reviews, this article presents a textual analysis of reviews extracted from eight educational applications available in Portuguese with a focus on autistic children, namely: “ABC Autismo”, “Aprendendo com Biel e seus amigos”, “AutApp Autismo”, “Autismo projeto integrar”, “Jade Autismo”, “Matraquinha”, “OTO (Olhar Tocar Ouvir)” and “Teacch.me”. We conducted an analysis based on the Guidelines for Accessible Interfaces for People with Autism (GAIA) and the BBC Mobile Accessibility Guidelines to classify user reviews.

Managing data replication and distribution in the fog with FReD

SummaryThe heterogeneous, geographically distributed infrastructure of fog computing poses challenges in data replication, data distribution, and data mobility for fog applications. Fog computing is still missing the necessary abstractions to manage application data, and fog application developers need to re‐implement data management for every new piece of software. Proposed solutions are limited to certain application domains, such as the IoT, are not flexible in regard to network topology, or do not provide the means for applications to control the movement of their data. In this paper, we present FReD, a data replication middleware for the fog. FReD serves as a building block for configurable fog data distribution and enables low‐latency, high‐bandwidth, and privacy‐sensitive applications. FReD is a common data access interface across heterogeneous infrastructure and network topologies, provides transparent and controllable data distribution, and can be integrated with applications from different domains. To evaluate our approach, we present a prototype implementation of FReD and show the benefits of developing with FReD using three case studies of fog computing applications.

An innovative interactive mapping tool to present research results: example of a terroir study in the context of climate change

Over the past decade, Story Map applications have been developed throughout the world under the impetus of software developers in the fields of visualization (Google Earth, Neatline, TripLine) and geographic information systems (ESRI, Knight Lab). These Story Map web applications allow information to be presented, shared and distributed in the form of interactive maps combined with images, text and audiovisual content. Using these tools to transfer the results of research projects is an innovative approach that can be highly effective, with their ease of access and user-friendly interface encouraging users to explore the data. Such a tool has been used to supplement scientific papers reporting the results of a research project on terroir and climate change in the Bordeaux region. The link to access it is https://www-iuem.univ-brest.fr/wapps/letg/adviclim/BDX/#.

SEAHORS: Spatial Exploration of ArcHaeological Objects in R Shiny

This paper presents SEAHORS, an R shiny application available as an R package, dedicated to the intra-site spatial analysis of piece-plotted archaeological remains. This open-source script generates 2D and 3D scatter and density plots for archaeological objects located with cartesian coordinates. Many different GIS software already exist for this, but they mostly require specific skills and training to be used and are rarely designed for the particular needs of archaeological applications. The goal of SEAHORS is to make the two and three-dimensional intra-site spatial exploration of archaeological data as user-friendly as possible, in order to give the opportunity to researchers not familiar with GIS and R software to utilise such approaches. SEAHORS has an easily accessible interface and can import data from text and Excel files (.csv and .xls/xlsx respectively) without preformatting. The application includes functions to concatenate columns and to merge databases, for example when spatial data (XYZ coordinates) and analytical data (e.g. taxonomical attribution of faunal remains, typo-technological attributes of artifacts, etc.) are stored in separate files. SEAHORS can generate five types of plots: 3D, 2D and density plots, as well as 2D plots by slices (i.e. subdivisions according to a third dimension) and 2D plots with a modification of the angle of projection (i.e. to explore spatial organization without the constraints of the field grid orientation). SEAHORS has visualization tools with several sorting and formatting options (color, size, etc.) applicable to coordinates and all possible analytical variables (i.e. levels, spits, identified species, taphonomical alterations, etc.). Orthophotos can also be imported and directly used in the program. The application also allows the grouping of objects into new variables by selecting items on the interactive 2D plots. We present an overview of the application’s functions by using the case study of the Cassenade Paleolithic site (France).