Prototyping Platform Research Articles

A lightweight CORONA-NET for COVID-19 detection in X-ray images.

Since December 2019, COVID-19 has posed the most serious threat to living beings. With the advancement of vaccination programs around the globe, the need to quickly diagnose COVID-19 in general with little logistics is fore important. As a consequence, the fastest diagnostic option to stop COVID-19 from spreading, especially among senior patients, should be the development of an automated detection system. This study aims to provide a lightweight deep learning method that incorporates a convolutional neural network (CNN), discrete wavelet transform (DWT), and a long short-term memory (LSTM), called CORONA-NET for diagnosing COVID-19 from chest X-ray images. In this system, deep feature extraction is performed by CNN, the feature vector is reduced yet strengthened by DWT, and the extracted feature is detected by LSTM for prediction. The dataset included 3000 X-rays, 1000 of which were COVID-19 obtained locally. Within minutes of the test, the proposed test platform's prototype can accurately detect COVID-19 patients. The proposed method achieves state-of-the-art performance in comparison with the existing deep learning methods. We hope that the suggested method will hasten clinical diagnosis and may be used for patients in remote areas where clinical labs are not easily accessible due to a lack of resources, location, or other factors.

Enabling Multicentric Participatory Disease Surveillance for Global Health Enhancement: Viewpoint on Global Flu View.

Participatory surveillance (PS) has been defined as the bidirectional process of transmitting and receiving data for action by directly engaging the target population. Often represented as self-reported symptoms directly from the public, PS can provide evidence of an emerging disease or concentration of symptoms in certain areas, potentially identifying signs of an early outbreak. The construction of sets of symptoms to represent various disease syndromes provides a mechanism for the early detection of multiple health threats. Global Flu View (GFV) is the first-ever system that merges influenza-like illness (ILI) data from more than 8 countries plus 1 region (Hong Kong) on 4 continents for global monitoring of this annual health threat. GFV provides a digital ecosystem for spatial and temporal visualization of syndromic aggregates compatible with ILI from the various systems currently participating in GFV in near real time, updated weekly. In 2018, the first prototype of a digital platform to combine data from several ILI PS programs was created. At that time, the priority was to have a digital environment that brought together different programs through an application program interface, providing a real time map of syndromic trends that could demonstrate where and when ILI was spreading in various regions of the globe. After 2 years running as an experimental model and incorporating feedback from partner programs, GFV was restructured to empower the community of public health practitioners, data scientists, and researchers by providing an open data channel among these contributors for sharing experiences across the network. GFV was redesigned to serve not only as a data hub but also as a dynamic knowledge network around participatory ILI surveillance by providing knowledge exchange among programs. Connectivity between existing PS systems enables a network of cooperation and collaboration with great potential for continuous public health impact. The exchange of knowledge within this network is not limited only to health professionals and researchers but also provides an opportunity for the general public to have an active voice in the collective construction of health settings. The focus on preparing the next generation of epidemiologists will be of great importance to scale innovative approaches like PS. GFV provides a useful example of the value of globally integrated PS data to help reduce the risks and damages of the next pandemic.

The Design and Implementation of an Open-source Programmable Bot for Educational Purposes

The ubiquity and an established framework for using open-source electronics and 3D prototyping platforms have enhanced the ways educational robotics (ER) is introduced. Low entry-level, a wide range of peripheral modules and 3D designs alleviate approaching the subject. Nevertheless, the relative ease such systems aim to provide tends to obscure the underlying machinery and basic principles. In this regard, the present article describes designing and implementing a simple programmable Arduino-based bot with a particular accent on the underpinning principles' exposition.

NeuroBridge: a prototype platform for discovery of the long-tail neuroimaging data.

Open science initiatives have enabled sharing of large amounts of already collected data. However, significant gaps remain regarding how to find appropriate data, including underutilized data that exist in the long tail of science. We demonstrate the NeuroBridge prototype and its ability to search PubMed Central full-text papers for information relevant to neuroimaging data collected from schizophrenia and addiction studies. The NeuroBridge architecture contained the following components: (1) Extensible ontology for modeling study metadata: subject population, imaging techniques, and relevant behavioral, cognitive, or clinical data. Details are described in the companion paper in this special issue; (2) A natural-language based document processor that leveraged pre-trained deep-learning models on a small-sample document corpus to establish efficient representations for each article as a collection of machine-recognized ontological terms; (3) Integrated search using ontology-driven similarity to query PubMed Central and NeuroQuery, which provides fMRI activation maps along with PubMed source articles. The NeuroBridge prototype contains a corpus of 356 papers from 2018 to 2021 describing schizophrenia and addiction neuroimaging studies, of which 186 were annotated with the NeuroBridge ontology. The search portal on the NeuroBridge website https://neurobridges.org/ provides an interactive Query Builder, where the user builds queries by selecting NeuroBridge ontology terms to preserve the ontology tree structure. For each return entry, links to the PubMed abstract as well as to the PMC full-text article, if available, are presented. For each of the returned articles, we provide a list of clinical assessments described in the Section "Methods" of the article. Articles returned from NeuroQuery based on the same search are also presented. The NeuroBridge prototype combines ontology-based search with natural-language text-mining approaches to demonstrate that papers relevant to a user's research question can be identified. The NeuroBridge prototype takes a first step toward identifying potential neuroimaging data described in full-text papers. Toward the overall goal of discovering "enough data of the right kind," ongoing work includes validating the document processor with a larger corpus, extending the ontology to include detailed imaging data, and extracting information regarding data availability from the returned publications and incorporating XNAT-based neuroimaging databases to enhance data accessibility.

Development of Digital-based Visual Learning Media for Physical Education, Sports, and Health for Students with Hearing Impairments

This research focuses on the development of digital-based learning media for individuals with hearing impairments. The aim of this study is to address the challenges faced by deaf learners in accessing and engaging with educational content effectively. The research question guiding this study is: "How can digital learning media be developed to cater to the specific needs and learning preferences of individuals with hearing impairments? “To investigate this question, a mixed-methods approach was employed, combining qualitative interviews and surveys with deaf learners and quantitative data analysis. The research team developed a prototype of a digital learning platform tailored to the unique requirements of deaf learners, incorporating visual and interactive elements to enhance their comprehension and engagement. This research includes Research and Development (R&D) research used to produce certain products and test the effectiveness of these products. The findings of the study reveal the significance of designing inclusive digital learning media that consider the sensory and communication needs of individuals with hearing impairments. The interviews and surveys highlighted the positive impact of the developed digital learning platform on the learning experiences of deaf learners, as it facilitated better understanding, increased motivation, and encouraged active participation. This research contributes to the field of inclusive education by providing insights into the design and implementation of digital learning media for individuals with hearing impairments. The developed platform offers a valuable resource for educators and instructional designers to create accessible and engaging learning experiences for deaf learners.

Designing a Collaborative Patient-Centered Digital Health Platform for Pediatric Diabetes Care in British Columbia: Formative Needs Assessment by Caregivers of Children and Youths Living With Type 1 Diabetes and Health Care Providers.

Digital health apps are becoming increasingly available for people living with diabetes, yet data silos continue to exist. This requires health care providers (HCPs) and patients to use multiple digital platforms to access health data. In this study, we gathered the perspectives of caregivers of children and youths living with type 1 diabetes (T1D) and pediatric diabetes HCPs in the user-centered design of TrustSphere, a secure, single-point-of-access, integrative digital health platform. We distributed web-based surveys to caregivers of children and youths living with T1D and pediatric diabetes HCPs in British Columbia, Canada. Surveys were designed using ordinal scales and had free-text questions. Survey items assessed key challenges, perceptions about digital trust and security, and potential desirable features for a digital diabetes platform. Similar challenges were identified between caregivers of children and youths living with T1D (n=99) and HCPs (n=49), including access to mental health support, integration of diabetes technology and device data, and the ability to collaborate on care plans with their diabetes team. Caregivers and HCPs identified potential features that directly addressed their challenges, such as more accessible diabetes data and diabetes care plans. Caregivers had more trust in sharing their child's data digitally than HCPs. Most caregivers and HCPs stated that an integrative platform for T1D would support collaborative patient care. Caregiver and HCP perspectives gathered in this study will inform the early prototype of an integrative digital health platform. This prototype will be presented and iterated upon through a series of usability testing sessions with caregivers and HCPs to ensure the platform meets end users' needs.

A blockchain-enabled sharing platform for personal health records

BackgroundLongitudinal personal health record (PHR) provides a foundation for managing patients' health care, but we do not have such a system in the U.S. except for the patients in the Department of Veterans Affairs. Such a gap exists mainly in the rest of the U.S. by the fact that patients' electronic health records are scattered across multiple health care facilities and often not shared due to privacy, security, and business interests concerns from both patients and health care organizations. In addition, patients have ethical concerns related to consent. To patients, data security, privacy, and consent are based on trustfulness, rather than patients’ engagement in ensuring only authorized people can view their PHRs with patient-managed granularity. Resolving these challenges is an important step in making longitudinal PHR useful for patient care. ObjectiveThis research aims to design and implement a blockchain-enabled sharing platform prototype for PHR with desired patient-controlled data security, privacy, and consent granularity. MethodsBuilt upon our prior work of a blockchain-enabled access control (BAC) model, we design a blockchain-enabled sharing platform for PHR with patient-controlled security, privacy, and consent granularity. We further implement the construct by building a prototypical platform among a patient and two typical health care organizations. Health organizations that hold the patient's electronic health records can join the platform with trust based on the validation from the patient. The mutual trust can be established through a rigorous validation process by both the patient and the built-in Hyperledger Fabric blockchain consensus mechanism. ResultsWe proposed a system trusted by patients and health care providers and constructed a Web-based PHR sharing platform with patient-controlled security, privacy, and consent granularity. We analyzed the system scalability in three aspects and showed millisecond range of performance when simultaneously changing access permissions on hundreds of PHRs. Consent, security and privacy of the model are ensured by the merits of the BAC model. We discovered the current blockchain model limits the system scalability due to using a non-graphical database. A new graphical database is suggested for future improvements. ConclusionsIn this research, we report a solution to electronically sharing and managing patients’ electronic health records originating from multiple organizations, focusing on privacy, security, and granularity control of consent in the U.S. Specifically, the system protects data security and privacy, and provides auditability, scalability, distributedness, patient consent autonomy, and zero-trust capabilities. The prototypical instantiation of the designed model suggested the feasibility of combining emerging blockchain technology with next generation access control model to tackle a longstanding longitudinal PHR problem.

Combining Intergroup Dialogue and Sociotechnical Infrastructure Design: Addressing Social and Technical Determinants of Health Information Disparities with the Latinx Community

This transdisciplinary research project employed a multi-method approach to address health information inequities in Kentucky’s Fayette County during the COVID-19 pandemic. We drew from the study of Sociotechnical Infrastructures, Health Inequities, and Community-Based and Intergroup Dialogue (IGD) to co-create an Alternative Sociotechnical Infrastructure to facilitate information sharing among three stakeholder groups: (1) Latinx community members, (2) civil society organizations, and (3) government officials. Our research design included a combination of methodologies that addressed the technical and, more importantly, the underlying social causes of information access disparities. Focus groups helped identify Information Communication Technology (ICT) use, preferences, barriers, and information-sharing strategies. Community dialogues highlighted information barriers, existing resources, and proposed community-based solutions. The findings informed development of a web-based platform prototype that will facilitate information sharing during a crisis among all stakeholders. The methodology used also allowed the emergence of community champions among Latinx people who need to be invited to the table for these initiatives. We found that combining participatory action research (PAR) principles with critical dialogic methods fosters an environment of trust that enhances collaboration among stakeholders and consequently makes the design of information infrastructures more equitable and sustainable. As Information Communication Technologies embody social relations, we recommend emphasizing dialogic competencies and knowledge around racism/difference while valuing differences, collaboration, equality, and inclusions.

ONLINE PLATFORM PROTOTYPE USING MICROSERVICE ARCHITECTURE AND CONTAINERIZATION FOR DIGITALIZATION OF THE EDUCATIONAL PROCESS

The COVID pandemic and full-scale military operations in our territory affected the implementation of digital and information technologies in the educational process. Digitalization has covered all spheres of education, and has especially affected distance learning technologies. But the problem of automating the process of managing the educational process remains unexplained. Ensuring quality management of the educational process requires a review of approaches to architecture, development processes, and implementation of appropriate software. Most of the modern information systems for the management of the educational process (ISMEP) are built according to the "monolithic" architecture. This limits the possibility of modernization without rebuilding the core of the system. The consequence of this is the problem of scaling and efficient use of cloud technologies. The purpose of the work is to develop a prototype of an online ISMEP platform using microservice architecture and containerization.

Multiport PV-Assisted Electric-Drive-Reconstructed Bidirectional Charger With G2V and V2G/V2L Functions for SRM Drive-Based EV Application

This paper develops a highly-integrated solar-assisted switched reluctance motor (SRM) drive for electric vehicle (EV) applications with electric-drive-reconstructed grid-to-vehicle (G2V) and vehicle-to-grid (V2G)/vehicle-to-load (V2L) functions. The flexible and efficient multimode energy transmission is realized among SRM, battery pack, solar photovoltaic (PV) panels, and AC grid. Under motoring condition, the standard switch modules are employed to implement bipolar current excitation and regenerative braking, which provides great benefits for balanced heat dissipation design and massive production of SRM drives for EVs. Under idle condition, the G2V and V2G/V2L modes can be well-regulated by multiplexing and reconstructing SRM windings and converter topology. The EV can be completely stationary without extra clamping device under the adopted positioning strategy. The battery pack can be charged by the developed bridgeless interleaved boost converter with excellent power factor correction capability, and can also act as discharging source to power the AC/DC grids/loads flexibly cooperated with the PV panels. A proof-of-concept prototype platform is built and the experiments based on a 1 kW three-phase 12/8 SRM are carried out to validate the feasibility of the proposed SRM system.

A novel hollow-type XY piezoelectric positioning platform

To enhance space efficiency and reduce the planar dimensions of the piezoelectric platform, propose an innovative three-stage flexible lever hollow XY piezoelectric platform powered by piezoelectric stack. This paper details the platform's design configuration and operational principles. Analyze and optimize the platform's static and dynamic characteristics using matrix-based compliance modeling and finite element methods. The platform measures 39 mm × 39 mm × 40 mm with a hollow diameter of 29 mm × 29 mm × 40 mm and weighs 60.12 g. An array of experiments was performed to evaluate the prototype platform's performance. Experimental results revealed that the platform's motion ranges are 30.76 μm and 29.79 μm, the cross-coupling ratios are 2.02% and 2.26%, the hysteresis ratios are approximately 5.48% and 5.56%, the displacement resolution are less than 29.3 nm and 31.4 nm, and the carrying load exceeds 1 kg, all measured in the X-axis and Y-axis respectively. Moreover, after installing a simulated laser generator load, achieved square and elliptical motion trajectories by exciting different signals. The study further highlights the successful application of the novel piezoelectric positioning platform for precise motion positioning and inspection of minute electronic components under an optical microscope, signifying its potential to enhance detection and sorting processes in the electronics industry. When compared with earlier piezoelectric positioning platforms, proposed platform not only provides a superior space utilization rate but also exhibits enhanced performance. In the future, the platform will be used for high performance scanning and optical system tracking for atomic force microscopes.

Ethical aspects of integrating AI expert models in the process of retrieval and use of ICH registry material

ABSTRACT This work arises in the context of the interdisciplinary research group hosted at the Laboratory of Innovation and Territory of the Department of Design of the Catholic University of Temuco. In this research, we delve into protecting indigenous cultural rights by proposing an experimental methodology from developing prototypes defining various approaches and attempting to create new cultural-based proposals. They all comprise the body of our method of approach to the digital humanities on the Intangible Cultural Heritage of the original peoples that inhabited the current Chilean territory. We highlight the use of digital prototyping platforms, some of them based on expert models in artificial intelligence and others based on the development of generative and parametric algorithms, making a distinction between these two technologies that in their combination offer a panorama of infinite interactions, possibilities, allowing us to configure a transcultural language where the elements are translated into a generic programming language, where we can change the category of the original information, these categories are image, text, and sound. In this process, we declare our research problem: how to use the records of the intangible cultural heritage of the native peoples to design new artistic interpretations without falling into cultural appropriation.

Bipedal driven inertial type piezoelectric motor working under quasi-static and resonant states

An inertia piezoelectric motor based on bipedal driven, which can work in not only quasi-static but also resonant states, is proposed, designed, fabricated and studied considering the high resolution of quasi-static piezoelectric motor and the high speed of resonant piezoelectric motor. The two stators of the piezoelectric motor are drived by two sinusoidal electrical signals with 1:2 frequency ratio to generate sinusoidal vibration on the corresponding driving foot. A continuous step motion without frequency limitation is realised under the action of inertia and friction forces after synthesising the sinusoidal vibration of different frequencies into mechanical sawtooth vibration. The natural resonant frequencies of the piezoelectric motor are adjusted to a specific proportion to combine the vibrations in the resonant state through finite element analysis. In the structure of two stators, each stator has a corresponding inertia block, and the corresponding resonant frequency can be altered by adjusting the mass of the inertial block without affecting the other resonant frequency, thus markedly simplifying the design difficulty of the piezoelectric motor which can work in quasi-static and resonant states. The motion characteristics of the prototype are tested by building the prototype and experimental platform. Experimental results show that the maximum speed of the prototype is 29.3 mm s−1 and the maximum load is 2 N in the resonant state, the minimum displacement resolution of prototype motor is 0.26 μm in the quasi-static state. The motion characteristics of the prototype are consistent with the theoretical analysis, which provides an effective idea to improve the comprehensive performance of the piezoelectric motor.

Thirteen-Level Switching Capacitor Inverter with Six Times Boost and Self-Balancing Capability

A thirteen-level inverter based on switching capacitor is proposed in order to improve the boost capacity and output power quality of inverter in renewable energy power generation system. The proposed topology is composed of one DC input power supply, three capacitors and 14 switching devices, and achieves thirteen-level output with six times voltage boost. It has smaller volume, lower cost and output harmonic content. Moreover, it can realize inverter without H bridge and reduce the voltage stress of switching tube. In addition, the proposed inverter can achieve self-balancing capacitor voltage without any auxiliary method, simplifying the complexity of control. The superiority of the proposed topology is verified by comparing with other traditional multilevel inverters. The simulation and experimental verification on the simulation and prototype platform show that the inverter has good performance in both steady and dynamic conditions.

A Unified Implementation Framework for Index Modulation Assisted MIMO Backscatter Communication

In this letter, a unified hardware implementation framework is designed for index modulation (IM) assisted multi-input multi-output (MIMO) backscatter communication, including space shift keying (SSK), spatial modulation (SM), SM assisted vertical bell labs space-time (SM-VBLAST), as well as SM assisted space-time block code (SM-STBC) schemes. Specifically, the concepts of SM-VBLAST and SM-STBC architectures are successfully applied into backscatter communication to balance an elegant tradeoff between spatial multiplexing and diversity gain. Then the coupled channel estimation and interference-cancellation-based signal detection algorithms are designed for hardware implementation. Furthermore, a unified IM-MIMO-based backscatter hardware prototype and experimental platform are designed. Experimental results verify that the proposed IM-MIMO implementation framework works efficiently and we can choose one proper IM-MIMO backscatter communication based on the required throughput, diversity gain as well as implementation complexity.

Managing Concurrent Queues for Efficient In- Vehicle Gateways

In modern vehicles, electrical control units communicate over multiple in-vehicle networks via domainor zone-oriented gateway architectures. This work examines efficient frame transfer across incoming and outgoing Controller Area Network (CAN) interfaces at a gateway. In our embedded platform prototype, each CAN interface of a CAN-to-CAN gateway is controlled independently by a corresponding Portable Operating System Interface (POSIX) thread. Inter-thread communication and synchronization are implemented using shared data structures, either lock-free concurrent queues or traditional lock-based circular queues that embody single-producer single-consumer (SPSC) principles. Our experimental framework provides a realistic open automotive platform that integrates multiple CAN interfaces. An Odroid XU3 device acts as a gateway, providing two Universal Asynchronous Receiver- Transmitter (UART) to CAN interfaces that lead to Raspberry Pi 3B nodes (connected to CAN via Serial Peripheral Interface (SPI)). To increase communication reliability and performance by minimizing frame loss and improving the egress CAN frame rate, low-level parameters at the gateway are optimized, especially the inter-character delay of the UART-to-CAN interfaces. Our experiments show that the frame waiting time in the queue is shorter for the concurrent queue, while relaying messages is equally fast, reaching a maximum output rate of ~380 frames/s for large enqueue rates near saturation. Power consumption is almost four times higher for the concurrent queue implementation.

Advancing Access to Care through Digital Health: Perspectives from Youth on a Novel Platform to Increase Access to Sexual and Reproductive Health Care and Education for Adolescents and Young Adults

Study ObjectiveYouth account for half of new sexually transmitted infections (STIs) in the United States annually. Barriers to STI prevention include a lack of accurate sexual and reproductive health (SRH) education and low STI testing. We sought to obtain youth feedback on a digital health platform prototype designed to address these barriers. MethodsThe platform prototype included SRH content, free STI testing and treatment, and anonymous question submission. Five focus group discussions, each lasting 45-60 minutes with 5-6 youth living in a high-prevalence STI region (Baltimore, Maryland), were conducted. Thematic analysis was conducted. ResultsThere were 28 participants with a mean age of 15.9 years (range 14-19), among whom 89% self-identified as female, 57% Black/African American, 29% Asian American, 14% White, and 7% Hispanic/Latino. Youth felt that the prototype platform was comprehensive and understandable. They suggested adding peer reviews to increase trustworthiness. ConclusionYouth reported that the platform (violetproject.org) was an acceptable tool for SRH education and STI testing. Participants expressed enthusiasm and willingness to use the platform as a reliable SRH educational tool to combat medical misinformation on the Internet and a non-clinic-based source of STI testing. This platform could fill gaps in access to SRH care and education for youth.

A Prototype Platform for Automated Chicken Feeding Control with an Embedded System

In this paper present a prototype platform for automated chicken feeding control with an embedded system. This prototype is an automated real-time chicken feeding mixing system that will help chicken farmers become more automated, which will be highly beneficial for the expansion of the chicken poultry farm in Phra Nakhon Si Ayutthaya, Thailand. This machine may take the role of a person in the chicken-feeding process, solving the farm's labor shortage. The apparatus for feeding chickens makes use of an Arduino Uno board as the heart of an embedded system controller. The two major components of this device are an Arduino that controls the servomotor opening for the food container and another Arduino that controls the servomotor opening for the food ingredients in a mixed food container. The prototype platform will have an alarm when the food ingredients are at the minimum quantity. This also helps the chickens get the amount of food and nutrients that are appropriate for their age while reducing labour costs, saving food, and controlling chicken feeding on time.

Testing distributed trajectory planning in the cyber-physical mobility lab

Abstract This article presents the testing of distributed trajectory planning algorithms using our rapid prototyping platform, the Cyber-Physical Mobility Lab (CPM Lab). We propose two algorithms for distributed trajectory planning which plan trajectories at intersections, highway on- and off-ramps, and lane changes for networked and autonomous vehicles. The algorithms avoid collisions between vehicles using a synchronization-based and a prioritized Distributed Model Predictive Control (DMPC) strategy. We test two algorithms in the CPM Lab which is able to handle parallel, sequential, and hybrid computations. The CPM Lab achieves reproducible experiments under non-deterministic computation times and stochastic communication times. Our evaluation shows that different algorithms for distributed trajectory planning can be efficiently tested in different in-the-loop tests.

A protective measles virus-derived vaccine inducing long-lasting immune responses against influenza A virus H7N9

A novel Influenza A virus (subtype H7N9) emerged in spring 2013 and caused considerable mortality in zoonotically infected patients. To be prepared for potential pandemics, broadly effective and safe vaccines are crucial. Recombinant measles virus (MeV) encoding antigens of foreign pathogens constitutes a promising vector platform to generate novel vaccines. To characterize the efficacy of H7N9 antigens in a prototypic vaccine platform technology, we generated MeVs encoding either neuraminidase (N9) or hemagglutinin (H7). Moraten vaccine strain-derived vaccine candidates were rescued; they replicated with efficiency comparable to that of the measles vaccine, robustly expressed H7 and N9, and were genetically stable over 10 passages. Immunization of MeV-susceptible mice triggered the production of antibodies against H7 and N9, including hemagglutination-inhibiting and neutralizing antibodies induced by MVvac2-H7(P) and neuraminidase-inhibiting antibodies by MVvac2-N9(P). Vaccinated mice also developed long-lasting H7- and N9-specific T cells. Both MVvac2-H7(P) and MVvac2-N9(P)-vaccinated mice were protected from lethal H7N9 challenge.