articles+ search results

штучний інтелект, fpga, ші як сервіс, гетерогенні проєкти ші систем, апаратні прискорювачі ші, dpu, інструментальні засоби розробки ші, xrt, Motor vehicles. Aeronautics. Astronautics, and TL1-4050

The subject of study in this article is modern technologies, tools and methods of building AI systems as a service using FPGA as a platform. The goal is to analyze modern technologies and tools used to develop FPGA-based projects for systems that implement artificial intelligence as a service and to prepare a practical AI service prototype. Task: to analyze the evolution of changes in the products of leading manufacturers of programmable logic devices and experimental and practical examples of the implementation of the paradigm of continuous reprogramming of programmable logic; analyze the dynamics of changes in the development environment of programmable logic systems for AI; analyze the essential elements of building projects for AI systems using programmable logic. According to the tasks, the following results were obtained. The area of application of hardware implementation of artificial intelligence for on-board and embedded systems including airspace industry, smart cars and medical systems is analyzed. The process of programming FPGA accelerators for AI projects is analyzed. The analysis of the capabilities of FPGA with HBM for building projects that require enough of high speed memory is performed. Description languages, frameworks, the hierarchy of tools for building of hardware accelerators for AI projects are analyzed in detail. The stages of prototyping of AI projects using new FPGA development tools and basic DPU blocks are analyzed. The parameters of the DPU blocks were analyzed. Practical steps for building such systems are offered. The practical recommendations for optimizing the neural network for FPGA implementation are given. The stages of neural network optimization are provided. The proposed steps include pruning of branches with low priority and the use of fixed point computations with custom range based on the requirements of an exact neural network. Based on these solutions, a practical case of AI service was prepared, trained and tested. Conclusions. The main contribution of this study is that, based on the proposed ideas and solutions, the next steps to create heterogeneous systems based on the combination of three elements are clear: AI as a service, FPGA accelerators as a technology for improving performance, reliability and security, and cloud or Edge resources to create FPGA infrastructure and AI as service. The development of this methodological and technological basis is the direction of further R&D.

3D printing, Zinc submicron particles, Osteoinductivity, Anti-inflammatory, Bone defect repair, Materials of engineering and construction. Mechanics of materials, TA401-492, Biology (General), and QH301-705.5

Long-term nonunion of bone defects has always been a major problem in orthopedic treatment. Artificial bone graft materials such as Poly (lactic-co-glycolic acid)/β-tricalcium phosphate (PLGA/β-TCP) scaffolds are expected to solve this problem due to their suitable degradation rate and good osteoconductivity. However, insufficient mechanical properties, lack of osteoinductivity and infections after implanted limit its large-scale clinical application. Hence, we proposed a novel bone repair bioscaffold by adding zinc submicron particles to PLGA/β-TCP using low temperature rapid prototyping 3D printing technology. We first screened the scaffolds with 1 wt% Zn that had good biocompatibility and could stably release a safe dose of zinc ions within 16 weeks to ensure long-term non-toxicity. As designed, the scaffold had a multi-level porous structure of biomimetic cancellous bone, and the Young's modulus (63.41 ± 1.89 MPa) and compressive strength (2.887 ± 0.025 MPa) of the scaffold were close to those of cancellous bone. In addition, after a series of in vitro and in vivo experiments, the scaffolds proved to have no adverse effects on the viability of BMSCs and promoted their adhesion and osteogenic differentiation, as well as exhibiting higher osteogenic and anti-inflammatory properties than PLGA/β-TCP scaffold without zinc particles. We also found that this osteogenic and anti-inflammatory effect might be related to Wnt/β-catenin, P38 MAPK and NFkB pathways. This study lay a foundation for the follow-up study of bone regeneration mechanism of Zn-containing biomaterials. We envision that this scaffold may become a new strategy for clinical treatment of bone defects.

Metal additive manufacturing (MAM), Laser powder bed fusion (L-PBF), Machine learning (ML), Process parameter optimization, Anomaly detection, and Technology

Metal Additive Manufacturing (MAM) applications are growing rapidly in high-tech industries such as biomedical and aerospace, and in many other industries including tooling, casting, automotive, oil and gas for production and prototyping. The onset of Laser Powder Bed Fusion (L-PBF) technology proved to be an efficient technique that can convert metal additive manufacturing into a reformed process if anomalies occurred during this process are eliminated. Industrial applications demand high accuracy and risk-free products whereas prototyping using MAM demand lower process and product development time. In order to address these challenges, Machine Learning (ML) experts and researchers are trying to adopt an efficient method for anomaly detection in L-PBF so that the MAM process can be optimized and desired final part properties can be achieved. This review provides an overview of L-PBF and outlines the ML methods used for anomaly detection in L-PBF. The paper also explains how ML methods are being used as a step forward toward enabling the real-time process control of MAM and the process can be optimized for higher accuracy, lower production time, and less material waste. Authors have a strong believe that ML techniques can reform MAM process, whereas research concerned to the anomaly detection using ML techniques is limited and needs attention.This review has been done with a hope that ML experts can easily find a direction and contribute in this field.

Android, Communication, Deaf, Disability, Dumb, Hardware, and Science

People living with disability constitute a significant percentage of the world population. For many people with disabilities, assistance and support are prerequisites for participating in societal activities. This research work developed a hardware prototype of a robotic hand forfor sign language communication with persons living with hard-of-hearing disabilities (deaf and/or dumb). The prototype has three basic modules: the input unit, the control unit, and the robotic hand. The input unit is designed as an Android-based mobile application with speech recognition capabilities while the control unit is ATMEGA 2560 microcontroller board. The robotic hand is constructed using locally available materials (bathroom Slippers, expandable rubber, straw pipe, and tiny rope) together with three servo motors and is designed to look and perform movements similar to a human hand. The prototype was evaluated quantitatively in terms of empirical accuracy and response time. It was also evaluated qualitatively by thirty-five (35) users which included fifteen (15) experience ASL users, eighteen (18) non-experience ASL users, and two (2) ASL experts, who completed questionnaires to rate the prototype on a 5-point Likert scale in terms of five parameters: functionality, reliability, ease of use, efficiency, and portability. An accuracy of 78.43% with an average response time of 2 s was obtained from empirical experiments. Statistical analysis of user responses showed that 97%, 68%, 77%, 80%, and 83% of users rated the system as above average for functionality, reliability, ease of use, efficiency, and portability, respectively. The robotic hand effectively communicates American Sign Language which includes English Alphabets, numbers (1–9), and some selected common words, which can be demonstrated with a single hand for hard of hearing persons. To the best of our knowledge, this work is the first ASL robotic hand that is based on locally sourced cost-effective materials, and we build on flaws from existing literature, most of which are either template-based, not real-time, or expensive. In terms of future work, the prototype can be improved by extending the single robotic hand to a fully robotic body with two hands.

cardiopulmonary resuscitation, Mechanical ventilation, Mechanical chest-compression, Respiratory monitoring, Thiel embalmed cadaver, Biomechanics, Computer applications to medicine. Medical informatics, R858-859.7, Science (General), and Q1-390

The data presented in this article relate to the research article, “Reliability of mechanical ventilation during continuous chest compressions: a crossover study of transport ventilators in a human cadaver model of CPR” [1].This article contains raw data of continuous recordings of airflow, airway and esophageal pressure during the whole experiment. Data of mechanical ventilation was obtained under ongoing chest compressions and from repetitive measurements of pressure-volume curves. All signals are presented as raw time series data with a sample rate of 200Hz for flow and 500 Hz for pressure. Additionally, we hereby publish extracted time series recordings of force and compression depth from the used automated chest compression device. Concomitantly, we report tables with time stamps from our laboratory book by which the data can be sequenced into different phases of the study protocol.We also present a dataset of derived volumes which was used for statistical analysis in our research article together with the used exclusion list.The reported dataset can help to understand mechanical properties of Thiel-embalmed cadavers better and compare different models of cardiopulmonary resuscitation (CPR). Future research may use this data to translate our findings from bench to bedside. Our recordings may become useful in developing respiratory monitors for CPR, especially in prototyping and testing algorithms of such devices.

aged, deprescribing, frailty, polypharmacy, primary health care, referral and consultation, Medicine (General), R5-920, Public aspects of medicine, and RA1-1270

Abstract Background In older people living with frailty, polypharmacy can lead to preventable harm like adverse drug reactions and hospitalization. Deprescribing is a strategy to reduce problematic polypharmacy. All stakeholders should be actively involved in developing a person‐centred deprescribing process that involves shared decision‐making. Objective To co‐design an intervention, supported by a logic model, to increase the engagement of older people living with frailty in the process of deprescribing. Design Experience‐based co‐design is an approach to service improvement, which uses service users and providers to identify problems and design solutions. This was used to create a person‐centred intervention with the potential to improve the quality and outcomes of the deprescribing process. A ‘trigger film’ showing older people talking about their healthcare experiences was created and facilitated discussions about current problems in the deprescribing process. Problems were then prioritized and appropriate solutions were developed. The review located the solutions in the context of current processes and procedures. An ideal care pathway and a complex intervention to deliver better care were developed. Setting and Participants Older people living with frailty, their informal carers and professionals living and/or working in West Yorkshire, England, UK. Deprescribing was considered in the context of primary care. Results The current deprescribing process differed from an ideal pathway. A complex intervention containing seven elements was required to move towards the ideal pathway. Three of these elements were prototyped and four still need development. The complex intervention responded to priorities about (a) clarity for older people about what was happening at all stages in the deprescribing process and (b) the quality of one‐to‐one consultations. Conclusions Priorities for improving the current deprescribing process were successfully identified. Solutions were developed and structured as a complex intervention. Further work is underway to (a) complete the prototyping of the intervention and (b) conduct feasibility testing. Patient or Public Contribution Older people living with frailty (and their informal carers) have made a central contribution, as collaborators, to ensure that a complex intervention has the greatest possible potential to enhance the experience of deprescribing medicines.

Perforations, Subtractive manufacturing, Negative Poisson’s ratio, 3D auxetic structures, Materials of engineering and construction. Mechanics of materials, and TA401-492

Prototyping of three-dimensional mechanical metamaterials that exhibit negative Poisson’s ratio is usually performed through additive manufacturing. Although this technique has a huge potential, its use to engineer mechanical metamaterials for consumer products is still challenging. In this work, a novel design method is being proposed where 3D auxetic metamaterials can be produced by introducing continuous voids of constant cross-sectional area. Such voids would be inserted at strategic positions in different perpendicular planes of a solid block to obtain a continuous three-dimensional mechanical metamaterial that can exhibit the desired mechanical characteristics. The use of continuous voids to design the 3D meatamaterial makes it possible to use additive manufacturing, subtractive manufacturing as well as casting to produce these systems. The proposed design method is explained by using continuous voids having a diamond shaped cross-sectional area. The resulting group of structures can be described as connected polygons and were found to exhibit a negative or zero Poisson’s ratio. The analysed systems were also found to have a strain independent Poisson’s ratio up to at least 7% strain. The proposed design method can thus facilitate the availability of three dimensional auxetic metamaterials in the consumer market which to date is conspicuous by their absence.

Bioprinting, Engineered living materials, Biosensors, Synthetic biology, Engineered bacteria, Medicine (General), R5-920, Biology (General), and QH301-705.5

The intertwined adoption of synthetic biology and 3D bioprinting has the potential to improve different application fields by fabricating engineered living materials (ELMs) with unnatural genetically-encoded sense & response capabilities. However, efforts are still needed to streamline the fabrication of sensing ELMs compatible with field use and improving their functional complexity. To investigate these two unmet needs, we adopted a workflow to reproducibly construct bacterial ELMs with synthetic biosensing circuits that provide red pigmentation as visible readout in response to different proof-of-concept chemical inducers. We first fabricated single-input/single-output ELMs and we demonstrated their robust performance in terms of longevity (cell viability and evolutionary stability >15 days, and long-term storage >1 month), sensing in harsh, non-sterile or nutrient-free conditions compatible with field use (soil, water, and clinical samples, including real samples from Pseudomonas aeruginosa infected patients). Then, we fabricated ELMs including multiple spatially-separated biosensor strains to engineer: level-bar materials detecting molecule concentration ranges, multi-input/multi-output devices with multiplexed sensing and information processing capabilities, and materials with cell-cell communication enabling on-demand pattern formation. Overall, we showed successful field use and multiplexed functioning of reproducibly fabricated ELMs, paving the way to a future automation of the prototyping process and boosting applications of such devices as in-situ monitoring tools or easy-to-use sensing kits.

Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Computer software, and QA76.75-76.765

Establishing the indoor and outdoor humidity values in a greenhouse allows us to describe the crop yield during its entire developmental cycle. This study seeks to develop a predictive model of indoor relative humidity values in a greenhouse with high accuracy and interpretability through the use of optimized fuzzy inference systems, in order to offer greenhouse users a clear and simple description of their behaviour. The three-phase methodology applied made use of descriptive statistics techniques, correlation analysis, and prototyping paradigm for the iterative and incremental development of the predictive model, validated through error measurement. The research resulted in six models which define the behaviour of humidity as a result of temperature, CO2, and soil moisture, with percentages of effectiveness above 90%. The implementation of a Mamdani-type fuzzy inference system, optimized by a hybrid method combining genetic and interior point algorithms, allowed to predict the relative humidity in greenhouses with high interpretability and precision, with an effectiveness percentage of 90.97% and MSE (mean square error) of 8.2e − 3.

3D printing, Arduino, educational robotics, design thinking, open-source project, open-source platform, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, and QD1-999

The dynamic spread of 3D printing technologies and open-source electronics prototyping platforms has significantly enriched the diversity of instruments used within educational robotics (ER) settings. An active, low-entry-level community offering ready-to-use libraries for a broad variety of devices assists in the development of quite sophisticated projects. However, the flipside of the coin is represented by the current research findings, which reveal that students’ interest in science, technology, engineering and mathematics (STEM) subjects has declined across Europe, as manifested in difficulties when approaching scientific topics and dealing with problems and phenomena studied from a multidisciplinary perspective. Consequently, a significant percentage of youths are at risk of social exclusion due to the direct relationship between low academic achievements and school dropout. Moreover, learners lack guidance in applied and life-context skills, such as creative thinking, problem solving, and collaboration, which highlights the need to introduce innovative pedagogical approaches. In this context, the design thinking (DT) methodology was proposed to tackle the problem. Originating in the development of psychological studies on creativity in the 1950s within the educational context, DT is known to foster creative thinking, help develop empathy, promote action-oriented actions, improve meta-cognitive awareness, contribute to problem-solving skills, and enhance students’ imagination. The last point supports the students’ development of critical thinking, social inclusion, teamwork skills, and academic performance. Thus, this paper introduces a methodological framework combining DT with ER classes. First, to approach the problem, the teachers’ survey data were collected and analysed to reveal the respondents’ level of integration of the DT methodology into current school curricula. Then, the work focused on the application of this framework in a learning experience by addressing the weakest points established and their elaboration through the combined ER and DT classes in the context of secondary schools.

chaos-based communication, covert transmission, secure communication systems, hardware chaos generators, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, and QD1-999

Chaos-based communications are a promising application of chaos theory and nonlinear dynamics. Their key features include concealed transmission, high security, and native broadband signals. Many studies have recently been published devoted to this technology. However, the practical implementations of chaos-based communications are rare due to multiple shortcomings: high hardware requirements, complex signal processing algorithms, and a lack of efficient modulation techniques for chaotic signals. In this study, we consider a simple hardware prototype of a coherent chaos-based communication system based on a novel type of modulation: adaptive symmetry of the finite-difference scheme used in a chaos generator. We explicitly demonstrate the possibility of covertly transmitting data using a chaotic transmitter and receiver implemented in a general-purpose microcontroller unit. A comparison between traditional parameter and symmetry modulation is given through a return map analysis and bit error rate estimation. The communication secrecy is analyzed using quantified return map analysis. The obtained results confirm the possibility of creating chaos-based communication systems based on symmetry modulation.

prototyping, design thinking, higher education institution, HEI management, cognitive biases, and Education

A project using design thinking (DT) was conducted among internal stakeholders of a large state Japanese university to design a user-centric brochure promoting study abroad programs at francophone partner universities. The low-fidelity prototype and the final product created with DT were tested by asking potential student-users to compare it with a standard brochure through two sets of surveys. Analysis of the quantitative and qualitative data revealed that low-fidelity prototyping was effective to enhance both the utility and usability of the final product. We also show how DT helped expose cognitive biases among designers.

axial fan, ventilation, efficiency, rapid prototyping, CFD, FEM, and Technology

The article discusses the process of designing and testing as well as their results, carried out in order to increase the efficiency of axial fans, implemented as part of the European project INESI. Modifications of existing solutions based on rapid prototyping methods were presented. Scanning, FEM and CFD numerical calculations and 3D printing were used for that purpose. Rapid prototyping involved the use of a steel blade base and 3D-printed complex aerodynamic shapes that were bonded to create completely new blades. After their installation on the new rotor, enabling the angle of attack adjusting, a number of verifying tests of the fan were carried out. The solution was successfully tested and the results are discussed in the article.

diesel engine, machine learning engine management, neural network models, control system coordination, and Technology

The tightening of diesel pollutant emission regulations has made Internal Combustion Engine (ICE) management through steady-state maps obsolete. To overcome the map’s scarce performance and efficiently manage the engine, control systems must cope with ICE transient operations, the coupling between its subsystem dynamics, and the tradeoff between different requirements. The work demonstrates the effectiveness of a reference generator that coordinates the air path and combustion control systems of a turbocharged heavy-duty diesel engine. The control system coordinator is based on neural networks and allows for following different engine-out Nitrogen Oxide (NOx) targets while satisfying the load request. The air path control system provides the global conditions for the correct functioning of the engine, targeting O2 concentration and pressure in the intake manifold. Through cooperation, the combustion control targets Brake Mean Effective Pressure (BMEP) and NOx to react to rapid changes in the engine operating state and compensates for the remaining deviations with respect to load and NOx targets. The reference generator and the two controller algorithms are suitable for real-time implementation on rapid-prototyping hardware. The performance overall was good, allowing the engine to follow different NOx targets with 150 ppm of deviation and to achieve an average BMEP error of 0.3 bar.

Education

This study aims to investigate lecturers' needs for academic writing learning materials and determine their prototypes. This study is qualitative research in the form of an exploratory case study. The research instruments were semi-open-ended questionnaires and unstructured and open-ended interview guides. The data were analyzed using content analysis. The results show that the developed learning material for academic writing skills contains seven needs for lecturers in the Department of Indonesian Language and Literature. Four of them have not been found by previous researchers. The results from this study provide new knowledge and contribution to the literature about the need to prototype the learning materials. The lecturers or other researchers can use these seven needs in prototyping learning materials for academic writing skills, such as the needs of learning materials, their forms, presentation system, language use, evaluation form, main menu design, and the way of creating learning materials.

3D printing, polylactic acid, bioreactor, mesenchymal niche, hematopoiesis, collagen scaffold, Biotechnology, and TP248.13-248.65

Faithful modeling of tissues and organs requires the development of systems reflecting their dynamic 3D cellular architecture and organization. Current technologies suffer from a lack of design flexibility and complex prototyping, preventing their broad adoption by the scientific community. To make 3D cell culture more available and adaptable we here describe the use of the fused deposition modeling (FDM) technology to rapid-prototype 3D printed perfusion bioreactors. Our 3D printed bioreactors are made of polylactic acid resulting in reusable systems customizable in size and shape. Following design confirmation, our bioreactors were biologically validated for the culture of human mesenchymal stromal cells under perfusion for up to 2 weeks on collagen scaffolds. Microenvironments of various size/volume (6–12 mm in diameter) could be engineered, by modulating the 3D printed bioreactor design. Metabolic assay and confocal microscopy confirmed the homogenous mesenchymal cell distribution throughout the material pores. The resulting human microenvironments were further exploited for the maintenance of human hematopoietic stem cells. Following 1 week of stromal coculture, we report the recapitulation of 3D interactions between the mesenchymal and hematopoietic fractions, associated with a phenotypic expansion of the blood stem cell populations.Our data confirm that perfusion bioreactors fit for cell culture can be generated using a 3D printing technology and exploited for the 3D modeling of complex stem cell systems. Our approach opens the gates for a more faithful investigation of cellular processes in relation to a dynamic 3D microenvironment.

Microservices, autoscalers, resource allocation, resource utilization, machine learning, random forest, Electrical engineering. Electronics. Nuclear engineering, and TK1-9971

Cloud service providers have been shifting their workloads to microservices to take advantage of their modularity, flexibility, agility, and scalability. However, numerous obstacles remain to achieving the most out of microservice deployments, especially in terms of a Quality of Service (QoS). One possible approach to overcoming these obstacles is to perform autoscaling, which is the ability of cloud infrastructure and services to scale themselves up or down by changing their resource pool. There are two major categories of autoscaling: reactive and proactive. In reactive autoscaling, a feedback loop based on current workload resource usage is implemented to guide resource scaling. One disadvantage of reactive autoscaling is that it may result in inconsistencies between workload demand and resource allocation. In proactive autoscaling, a prediction model is used to guide the future allocation of resources according to current workload metrics. In this paper, a novel proactive autoscaling method is introduced where a two-state, machine-learning Random Forest (RF) model is designed to forecast the future CPU and memory utilization values required by the microservice workload. These predicted values are then used to adjust the resource pool both vertically (hardware resources) and horizontally (microservice replicas). The RF proactive autoscaler has been implemented on a home-grown, open-source microservice prototyping platform and verified using real-world workloads. The experiments show that the RF proactive autoscaler outperforms state-of-the-art ones in terms of allocated resources and latency. The increase in the utilization of allocated resources can reach 90% and the improvement in end-to-end latency, measured by the $95^{th}$ percentile, can reach 95%.

Direct-ink-writing, silver-conductive ink, additive manufacturing, printed electronics, ultra-wideband antennas, electrical conductivity, Electrical engineering. Electronics. Nuclear engineering, and TK1-9971

Direct ink writing (DIW) of conductive ink is a printed electronics technology that allows a variety of electronic circuits to be produced in a simple way and with minimal waste of materials. In recent years it has been used for rapid prototyping of RF circuits typically working at S-band frequencies (2–4 GHz). In an attempt to extend this frequency range while maintaining cost-effective prototyping, this work has focused on proving the feasibility of DIW of silver-conductive (SC) ink for the fabrication of planar microwave circuits beyond 10 GHz, more specifically, ultra-wideband (UWB) antennas for medical applications. For this purpose, the DC and RF performance of the SC ink, as well as the FR4 substrate used, were first evaluated. Based on the comparison between experimental and simulated results, we have found that the effective RF conductivity of the SC ink is approximately 27.6% of its DC value and 3.4% of the copper conductivity. A few test microstrip circuits were fabricated by DIW, namely two S-band filters and one UWB antenna. The overall measured performance of all of them agreed well with simulations. In particular, the DIW antenna exhibited a bandwidth of 8.2 GHz (between 2.4 and 10.6 GHz), and was compared with an identical copper antenna showing that both have very similar characteristics. It was also found that the lower conductivity of SC ink as compared to copper led to a gain reduction of only 0.3 dB.

FPGA, hybrid multilevel converter, modular multilevel converter (MMC), rapid control prototyping (RCP), real-time simulation, voltage-source converter high voltage direct current (VSC-HVDC), Electrical engineering. Electronics. Nuclear engineering, and TK1-9971

Real-time simulation is important for ensuring the reliable operation of VSC-HVDC converters in power grids, particularly through the use of rapid control prototyping (RCP) and hardware-in-the-loop (HIL) based converter controllers. While real-time simulation is a common practice for modular multilevel converters (MMCs), it has been less frequently applied to the new class of hybrid cascaded multilevel converters (HCMCs). In this study, a universal equivalent model (UEM) is proposed for a range of HCMC topologies that combines accuracy and computational efficiency through the use of both CPUs and field-programmable gate arrays (FPGAs). The proposed UEM is derived using the hybrid five-level converter (H5LC), a compact, efficient, and fault-tolerant VSC within the HCMC family. The UEM relies on CPUs to simulate the main circuits and controls of the main converter, and utilizes FPGAs to calculate the instantaneous voltages of a large number of full-bridge submodules (FBSMs), flying capacitors, and DC-side pole capacitors. In addition, the FBSMs’ voltage-balancing and switching algorithms are implemented on the FPGAs. The proposed real-time CPU/FPGA-based H5LC-UEM is compared to an offline CPU-based detailed equivalent model to verify its accuracy.

AI in education (AIEd), hands-free AI speaker, hands-on science laboratory class, rapid prototyping, natural language processing (NLP), Education, Information technology, and T58.5-58.64

The recent progress of natural language processing (NLP), speech recognition, and speech generation envisions using hands-free artificial intelligence (AI) speakers in classrooms to support student learning. In science education, the conventional hands-on laboratory education has been considered crucial in fostering students’ manipulative experimentation skills. However, touching things with gloved hands other than experimental equipment and apparatuses is strictly restricted because of the safety issue, which calls for another channel to get timely support. Therefore, we ideated that adopting hands-free AI speakers in the hands-on science laboratory classroom would support student learning. Using the rapid prototyping method, we designed and developed an AI speaker-based system that answers student queries concerning solution-making, experimental process, and waste liquid disposal, which corresponds to the initial, middle, and final phases of a laboratory class. The system was internally validated by usability tests of 9 expert panels and 18 university students, and then revised. The revised system was externally validated in an analytical chemistry experiment class for 3 sessions with 13 university students. We present the result of the prototype development, internal and external validations with quantitative and qualitative data. The AI speaker system enabled students to use the auditory learning mode in the laboratory while concentrating on the experimentation with their hands in the external validation.