论文1
Title: A 6G meta-device for 3D varifocal
Author(s): Zhang, JC (Zhang, Jing Cheng); Wu, GB (Wu, Geng-Bo); et.al
Source: SCIENCE ADVANCES 2023 JAN 27
Abstract: The sixth-generation (6G) communication technology is being developed in full swing and is expected to be faster and better than the fifth generation. The precise information transfer directivity and the concentration of signal strength are the key topics of 6G technology. We report the synthetic phase design of rotary doublet Airy beam and triplet Gaussian beam varifocal meta-devices to fully control the terahertz beam's propagation direction and coverage area. The focusing spot can be delivered to arbitrary positions in a two-dimensional plane or a three-dimensional space. The highly concentrated signal can be delivered to a specific position, and the transmission direction can be adjusted freely to enable secure, flexible, and high-directivity 6G com-munication systems. This technology avoids the high costs associated with extensive use of active components. 6G communication systems, wireless power transfer, zoom imaging, and remote sensing will benefit from large-scale adoption of such a technology.
Accession Number: WOS:000934904500018
Corresponding Address: Tsai, DP; Chan, CH (corresponding author), City Univ Hong Kong, Dept Elect Engn, Hong Kong, Peoples R China.
论文2
Title: Integrated-resonant metadevices: a review
Author(s): Yao, J (Yao, Jin); Lin, R (Lin, Rong); et.al
Source: ADVANCED PHOTONICS 2023 MAR
Abstract: Integrated-resonant units (IRUs), associating various meta-atoms, resonant modes, and functionalities into one supercell, have been promising candidates for tailoring composite and multifunctional electromagnetic responses with additional degrees of freedom. Integrated-resonant metadevices can overcome many bottlenecks in conventional optical devices, such as broadband achromatism, efficiency enhancement, response selectivity, and continuous tunability, offering great potential for performant and versatile application scenarios. We focus on the recent progress of integrated-resonant metadevices. Starting from the design principle of IRUs, a variety of IRU-based characteristics and subsequent practical applications, including achromatic imaging, light-field sensing, polarization detection, orbital angular momentum generation, metaholography, nanoprinting, color routing, and nonlinear generation, are introduced. Existing challenges in this field and opinions on future research directions are also provided.
Accession Number: WOS:000979545600004
Corresponding Address: Tsai, DP (corresponding author), City Univ Hong Kong, Dept Elect Engn, Hong Kong, Peoples R China.
论文3
Title: Artificial intelligence in radiology: 100 commercially available products and their scientific evidence
Author(s): van Leeuwen, KG (van Leeuwen, Kicky G.);et.al
Source: EUROPEAN RADIOLOGY 2021 JUN
Abstract: Objectives Map the current landscape of commercially available artificial intelligence (AI) software for radiology and review the availability of their scientific evidence. Methods We created an online overview of CE-marked AI software products for clinical radiology based on vendor-supplied product specifications (). Characteristics such as modality, subspeciality, main task, regulatory information, deployment, and pricing model were retrieved. We conducted an extensive literature search on the available scientific evidence of these products. Articles were classified according to a hierarchical model of efficacy. Results The overview included 100 CE-marked AI products from 54 different vendors. For 64/100 products, there was no peer-reviewed evidence of its efficacy. We observed a large heterogeneity in deployment methods, pricing models, and regulatory classes. The evidence of the remaining 36/100 products comprised 237 papers that predominantly (65%) focused on diagnostic accuracy (efficacy level 2). From the 100 products, 18 had evidence that regarded level 3 or higher, validating the (potential) impact on diagnostic thinking, patient outcome, or costs. Half of the available evidence (116/237) were independent and not (co-)funded or (co-)authored by the vendor. Conclusions Even though the commercial supply of AI software in radiology already holds 100 CE-marked products, we conclude that the sector is still in its infancy. For 64/100 products, peer-reviewed evidence on its efficacy is lacking. Only 18/100 AI products have demonstrated (potential) clinical impact.
Accession Number: WOS:000640472000001
Corresponding Address: van Leeuwen, KG (corresponding author), Radboud Univ Nijmegen, Dept Med Imaging, Med Ctr, POB 9101, NL-6500 HB Nijmegen, Netherlands.
论文4
Title: The medical algorithmic audit
Author(s): Liu, XX (Liu, Xiaoxuan); Glocker, B (Glocker, Ben); et.al
Source: LANCET DIGITAL HEALTH 2022 MAY
Abstract: Artificial intelligence systems for health care, like any other medical device, have the potential to fail. However, specific qualities of artificial intelligence systems, such as the tendency to learn spurious correlates in training data, poor generalisability to new deployment settings, and a paucity of reliable explainability mechanisms, mean they can yield unpredictable errors that might be entirely missed without proactive investigation. We propose a medical algorithmic audit framework that guides the auditor through a process of considering potential algorithmic errors in the context of a clinical task, mapping the components that might contribute to the occurrence of errors, and anticipating their potential consequences. We suggest several approaches for testing algorithmic errors, including exploratory error analysis, subgroup testing, and adversarial testing, and provide examples from our own work and previous studies. The medical algorithmic audit is a tool that can be used to better understand the weaknesses of an artificial intelligence system and put in place mechanisms to mitigate their impact. We propose that safety monitoring and medical algorithmic auditing should be a joint responsibility between users and developers, and encourage the use of feedback mechanisms between these groups to promote learning and maintain safe deployment of artificial intelligence systems.
Accession Number: WOS:000821560800016
Corresponding Address: Ookden-Rayner, L (corresponding author), Univ Adelaide, Australian Inst Machine Learning, Adelaide, SA 5000, Australia.
论文5
Title: Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: A mixed-methods study
Author(s): Nadarzynski, T (Nadarzynski, Tom); Miles, O (Miles, Oliver);et.al
Source: DIGITAL HEALTH2019 AUG
Abstract: Background Artificial intelligence (AI) is increasingly being used in healthcare. Here, AI-based chatbot systems can act as automated conversational agents, capable of promoting health, providing education, and potentially prompting behaviour change. Exploring the motivation to use health chatbots is required to predict uptake; however, few studies to date have explored their acceptability. This research aimed to explore participants' willingness to engage with AI-led health chatbots. Methods The study incorporated semi-structured interviews (N-29) which informed the development of an online survey (N-216) advertised via social media. Interviews were recorded, transcribed verbatim and analysed thematically. A survey of 24 items explored demographic and attitudinal variables, including acceptability and perceived utility. The quantitative data were analysed using binary regressions with a single categorical predictor. Results Three broad themes: 'Understanding of chatbots', 'AI hesitancy' and 'Motivations for health chatbots' were identified, outlining concerns about accuracy, cyber-security, and the inability of AI-led services to empathise. The survey showed moderate acceptability (67%), correlated negatively with perceived poorer IT skills OR = 0.32 [CI95%:0.13-0.78] and dislike for talking to computers OR = 0.77 [CI95%:0.60-0.99] as well as positively correlated with perceived utility OR = 5.10 [CI95%:3.08-8.43], positive attitude OR = 2.71 [CI95%:1.77-4.16] and perceived trustworthiness OR = 1.92 [CI95%:1.13-3.25]. Conclusion Most internet users would be receptive to using health chatbots, although hesitancy regarding this technology is likely to compromise engagement. Intervention designers focusing on AI-led health chatbots need to employ user-centred and theory-based approaches addressing patients' concerns and optimising user experience in order to achieve the best uptake and utilisation. Patients' perspectives, motivation and capabilities need to be taken into account when developing and assessing the effectiveness of health chatbots.
Accession Number: WOS:000483763600001
Corresponding Address: Nadarzynski, T (corresponding author), Univ Westminster, 115 New Cavendish St, London W1W 6UW, England.
论文6
Title: Artificial Intelligence in Meta-optics
Author(s): Chen, MK (Chen, Mu Ku); Liu, XY (Liu, Xiaoyuan);et.al
Source: CHEMICAL REVIEWS 2022 JUN
Abstract: Recent years have witnessed promising artificial intelligence (AI) applications in many disciplines, including optics, engineering, medicine, economics, and education. In particular, the synergy of AI and meta-optics has greatly benefited both fields. Meta-optics are advanced flat optics with novel functions and light-manipulation abilities. The optical properties can be engineered with a unique design to meet various optical demands. This review offers comprehensive coverage of meta-optics and artificial intelligence in synergy. After providing an overview of AI and meta-optics, we categorize and discuss the recent developments integrated by these two topics, namely AI for meta-optics and meta-optics for AI. The former describes how to apply AI to the research of meta-optics for design, simulation, optical information analysis, and application. The latter reports the development of the optical Al system and computation via meta-optics. This review will also provide an in-depth discussion of the challenges of this interdisciplinary field and indicate future directions. We expect that this review will inspire researchers in these fields and benefit the next generation of intelligent optical device design.
Accession Number: WOS:000819493300001
Corresponding Address: Tsai, DP (corresponding author), City Univ Hong Kong, Dept Elect Engn, Kowloon, Hong Kong 999077, Peoples R China.
论文7
Title: Towards Intelligent-TPACK: An empirical study on teachers' professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education
Author(s): Celik, I (Celik, Ismail)
Source: COMPUTERS IN HUMAN BEHAVIOR 2023 JAN
Abstract: The affordances of artificial intelligence (AI) have not been totally utilized in education. To effectively integrate AI into education, teachers' AI-specific technological and pedagogical knowledge is important. Furthermore, due to novel ethical issues caused by Al, teachers also must have the knowledge to assess AI-based decisions. None of the previous studies so far explored teacher knowledge to pedagogically and ethically use AI-based tools. Considering this gap, we first developed a scale to measure the knowledge for instructional AI use based on the technological, pedagogical, and content knowledge (TPACK) framework. We extended TPACK with ethical as-pects. Secondly, we built a model to investigate the interplay of TPACK components and ethics. The results indicated that as long as teachers have more knowledge to interact with AI-based tools, they will have a better understanding of the pedagogical contributions of AI. Further, technological knowledge (TK) allows teachers to better assess decisions of AI. However, only TK is not sufficient educational integration of AI-based tools. For teachers to deploy AI in education efficiently, TK is meaningful when it is combined with pedagogical knowledge (PK), reflected in technological pedagogical knowledge (TPK). Given pedagogical and technological affordances of AI-based tools, the current study suggests the Intelligent-TPACK framework.
Accession Number: WOS:000911463200008
Corresponding Address: Celik, I (corresponding author), Univ Oulu, Fac Educ, Learning & Learning Proc Res Unit, FI-90014 Oulu, Finland.
论文8
Title: Teachers' AI digital competencies and twenty-first century skills in the post-pandemic world
Author(s): Ng, DTK (Ng, Davy Tsz Kit); Leung, JKL (Leung, Jac Ka Lok);et.al
Source: ETR&D-EDUCATIONAL TECHNOLOGY RESEARCH AND DEVELOPMENT 2023 FEB
Abstract: The pandemic has catalyzed a significant shift to online/blended teaching and learning where teachers apply emerging technologies to enhance their students' learning outcomes. Artificial intelligence (AI) technology has gained its popularity in online learning environments during the pandemic to assist students' learning. However, many of these AI tools are new to teachers. They may not have rich technical knowledge to use AI educational applications to facilitate their teaching, not to mention developing students' AI digital capabilities. As such, there is a growing need for teachers to equip themselves with adequate digital competencies so as to use and teach AI in their teaching environments. There are few existing frameworks informing teachers of necessary AI competencies. This study first explores the opportunities and challenges of employing AI systems and how they can enhance teaching, learning and assessment. Then, aligning with generic digital competency frameworks, the DigCompEdu framework and P21's framework for twenty-first century learning were adapted and revised to accommodate AI technologies. Recommendations are proposed to support educators and researchers to promote AI education in their classrooms and academia.
Accession Number: WOS:000936173900001
Corresponding Address: Ng, DTK (corresponding author), Univ Hong Kong, Fac Educ, Hong Kong, Peoples R China.
论文9
Title: AI literacy in K-12: a systematic literature review
Author(s): Casal-Otero, L (Casal-Otero, Lorena); Catala, A (Catala, Alejandro); et.al
Source: INTERNATIONAL JOURNAL OF STEM EDUCATION 2023 APR 19
Abstract: The successful irruption of AI-based technology in our daily lives has led to a growing educational, social, and political interest in training citizens in AI. Education systems now need to train students at the K-12 level to live in a society where they must interact with AI. Thus, AI literacy is a pedagogical and cognitive challenge at the K-12 level. This study aimed to understand how AI is being integrated into K-12 education worldwide. We conducted a search process following the systematic literature review method using Scopus. 179 documents were reviewed, and two broad groups of AI literacy approaches were identified, namely learning experience and theoretical perspective. The first group covered experiences in learning technical, conceptual and applied skills in a particular domain of interest. The second group revealed that significant efforts are being made to design models that frame AI literacy proposals. There were hardly any experiences that assessed whether students understood AI concepts after the learning experience. Little attention has been paid to the undesirable consequences of an indiscriminate and insufficiently thought-out application of AI. A competency framework is required to guide the didactic proposals designed by educational institutions and define a curriculum reflecting the sequence and academic continuity, which should be modular, personalized and adjusted to the conditions of the schools. Finally, AI literacy can be leveraged to enhance the learning of disciplinary core subjects by integrating AI into the teaching process of those subjects, provided the curriculum is co-designed with teachers.
Accession Number: WOS:000971423000001
Corresponding Address: Catala, A (corresponding author), Univ Santiago De Compostela, Dept Elect Comp, Santiago De Compostela 15782, Spain.
图文：车晓燕
编辑：吴继军 责编: 惠文玲
审核：戴玉华 易 久
