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International Conference on Modern Circuits and Systems Technologies (MOCAST)

作者： Konstantinos-Filippos Kollias Luis Miguel Maia Marques Torres E Silva Panagiotis Sarigiannidis Christine K. Syriopoulou-Delli George F. Fragulis Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Faculty of Engineering University of Porto Porto Portugal Department of Educational and Social Policy University of Macedonia Thessaloniki Greece

Early Autism Spectrum Disorder (ASD) diagnosis and intervention with state-of-the-art instruments, such as Artificial Intelligence and Robots is a rather challenging and promising research area which can optimise outcomes regarding the quality of life of ASD individuals and their families. Autistic individuals tend to show, among others, deficits in emotion recognition and expression. The present review study, aiming to review the literature concerning the contribution of Robotics to ASD research, found 27 review studies conducted from 2016 to February 2023 on PubMed and Web of Science databases in which robots were either employed in ASD diagnosis, or emotion recognition and expression. Results pointed out beneficial effects of robots’ employment as far as ASD diagnosis and emotion recognition and expression are concerned. Limitations and recommendations for future research are also involved, i.e., studies combining the Internet of Things (IoT) and Robotics with an aim to early ASD diagnosis, assessment, intervention, and inclusion.

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VERVE: Template-based ReflectiVE Rewriting for MotiVational IntErviewing

arXiv

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arXiv 2023年

作者： Min, Do June Pérez-Rosas, Verónica Resnicow, Kenneth Mihalcea, Rada Department of Electrical Engineering and Computer Science United States School of Public Health University of Michigan Ann ArborMI United States

Reflective listening is a fundamental skill that counselors must acquire to achieve proficiency in motivational interviewing (MI). It involves responding in a manner that acknowledges and explores the meaning of what the client has expressed in the conversation. In this work, we introduce the task of counseling response rewriting, which transforms non-reflective statements into reflective responses. We introduce VERVE, a template-based rewriting system with paraphrase-augmented training and adaptive template updating. VERVE first creates a template by identifying and filtering out tokens that are not relevant to reflections and constructs a reflective response using the template. Paraphrase-augmented training allows the model to learn less-strict fillings of masked spans, and adaptive template updating helps discover effective templates for rewriting without significantly removing the original content. Using both automatic and human evaluations, we compare our method against text rewriting baselines and show that our framework is effective in turning non-reflective statements into more reflective responses while achieving a good content preservation-reflection style trade-off. © 2023, CC BY.

关键词： Economic and social effects

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UAV weaknesses against deauthentication based hijacking attacks

UAV weaknesses against deauthentication based hijacking atta...

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International Symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： Brúnó Krasnyánszki Sándor Tihamér Brassai András Németh Under Graduate Student in Computer Science Engineering Óbuda University Budapest Hungary Department of Electrical Engineering Sapientia Hungarian University of Transylvania Corunca Romania Department of Electronic Warfare National University of Public Service Budapest Hungary

Unmanned Aerial Vehicles (UAVs) and Unmanned Aerial Systems (UAS) are more important than ever before and we’re using it daily for agriculture, photo making, film industry, Search & Rescue, long range cable quality control, Geo Informatics, cartography, and state use (including border protection, disaster recovery and the military). Most of the UAV/UAS devices are using digital communication protocols nowadays, especially the IEEE 802.11 Wireless Local Area of Network for the cheaper and middle price UAV/UAS. Unfortunately, the protocols specified by the previously mentioned IEEE standard are vulnerable against some attacks. This research paper proposes a method that can interrupt the normal operation of the UAV/UAS that are using the IEEE 802.11 protocol and hijack the interrupted UAV/UAS permanently. For this method, deauthentication attack has been performed against the UAV/UASs. The attack vector is capable of denying the communication between the UAV and the control station. With sufficient prior knowledge it is possible to hijack the UAV that communicates on a 802.11 based protocol. Deauthentication based attacks are much more sophisticated than for example traditional electronic jamming, because the target can be precisely chosen and the attack will not interrupt other devices using the same communication method. The research has unfortunately some limitations in equipment, measurements conducted only in three different types of UAVs from three price categories, but in the future the authors would like to extend the range of UAVs. From this three UAVs two are hijackable by this method and the third should also be hijackable with some modifications. This research could be a base later for UAV/UAS counter measure systems for the safety of all of us.

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Plow-Shaped Wideband Antenna for mm-wave 5G Communication

Plow-Shaped Wideband Antenna for mm-wave 5G Communication

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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022

作者： Kiani, Saad Hassan Rafique, Umair Alibakhshikenari, Mohammad Falcone, Fransisco Dalarsson, Mariana IIC University of Technology Department of Electrical Engineering Phnom Penh Cambodia Sapienza University Department of Information Engineering Electronics and Telecommunications Rome00184 Italy Universidad Carlos III de Madrid Department of Signal Theory and Communications Leganés28911 Spain Public University of Navarre Electric Electronic and Communication Engineering Department Pamplona31006 Spain Public University of Navarre Institute of Smart Cities Pamplona31006 Spain KTH Royal Institute of Technology School of Electrical Engineering and Computer Science StockholmSE 100-44 Sweden

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

In this paper, a simple planar plow-shaped wideband antenna is presented for mm-wave 5G devices. The proposed antenna is designed on a thin substrate with an overall size of 10×12 mm2. The results show that the antenna offers 49.5% fractional bandwidth ranging from 22.2 GHz to 36.8 GHz. Moreover, the radiation efficiency of the antenna is >90% throughout the operating bandwidth, with a peak gain of 3.3 dBi. Through its simple structure and high performance characteristics, it can be observed that the proposed antenna can be termed as a potential candidate for future mm-wave 5G communication devices. © 2022 IEEE.

关键词： Radiation efficiency

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Stimulating creativity and grit of high school students with creative STEM activities: an RCT with noncompliance

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Quality and Quantity 2024年第1期59卷 605-634页

作者： Ballerini, Veronica Dominici, Alice Ferracane, Martina Francesca Menchetti, Fiammetta Noirjean, Silvia Department of Statistics Computer Science Applications “G. Parenti” University of Florence Florence Italy Department of Economics European University Institute Fiesole Italy Dondena Centre for Research on Social Dynamics and Public Policy Bocconi University Milan Italy School of Computing Engineering & amp Digital Technologies Teesside University Middlesbrough United Kingdom Robert Schuman Centre for Advanced Studies European University Institute Fiesole Italy

Creativity and grit are widely recognized as vital components for the success and prosperity of individuals, even more so for younger people who will have to deal with the complex challenges connected to the digital era. Yet, whether these skills can be learnt or are innate traits is still subject to debate, which is further complicated by the difficulty of defining and, in turn, assessing these concepts. In this study, we challenge the idea that creativity and grit cannot be learnt and show that creative pedagogy activities, such as those offered by FabLabs, are powerful tools to enhance these non-cognitive skills. We conduct a randomized controlled trial in which 710 students from five Italian high schools are randomly assigned to creative STEM courses. The courses are delivered by FabLabs, small-scale workshops that offer access to tools for digital fabrication and employ a hands-on pedagogical approach expected to impact students’ creativity and grit positively. Assignment to the courses is at the class level: only students in classes randomly selected to join the Fablab activities can participate, and they may decide whether to enrol or not on a voluntary basis. We address noncompliance by adopting an instrumental variable approach. We use two modalities to measure creativity: a self-assessment through the Short Scale of Creative Self and an assessment made by an independent expert using an index of creativity developed by the authors. While the effect on self-assessed creativity is not significant, results show that the external, independent assessment of students’ creativity can capture a significant effect of Fablabs’ courses. It also emerges that FabLab activities have a positive significant effect on students’ grit, measured through the Duckworth scale. The encouraging results obtained for a relatively small sample of students should prompt a replication of the experiment on a broader scale. © The Author(s) 2024.

关键词： Causal inference Creative pedagogy FabLabs Instrumental variables Noncompliance

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DOMINO++: Domain-Aware Loss Regularization for Deep Learning Generalizability 26th

DOMINO++: Domain-Aware Loss Regularization for Deep Learning...

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26th International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2023

作者： Stolte, Skylar E. Volle, Kyle Indahlastari, Aprinda Albizu, Alejandro Woods, Adam J. Brink, Kevin Hale, Matthew Fang, Ruogu Gainesville United States Torch Technologies LLC ShalimarFL United States Center for Cognitive Aging and Memory McKnight Brain Institute UF Gainesville United States Department of Clinical and Health Psychology College of Public Health and Health Professions UF Gainesville United States Department of Neuroscience College of Medicine UF Gainesville United States United States Air Force Research Laboratory Eglin Air Force Base ValparaisoFL United States Department of Electrical and Computer Engineering Herbert Wertheim College of Engineering UF Gainesville United States Department of Computer Information and Science and Engineering Herbert Wertheim College of Engineering UF Gainesville United States Department of Mechanical and Aerospace Engineering Herbert Wertheim College of Engineering UF Gainesville United States

ISBN: (纸本)9783031439001

Out-of-distribution (OOD) generalization poses a serious challenge for modern deep learning (DL). OOD data consists of test data that is significantly different from the model’s training data. DL models that perform well on in-domain test data could struggle on OOD data. Overcoming this discrepancy is essential to the reliable deployment of DL. Proper model calibration decreases the number of spurious connections that are made between model features and class outputs. Hence, calibrated DL can improve OOD generalization by only learning features that are truly indicative of the respective classes. Previous work proposed domain-aware model calibration (DOMINO) to improve DL calibration, but it lacks designs for model generalizability to OOD data. In this work, we propose DOMINO++, a dual-guidance and dynamic domain-aware loss regularization focused on OOD generalizability. DOMINO++ integrates expert-guided and data-guided knowledge in its regularization. Unlike DOMINO which imposed a fixed scaling and regularization rate, DOMINO++ designs a dynamic scaling factor and an adaptive regularization rate. Comprehensive evaluations compare DOMINO++ with DOMINO and the baseline model for head tissue segmentation from magnetic resonance images (MRIs) on OOD data. The OOD data consists of synthetic noisy and rotated datasets, as well as real data using a different MRI scanner from a separate site. DOMINO++’s superior performance demonstrates its potential to improve the trustworthy deployment of DL on real clinical data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Magnetic resonance

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Miniaturization of High Voltage Power Supply for Portable Electrostatic Filtration

Miniaturization of High Voltage Power Supply for Portable El...

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Annual Conference of Industrial Electronics Society

作者： Jia Hao Joe Wang Cynthia Yu Cameron Urquhart Zane Hernke Jan Leuca Espelien Christopher Simpson Igor Novosselov Alexander Mamishev SpectTree LLC Seattle WA USA School of Public Health University of Washington Seattle WA USA Department of Electrical and Computer Engineering University of Washington Seattle WA USA Dept. of Electrical Engineering Columbia University New York NY USA Department of Mechanical Engineering University of Washington Seattle WA USA

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

Electrostatic Precipitation (ESP) is an effective method of removing particulates from the air. It is currently used in many large-scale industrial applications but sees limited use in smaller-scale cases due to the difficulty of generating high voltage in small packages. Additionally, safety concerns prevent the widespread use of this effective technique. This paper presents the motivation, design, and evaluation of a miniature high-voltage DC (HVDC) power supply for applications in small-scale ESP systems. The power supply’s potential for portable ESP application is tested on a personal protective device, the so-called Smart, Individualized, Noncontact, Extended-Wear (SINEW) mask. The results show that the power supply operates with acceptable efficiency and generates high voltages and power necessary to drive ESP setups in practical applications.

关键词： Electric potential Power supplies Filtration Electromagnetic interference High-voltage techniques Transformers Topology Electrostatics Wireless fidelity Testing

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Virtual Co-Pilot: Multimodal Large Language Model-enabled Quick-access Procedures for Single Pilot Operations

Virtual Co-Pilot: Multimodal Large Language Model-enabled Qu...

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Artificial Intelligence (CAI), IEEE Conference on

作者： Fan Li Shanshan Feng Yuqi Yan Ching-Hung Lee Yew Soon Ong Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University HKSAR Centre for Frontier AI Research A*STAR School of Public Policy and Administration Xi'an Jiaotong University Xi’an China School of Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (数字)9798350354096

ISBN: (纸本)9798350354102

Advancements in technology, pilot shortages, and cost pressures are driving a trend towards single-pilot and even remote operations in aviation. Considering the extensive workload and huge risks associated with single-pilot operations, the development of a Virtual Co-Pilot (V-CoP) is expected to be a potential way to ensure aviation safety. This study proposes a V-CoP concept and explores how humans and virtual assistants can effectively collaborate. A preliminary case study is conducted to explore a critical role of V-CoP, namely automated quick procedures searching, using the multimodal large language model (LLM). The LLM-enabled V-CoP integrates the pilot’s instruction and real-time cockpit instrumental data to prompt applicable aviation manuals and operation procedures. The results showed that the LLM-enabled V-CoP achieved high accuracy in situational analysis (90.5%) and effective retrieval of procedure information (86.5%). The proposed V-CoP is expected to provide a foundation for future virtual intelligent assistant development, improve the performance of single pilots, and reduce the risk of human errors in aviation.

关键词： Error analysis Virtual assistants Large language models Instruments Knowledge based systems Manuals Market research

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The motivated can encrypt (Even with PGP)

arXiv

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arXiv 2021年

作者： Borradaile, Glencora Kretschmer, Kelsy Gretes, Michele LeClerc, Alexandria School of Electrical Engineering and Computer Science School of Public Policy Oregon State University

Existing end-to-end-encrypted (E2EE) email systems, mainly PGP, have long been evaluated in controlled lab settings. While these studies have exposed usability obstacles for the average user and offer design improvements, there exist users with an immediate need for private communication, who must cope with existing software and its limitations. We seek to understand whether individuals motivated by concrete privacy threats, such as those vulnerable to state surveillance, can overcome usability issues to adopt complex E2EE tools for long-term use. We surveyed regional activists, as surveillance of social movements is well-documented. Our study group includes individuals from 9 social movement groups in the US who had elected to participate in a workshop on using Thunderbird+Enigmail for email encryption. These workshops tool place prior to mid-2017, via a partnership with a non-profit which supports social movement groups. Six to 40 months after their PGP email encryption training, more than half of the study participants were continuing to use PGP email encryption despite intervening widespread deployment of simple E2EE messaging apps such as Signal. We study the interplay of usability with social factors such as motivation and the risks that individuals undertake through their activism. We find that while usability is an important factor, it is not enough to explain long term use. For example, we find that riskiness of one's activism is negatively correlated with long-term PGP use. This study represents the first long-term study, and the first in-the-wild study, of PGP email encryption adoption. © 2021, CC BY.

关键词： Usability engineering

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Addressing Intersectionality, Explainability, and Ethics in AI-Driven Diagnostics: A Rebuttal and Call for Transdiciplinary Action

arXiv

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arXiv 2025年

作者： Tan, Myles Joshua Toledo Benos, Panayiotis V. Department of Electrical and Computer Engineering Herbert Wertheim College of Engineering University of Florida GainesvilleFL32611 United States Department of Epidemiology College of Public Health & Health Professions College of Medicine University of Florida GainesvilleFL32610 United States

The increasing integration of artificial intelligence (AI) into medical diagnostics necessitates a critical examination of its ethical and practical implications. While the prioritization of diagnostic accuracy, as advocated by Sabuncu et al. (2025), is essential, this approach risks oversimplifying complex socio-ethical issues, including fairness, privacy, and intersectionality. This rebuttal emphasizes the dangers of reducing multifaceted health disparities to quantifiable metrics and advocates for a more transdisciplinary approach. By incorporating insights from social sciences, ethics, and public health, AI systems can address the compounded effects of intersecting identities and safeguard sensitive data. Additionally, explainability and interpretability must be central to AI design, fostering trust and accountability. This paper calls for a framework that balances accuracy with fairness, privacy, and inclusivity to ensure AI-driven diagnostics serve diverse populations equitably and ethically. © 2025, CC BY.

关键词： Differential privacy

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