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Communicative Grounding of Analogical Explanations in Dialogue: A Corpus Study of Conversational Management Acts and Statistical Sequence Models for Tutoring through Analogy

Communicative Grounding of Analogical Explanations in Dialog...

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2021 Conference on Reasoning and interaction, ReInAct 2021

作者： Del-Bosque-Trevino, Jorge Hough, Julian Purver, Matthew Education Lab. Computational Linguistics Lab. Cognitive Science Research Group School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom Human Interaction Lab. Computational Linguistics Lab. Cognitive Science Research Group School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom Jožef Stefan Institute Computational Linguistics Lab. Cognitive Science Research Group School of Electronic Engineering and Computer Science Queen Mary University of London United Kingdom

ISBN: (纸本)9781955917070

We present a conversational management act (CMA) annotation schema for one-to-one tutorial dialogue sessions where a tutor uses an analogy to teach a student a concept. CMAs are more fine-grained sub-utterance acts compared to traditional dialogue act markup. The schema achieves an inter-annotator agreement (IAA) Cohen Kappa score of at least 0.66 across all 10 classes. We annotate a corpus of analogical episodes with the schema and develop statistical sequence models from the corpus which predict tutor content related decisions, in terms of the selection of the analogical component (AC) and tutor conversational management act (TCMA) to deploy at the current utterance, given the student’s behaviour. CRF sequence classifiers perform well on AC selection and robustly on TCMA selection, achieving respective accuracies of 61.9% and 56.3% on a cross-validation experiment over the corpus. © 2021 Association for Computational Linguistics.

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The Need for the human-Centred Explanation for ML-based Clinical Decision Support Systems

The Need for the Human-Centred Explanation for ML-based Clin...

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IEEE International Conference on Healthcare Informatics (ICHI)

作者： Yan Jia John McDermid Nathan Hughes Mark Sujan Tom Lawton Ibrahim Habli Department of Computer Science University of York York UK Human Factors Everywhere Ltd UK Bradford Royal Infirmary and Bradford Institute for Health Research Bradford UK

Machine learning has shown great promise in a variety of applications, but the deployment of these systems is hindered by the "opaque" nature of machine learning algorithms. This has led to the development of explainable AI methods, which aim to provide insights into complex algorithms through explanations that are comprehensible to humans. However, many of the explanations currently available are technically focused and reflect what machine learning researchers believe constitutes a good explanation, rather than what users actually want. This paper highlights the need to develop human-centred explanations for machine learning-based clinical decision support systems, as clinicians who typically have limited knowledge of machine learning techniques are the users of these systems. The authors define the requirements for human-centred explanations, then briefly discuss the current state of available explainable AI methods, and finally analyse the gaps between human-centred explanations and current explainable AI methods. A clinical use case is presented to demonstrate the vision for human-centred explanations.

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Theory of Mind Abilities Predict Robot's Gaze Effects on Object Preference

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IEEE Transactions on Affective Computing 2025年

作者： Manzi, Federico Ishikawa, Mitsuhiko Dio, Cinzia Di Itakura, Shoji Kanda, Takayuki Ishiguro, Hiroshi Massaro, Davide Marchetti, Antonella Università Cattolica del Sacro Cuore Research Unit on Theory of Mind Department of Psychology Milan Italy Università Cattolica del Sacro Cuore Research Unit in Psychology and Robotics in the Lifespan Department of Psychology Milan Italy IRCCS Fondazione Don Carlo Gnocchi Milan Italy Hitotsubashi University Hitotsubashi Institute for Advanced Study Japan Ritsumeikan University Kyoto Japan Kyoto University Department of Computer Science Human-Robot Interaction Laboratory Kyoto Japan IRC'HIL Keihana Science City Advanced Telecommunications Research Institute International Kyoto Japan Osaka University Department of Intelligent Systems Toyonaka Japan

This study investigated the differences between human and robot gaze in influencing preference formation, and examined the role of Theory of Mind (ToM) abilities in this process. human eye gaze is one of the most important sources of information for social interaction and research has demonstrated its effectiveness in influencing people's preference. With increasing technological development, we will interact with robots that can exhibit gaze behavior and influence people's preference. It is unclear whether there are any differences between humans and robots in this process. The present study aimed to analyze the role of the gaze of a robot and a human in influencing the ascription of a preference to the gazer and the participants' preference. Furthermore, we examined the role of ToM abilities in preference formation. The results showed that the gaze has a greater effect on the gazer preference compared to participants' preference regardless of the agent (human or robot). In addition, ToM abilities predict both gazer and individual preferences in the robot's condition only even though different socio-cognitive mechanisms are involved. The study suggests that adults are cognitively able to process the gaze of a robot similar to a human, recognizing the underlying mental state. However, only for the robot, different cognitive mechanisms are involved in the gazer (i.e., perspective taking) and participants' preference formation (i.e., advanced ToM). © 2010-2012 IEEE.

关键词： Social robots

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PrescriptIQ: Revolutionizing Healthcare with AI-Powered Multilingual Prescription Decoding 5

PrescriptIQ: Revolutionizing Healthcare with AI-Powered Mult...

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5th International Conference on Image Processing and Capsule Networks, ICIPCN 2024

作者： Roja Ramani, D. Santhosh Krishna, B.V. Balaji, L. Sathyanarayanan, S. Muthumanickam, M. Kaliappan, S. Computer Science and Engineering New Horizon College of Enineering Bengaluru India Electronics and Communication Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Technology Chennai India Sri Sathya Sai University for Human Excellence Gulbarga Karnataka Electronics & Communication RMK College of Engineering and Technology Chennai India Department of Mechanical Engineering AMITY University Dubai United Aram Emirates

ISBN: (纸本)9798350367171

In healthcare, legible prescription information is crucial but often compromised by hurried, illegible handwriting. This can lead to misinterpretation and errors in medication dispensing, posing risks to patient safety. Moreover, the inefficiency caused by unclear prescriptions can contribute to delays in treatment and administrative challenges for healthcare providers. In response to these issues, the 'PrescriptIQ' system introduces an innovative solution by leveraging advanced artificial intelligence technologies to interpret handwritten prescriptions accurately and efficiently. This research introduces a new multilingual handwriting identification system, 'PrescriptIQ,' which aims to translate handwritten prescriptions into understandable text. The system uses deep fusion techniques in consecutive computational steps that include picture enhancement and text segmentation, merging CNNs and FLSTM (Fusion of LSTM) networks for improved performance. Additionally, fuzzy search strategies are used to improve prescription accuracy and patient safety. By standardizing decoded text with Unicode mapping, the technology enables correct translation into many languages, bridging the digital and traditional prescription systems. This development has the potential to transform medication administration and patient care globally. © 2024 IEEE.

关键词： Patient treatment

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Trade-Offs Between Fairness and Privacy in Language Modeling

arXiv

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arXiv 2023年

作者： Matzken, Cleo Eger, Steffen Habernal, Ivan Trustworthy Human Language Technologies Department of Computer Science Technical University of Darmstadt Germany Natural Language Learning Group Faculty of Technology Universität Bielefeld Germany

Protecting privacy in contemporary NLP models is gaining in importance. So does the need to mitigate social biases of such models. But can we have both at the same time? Existing research suggests that privacy preservation comes at the price of worsening biases in classification tasks. In this paper, we explore the extent to which this tradeoff really holds when we incorporate both privacy preservation and debiasing techniques into training text generation models. How does improving the model along one dimension affect the other dimension as well as the utility of the model? We conduct an extensive set of experiments that include bias detection, privacy attacks, language modeling, and performance on downstream tasks. © 2023, CC BY.

关键词： Economic and social effects

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Hybrid WDM and Optical-CDMA over Multi-Mode Fiber Transmission System based on Optical Vortex 5

Hybrid WDM and Optical-CDMA over Multi-Mode Fiber Transmissi...

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5th International Conference on Electronic Design, ICED 2020

作者： Ghazi, Alaan Aljunid, S.A. Zulkarnain Syed Idrus, Syed Endut, R. Rashidi, C.B.M. Ali, N. Al-Dawoodi, Aras Fakhrudeen, Ahmed M. Fareed, Alaa Sharma, Teena School of Human Development and Techno-communication University Malaysia Perlis Malaysia School of Computer and Communication Engineering University Malaysia Perlis Malaysia Computer Science Department College of Computer Science and Information Technology Kirkuk University Iraq Networks Department College of Computer Science and Information Technology Kirkuk University Iraq Computer Technical Engineering Alkitab University Iraq School of Computing University Utara Malaysia Malaysia Centre of Excellence Universiti Malaysia Perlis Malaysia Universiti Malaysia Perlis Perlis Malaysia Department of Electronics and Communication Engineering Malviya National Institute of Technology Jaipur India

The optical vortex has recently attracted scholars to implement it in optical tweezers, microscopy, optical communications, quantum information processing, optical trapping, and laser machining. Optical vortex beam applied classically that can be transferred to the transverse amplitude of a heralded single-photon, and optical vortex possesses a helical wavefront and carries orbital angular momentum. In this study, Optical vortex is applied in optical-CDMA (optical code-division multiple-access) in conjunction with WDM (wavelength division multiplexing). This mechanism aims to increase the capacity and security in optical communication significantly. The implementation of Laguerre-Gaussian (LG) modes with optical vortex based on one dimension zero cross-correlation (ZCC) code shows that mode coupling reduces effectively. Consequently, a positive increase in channel performance and response. Accordingly, the LG modes based on the 1D-ZCC code are investigated and propagated over multi-mode fiber (MMF) based on an optical vortex, which also substantially reduces channel effects. Consequently, all these attributes combined will result in a hybrid WDM-Optical-CDMA with an optical vortex system over MMF. © 2021 Published under licence by IOP Publishing Ltd.

关键词： Optical tweezers

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Explainable human-centered Traits from Head Motion and Facial Expression Dynamics

arXiv

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arXiv 2023年

作者： Madan, Surbhi Gahalawat, Monika Guha, Tanaya Goecke, Roland Subramanian, Ramanathan Department of Computer Science Indian Institute of Technology Ropar India The Human-Centred Technology Research Centre Faculty of Science and Technology University of Canberra ACT Australia The School of Computing Science University of Glasgow United Kingdom

We explore the efficacy of multimodal behavioral cues for explainable prediction of personality and interview-specific traits. We utilize elementary head-motion units named kinemes, atomic facial movements termed action units and speech features to estimate these human-centered traits. Empirical results confirm that kinemes and action units enable discovery of multiple trait-specific behaviors while also enabling explainability in support of the predictions. For fusing cues, we explore decision and feature-level fusion, and an additive attention-based fusion strategy which quantifies the relative importance of the three modalities for trait prediction. Examining various long-short term memory (LSTM) architectures for classification and regression on the MIT Interview and First Impressions Candidate Screening (FICS) datasets, we note that: (1) Multimodal approaches outperform unimodal counterparts;(2) Efficient trait predictions and plausible explanations are achieved with both unimodal and multimodal approaches, and (3) Following the thin-slice approach, effective trait prediction is achieved even from two-second behavioral snippets. © 2023, CC BY.

关键词： Forecasting

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Age differences in the anticipated acceptance of egoistic versus altruistic crash-control-algorithms in automated vehicles 20

Age differences in the anticipated acceptance of egoistic ve...

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2020 Conference on Mensch und computer, MuC 2020

作者： Wischert-Zielke, Moritz Weigl, Klemens Steinhauser, Marco Riener, Andreas Catholic University Eichstätt-Ingolstadt Department of Psychology Eichstätt Germany Human-Computer Interaction Group Ingolstadt Germany

ISBN: (纸本)9781450375405

This paper presents the results of an online questionnaire study (N = 97) which examined participants' anticipated acceptance of crash-control-algorithms (CCAs, i.e., algorithms aimed at effecting certain ethical accident outcomes). Concerning a self-sacrifice trolley dilemma, participants displayed a specific age-dependent pattern, in which both younger (18 - 44 years) and older (65+ years) participants rated their acceptance for egoistic algorithms higher and for altruistic algorithms lower when compared to middle-aged participants (45 - 64 years). © 2020 ACM.

关键词： Accidents

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Smart MOOC integrated with intelligent tutoring: A system architecture and framework model proposal

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computers and Education: Artificial Intelligence 2022年 3卷

作者： Yilmaz, Ramazan Yurdugül, Halil Karaoğlan Yilmaz, Fatma Gizem Şahin, Muhittin Sulak, Sema Aydin, Furkan Tepgeç, Mustafa Müftüoğlu, Cennet Terzi Omer ORAL Bartın University Faculty of Science Department of Computer Technology and Information Systems Turkey Hacettepe University Faculty of Education Department of Computer Education and Instructional Technology Turkey Presidency of the Republic of Turkey Human Resources Office Ankara Turkey

Massive Open Online Courses (MOOCs) are a type of Learning Management Systems (LMSs), but it seems that the influence of the instructor in these systems is minimal or simply lacking. These systems present the learning content and materials to all learners attending the course in the same way and fail to offer individualized instruction that recognizes the individual differences and needs of the learners. It is reported that such problems can be eliminated by making the new generation intelligent learning systems. However, there is still an ongoing search for making such systems intelligent and a conceptual discussion concerning them. Integrating an intelligent tutoring system (ITS) with learning analytics, this study seeks to design and present the framework of an ITS with open access that a) identifies the learning needs of learners through adaptive mastery testing and guides learners based on these needs, b) overcomes learning deficiencies, monitors learners' interactions with content through learning analytics and offers suggestions, c) supports learning with dynamic assessment processes and d) tests learners’ learning competencies. This article aims to explain the conceptual and system framework for the design of an adaptive, dynamic, intelligent tutoring system (SMIT), supported by learning analytics, which is a product of the project, which aims to integrate LMS and ITS, on the idea of how to make systems such as MOOCs smarter. In line with the findings obtained from the research, various suggestions were made for the design of smart Moocs. © 2022 The Authors

关键词： Data mining

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Development of a compact mouse retinal imaging system using spectral domain optical coherence tomography (SD-OCT) with a full field stimulation channel for recording fast optoretinograms (ORGs) 34

Development of a compact mouse retinal imaging system using ...

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Ophthalmic Technologies XXXIV 2024

作者： Jo, Hang Chan Pijewska, Ewelina Meleppat, Ratheesh K. Jonnal, Ravi S. Kim, Dae Yu Zawadzki, Robert J. Department of Electrical and Computer Engineering Inha University 100 Inha-ro Michuhol-gu Incheon22212 Korea Republic of Dept. of Ophthalmology and Vision Science UC Davis Eye Center SacramentoCA95817 United States UC Davis Eye-Pod Small Animal Ocular Imaging Laboratory Department of Cell Biology and Human Anatomy University of California Davis 4320 Tupper Hall DavisCA95616 United States

ISBN: (纸本)9781510669079

While the a-wave of mouse electroretinogram (ERG) occurs within 50 milliseconds after exposure to light, the optoretinogram (ORG) slower than a 20Hz sampling rate could face limitations in observing immediate morphological changes from the retina. In this study, we develop a compact custom-built mouse ORG system based on spectral domain optical coherence tomography (SD-OCT) for 100Hz~1KHz B-scan rates comprised of 100 kHz A-scans. All the optics of the developed ORG system are designed on a 24 x 24 inches optical breadboard to move easily as well as to combine with the ERG system in a dark room. Without using a fundus camera, the OCT system provides en-face images from high-pass filtering and square of the OCT spectral signal for mouse retinal positioning in-vivo before acquiring ORG data. The 490nm LED for light stimulus is generated to make uniform illumination at the mouse retina using the Maxwellian view method. The common path of the OCT scanning light and the visible LED is built with achromatic doublet lens combinations based on optical simulation with Opticstudio® . The developed compact ORG system can not only observe light-evoked responses with 1~10 milliseconds but also be used for the studies of correlations between ORG and ERG in the mouse retina. © 2024 SPIE.

关键词： Optical tomography

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