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Euromicro Conference on Software Engineering and Advanced Applications (SEAA)

作者： Dario Di Dario Umberto Bilott Maurizio Sibilio Carmine Gravino Fabio Palomba Department of Computer Science SeSa Lab University of Salerno Salerno Italy Department of Human Science Lab H University of Salerno Salerno Italy

In the era of social distancing, distance learning represents a crucial educational challenge. Several 2D information technologies have been provided, yet these share multiple limitations and have negative social, educational, and psychological implications for learners. Metaverse promises to revolutionize education as we know it: this is a persistent, virtual, three-dimensional environment that is supposed to address most of the limitations of 2D information technologies. Nonetheless, there are still software engineering challenges to face to enable such a metaverse, especially when turning to software security and privacy. In this paper, we aim at performing the first steps toward an improved understanding of the security perspective of educational metaverse, by analyzing how blockchain can be employed within educational environments and how applications may be designed. Our ultimate goal is to provide insights into how blockchain can be further tailored in the context of educational metaverse. We conduct a systematic literature review, which targets 20 primary studies. The key findings of the study showcase the use of blockchain in 3 educational tasks, other than describing the blockchain design approaches, which protocol they commonly use and the associated limitations. We conclude by developing a conceptualization of a blockchain-based educational metaverse.

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Augmenting Scientific Creativity with Retrieval across Knowledge Domains

arXiv

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arXiv 2022年

作者： Kang, Hyeonsu B. Mysore, Sheshera Huang, Kevin Chang, Haw-Shiuan Prein, Thorben McCallum, Andrew Kittur, Aniket Olivetti, Elsa Human-Computer Interaction Institute CMU PA United States Manning College of Information and Computer Sciences UMASS AmherstMA United States Department of Materials Science and Engineering MIT MA United States

Exposure to ideas in domains outside a scientist’s own may benefit her in reformulating existing research problems in novel ways and discovering new application domains for existing solution ideas. While improved performance in scholarly search engines can help scientists efficiently identify relevant advances in domains they may already be familiar with, it may fall short of helping them explore diverse ideas outside such domains. In this paper we explore the design of systems aimed at augmenting the end-user ability in cross-domain exploration with flexible query specification. To this end, we develop an exploratory search system in which end-users can select a portion of text core to their interest from a paper abstract and retrieve papers that have a high similarity to the user-selected core aspect but differ in terms of domains. Furthermore, end-users can ‘zoom in’ to specific domain clusters to retrieve more papers from them and understand nuanced differences within the clusters. Our case studies with scientists uncover opportunities and design implications for systems aimed at facilitating cross-domain exploration and inspiration. © 2022, CC BY.

关键词： Search engines

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Astrocytic TRPA1 as a target in reversing social avoidance by low-intensity focused ultrasound stimulation in mice

Astrocytic TRPA1 as a target in reversing social avoidance b...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Ganjiang Wei Ling Wang Jingnan Zhu Xiao Wang Yuran Zang Jiajia Yang Chenguang Zheng Academy of Medical Engineering and Translational Medicine Medical College Tianjin University Tianjin China Tianjin Key Laboratory of Brain Science and Neuroengineering Tianjin China Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Social avoidance is a prominent clinical feature of multiple neuropsychiatric disorders. Increasing evidence showed that the medial prefrontal cortex (mPFC) regulates social avoidance with suppression of excitatory neurons. Our previous study found that the low-intensity focused ultrasound (LIFUS), as a novel noninvasive neuromodulation technique, could alleviate the social avoidance of social defeat stress (SDS) model mice by increasing the mPFC excitation. However, the underlying target of LIFUS on mPFC neurons in social defeated mice remains unclear. Here we injected AAV-shRNA to knock down astrocytic TRPA1 in the mPFC, and investigated whether astrocytic TRPA1 played a crucial role in LIFUS modulation. We found that the social avoidance of SDS mice with TRPA1 knocked down was not affected by LIFUS. Furthermore, LIFUS didn’t induce enhanced expression of membrane NMDAR2A and NMDAR2B in SDS mice with TRPA1 knocked down, compared with that in mice infected with the control virus. It is believed that LIFUS can act on astrocytic TRPA1 to improve social avoidance and hence synaptic function.

关键词： Ultrasonic imaging Modulation Brain modeling Mice Biomembranes Neuromodulation Engineering in medicine and biology Viruses (medical) Stress Immune system

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ToP-ToM: Trust-aware Robot Policy with Theory of Mind

ToP-ToM: Trust-aware Robot Policy with Theory of Mind

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Chuang Yu Baris Serhan Angelo Cangelosi Computer Science Department UCL Interaction Centre University College London London United Kingdom Cognitive Robotics Lab Manchester Centre for Robotics and AI The University of Manchester Manchester United Kingdom

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Theory of Mind (ToM) is a fundamental cognitive architecture that endows humans with the ability to attribute mental states to others. humans infer the desires, beliefs, and intentions of others by observing their behavior and, in turn, adjust their actions to facilitate better interpersonal communication and team collaboration. In this paper, we investigated trust-aware robot policy with the theory of mind in a multi-agent setting where a human collaborates with a robot against another human opponent. We show that by only focusing on team performance, the robot may resort to the reverse psychology trick, which poses a significant threat to trust maintenance. The human’s trust in the robot will collapse when they discover deceptive behavior by the robot. To mitigate this problem, we adopt the robot theory of mind model to infer the human’s trust beliefs, including true belief and false belief (an essential element of ToM). We designed a dynamic trust-aware reward function based on different trust beliefs to guide the robot policy learning, which aims to balance between avoiding human trust collapse due to robot reverse psychology and leveraging its potential to boost team performance. The experimental results demonstrate the importance of the ToM-based robot policy for human-robot trust and the effectiveness of our robot ToM-based robot policy in multiagent interaction settings.

关键词： Psychology Focusing Collaboration Maintenance Robots

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Preface: AVI-CH 2022: Workshop on Advanced Visual Interfaces and interactions in Cultural Heritage 14

Preface: AVI-CH 2022: Workshop on Advanced Visual Interfaces...

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14th AVI-CH Workshop on Advanced Visual Interfaces and interactions in Cultural Heritage, AVI-CH 2022

作者： Antoniou, Angeliki De Carolis, Berardina Kuflik, Tsvi Origlia, Antonio Raptis, George E. Gena, Cristina Department of Archival Library & Information Studies University of West Attica Aegaleo Greece Department of Computer Science University of Bari Bari Italy Information Systems Department The University of Haifa Haifa Israel Department of Electrical Engineering and Information Technologies University of Naples "Federico II" Naples Italy Human Opsis Patras Greece Computer Science Department University of Torino Turin Italy

AVI-CH is the 14th workshop in the series of PATCH workshops, since 2007 and the 4th in a row at AVI. It is the meeting place for researchers and practitioners focusing on the application of advanced information and communication technology (ICT) in cultural heritage with a specific focus on user interfaces, visualization and interaction. This year, eight papers were submitted by researchers from Greece, Italy and Israel. All were accepted. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)

关键词： User interfaces

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The Implementation of Digital Gamification in English Classroom: Teachers' and Students' Perspectives 5

The Implementation of Digital Gamification in English Classr...

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5th International Conference on Education Technology Management, ICETM 2022

作者： Johan, Nur Syarafana Bt Na, Kew Si Tasir, Zaidatun Koh, Tieng Wei Liew, Tze Wei Lee, Sze Seau Faculty of Social Science and Humanities Universiti Teknologi Malaysia Malaysia Nanyang Technological University Singapore Singapore Faculty of Computer Science and Information Technology Universiti Putra Malaysia Malaysia Human-Centric Technology Interaction Sig Multimedia University Melaka Malaysia Faculty of Social Sciences and Liberal Arts Ucsi University Malaysia

ISBN: (纸本)9781450398015

Teaching English is one of many challenging subjects to teach. English teachers have always been trying different methods to maximize students' proficiency and competency in the targeted language as it plays an important role in many aspects, especially in education. Some teachers have sorted to adapt the digital gamification method into their English classroom instruction. Furthermore, teaching using digital gamification is a relatively new concept. In the learning context, digital gamification is an educational method that incorporates game-like elements into the classroom to increase student engagement, promotes a learning environment with positive motivation, and benefits student performance. Research pertaining to digital gamification is growing but very limited study has yet to examine both perspectives of the teachers and the students towards its implementation and how it can influence the engagement level and performance outcomes in a Malaysian context. To urge this matter into the light, this research intended 1) to investigate the teachers' and students' perspectives towards the implementation of digital gamification in English classrooms on an engagement level;2) to investigate the teachers' and students' perspectives towards the implementation of digital gamification in English classrooms on performance outcomes. Adapting the quantitative research method, an online questionnaire consisting of 3 discrete sections to answer the research questions was distributed to 86 respondents from the high schools in Malaysia. Then, using SPSS version 27 the responses from the participants were processed to derive the numerical data such as the frequencies, means, average means, and the standard deviation. The main research findings indicated that both teachers and students have a positive perception of the implementation of digital gamification in the English classroom as it greatly improved the degree of engagement and performance outcome. The finding suggested that

关键词： Students

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Drone-based digital twins for water quality monitoring:A systematic review

Digital Twins and Applications

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Digital Twins and Applications 2024年第2期1卷 131-160页

作者： Abdulmughni Hamzah Faisal Aqlan Sabur Baidya Center for Human Systems Engineering University of LouisvilleLouisvilleKentuckyUSA Department of Industrial Engineering University of LouisvilleLouisvilleKentuckyUSA Department of Computer Science and Engineering University of LouisvilleLouisvilleKentuckyUSA

The rapid advancement of drone technology and digital twin systems has significantly transformed environmental monitoring,particularly in the field of water quality *** paper systematically reviews the current state of research on the application of drones,digital twins,and their integration for water quality monitoring and *** highlights key themes,insights,research trends,commonly used methodologies,and future directions from existing studies,aiming to provide a foundational reference for further research to harness the promising potential of these technologies for effective,scalable solutions in water resource management,addressing both immediate and long-term environmental *** systematic review followed PRISMA guidelines,rigorously analysing hundreds of relevant *** findings emphasise the effective-ness of drones in capturing real-time,high-resolution spatial and temporal data,as well as the value of digital twins for predictive and simulation-based *** importantly,the review demonstrates the potential of integrating these technologies to enhance sus-tainable water management ***,it also identifies a significant research gap in fully integrating drones with digital twins for comprehensive water quality *** response,the review outlines future research directions,including improvements in data integration techniques,predictive models,and interdisciplinary collaboration.

关键词： digital twin drones environmental management water monitoring water quality

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A Review of Physiological Signal Processing via Machine Learning (ML) for Personal Stress Detection 2

A Review of Physiological Signal Processing via Machine Lear...

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2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022

作者： Lourens, Melanie Beram, Shehab Mohamed Borah, Bidyut Bikash Dube, Anand Prakash Deka, Aniruddha Tripathi, Vikas Management Durban University of Technology Department of Human Resources South Africa Department of Computing and Information Systems Kuala Lumpur Malaysia Electronics and Communication Tezpur University Assam Tezpur India Shuats Department of Computer Science & Information Technology U.P. Prayagraj India The Assam Royal Global University Opposite Tirupati Balaji Temple Computer Science and Engineering Assam Betkuchi Guwahati India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9781665437899

Personal stress is maintained and measured by Machine learning. The device which is wearable has been used for the monitoring of personal self stress and data collection. In this research, it has been talked about the factors by which the physiological signal of the stress has been assessed. On the other hand, different type of technology has been used for the detection of the personal stress such as Electrocardiography (ECG) and many other devices. The observation and difficulties has been seen in this research by using this device and the technology. Stress disorder or ailment is one of the most common ailments in all individuals around the world. Stress and anxiety can greatly influence the life, emotion, behavioural pattern and thinking attributes of individuals. It is important to address this issue sooner or later. Psychological signal processing through machine learning effectively assists to detect the stress disorder at an early stage. The general system often considers some variables to detect stress. They are electrocardiogram, galvanic response, heart rate, respiration and many other elements. The ML tend to use algorithms to compare and contrast data to fetch effective e results. The paper has also carried out a statistical analysis based on three variables to fetch a proper result that provided the study group to comprehend a better understanding of the scenario. The researchers have taken the 'percentage of stress rate' cases' are considered independent variables whereas 'usage of a machine learning system' is considered a dependant variable. The study group has fetched and collected numerous data related to these three variables to get a better understanding. © 2022 IEEE.

关键词： Machine learning

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Classification Error Bound for Low Bayes Error Conditions in Machine Learning

Classification Error Bound for Low Bayes Error Conditions in...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zijian Yang Vahe Eminyan Ralf Schlüter Hermann Ney Computer Science Department Machine Learning and Human Language Technology Group Lehrstuhl Informatik 6 RWTH Aachen University Germany AppTek GmbH Germany

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

In statistical classification and machine learning, classification error is an important performance measure, which is minimized by the Bayes decision rule. In practice, the unknown true distribution is usually replaced with a model distribution estimated from the training data in the Bayes decision rule. This substitution introduces a mismatch between the Bayes error and the model-based classification error. In this work, we apply classification error bounds to study the relationship between the error mismatch and the Kullback-Leibler divergence in machine learning. Motivated by recent observations of low model-based classification errors in many machine learning tasks, bounding the Bayes error to be lower, we propose a linear approximation of the classification error bound for low Bayes error conditions. Then, the bound for class priors are discussed. Moreover, we extend the classification error bound for sequences. Using automatic speech recognition as a representative example of machine learning applications, this work analytically discusses the correlations among different performance measures with extended bounds, including cross-entropy loss, language model perplexity, and word error rate.

关键词： Error analysis Measurement uncertainty Linear approximation Training data Machine learning Signal processing Loss measurement Data models Bayes methods Speech processing

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Structure-from-Sherds++: Robust Incremental 3D Reassembly of Axially Symmetric Pots from Unordered and Mixed Fragment Collections

arXiv

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arXiv 2025年

作者： Yoo, Seong Jong Liu, Sisung Arshad, Muhammad Zeeshan Kim, Jinhyeok Kim, Young Min Aloimonos, Yiannis Fermüller, Cornelia Joo, Kyungdon Kim, Jinwook Hong, Je Hyeong Department of Computer Science University of Maryland College ParkMD United States Department of Artificial Intelligence Hanyang University Korea Republic of Faculty of Health Sciences University of Ottawa ON Canada Artificial Intelligence Graduate School UNIST Korea Republic of Department of Electrical and Computer Engineering Seoul National University Korea Republic of Intelligence and Interaction Research Center Korea Institute of Science and Technology Korea Republic of Artificial Intelligence Graduate School The Department of Computer Science and Engineering UNIST Korea Republic of Department of Electronic Engineering Hanyang University Korea Republic of

Reassembling multiple axially symmetric pots from fragmentary sherds is crucial for cultural heritage preservation, yet it poses significant challenges due to thin and sharp fracture surfaces that generate numerous false positive matches and hinder large-scale puzzle solving. Existing global approaches, which optimize all potential fragment pairs simultaneously or data-driven models, are prone to local minima and face scalability issues when multiple pots are intermixed. Motivated by Structure-from-Motion (SfM) for 3D reconstruction from multiple images, we propose an efficient reassembly method for axially symmetric pots based on iterative registration of one sherd at a time, called Structure-from-Sherds++ (SfS++). Our method extends beyond simple replication of incremental SfM and leverages multi-graph beam search to explore multiple registration paths. This allows us to effectively filter out indistinguishable false matches and simultaneously reconstruct multiple pots without requiring prior information such as base or the number of mixed objects. Our approach achieves 87% reassembly accuracy on a dataset of 142 real fragments from 10 different pots, outperforming other methods in handling complex fracture patterns with mixed datasets and achieving state-of-the-art performance. Code and results can be found in our project page https://***/sfs/. Copyright © 2025, The Authors. All rights reserved.

关键词： Historic preservation

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