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2025 IEEE Symposium on Computational Intelligence in Health and Medicine, CIHM 2025

作者： Pahar, Madhurananda Tao, Fuxiang Mirheidari, Bahman Pevy, Nathan Bright, Rebecca Gadgil, Swapnil Sproson, Lise Braun, Dorota Illingworth, Caitlin Blackburn, Daniel Christensen, Heidi School of Computer Science University of Sheffield SheffieldS1 4DP United Kingdom Therapy Box London United Kingdom NIHR Devices for Dignity HTC Sheffield Teaching Hospitals NHS Foundation Trust SheffieldS10 2JF United Kingdom University of Sheffield SheffieldS10 2HQ United Kingdom

ISBN: (纸本)9798331508333

The early signs of cognitive decline are often noticeable in conversational speech, and identifying those signs is crucial in dealing with later and more serious stages of neurodegenerative diseases. Clinical detection is costly and time-consuming and although there has been recent progress in the automatic detection of speech-based cues, those systems are trained on relatively small databases, lacking detailed metadata and demographic information. This paper presents CognoSpeak and its associated data collection efforts. CognoSpeak asks memory-probing long and short-term questions and administers standard cognitive tasks such as verbal and semantic fluency and picture description using a virtual agent on a mobile or web platform. In addition, it collects multimodal data such as audio and video along with a rich set of metadata from primary and secondary care, memory clinics and remote settings like people’s homes. Here, we present results from 126 subjects whose audio was manually transcribed. Several classic classifiers, as well as large language model-based classifiers, have been investigated and evaluated across the different types of prompts. We demonstrate a high level of performance;in particular, we achieved an F1-score of 0.873 using a DistilBERT model to discriminate people with cognitive impairment (dementia and people with mild cognitive impairment (MCI)) from healthy volunteers using the memory responses, fluency tasks and cookie theft picture description. CognoSpeak is an automatic, remote, low-cost, repeatable, non-invasive and less stressful alternative to existing clinical cognitive assessments. © 2025 IEEE.

关键词： Neurodegenerative diseases

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Parameter Estimation of Multiple Poles by Subspace-Based Method

Parameter Estimation of Multiple Poles by Subspace-Based Met...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Prabhu Vijayan Philippe Dreesen Ivan Markovsky Mariya Ishteva Department of Computer Science ADVISE-NUMA KU Leuven Geel Belgium Department ELEC Vrije Universiteit Brussel Brussel Belgium Department of Advanced Computing Sciences Maastricht University Maastricht The Netherlands Gran Capità International Centre for Numerical Methods in Engineering (CIMNE) Barcelona Spain Catalan Institution for Research and Advanced Studies (ICREA) Barcelona Spain

This work deals with the problem of estimating the parameters (i.e., pole multiplicity structure, pole locations, and complex amplitudes) of exponential polynomials for a given model order. We start from an exponential polynomial signal model and algebraically demonstrate the reasoning behind and the manner in which this model generalizes to the broader class of signals containing multiple poles. The poles and complex amplitudes are estimated by a subspace-based method. With the given model order as prior, a heuristic algorithm is developed to estimate the multiplicity structure of poles. Numerical simulations are conducted to study the performance of the subspace-based method and the sensitivity of poles and multiplicity estimation. Our simulations show that our pole estimation method is accurate for signals with poles of multiplicity greater than one, particularly for signals with lower orders. This allows for successful signal regeneration, producing estimates that closely match the original data. The estimation is sensitive, particularly in the presence of noise, and when the poles are complex and have a higher order of multiplicity.

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Uncertainties About Waste Using an Online Survey and Review Approach: Environmentalist Perceptions, Waste Compositions and Views from Media and science

SSRN

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SSRN 2023年

作者： Markley, Laura A.T. Grünzner, Maja Walker, Tony R. Syracuse University College of Engineering and Computer Science Civil and Environmental Engineering 223 Link Hall SyracuseNY13244 United States University of Vienna Faculty of Psychology Department of Cognition Emotion and Methods Environmental Psychology Group Wächtergasse 1 Vienna1010 Austria School for Resource and Environmental Studies Dalhousie University Halifax Canada

Waste generation and subsequent plastic pollution pose a major threat to both human and environmental health. Furthering our understanding of waste at individual levels can inform future waste reduction strategies, education, and policies. This study explores components and perceptions among individuals using survey data combined with a mini-review. An online Qualtrics survey was distributed pre-COVID19 following a global social media challenge, Futuristic February, which directed participants to collect their non-perishable waste during February 2020. Participants were asked about their waste generation, perceptions toward waste and plastic pollution issues, and environmental worldview using the New Ecological Paradigm (NEP) scale (n=50). We also conducted a mini-review of 8 waste and plastic pollution statements from our survey in both popular media and scientific journal articles. Survey results indicated participants had an overall pro-ecological worldview (M=4.32, SD=0.88) and reported cardboard and paper (66%) as the most commonly occurring non-perishable waste category. Across categories, food packaging was the most common waste type. Participants were most uncertain about statements focusing on bioplastic or biodegradable plastic, respectively (44% and 30%), while the statement on microplastic toxicity obtained 100% mild or strong agreement among participants. Uncertainty for reviewed statements varied depending on topic and group. Popular media and scholarly articles did not always agree, possibly due to differences in communication of uncertainty or terminology definitions. These results can inform future policy and educational campaigns around topics of misinformation. © 2023, The Authors. All rights reserved.

关键词： Health risks

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CognoSpeak: an automatic, remote assessment of early cognitive decline in real-world conversational speech

arXiv

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arXiv 2025年

关键词： Semantics

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Prediction of Flight Arrival Delay Time Using U.S. Bureau of Transportation Statistics

Prediction of Flight Arrival Delay Time Using U.S. Bureau of...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Jiarui Li Ran Ji Cheng'ao Li Xiaoying Yang Jiayi Li Yiran Li Xihan Xiong Yutong Fang Shusheng Ding Tianxiang Cui School of Computer Science University of Nottingham Ningbo China Ningbo China School of Aerospace Engineering University of Nottingham Ningbo China Ningbo China Department of Computing Imperial College London London UK Teaching Research Center Ningbo Open University Ningbo China Business School Ningbo University Ningbo China

According to the data from the Bureau of Trans-portation Statistics (BTS), the number of passengers and flights has been increasing year by year. However, flight delay has become a pervasive problem in the United States in recent years due to various factors, including human factors such as security regulations, as well as natural factors such as bad weather. Flight delay not only affects the profits of airlines but also affects the satisfaction of passengers. Therefore, a model that can predict the arrival time of airplanes needs to be developed. Machine learning methods have been widely applied to prediction problems. In this paper, a variety of machine learning and computational intelligence methods, including linear regression, decision tree (DT), random forest (RF), gradient boosting (GB), gaussian regression models and genetic programming were trained on the U.S. Department of Transportation's (DOT) BTS dataset. The results show that genetic programming performs best and can be used to predict the arrival time of the U.S. flights in advance, which is beneficial for airlines and passengers to make timely decisions.

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Enhanced Labeling Technique for Reddit Text and Fine-Tuned Longformer Models for Classifying Depression Severity in English and Luganda

Enhanced Labeling Technique for Reddit Text and Fine-Tuned L...

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Richard Kimera Daniela N. Rim Joseph Kirabira Ubong Godwin Udomah Heeyoul Choi Department of Advanced Convergence Handong Global University Pohang South Korea School of Computer Science and Electrical Engineering Handong Global University Pohang South Korea Department of Psychiatry Busitema University (Faculty of Health Sciences) Mbale Uganda Department of Psychiatry University of Uyo Teaching Hospital Uyo Akwa Ibom Nigeria

Depression is a global burden and one of the most challenging mental health conditions to control. Using the BDI questionnaire, experts can detect its severity early, administer appropriate medication to patients, and impede its progression. Owing to the fear of potential stigmatization, many patients turn to social media platforms such as Reddit for advice and assistance at various stages of their journey. This research extracts text from Reddit to facilitate the diagnostic process, employs a proposed labelling approach to categorize the text, and subsequently fine-tunes the Longformer model. The model’s performance is compared against the baseline models, including Naive Bayes, Random Forest, Support Vector Machines, and Gradient Boosting. Our findings reveal that the Longformer model outperforms the baseline models in both English (48%) and Luganda (45%) languages on a custom-made dataset.

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Engineering Students’ Attitudes and Perceptions towards Project-Based Learning: A Study from Kerala, Southern India

Engineering Students’ Attitudes and Perceptions towards Pro...

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IEEE International Conference on teaching, Assessment and Learning for Engineering (TALE)

作者： Akshay R S Alviya Sunny Saranya V S Aby John N. P. Subheesh S M Anzar Department of Electronics and Communication Engineering Government Engineering College Trivandrum India Department of Computer Science and Engineering Model Engineering College India Accenture Solutions Pvt Ltd Coimbatore India Faculty of Philology RUDN University Moscow Russia Teaching Learning Centre SRM University - AP Andhra Pradesh India Department of Electronics and Communication Engineering TKM College of Engineering Kollam India

ISBN: (数字)9798350376234

ISBN: (纸本)9798350376241

The shift from teacher-centric to student-centric education has been a subject of debate, with traditional instruction often criticized for fostering rote learning and passive engagement. Due to its emphasis on student autonomy and real-world application of knowledge, the growing popularity of Project-Based Learning as a novel alternative to traditional classroom-based teaching pedagogy is attracting educational institutions all around the world. In engineering education, multifaceted skill development is paramount. PjBL offers a dynamic approach to cultivate essential competencies and it significantly improves engineering education. The National Education Policy 2020 (NEP 2020) of India lays a strong emphasis on Project-Based Learning as the cornerstone of educational reform. But, only smaller number of research studies are conducted in the country to explore the attitudes and perceptions of students towards Project-Based Learning in the engineering sector. It lays bare the imminent need for educationalists to focus on this research gap. This paper explores the attitudes and perceptions of engineering students towards Project-Based Learning from Kerala, a state in Southern India. A novel questionnaire entitled Project-Based Learning in Engineering Education in Kerala (PLEEK) is developed by the IEEE Education Society Kerala Chapter to conduct the survey. A total of 136 students from all over Kerala attended the survey. It is observed that the students have a positive perception of Project-Based Learning and its impact on enhancing their education. On the other hand, an abysmally low count of 11% of students believed that their current campus ecosystem supported this teaching pedagogy. They highlighted the need for a drastic transformation in the present academic infrastructure to support Project-Based Learning. The findings of the study underscore the potential of Project-Based Learning in enhancing learning outcomes, fostering critical skills, and preparing studen

关键词： Surveys Training Hands Ecosystems Engineering students

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Low-Cost Automated Visual Screw Inspection System

Low-Cost Automated Visual Screw Inspection System

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Yiran Li Jiayi LI Xiaoying Yang Cheng'ao Li Xihan Xiong Yutong Fang Shusheng Ding Tianxiang Cui School of Computer Science University of Nottingham Ningbo China Ningbo China School of Aerospace Engineering University of Nottingham Ningbo China Ningbo China Deparment of Computing Imperial College London London UK Teaching Research Center Ningbo Open University Ningbo China Business School Ningbo University Ningbo China

Despite the significant achievements in the development of automation technologies, the application of autonomous robots to improve the production efficiency of small-scale indus-tries has been largely ignored. While there has been excellent progress in industrial image processing systems implementation, most of the work has focused on a unique aspect of specific objects rather than introducing a general inspection system. Thus, this paper discusses the critical industrial topic of quality control, which develops rapidly through the use of autonomous systems. Given the high cost of implementing automated systems, this paper presents an affordable low-budget solution for the visual inspection system. This method of inspecting screw dimensions consists of four visual inspection parts and a special mechanical supporting structure. The designed system was able to check the overall screw dimensions, including screw head diameter, screw head driven type, screw length, screw thread length, and screw head thickness. It could also separate the qualified screws from the unqualified ones after the inspection process. The accuracy of most inspection cases is 100%, meaning the error ranges within 0.1mm, which meets all the non-negotiable requirements and most of the target requirements. The visual inspection parts can be further enhanced by building a template matching library that includes different angles of the screw head or by using Hough Transform to identify the defect types of the screw thread.

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Architecture for disaster relief networks in underground coal mines: A survey 9

Architecture for disaster relief networks in underground coa...

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2019 9th International Workshop on computer science and Engineering, WCSE 2019

作者： Gu, Jie Xue, Pengfei Lin, Sheng Zhang, Guopeng Teaching and Research Support Center Airforce Logistics University Xuzhou221116 China School of Computer Science and Technology China University of Mining and Technology Xuzhou221116 China

ISBN: (纸本)9789811416842

It is increasingly being recognized that dedicated emergency networks are vital interfaces between rescue teams and trapped-miners in underground mines. This article proposes a network architecture for rescue applications in post-disaster mines, termed as Post-Disaster Emergency Network (PDEN). First, the special requirements for configuring a PDEN are outlined. Then, the emergency data flows transported in a PDEN are classified into uplink flows and downlink flows. The problem of transmission priority differentiation for uplink flows, and the energy efficiency for downlink transmissions are both examined. Finally, some primary numerical results are presented to reveal the effectiveness of the proposed PDEN architecture. © WCSE 2019. All rights reserved.

关键词： Network architecture

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Who Said what? An Automated Approach to Analyzing Speech in Preschool Classrooms

Who Said what? An Automated Approach to Analyzing Speech in ...

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IEEE International Conference on Development and Learning, ICDL

作者： Anchen Sun Juan J Londono Batya Elbaum Luis Estrada Roberto Jose Lazo Laura Vitale Hugo Gonzalez Villasanti Riccardo Fusaroli Lynn K Perry Daniel S Messinger Department of Electrical and Computer Engineering University of Miami Coral Gables FL USA Department of Psychology University of Miami Coral Gables FL USA Department of Teaching and Learning University of Miami Coral Gables FL USA Department of Mechanical Engineering University of Michigan Ann Arbor MI USA Department of Linguistics Cognitive Science and Semiotics Aarhus University Aarhus C Denmark

ISBN: (数字)9798350348552

ISBN: (纸本)9798350348569

Young children spend substantial portions of their waking hours in noisy preschool classrooms. In these environments, children's vocal interactions with teachers are critical contributors to their language outcomes, but manually transcribing these interactions is prohibitive. Using audio from child- and teacher-worn recorders, we propose an automated framework that uses open source software both to classify speakers (ALICE) and to transcribe their utterances (Whisper). We compare results from our framework to those from a human expert for 110 minutes of classroom recordings, including 85 minutes from child-word microphones ( $\mathrm{n}=4$ children) and 25 minutes from teacher-worn microphones ( $\mathrm{n}=2$ teachers). The overall proportion of agreement, that is, the proportion of correctly classified teacher and child utterances, was. 76, with an error-corrected kappa of. 50 and a weighted F1 of. 76. The word error rate for both teacher and child transcriptions was. 15, meaning that 15% of words would need to be deleted, added, or changed to equate the Whisper and expert transcriptions. Moreover, speech features such as the mean length of utterances in words, the proportion of teacher and child utterances that were questions, and the proportion of utterances that were responded to within 2.5 seconds were similar when calculated separately from expert and automated transcriptions. The results suggest substantial progress in analyzing classroom speech that may support children's language development. Future research using natural language processing is under way to improve speaker classification and to analyze results from the application of the automated framework to a larger dataset containing classroom recordings from 13 children and 3 teachers observed on 17 occasions over one year.

关键词： Error analysis Current measurement Pipelines Natural language processing Recording Reliability Noise measurement

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