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On the State of NLP Approaches to Modeling Depression in Social Media: A Post-COVID-19 Outlook

IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Bucur, Ana-Maria Moldovan, Andreea-Codrina Parvatikar, Krutika Zampieri, Marcos Khudabukhsh, Ashiqur R. Dinu, Liviu P. University of Bucharest Interdisciplinary School of Doctoral Studies Bucharest050663 Romania Universitat Politècnica de València PRHLT Research Center València46020 Spain Rochester Institute of Technology RochesterNY14623 United States George Mason University Fairfax22030 United States University of Bucharest Human Language Technology Research Center Department of Computer Science Faculty of Mathematics and Computer Science Bucharest050663 Romania

Computational approaches to predicting mental health conditions in social media have been substantially explored in the past years. Multiple reviews have been published on this topic, providing the community with comprehensive accounts of the research in this area. Among all mental health conditions, depression is the most widely studied due to its worldwide prevalence. The COVID-19 global pandemic, starting in early 2020, has had a great impact on mental health worldwide. Harsh measures employed by governments to slow the spread of the virus (e.g., lockdowns) and the subsequent economic downturn experienced in many countries have significantly impacted people's lives and mental health. Studies have shown a substantial increase of above 50% in the rate of depression in the population. In this context, we present a review on natural language processing (NLP) approaches to modeling depression in social media, providing the reader with a post-COVID-19 outlook. This review contributes to the understanding of the impacts of the pandemic on modeling depression in social media. We outline how state-of-the-art approaches and new datasets have been used in the context of the COVID-19 pandemic. Finally, we also discuss ethical issues in collecting and processing mental health data, considering fairness, accountability, and ethics. © 2013 IEEE.

关键词： COVID-19

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Threefolded motion perception during immersive walkthroughs 14

Threefolded motion perception during immersive walkthroughs

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20th ACM Symposium on Virtual Reality Software and Technology, VRST 2014

作者： Bruder, Gerd Steinicke, Frank Human-Computer Interaction Department of Computer Science University of Hamburg Germany

ISBN: (纸本)9781450332538

Locomotion is one of the most fundamental processes in the real world, and its consideration in immersive virtual environments (IVEs) is of major importance for many application domains requiring immersive walkthroughs. From a simple physics perspective, such self-motion can be defined by the three components speed, distance, and time. Determining motions in the frame of reference of a human observer imposes a significant challenge to the perceptual processes in the human brain, and the resulting speed, distance, and time percepts are not always veridical. In previous work in the area of IVEs, these components were evaluated in separate experiments, i. e., using largely different hardware, software and protocols. In this paper we analyze the perception of the three components of locomotion during immersive walkthroughs using the same setup and similar protocols. We conducted experiments in an Oculus Rift head-mounted display (HMD) environment which showed that subjects largely underestimated virtual distances, slightly underestimated virtual speed, and we observed that subjects slightly overestimated elapsed time. Copyright © 2014 by the Association for Computing Machinery, Inc (ACM).

关键词： Helmet mounted displays

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Synergistic eigenanalysis of covariance and Hessian matrices for enhanced binary classification on health datasets

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computers in Biology and Medicine 2025年 190卷 109985-109985页

作者： Hartoyo, Agus Argasiński, Jan Trenk, Aleksandra Przybylska, Kinga Blasiak, Anna Crimi, Alessandro Sano – Centre for Computational Personalised Medicine International Research Foundation Krakow Poland Department of Neurophysiology and Chronobiology Institute of Zoology and Biomedical Research Faculty of Biology Jagiellonian University Krakow Poland AGH University of Krakow Krakow Poland School of Computing Telkom University Bandung Indonesia Department of Human-Centered Artificial Intelligence Institute of Applied Computer Science Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Krakow Poland Doctoral School of Exact and Natural Sciences Jagiellonian University Krakow Poland

Covariance and Hessian matrices have been analyzed separately in the literature for classification problems. However, integrating these matrices has the potential to enhance their combined power in improving classification performance. We present a novel approach that combines the eigenanalysis of a covariance matrix evaluated on a training set with a Hessian matrix evaluated on a deep learning model to achieve optimal class separability in binary classification tasks. Our approach is substantiated by formal proofs that establish its capability to maximize between-class mean distance (the concept of separation) and minimize within-class variances (the concept of compactness), which together define the two linear discriminant analysis (LDA) criteria, particularly under ideal data conditions such as isotropy around class means and dominant leading eigenvalues. By projecting data into the combined space of the most relevant eigendirections from both matrices, we achieve optimal class separability as per these LDA criteria. Empirical validation across neural and health datasets consistently supports our theoretical framework and demonstrates that our method outperforms established methods. Our method stands out by addressing both separation and compactness criteria, unlike PCA and the Hessian method, which predominantly emphasize one criterion each. This comprehensive approach captures intricate patterns and relationships, enhancing classification performance. Furthermore, through the utilization of both LDA criteria, our method outperforms LDA itself by leveraging higher-dimensional feature spaces, in accordance with Cover's theorem, which favors linear separability in higher dimensions. Additionally, our approach sheds light on complex DNN decision-making, rendering them comprehensible within a 2D space. © 2025

关键词： Covariance matrix

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Enhancing DDoS Attack Detection in SDN with a Stacked Model Framework Utilizing Deep Neural Networks

Enhancing DDoS Attack Detection in SDN with a Stacked Model ...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Aishita Sharma Sunil K. Singh Sudhakar Kumar Shin Hung Pan Brij B. Gupta Kwok Tai Chui Department of CSE Chandigarh College of Engineering and Technology Chandigarh India Department of Information Management Asia University Taiwan Department of Computer Science and Information Engineering Asia University Taiwan University of Economics and Human Sciences in Warsaw Poland Hong Kong Metropolitan University Hong Kong

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

Software Defined Networking enhances network management and security through centralized control, vital for the growth of consumer electronics. With the rise of smart devices and IoT systems, the demand for scalable network management has intensified. While SDN streamlines network operations and supports essential technologies, it remains vulnerable to DDoS attacks that can disrupt these services. However, SDN environments are vulnerable to Distributed Denial of Service (DDoS) attacks, posing significant risks to operational integrity. This paper analyzes the performance of various machine learning models at the individual level, providing insights into their effectiveness in detecting DDoS attacks. Based on these findings, a hybrid model is introduced, utilizing stacking techniques with a Deep Neural Network (DNN) as the meta-learner. The hybrid approach achieves a remarkable accuracy of 99.09%. The results underscore the crucial role of machine learning, particularly deep learning methodologies, in safeguarding SDN networks against cyber threats. As reliance on complex networked systems in consumer electronics increases, enhancing the security of SDN environments becomes essential for maintaining seamless operations.

关键词： Deep learning Stacking Artificial neural networks Denial-of-service attack Security computer crime Software defined networking Smart devices Consumer electronics Centralized control

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Toward Anxiety-Reducing Pocket Robots for Children

arXiv

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arXiv 2025年

作者： Frederiksen, Morten Roed Stoy, Kasper Matarić, Maja Computer science department of The IT-University of Copenhagen Rued Langgaards vej 7 Copenhagen2300 Denmark Interaction Lab in the Computer Science Department The University of Southern California United States

A common denominator for most therapy treatments for children who suffer from an anxiety disorder is daily practice routines to learn techniques needed to overcome anxiety. However, applying those techniques while experiencing anxiety can be highly challenging. This paper presents the design, implementation, and pilot study of a tactile hand-held pocket robot "AffectaPocket", designed to work alongside therapy as a focus object to facilitate coping during an anxiety attack. The robot does not require daily practice to be used, has a small form factor, and has been designed for children 7 to 12 years old. The pocket robot works by sensing when it is being held and attempts to shift the child’s focus by presenting them with a simple three-note rhythm-matching game. We conducted a pilot study of the pocket robot involving four children aged 7 to 10 years, and then a main study with 18 children aged 6 to 8 years;neither study involved children with anxiety. Both studies aimed to assess the reliability of the robot’s sensor configuration, its design, and the effectiveness of the user tutorial. The results indicate that the morphology and sensor setup performed adequately and the tutorial process enabled the children to use the robot with little practice. This work demonstrates that the presented pocket robot could represent a step toward developing low-cost accessible technologies to help children suffering from anxiety disorders. © 2025, CC BY-NC-ND.

关键词： Machine design

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TOUCHSCREEN FIELD SPECIFICATION FOR PUBLIC-ACCESS DATABASE QUERIES - LET YOUR FINGERS DO THE WALKING 90

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18TH ANNUAL CONF OF THE ASSOC FOR COMPUTING MACHINERY ON computer science : COOPERATION ( CSC 90 )

作者： SEARS, A KOCHAVY, Y SHNEIDERMAN, B Human-Computer Interaction Laboratory Department of Computer Science University of Maryland College Park Maryland

ISBN: (纸本)0897913485

Database query is becoming a common task in public access systems; touchscreens can provide an appealing interface for such a system. This paper explores three interfaces for constructing queries on alphabetic field values with a touchscreen interface; including a QWERTY keyboard, an Alphabetic keyboard, and a Reduced Input Data Entry (RIDE) interface. The RIDE interface allows field values to be entered with fewer “keystrokes” (touches) than either keyboard while eliminating certain errors. In one test database, the RIDE interface required 69% fewer keystrokes than either keyboard interface.

关键词： Database systems

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human-computer interaction department Hewlett-Packard laboratories 89

Human-computer interaction department Hewlett-Packard labora...

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1989 SIGCHI Conference on human Factors in Computing Systems, CHI 1989

作者： Kendzierski, Nancy Human-Computer Interaction Department Software Technology Laboratory P.O. Box 10490 Palo Alto CA 94303-0969 United States

No abstract available.

ISBN: (纸本)0897913019

No abstract available.

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Dietary carbohydrate intake and risk of type 2 diabetes:a 16-year prospective cohort study

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science China(Life sciences) 2025年第4期68卷 1149-1157页

作者： Lu Gan Yi Yang Bin Zhao Kai Yu Kehua Guo Fang Fang Zhiguang Zhou Demetrius Albanes Jiaqi Huang National Clinical Research Center for Metabolic Diseases Metabolic Syndrome Research CenterKey Laboratory of Diabetes ImmunologyMinistry of Educationand Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityCSU-Sinocare Research Center for Nutrition and Metabolic HealthXiangya School of Public HealthCentral South UniversityFurong LaboratoryChangsha410011China Division of Cancer Epidemiology and Genetics National Cancer InstituteNIHDepartment of Health and Human ServicesBethesdaMD20892USA School of Computer Science and Engineering Central South UniversityChangsha410083China Institute of Environmental Medicine Karolinska InstituteStockholm17177Sweden National Clinical Research Center for Metabolic Diseases Key Laboratory of Diabetes ImmunologyMinistry of Educationand Department of Metabolism and EndocrinologyThe Second Xiangya Hospital of Central South UniversityChangsha410011China

Despite considerable research underscoring the importance of carbohydrate intake in relation to the risk of type 2 diabetes(T2D),a comprehensive assessment of this relationship is currently *** aimed to examine the associations of various types and food sources of dietary carbohydrate intake with the risk of T2D,to evaluate potential effect modification by other factors,including genetic susceptibility,and to explore the potential mediators for such *** present study included 161,872 participants of the UK Biobank who were free of prevalent cancer,cardiovascular disease,or diabetes,and had at least one validated 24-h dietary recall *** age-stratified Cox proportional hazard regression models were applied to estimate hazard ratios(HRs)and 95%confidence intervals(CI)for the associations of various types and food sources of dietary carbohydrate intake with risk of *** a median follow-up of 13.6 years,4,176 incident cases of T2D were *** the multivariable-adjusted models,a greater intake of fiber,carbohydrates from whole grains,and carbohydrates from non-starchy vegetables was significantly associated with a lower risk of T2D(highest *** quantile,HR[95%CI]=0.70[0.62–0.79],0.74[0.67–0.82],and 0.83[0.75–0.92],respectively,all P for trend<0.005).In contrast,a higher intake of starch and carbohydrate from starchy vegetables was associated with an increased risk of T2D(highest *** quantile,HR[95%CI]=1.31[1.16–1.48]and 1.19[1.09–1.31],respectively,both P for trend<0.005).Replacing one serving of refined grains or starchy vegetables with an equal amount of whole grains or non-starchy vegetables was associated with 4%to 10%lower risk of T2D(all P values<0.001).The observed associations were generally similar across population subgroups,including individuals with different genetic susceptibility to *** analyses of the inverse association between T2D risk and isocaloric substitution of carbohy

关键词： dietary carbohydrate type 2 diabetes prospective cohort study UK Biobank

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Benefits of merging command selection and direct manipulation

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ACM Transactions on computer-human interaction 2005年第3期12卷 460-476页

作者： Guimbretière, François Martin, Andrew Winograd, Terry University of Maryland Stanford University Human Computer Interaction Laboratory Department of Computer Science University of Maryland College Park MD 20742 Department of Computer Science Stanford University Stanford CA 94305-9035

Toolglass [Bier et al. 1993] demonstrated a two-handed command selection technique that combined command selection and direct manipulation. While empirical evaluations showed a speed advantage for ToolGlass, they did not examine the relative importance of two possible factors in its improved performance: (1) the use of two hands and (2) the merging of command selection and direct manipulation. We conducted a study comparing the relative benefits of three command selection techniques that merge command selection and direct manipulation: one two-handed technique, Toolglass, and two one-handed techniques, namely, control menus [Pook et al. 2000] and FlowMenu [Guimbretière and Winograd 2000], Participants performed sequences of operations that required both selecting a color and designating the endpoints of a line. Our results show that control menus and FlowMenu are significantly faster than Toolglass. Further analysis suggests that the merging of command selection and direct manipulation is the most important factor in the performance of all three techniques. © 2005 ACM.

关键词： human computer interaction

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Unfolding the Headline: Iterative Self-Questioning for News Retrieval and Timeline Summarization

arXiv

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arXiv 2025年

作者： Wu, Weiqi Huang, Shen Jiang, Yong Xie, Pengjun Huang, Fei Zhao, Hai Department of Computer Science and Engineering Shanghai Jiao Tong University China Tongyi Lab Alibaba Group China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China Shanghai Key Laboratory of Trusted Data Circulation and Governance in Web3 China

In the fast-changing realm of information, the capacity to construct coherent timelines from extensive event-related content has become increasingly significant and challenging. The complexity arises in aggregating related documents to build a meaningful event graph around a central topic. This paper proposes CHRONOS - Causal Headline Retrieval for Open-domain News Timeline SummarizatiOn via Iterative Self-Questioning, which offers a fresh perspective on the integration of Large Language Models (LLMs) to tackle the task of Timeline Summarization (TLS). By iteratively reflecting on how events are linked and posing new questions regarding a specific news topic to gather information online or from an offline knowledge base, LLMs produce and refresh chronological summaries based on documents retrieved in each round. Furthermore, we curate Open-TLS, a novel dataset of timelines on recent news topics authored by professional journalists to evaluate open-domain TLS where information overload makes it impossible to find comprehensive relevant documents from the web. Our experiments indicate that CHRONOS is not only adept at open-domain timeline summarization, but it also rivals the performance of existing state-of-the-art systems designed for closed-domain applications, where a related news corpus is provided for summarization. Copyright © 2025, The Authors. All rights reserved.

关键词： Modeling languages

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