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5th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2022

作者： Klumbyte, Goda Draude, Claude Taylor, Alex S. Faculty of Electrical Engineering and Computer Science University of Kassel Germany Centre for Human-Computer Interaction Design City University of London United Kingdom

ISBN: (纸本)9781450393522

This paper investigates how intersectional critical theoretical concepts from social sciences and humanities research can be worked with in machine learning systems design. It does so by presenting a case study of a series of speculative design workshops, conducted in 2021. These workshops drew on intersectional feminist methodologies to construct interdisciplinary interventions in the design of machine learning systems, towards more inclusive, accountable, and contextualized systems design. The concepts of "situating/situated knowledges", "figuration", "diffraction", and "critical fabulation/speculation"were taken up as theoretical and methodological tools for concept-led design workshops. This paper presents the design framework of the workshops and highlights tensions and possibilities with regards to interdisciplinary machine learning systems design towards more inclusive, contextualized, and accountable systems. It discusses the role that critical theoretical concepts can play in a design process and shows how such concepts can work as methodological tools that nonetheless require an open-ended experimental space to function. It presents insights and discussion points regarding what it means to work with critical intersectional knowledge that is inextricably connected to its historical and socio-political roots, and how this reframes what it might mean to design fair and accountable systems. © 2022 Owner/Author.

关键词： Systems analysis

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Spatial grids assisted multi-task fusing framework for incremental point cloud mapping of large scenes

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IEEE Transactions on Instrumentation and Measurement 2025年

作者： Luo, Nan Hu, Daoru Liang, Jie Wang, Yifeng Zhao, Hui Wang, Quan Xidian University Key Laboratory of Smart Human Computer Interaction and Wearable Technology of Shannxi Province School of Computer Science and Technology Xi'an710126 China

Recovering the point cloud maps of large-scale scenes from multi-sensor data is the fundamental building block of numerous 3D related applications. Available SLAM (Simultaneous Localization and Mapping) frameworks require rigorous constraints in data capturing and suffer from heavy workload when facing large-scale scenes. To push the research to further extent, this work proposes an incremental multi-task mapping framework for large-scale scenes under the guidance of spatial grids. (1) This framework first encodes the target scene into spatial grids according to the GNSS (The Global Navigation Satellite System) coordinates, then the mapping task is accomplished via multiple sub-scene SLAM tasks that can be executed independently, and finally the mapped point clouds are incrementally aligned with the assistance of encoded spatial grids to form the whole picture of the large-scale scene. (2) In each sub-scene SLAM task, we develop a new fast loop detection method based on spatial grids and perceptual hashing, which replaces the memory-expensive BoW (bag-of-words) model for image similarity determination, saves the unnecessary computational cost and lifts the localization accuracy. (3) In the aligning part, a new grid-wise merging method is designed for sub-scene point clouds, which improves the robustness and efficiency of point cloud registration and the applicability for large-scale scenes, supporting incremental multi-task mapping. We extensively evaluate the localization accuracy, loop detection efficiency on indoor EuRoC dataset, and multi-machine point cloud mapping on outdoor KITTI dataset. Experimental results reveal that the proposed framework provides a feasible multi-task fusing solution for incremental mapping of large scenes. © 1963-2012 IEEE.

关键词： Global positioning system

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Progress of research in the application of ultrasound technology for the treatment of Alzheimer’s disease

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Neural Regeneration Research 2025年第10期20卷 2823-2837页

作者： Qiuquan Cai Lianghui Meng Meina Quan Ling Wang Jing Ren Chenguang Zheng Jiajia Yang Dong Ming Academy of Medical Engineering and Translational Medicine Tianjin UniversityTianjinChina Innovation Center for Neurological Disorders Xuanwu HospitalCapital Medical UniversityBeijingChina Brain-Computer Interaction and Human-Machine Fusion Haihe Laboratory Tianjin UniversityTianjinChina Tianjin Key Laboratory of Brain Science and Neural Engineering Tianjin UniversityTianjinChina

Alzheimer’s disease is a common neurodegenerative disorder defined by decreased reasoning abilities,memory loss,and cognitive *** presence of the blood-brain barrier presents a major obstacle to the development of effective drug therapies for Alzheimer’s *** use of ultrasound as a novel physical modulation approach has garnered widespread attention in recent *** a safe and feasible therapeutic and drug-delivery method,ultrasound has shown promise in improving cognitive *** article provides a summary of the application of ultrasound technology for treating Alzheimer’s disease over the past 5 years,including standalone ultrasound treatment,ultrasound combined with microbubbles or drug therapy,and magnetic resonance imaging-guided focused ultrasound *** is placed on the benefits of introducing these treatment methods and their potential *** found that several ultrasound methods can open the blood-brain barrier and effectively alleviate amyloid-βplaque *** believe that ultrasound is an effective therapy for Alzheimer’s disease,and this review provides a theoretical basis for future ultrasound treatment methods.

关键词： Alzheimer’s disease blood-brain barrier drugs magnetic resonance imaging-guided focused ultrasound microbubbles scanning ultrasound ultrasound ultrasound stimulation

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InterLink: Linking Text with Code and Output in Computational Notebooks 25

InterLink: Linking Text with Code and Output in Computationa...

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2025 CHI Conference on human Factors in Computing Systems, CHI 2025

作者： Lin, Yanna Yang, Leni Li, Haotian Qu, Huamin Moritz, Dominik Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong Hong Kong Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh PA United States Microsoft Research Asia Beijing China

ISBN: (纸本)9798400713941

Computational notebooks, widely used for ad-hoc analysis and often shared with others, can be difficult to understand because the standard linear layout is not optimized for reading. In particular, related text, code, and outputs may be spread across the UI making it difficult to draw connections. In response, we introduce InterLink, a plugin designed to present the relationships between text, code, and outputs, thereby making notebooks easier to understand. In a formative study, we identify pain points and derive design requirements for identifying and navigating relationships among various pieces of information within notebooks. Based on these requirements, InterLink features a new layout that separates text from code and outputs into two columns. It uses visual links to signal relationships between text and associated code and outputs and offers interactions for navigating related pieces of information. In a user study with 12 participants, those using InterLink were 13.6% more accurate at finding and integrating information from complex analyses in computational notebooks. These results show the potential of notebook layouts that make them easier to understand. © 2025 Copyright held by the owner/author(s).

关键词： Computational Notebook Interactive Computational Notebook Text-Code/Output Linking User Comprehension

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How are ML-Based Online Content Moderation Systems Actually Used? Studying Community Size, Local Activity, and Disparate Treatment 22

How are ML-Based Online Content Moderation Systems Actually ...

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5th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2022

作者： Wang, Leijie Zhu, Haiyi Department of Computer Science and Technology Tsinghua University Beijing China Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA United States

ISBN: (纸本)9781450393522

Machine learning-based predictive systems are increasingly used to assist online groups and communities in various content moderation tasks. However, there are limited quantitative understandings of whether and how different groups and communities use such predictive systems differently according to their community characteristics. In this research, we conducted a field evaluation of how content moderation systems are used in 17 Wikipedia language communities. We found that 1) larger communities tend to use predictive systems to identify the most damaging edits, while smaller communities tend to use them to identify any edit that could be damaging;2) predictive systems are used less in content areas where there are more local editing activities;3) predictive systems have mixed effects on reducing disparate treatment between anonymous and registered editors across communities of different characteristics. Finally, we discuss the theoretical and practical implications for future human-centered moderation algorithms. © 2022 Owner/Author.

关键词： Online systems

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Interdisciplinary perspectives on privacy awareness in lifelogging technology development

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Journal of Ambient Intelligence and humanized Computing 2023年第3期14卷 2291-2312页

作者： Wilkowska, Wiktoria Offermann, Julia Colonna, Liane Florez-Revuelta, Francisco Climent-Pérez, Pau Mihailidis, Alex Poli, Angelica Spinsante, Susanna Ziefle, Martina Human-Computer Interaction Center RWTH Aachen University Aachen Germany Swedish Law and Informatics Research Institute Stockholm University Stockholm Sweden Department of Computer Technology University of Alicante Alicante Spain Department of Occupational Science and Occupational Therapy University of Toronto Toronto Canada Department of Information Engineering Marche Polytechnic University Ancona Italy

Population aging resulting from demographic changes requires some challenging decisions and necessary steps to be taken by different stakeholders to manage current and future demand for assistance and support. The consequences of population aging can be mitigated to some extent by assisting technologies that can support the autonomous living of older individuals and persons in need of care in their private environments as long as possible. A variety of technical solutions are already available on the market, but privacy protection is a serious, often neglected, issue when using such (assisting) technology. Thus, privacy needs to be thoroughly taken under consideration in this context. In a three-year project PAAL (‘Privacy-Aware and Acceptable Lifelogging Services for Older and Frail People’), researchers from different disciplines, such as law, rehabilitation, human-computer interaction, and computer science, investigated the phenomenon of privacy when using assistive lifelogging technologies. In concrete terms, the concept of Privacy by Design was realized using two exemplary lifelogging applications in private and professional environments. A user-centered empirical approach was applied to the lifelogging technologies, investigating the perceptions and attitudes of (older) users with different health-related and biographical profiles. The knowledge gained through the interdisciplinary collaboration can improve the implementation and optimization of assistive applications. In this paper, partners of the PAAL project present insights gained from their cross-national, interdisciplinary work regarding privacy-aware and acceptable lifelogging technologies. © 2022, The Author(s).

关键词： human computer interaction

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Practical and Rich User Digitization

arXiv

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arXiv 2024年

作者： Ahuja, Karan Human-Computer Interaction Institute School of Computer Science Carnegie Mellon University PittsburghPA15213 United States

A long-standing vision in computer science has been to evolve computing devices into proactive assistants that enhance our productivity, health and wellness, and many other facets of our lives. User digitization is crucial in achieving this vision as it allows computers to intimately understand their users, capturing activity, pose, routine, and behavior. Today's consumer devices - like smartphones and smartwatches - provide a glimpse of this potential, offering coarse digital representations of users with metrics such as step count, heart rate, and a handful of human activities like running and biking. Even these very low-dimensional representations are already bringing value to millions of people's lives, but there is significant potential for improvement. On the other end, professional, high-fidelity comprehensive user digitization systems exist. For example, motion capture suits and multi-camera rigs that digitize our full body and appearance, and scanning machines such as MRI capture our detailed anatomy. However, these carry significant user practicality burdens, such as financial, privacy, ergonomic, aesthetic, and instrumentation considerations, that preclude consumer use. In general, the higher the fidelity of capture, the lower the user's practicality. Most conventional approaches strike a balance between user practicality and digitization fidelity. My research aims to break this trend, developing sensing systems that increase user digitization fidelity to create new and powerful computing experiences while retaining or even improving user practicality and accessibility, allowing such technologies to have a societal impact. Armed with such knowledge, our future devices could offer longitudinal health tracking, more productive work environments, full-body avatars in extended reality, and embodied telepresence experiences, to name just a few domains. © 2024, CC BY.

关键词： Smartphones

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An Energy-Efficient Task Scheduling Strategy Based on Improved Fireworks Algorithm in Heterogeneous Cloud 23

An Energy-Efficient Task Scheduling Strategy Based on Improv...

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23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Zhao, Hui Meng, Fanxin Feng, Nanzhi Wang, Quan Wan, Bo Wang, Jing School of Computer Science and Technology Xidian University Xi'an China Key Laboratory of Smart Human-Computer Interaction and Wearable Technology of Shaanxi Province Xi'an China

ISBN: (纸本)9781665494571

With the development of cloud computing, energy consumption is getting bigger and bigger, and energy optimization has become one of the research focuses. Task scheduling is an efficient way to reduce the energy consumption of cloud. Most previous works ignored the heterogeneity of physical machines (PMs) configured with different CPUs and GPUs, which may result in high energy consumption in heterogeneous cloud. In this paper, an energy-efficient Task Scheduling Strategy based on Improved Fireworks Algorithm (TSS-IFWA) is proposed to reduce the energy consumption of the CPU/GPU heterogeneous cloud. First, a task scheduling model is constructed, in which the energy consumption of CPUs and GPUs are separately consid-ered. Then we obtain the task scheduling optimization problem of minimizing the energy consumption of heterogeneous cloud. Second, as traditional fireworks algorithm consumes massive computing resource and has a poor convergence performance, we improve a new calculation method of explosion amplitude of the fireworks algorithm. We also optimize the mutation strategy. Third, we utilize the improved fireworks algorithm to solve the task scheduling optimization problem. Specifically, the corre-sponding coding and decoding schemes of the fireworks algorithm are designed to initialize the fireworks individuals. We then obtain task scheduling results. Finally, TSS- IFWA is compared with traditional fireworks algorithm (FWA), round-robin algorithm (RR), and genetic algorithm (GA). The experimental results show that TSS- IFWA has a good performance in reducing energy consumption of heterogeneous cloud. © 2021 IEEE.

关键词： Cloud computing Fireworks algorithm Energy consumption Processor scheduling Scheduling Energy efficiency Explosions

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VTA-NAc neural pathways involved in the mechanism of depression-like behavior induced by chronic sleep deprivation in mice 24

VTA-NAc neural pathways involved in the mechanism of depress...

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11th International Conference on Biomedical and Bioinformatics Engineering, ICBBE 2024

作者： Li, Yaqing Mo, Weiyi Ren, Jing Sun, Tianyi Zheng, Chengguaang Wang, Ling Yang, Jiajia Ming, Dong Medical School Tianjin University Tianjin China ZhejiangLab Zhejiang Hangzhou China Tianjin Key Laboratory of Brain Science and Neuroengineering Tianjin China Haihe Laboratory of Brian-Computer Interaction and Human-Machine Integration Tianjin China

ISBN: (纸本)9798400718274

Sleep plays a crucial role in individual physical and mental health. Insufficient sleep leads to inattention, memory loss, cognitive dysfunction and emotional disorders. The mesolimbic pathway, ventral tegmental area (VTA) to nucleus accumbens (NAc) dopaminergic neural pathway has been shown to be associated with sleep-wake behavior and depression-like behavior. In this study, we investigated the relation between chronic sleep deprivation (CSD)-induced depression-like behaviors and the activity of VTA-NAc dopaminergic pathway. CSD caused weight loss and depression-like behaviors in the mice, including anhedonia and helplessness. CSD prominently reduced the change of mice' s DA signal when moving freely. Additionally, NAc DA release became less noticeable in rewarding event and retreat behavior after exposing to CSD. In conclusion, our findings indicated that VTA-NAc dopaminergic neural pathway is directly related to depressive-like behavior caused by chronic sleep deprivation. This study provides a theoretical basis for the in-depth understanding of the physiological function of sleep, and provides a potential target for clinical research on improving or treating sleep disorder-related depression. Copyright © 2024 held by the owner/author(s). Publication rights licensed to ACM.

关键词： Sleep research

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A Mapping-based Dynamic Semi-Online Task Scheduling Method for Minimizing Energy in Edge Computing 23

A Mapping-based Dynamic Semi-Online Task Scheduling Method f...

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作者： Zhao, Hui Feng, Nanzhi Meng, Fanxin Wang, Quan Wan, Bo Wang, Jing School of Computer Science and Technology Xidian University Xi'an China Key Laboratory of Smart Human-Computer Interaction and Wearable Technology of Shaanxi Province Xi'an China

ISBN: (纸本)9781665494571

Semi-online task scheduling in the edge computing platform refers to a scheduling scenario where there exists unknown performance computing nodes in the system. Existing online and offline task scheduling methods may lead to long makespan or transmission time due to the influence of unknown nodes, and existing semi-online methods are not fully applicable to the scenario discussed in this paper, which aggravates the problem of high energy consumption in edge computing plat-form. To solve this problem, this paper proposes a Mapping-based Dynamic Semi-online Scheduling(MDSS) strategy for edge computing platform. Firstly, we consider three main factors that affect the energy consumption in edge computing platform, that is, the energy consumption of task execution, task transmission and idle state. Then an energy consumption optimization problem is established from the perspectives of the processing speed, routing delay and queuing delay of the edge nodes, which correspond to those three factors. Secondly, for the unknown node, this paper introduces a mapping mechanism, which maps the performance of unknown nodes to a certain given node. Then the mapping relations are dynamically adjusted by continuously checking the task queue lengths of the mapped two-sides. Therefore, the prior knowledge of known nodes can be fully used. Thirdly, an im-proved Power-of- D algorithm based on the mapping mechanism is proposed to solving the formulated problem. It utilizes the prior knowledge of known node performance, which reduces task processing time and transmission time, so that the energy consumption can be reduced. Finally, some experiments are conducted to evaluate MDSS. Results show that the dynamic mapping mechanism is effective in the semi-online scenario and MDSS can greatly reduce the energy consumption in the edge computing platform. © 2021 IEEE.

关键词： Energy consumption Processor scheduling Heuristic algorithms Dynamic scheduling Routing Delays Task analysis

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