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arXiv 2024年

作者： Sidrane, Chelsea Tumova, Jana The Division of Robotics Perception and Learning Intelligent Systems Department School of Electrical Engineering & Computer Science KTH Royal Institute of Technology Brinellvägen 8 Stockholm114 28 Sweden

Reachable set computation is an important tool for analyzing control systems. Simulating a control system can show that the system is generally functioning as desired, but a formal tool like reachability analysis can provide a guarantee of correctness. For linear systems, reachability analysis is straightforward and fast, but as more complex components are added to the control system such as nonlinear dynamics or a neural network controller, reachability analysis may slow down or become overly conservative. To address these challenges, much literature has focused on spatial refinement, e.g., tuning the discretization of the input sets and intermediate reachable sets. However, this paper addresses a different dimension: temporal refinement. The basic idea of temporal refinement is to automatically choose when along the horizon of the reachability problem to execute slow symbolic queries which incur less approximation error versus fast concrete queries which incur more approximation error. Temporal refinement can be combined with other refinement approaches and offers an additional "tuning knob" with which to trade off tractability and tightness in approximate reachable set computation. Here, we introduce an automatic framework for performing temporal refinement and we demonstrate the effectiveness of this technique on computing approximate reachable sets for nonlinear systems with neural network control policies. We demonstrate the calculation of reachable sets of varying approximation error under varying computational budget and show that our algorithm is able to generate approximate reachable sets with a similar amount of error to the baseline approach in 20-70% less time. © 2024, CC BY.

关键词： Linear systems

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Metrics in a Dynamic Gaze Environment

Metrics in a Dynamic Gaze Environment

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IEEE International Workshop on Medical Measurement and Applications (MEMEA)

作者： Aidan Lochbihler Bruce Wallace Kathleen Van Benthem Chris Herdman Will Sloan Kirsten Brightman Rafik Goubran Frank Knoefel Shawn Marshall Systems and Computer Engineering Carleton University Ottawa Canada Systems and Computer Engineering Carleton University Bruyère Research Institute SAM Innovation Hub Ottawa Canada Department of Cognitive Science Carleton University Ottawa Canada SAM Innovation Hub Ottawa Canada Bruyère Research Institute Elisabeth-Bruyère Hospital Systems and Computer Engineering Carleton University SAM 3 Innovation Hub Ottawa Canada Ottawa Hospital Carleton University

ISBN: (数字)9798350307993

ISBN: (纸本)9798350308006

The development of algorithms for Areas of Interest (AOIs) segmentation represents a significant leap in dynamic gaze data analysis. These algorithms enable the transformation of two-dimensional raw data into meaningful one-dimensional metrics to unlock insights into human attention. Unlike traditional methods that focus on static gaze points in controlled environments, this research introduces novel algorithms for interpreting eye-tracking data in dynamic settings. The proposed techniques specifically address the challenge of processing gaze information in scenarios with changing frames of reference, such as driving, where understanding visual attention is critical for safety and to improve performance. This paper presents two innovative metrics designed to quantify the focus areas, duration, and scanning patterns of users in dynamic driving conditions. By employing advanced transfer learning for improved multiclass image segmentation methods, a percentage time AOI metric can be created. This metric gives insight into the amount of time a driver spends fixating on a given area. An enhancement in gaze pattern determination, achieved through class segmentation, provides a clearer depiction of drivers' true gaze patterns. This nuanced approach suggests that comprehensive attention assessment cannot rely solely on AOI metrics but requires the integration of gaze pattern derived metrics for a more accurate determination of attention-related scores. The introduction of these innovative gaze analysis methods marks a pivotal advancement in cognitive research and has practical applications. These metrics promise significant contribution to driver safety and attentiveness assessment methodologies.

关键词： Measurement Image segmentation Visualization Data analysis Heuristic algorithms Transfer learning Gaze tracking

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A Comprehensive Evaluation on Event Reasoning of Large Language Models

arXiv

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arXiv 2024年

作者： Tao, Zhengwei Jin, Zhi Zhang, Yifan Chen, Xiancai Zhao, Haiyan Li, Jia Liang, Bing Tao, Chongyang Liu, Qun Wong, Kam-Fai MOE School of Computer Science Peking University China Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong Beihang University China Huawei Noah’s Ark Lab Canada

Event reasoning is a fundamental ability that underlies many applications. It requires event schema knowledge to perform global reasoning and needs to deal with the diversity of the inter-event relations and the reasoning paradigms. How well LLMs accomplish event reasoning on various relations and reasoning paradigms remains unknown. To mitigate this disparity, we comprehensively evaluate the abilities of event reasoning of LLMs. We introduce a novel benchmark EV2 for EValuation of EVent reasoning. EV2consists of two levels of evaluation of schema and instance and is comprehensive in relations and reasoning paradigms. We conduct extensive experiments on EV2. We find that LLMs have abilities to accomplish event reasoning but their performances are far from satisfactory. We also notice the imbalance of event reasoning abilities in LLMs. Besides, LLMs have event schema knowledge, however, they’re not aligned with humans on how to utilize the knowledge. Based on these findings, we guide the LLMs in utilizing the event schema knowledge as memory leading to improvements on event reasoning. Code and Dataset are available on https://***/TZWwww/EV2. Copyright © 2024, The Authors. All rights reserved.

关键词： Natural language processing systems

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Recycling as a Service: IoT Enabled Smart Waste Management System with Machine Learning

Recycling as a Service: IoT Enabled Smart Waste Management S...

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Knowledge engineering and Communication systems (ICKECS), International Conference on

作者： R Poonkuzhali M Karamath P Sugumaran M Tharun S Arun Department of Information Technology K. S. Rangasamy College of Technology Tiruchengode India Computer Science and Business Systems Sri Sai Ram Engineering College Chennai India

ISBN: (数字)9798350359688

ISBN: (纸本)9798350359695

This paper introduces Smart Waste Management (SWM), a system integrating IoT technology and ML algorithms to enhance waste management efficiency. By leveraging real-time data from IoT sensors in waste bins, SWM dynamically optimizes collection routes and schedules. ML algorithms analyze data on fill levels and environmental factors to predict waste generation patterns, enabling informed decision-making. This adaptive approach minimizes fuel consumption, reduces costs, and lowers carbon emissions. SWM also offers actionable insights through customizable dashboards, empowering authorities to implement proactive measures such as predictive maintenance and targeted public awareness campaigns. Overall, the integration of IoT and ML technologies presents a transformative solution to optimize resource allocation, promote sustainability, and foster a cleaner urban environment.

关键词： Waste management Schedules Heuristic algorithms Urban areas Prediction algorithms Real-time systems Recycling

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Sparkling Silence: Practices and Challenges of Livestreaming Among Deaf or Hard of Hearing Streamers

arXiv

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arXiv 2023年

作者： Cao, Beiyan He, Changyang Zhou, Muzhi Fan, Mingming The Hong Kong University of Science and Technology Hong Kong Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong Division of Social Science The Hong Kong University of Science and Technology Hong Kong Hong Kong Division of Integrative Systems and Design Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong

Understanding livestream platforms' accessibility challenges for minority groups, such as people with disabilities, is critical to increasing the diversity and inclusion of those platforms. While prior work investigated the experiences of streamers with vision or motor loss, little is known about the experiences of deaf or hard of hearing (DHH) streamers who must work with livestreaming platforms that heavily depend on audio. We conducted semi-structured interviews with DHH streamers to learn why they livestream, how they navigate livestream platforms and related challenges. Our findings revealed their desire to break the stereotypes towards the DHH groups via livestream and the intense interplay between interaction methods, such as sign language, texts, lip language, background music, and viewer characteristics. Major accessibility challenges include the lack of real-time captioning, the small sign language reading window, and misinterpretation of sign language. We present design considerations for improving the accessibility of the livestream platforms. © 2023, CC BY-NC-ND.

关键词： Audition

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Three-dimensional Chaotic Fractional Maps without Fixed Points: Dynamics, Coexisting Hidden Attractors and Hardware Implementation

Three-dimensional Chaotic Fractional Maps without Fixed Poin...

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2023 International Conference on Fractional Differentiation and Its Applications, ICFDA 2023

作者： Grassi, Giuseppe Khennaoui, Amina Aicha Ouannas, Adel Pham, Viet-Thanh Universita Del Salento Dipartimento Ingegneria Innovazione Lecce Italy University of Constantine 2 Ntic Faculty Tlsi Department Constantine Algeria University of Oum El-Bouaghi Department of Mathematics and Computer Science Algeria Ton DucThang University Nonlinear Systems and Applications Faculty of Electrical and Electronics Engineering Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350321685

In recent years there has been a great interest in investigating the dynamic properties of fractional systems, described by differential or difference equations of non-integer order. A number of manuscripts have been written regarding the presence of chaos in fractional maps characterized by the existence of both 'self-excited attractors' and 'hidden attractors However, most of the papers have dealt with the underlying theory in chaotic dynamics, rather than the hardware implementation of the maps. Specifically, referring to the realization of fractional maps with 'hidden attractors no paper has been published so far. The paper aims to bridge the gap between theory and implementation by presenting the first example of hardware realization of a three-dimensional (3D) fractional map characterized by coexisting chaotic hidden attractors. The manuscript exploits first the Grunwald-Letnikov fractional difference operator to introduce a new class of chaotic discrete systems without fixed points. Then, the coexistence of several chaotic hidden attractors is shown, along with the coexistence of a number of bifurcations, depending on the values of the initial conditions. Finally, the conceived 3D fractional map is implemented in hardware via a microcontroller. The motivation is to probe the presence of coexisting chaotic hidden attractors in real working systems described by non-integer order difference equations. © 2023 IEEE.

关键词： Difference equations

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Research on Deep Learning Model of Feature Extraction Based on Convolutional Neural Network

Research on Deep Learning Model of Feature Extraction Based ...

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Image Processing and computer Applications (ICIPCA), IEEE International Conference on

作者： Houze Liu Iris Li Yaxin Liang Dan Sun Yining Yang Haowei Yang Department Computer Science and Engineering New York University New York USA Graduate School of Art & Science New York University New York USA Viterbi School of Engineering University of Southern California Los Angeles USA Department of Electrical and Systems Engineering Washington University St. Louis USA School of Computer Science Carnegie Mellon University Pittsburgh USA Cullen College of Engineering University of Houston Houston USA

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

Neural networks with relatively shallow layers and simple structures may have limited ability in accurately identifying pneumonia. In addition, deep neural networks also have a large demand for computing resources, which may cause convolutional neural networks to be unable to be implemented on terminals. Therefore, this paper will carry out the optimal classification of convolutional neural networks. Firstly, according to the characteristics of pneumonia images, AlexNet and InceptionV3 were selected to obtain better image recognition results. Combining the features of medical images, the forward neural network with deeper and more complex structure is learned. Finally, knowledge extraction technology is used to extract the obtained data into the AlexNet model to achieve the purpose of improving computing efficiency and reducing computing costs. The results showed that the prediction accuracy, specificity, and sensitivity of the trained AlexNet model increased by 4.25 percentage points, 7.85 percentage points, and 2.32 percentage points respectively. The graphics processing usage has decreased by 51% compared to the InceptionV3 mode.

关键词： Deep learning Pneumonia Accuracy Sensitivity Computational modeling Feature extraction Convolutional neural networks Data mining Medical diagnostic imaging Standards

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SLAM algorithm based on bounding box and deep continuity in dynamic scene

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International Journal of Wireless and Mobile Computing 2021年第4期21卷 349-364页

作者： Fang, Baofu Han, Xiumeng Wang, Zaijun Yuan, Xiaohui School of Computer Science and Information Engineering Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology Anhui Hefei230009 China Key Laboratory of Flight Techniques and Flight Safety Civil Aviation Flight University of China Sichuan Guanghan618307 China Department of Computer Science and Engineering University of North Texas DentonTX311277 United States

To solve the problems of low positioning accuracy and poor robustness caused by the inability of Simultaneous Localisation and Mapping (SLAM) algorithm to deal with dynamic targets in dynamic scenes, a SLAM algorithm based on bounding box and depth continuity in dynamic scenes is proposed. Firstly, the pixel random search filling process is carried out in combination with the depth and the bounding box to obtain the pixel-level segmentation result of the prior dynamic target. Then, the dynamic features are screened to eliminate the influence of dynamic targets. According to the screening results, relative static features which can be used for posture optimisation are selected. Posture optimisation is carried out by combining the static features to obtain the optimised camera posture. All experimental results show that the proposed algorithm significantly improves the positioning accuracy and real-time performance of SLAM algorithm in complex dynamic scenes. Copyright © 2021 Inderscience Enterprises Ltd.

关键词： Mapping

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Modern Computing: Vision and Challenges

arXiv

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arXiv 2024年

作者： Gill, Sukhpal Singh Wu, Huaming Patros, Panos Ottaviani, Carlo Arora, Priyansh Pujol, Victor Casamayor Haunschild, David Parlikad, Ajith Kumar Cetinkaya, Oktay Lutfiyya, Hanan Stankovski, Vlado Li, Ruidong Ding, Yuemin Qadir, Junaid Abraham, Ajith Ghosh, Soumya K. Song, Houbing Herbert Sakellariou, Rizos Rana, Omer Rodrigues, Joel J.P.C. Kanhere, Salil S. Dustdar, Schahram Uhlig, Steve Ramamohanarao, Kotagiri Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Center for Applied Mathematics Tianjin University Tianjin China Raygun Performance Monitoring Wellington New Zealand Department of Computer Science York Centre for Quantum Technologies University of York York United Kingdom Microsoft Schiphol Netherlands Distributed Systems Group Vienna University of Technology Vienna Austria Detecon International GmbH Munich Germany Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Department of Engineering Science University of Oxford Oxford United Kingdom Department of Computer Science University of Western Ontario London Canada Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Institute of Science and Engineering Kanazawa University Japan Tecnun School of Engineering University of Navarra Spain Department of Computer Science and Engineering College of Engineering Qatar University Doha Qatar Bennett University Greater Noida India Machine Intelligence Research Labs AuburnWA United States Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Baltimore United States Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Department of Computer Science College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia COPELABS Lusófona University Lisbon Portugal Sydney Australia The University of Melbourne Victoria Australia Laboratory School of Computing and Information Systems The University of Melbourne Australia

Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress. © 2024, CC BY.

关键词： Obsolescence

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Mechanical Design with Experimental Verification of a Lightweight Exoskeleton Chair

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Journal of Bionic engineering 2021年第2期18卷 319-332页

作者： Zihao Du Zefeng Yan Tiantian Huang Ou Bai Qin Huang Bin Han State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Human Cyber-Physical Systems Laboratory Department of Electrical and Computer EngineeringFlorida International UniversityMiami 33174USA Department of Rehabilitation Medicine Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China

In this study,a human-chair model was developed as the basis for a wearable-chair design.A prototype chair,HUST-EC,based on the model was fabricated and *** the optimization under the golden divisional method,an optimized simulation of the operating mode with the lowest chair height was implemented.A novel multi-link support structure has been established with parameters optimized using Matlab *** stress analysis of the solid models was conducted to ensure the adequate support from the designed chair for the *** subjects participated in the evaluation experiment,who performed both static tasks and dynamic *** experimental results consisted of subjective evaluation and objective *** experimental data demonstrate that(1)the HUST-EC can effectively reduce the activation level of related muscles at a variety of tasks;(2)the plantar pressure was reduced by 54%–67%;(3)the angle between the upper body and the vertical axis was reduced by 59%–77%;(4)the subjective scores for chair comfortability,portability,and stability were all higher than *** results further revealed that the designed chair can reduce the musculoskeletal burden and may improve work efficiency.

关键词： exoskeleton wearable chair bionic robot mechanism design ergonomics

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