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SSRN 2024年

作者： Lee, Byunghwee Ryu, Hyo-Sun Lee, Jae Kook Jeong, Hawoong Kim, Beom Jun Center for Complex Networks and Systems Research Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN47408 United States Institute of Basic Science Sungkyunkwan University Suwon16419 Korea Republic of Department of Media and Communication Sungkyunkwan University Seoul03063 Korea Republic of Department of Physics Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of Department of Physics Sungkyunkwan University Suwon16419 Korea Republic of

Unlike traditional media, online news platforms allow users to consume content that suits their tastes and to facilitate interactions with other people. However, as more personalized consumption of information and interaction with like-minded users increase, ideological bias can inadvertently increase and contribute to the formation of echo chambers, reinforcing the polarization of opinions. Although the structural characteristics of polarization among different ideological groups in online spaces have been extensively studied, research into how these groups emotionally interact with each other has not been as thoroughly explored. From this perspective, we investigate both structural and affective polarization between news media user groups on Naver News, South Korea's largest online news portal, during the period of 2022 Korean presidential election. By utilizing the dataset comprising 333,014 articles and over 36 million user comments, we uncover two distinct groups of users characterized by opposing political leanings and reveal significant bias and polarization among them. Additionally, we reveal the existence of echo chambers within co-commenting networks and investigate the asymmetric affective interaction patterns between the two polarized groups. Classification task of news media articles based on the distinct comment response patterns support the notion that different political groups may employ distinct communication strategies. Our approach based on network analysis on large-scale comment dataset offers novel insights into characteristics of user polarization in the online news platforms and the nuanced interaction nature between user groups. © 2024, The Authors. All rights reserved.

关键词： Polarization

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XorshiftH128+: A hybrid random number generator for lightweight IoT

XorshiftH128+: A hybrid random number generator for lightwei...

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Artificial Intelligence, Blockchain, and Internet of Things (AIBThings), IEEE International Conference on

作者： Serge Sandakly Charbel Salem Khalil Challita Shuvalaxmi Dass Joseph Azar Jacques Bou Abdo Jacques Demerjian LaRRIS Faculty of Sciences Lebanese University Fanar Lebanon Department of Computer Science University of Warwick Coventry UK School of Computing & Informatics University of Louisiana at Lafayette Louisiana USA FEMTO-ST Institute UMR 6174 CNRS Université de Franche-Comté France School of Information Technology University of Cincinnati OH USA Computer Science & IT Department Faculty of Arts and Sciences Holy Spirit University of Kaslik (USEK) Jounieh Lebanon

The main purpose of this paper is to develop a Hybrid Random Number Generator for resource-constrained slim nodes operating within a lightweight Internet of Things network. Our algorithm extends the lightweight Xorshift128+ random number generator by developing a randomized seed generation algorithm that leverages the network’s random features. Simulation of the network was conducted using Omnet++ software followed by the validation process of cryptographic security of our proposal using NIST SP 800-22, Diehard, and TestU01 statistical tests.

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Robust Stabilization of a Knee Exoskeleton Robot Using an LMI-Based Composite Controller

Robust Stabilization of a Knee Exoskeleton Robot Using an LM...

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Indian Control Conference (ICC)

作者： Sahar Jenhani Hassène Gritli Jyotindra Narayan Laboratory of Robotics Informatics and Complex Systems (RISC Lab - LR16ES07) National Engineering School of Tunis University of Tunis El Manar Tunis Tunisia RISC Lab. Higher Institute of Information and Communication Technologies University of Carthage Borj Cedria Tunis Tunisia Department of Mechanical Engineering Thapar Institute of Engineering and Technology Patiala Punjab India Department of Computing Imperial College London UK

ISBN: (数字)9798331517212

ISBN: (纸本)9798331517229

Rehabilitation exoskeleton robots are vital for restoring lower limb functionality in individuals with locomotor disorders. Extensive research has focused on optimizing the control of these robotic systems and make them more stable. However, there is still a considerable gap in developing robust controllers. This work introduces a robust control approach tailored for a one-degree-of-freedom (1-DoF) knee rehabilitation exoskeleton robot. Emphasizing position control, our method addresses challenges such as parameter uncertainties, solid and viscous frictions, external disturbances, and motion constraints. To effectively manage these issues, we propose a composite controller that integrates a linear state-feedback controller and a nonlinear control law. By employing a quadratic Lyapunov function, we derive the expression of the nonlinear controller and establish the LMI conditions required for calculating the matrix gain of the composite controller using two different design methods. To confirm the developed LMI conditions and demonstrate the proposed control method's ability to ensure robust position control of the knee exoskeleton robotic system, simulation results are finally provided.

关键词： Robust control Uncertain systems Limbs Friction Exoskeletons Position control Solids Systems simulation Robots Lyapunov methods

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TMS: A Temporal Multi-scale Backbone Design for Speaker Embedding

arXiv

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arXiv 2022年

作者： Zhang, Ruiteng Wei, Jianguo Lu, Xugang Lu, Wenhuan Jin, Di Xu, Junhai Zhang, Lin Ji, Yantao Dang, Jianwu College of Intelligence and Computing Tianjin University Tianjin China Computer College Qinghai Nationalities University Xining China National Institute of Information and Communications Technology Kyoto Japan National Institute of Informatics Tokyo Japan School of Software Engineering Xi'an Jiaotong University Xi’an China

Speaker embedding is an important front-end module to explore discriminative speaker features (e.g., X-vector) for many speech applications where speaker information is needed. Current state-of-the-art backbone networks for speaker embedding are designed to aggregate multi-scale features from an utterance with multi-branch network architectures for speaker representation (e.g., ECAPA-TDNN). However, naively adding many branches of multi-scale features with the simple fully convolutional operation could not efficiently improve the performance due to the rapid increase of model parameters and computational complexity. Therefore, in the most current state-of-the-art network architectures, only a few branches corresponding to a limited number of temporal scales could be designed for speaker embeddings. To address this problem, in this paper, we propose an effective temporal multi-scale (TMS) model where multi-scale branches could be efficiently designed in a speaker embedding network almost without increasing computational costs. The new model is based on the conventional time-delay neural network (TDNN), where the network architecture is smartly separated into two modeling operators: a channel-modeling operator and a temporal multi-branch modeling operator. Adding temporal multi-scale in the temporal multi-branch operator needs only a little bit increase of the number of parameters, and thus save more computational budget for adding more branches with large temporal scales. Moreover, after the model was trained, in the inference stage, we further developed a systemic re-parameterization method to convert the multi-branch network topology into a single-path-based topology in order to increase inference speed. We investigated the performance of the new TMS method for automatic speaker verification (ASV) on in-domain (VoxCeleb) and out-of-domain (CNCeleb) conditions. Results show that the model based on the TMS method obtained a significant increase in the performance ove

关键词： Network architecture

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Smart Donations: Event-Driven Conditional Donations Using Smart Contracts on the Blockchain 32

Smart Donations: Event-Driven Conditional Donations Using Sm...

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32nd Australian Computer-Human Interaction Conference, OzCHI 2020

作者： Trotter, Ludwig Harding, Mike Shaw, Peter Davies, Nigel Elsden, Chris Speed, Chris Vines, John Abadi, Aydin Hallwright, Josh School of Computing and Communications Lancaster University United Kingdom Design Informatics University of Edinburgh United Kingdom Northumbria University United Kingdom School of Business and Technology University of Gloucestershire United Kingdom Oxfam Australia Rmit University Australia

ISBN: (纸本)9781450389754

Recent work has questioned the largely unconditional nature of charitable donations and explored the value of conditional giving with contemporary donors. In this paper, we extend this work by exploring how to operationalise features of conditionality in charitable giving, situated in the context of large international non-governmental organisations (NGOs). Building on prior engagements with international aid organisations, we present design considerations and a conceptual architecture supporting real-time, conditional giving for individual and institutional donations. Our architecture leverages properties of distributed-ledger technologies (DLT) to empower donors to (i) attach conditions to their donation, (ii) store funds in a secure, decentralised escrow and (iii) automatically release funds once conditions are met. Unlike prior work that envisions radical disintermediation and the removal of intermediate NGOs using DLT, our work recognises the expertise of NGOs in tackling complex global problems and instead investigates compelling new way for charities to increase transparency and accountability by introducing dynamic pledge controls. © 2020 ACM.

关键词： Blockchain

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Site selection model for urban solid waste disposal management using GIS and remote sensing: A case of Gulu Municipality

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International Journal of Environment and Waste Management 2019年第4期24卷 405-436页

作者： Okot, Patrick Ogao, Patrick Job Abandu, Jackson Department of Computer Science Faculty of Science Gulu University Uganda Department of Information Systems School of Computing and Informatics Technology Makerere University Uganda

The management of solid waste disposal is an issue that features in urban planning due to population rise and hence build-up of solid wastes. Planners are forced to use suitable disposal means to minimise damages that may occur to ecosystem and population. This study sought to develop a site selection model for urban solid waste disposal management. The aim of the study was attained by assessing the current system of: waste collection;transportation;disposal and monitoring to identify model requirements before its design and validation in Gulu Municipality. A total of 370 respondents were purposively sampled using Morgan table for sample size and managed with the help of questionnaires and interviews. The methods of: GIS and remote sensing;spatial multi criteria evaluation and analytical hierarchy processing were used in the study. The determined damping sites were classified by aggregation based on criteria weights and the best one selected using a sizing procedure. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Remote sensing

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Determinants of customer purchase intention using Zalora mobile commerce application 2

Determinants of customer purchase intention using Zalora mob...

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2nd International Conference on Smart computing and Electronic Enterprise, ICSCEE 2021

作者： El-Ebiary, Yousef A. Baker Pathmanathan, P. Ravindran Tarshany, Yasser Mohamed Abdelrahman Jusoh, Julaily Aida Aseh, Khairi Al Moaiad, Yazeed Al-Kofahi, Mahmoud Pande, Bishwajeet Bamansoor, Samer UniSZA Faculty of Informatics and Computing Malaysia International Institute of Applied Science Swiss School of Management Netherlands MEDIU Faculty of Islamic Sciences Department of Fiqh and Usul Fiqh Malaysia MEDIU Faculty of Computer and Information Technology Malaysia Irbid National University Faculty of Administrative and Financial Sciences Irbid Jordan Gyancity Research Consultancy Pvt Ltd Motihari India Faculty of Computer and Information Technology MEDIU Malaysia

ISBN: (纸本)9781665432221

In the era of modern technologies and with the development of marketing, nowadays the customer can save time buying things without having to visit the store. They just need to shop online, find what they are buying and pay it with just a few simple clicks. With this convenience in mind, the indulgence of people buying online has risen quite well. The customer's decision to purchase a product through Internet commerce under the concept of electronic commerce - which has been developed into e-commerce or mobile commerce - usually takes a serious action with perceived confidence in the services and their suitability. Therefore, customer behaviour is an important factor to facilitate online electronic service. Hence, it is important to understand customer perceptions on these services and their intention of using it. Zalora is one of the fastest online search platforms providing kind of world-famous brands in Malaysia. The objective of this study is to examine factors that influence Malaysian consumers' purchase intention through Zalora mobile application. Based on the theory of planned behaviour along with other factors, the study proposes a theoretical model for the empirical examination of the customer intention for purchasing via Zalora mobile application. Data were collected from sixteen respondents to test the relationship between variables. Data analysis was carried out using PLS-SEM. The empirical results indicated that perceived friendliness, perceived convenience, and perceived influence have a significant impact on purchase intention. The result may be preserved by providing an easy shopping experience to the user when using commerce sites and building trust to maintain the intent to buy. In addition, this analysis is helpful for Zalora marketers to suggest the most effective promotion methods in reference to further marketing of their products. © 2021 IEEE.

关键词： Mobile commerce

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Benchmarking Neural Radiance Fields for Autonomous Robots: An Overview

SSRN

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SSRN 2024年

作者： Ming, Yuhang Yang, Xingrui Wang, Weihan Chen, Zheng Feng, Jinglun Xing, Yifan Zhang, Guofeng School of Computer Science Hangzhou Dianzi University Hangzhou310018 China High-speed Aerodynamics Institute CARDC Mianyang621000 China Stevens Institute of Technology HobokenNJ07030 United States Luddy School of Informatics Computing and Engineering Indiana University BloomingtonIN47405 United States City College of New York New YorkNY10031 United States School of Computer Science University of Bristol BristolBS8 1UB United Kingdom State Key Lab of CAD&CG Zhejiang University Hangzhou310058 China

Neural Radiance Field (NeRF) has emerged as a powerful paradigm for scene representation, offering high-fidelity renderings and reconstructions from a set of sparse and unstructured sensor data. In the context of autonomous robotics, where perception and understanding of the environment are pivotal, NeRF holds immense promise for improving performance. In this paper, we present a comprehensive survey and analysis of the state-of-the-art techniques for utilizing NeRF to enhance the capabilities of autonomous robots. We especially focus on the perception, localization and navigation, and decision-making modules of autonomous robots and delve into tasks crucial for autonomous operation, including 3-dimensional reconstruction, segmentation, pose estimation, simultaneous localization and mapping, navigation and planning, and interaction. Our survey meticulously benchmarks existing NeRF-based methods, providing insights into their strengths and limitations. Moreover, we explore promising avenues for future research and development in this domain. Notably, we discuss the integration of advanced techniques such as 3-dimensional Gaussian splatting, large language models, and generative artificial intelligence, envisioning enhanced reconstruction efficiency, scene understanding, decision-making capabilities. This survey serves as a roadmap for researchers seeking to leverage NeRF to empower autonomous robots, paving the way for innovative solutions that can navigate and interact seamlessly in complex environments. © 2024, The Authors. All rights reserved.

关键词： Decision making

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Benchmarking Neural Radiance Fields for Autonomous Robots: An Overview

arXiv

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arXiv 2024年

Neural Radiance Fields (NeRF) have emerged as a powerful paradigm for 3D scene representation, offering high-fidelity renderings and reconstructions from a set of sparse and unstructured sensor data. In the context of autonomous robotics, where perception and understanding of the environment are pivotal, NeRF holds immense promise for improving performance. In this paper, we present a comprehensive survey and analysis of the state-of-the-art techniques for utilizing NeRF to enhance the capabilities of autonomous robots. We especially focus on the perception, localization and navigation, and decision-making modules of autonomous robots and delve into tasks crucial for autonomous operation, including 3D reconstruction, segmentation, pose estimation, simultaneous localization and mapping (SLAM), navigation and planning, and interaction. Our survey meticulously benchmarks existing NeRF-based methods, providing insights into their strengths and limitations. Moreover, we explore promising avenues for future research and development in this domain. Notably, we discuss the integration of advanced techniques such as 3D Gaussian splatting (3DGS), large language models (LLM), and generative AIs, envisioning enhanced reconstruction efficiency, scene understanding, decision-making capabilities. This survey serves as a roadmap for researchers seeking to leverage NeRFs to empower autonomous robots, paving the way for innovative solutions that can navigate and interact seamlessly in complex environments. Copyright © 2024, The Authors. All rights reserved.

关键词： Benchmarking

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ADMM-based adaptive sampling strategy for nonholonomic mobile robotic sensor networks

arXiv

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arXiv 2021年

作者： Le, Viet-Anh Nguyen, Linh Nghiem, Truong X. School of Informatics Computing and Cyber Systems Northern Arizona University FlagstaffAZ86011 United States School of Engineering Information Technology and Physical Sciences Federation University Australia Churchill VIC3842 Australia

This paper discusses the adaptive sampling problem in a nonholonomic mobile robotic sensor network for efficiently monitoring a spatial field. It is proposed to employ Gaussian process to model a spatial phenomenon and predict it at unmeasured positions, which enables the sampling optimization problem to be formulated by the use of the log determinant of a predicted covariance matrix at next sampling locations. The control, movement and nonholonomic dynamics constraints of the mobile sensors are also considered in the adaptive sampling optimization problem. In order to tackle the nonlinearity and nonconvexity of the objective function in the optimization problem we first exploit the linearized alternating direction method of multipliers (L-ADMM) method that can effectively simplify the objective function, though it is computationally expensive since a nonconvex problem needs to be solved exactly in each iteration. We then propose a novel approach called the successive convexified ADMM (SC-ADMM) that sequentially convexify the nonlinear dynamic constraints so that the original optimization problem can be split into convex subproblems. It is noted that both the L-ADMM algorithm and our SC-ADMM approach can solve the sampling optimization problem in either a centralized or a distributed manner. We validated the proposed approaches in 1000 experiments in a synthetic environment with a real-world dataset, where the obtained results suggest that both the L-ADMM and SC-ADMM techniques can provide good accuracy for the monitoring purpose. However, our proposed SC-ADMM approach computationally outperforms the L-ADMM counterpart, demonstrating its better practicality. Copyright © 2021, The Authors. All rights reserved.

关键词： Sensor networks

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