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On Efficient Processing of Queries for Live Multi-Streaming Soiree Organization

IEEE Transactions on Services Computing 2023年第4期16卷 2812-2826页

作者： Kankeu Fotsing, C.P. Shen, Chih-Ya Huang, Liang-Hao Chen, Yi-Shin Lee, Wang-Chien Yang, De-Nian International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei115 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu300 Taiwan National Tsing Hua University Department of Computer Science Hsinchu300 Taiwan Academia Sinica Institute of Information Science Taipei115 Taiwan Pennsylvania State University Department of Computer Science and Engineering State CollegePA16801 United States

Real-time social interactions and multi-streaming are two critical features of live streaming services. In this paper, we formulate a new fundamental service query, Social-aware Diverse and Preferred Organization Query (SDSQ), that jointly selects a set of diverse and preferred live streaming channels and a group of socially tight viewers for organization of a live multi-streaming soiree. We prove that SDSQ is NP-hard and inapproximable within any factor, and design SDSSel, a 2-approximation algorithm with a guaranteed error bound. Moreover, we study SDSQ-T, a special case of SDSQ, where the social graph is a threshold graph, and propose TDSSel, a 2-approximation algorithm without any error to SDSQ-T. We propose two pruning strategies, PCP and CDP to boost SDSSel and TDSSel. We further propose a more challenging but practical service query, Generalized Social-aware Maximum Preferred and Diverse Query (GSPQ), a generalization of SDSQ. We design GPDSel, a 4-approximation algorithm for GSPQ with a guaranteed error bound. We propose a strategy to improve the approximation ratios of the proposed algorithms. A user study on Twitch validates SDSQ, and the large-scale experiments on real datasets demonstrate the superiority of the proposed algorithms over several baselines for live-streaming services. © 2008-2012 IEEE.

关键词： Approximation algorithms

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Fault Tolerant Dynamic Task Assignment for UAV-based Search Teams

arXiv

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arXiv 2024年

作者： Nasir, Ali AlDurgam, Mohammad Interdisciplinary Research Center for Intelligent Manufacturing and Robotics KFUPM Dhahran Saudi Arabia Control and Instrumentation Engineering Department KFUPM Dhahran Saudi Arabia Interdisciplinary Research Center for Smart Mobility and Logistics KFUPM Dhahran Saudi Arabia Industrial and Systems Engineering Department KFUPM Dhahran Saudi Arabia

This research offers a novel framework for dynamic task assignment for unmanned aerial vehicles (UAVs) in cooperative search settings. Notably, it incorporates post-fault UAV capabilities into job assignment techniques, assuring operational dependability in the event of sensor and actuator failures. A significant innovation is the utilization of UAV battery charge to assess range relative to search objectives, hence improving job distribution while conserving battery life. This model integrates repair, recharge, and stochastic goal recurrence, hence increasing its real-world applicability. Using stochastic dynamic programming, this method makes it simpler to determine optimal assignment policies offline so they may be implemented rapidly online. This paper emphasizes the holistic aspect of the proposed model, which connects high-level task rules to low-level control capabilities. A simulation-based case study proves its usefulness, highlighting its robustness in fault-prone and battery-variable settings. Overall, this paper proposes and demonstrates a comprehensive method for assigning UAV tasks that integrates defect awareness, battery management, and multilayer control through the use of stochastic dynamic programming. © 2024, CC BY.

关键词： Stochastic systems

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Thévenin Network Approach for Modeling Mutual Coupling in Narrowband Uniform Linear Arrays

Thévenin Network Approach for Modeling Mutual Coupling in N...

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IEEE Latin American Symposium on Circuits and systems (LASCAS)

作者： José A. Apolinário Cláudio A. B. Saunders Filho Antonio L. L. Ramos Program of Electrical Engineering Military Institute of Engineering (IME) Rio de Janeiro Brazil Department of Science and Industry Systems (IRI) TNM University of South-Eastern Norway (USN) Kongsberg Norway

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

This paper investigates mutual coupling in narrow-band uniform linear antenna arrays through Thévenin network modeling. After an in-depth analysis, we derive a Thévenin network representing a given mutual coupling matrix and develop a method to achieve an equivalent decoupled model that significantly reduces computational and memory requirements in practical applications.

关键词： Mutual coupling Analytical models Circuits and systems Array signal processing Computational modeling Memory management Linear antenna arrays Integrated circuit modeling Narrowband

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A Novel Consensus-driven Technique for Optimal Power Allocation in Smart Energy Networks Considering Multiple Fueling Feature of Thermal Plants

A Novel Consensus-driven Technique for Optimal Power Allocat...

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2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

作者： Ahmed, Ijaz Khardawi, Wasseem Al-Ismail, Fahad Saleh Khalid, Muhammad Islamabad44650 Pakistan Saudi Aramco Northern Area Technical Support Dhahran31311 Saudi Arabia Electrical Engineering Department Dhahran31261 Saudi Arabia Kfupm Interdisciplinary Research Center for Renewable Energy and Power Systems Dhahran 31261 Saudi Arabia

ISBN: (纸本)9781665471640

The goal of this research is to devised solution for energy dispatch problem based on consensus-driven method. The cost function for energy dispatch, which takes into account several fuel options, is typically formulated as a combined cost model. The aforementioned combined cost expression is subsequently employed to develop an incremental cost function by means of polynomial curve fitting methods. In order to address the issues related to the incremental cost function and take into account the many fuel sources utilized by private sector energy providers to deliver cost-effective electricity to consumers, a partly distributed consensus-based approach is utilized. The proposed approach adeptly addresses the concern of incremental cost within the integrated framework while simultaneously allowing the strategy of selecting several fuels. The suggested strategy effectively tackles the challenges arising from imbalances between supply and demand while also fostering consensus among stakeholders. Moreover, the system also accomplishes the tracking of the composite incremental cost and utilizes exponential optimization techniques. The effectiveness of the proposed design technique in generating steady exponential convergence is ultimately shown through simulations and the associated data. © 2023 IEEE.

关键词： Distributed protocols energy dispatch problem energy hubs multiple fueling

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On the Estimation Performance of Generalized Power Method for Heteroscedastic Probabilistic PCA

arXiv

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arXiv 2023年

作者： Wang, Jinxin Jiang, Chonghe Liu, Huikang So, Anthony Man-Cho Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong Research Institute for Interdisciplinary Sciences School of Information Management and Engineering Shanghai University of Finance and Economics China

The heteroscedastic probabilistic principal component analysis (PCA) technique, a variant of the classic PCA that considers data heterogeneity, is receiving more and more attention in the data science and signal processing communities. In this paper, to estimate the underlying low-dimensional linear subspace (simply called ground truth) from available heterogeneous data samples, we consider the associated non-convex maximum-likelihood estimation problem, which involves maximizing a sum of heterogeneous quadratic forms over an orthogonality constraint (HQPOC). We propose a first-order method—generalized power method (GPM)—to tackle the problem and establish its estimation performance guarantee. Specifically, we show that, given a suitable initialization, the distances between the iterates generated by GPM and the ground truth decrease at least geometrically to some threshold associated with the residual part of certain "population-residual decomposition". In establishing the estimation performance result, we prove a novel local error bound property of another closely related optimization problem, namely quadratic optimization with orthogonality constraint (QPOC), which is new and can be of independent interest. Numerical experiments are conducted to demonstrate the superior performance of GPM in both Gaussian noise and sub-Gaussian noise settings. Copyright © 2023, The Authors. All rights reserved.

关键词： Maximum likelihood estimation

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Ontologies in Design: How Imagining a Tree Reveals Possibilities and Assumptions in Large Language Models 25

Ontologies in Design: How Imagining a Tree Reveals Possibili...

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2025 CHI Conference on Human Factors in Computing systems, CHI 2025

作者： Haghighi, Nava Yu, Sunny Landay, James A. Rosner, Daniela Computer Science Stanford University StanfordCA United States Symbolic Systems Program Stanford University StanfordCA United States Computer Science Department Stanford University StanfordCA United States Human Centered Design & Engineering University of Washington SeattleWA United States

ISBN: (纸本)9798400713941

Amid the recent uptake of Generative AI, sociotechnical scholars and critics have traced a multitude of resulting harms, with analyses largely focused on values and axiology (e.g., bias). While value-based analyses are crucial, we argue that ontologies - concerning what we allow ourselves to think or talk about - is a vital but under-recognized dimension in analyzing these systems. Proposing a need for a practice-based engagement with ontologies, we offer four orientations for considering ontologies in design: pluralism, groundedness, liveliness, and enactment. We share examples of potentialities that are opened up through these orientations across the entire LLM development pipeline by conducting two ontological analyses: examining the responses of four LLM-based chatbots in a prompting exercise, and analyzing the architecture of an LLM-based agent simulation. We conclude by sharing opportunities and limitations of working with ontologies in the design and development of sociotechnical systems. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Ontology

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Classification Of Ornamental Fish Types Using CNN Method With VGG-16 And U-NET Architecture

Classification Of Ornamental Fish Types Using CNN Method Wit...

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Consumer Technology (ICCT-Pacific), International Conference on

作者： Ni Luh Wiwik Sri Rahayu Ginantra Christina Purnama Yati I Gusti Ayu Agung Diatri Indradewi I Komang Agus Yudiawan Technology and Informatics Informatics Engineering Institut Bisnis dan Teknologi Indonesia (INSTIKI) Denpasar Indonesia Department of Informatics Engineering Information Systems Study Program Faculty of Engineering and Vocational Studies Universitas Pendidikan Ganesha (UNDIKSHA) Denpasar Indonesia

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

Ornamental fish are a type of fish that live in freshwater or seawater habitats and are typically maintained for aesthetic purposes, often in ornamental ponds or as household pets. The diversity of colors, shapes, and patterns observed in ornamental fish presents a challenge in their classification. Therefore, a method capable of accurately recognizing the visual characteristics of these fish is required. The objective of this study is to evaluate the performance of two Convolutional Neural Network (CNN) architectures, specifically VGG-16 and U-Net, using five distinct types of ornamental fish, namely Angel Fish, Betta Fish, Clown Fish, Gold Fish, and Guppy Fish. The dataset comprises 3.240 images that have been processed using TensorFlow and Keras on Google Collaboratory. The results demonstrated that U-Net demonstrated superior performance in segmentation, with an Average Intersection over Union (IoU) of 58.91 % and an Average Dice Coefficient of 73.72%. In contrast, VGG-16 exhibited signs of overfitting, as evidenced by lower evaluation metrics. To enhance the efficacy of the transfer learning model, further optimization is recommended.

关键词： Measurement Image segmentation Visualization Shape Transfer learning Fish Internet Convolutional neural networks Optimization Overfitting

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Low-dose intrapulmonary drug delivery device for studies on next-generation therapeutics in mice

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Journal of Controlled Release 2023年第1期359卷 287-301页

作者： Gracioso Martins, Ana Maria Snider, Douglas B. Popowski, Kristen D. Schuchard, Karl G. Tenorio, Matias Akunuri, Sandip Wee, Junghyun Peters, Kara J. Jansson, Anton Shirwaiker, Rohan Cheng, Ke Freytes, Donald O. Cruse, Glenn P. Department of Molecular Biomedical Sciences College of Veterinary Medicine North Carolina State University RaleighNC United States Comparative Medicine and Translational Research Training Program North Carolina State University RaleighNC United States Comparative Medicine Institute North Carolina State University RaleighNC United States Joint Department of Biomedical Engineering College of Engineering North Carolina State University & University of North Carolina-Chapel Hill NC United States Edward P. Fitts Department of Industrial and Systems Engineering North Carolina State University RaleighNC United States Department of Mechanical and Aerospace Engineering North Carolina State University RaleighNC United States Analytical Instrumentation Facility Monteith Research Center North Carolina State University RaleighNC United States

Although nebulizers have been developed for delivery of small molecules in human patients, no tunable device has been purpose-built for targeted delivery of modern large molecule and temperature-sensitive therapeutics to mice. Mice are used most of all species in biomedical research and have the highest number of induced models for human-relevant diseases and transgene models. Regulatory approval of large molecule therapeutics, including antibody therapies and modified RNA highlight the need for quantifiable dose delivery in mice to model human delivery, proof-of-concept studies, efficacy, and dose-response. To this end, we developed and characterized a tunable nebulization system composed of an ultrasonic transducer equipped with a mesh nebulizer fitted with a silicone restrictor plate modification to control the nebulization rate. We have identified the elements of design that influence the most critical factors to targeted delivery to the deep lungs of BALB/c mice. By comparing an in silico model of the mouse lung with experimental data, we were able to optimize and confirm the targeted delivery of over 99% of the initial volume to the deep portions of the mouse lung. The resulting nebulizer system provides targeted lung delivery efficiency far exceeding conventional nebulizers preventing waste of expensive biologics and large molecules during proof-of-concept and pre-clinical experiments involving mice. (Word Count =207). © 2023 Elsevier B.V.

关键词： Molecules

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Enhanced thermal decomposition and combustion performance of ammonium perchlorate composite propellants using LaFeO3 catalyst

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Journal of the Taiwan Institute of Chemical Engineers 2025年

作者： Huang, Chao-Wei Wang, Tse-Hao Chen, Yi-Chu Tsai, Yu-An Huang, Chun-Fu Wang, To-Yu Wu, Chih-Yung Department of Engineering Science National Cheng Kung University Tainan Taiwan Department of Aeronautics and Astronautics National Cheng Kung University Tainan Taiwan International Degree Program on Energy in Engineering National Cheng Kung University Tainan Taiwan Institute of Space Systems Engineering National Cheng Kung University Tainan Taiwan

Background: Advancements in solid composite propellant technology hold significant promise for enhancing thrust capabilities, thereby improving booster performance in terms of payload capacity and trajectory precision. Consequently, the selection of a combustion catalyst is of paramount importance. Methods: LaFeO3 was proposed as a potential combustion catalyst. The characteristics of the catalyst were examined through Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDS), X-ray Diffraction (XRD), and Thermogravimetric Analysis (TGA). Concurrently, composite propellant specimens were prepared, and the enhancement of their performance attributable to the incorporation of LaFeO3 on the combustion velocity of the fuel was assessed. The efficacy of LaFeO3 was systematically compared against traditional iron oxide combustion catalysts. Significant findings: The outcomes underscore that introducing LaFeO3 as an additive effectively reduces the instantaneous activation energy of NH4ClO4 at the temperature corresponding to the peak decomposition rate. The results of the measured activation energy indicated that when LaFeO3 was mixed with an oxidant at a concentration of 1 %, the activation energy decreased by approximately 5.88 %. Consequently, this positively impacts the burning rate of the composite solid fuel. Significantly, the promotion of burning velocity by LaFeO3 surpasses that of classic Fe2O3, establishing the former's superiority. Notably, LaFeO3's distinct advantage lies in its capacity to achieve specific performance enhancements with a relatively lower catalyst dosage. © 2025

关键词： Composite propellants

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Dynamic channel estimation-aware routing protocol in mobile cognitive radio networks for smart IIoT applications

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Digital Communications and Networks 2023年第2期9卷 367-382页

作者： Qusay M.Salih Md Arafatur Rahman A.Taufiq Asyhari Muhammad Kamran Naeem Mohammad Patwary Ryan Alturki Mohammed Abdulaziz Ikram Faculty of Computing Universiti Malaysia Pahang26300GambangPahangMalaysia School of Engineering Computing and Mathematical SciencesUniversity of WolverhamptonUK Data Science Program Monash UniversityIndonesiaand Birmingham City UniversityB47XGUK Department of Information Science College of Computer and Information SystemsUmm Al-Qura UniversitySaudi Arabia Computer Science Department Al Jumoum University CollegeUmm Al-Qura UniversitySaudi Arabia

Cognitive Radio Networks(CRNs)have become a successful platform in recent years for a diverse range of future systems,in particularly,industrial internet of things(IIoT)*** order to provide an efficient connection among IIoT devices,CRNs enhance spectrum utilization by using licensed ***,the routing protocol in these networks is considered one of the main problems due to node mobility and time-variant channel ***,the channel selection for routing protocol is indispensable in CRNs to provide an adequate adaptation to the Primary User(PU)activity and create a robust routing *** study aims to construct a robust routing path by minimizing PU interference and routing delay to maximize throughput within the IIoT ***,a generic routing framework from a cross-layer perspective is investigated that intends to share the information resources by exploiting a recently proposed method,namely,Channel Availability ***,a novel cross-layer-oriented routing protocol is proposed by using a time-variant channel estimation *** protocol combines lower layer(Physical layer and Data Link layer)sensing that is derived from the channel estimation ***,it periodically updates and stores the routing table for optimal route ***,in order to achieve higher throughput and lower delay,a new routing metric is *** evaluate the performance of the proposed protocol,network simulations have been conducted and also compared to the widely used routing protocols,as a *** simulation results of different routing scenarios demonstrate that our proposed solution outperforms the existing protocols in terms of the standard network performance metrics involving packet delivery ratio(with an improved margin of around 5–20%approximately)under varying numbers of PUs and cognitive users in Mobile Cognitive Radio Networks(MCRNs).Moreover,the cross-layer routing protocol successfully achiev

关键词： Channel selection Cross-layer design Mobile cognitive radio networks Routing protocol IIoT applications

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