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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Xie, Jiayuan Cheng, Mengqiu Zhang, Xinting Cai, Yi Hu, Guimin Xie, Mengying Li, Qing Department of Computing The Hong Kong Polytechnic University Hong Kong School of Software Engineering South China University of Technology Guangzhou China Department of Computer Science University of Copenhagen Denmark Department of Mathematics The University of Hong Kong Hong Kong College of Computer Science Chongqing University China Guangdong Neusoft University Foshan China

ISBN: (纸本)157735897X

Visual question generation (VQG) aims to generate questions from images automatically. While existing studies primarily focus on the quality of generated questions, such as fluency and relevance, the difficulty of the questions is also a crucial factor in assessing their quality. Question difficulty directly impacts the effectiveness of VQG systems in applications like education and human-computer interaction, where appropriately challenging questions can stimulate learning interest and improve interaction experiences. However, accurately defining and controlling question difficulty is a challenging task due to its multidimensional and subjective nature. In this paper, we propose a new definition of the difficulty of questions, i.e., being positively correlated with the number of reasoning steps required to answer a question. For our definition, we construct a corresponding dataset and propose a benchmark as a foundation for future research. Our benchmark is designed to progressively increase the reasoning steps involved in generating questions. Specifically, we first extract the relationships among objects in the image to form a reasoning chain, then gradually increase the difficulty by rewriting the generated question to include more reasoning sub-chains. Experimental results on our constructed dataset show that our benchmark significantly outperforms existing baselines in controlling the reasoning chains of generated questions, producing questions with varying difficulty levels. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Family of Mutually Uncorrelated Codes for DNA Storage Address Design

IEEE Transactions on Nanobioscience

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IEEE Transactions on Nanobioscience 2025年 PP卷 PP页

作者： Liu, Zhenlu Cao, Ben Shao, Qi Zheng, Yanfen Wang, Bin Zhou, Shihua Zheng, Pan Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China University of Canterbury Upper Riccarton Department of Accounting and Information Systems Christchurch8140 New Zealand

Deoxyribonucleic acid (DNA) has become an ideal medium for long-term storage and retrieval due to its extremely high storage density and long-term stability. But access efficiency is an existing bottleneck in DNA storage, especially the lack of high-quality random access address sequences. Therefore, in this paper, we report a series of approaches based on k-weakly mutually uncorrelated (k-WMU) codes to design the address sequence to improve the access efficiency of DNA storage. To address the problem of DNA sequences that are poorly scalable at the base level, we propose a 0-m-ruling coding scheme combined with k-WMU codes that can make address sequences avoid generating secondary structure with stem lengths ranging from 3 to 9. Based on the decoupled structure, We further extend the k-WMU codes with error correction function while satisfying combinatorial biological constraints. In order to investigate the performance of the designed address sequences for real-world applications, we perform simulation experiments based on thermodynamic properties and error correction capability as well as compared the minimum free energy (MFE), melting temperature (TM), and average decoding success rate (ADSR) with previous work. The results show that designed address sequences have a high MFE value and ADSR and a substantial reduction in TM-variance while satisfying the combinatorial biological constraints. As the quality of address sequences improves, this will help to achieve accurate random access as well as enhance the robustness of the DNA storage system. © 2002-2011 IEEE.

关键词： DNA sequences

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Optimizing CDN Architectures: Multi-Metric Algorithmic Breakthroughs for Edge and Distributed Performance

Optimizing CDN Architectures: Multi-Metric Algorithmic Break...

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2025 International Conference on computing, Networking and Communications, ICNC 2025

作者： Absur, Md Nurul Saha, Sourya Nova, Sifat Nawrin Fahim Ahmad Nasif, Kazi Ul Nasib, Md Rahat City University of New York Department of Computer Science New York United States Chalmers University of Technology Department of Computer Science Gothenburg Sweden Kennesaw State University College of Computing and Software Engineering Georgia United States Samsung Austin Research Center AustinTX United States

ISBN: (纸本)9798331520960

A Content Delivery Network (CDN) is a powerful system of distributed caching servers that aims to accelerate content delivery, like high-definition video, IoT applications, and ultra-low-latency services, efficiently and with fast velocity. This has become of paramount importance in the post-pandemic era. Challenges arise when exponential content volume growth and scalability across different geographic locations are required. This paper investigates data-driven evaluations of CDN algorithms in dynamic server selection for latency reduction, bandwidth throttling for efficient resource management, real-time Round Trip Time analysis for adaptive routing, and programmatic network delay simulation to emulate various conditions. Key performance metrics, such as round-trip time (RTT) and CPU usage, are carefully analyzed to evaluate scalability and algorithmic efficiency through two experimental setups: a constrained edge-like local system and a scalable FABRIC testbed. The statistical validation of RTT trends, alongside CPU utilization, is presented in the results. The optimization process reveals significant trade-offs between scalability and resource consumption, providing actionable insights for effectively deploying and enhancing CDN algorithms in edge and distributed computing environments. © 2025 IEEE.

关键词： Cluster computing

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Analysis of android applications permissions 3

Analysis of android applications permissions

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3rd International Conference on Data Science, E-Learning and Information Systems, DATA 2021

作者： Saif, Amal Al-Kilani, Hamzeh Qasaimeh, Malik Al-Refai, Abdullah Computer Science Department King Hussein School of Computing Sciences Princess Sumaya University for Technology Amman Jordan Software Engineering Department Faculty of Computer and Information Technology Jordan University of Science and Technology Irbid Jordan

ISBN: (纸本)9781450388382

As Android is one of the most popular mobile open-source platforms, it is very important to ensure the security and privacy of Android apps. Android has an authorization system that allows developers to announce their applications requiring essential services, and when running such applications, users need to comply with these requirements. Users frequently download applications, giving them infinite permissions easily without thinking about the impact on their privacy. In this paper, we analyze 222 applications manually to grant these permissions to see how they are compatible with user privacy depending on many criteria. © 2021 Association for computing Machinery.

关键词： Android (operating system)

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Performance and Accuracy Evaluation of Distribution System State Estimators

SSRN

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SSRN 2024年

作者： Hebling, Gustavo M. Massignan, Julio A.D. de Melo, Vitor H.P. London Junior, Joao B.A. Department of Electrical and Computing Engineering University of Sao Paulo USP Avenida Trabalhador sao-carlense 400 - Parque Arnold Schimidt Sao Carlos Sao Paulo13566-590 Brazil Siemens AG Smart Infrastructure - Grid Software Curitiba Brazil

Recent initiatives towards smart grids have contributed to a growing inter- est in improving the real-time monitoring capabilities of active distribution systems. In this context, the sate estimator is the prevailing application, as it can provide reliable information about the current operational state of electrical networks. However, this application must be redesigned to deal with the complexity and challenges of distribution circuits and still be able to provide accurate estimates with low execution time. Therefore, this pa- per compares five different three-phase distribution system state estimators, namely, the Weighted Least Squares with Normal Equation State Estimator, Hatchel Augmented Matrix State Estimator, Branch Current Based State Estimator, Admittance Matrix Based State Estimator and the more recent Orthogonal QR State Estimator. The computational aspects assessed are execution time and iteration count until convergence and a Monte Carlo sim- ulation is used to determine accuracy. Furthermore, reordering algorithms focused on maintaining sparsity during the iterative process are evaluated for each distribution system estimator in order to determine the impact on the computational time. Simulations are carried out on IEEE distribution test systems and a real Brazilian test feeder with different measurement sets to represent a wide range of operating conditions. © 2024, The Authors. All rights reserved.

关键词： Numerical methods

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SymAware: A software Development Framework for Trustworthy Multi-Agent Systems with Situational Awareness

arXiv

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arXiv 2024年

作者： Casablanca, Ernesto Zhang, Zengjie Marchesini, Gregorio Haesaert, Sofie Dimarogonas, Dimos V. Soudjani, Sadegh School of Computing Newcastle University Newcastle United Kingdom Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Max Planck Institute for software systems Germany

Developing trustworthy multi-agent systems for practical applications is challenging due to the complicated communication of situational awareness (SA) among agents. This paper showcases a novel efficient and easy-to-use software framework for multi-agent simulation, named SymAware which provides a rich set of predefined data structures to compute, store, and communicate SA for agents. It also provides an abstract interface for the agents to compute their control inputs taking into account the awareness of the situation, knowledge, and risk of surrounding agents. Besides, utilizing a cluster of specialized components, SymAware hides the heavy computation of physical rendering and communication interfacing of simulation engines behind the control threads, resulting in high implementation efficiency in bridging the gap between conceptual prototyping and practical applications. Three multiagent case studies are used to validate the efficacy and efficiency of this software framework. © 2024, CC BY.

关键词： software design

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Results of the 2024 Video Browser Showdown

arXiv

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arXiv 2024年

作者： Rossetto, Luca Schoeffmann, Klaus Gurrin, Cathal Lokoč, Jakub Bailer, Werner Adapt Centre School of Computing Dublin City University Dublin Ireland Institute of Information Technology Klagenfurt University Austria Department of Software Engineering Charles University Prague Czech Republic DIGITAL Institute for Digital Technologies JOANNEUM RESEARCH Graz Austria

This report presents the results of the 13th Video Browser Showdown, held at the 2024 International Conference on Multimedia Modeling on the 29th of January 2024 in Amsterdam, the Netherlands. © 2024, CC BY.

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A Blockchain-Based Distributed Collaborative Sensing and Spectrum Access Approach for Consumer Electronics

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IEEE Transactions on Consumer Electronics 2025年

作者： Peng, Yuhuai Li, Yuan Guo, Yu Zhang, Dawei Khan, Fazlullah Alturki, Ryan Alshawi, Bandar Northeastern University College of Computer Science and Engineering Shenyang110819 China Zhiyuan Research Institute Xihu District Hangzhou China Zhengzhou University School of Computer and Artificial Intelligence Henan Zhengzhou450001 China University of Nottingham Ningbo China School of Computer Science Faculty of Science and Engineering Zhejiang Ningbo315104 China KKR and KSR Institute of Technology and Sciences Department of Computer Science and Engineering Andhra Pradesh Guntur India Division of Research and Development Lovely Professional University Phagwara India University Centre of Research and Development Chandigarh University Mohali India Umm Al-Qura University Department of Software Engineering College of Computing Makkah Saudi Arabia Umm Al-Qura University College of Computing Department of Computer and Network Engineering Makkah Saudi Arabia

Cognitive radio (CR) provides key technical support for the seamless communication of consumer electronic (CE) devices through distributed cooperative sensing and spectrum access. However, its openness and dynamic nature introduce potential security risks and challenges. Due to the openness of wireless communication, spectrum sensing and access are vulnerable to malicious attacks, and resource-constrained devices cannot effectively implement artificial intelligence (AI)-driven encryption and access control strategies. To address these limitations, this study proposes a blockchain-based distributed collaborative sensing method for CE devices. In the proposed method, after sensing, the smart contracts verify node legitimacy using the ring signature method. The malicious users are rejected by the outlier detection method, which improves the collaborative anti-interference ability. In addition, by using a centralized training and distributed execution architecture, a secure spectrum sensing strategy based on multi-agent reinforcement learning is designed. The proposed strategy ensures that each node makes independent decisions, which enhances the adaptability of the CE ecosystem. The proposed method is verified by extensive simulations, and the results show that it can maintain spectrum awareness of more than 95.72% and an access success rate of 91.19% under malicious attacks. Moreover, communication overhead is significantly reduced by approximately 93.53%. © 1975-2011 IEEE.

关键词： Blockchain

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Active Neighbor Exploitation for Fast Data Aggregation in IoT Sensor Networks

TechRxiv

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TechRxiv 2023年

作者： Vo, Van-Vi Le, Duc-Tai Raza, Syed M. Kim, Moonseong Choo, Hyunseung The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of The College of Computing and Informatics Sungkyunkwan University Suwon16419 Korea Republic of The Department of IT Convergence Software Seoul Theological University Bucheon14754 Korea Republic of

Fast data aggregation is crucial to facilitate critical Internet of Things (IoT) services as it collects all sensory data under restricted volume and time using in-network computation. The minimum latency data aggregation scheduling problem has attracted a lot of attention for the last decade. Existing approaches for the problem schedule all data transmissions based on an aggregation tree which was typically constructed without secondary interference awareness. Such interference causes numerous delay when scheduling a transmission from a node to its parent in the tree. When a sensor is active at multiple timeslots in a working period, the secondary interference can simply be omitted by scheduling a node to transmit its data to an active neighbor instead of its parent. This paper presents an Active Neighbor EXploitation (ANEX) approach which enables sensor nodes to switch their parents by discovering active neighbors for possible connectivity, regardless of the receivers established in the tree. Furthermore, the scheme prioritizes scheduling nodes with the fewest unscheduled active neighbors in order to execute more concurrent transmissions. We evaluate ANEX by theoretical analysis and extensive simulations with various scenarios. The results show that ANEX outstandingly achieves faster aggregation than the state-of-the-art approach by up to 86% while having an equivalent time complexity. © 2023, CC BY.

关键词： Internet of things

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Mixture of Knowledge Minigraph Agents for Literature Review Generation

arXiv

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arXiv 2024年

作者： Zhang, Zhi Liu, Yan Zhong, Sheng-Hua Chen, Gong Yang, Yu Cao, Jiannong The Hong Kong Polytechnic University the Department of Computing 999077 Hong Kong Shenzhen University the College of Computer Science and Software Engineering Guangdong Shenzhen518052 China The Education University of Hong Kong Centre for Learning Teaching and Technology 999077 Hong Kong

Literature reviews play a crucial role in scientific research for understanding the current state of research, identifying gaps, and guiding future studies on specific topics. However, the process of conducting a comprehensive literature review is yet time-consuming. This paper proposes a novel framework, collaborative knowledge minigraph agents (CKMAs), to automate scholarly literature reviews. A novel prompt-based algorithm, the knowledge minigraph construction agent (KMCA), is designed to identify relations between concepts from academic literature and automatically constructs knowledge minigraphs. By leveraging the capabilities of large language models on constructed knowledge minigraphs, the multiple path summarization agent (MPSA) efficiently organizes concepts and relations from different viewpoints to generate literature review paragraphs. We evaluate CKMAs on three benchmark datasets. Experimental results show the effectiveness of the proposed method, further revealing promising applications of LLMs in scientific research. © 2024, CC BY.

关键词： Reviews

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