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Computer Science, Information Systems
Michele Girolami, Davide La Rosa, Paolo Barsocchi
Summary: In this work, a CrowdSensing-based proximity detection technique for visitors in an indoor museum is proposed and investigated. The technique utilizes data collected from users' smartphones, which can collect and upload Received Signal Strength (RSS) values of nearby Bluetooth tags to a backend server along with context-information. Experimental results show a clear improvement in performance when data from the crowd are exploited with the proposed architecture.
Article
Computer Science, Information Systems
Paulo Cesar Prandel, Priscila Solis Barreto
Summary: This study proposes two stateful techniques, LGFS-C and LGFS-C-peak, which optimize AoI metrics by making conditional preemption decisions on packets based on system state variables. Experimental results show that both techniques achieve better optimization results than the state-of-the-art techniques and may improve CPS performance.
Article
Computer Science, Information Systems
Xiaochang Fang, Hongchen Wu, Jing Jing, Yihong Meng, Bing Yu, Hongzhu Yu, Huaxiang Zhang
Summary: This study proposes a novel fake news detection framework, utilizing news semantic environment perception (NSEP) to identify fake news content. The framework consists of steps such as dividing the semantic environment into macro and micro levels, applying graph convolutional networks, and utilizing multihead attention. Empirical experiments show that the NSEP framework achieves high accuracy in detecting Chinese fake news, outperforming other baseline methods and highlighting the importance of both micro and macro semantic environments in early detection of fake news.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Xudong Sun, Alladoumbaye Ngueilbaye, Kaijing Luo, Yongda Cai, Dingming Wu, Joshua Zhexue Huang
Summary: This paper proposes a scalable distributed frequent itemset mining (ScaDistFIM) algorithm to address the data scalability and flexibility issues in basket analysis in the big data era. Experiment results demonstrate that the ScaDistFIM algorithm is more efficient compared to the Spark FP-Growth algorithm.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Chunyong Zhang, Tianxiang Yu, Bin Liu, Yang Xin
Summary: This paper proposes a vulnerability detection framework based on federated learning (VDBFL), which combines code property graph, graph neural networks, and convolutional neural networks to detect vulnerability code. The experimental results show that this method outperforms other vulnerability detection methods.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Mislav Blazevic, Stefan Canzar, Khaled Elbassioni, Domagoj Matijevic
Summary: This paper studies the Tai mapping and anti Tai mapping problems between rooted labeled trees. For unordered trees, finding the maximum-weight Tai mapping is proven to be NP-complete. The paper provides an efficient algorithm for finding the maximum-weight anti Tai mapping and presents a polynomial computable lower bound for the optimal anti Tai mapping based on special conditions.
INFORMATION PROCESSING LETTERS
(2024)
Article
Computer Science, Information Systems
Boxu Guan, Xinhua Zhu, Shangbo Yuan
Summary: This paper aims to improve the interpretability of machine reading comprehension models by utilizing the pre-trained T5 model for evidence inference. They propose an interpretable reading comprehension model based on T5, which is trained on a more accurate evidence corpus and can infer precise interpretations for answers. Experimental results show that their model outperforms the baseline BERT model on the SQuAD1.1 task.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Artificial Intelligence
Shray Pathak, Shreya Sharma, Abhishek Banerjee, Sanjeev Kumar
Summary: The urgency to protect natural water resources in a sustainable manner has increased as water scarcity and global climate change worsen. Stormwater harvesting is considered the most environmentally friendly approach to alleviate strain on freshwater resources. This study introduces a robust method that considers technical and socioeconomic aspects to evaluate the potential for stormwater harvesting. The method effectively identifies and assesses suitable areas for implementing stormwater harvesting and incorporates input from water experts in the decision-making process.
Article
Computer Science, Information Systems
Phuong T. Tran, Le Thi Thanh Huyen, Ba Cao Nguyen, Huu Minh Nguyen, Tran Manh Hoang
Summary: This paper introduces and investigates a system utilizing an unmanned aerial vehicle (UAV) to assist terrestrial backscattering devices (BDs) in wireless energy charging and data transmission. The study considers energy efficiency (EE) and age-of-information (AoI) in performance assessment, and solves an optimization problem to maximize EE and minimize transmit power. Analytical and simulation results show that optimizing packet length and UAV altitude can achieve the best performance.
Article
Computer Science, Information Systems
Mohamed Selim Korium, Mohamed Saber, Alexander Beattie, Arun Narayanan, Subham Sahoo, Pedro H. J. Nardelli
Summary: This paper presents a novel framework for intrusion detection in the Internet of Vehicles environment, specifically designed to detect cyberattacks on vehicles. The proposed system uses machine learning to detect abnormal behavior by analyzing network traffic. Experimental results demonstrate the effectiveness of the system in terms of accuracy and speed.
Article
Computer Science, Information Systems
Xue Li, Xiaojuan Chen, Guohua Li
Summary: This study proposes a two-tier cooperative edge network model for Power Internet of Things (PIoT) and introduces a fairness indicator based on the Theil index. By formulating a fairness and delay guaranteed task offloading and load balancing optimization problem, the research demonstrates that cooperation at the edge can significantly improve the performance of PIoT.
Article
Computer Science, Information Systems
Youcef Azzoug, Abdelmadjid Boukra
Summary: This paper presents a novel JBR routing protocol based on swarm-inspired optimization to reduce data packet loss and introduces a concept of route stability to predict the stability degree of road segments.
Article
Computer Science, Information Systems
Kun Yang, Peng Sun, Dingkang Yang, Jieyu Lin, Azzedine Boukerche, Liang Song
Summary: The focus of this research is to effectively coordinate the limited computing power of various components in intelligent transportation systems (ITS) and provide reliable support for resource-intensive applications through efficient resource allocation methods in the highly dynamic Internet-of-Vehicles environment. A novel joint computing and communication resource scheduling method is proposed, which includes a hierarchical three-layer Vehicular Edge Computing (VEC) framework and onboard joint computation offloading and transmission scheduling policy. Extensive simulation tests and ablation experiments demonstrate the effectiveness and stability of the proposed method in achieving stable performance and reducing scheduling overhead, improving resource utilization, and minimizing data transmission delay caused by vehicle motion.
Article
Computer Science, Information Systems
Xinrong Zhang, Ye-Hwa Chen, Dongsheng Zhang, Ruiying Zhao, Lei Guo
Summary: This paper proposes a game-theoretic method based on constraint following theory to enhance the control resilience of cyber-physical systems. It addresses the uncertainties, mechanical constraints, and cyberattacks that these systems may encounter. Experimental results demonstrate the resilience of the controlled system against cyberattack disturbances and other threat attacks, and simulations verify the superiority of the optimal control design parameter.
Article
Computer Science, Information Systems
Shahaf Yamin, Haim H. Permuter
Summary: This study examines the problem of downlink wireless routing in integrated access backhaul (IAB) networks and proposes a multi-agent reinforcement learning algorithm for joint routing optimization. Experimental results demonstrate the effectiveness of the algorithm in achieving near-centralized performance.
Article
Computer Science, Information Systems
Muna Al-Hawawreh, Nour Moustafa
Summary: Cyber-physical control loops are crucial in the industrial Internet of Things, but vulnerable to attacks. This study proposes an AI-based attack intelligence framework for identifying and extracting attack intelligence, and demonstrates its effectiveness using a real-world case.
Article
Computer Science, Information Systems
Mohammed Aissaoui, Chiraz Houaidia, Adrien Van Den Bossche, Thierry Val, Leila Azouz Saidane
Summary: This paper proposes a distributed MAC protocol that supports PNC in static multi-hop wireless networks. The protocol's advantages over conventional CSMA/CA and PNCOPP MAC protocols are demonstrated through practical testing and numerical results.
Review
Computer Science, Information Systems
Nazli Tekin, Ahmet Aris, Abbas Acar, Selcuk Uluagac, Vehbi Cagri Gungor
Summary: This paper provides a review of existing studies on energy consumption of on-device machine learning models for IoT applications. It introduces a taxonomy to define approaches for energy-aware on-device ML models and discusses open issues for further research in this field.
Article
Computer Science, Information Systems
Yangyang Li, Lei Feng, Yang Yang, Wenjing Li
Summary: This study investigates a task offloading scheme and trajectory optimization in a multi-UAV-assisted system and proposes a heterogeneous multi-agent reinforcement learning-based approach. By training with generated environment states offline, the algorithm's performance is optimized, resulting in superior energy consumption and task latency.
Article
Computer Science, Information Systems
Alessio Cecconi, Luca Barbaro, Claudio Di Ciccio, Arik Senderovich
Summary: This paper introduces a framework for designing probabilistic measures for declarative process specifications, which can assess the degree of compliance between process data and specifications. Through experiments, the applicability of the approach for various process mining tasks is demonstrated.
INFORMATION SYSTEMS
(2024)
