Obstacle Aware Connectivity Restoration for Disjoint Wireless Sensor Networks Using a Mix of Stationary and Mobile Nodes by Guizhen Ma, Yang Yang, Xuesong Qiu, Zhipeng Gao

“…However, almost all of the works assumed that mobile nodes travel via a direct path, which may not be the case in real-world applications. In order to improve the applicability of the recovery strategy, obstacles should be taken into account. …”
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Swarm navigation of cyborg-insects in unknown obstructed soft terrain by Yang Bai, Phuoc Thanh Tran Ngoc, Huu Duoc Nguyen, Duc Long Le, Quang Huy Ha, Kazuki Kai, Yu Xiang See To, Yaosheng Deng, Jie Song, Naoki Wakamiya, Hirotaka Sato, Masaki Ogura

“…This research advances swarm robotics by integrating biological organisms with control theory to develop intelligent autonomous systems for real-world applications.…”
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An NoC Traffic Compiler for Efficient FPGA Implementation of Sparse Graph-Oriented Workloads by Nachiket Kapre, André Dehon

“…This allows us to demonstrate speedups between 1.2× and 22× (3.5× mean), area reductions (number of Processing Elements) between 3× and 15× (9× mean) and dynamic energy savings between 2× and 3.5× (2.7× mean) over a range of real-world graph applications in the BSP compute model. …”
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Evaluation and optimization of carbon emission for federal edge intelligence network by Peng ZHANG, Yong XIAO, Jiwei HU, Liang LIAO, Jianxin LYU, Zegang BAI

“…In recent years, the continuous evolution of communication technology has led to a significant increase in energy consumption.With the widespread application and deep deployment of artificial intelligence (AI) technology and algorithms in telecommunication networks, the network architecture and technological evolution of network intelligent will pose even more severe challenges to the energy efficiency and emission reduction of future 6G.Federated edge intelligence (FEI), based on edge computing and distributed federated machine learning, has been widely acknowledged as one of the key pathway for implementing network native intelligence.However, evaluating and optimizing the comprehensive carbon emissions of federated edge intelligence networks remains a significant challenge.To address this issue, a framework and a method for assessing the carbon emissions of federated edge intelligence networks were proposed.Subsequently, three carbon emission optimization schemes for FEI networks were presented, including dynamic energy trading (DET), dynamic task allocation (DTA), and dynamic energy trading and task allocation (DETA).Finally, by utilizing a simulation network built on real hardware and employing real-world carbon intensity datasets, FEI networks lifecycle carbon emission experiments were conducted.The experimental results demonstrate that all three optimization schemes significantly reduce the carbon emissions of FEI networks under different scenarios and constraints.This provides a basis for the sustainable development of next-generation intelligent communication networks and the realization of low-carbon 6G networks.…”
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Multi-task learning load time series situational prediction based on gated recurrent neural networks considering spatial correlations by Mei Huang, Qian Ai

“…This approach was validated using real-world data, demonstrating notable improvements in prediction accuracy when compared to single-task learning models. …”
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Theoretical Trade-Off Between Fairness and Efficiency in the Cooperative Driving Problem for CAVs at On-Ramps by Zimin He, Huaxin Pei, Yuqing Guo, Danya Yao, Li Li

“…Simulation results show that the modified strategies achieve trade-offs in agreement with the theoretical one, laying the foundation for implementing the trade-off in real-world scenarios. These findings are enlightening for the increasing research on fairness issues in cooperative driving, and contribute to the optimization of traffic management strategies.…”
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HGNN-GAMS: Heterogeneous Graph Neural Networks for Graph Attribute Mining and Semantic Fusion by Yufei Zhao, Hua Liu, Hua Duan

“…This work pioneers the integration of graph attributes with semantic information and validates the model’s effectiveness through extensive experiments on real-world datasets.…”
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„Nowe” problemy wychowawcze w dobie „nowych” mediów by Arkadiusz Olczyk

“…It is more and more difficult for them to find themselves in the real world. They need help and support. They need therefore, wise educators and appropriate upbringing which will help them to distinguish good from evil and choose the GOOD.…”
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Augmentation for Accuracy Improvement of YOLOv8 in Blind Navigation System by Erwin Syahrudin, Ema Utami, Anggit Dwi Hartanto

“…Final validation in real-world scenarios confirms the efficacy of the optimized model, demonstrating its readiness for practical deployment. …”
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A Topological Approach to Enhancing Consistency in Machine Learning via Recurrent Neural Networks by Muhammed Adil Yatkin, Mihkel Kõrgesaar, Ümit Işlak

“…Furthermore, we have verified our results with real-world datasets to ensure practical applicability and robustness. …”
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The Local Triangle Structure Centrality Method to Rank Nodes in Networks by Xiaojian Ma, Yinghong Ma

“…The performance of the proposed LTSC method is evaluated by comparing the spreading ability on both real-world and synthetic networks with the SIR model. …”
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EMM-CLODS: An Effective Microcluster and Minimal Pruning CLustering-Based Technique for Detecting Outliers in Data Streams by Mohamed Jaward Bah, Hongzhi Wang, Li-Hui Zhao, Ji Zhang, Jie Xiao

“…The analysis from our experimental studies on both synthetic and real-world datasets shows that the technique performs well with minimal memory and time consumption when compared to the other baseline algorithms, making it a very promising technique in dealing with outlier detection problems in data streams.…”
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A Pruning-Based Disk Scheduling Algorithm for Heterogeneous I/O Workloads by Taeseok Kim, Hyokyung Bahn, Youjip Won

“…Experiments with various synthetic and real-world I/O workloads show that G-SCAN outperforms existing disk scheduling algorithms significantly in terms of the average response time, throughput, and QoS-guarantees for heterogeneous I/O workloads. …”
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Rethinking spatial-temporal contrastive learning for Urban traffic flow forecasting: multi-level augmentation framework by Lin Pan, Qianqian Ren, Zilong Li, Xingfeng Lv

“…Extensive experimental results on four real-world urban datasets demonstrate that UrbanGCL significantly outperforms other state-of-the-art methods, with the maximum improvement reaching nearly 8.80%.…”
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Quantum Algorithms for the Physical Layer: Potential Applications to Physical Layer Security by Toshiki Matsumine, Hideki Ochiai, Junji Shikata

“…It is also anticipated that these technologies will continue to flourish and exert a considerable influence on society, i.e., a plethora of real-world problems that cannot be solved by classical algorithms are believed to benefit from the implementation of quantum algorithms. …”
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Clustering and Investigation of Human Driving Behavior Using Autoencoder and Risk Assessment by Donghoon Shin, Jinhee Myoung, Woongsun Jeon, Kang-Moon Park

“…Experiments were conducted in various real-world driving scenarios, involving two distinct types of shoes. …”
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Enhanced Adaptive Neural-Fuzzy Inference System for Dynamic Time Series Prediction Using Self-Feedback and Hybrid Training by Andrew Topper, Honglei Yao

“…The proposed technique is applied to predict and model multiple nonlinear and chaotic time series from real-world scenarios. Comparative analyses with recent works demonstrate the superior performance of the proposed method, particularly in terms of the prediction total error criterion for time series modeling and forecasting. …”
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A Small Tamper-Resistant Anti-Recycling IC Sensor With a Reused I/O Interface and DC Signalling by Alexandros Dimopoulos, Mihai Sima, Stephen W. Neville

“…This work proposes a novel real-world deployable on-chip sensor that: 1) is tamper-resistant by exploiting persistent changes caused by hot carrier injection (HCI); 2) generates a DC signal measurable by common low-cost test equipment; and 3) reuses an existing I/O interface, including existing pins; while 4) requiring a very small footprint. …”
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A Comparative Study of Parking Occupancy Prediction Methods considering Parking Type and Parking Scale by Ziyao Zhao, Yi Zhang, Yi Zhang

“…To compare the predictive performances of these models, real-world data of four parks in Shenzhen, Shanghai, and Dongguan were collected over 8 weeks to estimate the correlation between the parking lot attributes and forecast results. …”
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Mathematical Modeling for Water Quality Management under Interval and Fuzzy Uncertainties by J. Liu, Y. P. Li, G. H. Huang

“…IFCP is capable of tackling uncertainties presented as interval numbers and possibility distributions as well as analyzing the reliability of satisfying (or the risk of violating) system’s constraints. A real-world case for water quality management planning of the Xiangxi River in the Three Gorges Reservoir Region (which faces severe water quality problems due to pollution from point and nonpoint sources) is then conducted for demonstrating the applicability of the developed method. …”
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