AntBot-EX: Enhancing robot search efficiency in complex post-disaster environments. by Yao Xue, Chee Keong Tan, Wai Peng Wong

“…Thirdly, to address computational limitations in large and complex environments, a configurable boundary-aware and a score-based threshold are introduced to simplify paths by strategically disregarding irrelevant regions, optimizing search efficiency. …”
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An Efficient Reliable Communication Scheme in Wireless Sensor Networks Using Linear Network Coding by Jin Wang, Xiumin Wang, Shukui Zhang, Yanqin Zhu, Juncheng Jia

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Energy Efficiency and Reliability in Underwater Wireless Sensor Networks Using Cuckoo Optimizer Algorithm by M. Dosaranian-Moghadam, Z. Amo-Rahimi

“…In this paper, in order to maintain energy efficiency and reliability in a UWSN, Cuckoo Optimization Algorithm (COA) is adopted that is a combination of three techniques of geo-routing, multi-path routing, and Duty-Cycle mechanism. …”
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Energy and Spectral Efficiency Analysis for UAV-to-UAV Communication in Dynamic Networks for Smart Cities by Mfonobong Uko, Sunday Ekpo, Ubong Ukommi, Unwana Iwok, Stephen Alabi

“…Energy efficiency (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>η</mi><mi>e</mi></msub></semantics></math></inline-formula>) is evaluated by contrasting throughput with total power consumption, indicating that 2.4 GHz initiates at around 0.15 bits/Joule (decreasing to 0.02 bits/Joule after 10 s), whereas 28 GHz and 60 GHz demonstrate markedly worse <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>η</mi><mi>e</mi></msub></semantics></math></inline-formula> (as low as <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>10</mn><mrow><mo>−</mo><mn>3</mn></mrow></msup></semantics></math></inline-formula>–<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mn>10</mn><mrow><mo>−</mo><mn>4</mn></mrow></msup><mspace width="0.166667em"></mspace><mrow><mi>bits</mi><mo>/</mo><mi>Joule</mi></mrow></mrow></semantics></math></inline-formula>), resulting from increased path loss and oxygen absorption. …”
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LQT-Based Energy-Efficient Control for Intelligent Vehicles Optimized by Adaptive Genetic Algorithm by Xia Hong-Yang, Yang Ming, Luo Jing-Jing, Hong Xi, Xu Wei

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Intelligent Firefighting Technology for Drone Swarms with Multi-Sensor Integrated Path Planning: YOLOv8 Algorithm-Driven Fire Source Identification and Precision Deployment Strateg... by Bingxin Yu, Shengze Yu, Yuandi Zhao, Jin Wang, Ran Lai, Jisong Lv, Botao Zhou

“…This study aims to improve the accuracy of fire source detection, the efficiency of path planning, and the precision of firefighting operations in drone swarms during fire emergencies. …”
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A lightweight multi-path convolutional neural network architecture using optimal features selection for multiclass classification of brain tumor using magnetic resonance images by Amreen Batool, Yung-Cheol Byun

“…Furthermore, an optimal features module implemented to select the most promising features to enhance our proposed multi-path architecture's performance and computational efficiency. …”
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Real-time laser spot modulation in Laser Powder-Directed Energy Deposition via wobbling: A path to superior 316L stainless steel components by Stefano Felicioni, Alberta Aversa, Erica Librera, Mariangela Lombardi, Federica Bondioli

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Redundant Path Optimization in Smart Ship Software-Defined Networking and Time-Sensitive Networking Networks: An Improved Double-Dueling-Deep-Q-Networks-Based Approach by Yanli Xu, Songtao He, Zirui Zhou, Jingxin Xu

“…This research offers a novel and effective solution for shipboard switch path selection, thereby advancing the reliability and efficiency of smart ship communication systems.…”
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X-FuseRLSTM: A Cross-Domain Explainable Intrusion Detection Framework in IoT Using the Attention-Guided Dual-Path Feature Fusion and Residual LSTM by Adel Alabbadi, Fuad Bajaber

“…For cross-domain intrusion detection, this paper proposes a novel algorithm, X-FuseRLSTM, a dual-path feature fusion framework that is attention guided and coupled with a residual LSTM architecture. …”
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Design of an Active Axis Wind Turbine (AAWT) That Can Balance Centrifugal and Aerodynamic Forces to Reduce Support Infrastructure While Maintaining a Stable Flight Path by Jawad Mezaal, Jonathan Whale, Kim Schlunke, Parisa Arabzadeh Bahri, David Parlevliet

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IUmote: A Framework for the Efficient Modelling, Evaluation, and Deployment of Algorithms and Hardware for Underwater Communications by Antonio Sanchez, Angel Perles, Pedro Yuste, Juan V. Capella, Juan Jose Serrano

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ENERGY-EFFICIENT PASSIVE ANTENNA CODE PULSE MODULATION DUE TO THE REFLECTION OF MICROWAVE SIGNAL by T. A. Ismailov, H. M. Gadjiyev, T. A. Chelushkinа, A. S. Shkurko, P. A. Magomedova

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An Energy-Efficient Clustering Routing for Wireless Sensor Networks Based on Energy Consumption Optimization by Xu Huibin, Zeng Mengjia

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Autonomous deployment and energy efficiency optimization strategy of UAV based on deep reinforcement learning by Yi ZHOU, Xiaoyong MA, Fuxiao GAO, Wei LI, Nan CHENG, Ning LU

“…Utilizing a UAV to build aerial mobile small cell can provide more flexible and efficient access services for ground terminal users.Constrained by the coverage and limited energy of the UAV,it is necessary to study how to build a fast,efficient and energy-saving air-ground collaborative network.To deal with complex dynamic scenarios,the UAV needs to deploy an optimal coverage position,and meanwhile reduce both path loss and energy consumption in the deployment process.Based on the deep reinforcement learning,a strategy of autonomous UAV deployment and efficiency optimization was proposed.The coverage state set of UAV was established,and the energy efficiency was used as a reward function.Depth neural network and Q-learning were used to guide UAV to make autonomous decision and deploy the optimal position.The simulation results show that the deployment time of the proposed method can be effectively reduced by 60%,while the energy consumption can be reduced by 10%~20%.…”
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Improved Reliable Trust-Based and Energy-Efficient Data Aggregation for Wireless Sensor Networks by Chen-xu Liu, Yun Liu, Zhen-jiang Zhang

“…We call the protocol the iRTEDA protocol, and it combines the reputation system, residual energy, link availability, and a recovery mechanism to improve secure data aggregation and ensure that the network is secure, reliable, and energy-efficient. Simulations have shown that the iRTEDA protocol exceeds the performances of other protocols from the perspectives of the accuracy of the data, the reliability of the routing path, the consumption of energy, and the lifetime of secure data aggregation.…”
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Autonomous deployment and energy efficiency optimization strategy of UAV based on deep reinforcement learning by Yi ZHOU, Xiaoyong MA, Fuxiao GAO, Wei LI, Nan CHENG, Ning LU

“…Utilizing a UAV to build aerial mobile small cell can provide more flexible and efficient access services for ground terminal users.Constrained by the coverage and limited energy of the UAV,it is necessary to study how to build a fast,efficient and energy-saving air-ground collaborative network.To deal with complex dynamic scenarios,the UAV needs to deploy an optimal coverage position,and meanwhile reduce both path loss and energy consumption in the deployment process.Based on the deep reinforcement learning,a strategy of autonomous UAV deployment and efficiency optimization was proposed.The coverage state set of UAV was established,and the energy efficiency was used as a reward function.Depth neural network and Q-learning were used to guide UAV to make autonomous decision and deploy the optimal position.The simulation results show that the deployment time of the proposed method can be effectively reduced by 60%,while the energy consumption can be reduced by 10%~20%.…”
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Structural Efficiency and Robustness Evolution of the US Air Cargo Network from 1990 to 2019 by Changsong Zhao, Chunliang Xiu

“…Further, we discover that the average path lengths have increased, and the overall efficiency has decreased from 0.7 to 0.4 due to the dependency of the hub-and-spoke structure. …”
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A Simple and Efficient Way to Save Energy in Multihop Wireless Networks with Flow Aggregation by Alexandre Laube, Dominique Quadri, Steven Martin, Khaldoun Al Agha

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The effects of digital transformation on corporate energy efficiency: a supply chain spillover perspective by Fangfang Song

“…Moreover, both digital finance and public environmental concern show significant positive moderating effects, and digital finance can positively moderate the contribution of corporate digital transformation to the energy efficiency of downstream firms. Finally, we investigate the heterogeneous treatment impact across different firms, and find that the positive effect is more pronounced in a subsample of state-owned and eastern firms, short-distance downstream firms and downstream firms with low-resource endowments.DiscussionTherefore, a platform should be provided for enterprises to promote digital transformation and unblock the conduction path of green innovation and energy structure in order to realize the green transformation of the entire supply chain.…”
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