Carbon Lock-In Mechanisms in Transport Infrastructure and Temporal Spatial Dynamics by Yinghui Zhang, Yun Chen, Kai Li, Yong Wu, Chongsen Ma

“…A composite indicator system is constructed to quantify path dependence in transport-related carbon emissions. …”
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IECO: an improved educational competition optimizer for state-of-the-art engineering optimization by Xiaojie Tang, Junbo Jacob Lian, Ling Ma, Xincan Wu, Rui Zhong, Yujun Zhang, Huiling Chen

“…These enhancements significantly boost IECO’s exploration and exploitation capabilities, leading to superior convergence and efficiency in handling high-dimensional problems. We evaluate IECO on classical functions, CEC 2017 and CEC 2022 test functions, 2 engineering hyperparameter optimization problems, 10 real-world engineering design problems, and 2 multi-UAV path planning problems. …”
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Theoretical Study of Elliptic Drum of Vertical Spindle Cotton Picker by Shavkat Ravutov, Abdumalik Rakhimov, Gafurjan Ibragimov

“…Special attention is given to the shape and dimensions of the directional path, ensuring the elliptical movement of the spindles. …”
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A Quantitative Evaluation of UAV Flight Parameters for SfM-Based 3D Reconstruction of Buildings by Inho Jo, Yunku Lee, Namhyuk Ham, Juhyung Kim, Jae-Jun Kim

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Efficient Aerial Data Collection with UAV in Large-Scale Wireless Sensor Networks by Chengliang Wang, Fei Ma, Junhui Yan, Debraj De, Sajal K. Das

“…We have identified the key challenges in each of them and have proposed efficient solutions. This includes proposal of a Fast Path Planning with Rules (FPPWR) algorithm based on grid division, to increase the efficiency of path planning, while guaranteeing the length of the path to be relatively short. …”
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An Efficient Node Localization Approach with RSSI for Randomly Deployed Wireless Sensor Networks by Xihai Zhang, Junlong Fang, Fanfeng Meng

“…An efficient path planning approach in mobile beacon localization for the randomly deployed wireless sensor nodes is proposed in this paper. …”
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A Novel Method for Additive Manufacturing of Complex Shape Curved Parts by Using Variable Height Layers by Matthieu Rauch, Jorge Piedra Dorado, Jean-Yves Hascoet, Guillaume Ruckert

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Hydrodynamic efficient cell capture and pairing method on microfluidic cell electrofusion chip by Xuefeng Wang, Yaqi Bai, Xiaoling Zhang, Wei Li, Jun Yang, Ning Hu

“…In this study, we present a novel microfluidic device that utilizes a three-path symmetrical channel hydrodynamic capture method to achieve high-efficiency cell capture and pairing. …”
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Energy-Efficient UAV Relaying Robust Resource Allocation in Uncertain Adversarial Networks by Shakil Ahmed, Mostafa Zaman Chowdhury, Saifur Rahman Sabuj, Md Imtiajul Alam, Yeong Min Jang

“…We aim to optimize robust transmit power, both UAV and BS along, with relay hovering path, speed, and acceleration. The BS sends legitimate information, which is forwarded to the user by the relay. …”
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Efficient visible wavelength mode switch based on mode-engineered ring resonator by Pushkar Jha, Aseema Mohanty

“…This provides a viable path toward compact and high resolution beam shaping, structuring, and steering at visible wavelengths.…”
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An Efficient Procedure for Inserting Buffers to Generate Robust Berth Plans in Container Terminals by Yangcan Wu, Lixin Miao

“…Hence, the contribution in this paper will provide a short path that bridges the gap between berth allocation problem in deterministic and stochastic circumstances.…”
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Dynamic Topology Evolution and Multi-Objective Routing Optimization for Efficient VANET Communication by Hao Wang

“…Furthermore, the implementation of Dijkstra’s algorithm enables efficient path selection with low computational complexity. …”
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Hierarchical Reinforcement Learning for Quadrupedal Robots: Efficient Object Manipulation in Constrained Environments by David Azimi, Reza Hoseinnezhad

“…Furthermore, the RL framework effectively integrates path planning in complex environments, achieving energy-efficient and stable operations. …”
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Forwarding efficiency aware traffic scheduling algorithm based on deep reinforcement learning by Zongxuan SHA, Ru HUO, Chuang SUN, Shuo WANG, Tao HUANG

“…The software defined network separates the control plane from the data plane to achieve flexible traffic scheduling, which can use network resources more efficiently.However, with the increase of the number of flow entries, load rate, the number of connected hosts, and other factors, the forwarding efficiency of the SDN switch will be reduced, which will affect the end-to-end transmission delay.To solve the above problems, the forwarding efficiency aware traffic scheduling algorithm based on deep reinforcement learning was proposed.First, the switch state was integrated into the perception model, and the mapping relationship between switch state information and forwarding efficiency was established based on neural network.Then, combined with network state and traffic information, traffic scheduling policy was generated through deep reinforcement learning.Finally, the expert samples generated by the shortest path and load balance algorithms could guide the model training, which enabled the model to learn knowledge from expert samples to improve performance and accelerated the training process.The experimental results show that the proposed algorithm not only reduces the average end-to-end transmission delay by 15.31%, but also ensures the overall load balance of the network, compared with other algorithms.…”
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Forwarding efficiency aware traffic scheduling algorithm based on deep reinforcement learning by Zongxuan SHA, Ru HUO, Chuang SUN, Shuo WANG, Tao HUANG

“…The software defined network separates the control plane from the data plane to achieve flexible traffic scheduling, which can use network resources more efficiently.However, with the increase of the number of flow entries, load rate, the number of connected hosts, and other factors, the forwarding efficiency of the SDN switch will be reduced, which will affect the end-to-end transmission delay.To solve the above problems, the forwarding efficiency aware traffic scheduling algorithm based on deep reinforcement learning was proposed.First, the switch state was integrated into the perception model, and the mapping relationship between switch state information and forwarding efficiency was established based on neural network.Then, combined with network state and traffic information, traffic scheduling policy was generated through deep reinforcement learning.Finally, the expert samples generated by the shortest path and load balance algorithms could guide the model training, which enabled the model to learn knowledge from expert samples to improve performance and accelerated the training process.The experimental results show that the proposed algorithm not only reduces the average end-to-end transmission delay by 15.31%, but also ensures the overall load balance of the network, compared with other algorithms.…”
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High Efficiency Generalized Parallel Counters for Look-Up Table Based FPGAs by Burhan Khurshid, Roohie Naaz Mir

“…This results in low efficiency GPCs. In this work, we present a heuristic that efficiently maps the GPC logic onto the LUT fabric. …”
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Efficient Classification of Pomegranate Diseases Using Deep Learning Models and Interactive Visualization by Mishra Gaurav, Nagaonkar Jagruti, Parmar Harsh, Joshi Gaurav

“…The findings demonstrate the possibility of deep learning in plant disease management, paving the path for future AI-based advances in precision farming that would ensure global sustainability, economic stability, increased yield, and food security. …”
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Efficient Resource Allocation and Utilization: The Missing Link in Nigeria’s Quest for Sustainable Development by Ehiorobo Abraham Osa

“…Conclusion drawn from the study indicates that if proper project planning, execution, monitoring and evaluation are carried out in a transparent manner, and resources are efficiently allocated and utilized, Nigeria would be on the path to sustainable development. …”
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Efficient and Secure Routing Protocol Based on Encryption and Authentication for Wireless Sensor Networks by Jiliang Zhou

“…Furthermore, we still design routing path selection system, intrusion detection system, and the multiple-threaded process mechanism for BEARP. …”
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Research on Parameter-Efficient Knowledge Graph Completion Methods and Their Performance in the Cybersecurity Field by Bin Chen, Hongyi Li, Ze Shi

“…As an advanced knowledge management and reasoning tool, knowledge graph technology can significantly enhance the efficiency of managing and analyzing cyberthreat intelligence, providing strong technical support for cybersecurity threat identification and situational awareness. …”
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