Flex-route demand response transit scheduling based on station optimization by HU Di, JIN Wenzhou

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Location privacy protection method based on lightweight K-anonymity incremental nearest neighbor algorithm by Saite CHEN, Weihai LI, Yuanzhi YAO, Nenghai YU

“…The use of location-based service brings convenience to people’s daily lives, but it also raises concerns about users’ location privacy.In the k-nearest neighbor query problem, constructing K-anonymizing spatial regions is a method used to protects users’ location privacy, but it results in a large waste of communication overhead.The SpaceTwist scheme is an alternative method that uses an anchor point instead of the real location to complete the k-nearest neighbor query,which is simple to implement and has less waste of communication overhead.However,it cannot guarantee K-anonymous security, and the specific selection method of the anchor point is not provided.To address these shortcomings in SpaceTwist, some schemes calculate the user’s K-anonymity group by introducing a trusted anonymous server or using the way of user collaboration, and then enhance the end condition of the query algorithm to achieve K-anonymity security.Other schemes propose the anchor point optimization method based on the approximate distribution of interest points, which can further reduce the average communication overhead.A lightweight K-anonymity incremental nearest neighbor (LKINN) location privacy protection algorithm was proposed to improve SpaceTwist.LKINN used convex hull mathematical tool to calculate the key points of K-anonymity group, and proposed an anchor selection method based on it, achieving K-anonymity security with low computational and communication costs.LKINN was based on a hybrid location privacy protection architecture, making only semi-trusted security assumptions for all members of the system, which had lax security assumptions compared to some existing research schemes.Simulation results show that LKINN can prevent semi-trusted users from stealing the location privacy of normal users and has smaller query response time and communication overhead compare to some existing schemes.…”
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An investigation on energy-saving scheduling algorithm of wireless monitoring sensors in oil and gas pipeline networks by Zhifeng Ma, Zhanjun Hao, Zhenya Zhao

“…In this context, Wireless Sensor Networks (WSNs) are widely used for monitoring oil and gas pipelines due to their flexible deployment and cost-effectiveness. However, since sensor nodes typically rely on limited battery power, extending the network’s lifecycle and improving energy utilization efficiency have become focal points of research. …”
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Marine Voyage Optimization and Weather Routing with Deep Reinforcement Learning by Charilaos Latinopoulos, Efstathios Zavvos, Dimitrios Kaklis, Veerle Leemen, Aristides Halatsis

“…These algorithms are computationally costly, so we split optimization into an offline phase (costly pre-training for a route) and an online phase where the algorithms are fine-tuned as updated weather data become available. …”
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Resource-Efficient Context-Aware Dynamical Decoupling Embedding for Arbitrary Large-Scale Quantum Algorithms by Paul Coote, Roman Dimov, Smarak Maity, Gavin S. Hartnett, Michael J. Biercuk, Yuval Baum

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Occlusion mapping reveals the impact of flight and sensing parameters on vertical forest structure exploration with cost-effective UAV based laser scanning by Matthias Gassilloud, Barbara Koch, Anna Göritz

“…Our results offer transferable insights to optimize UAV LiDAR data acquisitions, thereby contributing to an enhanced structural metric retrieval and improved analysis of forest functional properties.…”
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Energy Aware Swarm Optimization with Intercluster Search for Wireless Sensor Network by Shanmugasundaram Thilagavathi, Bhavani Gnanasambandan Geetha

“…Challenges in WSN include a well-organized communication platform for the network with negligible power utilization. In this work, an improved binary particle swarm optimization (PSO) algorithm with modified connected dominating set (CDS) based on residual energy is proposed for discovery of optimal number of clusters and cluster head (CH). …”
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A Review of Smart Camera Sensor Placement in Construction by Wei Tian, Hao Li, Hao Zhu, Yongwei Wang, Xianda Liu, Rongzheng Yang, Yujun Xie, Meng Zhang, Jun Zhu, Xiangyu Wang

“…This comprehensive review navigates through the complexities of camera and environment models, advocating for advanced optimization techniques like genetic algorithms, greedy algorithms, Swarm Intelligence, and Markov Chain Monte Carlo to refine CSP strategies. …”
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The Application of the SubChain Salp Swarm Algorithm in the Less-Than-Truckload Freight Matching Problem by Yibo Sun, Lei Yue, Yi Liu, Weitong Chen, Zhe Sun

“…Traditional LTL matching methods are challenged by delays in updating logistic information and higher distribution costs. In order to solve LTL challenges, we developed a novel SubChain Salp Swarm Algorithm (SSSA) by improving the traditional Salp Swarm Algorithm with the utilization of a SubChain operation. …”
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Development and Comparison of Interrupt-Based and Analog-to-Digital Converter Algorithms for Seed Counting in Precision Planters by A. Ghaffarnezhad, H. Navid, H. Karimi

“…Both developed circuits featured the deployment of the STM32F103C8T6 microcontroller, renowned for its robust capabilities and cost efficiency.In the interrupt-based algorithm's development, the microcontroller's external interrupt was used, selecting its sensitivity to detect both rising and falling edges. …”
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Optimization of external container delivery and pickup scheduling based on appointment mechanism. by Pengfei Huang, Hao Wang, Fangjiao Tan, Yuyue Jiang, Jinfen Cai

“…Through case studies, we have demonstrated the superior performance of this algorithm in addressing relevant problems. The results show that, in terms of truck operational costs, the improved algorithm reduces costs by 10.96% and 3.02% compared to traditional Ant Colony Optimization and Variable Neighborhood Search algorithms, respectively, and by 4.89% compared to manual scheduling. …”
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Advancing sustainable renewable energy: XGBoost algorithm for the prediction of water yield in hemispherical solar stills by Salwa Ahmad Sarow, Hasan Abbas Flayyih, Maryam Bazerkan, Luttfi A. Al-Haddad, Zainab T. Al-Sharify, Ahmed Ali Farhan Ogaili

“…Initially explored was the effect of different sand types and bed heights on HSS performance, with the findings indicating that black sand, especially at a height of 1 cm combined with reflectors and a fan, markedly improved efficiency and production. An economic analysis revealed a significant reduction in water treatment costs with the optimized system. …”
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Adaptive Q-Learning Grey Wolf Optimizer for UAV Path Planning by Golam Moktader Nayeem, Mingyu Fan, Golam Moktader Daiyan

“…In path planning simulation, QGWO lowers the path cost by 27.4%, improves the convergence speed by 19.06%, and reduces the area under the curve (AUC) by 23.8% over standard GWO, achieving optimal trajectory. …”
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Investigating the Performance of Open-Vocabulary Classification Algorithms for Pathway and Surface Material Detection in Urban Environments by Kauê de Moraes Vestena, Silvana Phillipi Camboim, Maria Antonia Brovelli, Daniel Rodrigues dos Santos

“…The second experiment evaluates standardized pavement classification using the Deep Pavements dataset and a fine-tuned CLIP algorithm optimized for detecting OSM-compliant pavement categories. …”
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Multi-objective Optimization Design of Component Cooling System in HPR1000 by ZHAO Weiguang1, 2, YU Pei1, 3, ZENG Xiaobo1, 2, FAN Guangming1, 2, YAN Changqi1, 2

“…To manage this complexity, a novel optimization algorithm was implemented to perform multi-objective optimization. …”
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Assessment of Urban Water Supply System Based on Query Optimization Strategy by Shibao Lu, Yizi Shang, Wei Li, Zhimin Wang

“…As a complicated water treatment system project, an urban water supply plays a significant role in enhancing ecological civilization construction, promoting social-economic sustainable development, and improving the living environment of humans. This paper has the goal of improving water treatment efficiency and reducing water treatment cost based on comparative studies by applying two types of distributed database query optimization methods, including the system for a distributed database (SDD-1) and all reduction algorithms. …”
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Reliability Optimization Model of Stop-Skipping Bus Operation with Capacity Constraints by Zhenhua Mou, Hu Zhang, Shidong Liang

“…Finally, a numerical example based on a bus route in Changchun city is carried out to test the reliability optimization model. Results showed that the reliability optimization strategy can improve the stability of stop service and then save cost of passengers’ travel time.…”
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Application of deep reinforcement learning in parameter optimization and refinement of turbulence models by Zhan Zhang

“…The aim of this study is to improve the accuracy of simulations by optimizing turbulence model parameters, in order to address the cost and time limitations of traditional wind tunnel tests and on-site measurements. …”
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Optimized YOLOv8 framework for intelligent rockfall detection on mountain roads by Peng Peng, Langchao Gao, Jiachun Li, Hongzhen Zhang

“…To enable efficient detection, this study proposes a rockfall detection system based on embedded technology and an improved Yolov8 algorithm, termed Yolov8-GCB. The algorithm enhances detection performance through the following optimizations: (1) integrating a lightweight DeepLabv3+ road segmentation module at the input stage to generate mask images, which effectively exclude non-road regions from interference; (2) replacing Conv convolution units in the backbone network with Ghost convolution units, significantly reducing model parameters and computational cost while improving inference speed; (3) introducing the CPCA (Channel Priori Convolution Attention) mechanism to strengthen the feature extraction capability for targets with diverse shapes; and (4) incorporating skip connections and weighted fusion in the Neck feature extraction network to enhance multi-scale object detection. …”
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Cost-effectiveness of FIT and a FIT-based model to optimise symptomatic diagnosis of colorectal cancer: health economic modelling for the COLOFIT project by Linda Sharp, Sarah Bailey, Colin Rees, Willie Hamilton, Dawn Craig, Joe West, David Humes, Gary Abel, James Turvill, Brian Nicholson, Chloe Thomas, Jim Chilcott, Colin Crooks, Olena Mandrik, John Whelpton

“…Cost-effectiveness improves as risk thresholds rise. …”
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