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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Stability Analysis and Construction Parameter Optimization of Tunnels in the Fractured Zone of Faults by Banma Huang, Haibo Chen, Chenglong Duan, Wenhu Li

“…In order to improve the construction method of highway tunnel fault, improve the excavation level, improve the construction efficiency, reduce the project cost, and shorten the construction period, so as to find a specific road, this paper puts forward the research method of tunnel stability analysis and construction parameter optimization in the fault fracture zone. …”
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Comprehensive Comparison and Validation of Forest Disturbance Monitoring Algorithms Based on Landsat Time Series in China by Yunjian Liang, Rong Shang, Jing M. Chen, Xudong Lin, Peng Li, Ziyi Yang, Lingyun Fan, Shengwei Xu, Yingzheng Lin, Yao Chen

“…When considering different forest disturbance types, COLD achieved the highest accuracies for Fire, Harvest, and Other disturbances, while CCDC was most accurate for Forestation. These findings highlight the necessity of region-specific calibration and parameter optimization tailored to specific disturbance types to improve forest disturbance monitoring accuracy, and also provide a solid foundation for future studies on algorithm modifications and ensembles.…”
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Flex-route demand response transit scheduling based on station optimization by HU Di, JIN Wenzhou

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A combined model of shoot phosphorus uptake based on sparse data and active learning algorithm by Tianli Wang, Yi Zhang, Haiyan Liu, Fei Li, Dayong Guo, Ning Cao, Yubin Zhang

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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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Creation of a Custom 3D Algorithm for Proper Alignment of Straight Nails in Tibiotalocalcaneal Arthrodesis by Omer Subasi PhD, Wei Shao Tung BS, Julian Hollander Bsc, Samir Ghandour MD, Atta Taseh MD, Nour Nassour MD, Adarsh Aratikatla, Alireza Ebrahimi MD, Bernard Burgesson MD, Soheil Ashkani-Esfahani MD, John Y. Kwon MD

“…Conclusion: A straight nail passing through the sustentaculum tali places surrounding neurovascular structures at risk and can also compromise the biomechanical stability of the implant. Our novel 3D algorithm shows that intraoperative adjustment of the starting point lateral to the central tibial axis is required to obtain optimal alignment of the hindfoot nail. …”
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Medical Image Hybrid Watermark Algorithm Based on Frequency Domain Processing and Inception v3 by Yu Fan, Jingbing Li, Uzair Aslam Bhatti, Saqib Ali Nawaz, Yenwei Chen

“…Existing research has mostly focused on optimizing individual techniques, lacking comprehensive solutions that integrate the strengths of different methods. …”
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Significance of Machine Learning-Driven Algorithms for Effective Discrimination of DDoS Traffic Within IoT Systems by Mohammed N. Alenezi

“…Findings revealed that the RF model outperformed other models by delivering optimal detection speed and remarkable performance across all evaluation metrics, while KNN (K = 7) emerged as the most efficient model in terms of training time.…”
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Adaptive Q-Learning Grey Wolf Optimizer for UAV Path Planning by Golam Moktader Nayeem, Mingyu Fan, Golam Moktader Daiyan

“…Grey Wolf Optimization (GWO) is one of the most popular algorithms for solving such problems. …”
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RESEARCH ON PARAMETRIC ANALYSIS AND MULTI-OBJECTIVE OPTIMIZATION OF CYLINDRICAL PRESSURE STRUCTURE by LIU Feng, TU ChaoHua, ZHAO YanKai

“…In order to improve the design efficiency and performance of the cylindrical pressure structure,strength and stability analysis methods were determined,the initial scheme was analyzed. the second development of Abaqus software was carried out by using Python language,Abaqus was integrated with i Sight software,the parametric analysis flow of pressure structure was designed,could realize automatic modeling and analysis of cylindrical pressure structure. the most Latin hypercube method was used to selectting the sample points,the sensitivity analysis of the design variables were carried out,The comparison of the fitting accuracy shown that the response surface model had the highest accuracy,the approximate model of the cylindrical pressure structure based on the fourth-order response surface was obtained. the multi-objective optimization model was established,The second generation of non dominated sorting genetic algorithm was used to solving the multi-objective optimization problem,the results shown that the weight of the optimization scheme was reduced,while the ultimate strength was greatly improved,improved the performance of the cylindrical pressure structure.…”
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Post-Quantum Cryptographic Frameworks for Internet of Things (IoT) and Internet of Medical Things (IoMT) Authentication Systems by Thomas L Barna, Samson Isaac, Christopher Habu, Saratu Habu, Abimbola A Joseph

“…This work contributes three key advancements: (1) an optimized NTRU implementation for medical IoT devices, (2) a novel integration of metaheuristic optimization with post-quantum cryptography, and (3) comprehensive validation across IoMT device classes. …”
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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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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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An ensemble agglomerative hierarchical clustering algorithm based on clusters clustering technique and the novel similarity measurement by Teng Li, Amin Rezaeipanah, ElSayed M. Tag El Din

“…MCEMS uses the bi-weighting policy to solve the model selection associated problem to improve ensemble clustering. Specifically, multiple AHC individual methods cluster the data from different aspects to form the primary clusters. …”
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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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Optimizing concrete strength: How nanomaterials and AI redefine mix design by Dan Huang, Guangshuai Han, Ziyang Tang

“…XGB was identified as the most effective ML algorithm for predicting compressive strength among others in this study (R2=0.974). …”
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A Novel Two-Stage Learning-Based Phase Unwrapping Algorithm via Multimodel Fusion by Chao Yan, Tao Li, Yandong Gao, Shijin Li, Xiang Zhang, Xuefei Zhang, Di Zhang, Huiqin Liu

“…To solve this problem, this paper combines a deep neural network model with the traditional PhU model and proposes a novel two-stage learning-based phase unwrapping (TLPU) algorithm via multimodel fusion. The major advantages of TLPU are as follows: 1) A high-resolution U-Net (HRU-Net) model trained on a dataset constructed according to InSAR interferometric geometry is utilized for the PhU for the first time, which effectively improves the performance of the DLPU. 2) TLPU utilizes the traditional PhU method to optimize the results of DLPU, addressing the issue of weak generalization ability of a single DLPU, while improving accuracy in areas with large-gradient changes. …”
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