An online tool based on the Internet of Things and intelligent blockchain technology for data privacy and security in rural and agricultural development by Krishnaprasath Vellimalaipattinam Thiruvenkatasamy, Hayder M. A. Ghanimi, Sudhakar Sengan, Meshal Ghalib Alharbi

“…Central to this model is the proposed Quantum Neural Network + Bayesian Optimization (QNN + BO), a practiced algorithm that, when combined with methods like the Elliptic Curve Cryptography (ECC) and Coyote Optimization Algorithm (COA), guarantees secure data flow, processing, and storage. …”
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An Efficient Fine-Grained Access Control Scheme Based on Policy Protection in SGs by Xiaoqing Guo, Huayi Wu, Zhen Qin, Ruonan Ying, Jilai Yang

“…Security analysis demonstrates that the proposed scheme meets the defined security requirements, while performance evaluation indicates that it incurs minimal computational overhead while achieving enhanced privacy protection.…”
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ApproximateSecret Sharing in Field of Real Numbers by Jiaqi Wan, Ziyue Wang, Yongqiang Yu, Xuehu Yan

“…To address these issues, this paper proposes an innovative algorithm to optimize SSS via type-specific coding for real numbers. …”
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Task offloading and resource allocation for blockchain‐enabled mobile edge computing by Renbin Fang, Peng Lin, Yize Liu, Yan Liu

“…To manage the allocation of computing resources between task offloading and blockchain consensus, the task offloading and resource allocation are formulated as a joint optimization problem. The aim of the problem is to minimize the energy consumption of UTs while guaranteeing the delay requirement. …”
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Wide-Range Variable Cycle Engine Control Based on Deep Reinforcement Learning by Yaoyao Ding, Fengming Wang, Yuanwei Mu, Hongfei Sun

“…To solve this problem, this paper adopts a deep reinforcement learning method based on a deep deterministic policy gradient algorithm, and it applies an action space pruning technique to optimize the controller, which significantly improves the convergence speed of network training. …”
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Integrating distributed photovoltaic and energy storage in 5G networks for sustainable IoT applications by Yi Zhong, Yiting Wu, Yi Zheng, Xiaohu Ge

“…This paper explores the integration of distributed photovoltaic (PV) systems and energy storage solutions to optimize energy management in 5G base stations. By utilizing IoT characteristics, we propose a dual-layer modeling algorithm that maximizes carbon efficiency and return on investment while ensuring service quality. …”
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Development and evaluation of a triplex real-time PCR assay for enhanced plague diagnostics in Madagascar. by Beza Ramasindrazana, Zoé A Rahalison, Philippe Gauthier, Guillain Mikaty, Zaina I Bodoarison, Lanto A Maminirina, Soloandry Rahajandraibe, Mamy G Randriamanantsoa, Gilbert Kayoko, Jean-Claude Manuguerra, Anne-Sophie Le Guern, Andriamiliharison J Rasamindrakotroka, Minoarisoa Rajerison

“…Notably, the new assay resolved 100% of previously inconclusive cases from the duplex qPCR test targeting only pla and caf1.<h4>Discussion</h4>While a new plague diagnostic algorithm has been set up after the outbreak in 2017, the present study suggests a real-time PCR assay based on three genes to improve the speed and accuracy of plague diagnostic. …”
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Assessing ornamental tree maturity and spray requirements using depth sensing and LiDAR technologies by Aleena Rayamajhi, Guoyu Lu, Ernest William Tollner, Jean Williams-Woodward, Md Sultan Mahmud

“…Effective assessment of tree maturity and agrochemical application requirements is important for optimizing resource use and sustainability in woody ornamental nurseries. …”
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Scalable Hyperspectral Enhancement via Patch-Wise Sparse Residual Learning: Insights from Super-Resolved EnMAP Data by Parth Naik, Rupsa Chakraborty, Sam Thiele, Richard Gloaguen

“…The spectral and spatial characteristics of the scene encoded in the dictionary enable reconstruction through a first-order optimization algorithm to ensure an efficient sparse representation. …”
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Autonomous air combat decision making via graph neural networks and reinforcement learning by Lin Huo, Chudi Wang, Yue Han

“…To address these challenges, we propose a novel multi-aircraft autonomous decision-making approach based on graphs and multi-agent reinforcement learning (MADRL) under zero-order optimization, implemented through the GraphZero-PPO algorithm. …”
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Biopharmaceutical aspects of the development of transdermal forms of Lisinopril dihydrate by Shyteyeva Tatyana, Bezchasnyuk Elena, Kryskiv Oleg, Baranova Inna

“…Optimization of the algorithm for the development of transdermal drugs involves in vitro preformulation studies of the membrane permeability of APIs and the identification of factors that affect this process.…”
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Prediction of compressive strength and characteristics analysis of semi-flexible pavement desert sand grouting material based upon hybrid-BP neural network by Wenbang Zhu, Yuhang Li, Xiumei Zheng, Enze Hao, Dali Zhang, Zhen Wang

“…To precisely obtain DSGM exhibiting exceptional mechanical properties, the Backpropagation Neural Network (BPNN) model was optimized through the utilization of Particle Swarm Optimization (PSO), Sparrow Search Algorithm (SSA), and Genetic Algorithm (GA). …”
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An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage by German Gramajo, Praveen Shankar

“…The computed trajectory maximizes spatial coverage while closely satisfying terminal constraints on the position of the vehicle and minimizing the time of flight. …”
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Towards Robust Speech Models: Mitigating Backdoor Attacks via Audio Signal Enhancement and Fine-Pruning Techniques by Heyan Sun, Qi Zhong, Minfeng Qi, Uno Fang, Guoyi Shi, Sanshuai Cui

“…Second, we apply an adaptive fine-pruning algorithm to selectively deactivate malicious neurons while preserving the model’s linguistic capabilities. …”
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A 3D acid fracturing design calibrated to describe the productivity index in several southwestern Iranian oil fields by Mohammad Mirhashemi, Kaveh Ahangari, Ali Naghi Dehghan, Kamran Goshtasbi

“…Once these parameters are stabilized, the algorithm proceeds to calculate acid concentration at each node within the fracture area. …”
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Human adaptation to adaptive machines converges to game-theoretic equilibria by Benjamin J. Chasnov, Lillian J. Ratliff, Samuel A. Burden

“…Surprisingly, one algorithm can steer the human-machine interaction to the machine’s optimum, effectively controlling the human’s actions even while the human responds optimally to their perceived cost landscape. …”
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Deep learning-based energy efficient LSFD weights prediction for user centric cell free massive MIMO system by Moustafa Mohamed, Salwa El-Ramly, Bassant Abdelhamid

“…These models are trained using dataset generated from heuristic sparse LSFD optimization algorithm, this allows the models to learn the sparsity nature of the system and apply AP-UE association based on the values of the predicted LSFD weights at the receiver side while using the large scale fading coefficients as the models’ input. …”
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Cross-layer scheduling and dynamic resource allocation for MIMO-OFDMA/SDMA systems with multi-service by ZHONG Chong-xian1, LI Chun-guo1, YANG Lv-xi1

“…Cross-layer scheduling and dynamic resource allocation problems were investigated for downlink MIMO-OFDMA/SDMA systems with multi-service.Firstly,a mathematical formulation of the optimization problem was provided with the objective of maximizing the total system throughput under various constraints.Secondly,a user group-ing scheme was proposed utilizing clustering analysis method based on the type of services and the spatial compatibility of multiple users with multiple receive antennas.Thirdly,a new cross-layer scheduling and dynamic resource allocation algorithm was developed based on the proposed user grouping scheme combined with the priorities of different service,which maximizes the total system throughput by maximizing the throughput of each subcarrier.Simulation results show that compared with the existing schemes,the proposed algorithms obtain reasonable throughput performance while provide better QoS requirement for each user of different services.…”
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Multifactor Stock Selection Strategy Based on Machine Learning: Evidence from China by Jieying Gao, Huan Guo, Xin Xu

“…The main findings are as follows: the support vector regression has the most stable successful rate for predicting, while ridge regression and linear regression have the most unstable successful rate with more extreme cases; algorithm of support vector regression fitting higher-degree polynomials in Chinese A-share market is optimized, compared with the traditional linear regression both in terms of stock return and retracement control; the results of support vector regression significantly outperforming the CSI 500 index prove further.…”
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A Correlational Study on Architectural Design and Thermal Distribution Patterns Using a Novel Multi-Terminal Approach in Cylindrical Li-Ion Cell-Integrated Battery Packs by Sagar D, Raja Ramar, Shama Ravichandran

“…This approach features a multi-terminal configuration, incorporating a modified battery pack structure along with a multi-terminal switching algorithm that identifies the optimal terminal for current flow to the load. …”
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