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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Joint Caching and Computation in UAV-Assisted Vehicle Networks via Multi-Agent Deep Reinforcement Learning by Yuhua Wu, Yuchao Huang, Ziyou Wang, Changming Xu

“…To address these challenges, this paper proposes a MADRL-based joint optimization approach. We precisely model the problem as a Decentralized Partially Observable Markov Decision Process (Dec-POMDP) and adopt the Multi-Agent Proximal Policy Optimization (MAPPO) algorithm, which follows the Centralized Training Decentralized Execution (CTDE) paradigm. …”
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Minimum Error Integration Method for Quadrilateral Flat Plate Fitting in Steel Construction by Zhuoju Huang, Jiemin Ding

“…Current industry practices often approximate mildly curved surfaces with flat plates within tolerances, but optimizing this substitution to minimize fitting errors while reducing the quantity of curved plates remains a critical engineering challenge. …”
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An Efficient Energy Constraint Based UAV Path Planning for Search and Coverage by German Gramajo, Praveen Shankar

“…The proposed formulation has a high level of autonomy, without requiring an exact choice of optimization parameters, and is appropriate for real-time implementation. …”
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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

“…This data sharing plays a crucial role in improving power system stability, optimizing energy distribution, and enhancing energy efficiency. …”
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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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Resource Allocation in User-Centric Cell-Free Massive MIMO URLLC Systems With Network Slicing by Han Lu, Weiwei Xia, Weiwei Miao, Mingxuan Zhang, Feng Yan, Lianfeng Shen

“…The user-slice association problem is addressed using the simulated annealing algorithm. For the resource allocation problem, a successive rate lower bound maximization algorithm is employed to obtain the convex lower bound of the data rate under short packet transmission, and the successive convex approximation (SCA) method is used to determine the optimal bandwidth and frequency allocation. …”
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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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FPGA Acceleration With Hessian-Based Comprehensive Intra-Layer Mixed-Precision Quantization for Transformer Models by Woohong Byun, Jongseok Woo, Saibal Mukhopadhyay

“…Coupled with the proposed algorithm and dataflow optimization, it enables on-chip storage of all necessary parameters, minimizing off-chip memory access. …”
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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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Cost-efficient behavioral modeling of antennas by means of global sensitivity analysis and dimensionality reduction by Slawomir Koziel, Anna Pietrenko-Dabrowska

“…Abstract Computational tools, particularly electromagnetic (EM) solvers, are now commonplace in antenna design. While ensuring reliability, EM simulations are time-consuming, leading to high costs associated with EM-driven procedures like parametric optimization or statistical design. …”
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Dynamic characteristics of a semi-active fractional-order inerter-based suspension with acceleration-velocity switch control by Yong Wang, Jiachen Li, Mingzhu Ji, Xiwen Qiao, Yang Wang

“…The optimized SA-FOIB suspension further improves the dynamic performance of the suspension dynamic deflection and wheel dynamic load, which the corresponding RMS values are smaller than the unoptimized SA-FOIB suspension, while deteriorates the vehicle body acceleration.…”
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Texture mapping of warp knitted shoe upper based on ARAP parameterization method by Guilong Cheng, Aijun Zhang, Yanting Zhang

“…Additionally, discrete harmonic and parametric optimization unfolding algorithms are employed to enhance texture mapping quality. …”
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Quantum reinforcement learning in continuous action space by Shaojun Wu, Shan Jin, Dingding Wen, Donghong Han, Xiaoting Wang

“…Moreover, our approach facilitates single-shot quantum state generation: a one-time optimization produces a model that outputs the control sequence required to drive a fixed initial state to any desired target state. …”
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Many-to-Many Multicast Routing Schemes under a Fixed Topology by Wei Ding, Hongfa Wang, Xuerui Wei

“…This paper uses the dynamic programming method to devise an exact algorithm, respectively, for the centralized and decentralized versions of each optimization problem.…”
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STUDY OF THE INFLUENCE OF THE COMPOSITION OF CULTURAL MEDIUM ON THE BASIS OF A WHITE CABBAGE ON DEVELOPMENT OF LEUCONOSTOC MESENTEROIDES AT THE PRE-FERMENTATION STAGE by V. V. Kondratenko, O. Yu. Lyalina, N. E. Posokina, A. Yu. Kolokolova, V. I. Tereshonok

“…In connection with this, an algorithm was developed to determine the optimal duration of pre-fermentation – «stop points». …”
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The Use of AI in Elementary School Learning: A Systematic Literature Review by Natalina Purba, Desti Pujiati, Partohap Saut Raja Sihombing, Hendra Simanjuntak, Desi Sijabat

“…The results offer practical recommendations for educators, policymakers, and technology developers to optimize AI use in primary schools, ensuring that it becomes an inclusive tool for enhancing educational outcomes. …”
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Urban Air Mobility Vertiport’s Capacity Simulation and Analysis by Antoni Kopyt, Sebastian Dylicki

“…By examining the interplay between infrastructure design, operational workflows, and resource allocation, the research provides a versatile tool for urban planners and policymakers to optimize vertiport layouts and traffic management protocols. …”
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Leveraging machine learning to predict residential location choice: A comparative analysis by Vahid Noferesti, Hamid Mirzahossein

“…These findings offer valuable insights for policymakers and urban planners to optimize land use, transportation, and urban development strategies.…”
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