Comparative analysis of extensive form zero sum game algorithms for Poker like games by Behbod Keshavarzi, Hamidreza Navidi

“…Abstract The resolution of extensive-form zero-sum games is a fundamental challenge in computational game theory, addressed through various algorithms, each with unique strengths and limitations. …”
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Influence of Absorbing Material Distribution on Double Slope Sound Decay in L-Shaped Room by Mirosław MEISSNER

“… The sound decay process in L-shaped room was the subject of this investigation. …”
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Classification of fetal abnormalities based on CTG signal by Baghdad Science Journal

“…The fetal heart rate (FHR) signal processing based on Artificial Neural Networks (ANN),Fuzzy Logic (FL) and frequency domain Discrete Wavelet Transform(DWT) were analysis in order to perform automatic analysis using personal computers. …”
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基于拓扑演化理论的周转轮系综合构型与自动装配 by 史晓影, 孟祥丰, 王慧武

“…Focusing on the topology model of epicyclic gear trains in the excessive abstraction and the pursuit of extreme divergence,the innovation and optimization design on wheel system failed to achieve the expected results.All kinds of possible configurations of complex topology model are achieved from the topology combination theory based on topological unit.However,due to the complex topologies symbol meaning uncertainty and element meaning still diverge,so between the topology and simulation gear trains still not one to one relationship.To solve this problem,the topology evolution theory is proposed after the combination theory and establishing the evolution rules,the qualitative evolution for the topology elements is realized,the conversion process from combination-topology to assembly-topology is achieved,the purpose of search for all possible topologies are realized.Finally,epicyclic automatic assembly is realized rely on the extract information of assembly-topology which are obtained by computer.The result shows that methods are reasonable and feasible.Through these theories and methods,the foundation of simulation-experiment environment for trains mechanism innovation and optimization design is established,the new ideas for modeling analysis are provided.…”
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Influence of damping and fluid loading on the plate vibration control by Lucyna LENIOWSKA

“…The simulations of the active cancellation of the plate vibrations were made with a Simulink/Matlab computer program. …”
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An accurate semi-empirical model for PMT pulse signal analysis. by Shuo Li, Xudong Lyu, Fei Wang, Chao Sun

“…The energy information of pulse signals is significantly important for applications such as computed tomography (CT), positron emission tomography (PET), and research on defects in condensed matter. …”
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Gamefication in Communications by S. N. Lobanova

“…The article reveals principle difference between computer games and gameficated communications, which allows developers to use game content. …”
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The efficacy of practical skills mastering by students pharmacists during compounding practical training by L. O. Puchkan

“…This experiment confirmed that students have average 93±2 per cent in computer tests and practical skills during practical studies.…”
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Handwritten Text Recognition in Medieval Germanic Manuscripts: The Peterborough Chronicle as a Case Study by Elisabetta Magnanti

“… Over the past few decades, the mass digitisation of repositories has called for urgent development of computational methods to yield access to their contents. …”
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Artificial Intelligence Powered Automated and Early Diagnosis of Acute Lymphoblastic Leukemia Cancer in Histopathological Images: A Robust SqueezeNet-Enhanced Machine Learning Fram... by Vineet Mehan

“…Combining DL and ML algorithms addresses the complexity of understanding histopathological images and the classification process. Evaluation metrics computed for acute lymphoblastic leukemia reveal a good classification accuracy (CA) of 99.3%. …”
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Adaptive clustering federated learning via similarity acceleration by Suxia ZHU, Binke GU, Guanglu SUN

“…In order to solve the problem of model performance degradation caused by data heterogeneity in the federated learning process, it is necessary to consider personalizing in the federated model.A new adaptively clustering federated learning (ACFL) algorithm via similarity acceleration was proposed, achieving adaptive acceleration clustering based on geometric properties of local updates and the positive feedback mechanism during clients federated training.By dividing clients into different task clusters, clients with similar data distribution in the same cluster was cooperated to improve the performance of federated model.It did not need to determine the number of clusters in advance and iteratively divide the clients, so as to avoid the problems of high computational cost and slow convergence speed in the existing clustering federation methods while ensuring the performance of models.The effectiveness of ACFL was verified by using deep convolutional neural networks on commonly used datasets.The results show that the performance of ACFL is comparable to the clustered federated learning (CFL) algorithm, it is better than the traditional iterative federated cluster algorithm (IFCA), and has faster convergence speed.…”
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The Effect of Real-time Headbox Adjustments on Data Quality by Pieter Blignaut

“…Since only a portion of the camera sensor data is communicated to the computer and processed, much higher framerates can be achieved with the same CPU and camera. …”
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Fine-tuning neural network quantum states by Riccardo Rende, Sebastian Goldt, Federico Becca, Luciano Loris Viteritti

“…We argue that the reduced cost of this paradigm has significant potential to advance the exploration of strongly correlated systems using NQS, mirroring the success of fine-tuning in machine learning and natural language processing.…”
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A New Approach for Coverage Analysis of Multihop Cooperative Networks Subject to Lognormal-Rice Fading by Muhammad Bilal Haroon, Syed Ali Hassan

“…The theoretical results are validated by performing computer simulations.…”
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A Multi-Criteria Decision-Making Approach for Teaching Quality Evaluation in University Music Programs Using Plithogenic Sets and Weighted Decision Models by Mingjiao Liu, Hongdan Wan

“…Evaluation of university music program have various criteria affecting the decision-making process. So, we used the multi-criteria decision-making methodology (MCDM) to deal with these criteria and select best program. …”
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Perspective: advancing public health education by embedding AI literacy by Jose A. Acosta

“…The rapid emergence of large language models and other AI-driven technologies such as computer vision, predictive analytics, and natural language processing tools—used in applications ranging from epidemiological modeling and policy analysis to real-time health communication—highlights the urgent need to bridge a persistent knowledge gap in structured, competency-based AI training for public health students and professionals. …”
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Research on the Integrated Operation Platform for Autonomous-rail Rapid Transit by WU Junliang, PENG Qin, ZOU Bin, ZHANG Hongbin

“…The system uses FEP as middle layer, which works as the interface between subsystem functions of different services and background process. The realization of this system greatly reduces the workload and labor intensity of operation manager, and reduces labor cost.…”
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How Do Innovation Network Structures Affect Knowledge Sharing? A Simulation Analysis of Complex Networks by Lupeng Zhang, Wenbo Chen

“…In this regard, knowledge sharing in the process of cooperative innovation provides an important way to acquire knowledge. …”
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Resource allocation strategy based on optimal matching auction in the enterprise network by Xin CONG, Lingling ZI, Xueli SHEN

“…To address the issue that the owners of computer are selfish in the enterprise networks,which caused the low available number of resource nodes and low efficiency of resource allocation,an optimized matching resource allocation strategy OMRA was proposed and its core was the auction mechanism.Selfishness was restrained and the number of available resources was increased by OMRA,so as the operating efficiency of the whole auction market was improved.First,the initial prices were determined by normalizing the costs of different type of resources on the beginning of auction.Secondly,an optimal matching auction algorithm was designed to maximize the interests of the auction markets.Then,service perfecting algorithm was performed such that the sellers could get more services at the current transaction value,thus ensuring the benefits of resource providers.At last,a request price updating algorithm was adopted to assurance that both sellers and buyers could get priorities in the next auction processing.Compared with the cloud resource allocating algorithm via fitness-enabled auction (CRAA/FA),the experiment results indicate that the efficiency of resource allocation improves by 10% and the benefits of market increase by 11.4%.…”
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R-learning-based team game model for Internet of things quality-of-service control scheme by Sungwook Kim

“…Using the emerging and largely unexplored concept of the R-learning algorithm and docitive paradigm, system agents can teach other agents how to adjust their power levels while reducing computation complexity and speeding up the learning process. …”
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