Path–Based Continuous Spatial Keyword Queries by Fangshu Chen, Pengfei Zhang, Chengcheng Yu, Huaizhong Lin, Shan Tang, Xiaoming Hu

“…Extensive experiments on both real and synthetic data sets are conducted to evaluate the performance of our proposed algorithms, and the results show that our algorithms outperform competitors by several orders of magnitude.…”
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Comparative Analysis of Hybrid Model Performance Using Stacking and Blending Techniques for Student Drop Out Prediction In MOOC by Muhammad Ricky Perdana Putra, Ema Utami

“…These algorithms are used to build models with stacking and mixing techniques. …”
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Adaptive IP geolocation framework for target network scenarios by Shuodi ZU, Shichang DING, Fuxiang YUAN, Xiangyang LUO

“…The target location can be determined through IP geolocation, serving as a vital foundation for location-based services.Researchers have proposed various IP geolocation algorithms with different implementation principles to cater to different network scenarios.However, maintaining an ideal geolocation effect proves challenging for these algorithms in diverse network scenarios.Three typical implementation principles for IP geolocation based on network measurement were introduced.The advantages and disadvantages of these methods in various network scenarios were analyzed, and an adaptive IP geolocation framework specifically tailored to target network scenarios was proposed.The geolocation framework was functioned as follows: initially, a preliminary city-level location estimation was obtained by comparing the target’s location with the landmark database.Then, detection sources were deployed in a distributed manner, and information such as delay, topology and same subnet landmarks for the target city was gathered to determine the network scenario.Finally, an appropriate geolocation method was employed to accurately estimate the target’s location according to the identified network scenario.Through simulation geolocation experiments in 11 cities of China, the multi-level performance of various IP geolocation methods supported by landmark data of different quantities and distributions was evaluated.The results indicate that the proposed framework achieves a city-level geolocation success rate of 96.16% and a median error of 4.13 km for street-level geolocation.Moreover, the framework demonstrates stable geolocation performance across different conditions, including varying same subnet landmark numbers and target accessibility.These experimental findings validate the effectiveness of the proposed framework and offer novel insights for IP geolocation research.…”
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A review on control systems hardware and software for robots of various scale and purpose. Part 2. Service robotics by Aleksey M. Romanov

“…The following conclusions are made on the basis of the review results: the key technology in service robotics from the point of view of scalability is the Robot Operating System (ROS); service robotics is today the main springboard for testing intelligent algorithms for the tactical and strategic control levels that are integrated into a common system based on ROS; the problem of ensuring fault tolerance in the service robotics is practically neglected, with the exception of the issue of increasing reliability by changing behavioral algorithms; in a number of areas of service robotics, in which the reduction of mass and dimensions is especially important, the robot control systems are implemented on a single computing device, in other cases a multi-level architecture implemented on Linux-based embedded computers with ROS are used.…”
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Intelligent Modeling; Single (Multi-layer perceptron) and Hybrid (Neuro-Fuzzy Network) Method in Forest Degradation (Case Study: Sari County) by somayeh mehrabadi

“…The mean squared error (MSE) was used to evaluate the performance of models, which was 0.0535, 0.0704, and 0.0908 for the perceptron neural network in the Levenberg-Marquardt, Bayesian regularization, and scaled conjugate gradient algorithms, respectively. Also, the MSE value for the neuro-fuzzy model in the optimization and hybrid algorithms was 0.0190 and 0.0102, respectively. …”
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AN APPROACH TO CELL NUCLEI COUNTING IN HISTOLOGICAL IMAGE ANALYSIS by M. M. Lukashevich, V. V. Starovoitov

“…Critical parameters defined algorithms, configurable at each stage of image analysis. …”
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The potential of artificial intelligence (AI) to improve electronic word-of-mouth's (eWOM) efficacy by Baltezarević Radoslav V., Kwiatek Piotr B.

“…Nowadays, computer algorithms can automatically classify the sentiment polarity of digital communication after extracting plain text. …”
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Research of Simulation in Character Animation Based on Physics Engine by Yang Yu, Jucheng Yang, Xiaofei Zan, Jiangang Huang, Xiangbo Zhang

“…It is based on computer hardware and graphics algorithms and related sciences rapidly developed new technologies. …”
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Numerical Simulations on the Front Motion of Water Permeation into Anisotropic Porous Media by Xiangxiang Zhang, J. G. Wang, Xiaolin Wang, Feng Gao

“…The water permeation front moves with time and may significantly impact the field variable evolution near the water front. Many algorithms have been developed to calculate this water front motion, but few numerical algorithms have been available to calculate the water front motion in anisotropic fluid-solid couplings with high computational efficiency. …”
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Quality assessment of chicken using machine learning and electronic nose by Hassan Anwar, Talha Anwar

“…To evaluate the performance of the machine learning algorithms, different data splitting approaches were tested to understand their impact on model accuracy. …”
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Resource Scheduling Method for Integration of TT＆C and Observation Based on Multi-Agent Deep Reinforcement Learning by Siyue CHENG, Haoran LI, Weigang BAI, Di ZHOU, Yan ZHU

“…With the development of satellite communication technology and the continuous expansion of the constellation scale, the integration of TT＆amp;C and observation technology has become the mainstream trend.The large constellation scale, many scheduling objects and complex operation joint control bring great challenges to the integrated resource scheduling of satellite network TT＆amp;C and observation.Subject to the low solution effi ciency and complex constraints of scheduling algorithms, the traditional TT＆amp;C resource scheduling technology adopts the advance injection TT＆amp;C instructions to perform tasks according to the fi xed deployment, which is diffi cult to meet the scheduling needs of emergencies and emergency tasks.Therefore, a kind of resource scheduling method based on multi-agent actor-Agent Actor-Critic Deterministic Policy Gradient Algorithms (MADDPG) was presented.With centralized training and distributed execution, the multi-agent model of integrated task of TT＆amp;C and observation was established.By analyzed the scheduling strategy of neighbor agent, the response speed of local information was improved.According to the model and constraints in the integrated resource scheduling problem of TT＆amp;C and observation, selected signifi cant and interpretable constraints, then established the multi-agent resource scheduling reinforcement learning model, and carried on the simulation test.The simulation results showed that the task benefi t of this method was 22% higher than the traditional method.…”
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Identification of diabetic retinopathy lesions in fundus images by integrating CNN and vision mamba models. by Zenglei Liu, Ailian Gao, Hui Sheng, Xueling Wang

“…An evaluation of the suggested method was carried out by comparison experiments between state-of-the-art algorithms and the proposed methodology. Empirical findings demonstrate that the suggested methodology surpasses the most advanced algorithms on the datasets that are accessible openly. …”
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Meta's Challenge with Olives and Watermelon: The Case of Blocking Posts About Gaza by Nuran Kızmaz Öztürk

“…As a result, we will present examples of the efforts of social media users who are algorithmically censored, which we call symbolic subversion, to overcome this situation with symbols.…”
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A feature-based approach for atlas selection in automatic pelvic segmentation. by Guoping Shan, Xue Bai, Yun Ge, Binbing Wang

“…It highlighted the potential of feature-based subgrouping techniques in enhancing the efficacy of MAS algorithms in the field of medical image segmentation.…”
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Quantitative Analysis of the Main Controlling Factors of Oil Saturation Variation by Ruijie Huang, Chenji Wei, Jian Yang, Xin Xu, Baozhu Li, Suwei Wu, Lihui Xiong

“…This article presents a workflow analysing the main controlling factors of oil saturation variation utilizing machine learning algorithms based on static and dynamic data from actual reservoirs. …”
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External barycentric coordinates for arbitrary polygons and an approximate method for calculating them by Ivan S. Polyansky

“…The author of the article hopes that the detailed results of the algorithmic implementation of the calculation of external barycentric coordinates will arouse interest and make the publication material more accessible to a wide range of readers, which will lead to the development of the barycentric method in solving boundary and initial boundary value problems of mathematical physics.…”
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Emerging Technologies Driving Zero Trust Maturity Across Industries by Hrishikesh Joshi

“…Furthermore, the integration of AI and machine learning in Zero Trust frameworks raises questions about data privacy, algorithmic bias, and the need for explainable security decisions. …”
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Creation and interpretation of machine learning models for aqueous solubility prediction by Minyi Su, Enric Herrero

“…Conclusions: Overall, for certain applications simple ML algorithms such as RF work well and can outperform more complex methods and that combining them with fragment-coloring can offer guidance for chemists to modify the structure with a desired property. …”
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Shear Strength of Internal Reinforced Concrete Beam-Column Joints: Intelligent Modeling Approach and Sensitivity Analysis by De-Cheng Feng, Bo Fu

“…The proposed approach is established based on the famous boosting-family ensemble machine learning (ML) algorithms, i.e., gradient boosting regression tree (GBRT), which generates a strong predictive model by integrating several weak predictors, which are obtained by the well-known individual ML algorithms, e.g., DT, ANN, and SVM. …”
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Properties of solutions of optimization problems for set functions by Slawomir Dorosiewicz

“…It makes possible the applications of various algorithms for these optimization problems for finding conditional extrema of set functions.…”
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