<i>Apis mellifera</i> Bee Verification with IoT and Graph Neural Network by Apolinar Velarde Martínez, Gilberto González Rodríguez, Juan Carlos Estrada Cabral

“…Two object-recognition techniques, namely the k-Nearest Neighbor Algorithm (kNN) and Graph Neural Network (GNN), were evaluated with an image dataset of 600 images from a single beehive. …”
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Cooperative trajectory optimization for multiple connected vehicles at an unsignalized intersection by Hao Yang, Xianyang Li, Duoyang Qiu, Xiaomeng Zhu

“…Through numerical simulation analysis of intersection scenarios including crossroad and roundabout, the results demonstrate that the proposed algorithm can achieve optimal trajectories for multi-vehicle cooperative motion while ensuring safe vehicle operation, which improves the efficiency of future intelligent traffic networks.…”
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Error-Constrained Fixed-Time Synchronized Trajectory Tracking Control for Unmanned Airships with Disturbances by Jie Chen, Jiace Yuan, Ruohan Li

“…First, to guarantee strict adherence to prescribed performance bounds, an error transformation function (ETF) is integrated into the control algorithm, which can ensure all tracking errors remain within specified constraints throughout the convergence process. …”
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Optimizing alternate replacement strategy of k-out-of-n: F systems with common-mode degradation: An application to railway grid. by Liying Wang, Mingjie Ding, Boshi Liu, Qingan Qiu

“…The degradation of each steel rail is modeled using a Gamma process, while the dependence structure of the system is characterized through a copula function. …”
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Cooperative Optimization Analysis of Variable-Speed and Fixed-Speed Pumped-Storage Units Under Large Disturbances in the Power System by Weidong Chen, Jianyuan Xu

“…From a multi-time-scale perspective, we first investigate the fast power support control strategy of variable-speed pumped-storage (VSPS) units during new energy cluster off-grid scenarios. Using a consensus algorithm, the VSPS acts as the primary unit, while the constant-speed unit provides long-term power support. …”
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Constructing Fair Destination-Oriented Directed Acyclic Graphs for Multipath Routing by Katarzyna Kalinowska-Górska, Fernando Solano Donado

“…Some of these techniques make use of the so-called Destination-Oriented Directed Acyclic Graphs (DODAGs) which are constructed on the networks, usually in a distributed way. However, while defining methods of forming DODAGs, the authors of multipath algorithms tend to overlook a possibly significant issue which could, in a way, define the quality of a given DODAG in the context of multipath routing, namely, providing an equitable distribution of the paths between the nodes in the newly created DODAG. …”
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Modification of Multilayer Perceptron Using Detection Rate Model for Prediction of Nominal Exchange Rate by Al-Khowarizmi Al-Khowarizmi, Romi Fadillah Rahmat, Michael J Watts, Akrim Akrim, Arif Ridho Lubis, Muhammad Basri

“…The results obtained with absolute error achieve an accuracy of 99.73% while the accuracy based on the detection rate achieves an accuracy of 99.49%. this can be seen in the case of the prediction of (Indonesian Rupiah) IDR exchange rate against United State Dollar (USD) with the MLP algorithm by testing using MAPE to achieve sensitivity with absolute error. …”
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Self-Adaptive MOEA Feature Selection for Classification of Bankruptcy Prediction Data by A. Gaspar-Cunha, G. Recio, L. Costa, C. Estébanez

“…The proposed methodology makes use of self-adaptation by applying the feature selection algorithm while simultaneously optimising the parameters of the classifier used. …”
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A Novel Flexible Model for the Extraction of Features from Brain Signals in the Time-Frequency Domain by R. Heideklang, G. Ivanova

“…Electrophysiological signals such as the EEG, MEG, or LFPs have been extensively studied over the last decades, and elaborate signal processing algorithms have been developed for their analysis. Many of these methods are based on time-frequency decomposition to account for the signals’ spectral properties while maintaining their temporal dynamics. …”
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A Coverage Hole Healing Strategy with Awareness of Data Delivery Time in Wireless Sensor Networks by Fu-Tian Lin, Tien-Wen Sung, Chu-Sing Yang

“…In this work, the proposed hole healing strategy aims to shorten the delivery hop count by a dynamic hole healing process in order to improve the data delivery time while maintaining the coverage ratio and topology connectivity. …”
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Illustration image style transfer method design based on improved cyclic consistent adversarial network. by Xiaojun Wang, Jing Jiang

“…Through a series of quantitative and qualitative experiments, high-quality style transfer is achieved, especially while retaining the original features of the illustration. …”
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A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks. by Inés P Mariño, Alexey Zaikin, Joaquín Míguez

“…The schemes we assess are the particle Metropolis-Hastings (PMH) algorithm, the nonlinear population Monte Carlo (NPMC) method and the approximate Bayesian computation sequential Monte Carlo (ABC-SMC) scheme. …”
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RIM-Net: A Real-Imaginary-Magnitude Network for NLOS/LOS Identification in UWB Indoor Positioning Systems by Jiacheng Ni, Fang Li, Shuai Cao, Linsong Li

“…Furthermore, the optimization of the TOA algorithm validated the effectiveness of RIM-Net in localization, achieving an average performance improvement of 9.66%. …”
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Constructing a Computer Model of the Human Eye Based on Tissue Slice Images by Peishan Dai, Boliang Wang, Chunbo Bao, Ying Ju

“…Slice images were obtained from an in vitro Chinese human eye through an embryo specimen processing methods. A level set algorithm was used to extract contour points of eye tissues while a principle component analysis was used to detect the central axis of the image. …”
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DSGD++: Reducing Uncertainty and Training Time in the DSGD Classifier through a Mass Assignment Function Initialization Technique by Aik Tarkhanyan, Ashot Harutyunyan

“…We present a method for the Dempster-Shafer Gradient Descent (DSGD) algorithm that significantly reduces training time&amp;mdash;by a factor of 1.6&amp;mdash;and also reduces the uncertainty of each rule (a condition on features leading to a class label) by a factor of 2.1, while preserving accuracy comparable to other statistical classification techniques. …”
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Performance of the ALICE Zero Degree Calorimeters in LHC Run 3 by Zugravel Stefan Cristi

“…In order to fully exploit the potential offered by the LHC increased luminosity in Run 3, while preserving the time and charge resolution performance, the ZDC readout system was upgraded to allow the acquisition of all collisions in self-triggered mode without dead time. …”
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Fluid Dynamics of Biomimetic Pectoral Fin Propulsion Using Immersed Boundary Method by Ningyu Li, Yumin Su

“…The prescribed fin kinematics in each period consists of the power stroke and the recovery stroke, and the simulations indicate that the former is mainly used to provide the thrust while the latter is mainly used to provide the lift. …”
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A New Strategy to Modify Hopfield by Using XOR Operation by Rusul Hussein Hasan

“…In additional it learns to recognize an infinite number of patterns with varying sizes while preserving a suitable noise ratio.     …”
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Neuro-cognitive multilevel causal modeling: A framework that bridges the explanatory gap between neuronal activity and cognition. by Moritz Grosse-Wentrup, Akshey Kumar, Anja Meunier, Manuel Zimmer

“…Multilevel causal modeling allows us to interchangeably reason about the neuronal- and cognitive causes of behavior while maintaining a physicalist (in contrast to a strong dualist) position. …”
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Adaptive Learning Based Scheduling in Multichannel Protocol for Energy-Efficient Data-Gathering Wireless Sensor Networks by Kieu-Ha Phung, Bart Lemmens, Mihail Mihaylov, Lan Tran, Kris Steenhaut

“…In this paper, we propose a contention-free multichannel protocol to maximize network throughput while ensuring energy-efficient operation. Arguing that routing decisions influence to a large extent the network throughput, we formulate route selection and transmission scheduling as a joint problem and propose a Reinforcement Learning based scheduling algorithm to solve it in a distributed manner. …”
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