Design of federated routing mechanism in cross-domain scenario by Peizhuang CONG, Yuchao ZHANG, Ye TIAN, Wendong WANG, Dan LI

“…With the development of multi-network integration,how to ensure efficient interconnections among multiple independent network domains is becoming a key problem.Traditional interdomain routing protocol fails due to the limitation of domain information privacy,where each autonomous domain doesn’t share any specific intra-domain information.A machine learning-based federated routing mechanism was proposed to overcome the existing shortcomings.Each autonomous domain shares intra-domain information implicitly via neural network models and parameters.It not only breaks data islands problems but also greatly reduces the amount of transmitted data shared between domains,then decreases convergence delay of entire network information.Based on the federated routing mechanism,border routers can formulate global optimal routing strategies according to the status of entire network.…”
Get full text

The Impact of Failure Types in Construction Production Systems on Economic Risk Assessments in the Bidding Phase by Milan Mirkovic

“…Also, the failure rate and repair rate of the 34 machines from the machine park of the company for road construction were researched. …”
Get full text

Spoofing speech detection algorithm based on joint feature and random forest by Jiaqi YU, Zhihua JIAN, Jia XU, Lin YOU, Yunlu WANG, Chao WU

“…In order to describe the characteristic information of the speech signal more comprehensively and improve the detection rate of camouflage, a spoofing speech detection method based on the combination of uniform local binary pattern texture feature and constant Q cepstrum coefficient acoustic feature was proposed, which used random forest as the classifier model.The texture feature vector in the speech signal spectrogram was extracted by using the uniform local binary mode, and the joint feature was formed with the constant Q cepstrum coefficient.Then, the obtained joint feature vector was used to train the random forest classifier, so as to realize the camouflage speech detection.In the experiment, the performances of several spoofing detection systems constructed by other feature parameters and the support vector machine classifier model were compared, and the results show that the proposed speech spoofing detection system combined with the joint feature and the random forest model has the best performance.…”
Get full text

Spoofing speech detection algorithm based on joint feature and random forest by Jiaqi YU, Zhihua JIAN, Jia XU, Lin YOU, Yunlu WANG, Chao WU

“…In order to describe the characteristic information of the speech signal more comprehensively and improve the detection rate of camouflage, a spoofing speech detection method based on the combination of uniform local binary pattern texture feature and constant Q cepstrum coefficient acoustic feature was proposed, which used random forest as the classifier model.The texture feature vector in the speech signal spectrogram was extracted by using the uniform local binary mode, and the joint feature was formed with the constant Q cepstrum coefficient.Then, the obtained joint feature vector was used to train the random forest classifier, so as to realize the camouflage speech detection.In the experiment, the performances of several spoofing detection systems constructed by other feature parameters and the support vector machine classifier model were compared, and the results show that the proposed speech spoofing detection system combined with the joint feature and the random forest model has the best performance.…”
Get full text

EF yolov8s: A Human–Computer Collaborative Sugarcane Disease Detection Model in Complex Environment by Jihong Sun, Zhaowen Li, Fusheng Li, Yingming Shen, Ye Qian, Tong Li

“…This paper proposes a human–machine collaborative sugarcane disease detection method in complex environments. …”
Get full text

Computational simulation and mathematical modelling of thermal performance and energy enhancement of integrated infrared with hot air heated system by Hany S. El-Mesery, Ahmed H. ElMesiry, Oluwasola Abayomi Adelusi, Zicheng Hu, Sara Elhadad

“…Furthermore, 11 different machine learning models were applied to predict the relationships between the input parameters (infrared power, airflow rate, and air temperature) and response variables, including total energy utilization, specific energy consumption, and thermal and drying efficiency. …”
Get full text

Small- to Large-Scale Electron Beam Powder Bed Fusion of Functionally Graded Steels by Carlos Botero, William Sjöström, Emilio Jimenez-Pique, Andrey Koptyug, Lars-Erik Rännar

“…The ability to control process parameters over time and build space in electron beam powder bed fusion (PBF-EB) opens up unprecedented opportunities to tailor the process and use materials of a different nature in the same build. …”
Get full text

Energy saving in rail transport by Jan Antoš

“…In these cases they will be substituted by various algorithms, that can be machine-processed and that are part of the simulation calculations. …”
Get full text

Research on High-Accuracy, Lightweight, Superfast Model for Nitrogen Diagnosis and Plant Growth in Lettuce (<i>Lactuca sativa</i> L.) by Xuyang Li, Iftikhar Hussain Shah, Xiaohao Gong, Muhammad Azam, Wu Jinhui, Pengli Li, Yidong Zhang, Qingliang Niu, Liying Chang

“…This study aimed to determine the relationship between plant growth, nutritional quality formation, and different nitrogen levels of lettuce. A machine learning approach was also applied to data collected from RGB and hyperspectral imaging systems. …”
Get full text

Investigating the cost of mechanized unpaved road maintenance operations in Uganda by Obeti, Andrew Moses, Byaruhanga, Chris Bic, Muhwezi, Lawrence, Kakitahi, John Muhumuza

“…The selected case study areas were accessible and reachable in terms of data. Control parameters affecting unpaved mechanized road maintenance were identified as machine repair costs, tool costs, labour costs, material costs, fuel costs and machine fuel costs. …”
Get full text

Elucidating the Effects of Material Flow from Deposition Offset on AFSD Repair of AA7050 by Victor A. Rojas, Ismael Y. Hidalgo, Khaled Matalgah, Trevor J. Fleck, Luke N. Brewer, Gregory W. Kubacki, J. Brian Jordon, Paul G. Allison

“…In this work, the effects of tool bias as a processing parameter on an additive friction stir deposition repair of AA7050-T7451 plates were investigated. …”
Get full text

RESEARCH ON DEEP NEURAL NETWORK LEARNING BASED ON IMPROVED BP ALGORITHM by HUANG Pei

“…Deep learning can make the computing model that contains a number of processing layers to learn the data that contains many levels of abstract representation.This kind of learning way in the most advanced speech recognition,visual object recognition,object detection and many other areas,such as biology,genetics and medicine brought significant improvement.Deep learning can find the complex structure of large data,and the convolution neural network as one of the important models of the depth study in the processing of voice,image,video and text,and other aspects of a new breakthrough.It is the use of BP algorithm to guide the machine how to get the error before the layer to adjust the parameters of this layer,so that these parameters are more conducive to the calculation of the model.In view of the shortcomings of traditional BP algorithm,a fast BP algorithm is proposed,which has the disadvantages of slow convergence speed and often falls into local minimum points.The improved convolutional neural network is used to validate the data set MNIST,English character recognition and medical image.The simulation results show the effectiveness of the proposed algorithm.…”
Get full text

Application Assessment of OS-SART Reconstruction Algorithm with Limited Number of Projections in XCT Geometric Measurement by Kaojie Yue, Huan Shao, Stefano Petrὸ, Giovanni Moroni

“…A series of experiments is conducted, targeting three key algorithmic parameters. These experiments are based on a stepped cylinder part across varying Np levels, with the error between the values of XCT measurement and coordinate measurement machine as the evaluation metric. …”
Get full text

Method for Vocal Fold Paralysis Detection Based on Perceptual and Acoustic Assessment by Rafał HALAMA, Krzysztof SZKLANNY, Danijel KORŽINEK

“…Finally, a classifier is trained using machine learning algorithms from the WEKA (Waikato Environment for Knowledge Analysis) platform. …”
Get full text

Evaluation of Ecosystem Health Based on AWDO-SVR Algorithm in Shiyang River Basin by WANG Wenchuan, LI Lei, ZHENG Ye, XU Dongmei, XU Lei

“…This paper evaluates the ecological health of Shiyang River Basin by the adaptive wind-driven optimization (AWDO) algorithm and support vector regression (SVR) coupled algorithm for problems in health assessment of watershed ecosystem,finds the optimal parameters of support vector machine (SVM) by AWDO algorithm for uncertainty of parameters from SVM,proposes an evaluation model based on AWDO-SVR algorithm,and evaluates nine indexes such as water resource endowment,water resource development and utilization,and social and economic function of Shiyang River Basin by the model with advantages of fast and simple operation and no need of weight.The results show that the ecological health is sub-health for the upper reaches of Shiyang River,and morbid for the middle and lower reaches respectively.The evaluation result is the same as that of the variable set model,indicating that AWDO-SVR algorithm can be effectively applied to the ecosystem health evaluation of the river basin.…”
Get full text

The Long-Term Annual Datasets for Azov Sea Basin Ecosystems for 1925–2024 and Russian Sturgeon Occurrences in 2000–2024 by Mikhail M. Piatinskii, Dmitrii G. Bitiutskii, Arsen V. Mirzoyan, Valerii A. Luzhniak, Vladimir N. Belousov, Dmitry F. Afanasyev, Svetlana V. Zhukova, Sergey N. Kulba, Lyubov A. Zhivoglyadova, Dmitrii V. Hrenkin, Tatjana I. Podmareva, Polina M. Cherniavksaia, Dmitrii S. Burlachko, Nadejda S. Elfimova, Olga V. Kirichenko, Inna D. Kozobrod

“…Preliminary diagnostics of the annual dataset reveal no evidence of non-stationarity or significant outliers that cannot be explained by biological parameters. The published dataset allows any researcher to perform statistical and machine learning-based analysis in order to compare and describe the population abundance or spatial occurrence of Russian sturgeon in the Sea of Azov.…”
Get full text

Circadian clock disruption impairs immune oscillation in chronic endogenous hypercortisolism: a multi-level analysis from a multicentre clinical trialResearch in context by Valeria Hasenmajer, Emilia Sbardella, Francesca Sciarra, Chiara Simeoli, Claudia Pivonello, Filippo Ceccato, Riccardo Pofi, Marianna Minnetti, Flavio Rizzo, Davide Ferrari, Ilaria Bonaventura, Federica Barbagallo, Elisa Giannetta, Danilo Alunni Fegatelli, Simone Conia, Roberto Navigli, Giorgio Arnaldi, Carla Scaroni, Rosario Pivonello, Daniele Gianfrilli, Mary Anna Venneri, Andrea M. Isidori

“…Interpretation: In conclusion, the oscillation of circulating immune cells is profoundly altered in patients with CS, representing a convergence point of circadian rhythm disruption and metabolic and steroid hormone imbalances. Machine learning techniques proved the superiority of immune profiling over parameters such as cortisol, anthropometric and metabolic variables, and circadian gene expression analysis to identify CS activity. …”
Get full text

The finishing and cleaning of long parts in screw rotors by V. A. Lebedev, L. M. R. Al-Obaidi, N. S. Koval

“…Metal removal is accepted as the main parameter determining the intensity of the machining process in screw rotors. …”
Get full text

FPGA-Based Channel Coding Architectures for 5G Wireless Using High-Level Synthesis by Swapnil Mhaske, Hojin Kee, Tai Ly, Ahsan Aziz, Predrag Spasojevic

“…In spite of the mixed nature of data processing—digital signal processing and finite-state machines—LabVIEW FPGA Compiler significantly reduced time to explore the system parameter space and to optimize in terms of error performance and resource utilization. …”
Get full text

Revealing the mechanism of crystal orientation-dependent surface morphology and topography evolution in single-crystal ZnO using nanoindentation by Weihai Huang, Jiwang Yan

“…This study reveals how crystal orientation governs surface evolution in ZnO, offering guidance for machining method development and processing parameter optimization.…”
Get full text