PREVENTION AND MANAGEMENT OF INSUFFICIENT AEROSTASIS IN PULMONARY SURGERY by A. S. Shapovalov, A. A. Polezhaev, S. A. Belov

“…Machine stitch is a reliable way to seal the lung resection margin providing aerostasis in 24 hours after surgery in 63.6% (95% CI 50.4-75.1%) of the patients, while 38.2% of them suffered from concurrent emphysema.In case of bleeding from machine stitching of lung resection line, it is advisable to add manual stitching with consequent latex tissue adhesive (the frequency of aerostasis (in 24 hours) increases from 40.7 to 90.9%; χ2 = 30.6; p2-4 < 0.01).In pulmonary resections, use of latex tissue adhesive for additional sealing of machine stitch with a positive hydrostatic test result allowed achieving aerostasis in 24 hours in 95.2% given the high frequency (31.7%) of concurrent pulmonary emphysema.…”
Get full text

Blind Parameter Identification of MAR Model and Mutation Hybrid GWO-SCA Optimized SVM for Fault Diagnosis of Rotating Machinery by Wenlong Fu, Jiawen Tan, Xiaoyuan Zhang, Tie Chen, Kai Wang

“…Signals collected from different types of faults were firstly split into sets of intrinsic mode functions (IMFs) by variational mode decomposition (VMD), the decomposing mode number K of which was preset with central frequency observation method. Then the multivariate autoregressive (MAR) model of all IMFs was established, whose order was determined by Schwartz Bayes Criterion (SBC), and all parameters of the model were identified blindly through QR decomposition, where key features were subsequently extracted via principal component analysis (PCA) to construct feature vectors of different fault types. …”
Get full text

Landslide Susceptibility Mapping in Darjeeling Himalayas, India by Amit Chawla, Sowmiya Chawla, Srinivas Pasupuleti, A. C. S. Rao, Kripamoy Sarkar, Rajesh Dwivedi

“…Particle Swarm Optimization-Support Vector Machine technique was used for the prediction and classification of landslide susceptibility classes, and Genetic Programming method was used to generate models and to predict landslide susceptibility classes in conjunction with Geographic Information System output, respectively. …”
Get full text

Comprehensive performance assessment of an over-the-row olive harvester by Mohamed Ghonimy, Abdulaziz Alharbi, Mohamed M. Ibrahim

“…Purpose: This study aimed to assess the performance of an Over-The-Row (OTR) olive harvester, emphasizing the need for a mechanical harvesting plan that improves efficiency, minimizes damage to both fruit and trees, and ensures sustainable production in olive orchards. Methods: The performance of the OTR harvester was evaluated under two forward speeds (2 and 3 km h−1) and two shaking frequencies (7.2 and 7.8 Hz) for the Arbosana and Arbequina olive varieties. …”
Get full text

Spectral Entropic Radiomics Feature Extraction (SERFE): an adaptive approach for glioblastoma disease classification by V. L. Sowmya, A. Bharathi Malakreddy, Santhi Natarajan, N. Prathik, I. S. Rajesh

Get full text

Biodiversity is not declining in fiction by Andrew Piper

“…This paper applies the original paper's three primary measures to two additional data sets along with the original dataset and compares their dictionary-based method with an alternative supervised machine learning method. …”
Get full text

Improving Smart Grid security: Spectral and fractal analysis as tools for detecting cyberattacks by Sergey V. Kochergin, Svetlana V. Artemova, Anatoly A. Bakaev, Evgeny S. Mityakov, Zhanna G. Vegera, Elena A. Maksimova

“…For the effective detection of cyberattacks associated with harmonic signal distortions in power systems, a comprehensive approach is required, including time series analysis, frequency analysis, and machine learning methods. This approach not only detects anomalies in signals but also provides their quantitative assessment to improve the accuracy of classifying malicious impacts. …”
Get full text

Failure Diagnosis System for a Ball-Screw by Using Vibration Signals by Won Gi Lee, Jin Woo Lee, Min Sung Hong, Sung-Ho Nam, YongHo Jeon, Moon G. Lee

“…First, the vibration-based monitoring method, which uses vibration signal to monitor the condition of a machine, is proposed. …”
Get full text

Impact of different auditory environments on task performance and EEG activity by Zhen Xue, Wenxiao Zhong, Yong Cao, Shuang Liu, Xingwei An

Get full text

Rotating Machinery Remaining Useful Life Prediction Scheme Using Deep-Learning-Based Health Indicator and a New RVM by Gang Zhang, Weige Liang, Bo She, Fuqing Tian

“…Remaining useful life (RUL) prediction plays a significant role in developing the condition-based maintenance and improving the reliability and safety of machines. This paper proposes a remaining useful life prediction scheme combining deep-learning-based health indicator and a new relevance vector machine. …”
Get full text

On the Reduction of Radiation Damping of Dynamic Foundation on Gibson Elastic Halfspace by Hao Li, Xiaohui Cheng

“…For dynamic machine foundations, it is widely acknowledged that the radiation damping ratio estimated by Lysmer’s analogy method is often overestimated, leading to the adoption of modifications in design codes across various nations. …”
Get full text

Stock Market Index Prediction Using CEEMDAN-LSTM-BPNN-Decomposition Ensemble Model by John Kamwele Mutinda, Abebe Geletu

Get full text

A New Hybrid Model for Underwater Acoustic Signal Prediction by Guohui Li, Wanni Chang, Hong Yang

“…Then, extreme learning machine (ELM) is used to predict the low-frequency subsequence obtained by VMD-DE. …”
Get full text

Improvement of the dynamic properties of a column with step-variable flexural stiffness in terms of structural mounting damping and internal damping by Jurczyńska Anna

“…The problem was formulated on the basis of the Bernoulli-Euler’s theory and then solved using the variational method (Hamilton’s principle). Determination of differential equations o motion of individual segments of the column and their solutions, taking into account the boundary conditions, made it possible to determine the transcendental equation giving the vibration frequency values. …”
Get full text

Autonomous defect estimation in aluminum plate and prognosis through stochastic process modeling by Mrudul Jambulkar, Shivam Ojha, Amit Shelke, Anowarul Habib

“…Abstract The structural integrity and longevity of aluminum alloy components in lightweight engineering require accurate and efficient damage detection and prognosis methods. Traditional supervised machine learning (ML) techniques often face limitations due to dependency on large datasets, risk of overfitting, and high computational costs. …”
Get full text

Lateral vibration estimation of an elevator rope by sequential modal decomposition of elevator rope displacement observed near the traction sheave by Daisuke TAINAKA, Nanako MIURA, Keito SUMIDA, Arata MASUDA

“…In contrast, this paper proposes the estimation method by a sensor installed near the traction sheave in the machine room. …”
Get full text

Adaptive online modeling of ship maneuvering motion based on error monitoring by Yaohui YU, Suyang LIU, Zihao WANG, Wenbo XIE, Yan PENG

“…MethodsThe method determines model update timing through a model prediction error monitoring mechanism and realizes the adaptive retraining update of the model based on voyage data by combining the sliding window technique and support vector machine. …”
Get full text

Chaotic Threshold for a Class of Power System Model by Xiaodong Wang, Zhenyong Lu, Caiqin Song

“…By applying Melnikov’s method, the threshold value for the occurrence of chaotic motion is provided. …”
Get full text

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

“…The proposed methodology for estimating impact of the availability function is a modified method of the frequency balancing. It has been tested on a concrete project from the practice in the process of harmonizing construction norms of time that preceded the final adoption of the unit prices. …”
Get full text

Identification of Microseismic Signals Based on Multiscale Singular Spectrum Entropy by Xingli Zhang, Zhenhua Zhao, Ruisheng Jia, Lianyue Cao

“…The original signal was firstly broken down into a given number K variational mode components, which are ranked by frequency in descending order. Then, the characteristic pattern matrix was constructed according to the mode component signals, and the identification model of the microseismic signals based on the support vector machine was built by performing a multiscale singular spectrum entropy calculation of the collected vibration signals, constructing eigenvectors of signals. …”
Get full text