Artificial intelligence, chess and the risks of modern civilization by G. Sh. Pilavov

“…As the researchers of this issue have noted, artificial intelligence can be used as a tool to establish an autocratic regime (Wang Jianguang), or become a means for radical socio-political processes (G. I. Kolesnikova). In conclusion, proposals are put forward on the most effective methods of combating the possible use of artificial intelligence to radically change the vector of development of our civilization. …”
Get full text

Crowd Evacuation in Stadiums Using Fire Alarm Prediction by Afnan A. Alazbah, Osama Rabie, Abdullah Al-Barakati

“…To detect early fire risk indicators, the system processes data from 62,630 sensor measurements across 15 ecological parameters, including temperature, humidity, total volatile organic compounds (TVOC), CO₂ levels, and particulate matter. …”
Get full text

Infrared Small Target Detection Using Directional Derivative Correlation Filtering and a Relative Intensity Contrast Measure by Feng Xie, Dongsheng Yang, Yao Yang, Tao Wang, Kai Zhang

“…The final detection step involves fusing the DDCF and LRICM maps to generate a comprehensive saliency representation, which is then processed using an adaptive thresholding technique to extract small targets accurately. …”
Get full text

Multi-Modal Feature Set-Based Detection of Freezing of Gait in Parkinson’s Disease Patients Using SVM by Ghulam Murtaza, Mohammed Hammoud, Andrey Somov

“…First, the data were pre-processed and segmented into 3-second windows with 90% overlap. …”
Get full text

Benchmarking the Mapping of Address and Port With Encapsulation Border Relay Routers by Ahmed Al-Hamadani, Gabor Lencse

“…The research work presented in this paper involves conducting comprehensive benchmarking for the MAP-E BR implementation of the FD.io Vector Packet Processing (VPP), a well-known high-performance open-source networking software, and analyzing its performance and scalability, using two different test systems. …”
Get full text

The Level of IgG to Coronavirus Infection among the Medical Institution Employees by M. A. Yunusova, E. S. Lutsenko, N. N. Tsapkova, A. Yu. Brazhnikov, T. S. Saltykova, V. S. Yudina

“…Antibodies were examined by ELISA; immunological method for determining IgG (test system – "Vector Best", semi-quantitative analysis). Statistical processing of the study results was carried out using the SPSS-22 statistical software package and the OpenEpiver statistical calculator. 3.Results and discussion. …”
Get full text

Application and optimization of BP prediction model driven by internet of things in tourism education by Qi Lv

“…Regarding prediction time, the optimized model processes 1,000 data entries in just 0.05 s, which is considerably faster than SVM (0.12 s) and RF (0.08 s). …”
Get full text

ATTRIBUTION OF MEDIA TEXTS BASED ON A TRAINED NATURAL LANGUAGE MODEL AND LINGUISTIC ASSESSMENT OF IDENTIFICATION QUALITY by Vladimir A. Klyachin, Ekaterina V. Khizhnyakova

Get full text

Cloning and expression analysis of maize fucosyltransferase gene SPINDLY by LI Bowen, WANG Zhiqin, ZHU Xiaona, ZHU Zhenyu, GAO Xiaoxiao*

“…Previous studies have indicated that the SPY protein regulates plant growth and development by modulating various intracellular processes in Arabidopsis thaliana. Its mediated O-fucosylation plays an important role in maintaining cell homeostasis and regulating plant growth and development, however protein O-fucosylation regulated by SPY in other plants largely remain unknown. …”
Get full text

Using Supervised Machine Learning Algorithms to Predict Bovine Leukemia Virus Seropositivity in Florida Beef Cattle: A 10‐Year Retrospective Study by Ameer A. Megahed, Y. Reddy Bommineni, Michael Short, João H. J. Bittar

“…Methods Logistic regression (LR), decision tree (DT), gradient boosting (GB), random forest (RF), neural network (NN), and support vector machine (SVM) were used. Results Of the submitted samples, 11.6% were positive for BLV. …”
Get full text

Optimizing potato yield predictions in Uttar Pradesh, India: a comparative analysis of machine learning models by Ahmad Alsaber, Anurag Satpathi, Mariam Alsabah, Parul Setiya

“…The data was detrended, processed into weather indices, and split into 70% for training and 30% for testing. …”
Get full text

Linear Perturbations of the Bloch Type of Space-Periodic Magnetohydrodynamic Steady States. II. Numerical Results by Chertovskih R, Zheligovsky V

“…Thus, in a natural MHD system not affected by strong diffusion, a given scale range gives rise to perturbations involving only moderately larger spatial scales (i.e., |q| only moderately small), and the MHD evolution consists of a cascade of processes, each generating a slightly larger spatial scale; flows or magnetic fields characterized by a high scale separation are not produced. …”
Get full text

Automated Detection of Recent Mud Extrusions Using UAV Imagery and Deep Learning: A Comparative Analysis of Traditional and CNN-Based Approaches by M. Guastella, M. Guastella, A. Pisciotta, R. Martorana, A. D’Alessandro

“…Monitoring these formations provides critical insights into subsurface processes and geological hazards. This study focuses on detecting recent mud extrusions in mud volcano environments using high-resolution aerial imagery acquired by unmanned aerial vehicles (UAVs). …”
Get full text

Innovative approaches for skin disease identification in machine learning: A comprehensive study by Kuldeep Vayadande, Amol A. Bhosle, Rajendra G. Pawar, Deepali J. Joshi, Preeti A. Bailke, Om Lohade

“…Investigate the effectiveness and performance of several algorithms, such as the flexible k-nearest neighbor, the sturdy support vector machine (SVM), and the complex convolutional neural networks (CNNs), advanced techniques for automated skin disease detection encompass deep learning methods such as recurrent neural networks (RNNs) for sequential data processing, generative adversarial networks (GANs) for generating synthetic data, and attention mechanisms for focusing on relevant image regions by means of a thorough examination of the most recent studies. …”
Get full text

Automatic Detection of Laparoscopic Videos Distortion Using Machine Learning Classification by Mohamed Belmokeddem, Kamila Khemis, Salim Loudjedi

“…To classify defocus blur, motion blur, and smoke in the laparoscopic video, we adopt a novel approach utilizing a cascade support vector machine (SVM) classifier, which combines decisions from three binary classifiers. …”
Get full text

Research on digital matching methods integrating user intent and patent technology characteristics by Jianwei Yang, Yi Wang, Bonan Zang, Min Peng, George Torrens

“…Third, the BERT model and Principal Component Analysis (PCA) are applied for vector transformation and dimensionality reduction of feature texts, completing the digital characterization. …”
Get full text

Impact of agricultural industry transformation based on deep learning model evaluation and metaheuristic algorithms under dual carbon strategy by Xuan Zhao, Weiyun Tang, Qiuyan Liu, Hongtao Cao, Fei Chen

“…Compared with traditional methods—such as deep neural networks, support vector machines, and linear regression—the proposed model effectively integrates static and dynamic agricultural data. …”
Get full text

A precise machine learning model: Detecting cervical cancer using feature selection and explainable AI by Rashiduzzaman Shakil, Sadia Islam, Bonna Akter

“…Hence, in these studies, we presented a precise approach utilizing six different machine learning models (decision tree, logistic regression, naïve bayes, random forest, k nearest neighbors, support vector machine), which can predict the early stage of cervical cancer by analysing 36 risk factor attributes of 858 individuals. …”
Get full text

A Fault Diagnosis Model for Rotating Machinery Using VWC and MSFLA-SVM Based on Vibration Signal Analysis by Lei You, Wenjie Fan, Zongwen Li, Ying Liang, Miao Fang, Jin Wang

Get full text

GNNMutation: a heterogeneous graph-based framework for cancer detection by Nuriye Özlem Özcan Şimşek, Arzucan Özgür, Fikret Gürgen

“…Each patient node is represented by a feature vector derived from the mutations in specific genes. …”
Get full text