A Multi-Feature Fusion Approach for Road Surface Recognition Leveraging Millimeter-Wave Radar by Zhimin Qiu, Jinju Shao, Dong Guo, Xuehao Yin, Zhipeng Zhai, Zhibing Duan, Yi Xu

“…The statistical features and wavelet transform features are fused at the feature level, culminating in the formation of a 56-dimensional feature vector. Four machine learning models, namely the Wide Neural Network (WNN), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Kernel methods, are employed as classifiers for both training and testing purposes. …”
Get full text

Prediction of contact resistance of electrical contact wear using different machine learning algorithms by Zhen-bing Cai, Chun-lin Li, Lei You, Xu-dong Chen, Li-ping He, Zhong-qing Cao, Zhi-nan Zhang

“…Abstract H62 brass material is one of the important materials in the process of electrical energy transmission and signal transmission, and has excellent performance in all aspects. …”
Get full text

On ensuring joint tightness on the basis of technological induction by G. A. Pilyushina, P. G. Pyrikov, E. A. Pamfilov, V. V. Kapustin

“…In the former case, the magnetic induction vector was first oriented perpendicular to the longitudinal axis of the joint. …”
Get full text

Creation of the development strategy in enterprise based on dynamic SPACE-analysis by Valeriy Balan, Inna Tymchenko

“…The study offers an integrated approach to the definition of policy recommendations for each strategic unit based on an analysis of superposition defined basic trajectories. S-trajectory or S-vectors can be represented as the sum of two vectors (vectors base paths): numbers and appropriate call intensity factors relevant basic trajectories since their values determine the degree of contribution of each of these basic paths in the integrated S-vector is a vector strategic set of strategic business units to achieve strategic objectives, transfered into numerical form by partial criteria by expert predictive testing. …”
Get full text

A novel dataset and deep learning object detection benchmark for grapevine pest surveillance by Giorgio Checola, Paolo Sonego, Roberto Zorer, Valerio Mazzoni, Franca Ghidoni, Alberto Gelmetti, Pietro Franceschi

“…Another potential FD vector is the mosaic leafhopper, Orientus ishidae, commonly found in agroecosystems. …”
Get full text

Pengukuran Kemiripan Makna Menggunakan Cosine Similarity dan Basis Data Sinonim Kata by Ardi Sanjaya, Ahmad Bagus Setiawan, Umi Mahdiyah, Intan Nur Farida, Aprisa Risky Prasetyo

“…This is because the use of ID based on word groups and slices during the weighting process can increase the similarity value. The average similarity value in the use of ID as a calculating vector is 94.48% and the average similarity value in the comparison method or plot is 69.96%. …”
Get full text

Data driven models for predicting pH of CO2 in aqueous solutions: Implications for CO2 sequestration by Mohammad Rasool Dehghani, Moein Kafi, Hamed Nikravesh, Maryam Aghel, Erfan Mohammadian, Yousef Kazemzadeh, Reza Azin

“…To fill this research gap, this study developed 15 models comprising five machine learning methods: regression trees, support vector regression, Gaussian process regression, bagged trees, and boosted trees, and three optimization algorithms: random search, grid search, and Bayesian optimization. …”
Get full text

Two-dimensional QSAR-driven virtual screening for potential therapeutics against Trypanosoma cruzi by Naseer Maliyakkal, Sunil Kumar, Ratul Bhowmik, Harish Chandra Vishwakarma, Prabha Yadav, Bijo Mathew

“…In our study, we developed a standardized and robust machine learning-driven QSAR (ML-QSAR) model using a dataset of 1,183 Trypanosoma cruzi inhibitors curated from the ChEMBL database to speed up the drug discovery process. Following the calculation of molecular descriptors and feature selection approaches, Support Vector Machine (SVM), Artificial Neural Network (ANN), and Random Forest (RF) models were developed and optimized to elucidate and predict the inhibition mechanism of novel inhibitors. …”
Get full text

A Mobile Image-Driven PM2.5 Estimation Framework Using Deep Learning Techniques by Anupam Kamble, Somrawee Aramkul, Paskorn Champrasert

“…The EfficientNet-B1 neural network is applied in the image feature vector extraction process. EfficientNet-B1, with a resolution of <inline-formula> <tex-math notation="LaTeX">$240\times 240$ </tex-math></inline-formula> pixels, was determined to be the optimal variant of EfficientNet for a small dataset of images needed for the estimation of the PM2.5 concentration value. …”
Get full text

Resilience evaluation of memristor based PUF against machine learning attacks by Hebatallah M. Ibrahim, Heorhii Skovorodnikov, Hoda Alkhzaimi

“…Abstract Physical unclonable functions (PUFs) have emerged as a favorable hardware security primitive, they exploit the process variations to provide unique signatures or secret keys amidst other critical cryptographic applications. …”
Get full text

Predicting Surface Roughness and Grinding Forces in UNS S34700 Steel Grinding: A Machine Learning and Genetic Algorithm Approach to Coolant Effects by Mohsen Dehghanpour Abyaneh, Parviz Narimani, Mohammad Sadegh Javadi, Marzieh Golabchi, Samareh Attarsharghi, Mohammadjafar Hadad

“…This research study adds value by applying algorithms and various machine learning techniques—such as support vector regression, Gaussian process regression, and artificial neural networks—on a dataset related to the grinding process of UNS S34700 steel. …”
Get full text

A comparative study of machine learning in predicting the mechanical properties of the deposited AA6061 alloys via additive friction stir deposition by Qian Qiao, Quan Liu, Jiong Pu, Haixia Shi, Wenxiao Li, Zhixiong Zhu, Dawei Guo, Hongchang Qian, Dawei Zhang, Xiaogang Li, C. T. Kwok, L. M. Tam

“…Abstract Additive friction stir deposition (AFSD) provides strong flexibility and better performance in component design, which is controlled by the process parameters. It is an essential and difficult task to tune those parameters. …”
Get full text

Evaluating microstructural and machine learning predictive models for friction drilling of sustainable snail shell reinforced aluminium matrix composites by Rajesh Jesudoss Hynes Navasingh, R. Sankaranarayanan, Priyanka Mishra, Angela Jennifa Sujana J, Jebasingh Jeremiah Rajesh, Jana Petru

“…Random Forest (RF), Multilayer Perceptron (MLP), Gaussian Process Regression (GPR) and Support Vector Machine (SVM) models were employed for the prediction of distinct output responses.…”
Get full text

Self-synchronization Voltage Source LVRT Control Method for New Energy Inverter under Weak Grid by Dan LIU, Kezheng JIANG, Yiqun KANG, Xiaotong JI, Yunyu XU, Fang LIU

“…For this reason, the relationship between the grid voltage vector and the grid impedance and the grid-connected current in the case of voltage sag under the weak grid, as well as the influencing factors are derived in this paper. …”
Get full text

Semi-active radar systems for critical facilities monitoring and protection by A. V. Barkhatov, V. I. Veremjev, A. A. Golovkov, V. M. Kutuzov, V. N. Malyshev, O. G. Petkau, N. S. Stenjukov, M. S. Shmyrin

“…Ulyanov (Lenin) and JSC «SRI "Vector"» in this direction are given. The advantages of semi-active radar systems, the possibility of coherent processing with a large accumulation time in com.bination with the digital formation of the directional diagrams of the receiving antenna arrays, as well as prospects of application systems semi-active radar for the protection of important sites and monitoring areas, including the detection and orbital support of ground, surface and aerial objects. …”
Get full text

FORMATION OF GDP IN REGIONS: CASE OF GEORGIA by Natia Kurdgelia

“…Regional development is the main vector of the state's regional economic policy. Policies aimed at stimulating economic activity in a specific region of the country are always important. …”
Get full text

Calculation and Dressing Simulation of the Profile of the Form Grinding Wheel for Modified ZI Worms by Jianxin Su, Jiewei Xu

“…Subsequently, the normal vector of the tooth surface is derived. After that, space meshing theory and matrix transformation methods are applied. …”
Get full text

A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification by Guizhou Wang, Jianbo Liu, Guojin He

“…First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine). Second, the panchromatic image is subdivided by watershed segmentation. …”
Get full text

The mechanism of gene targeting in human somatic cells. by Yinan Kan, Brian Ruis, Sherry Lin, Eric A Hendrickson

“…Moreover, and in contrast to other systems, the positions of Holliday Junction resolution are evenly distributed along the homology arms of the targeting vector. Most unexpectedly, we demonstrate that when a meganuclease is used to introduce a chromosomal DSB to augment gene targeting, the mechanism of gene targeting is inverted to an ends-in process. …”
Get full text

Using Tractography to Distinguish SWEDD from Parkinson’s Disease Patients Based on Connectivity by Mansu Kim, Hyunjin Park

“…Diffusion magnetic resonance images of SWEDD (n=37) and PD (n=40) were obtained from a research database. Tractography, the process of obtaining neural fiber information, was performed using custom software. …”
Get full text