A Support Vector Regression Approach for Three–Level Longitudinal Data by Mohammad Moqaddasi Amiri, Leili Tapak, Javad Faradmal

“…In this paper a mixed-effects least squares support vector regression model is presented for three-level longitudinal data. …”
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APPLICATION OF MATHEMATICAL REGRESSION TO THREE-PHASE ASYNCHRONOUS MOTOR PARAMETERS DETERMINATION by Vladimir Borisovich Vorzhev, Ivan Victorovich Kaliyenko

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Clinical and Radiological Characterization of an Infant with Caudal Regression Syndrome Type III by Kavinda Dayasiri, V. Thadchanamoorthy, Kaushika Thudugala, Aruni Ranaweera, N. Parthipan

“…Both genetic and environmental factors are believed to play roles in aetiopathogenesis of caudal regression. The authors report a two-month-old child born to a diabetic mother, in whom the diagnosis of caudal regression syndrome type III was confirmed based on clinical and radiological characteristics. …”
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Predicting Three-Dimensional (3D) Printing Product Quality with Machine Learning-Based Regression Methods by Ahmet Burak Tatar

Subjects: “…3d printing…”
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A Recommendation System Based on Regression Model of Three-Tier Network Architecture by Wang Bailing, Huang Junheng, Zhu Dongjie, Hou Xilu

“…Based on this framework, a Regression Model Recommendation Approach (RMRA) is established to calculate the correlation score between the test user and test item. …”
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Performance Evaluation of A Three-Modality Biometric System using Multinomial Regression by Bopatriciat Boluma Mangata, Trésor Mazambi Kilongo, Pierre Tshibanda wa Tshibanda, Remy Mutapay Tshimona, Jean Pepe Buanga Mapetu, Eugène Mbuyi Mukendi

“…We then used the multinomial regression method to obtain the various parameter values, which are: FN=0.124, VPP=0.88, Sp=0.88, VPN=0.87, Se=0.87 and F-measure = 0.87 for voice recognition, FN=0.104, VPP=0.90, Sp=0.90, VPN=0.89, Se=0.89 and F-measure = 0.89 for face recognition, FN=0.08, VPP=0. 92, Sp=0.92, VPN=0.91, Se=0.91 and F-measure = 0.91 for fingerprints and FN=0.004, VPP=0.99, Sp=0.99, VPN=0.99, Se=0.99 and F-measure = 0.99 for the global system resulting from the fusion of these three modalities. …”
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Multi-Scale 3D Cephalometric Landmark Detection Based on Direct Regression with 3D CNN Architectures by Chanho Song, Yoosoo Jeong, Hyungkyu Huh, Jee-Woong Park, Jun-Young Paeng, Jaemyung Ahn, Jaebum Son, Euisung Jung

“…This study proposes a multi-scale 3D CNN-based approach utilizing direct regression to improve the accuracy of maxillofacial landmark detection. …”
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FOXP3 in Melanoma with Regression: Between Tumoral Expression and Regulatory T Cell Upregulation by Mirela Cioplea, Luciana Nichita, Daniela Georgescu, Liana Sticlaru, Alexandra Cioroianu, Roxana Nedelcu, Gabriela Turcu, Alin Rauta, Cristian Mogodici, Sabina Zurac, Cristiana Popp

“…FOXP3 expression in tumor cells seems an independent factor of poor prognosis in melanoma, while regression areas are characterized by a high number of dendritic cells and a low number of regulatory T cells. …”
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Statistical notes for clinical researchers: simple linear regression 3 – residual analysis by Hae-Young Kim

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Weighted mixed regression localization method based on three-dimensional Voronoi diagram division by Fenfang LI, Xiaochao DANG, Zhanjun HAO

“…With the development of the wireless communication technology and sensing technology, various technologies based on wireless sensor networks are applied.These technologies are widely used in the fields of intelligent agriculture, intelligent transportation, fire rescue and so on.Node localization technology is one of the basic technologies of wireless sensor networks.Location information is a part of the sensing data, which determines the specific measures to be taken in the next step.Due to the complexity of the three-dimensional (3D) space localization environment, the application of the plane positioning method in 3D space will have some limitations.Aiming at above problems, the weighted hybrid regression location algorithm WMR-SKR based on a 3D Voronoi diagram was studied.The localization algorithm was divided into two stages: offline training and online testing.The 3D space was divided into Voronoi diagrams according to the anchor nodes in the network.In the offline training stage, the sequence composed of the coordinates of the anchor nodes and Voronoi cell vertices was used as the training set for training.In the online test stage, the coordinates of unknown nodes in the network were predicted through the trained localization model.Simulation results show that the WMR-SKR algorithm can effectively reduce the node localization error and improve the node localization speed in 3D space.…”
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Lactational performance effects of 3-nitrooxypropanol supplementation to dairy cows: A meta-regression by L.F. Martins, M. Maigaard, M. Johansen, P. Lund, X. Ma, M. Niu, A.N. Hristov

“…ABSTRACT: A meta-regression was conducted to determine the production effects of 3-nitrooxypropanol (3-NOP) and investigate their associations with dose, dietary nutrient composition, and supplementation length in dairy cows. …”
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Large biogenic contribution to boundary layer O3‐CO regression slope in summer by Ye Cheng, Yuhang Wang, Yuzhong Zhang, Gao Chen, James H. Crawford, Mary M. Kleb, Glenn S. Diskin, Andrew J. Weinheimer

“…We analyze the model results to understand the factors contributing to the observed O3‐CO regression slope, which has been used in past studies to estimate the anthropogenic O3 production amount. …”
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Integration Analysis of Three Omics Data Using Penalized Regression Methods: An Application to Bladder Cancer. by Silvia Pineda, Francisco X Real, Manolis Kogevinas, Alfredo Carrato, Stephen J Chanock, Núria Malats, Kristel Van Steen

“…The overall analysis flow consisted of three steps: (1) SNPs/CpGs were selected per each gene probe within 1Mb window upstream and downstream the gene; (2) LASSO and ENET were applied to assess the association between each expression probe and the selected SNPs/CpGs in three multivariable models (SNP, CPG, and Global models, the latter integrating SNPs and CPGs); and (3) the significance of each model was assessed using the permutation-based MaxT method. …”
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Study on the efficiency of health resource allocation in the western region of China–based on three-stage DEA and Tobit regression analysis by Dongxue Zhao, Hua Huang, Yu Zhang, Shuanghang Li

Subjects: “…Three-stage DEA model…”
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REGRESSION OF SURVIVAL DAGUM 3 PARAMETER LINK FUNCTION IN HIV/AIDS PATIENTS IN EAST JAVA by Nur Mahmudah, Ifa Khoiria Ningrum

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3-PARAMETER GAMMA REGRESSION MODEL FOR ANALYZING HUMAN DEVELOPMENT INDEX OF CENTRAL JAVA PROVINCE by Hasbi Yasin, Syarifah Inayati, Setiawan Setiawan

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A TRAILR2/CDH3 bispecific antibody demonstrates selective apoptosis and tumor regression in CDH3-positive pancreatic cancer by Peter Jung, Stefan P. Glaser, Jing Han, Alexandra Popa, Laura Pisarsky, Ningping Feng, Antonia Geyer, Franziska Haderk, Donat Alpar, Christopher Bristow, Susanne Schmittner, Paula-Elena Traexler, Mikhila Mahendra, Birgit Poehn, Poojabahen Gandhi, Roberto Fiorelli, Sanket Awate, Nicole Budano, Florian Martin, Christoph Albrecht, Barbara Drobits-Handl, Sathanandam S. Anand, Srinath Kasturirangan, Francesca Trapani, Norbert Schweifer, Joseph R. Marszalek, Ulrike Tontsch-Grunt, Mark Pearson, Timothy P. Heffernan, Norbert Kraut, Christopher P. Vellano, Juan Manuel García-Martínez

“…TR2/CDH3 BAB demonstrated anti-tumor activity in a panel of PDAC patient-derived xenograft models, including tumor regressions. …”
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Temperature data of Hyderabad from the temperature of three neighboring cities using the ANN and the multiple regression methods by Adeel, Muhammad Ashraf, Atteeq Razzak, Syed Masood Raza, Zaheer Uddin

“…Amultiple regression analysis with three independent variables, i.e., the temperatures of Karachi, Nawabshah, and Badin, are used to find a linear equation of multiple variables for the temperature of Hyderabad. …”
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Associations of urinary caffeine metabolites with sex hormones: comparison of three statistical models by Jianli Zhou, Linyuan Qin, Linyuan Qin

“…We also fitted weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) methods to further assess these relationships.ResultsIn the PCA-multivariable linear regression, PC2 negatively correlates with E2: β = −0.01, p-value = 0.049 (male population). …”
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Classification of Red Foxes: Logistic Regression and SVM with VGG-16, VGG-19, and Inception V3 by Brian Sabayu, Imam Yuadi

“…This study conducts an evaluation of three deep learning architectures: Inception V3, VGG-16, and VGG-19, utilizing images of red foxes. …”
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