Proposing a framework for body mass prediction with point clouds: A study applied in typical swine pen environments by Gabriel Pagin, Luciane Silva Martello, Rubens André Tabile, Rafael Vieira de Sousa

“…Challenges persist in implementing these techniques in pens with a large number of animals, especially in extracting physical body characteristics from images in a production environment. In this context, the main objective of this research is to investigate a novel framework comprising effective algorithms for feature extraction, attribute selection, hyperparameter optimization, and prediction modelling, using point clouds collected from production animals (growing and finishing pigs). …”
Get full text

Assessing the spatiotemporal dynamics of seasonal and perennial surface water resources across Lesotho’s agroecological zones by Kunwar K. Singh, Sayedeh Sara Sayedi, Ariel BenYishay, Tšepiso A. Rantšo

Get full text

Research on Cultivated Land Quality Assessment at the Farm Scale for Black Soil Region in Northeast China Based on Typical Period Remote Sensing Images from Landsat 9 by Meng Gao, Zhao Yang, Xiaoming Li, Hongmin Sun, Yanhong Hang, Boyu Yang, Yang Zhou

Get full text

Reliability evaluation of dynamic face recognition systems based on improved Fuzzy Dynamic Bayesian Network by Zhiqiang Liu, Wenbo Zhu, Hongzhou Zhang, Shengjin Wang, Lu Fang, Weijun Hong, Hua Shao, Guopeng Wang

Get full text

The Controlling Factors and Prediction of Deep-Water Mass Transport Deposits in the Pliocene Qiongdongnan Basin, South China Sea by Jiawang Ge, Xiaoming Zhao, Qi Fan, Weixin Pang, Chong Yue, Yueyao Chen

Get full text

On precise path planning algorithm in wireless sensor network by Farhanda Javed, Samiullah Khan, Asfandyar Khan, Alweena Javed, Rohi Tariq, Matiullah, Faheem Khan

“…Simulation scenarios with three node densities are used in this research study such as sparse node density, medium node density, and dense node density. …”
Get full text

Evaluation of GLOCK 9 mm Firing Pin Aperture Shear Mark Individuality Based on 3,156 Different Pistols (Manufactured Over a 30 Year Period in Two Countries) Using Additional Patter... by James E. Hamby, Eric Warren, Stephen Norris, Nicholas D.K. Petraco

Get full text

Modified Meerkat Clan Algorithm for Association Rules Mining by Mohamad Ab. Saleh, Ahmed T. Sadiq Sadiq

Get full text

Hybrid Weighted Random Forests Method for Prediction & Classification of Online Buying Customers by Umesh Kumar Lilhore, Sarita Simaiya, Devendra Prasad, Deepak Kumar Verma

Get full text

Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

Get full text

Applying Genetic Algorithm for test pattern generation process optimization by V. I. Kuraedov

Get full text

Numerical Simulation of Diversion Tunnel Excavation Using GPU-Accelerated Anisotropic Random Fields by Guo-jin Zhu, Yu Ning, Zhi-hao Cui, Nanxiang Hu, Qing-xiang Meng, Chun Zhu

Get full text

Prediction of mung bean production using machine learning algorithms by Azanu Mirolgn Mequanenit, Aleka Melese Ayalew, Ayodeji Olalekan Salau, Eyerusalem Alebachew Nibret, Million Meshesha

Get full text

Forest canopy closure estimation in mountainous southwest China using multi-source remote sensing data by Wenwu Zhou, Wenwu Zhou, Qingtai Shu, Cuifen Xia, Li Xu, Qin Xiang, Lianjin Fu, Zhengdao Yang, Shuwei Wang

“…Then, the multi-source remote sensing image Sentinel-1/2 and terrain factors were combined to perform regional-scale FCC remote sensing estimation based on the geographically weighted regression (GWR) model. The research results showed that (1) among the 50 extracted ATLAS LiDAR feature indices, the best footprint-scale modeling factors are Landsat_perc, h_dif_canopy, asr, h_min_canopy, toc_roughness, and n_touc_photons after random forest (RF) feature variable optimization; (2) among the BO-RFR, BO-KNN, and BO-GBRT models developed at the footprint scale, the FCC results estimated by the BO-GBRT model were the best (R2 = 0.65, RMSE = 0.10, RS = 0.079, and P = 79.2%), which was used as the FCC estimation model for 74,808 footprints in the study area; (3) taking the FCC value of ATLAS footprint scale in forest land as the training sample data of the regional-scale GWR model, the model accuracy was R2 = 0.70, RMSE = 0.06, and P = 88.27%; and (4) the R² between the FCC estimates from regional-scale remote sensing and the measured values is 0.70, with a correlation coefficient of 0.784, indicating strong agreement. …”
Get full text

Regional Photovoltaic Consumption Control Strategy Based on Non-MPPT Algorithm by Geng NIU, Lingfeng KOU, Xiaogang HOU, Xiaoyun QU, Hui XIE, Bo GAO

Get full text

A simple and efficient algorithm for genome‐wide homozygosity analysis in disease by Wei Liu, Jinhui Ding, Jesse Raphael Gibbs, Sue Jane Wang, John Hardy, Andrew Singleton

Get full text

In-Memory Versus Disk-Based Computing with Random Forest for Stock Analysis: A Comparative Study by Chitra Joshi, Chitrakant Banchorr, Omkaresh Kulkarni, Kirti Wanjale

Get full text

Positioning Guselkumab in The Treatment Algorithm of Patients with Crohn’s Disease by D'Amico F, Bencardino S, Magro F, Dignass A, Gutiérrez Casbas A, Verstockt B, Hart A, Armuzzi A, Peyrin-Biroulet L, Danese S

“…Ferdinando D’Amico,1,* Sarah Bencardino,1,* Fernando Magro,2 Axel Dignass,3 Ana Gutiérrez Casbas,4 Bram Verstockt,5 Ailsa Hart,6 Alessandro Armuzzi,7,8 Laurent Peyrin-Biroulet,9 Silvio Danese1 1Gastroenterology and Endoscopy, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, Milan, Italy; 2CINTESIS@RISE, Faculty of Medicine of the University of Porto, Porto, Portugal; 3Department of Medicine I, Agaplesion Markus Hospital, Goethe University, Frankfurt/Main, Germany; 4Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Madrid, España; Hospital General Universitario de Alicante, Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL), Alicante, España; 5Department of Gastroenterology and Hepatology, University Hospitals Leuven, Leuven, KU, Belgium; 6Inflammatory Bowel Disease Unit, St Mark’s Hospital, LNWUH NHS Trust, Harrow, UK; 7IBD Unit, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy; 8Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy; 9Department of Gastroenterology, INFINY Institute, INSERM NGERE, CHRU Nancy, Vandœuvre-lès-Nancy, F-54500, France*These authors contributed equally to this workCorrespondence: Silvio Danese, Gastroenterology and Endoscopy, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, Tel +390226432069, Fax +390282242591, Email sdanese@hotmail.comAbstract: Guselkumab, a selective interleukin-23 (IL-23) inhibitor, has emerged as a promising biologic therapy for the management of patients with moderate-to-severe Crohn’s disease (CD) and has been recently approved for its treatment. …”
Get full text

Car Price Prediction and Recognition Using Deep Learning and Computer Vision Algorithms by Hira Farman, Saad Ahmed, Muhammad Hussain Mughal, Qurat -ul-ain Mastoi, Govari Shankar Lalwani

Get full text

Research on Cooperative Localization Method in Dynamic Networks by ZHANG Zhihua, SUN Bin, LI Bingchen, ZHOU Zhongfu, SHEN Feng

“…These circumstances can result in a decrease in the accuracy of cooperative localization algorithms or even cause them to malfunction. In order to address the above problems, this paper carries out the research on cooperative localization method, and proposes the filtering method of adaptive adjustment of observation error covariance matrix and the fusion of the federated filtering method, which enables the cooperative localization system to work normally in the case of the change of anchor nodes and ordinary nodes among mobile nodes, the disappearance or emergence of ranging values between nodes, and the random access and exit of nodes, etc. …”
Get full text