Results 41 to 50 of about 150,441 (331)

Machine learning-guided synthesis of advanced inorganic materials

, 2019
Synthesis of advanced inorganic materials with minimum number of trials is of paramount importance towards the acceleration of inorganic materials development.
Chouhan, Tushar, Golani, Prafful, Guan, Cuntai, Liu, Zheng, Lu, Yuhao, Tang, Bijun, Wang, Han, Xu, Manzhang, Xu, Quan, Zhou, Jiadong   +9 more
core   +1 more source

XGBoost-enhanced ensemble model using discriminative hybrid features for the prediction of sumoylation sites

BioData Mining
Posttranslational modifications (PTMs) are essential for regulating protein localization and stability, significantly affecting gene expression, biological functions, and genome replication.
Salman Khan, Sumaiya Noor, T. Javed, A. Naseem, Fahad Aslam, Salman A. Alqahtani, Nijad Ahmad   +6 more
semanticscholar   +1 more source

High‐Performance Transparent, Deformable, and Recoverable Biomimetic Stevia–PVA Hydrogel Triboelectric Nanogenerator with Machine Learning‐Assisted Motion Recognition

Advanced Materials, EarlyView.
A transparent, deformable stevia–PVA hydrogel triboelectric nanogenerator delivers significantly enhanced mechanical strength and electrical output through biomimetic hydrogen‐bonded networks. Coupled with machine learning–assisted signal recognition, the self‐powered hydrogel enables accurate human‐motion sensing for intelligent wearable and IoT ...
Thien Trung Luu, Bui Minh Quang, Toan Minh Pham, Jinsoo Kim, Kyungwho Choi, Dukhyun Choi   +5 more
wiley   +1 more source

A novel improved model for building energy consumption prediction based on model integration [PDF]

, 2020
Building energy consumption prediction plays an irreplaceable role in energy planning, management, and conservation. Constantly improving the performance of prediction models is the key to ensuring the efficient operation of energy systems.
Feng, W, Lu, S, Wang, R
core  

Comparative analysis of CatBoost, LightGBM, XGBoost, RF, and DT methods optimised with PSO to estimate the number of k-barriers for intrusion detection in wireless sensor networks

International Journal of Machine Learning and Cybernetics
The protection of borders is a critical concern for all countries, and Wireless Sensor Networks (WSNs) play a crucial role in assuring security by enabling intrusion detection and surveillance at border regions.
K. Ileri
semanticscholar   +1 more source

De Novo Multi‐Mechanism Antimicrobial Peptide Design via Multimodal Deep Learning

Advanced Science, EarlyView.
Current AI‐driven peptide discovery often overlooks complex structural data. This study presents M3‐CAD, a generative pipeline that leverages 3D voxel coloring and a massive database of over 12 000 peptides to capture nuanced physicochemical contexts.
Xiaojuan Li, Haifan Gong, Yue Wang, Yinuo Zhao, Lixiang Li, Peijing Bao, Qingzhou Kong, Jialu Fu, Boyao Wan, Yumeng Zhang, Jinghui Zhang, Jiekun Ni, Zhongxue Han, Xueping Nan, Kunping Ju, Longfei Sun, Yuerui Ma, Huijun Chang, Mengqi Zheng, Yanbo Yu, Xiaoyun Yang, Xiuli Zuo, Haina Wang, Yanqing Li   +23 more
wiley   +1 more source

Computational Identification and Analysis of Ubiquinone-Binding Proteins

Cells, 2020
Ubiquinone is an important cofactor that plays vital and diverse roles in many biological processes. Ubiquinone-binding proteins (UBPs) are receptor proteins that dock with ubiquinones.
Chang Lu, Wenjie Jiang, Hang Wang, Jinxiu Jiang, Zhiqiang Ma, Han Wang   +5 more
doaj   +1 more source

Compact Multi-Class Boosted Trees

, 2017
Gradient boosted decision trees are a popular machine learning technique, in part because of their ability to give good accuracy with small models. We describe two extensions to the standard tree boosting algorithm designed to increase this advantage ...
Colthurst, Thomas, Haykal, Salem, Hendry, Gilbert, Ponomareva, Natalia, Radpour, Soroush   +4 more
core   +1 more source

Influence-Balanced XGBoost: Improving XGBoost for Imbalanced Data Using Influence Functions

IEEE Access
Decision tree boosting algorithms, such as XGBoost, have demonstrated superior predictive performance on tabular data for supervised learning compared to neural networks. However, recent studies on loss functions for imbalanced data have primarily focused on deep learning.
Akiyoshi Sutou, Jinfang Wang
openaire   +2 more sources

Maternal Preconception Antibiotic Exposure Disrupts Microbial Succession: A Transgenerational Risk for Offspring Gut Mucosal Immaturity and Colitis Susceptibility

Advanced Science, EarlyView.
This study reveals that maternal antibiotic exposure prior to conception disrupts intergenerational gut microbial succession. By enhancing maternal‐offspring microbial transmission, altering microbial developmental trajectories and increasing selective pressures during community assembly, these disturbances lead to persistent gut mucosal immaturity and
Yuzhu Chen, Ruqiao Duan, Cunzheng Zhang, Gaonan Li, XiaoLin Ji, Qi Zhang, Fei Pei, Kun Wang, Liping Duan   +8 more
wiley   +1 more source