PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"

PoseidonQ: A Free Machine Learning Platform for the Development, Analysis, and Validation of Efficient and Portable QSAR Models for Drug Discovery حسب Muzammil Kabier (21028487)

"…The advent of powerful machine learning algorithms as well as the availability of high volume of pharmacological data has given new fuel to QSAR, opening new unprecedented options for deriving highly predictive models for assisting the rationale design of new bioactive compounds, for screening and prioritizing large molecular libraries, and for repurposing new drugs toward new clinical uses. …"

DataSheet1_Quantum-assisted fragment-based automated structure generator (QFASG) for small molecule design: an in vitro study.docx حسب Sergei Evteev (18294157)

"…</p><p>Methods: We developed Quantum-assisted Fragment-based Automated Structure Generator (QFASG), a fully automated algorithm designed to construct ligands for a target protein using a library of molecular fragments. …"

Supporting data for "clinical-oriented surgical planning based on finite element method and automate-generated surgical templates assisting the spinal surgery" حسب Tianchi Wu (11062323)

"…Remaining algorithm needed was reimplemented from open-source libraries.…"

Algorithms of Load Balancing in Next-Generation Mobile Netwoks: A systematic literature review حسب Juan Gabriel Ochoa-Aldeán (20678912)

"…Through a <b>systematic review following the PRISMA methodology</b>, we analyzed 45 studies from five scientific databases (IEEE Xplore, Scopus, ScienceDirect, SpringerLink, and ACM Digital Library), identifying key patterns:</p><ol><li>The correlation between optimization parameters (latency, throughput, user mobility) and the performance of automatic/hybrid algorithms.…"

Intelligent Selection of Metal–Organic Framework Arrays for Methane Sensing via Genetic Algorithms حسب Jenna A. Gustafson (3744139)

"…We build on our previously reported computational design methodology, which ranked MOF arrays by their Kullback–Liebler divergence (KLD) values for probabilistically describing the concentrations of each gas species in an unknown mixture. We ran the genetic algorithm to find optimal MOF arrays of various sizes when selecting from a library of 50 different MOF materials. …"

Segmentation, trace denoising and spike extraction framework. حسب Changjia Cai (10647521)

Efficient Regionalization for Spatially Explicit Neighborhood Delineation حسب Sergio Rey (8045333)

Chinese-STS-B dataset. حسب Meilong Zhu (17200360)

"…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …"

Ablation test results for character matching. حسب Meilong Zhu (17200360)

"…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …"

Image space visualization results. حسب Meilong Zhu (17200360)

"…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …"

Evaluation result of competition datasets. حسب Meilong Zhu (17200360)

"…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …"

Dot matrix space visualization results. حسب Meilong Zhu (17200360)

"…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …"

Reconstruction result. حسب Meilong Zhu (17200360)

"…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …"

Lcqmc dataset. حسب Meilong Zhu (17200360)

"…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …"

Test result comparison of general datasets. حسب Meilong Zhu (17200360)

"…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …"

AFQMC ant financial semantic similarity dataset. حسب Meilong Zhu (17200360)

"…The text similarity evaluation algorithm based on corpus and deep learning technology has problems such as insufficient amount of cross-library learning data and insufficient core content tendency in the similarity judgment of patent application technology disclosure document, which limits their performance and practical application. …"