Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Xuekun Song"'
Publikováno v:
IEEE Access, Vol 10, Pp 79986-79998 (2022)
Detecting traces of patients with novel coronavirus pneumonia (COVID-19) is a prerequisite for avoiding the virus’s rapid spread. However, too much patient privacy data uploaded to the cloud centre will overwhelm the network and cause user informat
Externí odkaz:
https://doaj.org/article/0a5d0e00e9f944319001faeb9bb10c53
Publikováno v:
IEEE Access, Vol 8, Pp 4775-4784 (2020)
Group recommender systems suggesting items for a group of users have received many attentions recently. Some aggregation-based and model-based group recommendation methods have been proposed. However, the cold-start problem in group recommendation ha
Externí odkaz:
https://doaj.org/article/cdaaf7ca14ed4d3394d6b498626ae573
Publikováno v:
IEEE Access, Vol 8, Pp 214050-214060 (2020)
Event recommendation has attracted an increasing attention with the popularity of event-based social networks (EBSNs). The previous studies mainly focus on exploiting various contextual information to alleviate the cold-start problem in event recomme
Externí odkaz:
https://doaj.org/article/55d301d89445499d9e359b303075850d
Autor:
Guozhi Li, Xuekun Song
Publikováno v:
IEEE Access, Vol 8, Pp 214332-214345 (2020)
Resource-constrained wireless sensor networks (WSNs) impose a substantial challenge to the transmission and processing of non-redundant perceptual data. Moreover, breakthroughs in this area have opened up a new dimension that integrates edge computin
Externí odkaz:
https://doaj.org/article/6a4e322817c14cd6a57fe08b079a255b
Publikováno v:
Frontiers in Molecular Biosciences, Vol 7 (2020)
Breast cancer cell lines are frequently used to elucidate the molecular mechanisms of the disease. However, a large proportion of cell lines are affected by problems such as mislabeling and cross-contamination. Therefore, it is of great clinical sign
Externí odkaz:
https://doaj.org/article/4e6ee74c1228403a89fbe3f76972a631
Publikováno v:
IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20:1563-1573
Sparse regressions applied to cancer diagnosis suffer from noise reduction, gene grouping, and group significance evaluation. This paper presented the weighted group regularized logistic regression (WGRLR) for dealing with the above problems. Clean d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39237578dc7fc9390b2d3b63a5f79a1e
https://doi.org/10.1109/tcbb.2022.3203167
https://doi.org/10.1109/tcbb.2022.3203167
Autor:
Joseph Naiman, Peter Xuekun Song
Publikováno v:
Entropy, Vol 24, Iss 2, p 203 (2022)
Motivated by mobile devices that record data at a high frequency, we propose a new methodological framework for analyzing a semi-parametric regression model that allow us to study a nonlinear relationship between a scalar response and multiple functi
Externí odkaz:
https://doaj.org/article/bb876a28e0c14a508939dd299765ba57
Publikováno v:
Future Generation Computer Systems. 130:19-32
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c56dedf4f7b860c1c00a598979229c0
https://doi.org/10.1016/j.future.2021.12.005
https://doi.org/10.1016/j.future.2021.12.005
Publikováno v:
Current Bioinformatics. 15:703-712
Background: Cancer threatens human health seriously. Diagnosing cancer via gene expression analysis is a hot topic in cancer research. Objective: The study aimed to diagnose the accurate type of lung cancer and discover the pathogenic genes. Methods:
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::abc1558fc7ac6905df1b42eca7f0d32d
https://doi.org/10.2174/1574893614666191017103557
https://doi.org/10.2174/1574893614666191017103557
Publikováno v:
IEEE Access, Vol 8, Pp 4775-4784 (2020)
Group recommender systems suggesting items for a group of users have received many attentions recently. Some aggregation-based and model-based group recommendation methods have been proposed. However, the cold-start problem in group recommendation ha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60ea8bc2f7a1cfa8ce1c6afe1180a81f
https://ieeexplore.ieee.org/document/8943959/
https://ieeexplore.ieee.org/document/8943959/