A5057303331- Cloud Computing and Resource Management
- Distributed and Parallel Computing Systems
- IoT and Edge/Fog Computing
- Complex Network Analysis Techniques
- Anomaly Detection Techniques and Applications
- Advanced Graph Neural Networks
- Optical Coherence Tomography Applications
- Recommender Systems and Techniques
- Retinal Imaging and Analysis
- Text and Document Classification Technologies
- Advanced Clustering Algorithms Research
- Advanced Neural Network Applications
- Neural Networks and Applications
- Business Process Modeling and Analysis
- Hand Gesture Recognition Systems
- Medical Image Segmentation Techniques
- Network Security and Intrusion Detection
- stochastic dynamics and bifurcation
- Neural dynamics and brain function
- Radiomics and Machine Learning in Medical Imaging
- Nonlinear Dynamics and Pattern Formation
- Image Retrieval and Classification Techniques
- Scientific Computing and Data Management
- Software Engineering Research
- AI in cancer detection
Putian University
2019-2025
Monash University
2025
University of Jinan
2017-2021
Anhui University
2007-2020
Beihang University
2018-2019
Shanxi Medical University
2015
The Ohio State University
2006
National Space Science Center
1998
Existing environmental quality indices often fail to account for the varying health impacts of different exposures and exclude socio-economic status indicators (SES). To develop validate a comprehensive Environmental Quality Health Index (EQHI) that integrates multiple SES assess mortality risks across Australia. We combined all-cause, cardiovascular, respiratory data (2016-2019) from 2,180 Statistical Areas Level 2 with annual mean values 12 exposures, including PM2.5, ozone, temperature,...
Cases of sporadic Alzheimer's disease (SAD) are the predominant form age-related dementia. New evidence suggests that metabolic syndrome (MS), a disorder, is an initiating factor some SAD cases. A high-sugar high-fat diet could cause MS, we aimed to investigate whether it directly lead SAD.
After the local outlier factor was first proposed, there is a large family of detection approaches derived from it. Since existing only focus on extent overall separation between an object and its neighbors, ignore degree dispersion them, precision these will be affected by various degrees in scattered datasets. In addition, data occupy relatively small amount dataset, but need to perform calculation all during detection, which greatly reduces efficiency algorithms. this paper, we redefine...
Summary Utilization of cloud computing resources has made a fast growth in e‐business. Business and government agencies often need to handle large volume service requests, the so‐called instance‐intensive business processes constrained period. On‐time completion for within time is very important issue. In past few years, traditional optimal task scheduling been well researched proven be nondeterministic polynomial (NP) time–complete problem. So many heuristic metaheuristic algorithms are put...
Objective.Locoregional recurrence (LRR) is one of the leading causes treatment failure in head and neck (H&N) cancer. Accurately predicting LRR after radiotherapy essential to achieving better outcomes for patients with H&N cancer through developing personalized strategies. We aim develop an end-to-end multi-modality multi-view feature extension method (MMFE) predict cancer.Approach.Deep learning (DL) has been widely used building prediction models achieved great success. Nevertheless,...
Logistic regression (LR) and artificial intelligence algorithms were used to analyze the risk factors for early rupture of acute type A aortic dissection (ATAAD). Data from electronic medical records 200 patients diagnosed with ATAAD Department Emergency Guangdong Provincial People’s Hospital April 2012 March 2017 collected. establish prediction models, effects four models analyzed. According LR we elucidated independent rupture, which included age > 63 years (odds ratio (OR) = 1.69), female...
Abstract Traditional competitive human resource allocation is no longer suitable for contemporary requirements. To improve the effectiveness of management and degree matching between jobs staffs, we propose a novel auto-encoder neural network-based method in cloud environment, which semi-automatic manner business process allocation. The proposed based on deep learning architecture by using appropriate resources takes into account similarities presentation staff modules. construction network...
Evolutionary algorithms have been widely applied for solving multi-objective optimization problems, while the feature selection in classification can also be treated as a discrete bi-objective problem if attempting to minimize both error and ratio of selected features. However, traditional evolutionary (MOEAs) may drawbacks tackling large-scale selection, due curse dimensionality decision space. Therefore, this paper, we concentrated on designing an multi-task decomposition-based algorithm...
A sliding mode control with a dynamic surface is proposed to solve the infinite-time optimal problem for linear systems. The advantage of this kind that it provides robust
Many researches of machine learning aim to improve the click prediction online advertisement (ads). One important method is investigate pairwise relevance among instances on impression data and global interaction key features instances. However, feature extraction ability not effective for large amounts variables in process. In this paper, we propose a novel model named optimally connected deep belief net (OCDBN) with rotation codes whitening technology based optimal mean removal. According...
Due to fast development of e-commerce, logistics, network and cloud computing, many businesses have changed their traditional production sale patterns. This brings big opportunities challenges logistics. Among the process delivery is a key issue. paper mainly focuses on logistics scheduling based business workflows. A constrained Dijkstra algorithm proposed select an optimal route for transportation with various parameters. We then put forward distribution solve tracking large numbers...
With the rapid development of e-business, large volume business processes need to be handled in a constrained time. There is always security issue related on-time completion many applications economic fields. So, how effectively manage and organize became very important. By using cloud computing, instance-intensive can more by applying just-right virtual machines. Hence, management resources an important that researchers focus on fully utilize advantage cloud. In this paper, we mainly...