A5013725152- Recommender Systems and Techniques
- Online Learning and Analytics
- Topic Modeling
- Energy Efficient Wireless Sensor Networks
- Multimodal Machine Learning Applications
- Cloud Computing and Resource Management
- Advanced Graph Neural Networks
- Domain Adaptation and Few-Shot Learning
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
- Sentiment Analysis and Opinion Mining
- Petri Nets in System Modeling
- Semantic Web and Ontologies
- Service-Oriented Architecture and Web Services
- IoT and Edge/Fog Computing
- Caching and Content Delivery
- Advanced Neural Network Applications
- Natural Language Processing Techniques
- Robotic Path Planning Algorithms
- Metaheuristic Optimization Algorithms Research
- Flexible and Reconfigurable Manufacturing Systems
- Rough Sets and Fuzzy Logic
- Video Surveillance and Tracking Methods
- Educational Technology and Assessment
- Advanced Image and Video Retrieval Techniques
Xi'an Jiaotong University
2016-2025
Peking University
2010-2025
Duke Kunshan University
2022-2024
Xi'an Honghui Hospital
2020-2024
Beijing Institute of Technology
2023-2024
Hebei University of Engineering
2022-2024
Southeast University
2024
Ningbo University
2024
Henan Institute of Technology
2024
Innovation Academy for Microsatellites of Chinese Academy of Sciences
2023
Abstract BACKGROUND In the human fetus, sex chromosome aneuploidies (SCAs) are as prevalent common autosomal trisomies 21, 18, and 13. Currently, most noninvasive prenatal tests (NIPTs) offer screening only for chromosomes 13, because sensitivity specificity markedly higher than chromosomes. Limited studies suggest that reduced accuracy associated with detecting SCAs is due to confined placental, or true fetal mosaicism. We hypothesized an altered maternal karyotype may also be important...
Accurate medical image segmentation is critical for early diagnosis. Most existing methods are based on U-shape structure and use element-wise addition or concatenation to fuse different level features progressively in decoder. However, both the two operations easily generate plenty of redundant information, which will weaken complementarity between features, resulting inaccurate localization blurred edges lesions. To address this challenge, we propose a general multi-scale subtraction...
Even for a simple automated manufacturing system (AMS), such as general single-unit resource allocation system, the computation of an optimal or maximally permissive deadlock-avoidance policy (DAP) is NP-hard. Based on its Petri-net model, this paper addresses problem in AMSs, which can be modeled by systems sequential processes with resources. First, deadlock characterized perfect resource-transition circuit that saturated at reachable state. Second, AMSs do not have one-unit resources...
The resource-transition circuit ( RTC) and siphon are two different structural objects of Petri nets used to develop deadlock control policies for automated manufacturing systems. They related the liveness property net models thus characterize avoid deadlocks. Based on them, there kinds methods developing controllers. Such rely computation all maximal perfect RTCs strict minimal siphons (SMSs), respectively. This paper concentrates a class called system simple sequential processes with...
A distributed and tamper proof media transaction framework is proposed based on the blockchain model. Current multimedia distribution does not preserve self-retrievable information of trails or content modification histories. For example, digital copies valuable artworks, creative entertainment contents are for various purposes including exhibitions, gallery collections in production workflow. Original often edited preparation tampered with to fabricate false propaganda over social media....
Aspect-based sentiment analysis aims to predict polarities of given aspects in text. Most current approaches employ attention-based neural methods capture semantic relationships between and words one sentence. However, these ignore the fact that sentences with same aspect polarity often share structure information a domain, which leads lower model performance. To mitigate this problem, we propose heterogeneous graph network (HAGNN) learn knowledge from intersentence relationships. Our is...
Generalized Category Discovery (GCD) aims to recognize both known and novel categories from a set of unlabeled data, based on another dataset labeled with only categories. Without considering differences between categories, current methods learn about them in coupled manner, which can hurt model's generalization discriminative ability. Furthermore, the training approach prevents these models transferring category-specific knowledge explicitly data lose high-level semantic information impair...
Sequential recommendation (SRS) has become the technical foundation in many applications recently, which aims to recommend next item based on user's historical interactions. However, sequential often faces problem of data sparsity, widely exists recommender systems. Besides, most users only interact with a few items, but existing SRS models underperform these users. Such problem, named long-tail user is still be resolved. Data augmentation distinct way alleviate two problems, they need...
There is evidence that an increasing number of enterprises plot together to evade tax in unperceived way. At the same time, taxation information related data a classic kind big data. These issues challenge effectiveness traditional mining-based evasion detection methods. To address this problem, we first investigate cases, and employ graph-based method characterize their property describes two suspicious relationship trails with antecedent node behind Interest-Affiliated Transaction (IAT)....
Fine particulate matter (PM2.5 ) has been a global environmental problem threatening public health in recent years. PM2.5 exposure was associated with an increased risk of neurodegenerative diseases related to neuronal apoptosis. Ferroptosis is nonapoptotic form programmed the cell death, characterized by excess iron-dependent lipid peroxidation products. Whether could induce ferroptosis cells and thus be involved its neurotoxicity unknown. In this study, we found that induced endoplasmic...
Aboveground biomass (AGB) serves as a crucial indicator of the carbon sequestration capacity coastal wetland ecosystems. Conducting extensive field surveys in wetlands is both time-consuming and labor-intensive. Unmanned aerial vehicles (UAVs) satellite remote sensing have been widely utilized to estimate regional AGB. However, mixed pixel effects hinder precise estimation AGB, while high-spatial resolution UAVs face challenges estimating large-scale To fill this gap, study proposed an...
Facial Expression Recognition (FER) for various low-resolution images is an important task and need in applications of analyzing crowd scenes (station, classroom, etc.). Due to the discriminative feature loss caused by reduced resolution, classifying facial into right category still a challenging task. In this work, we proposed novel generative adversarial network-based level super-resolution method robust expression recognition (FSR-FER), which can reduce chance privacy leaking without...
Container placement (CP) is a nontrivial problem in as Service (CaaS). Many works the literature solve it by using linear server energy-consumption models. However, solutions of model makes different CPs indistinguishable with regard to energy consumption homogeneous host environment that has same amount active hosts. As such, these are inefficient. In this paper, we demonstrate an energy-saving gain can be achieved optimizing containers under nonlinear model. Specifically, leverage strategy...