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- research-articleDecember 2023
FedStar: Efficient Federated Learning on Heterogeneous Communication Networks
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCADICS), Volume 43, Issue 6Pages 1848–1861https://doi.org/10.1109/TCAD.2023.3346274The proliferation of multimedia applications and increased computing power of mobile devices have led to the development of personalized artificial intelligent (AI) applications that utilize the massive user-information residing on them. However, the ...
- research-articleApril 2024
IFF-WAV2VEC: Noise Robust Low-Resource Speech Recognition Based on Self-supervised Learning and Interactive Feature Fusion
AICCC '23: Proceedings of the 2023 6th Artificial Intelligence and Cloud Computing ConferencePages 232–237https://doi.org/10.1145/3639592.3639624In recent years, self-supervised learning representation (SSLR) has shown remarkable performance in low-resource speech recognition. However, it lacks consideration for the robustness of low-resource models in noisy environments, making it crucial to ...
- research-articleSeptember 2023
A peak-current mode boost converter with fast linear transient response
AbstractThis paper proposes a peak-current mode boost converter with fast linear transient response. To achieve this, a fast linear transient response circuit is proposed, which can directly reflect the change in the input voltage to the ...
- ArticleNovember 2023
Wavelet-SVDD: Anomaly Detection and Segmentation with Frequency Domain Attention
AbstractAnomaly detection is a formidable challenge that entails the formulation of a model capable of detecting anomalous patterns in datasets, even when anomalous data points are absent. Traditional algorithms focused on learning knowledge regarding the ...
- research-articleAugust 2023
Ability-aware knowledge distillation for resource-constrained embedded devices
Journal of Systems Architecture: the EUROMICRO Journal (JOSA), Volume 141, Issue Chttps://doi.org/10.1016/j.sysarc.2023.102912AbstractDeep Neural Network (DNN) models have notably improved the efficiency of machine learning tasks. However, their high storage and computational costs restrict their deployment on resource-limited embedded devices. Knowledge distillation ...
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- ArticleJuly 2023
Constructing Cultural Branding for Sustainability: A Case Study of Designing ‘Traditional Circular’ into ‘Modern Product’
AbstractThe fusion of creativity and cultural elements is one of the topics that researchers have discussed for a long time. In addition to being able to integrate with innovation, the cultural elements are not only a carrier that highlights local culture ...
- research-articleJune 2023
Heter-Train: A Distributed Training Framework Based on Semi-Asynchronous Parallel Mechanism for Heterogeneous Intelligent Transportation Systems
- Jiawei Geng,
- Jing Cao,
- Haipeng Jia,
- Zongwei Zhu,
- Hai Fang,
- Chengxi Gao,
- Cheng Ji,
- Gangyong Jia,
- Guangjie Han,
- Xuehai Zhou
IEEE Transactions on Intelligent Transportation Systems (ITS-TRANSACTIONS), Volume 25, Issue 1Pages 959–972https://doi.org/10.1109/TITS.2023.3286400Transportation big data (TBD) are increasingly combined with artificial intelligence to mine novel patterns and information due to the powerful representational capabilities of deep neural networks (DNNs), especially for anti-COVID19 applications. The ...
- research-articleApril 2023
Effective pavement skid resistance measurement using multi‐scale textures and deep fusion network
Computer-Aided Civil and Infrastructure Engineering (MICE), Volume 38, Issue 8Pages 1041–1058https://doi.org/10.1111/mice.12931AbstractPavement skid resistance measurement is a fundamental component of roadway management and maintenance. Most traditional approaches rely on manual operations or heavy devices, which lead to a labor‐intensive, inefficient, and vulnerable testing ...
- research-articleFebruary 2023
hAP: A Spatial-von Neumann Heterogeneous Automata Processor with Optimized Resource and IO Overhead on FPGA
FPGA '23: Proceedings of the 2023 ACM/SIGDA International Symposium on Field Programmable Gate ArraysPages 185–196https://doi.org/10.1145/3543622.3573190Regular expression (REGEX) matching tasks drive much research on automata processors (AP). Among them, the von Neumann AP can efficiently utilize on-chip memory to process the Deterministic Finite Automata (DFA), but it is limited to small REGEX sets due ...
- research-articleDecember 2022
A novel systematic and evolved approach based on XGBoost-firefly algorithm to predict Young’s modulus and unconfined compressive strength of rock
Engineering with Computers (ENGC), Volume 38, Issue Suppl 5Pages 3829–3845https://doi.org/10.1007/s00366-020-01241-2AbstractTo design the tunnel excavations, the most important parameters are the engineering properties of rock, e.g., Young’s modulus (E) and unconfined compressive strength (UCS). Numerous researchers have attempted to propose methods to estimate E and ...
- research-articleDecember 2022
Study on Digital Signal Synchronization System of Confocal Micro Endoscope
CSSE '22: Proceedings of the 5th International Conference on Computer Science and Software EngineeringPages 53–59https://doi.org/10.1145/3569966.3569981Abstract: Laser confocal scanning micro endoscopy has become the focus of current research because of its ability to achieve high-resolution real-time histological diagnosis and certain depth tomography imaging. In the digital communication system of ...
- research-articleSeptember 2022
Improving Quality of Service for Cell-Edge Users in D2D-Relay Networks
Wireless Personal Communications: An International Journal (WPCO), Volume 126, Issue 2Pages 1789–1804https://doi.org/10.1007/s11277-022-09822-8AbstractIn this paper, we build a D2D-relay communications model where the D2D user is selected as a relay to forward data for the users at the edge of the networks. We aim at maximizing the achievable data rates of the cell-edge users, a resource ...
- research-articleAugust 2022
Sniper: cloud-edge collaborative inference scheduling with neural network similarity modeling
DAC '22: Proceedings of the 59th ACM/IEEE Design Automation ConferencePages 505–510https://doi.org/10.1145/3489517.3530474The cloud-edge collaborative inference demands scheduling the artificial intelligence (AI) tasks efficiently to the appropriate edge smart device. However, the continuously iterative deep neural networks (DNNs) and heterogeneous devices pose great ...
- ArticleJune 2022
From Nature to Reality: The Approach of Transforming Chinese Characters into Product
Cross-Cultural Design. Applications in Learning, Arts, Cultural Heritage, Creative Industries, and Virtual RealityPages 3–13https://doi.org/10.1007/978-3-031-06047-2_1AbstractHuman beings explore the relationship between humans and nature for linking them and pursuing the unity of function and aesthetics. Based on this kind of thought, the creation of “learning from nature” appears. In the past, creators usually ...
- research-articleJune 2022
Social-aware relay selection and energy-efficient resource allocation for relay-aided D2D communication
AbstractHow to improve the flexibility of limited communication resources to meet the increasing requirements of data services has become one of the research hotspots of the modern wireless communication network. In this paper, a novel social-...
- research-articleJune 2022
A risky large group emergency decision-making method based on topic sentiment analysis
Expert Systems with Applications: An International Journal (EXWA), Volume 195, Issue Chttps://doi.org/10.1016/j.eswa.2022.116527Highlights- A novel method is proposed for public intuition fuzzy attribute preference.
- ...
This study proposes a decision-making method based on topic sentiment analysis to address the problem of completely data-driven attribute information acquisition and risk control of the intuitionistic fuzzy preference in large group ...
- research-articleDecember 2021
HADFL: Heterogeneity-aware Decentralized Federated Learning Framework
2021 58th ACM/IEEE Design Automation Conference (DAC)Pages 1–6https://doi.org/10.1109/DAC18074.2021.9586101Federated learning (FL) supports training models on geographically distributed devices. However, traditional FL systems adopt a centralized synchronous strategy, putting high communication pressure and model generalization challenge. Existing ...
- research-articleOctober 2021
Self-learning transferable neural network for intelligent fault diagnosis of rotating machinery with unlabeled and imbalanced data
AbstractAs a promising tool for intelligent diagnosis of rotating machinery with unlabeled data, transfer learning (TL) has attracted considerable attentions from academia and industry. However, mechanical data in real-case have obviously ...
Highlights- A novel STNN is proposed for the intelligent fault diagnosis of rotating machinery.
- research-articleOctober 2021
Serving at the Edge: An Edge Computing Service Architecture Based on ICN
ACM Transactions on Internet Technology (TOIT), Volume 22, Issue 1Article No.: 22, Pages 1–27https://doi.org/10.1145/3464428Different from cloud computing, edge computing moves computing away from the centralized data center and closer to the end-user. Therefore, with the large-scale deployment of edge services, it becomes a new challenge of how to dynamically select the ...
- ArticleAugust 2021
An LDA and RBF-SVM Based Classification Method for Inertinite Macerals of Coal
AbstractIn view of the complicacy and the diversity of inertinite macerals of coal, a classification method based on linear discriminate analysis (LDA) and support vector machine (SVM) is proposed. Firstly, according to differences of texture and ...