Explanipedia

Feature extraction and pattern recognition of gas pipeline flow noise signals in a strong noisy background Open

Enbin Liu, Chang Lu, Zhaorong Wen, Tianshu Hao, Xudong Lü , et al. · 2024

The purpose of this study is to put forward a feature extraction and pattern recognition method for the flow noise signal of natural gas pipelines in view of the complex situation brought by the rapid development and expansion of urban nat…

Hypoxia-reprogramed megamitochondrion contacts and engulfs lysosome to mediate mitochondrial self-digestion Open

Tianshu Hao, Jianglong Yu, Zhida Wu, Jie Jiang, Longlong Gong , et al. · 2023

Edge AIBench 2.0: A scalable autonomous vehicle benchmark for IoT–Edge–Cloud systems Open

Tianshu Hao, Wanling Gao, Chuanxin Lan, Fei Tang, Zihan Jiang , et al. · 2022

Many emerging IoT–Edge–Cloud computing systems are not yet implemented or are too confidential to share the code or even tricky to replicate its execution environment, and hence their benchmarking is very challenging. This paper uses auton…

Hypoxia-reprogramed megamitochondrion contacts and engulfs lysosome to mediate mitoselfphagy Open

Tianshu Hao, Yu Jianglong, Zhida Wu, Jie Jiang, Long Gong , et al. · 2022

Mitochondria are the key organelles for sensing oxygen, which is consumed by oxidative phosphorylation to produce ATP to power the cell. Lysosomes contain hydrolytic enzymes that degrade misfolded proteins and damaged organelles, including…

OpenClinicalAI: enabling AI to diagnose diseases in real-world clinical settings Open

Yunyou Huang, Nana Wang, Suqin Tang, Li Ma, Tianshu Hao , et al. · 2021

This paper quantitatively reveals the state-of-the-art and state-of-the-practice AI systems only achieve acceptable performance on the stringent conditions that all categories of subjects are known, which we call closed clinical settings, …

Shift-and-Balance Attention Open

Chunjie Luo, Jianfeng Zhan, Tianshu Hao, Lei Wang, Wanling Gao · 2021

Attention is an effective mechanism to improve the deep model capability. Squeeze-and-Excite (SE) introduces a light-weight attention branch to enhance the network's representational power. The attention branch is gated using the Sigmoid f…

AIBench Training: Balanced Industry-Standard AI Training Benchmarking Open

Fei Tang, Wanling Gao, Jianfeng Zhan, Chuanxin Lan, Xu Wen , et al. · 2020

Earlier-stage evaluations of a new AI architecture/system need affordable benchmarks. Only using a few AI component benchmarks like MLPerfalone in the other stages may lead to misleading conclusions. Moreover, the learning dynamics are not…

AIBench: An Industry Standard AI Benchmark Suite from Internet Services. Open

Fei Tang, Wanling Gao, Jianfeng Zhan, Chuanxin Lan, Wen Xu , et al. · 2020

The booming successes of machine learning in different domains boost industry-scale deployments of innovative AI algorithms, systems, and architectures, and thus the importance of benchmarking grows. However, the confidential nature of the…

AIBench: An Agile Domain-specific Benchmarking Methodology and an AI Benchmark Suite Open

Wanling Gao, Fei Tang, Jianfeng Zhan, Chuanxin Lan, Chunjie Luo , et al. · 2020

Domain-specific software and hardware co-design is encouraging as it is much easier to achieve efficiency for fewer tasks. Agile domain-specific benchmarking speeds up the process as it provides not only relevant design inputs but also rel…

AI-oriented Medical Workload Allocation for Hierarchical Cloud/Edge/Device Computing Open

Tianshu Hao, Jianfeng Zhan, Kai Hwang, Wanling Gao, Xu Wen · 2020

In a hierarchically-structured cloud/edge/device computing environment, workload allocation can greatly affect the overall system performance. This paper deals with AI-oriented medical workload generated in emergency rooms (ER) or intensiv…

Edge AIBench: Towards Comprehensive End-to-end Edge Computing Benchmarking Open

Tianshu Hao, Yunyou Huang, Xu Wen, Wanling Gao, Fan Zhang , et al. · 2019

In edge computing scenarios, the distribution of data and collaboration of workloads on different layers are serious concerns for performance, privacy, and security issues. So for edge computing benchmarking, we must take an end-to-end vie…

LoadCNN: A Efficient Green Deep Learning Model for Day-ahead Individual Resident Load Forecasting. Open

Yunyou Huang, Nana Wang, Tianshu Hao, Wanling Gao, Cheng Huang , et al. · 2019

LoadCNN: A Low Training Cost Deep Learning Model for Day-Ahead Individual Residential Load Forecasting Open

Yunyou Huang, Nana Wang, Wanling Gao, Xiaoxu Guo, Cheng Huang , et al. · 2019

Accurate day-ahead individual residential load forecasting is of great importance to various applications of smart grid on day-ahead market. Deep learning, as a powerful machine learning technology, has shown great advantages and promising…

A new direction to promote the implementation of artificial intelligence in natural clinical settings Open

Yunyou Huang, Zhifei Zhang, Nana Wang, Nengquan Li, Mengjia Du , et al. · 2019

Artificial intelligence (AI) researchers claim that they have made great `achievements' in clinical realms. However, clinicians point out the so-called `achievements' have no ability to implement into natural clinical settings. The root ca…

10-millisecond Computing Open

Gang Lü, Jianfeng Zhan, Tianshu Hao, Lei Wang · 2016

Despite computation becomes much complex on data with an unprecedented scale, we argue computers or smart devices should and will consistently provide information and knowledge to human being in the order of a few tens milliseconds. We coi…

Isolate First, Then Share: a New OS Architecture for Datacenter Computing Open

Gang Lü, Jianfeng Zhan, Chongkang Tan, Xinlong Lin, Defei Kong , et al. · 2016

This paper presents the "isolate first, then share" OS model in which the processor cores, memory, and devices are divided up between disparate OS instances and a new abstraction, subOS, is proposed to encapsulate an OS instance that can b…

"Isolate First, Then Share": a New OS Architecture for the Worst-case Performance Open

Gang Lü, Jianfeng Zhan, Chongkang Tan, Xinlong Lin, Lei Wang , et al. · 2016

Previous OS abstractions and structures are mainly proposed for the average performance. The shift toward server side computing calls for new OS structures for the worst-case performance. This paper presents the isolate first, then share O…

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