A5048871266- IoT and Edge/Fog Computing
- Mobile Crowdsensing and Crowdsourcing
- Advanced MIMO Systems Optimization
- Age of Information Optimization
- Energy Harvesting in Wireless Networks
- Optimization and Search Problems
- Auction Theory and Applications
- Transportation and Mobility Innovations
- Cloud Computing and Resource Management
- Privacy-Preserving Technologies in Data
- Transportation Planning and Optimization
- Endodontics and Root Canal Treatments
- Software-Defined Networks and 5G
- Indoor and Outdoor Localization Technologies
- Energy Efficient Wireless Sensor Networks
- Robotic Path Planning Algorithms
- Experimental Behavioral Economics Studies
- Advanced Wireless Network Optimization
- Wireless Power Transfer Systems
- Mobile Ad Hoc Networks
- Underwater Vehicles and Communication Systems
- Congenital Heart Disease Studies
- Vehicle Routing Optimization Methods
- Occupational Health and Safety Research
- Caching and Content Delivery
Southeast University
2016-2025
Wuhan University
2025
Anhui Xinhua University
2011-2024
City University of Hong Kong
2008-2024
Harbin Institute of Technology
2019-2024
Tongji Hospital
2024
Huazhong University of Science and Technology
2013-2024
Sichuan University
2009-2024
China Academy of Building Research
2019-2024
Capital Medical University
2024
Due to the low pollution and sustainable properties, using electric buses for public transportation systems has attracted considerable attention, whereas how recharge with long continuous service hours remains an open problem. In this paper, we consider problem of placing vehicle (EV) charging stations at selected bus stops, minimize total installation cost stations. Specifically, study two EV station placement cases, without considering limited battery size, which are called ECSP_LB ECSP...
Federated Learning (FL) has recently attracted considerable attention in internet of things, due to its capability enabling mobile clients collaboratively learn a global prediction model without sharing their privacy-sensitive data the server. Despite great potential, main challenge FL is that training are usually non-Independent, Identically Distributed (non-IID) on clients, which may bring biases and cause possible accuracy degradation. To address this issue, paper aims propose novel...
Cloud computing has emerged as a very flexible service paradigm by allowing users to require virtual machine (VM) resources on-demand and cloud providers (CSPs) provide VM via pay-as-you-go model. This paper addresses the CSP's problem of efficiently allocating physical machines (PMs) with aim minimizing energy consumption. Traditional energy-aware allocations either allocate VMs PMs in centralized manner or implement migrations for reduction without considering migration cost systems. We...
Nowadays, vehicles have been increasingly adopted in mobile crowdsensing applications. Due to their predictable mobility trajectories, as participants bring new insight improving the quality. The of provides not only current locations vehicles, but also future trajectory. In this context, existing participant recruitment solutions, which are mainly based on participants, cannot be directly used vehicle-based crowdsensing. Utilizing predicted trajectory paper aims propose efficient vehicle...
Abstract The twenty-first century has seen an increase in stakeholders, highlighting the need to discuss role of corporate social responsibility technological innovation. objective current research is examine that innovation plays enhancing sustainable competitive performance firms. idea digital transformation mediates relationship between and proposed this study. Additionally, mastery climate may act as a boundary condition strengthens positive CSR transformation. data were collected...
Vehicle-to-vehicle/vehicle-to-infrastructure (referred to as V2X) communications have potential revolutionize current road transportation systems with respect vehicle safety, efficiency, and travel experience. This paper puts the first effort on applying network coding in cooperative V2X communication environments improve bandwidth efficiency enhance data service performance. Specifically, we investigate new arising challenges network-coding-assisted dissemination by considering both...
The growing size of convolutional neural networks (CNNs) requires large amounts on-chip storage. In many CNN accelerators, their limited memory capacity causes massive off-chip access and leads to very high system energy consumption. Embedded DRAM (eDRAM), with higher density than SRAM, can be used improve buffer reduce access. However, eDRAM periodic refresh maintain data retention, which costs much Refresh is unnecessary if the data's lifetime in shorter eDRAM's retention time. Based on...
Despite the increased capabilities of mobile devices, resource-demanded applications still transcend what can be accomplished on a single device. As such, device cloud (MDC), an environment that enables computation-intensive tasks to performed among set nearby offers promising architecture support real-time applications. To stimulate devices execute for others, it is essential design incentive mechanism appropriately charges owners tasks, acted as buyers, and rewards sellers. In this paper,...
Accurately predicting Origin-Destination (OD) passenger flow can help metro service quality and efficiency. Existing works have focused on incoming outgoing flows for individual stations, while little attention was paid to OD prediction in systems. The challenges are that 1) high temporal dynamics complex spatial correlations, 2) affected by external factors, 3) sparse incomplete data slices. In this paper, we propose an Adaptive Feature Fusion Network (AFFN) a) adaptively fuse dependencies...
In this letter, we consider the problem of cooperative application execution for mobile cloud computing. To encourage devices to share their unused resources, design an incentive scheme, which benefits both owner tasks and participated in task execution. A Stackelberg game is then formulated decide price that can be offered amount units each device willing provide. We discuss properties show there exists a unique equilibrium. Furthermore, efficient algorithm proposed reach equilibrium game....
Efficient data dissemination is critical for enabling emerging applications in vehicular ad hoc networks. As a typical traffic scenario, the bidirectional road scenario of highways bring unique challenges on well exploiting benefit vehicle-to-vehicle (V2V) communication sharing among vehicles driving opposite directions. This paper dedicated to investigating characteristics services such and exploring new opportunities enhancing overall system performance. Specifically, we present...
When deploying deep neural networks (DNNs) onto learning processors, we usually exploit mixed-precision quantization and voltage-frequency scaling to make tradeoffs among accuracy, latency, energy. Conventional methods determine the quantization-voltage-frequency (QVF) policy before DNNs are deployed local devices. However, they difficult optimal customizations for user scenarios. In this article, solve problem by enabling on-device QVF tuning with a new processor architecture Evolver....
Deep learning is a popular direction in computer vision and digital image processing. It widely utilized many fields, such as robot navigation, intelligent video surveillance, industrial inspection, aerospace. With the extensive use of deep techniques, classification object detection algorithms have been rapidly developed. In recent years, with introduction concept "unmanned retail," detection, play central role unmanned retail applications. However, open-source datasets traditional not yet...
Hospital buildings provide healthcare services at the costs of significant amounts energy consumption and carbon emissions, further exacerbating environmental load. Because limited research on life cycle emissions Chinese hospitals, this study conducted a detailed carbon-accounting comparative study. Firstly, BIM LCA were used to quantify inpatient building in each stage cycle. Secondly, differences by compared basis 20 cases public buildings. The results show that whole-life was 10,459.94...
With the increasing complexity of tasks that are crowdsourced, requesters need to form teams professional workers can satisfy complex task skill requirements. Team crowdsourcing in social networks (SNs) provides a promising solution for crowdsourcing, where requester hires team also socially connected work together collaboratively. Previous formation approaches have mainly focused on algorithmic aspect welfare maximization; however, within traditional objective maximizing alone, selfish...