Zobrazeno 1 - 10
of 400
pro vyhledávání: '"PATHIRANA, PUBUDU N."'
Autor:
Indrasiri, Pubudu L., Kashyap, Bipasha, Kolambahewage, Chandima, Nakisa, Bahareh, Ijaz, Kiran, Pathirana, Pubudu N.
Emotion recognition is significantly enhanced by integrating multimodal biosignals and IMU data from multiple domains. In this paper, we introduce a novel multi-scale attention-based LSTM architecture, combined with Squeeze-and-Excitation (SE) blocks
Externí odkaz:
http://arxiv.org/abs/2412.02283
Autor:
Islam, Muhammad, Fernando, Niroshinie, Loke, Seng W., Neiat, Azadeh Ghari, Pathirana, Pubudu N.
We propose Blockchain-enabled Device-enhanced Multi-access Edge Computing (BdMEC). BdMEC extends the Honeybee framework for on-demand resource pooling with blockchain technology to ensure trust, security, and accountability among devices (even when t
Externí odkaz:
http://arxiv.org/abs/2412.02233
Autor:
Shaham, Sina, Hajisafi, Arash, Quan, Minh K, Nguyen, Dinh C, Krishnamachari, Bhaskar, Peris, Charith, Ghinita, Gabriel, Shahabi, Cyrus, Pathirana, Pubudu N.
Privacy and fairness are two crucial pillars of responsible Artificial Intelligence (AI) and trustworthy Machine Learning (ML). Each objective has been independently studied in the literature with the aim of reducing utility loss in achieving them. D
Externí odkaz:
http://arxiv.org/abs/2307.15838
Autor:
Nguyen, Dinh C., Nguyen, Van-Dinh, Ding, Ming, Chatzinotas, Symeon, Pathirana, Pubudu N., Seneviratne, Aruna, Dobre, Octavia, Zomaya, Albert Y.
The convergence of mobile edge computing (MEC) and blockchain is transforming the current computing services in wireless Internet-of-Things networks, by enabling task offloading with security enhancement based on blockchain mining. Yet the existing a
Externí odkaz:
http://arxiv.org/abs/2206.09009
Publikováno v:
In Knowledge-Based Systems 3 December 2024 305
Autor:
Nguyen, Dinh C., Hosseinalipour, Seyyedali, Love, David J., Pathirana, Pubudu N., Brinton, Christopher G.
In this paper, we study a new latency optimization problem for blockchain-based federated learning (BFL) in multi-server edge computing. In this system model, distributed mobile devices (MDs) communicate with a set of edge servers (ESs) to handle bot
Externí odkaz:
http://arxiv.org/abs/2203.09670
Autor:
Nguyen, Dinh C., Pham, Quoc-Viet, Pathirana, Pubudu N., Ding, Ming, Seneviratne, Aruna, Lin, Zihuai, Dobre, Octavia A., Hwang, Won-Joo
Recent advances in communication technologies and Internet-of-Medical-Things have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI techniques require centralized data collection and processing that may be infeas
Externí odkaz:
http://arxiv.org/abs/2111.08834
COVID-19 has spread rapidly across the globe and become a deadly pandemic. Recently, many artificial intelligence-based approaches have been used for COVID-19 detection, but they often require public data sharing with cloud datacentres and thus remai
Externí odkaz:
http://arxiv.org/abs/2110.07136
Autor:
Gadekallu, Thippa Reddy, Pham, Quoc-Viet, Nguyen, Dinh C., Maddikunta, Praveen Kumar Reddy, Deepa, N, B, Prabadevi, Pathirana, Pubudu N., Zhao, Jun, Hwang, Won-Joo
In recent years, blockchain networks have attracted significant attention in many research areas beyond cryptocurrency, one of them being the Edge of Things (EoT) that is enabled by the combination of edge computing and the Internet of Things (IoT).
Externí odkaz:
http://arxiv.org/abs/2110.05022