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Eleni Vlachou, Aristeidis Karras, Christos Karras, Leonidas Theodorakopoulos, Constantinos Halkiopoulos and Spyros Sioutas
In this work, we present a Distributed Bayesian Inference Classifier for Large-Scale Systems, where we assess its performance and scalability on distributed environments such as PySpark. The presented classifier consistently showcases efficient inference...
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Feng Zhou, Shijing Hu, Xin Du, Xiaoli Wan and Jie Wu
In the current field of disease risk prediction research, there are many methods of using servers for centralized computing to train and infer prediction models. However, this centralized computing method increases storage space, the load on network band...
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Wenbin Li, Hakim Hacid, Ebtesam Almazrouei and Merouane Debbah
The union of Edge Computing (EC) and Artificial Intelligence (AI) has brought forward the Edge AI concept to provide intelligent solutions close to the end-user environment, for privacy preservation, low latency to real-time performance, and resource opt...
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Zhaoyan Wu, Hao Li and Peng Yue
Recent developments in Web Service and Semantic Web technologies have shown great promise for the automatic chaining of geographic information services (GIService), which can derive user-specific information and knowledge from large volumes of data in th...
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Da-In Kim, Sook-Jin Jang and Taewon Kim
Ghost crabs, as a species of the Ocypode within the subfamily Ocypodinae, are distributed in the upper intertidal zone worldwide and are ecologically remarkable. They play an important role in the energy circulation in the intertidal zone and are used as...
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Zacharias Anastasakis, Terpsichori-Helen Velivassaki, Artemis Voulkidis, Stavroula Bourou, Konstantinos Psychogyios, Dimitrios Skias and Theodore Zahariadis
Federated Learning is identified as a reliable technique for distributed training of ML models. Specifically, a set of dispersed nodes may collaborate through a federation in producing a jointly trained ML model without disclosing their data to each othe...
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Uzair Bhatti and Noralfishah Sulaiman
The purpose of this paper is to explore the impact of ESG sustainability practices (i.e., Environmental, Social, Governance/economic) on share performance. Moreover, the objective of the study is to investigate the sustainability practices with mediation...
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Mohammad Shahbazi, Kamyar Mohammadi, Sayed M. Derakhshani and Peter W. G. Groot Koerkamp
Laying hen activities in modern intensive housing systems can dramatically influence the policies needed for the optimal management of such systems. Intermittent monitoring of different behaviors during daytime cannot provide a good overview, since daily...
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Jin Cao, Bo Li, Mengni Fan and Huiyu Liu
Deep neural network-based computer vision applications have exploded and are widely used in intelligent services for IoT devices. Due to the computationally intensive nature of DNNs, the deployment and execution of intelligent applications in smart scena...
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Jun Na, Handuo Zhang, Jiaxin Lian and Bin Zhang
To fully unleash the potential of edge devices, it is popular to cut a neural network into multiple pieces and distribute them among available edge devices to perform inference cooperatively. Up to now, the problem of partitioning a deep neural network (...
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