Results 1 to 10 of about 1,147,770 (164)

Wireless Machine-to-Machine Networks [PDF]

International Journal of Distributed Sensor Networks, 2012
1 School of Electronics and Applied Science, Aston University, Birmingham B4 7ET, UK 2Simula Research Laboratory, Fornebu, 1325 Lysaker, Norway 3Telecommunications Research Laboratory, Toshiba Research Europe Ltd., Bristol BS1 4ND, UK 4Department of Engineering Science, National Cheng Kung University, Tainan City 70101, Taiwan 5School of Electronic and
Jianhua He, Yan Zhang, Zhong Fan, Hsiao-Hwa Chen, Lin Bai   +4 more
doaj   +4 more sources

Wireless Machine-to-Machine Networks 2013 [PDF]

International Journal of Distributed Sensor Networks, 2014
Editorial
Jianhua He, Yan Zhang, Zhong Fan, Hsiao-Hwa Chen, Lin Bai   +4 more
doaj   +3 more sources

Nutritional Status and Body Composition in Wilson Disease: A Cross-Sectional Study From China

Frontiers in Nutrition, 2021
Background: Abnormal nutritional status is frequently seen in patients with chronic diseases. To date, no study has investigated the detailed characteristics of abnormal nutritional status among Wilson's disease (WD) patients in the Chinese cohort.
Hao Geng, Hao Geng, Hao Geng, Shijing Wang, Yan Jin, Nan Cheng, Bin Song, Shan Shu, Bo Li, Yongsheng Han, Yongzhu Han, Lishen Gao, Lishen Gao, Zenghui Ding, Zenghui Ding, Yang Xu, Yang Xu, Xun Wang, Zuchang Ma, Zuchang Ma, Yining Sun, Yining Sun   +21 more
doaj   +1 more source

Genetically Optimized UFLANN for Uncovering Clusters

IEEE Access, 2023
In this work, we present a novel clustering approach which is inheriting the best characteristics of Unsupervised Functional Link Artificial Neural Network (UFLANN) and Genetic Algorithms (GAs) for uncovering clusters embedded in dataset represented ...
Himanshu Dutta, Saurabh Bilgaiyan, Bhabani Shankar Prasad Mishra, Satchidananda Dehuri, Ashish Ghosh   +4 more
doaj   +1 more source

Self-synchronization of Nonidentical Machines in Machine-to-Machine Systems

2013 IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems, 2013
The notion of common time is very important information in distributed systems (e.g., for maintaining the consistency of distributed data). Namely, due to the lack of global time and imperfections (e.g., skew) of physical clocks, in order to agree on common time, distributed nodes have to synchronize themselves.
Bojić, Iva, Kušek, Mario
openaire   +4 more sources

A Layered Middleware for OT/IT Convergence to Empower Industry 5.0 Applications

Sensors, 2021
We are still in the midst of Industry 4.0 (I4.0), with more manufacturing lines being labeled as smart thanks to the integration of advanced ICT in Cyber–Physical Systems (CPS). While I4.0 aims to provision cognitive CPS systems, the nascent Industry 5.0
Lorenzo Patera, Andrea Garbugli, Armir Bujari, Domenico Scotece, Antonio Corradi   +4 more
doaj   +1 more source

A ML-AI ENABLED ENSEMBLE MODEL FOR PREDICTING AGRICULTURAL YIELD

Cogent Food & Agriculture, 2022
Simplistic linear methods for predicting crop yield leave out important factors like climate, rainfall, soil, irrigation, and land characteristics.
Seeboli Ghosh Kundu, Anupam Ghosh, Avisek Kundu, Girish G P   +3 more
doaj   +1 more source

GPT-NAS: Neural Architecture Search Meets Generative Pre-Trained Transformer Model

Big Data Mining and Analytics
The pursuit of optimal neural network architectures is foundational to the progression of Neural Architecture Search (NAS). However, the existing NAS methods suffer from the following problem using traditional search strategies, i.e., when facing a large
Caiyang Yu, Xianggen Liu, Yifan Wang, Yun Liu, Wentao Feng, Xiong Deng, Chenwei Tang, Jiancheng Lv   +7 more
doaj   +1 more source

A Study on Tooth Wear Mechanisms During the Bandsawing of Cr12MoV with a Bimetal Bandsaw Blade

Crystals
Bandsaw blades are typical band-shaped cutting tools that are characterized by their low stiffness and micro-level cutting depth, resulting in distinct wear mechanisms compared to rigid cutting tools.
Yuzhen Jia, Jigang Wu, Yuqiang Chen, Bing Chen, Guoyue Liu, Zhiyong Ouyang   +5 more
doaj   +1 more source

Enhancing medical diagnosis on chest X-rays: knowledge distillation from self-supervised based model to compressed student model

Discover Computing
Deep learning and self-supervised learning techniques have advanced, making it possible to diagnose medical images more accurately. Our goal in this work is to increase the accuracy of medical diagnosis using chest X-rays by utilising information ...
Jaydeep Kishore, Akshita Jain, K. Krishna Koushika, Pawan Kumar Mishra, Shekhar Karanwal, Surendra Solanki   +5 more
doaj   +1 more source