Unpacking People\u27s Understandings of Bluetooth Beacon Systems - A Location-Based IoT Technology

Bluetooth beacon technology is an emerging location-based Internet of Things (IoT) technology, designed to transform proximity-based services in various domains such as retail. Beacons are part of the IoT infrastructure, but people rarely interact with them directly and yet they could still pose privacy risks to users. However, little is known about people\u27s understandings of how beacon-based systems work. This is an important question since it can influence people\u27s perceptions, adoption, and usage of this emerging technology. Drawing from 22 semi-structured interviews, we studied people\u27s understandings of how beacon-based systems work and identified several factors that shaped their understandings or misunderstandings, such as how information flows among the components and who owns the beacons. These understandings and misunderstandings can potentially pose significant privacy risks to beacon users

Unpacking People's Understandings of Bluetooth Beacon Systems - A Location-Based IoT Technology

Bluetooth beacon technology is an emerging location-based Internet of Things (IoT) technology, designed to transform proximity-based services in various domains such as retail. Beacons are part of the IoT infrastructure, but people rarely interact with them directly and yet they could still pose privacy risks to users. However, little is known about people's understandings of how beacon-based systems work. This is an important question since it can influence people's perceptions, adoption, and usage of this emerging technology. Drawing from 22 semi-structured interviews, we studied people's understandings of how beacon-based systems work and identified several factors that shaped their understandings or misunderstandings, such as how information flows among the components and who owns the beacons. These understandings and misunderstandings can potentially pose significant privacy risks to beacon users

The Core Values of Principals in School Management under Chinese Education Reform

The values of principals in school management play a pivotal role in shaping school leadership, teacher behaviours, and student performance. However, research studies focusing on principals’ values are relatively abundant in Western countries, yet still limited in the Chinese context. To fill this gap, this paper adopts a qualitative research approach to investigate the fundamental values of Chinese principals in leading and managing primary schools within the current education reform landscape. The findings reveal that the principals in the study emphasised nine core values: equity, fairness, openness, respect, empowerment, encouragement, recognition, trust, and democracy. These values were found to contribute to a positive school climate that promoted the growth of teachers, students, and the school. The results have significant implications for policy makers and principals in China, suggesting the necessity to foster ethical and relational skills among principals and to acknowledge the invaluable contributions of teacher leaders and teachers in school development. Keywords: principals, values, school management, education reform DOI: 10.7176/JEP/14-24-09 Publication date:August 31st 202

Covid-19 Diagnosis Based on CT Images Through Deep Learning and Data Augmentation

Coronavirus disease 2019(Covid-19) has made people around the world suffer. And there are many researchers make efforts on deep learning methods based on CT imgaes, but the limitation of  this work is the lackage of the dataset, which is not easy to obtain. In this study, we try to use data augmentation to compensate this weakness. In the first part, we use traditional DenseNet-169, and the result shows that data augmentation can help improve the calculating speed and the accuracy. In the second part, we combine Self-trans and DenseNet-169, and the result shows that when doing data augmentation, many model performance metrics have been improved. In the third part, we use UNet++, which reaches accuracy of 0.8645. Apart from this, we think GAN and CNN may also make difference

Does Multimodality Help Human and Machine for Translation and Image Captioning?

This paper presents the systems developed by LIUM and CVC for the WMT16 Multimodal Machine Translation challenge. We explored various comparative methods, namely phrase-based systems and attentional recurrent neural networks models trained using monomodal or multimodal data. We also performed a human evaluation in order to estimate the usefulness of multimodal data for human machine translation and image description generation. Our systems obtained the best results for both tasks according to the automatic evaluation metrics BLEU and METEOR.Comment: 7 pages, 2 figures, v4: Small clarification in section 4 title and conten