Security Extension and Robust Upgrade of Smart-Watch Wi-Fi Controller Firmware

Author(s):  
Wencong Han ◽  
Quanxin Zhang ◽  
Chongzhi Gao ◽  
Jingjing Hu ◽  
Fang Yan
Keyword(s):  
Author(s):  
Ryuichi IMAI ◽  
Daisuke KAMIYA ◽  
Haruka INOUE ◽  
Shigenori TANAKA ◽  
Jun SAKURAI ◽  
...  

2021 ◽  
Vol 77 (18) ◽  
pp. 2043
Author(s):  
Osama Tariq Niazi ◽  
Issa Ismail, BS ◽  
Nachiket Patel ◽  
Jaskanwal Bisla ◽  
Mohammad Hojjati

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
M. van Doorn ◽  
A. Popma ◽  
T. van Amelsvoort ◽  
C. McEnery ◽  
J. F. Gleeson ◽  
...  

Abstract Background The onset of mental disorders typically occurs between the ages of 12 and 25, and the burden of mental health problems is the most consequential for this group. Indicated prevention interventions to target individuals with subclinical symptoms to prevent the transition to clinical levels of disorders, even leading to suicide, have shown to be effective. However, the threshold to seek help appears to be high. Digital interventions could offer a solution, especially during the Covid-19 pandemic. This implementation study will investigate the digital indicated prevention intervention ENgage YOung people Early (ENYOY), the Dutch version of the original Moderated Online Social Therapy Platform (MOST+) from Australia. In addition, the relationship between stress biomarkers, symptoms and outcome measures of youth using the platform will be investigated in this study. Methods The MOST+ platform will be adapted, translated and developed for the situation in the Netherlands in collaboration with a Youth Panel. A prospective cohort of 125 young people (16–25 years) with beginning mental health complaints will be on the platform and followed for a year, of which 10 participants will have an additional smart watch and 10 participants will be asked to provide feedback about the platform. Data will be collected at baseline and after 3, 6 and 12 months. Outcome measures are Psychological Distress assessed with the Kessler Psychological Distress Scale (K10), Social and occupational functioning (measures by the SOFAS), positive mental health indicators measured by the Positive Health Instrument, stress biomarkers with a smart-watch, website journeys of visitors, and feedback of youth about the platform. It will be a mixed-method study design, containing qualitative and quantitative measures. Discussion This trial will specifically address young people with emerging mental health complaints, and offers a new approach for treatment in the Netherlands. Considering the waiting lists in (child and adolescent)-psychiatry and the increase in suicides among youth, early low-threshold and non-stigmatizing help to support young people with emerging psychiatric symptoms is of crucial importance. Moreover, this project aims to bridge the gap between child and adolescent and adult psychiatry. Trial registration Netherlands Trial Register ID NL8966, retrospectively registered on the 19th of October 2020.


2017 ◽  
Vol 383 ◽  
pp. 166-168 ◽  
Author(s):  
Gloria Dalla-Costa ◽  
Marta Radaelli ◽  
Simona Maida ◽  
Francesca Sangalli ◽  
Bruno Colombo ◽  
...  

Proceedings ◽  
2018 ◽  
Vol 2 (19) ◽  
pp. 1267 ◽  
Author(s):  
Macarena Espinilla ◽  
Javier Medina ◽  
Chris Nugent

Many real-world applications, which are focused on addressing the needs of a human, require information pertaining to the activities being performed. The UCAmI Cup is an event held within the context of the International Conference on Ubiquitous Computing and Ambient Intelligence, where delegates are given the opportunity to use their tools and techniques to analyse a previously unseen human activity recognition dataset and to compare their results with others working in the same domain. In this paper, the human activity recognition dataset used relates to activities of daily living generated in the UJAmI Smart Lab, University of Jaén. The dataset chosen for the first edition of the UCAmI Cup represents 246 activities performed over a period of ten days carried out by a single inhabitant. The dataset includes four data sources: (i) event streams from 30 binary sensors, (ii) intelligent floor location data, (iii) proximity data between a smart watch worn by the inhabitant and 15 Bluetooth Low Energy beacons and (iv) acceleration of the smart watch. In this first edition of the UCAmI Cup, 26 participants from 10 different countries contacted the organizers to obtain the dataset.‬‬‬‬‬


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