15 research outputs found
Cyber-Syndrome: Concept, Theoretical Characterization, and Control Mechanism
The prevalence of social media and mobile computing has led to intensive user engagement in the emergent Cyber-Physical-Social-Thinking (CPST) space. However, the easy access, the lack of governance, and excessive use has generated a raft of new behaviors within CPST, which affects users' physical, social, and mental states. In this paper, we conceive the Cyber-Syndrome concept to denote the collection of cyber disorders due to excessive or problematic Cyberspace interactions based on CPST theories. Then we characterize the Cyber-Syndrome concept in terms of Maslow's theory of Needs, from which we establish an in-depth theoretical understanding of Cyber-Syndrome from its etiology, formation, symptoms, and manifestations. Finally, we propose an entropy-based Cyber-Syndrome control mechanism for its computation and management. The goal of this study is to give new insights into this rising phenomenon and offer guidance for further research and development.<br/
Task Offloading for Smart Glasses in Healthcare: Enhancing Detection of Elevated Body Temperature
Wearable devices like smart glasses have gained popularity across various
applications. However, their limited computational capabilities pose challenges
for tasks that require extensive processing, such as image and video
processing, leading to drained device batteries. To address this, offloading
such tasks to nearby powerful remote devices, such as mobile devices or remote
servers, has emerged as a promising solution. This paper focuses on analyzing
task-offloading scenarios for a healthcare monitoring application performed on
smart wearable glasses, aiming to identify the optimal conditions for
offloading. The study evaluates performance metrics including task completion
time, computing capabilities, and energy consumption under realistic
conditions. A specific use case is explored within an indoor area like an
airport, where security agents wearing smart glasses to detect elevated body
temperature in individuals, potentially indicating COVID-19. The findings
highlight the potential benefits of task offloading for wearable devices in
healthcare settings, demonstrating its practicality and relevance
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N-cadherin prevents the premature differentiation of anterior heart field progenitors in the pharyngeal mesodermal microenvironment
The cardiac progenitor cells (CPCs) in the anterior heart field (AHF) are located in the pharyngeal mesoderm (PM), where they expand, migrate and eventually differentiate into major cell types found in the heart, including cardiomyocytes. The mechanisms by which these progenitors are able to expand within the PM microenvironment without premature differentiation remain largely unknown. Through in silico data mining, genetic loss-of-function studies, and in vivo genetic rescue studies, we identified N-cadherin and interaction with canonical Wnt signals as a critical component of the microenvironment that facilitates the expansion of AHF-CPCs in the PM. CPCs in N-cadherin mutant embryos were observed to be less proliferative and undergo premature differentiation in the PM. Notably, the phenotype of N-cadherin deficiency could be partially rescued by activating Wnt signaling, suggesting a delicate functional interaction between the adhesion role of N-cadherin and Wnt signaling in the early PM microenvironment. This study suggests a new mechanism for the early renewal of AHF progenitors where N-cadherin provides additional adhesion for progenitor cells in the PM, thereby allowing Wnt paracrine signals to expand the cells without premature differentiation
Response of soil bacterial community composition and its associated geochemical parameters to rapid short-term cyclic groundwater-level oscillations: soil column experiments
Groundwater-level oscillations change geochemical conditions, carbon cycling processes and bacterial community composition, and these changes may vary vertically with depth in a soil. In this study, soil column experiments were conducted to explore variations in soil bacterial community composition and its associated geochemical parameters to rapid short-term cyclic groundwater-level oscillations driven by natural fluctuations (NF) and rainfall infiltration (RI) and the results are compared with quasi static (QS) column. Water saturation patterns in vadose and oscillated zones, and oxygen level patterns, soil total organic carbon (TOC) removal rates and soil bacterial community composition in vadose, oscillated and saturated zones were evaluated. Results showed that water saturation and oxygen level oscillated with groundwater level in NF and RI columns. TOC removal rates in RI column were the highest across vadose (~38.4%), oscillated (~35.8%) and saturated (~35.2%) zones. Deltaproteobacteria, which was significantly correlated with TOC removal (p < 0.05), exhibited relatively higher abundances in the vadose and oscillated zones of RI column than those of QS and NF columns. Soil bacterial community structure was dynamic at the class level due to water saturation, oxygen level and TOC removal. TOC removal was the driver to separate distribution of bacterial community structure in the vadose and oscillated zones of RI column from those of QS and NF columns. This study suggests that RI induced rapid short-term cyclic groundwater-level oscillations could significantly influence both soil carbon cycle and bacterial community structure in vadose and oscillated zones
Effect of Winter Temperature Increase on Prolonging Green Period of Lawn
Taking mixed lawn of Festuca elata Keng ex E. Alexeev and Poa pratensis L. as the research object, through the comparison of the electric heating, covering by non-woven fabric or electric heating and non-woven fabric treatment group with the control group, exploring the effects of winter temperature increase on prolonging the green period of lawn. The results show that: compared with the control group, different temperature increasing measures have different effects on prolonging the green period of the lawn. The test group using only electric heating or only covering the non-woven fabric was completely yellow in mid-January, which was about 10 days longer than the green period of the control group. The effect of using electric heating and non-woven fabric was the best. During the research period, the lawn of this group did not appear completely yellow. Compared with the control group, the green period was prolonged by about 53 days
Research on the Evaluation of Ecological Assets Loss in Railway Construction Project Route Selection
At present, the route selection of railway construction projects from the perspective of environmental protection fails to objectively and comprehensively reflecting environmental protection requirements. Therefore, incorporating ecological asset assessment into the route selection of railway construction projects is conducive to promoting environmental protection to participate in railway route selection and improve railway route selection. This article summarizes the current status of railway route selection, identifies the existing problems in railway environmental route selection, and combines the research progress of ecological asset assessment, and proposes the assessment content and evaluation index system of ecological asset assessment in railway environmental route selection, and points out the future research prospects
A Survey of Data Semantization in Internet of Things
With the development of Internet of Things (IoT), more and more sensors, actuators and mobile devices have been deployed into our daily lives. The result is that tremendous data are produced and it is urgent to dig out hidden information behind these volumous data. However, IoT data generated by multi-modal sensors or devices show great differences in formats, domains and types, which poses challenges for machines to process and understand. Therefore, adding semantics to Internet of Things becomes an overwhelming tendency. This paper provides a systematic review of data semantization in IoT, including its backgrounds, processing flows, prevalent techniques, applications, existing challenges and open issues. It surveys development status of adding semantics to IoT data, mainly referring to sensor data and points out current issues and challenges that are worth further study