With the rising acceptance of virtual network functions (VNFs) as a replacement for traditional network functions, the optimal placement of VNFs has become a crucial task for ensuring constant performance within const...
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Named Data Networking (NDN) is a newly developing networking method that focuses on information, compared to TCP/IP, which focuses on hosts. This study proposed a solution to the growing complexity of computer network...
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The COVID-19 pandemic has drastically left the world with a profound impact that will resonate for years to come. The devastating loss of lives, the dramatic decline in economic output, and the disruption of social in...
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ISBN:
(数字)9798331527792
ISBN:
(纸本)9798331527808
The COVID-19 pandemic has drastically left the world with a profound impact that will resonate for years to come. The devastating loss of lives, the dramatic decline in economic output, and the disruption of social interactions have all contributed to a sudden shift in our global landscape. Monitoring COVID-19 symptoms has become essential in controlling the spread of the virus and preventing hospitalizations. This paper presents an innovative solution that leverages advanced wearable technology integrated with cutting-edge artificial intelligence (AI) algorithms to monitor biometric signals associated with the presence of COVID-19 and other pandemic diseases. For persistent monitoring, the system is designed to acquire biometric signals such as temperature, heart rate, and blood oxygen saturation from wearable devices, which are considered as input to the long short-term memory (LSTM) network. The model will then reconstruct the signals, process them, and predict the health status of the patient with respect to the COVID-19 pandemic. Experiments were conducted to evaluate the performance of the system using two parameters i.e. temperature and heart rates. The system’s performance was compared to a certified medical station, and both heart rate and temperature parameter tests obtained good correlation (R=0. 73 and R=0. 96 respectively). This indicates the feasibility of the proposed system in early prediction of the presence of COVID-19, representing a crucial step forward in our efforts to build a more resilient and prepared world to navigate the challenges posed by the ever-present threat of future epidemics and pandemics.
In this paper, we present a novel distributed algorithm (herein called MaxCUCL) designed to guarantee that max−consensus is reached in networks characterized by unreliable communication links (i.e., links suffering fr...
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The article the efficiency of the Microgrid network when transitioning to a transactive power system that uses control algorithms called to optimize the distribution of power between sources of distributed generation ...
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Crowdsourcing systems offer numerous advantages for acquiring data, which can contribute to the development of modern concepts such as Smart Cities. Air quality in urban areas has been identified as a crucial theme an...
Crowdsourcing systems offer numerous advantages for acquiring data, which can contribute to the development of modern concepts such as Smart Cities. Air quality in urban areas has been identified as a crucial theme and requirement, towards ideal city of the future that can be adapted upon its citizens' needs and comfort. Thus, besides the sensing infrastructure, a complementary system must be implemented in order to enable the public authority and municipality awareness over citizens' personalised and subjective input, in a cost efficient way that can be easily upscaled. In this work, we present HealthAir, an mHealth application alongside its subsystems (namely a web application and a smartwatch version), that aims to increase and complement the sensing capacity of a Smart City, with respect to the air quality-wise health of the citizens. This is achieved based on questionnaires and surveys approved by the health community, and services and features that implement a bidirectional interaction between the system and the users. Finally, users' data and air quality measurements from a third party platform are combined and presented for the case study realization and demonstration.
The primary objective of anomaly detection is to identify abnormal or unusual patterns within a dataset, where the number of normal samples typically exceeds that of abnormal samples. Due to the scarcity of labeled ab...
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The paper presents a wideband 8×8-element slot antenna array operating in the E-band. The proposed design employs a low-loss coaxial waveguide transmission line filled with air implemented using multilayer wavegu...
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