scholarly journals A Joint Power, Delay and Rate Optimization Model for Secondary Users in Cognitive Radio Sensor Networks

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4907 ◽  
Author(s):  
Bernard Ssajjabbi Muwonge ◽  
Tingrui Pei ◽  
Julianne Sansa Otim ◽  
Fred Mayambala

To maximize the limited spectrum among primary users and cognitive Internet of Things (IoT) users as we save the limited power and energy resources available, there is a need to optimize network resources. Whereas it is quite complex to study the impact of transmission rate, transmission power or transmission delay alone, the complexity is aggravated by the simultaneous consideration of all these three variables jointly in addition to a channel selection variable, since it creates a non-convex problem. Our objective is to jointly optimize the three major variables; transmission power, rate and delay under constraints of Bit Error Rate (BER), interference and other channel limitations. We analyze how total power, rate and delay vary with packet size, network size, BER and interference. The resulting problem is solved using a branch-and-cut polyhedral approach. For simulation of results, we use MATLAB together with the state-of-the-art BARON software. It is observed that an increase in packet size generally leads to an increase in total rate, total power and total transmission delay. It is also observed that increasing the number of secondary users on the channel generally leads to an increased power, delay and rate.

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xi Huo ◽  
Jing Chen ◽  
Shigui Ruan

Abstract Background The COVID-19 outbreak in Wuhan started in December 2019 and was under control by the end of March 2020 with a total of 50,006 confirmed cases by the implementation of a series of nonpharmaceutical interventions (NPIs) including unprecedented lockdown of the city. This study analyzes the complete outbreak data from Wuhan, assesses the impact of these public health interventions, and estimates the asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan. Methods By taking different stages of the outbreak into account, we developed a time-dependent compartmental model to describe the dynamics of disease transmission and case detection and reporting. Model coefficients were parameterized by using the reported cases and following key events and escalated control strategies. Then the model was used to calibrate the complete outbreak data by using the Monte Carlo Markov Chain (MCMC) method. Finally we used the model to estimate asymptomatic and undetected cases and approximate the overall antibody prevalence level. Results We found that the transmission rate between Jan 24 and Feb 1, 2020, was twice as large as that before the lockdown on Jan 23 and 67.6% (95% CI [0.584,0.759]) of detectable infections occurred during this period. Based on the reported estimates that around 20% of infections were asymptomatic and their transmission ability was about 70% of symptomatic ones, we estimated that there were about 14,448 asymptomatic and undetected cases (95% CI [12,364,23,254]), which yields an estimate of a total of 64,454 infected cases (95% CI [62,370,73,260]), and the overall antibody prevalence level in the population of Wuhan was 0.745% (95% CI [0.693%,0.814%]) by March 31, 2020. Conclusions We conclude that the control of the COVID-19 outbreak in Wuhan was achieved via the enforcement of a combination of multiple NPIs: the lockdown on Jan 23, the stay-at-home order on Feb 2, the massive isolation of all symptomatic individuals via newly constructed special shelter hospitals on Feb 6, and the large scale screening process on Feb 18. Our results indicate that the population in Wuhan is far away from establishing herd immunity and provide insights for other affected countries and regions in designing control strategies and planing vaccination programs.


Author(s):  
Bernd Brüggenjürgen ◽  
Hans-Peter Stricker ◽  
Lilian Krist ◽  
Miriam Ortiz ◽  
Thomas Reinhold ◽  
...  

Abstract Aim To use a Delphi-panel-based assessment of the effectiveness of different non-pharmaceutical interventions (NPI) in order to retrospectively approximate and to prospectively predict the SARS-CoV-2 pandemic progression via a SEIR model (susceptible, exposed, infectious, removed). Methods We applied an evidence-educated Delphi-panel approach to elicit the impact of NPIs on the SARS-CoV-2 transmission rate R0 in Germany. Effectiveness was defined as the product of efficacy and compliance. A discrete, deterministic SEIR model with time step of 1 day, a latency period of 1.8 days, duration of infectiousness of 5 days, and a share of the total population of 15% assumed to be protected by immunity was developed in order to estimate the impact of selected NPI measures on the course of the pandemic. The model was populated with the Delphi-panel results and varied in sensitivity analyses. Results Efficacy and compliance estimates for the three most effective NPIs were as follows: test and isolate 49% (efficacy)/78% (compliance), keeping distance 42%/74%, personal protection masks (cloth masks or other face masks) 33%/79%. Applying all NPI effectiveness estimates to the SEIR model resulted in a valid replication of reported occurrence of the German SARS-CoV-2 pandemic. A combination of four NPIs at consented compliance rates might curb the CoViD-19 pandemic. Conclusion Employing an evidence-educated Delphi-panel approach can support SARS-CoV-2 modelling. Future curbing scenarios require a combination of NPIs. A Delphi-panel-based NPI assessment and modelling might support public health policy decision making by informing sequence and number of needed public health measures.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wilfredo Angulo ◽  
José M. Ramírez ◽  
Dany De Cecchis ◽  
Juan Primera ◽  
Henry Pacheco ◽  
...  

AbstractCOVID-19 is a highly infectious disease that emerged in China at the end of 2019. The COVID-19 pandemic is the first known pandemic caused by a coronavirus, namely, the new and emerging SARS-CoV-2 coronavirus. In the present work, we present simulations of the initial outbreak of this new coronavirus using a modified transmission rate SEIR model that takes into account the impact of government actions and the perception of risk by individuals in reaction to the proportion of fatal cases. The parameters related to these effects were fitted to the number of infected cases in the 33 provinces of China. The data for Hubei Province, the probable site of origin of the current pandemic, were considered as a particular case for the simulation and showed that the theoretical model reproduces the behavior of the data, thus indicating the importance of combining government actions and individual risk perceptions when the proportion of fatal cases is greater than $$4\%$$ 4 % . The results show that the adjusted model reproduces the behavior of the data quite well for some provinces, suggesting that the spread of the disease differs when different actions are evaluated. The proposed model could help to predict outbreaks of viruses with a biological and molecular structure similar to that of SARS-CoV-2.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Abu Quwsar Ohi ◽  
M. F. Mridha ◽  
Muhammad Mostafa Monowar ◽  
Md. Abdul Hamid

AbstractPandemic defines the global outbreak of a disease having a high transmission rate. The impact of a pandemic situation can be lessened by restricting the movement of the mass. However, one of its concomitant circumstances is an economic crisis. In this article, we demonstrate what actions an agent (trained using reinforcement learning) may take in different possible scenarios of a pandemic depending on the spread of disease and economic factors. To train the agent, we design a virtual pandemic scenario closely related to the present COVID-19 crisis. Then, we apply reinforcement learning, a branch of artificial intelligence, that deals with how an individual (human/machine) should interact on an environment (real/virtual) to achieve the cherished goal. Finally, we demonstrate what optimal actions the agent perform to reduce the spread of disease while considering the economic factors. In our experiment, we let the agent find an optimal solution without providing any prior knowledge. After training, we observed that the agent places a long length lockdown to reduce the first surge of a disease. Furthermore, the agent places a combination of cyclic lockdowns and short length lockdowns to halt the resurgence of the disease. Analyzing the agent’s performed actions, we discover that the agent decides movement restrictions not only based on the number of the infectious population but also considering the reproduction rate of the disease. The estimation and policy of the agent may improve the human-strategy of placing lockdown so that an economic crisis may be avoided while mitigating an infectious disease.


2017 ◽  
Vol 39 (1) ◽  
Author(s):  
Mehtab Singh

AbstractOptical wireless communication (OWC) systems also known as Free space optics (FSO) are capable of providing high channel bandwidth, high data transmission rates, low power consumption, and high security. OWC links are being considered in different applications such as inter-satellite links, terrestrial links, and inter-aircraft communication links. This paper investigates the impact of different system parameters such as transmission power level, operating wavelength, transmitter pointing error angle, bit transmission rate, atmospheric attenuation, antenna aperture diameter, geometric losses, the responsivity of the photodetector, and link range on the performance of inter-aircraft optical wireless communication link.


Photonics ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 108
Author(s):  
Dong Qin ◽  
Yuhao Wang ◽  
Tianqing Zhou

This paper investigates the impact of cooperative spectrum sharing policy on the performance of hybrid radio frequency and free space optical wireless communication networks, where primary users and secondary users develop a band of the same spectrum resource. The radio frequency links obey Nakagami-m distribution with arbitrary fading parameter m, while the free space optical link follows gamma-gamma distributed atmospheric turbulence with nonzero pointing error. Because the secondary users access the spectrum band without payment, their behavior needs to be restricted. Specifically, the power of the secondary users is dominated by the tolerable threshold of the primary users. Considering both heterodyne and intensity modulation/direct detection strategies in optical receiver, the performance of optical relaying networks is completely different from that of traditional networks. With the help of bivariable Fox’s H function, new expressions for cumulative distribution function of equivalent signal to noise ratio at destination, probability density function, outage probability, ergodic capacity and symbol error probability are built in closed forms.


Circulation ◽  
2012 ◽  
Vol 125 (suppl_10) ◽  
Author(s):  
Amanda C Costa ◽  
Ana Gabriela C Silva ◽  
Cibele T Ribeiro ◽  
Guilherme A Fregonezi ◽  
Fernando A Dias

Background: Stress is one of the risk factors for cardiovascular disease and decreased heart rate variability is associated to increased mortality in some cardiac diseases. The aim of the study was to assess the impact of perceived stress on cardiac autonomic regulation in young healthy volunteers. Methods: 35 young healthy volunteers (19 to 29 years old, 6 men) from a Brazilian population were assessed for perceived stress by the translated and validated Perceived Stress Scale (PSS, 14 questions) and had the R-R intervals recorded at rest on supine position (POLAR RS800CX) and analyzed (5 minutes, Kubius HRV software) by Fast-Fourier Transform for quantification of Heart Rate Variability (HRV). Results: Average data (±SD) for age, heart rate, BMI, waist circumference and percentage of body fat (%BF) were: 21.3±2.7 years; 65.5±7.9 bpm; 22.3±1.9 Kg/m 2 ; 76.0±6.1 cm and 32.1±6.6%; respectively. The mean score for the PSS-14 was 23.5±7.2 and for the HRV parameter as follow: SSDN=54.8±21.2ms; rMSSD=55.9±32.2ms; low-frequency (LF)= 794.8±579.7ms 2 ; High-frequency (HF)= 1508.0±1783.0 ms 2 ; LF(n.u.)= 41.1±16.2; HF(n.u.)= 58.9±16.2; LF/HF=0.89±0.80 and Total power (TP)= 3151±2570ms 2 . Spearman nonparametric correlation was calculated and there was a significant correlation of PSS-14 scores and LF (ms 2 ) (r=−0.343; p= 0.044). Other HRV variables did not shown significant correlation but also had negative values for Spearman r (TP r=−0.265, p=0.124; HF r=−0.158; SSDN r=−0.207; rMSSD r=−0.243, p=0.160). LF/HF and LF(n.u.) did not correlate to PSS-14 having Spearman r very close to zero (LF/HF r=−0.007, p=0.969; LF(n.u.) r=−0.005, p=0.976). No correlation was found for HRV parameters and BMI and there was a trend for statistical correlation of %BF and LF (ms 2 ) (r=−0.309, p=0.071). Conclusions: These data demonstrate a possible association of perceived stress level and HRV at rest. Changes in LF can be a consequence of both sympathetic and parasympathetic activity, however, analyzing the other variables HF, TP, SSDN and rMSSD (all negative Spearman r) and due to the lack of changes in LF/HF ratio and LF(n.u.) we interpret that increased stress may be associated to decrease in overall heart rate variability. These changes were seen in healthy individuals and may point out an important mechanism in cardiovascular disease development.


2010 ◽  
Vol 26 (3) ◽  
pp. 288-293 ◽  
Author(s):  
Americo Cicchetti ◽  
Matteo Ruggeri ◽  
Lara Gitto ◽  
Francesco Saverio Mennini

Objectives: Influenza (vernacular name, flu) is a viral infection that causes a high consumption of resources. Several studies have been carried out to provide an economic evaluation of the vaccination programs against influenza. Nevertheless, there is still a lack of evidence about the dynamic effects resulting from the reduction of the transmission power. This study considers the impact on contagiousness of alternative strategies against influenza in people aged 50–64 in Italy, France, Germany, and Spain.Methods: By using the Influsim 2.0 dynamic model, we have determined the social benefits of different coverage levels in every country compared with the ones currently recommended. We have subsequently performed a Budget Impact Analysis to determine whether the currently recommended coverage results from an optimal budget allocation. A probabilistic sensitivity analysis was also conducted.Results: We found that in Germany, the optimal coverage level is 38.5 percent, in France 32.4 percent, in Italy 32.75 percent, and 28.3 percent in Spain. By extending the coverage level, social saving tends to increase up to 100 percent for France and Italy and up to 80 percent for Germany and Spain.Conclusions: Decision makers should allocate the budget for vaccination against influenza consistently with the estimation of the optimal coverage level and with the dynamic effects resulting from the reduction of the transmission power.


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