Quantization of Transmission Parameters in Stereo Linear Predictive Systems

2006 ◽  
Author(s):  
A. Biswas ◽  
A.C. den Brinker
Keyword(s):  
Transmission Parameters

scholarly journals Simulation of leaf curl disease dynamics in chili for strategic management options

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Buddhadeb Roy ◽  
Shailja Dubey ◽  
Amalendu Ghosh ◽  
Shalu Misra Shukla ◽  
Bikash Mandal ◽  
...  
Keyword(s):  
Disease Risk ◽  
Virus Transmission ◽  
Host Population ◽  
High Rate ◽  
Disease Dynamics ◽  
Model Framework ◽  
Management Options ◽  
Transmission Parameters ◽  
Vector Population ◽  
Leaf Curl

AbstractLeaf curl, a whitefly-borne begomovirus disease, is the cause of frequent epidemic in chili. In the present study, transmission parameters involved in tripartite interaction are estimated to simulate disease dynamics in a population dynamics model framework. Epidemic is characterized by a rapid conversion rate of healthy host population into infectious type. Infection rate as basic reproduction number, R0 = 13.54, has indicated a high rate of virus transmission. Equilibrium population of infectious host and viruliferous vector are observed to be sensitive to the immigration parameter. A small increase in immigration rate of viruliferous vector increased the population of both infectious host and viruliferous vector. Migrant viruliferous vectors, acquisition, and transmission rates as major parameters in the model indicate leaf curl epidemic is predominantly a vector -mediated process. Based on underlying principles of temperature influence on vector population abundance and transmission parameters, spatio-temporal pattern of disease risk predicted is noted to correspond with leaf curl distribution pattern in India. Temperature in the range of 15–35 °C plays an important role in epidemic as both vector population and virus transmission are influenced by temperature. Assessment of leaf curl dynamics would be a useful guide to crop planning and evolution of efficient management strategies.

scholarly journals Carbapenem-resistant Enterobacteriaceae carriage risk for parameterization of a regional healthcare network agent-based model

2020 ◽  
Vol 41 (S1) ◽  
pp. s148-s149
Author(s):  
Sarah Rhea ◽  
Lei Li ◽  
Pooja Iyer ◽  
Lauren DiBiase ◽  
Kasey Jones ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Length Of Stay ◽  
Intensive Care Unit Stay ◽  
Agent Based ◽  
Healthcare Network ◽  
Transmission Parameters ◽  
Carbapenem Resistant ◽  
Comorbidity Index ◽  
Systemic Antibiotics

Background: Carbapenem-resistant Enterobacteriaceae (CRE) are increasingly common in the United States and have the potential to spread widely across healthcare networks. Only a fraction of patients with CRE carriage (ie, infection or colonization) are identified by clinical cultures. Interventions to reduce CRE transmission can be explored with agent-based models (ABMs) comprised of unique agents (eg, patients) represented by a synthetic population or model-generated representation of the population. We used electronic health record data to determine CRE carriage risk, and we discuss how these results can inform CRE transmission parameters for hospitalized agents in a regional healthcare network ABM. Methods: We reviewed the laboratory data of patients admitted during July 1, 2016−June 30, 2017, to any of 7 short-term acute-care hospitals of a regional healthcare network in North Carolina (N = 118,022 admissions) to find clinically detected cases of CRE carriage. A case was defined as the first occurrence of Enterobacter spp, Escherichia coli, or Klebsiella spp resistant to any carbapenem isolated from a clinical specimen in an admitted patient. We used Poisson regression to estimate clinically detected CRE carriage risk according to variables common to data from both the electronic health records and the ABM synthetic population, including patient demographics, systemic antibiotic administration, intensive care unit stay, comorbidities, length of stay, and admitting hospital size. Results: We identified 58 (0.05%) cases of CRE carriage among all admissions. Among these cases, 30 (52%) were ≥65 years of age and 37 (64%) were female. During their admission, 47 cases (81%) were administered systemic antibiotics and 18 cases (31%) had an intensive care unit stay. Patients administered systemic antibiotics and those with an intensive care unit stay had CRE carriage risk 6.5 times (95% CI, 3.4–12.5) and 4.9 times (95% CI, 2.8–8.5) higher, respectively, than patients without these exposures (Fig. 1). Patients ≥50 years of age and those with a higher Elixhauser comorbidity index score and with longer length of stay also had increased CRE carriage risk. Conclusions: Among admissions in our dataset, CRE carriage risk was associated with systemic antibiotic exposure, intensive care unit stay, higher Elixhauser comorbidity index score, and longer length of stay. We will use these risk estimates in the ABM to inform agents’ CRE carriage status upon hospital admission and the CRE transmission parameters for short-term acute-care hospitals. We will explore CRE transmission interventions in the parameterized regional healthcare network ABM and assess the impact of CRE carriage underestimation.Funding: This work was supported by Centers for Disease Control and Prevention (CDC) Cooperative Agreement number U01CK000527. The conclusions, findings, and opinions expressed do not necessarily reflect the official position of CDC.Disclosures: None

Theoretical Study on the Influence of Transmission Parameters on the Transmission Performance of Magnetic Resonance Wireless Power Transmission Systems

2014 ◽  
Vol 926-930 ◽  
pp. 434-439
Author(s):  
Chang Sheng Li ◽  
Juan Cao ◽  
He Zhang
Keyword(s):  
Magnetic Resonance ◽  
High Efficiency ◽  
Power Transmission ◽  
Maximum Efficiency ◽  
System Quality ◽  
Wireless Power ◽  
Transmission Performance ◽  
Wireless Power Transmission ◽  
Transmission Systems ◽  
Transmission Parameters

Magnetic resonance wireless power transmission technology is based on the phenomenon of resonant coupling to realize non-contact power transmission via near magnetic field. Based on the mutual coupling model of resonance system, the influence laws of system transmission parameters, such as coil coupling coefficients, load resistance, etc., on the transmission performance are theoretically studied in this paper. The research results shows that the power high-efficiency and high-quality transmission does not depend on the large coil loop coupling coefficient and the working frequencies of maximum power and maximum efficiency transmission do not coincide at most condition. Transmission systems with a high resonance frequency can produce high power and efficiency transmission over short distances. In addition, by increasing the coil diameter or wire diameter can improve the system quality factor, and optimize the energy transmission performance.

scholarly journals Land use change alters malaria transmission parameters by modifying temperature in a highland area of Uganda

2000 ◽  
Vol 5 (4) ◽  
pp. 263-274 ◽  
Author(s):  
Kim A. Lindblade ◽  
Edward D. Walker ◽  
Ambrose W. Onapa ◽  
Justus Katungu ◽  
Mark L. Wilson
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Malaria Transmission ◽  
Highland Area ◽  
Transmission Parameters

МЕТОД ГЛУБОКОГО ОБУЧЕНИЯ С ПОДКРЕПЛЕНИЕМ ДЛЯ СИСТЕМ ИНТЕРНЕТА ВЕЩЕЙ НА БАЗЕ ТЕХНОЛОГИИ LORA С ОГРАНИЧЕННЫМИ РЕСУРСАМИ И ПОДДЕРЖКОЙ QoS

2021 ◽  
Author(s):  
 M.S. MUTHANNA ◽  
A.S. MUTHANNA ◽  
 A.S. BORODIN
Keyword(s):  
Data Transmission ◽  
Environmental Parameters ◽  
Code Rate ◽  
Frame Structure ◽  
Signal Quality ◽  
High Quality ◽  
Spreading Factor ◽  
Transmission Parameters ◽  
Factor Code

Achieving high Quality of Service (QoS) remains a challenge for LoRa technology. However, high QoS can be achieved via optimizing the transmission policy parameters such as bandwidth and code rate. Existing approaches do not provide an opportunity to optimize the LoRa networks' data transmission parameters. The article proposes transmission policy enforcementfor QoS-aware LoRanetworks.The QoSparameter ranking is implemented for IoT nodes where priority and nonpriority information is identified by the new field of LoRa frame structure(QRank).The optimaltransmissionpolicyenforcement uses fast deep reinforcement learning that utilizes the environmental parameters including QRank, signal quality, and signal-to-interference-plus-noise-ratio. The transmission policy is optimized for spreading factor, code rate, bandwidth, and carrier frequency. Performance evaluation is implemented using an NS3.26 LoRaWAN module. The performance is examined for various metrics such as delay and throughput. Достижение высокого качества обслуживания (QoS) по-прежнему остается достаточно сложной задачей для технологии LoRa. В принципе высокий уровень QoS может быть достигнут за счет оптимизации параметров передачи, например, пропускной способности и скорости передачи информации в сети. Известные на сегодняшний день решения не дают возможности оптимизировать параметры передачи данных для сетей LoRa. В статье предложен эффективный метод передачи данных, обеспечивающий требования по QoS при использовании технологии LoRa. Ранжирование параметров QoS для узлов интернета вещей определяется новым полем структуры фрейма LoRa (QRank) для приоритетной и неприоритетной информации. Для обеспечения эффективной передачи применяется быстрое глубокое обучение с подкреплением, для которого используются как параметры качества обслуживания, так и отношение сигнал/шум. Метод передачи оптимизирован с учетом коэффициента распространения, скорости передачи данных, полосы пропускания и несущей частоты. Оценка производительности при применении предложенного метода проведена с использованием модуля LoRaWAN в пакете имитационного моделирования NS3.26. Производительность оценивается на основе параметров задержки и пропускной способности.

scholarly journals Transmission dynamics of lumpy skin disease in Ethiopia

2017 ◽  
Vol 145 (13) ◽  
pp. 2856-2863 ◽  
Author(s):  
W. MOLLA ◽  
K. FRANKENA ◽  
M. C. M. DE JONG
Keyword(s):  
Production System ◽  
Skin Disease ◽  
Transmission Rate ◽  
Severe Disease ◽  
Livestock Production ◽  
Sir Epidemic Model ◽  
Reproduction Ratio ◽  
Lumpy Skin Disease ◽  
Transmission Parameters ◽  
Intensive Production

SUMMARYLumpy skin disease (LSD) is a severe disease of cattle caused by a Capripoxvirus and often caused epidemics in Ethiopia and many other countries. This study was undertaken to quantify the transmission between animals and to estimate the infection reproduction ratio in a predominantly mixed crop–livestock system and in intensive commercial herd types. The transmission parameters were based on a susceptible-infectious-recovered (SIR) epidemic model with environmental transmission and estimated using generalized linear models. The transmission parameters were estimated using a survival rate of infectious virus in the environment equal to 0·325 per day, a value based on the best-fitting statistical model. The transmission rate parameter between animals was 0·072 (95% CI 0·068–0·076) per day in the crop–livestock production system, whereas this transmission rate in intensive production system was 0·076 (95% CI 0·068–0·085) per day. The reproduction ratio (R) of LSD between animals in the crop–livestock production system was 1·07, whereas it was 1·09 between animals in the intensive production system. The calculated R provides a baseline against which various control options can be assessed for efficacy.

scholarly journals A stochastic metapopulation state-space approach to modeling and estimating COVID-19 spread

2021 ◽  
Vol 18 (6) ◽  
pp. 7685-7710
Author(s):  
Yukun Tan ◽  
◽  
Durward Cator III ◽  
Martial Ndeffo-Mbah ◽  
Ulisses Braga-Neto ◽  
...  
Keyword(s):  
State Space ◽  
State Space Model ◽  
Synthetic Data ◽  
Public Health Intervention ◽  
Disease Outbreaks ◽  
Real Data ◽  
Epidemiological Data ◽  
Transmission Parameters ◽  
Intervention Measures ◽  
Spatio Temporal

<abstract><p>Mathematical models are widely recognized as an important tool for analyzing and understanding the dynamics of infectious disease outbreaks, predict their future trends, and evaluate public health intervention measures for disease control and elimination. We propose a novel stochastic metapopulation state-space model for COVID-19 transmission, which is based on a discrete-time spatio-temporal susceptible, exposed, infected, recovered, and deceased (SEIRD) model. The proposed framework allows the hidden SEIRD states and unknown transmission parameters to be estimated from noisy, incomplete time series of reported epidemiological data, by application of unscented Kalman filtering (UKF), maximum-likelihood adaptive filtering, and metaheuristic optimization. Experiments using both synthetic data and real data from the Fall 2020 COVID-19 wave in the state of Texas demonstrate the effectiveness of the proposed model.</p></abstract>

scholarly journals The Spectrum Sensing and Path Optimization Techniques in Cognitive Radio Networks

2019 ◽  
Vol 8 (10) ◽  
pp. 2406-2411
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Radio Networks ◽  
Optimization Techniques ◽  
Path Optimization ◽  
System Innovation ◽  
Transmission Parameters ◽  
The Earth ◽  
Intellectual System

Cognitive Radio (CR) is a versatile, insightful radio and system innovation that can naturally recognize accessible directs in a remote range and change transmission parameters empowering more interchanges to run simultaneously and furthermore improve radio working conduct. The primary thought of the intellectual system is to give the range band to the unlicensed clients without making any damage to the earth. By utilizing the recurrence range band, we came to utilization of these intellectual systems. Right off the bat, we have to frame the system through any methodologies .we are utilizing optimization Mechanisms for path identification in cognitive Radio.

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