• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.

• Korean Journal of Ecology and Environment
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• v.38 no.2 s.112
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• pp.225-236
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• 2005

The protection of public health In wastewater reclamation and reuse is one of the most important issues. Monitoring data of Escherichia coli were collected from paddy rice plots in 2003 and 2004 experiments. Five treatments were used and each one was triplicated to evaluate the changes of E. coli: surface water, biofilter effluent (secondary level), UV-disinfected water and pond treatment. Microbial risk was quantified to assess human health risk by exposure to E. coli in paddy rice plots, which were irrigated with reclaimed wastewater. Beta-Poisson model was used to estimate the microbial risk of pathogen ingestion that may occur to farmer and neighbor children. Monte-Carlo analysis (10,000 trials) was used to estimate the risk characterization of uncertainty. In the following analysis, two scenarios were related to the reduction of risk against direct ingestion and exposure times. Scenarios A and B were assumed that the risk was 1,000 and 10,000 times lower than direct ingestion.'Golfers were assumed to be 0.001 L of reclaimed water by contact with balls and their cloths. Opportunity of contact in paddy rice field with pathogens was more frequent than handing golf balls, because of agricultural activity was practiced in ponded water in paddy rice culture. As a result of microbial risk assessment using total data of experimental period, risk value of E. coli in 2003 and 2004 experiment ranged from $10^{-5}$ to $10^{-8}$ and $10^{-4}$ to $10^{-8}$, respectively. The risk values in biofilter effluent irrigation was the highest, which is $10^{-4}$ in 2003 and $10^{-5}$ in 2004 experiments with scenario A. Ranges of $10^{-6}$ to $10^{-8}$ were considered at reasonable levels of risk for communicable disease transmission from environmental exposure and the risk value above $10^{-4}$ was considered to be attributable to the risk of infection. Irrigation with UV-disinfected water in the paddy field during the agricultural Period showed significantly lower microbial risk than others, and their levels of risk value were within the range of actual paddy rice field with surface water.