{"title":"Face recognition for smart attendance system using deep learning","authors":"Gede GALUH PUTRA WARMAN, P. Kusuma","doi":"10.28919/cmbn/7872","DOIUrl":"https://doi.org/10.28919/cmbn/7872","url":null,"abstract":",","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69238725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
. We study a smoking dynamical model with two types of smokers: beginners and heavy smokers. The qualitative behavior of the model, such as the stability of the equilibrium points and the basic reproduction number, is investigated. We show some simulations to validate the analytical findings, such as solution dynamics at different time scales and phase portraits of solutions with varying initial conditions. We also present a normalized sensitivity analysis of the basic reproduction number to discover which parameter has the most impact on smoking transmission, and perform a time-dependent sensitivity analysis of parameters to examine their impact on population dynamics.
{"title":"Dynamic model of smokers and its sensitivity analysis","authors":"Moch. Fandi Ansori, R. Herdiana","doi":"10.28919/cmbn/7947","DOIUrl":"https://doi.org/10.28919/cmbn/7947","url":null,"abstract":". We study a smoking dynamical model with two types of smokers: beginners and heavy smokers. The qualitative behavior of the model, such as the stability of the equilibrium points and the basic reproduction number, is investigated. We show some simulations to validate the analytical findings, such as solution dynamics at different time scales and phase portraits of solutions with varying initial conditions. We also present a normalized sensitivity analysis of the basic reproduction number to discover which parameter has the most impact on smoking transmission, and perform a time-dependent sensitivity analysis of parameters to examine their impact on population dynamics.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69241161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The insurance plan depends on the compartment model to the risk factors for the cost of health care for infectious diseases","authors":"Haposan Sirait, Nursanti Anggriani","doi":"10.28919/cmbn/7948","DOIUrl":"https://doi.org/10.28919/cmbn/7948","url":null,"abstract":",","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69242027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Francisco Calvin, Arnel Ferano, Jonathan Christian Setyono, Ardivo Virsa Siswanto, N. Dominic, B. Pardamean
. A single Nucleotide Polymorphism (SNP) array is the largest variation of genetic information to detect specific traits in organisms. SNP is located in a specific locus of DNA sequences. To the day this study was conducted, the representation of SNPs for machine learning models is still questionable. Based on the previous works, we proposed a comparative study of distributed representation methods against SNPs data. This study used 1,232 SNPs from the genomic data of 687 Indonesian rice samples collected from four distinct rice fields. The SNP data used was converted into an encoded format. Entity embedding (Embedder) and several comparative models, i.e., Node2Vec, Struc2Vec, and LINE, were chosen to predict the rice yield of the SNP data. The entity embedding using Embedder outperformed the comparative methods used in this study, namely Node2Vec, Struc2Vec, and LINE with the best R2 and MSE scores of 0.9368 and 0.2425 respectively.
{"title":"SNP distributed representation using entity embedding","authors":"Francisco Calvin, Arnel Ferano, Jonathan Christian Setyono, Ardivo Virsa Siswanto, N. Dominic, B. Pardamean","doi":"10.28919/cmbn/7962","DOIUrl":"https://doi.org/10.28919/cmbn/7962","url":null,"abstract":". A single Nucleotide Polymorphism (SNP) array is the largest variation of genetic information to detect specific traits in organisms. SNP is located in a specific locus of DNA sequences. To the day this study was conducted, the representation of SNPs for machine learning models is still questionable. Based on the previous works, we proposed a comparative study of distributed representation methods against SNPs data. This study used 1,232 SNPs from the genomic data of 687 Indonesian rice samples collected from four distinct rice fields. The SNP data used was converted into an encoded format. Entity embedding (Embedder) and several comparative models, i.e., Node2Vec, Struc2Vec, and LINE, were chosen to predict the rice yield of the SNP data. The entity embedding using Embedder outperformed the comparative methods used in this study, namely Node2Vec, Struc2Vec, and LINE with the best R2 and MSE scores of 0.9368 and 0.2425 respectively.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69242260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Otoo, Albert Gyan, Hawa Adusei, Daniel Gyamfi, Shaibu Osman
. COVID-19 exposed most of the world healthcare systems as many countries were compelled to request for international support. The disease spreads through contact with bodily fluids of the infected person. COVID-19 poses great threat to people in old age with the disease’s severity risks factor borne by them. In this study, we developed a Covid-19 that explains the transmission mechanism of the disease. Model’s equilibrium points were determined and local stability analyses of the model at equilibrium was carried out. The analyses showed that disease free-equilibrium is stable when R 0 < 1 and unstable when R 0 > 1. Global stability analyses were also performed for the models using analytic methods of Lyapunov function approach. The model is then extended to optimal control by adding time-dependent controls. The model was analysed qualitatively with Pontryagin’s Maximum principle. Numerical simulations were carried out for the model by designing an iterative scheme that used a fourth-order Runge Kutta method. The numerical analyses also determine the effective strategy in controlling the disease. Best control strategy is education and sensitisation of the public on the dangers and possible causes of the infection.
{"title":"Global stability analysis and optimal prevention of COVID-19 spread in Ghana: A compartmental modelling perspective","authors":"D. Otoo, Albert Gyan, Hawa Adusei, Daniel Gyamfi, Shaibu Osman","doi":"10.28919/cmbn/7971","DOIUrl":"https://doi.org/10.28919/cmbn/7971","url":null,"abstract":". COVID-19 exposed most of the world healthcare systems as many countries were compelled to request for international support. The disease spreads through contact with bodily fluids of the infected person. COVID-19 poses great threat to people in old age with the disease’s severity risks factor borne by them. In this study, we developed a Covid-19 that explains the transmission mechanism of the disease. Model’s equilibrium points were determined and local stability analyses of the model at equilibrium was carried out. The analyses showed that disease free-equilibrium is stable when R 0 < 1 and unstable when R 0 > 1. Global stability analyses were also performed for the models using analytic methods of Lyapunov function approach. The model is then extended to optimal control by adding time-dependent controls. The model was analysed qualitatively with Pontryagin’s Maximum principle. Numerical simulations were carried out for the model by designing an iterative scheme that used a fourth-order Runge Kutta method. The numerical analyses also determine the effective strategy in controlling the disease. Best control strategy is education and sensitisation of the public on the dangers and possible causes of the infection.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69242449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Otoo, Hawa Edusei, Albert Gyan, Daniel Gyamfi, Shaibu Osman
. HIV accounts for more than thirty three million death and approximately thirty eight million infected cases since it’s inception. The disease unfolds in three stages; Chronic, Acute and fully blown AIDS. Adhering to preventive protocols such as use of condoms, preventing oneself from unprotected sex and limiting one’s sexual partners could help minimize the disease spread. In this study, a deterministic model for HIV-AIDS is formulated. The equilibrium points, local and global stability of the equilibrium points, and HIV reproductive rate were determined and interpreted. The model was extended to optimal control by simulating the optimality system. This was done by incorporating the use of condoms and education of susceptible population as intervention strategies. It was established that the best and most effective control strategy was optimal education and sensitisation of susceptible population.
{"title":"Optimal prevention of HIV-AIDS with emphasis on unprotected and unnatural canal activities: a deterministic modelling perspective","authors":"D. Otoo, Hawa Edusei, Albert Gyan, Daniel Gyamfi, Shaibu Osman","doi":"10.28919/cmbn/7972","DOIUrl":"https://doi.org/10.28919/cmbn/7972","url":null,"abstract":". HIV accounts for more than thirty three million death and approximately thirty eight million infected cases since it’s inception. The disease unfolds in three stages; Chronic, Acute and fully blown AIDS. Adhering to preventive protocols such as use of condoms, preventing oneself from unprotected sex and limiting one’s sexual partners could help minimize the disease spread. In this study, a deterministic model for HIV-AIDS is formulated. The equilibrium points, local and global stability of the equilibrium points, and HIV reproductive rate were determined and interpreted. The model was extended to optimal control by simulating the optimality system. This was done by incorporating the use of condoms and education of susceptible population as intervention strategies. It was established that the best and most effective control strategy was optimal education and sensitisation of susceptible population.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69242491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the increasing of human population and the development of technology, crowd counting models are needed to estimate people in certain areas. This research paper compares the prediction performance and computational requirement of four state of the art crowd counting models: M-SFAnet, DM-Count, Context-Aware Crowd Counting (ECAN), and Supervised Spatial Divide-and-Conquer (SS-DCNet). The evaluations were performed to find the most high-performance model in term of prediction performance and computational requirement. The computational requirement is being compared and considered because of the development of Internet of Things devices, crowd counting models that have good prediction performance and low computational requirements can be implemented in low-compute devices. We evaluated the models on four different datasets. From the evaluation we found that SS-DCNet approach achieved the most favorable results.
{"title":"Evaluation of crowd counting models in term of prediction performance and computational requirement","authors":"","doi":"10.28919/cmbn/8097","DOIUrl":"https://doi.org/10.28919/cmbn/8097","url":null,"abstract":"With the increasing of human population and the development of technology, crowd counting models are needed to estimate people in certain areas. This research paper compares the prediction performance and computational requirement of four state of the art crowd counting models: M-SFAnet, DM-Count, Context-Aware Crowd Counting (ECAN), and Supervised Spatial Divide-and-Conquer (SS-DCNet). The evaluations were performed to find the most high-performance model in term of prediction performance and computational requirement. The computational requirement is being compared and considered because of the development of Internet of Things devices, crowd counting models that have good prediction performance and low computational requirements can be implemented in low-compute devices. We evaluated the models on four different datasets. From the evaluation we found that SS-DCNet approach achieved the most favorable results.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135909858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Coronavirus Disease 2019 (COVID-19) is an infectious disease caused by SARS-CoV-2 and designated a pandemic by the World Health Organization (WHO) on March 11, 2020. As cases increase, the number of patients requiring services is more than the available staff and facilities, in queues resulting in longer patient waiting times. One way to analyze the queuing system is to model using max-plus algebra. Before forming the Max-Plus Algebra model, Petri Net was built, which is a graphical and mathematical modeling tool for analyzing a system, so in this study, the results obtained in the form of a model Petri Net and max-plus algebra in the treatment of COVID-19 patients, where is the service flow patients used are limited to referral patient services with positive and suspected cases Patients Under Surveillance (PDP) COVID-19.
{"title":"The stability of Petri net model for the COVID-19 patient service system","authors":"","doi":"10.28919/cmbn/8130","DOIUrl":"https://doi.org/10.28919/cmbn/8130","url":null,"abstract":"Coronavirus Disease 2019 (COVID-19) is an infectious disease caused by SARS-CoV-2 and designated a pandemic by the World Health Organization (WHO) on March 11, 2020. As cases increase, the number of patients requiring services is more than the available staff and facilities, in queues resulting in longer patient waiting times. One way to analyze the queuing system is to model using max-plus algebra. Before forming the Max-Plus Algebra model, Petri Net was built, which is a graphical and mathematical modeling tool for analyzing a system, so in this study, the results obtained in the form of a model Petri Net and max-plus algebra in the treatment of COVID-19 patients, where is the service flow patients used are limited to referral patient services with positive and suspected cases Patients Under Surveillance (PDP) COVID-19.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135497508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Taking into account the significance of food chains in the environment, it demonstrates the interdependence of all living things and has economic implications for people. Hunting cooperation, fear, and intraspecific competition are all included in a food chain model that has been developed and researched. The study tries to comprehend how these elements affect the behavior of species along the food chain. We first examined the suggested model's solution properties before calculating every potential equilibrium point and examining the stability and bifurcation nearby. We have identified the factors that guarantee the global stability of the positive equilibrium point using the geometric approach. Additionally, the circumstances that would guarantee the continued existence of all living beings were computed. The theoretical findings were supported by numerical simulations, which also showed how altering parameter values affected the food chain's dynamic behavior.
{"title":"Effect of hunting cooperation and fear in a food chain model with intraspecific competition","authors":"","doi":"10.28919/cmbn/8246","DOIUrl":"https://doi.org/10.28919/cmbn/8246","url":null,"abstract":"Taking into account the significance of food chains in the environment, it demonstrates the interdependence of all living things and has economic implications for people. Hunting cooperation, fear, and intraspecific competition are all included in a food chain model that has been developed and researched. The study tries to comprehend how these elements affect the behavior of species along the food chain. We first examined the suggested model's solution properties before calculating every potential equilibrium point and examining the stability and bifurcation nearby. We have identified the factors that guarantee the global stability of the positive equilibrium point using the geometric approach. Additionally, the circumstances that would guarantee the continued existence of all living beings were computed. The theoretical findings were supported by numerical simulations, which also showed how altering parameter values affected the food chain's dynamic behavior.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135448703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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