This paper presents a model to approach the dynamics of infectious diseases expansion. Our
model aims to establish a link between traditional simulation of the Susceptible-Infectious (SI)
model of disease expansion based on ordinary differential equations (ODE), and a very simple
approach based on both connectivity between people and elementary binary rules that define
the result of these contacts. The SI deterministic compartmental model has been analysed and
successfully modelled by our method, in the case of 4-connected neighbourhood.
Mathematical Model for Infection and Removalijtsrd
The document presents a mathematical model for studying the spread of infectious diseases within a community. It envisions a population of n individuals comprising x susceptible individuals, y infectious individuals, and z recovered/immune individuals at time t. Infection and removal rates (β and γ) are postulated. The model is represented as damped harmonic oscillations where the body's resistance to infection decays over time similar to damped motion. Solving the model equations results in a solution indicating seasonal variation in infections. Modifications to the model are discussed, including allowing for an incubation period between infection and becoming infectious. The model can provide insight into disease spread and evaluate control strategies.
MATHEMATICAL MODELLING OF EPIDEMIOLOGY IN PRESENCE OF VACCINATION AND DELAYcscpconf
The Mathematical modeling of infectious disease is currently a major research topic in the public health domain. In some cases the infected individuals may not be infectious at the time of
infection. To become infectious, the infected individuals take some times which is known as latent period or delay. Here the two SIR models are taken into consideration for present analysis where the newly entered individuals have been vaccinated with a specific rate. The analysis of these models show that if vaccination is administered to the newly entering individuals then the system will be asymptotically stable in both cases i.e. with delay and
without delay
Hey DIVYA SHREE NANDINI is here. I'm going to present my topic on Kermack and Mckendrik epidemic model. Want to know more about epidemic model. Then come with me✌
This chapter provides a historical introduction to mathematical modeling of epidemics and rumors. It discusses early empirical modeling from the 1700s, the first deterministic SIR model from the early 1900s, the development of homogeneous mixing models in the mid-1900s, and early stochastic models. The chapter outlines different modeling approaches and terminology. It concludes that modeling has progressed from curve-fitting empirical data to developing deterministic and stochastic models in both continuous and discrete time to better understand disease transmission dynamics.
Amodelbasedoncellularautomatatosimulatea si sepidemicdiseaseCarlosReyes671
This document presents a cellular automata model to simulate the spread of an SIS epidemic disease. The model divides the environment into square or hexagonal cells, with each cell representing a portion of the total population. The state of each cell indicates the fraction of susceptible and infected individuals. The local transition function determines the new state based on the states of neighboring cells, considering factors like infection rate, recovery rate, and movement between cells. Simulations using this model aim to better capture spatial factors and local interactions in epidemic spreading compared to traditional differential equation models.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
This document presents an agent-based simulation model of the 2009 H1N1 influenza outbreak at Bates College. It begins with an overview of the traditional SIR modeling approach and its limitations in fitting the irregular infection patterns observed at Bates and other small colleges. It then introduces agent-based modeling as an alternative approach that can incorporate changes in individual interactions over time. The document proceeds to build increasingly complex agent-based models, starting with a simple SIR-inspired model and culminating in a "clinic day model" that attempts to replicate Bates' infection spikes following large mixing events like vaccination clinics. The results of these models are analyzed to evaluate their ability to better explain the outbreak dynamics.
A COMPUTER VIRUS PROPAGATION MODEL USING DELAY DIFFERENTIAL EQUATIONS WITH PR...IJCNCJournal
The SIR model is used extensively in the field of epidemiology, in particular, for the analysis of communal
diseases. One problem with SIR and other existing models is that they are tailored to random or Erdos type networks since they do not consider the varying probabilities of infection or immunity per node. In this paper, we present the application and the simulation results of the pSEIRS model that takes into account the probabilities, and is thus suitable for more realistic scale free networks. In the pSEIRS model, the death rate and the excess death rate are constant for infective nodes. Latent and immune periods are assumed to be constant and the infection rate is assumed to be proportional to I (t) N(t) , where N (t) is the size of the total population and I(t) is the size of the infected population. A node recovers from an infection
temporarily with a probability p and dies from the infection with probability (1-p).
Mathematical Model for Infection and Removalijtsrd
The document presents a mathematical model for studying the spread of infectious diseases within a community. It envisions a population of n individuals comprising x susceptible individuals, y infectious individuals, and z recovered/immune individuals at time t. Infection and removal rates (β and γ) are postulated. The model is represented as damped harmonic oscillations where the body's resistance to infection decays over time similar to damped motion. Solving the model equations results in a solution indicating seasonal variation in infections. Modifications to the model are discussed, including allowing for an incubation period between infection and becoming infectious. The model can provide insight into disease spread and evaluate control strategies.
MATHEMATICAL MODELLING OF EPIDEMIOLOGY IN PRESENCE OF VACCINATION AND DELAYcscpconf
The Mathematical modeling of infectious disease is currently a major research topic in the public health domain. In some cases the infected individuals may not be infectious at the time of
infection. To become infectious, the infected individuals take some times which is known as latent period or delay. Here the two SIR models are taken into consideration for present analysis where the newly entered individuals have been vaccinated with a specific rate. The analysis of these models show that if vaccination is administered to the newly entering individuals then the system will be asymptotically stable in both cases i.e. with delay and
without delay
Hey DIVYA SHREE NANDINI is here. I'm going to present my topic on Kermack and Mckendrik epidemic model. Want to know more about epidemic model. Then come with me✌
This chapter provides a historical introduction to mathematical modeling of epidemics and rumors. It discusses early empirical modeling from the 1700s, the first deterministic SIR model from the early 1900s, the development of homogeneous mixing models in the mid-1900s, and early stochastic models. The chapter outlines different modeling approaches and terminology. It concludes that modeling has progressed from curve-fitting empirical data to developing deterministic and stochastic models in both continuous and discrete time to better understand disease transmission dynamics.
Amodelbasedoncellularautomatatosimulatea si sepidemicdiseaseCarlosReyes671
This document presents a cellular automata model to simulate the spread of an SIS epidemic disease. The model divides the environment into square or hexagonal cells, with each cell representing a portion of the total population. The state of each cell indicates the fraction of susceptible and infected individuals. The local transition function determines the new state based on the states of neighboring cells, considering factors like infection rate, recovery rate, and movement between cells. Simulations using this model aim to better capture spatial factors and local interactions in epidemic spreading compared to traditional differential equation models.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
This document presents an agent-based simulation model of the 2009 H1N1 influenza outbreak at Bates College. It begins with an overview of the traditional SIR modeling approach and its limitations in fitting the irregular infection patterns observed at Bates and other small colleges. It then introduces agent-based modeling as an alternative approach that can incorporate changes in individual interactions over time. The document proceeds to build increasingly complex agent-based models, starting with a simple SIR-inspired model and culminating in a "clinic day model" that attempts to replicate Bates' infection spikes following large mixing events like vaccination clinics. The results of these models are analyzed to evaluate their ability to better explain the outbreak dynamics.
A COMPUTER VIRUS PROPAGATION MODEL USING DELAY DIFFERENTIAL EQUATIONS WITH PR...IJCNCJournal
The SIR model is used extensively in the field of epidemiology, in particular, for the analysis of communal
diseases. One problem with SIR and other existing models is that they are tailored to random or Erdos type networks since they do not consider the varying probabilities of infection or immunity per node. In this paper, we present the application and the simulation results of the pSEIRS model that takes into account the probabilities, and is thus suitable for more realistic scale free networks. In the pSEIRS model, the death rate and the excess death rate are constant for infective nodes. Latent and immune periods are assumed to be constant and the infection rate is assumed to be proportional to I (t) N(t) , where N (t) is the size of the total population and I(t) is the size of the infected population. A node recovers from an infection
temporarily with a probability p and dies from the infection with probability (1-p).
This document discusses epidemiological modeling of infectious diseases. It describes several common deterministic compartmental models, including SIR, SIS, and SEIR models. These models divide the population into compartments based on disease status, such as susceptible, infected, and recovered. The models are formulated using systems of differential equations to capture the flows between compartments over time. The basic reproduction number is used to determine when herd immunity is achieved in a population through vaccination. More complex models incorporate additional factors like latent periods, temporary immunity, and age structure.
A Review On Mathematical Modeling Of Infectious DiseasesSara Alvarez
This document reviews the use of mathematical modeling to study infectious disease transmission and dynamics. It discusses how compartmental models have been widely used since the early 20th century to understand disease spread and identify key factors like reproduction numbers. The review outlines some of the earliest and most influential disease models, and describes how models have become more advanced over time by incorporating additional real-world factors. Compartmental models like SIR are commonly employed to predict outbreaks and guide control strategies.
A SEIR MODEL FOR CONTROL OF INFECTIOUS DISEASESSOUMYADAS835019
This document presents a SEIR model for controlling infectious diseases with constraints. It begins with an introduction to SEIR models and their use in modeling disease transmission and testing control strategies. It then motivates the study by discussing the COVID-19 pandemic. The document outlines the basic ideas of the SEIR model and describes the compartments and parameters. It presents the optimal control problem formulated to determine vaccination strategies over time. Potential application areas and future research scope are discussed before concluding with references.
This document outlines an epidemiological modeling project on modeling the impact of childhood vaccination strategies on the spread of measles. It introduces key epidemiological concepts like the basic reproductive number R0 and discusses measles as a highly contagious disease. It then presents the SIR compartmental model and its extensions, including incorporating births and deaths, age stratification, and different pediatric vaccination strategies. The document will use these mathematical models to simulate different vaccination scenarios and their effect on measles transmission dynamics.
A general stochastic information diffusion model in social networks based on ...IJCNCJournal
Social networks are an important infrastructure for information, viruses and innovations propagation. Since users’
behavior has influenced by other users’ activity, some groups of people would be made regard to similarity of users’
interests. On the other hand, dealing with many events in real worlds, can be justified in social networks; spreading
disease is one instance of them. People’s manner and infection severity are more important parameters in
dissemination of diseases. Both of these reasons derive, whether the diffusion leads to an epidemic or not. SIRS is a
hybrid model of SIR and SIS disease models to spread contamination. A person in this model can be returned to
susceptible state after it removed. According to communities which are established on the social network, we use the
compartmental type of SIRS model. During this paper, a general compartmental information diffusion model would
be proposed and extracted some of the beneficial parameters to analyze our model. To adapt our model to realistic
behaviors, we use Markovian model, which would be helpful to create a stochastic manner of the proposed model.
In the case of random model, we can calculate probabilities of transaction between states and predicting value of
each state. The comparison between two mode of the model shows that, the prediction of population would be
verified in each state.
Mathematics Model Development Deployment of Dengue Fever Diseases by Involve ...Dr. Amarjeet Singh
Dengue virus is one of virus that cause deadly disease
was dengue fever. This virus was transmitted through bite of
Aedes aegypti female mosquitoes that gain virus infected by
taking food from infected human blood, then mosquitoes
transmited pathogen to susceptible humans. Suppressed the
spread and growth of dengue fever was important to avoid
and prevent the increase of dengue virus sufferer and
casualties. This problem can be solved with studied
important factors that affected the spread and equity of
disease by sensitivity index. The purpose of this research
were to modify mathematical model the spread of dengue
fever be SEIRS-ASEI type, to determine of equilibrium
point, to determined of basic reproduction number, stability
analysis of equilibrium point, calculated sensitivity index, to
analyze sensitivity, and to simulate numerical on
modification model. Analysis of model obtained disease free
equilibrium (DFE) point and endemic equilibrium point. The
numerical simulation result had showed that DFE, stable if
the basic reproduction number is less than one and endemic
equilibrium point was stable if the basic reproduction
number is more than one.
Modeling and Threshold Sensitivity Analysis of Computer Virus EpidemicIOSR Journals
This document presents a mathematical model for analyzing the spread of computer viruses through a network. It modifies an existing epidemic model by incorporating a range of parameters rather than constant values. The model classifies computers into four groups: susceptible, exposed, infected, and immunized. It uses differential equations to model how the population in each group changes over time and analyzes the epidemic threshold. The document estimates parameter values based on studies of real computer viruses. It aims to help understand virus spreading and determine measures to control viral epidemics.
This document presents a mathematical model for analyzing the spread of computer viruses through a network. It modifies an existing epidemic model by incorporating a range of parameters rather than constant values. The model classifies computers into four groups: susceptible, exposed, infected, and immunized. It uses differential equations to model how the population in each group changes over time and analyzes the epidemic threshold. The document estimates parameter values based on studies of real computer viruses. It aims to help understand virus spreading and determine measures to control viral epidemics.
A unified prediction of computer virus spread in connected networksUltraUploader
This document presents two models for predicting the spread of computer viruses in connected networks: a discrete Markov model and a continuous differential equation model. The Markov model captures short-term behavior dependent on initial conditions, providing extinction probabilities. The differential equation model predicts long-term behavior by defining a boundary between parameter values where the virus will survive or die out. Simulations show good agreement between the models. The models provide new insights into controlling computer virus persistence on networks.
Epidemiological modeling of online social network dynamicsDario Caliendo
Facebook si è diffuso come un'epidemia virale, alla quale gli utenti stanno lentamente diventando immuni. Ad affermarlo sono John Cannarella e Joshua A. Spechler, due ricercatori della Princeton Universiry che in un'analisi nella quale hanno studiato il fenomeno del social network applicando un modello utilizzato per lo studio dello sviluppo delle epidemie, hanno determinato che la diffusione della piattaforma di Zuckerberg ha ormai superato il sui punto più alto ed a breve inizierà ad implodere, fino a perdere l'80% degli utenti entro il 2017.
The document describes an epidemiological model called the infectious recovery SIR model (irSIR) that can be used to model user adoption and abandonment of online social networks (OSNs). The irSIR model modifies the traditional SIR disease model by incorporating infectious recovery dynamics, where contact between a recovered and infected user is required for a user to be "recovered" from using the OSN. The authors validate the irSIR model using Google search query data for MySpace and apply it to data for Facebook, predicting Facebook will see a rapid decline in the next few years based on the model.
IOSR Journal of Mathematics(IOSR-JM) is an open access international journal that provides rapid publication (within a month) of articles in all areas of mathemetics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in mathematics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Modeling and qualitative analysis of malaria epidemiologyIOSR Journals
We develop and analyze a mathematical model on malaria dynamics using ordinary differential equations, in order to investigate the effect of certain parameters on the transmission and spread of the disease. We introduce dimensionless variables for time, fraction of infected human and fraction of infected mosquito and solve the resulting system of ordinary differential equations numerically. Equilibrium points are established and stability criteria analyzed. The results reveal that the parameters play a crucial role in the interaction between human and infected mosquito.
Mathematical Model of Varicella Zoster Virus - Abbie JakubovicAbbie Jakubovic
This paper uses a mathematical model called the SIR model to simulate the spread of chickenpox (varicella) caused by the varicella-zoster virus. The SIR model divides a population into susceptible (S), infected (I), and removed/recovered (R) groups and models how individuals move between these groups over time. The paper applies the SIR model to a sample population of 1,000 individuals to demonstrate how an outbreak of chickenpox might progress. It estimates key parameters like infection rate and removal rate based on characteristics of the chickenpox virus. The model simulation shows the number of susceptible individuals decreasing as the number of infected individuals increases and peaks before declining as individuals recover and become removed
Highlighted notes while preparing for project on Computational Epidemics:
Computational Epidemiology (Review)
By Madhav Marathe, Anil Kumar S. Vullikanti
Communications of the ACM, July 2013, Vol. 56 No. 7, Pages 88-96
10.1145/2483852.2483871
An epidemic is said to arise in a community or region when cases of an illness or other health-related events occur in excess of normal expectancy. Epidemics are considered to have influenced significant historical events, including the plagues in Roman times and Middle Ages, the fall of the Han empire in the 3rd century in China, and the defeat of the Aztecs in the 1500s, due to a smallpox outbreak. The 1918 flu pandemic in the U.S. was responsible for more deaths than those due to World War I. The last 50 years have seen epidemics caused by HIV/AIDS, SARS, and influenza-like illnesses. Despite significant medical advances, according to the World Health organization (WHO), infectious diseases account for more than 13 million deaths a year.
A computational model of computer virus propagationUltraUploader
1) A computational model is developed to simulate the propagation of computer viruses and warning messages within organizational social and computer networks.
2) The model represents the networks as graphs and incorporates mechanisms of virus propagation, node state transitions, and the dissemination of warning messages.
3) Experiments show that random graphs with similar characteristics to real-world networks can model social networks, and isolating organizations may prevent virus infection but also limit receipt of important warning messages.
COVID-19 (Coronavirus Disease) Outbreak Prediction Using a Susceptible-Exposed-Symptomatic Infected-Recovered-Super Spreaders-Asymptomatic Infected-Deceased-Critical (SEIR-PADC) Dynamic Model
ANALYSIS OF LAND SURFACE DEFORMATION GRADIENT BY DINSAR cscpconf
The progressive development of Synthetic Aperture Radar (SAR) systems diversify the exploitation of the generated images by these systems in different applications of geoscience. Detection and monitoring surface deformations, procreated by various phenomena had benefited from this evolution and had been realized by interferometry (InSAR) and differential interferometry (DInSAR) techniques. Nevertheless, spatial and temporal decorrelations of the interferometric couples used, limit strongly the precision of analysis results by these techniques. In this context, we propose, in this work, a methodological approach of surface deformation detection and analysis by differential interferograms to show the limits of this technique according to noise quality and level. The detectability model is generated from the deformation signatures, by simulating a linear fault merged to the images couples of ERS1 / ERS2 sensors acquired in a region of the Algerian south.
4D AUTOMATIC LIP-READING FOR SPEAKER'S FACE IDENTIFCATIONcscpconf
A novel based a trajectory-guided, concatenating approach for synthesizing high-quality image real sample renders video is proposed . The lips reading automated is seeking for modeled the closest real image sample sequence preserve in the library under the data video to the HMM predicted trajectory. The object trajectory is modeled obtained by projecting the face patterns into an KDA feature space is estimated. The approach for speaker's face identification by using synthesise the identity surface of a subject face from a small sample of patterns which sparsely each the view sphere. An KDA algorithm use to the Lip-reading image is discrimination, after that work consisted of in the low dimensional for the fundamental lip features vector is reduced by using the 2D-DCT.The mouth of the set area dimensionality is ordered by a normally reduction base on the PCA to obtain the Eigen lips approach, their proposed approach by[33]. The subjective performance results of the cost function under the automatic lips reading modeled , which wasn’t illustrate the superior performance of the
method.
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This document discusses epidemiological modeling of infectious diseases. It describes several common deterministic compartmental models, including SIR, SIS, and SEIR models. These models divide the population into compartments based on disease status, such as susceptible, infected, and recovered. The models are formulated using systems of differential equations to capture the flows between compartments over time. The basic reproduction number is used to determine when herd immunity is achieved in a population through vaccination. More complex models incorporate additional factors like latent periods, temporary immunity, and age structure.
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This document outlines an epidemiological modeling project on modeling the impact of childhood vaccination strategies on the spread of measles. It introduces key epidemiological concepts like the basic reproductive number R0 and discusses measles as a highly contagious disease. It then presents the SIR compartmental model and its extensions, including incorporating births and deaths, age stratification, and different pediatric vaccination strategies. The document will use these mathematical models to simulate different vaccination scenarios and their effect on measles transmission dynamics.
A general stochastic information diffusion model in social networks based on ...IJCNCJournal
Social networks are an important infrastructure for information, viruses and innovations propagation. Since users’
behavior has influenced by other users’ activity, some groups of people would be made regard to similarity of users’
interests. On the other hand, dealing with many events in real worlds, can be justified in social networks; spreading
disease is one instance of them. People’s manner and infection severity are more important parameters in
dissemination of diseases. Both of these reasons derive, whether the diffusion leads to an epidemic or not. SIRS is a
hybrid model of SIR and SIS disease models to spread contamination. A person in this model can be returned to
susceptible state after it removed. According to communities which are established on the social network, we use the
compartmental type of SIRS model. During this paper, a general compartmental information diffusion model would
be proposed and extracted some of the beneficial parameters to analyze our model. To adapt our model to realistic
behaviors, we use Markovian model, which would be helpful to create a stochastic manner of the proposed model.
In the case of random model, we can calculate probabilities of transaction between states and predicting value of
each state. The comparison between two mode of the model shows that, the prediction of population would be
verified in each state.
Mathematics Model Development Deployment of Dengue Fever Diseases by Involve ...Dr. Amarjeet Singh
Dengue virus is one of virus that cause deadly disease
was dengue fever. This virus was transmitted through bite of
Aedes aegypti female mosquitoes that gain virus infected by
taking food from infected human blood, then mosquitoes
transmited pathogen to susceptible humans. Suppressed the
spread and growth of dengue fever was important to avoid
and prevent the increase of dengue virus sufferer and
casualties. This problem can be solved with studied
important factors that affected the spread and equity of
disease by sensitivity index. The purpose of this research
were to modify mathematical model the spread of dengue
fever be SEIRS-ASEI type, to determine of equilibrium
point, to determined of basic reproduction number, stability
analysis of equilibrium point, calculated sensitivity index, to
analyze sensitivity, and to simulate numerical on
modification model. Analysis of model obtained disease free
equilibrium (DFE) point and endemic equilibrium point. The
numerical simulation result had showed that DFE, stable if
the basic reproduction number is less than one and endemic
equilibrium point was stable if the basic reproduction
number is more than one.
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This document presents a mathematical model for analyzing the spread of computer viruses through a network. It modifies an existing epidemic model by incorporating a range of parameters rather than constant values. The model classifies computers into four groups: susceptible, exposed, infected, and immunized. It uses differential equations to model how the population in each group changes over time and analyzes the epidemic threshold. The document estimates parameter values based on studies of real computer viruses. It aims to help understand virus spreading and determine measures to control viral epidemics.
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Facebook si è diffuso come un'epidemia virale, alla quale gli utenti stanno lentamente diventando immuni. Ad affermarlo sono John Cannarella e Joshua A. Spechler, due ricercatori della Princeton Universiry che in un'analisi nella quale hanno studiato il fenomeno del social network applicando un modello utilizzato per lo studio dello sviluppo delle epidemie, hanno determinato che la diffusione della piattaforma di Zuckerberg ha ormai superato il sui punto più alto ed a breve inizierà ad implodere, fino a perdere l'80% degli utenti entro il 2017.
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Highlighted notes while preparing for project on Computational Epidemics:
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By Madhav Marathe, Anil Kumar S. Vullikanti
Communications of the ACM, July 2013, Vol. 56 No. 7, Pages 88-96
10.1145/2483852.2483871
An epidemic is said to arise in a community or region when cases of an illness or other health-related events occur in excess of normal expectancy. Epidemics are considered to have influenced significant historical events, including the plagues in Roman times and Middle Ages, the fall of the Han empire in the 3rd century in China, and the defeat of the Aztecs in the 1500s, due to a smallpox outbreak. The 1918 flu pandemic in the U.S. was responsible for more deaths than those due to World War I. The last 50 years have seen epidemics caused by HIV/AIDS, SARS, and influenza-like illnesses. Despite significant medical advances, according to the World Health organization (WHO), infectious diseases account for more than 13 million deaths a year.
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1) A computational model is developed to simulate the propagation of computer viruses and warning messages within organizational social and computer networks.
2) The model represents the networks as graphs and incorporates mechanisms of virus propagation, node state transitions, and the dissemination of warning messages.
3) Experiments show that random graphs with similar characteristics to real-world networks can model social networks, and isolating organizations may prevent virus infection but also limit receipt of important warning messages.
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The progressive development of Synthetic Aperture Radar (SAR) systems diversify the exploitation of the generated images by these systems in different applications of geoscience. Detection and monitoring surface deformations, procreated by various phenomena had benefited from this evolution and had been realized by interferometry (InSAR) and differential interferometry (DInSAR) techniques. Nevertheless, spatial and temporal decorrelations of the interferometric couples used, limit strongly the precision of analysis results by these techniques. In this context, we propose, in this work, a methodological approach of surface deformation detection and analysis by differential interferograms to show the limits of this technique according to noise quality and level. The detectability model is generated from the deformation signatures, by simulating a linear fault merged to the images couples of ERS1 / ERS2 sensors acquired in a region of the Algerian south.
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A novel based a trajectory-guided, concatenating approach for synthesizing high-quality image real sample renders video is proposed . The lips reading automated is seeking for modeled the closest real image sample sequence preserve in the library under the data video to the HMM predicted trajectory. The object trajectory is modeled obtained by projecting the face patterns into an KDA feature space is estimated. The approach for speaker's face identification by using synthesise the identity surface of a subject face from a small sample of patterns which sparsely each the view sphere. An KDA algorithm use to the Lip-reading image is discrimination, after that work consisted of in the low dimensional for the fundamental lip features vector is reduced by using the 2D-DCT.The mouth of the set area dimensionality is ordered by a normally reduction base on the PCA to obtain the Eigen lips approach, their proposed approach by[33]. The subjective performance results of the cost function under the automatic lips reading modeled , which wasn’t illustrate the superior performance of the
method.
MOVING FROM WATERFALL TO AGILE PROCESS IN SOFTWARE ENGINEERING CAPSTONE PROJE...cscpconf
Universities offer software engineering capstone course to simulate a real world-working environment in which students can work in a team for a fixed period to deliver a quality product. The objective of the paper is to report on our experience in moving from Waterfall process to Agile process in conducting the software engineering capstone project. We present the capstone course designs for both Waterfall driven and Agile driven methodologies that highlight the structure, deliverables and assessment plans.To evaluate the improvement, we conducted a survey for two different sections taught by two different instructors to evaluate students’ experience in moving from traditional Waterfall model to Agile like process. Twentyeight students filled the survey. The survey consisted of eight multiple-choice questions and an open-ended question to collect feedback from students. The survey results show that students were able to attain hands one experience, which simulate a real world-working environment. The results also show that the Agile approach helped students to have overall better design and avoid mistakes they have made in the initial design completed in of the first phase of the capstone project. In addition, they were able to decide on their team capabilities, training needs and thus learn the required technologies earlier which is reflected on the final product quality
PROMOTING STUDENT ENGAGEMENT USING SOCIAL MEDIA TECHNOLOGIEScscpconf
This document discusses using social media technologies to promote student engagement in a software project management course. It describes the course and objectives of enhancing communication. It discusses using Facebook for 4 years, then switching to WhatsApp based on student feedback, and finally introducing Slack to enable personalized team communication. Surveys found students engaged and satisfied with all three tools, though less familiar with Slack. The conclusion is that social media promotes engagement but familiarity with the tool also impacts satisfaction.
A SURVEY ON QUESTION ANSWERING SYSTEMS: THE ADVANCES OF FUZZY LOGICcscpconf
In real world computing environment with using a computer to answer questions has been a human dream since the beginning of the digital era, Question-answering systems are referred to as intelligent systems, that can be used to provide responses for the questions being asked by the user based on certain facts or rules stored in the knowledge base it can generate answers of questions asked in natural , and the first main idea of fuzzy logic was to working on the problem of computer understanding of natural language, so this survey paper provides an overview on what Question-Answering is and its system architecture and the possible relationship and
different with fuzzy logic, as well as the previous related research with respect to approaches that were followed. At the end, the survey provides an analytical discussion of the proposed QA models, along or combined with fuzzy logic and their main contributions and limitations.
DYNAMIC PHONE WARPING – A METHOD TO MEASURE THE DISTANCE BETWEEN PRONUNCIATIONS cscpconf
Human beings generate different speech waveforms while speaking the same word at different times. Also, different human beings have different accents and generate significantly varying speech waveforms for the same word. There is a need to measure the distances between various words which facilitate preparation of pronunciation dictionaries. A new algorithm called Dynamic Phone Warping (DPW) is presented in this paper. It uses dynamic programming technique for global alignment and shortest distance measurements. The DPW algorithm can be used to enhance the pronunciation dictionaries of the well-known languages like English or to build pronunciation dictionaries to the less known sparse languages. The precision measurement experiments show 88.9% accuracy.
INTELLIGENT ELECTRONIC ASSESSMENT FOR SUBJECTIVE EXAMS cscpconf
In education, the use of electronic (E) examination systems is not a novel idea, as Eexamination systems have been used to conduct objective assessments for the last few years. This research deals with randomly designed E-examinations and proposes an E-assessment system that can be used for subjective questions. This system assesses answers to subjective questions by finding a matching ratio for the keywords in instructor and student answers. The matching ratio is achieved based on semantic and document similarity. The assessment system is composed of four modules: preprocessing, keyword expansion, matching, and grading. A survey and case study were used in the research design to validate the proposed system. The examination assessment system will help instructors to save time, costs, and resources, while increasing efficiency and improving the productivity of exam setting and assessments.
TWO DISCRETE BINARY VERSIONS OF AFRICAN BUFFALO OPTIMIZATION METAHEURISTICcscpconf
African Buffalo Optimization (ABO) is one of the most recent swarms intelligence based metaheuristics. ABO algorithm is inspired by the buffalo’s behavior and lifestyle. Unfortunately, the standard ABO algorithm is proposed only for continuous optimization problems. In this paper, the authors propose two discrete binary ABO algorithms to deal with binary optimization problems. In the first version (called SBABO) they use the sigmoid function and probability model to generate binary solutions. In the second version (called LBABO) they use some logical operator to operate the binary solutions. Computational results on two knapsack problems (KP and MKP) instances show the effectiveness of the proposed algorithm and their ability to achieve good and promising solutions.
DETECTION OF ALGORITHMICALLY GENERATED MALICIOUS DOMAINcscpconf
In recent years, many malware writers have relied on Dynamic Domain Name Services (DDNS) to maintain their Command and Control (C&C) network infrastructure to ensure a persistence presence on a compromised host. Amongst the various DDNS techniques, Domain Generation Algorithm (DGA) is often perceived as the most difficult to detect using traditional methods. This paper presents an approach for detecting DGA using frequency analysis of the character distribution and the weighted scores of the domain names. The approach’s feasibility is demonstrated using a range of legitimate domains and a number of malicious algorithmicallygenerated domain names. Findings from this study show that domain names made up of English characters “a-z” achieving a weighted score of < 45 are often associated with DGA. When a weighted score of < 45 is applied to the Alexa one million list of domain names, only 15% of the domain names were treated as non-human generated.
GLOBAL MUSIC ASSET ASSURANCE DIGITAL CURRENCY: A DRM SOLUTION FOR STREAMING C...cscpconf
The document proposes a blockchain-based digital currency and streaming platform called GoMAA to address issues of piracy in the online music streaming industry. Key points:
- GoMAA would use a digital token on the iMediaStreams blockchain to enable secure dissemination and tracking of streamed content. Content owners could control access and track consumption of released content.
- Original media files would be converted to a Secure Portable Streaming (SPS) format, embedding watermarks and smart contract data to indicate ownership and enable validation on the blockchain.
- A browser plugin would provide wallets for fans to collect GoMAA tokens as rewards for consuming content, incentivizing participation and addressing royalty discrepancies by recording
IMPORTANCE OF VERB SUFFIX MAPPING IN DISCOURSE TRANSLATION SYSTEMcscpconf
This document discusses the importance of verb suffix mapping in discourse translation from English to Telugu. It explains that after anaphora resolution, the verbs must be changed to agree with the gender, number, and person features of the subject or anaphoric pronoun. Verbs in Telugu inflect based on these features, while verbs in English only inflect based on number and person. Several examples are provided that demonstrate how the Telugu verb changes based on whether the subject or pronoun is masculine, feminine, neuter, singular or plural. Proper verb suffix mapping is essential for generating natural and coherent translations while preserving the context and meaning of the original discourse.
EXACT SOLUTIONS OF A FAMILY OF HIGHER-DIMENSIONAL SPACE-TIME FRACTIONAL KDV-T...cscpconf
In this paper, based on the definition of conformable fractional derivative, the functional
variable method (FVM) is proposed to seek the exact traveling wave solutions of two higherdimensional
space-time fractional KdV-type equations in mathematical physics, namely the
(3+1)-dimensional space–time fractional Zakharov-Kuznetsov (ZK) equation and the (2+1)-
dimensional space–time fractional Generalized Zakharov-Kuznetsov-Benjamin-Bona-Mahony
(GZK-BBM) equation. Some new solutions are procured and depicted. These solutions, which
contain kink-shaped, singular kink, bell-shaped soliton, singular soliton and periodic wave
solutions, have many potential applications in mathematical physics and engineering. The
simplicity and reliability of the proposed method is verified.
AUTOMATED PENETRATION TESTING: AN OVERVIEWcscpconf
The document discusses automated penetration testing and provides an overview. It compares manual and automated penetration testing, noting that automated testing allows for faster, more standardized and repeatable tests but has limitations in developing new exploits. It also reviews some current automated penetration testing methodologies and tools, including those using HTTP/TCP/IP attacks, linking common scanning tools, a Python-based tool targeting databases, and one using POMDPs for multi-step penetration test planning under uncertainty. The document concludes that automated testing is more efficient than manual for known vulnerabilities but cannot replace manual testing for discovering new exploits.
CLASSIFICATION OF ALZHEIMER USING fMRI DATA AND BRAIN NETWORKcscpconf
Since the mid of 1990s, functional connectivity study using fMRI (fcMRI) has drawn increasing
attention of neuroscientists and computer scientists, since it opens a new window to explore
functional network of human brain with relatively high resolution. BOLD technique provides
almost accurate state of brain. Past researches prove that neuro diseases damage the brain
network interaction, protein- protein interaction and gene-gene interaction. A number of
neurological research paper also analyse the relationship among damaged part. By
computational method especially machine learning technique we can show such classifications.
In this paper we used OASIS fMRI dataset affected with Alzheimer’s disease and normal
patient’s dataset. After proper processing the fMRI data we use the processed data to form
classifier models using SVM (Support Vector Machine), KNN (K- nearest neighbour) & Naïve
Bayes. We also compare the accuracy of our proposed method with existing methods. In future,
we will other combinations of methods for better accuracy.
VALIDATION METHOD OF FUZZY ASSOCIATION RULES BASED ON FUZZY FORMAL CONCEPT AN...cscpconf
The document proposes a new validation method for fuzzy association rules based on three steps: (1) applying the EFAR-PN algorithm to extract a generic base of non-redundant fuzzy association rules using fuzzy formal concept analysis, (2) categorizing the extracted rules into groups, and (3) evaluating the relevance of the rules using structural equation modeling, specifically partial least squares. The method aims to address issues with existing fuzzy association rule extraction algorithms such as large numbers of extracted rules, redundancy, and difficulties with manual validation.
PROBABILITY BASED CLUSTER EXPANSION OVERSAMPLING TECHNIQUE FOR IMBALANCED DATAcscpconf
In many applications of data mining, class imbalance is noticed when examples in one class are
overrepresented. Traditional classifiers result in poor accuracy of the minority class due to the
class imbalance. Further, the presence of within class imbalance where classes are composed of
multiple sub-concepts with different number of examples also affect the performance of
classifier. In this paper, we propose an oversampling technique that handles between class and
within class imbalance simultaneously and also takes into consideration the generalization
ability in data space. The proposed method is based on two steps- performing Model Based
Clustering with respect to classes to identify the sub-concepts; and then computing the
separating hyperplane based on equal posterior probability between the classes. The proposed
method is tested on 10 publicly available data sets and the result shows that the proposed
method is statistically superior to other existing oversampling methods.
CHARACTER AND IMAGE RECOGNITION FOR DATA CATALOGING IN ECOLOGICAL RESEARCHcscpconf
Data collection is an essential, but manpower intensive procedure in ecological research. An
algorithm was developed by the author which incorporated two important computer vision
techniques to automate data cataloging for butterfly measurements. Optical Character
Recognition is used for character recognition and Contour Detection is used for imageprocessing.
Proper pre-processing is first done on the images to improve accuracy. Although
there are limitations to Tesseract’s detection of certain fonts, overall, it can successfully identify
words of basic fonts. Contour detection is an advanced technique that can be utilized to
measure an image. Shapes and mathematical calculations are crucial in determining the precise
location of the points on which to draw the body and forewing lines of the butterfly. Overall,
92% accuracy were achieved by the program for the set of butterflies measured.
SOCIAL MEDIA ANALYTICS FOR SENTIMENT ANALYSIS AND EVENT DETECTION IN SMART CI...cscpconf
Smart cities utilize Internet of Things (IoT) devices and sensors to enhance the quality of the city
services including energy, transportation, health, and much more. They generate massive
volumes of structured and unstructured data on a daily basis. Also, social networks, such as
Twitter, Facebook, and Google+, are becoming a new source of real-time information in smart
cities. Social network users are acting as social sensors. These datasets so large and complex
are difficult to manage with conventional data management tools and methods. To become
valuable, this massive amount of data, known as 'big data,' needs to be processed and
comprehended to hold the promise of supporting a broad range of urban and smart cities
functions, including among others transportation, water, and energy consumption, pollution
surveillance, and smart city governance. In this work, we investigate how social media analytics
help to analyze smart city data collected from various social media sources, such as Twitter and
Facebook, to detect various events taking place in a smart city and identify the importance of
events and concerns of citizens regarding some events. A case scenario analyses the opinions of
users concerning the traffic in three largest cities in the UAE
SOCIAL NETWORK HATE SPEECH DETECTION FOR AMHARIC LANGUAGEcscpconf
The anonymity of social networks makes it attractive for hate speech to mask their criminal
activities online posing a challenge to the world and in particular Ethiopia. With this everincreasing
volume of social media data, hate speech identification becomes a challenge in
aggravating conflict between citizens of nations. The high rate of production, has become
difficult to collect, store and analyze such big data using traditional detection methods. This
paper proposed the application of apache spark in hate speech detection to reduce the
challenges. Authors developed an apache spark based model to classify Amharic Facebook
posts and comments into hate and not hate. Authors employed Random forest and Naïve Bayes
for learning and Word2Vec and TF-IDF for feature selection. Tested by 10-fold crossvalidation,
the model based on word2vec embedding performed best with 79.83%accuracy. The
proposed method achieve a promising result with unique feature of spark for big data.
GENERAL REGRESSION NEURAL NETWORK BASED POS TAGGING FOR NEPALI TEXTcscpconf
This article presents Part of Speech tagging for Nepali text using General Regression Neural
Network (GRNN). The corpus is divided into two parts viz. training and testing. The network is
trained and validated on both training and testing data. It is observed that 96.13% words are
correctly being tagged on training set whereas 74.38% words are tagged correctly on testing
data set using GRNN. The result is compared with the traditional Viterbi algorithm based on
Hidden Markov Model. Viterbi algorithm yields 97.2% and 40% classification accuracies on
training and testing data sets respectively. GRNN based POS Tagger is more consistent than the
traditional Viterbi decoding technique.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
2. 2 Computer Science & Information Technology (CS & IT)
His mathematical model of expansion is based on a set of equations to approximate the discrete-
time dynamics of malaria and asserts is possible to control the disease whenever the population of
mosquitos is reduced below a threshold. This was a new and crucial idea. Between 1927 and 1939
Kermack and McKendrick [6, 7] published papers on epidemic models and obtained the epidemic
threshold that the density of susceptibles must exceed for an epidemic outbreak to occur. This
model includes three states, the S (susceptible), I (Infectious) and R (Recovered) instead of the
two, S and I, of the Bernouilli’s model. From the mid-twentieth century a great variety of
epidemiological models have been developed after the recognition of the importance of modeling
in public health decision making [8]. In the nineties, when the scientists began to pay attention to
complex systems new paradigms spread out in order to better understand and model the impact of
numerous variables that go beyond the micro host–pathogen level, such as ecological, social,
economic, and demographic factors. Many scientists coming from such different fields as
medicine, molecular biology, computer science and applied mathematics or economy have
teamed up for rapid assessment of urgent situations of contagious diseases by means of a
multidisciplinary approach. The case of HIV/AIDS pandemic [9-12] is a good example.
This paper presents a model to approach the dynamics of infectious diseases expansion by means
of a set of neighbour rules between elements located in a lattice that represents the whole
population. Following the introduction, Section 2 provides a brief summary of the deterministic
compartmental models and highlights the Susceptible-Infectious (SI) model which has
traditionally been solved by ODE. Section 3 presents our model which considers the population
confined in a lattice. The contacts between people are performed by neighbour binary rules, that
are tailored to model different situations such as Susceptible, Infected, with or without capability
to infect further. The neighborhood is also defined depending of connectivity. We consider 4-
connection, 8-connection and horse jumping chess connection. The results are compared with
those of the simulation of ODE. Section 4 presents a discussion upon the suitability of the model
and proposes futures research. Section 5 summarises the work and presents concluding remarks.
2. MATHEMATICAL MODELLING
Three are the main categories encompassing mathematical modeling [1]. The statistical methods
deal with real epidemics. They identify their spatial patterns and allow surveillance of outbreaks.
The empirical models are based on machine learning methods such as data mining that allow the
forecasting of the evolution of an ongoing epidemic spread. The mathematical or state-space
methods provide quantitative predictions that have to be validated to forecast the evolution of a
hypothetical or real epidemic spread. These methods also redefine our understanding of
underlying mechanisms.
2.1. The Deterministic Compartmental Models
The description used in epidemiologic compartmental models is composed of standard categories
represented by the variables that model the main characteristics of the system. These
compartments, in the simplest case, divide the population into two health states: susceptible to the
infection (denoted by S) and infected (denoted by I) [13]. The way that these compartments
interact is often based upon phenomenological assumptions, and the model is built up from there.
Usually these models are depicted by ODE, which are deterministic, but can also be viewed in
more realistic stochastic framework [14]. To achieve more realism, other compartments are often
included, namely the recovered (or removed or immune) compartment labelled by R, or the
3. Computer Science & Information Technology (CS & IT) 3
exposed compartment, labelled by E. The stratification of these compartments lead to well-known
models such as SIS [15], SIR [16], SEIR [17, 18],…or more complex ones [19]. The number of
variables to be incorporated to the model depends on the particular disease being studied as well
as on the desired complexity of the model. Other variables incorporated into the equation
represent fundamental quantities such as birth rate, rate of transmission of infectious agent, death
rate, and so forth, and are constants that can be changed.
2.2. The Traditional Susceptible-Infectious (SI) Model
In the SI model the two groups are the susceptible hosts, S, that are not infected by the pathogen
but can get infected, and the infected hosts, I, who are infected by the pathogen. Assuming the
mass-action model, the rate at which susceptible hosts become infected is a product of the number
of contacts each host has per unit time, r, the probability of transmission of infection per contact,
β, and the proportion of the host population that is infectious, I/N, where N = S + I is the total
population size. This model is suitable to represent the case of the human immune deficiency
virus (HIV) where there is no recovery. A schematic of the model is shown in Figure 1.
Figure 1. SI Model
Equations (1) for the SI model are as follows:
Since the population size is fixed, we can reduce the system to one dimension with the
substitution S = N – I to provide the logistic Equation (2).
We can analytically solve Equation (2) with the initial condition I(0) = I0, so
The simulation of the SI model is shown in Figure 2 with the initial value I (0) = I0 = 1
4. 4 Computer Science & Information Technology (CS & IT)
Figure 2. Simulation of the traditional SI Model
3. OUR PROPOSAL
Our proposal is based on a set of elementary binary rules that have the capability to model
interactions between two individuals [20-23]. Without loss of generality we consider a two-
dimensional square lattice, every cell represents a susceptible person except the one at the center
which locates an infected one. When the infected person contacts with his/her neighbors he/she
spreads the disease. The new infected people have then the capability to infect other people.
3.1. Binary neighbor rules
Equation (4) defines a generic binary neighbor rule denoted ⊗.
The ⊗ rule can be represented by a two input table that defines concretely the operation, as shown
in Figure 3.
Figure 3. Generic neighbor rule represented by a table
Let m stand for the number of the rule. The number is represented by the four bits stored in the
cells; m = a3 a2 a1 a0, ∈ [0, 24
-1]; ai ∈ (0, 1); i ∈ [0, 3]. As an example, we consider m = 7, that is
to say a3 = 0; a2 = 1; a1 = 1 and a0 = 1.
5. Computer Science & Information Technology (CS & IT) 5
Figure 4. The rule nº 7 represented by a table (a3 = 0; a2 = 1; a1 = 1; a0 = 1)
The table defines concretely the operation as follows:
0 ⊗ 0 = 0; 0 ⊗ 1 = 1; 1 ⊗ 0 = 1 and 1 ⊗ 1 = 1
This operation is suitable to model the interaction between infected people and susceptible people
by identifying “0” as susceptible and “1” as infected. The previous operation means that infected
people can transmit the disease to susceptible people (1 ⊗ 0 = 1), when infected people contact
other infected people, all them remain infected (1 ⊗ 1 = 1), susceptible people have no effects
upon people (0 ⊗ 0 = 0 and 0 ⊗ 1 = 1).
3.2. Neighborhood rules modelling the spreading of a disease
In the following two-dimensional square lattices we present the spreading of a disease by a
unique Infected (“1”) located at the center of the lattice. All the empty cells are considered to be
Susceptible (“0”). The red numbers stand for the generation number (time unit) the spreading
occurs. Figure 5 shows the case of a 5x5 lattice with a contagion rate ρ = 4 per generation (4-
connected cells are neighbors to every cell that touches one of their edges, following the Von
Neumann neighbourhood).
Figure 5. The spreading of a disease in a 5x5 lattice with ρ = 4 (4-connected cells)
The spreading of the disease results in a diamond-shaped region shown for rate = 4 in Figure 5.
The evolution of the infected people can be carried out by means of the equation 1+2ρ(ρ+1),
where ρ stands for the rate.
6. 6 Computer Science & Information Technology (CS & IT)
The same example is presented for 8-connected cells (with horizontal, vertical, and diagonal
connection) following the Moore neighborhood, and for the jumping chess neighbourhood. See
Figures 6 and 7 respectively.
Figure 6. The spreading of a disease in a 5x5 lattice with ρ = 8 (8-connected cells)
For the 8-connected neighborhood, the evolution of the infected people can be carried out by
means of the equation (2ρ+1)2
.
Figure 7. The spreading of a disease in a 5x5 lattice with ρ = 8 (horse jumping chess connected cells)
3.3. Comparison Between the Traditional SI Model and the 4-Connected
Neigborhood Model
The following graph represents the 4-connected case in a 32x32 lattice, equivalent to N=1024 (in
order to approximate the graphic shown in Figure 2 where N=1000).
7. Computer Science & Information Technology (CS & IT) 7
Figure 8. The spreading of a disease in a 32x32=1024 lattice with ρ = 4 (4 -connected cells).
The comparison between Figures 2 and 8 suggests that the 4-connected cells (Von Neumann
neighbourhood) could be a suitable approximation to approach the traditional SI model. In order
to better compare the models, we now compare the previous simulation based on Equation 2 with
our 4-connected neighborhood model for similar populations, lattices 10x10, equivalent to N=100
and 100x100, equivalent to N=10000, See Figures 9 and 10.
Figure 9. The spreading of a disease in a 10x10 lattice with a ρ = 4 (4 -connected cells), compared to the
simulation of the traditional model (N=100, βr = 0,82).
Figure 10. The spreading of a disease in a 100x100 lattice with ρ = 4 (4 -connected cells), compared to the
simulation of the traditional model (N=10000, βr = 0,182).
9. Computer Science & Information Technology (CS & IT) 9
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AUTHORS
Maria Teresa Signes Pont received the BS degree in Computer Science at the
Institut National des Sciences Appliquées, Toulouse (France) and the BS degree
in Physics at the Universidad Nacional de Educación a Distancia (Spain). She
received the PhD in Computer Science at the University of Alicante in 2005.
Since 1996, she is a member of the Computer Science and Technology
department of the same university where she is currently an associate professor
and researcher. Her areas of research at the Specialized Processors Architecture
Laboratory include computer arithmetic and the design of floating point units,
approximation algorithms related to VLSI design and natural systems modelling.
Higinio Mora Mora received the BS degree in computer science engineering and
the BS degree in business studies in University of Alicante, Spain, in 1996 and
1997, respectively. He received the PhD degree in computer science from the
University of Alicante in 2003. Since 2002, he is a member of the faculty of the
Computer Technology and Computation Department at the same university where
he is currently an associate professor and researcher of Specialized Processors
Architecture Laboratory. His areas of research interest include computer
modelling, computer architectures, high performance computing, embedded
systems, internet of things and cloud computing paradigm.
Antonio Cortes Castillo is a computer engineer trained in the Latin American
University of Science and Technology (ULACIT), Costa Rica, 1995. He obtained
his bachelor's degree in computer engineering with an emphasis in Management
Information Systems at the National University of Heredia, Costa Rica, 2002.
Adquiere his Master's degree in Computer Science (Telematics) at the
Technological Institute of Costa Rica. He is now teaching at the University of
Panama and is with his PhD. at the University of Alicante.