Life science research aims to continuously improve the quality and standard of human life. One of the major challenges in this area is to maintain food safety and security. A number of image processing techniques have...Life science research aims to continuously improve the quality and standard of human life. One of the major challenges in this area is to maintain food safety and security. A number of image processing techniques have been used to investigate the quality of food products. In this paper, we propose a new algorithm to effectively segment connected grains so that each of them can be inspected in a later processing stage. One family of the existing segmentation methods is based on the idea of watersheding, and it has shown promising results in practice. However, due to the over-segmentation issue, this technique has experienced poor performance in various applications, such as inhomogeneous background and connected targets. To solve this problem, we present a combination of two classical techniques to handle this issue. In the first step, a mean shift filter is used to eliminate the inhomogeneous background,where entropy is used to be a converging criterion. Secondly, a color gradient algorithm is used in order to detect the most significant edges, and a marked watershed transform is applied to segment cluttered objects out of the previous processing stages. The proposed framework is capable of compromising among execution time, usability, efficiency and segmentation outcome in analyzing ring die pellets. The experimental results demonstrate that the proposed approach is effectiveness and robust.展开更多
The time dependence of probability and Shannon entropy of a modified damped harmonic oscillator is studied by using single and double Gaussian wave functions through the Feynman path method. We establish that the damp...The time dependence of probability and Shannon entropy of a modified damped harmonic oscillator is studied by using single and double Gaussian wave functions through the Feynman path method. We establish that the damped coefficient as well as the system frequency and the distance separating two consecutive waves of the initial double Gaussian function influences the coherence of the system and can be used to control its decoherence.展开更多
Under natural assumptions on the thermodynamic properties of space and time with the holo-graphic principle, we reproduce a MOND-like behaviour of gravity on particular scales of mass and length, where Newtonian gravi...Under natural assumptions on the thermodynamic properties of space and time with the holo-graphic principle, we reproduce a MOND-like behaviour of gravity on particular scales of mass and length, where Newtonian gravity requires a modification or extension if no dark matter component is introduced in the description of gravitational phenomena. The result is directly obtained with the assumption that a fundamental constant of nature with dimensions of acceleration needs to be introduced into gravitational interactions. This in turn allows for modifications or extensions of the equipartion law and/or the holographic principle. In other words, MOND-like phenomenology can be reproduced when appropriate generalised concepts at the thermodynamical level of space and/or at the holographic principle are introduced. Thermodynamical modifications are reflected in extensions to the equipartition law which occur when the temperature of the system drops below a critical value, equals to Unruh’s temperature evaluated at the acceleration constant scale introduced for the description of the gravitational phenomena. Our calculations extend the ones by [1] in which Newtonian gravity is shown to be an emergent phenomenon, and together with it reinforces the idea that gravity at all scales is emergent.展开更多
This paper suggests a new modified version of the traditional Weibull distribution by adding a new shape parameter utilising the modified alpha power transformed technique.We refer to the new model as modified alpha p...This paper suggests a new modified version of the traditional Weibull distribution by adding a new shape parameter utilising the modified alpha power transformed technique.We refer to the new model as modified alpha power transformed Weibull distribution.The attractiveness and significance of the new distribution lie in its power to model monotone and non-monotone failure rate functions,which are quite familiar in environmental investigations.Its hazard rate function can be decreasing,increasing,bathtub and upside-down then bathtub shaped.Diverse structural properties of the proposed model are acquired including quantile function,moments,entropies,order statistics,residual life and reversed failure rate function.The parameters of the distribution were estimated using the maximum likelihood function.The maximum likelihood method is employed to estimate the model parameters and the approximate confidence intervals are also computed.Via a simulation study,the performance of the point and interval estimates are compared using different criteria.Employing real lifetime data sets,we verify that the offered model furnishes a better fit than some other lifetime models including Weibull,gamma and alpha powerWeibull models.展开更多
We assume exponential corrections to the entropy of 5D charged Ad S black hole solutions,which are derived within the framework of Einstein-Gauss-Bonnet gravity and nonlinear electrodynamics.Additionally,we consider t...We assume exponential corrections to the entropy of 5D charged Ad S black hole solutions,which are derived within the framework of Einstein-Gauss-Bonnet gravity and nonlinear electrodynamics.Additionally,we consider two distinct versions of 5D charged Ad S black holes by setting the parameters q→0 and k→0(where q represents the charge,and k is the non-linear parameter).We investigate these black holes in the extended phase space,where the cosmological constant is interpreted as pressure,demonstrating the first law of black hole thermodynamics.The focus extends to understanding the thermal stability or instability,as well as identifying first and second-order phase transitions.This exploration is carried out through the analysis of various thermodynamic quantities,including heat capacity at constant pressure,Gibbs free energy(GFE),Helmholtz free energy(HFE),and the trace of the Hessian matrix.In order to visualize phase transitions,identify critical points,analyze stability and provide comprehensive analysis,we have made the contour plot of the mentioned thermodynamic quantities and observed that our results are very consistent.These investigations are conducted within the context of exponentially corrected entropies,providing valuable insights into the intricate thermodynamic behavior of these 5D charged Ad S black holes under different parameter limits.展开更多
Under the modern risk-oriented audit, a reasonable evaluation of materialmisstatement risk is crucial for certified public accountants to determine the level ofmateriality and implement further substantive procedures....Under the modern risk-oriented audit, a reasonable evaluation of materialmisstatement risk is crucial for certified public accountants to determine the level ofmateriality and implement further substantive procedures. This paper proposes a materialmisstatement risk assessment model based on the combined use of entropy weight-TOPSISand grey relational analysis methods and evaluates the material misstatement risk in China'sMedical CRO Industry by quantitative means. Taking the medical CRO industry as anexample, this paper selects some case companies in the industry for horizontal comparison,and at the same time conducts a multi-year data comparison on the enterprise with the highestaudit risk among them. The results show that Bio-Sincerity Pharmaceutical is an enterprisewith relatively high audit risk in the Medical CRO Industry in recent years, and thecalculation results of the model are basically consistent with the actual analysis. Toeffectively prevent financial risks and audit risks, financial personnel should participate inbusiness management, analysis and budgeting, and auditors should also focus on auditsegments such as dynamic cash flow, debt structure, and business contracts and debtmanagement in combination with the characteristics of the Medical CRO Industry, so as toeffectively reduce the risk of audit misstatements.展开更多
In this assignment we will present a reconstruction scheme between f(R) gravity with ordinary and entropy corrected(m, n)-type holographic dark energy. The correspondence is established and expressions for the reconst...In this assignment we will present a reconstruction scheme between f(R) gravity with ordinary and entropy corrected(m, n)-type holographic dark energy. The correspondence is established and expressions for the reconstructed f(R) models are determined. To study the evolution of the reconstructed models plots are generated. The stability of the calculated models are also investigated using the squared speed of sound in the background of the reconstructed gravities.展开更多
While smart wearables and remote devices have improved the speed of diagnosis and treatment,they have also created significant cybersecurity risks,especially with regard to the confidentiality and integrity of medical...While smart wearables and remote devices have improved the speed of diagnosis and treatment,they have also created significant cybersecurity risks,especially with regard to the confidentiality and integrity of medical data.Because the primary means of operation for these Internet of Things(IoT)devices is constant data transmission,they are vulnerable to cyberthreats including Distributed Denial-of-Service(DDoS)assaults and data injection.This study suggests an AI-based Healthcare Cybersecurity System(AI-HCsS)that integrates blockchain tech-nology to mitigate these vulnerabilities and provide strong,real-time patient data and healthcare system pro-tection.A new architecture is shown to identify and counteract DDoS attacks on the cloud infrastructure,and blockchain is used for safe and unchangeable data storage.The system extracts statistical,raw,and enhanced entropy-based features after performing improved min-max normalization for data pre-processing.Then,for precise DDoS attack detection,a modified Parallel Convolutional Neural Network(PCNN)is used.The model's output is interpreted using the SHapley Additive exPlanations(SHAP)approach,which identifies important characteristics that affect detection performance in order to improve transparency and aid clinical decision-making.According to experimental results,the modified PCNN outperforms traditional methods with a high detection accuracy of 91.1%.In addition to bolstering the cybersecurity of healthcare IoT ecosystems,this in-tegrated solution guarantees the real-time defense of clinical systems and patient data against changing cyberthreats.展开更多
Railway point machine(RPM)condition monitoring has attracted engineers’attention for safe train operation and accident prevention.To realize the fast and accurate fault diagnosis of RPMs,this paper proposes a method ...Railway point machine(RPM)condition monitoring has attracted engineers’attention for safe train operation and accident prevention.To realize the fast and accurate fault diagnosis of RPMs,this paper proposes a method based on entropy measurement and broad learning system(BLS).Firstly,the modified multi-scale symbolic dynamic entropy(MMSDE)module extracts dynamic characteristics from the collected acoustic signals as entropy features.Then,the fuzzy BLS takes the above entropy features as input to complete model training.Fuzzy BLS introduces the Takagi-Sug eno fuzzy system into BLS,which improves the model’s classification performance while considering computational speed.Experimental results indicate that the proposed method significantly reduces the running time while maintaining high accuracy.展开更多
基金supported by National Key Scientific Apparatus Development of Special Item of China(No.2012YQ15008703)Nantong Research Program of Application Foundation(No.BK2012030)Key Project of Science and Technology Commission of Shanghai Municipality(No.14JC1402200)
文摘Life science research aims to continuously improve the quality and standard of human life. One of the major challenges in this area is to maintain food safety and security. A number of image processing techniques have been used to investigate the quality of food products. In this paper, we propose a new algorithm to effectively segment connected grains so that each of them can be inspected in a later processing stage. One family of the existing segmentation methods is based on the idea of watersheding, and it has shown promising results in practice. However, due to the over-segmentation issue, this technique has experienced poor performance in various applications, such as inhomogeneous background and connected targets. To solve this problem, we present a combination of two classical techniques to handle this issue. In the first step, a mean shift filter is used to eliminate the inhomogeneous background,where entropy is used to be a converging criterion. Secondly, a color gradient algorithm is used in order to detect the most significant edges, and a marked watershed transform is applied to segment cluttered objects out of the previous processing stages. The proposed framework is capable of compromising among execution time, usability, efficiency and segmentation outcome in analyzing ring die pellets. The experimental results demonstrate that the proposed approach is effectiveness and robust.
文摘The time dependence of probability and Shannon entropy of a modified damped harmonic oscillator is studied by using single and double Gaussian wave functions through the Feynman path method. We establish that the damped coefficient as well as the system frequency and the distance separating two consecutive waves of the initial double Gaussian function influences the coherence of the system and can be used to control its decoherence.
文摘Under natural assumptions on the thermodynamic properties of space and time with the holo-graphic principle, we reproduce a MOND-like behaviour of gravity on particular scales of mass and length, where Newtonian gravity requires a modification or extension if no dark matter component is introduced in the description of gravitational phenomena. The result is directly obtained with the assumption that a fundamental constant of nature with dimensions of acceleration needs to be introduced into gravitational interactions. This in turn allows for modifications or extensions of the equipartion law and/or the holographic principle. In other words, MOND-like phenomenology can be reproduced when appropriate generalised concepts at the thermodynamical level of space and/or at the holographic principle are introduced. Thermodynamical modifications are reflected in extensions to the equipartition law which occur when the temperature of the system drops below a critical value, equals to Unruh’s temperature evaluated at the acceleration constant scale introduced for the description of the gravitational phenomena. Our calculations extend the ones by [1] in which Newtonian gravity is shown to be an emergent phenomenon, and together with it reinforces the idea that gravity at all scales is emergent.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project No.(PNURSP2022R50),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘This paper suggests a new modified version of the traditional Weibull distribution by adding a new shape parameter utilising the modified alpha power transformed technique.We refer to the new model as modified alpha power transformed Weibull distribution.The attractiveness and significance of the new distribution lie in its power to model monotone and non-monotone failure rate functions,which are quite familiar in environmental investigations.Its hazard rate function can be decreasing,increasing,bathtub and upside-down then bathtub shaped.Diverse structural properties of the proposed model are acquired including quantile function,moments,entropies,order statistics,residual life and reversed failure rate function.The parameters of the distribution were estimated using the maximum likelihood function.The maximum likelihood method is employed to estimate the model parameters and the approximate confidence intervals are also computed.Via a simulation study,the performance of the point and interval estimates are compared using different criteria.Employing real lifetime data sets,we verify that the offered model furnishes a better fit than some other lifetime models including Weibull,gamma and alpha powerWeibull models.
基金the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Research Project under Grant No.RGP2/539/45。
文摘We assume exponential corrections to the entropy of 5D charged Ad S black hole solutions,which are derived within the framework of Einstein-Gauss-Bonnet gravity and nonlinear electrodynamics.Additionally,we consider two distinct versions of 5D charged Ad S black holes by setting the parameters q→0 and k→0(where q represents the charge,and k is the non-linear parameter).We investigate these black holes in the extended phase space,where the cosmological constant is interpreted as pressure,demonstrating the first law of black hole thermodynamics.The focus extends to understanding the thermal stability or instability,as well as identifying first and second-order phase transitions.This exploration is carried out through the analysis of various thermodynamic quantities,including heat capacity at constant pressure,Gibbs free energy(GFE),Helmholtz free energy(HFE),and the trace of the Hessian matrix.In order to visualize phase transitions,identify critical points,analyze stability and provide comprehensive analysis,we have made the contour plot of the mentioned thermodynamic quantities and observed that our results are very consistent.These investigations are conducted within the context of exponentially corrected entropies,providing valuable insights into the intricate thermodynamic behavior of these 5D charged Ad S black holes under different parameter limits.
文摘Under the modern risk-oriented audit, a reasonable evaluation of materialmisstatement risk is crucial for certified public accountants to determine the level ofmateriality and implement further substantive procedures. This paper proposes a materialmisstatement risk assessment model based on the combined use of entropy weight-TOPSISand grey relational analysis methods and evaluates the material misstatement risk in China'sMedical CRO Industry by quantitative means. Taking the medical CRO industry as anexample, this paper selects some case companies in the industry for horizontal comparison,and at the same time conducts a multi-year data comparison on the enterprise with the highestaudit risk among them. The results show that Bio-Sincerity Pharmaceutical is an enterprisewith relatively high audit risk in the Medical CRO Industry in recent years, and thecalculation results of the model are basically consistent with the actual analysis. Toeffectively prevent financial risks and audit risks, financial personnel should participate inbusiness management, analysis and budgeting, and auditors should also focus on auditsegments such as dynamic cash flow, debt structure, and business contracts and debtmanagement in combination with the characteristics of the Medical CRO Industry, so as toeffectively reduce the risk of audit misstatements.
文摘In this assignment we will present a reconstruction scheme between f(R) gravity with ordinary and entropy corrected(m, n)-type holographic dark energy. The correspondence is established and expressions for the reconstructed f(R) models are determined. To study the evolution of the reconstructed models plots are generated. The stability of the calculated models are also investigated using the squared speed of sound in the background of the reconstructed gravities.
文摘While smart wearables and remote devices have improved the speed of diagnosis and treatment,they have also created significant cybersecurity risks,especially with regard to the confidentiality and integrity of medical data.Because the primary means of operation for these Internet of Things(IoT)devices is constant data transmission,they are vulnerable to cyberthreats including Distributed Denial-of-Service(DDoS)assaults and data injection.This study suggests an AI-based Healthcare Cybersecurity System(AI-HCsS)that integrates blockchain tech-nology to mitigate these vulnerabilities and provide strong,real-time patient data and healthcare system pro-tection.A new architecture is shown to identify and counteract DDoS attacks on the cloud infrastructure,and blockchain is used for safe and unchangeable data storage.The system extracts statistical,raw,and enhanced entropy-based features after performing improved min-max normalization for data pre-processing.Then,for precise DDoS attack detection,a modified Parallel Convolutional Neural Network(PCNN)is used.The model's output is interpreted using the SHapley Additive exPlanations(SHAP)approach,which identifies important characteristics that affect detection performance in order to improve transparency and aid clinical decision-making.According to experimental results,the modified PCNN outperforms traditional methods with a high detection accuracy of 91.1%.In addition to bolstering the cybersecurity of healthcare IoT ecosystems,this in-tegrated solution guarantees the real-time defense of clinical systems and patient data against changing cyberthreats.
基金supported in part by the Fundamental Research Funds for the Central Universities(Grant No.2021RC271)NSFC(Grants No.62120106011,52172323 and U22A2046).
文摘Railway point machine(RPM)condition monitoring has attracted engineers’attention for safe train operation and accident prevention.To realize the fast and accurate fault diagnosis of RPMs,this paper proposes a method based on entropy measurement and broad learning system(BLS).Firstly,the modified multi-scale symbolic dynamic entropy(MMSDE)module extracts dynamic characteristics from the collected acoustic signals as entropy features.Then,the fuzzy BLS takes the above entropy features as input to complete model training.Fuzzy BLS introduces the Takagi-Sug eno fuzzy system into BLS,which improves the model’s classification performance while considering computational speed.Experimental results indicate that the proposed method significantly reduces the running time while maintaining high accuracy.
