Pub Date : 2022-09-09DOI: 10.1080/09720510.2022.2119000
Yashpal Soni, G. Gandhi, D. Goyal
Abstract India is a country that needs lot of effort to be put in on healthcare, specially on infrastructure and manpower both. Government of India & Rajasthan both are focusing on great schemes like Aayushman, Chirangivi, RGHS etc. Technological enhancements have helped world access facilities in much better way and health sector is no exception and e-health with different facilities like doctor on phone (tele-health), and medicine delivery (tele-medicine) etc. have extended like anything. With advances in AI and Cloud, strong e-health infrastructure for countries likes India has become a priority. This paper proposes a strong and secure framework for delivering good healthcare to the rural Rajasthan, facilitating all resources at their door step.
{"title":"A secure e-health framework for rural Rajasthan","authors":"Yashpal Soni, G. Gandhi, D. Goyal","doi":"10.1080/09720510.2022.2119000","DOIUrl":"https://doi.org/10.1080/09720510.2022.2119000","url":null,"abstract":"Abstract India is a country that needs lot of effort to be put in on healthcare, specially on infrastructure and manpower both. Government of India & Rajasthan both are focusing on great schemes like Aayushman, Chirangivi, RGHS etc. Technological enhancements have helped world access facilities in much better way and health sector is no exception and e-health with different facilities like doctor on phone (tele-health), and medicine delivery (tele-medicine) etc. have extended like anything. With advances in AI and Cloud, strong e-health infrastructure for countries likes India has become a priority. This paper proposes a strong and secure framework for delivering good healthcare to the rural Rajasthan, facilitating all resources at their door step.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132838188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-18DOI: 10.1080/09720510.2022.2092262
Rakesh Kumar Pattanaik, B. K. Pattanayak, M. Mohanty
Abstract In practice, the dynamics of the system are uncertain due to nonlinear and dynamic characteristics. It is difficult to establish accurate identification and prediction of the nonlinear plants that require dynamic modelling of the system. Extreme learning machine (ELM) as the recursive model due to its fast training and convergence speed is utilized in this work. However, its limitation is that it has only 1 hidden neuron which tends to make evolution speed low. Further, Multi-layer ELM (ML-ELM) model is applied on a nonlinear Auto-regressive complex benchmark system. The performance of ML-ELM is compared with dynamic recurrent functional link neural network (DRFLNN), functional link neural network (FLNN), nonlinear auto-regressive moving average (NARAX), multi-layer perception (MLP), radial basis function network (RBFN), Elman recurrent neural network (ERNN), and basic ELM models. From the comparison table, it can be seen that ML-ELM has better performance as compared with other models.
{"title":"Use of multilayer recursive model for non-linear dynamic system identification","authors":"Rakesh Kumar Pattanaik, B. K. Pattanayak, M. Mohanty","doi":"10.1080/09720510.2022.2092262","DOIUrl":"https://doi.org/10.1080/09720510.2022.2092262","url":null,"abstract":"Abstract In practice, the dynamics of the system are uncertain due to nonlinear and dynamic characteristics. It is difficult to establish accurate identification and prediction of the nonlinear plants that require dynamic modelling of the system. Extreme learning machine (ELM) as the recursive model due to its fast training and convergence speed is utilized in this work. However, its limitation is that it has only 1 hidden neuron which tends to make evolution speed low. Further, Multi-layer ELM (ML-ELM) model is applied on a nonlinear Auto-regressive complex benchmark system. The performance of ML-ELM is compared with dynamic recurrent functional link neural network (DRFLNN), functional link neural network (FLNN), nonlinear auto-regressive moving average (NARAX), multi-layer perception (MLP), radial basis function network (RBFN), Elman recurrent neural network (ERNN), and basic ELM models. From the comparison table, it can be seen that ML-ELM has better performance as compared with other models.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122909270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-18DOI: 10.1080/09720510.2022.2092263
G. Patra, M. Mohanty
Abstract The prediction of the stock prices is a very challenging task as the data is associated with nonlinearity and volatility. The machine learning and artificial intelligence methods have been found to make this task more efficient and the advent of high throughput computes have proved to be beneficial in these tasks. In this work a hybrid LSTM-GRU network has been used for prediction of the adjusted closing price of the Standard & Poor 500 index. Also, the initial number of six features have been increased to 25 features by adding several technical indicators. The performance indicators like Return ratio, R2, MSE, Optimism and Pessimism ratios are used to compare the proposed model with stand-alone LSTM, GRU and MLP models. This comparison establishes that the proposed model is capable of more accurate prediction of the stock market prices.
{"title":"An LSTM-GRU based hybrid framework for secured stock price prediction","authors":"G. Patra, M. Mohanty","doi":"10.1080/09720510.2022.2092263","DOIUrl":"https://doi.org/10.1080/09720510.2022.2092263","url":null,"abstract":"Abstract The prediction of the stock prices is a very challenging task as the data is associated with nonlinearity and volatility. The machine learning and artificial intelligence methods have been found to make this task more efficient and the advent of high throughput computes have proved to be beneficial in these tasks. In this work a hybrid LSTM-GRU network has been used for prediction of the adjusted closing price of the Standard & Poor 500 index. Also, the initial number of six features have been increased to 25 features by adding several technical indicators. The performance indicators like Return ratio, R2, MSE, Optimism and Pessimism ratios are used to compare the proposed model with stand-alone LSTM, GRU and MLP models. This comparison establishes that the proposed model is capable of more accurate prediction of the stock market prices.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123001970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-18DOI: 10.1080/09720510.2022.2083831
Yang-Chu Lin, Ming-Jheng Lin
Abstract The advertising effect on consumers would be affected not only by the presentation of advertising messages but also by other factors. This study was based on the regulatory focus theory, mainly discussing the relationship among consumer goal orientation fits, the consumers’ product knowledge and advertising effects. In this study, 285 valid questionnaires were obtained. The results of the study showed that it has a better advertising effect in terms of the attitude toward advertising, attitude toward the brand, and purchase intention when the consumer goal orientation is the promotion focus, and the messages on advertising have promotion benefits. Moreover, when the consumer goal orientation fits the benefits of the advertising messages, and the consumers’ product knowledge is on the novice level, rather than expert level, consumers in the fit situation are more likely to have a better attitude toward advertising, attitude toward the brand and, purchase intention than in non-fit situations.
{"title":"Exploring the influence of regulatory fit on advertising effect - the moderating effect of consumer product knowledge","authors":"Yang-Chu Lin, Ming-Jheng Lin","doi":"10.1080/09720510.2022.2083831","DOIUrl":"https://doi.org/10.1080/09720510.2022.2083831","url":null,"abstract":"Abstract The advertising effect on consumers would be affected not only by the presentation of advertising messages but also by other factors. This study was based on the regulatory focus theory, mainly discussing the relationship among consumer goal orientation fits, the consumers’ product knowledge and advertising effects. In this study, 285 valid questionnaires were obtained. The results of the study showed that it has a better advertising effect in terms of the attitude toward advertising, attitude toward the brand, and purchase intention when the consumer goal orientation is the promotion focus, and the messages on advertising have promotion benefits. Moreover, when the consumer goal orientation fits the benefits of the advertising messages, and the consumers’ product knowledge is on the novice level, rather than expert level, consumers in the fit situation are more likely to have a better attitude toward advertising, attitude toward the brand and, purchase intention than in non-fit situations.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134476058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-18DOI: 10.1080/09720510.2022.2099066
Ben Ebo Attom, Afzalur Rahman
Abstract This study checked the impact of Working Capital on the performance of the manufacturing company. The result of the study has been taken form the manufacturing companies listed in the Ghana. The GSE (Ghana Stock Exchange) published data from January 1, 2013, to December 31, 2019 were collected for the research purpose. Based on the Hausman test, a random effect model (REM) of OLS panel estimation was appropriately used as model specification using E-Views. The study found that the accounts receivables period (ARP) negatively affects the Return on Assets (ROA) at a 10% significance level, but it has a negative insignificant relationship with the market value of companies. At a 1% level of significance, ROA and GROWTH have a significant positive relationship.
{"title":"Impact of the components of working capital on profitability and market value of listed manufacturing firms in Ghana","authors":"Ben Ebo Attom, Afzalur Rahman","doi":"10.1080/09720510.2022.2099066","DOIUrl":"https://doi.org/10.1080/09720510.2022.2099066","url":null,"abstract":"Abstract This study checked the impact of Working Capital on the performance of the manufacturing company. The result of the study has been taken form the manufacturing companies listed in the Ghana. The GSE (Ghana Stock Exchange) published data from January 1, 2013, to December 31, 2019 were collected for the research purpose. Based on the Hausman test, a random effect model (REM) of OLS panel estimation was appropriately used as model specification using E-Views. The study found that the accounts receivables period (ARP) negatively affects the Return on Assets (ROA) at a 10% significance level, but it has a negative insignificant relationship with the market value of companies. At a 1% level of significance, ROA and GROWTH have a significant positive relationship.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131270263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-29DOI: 10.1080/09720510.2021.2000169
S. Yaghoubi, R. Farnoosh, M. Behzadi
{"title":"Model-based clustering (MBC) for road data via multivariate mixture of normal distributions and factor analysis (FA)","authors":"S. Yaghoubi, R. Farnoosh, M. Behzadi","doi":"10.1080/09720510.2021.2000169","DOIUrl":"https://doi.org/10.1080/09720510.2021.2000169","url":null,"abstract":"","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121714041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-29DOI: 10.1080/09720510.2022.2060613
Lucas David Ribeiro-Reis
Abstract A new distribution for the unit interval is defined. This distribution can be inflated in 1’s, thus being superior to the beta and Kumaraswamy distributions. Analytical expressions for the mode, quantile function, ordinary moments, incomplete moments and Rényi entropy are described. The generation of random numbers can be done easily. The estimation of the parameters is done by maximum likelihood. To validate the accuracy of the maximum likelihood estimator, Monte Carlo simulation studies are performed. Application to real data has shown that the new model is better than other well-known distributions.
{"title":"Truncated exponentiated-exponential distribution: A distribution for unit interval","authors":"Lucas David Ribeiro-Reis","doi":"10.1080/09720510.2022.2060613","DOIUrl":"https://doi.org/10.1080/09720510.2022.2060613","url":null,"abstract":"Abstract A new distribution for the unit interval is defined. This distribution can be inflated in 1’s, thus being superior to the beta and Kumaraswamy distributions. Analytical expressions for the mode, quantile function, ordinary moments, incomplete moments and Rényi entropy are described. The generation of random numbers can be done easily. The estimation of the parameters is done by maximum likelihood. To validate the accuracy of the maximum likelihood estimator, Monte Carlo simulation studies are performed. Application to real data has shown that the new model is better than other well-known distributions.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114294045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-29DOI: 10.1080/09720510.2021.2020429
Nita H. Shah, Nisha Sheoran, E. Jayswal
Abstract With a major loss to human life due to the ongoing COVID-19 pandemic, it has become a major challenge for malaria endemic countries to fight against malaria - COVID-19 coinfection. This paper formulates malaria - COVID-19 co-infection model governed by a set of non-linear ordinary differential equations. The two sub-models namely- malaria only and COVID-19 only are also studied. The local stability of the disease-free equilibrium point of each sub-model and co-infection model is established. Existence of endemic equilibria for each sub-model is carried out. Moreover, we extend our co-infection model by incorporating six-time dependent controls. Using Pontryagins maximum principle we compute necessary optimal conditions and also observe the effect of each control on co-infected population.
{"title":"Optimum controls to avert co-infection of Malaria - COVID-19","authors":"Nita H. Shah, Nisha Sheoran, E. Jayswal","doi":"10.1080/09720510.2021.2020429","DOIUrl":"https://doi.org/10.1080/09720510.2021.2020429","url":null,"abstract":"Abstract With a major loss to human life due to the ongoing COVID-19 pandemic, it has become a major challenge for malaria endemic countries to fight against malaria - COVID-19 coinfection. This paper formulates malaria - COVID-19 co-infection model governed by a set of non-linear ordinary differential equations. The two sub-models namely- malaria only and COVID-19 only are also studied. The local stability of the disease-free equilibrium point of each sub-model and co-infection model is established. Existence of endemic equilibria for each sub-model is carried out. Moreover, we extend our co-infection model by incorporating six-time dependent controls. Using Pontryagins maximum principle we compute necessary optimal conditions and also observe the effect of each control on co-infected population.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117133120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-29DOI: 10.1080/09720510.2021.1995199
C. Chesneau, H. Bakouch, Lishamol Tomy, G. Veena
Abstract This paper is devoted to the properties and applications of a new one-parameter discrete distribution with support on integers. The new distribution represents a discrete analogue of the double Lindley distribution, a symmetric version of the negative binomial distribution and a weighted version of the Inusah-Kozubowski distribution. Some properties of the new distribution are derived, such as log-concavity, mode(s), cumulative density function, quantile function, probability generating function, raw moments, skewness, kurtosis, and order statistics. The parameter of the distribution is estimated by the maximum likelihood method. The usefulness of the new distribution is illustrated by means of two practical datasets with integer values on ℤ, namely stock exchange and flood data.
{"title":"A new discrete distribution on integers: Analytical and applied study on stock exchange and flood data","authors":"C. Chesneau, H. Bakouch, Lishamol Tomy, G. Veena","doi":"10.1080/09720510.2021.1995199","DOIUrl":"https://doi.org/10.1080/09720510.2021.1995199","url":null,"abstract":"Abstract This paper is devoted to the properties and applications of a new one-parameter discrete distribution with support on integers. The new distribution represents a discrete analogue of the double Lindley distribution, a symmetric version of the negative binomial distribution and a weighted version of the Inusah-Kozubowski distribution. Some properties of the new distribution are derived, such as log-concavity, mode(s), cumulative density function, quantile function, probability generating function, raw moments, skewness, kurtosis, and order statistics. The parameter of the distribution is estimated by the maximum likelihood method. The usefulness of the new distribution is illustrated by means of two practical datasets with integer values on ℤ, namely stock exchange and flood data.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129736602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-26DOI: 10.1080/09720510.2022.2060614
A. Fallah, R. Kazemi, Sajedeh Alipour
Abstract This paper investigated the accuracy of linear-moment (L-moment) approximation for spectral risk measures (SRMs). The problem is considered in two cases of individual and aggregated loss measurements. The results showed that the absolute error of this approximation increases, in terms of a linear relation, when the loss goes to have a more heavy tail distribution. Therefore, due to the right skewed and heavy tail structure of the usual loss distributions in real word applications, using the L-moment approximation to estimate the SRMs leading to inaccurate estimation of spectral risk measures.
{"title":"Accuracy of L-moments approximation for spectral risk measures in heavy tail distributions","authors":"A. Fallah, R. Kazemi, Sajedeh Alipour","doi":"10.1080/09720510.2022.2060614","DOIUrl":"https://doi.org/10.1080/09720510.2022.2060614","url":null,"abstract":"Abstract This paper investigated the accuracy of linear-moment (L-moment) approximation for spectral risk measures (SRMs). The problem is considered in two cases of individual and aggregated loss measurements. The results showed that the absolute error of this approximation increases, in terms of a linear relation, when the loss goes to have a more heavy tail distribution. Therefore, due to the right skewed and heavy tail structure of the usual loss distributions in real word applications, using the L-moment approximation to estimate the SRMs leading to inaccurate estimation of spectral risk measures.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127652025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：