In this paper, the performance of existing biased estimators (Ridge Estimator (RE), Almost Unbiased Ridge Estimator (AURE), Liu Estimator (LE), Almost Unbiased Liu Estimator (AULE), Principal Component Regression Esti...In this paper, the performance of existing biased estimators (Ridge Estimator (RE), Almost Unbiased Ridge Estimator (AURE), Liu Estimator (LE), Almost Unbiased Liu Estimator (AULE), Principal Component Regression Estimator (PCRE), r-k class estimator and r-d class estimator) and the respective predictors were considered in a misspecified linear regression model when there exists multicollinearity among explanatory variables. A generalized form was used to compare these estimators and predictors in the mean square error sense. Further, theoretical findings were established using mean square error matrix and scalar mean square error. Finally, a numerical example and a Monte Carlo simulation study were done to illustrate the theoretical findings. The simulation study revealed that LE and RE outperform the other estimators when weak multicollinearity exists, and RE, r-k class and r-d class estimators outperform the other estimators when moderated and high multicollinearity exist for certain values of shrinkage parameters, respectively. The predictors based on the LE and RE are always superior to the other predictors for certain values of shrinkage parameters.展开更多
This study investigates the nitrogen (N), phosphorous (P), and potassium (K) contents in raw biomasses of Camellia sinensis, Gliricidia sepium, and Musa acuminata. Therein, the highest N and P content was seen in Came...This study investigates the nitrogen (N), phosphorous (P), and potassium (K) contents in raw biomasses of Camellia sinensis, Gliricidia sepium, and Musa acuminata. Therein, the highest N and P content was seen in Camellia sinensis 116.80 ± 0.08 mg and 66.00 ± 0.14 mg respectively. The highest K content (106.80 ± 0.04 mg) was observed in Musa acuminata. Next, all three types of plant materials were allowed to decompose in water for 3 weeks, and a sample from each was analyzed for NPK after the 1st, 2nd, and 3rd week during decomposition. A significant increase in the release of N, P, and K by the Camellia sinensis to water (P Musa acuminate were not significantly changed (P > 0.05) over time. The ratio for N:P:K was calculated for raw biomass samples and decomposed samples to find the best fitting N:P:K ratio to apply to young tea plants as organic fertilizers. In addition to that, the microbial insight of these organic compounds was analyzed by observing how microbial population increased with decomposition by the enumeration of the total microbial count. A considerable increment in total microbial count was observed up to 3.28 × 10<sup>6</sup>, 1.21 × 10<sup>10</sup>, 2.18 × 10<sup>8</sup>, and 6.49 × 10<sup>7</sup> CFU/ml for Camellia sinensis, Gliricidia sepium, Musa accuminata (leaves), and Musa accuminata (trunk) respectively. The presence of phosphate solubilizing bacteria (PSB) and nitrogen solubilizing bacteria (NSB) throughout the decomposition period was confirmed by their growth on NBRIP and a modified nutrient medium that was specifically designed for the identification of ammonifiers respectively. Prepared fertilizer samples were applied to young tea plants that were grown in the Mawanella area in Sri Lanka (7°15'12.42"N 80°26'47.62"E) and according to the results, it is clear that fertilizer mixture 1 (N:P:K, 10:5:10, tea dust + Gliricidia + banana trunk) and fertilizer mixture 2 (N:P:K, 10:5:10, tea dust + Gliricidia + banana leaves) has the potential to increase the growth of young tea plants.展开更多
Around one in eight women will be diagnosed with breast cancer at some time.Improved patient outcomes necessitate both early detection and an accurate diagnosis.Histological images are routinely utilized in the proces...Around one in eight women will be diagnosed with breast cancer at some time.Improved patient outcomes necessitate both early detection and an accurate diagnosis.Histological images are routinely utilized in the process of diagnosing breast cancer.Methods proposed in recent research only focus on classifying breast cancer on specific magnification levels.No study has focused on using a combined dataset with multiple magnification levels to classify breast cancer.A strategy for detecting breast cancer is provided in the context of this investigation.Histopathology image texture data is used with the wavelet transform in this technique.The proposed method comprises converting histopathological images from Red Green Blue(RGB)to Chrominance of Blue and Chrominance of Red(YCBCR),utilizing a wavelet transform to extract texture information,and classifying the images with Extreme Gradient Boosting(XGBOOST).Furthermore,SMOTE has been used for resampling as the dataset has imbalanced samples.The suggested method is evaluated using 10-fold cross-validation and achieves an accuracy of 99.27%on the BreakHis 1.040X dataset,98.95%on the BreakHis 1.0100X dataset,98.92%on the BreakHis 1.0200X dataset,98.78%on the BreakHis 1.0400X dataset,and 98.80%on the combined dataset.The findings of this study imply that improved breast cancer detection rates and patient outcomes can be achieved by combining wavelet transformation with textural signals to detect breast cancer in histopathology images.展开更多
In this paper, we introduce a modification of the Quasi Lindley distribution which has various advantageous properties for the lifetime data. Several fundamental structural properties of the distribution are explored....In this paper, we introduce a modification of the Quasi Lindley distribution which has various advantageous properties for the lifetime data. Several fundamental structural properties of the distribution are explored. Its density function can be left-skewed, symmetrical, and right-skewed shapes with various rages of tail-weights and dispersions. The failure rate function of the new dist</span><span style="font-family:Verdana;">ribution has the flexibility to be increasing, decreasing, constant, an</span><span style="font-family:Verdana;">d bathtub shapes. A simulation study is done to examine the performance of maximum likelihood and moment estimation methods in its unknown parameter estimations based on the asymptotic theory. The potentiality of the new distribution is illustrated by means of applications to the simulated and three real-world data sets.展开更多
Load balancing is a technique for identifying overloaded and underloaded nodes and balancing the load between them.To maximize various performance parameters in cloud computing,researchers suggested various load balan...Load balancing is a technique for identifying overloaded and underloaded nodes and balancing the load between them.To maximize various performance parameters in cloud computing,researchers suggested various load balancing approaches.To store and access data and services provided by the different service providers through the network over different regions,cloud computing is one of the latest technology systems for both end-users and service providers.The volume of data is increasing due to the pandemic and a significant increase in usage of the internet has also been experienced.Users of the cloud are looking for services that are intelligent,and,can balance the traffic load by service providers,resulting in seamless and uninterrupted services.Different types of algorithms and techniques are available that can manage the load balancing in the cloud services.In this paper,a newly proposed method for load balancing in cloud computing at the database level is introduced.The database cloud services are frequently employed by companies of all sizes,for application development and business process.Load balancing for distributed applications can be used to maintain an efficient task scheduling process that also meets the user requirements and improves resource utilization.Load balancing is the process of distributing the load on various nodes to ensure that no single node is overloaded.To avoid the nodes from being overloaded,the load balancer divides an equal amount of computing time to all nodes.The results of two different scenarios showed the cross-region traffic management and significant growth in revenue of restaurants by using load balancer decisions on application traffic gateways.展开更多
In the presence of multicollinearity in logistic regression, the variance of the Maximum Likelihood Estimator (MLE) becomes inflated. Siray et al. (2015) [1] proposed a restricted Liu estimator in logistic regression ...In the presence of multicollinearity in logistic regression, the variance of the Maximum Likelihood Estimator (MLE) becomes inflated. Siray et al. (2015) [1] proposed a restricted Liu estimator in logistic regression model with exact linear restrictions. However, there are some situations, where the linear restrictions are stochastic. In this paper, we propose a Stochastic Restricted Maximum Likelihood Estimator (SRMLE) for the logistic regression model with stochastic linear restrictions to overcome this issue. Moreover, a Monte Carlo simulation is conducted for comparing the performances of the MLE, Restricted Maximum Likelihood Estimator (RMLE), Ridge Type Logistic Estimator(LRE), Liu Type Logistic Estimator(LLE), and SRMLE for the logistic regression model by using Scalar Mean Squared Error (SMSE).展开更多
Wireless Body Area Sensor Network(WBASN)is an automated system for remote health monitoring of patients.WBASN under umbrella of Internet of Things(IoT)is comprised of small Biomedical Sensor Nodes(BSNs)that can commun...Wireless Body Area Sensor Network(WBASN)is an automated system for remote health monitoring of patients.WBASN under umbrella of Internet of Things(IoT)is comprised of small Biomedical Sensor Nodes(BSNs)that can communicate with each other without human involvement.These BSNs can be placed on human body or inside the skin of the patients to regularly monitor their vital signs.The BSNs generate critical data as it is related to patient’s health.The data traffic can be classified as Sensitive Data(SD)and Non-sensitive Data(ND)packets based on the value of vital signs.These data packets have different priority to deliver.The ND packets may tolerate some delay or packet loss whereas,the SD packets required to be delivered on time with minimized packet loss otherwise it can be life threating to the patients.In this research,we propose a Traffic Priority-aware Medical Data Dissemination(TPMD2)scheme forWBASN to deliver the data packets according to their priority based on the sensitivity of the data.The assessment of the proposed scheme is carried out in various experiments.The simulation results of the TPMD2 scheme indicate a significant improvement in packets delivery,transmission delay and energy efficiency in comparison with the existing schemes.展开更多
Cloud systems are tools and software for cloud computing that are deployed on the Internet or a cloud computing network,and users can use them at any time.After assessing and choosing cloud providers,however,customers...Cloud systems are tools and software for cloud computing that are deployed on the Internet or a cloud computing network,and users can use them at any time.After assessing and choosing cloud providers,however,customers confront the variety and difficulty of quality of service(QoS).To increase customer retention and engagement success rates,it is critical to research and develops an accurate and objective evaluation model.Cloud is the emerging environment for distributed services at various layers.Due to the benefits of this environment,globally cloud is being taken as a standard environment for individuals as well as for the corporate sector as it reduces capital expenditure and provides secure,accessible,and manageable services to all stakeholders but Cloud computing has security challenges,including vulnerability for clients and association acknowledgment,that delay the rapid adoption of computing models.Allocation of resources in the Cloud is difficult because resources provide numerous measures of quality of service.In this paper,the proposed resource allocation approach is based on attribute QoS Scoring that takes into account parameters the reputation of the asset,task completion time,task completion ratio,and resource loading.This article is focused on the cloud service’s security,cloud reliability,and could performance.In this paper,the machine learning algorithm neuro-fuzzy has been used to address the cloud security issues to measure the parameter security and privacy,trust issues.The findings reveal that the ANFIS-dependent parameters are primarily designed to discern anomalies in cloud security and features output normally yields better results and guarantees data consistency and computational power.展开更多
Cloud computing is an emerging domain that is capturing global users from all walks of life—the corporate sector,government sector,and social arena as well.Various cloud providers have offered multiple services and f...Cloud computing is an emerging domain that is capturing global users from all walks of life—the corporate sector,government sector,and social arena as well.Various cloud providers have offered multiple services and facilities to this audience and the number of providers is increasing very swiftly.This enormous pace is generating the requirement of a comprehensive ecosystem that shall provide a seamless and customized user environment not only to enhance the user experience but also to improve security,availability,accessibility,and latency.Emerging technology is providing robust solutions to many of our problems,the cloud platform is one of them.It is worth mentioning that these solutions are also amplifying the complexity and need of sustenance of these rapid solutions.As with cloud computing,new entrants as cloud service providers,resellers,tech-support,hardware manufacturers,and software developers appear on a daily basis.These actors playing their role in the growth and sustenance of the cloud ecosystem.Our objective is to use convergence for cloud services,software-defined networks,network function virtualization for infrastructure,cognition for pattern development,and knowledge repository.In order to gear up these processes,machine learning to induce intelligence to maintain ecosystem growth,to monitor performance,and to become able to make decisions for the sustenance of the ecosystem.Workloads may be programmed to“superficially”imitate most business applications and create large numbers using lightweight workload generators that merely stress the storage.In today’s current IT environment,when many enterprises use the cloud to service some of their application demands,a different performance testing technique that assesses more than the storage is necessary.Compute and storage are merged into a single building block with HCI(Hyper-converged infrastructure),resulting in a huge pool of compute and storage resources when clustered with other building blocks.The novelty of thiswork to design and test cloud storage using themeasurement of availability,downtime,and outage parameters.Results showed that the storage reliability in a hyper-converged system is above 92%.展开更多
The past two decades witnessed a broad-increase in web technology and on-line gaming.Enhancing the broadband confinements is viewed as one of the most significant variables that prompted new gaming technology.The imme...The past two decades witnessed a broad-increase in web technology and on-line gaming.Enhancing the broadband confinements is viewed as one of the most significant variables that prompted new gaming technology.The immense utilization of web applications and games additionally prompted growth in the handled devices and moving the limited gaming experience from user devices to online cloud servers.As internet capabilities are enhanced new ways of gaming are being used to improve the gaming experience.In cloud-based video gaming,game engines are hosted in cloud gaming data centers,and compressed gaming scenes are rendered to the players over the internet with updated controls.In such systems,the task of transferring games and video compression imposes huge computational complexity is required on cloud servers.The basic problems in cloud gaming in particular are high encoding time,latency,and low frame rates which require a new methodology for a better solution.To improve the bandwidth issue in cloud games,the compression of video sequences requires an alternative mechanism to improve gaming adaption without input delay.In this paper,the proposed improved methodology is used for automatic unnecessary scene detection,scene removing and bit rate reduction using an adaptive algorithm for object detection in a game scene.As a result,simulations showed without much impact on the players’quality experience,the selective object encoding method and object adaption technique decrease the network latency issue,reduce the game streaming bitrate at a remarkable scale on different games.The proposed algorithm was evaluated for three video game scenes.In this paper,achieved 14.6%decrease in encoding and 45.6%decrease in bit rate for the first video game scene.展开更多
In this article, the restricted almost unbiased ridge logistic estimator (RAURLE) is proposed to estimate the parameter in a logistic regression model with exact linear re-strictions when there exists multicollinearit...In this article, the restricted almost unbiased ridge logistic estimator (RAURLE) is proposed to estimate the parameter in a logistic regression model with exact linear re-strictions when there exists multicollinearity among explanatory variables. The performance of the proposed estimator over the maximum likelihood estimator (MLE), ridge logistic estimator (RLE), almost unbiased ridge logistic estimator (AURLE), and restricted maximum likelihood estimator (RMLE) with respect to different ridge parameters is investigated through a simulation study in terms of scalar mean square error.展开更多
It is well known that the Einstein tensor G for a Riemannian manifold defined by Gα^β = 1/2α^β ,Rα^β=g^α^β γ where Rγα and R are respectively the Ricci tensor and the scalar curvature of the manifold, p...It is well known that the Einstein tensor G for a Riemannian manifold defined by Gα^β = 1/2α^β ,Rα^β=g^α^β γ where Rγα and R are respectively the Ricci tensor and the scalar curvature of the manifold, plays an important part in Einstein s theory of gravitation as well as in proving some theorems in Riemannian geometry. In this work, we first obtain the generalized Einstein tensor for a Weyl manifold. Then, after studying some properties of generalized Einstein tensor, we prove that the conformal invariance of the generalized Einstein tensor implies the conformal invariance of the curvature tensor of the Weyl manifold and conversely. Moreover, we show that such Weyl manifolds admit a one-parameter family of hypersurfaces the orthogonal trajectories of which are geodesics. Finally, a necessary and sufficient condition in order that the generalized circles of a Weyl manifold be preserved by a conformal mapping is stated in terms of generalized Einstein tensors at corresponding points.展开更多
Rotatability is a desirable quality of fitting response surface experimental designs. The propertystates that the variance of the estimated response made from the Taylor’s series expansion areconstant on circles, sph...Rotatability is a desirable quality of fitting response surface experimental designs. The propertystates that the variance of the estimated response made from the Taylor’s series expansion areconstant on circles, spheres and hyper-spheres about the centre of the design. In this article,a measure of rotatability of modified second-order rotatable design is presented. The variancefunction of a second-order response design and an infinite class of supplementary difference setsis used in coming up with the design.展开更多
Determination of sex from the tibial dimensions has been attempted before in different populations.The formulae developed to determine sex of one population are not appropriate to be applied to another.Seven standard ...Determination of sex from the tibial dimensions has been attempted before in different populations.The formulae developed to determine sex of one population are not appropriate to be applied to another.Seven standard variables including the maximum length of tibia,proximal epiphyseal breadth,distal epiphyseal breadth,minimum circumference of shaft,anteroposterior diameter at nutrient foramen,transverse diameter at the nutrient foramen(TDNF),and circumference at the nutrient foramen obtained from 81 adult tibiae(56 male and 25 female)were analyzed to investigate the sexual dimorphism in the tibial dimensions to establish sex estimating formulae from the tibia in a contemporary Sri Lankan population.Results confirmed the existence of sexual dimorphism of the tibia.Discriminant functions obtained resulted in the classification accuracies ranging from 61.9%to 80.2%.The most dimorphic single parameter in males was the TDNF providing an accuracy of 92.9%,while in females,the minimum circumference of shaft provided an accuracy of 70.4%.The best multivariate equation utilizing two tibial dimensions resulted in an accuracy of 80.2%after cross‑validation.We envisage that sex estimating formulae established in this study for a contemporary Sri Lankan population will contribute toward the biological profiling and identification of unknown skeletal remains.展开更多
In this paper,we propose a new biased estimator namely modified almost unbiased Liu estimator by combining almost unbiased Liu estimator(AULE)andridge estimator(RE)in a linear regression model when multicollinearity p...In this paper,we propose a new biased estimator namely modified almost unbiased Liu estimator by combining almost unbiased Liu estimator(AULE)andridge estimator(RE)in a linear regression model when multicollinearity presents amongthe independent variables.Necessary and sufficient conditions for the proposed estimator over the ordinary least square estimator,RE,AULE and Liu estimator(LE)in the mean squared error matrix sense are derived,and the optimal biasing parameters are obtained.To illustrate the theoretical findings,a Monte Carlo simulation study is carried out and a numerical example is used.展开更多
Background:Understanding the processes that structure species is one of the primary focuses in community ecology.Hubbell’s neutral model shows stochastic processes alone can describe the two macro-ecological patterns...Background:Understanding the processes that structure species is one of the primary focuses in community ecology.Hubbell’s neutral model shows stochastic processes alone can describe the two macro-ecological patterns,species richness and species-area relationship,of the community.Although Hubbell’s neutral model can explain the macro-ecological patterns of the species at large scales,it paid less attention to construct the spatial structure of the community.Previous studies suggest that such spatial structures are mostly due to habitat filtering processes work at the intermediate spatial scales.Therefore,Hubbell’s neutral model does not explain the full picture of the community structuring due to its fully stochastic nature.Results:In this study,we proposed a two-schema model that has the habitat filtering component and the stochastic component to construct the species assemblages seen in the community level.The proposed model uses one additional parameter(i.e.number of individuals in habitat)in addition to Hubbell’s three-parameter neutral model(i.e.fundamental bio-diversity number(θ),dispersal limitation(m)and speciation(v)).The proposed model works at two spatial scales:habitat filtering at the intermediate scales and stochastic processes at the large and very small spatial scales.The model coupled the local community dynamics with the meta-community dynamics.The local community has a fixed area with carrying capacity that is proportional to the local community size.The number of habitats in the proposed model can vary.Individuals are placed into habitats with probabilities according to the habitat suitability.Species richness and species composition in each habitat were calculated.The model is fitted for differentθvalues,m values,and a different number of habitats.Conclusions:We assume that habitat filtering plays an important role together with stochastic processes to structure species in forests.Therefore,the proposed model with only four parameters can explain a large proportion of the species structuring of the communities.We found that more species can be maintained in a heterogeneous environment than a uniform environment.Therefore,habitat conservation is highly important for maintaining species diversity in forest communities.展开更多
The technique of fitting a response surface design is useful in modelling of experimental designs.Response surface is used in situations where the response of interest is influenced by several experimental variables.T...The technique of fitting a response surface design is useful in modelling of experimental designs.Response surface is used in situations where the response of interest is influenced by several experimental variables.The objective of fitting a response surface design is to reduce cost of experimentation and to obtain optimal designs.The property of rotatability is a desirable quantity of experimental design and requires the variance of the fitted design to be constant on circles or spheres about the centre of the design.In this article,a construction technique of fitting modified non-sequential third order rotatable design(TORD)using Pairwise Balanced Design(PBD)is presented.The variance function of a third order response surface design and the properties of Pairwise Balanced Design are utilised for the construction.展开更多
文摘In this paper, the performance of existing biased estimators (Ridge Estimator (RE), Almost Unbiased Ridge Estimator (AURE), Liu Estimator (LE), Almost Unbiased Liu Estimator (AULE), Principal Component Regression Estimator (PCRE), r-k class estimator and r-d class estimator) and the respective predictors were considered in a misspecified linear regression model when there exists multicollinearity among explanatory variables. A generalized form was used to compare these estimators and predictors in the mean square error sense. Further, theoretical findings were established using mean square error matrix and scalar mean square error. Finally, a numerical example and a Monte Carlo simulation study were done to illustrate the theoretical findings. The simulation study revealed that LE and RE outperform the other estimators when weak multicollinearity exists, and RE, r-k class and r-d class estimators outperform the other estimators when moderated and high multicollinearity exist for certain values of shrinkage parameters, respectively. The predictors based on the LE and RE are always superior to the other predictors for certain values of shrinkage parameters.
文摘This study investigates the nitrogen (N), phosphorous (P), and potassium (K) contents in raw biomasses of Camellia sinensis, Gliricidia sepium, and Musa acuminata. Therein, the highest N and P content was seen in Camellia sinensis 116.80 ± 0.08 mg and 66.00 ± 0.14 mg respectively. The highest K content (106.80 ± 0.04 mg) was observed in Musa acuminata. Next, all three types of plant materials were allowed to decompose in water for 3 weeks, and a sample from each was analyzed for NPK after the 1st, 2nd, and 3rd week during decomposition. A significant increase in the release of N, P, and K by the Camellia sinensis to water (P Musa acuminate were not significantly changed (P > 0.05) over time. The ratio for N:P:K was calculated for raw biomass samples and decomposed samples to find the best fitting N:P:K ratio to apply to young tea plants as organic fertilizers. In addition to that, the microbial insight of these organic compounds was analyzed by observing how microbial population increased with decomposition by the enumeration of the total microbial count. A considerable increment in total microbial count was observed up to 3.28 × 10<sup>6</sup>, 1.21 × 10<sup>10</sup>, 2.18 × 10<sup>8</sup>, and 6.49 × 10<sup>7</sup> CFU/ml for Camellia sinensis, Gliricidia sepium, Musa accuminata (leaves), and Musa accuminata (trunk) respectively. The presence of phosphate solubilizing bacteria (PSB) and nitrogen solubilizing bacteria (NSB) throughout the decomposition period was confirmed by their growth on NBRIP and a modified nutrient medium that was specifically designed for the identification of ammonifiers respectively. Prepared fertilizer samples were applied to young tea plants that were grown in the Mawanella area in Sri Lanka (7°15'12.42"N 80°26'47.62"E) and according to the results, it is clear that fertilizer mixture 1 (N:P:K, 10:5:10, tea dust + Gliricidia + banana trunk) and fertilizer mixture 2 (N:P:K, 10:5:10, tea dust + Gliricidia + banana leaves) has the potential to increase the growth of young tea plants.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2023R236),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Around one in eight women will be diagnosed with breast cancer at some time.Improved patient outcomes necessitate both early detection and an accurate diagnosis.Histological images are routinely utilized in the process of diagnosing breast cancer.Methods proposed in recent research only focus on classifying breast cancer on specific magnification levels.No study has focused on using a combined dataset with multiple magnification levels to classify breast cancer.A strategy for detecting breast cancer is provided in the context of this investigation.Histopathology image texture data is used with the wavelet transform in this technique.The proposed method comprises converting histopathological images from Red Green Blue(RGB)to Chrominance of Blue and Chrominance of Red(YCBCR),utilizing a wavelet transform to extract texture information,and classifying the images with Extreme Gradient Boosting(XGBOOST).Furthermore,SMOTE has been used for resampling as the dataset has imbalanced samples.The suggested method is evaluated using 10-fold cross-validation and achieves an accuracy of 99.27%on the BreakHis 1.040X dataset,98.95%on the BreakHis 1.0100X dataset,98.92%on the BreakHis 1.0200X dataset,98.78%on the BreakHis 1.0400X dataset,and 98.80%on the combined dataset.The findings of this study imply that improved breast cancer detection rates and patient outcomes can be achieved by combining wavelet transformation with textural signals to detect breast cancer in histopathology images.
文摘In this paper, we introduce a modification of the Quasi Lindley distribution which has various advantageous properties for the lifetime data. Several fundamental structural properties of the distribution are explored. Its density function can be left-skewed, symmetrical, and right-skewed shapes with various rages of tail-weights and dispersions. The failure rate function of the new dist</span><span style="font-family:Verdana;">ribution has the flexibility to be increasing, decreasing, constant, an</span><span style="font-family:Verdana;">d bathtub shapes. A simulation study is done to examine the performance of maximum likelihood and moment estimation methods in its unknown parameter estimations based on the asymptotic theory. The potentiality of the new distribution is illustrated by means of applications to the simulated and three real-world data sets.
文摘Load balancing is a technique for identifying overloaded and underloaded nodes and balancing the load between them.To maximize various performance parameters in cloud computing,researchers suggested various load balancing approaches.To store and access data and services provided by the different service providers through the network over different regions,cloud computing is one of the latest technology systems for both end-users and service providers.The volume of data is increasing due to the pandemic and a significant increase in usage of the internet has also been experienced.Users of the cloud are looking for services that are intelligent,and,can balance the traffic load by service providers,resulting in seamless and uninterrupted services.Different types of algorithms and techniques are available that can manage the load balancing in the cloud services.In this paper,a newly proposed method for load balancing in cloud computing at the database level is introduced.The database cloud services are frequently employed by companies of all sizes,for application development and business process.Load balancing for distributed applications can be used to maintain an efficient task scheduling process that also meets the user requirements and improves resource utilization.Load balancing is the process of distributing the load on various nodes to ensure that no single node is overloaded.To avoid the nodes from being overloaded,the load balancer divides an equal amount of computing time to all nodes.The results of two different scenarios showed the cross-region traffic management and significant growth in revenue of restaurants by using load balancer decisions on application traffic gateways.
文摘In the presence of multicollinearity in logistic regression, the variance of the Maximum Likelihood Estimator (MLE) becomes inflated. Siray et al. (2015) [1] proposed a restricted Liu estimator in logistic regression model with exact linear restrictions. However, there are some situations, where the linear restrictions are stochastic. In this paper, we propose a Stochastic Restricted Maximum Likelihood Estimator (SRMLE) for the logistic regression model with stochastic linear restrictions to overcome this issue. Moreover, a Monte Carlo simulation is conducted for comparing the performances of the MLE, Restricted Maximum Likelihood Estimator (RMLE), Ridge Type Logistic Estimator(LRE), Liu Type Logistic Estimator(LLE), and SRMLE for the logistic regression model by using Scalar Mean Squared Error (SMSE).
基金This work was supported in part by Universiti TeknologiMalaysia(UTM)in the project under Institutional grant vote 08G49 and FRGS vote 5F349.
文摘Wireless Body Area Sensor Network(WBASN)is an automated system for remote health monitoring of patients.WBASN under umbrella of Internet of Things(IoT)is comprised of small Biomedical Sensor Nodes(BSNs)that can communicate with each other without human involvement.These BSNs can be placed on human body or inside the skin of the patients to regularly monitor their vital signs.The BSNs generate critical data as it is related to patient’s health.The data traffic can be classified as Sensitive Data(SD)and Non-sensitive Data(ND)packets based on the value of vital signs.These data packets have different priority to deliver.The ND packets may tolerate some delay or packet loss whereas,the SD packets required to be delivered on time with minimized packet loss otherwise it can be life threating to the patients.In this research,we propose a Traffic Priority-aware Medical Data Dissemination(TPMD2)scheme forWBASN to deliver the data packets according to their priority based on the sensitivity of the data.The assessment of the proposed scheme is carried out in various experiments.The simulation results of the TPMD2 scheme indicate a significant improvement in packets delivery,transmission delay and energy efficiency in comparison with the existing schemes.
文摘Cloud systems are tools and software for cloud computing that are deployed on the Internet or a cloud computing network,and users can use them at any time.After assessing and choosing cloud providers,however,customers confront the variety and difficulty of quality of service(QoS).To increase customer retention and engagement success rates,it is critical to research and develops an accurate and objective evaluation model.Cloud is the emerging environment for distributed services at various layers.Due to the benefits of this environment,globally cloud is being taken as a standard environment for individuals as well as for the corporate sector as it reduces capital expenditure and provides secure,accessible,and manageable services to all stakeholders but Cloud computing has security challenges,including vulnerability for clients and association acknowledgment,that delay the rapid adoption of computing models.Allocation of resources in the Cloud is difficult because resources provide numerous measures of quality of service.In this paper,the proposed resource allocation approach is based on attribute QoS Scoring that takes into account parameters the reputation of the asset,task completion time,task completion ratio,and resource loading.This article is focused on the cloud service’s security,cloud reliability,and could performance.In this paper,the machine learning algorithm neuro-fuzzy has been used to address the cloud security issues to measure the parameter security and privacy,trust issues.The findings reveal that the ANFIS-dependent parameters are primarily designed to discern anomalies in cloud security and features output normally yields better results and guarantees data consistency and computational power.
文摘Cloud computing is an emerging domain that is capturing global users from all walks of life—the corporate sector,government sector,and social arena as well.Various cloud providers have offered multiple services and facilities to this audience and the number of providers is increasing very swiftly.This enormous pace is generating the requirement of a comprehensive ecosystem that shall provide a seamless and customized user environment not only to enhance the user experience but also to improve security,availability,accessibility,and latency.Emerging technology is providing robust solutions to many of our problems,the cloud platform is one of them.It is worth mentioning that these solutions are also amplifying the complexity and need of sustenance of these rapid solutions.As with cloud computing,new entrants as cloud service providers,resellers,tech-support,hardware manufacturers,and software developers appear on a daily basis.These actors playing their role in the growth and sustenance of the cloud ecosystem.Our objective is to use convergence for cloud services,software-defined networks,network function virtualization for infrastructure,cognition for pattern development,and knowledge repository.In order to gear up these processes,machine learning to induce intelligence to maintain ecosystem growth,to monitor performance,and to become able to make decisions for the sustenance of the ecosystem.Workloads may be programmed to“superficially”imitate most business applications and create large numbers using lightweight workload generators that merely stress the storage.In today’s current IT environment,when many enterprises use the cloud to service some of their application demands,a different performance testing technique that assesses more than the storage is necessary.Compute and storage are merged into a single building block with HCI(Hyper-converged infrastructure),resulting in a huge pool of compute and storage resources when clustered with other building blocks.The novelty of thiswork to design and test cloud storage using themeasurement of availability,downtime,and outage parameters.Results showed that the storage reliability in a hyper-converged system is above 92%.
文摘The past two decades witnessed a broad-increase in web technology and on-line gaming.Enhancing the broadband confinements is viewed as one of the most significant variables that prompted new gaming technology.The immense utilization of web applications and games additionally prompted growth in the handled devices and moving the limited gaming experience from user devices to online cloud servers.As internet capabilities are enhanced new ways of gaming are being used to improve the gaming experience.In cloud-based video gaming,game engines are hosted in cloud gaming data centers,and compressed gaming scenes are rendered to the players over the internet with updated controls.In such systems,the task of transferring games and video compression imposes huge computational complexity is required on cloud servers.The basic problems in cloud gaming in particular are high encoding time,latency,and low frame rates which require a new methodology for a better solution.To improve the bandwidth issue in cloud games,the compression of video sequences requires an alternative mechanism to improve gaming adaption without input delay.In this paper,the proposed improved methodology is used for automatic unnecessary scene detection,scene removing and bit rate reduction using an adaptive algorithm for object detection in a game scene.As a result,simulations showed without much impact on the players’quality experience,the selective object encoding method and object adaption technique decrease the network latency issue,reduce the game streaming bitrate at a remarkable scale on different games.The proposed algorithm was evaluated for three video game scenes.In this paper,achieved 14.6%decrease in encoding and 45.6%decrease in bit rate for the first video game scene.
文摘In this article, the restricted almost unbiased ridge logistic estimator (RAURLE) is proposed to estimate the parameter in a logistic regression model with exact linear re-strictions when there exists multicollinearity among explanatory variables. The performance of the proposed estimator over the maximum likelihood estimator (MLE), ridge logistic estimator (RLE), almost unbiased ridge logistic estimator (AURLE), and restricted maximum likelihood estimator (RMLE) with respect to different ridge parameters is investigated through a simulation study in terms of scalar mean square error.
文摘It is well known that the Einstein tensor G for a Riemannian manifold defined by Gα^β = 1/2α^β ,Rα^β=g^α^β γ where Rγα and R are respectively the Ricci tensor and the scalar curvature of the manifold, plays an important part in Einstein s theory of gravitation as well as in proving some theorems in Riemannian geometry. In this work, we first obtain the generalized Einstein tensor for a Weyl manifold. Then, after studying some properties of generalized Einstein tensor, we prove that the conformal invariance of the generalized Einstein tensor implies the conformal invariance of the curvature tensor of the Weyl manifold and conversely. Moreover, we show that such Weyl manifolds admit a one-parameter family of hypersurfaces the orthogonal trajectories of which are geodesics. Finally, a necessary and sufficient condition in order that the generalized circles of a Weyl manifold be preserved by a conformal mapping is stated in terms of generalized Einstein tensors at corresponding points.
文摘Rotatability is a desirable quality of fitting response surface experimental designs. The propertystates that the variance of the estimated response made from the Taylor’s series expansion areconstant on circles, spheres and hyper-spheres about the centre of the design. In this article,a measure of rotatability of modified second-order rotatable design is presented. The variancefunction of a second-order response design and an infinite class of supplementary difference setsis used in coming up with the design.
文摘Determination of sex from the tibial dimensions has been attempted before in different populations.The formulae developed to determine sex of one population are not appropriate to be applied to another.Seven standard variables including the maximum length of tibia,proximal epiphyseal breadth,distal epiphyseal breadth,minimum circumference of shaft,anteroposterior diameter at nutrient foramen,transverse diameter at the nutrient foramen(TDNF),and circumference at the nutrient foramen obtained from 81 adult tibiae(56 male and 25 female)were analyzed to investigate the sexual dimorphism in the tibial dimensions to establish sex estimating formulae from the tibia in a contemporary Sri Lankan population.Results confirmed the existence of sexual dimorphism of the tibia.Discriminant functions obtained resulted in the classification accuracies ranging from 61.9%to 80.2%.The most dimorphic single parameter in males was the TDNF providing an accuracy of 92.9%,while in females,the minimum circumference of shaft provided an accuracy of 70.4%.The best multivariate equation utilizing two tibial dimensions resulted in an accuracy of 80.2%after cross‑validation.We envisage that sex estimating formulae established in this study for a contemporary Sri Lankan population will contribute toward the biological profiling and identification of unknown skeletal remains.
文摘In this paper,we propose a new biased estimator namely modified almost unbiased Liu estimator by combining almost unbiased Liu estimator(AULE)andridge estimator(RE)in a linear regression model when multicollinearity presents amongthe independent variables.Necessary and sufficient conditions for the proposed estimator over the ordinary least square estimator,RE,AULE and Liu estimator(LE)in the mean squared error matrix sense are derived,and the optimal biasing parameters are obtained.To illustrate the theoretical findings,a Monte Carlo simulation study is carried out and a numerical example is used.
文摘Background:Understanding the processes that structure species is one of the primary focuses in community ecology.Hubbell’s neutral model shows stochastic processes alone can describe the two macro-ecological patterns,species richness and species-area relationship,of the community.Although Hubbell’s neutral model can explain the macro-ecological patterns of the species at large scales,it paid less attention to construct the spatial structure of the community.Previous studies suggest that such spatial structures are mostly due to habitat filtering processes work at the intermediate spatial scales.Therefore,Hubbell’s neutral model does not explain the full picture of the community structuring due to its fully stochastic nature.Results:In this study,we proposed a two-schema model that has the habitat filtering component and the stochastic component to construct the species assemblages seen in the community level.The proposed model uses one additional parameter(i.e.number of individuals in habitat)in addition to Hubbell’s three-parameter neutral model(i.e.fundamental bio-diversity number(θ),dispersal limitation(m)and speciation(v)).The proposed model works at two spatial scales:habitat filtering at the intermediate scales and stochastic processes at the large and very small spatial scales.The model coupled the local community dynamics with the meta-community dynamics.The local community has a fixed area with carrying capacity that is proportional to the local community size.The number of habitats in the proposed model can vary.Individuals are placed into habitats with probabilities according to the habitat suitability.Species richness and species composition in each habitat were calculated.The model is fitted for differentθvalues,m values,and a different number of habitats.Conclusions:We assume that habitat filtering plays an important role together with stochastic processes to structure species in forests.Therefore,the proposed model with only four parameters can explain a large proportion of the species structuring of the communities.We found that more species can be maintained in a heterogeneous environment than a uniform environment.Therefore,habitat conservation is highly important for maintaining species diversity in forest communities.
文摘The technique of fitting a response surface design is useful in modelling of experimental designs.Response surface is used in situations where the response of interest is influenced by several experimental variables.The objective of fitting a response surface design is to reduce cost of experimentation and to obtain optimal designs.The property of rotatability is a desirable quantity of experimental design and requires the variance of the fitted design to be constant on circles or spheres about the centre of the design.In this article,a construction technique of fitting modified non-sequential third order rotatable design(TORD)using Pairwise Balanced Design(PBD)is presented.The variance function of a third order response surface design and the properties of Pairwise Balanced Design are utilised for the construction.
