Background:This paper examines the role of monetary and fiscal factors in interest rate variations in Sri Lanka under its deregulated regime of interest rates.In addition the paper also examines the role of monetary f...Background:This paper examines the role of monetary and fiscal factors in interest rate variations in Sri Lanka under its deregulated regime of interest rates.In addition the paper also examines the role of monetary factors in the variation of interest rates,using a quarterly dataset for the post-global recession period,when the exchange rate is determined by market forces.Results:Empirical analysis uses a dataset of nominal interest rates,money growth,income growth,changes in nominal exchange rate,and budget deficit.From the methodological point of view the paper involves vector autoregression model and Wald tests of Granger causality,followed by impulse response analysis while stationarity and the order of integration of the selected variables are confirmed involving the augmented Dickey-Fuller and the Phillips-Perron unit-root tests.Results:The paper confirms that both monetary and fiscal factors have significant effects on the variations of interest rates.Money growth triggers an increase in interest rates,which supports the Fisher equation view,while income growth has a negative impact.Budget deficit causes a rise in interest rates,but the role of the exchange rate is found to be almost insignificant,probably due to including exchange rate series that cover both the pegged and market-based regimes of exchange rates.The second part of the analysis,using a quarterly dataset for the post-global recession period,further establishes the positive impact of M2 money growth and income growth on interest rates.In this case,exchange rate depreciation causes an increase in interest rates.Conclusions:The significant role of monetary and fiscal factors in interest rate variations implies it would be possible to manage interest rates through a judiciary management of monetary and fiscal policies.展开更多
Searching,recognizing and retrieving a video of interest froma large collection of a video data is an instantaneous requirement.This requirement has been recognized as an active area of research in computer vision,mac...Searching,recognizing and retrieving a video of interest froma large collection of a video data is an instantaneous requirement.This requirement has been recognized as an active area of research in computer vision,machine learning and pattern recognition.Flower video recognition and retrieval is vital in the field of floriculture and horticulture.In this paper we propose a model for the retrieval of videos of flowers.Initially,videos are represented with keyframes and flowers in keyframes are segmented from their background.Then,the model is analysed by features extracted from flower regions of the keyframe.A Linear Discriminant Analysis(LDA)is adapted for the extraction of discriminating features.Multiclass Support VectorMachine(MSVM)classifier is applied to identify the class of the query video.Experiments have been conducted on relatively large dataset of our own,consisting of 7788 videos of 30 different species of flowers captured from three different devices.Generally,retrieval of flower videos is addressed by the use of a query video consisting of a flower of a single species.In this work we made an attempt to develop a system consisting of retrieval of similar videos for a query video consisting of flowers of different species.展开更多
文摘Background:This paper examines the role of monetary and fiscal factors in interest rate variations in Sri Lanka under its deregulated regime of interest rates.In addition the paper also examines the role of monetary factors in the variation of interest rates,using a quarterly dataset for the post-global recession period,when the exchange rate is determined by market forces.Results:Empirical analysis uses a dataset of nominal interest rates,money growth,income growth,changes in nominal exchange rate,and budget deficit.From the methodological point of view the paper involves vector autoregression model and Wald tests of Granger causality,followed by impulse response analysis while stationarity and the order of integration of the selected variables are confirmed involving the augmented Dickey-Fuller and the Phillips-Perron unit-root tests.Results:The paper confirms that both monetary and fiscal factors have significant effects on the variations of interest rates.Money growth triggers an increase in interest rates,which supports the Fisher equation view,while income growth has a negative impact.Budget deficit causes a rise in interest rates,but the role of the exchange rate is found to be almost insignificant,probably due to including exchange rate series that cover both the pegged and market-based regimes of exchange rates.The second part of the analysis,using a quarterly dataset for the post-global recession period,further establishes the positive impact of M2 money growth and income growth on interest rates.In this case,exchange rate depreciation causes an increase in interest rates.Conclusions:The significant role of monetary and fiscal factors in interest rate variations implies it would be possible to manage interest rates through a judiciary management of monetary and fiscal policies.
文摘Searching,recognizing and retrieving a video of interest froma large collection of a video data is an instantaneous requirement.This requirement has been recognized as an active area of research in computer vision,machine learning and pattern recognition.Flower video recognition and retrieval is vital in the field of floriculture and horticulture.In this paper we propose a model for the retrieval of videos of flowers.Initially,videos are represented with keyframes and flowers in keyframes are segmented from their background.Then,the model is analysed by features extracted from flower regions of the keyframe.A Linear Discriminant Analysis(LDA)is adapted for the extraction of discriminating features.Multiclass Support VectorMachine(MSVM)classifier is applied to identify the class of the query video.Experiments have been conducted on relatively large dataset of our own,consisting of 7788 videos of 30 different species of flowers captured from three different devices.Generally,retrieval of flower videos is addressed by the use of a query video consisting of a flower of a single species.In this work we made an attempt to develop a system consisting of retrieval of similar videos for a query video consisting of flowers of different species.
