Real time sobel square edge detector for night vision analysis

Vision analysis with low or no illumination is gaining more and more attention recently, especially in the fields of security surveillance and medical diagnosis. In this paper, a real time sobel square edge detector is developed as a vision enhancer in order to render clear shapes of object in targeting scenes, allowing further analysis such as object or human detection, object or human tracking, human behavior recognition, and identification on abnormal scenes or activities. The method is optimized for real time applications and compared with existing edge detectors. Program codes are illustrated in the content and the results show that the proposed algorithm is promising to generate clear vision data with low noise

The Limits to Competition in the Jamaican Urban Bus Service.

In the context of best practice with regards to the market structure and organization of urban public transport over the last 30 years or so would reveal the popularity of a hybrid transport model, that is a model in which the public and the private sector share responsibilities for the delivery of the service. A more careful review would reveal an evolving consensus with respect to the optimal degree and form of government intervention in this hybrid model. We look at the Chilean model, which has had similar experiences to us in a similar time period to see if Jamaican policy makers can enhance our system, the JUTC (Jamaican Urban Transport System) by their experiences.

An Empirical Analysis of the Taiwan Institutional Trading Volume Volatility Spillover on Stock Market Index Return

This paper provides interesting empirical evidence on the relation between the volatility impact effect of the Taiwan institutional trading volume and the stock market index by using the MEGARCH model. We found a significant autoregressive coefficient of institutional trading volume and stock market index. The cross-volatility spillover effect, asymmetric leverage effect, and persistence of volatility effect are statistically significant. The feedback and lead-lag relationship between trading volume and stock index return are also statistically significant. Therefore, Taiwan¡¦s institutional trading volume can affect the stock market index through volatility effect and causality.

The analysis of interest rate mean and volatility spillover to the industrial production index and stock markets: The case of China

Empirical results found the parameter estimates for the CCC-MGARCH models display that the short run persistence is positive and significant and the positive and significant ARCH and GARCH term show the ARCH and GARCH effect exist in these models. By concerning the correlations of bank reserve rate and discount rate to industrial production index, the correlation is positive and statistically significant for those variables. It indicated that China monetary policy have a positive impact to industrial production. The parameters estimates for DCC-MGARCH(1.1) model for China monetary policy to industrial production index and stock markets show the short-run persistence is positive significantly and at DCC(1.1) parameters. The sum of the DCC(1.1) parameter is less than one which implies that the model is strictly mean reverting.interest rate variables

A low variance error boosting algorithm

This paper introduces a robust variant of AdaBoost, cw-AdaBoost, that uses weight perturbation to reduce variance error, and is particularly effective when dealing with data sets, such as microarray data, which have large numbers of features and small number of instances. The algorithm is compared with AdaBoost, Arcing and MultiBoost, using twelve gene expression datasets, using 10-fold cross validation. The new algorithm consistently achieves higher classification accuracy over all these datasets. In contrast to other AdaBoost variants, the algorithm is not susceptible to problems when a zero-error base classifier is encountered

A Note on Near-factor-critical Graphs

A near-factor of a finite simple graph $G$ is a matching that saturates all vertices except one. A graph $G$ is said to be near-factor-critical if the deletion of any vertex from $G$ results in a subgraph that has a near-factor. We prove that a connected graph $G$ is near-factor-critical if and only if it has a perfect matching. We also characterize disconnected near-factor-critical graphs.Comment: 4 page