A new block-based method for copy move forgery detection under image geometric transforms

Copy move forgery detection (CMFD) is one of the most active subtopic in forgery scheme. The methods of CMFD are divided into to block-based method and keypoint-based method in general. Compared with keypoint-based method, block-based method can detect undetectable detail without morphology segmentation. But many block-based methods detect the plain copy-move forgeries only. They have been incompetent to detect the post-processing operations such as various geometrical distortions, and then fail to detect the forgery regions accurately. Therefore, this paper presents an improved block-based efficient method for CMFD. Firstly, after pre-processing, an auxiliary overlapped circular block is presented to divide the forged image into overlapped circular blocks. The local and inner image feature is extracted by the Discrete Radial Harmonic Fourier Moments (DRHFMs) with the overlapped circular block from the suspicious image. Then, the similar feature vectors of blocks are searched by 2 Nearest Neighbors (2NN) test. Euclidean distance and correlation coefficient is employed to filter these features and then remove the false matches. Morphologic operation is employed to delete the isolated pixels. A series of experiments are done to analyze the performance for CMFD. Experimental results show that the new DRHFMs can obtain outstanding performance even under image geometrical distortions.     

Bayesian sample-size determination for two independent Poisson rates

Because of the high cost and time constraints for clinical trials, researchers often need to determine the smallest sample size that provides accurate inferences for a parameter of interest. Although most experimenters have employed frequentist sample-size determination methods, the Bayesian paradigm offers a wide variety of sample-size determination methodologies. Bayesian sample-size determination methods are becoming increasingly more popular in clinical trials because of their flexibility and easy interpretation inferences. Recently, Bayesian approaches have been used to determine the sample size of a single Poisson rate parameter in a clinical trial setting. In this paper, we extend these results to the comparison of two Poisson rates and develop methods for sample-size determination for hypothesis testing in a Bayesian context. We have created functions in R to determine the parameters for the conjugate gamma prior and calculate the sample size for the average length criterion and average power methods. We also provide two examples that implement our sample-size determination methods using clinical data.     

Hybrid accident simulation methodology using artificial neural networks for nuclear power plants

A hybrid accident simulation methodology for nuclear power plants is proposed to enhance the capabilities of compact simulator by introducing artificial neural networks. Two neural networks are trained with the target values obtained from the analyses of detailed computer codes and trained results are combined with the compact simulator to perform the following roles: (i) compensation for inaccuracies of a compact simulator occurring from simplified governing equation and reduced number of physical control volumes, and (ii) prediction of the critical parameter usually calculated from the sophisticated computer code: the autoassociative neural network improves the computational results of the compact simulator up to the accuracy level of detailed best estimate computer code, while the backpropagation neural network predicts the minimum departure from nucleate boiling ratio (DNBR). Simulations are carried out to verify the applicability of the proposed methodology for the loss of flow accidents and the results show that the neural networks can be used as a complementary tool to improve the results of a compact simulator.     

Improving Usability Perception of Error-Prone AI Speakers: Elaborated Feedback Mitigates Negative Consequences of Errors

ABSTRACT

Users of voice user interface (VUI) often encounter errors, such as when a VUI attempts to recognize a user’s voice inputs or execute tasks. Conversation is prone to errors, and in the collaborative perspective, communicators manage common ground together to handle erroneous situations. Adopting a collaborative view of conversation, we propose that a VUI can address different types of errors by providing users with feedback to aid them in developing common ground to communicate more effectively. To test this proposal, we conducted a 2 (error type: recognition vs. execution error) × 2 (feedback elaboration: present vs. absent) mixed-design experiment in which users interacted with a VUI speaker and evaluated its usability in these four modes. Participants reported greater acceptance of feedback and higher usability perception for a speaker returning execution errors than for one returning recognition errors, particularly when the speaker presented feedback articulating reasons for the errors. This finding indicates that a VUI can employ feedback explaining the causes of errors to facilitate the development of common ground and to minimize the negative consequences of errors.     

Classification of road surface status using a 94 GHz dual-channel polarimetric radiometer

In this article, we classify road surface statuses using a Bayesian classification method. This article uses principal component analysis (PCA) that combines a 94 GHz dual-channel polarimetric radiometer. The radiometer is used to investigate the behaviour of the brightness temperature (BT) of different road surface statuses in an open-air laboratory. The aim of this investigation is to characterize four different road surface classes (dry, wet, snowy and icy). Here, the BT (radiothermal emission) characteristics are measured at horizontal and vertical polarizations. For a given database of weather information (including BT, road surface temperature, wind speed, etc.), a PCA subspace is constructed, and the score vectors are classified by solving the Bayesian classification method. As a result, the road surface statuses were found to be well classified by the proposed method in real time.     

Hiring Qualified College Graduates: MIS Business Majors Versus Computer Science Majors

When decisions must be made regarding systems productivity and control trade-offs, many companies automatically opt for productivity improvement. However, critical functions, documentation, testing, and training are sometimes sacrificed. To establish a balance between these competing needs, MIS management should educate systems developers and users about the nature of and need for controls.     

Land surface response to precipitation events using MODIS and NEXRAD data

We have developed a wavelet‐based information theoretic approach to examine the interaction between precipitation (PPT) forcing events and the land surface response. Combining Next Generation Weather Radar (NEXRAD) PPT with Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation (NDVI) and surface temperature (T _s) data over the Missouri Basin in the north‐central USA, we are able to address the spatial and temporal fluctuations surrounding the hydrometeorology of grassland ecosystems. Information theory metrics of entropy and mutual information content are combined with a wavelet multi‐resolution analysis to examine to what extent the observed PPT signal directly determines the spatial distribution of the land surface temperature and vegetation and how this relationship varies with spatial scale. Results indicate that (1) there is a reduction in the temporal variance of the wavelet coefficients as the signal is transferred from the PPT into the surface temperature and finally the vegetation signal, (2) there are significant correlations as a function of spatial resolution between PPT–NDVI and PPT–T _s signals which generally increase with spatial resolution, while there is little correlation between the NDVI and T _s signals as a function of resolution, and (3) the scale‐wise entropy and the mutual information content of the signals increase for all fields as the spatial resolution increases. This provides a methodology for determining the relative impact of regional climatology and local land–atmosphere interactions as a function of spatial scale.     

Neonatal hind-paw injury disrupts acquisition of an instrumental response in adult spinal rats.

The present study was designed to evaluate the impact of neonatal injury on adult spinal plasticity in rats. Subjects were randomly assigned to 1 of 4 experimental conditions: (a) hind-paw injury at Postnatal Day (PD) 2, (b) hind-paw injury at PD 5, (c) anesthesia exposure only on PD 2, or (d) anesthesia exposure only on PD 5. Subjects receiving a unilateral neonatal hind-paw injury showed decreased mechanical threshold (hyperalgesia) on the previously injured hind paw throughout development. This decrease in threshold survived spinal transection (at T2) at 12 weeks of age. Injured subjects also showed significant impairment in a spinal instrumental learning task performed by the previously injured hind paw. This disruption of learning indicates a disruption of spinal plasticity that may be due to induction of long-term changes in nociceptive processing within the spinal cord. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Fundamental connections among the stability conditions using higher-order time-derivatives of Lyapunov functions for the case of linear time-invariant systems

It has already been recognized that looking for a positive definite Lyapunov function such that a high-order linear differential inequality with respect to the Lyapunov function holds along the trajectories of a nonlinear system can be utilized to assess asymptotic stability when the standard Lyapunov approach examining only the first derivative fails. In this context, the main purpose of this paper is, on one hand, to theoretically unveil deeper connections among existing stability conditions especially for linear time-invariant (LTI) systems, and from the other hand to examine the effect of the higher-order time-derivatives approach on the stability results for uncertain polytopic LTI systems in terms of conservativeness. To this end, new linear matrix inequality (LMI) stability conditions are derived by generalizing the concept mentioned above, and through the development, relations among some existing stability conditions are revealed. Examples illustrate the improvement over the quadratic approach.