Rejection rate

About: Rejection rate is a research topic. Over the lifetime, 279 publications have been published within this topic receiving 1787 citations.

An optimum character recognition system using decision functions

Abstract: The character recognition problem, usually resulting from characters being corrupted by printing deterioration and/or inherent noise of the devices, is considered from the viewpoint of statistical decision theory. The optimization consists of minimizing the expected risk for a weight function which is preassigned to measure the consequences of system decisions As an alternative minimization of the error rate for a given rejection rate is used as the critenon. The optimum recogition is thus obtained. The optimum system consists of a conditional-probability densisities computer; character channels, one for each character; a rejection channel; and a comparison network. Its precise structure and and ultimate performance depend essentially upon the signals and noise structure. Explicit examples for an additive Gaussian noise and a ``cosine'' noise are presented. Finally, an error-free recognition system and a possible criterion to measure the character style and deteriortation are presented.

Wind energy rejection in China: Current status, reasons and perspectives

Abstract: Currently, parts of the potential energy generated by the wind turbines could not be transmitted to the electric power grid in China, leading to a serious wind energy rejection problem. In some local areas (e.g. Gansu province), the wind energy rejection rate reaches 47% in the first half year of 2016. Wind energy rejection problem is currently the biggest barrier for the further development of the wind energy in China. In this review, the current status of the wind energy rejection (between 2010 and 2016) are reviewed with a detailed analysis of the reasons based on the statistical data released by the authorities. Two cases studies (Inner Mongolia Autonomous Region and Gansu province respectively) are also performed to specify the reasons for the rejection and provide an in-depth discussion on the influences of related policies. Based on the recent trends and policies, several solutions and perspectives are also given together with some specific suggestions for the policy makers. Furthermore, in this review, a brief description of China's electric system is also given for the convenience of the readers. This review is not only informative for solving the wind energy rejection problem in China but also helps the policy makers in other developing countries for building the roadmaps of the renewable energies.

Bang for Your Buck: Rejection Rates and Impact Factors in Ecological Journals

Abstract: When choosing where to submit their research for publication, most ecologists are concerned with journal impact factor, but they are also concerned with the likelihood that their manuscripts will be accepted. Based on a survey of ecologists, we found different degrees of relative concern for these journal attributes depending on author experience and gender. However, the ability of authors to choose among journals based on these journal attributes is limited: while journal impact factors are published regularly, journal rejection rates are not. We obtained, by permission, rejection rate data for a sample of 60 ecology journals for the year 2004. As expected, journals with higher impact factors also have higher rejection rates, but the ratio of (rejection rate) / (impact factor) increases sharply with decreasing impact factor below 1.76. Journals with impact factors below this value therefore provide relatively low payback in terms of impact against cost as estimated by rejection rate. We discuss alternative possible interpretations of this relationship and alternative criteria that might affect an author's decision about journal choice. Most importantly, our analysis indicates that the ability to make informed choices requires that journals publish their rejection rates annually. PREAMBLE How does an author decide where to submit a paper for publication? This important decision is made routinely throughout the career of a typical researching scientist/academic. The choices made can profoundly affect the trajectory, rate of progress, and status of one's research career. Necessarily, the subject category of the journals under consideration must be concordant with the research topic of the paper. However after this, most authors in the field of ecology at least, are usually still presented with more than one choice of a topically suitable subset of candidate journals. And, when the paper is rejected (an experience that few if any manage to avoid completely), the author is commonly inclined to iteratively select alternative journals.

Combined classifiers for invariant face recognition

Abstract: We present a system for invariant face recognition. A combined classifier uses the generalization capabilities of both learning vector quantization (LVQ) and radial basis function (RBF) neural networks to build a representative model of a face from a variety of training patterns with different poses, details and facial expressions. The combined generalization error of the classifier is found to be lower than that of each individual classifier. A new face synthesis method is implemented for reducing the false acceptance rate and enhancing the rejection capability of the classifier. The system is capable of recognizing a face in less than one second. The system is tested on the well-known ORL database. The system performance compares favorably with the state-of-the-art systems. In the case of the ORL database, a correct recognition rate of 99.5% at 0.5% rejection rate is achieved. This rate compares favorably with the rates achieved by other systems on the same database. The volumetric frequency domain representation resulted in a rate of 92.5% while the combination of a convolutional neural network and self-organizing map resulted in 96.2% for the same number of training faces (five) per person in a database representing 40 people.

Load balancing web service by rejecting connections

Abstract: A load balancer allocates requests to a pool of web servers configured to have low queue capacities. If the queue capacity of a web server is reached, the web server responds to an additional request with a rejection notification to the load balancer, which enables the load balancer to quickly send the rejected request to another web server. Each web server self-monitors its rejection rate. If the rejection rate exceeds a threshold, the number of processes concurrently running on the web server is increased. If the rejection rate falls below a threshold, the number of processes concurrently running on the web server is decreased.