Excellent book is always being the best friend for spending little time in your office, night time, bus, and everywhere. It will be a good way to just look, open, and read the book while in that time. As known, experience and skill don't always come with the much money to acquire them. Reading this book with the PDF parameter estimation and hypothesis testing in linear models will let you know ...

Eye movements during scene comprehension can be seen as a series of decisions where and when to look. There has been substantial work towards determining likely fixation locations and the best known methods involve the computation of saliency maps which assign “interestingness” values to each coordinate of analyzed image. However these methods are usually purely bottom-up and only consider low-...

The paper proposes the use of the Silhouette Coefficient (SC) as a ranking measure to perform instance selection in text classification. Our selection criterion was to keep instances with mid-range SC values while removing the instances with high and low SC values. We evaluated our hypothesis across three well-known datasets and various machine learning algorithms. The results show that our met...

In this paper we present known-plaintext single-key and chosenkey attacks on round-reduced LED-64 and LED-128. We show that with an application of the recently proposed slidex attacks [7], one immediately improves the complexity of the previous single-key 4-step attack on LED-128. Further, we explore the possibility of multicollisions and show single-key attacks on 6 steps of LED-128. A general...

This paper describes three experiments in using frame level observation probabilities as the basis for word confidence annotation in an HMM speech recognition system. One experiment is at the word level, one uses word classes, and the other uses phone classes. In each experiment we categorize hypotheses into correct and incorrect categories by aligning a best recognition hypothesis with the kno...

We present a general theoretical analysis of structured prediction. By introducing a new complexity measure that explicitly factors in the structure of the output space and the loss function, we are able to derive new learning guarantees for hypothesis sets with an arbitrary factor graph decomposition. To the best of our knowledge, these are both the most favorable and the most general guarante...

| We study a simple learning algorithm for binary classiication. Instead of predicting with the best hypothesis in the hypothesis class, this algorithm predicts with a weighted average of all hypotheses , weighted exponentially with respect to their training error. We show that the prediction of this algorithm is much more stable than the prediction of an algorithm that predicts with the best h...

In this article, we provide the first third-party security analysis of the PRINCE lightweight block cipher, and the underlying PRINCEcore. First, while no claim was made by the authors regarding related-key attacks, we show that one can attack the full cipher with only a single pair of related keys, and then reuse the same idea to derive an attack in the single-key model for the full PRINCEcore...

I lied to the future last night. I told it that soon it would be big and strong and profitable. I then tucked it into its crib, turned off the lights, and hoped the day would never come when the future would curse this lie. I not only assured the future it would someday be strong and profitable, I also told it how it would strong and profitable. My lie was a little more prosaic than my words su...

Recently, a RGB image encryption algorithm based on DNA encoding and chaos map has been proposed. It was reported that the encryption algorithm can be broken with four pairs of chosen plain-images and the corresponding cipher-images. This paper re-evaluates the security of the encryption algorithm, and finds that the encryption algorithm can be broken efficiently with only one known plain-image...