PURPOSE Willingness and ability to learn from health information in text are crucial for people to be informed and make better medical decisions. These two user characteristics are influenced by the perceived and actual difficulty of text. Our goal is to find text features that are indicative of perceived and actual difficulty so that barriers to reading can be lowered and understanding of info...

Text line segmentation is an essential pre-processing stage for handwriting recognition in many Optical Character Recognition (OCR) systems. It is an important step because inaccurately segmented text lines will cause errors in the recognition stage. Text line segmentation of the handwritten documents is still one of the most complicated problems in developing a reliable OCR. The nature of hand...

Text detection is fundamental to video information retrieval and indexing. Existing methods cannot handle well those texts with different contrast or embedded in a complex background. To handle these difficulties, this paper proposes an efficient text detection approach, which is based on invariant features, such as edge strength, edge density, and horizontal distribution. First, it applies edg...

In this study a new and robust procedure is presented to solve synthesis of isothermal reactor networks (RNs) which considers more than one objective function. This <span style="font-size: 9pt; color: #0...

Dealing with the large-scale text knowledge on the Web has become increasingly important with the development of the Web, yet it confronts with several challenges, one of which is to find out as much semantics as possible to represent text knowledge. As the text semantic mining process is also the knowledge representation process of text, this paper proposes a text knowledge representation mode...

Classifying text data has been an active area of research for a long time. Text document is multifaceted object and often inherently ambiguous by nature. Multi-label learning deals with such ambiguous object. Classification of such ambiguous text objects often makes task of classifier difficult while assigning relevant classes to input document. Traditional single label and multi class text cla...

In this paper, we present improved related-key attacks on the original DESX, and DESX+, a variant of the DESX with its preand post-whitening XOR operations replaced with addition modulo 2. Compared to previous results, our attack on DESX has reduced text complexity, while our best attack on DESX+ eliminates the memory requirements at the same processing complexity.

Searching for a pattern in a text file is a very common operation in many applications ranging from text editors and databases to applications in molecular biology. In many instances the pattern does not appear in the text exactly. Errors in the text or in the query can result from misspelling or from experimental errors (e.g., when the text is a DNA sequence). The use of such approximate patte...

Text document is multifaceted object and associated with many properties such as multi labeledness. Under this a single text document can inherently belongs to more than one category simultaneously. Traditional single label and multi class text class ification paradigms cannot efficiently classify such multifaceted text corpus. Through our paper we are proposing a graph based frame work for Mul...

Measuring reading effort is useful for practical purposes such as designing learning material and personalizing text comprehension environment. We propose a quantification of reading effort by measuring the complexity of eye-movement patterns of readers. We call the measure Scanpath Complexity. Scanpath complexity is modeled as a function of various properties of gaze fixations and saccadesthe ...