The purpose of this study is to describe how the attribute hierarchy method (AHM) can be applied to assessment engineering. The AHM is a psychometric method for classifying examinees’ test item responses into a set of attribute mastery patterns associated with different components in a cognitive model of task performance. Attribute probabilities, computed using a neural network, can be estimate...

Attribute-based encryption is a form of encryption which offers the capacity to encrypt data such that it is only accessible to individuals holding a satisfactory configuration of attributes. As cloud and distributed computing become more pervasive in both private and public spheres, attribute-based encryption holds potential to address the issue of achieving secure authentication, authorizatio...

An approach to detecting the presence of HTML Attribute Permutation Steganography (APS) is proposed and founded on the idea of using a classification (prediction) model. To this end a position changes count metric, the Attribute Position Changes Count (APCC), is presented with which to capture attribute ordering information. The main advantage offered by the APCC metric, unlike other APS detect...

We introduce a method for improving facial attribute predictions using other attributes. In the domain of face recognition and verification, attributes are high-level descriptions of face images. Attributes are very useful for identification as well as image search as they provide easily understandable descriptions of faces, rather than most other image descriptors (i.e. HOG, LBP, and SIFT). A ...

Visual binding of edge segments embedded in noise and created by luminance, motion and disparity contrasts were studied in three experiments. The results showed that path formation was limited by the same rules across all attributes tested. The first experiment showed that binding could be accomplished with either attribute used in isolation. The second experiment showed that closed paths were ...

Classification performance can degrade if data contain missing attribute values. Many methods deal with missing information in a simple way, such as replacing missing values with the global or class-conditional mean/mode. We propose a new iterative algorithm to effectively estimate missing attribute values in both training data and test data. The attributes are selected one by one to be complet...

In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics val...

Support vector machine (SVM) was used to analyze the occurrence of roach in Flemish stream basins (Belgium). Several habitat and physico?chemical variables were used as inputs for the model development. The biotic variable merely consisted of abundance data which was used for predicting presence/absence of roach. Genetic algorithm (GA) was combined with SVM in order to select the most important...

support vector machine (svm) was used to analyze the occurrence of roach in flemish stream basins (belgium). several habitat and physico?chemical variables were used as inputs for the model development. the biotic variable merely consisted of abundance data which was used for predicting presence/absence of roach. genetic algorithm (ga) was combined with svm in order to select the most important...