When faced with a limited budget to collect data in support of a multiple attribute selection decision, the decisionmaker must decide how many samples to observe from each alternative and attribute. This allocation decision is of particular importance when the observation process is uncertain, such as with physical measurements. For example, when the U.S. Department of Homeland Security must de...

This study examines the effect of writing attributes on English performance pre-service engineering teachers. research adopts descriptive with a survey type. The population for this was all target is teachers in three (3) selected Educational Colleges. A multi-stage sampling procedure adopted study. data collection instrument an adapted questionnaire. Descriptive and inferential statistics were...

The increasing popularity of remote Cloud File Sharing (CFS) has become a major concern for privacy breach sensitive data. Aiming at this concern, we present new resource sharing framework by integrating enterprise-side Attribute-Based Access Control/eXtensible Control Markup Language (ABAC/XACML) model, client-side Ciphertext-Policy Encryption (CP-ABE) scheme, and cloud-side CFS service. Moreo...

With the largely growing quantity of face images in the social networks and media, different face analyzing systems are developed to be employed in real-world situations such as face recognition, facial expression detection, or automated face tagging. Two demanding face-related applications are studied in this paper: facial attribute classification and face image retrieval. The main common issu...

Although various methods have been proposed for pedestrian attribute recognition, most studies follow the same feature learning mechanism, \ie, a shared image to classify multiple attributes. However, this mechanism leads low-confidence predictions and non-robustness of model in inference stage. In paper, we investigate why is case. We mathematically discover that central cause optimal cannot m...

The fast increase and update of big data brings a new challenge to quickly acquire the useful information with classical attribute reduction methods. In this paper, a parallel minimum attribute co-reduction accelerator (QSMFAC) based on quantum-inspired SFLA and MapReduce framework is presented. First, a novel framework of N-populations distributed co-evolutionary cloud model is designed to div...

Attribute based encryption (ABE) and attribute based signature (ABS) provide flexible access control with authentication for data sharing between users, but realizing both functions will bring about too much computation burden. In this paper, we combine the advantages of CP-ABE with ABS and propose a ciphertext policy attribute based signcryption scheme. In our scheme, only legal receivers can ...

In the present paper we propose an unsupervised attribute ranking method based on evaluating the quality of clustering that each attribute produces by partitioning the data into subsets according to its values. We use the Minimum Description Length (MDL) principle to evaluate the quality of clustering and describe an algorithm for attribute ranking and a related clustering algorithm. Both algor...

Attribute clustering has been previously employed to detect statistical dependence between subsets of variables. We propose a novel attribute clustering algorithm motivated by research of complex networks, called the Star Discovery algorithm. The algorithm partitions and indirectly discards inconsistent edges from a maximum spanning tree by starting appropriate initial modes, therefore generati...