Collaboration based Multi-Label Learning

It is well-known that exploiting label correlations is crucially important to multi-label learning. Most of the existing approaches take label correlations as prior knowledge, which may not correctly characterize the real relationships among labels. Besides, label correlations are normally used to regularize the hypothesis space, while the final predictions are not explicitly correlated. In this paper, we suggest that for each individual label, the final prediction involves the collaboration between its own prediction and the predictions of other labels. Based on this assumption, we first propose a novel method to learn the label correlations via sparse reconstruction in the label space. Then, by seamlessly integrating the learned label correlations into model training, we propose a novel multi-label learning approach that aims to explicitly account for the correlated predictions of labels while training the desired model simultaneously. Extensive experimental results show that our approach outperforms the state-of-the-art counterparts.Comment: Accepted by AAAI-1

Design and Implementation of Smart Sensors with Capabilities of Process Fault Detection and Variable Prediction

A typical sensor consists of a sensing element and a transmitter. The major functions of a transmitter are limited to data acquisition and communication. The recently developed transmitters with ‘smart’ functions have been focused on easy setup/maintenance of the transmitter itself such as self-calibration and self-configuration. Recognizing the growing computational capabilities of microcontroller units (MCUs) used in these transmitters and underutilized computational resources, this thesis investigates the feasibility of adding additional functionalities to a transmitter to make it ‘smart’ without modifying its foot-print, nor adding supplementary hardware. Hence, a smart sensor is defined as sensing elements combined with a smart transmitter. The added functionalities enhance a smart sensor with respect to performing process fault detection and variable prediction. This thesis starts with literature review to identify the state-of-the-arts in this field and also determine potential industry needs for the added functionalities. Particular attentions have been paid to an existing commercial temperature transmitter named NCS-TT105 from Microcyber Corporation. Detailed examination has been made in its internal hardware architecture, software execution environment, and additional computational resources available for accommodating additional functions. Furthermore, the schemes of the algorithms for realizing process fault detection and variable prediction have been examined from both theoretical and feasibility perspectives to incorporate onboard NCS-TT105. An important body of the thesis is to implement additional functions in the MCUs of NCS-TT105 by allocating real-time execution of different tasks with assigned priorities in the real-time operating system (RTOS). The enhanced NCS-TT105 has gone through extensive evaluation on a physical process control test facility under various normal/fault conditions. The test results are satisfactory and design specifications have been achieved. To the best knowledge of the author, this is the first time that process fault detection and variable prediction have been implemented right onboard of a commercial transmitter. The enhanced smart transmitter is capable of providing the information of incipient faults in the process and future changes of critical process variables. It is believed that this is an initial step towards the realization of distributed intelligence in process control, where important decisions regarding the process can be made at a sensor level

Non-transferable unidirectional proxy re-encryption scheme for secure social cloud storage sharing

(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Proxy re-encryption (PRE), introduced by Blaze et al. in 1998, allows a semi-trusted proxy with the re-encryption key to translatea ciphertext under the delegator into another ciphertext, which can be decrypted by the delegatee. In this process, the proxy is required to know nothing about the plaintext. Many PRE schemes have been proposed so far, however until now almost all the unidirectional PRE schemes suffer from the transferable property. That is, if the proxy and a set of delegatees collude, they can re-delegate the delegator's decryption rights to the other ones, while the delegator has no agreement on this. Thus designing non-transferable unidirectional PRE scheme is an important open research problem in the field. In this paper, we tackle this open problem by using the composite order bilinear pairing. Concretely, we design a non-transferable unidirectional PRE scheme based on Hohenberger et al.'s unidirectional PRE scheme. Furthermore, we discuss our scheme's application to secure cloud storage, especially for sharing private multimedia content for social cloud storage users.Peer ReviewedPostprint (author's final draft

Demonstration of the double Q^2-rescaling model

In this paper we have demonstrated the double Q^2-rescaling model (DQ^2RM) of parton distribution functions of nucleon bounded in nucleus. With different x-region of l-A deep inelastic scattering process we take different approach: in high x-region (0.1\le x\le 0.7) we use the distorted QCD vacuum model which resulted from topologically multi -connected domain vacuum structure of nucleus; in low x-region (10^{-4}\le x\le10^{-3}) we adopt the Glauber (Mueller) multi- scattering formula for gluon coherently rescattering in nucleus. From these two approach we justified the rescaling parton distribution functions in bound nucleon are in agreement well with those we got from DQ^2RM, thus the validity for this phenomenologically model are demonstrated.Comment: 19 page, RevTex, 5 figures in postscrip