Exploring the Individual's Behavior on Self-Disclosure Online

Even though the ubiquity of technology can make many aspects of life more convenient, it may simultaneously raise some concerns about the privacy issues related to personal information. This research focused on the individual's behavior toward self-disclosure online and his or her cognition on personal privacy that was affected by not only the personal psychological factors but also the individual's computer knowledge and associated skills. To study how technological and psychological factors can simultaneously affect one's privacy concern and restrain behavior on disclosure, this study applied both perceived privacy and privacy concern to assess such factors as personal subjective attitude, computer self-efficacy, and perceived behavioral control to investigate the technological influence. A hypothesized model was proposed to describe the relationships among these constructs. After structural equation modeling is utilized to analyze the proposed hypotheses, the research findings showed that, although the perceived behavioral control had a negative effect on self-disclosure online, all the other hypotheses indicated a positive casual effect.     

Patchy solution of a Francis–Byrnes–Isidori partial differential equation

The solution to the nonlinear output regulation problem requires one to solve a first‐order partial differential equation, known as the Francis–Byrnes–Isidori equations. In this paper, we propose a method to compute approximate solutions to the Francis–Byrnes–Isidori equations when the zero dynamics of the plant are hyperbolic and the exosystem is two dimensional. With our method, we are able to produce approximations that converge uniformly to the true solution. Our method relies on the periodic nature of two‐dimensional analytic center manifolds. Copyright © 2012 John Wiley & Sons, Ltd.     

A survey on enhanced subspace clustering

Subspace clustering finds sets of objects that are homogeneous in subspaces of high-dimensional datasets, and has been successfully applied in many domains. In recent years, a new breed of subspace clustering algorithms, which we denote as enhanced subspace clustering algorithms, have been proposed to (1) handle the increasing abundance and complexity of data and to (2) improve the clustering results. In this survey, we present these enhanced approaches to subspace clustering by discussing the problems they are solving, their cluster definitions and algorithms. Besides enhanced subspace clustering, we also present the basic subspace clustering and the related works in high-dimensional clustering.     

Design and Implementation of an Agent Home Scheme Strategy for Prefetch-Based DSM Systems

In recent years, cluster computing has been widely investigated and there is no doubt that it can provide a cost-effective computing infrastructure by aggregating computational power, communication, and storage resources. Moreover, it is also considered to be a very attractive platform for low-cost supercomputing. Distributed shared memory (DSM) systems utilize the physical memory of each computing node interconnected in a private network to form a global virtual shared memory. Since this global shared memory is distributed among the computing nodes, accessing the data located in remote computing nodes is an absolute necessity. However, this action will result in significant remote memory access latencies which are major sources of overhead in DSM systems. For these reasons, in order to increase overall system performance and decrease this overhead, a number of strategies have been devised. Prefetching is one such approach which can reduce latencies, although it always increases the workload in the home nodes. In this paper, we propose a scheme named Agent Home Scheme. Its most noticeable feature, when compared to other schemes, is that the agent home distributes the workloads of each computing nodes when sending data. By doing this, we can reduce not only the workload of the home nodes by balancing the workload for each node, but also the waiting time. Experimental results show that the proposed method can obtain about 20% higher performance than the original JIAJIA, about 18% more than History Prefetching Strategy (HPS), and about 10% higher than Effective Prefetch Strategy (EPS).     

Realization of robust nonlinear model predictive control by offline optimisation

This paper describes a new method for increasing the computational efficiency of nonlinear robust model-based predictive control. It is based on the application of neuro-fuzzy networks and improves the computation efficiency by arranging the online optimisation to be done offline. The offline optimisation is realized by offline training a neuro-fuzzy network, consisting of zero-order T–S fuzzy rules, which is designed to approximate the input–output relationship of a robust model-based predictive controller. The design and the training of the neuro-fuzzy network are described, and the corresponding control algorithm is developed. Experiment results performed on the temperature control loop of an experimental air-handling unit (AHU) demonstrate the effectiveness of this approach.     

A H-QoS-demand personalized home physiological monitoring system over a wireless multi-hop relay network for mobile home healthcare applications

For the elderly and chronic patients with cardiovascular disease who live alone, it is necessary to constantly monitor their physiological parameters, especially the electrocardiogram (ECG), to effectively prevent and control their health condition and even to provide urgent treatment or care while an emergency such as the abnormal variation of heart rate (HR) occurs. In this paper, a wireless in-home physiological monitoring system, based on multi-hop relay communications, which can ubiquitously and continuously monitor the patient's ECG at any time or any place at home without space limit and the “dead spot” due to the extended communication coverage by multi-hop wireless connectivity, is proposed. The system consists of a mobile-care device, which is responsible for capturing and wirelessly sending the patient's ECG data, a wireless multi-hop relay network (WMHRN) that is in charge of relaying the data sent by the former, and a residential gateway (RG), which is responsible for gathering and uploading the received ECG data to the remote care server through the Internet to carry out the patient's health condition monitoring and the management of pathological data. However, in order to assure that the ECG data can be effectively and timely forwarded, from the mobile-care device to the RG through the WMHRN, to meet the healthcare quality of service (H-QoS) demand for reliable and real-time end-to-end ECG transmission, the analysis of WMHRN latency in data-forwarding stage and the deployment consideration of wireless relay nodes are investigated in detail in this work. Moreover, an emergency alert service using short message service (SMS), based on the detection of abnormal variation of HR, is also used in the RG to further enhance the healthcare service quality. A prototype of this system has been developed and implemented. Finally, the experimental results are presented to verify the feasibility of the proposed system.     

Fabrication and flow test of long-term hydrophilic fluidic chip without using any surface modification treatment

In order to effectively pump liquid in a fluidic chip, the PDMS or SU8 channels were frequently modified by surface treatments to obtain the hydrophilic surface but encountered the problem of the hydrophobic recovery. In this article, long-term highly hydrophilic fluidic chips were demonstrated using rapid fabrication of low-power CO₂ laser ablation and low-temperature glass bonding with an interlayer of liquid crystal polymer (LCP). The intrinsic hydrophilic materials of glass and LCP were beneficial for self-driven flow in the long-term fluidic chip by surface-tension force with no extra fluidic pumps. The higher viscosity fluid could increase the difficulty of self-driven capability. The stability of contact angle and flow test of the chip after 2 months is similar to that at beginning. The high-viscosity human whole blood was successfully driven at an average moving velocity of about 1.89 mm/s for the beginning and at 2.04 mm/s after 2 months. Our fluidic chip simplifies the traditional complex fabrication procedure of glass chips and conquers the problem of traditional hydrophobic recovery.     

Questionnaire-based variability modeling for system configuration

Variability management is a recurrent issue in systems engineering. It arises for example in enterprise systems, where modules are configured and composed to meet the requirements of individual customers based on modifications to a reference model. It also manifests itself in the context of software product families, where variants of a system are built from a common code base. This paper proposes an approach to capture system variability based on questionnaire models that include order dependencies and domain constraints. The paper presents analysis techniques to detect circular dependencies and contradictory constraints in questionnaire models, as well as techniques to incrementally prevent invalid configurations by restricting the space of allowed answers to a question based on previous answers. The approach has been implemented as a toolset and has been used in practice to capture configurable process models for film post-production.