Abstract: Social media platforms are emerging digital communication channels that provide an easy way for common people to share their health and medication experiences online. With more people discussing their health information online publicly, social media platforms present a rich source of information for exploring adverse drug reactions (ADRs). ADRs are major public health problems that result in deaths and hospitalizations of millions of people. Unfortunately, not all ADRs are identified before a drug is made available in the market. In this study, an ADR event monitoring system is developed which can recognize ADR mentions from a tweet and classify its assertion. We explored several entity recognition features, feature conjunctions, and feature selection and analyzed their characteristics and impacts on the recognition of ADRs, which have never been studied previously. The results demonstrate that the entity recognition performance for ADR can achieve an F-score of 0.562 on the PSB Social Media Mining shared task dataset, which outperforms the partial-matching-based method by 0.122. After feature selection, the F-score can be further improved by 0.026. This novel technique of text mining utilizing shared online social media data will open an array of opportunities for researchers to explore various health related issues.
Abstract: Technology has become an increasingly integral part of life. For example, technology allows individuals to stay in touch with loved ones, obtain medical services through telehealthcare, and enjoy an overall higher quality of life. Particularly for older adults, using technology increases the likelihood that they will maintain their independence and autonomy. Long-distance caregiving has recently become a feasible option where caregivers for older adults can access reports and information about their loved one’s patterns that day (e.g., food and medication intake). Technology may be able to offset age-related challenges (e.g., caregiving, accessing healthcare, decreased social networks) by applying technology to the needs of older adults. Solutions for meeting such challenges, however, have been less targeted. In addition, the healthcare system is evolving to focus on providing options and services in the home. This has direct implications for older adults, as the majority of healthcare services are utilized by older adults. Research is still at the beginning stages of developing successful technology tools that are compatible with older adult users. Therefore, the design, implementation, and outcome of such computer-based communication activities will be discussed in this paper in order to guide future endeavors in technology marketed for older adults.
Abstract: Routing Protocol for Low power and Lossy network (RPL) topology attacks can downgrade the network performance significantly by disrupting the optimal protocol structure. To detect such threats, we propose a RPL-specification, obtained by a semi-auto profiling technique that constructs a high-level abstract of operations through network simulation traces, to use as reference for verifying the node behaviors. This specification, including all the legitimate protocol states and transitions with corresponding statistics, will be implemented as a set of rules in the intrusion detection agents, in the form of the cluster heads propagated to monitor the whole network. In order to save resources, we set the cluster members to report related information about itself and other neighbors to the cluster head instead of making the head overhearing all the communication. As a result, information about a cluster member will be reported by different neighbors, which allow the cluster head to do cross-check. We propose to record the sequence in RPL Information Object (DIO) and Information Solicitation (DIS) messages to eliminate the synchronized issue created by the delay in transmitting the report, in which the cluster head only does cross-check on information that come from sources with the same sequence. Simulation results show that the proposed Intrusion Detection System (IDS) has a high accuracy rate in detecting RPL topology attacks, while only creating insignificant overhead (about 6.3%) that enable its scalability in large-scale network.
Abstract: The wiretap channel models secure communication between two users in the presence of an eavesdropper who must be kept ignorant of transmitted messages. This communication scenario is studied for arbitrarily varying channels (AVCs), in which the legitimate users know only that the true channel realization comes from a pre-specified uncertainty set and that it varies from channel use to channel use in an arbitrary and unknown manner. This concept not only captures the case of channel uncertainty, but also models scenarios in which malevolent adversaries influence or jam the transmission of the legitimate users. For secure communication over orthogonal arbitrarily varying wiretap channels (AVWCs) it has been shown that the phenomenon of super-activation occurs; that is, there are orthogonal AVWCs, each having zero secrecy capacity, which allow for transmission with positive rate if they are used together. It is shown that for such orthogonal AVWCs super-activation is generic in the sense that whenever super-activation is possible, it is possible for all AVWCs in a certain neighborhood as well. As a consequence, a super-activated AVWC is robust and continuous in the uncertainty set, although a single AVWC might not be. Moreover, it is shown that the question of super-activation and the continuity of the secrecy capacity solely depends on the legitimate link. Accordingly, the single-user AVC is subsequently studied and it is shown that in this case, super-activation for non-secure message transmission is not possible making it a unique feature of secure communication over AVWCs. However, the capacity for message transmission of the single-user AVC is shown to be super-additive including a complete characterization. Such knowledge is important for medium access control and in particular resource allocation as it determines the overall performance of a system.
Information2016, 7(2), 23; doi:10.3390/info7020023 - published 26 April 2016 Show/Hide Abstract
Abstract: The most effective approach to evaluating the security of complex systems is to deliberately construct the systems using security patterns specifically designed to make them evaluable. Just such an integrated set of security patterns was created decades ago based on the Reference Monitor abstraction. An associated systematic security engineering and evaluation methodology was codified as an engineering standard in the Trusted Computer System Evaluation Criteria (TCSEC). This paper explains how the TCSEC and its Trusted Network Interpretation (TNI) constitute a set of security patterns for large, complex and distributed systems and how those patterns have been repeatedly and successfully used to create and evaluate some of the most secure government and commercial systems ever developed.
Information2016, 7(2), 22; doi:10.3390/info7020022 - published 14 April 2016 Show/Hide Abstract
Abstract: Knowledge management systems are widely used to manage the knowledge in organizations. Consulting experts is an effective way to utilize tacit knowledge. The paper aims to optimize the match between users and experts to improve the efficiency of tacit knowledge-sharing. Firstly, expertise, trust and feedback are defined to characterize the preference of users for experts. Meanwhile, factors including trust, relationship and knowledge distance are defined to characterize the preference of experts for users. Then, a new method for the measurement of satisfaction based on the principle of axiomatic design is proposed. Afterwards, in order to maximize the satisfaction of both experts and users, the optimization model is constructed and the optimal solution is shown in the matching results. The evaluation results show the approach is feasible and performs well. The approach provides new insights for research on tacit knowledge-sharing. It can be applied as a tool to match experts with users in the development of knowledge management systems. The fuzzy linguistic method facilitates the expression of opinions, and as a result, the users-system interaction is improved.