Incidental Exposure,Selective Exposure,and Political Information Sharing: Integrating Online Exposure Patterns and Expression on Social Media

Political information sharing in social media offers citizens opportunities to engage with news and express their political views, but how do different patterns of online political information exposure, including both incidental and selective exposure, affect sharing? Using two‐wave panel survey data collected in the United States, we examine the relationship between incidental and selective exposure and their consequent links to political information sharing, across different levels of strength of political party affiliation. Our results demonstrate that incidental exposure to counter‐attitudinal information drives stronger partisans to more actively seek out like‐minded political content, which subsequently encourages political information sharing on social media. The results highlight the need to consider both types of political information exposure when modeling citizens' political behavior online.     

When brands come to life: experimental research on the vividness effect of Virtual Reality in transformational marketing communications

Mobile Virtual Reality provides a gateway for marketers to innovatively reach consumers. This study examines the impact of Virtual Reality in the context of transformational brand experience appeals, focussing specifically on the determining role of vividness. A three-dimensional conceptual framework is presented, offering a systematic review of the literature on vividness effects in marketing communications, revealing the major gap that most available studies only focus on informational messages. We conducted an experiment to address this gap and demonstrate in the context of a transformational ad that Virtual Reality generates higher perceptions of vividness and presence than a regular two-dimensional video, with vividness positively affecting attitude toward the ad, both directly and indirectly via presence. Our study also reveals that vividness in turn elicits a positive effect on brand attitudes which stimulates consumers’ purchase intentions. As such, the strategic potential of Virtual Reality for marketing communications is highlighted.     

Semi-automatic construction of a named entity dictionary for entity-based sentiment analysis in social media

To understand the user experience in social media or to facilitate the design of human-centric services by social media, users’ opinions about specific entities in text messages should be captured. A fine-grained named entity recognizer (NER) is an essential module for identifying opinion targets in text messages, and a named-entity (NE) dictionary is a major resource that affects the performance of an NER. However, it is not easy to construct an NE dictionary manually, because human annotation is time-consuming and labor-intensive. To reduce construction time and labor, we propose a semi-automatic system to construct an NE dictionary from the free online resource, Wikipedia. The proposed system constructs a pseudo-document for each Wikipedia NE by using an active-learning technique. It then classifies Wikipedia entries into NE classes based on similarities between the entries and pseudo-documents located in a vector space. In experiments, the proposed system classified 92.3 % of Wikipedia entries into 29 NE classes. It showed a high performance, with a macro-averaging F1-measure of 0.872 and micro-averaging F1-measure of 0.935.     

Enhanced image similarity analysis system in digital pathology

Multimedia Tools and Applications - In digital pathology, image similarity algorithms are used to find cancer in tissue cells from medical images. However, it is very difficult to apply image...     

Ontology-based mobile augmented reality in cultural heritage sites: information modeling and user study

Augmented reality (AR) has received much attention in the cultural heritage domain as an interactive medium for requesting and accessing information regarding heritage sites. In this study, we developed a mobile AR system based on Semantic Web technology to provide contextual information about cultural heritage sites. Most location-based AR systems are designed to present simple information about a point of interest (POI), but the proposed system offers information related to various aspects of cultural heritage, both tangible and intangible, linked to the POI. This is achieved via an information modeling framework where a cultural heritage ontology is used to aggregate heterogeneous data and semantically connect them with each other. We extracted cultural heritage data from five web databases and modeled contextual information for a target heritage site (Injeongjeon Hall and its vicinity in Changdeokgung Palace in South Korea) using the selected ontology. We then implemented a mobile AR application and conducted a user study to assess the learning and engagement impacts of the proposed system. We found that the application provides an agreeable user experience in terms of its affective, cognitive, and operative features. The results of our analysis showed that specific usage patterns were significant with regard to learning outcomes. Finally, we explored how the study’s key findings can provide practical design guidance for system designers to enhance mobile AR information systems for heritage sites, and to show system designers how to support particular usage patterns in order to accommodate specific user experiences better.

     

The q-Ad Hoc Hub Location Problem for Multi-modal Networks

This research proposes a spatial optimization problem over a multi-modal transportation network, termed the q-Ad-hoc hub location problem (AHLP), to utilize alternative hubs in an ad-hoc manner in the wake of a hub outage. The model aims to reorganize the spatial structure of disrupted networks: unaffected hubs are utilized as ad-hoc hubs through which alternative routes connect supply and demand nodes. As a case study, the AHLP is applied to a multi-modal freight transport system connecting international destinations with the United States. The models are utilized to establish a new ranking methodology for critical infrastructure by combining metrics capturing nodal criticality and network resilience and recuperability. The results show that the AHLP is both an effective and practical recovery approach for a hub network to respond to the potential disruptions of hubs and a novel methodology for ranking critical infrastructure.     

B-plane targeting method for orbit maneuver using low thrust

International Journal of Control, Automation and Systems - In this research, a new control law for the trajectory correction maneuver (TCM) is proposed for a spacecraft assumed to be actuated by a...     

On design optimization for structural crashworthiness and its state of the art

Optimization for structural crashworthiness and energy absorption has become an important topic of research attributable to its proven benefits to public safety and social economy. This paper provides a comprehensive review of the important studies on design optimization for structural crashworthiness and energy absorption. First, the design criteria used in crashworthiness and energy absorption are reviewed and the surrogate modeling to evaluate these criteria is discussed. Second, multiobjective optimization, optimization under uncertainties and topology optimization are reviewed from concepts, algorithms to applications in relation to crashworthiness. Third, the crashworthy structures are summarized, from generically novel structural configurations to industrial applications. Finally, some conclusions and recommendations are provided to enable academia and industry to become more aware of the available capabilities and recent developments in design optimization for structural crashworthiness and energy absorption.

     

Note on stability of linear systems with time-varying delay

This note considers the stability of linear systems with a time-varying delay. We are interested in a simple Lyapunov–Krasovskii functional (LKF) approach without delay decomposition. In this category, all recent tractable results had a fixed bound on the allowable maximum size of the delay for years. We propose a new simple LKF including the cross terms of variables and quadratic terms multiplied by a higher degree scalar function, and present a new result expressed in the form of LMIs. We show, by two well-known examples, that our result overcomes the previous allowable maximum size of delay and it is less conservative than the previous results having a relatively small upper bound in the derivative of time-delay.     

Real-time approximation of molecular interaction interfaces based on hierarchical space decomposition

The interaction interface between two molecules can be represented as a bisector surface equidistant from the two sets of spheres of varying radii representing atoms. We recursively divide a box containing both sphere-sets into uniform pairs of sub-boxes. The distance from each new box to each sphere-set is conservatively approximated by an interval, and the number of sphere-box computations is greatly reduced by pre-partitioning each sphere-set using a kd-tree. The subdivision terminates at a specified resolution, creating a box partition (BP) tree. A piecewise linear approximation of the bisector surface is then obtained by traversing the leaves of the BP tree and connecting points equidistant from the sphere-sets. In 124 experiments with up to 16,728 spheres, a bisector surface with a resolution of 1/2⁴ of the original bounding box was obtained in 28.8 ms on average.