Understanding the rapid information diffusion process in social media is critical for crisis management. Most of existing studies mainly focus on information diffusion patterns under the word-of-mouth spread mechanism...
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Despite the growing number of videos featuring electronic cigarettes, there has been no investigation of the portrayal of these videos. This paper presents the first surveillance data of electronic cigarette videos on...
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Group behavior forecasting is an emergent re- search and application field in social computing. Most of the existing group behavior forecasting methods have heavily re- lied on structured data which is usually hard to...
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Group behavior forecasting is an emergent re- search and application field in social computing. Most of the existing group behavior forecasting methods have heavily re- lied on structured data which is usually hard to obtain. To ease the heavy reliance on structured data, in this paper, we pro- pose a computational approach based on the recognition of multiple plans/intentions underlying group behavior. We fur- ther conduct human experiment to empirically evaluate the effectiveness of our proposed approach.
Among the most important and distinctive actionable knowledge are actionable behavioral rules that can directly and explicitly suggest specific actions to take to influence the behavior in the users' best interest...
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ISBN:
(纸本)9781467362146
Among the most important and distinctive actionable knowledge are actionable behavioral rules that can directly and explicitly suggest specific actions to take to influence the behavior in the users' best interest. However, in mining such rules, it often occurs that different rules may suggest the same actions with different expected utilities, which we call conflicting rules. To resolve the conflicts, a previous pruning method was proposed. However, inconsistency of the measure for rule pruning may hinder its performance. To overcome this problem, we develop a new pruning method to achieve rule pruning in actionable rule discovery. We conduct several experiments to test our proposed approach and evaluate the sensitivity of the weight parameter. Empirical results based on a benchmark terrorism dataset indicate that our approach outperforms those from previous research.
In this paper, we propose a unified TDMA-based scheduling protocol for Vehicle-to-Infrastructure (V2I) communications. In the proposed TDMA-based scheduling protocol, the roadside infrastructure collects the informati...
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In this paper, we propose a unified TDMA-based scheduling protocol for Vehicle-to-Infrastructure (V2I) communications. In the proposed TDMA-based scheduling protocol, the roadside infrastructure collects the information from the vehicles within its communication coverage through a control channel at the beginning of each transmission frame and then decides how to allocate the time slots to the vehicles for their data transmission requests based on a new designed weight-factor-based scheduler. The provided weight factor jointly takes into consideration the channel quality of communication links, the speed based fairness among vehicles, and different access categories. Simulation results verify the efficiency of the proposed scheduling protocol in terms of the network throughput performance, the fairness among the vehicles, and different accessing priorities of different access categories.
In a world where possessing raw materials or manufacturing commodities are not sufficient for long-term economic success, innovativeness and a knowledge-based economy form the basis for prosperity. In this report, we ...
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In a world where possessing raw materials or manufacturing commodities are not sufficient for long-term economic success, innovativeness and a knowledge-based economy form the basis for prosperity. In this report, we discuss the link between a nation's higher education system and its ability to bring about and foster innovativeness and economic growth. In particular, we will concentrate on the roles that universities play in the national innovation system. Some of the questions we address include: How strong a link is there between the education system and nation's innovativeness? How important is industry-academia collaboration? From the perspective of a knowledge-based economy, what would an ideal university be like? To answer these questions, we summarize key findings from the literature. The aim of this report is to present the key factors and decisions that should be considered in future higher education strategies.
Video detection is one of the primary collection means of traffic states in Parallel traffic managementsystems (PtMS). In order to accurately and automatically obtain road areas in highway surveillance videos, this p...
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ISBN:
(纸本)9781479905287
Video detection is one of the primary collection means of traffic states in Parallel traffic managementsystems (PtMS). In order to accurately and automatically obtain road areas in highway surveillance videos, this paper presents an automatic detection algorithm based on the frequency-domain information of video images. This algorithm uses the frequency-domain feature that is produced by the vehicles passing through road areas in videos, to realize automatic segmentation and recognition of the road areas. The experiment comparing with the traditional vehicle-tracking-based method, which uses the information in the time-space domain, illustrates the advantages of the proposed algorithm.
Discovering temporal patterns and changes in tobacco use has important practical implications in tobacco control. This paper presents one of the first comprehensive international studies of seasonal smoking patterns b...
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ISBN:
(纸本)9781467362146
Discovering temporal patterns and changes in tobacco use has important practical implications in tobacco control. This paper presents one of the first comprehensive international studies of seasonal smoking patterns based on online searches performed. Using periodogram and cross-correlation, we find that smoking-related search behavior shows strong seasonality effect across countries. In addition, there are significant pairwise associations between such seasonality in different countries.
Extracting emotions from online reviews is crucial to many security-related applications as well as applications in other domains. Traditional approaches to emotion extraction have mainly focused on mining the polarit...
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ISBN:
(纸本)9781467362146
Extracting emotions from online reviews is crucial to many security-related applications as well as applications in other domains. Traditional approaches to emotion extraction have mainly focused on mining the polarities of opinions or using annotated data to extract emotion types. Emotion theories, which identify the underlying cognitive structure and emotional dimensions that are key to generate emotions, have almost been totally ignored in previous work. To facilitate the automatic extraction of emotions from textual data, in this paper, we propose an emotion model based approach to emotion extraction from online reviews. Informed by the widely used OCC emotion model, we employ a statistical method to extract emotion words with their dimension values from texts, and implement OCC model to obtain emotions based on the emotion-dimension dictionary. We conduct an empirical study using security-related news reviews. The experimental results demonstrate the effectiveness of our proposed approach.
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