• Knowledge Management Research
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• v.20 no.4
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• pp.1-22
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• 2019

The purpose of this study is to investigate the role of IT-enabled dynamic capability in the relationship between intellectual capital and innovation performance under Industry 4.0. We approach the intellectual capital from the perspective of the resource-based view and define the components of intellectual capital as human capital, social capital, and organizational capital. On the other hand, the IT-based dynamic capability means that the information technology and the utilization ability of the enterprise are combined to overcome the turbulent environment. The empirical results showed that the IT-enabled dynamic capabilities mediated the relationship between intellectual capital and innovation performance as it revealed in theory. And in terms of practical implications, we found the importance of an organization's information technology ability to effectively utilize intangible resources for organizational performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5805-5825
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• 2019

Smartphones are important platforms because of their sophisticated computation, communication, and sensing capabilities, which enable a variety of applications in the Internet of Things (IoT) systems. Moreover, advancements in hardware have enabled sensors on smartphones such as environmental and chemical sensors that make sensor data collection readily accessible for a wide range of applications. However, dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users that vary throughout the day, which greatly affects the efficacy of sensor data collection. Therefore, it is necessary to consider phone users mobility patterns to design data collection schedules that can reduce the loss of sensor data. In this paper, we propose a mobility-based weighted adaptive opportunistic scheduling framework that can adaptively adjust to the dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users and provide prioritized scheduling based on various application scenarios, such as velocity, region of interest, and sensor type. The performance of the proposed framework is compared with other scheduling frameworks in various heterogeneous smartphone user mobility scenarios. Simulation results show that the proposed scheduling improves the transmission rate by 8 percent and can also improve the collection of higher-priority sensor data compared with other scheduling approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2901-2919
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• 2012

Recent research in MEMS (Micro-Electro-Mechanical Systems) and wireless communication has enabled tracking of continuous objects, including fires, nuclear explosions and bio-chemical material diffusions. This paper proposes an energy-efficient scheme that detects and tracks different dynamic shapes of a continuous object (i.e., the inner and outer boundaries of a continuous object). EBCO (Efficient Boundary detection and tracking of Continuous Objects in WSNs) exploits the sensing capabilities of sensor nodes by automatically adjusting the sensing range to be either a boundary sensor node or not, instead of communicating to its neighboring sensor nodes because radio communication consumes more energy than adjusting the sensing range. The proposed scheme not only increases the tracking accuracy by choosing the bordering boundary sensor nodes on the phenomenon edge, but it also minimizes the power consumption by having little communication among sensor nodes. The simulation result shows that our proposed scheme minimizes the energy consumption and achieves more precise tracking results than existing approaches.

• Wind and Structures
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• v.30 no.3
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• pp.231-243
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• 2020

Downbursts are acknowledged for being a major loading hazard for horizontally-extending structures like transmission line systems. With these structures being inherently flexible, it is important to characterize the turbulence associated with the wind flow of downburst events being essential to quantify dynamic excitations on structures. Accordingly, the current study numerically characterizes the downburst wind field of open terrain simulated at the Wind Engineering, Energy and Environment (WindEEE) dome testing facility at The University of Western Ontario in Canada through a high-resolution large eddy simulation (LES). The study validates the numerical simulation considering both the mean and the turbulent components of the flow. It then provides a detailed visual description of the flow at WindEEE through the capabilities enabled by LES to identify the key factors affecting the flow. The study also presents the spatial distribution of turbulence intensities and length scales computed from the numerical model and compares them with previous values reported in the literature. The comparison shows the ability of the downburst simulated at WindEEE to reproduce turbulence characteristics similar to those reported from field measurements. The study also indicates that downburst turbulence is well-correlated circumferentially which imposes high correlated loads on horizontally-distributed structures such as transmission lines.