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Contribution-Based Energy-Trading Mechanism in Microgrids for Future Smart Grid: A Game Theoretic Approach
TLDR
This paper designs a contribution-based energy-trading mechanism among microgrids in a competitive market that is fast enough for real-time implementation. Expand
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Abnormal Object Detection by Canonical Scene-Based Contextual Model
TLDR
In this paper, we propose a novel generative model that can detect out-of-context objects, also referred to as abnormal objects. Expand
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Competitive Partial Computation Offloading for Maximizing Energy Efficiency in Mobile Cloud Computing
TLDR
We newly model computation offloading competition when multiple clients compete with each other so as to reduce energy cost and improve computational performance by considering a trade-off between different types of destinations. Expand
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Integrated Intelligence for Human-Robot Teams
TLDR
We present an intelligence architecture for human-robot teams that has been fully integrated into a mobile robot platform. Expand
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Personal Data Trading Scheme for Data Brokers in IoT Data Marketplaces
TLDR
This paper proposes an optimized trading model for data brokers who buy personal data with proper incentives based on the WTS, and they sell valuable information from the refined dataset by considering the WTB and the dataset quality. Expand
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Calibrated Prediction with Covariate Shift via Unsupervised Domain Adaptation
TLDR
We propose an algorithm for calibrating predictions that accounts for the possibility of covariate shift, given labeled example from the training distribution and unlabeled examples from the real-world distribution. Expand
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Event-Driven Energy Trading System in Microgrids: Aperiodic Market Model Analysis With a Game Theoretic Approach
TLDR
This paper presents the design of an event-driven energy trading system among microgrids. Expand
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An Optimal Pricing Scheme for the Energy-Efficient Mobile Edge Computation Offloading With OFDMA
TLDR
We consider a single-cloud-multi-user MECO system with orthogonal frequency-division multiple access and propose an optimal pricing scheme to consider each mobile user’s (MU) need for resources. Expand
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Three Hierarchical Levels of Big-Data Market Model Over Multiple Data Sources for Internet of Things
TLDR
This paper proposes three hierarchical levels of a competitive big-data market model in which a service provider gathers data from multiple data sources and provides valuable information from refined data as a service to its customers. Expand
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Learning-Based Adaptive Imputation Methodwith kNN Algorithm for Missing Power Data
TLDR
This paper proposes a learning-based adaptive imputation method (LAI) for imputing missing power data in an energy system. Expand
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