In this paper, we proposed a novel and practical solution for the real-time indoor localization of autonomous driving in parking lots. High-level landmarks, the parking slots, are extracted and enriched with labels to...
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In order to reduce traffic accidents and road congestion in many cities, vehicle speed estimation is very critical and important to observe speed limitation law and traffic conditions. In this paper, we present a spee...
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Object measurement based on surveillance video-images is a critical task in the field of intelligent video surveillance. In this paper, we proposed an object measurement system based on surveillance video-images. Firs...
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Observability and/or controllability are paid much attention to by researchers not only from the control science field[1–3]but also from the computer science field[4–9].Recently,Desel and Kilinc[4]proposed the notio...
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Observability and/or controllability are paid much attention to by researchers not only from the control science field[1–3]but also from the computer science field[4–9].Recently,Desel and Kilinc[4]proposed the notion of observable liveness for Petri nets with(un-)observable and(un-)controllable *** purpose of defining observable liveness is to represent that"a user can always enforce the occurrence of any observable transition only by stimulating the net by choosing appropriate enabled controllable transition"[4].An important assumption of
Compressive Sensing (CS) is a new paradigm for the efficient acquisition of signals that have sparse representation in a certain domain. Traditionally, CS has provided numerous methods for signal recovery over an orth...
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With the advance of the information and communication technology, smart grid, and smart metering, residential electricity usage data are available for analyzing household usage pattern. However, most such usage patter...
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With the advance of the information and communication technology, smart grid, and smart metering, residential electricity usage data are available for analyzing household usage pattern. However, most such usage pattern analyses have been based on smart meter data. Geographical location and environment factors have not been well considered. In order to have a better understanding of residential electricity usage pattern, this paper studies the usage pattern based on both environment data and smart meter data. A Hidden Markov Model (HMM) is applied to learn the consumption dynamic behavior under the corresponding environments and a clustering method is applied to discover the typical usage patterns. The environmental adaptation which indicates the household reaction to the environment during the electricity consumption is revealed.
Applying the proliferated location-based services (LBS) to social networks has spawned mobile social network (MSN) services that it allows users to discover potential friends around them. In this paper, we focus on th...
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Applying the proliferated location-based services (LBS) to social networks has spawned mobile social network (MSN) services that it allows users to discover potential friends around them. In this paper, we focus on the problem of location privacy preserving in MSN. Particularly, we propose a location privacy preserving (RPAR) scheme via to repartition anonymous region where the central anonymous location minimizes the traffic between the anonymous server and the LBS server while protecting the privacy of the user location.
It is challenging to design a secure recommendation system on the Internet which can help users to select their favorite products as less privacy leaked as possible. In this paper, we present a hybrid filtrations reco...
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It is challenging to design a secure recommendation system on the Internet which can help users to select their favorite products as less privacy leaked as possible. In this paper, we present a hybrid filtrations recommendation system based on privacy preserving in edge computing (HFRS-PP), which can prevent the users’ privacy information from being leaked via the merits of edge computing in the process of computing and ensure the real-time, accuracy and stability of the query results. Particularly, we propose a privacy-preserving recommendation algorithm to obtain the desired results for the end users through hybrid filtrations. The filtration-rough set theory algorithm is given to distinguish the valid reviews from spam reviews for the next filtration.
This paper proposes a C-RNN forecasting method for Forex time series data based on deep-Recurrent Neural Network (RNN) and deep Convolutional Neural Network (CNN), which can further improve the prediction accuracy of ...
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This paper proposes a C-RNN forecasting method for Forex time series data based on deep-Recurrent Neural Network (RNN) and deep Convolutional Neural Network (CNN), which can further improve the prediction accuracy of deep learning algorithm for the time series data of exchange rate. We fully exploit the spatio-temporal characteristics of forex time series data based on the data-driven method. On the exchange rate data of nine major foreign exchange currencies, the experimental comparison of the forecasting method shows that the C-RNN foreign exchange time series data prediction method constructed in this paper has better applicability and higher accuracy.
Clustering analysis has been widely used in pattern recognition and image processing in recent years, which is an important research field of data mining. Data publishing in social networks is threatened by the leakag...
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Clustering analysis has been widely used in pattern recognition and image processing in recent years, which is an important research field of data mining. Data publishing in social networks is threatened by the leakage of private information nowadays. This paper proposes a privacy preservation scheme of sensitive data publishing in social networks based on Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) algorithm to tackle this issue. The scheme is divided into an online process and an offline process. Specifically, we present the Maximum Delay Anonymous Clustering Feature (MDACF) tree data publishing algorithm.
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