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In-network content caching has recently emerged in the context of Information-Centric Networking (ICN), which allows content objects to be cached at the content router side. In this paper, we specifically focus on in-network caching of Peer-to-Peer (P2P) content objects for improving both service and operation efficiencies. We propose an intelligent in-network caching scheme of P2P content chunks,...
In this paper, we assess the performance of inter-cell coordination in the presence of mobility. This performance depends primarily on the resource allocation scheme. Indeed, a scheduling strategy which may seem efficient when users are static can lead to bad performance when users are mobile. Several scheduling policies are investigated. Their performance critically depends on their ability to predict...
We study the problem of data compression, gambling and prediction of strings xn = x1x2…xn in terms of coding regret, where the tree model is assumed as a target class. We apply the minimax Bayes strategy for curved exponential families to this problem and show that it achieves the minimax regret without restriction on the data strings. This is an extension of the minimax result by (Takeuchi et al...
Cancer is a disease driven largely by the accumulation of somatic mutations during the lifetime of a patient. Distinguishing driver mutations from passenger mutations had posed a challenge in modern cancer research. With the widespread use of microarray experiments and clinical studies, a large numbers of candidate cancer genes are produced and extracting informative genes out of them is essential...
Current electrical grid is facing increased penetration of intermittent energy resources, in particular wind and solar energy. Fast variability of the power supply due to renewable energy resources can be balanced out using different energy storage systems or shifting the loads. Efficiently managing this fast flexibility requires two-way data exchange between a controller and sensors/meters via communication...
This paper presents a heterogeneous computing solution for an optimized genetic selection analysis tool, GenSel. GenSel can be used to efficiently infer the effects of genetic markers on a desired trait or to determine the genomic estimated breeding values (GEBV) of genotyped individuals. To predict which genetic markers are informational, GenSel performs Bayesian inference using Gibbs sampling, a...
We consider a system where inelastic demand for electric power is met from three sources: the grid, in-house renewables such as wind turbines or solar panels, and an in-house energy storage device. In our setting, power demand, renewable power supply, and cost for grid power are all time-varying and stochastic. Further, there are limits and efficiency issues for charging and discharging the energy...
The analysis of realization low-intensity HTTP-attacks was performed. Were described scenarios of Slowloris, Slow POST and Slow READ attack. Features of this type of attacks in comparison with low-level attacks such as “denial of service” were selected: they do not require a large number of resources from the attacking machine, and they are difficult for the detection, since their parameters are similar...
A novel application of Hidden Markov Models is used to help research intended to test the immunuregulatory effects of mesenchymal stem cells in a cynomolgus monkey model of islet transplantation. The Hidden Markov Model, an unsupervised learning data mining technique, is used to automatically determine the postoperative day (POD) corresponding to a decrease of graft function, a possible sign of transplant...
This paper proposes the application of the Markov decision problem (MDP) framework for optimizing the autonomous charging of individual plug-in electric vehicles (EVs). Two infinite horizon average cost MDP formulations are described, one for plug-in hybrid electric vehicles (PHEVs) and one for battery only electric vehicles (BEVs). In both formulations, we assume no direct input from the driver to...
We present AutoLeadGuitar, a system for automatically generating guitar solo tablatures from an input chord and key sequence. Our system generates solos in distinct musical phrases, and is trained using existing digital tablatures sourced from the web. When generating solos AutoLeadGuitar assigns phrase boundaries, rhythms and fretboard positions within a probabilistic framework, guided towards chord...
In the opportunistic networks, nodes carry and store the data and forward it until they encounter each other. How to choose an appropriate opportunity to forward data is pivotal for nodes' routing in this type of networks. Since nodes currently will keep a regular movement state in the scene of this paper discussed, forecasting a node's moving track in the near future would be very helpful. Through...
In this paper we present a proposal for a new prognostic model to be included in a future revision of the IEEE Std 1232–2010 Standard for Artificial Intelligence Exchange and Service Tie to All Test Environments (AI-ESTATE). Specifically, we introduce the continuous time Bayesian network (CTBN) as an alternative to the previously proposed dynamic Bayesian network to provide an additional model for...
Hidden Markov models are frequently used in handwriting-recognition applications. While a large number of methodological variants have been developed to accommodate different use cases, the core concepts have not been changed much. In this paper, we develop a number of datasets to benchmark our own implementation as well as various other tool kits. We introduce a gradual scale of difficulty that allows...
Recommender systems are a real example of human computer interaction systems that both consumer/user and seller/service-provider benefit from them. Different techniques have been published in order to improve the quality of these systems. One of the approaches is using context information such as location of users or items. Most of the location-aware recommender systems utilize users' location to...
In recent years, vessel traffic and maritime situation awareness become more and more important for countries across the world. AIS data contains much information about vessel motion and reflects traffic characteristics. In this paper, data mining is introduced to discover motion patterns of vessel movements. Firstly, we do statistical analysis for large scale of AIS data. Secondly, we use association...
With the development of trajectory data mining, personal privacy information is facing a great threaten. To prevent privacy disclosure, some anonymous methods should be used before the raw trajectory data is published. Yet, most existing methods did not consider the uncertainty in trajectory, largely due to the inherent inaccuracy of data acquisition equipments, delayed update of mobile objects and...
Crowd sourcing is emerging as a powerful paradigm to solve a wide range of tedious and complex problems in various enterprise applications. It spawns the issue of finding the unknown collaborative and competitive group of solvers. The formation of collaborative team should provide the best solution and treat that solution as a trade secret avoiding data leak between competitive teams due to reward...
The Self-Organizing Networks (SON) concept includes the functional area known as self-healing, which aims to automate the detection and diagnosis of, and recovery from, network degradations and outages. Changes to the configuration management (CM) parameters for network elements could be a cause for degraded network performance and stability; hence, the verification of their effects becomes crucial...
Accurate modeling of building occupancy is an important issue in building energy optimization, but it is a difficult problem due to its stochastic property. This paper proposed an inhomogeneous Markov chain approach to model building occupancy under two scenarios of multi-occupant single-zone (MOSZ) and multi-occupant multi-zone (MOMZ). In this study, we define the state of the Markov chain as an...
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