GPS calibrated ad-hoc localization for geosocial networking

LNCS v. 6406 is conference proceedings of UIC 2010Cost-effective localization for large-scale Geosocial networking service is a challenging issue in urban environment. This paper studies an ad-hoc localization technique which takes advantages of short-range interchanged location information for calibrating the location of mobile users carrying non-GPS mobile phones. We demonstrate by simulation that a small percentage of GPS-enabled mobile phones can greatly enable the localization of other non-GPS pedestrians in the urban environment. Based on the proposed localization technique, we implement a location-aware social networking tool called Mobile Twitter, similar to the microblogging service of Twitter, for fast propagation of social events happening in surroundings. Evaluation shows the our localization algorithm can achieve better accuracy of the location estimation and wider coverage as compared with the Amorphous algorithm and the Monte Carlo Localization (MCL) method. Moreover, we show that the Mobile Twitter implemented on an Android mobile phone is power-efficient in real-life usage scenarios. © 2010 Springer-Verlag.postprintThe 7th International Conference on Ubiquitous Intelligence and Computing (UIC) 2010, Xi'an, China, 26-29 October 2010. In Lecture Notes in Computer Science, 2010, v. 6406, p. 52-6

BetterLife 2.0: large-scale social intelligence reasoning on cloud

This paper presents the design of the BetterLife 2.0 framework, which facilitates implementation of large-scale social intelligence application in cloud environment. We argued that more and more mobile social applications in pervasive computing need to be implemented this way, with a lot of user generated activities in social networking websites. We adopted the Case-based Reasoning technique to provide logical reasoning and outlined design considerations when porting a typical CBR framework jCOLIBRI2 to cloud, using Hadoop's various services (HDFS, HBase). These services allow efficient case base management (e.g. case insertion) and distribution of computational intensive jobs to speed up reasoning process more than 5 times. With the scalability merit of MapReduce, we can improve recommendation service with social network analysis that needs to handle millions of users' social activities. © 2010 IEEE.published_or_final_versionThe 2nd IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2010), Indianapolis, IN., 30 November-3 December 2010. In Proceedings of the 2nd CloudCom, 2010, p. 529-53

Adaptive sampling-based profiling techniques for optimizing the distributed JVM runtime

Extending the standard Java virtual machine (JVM) for cluster-awareness is a transparent approach to scaling out multithreaded Java applications. While this clustering solution is gaining momentum in recent years, efficient runtime support for fine-grained object sharing over the distributed JVM remains a challenge. The system efficiency is strongly connected to the global object sharing profile that determines the overall communication cost. Once the sharing or correlation between threads is known, access locality can be optimized by collocating highly correlated threads via dynamic thread migrations. Although correlation tracking techniques have been studied in some page-based sof Tware DSM systems, they would entail prohibitively high overheads and low accuracy when ported to fine-grained object-based systems. In this paper, we propose a lightweight sampling-based profiling technique for tracking inter-thread sharing. To preserve locality across migrations, we also propose a stack sampling mechanism for profiling the set of objects which are tightly coupled with a migrant thread. Sampling rates in both techniques can vary adaptively to strike a balance between preciseness and overhead. Such adaptive techniques are particularly useful for applications whose sharing patterns could change dynamically. The profiling results can be exploited for effective thread-to-core placement and dynamic load balancing in a distributed object sharing environment. We present the design and preliminary performance result of our distributed JVM with the profiling implemented. Experimental results show that the profiling is able to obtain over 95% accurate global sharing profiles at a cost of only a few percents of execution time increase for fine- to medium- grained applications. © 2010 IEEE.published_or_final_versionThe 24th IEEE International Symposium on Parallel & Distributed Processing (IPDPS 2010), Atlanta, GA., 19-23 April 2010. In Proceedings of the 24th IPDPS, 2010, p. 1-1

Microwave characterization of (Pb,La)TiO₃ thin films integrated on ZrO₂/SiO₂/Si wafers by sol-gel techniques

2004-2005 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Fusion splicing photonic crystal fibers and conventional single-mode fibers : microhole collapse effect

Author name used in this publication: M. S. Demokan2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Control of the strain and magnetoresistance of LaMnO[sub 3+δ] thin films using the magnetostriction of Terfenol-D alloy

Author name used in this publication: Y. WangAuthor name used in this publication: H. L. W. ChanAuthor name used in this publication: C. L. ChoyAuthor name used in this publication: H. S. Luo2010-2011 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Unsupervised Holistic Image Generation from Key Local Patches

We introduce a new problem of generating an image based on a small number of key local patches without any geometric prior. In this work, key local patches are defined as informative regions of the target object or scene. This is a challenging problem since it requires generating realistic images and predicting locations of parts at the same time. We construct adversarial networks to tackle this problem. A generator network generates a fake image as well as a mask based on the encoder-decoder framework. On the other hand, a discriminator network aims to detect fake images. The network is trained with three losses to consider spatial, appearance, and adversarial information. The spatial loss determines whether the locations of predicted parts are correct. Input patches are restored in the output image without much modification due to the appearance loss. The adversarial loss ensures output images are realistic. The proposed network is trained without supervisory signals since no labels of key parts are required. Experimental results on six datasets demonstrate that the proposed algorithm performs favorably on challenging objects and scenes.Comment: 16 page

Effects of ferroelectric polarization and converse piezoelectric effect induced lattice strain on the electrical properties of La[sub 0.7]Sr[sub 0.3]MnO₃ thin films

Author name used in this publication: R. K. ZhengAuthor name used in this publication: J. WangAuthor name used in this publication: X. Y. ZhouAuthor name used in this publication: Y. WangAuthor name used in this publication: H. L. W. ChanAuthor name used in this publication: C. L. ChoyAuthor name used in this publication: H. S. Luo2005-2006 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Tuning the electrical properties of La[sub 0.75]Ca[sub 0.25]MnO₃ thin films by ferroelectric polarization, ferroelectric-field effect, and converse piezoelectric effect

2006-2007 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

In-plane dielectric properties of epitaxial 0.65Pb(Mg[sub ⅓]Nb[sub ⅔])O₃-0.35 PbTiO₃ thin films in a very wide frequency range

Author name used in this publication: Y. WangAuthor name used in this publication: H. L. W. ChanAuthor name used in this publication: C. L. ChoyAuthor name used in this publication: K. C. Cheng2004-2005 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe