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Parallel field ranking

Parallel field ranking

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作者： Ji, Ming Lin, Binbin He, Xiaofei Cai, Deng Han, Jiawei Department of Computer Science University of Illinois Urbana-Champaign IL United States Center for Evolutionary Medicine and Informatics Biodesign Institute Arizona State University United States State Key Lab of CAD and CG College of Computer Science Zhejiang University China

Recently, ranking data with respect to the intrinsic geometric structure (manifold ranking) has received considerable attentions, with encouraging performance in many applications in pattern recognition, information retrieval and recommendation systems. Most of the existing manifold ranking methods focus on learning a ranking function that varies smoothly along the data manifold. However, beyond smoothness, a desirable ranking function should vary monotonically along the geodesics of the data manifold, such that the ranking order along the geodesics is preserved. In this article, we aim to learn a ranking function that varies linearly and therefore monotonically along the geodesics of the data manifold. Recent theoretical work shows that the gradient field of a linear function on the manifold has to be a parallel vector field. Therefore, we propose a novel ranking algorithm on the data manifolds, called Parallel Field Ranking. Specifically, we try to learn a ranking function and a vector field simultaneously. We require the vector field to be close to the gradient field of the ranking function, and the vector field to be as parallel as possible. Moreover, we require the value of the ranking function at the query point to be the highest, and then decrease linearly along the manifold. Experimental results on both synthetic data and real data demonstrate the effectiveness of our proposed algorithm. © 2013 ACM.

关键词： Recommender systems

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Multi-person identification and localization for ambient assistive living

Multi-person identification and localization for ambient ass...

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1st International Conference on Distributed, Ambient, and Pervasive Interactions, DAPI 2013, Held as Part of 15th International Conference on Human-computer Interaction, HCI International 2013

作者： Galatas, Georgios Ferdous, Shahina Makedon, Fillia Heracleia Human Centered Computing Lab Computer Science and Engineering Dept. University of Texas at Arlington United States Institute of Informatics and Telecommunications NCSR Demokritos Athens Greece

ISBN: (纸本)9783642393501

In this paper, we present a novel, non-intrusive system that uses RFID technology and the Kinect sensor in order to identify and track multiple people in an assistive apartment. RFID is used for both identification and location estimation while information from the Kinect sensor is used for accurate localization. Data from the various modalities is fused using two techniques. During the experiments conducted, our system exhibited high accuracy, thus proving the effectiveness of the proposed design. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Radio frequency identification (RFID)

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A novel cardiovascular decision support framework for effective clinical risk assessment

A novel cardiovascular decision support framework for effect...

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IEEE Symposium on Computational Intelligence in Healthcare and e-health

作者： Kamran Farooq Jan Karasek Hicham Atassi Amir Hussain Peipei Yang Calum MacRae Mufti Mahmud Bin Luo Warner Slack Computing Science and Mathematics Division University of Stirling Stirling UK Department of Telecommunications Brno University of Technology Brno Czech Republic National Laboratory of Pattern Recognition Chinese Academy of Science Beijing China Harvard Medical School Brigham and Women's Hospital Boston US COSIPRA Lab University of Stirling Stirling United Kingdom Institute of Information Technology Jahangirnagar University Savar Dhaka Bangladesh Theoretical Neurobiology and Neuroengineering Lab University of Antwerp Belgium School of Computer Science and Technology Anhui University Anhui China Beth Israel Clinical Informatics Division Harvard Medical School Boston US

The aim of this study is to help improve the diagnostic and performance capabilities of Rapid Access Chest Pain Clinics (RACPC), by reducing delay and inaccuracies in the cardiovascular risk assessment of patients with chest pain by helping clinicians effectively distinguish acute angina patients from those with other causes of chest pain. Key to our new approach is (1) an intelligent prospective clinical decision support framework for primary and secondary care clinicians, (2) learning from missing/impartial clinical data using Bernoulli mixture models and Expectation Maximisation (EM) techniques, (3) utilisation of state-of-the-art feature section, pattern recognition and data mining techniques for the development of intelligent risk prediction models for cardiovascular patients. The study cohort comprises of 632 patients suspected of cardiac chest pain. A retrospective data analysis of the clinical studies evaluating clinical risk factors for chest pain patients was performed for the development of RACPC specific risk assessment models to distinguish between cardiac and non cardiac chest pain. A comparative analysis case study of machine learning methods was carried out for predicting RACPC clinical outcomes using real patient data acquired from Raigmore Hospital in Inverness, UK. The proposed framework was also validated using the University of Cleveland's Heart Disease dataset which contains 76 attributes, but all published experiments refer to using a subset of 14 of them. Experiments with the Cleveland database (based on 18 clinical features of 270 patients) were concentrated on attempting to distinguish the presence of heart disease (values 1, 2, 3, 4) from absence (value 0). The new clinical models, having been evaluated in clinical practice, resulted in very good predictive power, demonstrating general performance improvement over benchmark multivariate statistical classifiers. As part of these case studies, various online RACPC risk assessment prototypes

关键词： Pain Diseases Educational institutions Heart Data models Electronic mail Guidelines

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Meta-level Statistical Machine Translation 6

Meta-level Statistical Machine Translation

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6th International Joint Conference on Natural Language Processing, IJCNLP 2013

作者： Ebrahimi, Sajad Meshgi, Kourosh Khadivi, Shahram Abady, Mohammad Ebrahim Shiri Ahmad Human Language Technology Lab Amirkabir University of Technology Tehran Iran Graduate School of Informatics Kyoto University Kyoto Japan Department of Computer Science Amirkabir University of Technology Tehran Iran

ISBN: (纸本)9784990734800

We propose a simple and effective method to build a meta-level Statistical Machine Translation (SMT), called meta-SMT, for system combination. Our approach is based on the framework of Stacked Generalization, also known as Stacking, which is an ensemble learning algorithm, widely used in machine learning tasks. First, a collection of base-level SMTs is generated for obtaining a meta-level corpus. Then a meta-level SMT is trained on this corpus. In this paper we address the issue of how to adapt stacked generalization to SMT. We evaluate our approach on English-to-Persian machine translation. Experimental results show that our approach leads to significant improvements in translation quality over a phrase-based baseline by about 1.1 BLEU points. © IJCNLP *** right reserved.

关键词： Machine translation

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Experiment-Based Scatter Correction for Cone-Beam Computed Tomography Using the Statistical Method

Experiment-Based Scatter Correction for Cone-Beam Computed T...

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35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Aootaphao, Sorapong Thongvigitmanee, Saowapak S. Rajruangrabin, Jatuwat Junhunee, Parinya Thajchayapong, Pairash Image Technology Lab Intelligent Informatics Research Unit National Electronics and Computer Technology Center Thailand Medical Devices Lab Biomedical Engineering Research Unit National Metal and Materials Technology Center Thailand National Science and Technology Development Agency Pathumthani Thailand

ISBN: (纸本)9781457702167

Scatter signals in cone-beam computed tomography (CBCT) cause a significant problem that degrades image quality of reconstructed images, such as inaccuracy of CT numbers and cupping artifacts. In this paper, we will present an experiment-based scatter correction method by preprocessing projection images using a statistical model combined with experimental kernels. The convolution kernels are estimated by using different thickness of PMMA plates attached to a beam stop lead sheet such that the scatter signal values can be measure in the shadow area of the projection images caused by the lead sheet. The scatter signal values of different thickness levels can be measured in the shadow area of projection images caused by the lead sheet. Then, the projection images are convolved with the kernels that are derived from the actual measurement of scatter signals in PMMA plates. Finally, the primary signals can be estimated using the maximum likelihood expectation maximization method. Experimental results by using the proposed method show that the quality of the reconstruction images is significantly improved. The CT numbers become more accurate and the cupping artifact is reduced.

关键词： computerised tomography expectation-maximisation algorithm image reconstruction medical image processing statistical analysis

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ADAPTIVE SINUSOIDAL MODELING OF PERCUSSIVE MUSICAL INSTRUMENT SOUNDS

ADAPTIVE SINUSOIDAL MODELING OF PERCUSSIVE MUSICAL INSTRUMEN...

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European Signal Processing Conference

作者： Marcelo Caetano George P. Kafentzis Athanasios Mouchtaris Yannis Stylianou Institute of Computer Science Foundation for Research and Technology Hellas (FORTH) Multimedia Informatics Lab Computer Science Department University of Crete

Percussive musical instrument sounds figure among the most challenging to model using sinusoids particularly due to the characteristic attack that features a sharp onset and transients. Attack transients present a highly nonstationary inharmonic behaviour that is very difficult to model with traditional sinusoidal models which use slowly varying sinusoids, commonly introducing an artifact known as preecho. In this work we use an adaptive sinusoidal model dubbed eaQHM to model percussive sounds from musical instruments such as plucked strings or percussion and investigate how eaQHM handles the sharp onsets and the nonstationary inharmonic nature of the attack transients. We show that adaptation renders a virtually perceptually identical sinusoidal representation of percussive sounds from different musical instruments, improving the Signal to Reconstruction Error Ratio (SRER) obtained with a traditional sinusoidal model. The result of a listening test revealed that the percussive sounds modeled with eaQHM were considered perceptually closer to the original sounds than their traditional-sinusoidal-modeled counterparts. Most listeners reported that they used the attack as cue.

关键词： Musical instrument modeling Percussion musical instruments Adaptive sinusoidal models Attack transients Preecho

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A HLA-based Multi-Resolution Approach to Simulating Electric Vehicles in Simulink and SUMO

A HLA-based Multi-Resolution Approach to Simulating Electric...

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International IEEE Conference on Intelligent Transportation Systems

作者： Jose Macedo Zafeiris Kokkinogenis Guilherme Soares Deborah Perrotta Rosaldo J. F. Rossetti Artificial Intelligence and Computer Science Lab Department of Informatics Engineering Faculty of Engineering University of Porto Artificial Intelligence and Computer Science Lab University of Porto

ISBN: (纸本)9781479929153

Traffic congestion affects not only the economic activity of cities but is also responsible for air quality and global warming problems. The employment of electric buses in metropolitan transportation as an alternative to internal combustion engine buses appears to be a promising eco-sustainable solution. However, an important aspect in evaluating the performance and adequateness of such vehicles is the fact they are immersed in an urban context. This work follows a HLA-based distributed architecture for electric bus powertrain simulation within a realistic urban mobility environment. In that sense, it discusses on coupling the SUMO (Simulation of Urban MObility) microscopic traffic simulator with a model of an electric bus powertrain subsystem designed in the Matlab/Simulink environment. Both the electric bus traction subsystems and the integration have been validated using field test experimental data. The proposed simulation framework is multi-faceted. As a matter of fact it can be used, not only as electric vehicle evaluation tool under different dynamics of traffic conditions and driving behavior, but also as a planner for charging strategies and optimizations.

关键词： Electric buses Electric vehicles urban mobility simulating traffic congestion Driver Behavior Powertrain Multi-resolution SUB-SYSTEM Air quality city

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Digital auto-tuning for center frequency and Q-factor of Gm-C band-pass filter 5

Digital auto-tuning for center frequency and Q-factor of Gm-...

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5th International Conference on Advanced Micro-Device Engineering, AMDE 2013

作者： Jin, Guanglei Chen, Hao Gao, Chuan Zhang, Yunpeng Kobayashi, Murong Li Haruo Wu, Shu Takai, Nobukazu Niitsu, Kiichi Hadidi, Khayrollah Department of Electronics and Informatics Gunma University Kiryu376-8515 Japan Department of Electric Engineering and Computer Science Nagoya University Nagoya Japan Microelectronics Research Lab. Urmia University Urmia Iran

ISBN: (纸本)9783038354659

This paper describes digital auto-tuning schemes for second-order Gm-C bandpass filters which are suitable for fine CMOS implementation. We propose a switched Gm-C analog filter and two digital tuning schemes: a center frequency tuning scheme using the phase information and a Q factor tuning scheme using the magnitude information. We present circuits, describe their operations, and present SPICE simulation results.. © (2015) Trans Tech Publications, Switzerland.

关键词： Bandpass filters

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Towards an integrated service-oriented reference enterprise architecture

Towards an integrated service-oriented reference enterprise ...

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2013 1st International Workshop on Software Ecosystem Architectures, WEA 2013

作者： Zimmermann, Alfred Sandkuhl, Kurt Pretz, Michael Falkenthal, Michael Jugel, Dierk Wissotzki, Matthias Reutlingen University Faculty of Informatics Architecture Reference Lab. Reutlingen Germany University of Rostock Faculty of Computer Science Business Information Systems Rostock Germany Daimler AG Enterprise Architecture Management SOA Innovation Lab. Stuttgart Germany

ISBN: (纸本)9781450323147

New business information systems are integrating emerging cloud infrastructures with service-oriented platforms and intelligent user-centered mobile systems. Both architecture engineering and management of service-oriented enterprise architectures is complex and has to integrate synergistic disciplines like EAM-Enterprise Architecture and Management for Services & Cloud Computing, Semantic-based Decision Support through Ontologies and Knowledge-based Systems, Big Data Management, as well as Mobility and Collaboration Systems. It is necessary to identify affected decisions by runtime changes of a service-oriented runtime environment and architecture. We have to make transparent the impact of these changes over the integral landscape of affected EAM-capabilities, like directly and transitively impacted business categories, processes, applications, services, platforms and infrastructures. The paper describes a new Metamodel-based integration approach for Service-oriented Reference Enterprise Architectures.

关键词： Knowledge based systems

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Robust multi-modal speech recognition in two languages utilizing video and distance information from the kinect

Robust multi-modal speech recognition in two languages utili...

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15th International Conference on Human-computer Interaction, HCI International 2013

作者： Galatas, Georgios Potamianos, Gerasimos Makedon, Fillia Heracleia Human Centered Computing Lab. Computer Science and Engineering Dept. University of Texas Arlington TX United States Institute of Informatics and Telecommunications NCSR Demokritos Athens Greece Dept. of Computer and Communication Engineering University of Thessaly Volos Greece

ISBN: (纸本)9783642393297

We investigate the performance of our audio-visual speech recognition system in both English and Greek under the influence of audio noise. We present the architecture of our recently built system that utilizes information from three streams including 3-D distance measurements. The feature extraction approach used is based on the discrete cosine transform and linear discriminant analysis. Data fusion is employed using state-synchronous hidden Markov models. Our experiments were conducted on our recently collected database under a multi-speaker configuration and resulted in higher performance and robustness in comparison to an audio-only recognizer. © 2013 Springer-Verlag.

关键词： Discrete cosine transforms

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