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Understanding behavioral differences between short and long-term drinking abstainers from social media 1

12th International Conference on Advanced data Mining and Applications, ADMA 2016

作者： Harikumar, Haripriya Nguyen, Thin Gupta, Sunil Rana, Santu Kaimal, Ramachandra Venkatesh, Svetha Centre for Pattern Recognition and Data Analytics Deakin University Geelong Australia Computer Science and Engineering Department Amrita University Kollam India

ISBN: (数字)9783319495866

ISBN: (纸本)9783319495859

Drinking alcohol has high cost on society. The journey from being a regular drinker to a successful quitter may be a long and hard journey, fraught with the risk to relapse. Research has shown that certain behavioral changes can be effective towards staying abstained. Traditional way to conduct research on drinking abstainers uses questionnaire based approach to collect data from a curated group of people. However, it is an expensive approach in both cost and time and often results in small data with less diversity. Recently, social media has emerged as a rich data source. Reddit is one such social media platform that has a community (‘subreddit’) with an interest to quit drinking. The discussions among the group dates back to year 2011 and contain more than 40,000 posts. This large scale data is generated by users themselves and without being limited by any survey questionnaires. The most predictive factors from the features (unigrams, topics and LIWC) associated with short-term and long-term abstinence are identified using Lasso. It is seen that many common patterns manifest in unigrams, topics and LIWC. Whilst topics provided much richer associations between a group of words and the outcome, unigrams and LIWC are found to be good at finding highly predictive solo and psycho linguistically important words. Combining them we have found that many interesting patterns that are associated with the successful attempt made by the long-term abstainer, at the same time finding many of the common issues faced during the initial period of abstinence. © Springer International Publishing AG 2016.

关键词： Surveys

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Highly accurate model for prediction of lung nodule malignancy with ct scans

arXiv

引用

arXiv 2018年

作者： Causey, Jason Zhang, Junyu Ma, Shiqian Jiang, Bo Qualls, Jake Politte, David G. Prior, Fred Zhang, Shuzhong Huang, Xiuzhen Department of Computer Science Arkansas State University JonesboroAR72467 United States Department of Industrial and Systems Engineering University of Minnesota MinneapolisMN55455 United States Department of Systems Engineering and Engineering Management Chinese University of Hong Kong Shatin N.T. Hong Kong Research Center for Management Science and Data Analytics School of Information Management and Engineering Shanghai University of Finance and Economics Shanghai200433 China Mallinckrodt Institute of Radiology Washington University St. LouisMO63110 United States Department of Biomedical Informatics University of Arkansas for Medical Sciences Little RockAR72205 United States UALR/UAMS Joint Graduate Program in Bioinformatics Little RockAR72204 United States

Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve performance comparable to experienced radiologists. Here we present NoduleX, a systematic approach to predict lung nodule malignancy from CT data, based on deep learning convolutional neural networks (CNN). For training and validation, we analyze >1000 lung nodules in images from the LIDC/IDRI cohort. All nodules were identified and classified by four experienced thoracic radiologists who participated in the LIDC project. NoduleX achieves high accuracy for nodule malignancy classification, with an AUC of ~0.99. This is commensurate with the analysis of the dataset by experienced radiologists. Our approach, NoduleX, provides an effective framework for highly accurate nodule malignancy prediction with the model trained on a large patient population. Our results are replicable with software available at http://***/NoduleX. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

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data-driven modeling techniques for indoor CO2 estimation

Data-driven modeling techniques for indoor CO2 estimation

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IEEE Sensors

作者： Bob Vergauwen Oscar Mauricio Agudelo Raj Thilak Rajan Frank Pasveer Bart De Moor KU Leuven Department of Electrical Engineering (ESAT) Stadius Center for Dynamical Systems Signal Processing and Data Analytics Leuven Belgium imec/Holst Centre High Tech Campus 31 5656 AE Eindhoven The Netherlands

ISBN: (纸本)9781509010134

This paper presents the results of using the Least-Squares Support Vector Machines (LS-SVMs) framework for estimating CO_2 levels at the Holst Center building in the Netherlands. Within the IoT framework, a Wireless Sensor Network (WSN) consisting of seven sensors is currently deployed at the third floor of the building. Each sensor node provides measures of temperature, relative humidity and CO_2 levels, and transmits the readings to a consumer accessible cloud. Given that CO_2 has a big impact on people comfort and productivity, its monitoring and control has become a common practice in recent years. In this work we provide a way to estimate the CO_2 concentration when a CO_2 sensor is not trustworthy (e.g., due to maintenance or a malfunction), by using nonlinear models built from historical sensor data. Results showed that the model structures proposed in this work provided better CO_2 estimates than those given by conventional linear autoregressive (AR) and autoregressive exogenous (ARX) models.

关键词： LS-SVM non-linear modeling air quality CO2-estimation WSN

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A low-complexity algorithm for utility based spectrum coordination in DSL systems

A low-complexity algorithm for utility based spectrum coordi...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Jeroen Verdyck Chris Blondia Marc Moonen KU Leuven Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics Belgium University of Antwerp Department of Mathematics-Computer Sciences MOSAIC Modeling of Systems And Internet Communication Belgium

ISBN: (纸本)9781509041183

The static resource allocation which is usually assumed for the DSL physical layer leaves unused a significant portion of the achievable rate region. An alternative approach is to divide time into slots of short duration, and to change the resource allocation from each time slot to the next. A crosslayer scheduler then chooses a different resource allocation setting for each time slot by defining a utility function for each user n, and solving the corresponding network utility maximization (NUM) problem. For spectrum coordination, this NUM problem is non-convex and solving it is NP-Hard. This paper therefore introduces a fast algorithm, referred to as NUM-DSB, which converges to a local solution of the NUM problem. NUM-DSB can be applied to any NUM problem, regardless of the considered utility functions's characteristics. Simulation results show that NUM-DSB can compete with the state of the art algorithm for smooth non-convex network utility maximization.

关键词： DSL Spectrum Coordination Cross-Layer Scheduling Network Utility Maximization digital subscriber lines Resource utilization state of the art Non-Convex management of resources

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Reconstruction of digital holograms by iterative phase retrieval algorithm: Improvements and analysis

Reconstruction of digital holograms by iterative phase retri...

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Digital Holography and Three-Dimensional Imaging, DH 2017

作者： Zhao, Liang Healy, John Wu, Yang Muniraj, Inbarasan Malallah, Ra'ed Kelly, Damien P. Sheridan, John T. Insight Centre for Data Analytics University College Dublin Belfield Dublin 4 Ireland School of Electrical Electronic and Communications Engineering IoE2 Lab SFI-Strategic Research Cluster in Solar Energy Conversion College of Engineering and Architecture University College Dublin Belfield Dublin 4 Ireland Coherent LaserSystems GmbH and Co. KG Hans-Böckler-Straße 12 Göttingen37079 Germany Oryx Optics Ltd 19 The Elms Athlone Iran

ISBN: (纸本)9781943580286

Iterative phase retrieval usually requires a good initial guess for the phase. In this paper, we consider two improvements to a recently proposed scheme (Opt. Eng. 55 (3), 033106 (2016)) to acquire the initial guess from a digital holographic system. This set-up is simpler than phase-shifting interferometry, and suppresses the twin image and dc terms without the resolution trade-off involved in off-axis holography. In this paper, we show the benefits of ensuring the propagation algorithm is unitary. We also use a recently proposed iterative phase retrieval algorithm which uses a combination of the Gerschberg-Saxton and hybrid input-output algorithms, and demonstrate the benefit of this algorithm for avoiding stagnation of the algorithm. © OSA 2017.

关键词： Iterative methods

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The influence of pharmacological autonomic blockades on multi-scale measures of heart rate variability

The influence of pharmacological autonomic blockades on mult...

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Joint Conference of the European Medical and Biological engineering Conference, EMBEC 2017 and Nordic-Baltic Conference on Biomedical engineering and Medical Physics, NBC 2107

作者： Marzbanrad, Faezeh Karmakar, C.K. Khandoker, A.H. Palaniswami, M. Moritani, T. Jelinek, H.F. Department of Electrical and Computer Systems Engineering Monash University ClaytonVIC3168 Australia Centre for Research in Complex Systems and School of Community Health Charles Sturt University Albury Australia Centre of Pattern Recognition and Data Analytics Deakin University GeelongVIC Australia Khalifa University of Science Technology and Research Abu Dhabi United Arab Emirates The University of Melbourne ParkvilleVIC3010 Australia Kyoto University Kyoto Japan

ISBN: (纸本)9789811051210

Multi-scale measures have been used extensively to characterize non-linear dynamics of heart beats. However a physiological interpretation of the exponents associated with various scales of these measures and the role of the sympathetic and parasympathetic activities have not been attempted. In this study three multi-scale measures were compared at different scales in a pharmacological autonomic blockade experiment, starting with a control phase. It was then followed by injection of propranolol causing sympathetic blockade and injection of atropine resulting in the blockade of both sympathetic and parasympathetic pathways. Multiscale Entropy (MSE), Multi Fractal Detrended Fluctuation Analysis (MFDFA) and Renyi Entropy (RE) were compared using a paired test statistics. The measures performed differently depending on the scale factors and RE showed the best results indicating a good discrimination particularly at higher scale exponents. This study provides a basis for understanding the effect of autonomic activity on multi-scale measures with respect to changes in parasympathetic and sympathetic activity. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Entropy

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Cascade Bayesian optimization 29th

引用

29th Australasian Joint Conference on Artificial Intelligence, AI 2016

作者： Nguyen, Thanh Dai Gupta, Sunil Rana, Santu Nguyen, Vu Venkatesh, Svetha Deane, Kyle J. Sanders, Paul G. Center for Pattern Recognition and Data Analytics Deakin University Geelong3216 Australia Materials Science and Engineering Michigan Technological University Houghton United States

ISBN: (纸本)9783319501260

Multi-stage cascade processes are fairly common, especially in manufacturing industry. Precursors or raw materials are transformed at each stage before being used as the input to the next stage. Setting the right control parameters at each stage is important to achieve high quality products at low cost. Finding the right parameters via trial and error approach can be time consuming. Bayesian optimization is an efficient way to optimize costly black-box function. We extend the standard Bayesian optimization approach to the cascade process through formulating a series of optimization problems that are solved sequentially from the final stage to the first stage. Epistemic uncertainties are effectively utilized in the formulation. Further, cost of the parameters are also included to find cost-efficient solutions. Experiments performed on a simulated testbed of Al-Sc heat treatment through a three-stage process showed considerable efficiency gain over a naïve optimization approach. © Springer International Publishing AG 2016.

关键词： Uncertainty analysis

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Educational video classification by using a transcript to image transform and supervised learning

Educational video classification by using a transcript to im...

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Workshops on Image Processing Theory, Tools and Applications, IPTA

作者： Houssem Chatbri Marlon Oliveira Kevin McGuinness Suzanne Little Keisuke Kameyama Paul Kwan Alistair Sutherland Noel E. O’Connor Insight Centre for Data Analytics Dublin City University Ireland School of Computing Dublin City University Ireland Faculty of Engineering Information and Systems University of Tsukuba Japan School of Science & Technology University of New England NSW Australia

In this work, we present a method for automatic topic classification of educational videos using a speech transcript transform. Our method works as follows: First, speech recognition is used to generate video transcripts. Then, the transcripts are converted into images using a statistical cooccurrence transformation that we designed. Finally, a classifier is used to produce video category labels for a transcript image input. For our classifiers, we report results using a convolutional neural network (CNN) and a principal component analysis (PCA) model. In order to evaluate our method, we used the Khan Academy on a Stick dataset that contains 2,545 videos, where each video is labeled with one or two of 13 categories. Experiments show that our method is effective and strongly competitive against other supervised learning-based methods.

关键词： Principal component analysis Transforms Visualization Feature extraction Training Convolutional neural networks Histograms

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Upper limb activity in chronic post-stroke survivors: A comparison of accelerometry data with the Action Research Arm Test (ARAT)

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Annals of Physical and Rehabilitation Medicine 2018年 61卷 e187-e187页

作者： Parker, J. Powell, L. Heller, B. Schweiss, E. Mawson, S. University of Sheffield School of Health and Related Research Sheffield United Kingdom Sheffield Hallam University The Centre for Sports Engineering Research Sheffield United Kingdom RunScribe Research & Data Analytics Greater St. Louis USA

Introduction/Background Only 5–20% of stroke survivors will regain full function of the upper limb (UL) with up to 60% still being impaired in the chronic phase. A plethora of outcome measures are used to assess UL function. However, they are often only a snap shot in time of the stroke survivor's capability and do not always reflect the stroke survivor's UL use in everyday real-world settings and contexts. The use of technologies has become a viable option for quantifying movements and activities during post-stroke rehabilitation in real-world contexts. This research compares the use of accelerometry with the ARAT over 96 hours with chronic stroke survivors and age-matched controls. Material and method Thirty chronic stroke survivors and 30 age-matched controls wore an accelerometer on each wrist for 96 hours. Stroke survivors were also assessed using the ARAT and reported their functional ability. data were analysed to compare affected UL v non-affected UL, stroke survivor movement v control, and hand dominance v non-dominance. Accelerometry data were compared with the stroke survivors’ functional capability. Results Findings suggest there is an association between the ARAT and accelerometry; the greater the capability score the higher the usage of the affected UL. Controls carryout more bi-lateral activities compared to the stroke survivors who tend to use each arm independently. However, despite full functional capability scores, stroke survivors still do not use their impaired UL compared to their non-affected UL. This is due to sensory loss or mistrust of their affected UL. Conclusion Compared to controls, chronic stroke survivors do not use their affected UL, nor do they carry out as much bi-lateral activity despite full capability. Accelerometry has the potential to measure UL movement and movement characteristics over long periods, which can provide essential feedback for both clinicians and stroke survivors.

关键词： Stroke Technology Upper limb

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A unified scheme to accelerate adaptive cubic regularization and gradient methods for convex optimization

arXiv

引用

arXiv 2017年

作者： Jiang, Bo Lin, Tianyi Zhang, Shuzhong Research Center for Management Science and Data Analytics School of Information Management and Engineering Shanghai University of Finance and Economics Shanghai200433 China Department of Industrial Engineering and Operations Research UC Berkeley BerkeleyCA94720 United States Department of Industrial and Systems Engineering University of Minnesota MinneapolisMN55455 United States

In this paper we propose a unified two-phase scheme for convex optimization to accelerate: (1) the adaptive cubic regularization methods with exact/inexact Hessian matrices, and (2) the adaptive gradient method, without any knowledge of the Lipschitz constants for the gradient or the Hessian. This is achieved by tuning the parameters used in the algorithm adaptively in its process of progression, which can be viewed as a relaxation over the existing algorithms in the literature. Under the assumption that the sub-problems can be solved approximately, we establish overall iteration complexity bounds for three newly proposed algorithms to obtain an ϵ-optimal solution. Specifically, we show that the adaptive cubic regularization methods with the exact/inexact Hessian matrix both achieve an iteration complexity in the order of O(1/ϵ 1/3), which matches that of the original accel-erated cubic regularization method presented in [24] assuming the availability of the exact Hessian information and the Lipschitz constants, and the global solution of the sub-problems. Under the same two-phase adaptive acceleration framework, the gradient method achieves an iteration complexity in the order of O(1/ϵ 1/2), which is known to be best possible (cf. [26]). Our numerical experiment results show a clear effect of acceleration displayed in the adaptive Newton's method with cubic regularization on a set of regularized logistic regression instances. Copyright © 2017, The Authors. All rights reserved.

关键词： Convex optimization

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