[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Data Mining Practical Machine Learning Tools and Techniques

MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

http://ieeexplore.ieee.org/iel2/4524/12820/00592460.pdf

Image Processing

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Biomechanics And Motor Control Of Human Movement

The goal of this Chapter is to review the applications of the Thomson Multitaper analysis (Percival and Walden; 1993b), (Thomson; 1982) for problems encountered in communications (Thomson; 1998; Stoica and Sundin; 1999). In particular we will focus on issues related to channel modelling, estimation and prediction. Sum of Sinusoids (SoS) or Sum of Cisoids (SoC) simulators (Patzold; 2002; SCM Editors; 2006) are popular ways of building channel simulators both in SISO and MIMO case. However, this approach is not a very good option when features of communications systems such as prediction and estimation are to be simulated. Indeed, representation of signals as a sum of coherent components with large prediction horizon (Papoulis; 1991) leads to overly optimistic results. In this Chapter we develop an approach which allows one to avoid this difficulty. The proposed simulator combines a representation of the scattering environment advocated in (SCM Editors; 2006; Almers et al.; 2006; Molisch et al.; 2006; Asplund et al.; 2006; Molish; 2004) and the approach for a single cluster environment used in (Fechtel; 1993; Alcocer et al.; 2005; Kontorovich et al.; 2008) with some important modifications (Yip and Ng; 1997; Xiao et al.; 2005). The problem of estimation and interpolation of a moderately fast fading Rayleigh/Rice channel is important in modern communications. TheWiener filter provides the optimum solution when the channel characteristics are known (van Trees; 2001). However, in real-life applications basis expansions such as Fourier bases and discrete prolate spheroidal sequences (DPSS) have been adopted for such problems (Zemen and Mecklenbrauker; 2005; Alcocer-Ochoa et al.; 2006). If the bases and the channel under investigation occupy the same band, accurate

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Wireless Communications and Multitaper Analysis: Applications to Channel Modelling and Estimation

Falls and falls related injuries are the major causes of non-fatal injuries in older adults. With recent advances in mathematics, science and technology, many scientists and engineers are devoting their efforts to prevent falls or to diminish the negative health outcomes after falls. In this chapter, we briefly review major engineering approaches to recover or augment the human gait function pre- and post-falls. Given the proliferation of wearable sensors and the availability of computational resources in the last decade, we focused on the role of wearable sensors to monitor gait instabilities and potentially prevent falls. We reviewed the general framework for gait monitoring using wearables and its utility in real-life settings such as homes or retirement communities. In the last part of the chapter, we focused on recent contributions that have proposed wearable sensors for gait monitoring and fall inferences.

Engineering Human Gait and the Potential Role of Wearable Sensors to Monitor Falls

We present a non-invasive brain-machine-interface (BMI) prototype system which allows the simple control of a switch. The main goal of the system, based on electroencephalogram (EEG) recordings, is to create mechanical action from brain activity. Experimental work presented in this paper outlines the operation of a system which is a crude imitation of an ultrasound echolocation based vision mechanism, commonly used by bats and dolphins, which is controlled by brain activity. Simple time-frequency-space domain signal analysis methods are employed to generate the electrical control-signal, while the sonar transducer is mounted on a robotic arm capable of scanning the upper hemisphere.

A brain-controlled 3D sonar scanner

Emergency department (ED) nurses need to identify patients with potential acute coronary syndrome (ACS) rapidly because treatment delay could impact patient outcomes. Aims of this secondary analysis were to identify key patient factors that could be available at initial ED nurse triage that predict ACS. Consecutive patients with chest pain who called 9-1-1, received a 12-lead electrocardiogram in the prehospital setting, and were transported via emergency medical service were included in the study. A total of 750 patients were recruited. The sample had an average age of 59 years old, was 57% male, and 40% Black. One hundred and fifteen patients were diagnosed with ACS. Older age, non-Caucasian race, and faster respiratory rate were independent predictors of ACS. There was an interaction between heart rate by Type II diabetes receiving insulin in the context of ACS. Type II diabetics requiring insulin for better glycemic control manifested a faster heart rate. By identifying patient factors at ED nurse triage that could be predictive of ACS, accuracy rates of triage may improve, thus impacting patient outcomes.

Exploring the complex interactions of baseline patient factors to improve nursing triage of acute coronary syndrome.

Objective Adequate upper esophageal sphincter (UES) opening is essential during swallowing to enable clearance of material into the digestive system, and videofluoroscopy(VF) is the most commonly deployed instrumental examination for assessment of UES opening. High-resolution cervical auscultation (HRCA) has been shown to be an effective, portable and cost-efficient screening tool for dysphagia with strong capabilities in non-invasively and accurately approximating manual measurements of VF images. In this study, we aimed to examine whether the HRCA signals are correlated to the manually measured anterior-posterior (AP) distension of maximal UES opening from VF recordings, under the hypothesis that they would be strongly associated. Approach We developed a standardized method to spatially measure the AP distension of maximal UES opening in 203 swallows VF recording from 27 patients referred for VF due to suspected dysphagia. Statistical analysis was conducted to compare the manually measured AP distension of maximal UES opening from lateral plane VF images and features extracted from two sets of HRCA signal segments: whole swallow segments and segments excluding all events other than the duration of UES is opening. Main results HRCA signal features were significantly associated with the normalized AP distension of the maximal UES opening in the longer whole-swallowing segments and the association became much stronger when analysis was performed solely during the duration of UES opening. Significance This preliminary feasibility study demonstrated the potential value of HRCA signals features in approximating the objective measurements of maximal UES AP distension and paves the way of developing HRCA to non-invasively and accurately predict human spatial measurement of VF kinematic events.

https://iopscience.iop.org/article/10.1088/1361-6579/abe7cb/pdf

Ervin Sejdic

Papers

Wireless Communications and Multitaper Analysis: Applications to Channel Modelling and Estimation

Engineering Human Gait and the Potential Role of Wearable Sensors to Monitor Falls

A brain-controlled 3D sonar scanner

Exploring the complex interactions of baseline patient factors to improve nursing triage of acute coronary syndrome.

Anterior–posterior distension of maximal upper esophageal sphincter opening is correlated with high-resolution cervical auscultation signal features