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Erratum to: The real cost of sequencing: scaling computation to keep pace with data generation

Genome biology 2016年第1期17卷 78页

作者： Paul Muir Shantao Li Shaoke Lou Daifeng Wang Daniel J Spakowicz Leonidas Salichos Jing Zhang George M Weinstock Farren Isaacs Joel Rozowsky Mark Gerstein Department of Molecular Cellular and Developmental Biology Yale University New Haven CT 06520 USA. Systems Biology Institute Yale University West Haven CT 06516 USA. Integrated Graduate Program in Physical and Engineering Biology Yale University New Haven CT 06520 USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. Department of Molecular Biophysics and Biochemistry Yale University New Haven CT 06520 USA. The Jackson Laboratory for Genomic Medicine Farmington CT 06032 USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. mark@***. Department of Molecular Biophysics and Biochemistry Yale University New Haven CT 06520 USA. mark@***. Department of Computer Science Yale University New Haven CT 06520 USA. mark@***.

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High-Performance Brain-Machine Interface Enabled by an Adaptive Optimal Feedback-Controlled Point Process Decoder

High-Performance Brain-Machine Interface Enabled by an Adapt...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Maryam M. Shanechi Amy Orsborn Helene Moorman Suraj Gowda Jose M. Carmena Department of Electrical Engineering and Computer Science University of California Berkeley CA USA School of Electrical and Computer Engineering Cornell University Ithaca NY USA UCB-UCSF Graduate Group in Bio-engineering University of California Berkeley CA USA University of California Berkeley Berkeley CA US Suraj Gowda is with the Department of Electrical Engineering and Computer Science University of California Berkeley CA USA

Brain-machine interface (BMI) performance has been improved using Kalman filters (KF) combined with closed-loop decoder adaptation (CLDA). CLDA fits the decoder parameters during closed-loop BMI operation based on the neural activity and inferred user velocity intention. These advances have resulted in the recent ReFIT-KF and SmoothBatch-KF decoders. Here we demonstrate high-performance and robust BMI control using a novel closed-loop BMI architecture termed adaptive optimal feedback-controlled (OFC) point process filter (PPF). Adaptive OFC-PPF allows subjects to issue neural commands and receive feedback with every spike event and hence at a faster rate than the KF. Moreover, it adapts the decoder parameters with every spike event in contrast to current CLDA techniques that do so on the time-scale of minutes. Finally, unlike current methods that rotate the decoded velocity vector, adaptive OFC-PPF constructs an infinite-horizon OFC model of the brain to infer velocity intention during adaptation. Preliminary data collected in a monkey suggests that adaptive OFC-PPF improves BMI control. OFC-PPF outperformed SmoothBatch-KF in a self-paced center-out movement task with 8 targets. This improvement was due to both the PPF's increased rate of control and feedback compared with the KF, and to the OFC model suggesting that the OFC better approximates the user's strategy. Also, the spike-by-spike adaptation resulted in faster performance convergence compared to current techniques. Thus adaptive OFC-PPF enabled proficient BMI control in this monkey.

关键词： Decoding Adaptation models Brain modeling Kinematics Estimation Neurons Convergence

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Adaptive practical output tracking of stack piezo-actuators with coupling hysteresis for dynamic loading applications

Adaptive practical output tracking of stack piezo-actuators ...

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World Congress on Intelligent Control and Automation (WCICA)

作者： Yangyang Dong Hong Hu Wei Lin Department of Mechanical Engineering Shenzhen Graduate School Shenzhen China Department of Electrical Engineering and Computer Science University of Case Western Reserve University Cleveland Ohio USA

The piezoelectric stack actuators (PEAs), being limited to unknown hysteresis, present undesired accuracy. However, experiments show that the effect of dynamic load and the rate of excitation voltage can also cause inclination in hysteresis loop and deteriorate tracking performance. By taking into account the two factors, we propose a coupling hysteresis model based on the modified Prandtl-Ishlinskii operator to estimate the hysteresis nonlinearity in PEAs. When the bounds of system parameters and reference signal are unknown, we develop an adaptive control technique to solve the problem of practical output tracking of PEAs preceded by a non-measureable coupling hysteresis. The method employs the ideas of adding a power integrator technique and universal control, and combines with the proposed coupling hysteresis model without constructing a hysteresis inverse. Simulations demonstrate the efficacy of this adaptive control strategy.

关键词： Couplings Hysteresis Load modeling Magnetic hysteresis Adaptation models Mathematical model Actuators

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Improvement of wireless temperature measurement system for Hyperthermia using Ferromagnetic Implant with Low Curie Temperature

Transactions of Japanese Society for Medical and Biological ...

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Transactions of Japanese Society for Medical and Biological engineering 2014年 52卷 O-92-O-93页

作者： Aki, Fumitaka Miyamoto, Ryuhei Saito, Hajime Suzuki, Masafumi Yoshimura, Noboru Mitobe, Kazutaka Department of Electronic and Computer System Engineering Graduate School of Engineering and Resource Science Akita University Japan Department of Electrical and Electronic Engineering Graduate School of Engineering and Resource Science Akita University Japan The Second Department of Surgery Akita University Japan Akita University Japan

Hyperthermia is a cancer therapy by using thermosensitivity of cancer cells. We previously developed a wireless temperature measurement system for Hyperthermia using Ferromagnetic Implant with Low Curie Temperature (FILCT). However, when initial bias, caused by the position and posture of the detection coil, is large enough, change of feeble voltage in the detection coil cannot detect. In this report, therefore, we suggest a method for reducing the initial bias by analog signal superimposition. A reverse phase voltage of an additional coil is added to the voltage of the original detection coil, as a result the initial bias value is by 0V. Furthermore, as the reverse phase voltage changes concurrently, the influence caused by the fluctuation in applied magnetic field can be also reduced. We verified our analog signal superimposition method and confirmed its validity by physical experiments. © 2014, Japan Soc. of Med. Electronics and Biol. engineering. All rights reserved.

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Zeno and anti-Zeno effects on dephasing

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Physical Review A 2014年第1期90卷 012101-012101页

作者： Adam Zaman Chaudhry Jiangbin Gong Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore 117583 Singapore Department of Physics and Center for Computational Science and Engineering National University of Singapore Singapore 117542 Singapore NUS Graduate School for Integrative Sciences and Engineering Singapore 117597 Singapore

Quantum Zeno and anti-Zeno effects on pure dephasing are studied using exactly solvable microscopic models. The crossover between these two opposite effects is investigated. The case of a single two-level system undergoing dephasing is already different from the previously studied population-decay problem, even without taking into account any back action from the environment. For many two-level systems interacting with a common environment, multiple transitions between Zeno and anti-Zeno regimes are predicted. Finally, if the system-environment coupling strength is not weak, we show that the nontrivial evolution of the environment between measurements can considerably alter the quantum Zeno and anti-Zeno effects. This is qualitatively different from population-decay models where the environment state is reset to equilibrium after each measurement.

关键词： QUANTUM Zeno dynamics QUANTUM theory HILBERT space DECAY-associated spectra MICROSCOPY

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Automatic stress-relieving music recommendation system based on photoplethysmography-derived heart rate variability analysis

Automatic stress-relieving music recommendation system based...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Il-hyung Shin Jaepyeong Cha Gyeong Woo Cheon Choonghee Lee Seung Yup Lee Hyung-Jin Yoon Hee Chan Kim Interdisciplinary Program Biomedical Engineering Major Graduate School Seoul National University Department of Electrical and Computer Engineering Johns Hopkins University Interdisciplinary Program Bioengineering Major Graduate School Seoul National University Department of Biomedical Engineering University of Michigan Department of Biomedical Engineering College of Medicine Seoul National University

ISBN: (纸本)9781424479276

This paper presents an automatic stress-relieving music recommendation system (ASMRS) for individual music listeners. The ASMRS uses a portable, wireless photoplethysmography module with a finger-type sensor, and a program that translates heartbeat signals from the sensor to the stress index. The sympathovagal balance index (SVI) was calculated from heart rate variability to assess the user's stress levels while listening to music. Twenty-two healthy volunteers participated in the experiment. The results have shown that the participants' SVI values are highly correlated with their prespecified music preferences. The sensitivity and specificity of the favorable music classification also improved as the number of music repetitions increased to 20 times. Based on the SVI values, the system automatically recommends favorable music lists to relieve stress for individuals.

关键词： Heart rate variability Stress Recommender systems Indexes Multiple signal classification Educational institutions Music

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A web-based, hospital-wide health care-associated bloodstream infection surveillance and classification system: Development and evaluation

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JMIR Medical Informatics 2015年第3期3卷 e31页

作者： Tseng, Yi-Ju Wu, Jung-Hsuan Lin, Hui-Chi Chen, Ming-Yuan Ping, Xiao-Ou Sun, Chun-Chuan Shang, Rung-Ji Sheng, Wang-Huei Chen, Yee-Chun Lai, Feipei Chang, Shan-Chwen Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Computational Health Informatics Program Boston Children's Hospital Boston MA United States Department of Electrical Engineering National Taiwan University Taipei Taiwan Center for Infection Control National Taiwan University Hospital Taipei Taiwan National Taiwan University Hospital Information Systems Office Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Department of Internal Medicine National Taiwan University Hospital and College of Medicine Taipei Taiwan National Health Research Institutes National Institute of Infectious Diseases and Vaccinology Miaoli Taiwan

Background: Surveillance of health care-associated infections is an essential component of infection prevention programs, but conventional systems are labor intensive and performance dependent. Objective: To develop an automatic surveillance and classification system for health care-associated bloodstream infection (HABSI), and to evaluate its performance by comparing it with a conventional infection control personnel (ICP)-based surveillance system. Methods: We developed a Web-based system that was integrated into the medical information system of a 2200-bed teaching hospital in Taiwan. The system automatically detects and classifies HABSIs. Results: In this study, the number of computer-detected HABSIs correlated closely with the number of HABSIs detected by ICP by department (n=20;r=.999 P<.001) and by time (n=14;r=.941;P<.001). Compared with reference standards, this system performed excellently with regard to sensitivity (98.16%), specificity (99.96%), positive predictive value (95.81%), and negative predictive value (99.98%). The system enabled decreasing the delay in confirmation of HABSI cases, on average, by 29 days. Conclusions: This system provides reliable and objective HABSI data for quality indicators, improving the delay caused by a conventional surveillance system. © 2020 JMIR Publications Inc. All rights reserved.

关键词： Health care-associated infection Infection control Information systems Surveillance Web-based services

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Learning sparse representation for leaf image recognition

Learning sparse representation for leaf image recognition

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Jou-Ken Hsiao Li-Wei Kang Ching-Long Chang Chao-Yung Hsu Chia-Yen Chen Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan Graduate School of Engineering Science and Technology-Doctoral Program National Yunlin University of Science and Technology Yunlin Taiwan Institute of Information Science Taipei Taiwan Department of Computer Science and Information Engineering National University of Kaohsiung Taiwan

Automatic plant identification via computer vision techniques has been greatly important for a number of professionals, such as environmental protectors, land managers, and foresters. In this paper, a novel leaf image recognition technique via sparse representation is proposed for automatic plant identification. In order to model leaf images, we learn an overcomplete dictionary for sparsely representing the training images of each leaf species. Each dictionary is learned using a set of descriptors extracted from the training images in such a way that each descriptor is represented by linear combination of a small number of dictionary atoms. For each test leaf image, we calculate the correlation between the image and each learned dictionary of leaf species to achieve the identification of the leaf image. As a result, efficient leaf recognition can be achieved on public leaf dataset based on the proposed framework leading to a more compact and richer representation of leaf images compared to traditional clustering approaches. Moreover, our method is also adapted to newly added leaf species without retraining classifiers and suitable to be highly parallelized as well as integrated with any leaf image descriptors/features.

关键词： Image recognition Dictionaries Training Feature extraction Shape Educational institutions computer vision

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Multiple Time Series Data Processing for Classification with Period Merging Algorithm

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Procedia computer science 2014年 37卷 301-308页

作者： Wei-Ti Su Xiao-Ou Ping Yi-Ju Tseng Feipei Lai Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University TaipeiTaiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan

Cancer has been ranked first in the causes of death for 31 consecutive years in Taiwan. Radiofrequency ablation (RFA) is a treatment for hepatocellular carcinoma (HCC) and it becomes one of the important therapies for HCC these years. For those who had HCC and were treated by RFA, their clinical data are collected to build predictive models which can be used in predicting the recurrence or not of liver cancer after RAF treatment. Clinical data with multiple measurements are merged based on different time periods and these data are further transformed based on temporal abstraction (TA). Data processed by TA reveal variations of clinical data with different time points. The goal of this study is to evaluate whether clinical data handled by TA could facilitate performance of predictive models. Different data sets are used in developing predictive models, including clinical data which are not processed by TA called the original data set, clinical data which are processed by TA called the TA data set, and combination of the original data set and the TA data set called the TA+original data set. Support vector machine (SVM) was selected as a classifier to develop predictive models. The results demonstrate data sets processed by TA provide benefit for predictive models.

关键词： Temporal abstraction TA Time Series RFA Liver cancer

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Auditory space perception during linearly self-motion 7

Auditory space perception during linearly self-motion

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7th Forum Acusticum, FA 2014

作者： Sakamoto, Shuichi Cui, Zhenglie Suzuki, Yôiti Teramoto, Wataru Gyoba, Jiro Research Institute of Electrical Communication Tohoku University 2-1-1 Katahira Aoba-ku Sendai980-8577 Japan Department of Computer Science and Systems Engineering Muroran Institute of Technology Muroran050-8585 Japan Graduate School of Arts and Letters Tohoku University Sendai980-8576 Japan

ISBN: (纸本)9788361402282

Spatial inputs from the auditory periphery can be changed with listener's various movements relative to the sound source. Nevertheless, humans can perceive a stable auditory environment and appropriately react to a sound source. This suggests that the inputs are reinterpreted in the brain, while being integrated with information on the movements. Little is known, however, about how these movements modulate auditory perceptual processing, especially under linearly moving environment. We investigate the effect of linearly self-motion on auditory space representation. Results of our experiments showed that the sound position judged as being located at the subjective coronal plane was displaced compared with the the listener's physical coronal plane. This distortion was observed irrespective of the style of the self-motion (active or passive). Moreover, the distortion was observed both with and without vestibular stimulation. These results suggest that self-motion information, irrespective of its origin (vestibule or any other sources), is crucial to evoke this distortion of auditory space perception.

关键词： Acoustic generators

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