87,591 results match your criteria IEEE transactions on ultrasonics ferroelectrics and frequency control[Journal]


Collision-Free Advertisement Scheduling for IEEE 802.15.4-TSCH Networks.

Sensors (Basel) 2019 Apr 14;19(8). Epub 2019 Apr 14.

Department of Informatics, University of Piraeus, 18534 Piraeus, Greece.

IEEE802.15.4-time slotted channel hopping (TSCH) is a medium access control (MAC) protocol designed to support wireless device networking, offering high reliability and low power consumption, two features that are desirable in the industrial internet of things (IIoT). Read More

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http://dx.doi.org/10.3390/s19081789DOI Listing

Distributed Finite Time Consensus of Secondorder Multi-agent Systems via Pinning Control (August 2018).

IEEE Access 2018 14;6:45617-45624. Epub 2018 Aug 14.

National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), National Institutes of Health (NIH), 8600 Rockville Pike, Bethesda, MD 20894, USA.

The robust distributed finite time consensus of second-order multi-agent systems via pinning control has been investigated in this paper. A new nonsingular finite time TSM control method is proposed for second-order single system with disturbances. Based on the pinning error function vector, robust distributed finite time consensus of second-order multi-agent systems via pinning control method is given. Read More

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http://dx.doi.org/10.1109/ACCESS.2018.2865479DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6474383PMC

Altered large-scale functional brain networks in neurological Wilson's disease.

Brain Imaging Behav 2019 Apr 22. Epub 2019 Apr 22.

Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.

Wilson's disease patients with neurological symptoms have motor symptoms and cognitive deficits, including frontal executive, visuospatial processing, and memory impairments. Although the brain structural abnormalities associated with Wilson's disease have been documented, it remains largely unknown how Wilson's disease affects large-scale functional brain networks. In this study, we investigated functional brain networks in Wilson's disease. Read More

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http://dx.doi.org/10.1007/s11682-019-00066-yDOI Listing
April 2019
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Simulations of a Multi-Pinhole SPECT Collimator for Clinical Dopamine Transporter (DAT) Imaging.

IEEE Trans Radiat Plasma Med Sci 2018 Sep 30;2(5):444-451. Epub 2018 Apr 30.

Department of Radiology, UMass Medical School, Worcester, MA, USA.

SPECT imaging of the dopamine transporter (DAT) is used for diagnosis and monitoring progression of Parkinson's Disease (PD), and differentiation of PD from other neurological disorders. The diagnosis is based on the DAT binding in the caudate and putamen structures in the striatum. We previously proposed a relatively inexpensive method to improve the detection and quantification of these structures for dual-head SPECT by replacing one of the fan-beam collimators with a specially designed multi-pinhole (MPH) collimator. Read More

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http://dx.doi.org/10.1109/TRPMS.2018.2831208DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6474676PMC
September 2018

High Performance SDN WLAN Architecture.

Sensors (Basel) 2019 Apr 19;19(8). Epub 2019 Apr 19.

Faculty of Informatics and Information Technologies, Slovak University of Technology in Bratislava, 842 16 Bratislava, Slovakia.

Wireless Local Area Network (WLAN) infrastructure is a dominant technology for direct access to the Internet and for cellular mobile data traffic offloading to WLANs. Additionally, the enterprise infrastructure can be used to provide functionality for the Internet of Things and Machine to Machine scenarios. This work is focused on improvements of radio resources control scalability similar to mobile networks via handover between cells. Read More

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http://dx.doi.org/10.3390/s19081880DOI Listing

An Exploration Into Improving DNA Motif Inference by Looking for Highly Conserved Core Regions.

IEEE Symp Comput Intell Bioinforma Comput Biol Proc 2013 Apr 12;2013:60-67. Epub 2013 Sep 12.

Department of Computer Science, University of Southern Maine, Portland, Maine 04104.

Although most verified functional elements in noncoding DNA contain a highly conserved core region, this concept is not generally incorporated into motif inference systems. In this work, we explore the utility of adding the notion of conserved core regions into a comparative genomics approach for the search for putative functional elements in noncoding DNA. By modifying the scoring function for GAMI, Genetic Algorithms for Motif Inference, we investigate tradeoffs between the strength of conservation of the full motif vs. Read More

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http://dx.doi.org/10.1109/CIBCB.2013.6595389DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6474685PMC

A dataset of attributes from papers of a machine learning conference.

Data Brief 2019 Jun 26;24:103836. Epub 2019 Mar 26.

Universitat Politècnica de València, DSIC, València, Spain.

In this work, we present a dataset which provides information on the scientific program of a set conferences of Machine Learning. Data were extracted from the IEEE Xplore Digital Library and the official web site of the International Conference on Machine Learning Applications (ICMLA). We include data of four different editions (from 2014 to 2017). Read More

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http://dx.doi.org/10.1016/j.dib.2019.103836DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6458448PMC

MLS: Joint Manifold-Learning and Sparsity-Aware Framework for Highly Accelerated Dynamic Magnetic Resonance Imaging.

Proc IEEE Int Symp Biomed Imaging 2018 Apr 24;2018:1213-1216. Epub 2018 May 24.

Department of Electrical Engineering, University at Buffalo, The State University of New York.

Manifold-based models have been recently exploited for accelerating dynamic magnetic resonance imaging (dMRI). While manifold-based models have shown to be more efficient than conventional low-rank approaches, joint low-rank and sparsity-aware modeling still appears to be very efficient due to the inherent sparsity within dMR images. In this paper, we propose a joint manifold-learning and sparsity-aware framework for dMRI. Read More

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http://dx.doi.org/10.1109/ISBI.2018.8363789DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469692PMC

THE FOURIER RADIAL ERROR SPECTRUM PLOT: A MORE NUANCED QUANTITATIVE EVALUATION OF IMAGE RECONSTRUCTION QUALITY.

Proc IEEE Int Symp Biomed Imaging 2018 Apr 24;2018:61-64. Epub 2018 May 24.

Signal and Image Processing Institute, University of Southern California, Los Angeles, CA 90089.

In the modern biomedical image reconstruction literature, the quality of a reconstructed image is often numerically quantified using scalar error measures such as mean-squared error or the structural similarity index. While such measures provide a rough summary of image quality, they also suffer from well-known limitations. For example, a substantial amount of information is necessarily lost whenever the characteristics of a high-dimensional image are summarized by a single number. Read More

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http://dx.doi.org/10.1109/ISBI.2018.8363523DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6472927PMC

Scanning Microwave Microscopy of Vital Mitochondria in Respiration Buffer.

IEEE MTTS Int Microw Symp 2018 Jun 20;2018:115-118. Epub 2018 Aug 20.

Integrated Nanosystems Research Facility, University of California, Irvine, Irvine, CA 92697, USA.

We demonstrate imaging using scanning microwave microscopy (SMM) of vital mitochondria in respiration buffer. The mitochondria are isolated from cultured HeLa cells and tethered to a solid graphene support. The mitochondria are kept vital (alive) using a respiration buffer, which provides nutrients to sustain the Krebs cycle. Read More

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http://dx.doi.org/10.1109/MWSYM.2018.8439645DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469850PMC

Rapid automatic identification of parameters of the Bergman Minimal Model in Sprague-Dawley rats with experimental diabetes for adaptive insulin delivery.

Comput Biol Med 2019 Apr 8;108:242-248. Epub 2019 Apr 8.

IEEE Engineering in Medicine and Biology, Mexico City, Mexico. Electronic address:

Glucose-Insulin regulation models can be used to individualize insulin therapy. However, the experimental techniques currently used to identify the appropriate parameter sets of an individual are expensive, time consuming, and very unpleasant for the patient. Since there is a wide range of intrapersonal parameter variability, the identified parameters in a laboratory setting (at rest) are not optimal for dynamic conditions of daily activities. Read More

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http://dx.doi.org/10.1016/j.compbiomed.2019.03.028DOI Listing

The present and future of deep learning in radiology.

Eur J Radiol 2019 May 2;114:14-24. Epub 2019 Mar 2.

Stroke Monitoring and Diagnostic Division, AtheroPoint™, Roseville, CA, USA. Electronic address:

The advent of Deep Learning (DL) is poised to dramatically change the delivery of healthcare in the near future. Not only has DL profoundly affected the healthcare industry it has also influenced global businesses. Within a span of very few years, advances such as self-driving cars, robots performing jobs that are hazardous to human, and chat bots talking with human operators have proved that DL has already made large impact on our lives. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S0720048X193009
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http://dx.doi.org/10.1016/j.ejrad.2019.02.038DOI Listing
May 2019
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Modeling of spike trains in auditory nerves with self-exciting point processes of the von Mises type.

Authors:
Hiroyuki Mino

Biol Cybern 2019 Apr 19. Epub 2019 Apr 19.

Department of Electrical Engineering, Kanto Gakuin University, 1-50-1 Mutsuura E., Kanazawa-ku, Yokohama, 236-8501, Japan.

This article presents the modeling of spike trains in auditory nerve fiber (ANF) models with a one-memory self-exciting point process (SEPP) of the von Mises type. The ANF models were acoustically stimulated by a synaptic current of inner hair cells, or electrically stimulated by sinusoidally amplitude-modulated pulsatile waveforms. It has been shown that the parameters of one-memory SEPP of the von Mises type could be estimated by numerically maximizing the likelihood function from sample realizations of the spike trains in response to acoustic or electric stimulus. Read More

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http://dx.doi.org/10.1007/s00422-019-00799-5DOI Listing

Online Siamese Network for Visual Object Tracking.

Sensors (Basel) 2019 Apr 18;19(8). Epub 2019 Apr 18.

School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.

Offline-trained Siamese networks are not robust to the environmental complication in visual object tracking. Without online learning, the Siamese network cannot learn from instance domain knowledge and adapt to appearance changes of targets. In this paper, a new lightweight Siamese network is proposed for feature extraction. Read More

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http://dx.doi.org/10.3390/s19081858DOI Listing

Fracture Healing Monitoring by Impact Tests: Single Case Study of a Fractured Tibia With External Fixator.

IEEE J Transl Eng Health Med 2019 15;7:2100206. Epub 2019 Mar 15.

Dipartimento di Ricerca Traslazionale e delle Nuove Tecnologie in Medicina e ChirurgiaUniversità di Pisa56122PisaItaly.

The correct evaluation of the healing process is important to define proper times of fixator dynamization and removal, avoiding refractures. Unfortunately, a quantitative healing assessment is not yet available in clinical practice. The aim of the paper is to prove the feasibility of the mechanical vibration method to assess bone healing in fractures treated with external fixation, in conditions. Read More

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https://ieeexplore.ieee.org/document/8667865/
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http://dx.doi.org/10.1109/JTEHM.2019.2901455DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6467180PMC
March 2019
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Rényi entropy yields artificial biases not in the data and incorrect updating due to the finite-size data.

Phys Rev E 2019 Mar;99(3-1):032134

Department of Physics, Mersin University, 33110 Mersin, Turkey.

We show that the Rényi entropy implies artificial biases not warranted by the data and incorrect updating information due to the finite size of the data despite being additive. It is demonstrated that this is so because it does not conform to the system and subset independence axioms of Shore and Johnson [J. IEEE Trans. Read More

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http://dx.doi.org/10.1103/PhysRevE.99.032134DOI Listing

Hidden Markov Model-Based Nonfragile State Estimation of Switched Neural Network With Probabilistic Quantized Outputs.

IEEE Trans Cybern 2019 Apr 17. Epub 2019 Apr 17.

This paper focuses on the state estimator design problem for a switched neural network (SNN) with probabilistic quantized outputs, where the switching process is governed by a sojourn probability. It is assumed that both packet dropouts and signal quantization exist in communication channels. Asynchronous estimator and quantification function are described by two different hidden Markov model between the SNNs and its estimator. Read More

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https://ieeexplore.ieee.org/document/8693640/
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http://dx.doi.org/10.1109/TCYB.2019.2909748DOI Listing
April 2019
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Event-Triggered Active MPC for Nonlinear Multiagent Systems With Packet Losses.

IEEE Trans Cybern 2019 Apr 17. Epub 2019 Apr 17.

In this paper, event-triggered active model predictive control is investigated for a nonlinear multiagent system (MAS) with packet losses. By designing event-triggered mechanisms which reduce sensing cost, event-triggered conditions are detected at certain sampling instants. The prediction horizons of all agents are selected actively through the event-triggered mechanisms. Read More

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http://dx.doi.org/10.1109/TCYB.2019.2908389DOI Listing

Active Event-Triggered Control for Nonlinear Networked Control Systems With Communication Constraints.

IEEE Trans Cybern 2019 Apr 16. Epub 2019 Apr 16.

In this paper, a novel reference input and hysteresis quantizer-based active event-triggered control (RIHQAETC) scheme is proposed for nonlinear networked control systems with quantizer, networked induced delay, and packet dropout. Different from the traditional methods, such a design method is constructed involving the structure of the hysteresis quantizer. In view of the network induced delay and the potential packet dropout, our RIHQAETC method is designed to actively compensate the negative effects caused by these two issues. Read More

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https://ieeexplore.ieee.org/document/8692715/
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http://dx.doi.org/10.1109/TCYB.2019.2907619DOI Listing
April 2019
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Fuzzy Clustering to Identify Clusters at Different Levels of Fuzziness: An Evolutionary Multiobjective Optimization Approach.

IEEE Trans Cybern 2019 Apr 16. Epub 2019 Apr 16.

Fuzzy clustering methods identify naturally occurring clusters in a dataset, where the extent to which different clusters are overlapped can differ. Most methods have a parameter to fix the level of fuzziness. However, the appropriate level of fuzziness depends on the application at hand. Read More

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http://dx.doi.org/10.1109/TCYB.2019.2907002DOI Listing

Maneuvering Target Tracking With Event-Based Mixture Kalman Filter in Mobile Sensor Networks.

IEEE Trans Cybern 2019 Apr 17. Epub 2019 Apr 17.

In this paper, the distributed remote state estimation problem for conditional dynamic linear systems in mobile sensor networks with an event-triggered mechanism is investigated. The distributed mixture Kalman filtering method is proposed to track the state of the maneuvering target, which uses particle filtering to estimate the nonlinear variables and apply Kalman filtering to estimate the linear variables. An event-based distributed filtering scheme is designed, which is an energy-efficient way to transmit data between sensors and estimators. Read More

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https://ieeexplore.ieee.org/document/8693671/
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http://dx.doi.org/10.1109/TCYB.2019.2901515DOI Listing
April 2019
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Leveraging a Big Dataset to Develop a Recurrent Neural Network to Predict Adverse Glycemic Events in Type 1 Diabetes.

IEEE J Biomed Health Inform 2019 Apr 17. Epub 2019 Apr 17.

Patients with type 1 diabetes (T1D) do not produce their own insulin. They must continuously monitor their glucose and make decisions about insulin dosing to avoid the consequences of adverse glucose excursions. Continuous glucose monitoring (CGM) systems and insulin pumps are state-of-the-art systems that can help people with T1D manage their glucose. Read More

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http://dx.doi.org/10.1109/JBHI.2019.2911701DOI Listing

Computational identification of RNA-Seq based miRNA-mediated prognostic modules in cancer.

IEEE J Biomed Health Inform 2019 Apr 16. Epub 2019 Apr 16.

Systematic identification of miRNA prognostic signature can help decipher the effects of biomarkers in cancer treatment. A number of previous studies have only characterized a single miRNA as a promising prognostic biomarker. There is currently a trend towards combining several miRNAs as a panel of prognostic signatures, but few attempt to explain the mechanism of miRNA combination. Read More

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http://dx.doi.org/10.1109/JBHI.2019.2911528DOI Listing
April 2019
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Novel Data Imputation for Multiple Types of Missing Data in Intensive Care Units.

IEEE J Biomed Health Inform 2019 Apr 16. Epub 2019 Apr 16.

The diversity and number of parameters monitored in an intensive care unit (ICU) make the resulting databases highly susceptible to quality issues such as missing information and erroneous data entry, which adversely affect the downstream processing and predictive modeling. Missing data interpolation and imputation techniques such as multiple imputation, expectation maximization, and hot - deck imputation techniques do not account for the type of missing data, which can lead to bias. In our study, we first model the missing data as three types: "Neglectable" also known as (a. Read More

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https://ieeexplore.ieee.org/document/8692392/
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http://dx.doi.org/10.1109/JBHI.2018.2883606DOI Listing
April 2019
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A SYSTEMATIC REVIEW OF IN VITRO AND IN VIVO RADIO FREQUENCY EXPOSURE METHODS.

IEEE Rev Biomed Eng 2019 Apr 18. Epub 2019 Apr 18.

The interests in the effects of radio frequency (RF) on biological systems has increased. This interest has increased partially due to the advancements and increase implementations of RF into technology. As research in the area has progressed, the reliability and reproducibility of those experiments has not crossed multidisciplinary boundaries. Read More

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http://dx.doi.org/10.1109/RBME.2019.2912023DOI Listing
April 2019
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Amino acid encoding methods for protein sequences: a comprehensive review and assessment.

IEEE/ACM Trans Comput Biol Bioinform 2019 Apr 16. Epub 2019 Apr 16.

As the first step of machine-learning based protein structure and function prediction, the amino acid encoding play a fundamental role in the final success of those methods. Different with the protein sequence encoding, the amino acid encoding can be used in both residue-level and sequence-level prediction of protein properties by combining with different algorithms. However, it does not attract enough attention in the past decades, and there are no comprehensive reviews and assessments about encoding methods so far. Read More

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https://ieeexplore.ieee.org/document/8692651/
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http://dx.doi.org/10.1109/TCBB.2019.2911677DOI Listing
April 2019
2 Reads

Deep Robust Framework for Protein Function Prediction using Variable-Length Protein Sequences.

IEEE/ACM Trans Comput Biol Bioinform 2019 Apr 16. Epub 2019 Apr 16.

The order of amino acids in a protein sequence enables the protein to acquire a conformation suitable for performing functions, thereby motivating the need to analyse these sequences for predicting functions. Although machine learning based approaches are fast compared to methods using BLAST, FASTA, etc., they fail to perform well for long protein sequences (with more than 300 amino acids). Read More

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https://ieeexplore.ieee.org/document/8692646/
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http://dx.doi.org/10.1109/TCBB.2019.2911609DOI Listing
April 2019
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XGBoost Model for Chronic Kidney Disease Diagnosis.

IEEE/ACM Trans Comput Biol Bioinform 2019 Apr 17. Epub 2019 Apr 17.

Chronic Kidney Disease (CKD) is a menace that is affecting 10% of the world population and 15% of the South African population. The early and cheap diagnosis of this disease with accuracy and reliability will save 20,000 lives in South Africa per year. Scientists are developing smart solutions with Artificial Intelligence (AI). Read More

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https://ieeexplore.ieee.org/document/8693581/
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http://dx.doi.org/10.1109/TCBB.2019.2911071DOI Listing
April 2019
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Multichannel AC Biosusceptometry system to map biodistribution and assess the pharmacokinetic profile of magnetic nanoparticles by imaging.

IEEE Trans Nanobioscience 2019 Apr 18. Epub 2019 Apr 18.

In this paper, the application of a technique to evaluate in vivo biodistribution of magnetic nanoparticles (MNP) is addressed: the Multichannel AC Biosusceptometry System (MC-ACB). It allows real-time assessment of magnetic nanoparticles in both bloodstream clearance and liver accumulation, where a complex network of inter-related cells is responsible for MNP uptake. Based on the acquired MC-ACB images, we propose a mathematical model to help understand the distribution and accumulation pharmacokinetics of MNP. Read More

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http://dx.doi.org/10.1109/TNB.2019.2912073DOI Listing

A Single-Channel EEG-Based Approach to Detect Mild Cognitive Impairment via Speech-Evoked Brain Responses.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 18. Epub 2019 Apr 18.

Mild Cognitive Impairment (MCI) is the preliminary stage of dementia, which may lead to Alzheimer's disease (AD) in the elderly people. Therefore, early detection of MCI has the potential to minimize the risk of AD by ensuring the proper mental health care before it is too late. In this study, we demonstrate a single-channel EEG based MCI detection method, which is cost-effective and portable, and thus suitable for regular home-based patient monitoring. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2911970DOI Listing
April 2019
11 Reads

Precise tubular braid structures of ultrafine microwires as neural probes: significantly reduced chronic immune response and greater local neural survival in rat cortex.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 18. Epub 2019 Apr 18.

Braided multi-electrode probes (BMEPs) for neural interfaces comprise ultrafine microwire bundles interwoven into tubular braids. BMEPs provide highly flexible probes and tethers, and an open lattice structure with up to 24 recording/stimulating channels in precise geometries, currently all within a 150~200 μm diameter footprint. This paper compares the long-term tissue effects of BMEPs (12 × 9. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2911912DOI Listing

Quantitative Evaluation of Cerebellar Ataxia through Automated Assessment of Upper Limb Movements.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 16. Epub 2019 Apr 16.

Cerebellar damage can result in peripheral dysfunction manifesting as poor and inaccurate coordination, irregular movements and tremors. Conventionally, the severity assessment of Cerebellar ataxia (CA) is primarily based on expert clinical opinion and hence likely to be subjective. In order to establish inter rater concordance with enhanced reliability and effectiveness in the assessment of upper limb function, a novel automated system employing Microsoft Kinect is considered to capture the motion of the patient's finger for objective assessment. Read More

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https://ieeexplore.ieee.org/document/8692611/
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http://dx.doi.org/10.1109/TNSRE.2019.2911657DOI Listing
April 2019
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A Patient-Specific Single Sensor IoT-Based Wearable Fall Prediction and Detection System.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 16. Epub 2019 Apr 16.

Falls in! older adults are a major cause of morbidity and mortality and are a key class of preventable injuries. This paper presents a patient-specific (PS) fall prediction and detection prototype system that utilizes a single tri-axial accelerometer attached to the patient's thigh to distinguish between activities of daily living (ADL) and fall events. The proposed system consists of two modes of operation: 1) fast mode for fall predication (FMFP) predicting a fall event (300msec-700msec) before occurring, 2) slow mode for fall detection (SMFD) with a 1-sec latency for detecting a fall event. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2911602DOI Listing

Adaptive Hybrid Classifier for Myoelectric Pattern Recognition Against the Interferences of Outlier Motion, Muscle Fatigue, and Electrode Doffing.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 16. Epub 2019 Apr 16.

Traditional myoelectric prostheses that employ a static pattern recognition model to identify human movement intention from surface electromyography (sEMG) signals hardly adapt to the changes in the sEMG characteristics caused by interferences from daily activities, which hinders the clinical applications of such prostheses. In this study, we focus on methods to reduce or eliminate the impacts of three types of daily interferences on myoelectric pattern recognition (MPR), i.e. Read More

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https://ieeexplore.ieee.org/document/8692622/
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http://dx.doi.org/10.1109/TNSRE.2019.2911316DOI Listing
April 2019
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Automated Fine Motor Evaluation for Developmental Coordination Disorder.

IEEE Trans Neural Syst Rehabil Eng 2019 Apr 16. Epub 2019 Apr 16.

Developmental Coordination Disorder (DCD) is a type of motor learning difficulty that affects five to six percent of school-aged children, which may have a negative impact on the life of the sufferers. Timely and objective diagnosis of DCD is important for the success of the intervention. The present evaluation methods of DCD rely heavily on observational analysis of occupational therapists and physiotherapists who score the performance when children conduct some designed tasks. Read More

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http://dx.doi.org/10.1109/TNSRE.2019.2911303DOI Listing

Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes.

IEEE Trans Image Process 2019 Apr 17. Epub 2019 Apr 17.

Semantic segmentation, a pixel-level vision task, is developed rapidly by using convolutional neural networks (CNNs). Training CNNs requires a large amount of labeled data, but manually annotating data is difficult. For emancipating manpower, in recent years, some synthetic datasets are released. Read More

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https://ieeexplore.ieee.org/document/8693661/
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http://dx.doi.org/10.1109/TIP.2019.2910667DOI Listing
April 2019
10 Reads

Discrete Curvature Representations for Noise Robust Image Corner Detection.

IEEE Trans Image Process 2019 Apr 17. Epub 2019 Apr 17.

Image corner detection is very important in the fields of image analysis and computer vision. Curvature calculation techniques are used in many contour-based corner detectors. We identify that existing calculation of curvature is sensitive to local variation and noise in the discrete domain and does not perform well when corners are closely located. Read More

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https://ieeexplore.ieee.org/document/8693687/
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http://dx.doi.org/10.1109/TIP.2019.2910655DOI Listing
April 2019
1 Read
3.625 Impact Factor

Exploiting Typicality for Selecting Informative and Anomalous Samples in Videos.

IEEE Trans Image Process 2019 Apr 17. Epub 2019 Apr 17.

In this paper, we present a novel approach to find informative and anomalous samples in videos exploiting the concept of typicality from information theory. In most video analysis tasks, selection of the most informative samples from a huge pool of training data in order to learn a good recognition model is an important problem. Furthermore, it is also useful to reduce the annotation cost as it is time-consuming to annotate unlabeled samples. Read More

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https://ieeexplore.ieee.org/document/8693693/
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http://dx.doi.org/10.1109/TIP.2019.2910634DOI Listing
April 2019
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Low-Light Image Enhancement via a Deep Hybrid Network.

IEEE Trans Image Process 2019 Apr 16. Epub 2019 Apr 16.

Camera sensors often fail to capture clear images or videos in a poorly-lit environment. In this paper, we propose a trainable hybrid network to enhance the visibility of such degraded images. The proposed network consists of two distinct streams to simultaneously learn the global content and salient structures of the clear image in a unified network. Read More

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https://ieeexplore.ieee.org/document/8692732/
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http://dx.doi.org/10.1109/TIP.2019.2910412DOI Listing
April 2019
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Two-Level Attention Network with Multi-Grain Ranking Loss for Vehicle Re-Identification.

IEEE Trans Image Process 2019 Apr 16. Epub 2019 Apr 16.

Vehicle re-identification (re-ID) aims to identify the same vehicle across multiple non-overlapping cameras, which is a rather challenging task. On one hand, subtle changes in viewpoint and illumination condition can make the same vehicle look much different. On the other hand, different vehicles even different vehicle models may look quite similar. Read More

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https://ieeexplore.ieee.org/document/8692748/
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http://dx.doi.org/10.1109/TIP.2019.2910408DOI Listing
April 2019
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Demosaicking Using a Spatial Reference Image for an Anti-Aliasing Multispectral Filter Array.

IEEE Trans Image Process 2019 Apr 16. Epub 2019 Apr 16.

Multispectral imaging with a multispectral filter array (MSFA) facilitates snapshot imaging; however, a demosaicking process is required to estimate a fully-defined multispectral image based on undersampled sensor data. Undersampling induces aliasing and adverse artifacts in the reconstructed image. To solve this problem, Jia et al. Read More

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https://ieeexplore.ieee.org/document/8692717/
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http://dx.doi.org/10.1109/TIP.2019.2910392DOI Listing
April 2019
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NARROW GAP DETECTION IN MICROSCOPE IMAGES USING MARKED POINT PROCESS MODELING.

IEEE Trans Image Process 2019 Apr 16. Epub 2019 Apr 16.

Differentiating objects separated by narrow gaps is a challenging and important task in analyzing microscopic images. These small separations provide useful information for applications that require detailed boundary information and/or an accurate particle count. We present a new approach to the modeling of these gaps based on a marked point process(MPP) framework. Read More

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https://ieeexplore.ieee.org/document/8692712/
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http://dx.doi.org/10.1109/TIP.2019.2910389DOI Listing
April 2019
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Three-Zone Segmentation Based Motion Compensation for Video Compression.

IEEE Trans Image Process 2019 Apr 16. Epub 2019 Apr 16.

Motion compensation has been widely employed for removing temporal redundancies in typical hybrid video coding framework. The popular video compression standards, such as H.264/AVC and HEVC, adopt the block based partitioning model to describe the motion filed due to its high compression efficiency and relatively low computational complexity. Read More

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https://ieeexplore.ieee.org/document/8692726/
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http://dx.doi.org/10.1109/TIP.2019.2910382DOI Listing
April 2019
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Deep Group-wise Fully Convolutional Network for Co-saliency Detection with Graph Propagation.

IEEE Trans Image Process 2019 Apr 15. Epub 2019 Apr 15.

A key problem in co-saliency detection is how to effectively model the interactive relationship of a whole image group and the individual perspective of each image in a united data-driven manner. In this paper, we propose a group-wise deep co-saliency detection approach to address the co-saliency object discovery problem based on the fully convolutional network (FCN). The proposed approach captures the group-wise interaction information for group images by learning a semantics-aware image representation based on a convolutional neural network, which adaptively learns the group-wise features for co-saliency detection. Read More

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http://dx.doi.org/10.1109/TIP.2019.2909649DOI Listing
April 2019
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Deep Q Learning Driven CT Pancreas Segmentation with Geometry-Aware U-Net.

IEEE Trans Med Imaging 2019 Apr 16. Epub 2019 Apr 16.

Segmentation of pancreas is important for medical image analysis, yet it faces great challenges of class imbalance, background distractions and non-rigid geometrical features. To address these difficulties, we introduce a Deep Q Network(DQN) driven approach with deformable U-Net to accurately segment the pancreas by explicitly interacting with contextual information and extract anisotropic features from pancreas. The DQN based model learns a context-adaptive localization policy to produce a visually tightened and precise localization bounding box of the pancreas. Read More

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http://dx.doi.org/10.1109/TMI.2019.2911588DOI Listing
April 2019
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An Improved Method of Total Variation Superiorization Applied to Reconstruction in Proton Computed Tomography.

IEEE Trans Med Imaging 2019 Apr 16. Epub 2019 Apr 16.

Previous work has shown that total variation superiorization (TVS) improves reconstructed image quality in proton computed tomography (pCT). The structure of the TVS algorithm has evolved since then and this work investigated if this new algorithmic structure provides additional benefits to pCT image quality. Structural and parametric changes introduced to the original TVS algorithm included: (1) inclusion or exclusion of TV reduction requirement, (2) a variable number, N, of TV perturbation steps per feasibility-seeking iteration, and (3) introduction of a perturbation kernel 0 < α < 1. Read More

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http://dx.doi.org/10.1109/TMI.2019.2911482DOI Listing

A Novel Dynamic Model Capturing Spatial and Temporal Patterns for Facial Expression Analysis.

IEEE Trans Pattern Anal Mach Intell 2019 Apr 17. Epub 2019 Apr 17.

Facial expression analysis could be greatly improved by incorporating spatial and temporal patterns present in facial behavior, but the patterns have not yet been utilized to their full advantage. We remedy this via a novel dynamic model - an interval temporal restricted Boltzmann machine (IT-RBM) - that is able to capture both universal spatial patterns and complicated temporal patterns in facial behavior for facial expression analysis. We regard a facial expression as a multifarious activity composed of sequential or overlapping primitive facial events. Read More

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http://dx.doi.org/10.1109/TPAMI.2019.2911937DOI Listing

Fine-grained Human-centric Tracklet Segmentation with Single Frame Supervision.

IEEE Trans Pattern Anal Mach Intell 2019 Apr 17. Epub 2019 Apr 17.

In this paper, we target at the Fine-grAined human-Centric Tracklet Segmentation (FACTS) problem, where 12 human parts, e.g., face, pants, left-leg, are segmented. Read More

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http://dx.doi.org/10.1109/TPAMI.2019.2911936DOI Listing

A Spine-Specific Phased Array for Transvertebral Ultrasound Therapy: Design & Simulation.

IEEE Trans Biomed Eng 2019 Apr 18. Epub 2019 Apr 18.

Objective: To design and simulate the performance of two spine-specific phased arrays in sonicating targets spanning the thoracic spinal canal, with the objective of efficiently producing controlled foci in the spinal canal.

Methods: Two arrays (256 elements each, 500 kHz) were designed using multi-layered ray acoustics simulation; a 4-component array with dedicated components for sonicating via the paravertebral and transvertebral paths, and a 2-component array with spine-specific adaptive focusing. Mean array efficiency (canal focus pressure/water focus pressure) was evaluated using forward simulation in neutral and flexed spines. Read More

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http://dx.doi.org/10.1109/TBME.2019.2912146DOI Listing
April 2019
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A Riemannian geometry approach to reduced and discriminative covariance estimation in Brain Computer Interfaces.

IEEE Trans Biomed Eng 2019 Apr 18. Epub 2019 Apr 18.

Objective: Spatial covariance matrices are extensively employed as brain activity descriptors in BCI research that, typically, involve the whole array of sensors. Here, we introduce a methodological framework for delineating the subset of sensors, the covariance structure of which offers a reduced, but more powerful, representation of brain's coordination patterns that ultimately leads to reliable mind reading.

Methods: Adopting a Riemannian geometry approach, we turn the problem of sensor selection as a maximization of a functional that is computed over the manifold of symmetric positive definite (SPD) matrices and encapsulates class separability in a way that facilitates the search among subsets of different size. Read More

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http://dx.doi.org/10.1109/TBME.2019.2912066DOI Listing
April 2019
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