Publications

@article{sobhani2019exploring,

title = {Exploring deep neural networks for multitarget stance detection},

author = { Parinaz Sobhani and Diana Inkpen and Xiaodan Zhu},

doi = {10.1111/coin.12189},

year  = {2019},

date = {2019-01-01},

journal = {Computational Intelligence},

volume = {35},

number = {1},

pages = {82--97},

publisher = {Wiley Online Library},

abstract = {Abstract Detecting subjectivity expressed toward concerned targets is an interesting problem and has received intensive study. Previous work often treated each target independently, ignoring the potential (sometimes very strong) dependency that could exist among targets (eg, the subjectivity expressed toward two products or two political candidates in an election). In this paper, we relieve such an independence assumption in order to jointly model the subjectivity expressed toward multiple targets. We propose and show that an attention-based encoder-decoder framework is very effective for this problem, outperforming several alternatives that jointly learn dependent subjectivity through cascading classification or multitask learning, as well as models that independently predict subjectivity toward individual targets.},

keywords = {Natural Language Processing, Sentiment Analysis},

pubstate = {published},

tppubtype = {article}

}

@article{rognon2019haptic,

title = {Haptic feedback perception and learning with cable-driven guidance in exosuit teleoperation of a simulated drone},

author = { Carine Rognon and Vivek Ramachandran and Amy R Wu and Auke J Ijspeert and Dario Floreano},

doi = {10.1109/TOH.2019.2925612},

issn = {2329-4051},

year  = {2019},

date = {2019-01-01},

journal = {IEEE Transactions on Haptics},

volume = {12},

number = {3},

pages = {375--385},

publisher = {IEEE},

abstract = {Robotics teleoperation enables human operators to control the movements of distally located robots. The development of new wearable interfaces as alternatives to hand-held controllers has created new modalities of control, which are more intuitive to use. Nevertheless, such interfaces also require a period of adjustment before operators can carry out their tasks proficiently. In several fields of human-machine interaction, haptic guidance has proven to be an effective training tool for enhancing user performance. This paper presents the results of psychophysical and motor learning studies that were carried out with human participant to assess the effect of cable-driven haptic guidance for a task involving aerial robotic teleoperation. The guidance system was integrated into an exosuit, called the Flyjacket, that was developed to control drones with torso movements. Results for the just noticeable difference and from the Stevens Power Law suggest that the perception of force on the users' torso scales linearly with the amplitude of the force exerted through the cables and the perceived force is close to the magnitude of the stimulus. Motor learning studies reveal that this form of haptic guidance improves user performance in training, but this improvement is not retained when participants are evaluated without guidance.},

keywords = {Human Machine Interaction, Robotics, Unmanned Aerial Vehicles, Wearables},

pubstate = {published},

tppubtype = {article}

}

@article{chun2019deep,

title = {Deep learning-based joint pilot design and channel estimation for multiuser MIMO channels},

author = { Chang-Jae Chun and Jae-Mo Kang and Il-Min Kim},

doi = {10.1109/LCOMM.2019.2937488},

issn = {1558-2558},

year  = {2019},

date = {2019-01-01},

journal = {IEEE Communications Letters},

volume = {23},

number = {11},

pages = {1999--2003},

publisher = {IEEE},

abstract = {In this letter, we propose a joint pilot design and channel estimation scheme based on the deep learning (DL) technique for multiuser multiple-input multiple output (MIMO) channels. To this end, we construct a pilot designer using two-layer neural networks (TNNs) and a channel estimator using deep neural networks (DNNs), which are jointly trained to minimize the mean square error (MSE) of channel estimation. To effectively reduce the interference among the multiple users, we also use the successive interference cancellation (SIC) technique in the channel estimation process. The numerical results demonstrate that the proposed scheme considerably outperforms the linear minimum mean square error (LMMSE) based channel estimation scheme.},

keywords = {Neural Networks, Telecommunication},

pubstate = {published},

tppubtype = {article}

}

@article{yun2019artificial,

title = {Artificial noise scheme for correlated MISO wiretap channels},

author = { Sangseok Yun and Il-Min Kim and Jeongseok Ha},

doi = {10.1109/TVT.2019.2931277},

isbn = {1939-9359 },

year  = {2019},

date = {2019-01-01},

journal = {IEEE Transactions on Vehicular Technology},

volume = {68},

number = {9},

pages = {9323--9327},

publisher = {IEEE},

abstract = {This correspondence paper studies how correlation of the wiretap channel affects the secrecy rate of the artificial noise (AN) scheme. To this end, we first develop a simple but tight lower bound on the ergodic secrecy rate of the AN scheme on correlated multiple-input single-output wiretap channels. Then, utilizing the derived bound, we investigate the influence of correlation on the secrecy rate, which explicitly manifests how the channel correlation affects the optimal power allocation. Ultimately, this paper answers two fundamental questions: when is the AN signal beneficial? and how much power should be allocated for the AN signal to achieve a higher ergodic secrecy rate? in terms of channel correlation.},

keywords = {Telecommunication},

pubstate = {published},

tppubtype = {article}

}

@article{chun2019deepb,

title = {Deep learning-based channel estimation for massive MIMO systems},

author = { Chang-Jae Chun and Jae-Mo Kang and Il-Min Kim},

doi = {10.1109/LWC.2019.2912378},

issn = {2162-2345 },

year  = {2019},

date = {2019-01-01},

journal = {IEEE Wireless Communications Letters},

volume = {8},

number = {4},

pages = {1228--1231},

publisher = {IEEE},

abstract = {In this letter, we propose a deep learning (DL)-based channel estimation scheme for the massive multiple-input multiple-output (MIMO) system. Unlike existing studies, we develop the channel estimation scheme for the case that the pilot length is smaller than the number of transmit antennas. The proposed scheme takes a two-stage estimation process: 1) a DL-based pilot-aided channel estimation and 2) a DL-based data-aided channel estimation. In the first stage, the pilot itself and the channel estimator are jointly designed by using both a two-layer neural network (TNN) and a deep neural network (DNN). In the second stage, the accuracy of channel estimation is further enhanced by using another DNN in an iterative manner. The simulation results demonstrate that the proposed channel estimation scheme has much better performance than the conventional channel estimation scheme. We also derive a useful insight into the optimal pilot length given the number of transmit antennas.},

keywords = {Artificial Intelligence, Neural Networks, Telecommunication},

pubstate = {published},

tppubtype = {article}

}

@article{jang2019deep,

title = {Deep autoencoder based CSI feedback with feedback errors and feedback delay in FDD massive MIMO systems},

author = { Youngrok Jang and Gyuyeol Kong and Minchae Jung and Sooyong Choi and Il-Min Kim},

doi = {10.1109/LWC.2019.2895039},

year  = {2019},

date = {2019-01-01},

journal = {IEEE Wireless Communications Letters},

volume = {8},

number = {3},

pages = {833--836},

publisher = {IEEE},

abstract = {In this letter, we study the channel state information (CSI) feedback based on the deep autoencoder (AE) considering the feedback errors and feedback delay in the frequency division duplex massive multiple-input multiple-output system. We construct the deep AE by modeling the CSI feedback process, which involves feedback transmission errors and delays. The deep AE is trained by setting the delayed version of the downlink channel as the desired output. The proposed scheme reduces the impact of the feedback errors and feedback delay. Simulation results demonstrate that the proposed scheme achieves better performance than other comparable schemes.},

keywords = {Telecommunication},

pubstate = {published},

tppubtype = {article}

}

@article{jia2019worst,

title = {Worst-case robust beamforming design for wireless powered multirelay multiuser network with a nonlinear EH model},

author = { Xinghua Jia and Chaozhu Zhang and Il-Min Kim},

doi = {10.1109/TVT.2019.2896214},

issn = {1939-9359 },

year  = {2019},

date = {2019-01-01},

journal = {IEEE Transactions on Vehicular Technology},

volume = {68},

number = {3},

pages = {3038--3042},

publisher = {IEEE},

abstract = {This paper studies joint source and relay beamforming for a wireless powered downlink multirelay multiuser network. Considering nonlinear energy harvesting and imperfect channel state information, we aim to minimize the total transmit power at the base station by jointly optimizing the source beamforming and the relay beamforming weights under the energy causality constraints at the relays and the signal-to-noise ratio constraints at the users. The formulated problem is highly nonconvex, and thus, it is difficult to solve. To solve the problem, we first transform it into a worst-case optimization, and then, an iterative algorithm is developed to solve this worst-case optimization. Numerical results show the advantage of the proposed robust scheme.},

keywords = {Energy Harvesting, Telecommunication, Wireless},

pubstate = {published},

tppubtype = {article}

}

@article{nicoletta2019postfire,

title = {Postfire performance of GFRP stay-in-place formwork for concrete bridge decks},

author = { Benjamin Nicoletta and Joshua Woods and John Gales and Amir Fam},

doi = {10.1061/(ASCE)CC.1943-5614.0000941},

year  = {2019},

date = {2019-01-01},

journal = {Journal of Composites for Construction},

volume = {23},

number = {3},

pages = {04019015},

publisher = {American Society of Civil Engineers},

abstract = {This study focuses on the fire performance of glass fiber–reinforced polymer (GFRP) stay-in-place structural formwork used for the rapid construction of reinforced concrete (RC) bridge decks and serves to direct future studies on the matter. Seven beam sections of a concrete deck reinforced using a GFRP stay-in-place form are tested. The beams in this study are subjected to both fire and simulated-fire damage and tested in four-point bending to assess the mechanical contribution of the GFRP stay-in-place formwork. Fire damage was applied to one beam via a 14.5-min heptane pool fire. Experimental results show that the simulated damage was an overly conservative representation of the fire damage sustained. The fire damage was insufficient to reduce the ultimate load or change the failure mode of the specimen when compared to an undamaged control. The embedded T-rib of the GFRP form was protected from fire damage and provided redundancy to the system. Despite a char thickness of about 15% of the base thickness, the GFRP base plate was able to protect the adjacent concrete from temperatures exceeding 100°C. An increased flexural capacity was observed in the fire-damaged specimen hypothesized to be a result of concrete precompression arising from the heating and cooling of the GFRP formwork. A series of direct bond shear tests between GFRP–concrete samples at elevated temperatures found a decrease in bond shear stress and bond stiffness as bond temperatures increased.},

keywords = {Civil Infrastructure},

pubstate = {published},

tppubtype = {article}

}

@article{behinaein2019optimal,

title = {Optimal Information Release for Mixed Opacity in Discrete-Event Systems},

author = { Behnam Behinaein and Feng Lin and Karen Rudie},

doi = {10.1109/TASE.2019.2917136},

issn = {1558-3783},

year  = {2019},

date = {2019-01-01},

journal = {IEEE Transactions on Automation Science and Engineering},

volume = {16},

number = {4},

pages = {1960--1970},

publisher = {IEEE},

abstract = {Opacity is a property of a system that captures whether certain event sequences (or certain states) are indistinguishable from other event sequences (or states) in the system. Opacity is used in analyzing privacy, secrecy, and other aspects of systems modeled by discrete-event systems. In this paper, we introduce the concept of minimal information release policies for non-opacity and the concept of mixed opacity. Mixed opacity policies are introduced as a holistic approach for solving problems that involve a combination of releasing information to make some objectives of the system opaque while making some other objectives non-opaque. We present a set of algorithms for information release under a mixed opacity policy. These algorithms compute policies in a system such that two given sublanguages are opaque, and at the same time, two other sublanguages in the same system are non-opaque. The application of mixed opacity is demonstrated on the Dining Cryptographers Problem.},

keywords = {Computer Security, Discrete Event Systems},

pubstate = {published},

tppubtype = {article}

}

@article{davoodnia2019bed,

title = {In-bed pressure-based pose estimation using image space representation learning},

author = { Vandad Davoodnia and Saeed Ghorbani and Ali Etemad},

url = {https://arxiv.org/abs/1908.08919},

year  = {2019},

date = {2019-01-01},

journal = {arXiv preprint arXiv:1908.08919},

abstract = {In-bed pose estimation has shown value in fields such as hospital patient monitoring, sleep studies, and smart homes. In this paper, we present a novel in-bed pressure-based pose estimation approach capable of accurately detecting body parts from highly ambiguous pressure data. We exploit the idea of using a learnable pre-processing step, which transforms the vague pressure maps to a representation close to the expected input space of common purpose pose identification modules, which fail if solely used on the pressure data. To this end, a fully convolutional network with multiple scales is used as the learnable pre-processing step to provide the pose-specific characteristics of the pressure maps to the pre-trained pose identification module. A combination of loss functions is used to model the constraints, ensuring that unclear body parts are reconstructed correctly while preventing the pre-processing block from generating arbitrary images. The evaluation results show high visual fidelity in the generated pre-processed images as well as high detection rates in pose estimation. Furthermore, we show that the trained pre-processing block can be effective for pose identification models for which it has not been trained as well. },

keywords = {Artificial Intelligence, Computer Vision, Neural Networks},

pubstate = {published},

tppubtype = {article}

}

@article{zhang2019classification,

title = {Classification of hand movements from EEG using a deep attention-based LSTM network},

author = { Guangyi Zhang and Vandad Davoodnia and Alireza Sepas-Moghaddam and Yaoxue Zhang and Ali Etemad},

doi = {10.1109/JSEN.2019.2956998},

issn = {1558-1748},

year  = {2019},

date = {2019-01-01},

journal = {IEEE Sensors Journal},

volume = {20},

number = {6},

pages = {3113--3122},

publisher = {IEEE},

abstract = {Classifying limb movements using brain activity is an important task in Brain-computer Interfaces (BCI) that has been successfully used in multiple application domains, ranging from human-computer interaction to medical and biomedical applications. This paper proposes a novel solution for classification of left/right hand movement by exploiting a Long Short-Term Memory (LSTM) network with attention mechanism to learn the electroencephalogram (EEG) time-series information. To this end, a wide range of time and frequency domain features are extracted from the EEG signals and used to train an LSTM network to perform the classification task. We conduct extensive experiments with the EEG Movement dataset and show that our proposed solution our method achieves improvements over several benchmarks and state-of-the-art methods in both intra-subject and cross-subject validation schemes. Moreover, we utilize the proposed framework to analyze the information as received by the sensors and monitor the activated regions of the brain by tracking EEG topography throughout the experiments.},

keywords = {Artificial Intelligence, Healthcare},

pubstate = {published},

tppubtype = {article}

}

@article{kang2019deep,

title = {Deep learning-based MIMO-NOMA with imperfect SIC decoding},

author = { Jae-Mo Kang and Il-Min Kim and Chang-Jae Chun},

doi = {10.1109/JSYST.2019.2937463},

issn = {1937-9234},

year  = {2019},

date = {2019-01-01},

journal = {IEEE Systems Journal},

publisher = {IEEE},

abstract = {Nonorthogonal multiple access (NOMA) and multiple-input multiple-output (MIMO) are two key enablers for 5G systems. In this article, considering the practical issue that successive interference cancellation (SIC) decoding is imperfect in the real-world NOMA system, we propose a novel scheme for the downlink of the MIMO-NOMA system based on deep learning. In this scheme, both precoding and SIC decoding of the MIMO-NOMA system are jointly optimized (or learned) in the sense of minimizing total mean square error of the users’ signals. To this end, we construct the precoder and SIC decoders using deep neural networks such that the transmitted signals intended to multiple users can be properly precoded at the transmitter based on the superposition coding technique and the received signals are accurately decodable at the users by the SIC decoding. Numerical results demonstrate the effectiveness and superior performance of the proposed scheme.},

keywords = {Deep Learning, Neural Networks, Telecommunication},

pubstate = {published},

tppubtype = {article}

}

@article{park2019secure,

title = {Secure Communications With a Full-Duplex Relay Network Under Residual Self-Interference},

author = { Junguk Park and Sangseok Yun and Il-Min Kim and Jeongseok Ha},

doi = {10.1109/LCOMM.2019.2958809},

issn = {1558-2558},

year  = {2019},

date = {2019-01-01},

journal = {IEEE Communications Letters},

volume = {24},

number = {3},

pages = {496--500},

publisher = {IEEE},

abstract = {This letter studies secure communications in a full-duplex relay (FDR) network when an eavesdropper overhears communications between legitimate parties. In a FDR network, both the amplify-and-forward relay and the destination operate in full-duplex for the purpose of achieving a higher secrecy rate and/or improving security. In particular, the destination is capable of receiving the relayed signal and simultaneously emitting a cooperative jamming signal. This work is motivated by an intriguing question: how much residual self-interference (SI) in a FDR network is allowed to achieve a superiority of secrecy performance over conventional half-duplex relay (HDR) networks? To answer the question, the secrecy outage probability (SOP) of the FDR network is derived as a function of residual SI. The analytic results enable us to compare the SOPs of existing HDR networks and the FDR network at various levels of residual SI. In addition, this work allows one to opportunistically select either FD or HD, which leads to a significant performance improvement.},

keywords = {Signal Processing, Telecommunication},

pubstate = {published},

tppubtype = {article}

}

@article{kang2019deepb,

title = {A Deep CNN-Based Ground Vibration Monitoring Scheme for MEMS Sensed Data},

author = { Jae-Mo Kang and Il-Min Kim and Sangho Lee and Dong-Woo Ryu and Jihoe Kwon},

doi = {10.1109/LGRS.2019.2918641},

issn = {1558-0571},

year  = {2019},

date = {2019-01-01},

journal = {IEEE Geoscience and Remote Sensing Letters},

volume = {17},

number = {2},

pages = {347--351},

publisher = {IEEE},

abstract = {Ground vibration monitoring with microelectromechanical systems (MEMS) sensors is very effective and promising for alerting geological disasters. In this letter, explicitly considering and effectively addressing several specific issues related to practical MEMS sensors, we develop a novel ground vibration monitoring scheme for MEMS sensed data based on a deep convolutional neural network (CNN). Experiments are then conducted on the synthetic and real data sets. Experimental results on both data sets demonstrate that the proposed scheme significantly outperforms the other comparable schemes. For the synthetic data set, the proposed scheme achieves a very high overall accuracy of 98.82%. Also, for the real data set, the proposed scheme achieves a high overall accuracy of 81.64%, which is about 7% higher than that reported in the literature.},

keywords = {Artificial Intelligence, Neural Networks, Signal Processing},

pubstate = {published},

tppubtype = {article}

}

@article{hajavi2019deep,

title = {A deep neural network for short-segment speaker recognition},

author = { Amirhossein Hajavi and Ali Etemad},

url = {https://arxiv.org/abs/1907.10420},

year  = {2019},

date = {2019-01-01},

journal = {arXiv preprint arXiv:1907.10420},

abstract = {Todays interactive devices such as smart-phone assistants and smart speakers often deal with short-duration speech segments. As a result, speaker recognition systems integrated into such devices will be much better suited with models capable of performing the recognition task with short-duration utterances. In this paper, a new deep neural network, UtterIdNet, capable of performing speaker recognition with short speech segments is proposed. Our proposed model utilizes a novel architecture that makes it suitable for short-segment speaker recognition through an efficiently increased use of information in short speech segments. UtterIdNet has been trained and tested on the VoxCeleb datasets, the latest benchmarks in speaker recognition. Evaluations for different segment durations show consistent and stable performance for short segments, with significant improvement over the previous models for segments of 2 seconds, 1 second, and especially sub-second durations (250 ms and 500 ms). },

keywords = {Neural Networks, Signal Processing},

pubstate = {published},

tppubtype = {article}

}

@article{woo2019dermoscopic,

title = {Dermoscopic Evaluation of Skin Frailty},

author = { Kevin Woo and Will Mueller and Ali Etemad},

year  = {2019},

date = {2019-01-01},

journal = {Journal of Wound Ostomy & Continence Nursing},

volume = {46},

number = {6},

pages = {547--549},

publisher = {LWW},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ross2019toward,

title = {Toward dynamically adaptive simulation: Multimodal classification of user expertise using wearable devices},

author = { Kyle Ross and Pritam Sarkar and Dirk Rodenburg and Aaron Ruberto and Paul Hungler and Adam Szulewski and Daniel Howes and Ali Etemad},

doi = {10.3390/s19194270},

year  = {2019},

date = {2019-01-01},

journal = {Sensors},

volume = {19},

number = {19},

pages = {4270},

publisher = {Multidisciplinary Digital Publishing Institute},

abstract = {Simulation-based training has been proven to be a highly effective pedagogical strategy. However, misalignment between the participant’s level of expertise and the difficulty of the simulation has been shown to have significant negative impact on learning outcomes. To ensure that learning outcomes are achieved, we propose a novel framework for adaptive simulation with the goal of identifying the level of expertise of the learner, and dynamically modulating the simulation complexity to match the learner’s capability. To facilitate the development of this framework, we investigate the classification of expertise using biological signals monitored through wearable sensors. Trauma simulations were developed in which electrocardiogram (ECG) and galvanic skin response (GSR) signals of both novice and expert trauma responders were collected. These signals were then utilized to classify the responders’ expertise, successive to feature extraction and selection, using a number of machine learning methods. The results show the feasibility of utilizing these bio-signals for multimodal expertise classification to be used in adaptive simulation applications.},

keywords = {Affective Computing, Machine Learning, Wearables},

pubstate = {published},

tppubtype = {article}

}

@article{martin2019design,

title = {Design, model, and performance evaluation of a biomechanical energy harvesting backpack},

author = { Jean-Paul Martin and Qingguo Li},

doi = {10.1016/j.ymssp.2019.106318},

issn = {0888-3270},

year  = {2019},

date = {2019-01-01},

journal = {Mechanical Systems and Signal Processing},

volume = {134},

pages = {106318},

publisher = {Elsevier},

abstract = {Introducing compliant elements to backpack structures has been shown to reduce both the peak forces experienced by the user and the metabolic cost of walking. In previous work, we developed a novel load carriage system that allowed weight carried in a backpack to oscillate in the medial-lateral direction. In this paper, we introduce a new energy harvesting module, to be added to the load carriage module, that generates electricity from the movement of the carried mass. The energy harvesting module is implemented for two outcomes: to generate electricity for powering portable electronics and to effectively modulate oscillation amplitude and phase of the carried mass in the load carriage system. This paper outlines the design, model, and performance evaluation of our novel energy harvesting device. First, a model was developed so that we may determine device parameters that result in desired device behaviour. Then, the model was evaluated using a combination of bench top experiments and human walking experiments to validate its predictive capabilities. Testing revealed that the model can be used to predict general device behaviour, but could be further developed to improve accuracy. Lastly, we evaluated device performance in human walking experiments. The energy harvesting device generated up to 0.22 ± 0.08 W of electrical power while walking. Walking with the device while generating electricity did not significantly increase user effort, compared to walking with the weight rigidly fixed.},

keywords = {Biomechanics, Energy Harvesting},

pubstate = {published},

tppubtype = {article}

}

@article{martin2019generating,

title = {Generating electricity while walking with a medial--lateral oscillating load carriage device},

author = { Jean-Paul Martin and Qingguo Li},

doi = {10.1098/rsos.182021},

issn = {2054-5703},

year  = {2019},

date = {2019-01-01},

journal = {Royal Society open science},

volume = {6},

number = {7},

pages = {182021},

publisher = {The Royal Society},

abstract = {Biomechanical energy harvesters generate electricity, from human movement, to power portable electronics. We developed an energy harvesting module to be used in conjunction with a load carriage device that allows carried mass in a backpack to oscillate in the medial–lateral (M–L) direction. The energy harvesting module was designed to tune M–L oscillations of the carried mass to create favourable device–user interaction. We tested seven energy harvesting conditions and compared them to walking with the device when the weight was rigidly fixed to the backpack frame. For each energy harvesting condition, we changed the external load resistance: altering how much electricity was being generated and how much the carried mass would oscillate. We then correlated device behaviour to the biomechanical response of the user. The energy harvesting load carriage system generated electricity with no significant increase in the metabolic power required to walk, when compared to walking with the carried weight rigidly fixed. The device was able to generate up to 0.22 ± 0.03 W of electricity, while walking with 9 kg of carried weight. The device also reduced the interaction forces experienced by the user, in the M–L direction, compared to walking with the device when the mass was rigidly fixed.},

keywords = {Biomechanics, Energy Harvesting},

pubstate = {published},

tppubtype = {article}

}

@article{li2019actuated,

title = {An actuated dissipative spring-mass walking model: Predicting human-like ground reaction forces and the effects of model parameters},

author = { Tong Li and Qingguo Li and Tao Liu},

doi = {10.1016/j.jbiomech.2019.04.028},

issn = {0021-9290},

year  = {2019},

date = {2019-01-01},

journal = {Journal of biomechanics},

volume = {90},

pages = {58--64},

publisher = {Elsevier},

abstract = {Simple models are widely used to understand the mechanics of human walking. The optimization-based minimal biped model and spring-loaded-inverted-pendulum (SLIP) model are two popular models that can achieve human-like walking patterns. However, ground reaction forces (GRF) from these two models still deviate from experimental data. In this paper, we proposed an actuated dissipative spring-mass model by integrating these two models to realize more human-like GRF patterns. We first explored the function of stiffness, damping, and weights of both energy cost and force cost in the objective function and found that these parameters have distinctly different influences on the optimized gait and GRF profiles. The stiffness and objective weight affect the number and size of peaks in the vertical GRF and stance time. The damping changes the relative size of the peaks but has little influence on stance time. Based on these observations, these parameters were manually tuned at three different speeds to approach experimentally measured vertical GRF and the highest correlation coefficient can reach 0.983. These results indicate that the stiffness, damping, and proper objective functions are all important factors in achieving human-like motion for this simple walking model. These findings can facilitate the understanding of human walking dynamics and may be applied in future biped models.},

keywords = {Biomechanics, Predictive Model},

pubstate = {published},

tppubtype = {article}

}

@article{li2019understanding,

title = {Understanding the mechanics and balance control of the carrying pole through modeling and simulation},

author = { Tong Li and Qingguo Li and Tao Liu},

doi = {10.1371/journal.pone.0218072},

year  = {2019},

date = {2019-01-01},

journal = {Plos one},

volume = {14},

number = {6},

pages = {e0218072},

publisher = {Public Library of Science San Francisco, CA USA},

abstract = {The carrying pole has existed as a load carrying tool for thousands of years and is still popular in many parts of Asia. Previous studies attempted to determine whether the elasticity of the carrying pole is energetically beneficial compared with other load carrying methods. However, conflicting results indicate that the effects of the carrying pole stiffness on the carrier are still unclear. The carrying pole exhibits more complex characteristics beyond stiffness, which invites further investigation. As the first step towards the goal, this paper explores the underlying mechanics of the carrying pole, including the structural and dynamic properties, to determine its impact on the carrier. The structure of the carrying pole is modeled and characterized by pole length, pole stiffness, and length of suspension rope. We argue that maintaining the pole’s balance should be a major prerequisite during load carriage and that active feedback control from the carrier is required. Simulations reveal that the structural parameters of the pole have significant influences on the pole’s balance and the interaction between the pole and the carrier. This work suggests mechanical characteristics of the carrying pole can potentially have an extensive impact on gait mechanics and energetics of the carrier.},

keywords = {Biomechanics},

pubstate = {published},

tppubtype = {article}

}

@article{brault2019distributed,

title = {Distributed Reinforcement Strains: Measurement and Application},

author = { Andre Brault and Neil A Hoult},

doi = {10.1139/cgj-2017-0163},

year  = {2019},

date = {2019-01-01},

journal = {ACI Structural Journal},

volume = {116},

number = {4},

pages = {115-127},

abstract = {Distributed reinforcement strain measurements could provide invaluable information for reinforced concrete (RC) model development and evaluation. A technique to measure distributed reinforcement strains using fiber optic sensors in RC elements is developed, which is more cost-effective and less time-consuming than existing methods. Nine RC beams were tested in three-point bending to evaluate the measurements, which were found to be accurate when compared to electrical strain gauges and theoretical predictions. This is the first instance where distributed fiber optic sensors have measured reinforcement strains accurately after cracking; however, strains well above yield were not reliably measured. Relating reinforcement strains with corresponding crack width measurements highlighted differences in how cracks initiate from crack to crack in a single specimen. Lastly, the experimental data were used to evaluate the potential for existing models to be used to predict reinforcement strains from external crack width measurements for RC assessment purposes.},

keywords = {Fibre Optic Sensors},

pubstate = {published},

tppubtype = {article}

}

@article{nurmi2019distributed,

title = {Distributed strain monitoring of two-way slabs},

author = { Sara Nurmi and Neil A Hoult and Simon D Howell},

doi = {10.1016/j.engstruct.2019.04.002},

issn = {0141-0296},

year  = {2019},

date = {2019-01-01},

journal = {Engineering Structures},

volume = {189},

pages = {580--588},

publisher = {Elsevier},

abstract = {Two-way slab design and assessment is often based on conservative approaches due to a lack of data regarding slab behaviour. Distributed fibre optic strain sensors have the potential to provide extensive data sets for both lab experiments and field assessments. A proof of concept study was undertaken that involved four two-way slabs, with varying reinforcement ratios and levels of axial restraint, that were instrumented with distributed fibre optic strain sensors and tested under a central point load. The slabs with less reinforcement demonstrated a ductile flexural failure while the more heavily reinforced slabs failed due to punching shear. The axial restraint system developed for this research provided partial restraint and enhanced the capacity of both restrained specimens compared to the control specimens. The strain data enabled differences in support conditions (both vertical and axial) to be identified. Additionally, the data enabled the onset of reinforcement yielding to be captured and thus proved it to be a promising approach for measuring the beneficial of effects of membrane action. The results of the experiments were compared to a yield-line analysis and were found to be within 5% for the unrestrained specimens and within 10% for the axially restrained specimens despite the fact that two specimens failed in punching shear.},

keywords = {Fibre Optic Sensors},

pubstate = {published},

tppubtype = {article}

}

@article{malek2019postyield,

title = {Postyield Bond Deterioration and Damage Assessment of RC Beams Using Distributed Fiber-Optic Strain Sensing System},

author = { Amirmasoud Malek and Allan Scott and Stefano Pampanin and Neil A Hoult},

doi = {10.1061/(ASCE)ST.1943-541X.0002286},

year  = {2019},

date = {2019-01-01},

journal = {Journal of Structural Engineering},

volume = {145},

number = {4},

pages = {04019007},

publisher = {American Society of Civil Engineers},

abstract = {Postyield steel–concrete bond has been the subject of considerable investigations using pull-out or direct tensile tests; however, the degradation in bond due to reinforcement yielding in RC beams subjected to lateral loading has not been fully scrutinized. Conventional measuring instruments (strain gauges or LVDTs) cannot precisely measure strain distribution along the yielded reinforcing bar with a minimum level of interference to the bond. Therefore, this study reports the postyield behavior of bond in RC cantilever beams subjected to monotonic lateral loading monitored using a distributed fiber-optic strain sensing system (DFOSSS). The DFOSSS enabled accurate monitoring of deformations of the embedded reinforcing bars and the strains on the concrete surface. This allowed slip, steel stress, bond stress, bond deterioration length, and the locations of cracks to be determined. Using the new values for maximum bond stress, a model was proposed to predict pre- and postyield bond behavior, including steel strain effect. Finally, the mean bond stress values were presented for the simple assessment of bond strength in both pre- and postyield regions. 

},

keywords = {Fibre Optic Sensors},

pubstate = {published},

tppubtype = {article}

}

@article{brault2019monitoring,

title = {Monitoring of beams in an RC building during a load test using distributed sensors},

author = { Andre Brault and Neil A Hoult and Tom Greenough and Ian Trudeau},

doi = {10.1061/(ASCE)CF.1943-5509.0001250},

year  = {2019},

date = {2019-01-01},

journal = {Journal of Performance of Constructed Facilities},

volume = {33},

number = {1},

pages = {04018096},

publisher = {American Society of Civil Engineers},

abstract = {The understanding of the complex behavior of reinforced concrete elements in situ would be aided if distributed strain measurements were captured during load tests, potentially leading to more accurate assessments and load ratings, and optimized future designs. This research investigates the use of distributed fiber optic sensors (FOS) to monitor three beams in a newly constructed RC building during a load test. It is the first case where an FOS technique capable of monitoring distributed strains, distributed deflections, and crack widths simultaneously is implemented in the field. The FOS data captured inflection points, moment transfer at the supports, crack locations, and crack openings. The FOS also captured deflected shapes, enabling maximum deflections to be determined without prior knowledge of where they would occur. Lastly, the measured results from the load test were compared to design model predictions for each element. },

keywords = {Fibre Optic Sensors},

pubstate = {published},

tppubtype = {article}

}

@article{broth2019distributed,

title = {Distributed Sensing to Assess Bond Degradation},

author = { ZACHARY E BROTH and NEIL A HOULT},

doi = {10.12783/shm2019/32295},

year  = {2019},

date = {2019-01-01},

journal = {Structural Health Monitoring 2019},

abstract = {It is well known that reinforced concrete beams with low shear span to depth ratios have higher shear capacity due to the change in load carrying mechanism from beam action to arching action. However, up until now it has not been possible to understand the development of these mechanisms, which in turn makes it difficult to assess these beams. Distributed fiber optic strain sensing offers the ability to capture strain distributions along the full length of the reinforcement. When coupled with dynamic sensing capability, it then becomes possible to capture the formation of bond degradation that leads to arching action, as well as the impact that load cycling has on further bond degradation. In this study two beams were tested with identical shear span lengths but different effective depths, resulting in different a / d ratios. One beam carried load through beam action while the other beam carried load, once degradation had taken place, through arching action. The beams were loaded, then cycled for 3600 cycles, before being tested to failure. The behavior of the two beams is investigated by comparing the deflection and longitudinal strain behavior during the load cycles and just before failure. Significant differences in the longitudinal strain distribution developed during the tests, clearly highlighting the formation of arching action in the specimen with the smaller a / d ratio. The results of these experiments could be used to refine assessment techniques such as code models and finite element analysis.},

keywords = {Fibre Optic Sensors},

pubstate = {published},

tppubtype = {article}

}

@article{brault2019monitoringb,

title = {Monitoring reinforced concrete serviceability performance using fiber-optic sensors},

author = { Andre Brault and Neil Hoult},

doi = {10.14359/51710870},

year  = {2019},

date = {2019-01-01},

journal = {ACI Structural Journal},

volume = {116},

number = {1},

pages = {57},

publisher = {American Concrete Institute},

abstract = {Monitoring  the  serviceability  performance  of  reinforced  concrete  (RC) structures in the field provides critical data for informing RC  modeling,  analysis,  and  design.  Currently,  there  is  a  lack  of  monitoring  technology  that  can  capture  the  complex  behavior  of  RC elements in place, in detail, while also being feasible to imple-ment. A technique of using fiber-optic sensors to simultaneously monitor both distributed RC beam deflections and crack widths is developed  and  described.  Thirteen  beam  specimens  with  varying  properties  were  tested  in  three-point  bending  to  evaluate  the  technique  against  other  sensor  technologies.  The  results  showed  that distributed beam deflections can be accurately measured up until  load  levels  approaching  failure,  while  crack  widths  can  be  measured up until a width of 0.3 mm (0.0118 in.). The technique is practical to implement and provides robust data sets not achievable with  other  sensing  technologies,  making  it  an  effective  option  for  field-monitoring applications.},

keywords = {Fibre Optic Sensors},

pubstate = {published},

tppubtype = {article}

}

@article{wheeler2019use,

title = {Use of fiber optic sensing to measure distributed rail strains and determine rail seat forces under a moving train},

author = { Lisa N Wheeler and W Andy Take and Neil A Hoult and Hoat Le},

doi = {10.1139/cgj-2017-0163},

year  = {2019},

date = {2019-01-01},

journal = {Canadian Geotechnical Journal},

volume = {56},

number = {1},

pages = {1--13},

publisher = {NRC Research Press},

abstract = {Rayleigh backscatter fiber optic sensing permits dynamic strains to be measured along an optical fiber with a gauge spacing and temporal resolution sufficient for rail applications. However, this sensing technology is highly sensitive to vibration. A 7.5 m long section of rail was instrumented with optical fiber and strain measurements were recorded during passage of a freight train slowed to 8–11 km/h. This strategy to minimize rail vibration was successful in permitting distributed dynamic rail strains to be measured under freight car loading. The measured rail strains were used to determine the rail shear forces, which were then used with the static wheel loads to determine the rail seat load for 14 consecutive sleepers as the train passed over the field monitoring site. These data were then combined with measurements of dynamic rail displacement captured using digital image correlation to infer the rail seat load–deflection relationships for individual sleepers. These relationships were observed to provide significantly more detailed information about unsupported voids and the sleeper contact stiffnesses than the traditional consideration of the relationship between applied load and rail deflection and highlights how track behavior at a monitored location can be dependent on the conditions and behavior of neighbouring sleeper.},

keywords = {Fibre Optic Sensors, Railway},

pubstate = {published},

tppubtype = {article}

}

@article{poldon2019distributed,

title = {Distributed Sensing in Large Reinforced Concrete Shear Test},

author = { Jack J Poldon and Neil A Hoult and Evan C Bentz},

doi = {10.14359/51716765 },

year  = {2019},

date = {2019-01-01},

journal = {ACI Structural Journal},

volume = {116},

number = {5},

pages = {235--245},

publisher = {American Concrete Institute},

abstract = {A  large  reinforced  concrete  (RC)  beam  designed  to  fail  in  shear  was experimentally tested and monitored with distributed sensing technologies.  Fiber-optic  sensors  (FOS)  were  used  to  monitor  the strain along the flexural and shear reinforcement, and digital image correlation (DIC) was used to measure strains and displace-ments on the concrete surface. Measurements from the distributed sensing technologies were found to be in agreement with conven-tional sensors when tensile elongation and midspan deflection were analyzed prior to the development of extensive shear cracks. Results showed  that  cracking  on  the  concrete  surface  was  correlated  with peaks in the FOS strain data for both the flexural and shear reinforcement.  Combined  distributed  measurement  (CDM)  plots  presented the full beam response at a given load. A method of moni-toring the distributed shear strain was proposed and used to assess the behavior with increasing load and showed that prior to failure, approximately  45%  of  the  beam  displacement  was  due  to  shear  strain. The presented measurement technique using FOS and DIC is shown to enable a more detailed study of shear failures, specifi-cally, in a fashion that enables the quantification of the individual response of reinforcing steel and concrete under loading},

keywords = {Civil Infrastructure, Fibre Optic Sensors},

pubstate = {published},

tppubtype = {article}

}

@article{motaharifar2019control,

title = {Control of Dual-User Haptic Training System With Online Authority Adjustment: An Observer-Based Adaptive Robust Scheme},

author = { Mohammad Motaharifar and Hamid D Taghirad and Keyvan Hashtrudi-Zaad and Seyed Farzad Mohammadi},

doi = {10.1109/TCST.2019.2946943},

issn = {1558-0865},

year  = {2019},

date = {2019-01-01},

journal = {IEEE Transactions on Control Systems Technology},

publisher = {IEEE},

abstract = {The design problem for the control a dual-user haptic surgical training system is studied in this article. The system allows the trainee to perform the task on a virtual environment, while the trainer is able to interfere in the operation and correct probable mistakes made by the trainee. The proposed methodology allows the trainer to transfer the task authority to or from the trainee in real time. The robust adaptive nature of the controller ensures position tracking. The stability of the closed-loop system is analyzed using the input-to-output stability approach and the small-gain theorem. Simulation and experimental results are presented to validate the effectiveness of the proposed control scheme.},

keywords = {Haptics, Simulation},

pubstate = {published},

tppubtype = {article}

}

@article{mokogwu2019experimental,

title = {Experimental Assessment of Absolute Stability in Bilateral Teleoperation},

author = { Chiedu Nnaji Mokogwu and Kamran Razi and Keyvan Hashtrudi-Zaad},

doi = {10.1109/TOH.2019.2949819},

issn = {2329-4051},

year  = {2019},

date = {2019-01-01},

journal = {IEEE Transactions on Haptics},

publisher = {IEEE},

abstract = {Absolute stability analysis of bilateral teleoperation systems are typically model-based. Under borderline conditions of absolute stability, depending on the degree of uncertainty in the dynamic model of the teleoperator and existing noise, the system may behave as potentially unstable when the model-based analysis predicts otherwise. In this article, we propose a methodology to experimentally verify the absolute stability of master-slave teleoperation systems. Since absolute stability demands bounds of all possible environments, we achieve this by conducting only three experiments that are often experienced in teleoperation: free slave, mass-carrying slave and locked slave (rigid environment). We will validate and compare our proposed method with the benchmark Llewellyns absolute stability criterion. Furthermore, we will examine the robustness of the proposed method and will provide guidelines for choosing the mass for the mass-carrying load condition.},

keywords = {Motion Control, Robotics},

pubstate = {published},

tppubtype = {article}

}

@article{motaharifar2019controlb,

title = {Control synthesis and ISS stability analysis of a dual-user haptic training system based on S-shaped function},

author = { Mohammad Motaharifar and Hamid D Taghirad and Keyvan Hashtrudi-Zaad and Seyed Farzad Mohammadi},

doi = {10.1109/TMECH.2019.2917448},

issn = {1941-014X},

year  = {2019},

date = {2019-01-01},

journal = {IEEE/ASME Transactions on Mechatronics},

volume = {24},

number = {4},

pages = {1553--1564},

publisher = {IEEE},

abstract = {The controller design and stability analysis of a dual user training haptic system is studied. Most of the previously proposed control methodologies for this system have not simultaneously considered special requirements of surgery training and stability analysis of the nonlinear closed-loop system which is the objective of this paper. In the proposed training approach, the trainee is allowed to freely experience the task and be corrected as needed, while the trainer maintains the task dominance. A special S-shaped function is suggested to generate the corrective force according to the magnitude of motion error between the trainer and the trainee. The closed-loop stability of the system is analyzed considering the nonlinearity of the system components using the Input-to-State Stability approach. Simulation and experimental results show the effectiveness of the proposed approach.},

keywords = {Haptics, Healthcare, Simulation},

pubstate = {published},

tppubtype = {article}

}

@article{lugez2019field,

title = {Field distortion compensation for electromagnetic tracking of ultrasound probes with application in high-dose-rate prostate brachytherapy},

author = { Elodie Lugez and Hossein Sadjadi and Chandra P Joshi and Keyvan Hashtrudi-Zaad and Selim G Akl and Gabor Fichtinger},

doi = {10.1088/2057-1976/ab12b6},

year  = {2019},

date = {2019-01-01},

journal = {Biomedical Physics & Engineering Express},

volume = {5},

number = {3},

pages = {035026},

publisher = {IOP Publishing},

abstract = {Purpose: Electromagnetic (EM) tracking of ultrasound (US) probes has been introduced to expand US imaging capabilities and benefit challenging procedures. However, various instruments—including the US probe itself—may introduce dynamic distortions to the EM field, and compromise the EM measurements. Basic filtering methods, such as those provided by manufacturers, are usually inefficient as they do not allow for field distortion compensation. We propose to use a simultaneous localization and mapping (SLAM) algorithm to track the transrectal US (TRUS) probe while dynamically detect, map, and correct the EM field distortions. Methods: Combining the motion model of the tracked probe, the observations made by a few redundant EM sensors, and the field distortions map, the SLAM algorithm relied on an extended Kalman filter (EKF) to estimate the tracking measurements. The SLAM technique was experimentally validated in a brachytherapy suite. Tracking of a TRUS probe was performed by means of an Ascension trakSTAR tracking system and four EM sensors. In addition, an optical tracking system was employed to provide a ground truth to our data. The performance of the SLAM technique was analysed by varying pertinent parameters, such as the number of redundant measurements and the motion trajectory. Probe trajectories included longitudinal translation, rotation, and freehand motions (consisting of simultaneous longitudinal translation and rotation motions) in order to comprehensively simulate imaging scenarios. Finally, the accuracy of the SLAM estimations was compared with that of the standard filtering methods provided by the manufacturer, as well as that of a simpler sensor fusion technique. Results: SLAM efficiently reduced position tracking errors up to 46.4% during freehand motions of the TRUS probe. Moreover, higher SLAM estimation accuracies were observed as the number of redundant measurements increased. While both TRUS probe motions did not yield a clinically significant trend on position tracking accuracy, orientation measurements were considerably improved during translation of the TRUS probe. Conclusions: The SLAM technique was effective in increasing the tracking accuracy of the TRUS probe. Higher number of redundant sensors and favorable sensor configurations improved the SLAM estimations of EM measurements. In turn, SLAM can further encourage the introduction of EM tracking assistance in clinical procedures such as prostate brachytherapy.},

keywords = {Healthcare, Tracking},

pubstate = {published},

tppubtype = {article}

}