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Artificial neural networks

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https://www.readbyqxmd.com/read/28325033/user-intent-prediction-with-a-scaled-conjugate-gradient-trained-artificial-neural-network-for-lower-limb-amputees-using-a-powered-prosthesis
#1
Richard B Woodward, John A Spanias, Levi J Hargrove
Powered lower limb prostheses have the ability to provide greater mobility for amputee patients. Such prostheses often have pre-programmed modes which can allow activities such as climbing stairs and descending ramps, something which many amputees struggle with when using non-powered limbs. Previous literature has shown how pattern classification can allow seamless transitions between modes with a high accuracy and without any user interaction. Although accurate, training and testing each subject with their own dependent data is time consuming...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28324778/measurement-of-weld-penetration-depths-in-thin-structures-using-transmission-coefficients-of-laser-generated-lamb-waves-and-neural-network
#2
Lei Yang, I Charles Ume
The Laser/EMAT ultrasonic (LEU) technique has shown the capability to measure weld penetration depths in thick structures based on ray-tracing of laser-generated bulk and surface waves. The ray-tracing method is not applicable to laser-generated Lamb waves when the LEU technique is used to measure weld penetration depths in thin structures. In this work, transmission coefficients of Lamb waves present in the LEU signals are investigated against varying weld penetration depths. An artificial neural network is developed to use transmission coefficients of sensitive Lamb waves and LEU signal energy to predict weld penetration depths accurately...
February 28, 2017: Ultrasonics
https://www.readbyqxmd.com/read/28324707/chemical-structure-based-predictive-model-for-the-oxidation-of-trace-organic-contaminants-by-sulfate-radical
#3
Tiantian Ye, Zongsu Wei, Richard Spinney, Chong-Jian Tang, Shuang Luo, Ruiyang Xiao, Dionysios D Dionysiou
Second-order rate constants [Formula: see text] for the reaction of sulfate radical anion (SO4(•-)) with trace organic contaminants (TrOCs) are of scientific and practical importance for assessing their environmental fate and removal efficiency in water treatment systems. Here, we developed a chemical structure-based model for predicting [Formula: see text] using 32 molecular fragment descriptors, as this type of model provides a quick estimate at low computational cost. The model was constructed using the multiple linear regression (MLR) and artificial neural network (ANN) methods...
March 6, 2017: Water Research
https://www.readbyqxmd.com/read/28319760/improved-prediction-of-higher-heating-value-of-biomass-using-an-artificial-neural-network-model-based-on-proximate-analysis
#4
Harun Uzun, Zeynep Yıldız, Jillian L Goldfarb, Selim Ceylan
As biomass becomes more integrated into our energy feedstocks, the ability to predict its combustion enthalpies from routine data such as carbon, ash, and moisture content enables rapid decisions about utilization. The present work constructs a novel artificial neural network model with a 3-3-1 tangent sigmoid architecture to predict biomasses' higher heating values from only their proximate analyses, requiring minimal specificity as compared to models based on elemental composition. The model presented has a considerably higher correlation coefficient (0...
March 9, 2017: Bioresource Technology
https://www.readbyqxmd.com/read/28319649/optimization-of-extraction-of-linarin-from-flos-chrysanthemi-indici-by-response-surface-methodology-and-artificial-neural-network
#5
Hongye Pan, Qing Zhang, Keke Cui, Guoquan Chen, Xuesong Liu, Longhu Wang
The extraction of linarin from Flos chrysanthemi indici by ethanol was investigated. Two modeling techniques, response surface methodology and artificial neural network, were adopted to optimize the process parameters, such as, ethanol concentration, extraction period, extraction frequency, and solvent to material ratio. We showed that both methods provided good predictions, but artificial neural network provided a better and more accurate result. The optimum process parameters include, ethanol concentration of 74%, extraction period of 2 h, extraction three times, solvent to material ratio of 12 mL/g...
March 20, 2017: Journal of Separation Science
https://www.readbyqxmd.com/read/28319275/mrf-ann-a-machine-learning-approach-for-automated-er-scoring-of-breast-cancer-immunohistochemical-images
#6
T Mungle, S Tewary, D K DAS, I Arun, B Basak, S Agarwal, R Ahmed, S Chatterjee, C Chakraborty
Molecular pathology, especially immunohistochemistry, plays an important role in evaluating hormone receptor status along with diagnosis of breast cancer. Time-consumption and inter-/intraobserver variability are major hindrances for evaluating the receptor score. In view of this, the paper proposes an automated Allred Scoring methodology for estrogen receptor (ER). White balancing is used to normalize the colour image taking into consideration colour variation during staining in different labs. Markov random field model with expectation-maximization optimization is employed to segment the ER cells...
March 20, 2017: Journal of Microscopy
https://www.readbyqxmd.com/read/28318903/understanding-human-intention-by-connecting-perception-and-action-learning-in-artificial-agents
#7
Sangwook Kim, Zhibin Yu, Minho Lee
To develop an advanced human-robot interaction system, it is important to first understand how human beings learn to perceive, think, and act in an ever-changing world. In this paper, we propose an intention understanding system that uses an Object Augmented-Supervised Multiple Timescale Recurrent Neural Network (OA-SMTRNN) and demonstrate the effects of perception-action connected learning in an artificial agent, which is inspired by psychological and neurological phenomena in humans. We believe that action and perception are not isolated processes in human mental development, and argue that these psychological and neurological interactions can be replicated in a human-machine scenario...
February 11, 2017: Neural Networks: the Official Journal of the International Neural Network Society
https://www.readbyqxmd.com/read/28296020/memristive-devices-with-highly-repeatable-analog-states-boosted-by-graphene-quantum-dots
#8
Changhong Wang, Wei He, Yi Tong, Yishu Zhang, Kejie Huang, Li Song, Shuai Zhong, Rajasekaran Ganeshkumar, Rong Zhao
Memristive devices, having a huge potential as artificial synapses for low-power neural networks, have received tremendous attention recently. Despite great achievements in demonstration of plasticity and learning functions, little progress has been made in the repeatable analog resistance states of memristive devices, which is, however, crucial for achieving controllable synaptic behavior. The controllable behavior of synapse is highly desired in building neural networks as it helps reduce training epochs and diminish error probability...
March 15, 2017: Small
https://www.readbyqxmd.com/read/28293163/an-fpga-platform-for-real-time-simulation-of-spiking-neuronal-networks
#9
Danilo Pani, Paolo Meloni, Giuseppe Tuveri, Francesca Palumbo, Paolo Massobrio, Luigi Raffo
In the last years, the idea to dynamically interface biological neurons with artificial ones has become more and more urgent. The reason is essentially due to the design of innovative neuroprostheses where biological cell assemblies of the brain can be substituted by artificial ones. For closed-loop experiments with biological neuronal networks interfaced with in silico modeled networks, several technological challenges need to be faced, from the low-level interfacing between the living tissue and the computational model to the implementation of the latter in a suitable form for real-time processing...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28292907/overcoming-catastrophic-forgetting-in-neural-networks
#10
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, Demis Hassabis, Claudia Clopath, Dharshan Kumaran, Raia Hadsell
The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitable feature of connectionist models. We show that it is possible to overcome this limitation and train networks that can maintain expertise on tasks that they have not experienced for a long time. Our approach remembers old tasks by selectively slowing down learning on the weights important for those tasks...
March 14, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28292179/cross-linking-approaches-to-tuning-the-mechanical-properties-of-peptide-%C3%AF-electron-hydrogels
#11
Wathsala Liyanage, Herdeline Ann M Ardoña, Hai-Quan Mao, John D Tovar
Self-assembling peptides are extensively exploited as bioactive materials in applications such as regenerative medicine and drug delivery despite the fact that their relatively weak noncovalent interactions often render them susceptible to mechanical destruction and solvent erosion. Herein, we describe how covalent cross-linking enhances the mechanical stability of self-assembling π-conjugated peptide hydrogels. We designed short peptide-chromophore-peptide sequences displaying different reactive functional groups that can form cross-links with appropriately modified bifunctional polyethylene glycol (PEG)-based small guest molecules...
March 15, 2017: Bioconjugate Chemistry
https://www.readbyqxmd.com/read/28289564/binsanity-unsupervised-clustering-of-environmental-microbial-assemblies-using-coverage-and-affinity-propagation
#12
Elaina D Graham, John F Heidelberg, Benjamin J Tully
Metagenomics has become an integral part of defining microbial diversity in various environments. Many ecosystems have characteristically low biomass and few cultured representatives. Linking potential metabolisms to phylogeny in environmental microorganisms is important for interpreting microbial community functions and the impacts these communities have on geochemical cycles. However, with metagenomic studies there is the computational hurdle of 'binning' contigs into phylogenetically related units or putative genomes...
2017: PeerJ
https://www.readbyqxmd.com/read/28287986/deepx-deep-learning-accelerator-for-restricted-boltzmann-machine-artificial-neural-networks
#13
Lok-Won Kim
Although there have been many decades of research and commercial presence on high performance general purpose processors, there are still many applications that require fully customized hardware architectures for further computational acceleration. Recently, deep learning has been successfully used to learn in a wide variety of applications, but their heavy computation demand has considerably limited their practical applications. This paper proposes a fully pipelined acceleration architecture to alleviate high computational demand of an artificial neural network (ANN) which is restricted Boltzmann machine (RBM) ANNs...
March 8, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28287830/artificial-neural-network-system-to-predict-the-postoperative-outcome-of-percutaneous-nephrolithotomy
#14
Alireza Aminsharifi, Dariush Irani, Shima Pooyesh, Hamid Parvin, Sakineh Dehghani, Khalilolah Yousofi, Ebrahim Fazel, Fatemeh Zibaie
PURPOSE: To construct, train, and apply an artificial neural network (ANN) system for prediction of different outcome variables of percutaneous nephrolithotomy (PCNL). We calculated predictive accuracy, sensitivity, and precision for each outcome variable. METHODS: During the study period, all adult patients who underwent PCNL at our institute were enrolled in the study. Preoperative and postoperative variables were recorded, and stone-free status was assessed perioperatively with computed tomography scans...
March 13, 2017: Journal of Endourology
https://www.readbyqxmd.com/read/28283971/comparative-study-of-adsorptive-removal-of-cr-vi-ion-from-aqueous-solution-in-fixed-bed-column-by-peanut-shell-and-almond-shell-using-empirical-models-and-ann
#15
Munmun Banerjee, Nirjhar Bar, Ranjan Kumar Basu, Sudip Kumar Das
Cr(VI) is a toxic water pollutant, which causes cancer and mutation in living organisms. Adsorption has become the most preferred method for removal of Cr(VI) due to its high efficiency and low cost. Peanut and almond shells were used as adsorbents in downflow fixed bed continuous column operation for Cr(VI) removal. The experiments were carried out to scrutinise the adsorptive capacity of the peanut shells and almond shells, as well as to find out the effect of various operating parameters such as column bed depth (5-10 cm), influent flow rate (10-22 ml min(-1)) and influent Cr(VI) concentration (10-20 mg L(-1)) on the Cr(VI) removal...
March 10, 2017: Environmental Science and Pollution Research International
https://www.readbyqxmd.com/read/28283297/a-new-approach-for-the-estimation-of-phytoplankton-cell-counts-associated-with-algal-blooms
#16
Majid Nazeer, Man Sing Wong, Janet Elizabeth Nichol
This study proposes a method for estimating phytoplankton cell counts associated with an algal bloom, using satellite images coincident with in situ and meteorological parameters. Satellite images from Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), Operational Land Imager (OLI) and HJ-1 A/B Charge Couple Device (CCD) sensors were integrated with the meteorological observations to provide an estimate of phytoplankton cell counts. All images were atmospherically corrected using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) atmospheric correction method with a possible error of 1...
March 7, 2017: Science of the Total Environment
https://www.readbyqxmd.com/read/28282877/impact-of-calcium-and-magnesium-in-groundwater-and-drinking-water-on-the-health-of-inhabitants-of-the-slovak-republic
#17
Stanislav Rapant, Veronika Cvečková, Katarína Fajčíková, Darina Sedláková, Beáta Stehlíková
This work aims to evaluate the impact of the chemical composition of groundwater/drinking water on the health of inhabitants of the Slovak Republic. Primary data consists of 20,339 chemical analyses of groundwater (34 chemical elements and compounds) and data on the health of the Slovak population expressed in the form of health indicators (HI). Fourteen HIs were evaluated including life expectancy, potential years of lost life, relative/standardized mortality for cardiovascular and oncological diseases, and diseases of the gastrointestinal and respiratory systems...
March 8, 2017: International Journal of Environmental Research and Public Health
https://www.readbyqxmd.com/read/28280505/advanced-interval-type-2-fuzzy-sliding-mode-control-for-robot-manipulator
#18
Ji-Hwan Hwang, Young-Chang Kang, Jong-Wook Park, Dong W Kim
In this paper, advanced interval type-2 fuzzy sliding mode control (AIT2FSMC) for robot manipulator is proposed. The proposed AIT2FSMC is a combination of interval type-2 fuzzy system and sliding mode control. For resembling a feedback linearization (FL) control law, interval type-2 fuzzy system is designed. For compensating the approximation error between the FL control law and interval type-2 fuzzy system, sliding mode controller is designed, respectively. The tuning algorithms are derived in the sense of Lyapunov stability theorem...
2017: Computational Intelligence and Neuroscience
https://www.readbyqxmd.com/read/28280454/perception-of-time-in-music-in-patients-with-parkinson-s-disease-the-processing-of-musical-syntax-compensates-for-rhythmic-deficits
#19
Daniel Bellinger, Eckart Altenmüller, Jens Volkmann
Objective: Perception of time as well as rhythm in musical structures rely on complex brain mechanisms and require an extended network of multiple neural sources. They are therefore sensitive to impairment. Several psychophysical studies have shown that patients with Parkinson's disease (PD) have deficits in perceiving time and rhythms due to a malfunction of the basal ganglia (BG) network. Method: In this study we investigated the time perception of PD patients during music perception by assessing their just noticeable difference (JND) in the time perception of a complex musical Gestalt...
2017: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/28279828/intelligent-evaluation-of-color-sensory-quality-of-black-tea-by-visible-near-infrared-spectroscopy-technology-a-comparison-of-spectra-and-color-data-information
#20
Qin Ouyang, Yan Liu, Quansheng Chen, Zhengzhu Zhang, Jiewen Zhao, Zhiming Guo, Hang Gu
Instrumental test of black tea samples instead of human panel test is attracting massive attention recently. This study focused on an investigation of the feasibility for estimation of the color sensory quality of black tea samples using the VIS-NIR spectroscopy technique, comparing the performances of models based on the spectra and color information. In model calibration, the variables were first selected by genetic algorithm (GA); then the nonlinear back propagation-artificial neural network (BPANN) models were established based on the optimal variables...
March 3, 2017: Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
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