Soft-Boosted Self-Constructing Neural Fuzzy Inference Network

© 2013 IEEE. This correspondence paper proposes an improved version of the self-constructing neural fuzzy inference network (SONFIN), called soft-boosted SONFIN (SB-SONFIN). The design softly boosts the learning process of the SONFIN in order to decrease the error rate and enhance the learning speed. The SB-SONFIN boosts the learning power of the SONFIN by taking into account the numbers of fuzzy rules and initial weights which are two important parameters of the SONFIN, SB-SONFIN advances the learning process by: 1) initializing the weights with the width of the fuzzy sets rather than just with random values and 2) improving the parameter learning rates with the number of learned fuzzy rules. The effectiveness of the proposed soft boosting scheme is validated on several real world and benchmark datasets. The experimental results show that the SB-SONFIN possesses the capability to outperform other known methods on various datasets

Generating a fuzzy rule-based brain-state-drift detector by riemann-metric-based clustering

© 2017 IEEE. Brain-state drifts could significantly impact on the performance of machine-learning algorithms in brain computer interface (BCI). However, less is understood with regard to how brain transition states influence a model and how it can be represented for a system. Herein we are interested in the hidden information of brain state-drift occurring in both simulated and real-world human-system interaction. This research introduced the Riemann metric to categorize EEG data, and visualized the clustering result so that the distribution of the data can be observable. Moreover, to defeat subjective uncertainty of electroencephalography (EEG) signals, fuzzy theory was employed. In this study, we built a fuzzy rule-based brain-statedrift detector to observe the brain state and imported data from different subjects to testify the performance. The result of the detection is acceptable and shown in this paper. In the future, we expect that brain-state drifting can be connected with human behaviors via the proposed fuzzy rule-based classification. We also will develop a new structure for a fuzzy rule-based brain-statedrift detector to improve the detection accuracy

Automatic age estimation system for face images

Humans are the most important tracking objects in surveillance systems. However, human tracking is not enough to provide the required information for personalized recognition. In this paper, we present a novel and reliable framework for automatic age estimation based on computer vision. It exploits global face features based on the combination of Gabor wavelets and orthogonal locality preserving projections. In addition, the proposed system can extract face aging features automatically in real-time. This means that the proposed system has more potential in applications compared to other semi-automatic systems. The results obtained from this novel approach could provide clearer insight for operators in the field of age estimation to develop real-world applications. © 2012 Lin et al

Effect of fermentation time on the antioxidant activities of tempeh prepared from fermented soybean using Rhizopus oligosporus

[[abstract]]The objective of this study was to evaluate the effect of fermentation time on the antioxidant activity of tempeh, a fermented product from soybean. Rhizopus oligosporus was used to ferment soybean for 0, 1, 2, 5 and 10 days. Lyophilised tempeh powder was extracted with hexane followed by petroleum ether, ether, 95% ethanol and water. Antioxidant activities of the extracts were evaluated with various models including alpha,alpha-diphenyl-beta-pricryl-hydrazyl (DPPH) and superoxide-scavenging activities, reducing power and inhibitory activity towards lipid peroxidation. The results revealed that tempeh showed greater antioxidant activities than unfermented soybean. On behalf of a DPPH scavenger, water extracts were as good as 95% ethanol extracts. In comparison of superoxide anion-scavenging activity, inhibition of lipid peroxidation and reducing power, 95% ethanol extracts were superior to water extracts. Tempeh fermented with R. oligosporus for 10 days exhibited the highest antioxidant activities than the others

Monetary reward and punishment to response inhibition modulate activation and synchronization within the inhibitory brain network

© 2018 Chikara, Chang, Lu, Lin, Lin and Ko. A reward or punishment can modulate motivation and emotions, which in turn affect cognitive processing. The present simultaneous functional magnetic resonance imaging-electroencephalography study examines neural mechanisms of response inhibition under the influence of a monetary reward or punishment by implementing a modified stop-signal task in a virtual battlefield scenario. The participants were instructed to play as snipers who open fire at a terrorist target but withhold shooting in the presence of a hostage. The participants performed the task under three different feedback conditions in counterbalanced order: a reward condition where each successfully withheld response added a bonus (i.e., positive feedback) to the startup credit, a punishment condition where each failure in stopping deduced a penalty (i.e., negative feedback), and a no-feedback condition where response outcome had no consequences and served as a control setting. Behaviorally both reward and punishment conditions led to significantly down-regulated inhibitory function in terms of the critical stop-signal delay. As for the neuroimaging results, increased activities were found for the no-feedback condition in regions previously reported to be associated with response inhibition, including the right inferior frontal gyrus and the pre-supplementary motor area. Moreover, higher activation of the lingual gyrus, posterior cingulate gyrus (PCG) and inferior parietal lobule were found in the reward condition, while stronger activation of the precuneus gyrus was found in the punishment condition. The positive feedback was also associated with stronger changes of delta, theta, and alpha synchronization in the PCG than were the negative or no-feedback conditions. These findings depicted the intertwining relationship between response inhibition and motivation networks

New flexible silicone-based EEG dry sensor material compositions exhibiting improvements in lifespan, conductivity, and reliability

© 2016 by the authors; licensee MDPI, Basel, Switzerland. This study investigates alternative material compositions for flexible silicone-based dry electroencephalography (EEG) electrodes to improve the performance lifespan while maintaining high-fidelity transmission of EEG signals. Electrode materials were fabricated with varying concentrations of silver-coated silica and silver flakes to evaluate their electrical, mechanical, and EEG transmission performance. Scanning electron microscope (SEM) analysis of the initial electrode development identified some weak points in the sensors’ construction, including particle pull-out and ablation of the silver coating on the silica filler. The newly-developed sensor materials achieved significant improvement in EEG measurements while maintaining the advantages of previous silicone-based electrodes, including flexibility and non-toxicity. The experimental results indicated that the proposed electrodes maintained suitable performance even after exposure to temperature fluctuations, 85% relative humidity, and enhanced corrosion conditions demonstrating improvements in the environmental stability. Fabricated flat (forehead) and acicular (hairy sites) electrodes composed of the optimum identified formulation exhibited low impedance and reliable EEG measurement; some initial human experiments demonstrate the feasibility of using these silicone-based electrodes for typical lab data collection applications

Online video streaming for human tracking based on weighted resampling particle filter

© 2018 The Authors. Published by Elsevier Ltd. This paper proposes a weighted resampling method for particle filter which is applied for human tracking on active camera. The proposed system consists of three major parts which are human detection, human tracking, and camera control. The codebook matching algorithm is used for extracting human region in human detection system, and the particle filter algorithm estimates the position of the human in every input image. The proposed system in this paper selects the particles with highly weighted value in resampling, because it provides higher accurate tracking features. Moreover, a proportional-integral-derivative controller (PID controller) controls the active camera by minimizing difference between center of image and the position of object obtained from particle filter. The proposed system also converts the position difference into pan-tilt speed to drive the active camera and keep the human in the field of view (FOV) camera. The intensity of image changes overtime while tracking human therefore the proposed system uses the Gaussian mixture model (GMM) to update the human feature model. As regards, the temporal occlusion problem is solved by feature similarity and the resampling particles. Also, the particle filter estimates the position of human in every input frames, thus the active camera drives smoothly. The robustness of the accurate tracking of the proposed system can be seen in the experimental results

Study on the Micro-structures of Long Fiber through Runner and Cavity in Injection Molding for Reinforced Thermoplastics (FRT)

[[abstract]]Lightweight technology has been applied into many industries especially for automotive to enhance the fuel efficiency. One of most famous methods is applied fiber-reinforced thermoplastics (FRT) technology, it includes short and long fiber-reinforced thermoplastics (FRT) to support lightweight technology. However, the enhancement mechanism by the microstructures of the fibers in FRT is still too complicated to understand. In this study, we designed a benchmark to study the fiber microstructures based on ASTM D638 with dog-bond system. First, we have tried to study how the geometry of cavity influences the fiber orientation during the injection processes. Furthermore, we have paid the attention on the variation of the fiber length distribution as the injection molding processing. Results show that the geometry of cavity has significant effect on the fiber orientation during the injection processes. Since the system has contraction and expansion structure, the orientation tensor component a11 corresponding to the flow direction, will be enhanced and then decreased along the cavity. Moreover, the fiber lengths have dramatically sharp distribution on skin layer when melt goes through the gate into the cavity. It will allow almost 90% lengths are broken through the skin layer. Meanwhile, using numerical visualization from runner to cavity through core layer, there is about 30% length broken during the journey in runner section. Finally, some fiber orientation results are compared with some literature’s. Results showed that our numerical predictions are matched with that of literature quite well in the trend.[[notice]]補正完

Inactivation of myosin binding protein C homolog in zebrafish as a model for human cardiac hypertrophy and diastolic dysfunction

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Synthesis of single-walled carbon nanotubes in rich hydrogen/air flames

© 2020 Elsevier B.V. We explore the production of single-walled carbon nanotubes (CNTs) in a stream surrounded by rich premixed laminar H2/air flames using a feedstock containing ethanol and ferrocene. The as-produced nanomaterials were characterised by Raman spectroscopy, transmission electron microscopy, scanning electron microscopy and X-ray diffraction. A formation window of equivalence ratios of 1.00–1.20 was identified, and single-walled CNT bundles with individual CNTs of an average diameter of 1 nm were observed. The formation of CNTs was accompanied by the production of highly crystalline Fe3O4 nanoparticles of a size of 20–100 nm. The investigation of the limiting factors for the CNT synthesis was carried out systematically, assisted by numerical modelling. We conclude that the key factors affecting CNT synthesis are the surrounding flame temperatures, and the concentration of carbon available for CNT nucleation.EPSRC (ANAM