Environmental Noise Classification Using Convolutional Neural Networks with Input Transform for Hearing Aids

Hearing aids are essential for people with hearing loss, and noise estimation and classification are some of the most important technologies used in devices. This paper presents an environmental noise classification algorithm for hearing aids that uses convolutional neural networks (CNNs) and image signals transformed from sound signals. The algorithm was developed using the data of ten types of noise acquired from living environments where such noises occur. Spectrogram images transformed from sound data are used as the input of the CNNs after processing of the images by a sharpening mask and median filter. The classification results of the proposed algorithm were compared with those of other noise classification methods. A maximum correct classification accuracy of 99.25% was achieved by the proposed algorithm for a spectrogram time length of 1 s, with the correct classification accuracy decreasing with increasing spectrogram time length up to 8 s. For a spectrogram time length of 8 s and using the sharpening mask and median filter, the classification accuracy was 98.73%, which is comparable with the 98.79% achieved by the conventional method for a time length of 1 s. The proposed hearing aid noise classification algorithm thus offers less computational complexity without compromising on performance

Optical Properties of Crystalline α-Lactose Monohydrate in Terahertz Range

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THz Vibration Spectroscopy of Crystalline α-Lactose Monohydrate

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Relation of R&D expense to turnover and number of listed companies in all industrial fields

In this research, we studied the relation of research and development (R&D) investment to turnover and number of listed companies by using the financial information of publicly listed enterprises in all industrial fields of the world from 2007 to 2015. First of all, the present condition (as of 2017) of number and distribution of publicly listed enterprises was investigated. Secondly, the industrial areas having top 10 average turnovers and R&D expenses during 9 years (2007 ~ 2015) were analyzed by using their descriptive statistics and CAGR values. Finally, the analyses of correlation and linear regression were performed by using average R&D expense (independent variable) and average turnover or the number of listed enterprises (dependent variables). In other words, two models with different combination of independent and dependent variables (Model A: R&D expense and turnover, Model B: R&D expense and number of listed firms) were developed for the statistical analyses. As a result, it was confirmed that both the turnover and the number of listed companies were influenced by the R&D investment because the coefficients of determination for Model A and Model B were 0.686 and 0.612, respectively (both pvalues < 2.2 × 10− 16). From the results of this study, it is expected that the unlisted firms (e.g., start-up companies) can build the basis of their growth and innovation when they invest in R&D higher inducing the increases in (1) turnover and (2) probability of becoming a listed firm. Thus, the financial information of enterprises can be utilized effectively as the quantitative evidence in order to develop the research model and methodology related to their growth and innovation

Terahertz spectroscopy of Alzheimer’s Amyloid Fibrils

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Determination of Freshness of Mackerel (<i>Scomber japonicus</i>) Using Shortwave Infrared Hyperspectral Imaging

Shortwave infrared (SWIR) hyperspectral imaging was applied to classify the freshness of mackerels. Total volatile basic nitrogen (TVB-N) and acid values, as chemical compounds related to the freshness of mackerels, were also analyzed to develop a prediction model of freshness by combining them with hyperspectral data. Fresh mackerels were divided into three groups according to storage periods (0, 24, and 48 h), and hyperspectral data were collected from the eyes and whole body, separately. The optimized classification accuracies were 81.68% using raw data from eyes and 90.14% using body data by multiple scatter correction (MSC) pretreatment. The prediction accuracy of TVB-N was 90.76%, and the acid value was 83.76%. These results indicate that hyperspectral imaging, as a nondestructive method, can be used to verify the freshness of mackerels and predict the chemical compounds related to the freshness

Strong emission of THz radiation from GaAs microstructures on Si

Remarkably strong emission of terahertz radiation from illuminated GaAs microstructures on a Si substrate is reported. The peak–to–peak amplitude of terahertz radiation from the sample is 9 times larger than that of THz radiation from a semi-insulating GaAs wafer. The spectral width of the sample is larger than that of a semi-insulating GaAs wafer; in particular, the spectral amplitude increases at higher frequencies. The presented GaAs microstructures on a Si substrate can be suitable for practical and efficient THz sources required in various THz applications

Observation of convection phenomenon by high-performance transparent heater based on Pt-decorated Ni micromesh

In this study, we report for the first time on the convection phenomenon for the consistent and sensitive detection of target materials (particulate matter (PM) or gases) with a high-performance transparent heater. The high-performance transparent heater, based on Pt-decorated Ni micromesh, was fabricated by a combination of transfer printing process and Pt sputtering. The resulting transparent heater exhibited excellent mechanical durability, adhesion with substrates, flexibility, and heat-generating performance. We monitored the changes in the PM concentration and temperature in an airtight chamber while operating the heater. The temperature in the chamber was increased slightly, and the PM2.5 concentration was increased by approximately 50 times relative to the initial state which PM is deposed in the chamber. We anticipate that our experimental findings will aid in the development and application of heaters for sensors and actuators as well as transparent electrodes and heating devices