5aEA2 – What Does Your Signature Sound Like?

Daichi Asakura – asakura@pa.info.mie-u.ac.jp
Mie University
Tsu, Mie, Japan

Popular version of poster, 5aEA2. “Writer recognition with a sound in hand-writing”
172nd ASA Meeting, Honolulu

We can notice a car approaching by noise it makes on the road or can recognize a person by the sound of their footsteps. There are many studies analyzing and recognizing these noises. In the computer security industry, studies have even been proposed to estimate what is being typed from the sound of typing on the keyboard [1] and extracting RSA keys through noises made by a PC [2].

Of course, there is a relationship between a noise and its cause and that noise, therefore, contains information. The sound of a person writing, or “hand writing sound,” is one of the noises in our everyday environment. Previous studies have addressed the recognition of handwritten numeric characters by using the resulting sound, finding an average recognition of 88.4%. Based on this study, we seek the possibility of recognizing and identifying a writer by using the sound of their handwriting. If accurate identification is possible, it could become a method of signature verification without having to ever look at the signature.

We used the handwriting sounds of nine participants, conducting recognition experiments. We asked them to write the same text, which were names in Kanji, the Chinese characters, under several different conditions, such as writing slowly or writing on a different day. Figure 1 shows an example of a spectrogram of the hand-writing sound we analyzed. The bottom axis represents time and the vertical axis shows frequency. Colors represent the magnitude – or intensity – of the frequencies, where red indicates high intensity and blue is low.
handwriting

The spectrogram showed features corresponding to the number of strokes in the Kanji. We used a recognition system based on a hidden Markov model (HMM) – typically used for speech recognition –, which represents transitions of spectral patterns as they evolve in time. The results showed an average identification rate of 66.3%, indicating that writer identification is possible in this manner. However, the identification rate decreased under certain conditions, especially a slow writing speed.

To improve performances, we need to increase the number of hand writing samples and include various written texts as well as participants. We also intend to include writing of English characters and numbers. We expect that Deep Learning, which is attracting increasing attention around the world, will also help us achieve a higher recognition rate in future experiments.

 

  1. Zhuang, L., Zhou, F., and Tygar, J. D., Keyboard Acoustic Emanations Revisited, ACM Transactions on Information and Systems Security, 2009, vol.13, no.1, article 3, pp.1-26.
  2. Genkin, D., Shamir, A., and Tromer, E., RSA Key Extraction via Low-Bandwidth Acoustic Cryptanalysis, Proceedings of CRYPTO 2014, 2014, pp.444-461.
  3. Kitano, S., Nishino, T. and Naruse, H., Handwritten digit recognition from writing sound using HMM, 2013, Technical Report of the Institute of Electronics, Information and Communication Engineers, vol.113, no.346, pp.121-125.

2aEAa5 – Miniature Directional Sound Sensor Inspired by Fly’s Ears

Daniel Wilmott – dwilmott@nps.edu
Fabio Alves – fdalves@nps.edu
Gamani Karunasiri – karunasiri@nps.edu

Department of Physics
Naval Postgraduate School
Monterey, CA 93943

Popular version of paper 2aEAa
Presented Tuesday morning, November 3, 2015
170th ASA Meeting, Jacksonville

Humans and animals that posses a relatively large separation between ears, compared to the wavelength of sound, utilize the delay of sound arrival between ears to sense its direction with relatively good accuracy.  This approach is less effective when the separation between ears is small, such as in insects.  However, the parasitic Ormia Ochracea fly is particularly adept at finding crickets by listening to their chirps, though the separation of their ears is much smaller than the wavelengths generated by the chirps. The female of this species seek out chirping crickets (see Fig. 1) to lay their eggs on, and do so with an accuracy of few degrees. The two eardrums of the fly are separated by a mere 1.5 millimeters (mm) yet it homes in on the cricket chirping with 50 times longer wavelength where the arrival time difference between ears is only a few millionths of a second.  It is interesting to note that Zuk and coworkers found that “between the late 1990s and 2003, in just 20 or so cricket generations, Kauai’s cricket population had evolved into an almost entirely silent one” to avoid detection by the flies.  The studies carried out on the fly’s hearing organ by Miles and coworkers in the mid-90s found that workings of the fly ears are different from that of the large species and are mechanically coupled at the middle and tuned to the cricket chirps giving them remarkable ability locate them.

1 - Ormia Ochracea fly

Figure 1. Ormia Ochracea uses direction finding ears to locate crickets.

In this paper, we present a miniature directional sensor that was designed based on the fly’s ears, which consists of two wings connected in the middle using a bridge and fabricated using micro-electro-mechanical-system (MEMS) technology as shown in Fig. 2.  The sensor is made of the same material used in making microchips (silicon) with the two wings having dimensions 1 mm x 1 mm each and thickness of less than half the width of human hair (25 micrometers).  The sensor is tuned to a narrow frequency range, which depends on the size of the bridge that connects the two wings.  The vibration amplitudes of the sensor wings (less than one millionth of a meter) under sound excitation was electronically probed using highly sensitive comb finger capacitors (similar to tuning capacitors employed in older radios) attached to the edges of the wings.  It was found that the response of the sensor is highly directional (see Fig. 3) and matches well with the expected behavior.

2

Figure 2. Designed (left) and fabricated (right) directional sound sensor showing the comb finger capacitors for electronically measuring nanometer scale vibrations generated by incident sound.  The size of the entire sensor is less than that of a pea.
3

Figure 3. Measured directional response of the sensor tuned to 1.67 kHz for a set of sound pressures down to 33 dB.

The sensor was able to detect sound levels close to that of a quite whisper 30 decibel (dB) which is thousand times smaller than the sound level generated in a typical conversation (60 dB).  The sensor has many potential civilian and military applications involving localization of sound sources including explosions and gunshots.

4aEA2 – How soon can you use your new concrete driveway?

Jinying Zhu: jyzhu@unl.edu
Department of Civil Engineering
University of Nebraska-Lincoln
1110 S 67th St., Omaha, NE 68182, USA

Popular version of paper 4aEA2, “Monitoring hardening of concrete using ultrasonic guided waves” Presented Thursday morning, Nov. 5, 2015, 8:50 AM, ORLANDO room,
170th ASA Meeting, Jacksonville, FL

Concrete is the most commonly used construction material in the world. The performance of concrete structures is largely determined by properties of fresh concrete at early ages. Concrete gains strength through a chemical reaction between water and cement (hydration), which gradually change a fluid fresh concrete mix to a rigid and hard solid. The process is called setting and hardening.  It is important to measure the setting times, because you may not have enough time to mix and place concrete if the setting time is too early, while too late setting will cause delay in strength gain.  The setting and hardening process is affected by many parameters, including water and cement ratio, temperature, and chemical admixtures.  The standard method to test setting time is to measure penetration resistance of fresh concrete samples in laboratory, which may not represent the real condition in field.

Zhu1 - concrete

Figure. 1 Principle of ultrasonic guided wave test.

Ultrasonic waves have been proposed to monitor the setting and hardening process of concrete by measuring wave velocity change. When concrete becomes hard, the stiffness increases, and the ultrasonic velocity also increases. The authors found there is a clear relationship between the shear wave velocity and the traditional penetration resistance. However, most ultrasonic tests measure a small volume of concrete sample in laboratory, and they are not suitable for field application. In this paper, the authors proposed an ultrasonic guided wave test method. Steel reinforcements (rebars) are used in most concrete structures. When ultrasonic guided waves propagate within rebar, they leak energy to surrounding concrete, and the energy leakage rate is proportion to the stiffness of concrete.  Ultrasonic waves can be introduced into rebars from one end and the echo signal will be received at the same end using the same ultrasonic sensor.  This test method has a simple test setup, and is able to monitor the concrete hardening process continuously.

zhu2 - concrete Zhu3 - concrete
Figure. 2 Ultrasonic echo signals measured in an embedded rebar for concrete age of 2~6 hours. Figure. 3 Guided wave attenuation rate in a rebar embedded in different cement pastes.

Figure 2 shows guided wave echo signals measured on a 19mm diameter rebar embedded in concrete. It is clear that the signal amplitude decreases with the age of concrete (2 ~ 6 hours). The attenuation can be plotted vs. age for different cement/concrete mixes. Figure 3 shows the attenuation curves for 3 cement paste mixes. It is known that a cement mix with larger water cement ratio (w/c) will have slower strength gain, which agrees with the ultrasonic guided wave test, where the w/c=0.5 mix has lower attenuation rate.  When there is a void around the rebar, energy leakage will be less than the case without a void, which is also confirmed by the test result in Figure 3.

Summary: This study presents experimental results using ultrasonic guided waves to monitor concrete setting and hardening process. It shows the guided wave leakage attenuation is proportional to the stiffness change of fresh concrete. Therefore the leakage rate can be used to monitor the concrete strength gain at early ages. This study may have broader applications in other disciplines to measure mechanical property of material using guided wave.

4aEA10 – Preliminary evaluation of the sound absorption coefficient of a thin coconut coir fiber panel for automotive applications

Key F. Lima – keyflima@gmail.com
Pontifical Catholic University of Paraná
Curitiba, Paraná, Brazil

Popular version of paper 4aEA10, “Preliminary evaluation of the sound absorption coefficient of a thin coconut fiber panel for automotive applications”
Presented Thursday morning, November 5, 2015, 11:15 AM, Orlando Room
170th ASA Meeting, Jacksonville, Fl

Absorbents materials are fibrous or porous and must have the property of being good acoustic dissipaters. Sound propagation causes multiples reflections and friction of the air present in the absorbent medium converting sound energy to thermal energy. The acoustic surface treatment with absorbent material are widely used to reduce the reverberation in enclosed spaces or to increase the sound transmission loss of acoustics panels. In addition, these materials can be applied into acoustics filters with the purpose to increase their efficiencies. The sound absorption depends on the excitation frequency of the sound and it is more effective at high frequencies. Natural fibers such as coconut coir fiber have a great potential to be used like sound absorbent material. As natural fibers are agriculture waste, manufacturing this fiber is a natural product, therefore an economic and interesting option. This work compares the sound absorption coefficient between a thin coconut fiber panel and a composite panel made by fiberglass and expanded polyurethane foam, no-woven woven, and polyester woven, which are used in the automotive industry as a roof trim. The evaluation of sound absorption coefficient was carried out with the impedance tube technique.

In 1980, Chung and Blaser evaluated the normal incidence sound absorption coefficient through transfer function method.  The standard ASTM E1050-10 and ISO 10534-2 was based in Chung and Blaser’s method, Figure 1. In summary, this method uses an impedance tube with the sound source placed to one end and at another, the absorbent material backed in a rigid wall. The decomposition of the stationary sound wave pattern into forward and backward traveling components is achieved by measuring sound pressures. This evaluating is carried out simultaneously at two spaced locations in the tube’s sidewall where two microphones are located, Figure 1.

Impedance Tube Fig1

Figure 1. Impedance Tube

The wave decomposition allows to the determination of the complex reflection coefficient R(f) from which the complex acoustic impedance and the normal incidence sound absorption coefficient (a) of an absorbent material can be determined. Furthermore, the two coefficients R(f) and a are calculated by Transfer Function H12 between the two microphones through:fig1, where s is the distance between the microphones, x1 is the distance between the farthest microphone and the sample, i is the imaginary unity and k0 is the wave number of the air. If R(f) is known, the coefficient a is easily obtained by expression:fig2.

In this work, eight samples of coconut fiber and eight samples of composite panel made by fiberglass and expanded polyurethane foam, no-woven woven, and polyester woven used in the automotive industry, Figure 2 and 3. The material properties are shown in Table 1.

Sample Fig2 - coconut coir fiber

Figure 2. Samples

Composite Panel Fig3 - coconut coir fiber

Figure 3. Composite panel structure.

Table 1. Material Properties.
Coconut Fiber Composite Panel
Sample

diameter

[mm]

thickness

[mm]

mass

[g]

density

[kg/m3]

 Sample

diameter

[mm]

thickness

[mm]

mass

[g]

density

[kg/m3]
1 28,25 5,17 0,67 649,5 1 28,05 5,78 0,41 360,6
2 28,20 5,04 0,62 618,8 2 28,08 5,66 0,42 376,6
3 28,20 4,93 0,60 612,6 3 28,15 5,59 0,42 379,6
4 28,35 5,09 0,69 674,7 4 28,23 5,54 0,44 398,8
5 100,43 4,98 8,89 708,0 5 99,55 5,86 5,40 371,9
6 100,43 4,84 9,73 797,7 6 99,55 6,20 5,54 360,9
7 100,73 5,34 9,64 712,1 7 99,68 6,06 5,57 370,4
8 100,45 4,79 9,13 755,2 8 99,55 5,99 5,62 378,9

The random noise signal with frequency band between 200 Hz and 5000 Hz was utilized to evaluate a.  The Figure 4 shows the mean normal incidence absorption coefficient obtained from the measurements.

Comparison absorption coeff Fig4

Figure 4. Comparison of normal absorption coefficient (a)

The results shows that the composite panel have a better sound absorption coefficient than coconut fiber panel. To improve the coconut fiber panel acoustical efficiency it is needed to add some filling material with the same effect of the polyurethane foam of the composite panel.

REFERENCES
Chung, J. Y. and Blaser D. A. (1980) “ Transfer function method of measuring  in-duct acoustic properties – I Theory,” J. Acoust. Soc. Am. 68, 907-913.

Chung, J. Y. and Blaser D. A. (1980) “ Transfer function method of measuring  in-duct acoustic properties – II Experiment,” J. Acoust. Soc. Am. 68, 913-921.

ASTM E1050:2012. “Standard test method for impedance and absorption of acoustical materials using a tube, two microphones and a digital frequency analysis system,” American Society for Testing and Materials, Philadelphia, PA, 2012.

ISO 10534-2:1998. “Determination of sound absorption coefficient and impedance in impedance tubes – Part 2: Transfer-function method”, International Organization for Standardization, Geneva, 1998.

4pEA4 – “See” subsurface soils using surface waves

Zhiqu Lu – zhiqulu@olemiss.edu
National Center for Physical Acoustics, The University of Mississippi,
1 Chucky Mullins,
University, MS, 38677

Lay language paper for 4pEA4
Presented Thursday afternoon, November 5, 2015
170th ASA Meeting, Jacksonville

Within a few meters beneath the earth surface, three distinctive soil layers are formed: a top dry and hard layer, a middle moist and soft region, and a deeper zone where the mechanical strength of the soil increases with depth.  The information of this subsurface soil is required for agricultural, environmental, civil engineering, and military applications. A seismic surface wave method has been recently developed to non-invasively obtain such information (Lu, 2014; Lu, 2015).  The method, known as the multichannel analysis of surface wave method (MASW) (Park, et al., 1999; Xia, et al., 1999), consists of three essential parts: surface wave generation and collection (Figure 1), spectrum analysis, and inversion process. The implement of the technique employs sophisticated sensor technology, wave propagation modeling, and inversion algorithm.

Lu1

Figure 1. The experimental setup for the MASW method

The technique makes use of the characteristic of one type of surface waves, the so-called Rayleigh waves that travel along the earth’s surface within a depth of one and a half wavelengths. Therefore the components of surface waves with short wavelength contain information of shallow soil, whereas the longer wavelength surface waves provide the properties of deep soil (Figure 2).

Lu2

Figure 2. Rayleigh wave propagation

The outcome of the MASW method is a soil vertical profile, i.e., the acoustic shear (S) wave velocity as a function of depth (Figure 3).

Lu3 - soil profile

Figure 3. A typical soil profile

By repeating the MASW measurements either spatially or temporarily, one can measure and “see” the spatial and temporal variations of the subsurface soils. Figure 4 shows a typical vertical cross-section image in which the intensity of the image represents the value of the shear wave velocity. From this image, three different layers mentioned above are identified.

Lu4 - soil vertical cross-section

Figure 4. A typical example of soil vertical cross-section image

Lu5

Figure 5. A vertical cross-section image showing the presence of a fragipan layer

Figure 5 displays another two-dimensional image in which a middle high velocity zone (red area) appears. This high velocity zone represents a geological anomaly, known as a fragipan, a naturally occurring dense and hard soil layer (Lu, et al., 2014). The detection of fragipan is important in agricultural land managements.

The MASW method can also be applied to monitor weather influence on soil properties (Lu 2014). Figure 6 shows the temporal variations of the underground soil.  This is a result of a long term survey conducted in 2012.  By drawing a vertical line and moving it from left side to right side, i.e., along the time index number axis, the evolution of the soil profile due to weather effects can be evaluated. In particular, the high velocity zones occurred in the summer of 2012, reflecting very dry soil conditions.

Lu6

Figure 6. The  temporal variations of soil profile due to weather effects

Lu,  Z., 2014.  Feasibility of using a seismic surface wave method to study seasonal and weather effects on shallow surface soils. Journal of Environmental & Engineering Geophysics, DOI: 10.2113/JEEG19.2.71, Vol.19, 71–85.

Lu, Z. 2015. Self-adaptive method for high frequency multi-channel analysis of surface wave method, Journal of Applied Geophysics, Vol. 121, 128-139. http://dx.doi.org/10.1016/j.jappgeo.2015.08.003

Lu, Z., Wilson, G.V., Hickey, C.J., 2014. Imaging a soil fragipan using a high-frequency MASW method. In Proceedings of the Symposium on the Application of Geophysics to Engineering and Environmental Problems (SAGEEP 2014), Boston, MA., Mar. 16-20.

Park, C.B., Miller, R.D., Xia, J., 1999. Multichannel analysis of surface waves. Geophysics, Vol. 64, 800-808.

Xia, J., Miller, R.D., Park, C.B., 1999. Estimation of near-surface shear-wave velocity by inversion of Rayleigh waves. Geophysics, Vol. 64, 691-700.