Mass Stabilization as a Ground Improvement Method for Soft Peaty

Construction of road embankments or other infrastructures on soft peat is a challenge. The main problems are high compressibility and rather low undrained shear strength of peat. Mass stabilization provides a solution to improve the properties of a peaty subgrade. Mass stabilization is a ground improvement method, where hardened soil mass is created by adding binder into soil and by controlled in situ mixing. Mass stabilization poses an alternative solution for conventional mass replacement or other techniques, which leave peat in place. The chapter deals with mass stabilization of soft peat soil. Specific attention is paid to design, research and construction considerations, and experience obtained during last three decades. Peat properties before and after stabilization, design methods including pre-testing, stabilization technique and machinery, quality control methods and practices, binder technology, long-term performance of mass stabilized peat, environmental effects, feasibility, applications, and limitations are all presented and discussed in this chapter. The long-term observations (during the last 25 years) have shown that the strength of stabilized peat has continued to increase in average 1.6 times from the strength of 30 days. Therefore, mass stabilization has proven to be a flexible ground improvement method for peat layers with maximum thickness of 8 m

Deep Learning Case Study for Automatic Bird Identification

An automatic bird identification system is required for offshore wind farms in Finland. Indubitably, a radar is the obvious choice to detect flying birds, but external information is required for actual identification. We applied visual camera images as external data. The proposed system for automatic bird identification consists of a radar, a motorized video head and a single-lens reflex camera with a telephoto lens. A convolutional neural network trained with a deep learning algorithm is applied to the image classification. We also propose a data augmentation method in which images are rotated and converted in accordance with the desired color temperatures. The final identification is based on a fusion of parameters provided by the radar and the predictions of the image classifier. The sensitivity of this proposed system, on a dataset containing 9312 manually taken original images resulting in 2.44 × 106 augmented data set, is 0.9463 as an image classifier. The area under receiver operating characteristic curve for two key bird species is 0.9993 (the White-tailed Eagle) and 0.9496 (The Lesser Black-backed Gull), respectively. We proposed a novel system for automatic bird identification as a real world application. We demonstrated that our data augmentation method is suitable for image classification problem and it significantly increases the performance of the classifier

Wavelets in Recognition of Bird Sounds

This paper presents a novel method to recognize inharmonic and transient bird sounds efficiently. The recognition algorithm consists of feature extraction using wavelet decomposition and recognition using either supervised or unsupervised classifier. The proposed method was tested on sounds of eight bird species of which five species have inharmonic sounds and three reference species have harmonic sounds. Inharmonic sounds are not well matched to the conventional spectral analysis methods, because the spectral domain does not include any visible trajectories that computer can track and identify. Thus, the wavelet analysis was selected due to its ability to preserve both frequency and temporal information, and its ability to analyze signals which contain discontinuities and sharp spikes. The shift invariant feature vectors calculated from the wavelet coefficients were used as inputs of two neural networks: the unsupervised self-organizing map (SOM) and the supervised multilayer perceptron (MLP). The results were encouraging: the SOM network recognized 78% and the MLP network 96% of the test sounds correctly

Hammerstein Model for Speech Coding

<p/> <p>A nonlinear Hammerstein model is proposed for coding speech signals. Using Tsay's nonlinearity test, we first show that the great majority of speech frames contain nonlinearities (over 80% in our test data) when using 20-millisecond speech frames. Frame length correlates with the level of nonlinearity: the longer the frames the higher the percentage of nonlinear frames. Motivated by this result, we present a nonlinear structure using a frame-by-frame adaptive identification of the Hammerstein model parameters for speech coding. Finally, the proposed structure is compared with the LPC coding scheme for three phonemes /a/, /s/, and /k/ by calculating the Akaike information criterion of the corresponding residual signals. The tests show clearly that the residual of the nonlinear model presented in this paper contains significantly less information compared to that of the LPC scheme. The presented method is a potential tool to shape the residual signal in an encode-efficient form in speech coding.</p

3D simulations of deep mixed columns under road embankment

When column stabilisation is meant to function as a ground improvement under an embankment, the design cases to be considered consist of overall stability, compression resistance of the column heads, arching of the embankment on the columns and settlements. This paper focuses on the compression resistance of the columns. The proper geotechnical design of deep mixed (deep stabilised) columns under road embankment requires good estimation of the stress-strain behaviour of the columns and the surrounding soil under the embankment and traffic loading. Earlier Finnish design approaches relied on an even traffic load of 10 kN/m2 on the road surface. The dimensioning methods for column stabilised soil are also based on the idea of an even traffic load. Due to Eurocode recommendations a more realistic scenario is introduced, which remarkably increases the magnitude of the traffic loading. After deriving suitable material properties and stiffness parameters for static and dynamic traffic loading, three-dimensional finite element calculations are performed to achieve better understanding of the mechanical interaction between the embankment, columns and soil under the new loading configuration. Even though more investigations are needed before delivering a final statement, the calculations show that, for the considered case in this paper, the new loading scenario has no relevant consequences on the design compared to the earlier design approach