ADSORPTION OF HEAVY METAL CATIONS ON KLASON LIGNIN FROM PAULOWNIA ELONGATA AND KRAFT LIGNIN

Lignin produced from two processes, 1. An acid hydrolysis process: sequential acid hydrolysis of Paulownia elongata wood powder (Klason lignin); 2. Kraft pulping process: black liquor (Kraft lignin), were studied for their heavy metal adsorption affinities. Both lignin samples were effective in removing Pb(II), providing the industrial application potential of lignin in treating lead contaminated wastewater. Hot water treatment of woody biomass is a typical biorefinery process that can result in lignin extraction for potential applications. Hot-water treatment was thus evaluated for its impact on the heavy metal adsorption affinities of Klason lignin. It was found hot water treatment can either enhance or weaken the lignin adsorption capacity depending on the severity of the treatment. Samples with long duration of treatment encountered a substantial loss in the adsorption ability. Depolymerization and condensation lignin reaction schemes under acidic and high temperature environment were summarized and applied to explain the affinity changes. The adsorption mechanism was further studied with Kraft lignin. The Pb(II) adsorption affinity of Kraft lignin was found to follow an “S” dependency on the environmental pH, indicating the existence of more than one ion-exchanging functional groups involved in the adsorption process. NMR characterization of Kraft lignin discovered phenolic hydroxyl groups and carboxyl groups as ion-exchanging functional groups. Other chemical structures in Kraft lignin such as aldehyde groups, ketone groups, ether bond, and aromatic rings are also considered as adsorption functional group because of their potential to complex with heavy metal cations. In order to explain the process from a mechanistic point of view, an novel adsorption theory named “1-n cooperative adsorption theory” was proposed which considered the existence of multiple active sites and the interaction of one adsorbate to multiple sites. The derived model evaluated the effect of temperature and pH on the adsorption affinity, which achieved a significant improvement compared to the Langmuir model. The simulation results show the binding affinity towards Pb(II) is significantly higher than Cd(II) and Ni(II). The new theory also has wide application range to other multivalent interactions including adsorption, flocculation, chelation, and filtration

Theory and Design of Spatial Active Noise Control Systems

The concept of spatial active noise control is to use a number of loudspeakers to generate anti-noise sound waves, which would cancel the undesired acoustic noise over a spatial region. The acoustic noise hazards that exist in a variety of situations provide many potential applications for spatial ANC. However, using existing ANC techniques, it is difficult to achieve satisfying noise reduction for a spatial area, especially using a practical hardware setup. Therefore, this thesis explores various aspects of spatial ANC, and seeks to develop algorithms and techniques to promote the performance and feasibility of spatial ANC in real-life applications. We use the spherical harmonic analysis technique as the basis for our research in this work. This technique provides an accurate representation of the spatial noise field, and enables in-depth analysis of the characteristics of the noise field. Incorporating this technique into the design of spatial ANC systems, we developed a series of algorithms and methods that optimizes the spatial ANC systems, towards both improving noise reduction performance and reducing system complexity. Several contributions of this work are: (i) design of compact planar microphone array structures capable of recording 3D spatial sound fields, so that the noise field can be monitored with minimum physical intrusion to the quiet zone, (ii) derivation of a Direct-to-Reverberant Energy Ratio (DRR) estimation algorithm which can be used for evaluating reverberant characteristics of a noisy environment, (iii) propose a few methods to estimate and optimize spatial noise reduction of an ANC system, including a new metric for measuring spatial noise energy level, and (iv) design of an adaptive spatial ANC algorithm incorporating the spherical harmonic analysis technique. The combination of these contributions enables the design of compact, high performing spatial ANC systems for various applications

3D sound field analysis using circular higher-order microphone array

This paper proposes the theory and design of circular higher-order microphone arrays for 3D sound field analysis using spherical harmonics. Through employing the spherical harmonic translation theorem, the local spatial sound fields recorded by each higher-order microphone placed in the circular arrays are combined to form the sound field information of a large global spherical region. The proposed design reduces the number of the required sampling points and the geometrical complexity of microphone arrays. We develop a two-step method to calculate sound field coefficients using the proposed array structure, i) analytically combine local sound field coefficients on each circular array and ii) solve for global sound field coefficients using data from the first step. Simulation and experimental results show that the proposed array is capable of acquiring the full 3D sound field information over a relatively large spherical region with decent accuracy and computational simplicity.This work was supported under the Australian Research Councils Discovery Projects funding scheme (project no. DP140103412)

Estimating the Direct-to-Reverberant Energy Ratio Using a Spherical Harmonics-Based Spatial Correlation Model

The direct-to-reverberant ratio (DRR), which describes the energy ratio between the direct and reverberant component of a soundfield, is an important parameter in many audio applications. In this paper, we present a multichannel algorithm, which utilizes the blind recordings of a spherical microphone array to estimate the DRR of interest. The algorithm is developed based on a spatial correlation model formulated in the spherical harmonics domain. This model expresses the cross correlation matrix of the recorded soundfield coefficients in terms of two spatial correlation matrices, one for direct sound and the other for reverberation. While the direct path arrives from the source, the reverberant path is considered to be a nondiffuse soundfield with varying directional gains. The direct and reverberant sound energies are estimated from the aforementioned spatial correlation model, which then leads to the DRR estimation. The practical feasibility of the proposed algorithm was evaluated using the speech corpus of the acoustic characterization of environments challenge. The experimental results revealed that the proposed method was able to effectively estimate the DRR of a large collection of reverberant speech recordings including various environmental noise types, room types and speakers.DP14010341

A planar microphone array for spatial coherence-based source separation

We proposed a spatial coherence-based PSD estimation and source separation technique in [1] using a 32-channel spherical microphone array. While the proposed spherical microphone-based method exhibited a satisfactory performance in separating multiple sound sources in a reverberant environment, the use of a large number of microphones remains an issue for some practical considerations. In this paper, we investigate an alternative array structure to achieve spatial coherence-based source separation using a planar microphone array. This method is particularly useful in separating a limited number of sound sources in a mixed acoustic scene. The simplified array structure we used here can easily be integrated with many commercial acoustical instruments such as smart home devices to achieve better speech enhancements.This work is supported by Australian Research Council (ARC) Discovery Projects funding scheme (project no. DP140103412

A survey on vulnerability of federated learning: A learning algorithm perspective

Federated Learning (FL) has emerged as a powerful paradigm for training Machine Learning (ML), particularly Deep Learning (DL) models on multiple devices or servers while maintaining data localized at owners’ sites. Without centralizing data, FL holds promise for scenarios where data integrity, privacy and security and are critical. However, this decentralized training process also opens up new avenues for opponents to launch unique attacks, where it has been becoming an urgent need to understand the vulnerabilities and corresponding defense mechanisms from a learning algorithm perspective. This review paper takes a comprehensive look at malicious attacks against FL, categorizing them from new perspectives on attack origins and targets, and providing insights into their methodology and impact. In this survey, we focus on threat models targeting the learning process of FL systems. Based on the source and target of the attack, we categorize existing threat models into four types, Data to Model (D2M), Model to Data (M2D), Model to Model (M2M) and composite attacks. For each attack type, we discuss the defense strategies proposed, highlighting their effectiveness, assumptions and potential areas for improvement. Defense strategies have evolved from using a singular metric to excluding malicious clients, to employing a multifaceted approach examining client models at various phases. In this survey paper, our research indicates that the to-learn data, the learning gradients, and the learned model at different stages all can be manipulated to initiate malicious attacks that range from undermining model performance, reconstructing private local data, and to inserting backdoors. We have also seen these threat are becoming more insidious. While earlier studies typically amplified malicious gradients, recent endeavors subtly alter the least significant weights in local models to bypass defense measures. This literature review provides a holistic understanding of the current FL threat landscape and highlights the importance of developing robust, efficient, and privacy-preserving defenses to ensure the safe and trusted adoption of FL in real-world applications. The categorized bibliography can be found at: https://github.com/Rand2AI/Awesome-Vulnerability-of-Federated-Learning

Direct-to-Reverberant Energy Ratio Estimation Using a First-Order Microphone

The direct-to-reverberant ratio (DRR) is an important characterization of a reverberant environment. This paper presents a novel blind DRR estimation method based on the coherence function between the sound pressure and particle velocity at a point. First, a general expression of coherence function and DRR is derived in the spherical harmonic domain, without imposing assumptions on the reverberation. In this paper, DRR is expressed in terms of the coherence function as well as two parameters that are related to statistical characteristics of the reverberant environment. Then, a method to estimate the values of these two parameters using a microphone system capable of capturing first-order spherical harmonics is proposed, under three assumptions which are more realistic than the diffuse field model. Furthermore, a theoretical analysis on the use of plane wave model for direct path signal and its effect on DRR estimation is presented, and a rule of thumb is provided for determining whether the point source model should be used for the direct path signal. Finally, the ACE challenge dataset is used to validate the proposed DRR estimation method. The results show that the average full band estimation error is within 2 dB, with no clear trend of bias.DP14010341

Spherical harmonics based generalized image source method for simulating room acoustics

Allen and Berkley's image source method (ISM) is proven to be a very useful and popular technique for simulating the acoustic room transfer function (RTF) in reverberant rooms. It is based on the assumption that the source and receiver of interest are both omnidirectional. With the inherent directional nature of practical loudspeakers and the increasing use of directional microphones, the above assumption is often invalid. The main objective of this paper is to generalize the frequency domain ISM in the spherical harmonics domain such that it could simulate the RTF between practical transducers with higher-order directivity. This is achieved by decomposing transducer directivity patterns in terms of spherical harmonics and by applying the concept of image sources in spherical harmonics based propagation patterns. Therefore, from now on, any transducer can be modeled in the spherical harmonics domain with a realistic directivity pattern and incorporated with the proposed method to simulate room acoustics more accurately. We show that the proposed generalization also has an alternate use in terms of enabling RTF simulations for moving point-transducers inside pre-defined source and receiver regions.Thanks to Australian Research Council Linkage Grant funding scheme (Project No. LP160100379)

Surround by Sound: A Review of Spatial Audio Recording and Reproduction

In this article, a systematic overview of various recording and reproduction techniques for spatial audio is presented. While binaural recording and rendering is designed to resemble the human two-ear auditory system and reproduce sounds specifically for a listener’s two ears, soundfield recording and reproduction using a large number of microphones and loudspeakers replicate an acoustic scene within a region. These two fundamentally different types of techniques are discussed in the paper. A recent popular area, multi-zone reproduction, is also briefly reviewed in the paper. The paper is concluded with a discussion of the current state of the field and open problemsThe authors acknowledge National Natural Science Foundation of China (NSFC) No. 61671380 and Australian Research Council Discovery Scheme DE 150100363