**Acknowledgements**

The results given in this chapter were conducted under two projects: Transformation of Wood Biomass Ash into Resilient Construction Composites-TAREC2 (IP-2016-06-7701) funded by the Croatian Science Foundation and the project Development of innovative construction products with biomass ash financed by European structural and investment funds for a 2014–2020 financial period (grant number KK.<IP_ADDRESS>.0049).


4.3.1. Groundwater Chemistry Control Mechanisms

A Gibbs plot can be used to illustrate the causal mechanism of water chemical composition [41]. In the Gibbs plot, if the TDS value is high and the Na+/(Na++Ca2+) or Cl−/(Cl−+HCO3 −) ratio is close to 1, the ion control mechanism is evaporative crystallization. If the TDS value is medium and the Na+/(Na++Ca2+) or Cl−/(Cl−+HCO3 −) ratio is less than 0.5, the ion control mechanism is water rock effect. If TDS value is low and the Na+/(Na++Ca2+) or Cl−/(Cl−+HCO3 −) ratio is close to 1, the water chemistry component control mechanism is the rainfall effect [42,43]. From the Figure 6, it can be seen that the chemical composition of groundwater in the study area is mainly dominated by water–rock action.

**Figure 6.** Gibbs diagrams showing the groundwater chemistry controlling mechanisms.


**2.1. Study area description**

The study was conducted in the adjacent communities of the THWS, located in the Lebialemhighlands, Southwest Region of Cameroon (**Figure 1**). The THWS is located specifically between 5037′ and 5042′ latitude and 9053′–9058′ longitude covers approximately 15,000 ha. The area ranges from 230 to 2400 m above sea level. This forest area range is known to contain 84% of African primates, 64% of African passerine birds and 66% of known African butterflies [19]. The THWS forest is home to 26 species of large mammals including some of Africa's most threatened primates species; the critically endangered Cross River gorilla (*G. gorilla diehli*) and the endangered Nigeria-Cameroon chimpanzee (*Pan troglodytes vellerosus*) [20]. The forest equally harbours endemic birds including the Bannerman's turaco, Banded-wattled eye, Bangwa forest warbler and the Bannerman's weaver as well as many endemic plants [21]. The THWS is surrounded by 10 main communities (Fossimondi, M'mock mbin, Bamumbu, Folepi, Bechati, Banti, Igumbo, Besali, Bangang and Nkong). The population of the THWS is estimated to be about 7000 inhabitant [22].


**4.4 Bone**

An aging population and the use of bone grafts to augment bone for repair and regeneration, have led to an increasing demand of functional bone grafts. The current gold standard of treatment involves autologous bone retrieved from the patients' iliac crest, however this requires multiple surgery sites, is expensive to perform and increases the associated risks involved with a second surgery site [58]. Therefore an alternative solution, such as the development of bioprinted bone grafts, presents an attractive alternative.

Using SLA, stem cells derived from mouse bone marrow stromal cells (OP-9 cells) were embedded in crosslinked PEGDA hydrogels [59]. After 24 h, the cells remained viable and subsequent seeding of mouse mesenchymal stem cells (mMSCs) onto the scaffold showed intensive mineralization.

Catros et al. used LAB to position osteosarcoma cells (MG63) onto poly(caprolactone) (PCL) scaffolds [60]. Cells were printed either between layers of electrospun PCL or only as a final layer. *In vitro* testing initially showed no difference in proliferation rate between the two groups, however, after 14 days, the scaffolds that included printed cells between layers of PCL exhibited a significantly higher proliferation rate. When implanted in calvarial defects in mice, significant bone tissue ingrowth was observed that had an organized structure. Extruded PCL scaffolds containing decellularized bone matrix and human adipose-derived stem cells (hASCs) used for craniofacial regeneration in mice, showed improved bone regeneration in comparison to a pure PCL scaffold [61].

Using a bioink consisting of either a matrigel or matrigel and alginate, endothelial progenitor cells (EPCs) and multipotent stromal cells (MSCs) were extruded into bone tissue scaffolds [62]. Implanted into subcutaneous dorsal pockets of mice, the scaffolds without the inclusion of alginate performed better, as they developed a bone-like tissue structure.

Zhou et al. employed a table-top stereolithographic printer to create biomimetic bone matrices to study metastasis of bone cancer in bone tissue [63], as shown in **Figure 4**. Scaffolds containing osteoblasts and hMSCs suspended in hydrogels containing different concentrations of GelMA and nanocrystalline hydroxyapatite, were subsequently seeded with breast cancer cells (BrCas). Placed in cell culture, osteoblast proliferation rates were observed to decrease, while BrCas proliferation rates increased. Interactions between the cell types within the bioprinted model led to the conclusion that the osteoblasts and MSCs secrete macromolecules that promote BrCas growth.


Data represent means and %CV of 6 mice per group; \* *p* < 0.05 versus control.

The IELs subpopulation percentages in jejunum (panel A) and colon (panel B) of mice fed control, wheat bread or wheat–lentil bread diets are presented in Figure 1. Histograms show a significant increase of cytotoxic T cell (CD3+CD8+) percentages in the jejunum of mice fed both types of bread compared to the control diet, whereas the percentage of total T cells (CD3+CD45+) were reduced in mice fed wheat bread compared to control and wheat–lentil bread. In the colon, only a significant increase of B cell (CD19+CD45+) percentages was observed in mice fed wheat–lentil bread. No differences in the percentages of other lymphocyte subpopulations were observed among the groups.

**Figure 1.** Intraepithelial lymphocyte (IEL) subpopulations in the jejunum (**A**) and colon (**B**) of mice fed a control, a wheat bread and a wheat–lentil diet measured by flow cytometry. (The percentage of B and T lymphocytes was calculated on leukocyte (CD45+) gate, whereas the CD4+, CD8+ and CD4+CD8+ subsets, as well as αβ and γδ lymphocytes, were calculated on T lymphocyte (CD3+) gate). Data represent the means ± SD of 6 mice. \* *p* < 0.05 versus control.

Western blot analysis of the phosphorylated form of the p65 subunit of NF-kB in the jejunum and colon of mice did not show any significant difference among groups, indicating that the treatment with wheat and wheat–lentil bread did not induce an inflammatory status in the mice intestine (data not shown).

#### **4. Discussion**

As expected, the proximate composition of the wheat and the wheat–lentil bread mirrored the proximate composition of the flours of origin (see the Materials and Methods section and Table 1). In fact, the wheat–lentil bread contained 30% more proteins than wheat bread, it had an almost double ash content, therefore a higher level of minerals in general, together with an almost double amount of total dietary fibre, especially the insoluble component. Moreover, the lentil–wheat bread contained a lower amount of available carbohydrates than wheat bread.

Besides having a higher protein content, wheat–lentil bread had a more balanced amino acid profile than wheat bread (Table 2). Indeed, the amino acid profiles of wheat and lentils are complementary. For example, lysine is abundant in lentils, whereas sulphur amino acids are present in higher amounts in wheat. Lentil proteins are, in fact, mainly constituted by globulins and albumins [40] and, thus, have a different composition from wheat proteins, which are mainly constituted of prolamins and glutelins. The presence of the lentil flour increases the level of almost all the essential amino acids in bread (Table 2).

The lower amount of available carbohydrates in wheat–lentil bread is due to the fact that lentils contain less starch than wheat (about 40–45%, [18]); it is also reported that legume starch has a higher fraction of amylose than wheat (about 35%, [41]).

Regarding dietary fibre, both wheat and wheat–lentil breads contain only a small amount of the soluble component, around 1%; however, the soluble fibre of lentils is reported to contain beta glucans [18]. Beta-glucans are very interesting from a functional point of view, because they are known to induce a variety of physiological effects with a positive impact on health, acting in particular through immunomodulatory pathways, that can suppress cancer proliferation, lower cholesterol levels and thus reduce the risk for cardiovascular disease [42,43].

The wheat–lentil bread was richer in phenolic substances, in particular those present in the aqueous organic extract, than wheat bread and this is the reason why it also had better antioxidant properties (Table 3). The soluble free phenolics found in the extract come mainly from cellular vacuoles whereas the insoluble phenolics present in the residue are bound to other components mainly fibre. The hydrolysable bound phenols represent the main polyphenol fraction in both bread types (between 73% and 87% of TPC). The literature reports that significant amounts of phenolic compounds remain in the extraction residues, associated with the food matrix [44]. The phenolic molecules most frequently found in cereals are phenolic acids and flavonoids whereas in pulses we also find tannins [45]. Polyphenols in general, both the free and the bound ones, thanks to their antioxidant properties are considered to exert a protective effect on human health [46].

The lignans, secoisolariciresinol and isolariciresinol, were found in both breads (Table 3). However, the wheat–lentil bread not only contained higher amounts of these lignans, but also had additional lignan types and, in particular, lariciresinol and pinoresinol in the following order: Isolariciresinol > lariciresinol > pinoresinol > secoisolariciresinol. These results are in agreement with data on lignan content in legume flours reported by Durazzo et al. [30]. Literature data indicate flaxseed and sesame as major alimentary sources of lignans and rye and lentils as good sources [30,47]. Lignans are a large group of polyphenols of increasing interest because their intake has been related to beneficial health effects, including cancer and cardiovascular disease prevention [48]. In this regard it is interesting to report that in 2012 the research group of During et al. [49] published a paper to report on their investigation of whether plant lignans are taken up by intestinal cells and modulate the intestinal inflammatory response using the Caco-2 cell model. Their findings suggest that plant lignans can be absorbed and metabolised in the small intestine and, among the plants lignans tested, pinoresinol exhibited the strongest anti-inflammatory properties.

The antioxidant power as measured by FRAP was significantly higher in wheat–lentil bread than in wheat bread. The FRAP assay is a quick and sensitive way to measure the antioxidant capacity of biological samples. In both cases, the hydrolysable residue had a higher FRAP value than the aqueous–organic extract thus providing the major contribution to the total antioxidant power (from 69% to 77%); this matches the results of the total polyphenols content. Thus, a bread recipe where about one-quarter of the wheat flour is substituted by red lentil flour more than doubles the antioxidant capacity of bread (Table 3).

Concerning animal experiments, our first consideration was that no significant differences were observed in body weight and food intake among the groups of mice fed the control and the two types of bread diets; this indicates that the different diets had the same palatability for the mice, and that they did not impact on eating behaviour and appetite; and that all the differences observed in our sets of data were due to differences in the composition of the diets.

Analysis of the immune parameters in IELs isolated from jejunum showed an increase of cytotoxic T lymphocytes (CD3+CD8+) percentages in both wheat and wheat–lentil bread-treated animals, as compared to the control. Moreover, total T lymphocytes (CD3+CD45+) were significantly reduced in the wheat bread group and increased in the wheat–lentil bread group, compared to the control (Figure 1A). The IEL subpopulation's analysis in colon showed a significant increase of the B lymphocytes (CD19+CD45+) percentage in lentil bread-treated animals as compared to wheat bread and the control (Figure 1B). In this regard, we could hypothesise a role of the higher amount of β-glucans in the lentil bread while not ignoring that such compounds can increase the percentage of activated B lymphocytes and stimulate immune response [50,51].

We can say that the results of our study indicate a positive effect of wheat–lentil bread supplementation on the intestinal immune system of aged mice, as this supplementation was able to counteract some of the immune alterations typical of the older adults. In fact, aging is characterised by intrinsic changes in hematopoietic precursors that affect their proliferative potential, and this represents a key factor contributing to age-related decline in B- and T-cell production [52]. Thus, the increase of total T lymphocytes indicates a better immune response, and the increase of cytotoxic T lymphocytes suggests an improved capacity to respond to toxic agents and/or pathogens, that is known to be reduced in older adults. We can also hypothesise that the increase of B lymphocytes in the colon indicates a more efficient antibody response. In fact, it is well known that the antibody response is impaired in the older adults [53]. Moreover, it has been largely demonstrated that an antioxidants-containing diet may ameliorate lymphocyte response and protect immune cells from oxidative stress-induced apoptosis [54]. Besides polyphenols in general, the positive effects on the immune system in our specific case could also be ascribed to the significantly higher amount of the lignan isolariciresinol (27 times higher) and the presence of the lignan pinoresinol in wheat–lentil bread compared to wheat bread; these two lignans in particular have been shown to exert immunomodulatory and anti-inflammatory effects [49,55].

No significant differences were observed in the other analysed IELs subpopulations (Figure 1A,B).

Among all the analysed cytokines in serum, only IL-10 was significantly decreased in the wheat and wheat–lentil bread treated animals as compared to the control (Table 6). The role of IL-10 in older adults is controversial; while some studies report that IL-10 increased the inflammatory status, others indicate that this cytokine plays a key role as an anti-inflammatory factor [56,57]. It has also been reported that aging is associated with an increase of IL-10 that, together with other cytokines, could be considered as a marker of frailty [58,59].

#### **5. Conclusions**

It is increasingly coming to general attention that the aging population needs to eat appropriately to prevent and reduce all the health risks associated with this phase of human life. In other words, there is a need for tailored foods for aging people. Enriching staple or widely consumed foods can be a simple strategy to guaranty the intake of key nutrients able to have a beneficial effect on the negative aspects associated with aging such as the decline of the immune function. Based on previous studies done in our laboratory, we identified bread as a target food and red lentil flour as a raw material useful to add functionality to bread. We also identified technological constraints that allowed a maximum addition of 24% lentil flour.

For the purpose of this study, we baked two kinds of bread: A common wheat bread and a wheat–24% lentil flour bread. The chemical analysis of the bread components showed that the wheat–lentil bread had 30% more proteins than wheat bread coupled with a more balanced amino acid composition; it had an almost double mineral as well as total dietary fibre content, especially the insoluble component, double the amount of polyphenols, an interesting lignans content and more than double the antioxidant capacity. Thus, this wheat–lentil bread proved to be nutritionally richer and more functional than common wheat bread.

The in vivo effect of the consumption of wheat–lentil bread versus wheat bread on the immune response was studied by means of a murine model of aged mice. Analysis of the immune parameters in intraepithelial lymphocytes isolated from the mice intestine showed significant differences between the two types of bread indicating a positive effect of the lentil–wheat bread on the intestinal immune system. Cytokines in serum were also analysed. Considering that IL-10 is indicated as a frailty marker, we suppose that wheat and wheat–lentil breads in diets could have a positive effect on inflammatory status and improve the health status of aged mice.

This study clearly demonstrates that this is possible by substituting wheat flour with another suitable flour to manufacture a simple and well-accepted food, such as bread, which shows more functionality and is more tailored for the aging population than traditional, common bread with soft wheat only.

**Author Contributions:** M.C. planned and supervised the research, acquired funds and wrote the final manuscript, V.N. and V.T. performed all the bread analyses but the lignans which were performed by A.D. A.F. and M.R. designed the animal experimental setup and performed the experiments and analysed and interpreted the data. R.R. prepared the experimental diets and took care of the animals.

**Funding:** This research was carried out within the CERSUOM project financed by the Italian Ministry for Agricultural, Alimentary and Forest Policies (MiPAAF).

**Acknowledgments:** Grateful acknowledgements are due to Luigi Bartoli and Francesco Mellara for technical help in the bread preparation.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).


**3.2.1 Virtualization considerations**

6 Will-be-set-by-IN-TECH

VM VM

Physical Server (Host)

(b) Para Virtualization

scheduling, input/output operations, error actions, and similar functions and regulates the flow of work in a data processing system. The supervisor is generally called kernel. The hypervisor presents to the guest OS a virtual hardware platform and manages the execution of the guest OS. Multiple instances of different operating systems may share the virtualized hardware resources. Hypervisors are installed on server hardware whose only task is to run guest operating systems. Non hypervisor virtualization systems are used for similar tasks on dedicated server hardware, but also commonly on desktop, portable and even handheld computers. There are three popular approaches to server virtualization: Full Virtualization, Para Virtualization and virtualization with hardware support (Hardware Virtual Machine, or

**Full Virtualization** provides emulation of the underlying platform on which a guest operating system and application set run without modifications and unaware that the platform is virtualized. This approach is idealistic, in real world scenarios virtualization

Providing a Full Virtualization implies that every platform device is emulated with enough details to permit the guest OS to manipulate them at their native level (such as register-level interfaces). Moreover, it allows administrators to create guests that use different operating systems. These guests have no knowledge about the host OS since they are not aware that the hardware they see is not real but emulated. The guests, however, require real computing resources from the host, so they use a hypervisor to coordinate instructions to the CPU. The hypervisor provides virtual machine to show all the needed hardware to start and run the operating system. Via a virtual bios, it shows CPU, RAM and storage devices. The main advantage of this paradigm concerns the ability to run virtual machines on all popular operating systems without requiring them to be modified since

**Para Virtualization Machine** approach is based on the host-guest paradigm and uses a virtual machine monitor. In this model the hypervisor modifies the guest operating system's code in order to run as a guest operating system in a specific virtual machine environment. Like virtual machines, Para Virtual Machines are able to run multiple operating systems. The main advantage of this approach is the execution speed, always faster than HVM and Full Virtualization approach. The Para Virtualization method uses

Hypervisor (Para Virtualized)

PV Drivers

OS

PV Drivers

Physical Server (Host)

(c) HVM Virtualization

Host Operating System

Hypervisor (Emulator)

VM VM OS

Apps

Apps

Modified OS

Physical Server (Host)

(a) Full Virtualization

Fig. 3. Virtualization approaches.

HVM).

comes with costs.

the emulated hardware is completely transparent.

Hypervisor (Full Virtualized)

Device Emulation

OS

Apps Unmodified OS

VM VM

As anticipated, several advantages ensue from virtualization use. The number reduction of physical servers is one of the most evident: the hardware (software) solution for virtualization allows multiple virtual machines running on one physical machine, moreover additional advantages are power consumption reduction, better fault tolerance, optimization of time needed for device installation and of the number of cabinets. Another advantage is that virtualization can be used to abstract hardware resources, since operating systems are closely related to the underlying hardware, several issues need to be taken into account when a server is moved or cloned, e.g., incompatible hardware, different drivers and so on. Another virtualization feature is the creation of abstraction levels such that the operating system does not see the actual physical hardware, but a virtualized one. Administrator can move or clone a system on other machines that run the same virtualization environment without worrying about physical details (network and graphics cards, chipsets, etc.).

Another important aspect is adaptability: if a company changes its priorities and needs, a service may become more important than another or may require more resources. Virtualization allows resource allocation to virtual hardware easily and quickly. Some companies maintain old servers with obsolete operating systems that cannot be moved to new servers as these OS would not be supported. In virtualized environments it is possible to run legacy systems allowing IT managers to get rid of old hardware no longer supported, and more prone to failure. In many cases it is appropriate to use virtualization to create test environments. It frequently happens that production systems need to be changed without knowledge about consequences, i.e., installing an operating system upgrade or a particular service pack is not a risk-free. Virtualization allows immediate replication of virtual machines in order to run all necessary tests.

Like any other technology, the virtualization gives disadvantages that depends on the application scenario. The most important are performance overhead and presence of hardware virtualization. Each virtualization solution is decreasing the overall performance, such as disk access times or access to memory. Some critical applications may suffer from this overhead introduced by virtualization. Depending on the products used, some devices may not be used by virtual machines, such as serial and parallel ports, USB and Bluetooth interfaces, or graphics acceleration hardware.

requirements in all information and communication areas, but become extremely critical in distributed and heterogeneous environment like grids. The Open Grid Forum released an open standard called Open Grid Standards Architecture OGSA (2007) which is the referring point for worldwide researchers. OGSA specifies a layer called Grid Security Infrastructure GSI (2010) which aim is to undertake these matters, for further details see Section 3.3.4. The GSI is based on X.509 infrastructure and Secure Socket Layer (SSL) protocol, and uses public key cryptography and certificates for creating secure grid and application level data encryption. The X.509 certificates are used to ensure authentication: every user or service owns a certificate which contains needed information to identify and

Grid Infrastructure for Domain Decomposition Methods in Computational ElectroMagnetics 255

**Authorization** is a security feature that implies the definition of "who" can access "what", clearly this definition can be extended by adding "when", "how", "how long", and so on. In the grid environment authorization is very important as resources are shared between several users and services. The Authorization Systems (AS) can be classified into two groups: (1) Virtual Organization (VO) Level and (2) Resource Level Systems. The former is centralized AS for an entire VO: when an user needs to access a resource of Resource Provider (RP) he requests for credentials to the AS and presents them to the RP which allows/denies rights to the user. The latter, instead, specifies the authorization to a set of resources, these systems allow the (authenticated) users to access the resources based on the credentials he presents. Examples of the first authorization systems are Community Authorization Service CAS (2010) and Virtual Organization Membership Service VOMS (2003), while example of the second are Privilege and Role Management Infrastructure

**Service Security** entails the implementation of protection mechanisms focussed to guarantee the availability of services. Attack class examples are QoS violation and Denial-of-Service (DoS). The first is achieved through traffic congestion, packet delay or drop, while the second aims to cause software crash and to completely disrupt the service. The countermeasures to contain these attacks are mainly based on prevention and monitoring in order to limit damages and to raise alarms. Some approaches also try to detect the

Infrastructure threats regards network and host devices that form the grid infrastructure and are classified in Host level and Network level. These issues impact data protection, job protection, host availability, access control functionalities, secure routing and all the

**Host Security** impacts data protection and job starvation. The former regards the protection of data already stored in the host, in fact the host submitting the job may be untrusted and the job code may be malicious. The latter is a scenario in which resources assigned to a job are denied to the original job and assigned to a different (malicious) job. The most effective countermeasures to limit data threats are: (1) application level sandboxing, (2) virtualization, and (3) sandboxing. The first approach uses proof carrying code (PCC), the compiler creates proofs of code-safeness and embed those in the executable binary. The second solution is based on the creation of Virtual Machines upon the physical host, this technique ensures strong isolation between different VMs and the host system. The third method confines system calls and sandboxes (isolates) the applications to avoid data and memory access not allowed. The solution adopted to avoid job starvation are based on

source, but an effective defense against these attacks is really hard to achieve.

Standards Validation PERMIS (2002), and the GridMap system.

authenticate the owner.

**3.3.2 Infrastructure issues**

communication aspects.

Fig. 4. Taxonomy of grid security issues.


Section 1 Signal Denoising

#### **Chapter 1**

## Introductory Chapter: Signal and Image Denoising

*Mourad Talbi*

#### **1. Introduction**

Both signal and image are unfortunately degraded by different factors that affect as noise during acquisition or transmission. Those noisy effects decrease the performance of visual and computerized analysis. It is clear that cancelling the noise from the signal facilitates its processing. The denoising process can be described as to cancel the noise while retaining and not distorting the quality of processed signal or image [1–4]. The conventional manner of denoising for noise cancelling consists in applying a band/low-pass filter with cut-off frequencies. Though conventional filtering methods are capable to suppress a relevant of the noise, they are not able when the noise is located in the band of the signal to be processed. Consequently, numerous denoising techniques were introduced in order to overcome this problem. The algorithms and processing approaches employed for signals can be also used for images and this is due to fact that an image is viewed as a two-dimensional signal. Consequently, the signal processing methods for one-dimensional signals can be adapted for processing two-dimensional images. Due to the fact that the origin and non-stationarity of the noise corrupt the signal, it is not easy to model it. Nevertheless, when the noise can be considered as stationary, an empirically recorded signal that is degraded by an additive noise is formulated as follows [1]:

$$\mathbf{y}(j) = \mathbf{x}(j) + \sigma \cdot \varepsilon(j), j = \mathbf{0}, \mathbf{1}, \dots, n - \mathbf{1} \tag{1}$$

With *y j*ð Þ is the noisy signal, *x j*ð Þ is the clean signal and εð Þ*j* are independently normal random variables and σ designates the level noise corrupting ð Þ*j* . The noise can be modeled as stationary independent zero-mean white Gaussian variables [5, 6]. If this model is employed, the objective of noise cancellation consists in reconstructing *x j*ð Þ from a finite set of *y j*ð Þ values without considering a particular structure for the signal. The commonly used approach for noise cancellation models noise as a high frequency signal corrupting in additive manner, the clean signal. These high frequencies can be bringing out employing Fourier transform, ultimately cancelling them by an adequate filtering. This noise cancelling method is conceptually clear and efficient since it is depending only on computing DFT (Discrete Fourier Transform) [7]. However, there is some issue that should be considered. The most important having same frequency since the noise owns important information in the original signal. Filtering out these frequency components introduces noticeable information loss of the desired signal. It is clear that a technique is strongly needed for preserving the prominent part of the signal having relatively high frequencies as the noise has. As an example, the wavelet-based noise removal approaches have provided this prominent part conservation. De-noising of natural images degraded by Gaussian Noise employing wavelet based denoising techniques are very efficient due to the fact that it is able to capture the energy of a signal in few energy transform values. The wavelet de-noising scheme thresholds the wavelet coefficients arising from the standard discrete wavelet transform [8]. In Ref. [8], it was introduced to investigate the suitability of different wavelet bases and the size of different neighborhood on the performance of image denoising techniques in term of peak signal-to-noise ratio (PSNR) [8].

In Ref. [9], Di Liu and Xiyuan Chen introduced an image denoising technique applying an ameliorated bidimensional empirical mode decomposition (BEMD) and using soft interval thresholding. At first step, a noise compressed image is constructed. After that, this noise compressed image is decomposed by applying BEMD into a series of intrinsic mode functions (IMFs), which are separated into signal-dominant IMFs and noise-dominant IMFs employing a similarity measure based on ℓ2-norm and a probability density function, and a soft interval thresholding is employed in adaptive manner for cancelling the noise inherent in noise-dominant IMFs. The denoised image is finally obtained *via* the combination of the signal dominant IMFs and the denoised noise dominant IMFs. The performance of this image denoising technique [1] was applied to multiple images with different sorts of noise, and the results obtained from the application of this technique [1] were compared to those obtained from the application the some traditional techniques in different noisy environments. Simulation results in terms of peak signal-to-noise ratio, mean square error, and energy of the first IMF, proved that this denoising technique [9] outperforms the other denoising techniques.

Hybridization of the BEMD with denoising approaches has been introduced in the literature as an efficient image denoising technique.

In Ref. [10], Student's probability density function was proposed in the calculation of the Mean Envelope of the data during the BEMD sifting process for making it robust to values that are far from the mean. The obtained BEMD was named tBEMD. To prove the efficiency of the tBEMD, many image denoising approaches were used in the tBEMD field. Among these approaches, we can mention the discrete wavelet transform (DWT), fourth-order partial differential equation (PDE), linear complex diffusion process (LCDP), and nonlinear complex diffusion process (NLCDP). For experiments, a standard digital image and two biomedical images are considered. The original images are degraded by additive Gaussian Noise with three diverse levels. Based on PSNR (peak signal-to-noise ratio), the obtained results show that DWT, PDE, LCDP, and NLCDP, all perform better in the tBEMD domain compared to the conventional BEMD domain. Moreover, the tBEMD is faster than conventional BEMD in case where the noise level is low. However, in case where it is high, the calculation cost in terms of processing time is similar. The efficiency of the presented approach makes it promising for clinical applications.

This book is intended for engineers and researchers in the fields of signal and image processing. Indeed, this book deal with a large number of signal and image denoising techniques. These techniques include an innovative image denoising approaches.

#### **2. Examples of signal and image denoinsing**

In this section, we will give some examples of signal and image denoising obtained from the application of the discrete wavelet transform (DWT).

*Introductory Chapter: Signal and Image Denoising DOI: http://dx.doi.org/10.5772/intechopen.112689*

#### **Figure 1.**

*An example of PCG denoising using DWT [1]: (a) clean PCG signal, (b) noisy PCG signal, (c) denoised PCG signal, (d) difference between the original and the denoised signal.*

#### **2.1 Phonocardiogram denoising**

The acoustical vibrations records from the heart, acquired through microphones from human chest, named phonocardiogram (PCG), consist of both the murmurs and the heart sounds. Those records of acoustic signals are unfortunately corrupted by diverse factors which effecting as noise. Those effects cause the decreasing of the performance of visual and computerized analysis [1, 11, 12].

**Figure 1** illustrates an example of PCG denoising using DWT.

According to **Figure 1**, the noise is considerably reduced and the waveform of the original signal is conserved because the difference between the original and the denoised signals is very small. Consequently, the denoising technique based on thresholding in DWT domain and applied in Ref. [1], shows its performance in noise reduction while conserving the information contained in the original PCG signal.

**Figure 2.**

*An example of medical image denoising by applying thresholding in the DWT domain: (a) a noisy medical image with PSNR* ¼ 62 *dB, (b) denoised image obtained from the application of a denoising technique based on thresholding in the DWT domain.*

#### **2.2 Image denoising**

All digital images are degraded by different types of noise during their acquisition and transmission. As an example of these images, the medical one is likely disturbed by a complex sort of addition noise depending on the devices that are employed for capturing or storing it. There are no medical imaging devices that are noise free. The most commonly employed medical images are produced from MRI and CT equipment [1]. The additive noise corrupting medical image causes the reducing of the visual quality that complicates diagnosis and treatment.

**Figure 2** illustrates an example of a medical image denoising using DWT.

A noise-added medical image and its denoised one obtained from employing a wavelet denoising technique are illustrated in **Figure 2**. The added noise has Gaussian distribution, and symlet 6, decomposition level of two, hard thresholding were used as the parameters for the application the wavelet-based denoising technique [1].

#### **3. Conclusion**

In this chapter, we deal with a number of signal and image denoising techniques existing in the literature. We also give two examples of signal and image denoising by applying the denoising techniques based on thresholding in the Discrete Wavelet Transform domain. Those examples show the performance of these denoising techniques.

#### **Author details**

Mourad Talbi Laboratory of Nanomaterials and Systems for Renewable Energies (LaNSER), Center of Researches and Technologies of Energy (CRTEn), Tunis, Tunisia

\*Address all correspondence to<EMAIL_ADDRESS>
© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

### **References**

[1] Ergen B. Signal and image denoising using wavelet transform. In: Advances in Wavelet Theory and their Applications in Engineering, Physics and Technology. London, UK: InTech; 2012

[2] Chen G, Bui T. Multiwavelets denoising using neighboring coefficients. IEEE Signal Processing Letters. 2003; **10**(7):211-214

[3] Portilla J, Strela V, et al. Image denoising using scale mixtures of Gaussians in the wavelet domain. IEEE Transactions on Image Processing. 2003; **12**(11):1338-1351

[4] Buades A, Coll B, et al. A review of image denoising algorithms, with a new one. Multiscale Modeling and Simulation. 2006;**4**(2):490-530

[5] Moulin P, Liu J. Analysis of multiresolution image denoising schemes using generalized Gaussian and complexity priors. IEEE Transactions on Information Theory. 1999;**45**(3):909-919

[6] Alfaouri M, Daqrouq K. ECG signal denoising by wavelet transform thresholding. American Journal of Applied Sciences. 2008;**5**(3):276-281

[7] Wachowiak MP, Rash GS, et al. Wavelet-based noise removal for biomechanical signals: A comparative study. IEEE Transactions on Biomedical Engineering. 2000;**47**(3):360-368

[8] Kother Mohideen S, Perumal SA, Sathik MM. Image de-noising using discrete wavelet transform. IJCSNS International Journal of Computer Science and Network Security. 2008;**8**(1):2

[9] Liu D, Chen X. Image denoising based on improved bidimensional empirical mode decomposition thresholding

technology. Multimedia Tools and Applications. 2019;**78**:7381-7417. DOI: 10.1007/s11042-018-6503-6

[10] Lahmiri S. Image denoising in bidimensional empirical mode decomposition domain: The role of Student's probability distribution function. Healthcare Technology Letters. 2016;**3**(1):67-71

[11] Akay M, Semmlow J, et al. Detection of coronary occlusions using autoregressive modeling of diastolic heart sounds. IEEE Transactions on Biomedical Engineering. 1990;**37**(4): 366-373

[12] Ergen B, Tatar Y, et al. Timefrequency analysis of phonocardiogram signals using wavelet transform: A comparative study. Computer Methods in Biomechanics and Biomedical Engineering. 2010;**99999**(1):1-1

#### **Chapter 2**

## Sound Absorption Measurement: Alpha Cabin and Impedance Tube

*Pavel Němeček*

#### **Abstract**

The stage of development of absorbent materials, when necessary to verify their properties in relation to established requirements, plays one of the key challenges in current research. Nowadays, experimentation represents the only reliable way to quantify sound absorption. Thus, the determined sound absorption coefficient is used to compare individual development variants, and also, it is used in a selection of material from the commercial offer. Therefore, the main part of research is devoted to measurements in the impedance tube and in the alpha cabin, because these procedures play one of the most challenging roles in practice. All used experimental methods are based on the theory about transformation of sound energy into other forms of energy in the material. Nevertheless, the physical nature of sound absorption and individual measurement principles are not covered in this chapter, nor are any sound insulation measurements. It deals solely with the sound absorption and determination of the sound absorption coefficient. As a results, this chapter further summarizes basic information on a sound absorption measurement, and mainly, focuses on practical recommendations as well as applicability of results. First and foremost, these individual procedures may represent a considerable international overlap in the field.

**Keywords:** sound absorption coefficient, impedance tube, alpha cabin, sound absorption measurement, reverberation time

#### **1. Introduction**

Sound absorption measurement serves as an activity associated with the design, verification and application of suitable materials for solving an acoustic situation of enclosed spaces. These materials have a specific composition, may be applied to large surfaces, and their properties must typically meet many requirements (thermal insulation, mechanical resistance, low dirtiness, compactness, etc.). Absorbent materials are used in building acoustics, the automotive industry and everywhere where humans and noise sources are in a confined space.

This chapter covers the experimental determination of the sound absorption coefficient of industrially produced materials or samples in the stage of development, which are intended for the reduction, or regulation of noise in closed spaces. The chapter also contains a brief description of basic comparison methods and a more

detailed description of two laboratory methods, i.e. the measurement of sound absorption in an impedance tube and in an alpha cabin. The goal is to provide a basic description of experimental methods, their comparison, evaluation and determination of accuracy.

In practice:

### **2. Basics of measuring sound absorption**

Sound absorption is the ability of a material environment to absorb coming sound. It is a process in which sound energy falling on a sample of material is transformed into another form, mainly thermal energy. In the ideal case, the sound energy that encounters the sample (WINBOUND) is partly reflected (WREFLECTION), partly transmitted through the sample (WTRANSMISSION) and partly absorbed into the sample (WABSORPTION). Applies to:

WINBOUND = WREFLECTION + WABSORPTION + WTRANSMISSION.

When experimentally investigating absorption, certain conditions need to be met so the equation above can be applied. The conditions are:

There are additional requirements for experimental methods:

To the methods used, it should also be mentioned:

#### **3. Physical and metrological basis of sound absorption measurement**

A measurement can be considered as the only objective option to determine the sound absorption coefficient α. Other options, such as simulations and modeling in a virtual environment, face problems with an accurate determination of the boundary conditions and with the definition of the internal structure of the material. Validation of materials intended to solve a sound situation in closed spaces requires a determination of the sound absorption factor by experiment, therefore on a real part by objective methods. Requirements are set, for example, by the automotive industry or the building materials industry. Knowledge of the sound absorption coefficient makes it possible to model sound propagation in closed spaces using special software.

Measuring the sound absorption coefficient is a topic mainly for:

1. Independent testing laboratories,

In the next part of the text, 4 measurement methods are described. Two of them are very simple and serve more for a comparison to the reference sample, the other two ones are the most used in practice. A method, which is used mainly by independent testing laboratories and complies the international standards be briefly mentioned.

The following points apply to all described methods:

#### **3.1 Approximate and comparative methods of measuring sound absorption**

In this chapter are described simple methods of sound absorption measurement. Their description serves rather to complement the technical and historical context of sound absorption measurements. It is based on conditions where it is not possible or preferred to use more advanced methods. These methods:

These methods cannot be characterized as laboratory methods for an objective determination of sound absorption. They only serve as quick comparison tests in the optimization of the composition of absorbing layers and can be used directly at the place of application.

#### *3.1.1 Tone burst method*

This method is currently used very rarely. However, in the available literary sources, it is still found in various methodological variants [1–3], it is popular with students who use it in a case when sound absorption is only one of the properties they investigate on materials.

This is a simple method based on the idea that when a sound wave strikes a sample at a certain angle, a reflected wave propagates at the same angle with energy reduced by the absorbed energy. The calculation is based on processing the ratio of incident energy and reflected energy.

The measurement takes place in a space that is as anechoic as possible, ideally using a directional microphone and a directional speaker.

1.Measurement step: a signal with sufficient energy and bandwidth is applied to the speaker and the sound pressure level Lp,d (its frequency spectrum) is measured at the distance A between the speaker and the microphone.

2.Measurement step: a testing object of sufficient dimensions is placed on the reflective pad. The distances from the microphone to the point of reflection of the sound waves and the distance of the loudspeaker from the point of reflection of the waves are identically A/2. The identical signal emitted by the speaker is partially absorbed in the absorbing wave, the rest is reflected to the microphone. The measurement takes place according to the diagram below, the important thing is the same angle of incidence/reflection φ. The frequency spectrum of the sound pressure level Lp,r is evaluated at the microphone.

3. Step 3: at individual frequencies (1/3 octave), the sound absorption coefficient α(φ;f) is estimated according to the formula:

$$a(\varphi; f) = \mathbf{1} - \mathbf{10}^{\frac{\binom{\mathcal{L}\_{p, \mathcal{d}}(\varphi; f) - \mathcal{L}\_{p, \mathcal{r}}(\varphi; f)}{\cdot \otimes}}} \tag{1}$$

Method Notes:

#### *3.1.2 Sound intensity measurement method*

This approximate method requires the use of a measuring system with a sound intensity probe.

In an open field, the reflective surface is covered with a sufficiently large sample of the measured material. A sound source is placed at a sufficient distance from the surface of the sample. At a close distance from the sample (approx. 0.2 distance between the surface of the sample and the speaker), the average sound pressure level Lp and the average sound intensity level LI reflected from the sample are measured. The sound absorption coefficient is then calculated by the formula:

$$a(f) = \frac{4}{1 + 10^{\frac{L\_p(f) - L\_I(f)}{10}}} \tag{2}$$

The incident energy is proportional to the sound pressure level, the reflected energy is identified as a component of the sound intensity vector. Both quantities are identified by the sound intensity probe.

Advantages of the Sound Intensity Measurement Method may be:

The disadvantages of the Sound Intensity Measurement Method may be:

• Lower accuracy,

• The impossibility of relating the result only to the absorbent material sample. It is not possible to separate the absorption of the sample and the absorption of the substrate on which it is placed.

#### **3.2 Accurate methods of measuring the sound absorption coefficient**

#### *3.2.1 Standard ISO 354*

This international standard [4] defines the basic laboratory procedure for determining the sound absorption coefficient in a reverberation space. The procedure can be considered the most accurate procedure leading to the determination of the sound absorption coefficient. The method determines the sound absorption coefficient for diffusing the sound impact and can be used to measure materials with distinct shape structures in the straight and perpendicular direction. It is described in great detail in the standard and is especially suitable for specialized laboratories. The standard places strict requirements on the reverberation space, its dimensions and above all on the dimensions of the sample. The declared frequency range is from 100 Hz to 5000 Hz. The principle of indirect measurement of the sound absorption coefficient is based on Sabin's formula [5]:

A formula developed by Wallace Clement Sabine that allows designers to plan reverberation time in a room in advance of construction and occupancy. Defined and improved empirically the Sabine Formula [5] is.

$$T(\mathbf{60}) = \mathbf{0}.\mathbf{161} \cdot \frac{V}{A} |\mathbf{s}|,\tag{3}$$

Where:

T(60) = reverberation time or time required (for sound to decay 60 dB after source has stopped) |s|,

V = Volume of room |m<sup>3</sup> |,

A = the equivalent absorption surface |m<sup>2</sup> |.

In the test room, the reverberation time is measured with and without the mounted test sample. The reverberation time is the time during which the sound pressure level decreases by 60 dB after the sound source is turned off. This means that the original acoustic energy drops to 1/1000000 of its original size. In the test room, the reason for the decrease is the sound absorption and then the reverberation time is its measure. The equivalent surface is a hypothetical surface of a perfectly absorbing sample that has the same properties as a real sample. The equivalent area is the basis for calculating the sound absorption coefficient.

Advantages of determining the sound absorption coefficient according to ISO 354:

Disadvantages of determining the sound absorption coefficient according to ISO 354:

Above all, the requirement for a size of a sample is a problem of using this basic method in the sample development phase, when many possible variants are experimentally verified with subsequent optimization. It is practically impossible for manufacturers of absorbent materials and research organizations that are not directly oriented towards this research to acquire such expensive laboratory facilities.

Specific information on the measurement and calculation procedure is contained in the mentioned standard and it is not the aim of this chapter to discuss them in more detail.

#### *3.2.2 Measurement in an impedance tube*

An impedance tube is the most common device used today to estimate sound absorption. In the professional literature, this method is currently mentioned most often. There are more concrete technical versions of the tube, from the own construction of a research workplace to commercially offered versions. As an example, **Figure 1** shows the assembly from Brüel & Kjær Impedance Tube Kit 4206 (4206-A), which is described in the following text.

The impedance tube principle is based on the creation of a combination of direct and reflected waves in a rigid closed tube with an internal smooth and reflective surface. The skeleton of the tube must be as soundproof as possible. One end of the tube covers a sample that is being measured, on the other end of the tube there is placed a speaker that excites by broadband noise the inner volume of the tube. A plane wave is created between the speaker and the sample, which is a combination of incident and reflected waves. The energy of the reflected wave is reduced by the energy absorbed in the sample. The resulting wave is sampled in the tube and an estimate of the sound absorption coefficient is determined by evaluating the data obtained. The sound wave strikes the sample perpendicularly.

Basic characteristics of impedance tube measurement:

*Sound Absorption Measurement: Alpha Cabin and Impedance Tube DOI: http://dx.doi.org/10.5772/intechopen.110410*

**Figure 1.** *Impedance tube and absorptive material samples (author's archive).*

the methods in the diffusion field according to ISO 354 [4] and in the alpha cabin [7, 8].

#### *<IP_ADDRESS> Method using standing Wawa ratio*

This method determines the sound absorption coefficient of acoustic materials when the sound is incident perpendicularly. The specific procedure for determining the sound absorption coefficient is described in [9]. The absorbing sample is fixed at one end of the tube. An incident plane sine wave pi is excited by a speaker at the opposite end of the tube. By superposition p = pi + pr of the pressures of the incident wave pi and the reflected wave pr from the test sample, a standing wave is created in the tube. The course of the sound pressure level of this standing wave is measured by an adjustable microphone, which is moved along the axis of the tube through the hole in the center of the speaker. The evaluation of sound absorption is based on the difference in sound pressure levels ΔL between the pressure maximum and minimum in the tube.

$$a = \frac{4 \cdot 10^{\Delta l\_{\text{20}}}}{\left(10^{\Delta l\_{\text{20}}} + 1\right)^2} \tag{4}$$

Moving the microphone and accurately identifying the maximum and minimum sound pressure level reduces the speed of the sound absorption coefficient measurement. Impedance tubes for this evaluation method are more often an individual product of test laboratories, which allows adaptation to the desired frequency band and the way of moving the microphone and evaluating the absorption.

#### *<IP_ADDRESS> Transfer-function method*

This test method is similar to the previous method in that it uses the same experimental scheme with a sound source at one end and a sample fixed in an impedance tube at the other end. The procedure is described in detail in [10, 11]. In this test method, plane waves in the tube are excited by a noise source and the sound pressure is measured by microphones located at two fixed points (or by one microphone moved in the tube) and by subsequent calculation of the complex transfer function at a perpendicular incidence of sound waves. The test method is overall much faster than the measurement procedure described in the previous chapter.

The test sample is fixed to one end of a straight, rigid, smooth and sealed impedance tube. Plane waves are excited in the tube by a sound source (noise) and the sound pressure is measured by microphones at two locations near the sample. A complex transfer function is determined from the measured signals, which is used to calculate the sound absorption coefficient. The frequency range of the measurement depends on the dimensions of the tube and the distance between the positions of the microphones. In order to determine the sound absorption coefficient in a wider frequency range, measurements are made on an assembly that contains tubes of two different diameters. **Figure 1** shows a measuring set-up that allows determining the sound absorption coefficient for a sample diameter of 100 mm in the frequency range of 50 Hz to 6.4 kHz (for a sample thickness of 440 mm maximum [6]) and for a sample diameter of 29 mm in the frequency range of 100 Hz to 3.2 kHz (for a sample thickness of 200 mm maximum [6]).

Measurements can be done:

Procedure 1 is quick, accurate and easier to do. It is widespread in practice and much more published.

Procedure 2 requires a specialized excitation signal, has more demanding requirements for processing the measured signals, and is more time-consuming. It better eliminates phase mismatch between microphones and allows optimal selection of microphone locations for each measured frequency. According to [10], this procedure is recommended for evaluating of tuned resonators.

Advantages of measuring in an impedance tube:

Disadvantages of measuring in an impedance tube:

#### *3.2.3 Measurements in the alpha cabin*

The Alpha cabin [7, 8, 12, 13] is an internationally acknowledged measurement platform for determining the sound absorption coefficient at the omnidirectional impact of sound waves. It is therefore close to measurements according to ISO 354, it is based on the requirements of this standard, it respects the methodology as much as possible, but removes the disadvantage of the need for large samples.

The Alpha cabin is a platform that is scaled 1:3.2 to the echo chamber parameters of the Swiss Material Testing and Testing Laboratory (EMPA) in Dübendorf. **Figure 2** shows an example of the latest design of the alpha cabin. It is a reverberant space sound-isolated from the outside environment with non-parallel walls.

The main technical data of the alpha cabin are:

**Figure 2.** *Alpha cabin - Technical University of Liberec (author's archive).*

The formula [7] is used to determine the sound absorption coefficient:

$$a\_{\mathcal{S}} = \frac{0,966}{\mathcal{S}} \left( \frac{1}{T\_1} - \frac{1}{T\_0} \right) \tag{5}$$

Where the measured quantities are:

S = sample area |m<sup>2</sup> |.

T1 = reverberation time in the sample booth |s|,

T0 = reverberation time in the cabin without sample |s|.

The ratios in the diffusion field of the alpha cabin (**Figure 3**) are practically the same as in the large reverberation chamber, but for three times shorter wavelengths (three times higher frequencies). The Alpha cabin therefore provides comparable results on much smaller sample areas than required by ISO 354. However, the proportional changes in cabin conditions run into one problem. The thickness of the sample is the only geometric quantity that cannot be reduced in a ratio of 1:3, and thus the absorbing surface corresponding to the edges of the sample appears three times larger in proportion to its surface. The problem must be eliminated by edging the side surface of the sample with soundproof material. As standard, it is solved by a metal bounding frame with the dimensions of a standard sample, which is higher than the usual thicknesses of the developed materials. In the case of larger thicknesses, it is recommended to manufacture your own frame and validate it using a reference sample. The importance of sample edging can be shown on the measurement results of the same sample with a thickness of 20 mm with and without a bounding frame in **Figure 4**. The course shows that the error of determining the sound absorption coefficient increases with increasing frequency (**Figure 5**).

*Sound Absorption Measurement: Alpha Cabin and Impedance Tube DOI: http://dx.doi.org/10.5772/intechopen.110410*

**Figure 3.** *Alpha cabin with embedded and framed sample (author's archive).*

The Alpha cabin measurement procedure generally requires two measurements.

The sound absorption coefficient is then calculated according to formula (5).

**Figure 4.** *Results of measurements with and without a border frame.*

**Figure 5.** *Frames for delimiting samples (author's archive).*

The Alpha cabin has one more function, which is the evaluation of absorbing objects. These are shaped parts that absorb sound, but the absorbing surface cannot be determined. A typical example is the seat of a passenger car [12], which significantly affects the noise in the closed space of the cabin due to its absorption, but it is not possible to clearly determine the absorbing surface, or to create a sample of standardized dimensions from the seat. In Eq. (5) it is not possible to substitute the absorbing surface S, and thus the measurement result is equal to the equivalent absorbing surface A:

*Sound Absorption Measurement: Alpha Cabin and Impedance Tube DOI: http://dx.doi.org/10.5772/intechopen.110410*

$$A = 0, 966 \cdot \left(\frac{1}{T\_1} - \frac{1}{T\_0}\right) \qquad |m^2| \tag{6}$$

The equivalent absorptive surface corresponds to the absolute absorptive surface (α<sup>S</sup> = 1), which has the same absorptive capacity as the shaped part. Therefore, the larger the equivalent surface area, the more the shaped part is able to absorb more sound energy. An example of the result of measuring the equivalent absorbing surface for a shaped part in the construction of a passenger car is shown in **Figure 6**.

The equivalent absorptive surface of shaped parts is primarily a comparative parameter when developing or selecting a part for a protected space. However, it can be used in the calculations of the total absorption, because according to Eq. (5):

$$A = \mathbb{S} \cdot a\_{\mathbb{S}} \tag{7}$$

Advantages of measuring sound absorption in the alpha cabin:

Disadvantages of measuring sound absorption in the alpha cabin:

#### **4. Conclusion**

Measurement is still the most accurate and fastest procedure for determining the sound absorption coefficient. The practical use of absorbing materials in practice requires an objective determination of absorption for the purpose of optimizing the acoustic properties of enclosed spaces.

The current development of absorbent materials is predominantly still using fibers or porous raw materials with an emphasis on other important properties, such as ecology, usability of waste and recyclable resources, esthetics, non-flammability, etc. For products designed in this way (mats, panels, absorbent elements) the main principle of absorption is the conversion of sound energy into heat by friction of the internal structure of the absorbing element. In general, the elements then have optimal efficiency starting from the frequency that is determined by following equation:

$$f = \frac{\text{86000}}{H} \left| \text{Hz} \right| \tag{8}$$

Where:

H = the thickness of the absorbing element |mm|,

f = frequency |Hz|.

The optimal thickness equals to a quarter of the wavelength of a perpendicular incident wave, so it can be considered the minimum value at which the material is able to use its full potential to absorb sound. With omnidirectional impact, it can be assumed that the optimal bandwidth will shift to lower frequencies. **Figure 7** shows an example of the measurement result in the Alpha cabin of a sample of absorbent material with a reference thickness of 22 mm. A frequency of 3.9 kHz (4 kHz 1/3 octave) corresponds to a thickness of 22 mm. Due to the omnidirectional impact of sound waves, the maximum absorption value is maintained even at lower frequencies (2 kHz).

There is an inverse proportional relationship between the optimal frequency and the thickness of the material. When considering declared frequency ranges of individual measurement methods, **Figure 8** provides a comprehensive overview of the methods and their practical use for materials testing.

It is clear from **Figure 8** that the lowest declared measurement frequency achievable in the impedance tube is at frequency of 50 Hz. This would correspond to the

*Sound Absorption Measurement: Alpha Cabin and Impedance Tube DOI: http://dx.doi.org/10.5772/intechopen.110410*

**Figure 7.** *Sound absorption of a sample with a thickness of 22 mm - measured in the alpha cabin.*

#### **Figure 8.**

*Measurement methods in relation to the optimization of the thickness of the absorbent material.*

optimal absorption of materials with a thickness of approx. 1700 mm, which is technically impossible. An impedance tube of such dimensions is not used in practice, but a sufficiently wide frequency band is available for an objective assessment of

commonly used materials. The Alpha cabin starts at a frequency of 400 Hz, which corresponds to roughly 200 mm of material thickness when optimally used. This thickness is usable for the Alpha cabin. The ISO 354 standard declares a minimum frequency of 100 Hz, which corresponds to 860 mm of optimal thickness, which is also acceptable given the dimensions of the space and the area of the sample. It should be emphasized that the measurement according to the ISO 354 standard and in the Alpha cabin is based on the omnidirectional impact of sound waves, the impedance tube is based on only a perpendicular impact.

From the **Figure 8**, an uncovered bandwidth of sound absorption measurements up to 100 Hz can be seen in the case of omnidirectional impact of sound waves. It should be emphasized that physical and technical obstacles to the use of independent methods are encountered here. The optimal thickness of the materials is greater than 860 mm and ends at 4.3 m for 20 Hz, which is the lowest frequency of the audible band. However, this range of thicknesses of absorbing materials is difficult to use in the real world for practical reasons. The exception is specialized anechoic chambers with high volumes. Here, the effectiveness of absorbing materials is assessed by measuring the reverberation time directly during implementation.

If the commercially usual area of absorbent materials (up to a maximum thickness of 200 mm) were to be evaluated, it can be seen from **Figure 9** that the optimal platform is the alpha cabin.

#### **Recommendations for the design and experimental verification of the properties of absorbent materials**

If the absorbing material is to fulfill the expectations, its structure must be properly designed. This is a matter of material development respecting other requirements (legislative requirements, esthetic requirements, applicability in specific conditions,

#### **Figure 9.** *Measurement methods in relation to thickness optimization of conventional absorbent material | author's archive |.*

other specific customer requirements). An objective assessment of sound absorption can only be achieved by measuring on an existing sample. Below is the basic procedure for determining the sound absorption coefficient by experiment.

1.To perform the measurement, a sample must be taken that clearly states:

Lower accuracy methods:

Higher accuracy methods:

#### **5. Discussion**

This chapter summarizes experimental methods for determining the sound absorption coefficient α. The chapter addresses the user (researcher, customer, project solvers) who are tasked with designing (developing) absorbing material and need to verify it during the development stage or after application. Available approximate and exact methods, their starting points, limitations, advantages and disadvantages and usability in practice are described. The solver can thus choose a suitable method for

#### *Denoising – New Insights*

the individual stages of the project solution or correctly formulate requirements for external laboratories. The chapter further helps to understand the measurement results in relation to the application to a specific space and guides the project solver to be aware of possible limitations and problems.

Recommendation:

### **Author details**

Pavel Němeček Technical University of Liberec, Liberec, Czech Republic

\*Address all correspondence to<EMAIL_ADDRESS>
© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Sound Absorption Measurement: Alpha Cabin and Impedance Tube DOI: http://dx.doi.org/10.5772/intechopen.110410*

### **References**

[1] Brüel & Kjær. Measurements in Building Acoustic [Internet]. 1988. Available from: https://www.academia. edu/17353265/Measurementsin\_Build ing\_Acoustics?email\_work\_card=viewpaper

[2] Bérengier M, Garai M. A State-of-the-Art of in situ Measurement of the Sound Absorption Coefficient of Road Pavements. Available from: https:// www.academia.edu/34047160/ MEASUREMENT\_METHODS\_OF\_ ACOUSTICAL\_PROPERTIES\_OF\_ MATERIALS\_SESSIONS\_A\_state\_of\_ the\_art\_of\_in\_situ\_measurement\_of\_ the\_sound\_absorption\_coefficient\_of\_ road\_pavements

[3] Quintero-Rincón A. Measurement of the Sound-Absorption Coefficient in situ in Eggs Cartons using the Tone Burst Method. Available from: https://www. academia.edu/12996142/Measurement\_ of\_the\_sound\_absorption\_coefficient\_ in\_situ\_in\_eggs\_cartons\_using\_the\_ Tone\_Burst\_Method?email\_work\_card= title

[4] ISO 354, Acoustic - Measurement of Sound Absorption in a Reverberation Room. Switzerland; International Organization for Standardization; 2003

[5] Reverberation Time and Sabine's Formula. Available from: https://www. acousticlab.com/en/reverberation-timeand-sabines-formula/

[6] Product Data. Impedance Tube Kit (50 Hz – 6.4 kHz) Type 4206, Impedance Tube Kit (100 Hz – 3.2 kHz) Type 4206-A, Transmission Loss Tube Kit (50 Hz – 6.4 kHz) Type 4206. Available from: https://www.bksv.com/ media/doc/bp1039.pdf

[7] Alpha Cabin. A Global Standard for Acoustic Absorption Measurements. Available from: https://www.autoneum. com/alpha-cabin-ii/

[8] Alpha Cabin. Available from: http:// www.cttm-lemans.com/en/acoustics-vib rations/produits/alpha-cabin.html

[9] ISO 10534-1, Acoustics - Determination of Sound Absorption Coefficient and Impedance in Impedance Tubes - Part 1: Method using Standing Wave Ratio. Switzerland: International Organization for Standardization; 1996

[10] ISO 10534-2, Acoustics – Determination of Sound Absorption Coefficient and Impedance in Impedance Tubes – Part 2: Transfer-Function Method. Switzerland: International Organization for Standardization; 1998

[11] Yaochi Tang Y, Chuang X-J. Tuning of Estimated Sound Absorption Coefficient of Materials of Reverberation Room Method. 2022. Available from: https://www.hindawi.com/journals/sv/ 2022/5192984/

[12] Megasorber, Alpha Cabin. Acoustic Performance, Sound Absorption Test Chamber. Available from: https:// megasorber.com/alpha-cabin/

[13] Nemecek P. Sound Absorption Measurement in Alpha Cabin. 2014. Available from: https://link.springer. com/chapter/10.1007/978-3-319- 05203-8\_52

Section 2


**BROADBAND COMMUNICATIONS NETWORKS - RECENT ADVANCES AND LESSONS FROM PRACTICE**

Edited by **Abdelfatteh Haidine** and **Abdelhak Aqqal**

#### **Broadband Communications Networks - Recent Advances and Lessons from Practice**

http://dx.doi.org/10.5772/intechopen.69590 Edited by Abdelfatteh Haidine and Abdelhak Aqqal

#### **Contributors**

Ulrich H.P. Fischer-Hirchert, Matthias Haupt, Mladen Joncic, Stefanie Haupt, Sebastian Höll, Pavel Loskot, Salman Al-Shehri, Tolga Numanoğlu, Mehmet Mert, Vjaceslavs Bobrovs, Guntis Ancans, Arturo Peralta, Roberto Hincapie, Sheng Xu, Milan Aleksandar Ivanović, Nguyen Xuan Tien, Jong Myung Rhee, Milda Tamošiūnaitė, Stasys Tamošiūnas, Mindaugas Žilinskas, Francesco Marcuzzi, Andrea Tonello, Vipin Balyan, Ben Groenewald, Mario Ligwa, Raad Alhumaima, Hamzeh Khalili, David Rincon, Sebastia Sallent, Jose Ramon, Sonia Gul, Jairo Gutierrez, Krzysztof Borzycki, Eneko Atxutegi, Jose Oscar Fajardo, Fidel Liberal, Md Maruf Ahamed, Saleh Faruque, Ales Svigelj, Melisa Junuzovic, Hui Yang, Liping Ai, Hermann J. Helgert, Hyun Jung Lee, Myungho Kim, Abdelfatteh Haidine, Abdelhak Aqqal

#### **© The Editor(s) and the Author(s) 2018**

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Broadband Communications Networks - Recent Advances and Lessons from Practice Edited by Abdelfatteh Haidine and Abdelhak Aqqal

p. cm. Print ISBN 978-1-78923-742-9

Online ISBN 978-1-78923-743-6 eBook (PDF) ISBN 978-1-83881-399-4