*3.2. Microstructure in the Mid-Radius Area*

In contrast to the inhomogeneous microstructure observed in the central part of the processed sample, the grain structure in the mid-radius area was rather uniform. The average grain size of both D15 and D3 were significantly smaller than those in the central area (Table 1) and grain morphology was equiaxed (Figure 3b).

The SEM-BSE images revealed that the volume fraction of the second-phase particles was slightly smaller than that of the central area. Furthermore, no precipitates in the grains after HPTE were seen in TEM bright field (BF) images (Figure 6a).

**Figure 6.** Microstructure of the HPTE Cu in the mid-radius area of the longitudinal section; all the images are at the same scale. (**a**) TEM BF image; (**b**) ACOM TEM OIM map in which LABs (3◦ < Θ < 15◦ are highlighted with white lines) and HABs (Θ > 15◦) are highlighted with black lines; (**c**) GND distribution map from ACOM TEM (all GBs are marked with white lines; and (**d**) EBSD OIM GBs network (LABs marked with red lines, HABs marked with blue lines).

The BF TEM image shown in Figure 6a also illustrates the grain substructure of copper after HPTE in the mid-radius area. The majority of triple junctions had contact angles close to 120◦ (Figure 6a,b). Some grains contained a higher dislocation density compared to that of the adjacent grains, manifested by the diffraction contrast in the image. In general, the TEM observations were consistent with the EBSD maps with respect to the grain size values (Table 2).

**Table 2.** Vickers hardness (HV), yield strength (YS), ultimate strength (UTS) and elongation to failure (δ) of CP Cu after HPTE and after some other SPD processing methods.

Grain size histograms for transverse and longitudinal sections demonstrated similar lognormal distributions. The maxima in both distributions corresponded to 0.8–0.9 μm in the transverse and to 0.7–0.8 μm in the longitudinal sections (Figure 4). However, in the transverse section the number of very small grains, of sizes less than 0.3 μm, was larger than that present in the longitudinal section (Figure 4). The grain size distribution was broader in the transverse section, with grains in range 3 μm < D15 < 6 μm, whereas no grains larger than 3 μm were observed in the longitudinal section (Figure 4). From this, we concluded that the grain structure in copper after HPTE in the mid-radius area was quite similar both in transverse and longitudinal sections, which was not the case for the sample´s central area.

From GB misorientation distributions, it can be observed that the volume fraction of HABs in longitudinal section was higher than that in the transverse one (49% and 33%, respectively, Table 1). This difference was similar to the difference found in the central area and was most likely due to the same grain refinement mechanism.

The differences in grain size and grain size distribution provide evidence that in the mid-radius area the HPTE creates conditions for efficient grain refinement, resulting in smaller grain size than that in the central area of the sample (Table 1).

Examination of the CP copper microstructure after HPTE in the mid-radius area by means of ACOM TEM provided additional microstructural details. Grain substructure was examined in detail using the BF images like that shown in Figure 6a. A typical orientation map is shown in Figure 6b, whereas a GND spatial distribution is shown in Figure 6c. It should be noted here that twins were observed inside the ultrafine grains, which is the reason for the characteristic peak at 60◦ present in the boundary misorientation histogram (Figure 6b). The volume fraction of the twin-type boundaries was 14% and this value was greater by 5.5% compared to that obtained by the EBSD method (Table 1). Most probably, this difference could be the result of the different step sizes used in the two methods as well as by higher spatial resolution in ACOM TEM.

The average thickness of the twins was about 40 nm (Figure 6b), and the average twin size, estimated using equal circles method, was about 110 nm, i.e., smaller than the measured grain size, D3 = 250 nm. The nano-size twins and grains less than 50 nm could not be resolved in SEM, using a 50 nm step size. Figure 6a,b shows that a high number of very small subgrains, bounded by LABs, was present in the HPTE-processed sample. In general, the majority of grains, bounded by HABs (and marked with blue lines in Figure 6d) contained one or more LABs.

We can see in the ACOM TEM maps (Figure 6b,c) that many twin-type GBs were formed during the HPTE deformation within the fine grains, in this way dividing them into smaller grains. The GND density differed significantly in neighboring (sub)grains (Figure 6c), which means that both LABs and twin-types GBs provided effective barriers for the dislocation slip and they should be taken into account in the analysis of possible strengthening factors, in particular Hall–Petch strengthening. Since the volume fraction of twin boundaries increases from the sample´s center to the edge (Table 1), we can conclude that twinning was more active at higher strains. From the nano-twins morphology, it is hypothesized that twinning occurred in the newly formed small grains.


*7.9. Mass Transfer Rate*

Table 5 show the numerical variation in Sherwood number *Shx*. Numerical variation of *Sc*, *Gr*, *n*, and *Nr* are shown. It is observed that the higher value of *Sc*, *Gr*, *n*, and *Nr* augmented the mass transfer rate *Shx* in both SWCNTs and MWCNTs while the opposite impact is found for *Nr*.


**3. Proposed system**

Our protocol is an adaptation of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol that offers an improvement in the clustering procedure.

In our adaptation the random clustering of LEACH will be changed with the K-means clustering algorithm. This adaptation have been improve the clustering allocation and cluster features and generate energy efficient clustering to increase the life of WSNs.

The use of the K-means algorithm as a clustering technique for cluster formation ensures perfect clustering and reduces overheads when the CHs reelection.

This section presents the configuration of the proposed LEACH protocol adaptation, which consists of two phases: the initialization phase and the transmission phase. **Figure 4** illustrates the two phases of proposed adaptation.

**183**

**Figure 5.**

**4. Experiments and performance evaluation**

*The proposed adaptation using clustering with k-means method.*

For example, 100 sensor nodes are randomly deployed over a 100 m2

CH, so the nodes are all normal type. The **Table 2** shows simulation setting.

interest. The SB is positioned at the coordinates (50 m, 200 m). Initially, there is no

area of

**4.1 Sensor nodes deployment**

*K-Means Efficient Energy Routing Protocol for Maximizing Vitality of WSNs*

tance from k-means distance to choose the CH of each cluster.

1.**The initialization phase:** nodes are randomly distributed in the network area, after the clustering process with the K-means method begins, the choice of k-CH is made in this phase using the maximum energy and the minimum dis-

2.**The transmission phase:** the nodes of each cluster begins sending collected data to their own cluster head CH, after some iteration, (if the CH energy of cluster <=Min Energy), a CH update procedure will begin among the alive nodes belongs to the cluster using the same parameters of choice new CH(Min

distance and Max energy) as the beginning in the initialization phase.

**Figure 5** below illustrates the flowchart of operation of the proposed adaptation.

*DOI: http://dx.doi.org/10.5772/intechopen.96567*

**Figure 4.** *The two phases of the proposed adaptation.*

*Computational Optimization Techniques and Applications*

**182**

**Figure 4.**

*The two phases of the proposed adaptation.*

**3. Proposed system**

*Flowcharts of K-means algorithm.*

**Figure 3.**

the life of WSNs.

Our protocol is an adaptation of Low Energy Adaptive Clustering Hierarchy

In our adaptation the random clustering of LEACH will be changed with the K-means clustering algorithm. This adaptation have been improve the clustering allocation and cluster features and generate energy efficient clustering to increase

The use of the K-means algorithm as a clustering technique for cluster formation

This section presents the configuration of the proposed LEACH protocol adaptation, which consists of two phases: the initialization phase and the transmission

(LEACH) protocol that offers an improvement in the clustering procedure.

ensures perfect clustering and reduces overheads when the CHs reelection.

phase. **Figure 4** illustrates the two phases of proposed adaptation.

**Figure 5** below illustrates the flowchart of operation of the proposed adaptation.

**Figure 5.** *The proposed adaptation using clustering with k-means method.*


**2.7 Biosparging**

Biosparging involves the injection of air (oxygen) and nutrients into the saturated zone under pressure to increase groundwater oxygen concentration to stimulate biological activities of the indigenous microorganisms to degrade contaminants [67, 75].

**Figure 7.** *Biotransformation mechanism under the denitrifying conditions.*

### *Biological Treatments for Petroleum Hydrocarbon Pollutions: The Eco-Friendly Technologies DOI: http://dx.doi.org/10.5772/intechopen.102053*

Biosparging technology helps to reduce the contaminant concentration adsorbed to the soil, within the capillary fringe above the water table, and contaminants dissolved in the groundwater. The effectiveness of biosparging depends on soil permeability and pollutant degradability [76]. **Figure 8** illustrates the biosparging process in a polluted site.

In a study conducted by Kao et al. [78], a biosparging technique was deployed in a petroleum oil spill site for 10 months, and the result produced 70% removal efficiency for benzene, toluene, ethylbenzene and xylene (BTEX) within the remedial period.

The benefits of biosparging include; the equipment is easy to instal, creates minimal disturbance to site operation, requires no soil removal or excavation, and a low air injection rate minimises the potential need for vapour capture, and treatment is cost-competitive. The limitation of biosparging is in predicting the direction of airflow in the process as it depends on the high airflow rate to achieve pollutant volatilisation and promote degradation [79]. It is site-specific and can cause the migration of contaminants, some interactions among complex chemicals and biophysical processes are not well understood and used only where suitable [66].

#### **2.8 Bioslurry**

Bioslurry involves the treatment of contaminated soil in a controlled bioreactor such as sequencing batch, feed-batch, continuous and multistage bioreactors [80, 81]. In a bioslurry treatment system, nutrients are added to enhance microbial activities to degrade hazardous contaminants. The bioslurry reactor is designed with various process controls to monitor, control, and manipulate temperature, mix, and add nutrients to achieve maximum removal efficiency. Amendments such as designer bacteria, surfactants, and enzyme inducers can be used in slurry bioreactors to stimulate and enhance biodegradative activities [82]. Bioslurry reactors may be constructed to provide sequential anaerobic/aerobic treatment conditions, as illustrated in **Figure 9**.

Bioslurry is an *ex situ* technology that can be used for bioremediation of problematic sites (when the less expensive natural attenuation or stimulated *in situ* bioremediation are not feasible [84]. The technology has been applied only to remove substances that are not readily degradable and non-halogenated volatile organic compounds, petroleum hydrocarbons and explosive compounds. Slurry-phase bioreactors

**Figure 8.** *Biosparging in petroleum hydrocarbon polluted soil [77].*

**Figure 9.** *Bioslurry mechanisms [83].*

containing co-metabolites and specially adapted microorganisms are used *ex-situ* to treat halogenated compounds, pesticides, polychlorinated biphenyls (PCBs) [85].

In a study conducted by Tuhuloula et al. [86, 87], bioslurry treatment was demonstrated on petroleum hydrocarbon contaminated soil obtained from the oil drilling site of Pertamina Petrochina in Indonesia using microbial consortia of *Bacillus cereus* and *Pseudomonas putida.* The result obtained showed naphthalene removal efficiency between 79.35–99.73% in a slurry bioreactor after 49 days. A similar pilot-scale study conducted by Zhang et al. [85] evaluated aerobic bioslurry phase reactors in treating soil contaminated with explosive compounds (2,4 and 2,6-dinitrotoluenes) at Army Ammunition Plant in Tennesse and Wisconsin, USA. The result obtained showed a removal efficiency of 99%.

The benefits of bioslurry-phase treatment include increased intimated contact between microorganisms and the contaminants, faster degradation rate more than other biological treatments, provides greater control of environmental and operating conditions, and gas emissions are controlled and harnessed as biogas and requires small site space. The disadvantages include; it is an *ex situ* process and requires soil excavation, dewatering of soil after treatment is required and can be expensive, the treatment cost is high when off-gas is treated due to volatile compounds, and sizing materials is difficult and expensive as non-homogeneous soil and clayey soil create materials handling issues, and further treatment of non-recycled effluent is required [82].

#### **2.9 Landfarming**

Landfarming, also known as land treatment or land application, is an aboveground form of bioremediation technology that involves engineered bioremediation systems that employ tilling, ploughing, and spreading the polluted soil in a thin layer on the land surface to enhance and stimulate aerobic microbial activities with the addition of nutrients, mineral and moisture to reduce the pollutant level


Contents

#### **Preface XIII**

#### **X** Contents

**Section 3 Mergers and Acquisitions and Corporate Governance 129**

Chapter 7 **A Comparative Abnormal Return Analysis of Mergers and Acquisitions in the Emerging Markets 131**

Chapter 8 **Corporate Governance and Financial Performance in the**

**Emerging Markets: Do ADRs Perform any Better than**

Chapter 9 **Financing of Working Capital Requirement and Profitability:**

Chapter 10 **The Effects of Working Capital Management on Mining Firm's**

Chapter 11 **The Effect of Working Capital Management on Profitability in Emerging Countries: Evidence from Turkey 205**

**Investment: Panel Evidence from Emerging Markets and**

**Profitability: Empirical Evidence from an**

Mutlu Başaran Öztürk and Gizem Vergili

**Section 5 Financial Economics and Digital Currency 219**

Chapter 12 **The Impact of Exchange Rate Uncertainty on Domestic**

Chapter 13 **Effects of Inflation Uncertainty on Economic Policies: Inflation-Targeting Regime 235**

Okyay Ucan and Nizamettin Basaran

Chapter 14 **The Economics of Foreign Exchange in Emerging Markets 251**

**Evidence from Borsa Istanbul Chemical, Petroleum, Rubber,**

İrem Sevindik and Fazıl Gökgöz

**VI** Contents

**Non-Cross-Listed Firms? 149** Naz Sayari and Bill Marcum

**Section 4 Working Capital Management 173**

**and Plastic Sector 175**

**Emerging Market 189**

Samet Evci and Nazan Şak

**Developing Economies 221** Bilge Canbaloglu and Gozde Gurgun

Mehmet Kenan Terzioğlu

Burcu Dinçergök

Taerel, Anamaria Boboia and Anca Berbecaru-Iovan


i. *"Smart" card fare collection methods -* use read and write technology to store dollar value on a microprocessor chip inside a plastic card. As passengers board a bus, the card reader determines the card's value, debits the appropriate amount for the bus ride, and writes the balance back onto the card, all within a fraction of a second. There are two types of card readers, the proximity reader which can read cards held a few inches away, and the contact reader which requires physical contact with a card. Under development are systems that will be able to read cards carried in passengers' pockets, wallets and purses. Cashless systems such as "smart" cards speed up the fare collection process and eliminate expensive cash handling operations at transit agencies. "Smart" cards can also be programmed for distance - based pricing by recording where a passenger enters a transit system and debiting the appropriate amount from the card

minimized by the DART system operators obtaining a syndicate loan(s).

alternative power source at bus stations and terminals.

affordable rate; close collaboration of the public and private sectors.

employ are described below, but this list is by no means exhaustive:

**5. Intelligent transportation system technology in bus rapid transit**

The success of the DART Project is challenged by the following key factors:

established to cushion against sudden or unusual fare increases.

**4.4.7 Dart project risks and mitigating actions**

fuel price increases.

create awareness or acceptance.

services.

balance according to the point where the passenger exits the system, regardless of the number of internal transfers.

ITS Applications in Developing Countries: A Case Study of Bus Rapid

quality of life.

**9. References**

GmbH.

Corridor:

Vol. 6, pp. 235–248.

1–15–40. *Received April, 2005*

**8. Acknowledgment**

Science foundation of China (No. 70940008).

Transportation Geography, 5 (3), 215-218.

Transit and Mobility Management Strategies in Dar es Salaam – Tanzania 97

need for adequate cross sections on city streets to provide separate rights of way for buses, to maintaining the quality of general purpose traffic flow and minimizing local noise and air quality impacts. These challenges require detailed analysis in the context of specific local applications to identify appropriate solutions and to determine where Bus Rapid Transit can have the greatest benefit. Bus Rapid Transit is a concept that merits widespread evaluation and consideration as an adaptable, effective public transportation alternative to automobiles that has the potential to meet a broad range of mobility needs and support an improved

The author would like to express appreciation to Prof. Yan Chen for guidance and Dr. Qu Lili for providing useful contact. This work was supported by specialized research fund for the doctoral programme of Higher Education (No<PHONE_NUMBER>01) and National Natural

A. K. Bit, M. P. Biswal and S. S. Alam (1993), Fuzzy programming approach to multi

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## **6. Effect of bus rapid transit**

Successful Bus Rapid Transit systems can be expected to produce improvements in bus service, operations, and ridership, and to affect traffic congestion and air quality:

## **7. Conclusion**

The example of Curitiba - Brazil, the experience in the Bogota – Colombia, South Africa and the application of Bus Rapid Transit system in Dar es Salaam Tanzania illustrate the potential of improved bus services to address mobility needs in metropolitan areas. Buses provide flexible and cost effective public transportation. Metropolitan areas throughout the developing cities can build on the experience of Curitiba, Bogota and other developing cities to develop Bus Rapid Transit systems that provide fast, reliable, and convenient service in cities and suburbs. Upgrading the performance of bus services to meet the objectives of Bus Rapid Transit will require policies that give priority to bus operations and provide for investment in crucial system components: infrastructure that separates bus operations from general purpose traffic; facilities that provide for increased comfort and system visibility; and technology that provides for faster and more reliable operations. New guidance, information, and fare technologies offer an expanded range of possibilities for operating bus systems that have the potential to produce marked improvements in performance, surpassing previous standards and changing public perceptions of bus service. High quality bus operations have the potential to create new, improved land use options that provide for compact, pedestrian friendly and environmentally sensitive development patterns that preserve neighborhoods and open space. Bus Rapid Transit thus will have maximum benefit when developed in close coordination with land use policies and community development plans. Implementation of Bus Rapid Transit poses a number of challenges, ranging from the need for adequate cross sections on city streets to provide separate rights of way for buses, to maintaining the quality of general purpose traffic flow and minimizing local noise and air quality impacts. These challenges require detailed analysis in the context of specific local applications to identify appropriate solutions and to determine where Bus Rapid Transit can have the greatest benefit. Bus Rapid Transit is a concept that merits widespread evaluation and consideration as an adaptable, effective public transportation alternative to automobiles that has the potential to meet a broad range of mobility needs and support an improved quality of life.

## **8. Acknowledgment**

96 Intelligent Transportation Systems

Successful Bus Rapid Transit systems can be expected to produce improvements in bus

i. *Bus speeds and schedule adherence -* Perhaps the most fundamental effect of a Bus Rapid Transit system, travel times would likely improve due to the lack of impediments to bus movement along exclusive bus lanes. Bus speeds would be expected to improve not only in absolute terms, but also relative to the automobile traffic that parallels the

ii. *Ridership -* Ridership would be expected to increase due to improved bus speeds and schedule adherence. Customers who use buses infrequently might ride more often, and some automobile users might convert to transit. A visible improvement in bus speeds might be noticeable to drivers of other vehicles, presenting a positive image of transit as

iii. *Other traffic -* If the creation of exclusive bus lanes reduces the number of lanes available for other traffic, then in the short term the possibility of increased congestion on the roadways is raised. Traffic flow on cross streets and turning traffic may be disrupted as buses use their signal priority to travel uninterrupted through intersections. Further, mobility on alternate routes may deteriorate, as drivers seek ways to avoid roads with exclusive bus lanes. One of the challenges of implementing an exclusive bus lane would

iv. *Air quality -* Long term, as ridership increases and the overall level of general purpose traffic decreases, urban areas may experience improved air quality due to reduced

The example of Curitiba - Brazil, the experience in the Bogota – Colombia, South Africa and the application of Bus Rapid Transit system in Dar es Salaam Tanzania illustrate the potential of improved bus services to address mobility needs in metropolitan areas. Buses provide flexible and cost effective public transportation. Metropolitan areas throughout the developing cities can build on the experience of Curitiba, Bogota and other developing cities to develop Bus Rapid Transit systems that provide fast, reliable, and convenient service in cities and suburbs. Upgrading the performance of bus services to meet the objectives of Bus Rapid Transit will require policies that give priority to bus operations and provide for investment in crucial system components: infrastructure that separates bus operations from general purpose traffic; facilities that provide for increased comfort and system visibility; and technology that provides for faster and more reliable operations. New guidance, information, and fare technologies offer an expanded range of possibilities for operating bus systems that have the potential to produce marked improvements in performance, surpassing previous standards and changing public perceptions of bus service. High quality bus operations have the potential to create new, improved land use options that provide for compact, pedestrian friendly and environmentally sensitive development patterns that preserve neighborhoods and open space. Bus Rapid Transit thus will have maximum benefit when developed in close coordination with land use policies and community development plans. Implementation of Bus Rapid Transit poses a number of challenges, ranging from the

service, operations, and ridership, and to affect traffic congestion and air quality:

**6. Effect of bus rapid transit**

exclusive lanes.

an alternative to driving.

be to minimize this disruption.

emissions from automobiles

**7. Conclusion**

The author would like to express appreciation to Prof. Yan Chen for guidance and Dr. Qu Lili for providing useful contact. This work was supported by specialized research fund for the doctoral programme of Higher Education (No<PHONE_NUMBER>01) and National Natural Science foundation of China (No. 70940008).

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**4**

*Cyprus*

**Modelling, Simulation Methods for Intelligent Transportation Systems**

Effective transportation systems lead to the efficient movement of goods and people, which significantly contribute to the quality of life in every society. In the heart of every economic and social development, there is always a transportation system. Meanwhile, traffic congestion has been increasing worldwide because of increased motorization, urbanization, population growth, and changes in population density. This threatens the social and economic prosperity of communities all over the world. Congestion reduces utilization of the transportation infrastructure and increases travel time, air pollution, and fuel consumption. Therefore, managing and controlling transportation systems becomes a high priority task for every community, as it constitutes a matter of survival and prosperity for

In the search for meeting the demand for more traffic capacity, it has been realised repeatedly that building more roads is no longer a feasible solution due to the high cost and/or scarcity of land especially in metropolitan areas. In addition, the length of time that it takes to build additional roads and the disruption that this introduces to the rest of the traffic network makes the option of building new roads as the worst case scenario. The current highway transportation system runs almost open loop whereas traffic lights at surface streets are still lacking the intelligence that is necessary to reduce delays and speed up traffic flows. The recent advances in electronics, communications, controls, computers, and sensors provide an opportunity to develop appropriate transportation management policies and strategies in order to effectively utilize the existing infrastructure rather than building new road systems. The use of technologies will help provide accurate traffic data, implement control actions, and in general reduce the level of uncertainty and randomness that exists in today's transportation networks. The successful implementation of intelligent transportation systems will require a good understanding of the dynamics of traffic on a local as well as global system level and the effect of associated phenomena and disturbances such as shock wave generation and propagation, congestion initiation and so on.  There

**1. Introduction**

humanity.

crucial.

George Papageorgiou and Athanasios Maimaris *European University Cyprus and University of Cyprus*


**3. Inversion of** *σ***(***ω***) to Measure the Directional Wave Spectrum**

The aim of inversion is to obtain the ocean wave directional spectrum, *S*( *k*), from the power spectrum of the measured radar cross section, *σ*(*ω*) using Equations (24) and (28). The power spectrum of the backscattered radar signal is proportional to *σ*(*ω*) and therefore in principle needs to be calibrated to account for antenna gains, propagation losses and other factors. To avoid this the problem is usually framed in terms of the ratio of the second and first order backscatter power spectra. A number of inversion methods have been published e.g., [6,8,9,15,16,30]. Here we use the method of Wyatt [10,11] which is referred to in this paper as the Seaview inversion method since Seaview Sensing Ltd has an exclusive license from the University of Sheffield to commercialise the software package and continue its development.


**Yanjun Zhang**

Yanjun Zhang is a Professor at the Spice and Beverage Research Institute, Chinese Academy of Tropical Agricultural Sciences. He graduated from Nanchang University with a major in Food Science and Engineering in 2012. He is engaged in scientific research on starch. Taking tropical grain crops and jackfruit starch as representative material, research has been carried out on the basic theory and application of technology with ideas including the relationship between starch functional characteristics and molecular structure, the pasting and retrogradation properties of starch controlled by the molecular weight of amylopectin, and starch digestion improved through innovative methods. The special functional properties and molecular structure of jackfruit starch have been clarified. The control theory of starch pasting and retrogradation has been enriched based on the cognition of starch structure and function. An efficient preparation method has also been established for improving the digestibility and utilization rate of jackfruit starch. The previous research led to 64 publications, 7 national invention patents, and the Hainan Provincial Science and Technology Progress Award in 2017. The applicant was selected from national-level talents: Shennong Talents, Jiangxi Province Double Thousand Plan leading talents, Hainan Province South Sea famous, 515 talent project second level, hot science excellent youth, and other candidates.