Computational complexity at the receiver of RC, SMP, and SM techniques [22].
\\n\\n
More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:{caption:"IntechOpen Maintains",originalUrl:"/media/original/113"}},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
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\r\n\tThe global population will be nearly 10 billion by 2050, which means there will be about 2 billion more mouths to feed than in 2021. Rice is one of the most important staple foods in the world, where more than half of the population relies on it for more than 20% of their daily caloric intake. It is projected that global rice production will need to increase by 70% by 2050 to meet the food demands of the world’s growing population. Satisfying future rice demands will mainly depend on our ability to improve rice productivity rather than on the area enlargement of rice paddies because of space limitations caused by urban expansion. At the same time, we also require efforts to improve the rice quality because the demand and consumption of high-quality rice will increase as living standards improve. In addition, we urgently need to develop new technologies and strategies to overcome the constraints (e.g., climate change, soil degradation, and biodiversity loss) confronting the sustainable development of rice production. This book will aim to collect original research and review articles focused on but not limited to, the topics of rice productivity, quality, and sustainability.
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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"72",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",isOpenForSubmission:!1,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",slug:"ionic-liquids-theory-properties-new-approaches",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"2270",title:"Fourier Transform",subtitle:"Materials Analysis",isOpenForSubmission:!1,hash:"5e094b066da527193e878e160b4772af",slug:"fourier-transform-materials-analysis",bookSignature:"Salih Mohammed Salih",coverURL:"https://cdn.intechopen.com/books/images_new/2270.jpg",editedByType:"Edited by",editors:[{id:"111691",title:"Dr.Ing.",name:"Salih",surname:"Salih",slug:"salih-salih",fullName:"Salih Salih"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"117",title:"Artificial Neural Networks",subtitle:"Methodological Advances and Biomedical Applications",isOpenForSubmission:!1,hash:null,slug:"artificial-neural-networks-methodological-advances-and-biomedical-applications",bookSignature:"Kenji Suzuki",coverURL:"https://cdn.intechopen.com/books/images_new/117.jpg",editedByType:"Edited by",editors:[{id:"3095",title:"Prof.",name:"Kenji",surname:"Suzuki",slug:"kenji-suzuki",fullName:"Kenji Suzuki"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"56160",title:"Spatial Modulation – A Low Complexity Modulation Technique for Visible Light Communications",doi:"10.5772/intechopen.68888",slug:"spatial-modulation-a-low-complexity-modulation-technique-for-visible-light-communications",body:'The need for high data rate transmission to meet the demands of existing and emerging data-intensive applications and services is one of the key elements driving the research in the area of wireless communications access technology. Visible light communication (VLC) system, with its significantly large inherent optical spectrum, is a promising technology capable of delivering high data rates. However, one of its major drawbacks is the limited modulation bandwidth of light emitting diodes (LEDs). This limitation prevents some of the conventional wireless modulation techniques from fully exploiting the huge optical spectrum in achieving high-speed communications. To fully utilise the inherent resources of VLC while mitigating the effects of this limitation, a multiple-input multiple-output (MIMO) access technique such as spatial modulation (SM) is an attractive option.
SM technique in VLC facilitates efficient management of the limited LED modulation bandwidth in a power-efficient manner without sacrificing the complexity of the system. A study in Ref. [1] proposed SM for optical wireless systems using the same principle of SM for a radio frequency (RF) system [2]. One of the interesting features of VLC is the possibility of the system to serve a dual function of data transmission by intensity-modulating LEDs alongside their primary purpose of illumination. In practice, an LED luminaire usually has multiple LEDs used for illumination due to the limited luminous flux of an individual LED. Thus, SM leverages the spatial dimensions of these multiple LEDs as an additional degree of freedom for high data rate transmission [1]. The information sequence to be transmitted is mapped to symbols chosen from the signal constellation points of a digital modulation technique. The fundamental concept of SM relies on these spatially separated LEDs considered as spatial constellation points, which are utilised to convey additional information bits [3]. During a symbol duration, the transmit bits are mapped to one of the spatial constellation points, thereby activating one transmit unit only at a particular time instance. The strength of channel correlation between the transmit-receive unit plays a significant role in the performance of the SM technique. Hence, there is a need for intensive research on performance enhancement schemes of SM.
Various optical SM techniques in VLC reported in the literature to enhance the data rate include spatial pulse position modulation (SPPM) proposed in Ref. [4], where a combination of space shift keying (SSK) and pulse position modulation (PPM) is considered. The idea was later generalised in Ref. [5] by activating multiple LEDs during each symbol’s duration in order to increase the number of bits transmitted at a time instance. The use of optical space shift keying (OSSK) [6], spatial pulse amplitude modulation (S-PAM) [7], and generalised space shift keying (GSSK) [8] to boost VLC spectral efficiency using SM has equally been investigated.
The focus of this chapter is to address the error performance challenges of SM in VLC. A detailed description of the conventional SM and different variants of SM is presented. Analytical expressions for the error performance evaluations of these variants are derived in the presence of VLC channel impairments and additive white Gaussian noise (AWGN). These solutions are compared with computer-based simulations to validate the closed-form expressions. Furthermore, the attainable data rate using SM is quantified by comparing the spectral efficiency of SM with the classical modulation techniques such as on-off keying (OOK) and PPM.
In a VLC system with
An illustration of the encoding mechanism of an optical SM technique.
The signal emitted by the active LED propagates through the optical wireless channel. At the receiving end, the radiated signal is detected by one or more PDs. The channel condition of each transmitter-receiver path is described by the channel impulse response
where
where
At the receiver, the detector exploits the uniqueness of the channel condition associated with each transmit-receive channel path to estimate the transmitted data symbol. Thus, a prior knowledge of channel impulse response (CIR) of all the transmit-receive paths is required at the receiver. In practice, the CIR can be obtained through channel estimation technique. According to the maximum likelihood (ML) criterion, the detector computes the Euclidean distance between the received signal and the set of possible signals from all the
where
Due to its promising potentials as highlighted in Section 1, SM has been implemented for VLC systems in various forms. Differences in these variants include, but are not limited to, the inclusion or exclusion of digital signal modulation, the type of digital signal modulation employed, and the number of optical sources that are activated concurrently. Brief descriptions of some reported variants of optical SM are provided as follows.
An illustration of OSSK modulation using four LEDs.
An illustration of the pulse pattern for GSSK scheme using two LEDs.
An illustration of intensity modulation for SPPM scheme using four LEDs.
where
In the GSPPM scheme [5], during a given symbol duration, one or more LEDs can be activated to concurrently transmit the same
An illustration of GSPPM scheme.
Beside SM, other MIMO transmission techniques that have been considered for VLC include repetitive coding (RC) and spatial multiplexing (SMP). In RC, the same information is simultaneously transmitted from all the transmitters, and the transmitted signals add up constructively at the receiver. In essence, RC offers diversity gain, which makes it more robust to channel the correlation compared to SMP and SM. However, since RC does not provide spatial multiplexing gains, large signal constellation sizes will be required to achieve high spectral efficiency. In contrast, SMP enables high data rates by transmitting different kinds of information from each transmitter. The drawback of SMP is that it requires sufficiently low channel correlation. SM is more robust to correlated channels compared to SMP, and it provides larger spectral efficiency compared to RC [7].
In terms of complexity, the optical SM constitutes a low complexity technique of increasing the achievable transmission rates in VLC systems. Compared to other spectrally efficient modulation schemes like the optical OFDM [19] and PAM, the SM technique is not as sensitive to nonlinearity effects of the system components [4, 20]. Hence, SM-based VLC systems do not require the complex pre-distortion algorithm to compensate for device nonlinearity. Moreover, since only one or a few LED(s) is active in each symbol duration, inter-channel interference (ICI), which results from multiple and concurrent signal transmission, is reduced in optical SM as compared to RC and SMP. Hence, receiver design is made simpler and ML-optimum performance can be achieved at a reduced decoding complexity [21].
The computational complexity of the ML-based detection of optical S-PAM is compared with that of RC and SMP in Table 1 [22]. The computational complexity is defined as the total number of required mathematical operations, that is, multiplications, additions, and subtractions that are required for ML detection. Table 1 shows that, to achieve equal spectral efficiency, the detection of SM is less computationally intensive compared to RC and SMP. Because SM conveys additional bits via the spatial domain, it employs a smaller digital signal constellation size to achieve the same spectral efficiency as RC.
MIMO technique | Number of mathematical operations at the receiver |
---|---|
RC | |
SMP | |
SM |
Computational complexity at the receiver of RC, SMP, and SM techniques [22].
In this section, the error performance of four variants of optical SM technique is analysed and closed-form expressions for their symbol error are derived. These expressions are validated using Monte-Carlo simulations. The optical SM variants considered are SPPM, OSSK, GSSK, and GSPPM. In the following, without any loss of generality, a MIMO VLC system,
As described in Section 2.2, the data symbol in SPPM is conveyed by the index of the active LED and the pulse position of the transmitted PPM signal. These two parameters must be estimated at the receiver in order to demodulate the transmitted symbol. Hence, error performance analysis will involve evaluating the probability of the correct pulse position and LED index detection. Considering that an SPPM symbol is transmitted by activating the
The nonzero entry,
where
where
where
The joint probability density function of
and the Euclidean distance metric
where
and then estimating the index of the activated LED from the minimum Euclidean distance metric using the ML detection criterion.
Let the probability of a correctly decoded pulse position be defined by
and the probability of symbol error is obtained as:
where
and the probability of correctly decoding the index of the activated LED is computed as:
where,
Therefore,
For
Thus, the average probability of correctly decoding the transmitted pulse position is:
By combining Eqs. (16), (19), and (25), the union bound on the average probability of symbol error of the SPPM scheme is derived as [4]:
The expression in Eq. (26) indicates that for a given SNR, the error performance of SPPM strongly depends on the individual channel path gain of each transmitter-receiver link as well as the difference between these channel gain values. The error performance plots for different system configurations are shown in Figure 6. For the case of
Error performance plot of SPPM for
Moreover, as
Using the description of the OSSK scheme provided in Section 2.2, OSSK can be viewed as a subset of SPPM scheme in which
where
Using the closed-form expression in Eq. (27), the SER of OSSK is plotted against the SNR per bit
Error performance plot of OSSK for
According to the GSSK scheme described in Section 2.2, during a symbol duration, the number and the indices of the active LEDs are determined by the bits of the data symbol to be transmitted. Using
For tractability,
As an illustration, considering a 2-LED GSSK system with
Binary equivalent | Activated LED | |||
---|---|---|---|---|
0 | 00 | LED 1 and LED 2 | ||
1 | 01 | LED 1 | ||
2 | 10 | LED 2 | ||
3 | 11 | LED 1 and LED 2 |
LED activation for GSSK modulation using two LEDs.
where
where
Without loss of generality, using
Error performance plot of GSSK for
The performance analysis of GSPPM scheme entails combining the detection process in GSSK with the pulse position detection in SPPM. The transmitted symbol consists of the spatial constellation point, which determines the active LED and the pulse position of the transmitted PPM signal. Let
where
Spatial constellation | Activated LED | |||
---|---|---|---|---|
00 | LED 1 and LED 2 | −1 | ||
01 | LED 1 | 1 | ||
10 | LED 2 | 1 | ||
11 | LED 1 and LED 2 | 1 |
LED activation and received signal for two-LED GSSPM system.
The error performance analysis will involve evaluating the probability of correctly estimating the spatial constellation point and the pulse position. The detection of the transmitted spatial constellation in GSPPM is equivalent to the detection of the transmitted GSSK symbol in Section 3.3. Hence, the probability of correctly detecting the transmitted spatial constellation is obtained as [5]:
where
By combining Eqs. (34) and (35), the union bound on the average probability of symbol error of the GSPPM scheme is derived as [5]:
As shown in Figure 9, the closed-form expression for the theoretical SER of GSPPM in Eq. (36) is validated by simulation results. Moreover, the plot also highlights the energy efficiency benefit that PPM adds to GSPPM. As
Error performance plot of GSPPM for
Using GSPPM as a case study, the impact of channel gains on the performance of optical SM is illustrated in Figure 10 with the error performance plot for different channel gain values. The plots show that the higher the difference between the channel gains, the lower the SNR required to achieve a given SER. According to Eq. (36), the SER also depends on the absolute value of the channel gains. For instance, to achieve an SER of 10−6, the normalised channel gain [
Error performance plot of GSPPM for different channel gains,
A performance comparison among different variants of optical SM and other common modulation schemes used for optical wireless communications is shown in Table 4. These modulation schemes are compared based on the average transmitted optical power
Modulation type | |||
---|---|---|---|
RC RZ-OOK | 1 | ||
RC | |||
SSK | |||
GSSK | |||
SPPM | |||
GSPPM |
Comparison of optical modulation schemes.
Considering the case of
Spectral efficiency comparison of optical SM schemes.
Energy efficiency comparison of optical SM schemes.
In this chapter, a detailed description of SM signal generation and detection for VLC systems has been discussed. An overview of different variants of optical SM—OSSK, GSSK, SPPM, S-PAM, and GSM—with their error performance analysis under VLC channel impairments and AWGN has been presented. The analyses of the error performance of these variants have been derived using union bound method and ML criteria. The analytical expressions enabled the theoretical evaluation of the error probability of optical SM technique in a typical MIMO VLC system. Results showed a perfect match between theory and simulations. A summary of the differences between optical SM and other MIMO transmission schemes like SMP, RC, and spatial diversity has also been discussed. The optical SM is thus a technique capable of delivering high data rates in the presence of the limitations of the optical front-end devices. This chapter concludes with the comparison of the spectral and energy efficiency of the variants of optical SM.
As early as 1922, Harvey Cushing distinguished two types of meningiomas: spherical
While meningiomas account for approximately 20% of all intracranial tumors in males and 38% in females (with a 2:1 female-to-male ratio) [9, 10], SOMs comprise between 4% and 9% of all meningiomas [11]. In a meta-analysis of 38 retrospective studies about SOM that included a total of 1486 patients, Fisher
In a review of the literature, Apra
Patients typically present with progressive, unilateral, and nonpulsatile proptosis (84%), often associated with cosmetic deformity [12, 15]. The frequent optic nerve (ON) disturbances result in unilateral decreased visual acuity (46%), constricted visual field (31%), and sometimes loss of color vision (5%) [12]. Ophthalmoplegia is seen in 25% of patients with SOM, often due to cranial oculomotor nerves deficit (oculomotor nerve 11%; trochlear nerve 6%; abducens nerve 4%). Diplopia can also be caused by intraorbital compression of the oculomotor muscles. Deficits in other cranial nerves (trigeminal, vestibulocochlear, and facial nerves) are less common. Finally, other general neurological signs, such as headaches (25%) and epileptic seizures (4%), are observed in patients with SOM.
Skull radiographs were historically used to diagnose SOM by demonstrating unilateral sphenoid hyperostosis. With the emergence of computed tomography (CT) and magnetic resonance imaging (MRI), these techniques became the standard before any surgical procedure involving the removal of a SOM.
CT precisely demonstrates the bone features of the SOM, as well as its extension (Figures 1 and 2). Using CT, the involvement of the orbit walls, floor of the middle cranial fossa (including the foramens rotundum and ovale), SOF, ACP, and optic canal can be easily identified.
(a) Axial contrast-enhanced T1-weighted magnetic resonance imaging demonstrates thickening of the temporopolar dura mater on the right side, with a deviated optic nerve compared to the left side. A temporopolar arachnoid cyst is seen on the left side. (b) Axial computed tomographic scan shows hyperostosis of both the lesser and greater sphenoid wings, sparing the anterior clinoid process. Proptosis can be easily measured on axial brain slices passing through the lens on both sides, by firstly taking as reference the line joining the two lateral orbital margins. This line is then projected to the level of each cornea and the distance between these two new lines is measured, giving an accurate and relevant estimate of proptosis for follow-up.
(a) Axial contrast-enhanced T1-weighted magnetic resonance imaging demonstrates a large right spheno-orbital meningioma with middle sphenoid wing center, invading the temporal fossa (TF), the superior orbital fissure (SOF), and the orbit (O). There was no true invasion of the optic canal (OC) by the meningioma on thin-section MRI analysis. (b) Axial computed tomographic scan shows hyperostosis of the lesser and greater sphenoid wings (L&GSW) and anterior clinoid process (ACP) on the right side.
MRI completes the radiological assessment, showing the globoid or plaque-like shape of the intradural portion of the meningioma and its impact on the brain parenchyma (mass effect and edema). The epicenter of the tumor on the sphenoid wing is identified, and the specific involvement of the temporal and infratemporal fossae, orbit, SOF, optic canal, and CS is determined. At this stage, it is important to differentiate between simple involvement of the lateral wall of the CS and true intracompartment invasion. Similarly, the presence of meningioma within the optic canal or SOF should be similarly distinguished from tumor bony involvement of these structures (Figures 1 and 2). All of these details are critical, as they contribute to the planning of the upcoming surgical procedure for optimal tumor resection.
A comprehensive preoperative ophthalmological exam is mandatory and should include at least an objective assessment of visual acuity and field, a dilated-pupil fundus examination and ideally an optical coherence tomography (OCT). The Lancaster red-green test for assessment of oculomotor muscle function is performed according to the presence of diplopia. Accurate measurement of the proptosis can be achieved with an exophthalmometer or with correctly oriented cerebral imaging (Figure 1).
At this time, differential diagnosis for hyperostosis due to SOM should also be considered. These include fibrous dysplasia, osteoma, osteoblastoma, Paget’s disease, hyperostosis frontalis interna, osteoblastic metastases, and erythroid hyperplasia [15].
As with all other meningiomas, the decision-making process for SOM must be tailored to each patient. Mass effect of the tumor, age, general condition, comorbidities, symptomatology, its impact on daily life, and the patient’s wishes must be taken into account. In cases with absent or mild symptoms without mass effect on imaging, simple clinical and radiological monitoring can be chosen initially, with patient follow-up on a regular basis (every 3–6 months). In contrast, the presence of optic neuropathy, severe neurological symptoms, significant proptosis, or serious mass effect warrants surgical operation. Although a subject of debate, optimal surgical resection remains the current reference treatment for SOM, in accordance with the general EANO (European Association of Neuro-Oncology) guidelines for the management of meningiomas published in 2016 [16]. If the patient is in a fragile state of health or categorically refuses the operation, radiation treatment may be offered as an alternative. The choice of technique is then mainly based on the tumor volume, stereotactic radiosurgery being preferred for smaller tumors and radiotherapy being preferred for larger tumors. To summarize this reasoning, we propose a simple algorithm highlighting the main points to be taken into account during decision-making in cases of SOM (Figure 3).
Decision-making algorithm of first-line treatment for spheno-orbitary meningiomas, in accordance with the 2016 EANO guidelines [
Despite their common features, SOMs are a heterogeneous group of tumors due to the complex anatomy of the sphenoid bone, which is a part of both the skull base and the orbit. Few attempts have been made to classify SOMs. Roser
Classification of spheno-orbital meningiomas according to their morphology (a), sphenoid wing epicenter (b), and specific extensions (c).
The patient is placed in a supine position with the head rotated 30° to the contralateral side and fixed in a three-pin Mayfield head-holder. The neck is slightly extended to 15°, as is done for a classical pterional approach. Neuronavigation is used to delineate the craniotomy and skin incision. We recommend using millimeter slices of the bone window of the CT scan for registration, to both highlight bone tumor extension and increase the accuracy of this technique [19, 20]. The CT scan is then merged with the MRI, including the gadolinium-enhanced 3D T1-weighted sequence, for intra- and extracranial tumor extensions (Figure 4). A paraumbilical field is prepared and draped to harvest abdominal fat for closure if needed.
The frontotemporal arciform incision starts 1 cm in front of the tragus, with the medial extent adjusted to the size of the surgical target. The scalp is progressively elevated in one layer and reclined forward, preserving the pericranial tissue for dural repair at the time of closure. A standard interfascial dissection is performed over the anterior quarter of the temporal muscle in order to spare the frontotemporal branches of the facial nerve [21, 22]. The orbital rim and zygomatic arch are progressively exposed in a subperiosteal manner. The temporal muscle is incised along the lateral orbital rim, along the superior temporal line, and at its posterior part along the skin incision. Retrograde dissection of the temporal muscle is performed using a cutting spatula from anterior to posterior and from inferior to superior in order to preserve the deep vascularization and innervation of the muscle and thus prevent postoperative atrophy [23]. Tumor-infiltrating of the muscle (1.) temporal fossa extension) must be resected at this stage. If the infratemporal fossa is invaded by the meningioma (2.) infratemporal fossa extension), the zygomatic arch must be cut anteriorly and posteriorly, maintaining its attachment to the masseter muscle, in order to recline the temporal muscle downwards as much as possible. This optional step facilitates resection of the tumor portion located in the infratemporal fossa, with particular attention to the mandibular nerve exiting the foramen ovale. In cases of major invasion of this location, the collaboration of an ear, nose, and throat surgeon is required.
Depending on the extension of the intraosseous portion of the SOM, either a classical pterional craniotomy or a more complex orbitozygomatic approach is performed [24]. Guided by neuronavigation, the tumor-infiltrated bone must be resected as completely as possible using a high-speed drill and rongeurs, without overlooking the craniotomy part. The lateral wall and the roof of the orbit are drilled, initially respecting the periorbita (Figure 5). The intraorbital tumor extension (3.) mostly remains extraconal and can therefore be easily removed once the orbit is correctly opened. Nevertheless, the periorbit must be longitudinally opened and resected in cases of intraconal invasion [25]. If the tumor adheres too much to the cranial nerves, it is recommended to leave a residue in place to avoid postoperative deficits. The drilling continues medially at the level of the greater and lesser wings of the sphenoid bone, opening the SOF (4.), and inferiorly at the level of the floor of the middle cranial fossa, opening the foramens rotundum and ovale if necessary. With the involvement of the ACP (5.) and the invasion of the optic canal (6.), an extradural anterior clinoidectomy, which is carried out under magnification and constant irrigation, must be performed to optimize the decompression of the ON and prevent thermic lesions [26]. This step also allows the surgeon to extradurally split the lateral wall of the CS (7.) when there is a tumor at this level, in order to improve the devascularization of the meningioma.
Intraoperative views of the resection of a left sphenoid-orbital meningioma with invasion of the anterior clinoid process (ACP), optic canal, and orbit. (a) Left pterional approach with drilling of the lesser sphenoid wing (LSW) and lateral wall of the orbit, in order to open the superior orbital fissure (SOF). The orbito-temporal periosteal fold is then identified at the external part of the SOF and divided to optimize the retraction of the frontal and temporal lobes and expose the contours of the ACP. (b) The final step of the extradural resection of the ACP. The LSW, optic strut, and roof of the optic canal were drilled before resecting the bony content inside the ACP. A thin shell of bony contour is preserved in order to remove the clinoid tip en bloc. (c) Once the drilling is completed, the orbit is properly exposed in continuity with the SOF and optic canal which have been opened. (d) The dura mater is opened in an arciform fashion, revealing the intradural portion of the meningioma (asterisk). (e) The dura mater of the optic canal is gently opened with a fine scalpel to remove the tumor fragments compressing the optic nerve at this level. (f) At the end of the procedure, the chiasma and the two optic nerves are correctly exposed. The coagulated portion of the dura mater at the level of the tuberculum sellae can be seen (asterisk; Simpson grade 2 resection).
The dura mater is opened in a curvilinear fashion and the intradural portion of the tumor is progressively resected using conventional microsurgical methods, alternating debulking and peripheral dissection from the brain parenchyma and vessels. An additional dural incision directed medially toward the optic canal may cautiously be performed to complete the extradural anterior clinoidectomy. Once the optic canal has been widely opened intradurally (Figure 5), the tumor fragments at this level can be easily removed using a small blunt hook.
Complete resection is not always possible due to true intracavernous invasion (as opposed to a simple extension to the lateral wall) or excessive tumor adherence in the SOF or optic canal. In such situations, the key is to optimally decompress the ON so that the residual tumor can later be effectively treated with radiation therapy. The radiosensitivity of the ON justifies the creation of a safety zone around it, in order to avoid deleterious iatrogenic irradiation during radiation treatment. It is essential to preserve the function of the cranial nerves as much as possible, as their postoperative recovery is often uncertain.
If the ethmoidal or sphenoidal sinuses are open during the extradural steps, either autologous fat or a temporal muscle graft should be harvested to plug the defect, depending on the size of the opening (for example, the muscle should be used for a small aperture of a pneumatized ACP and fat should be used for a large sinus opening secondary to intranasal tumor invasion). A synthetic fibrin sealant may be used in addition to these measures to prevent postoperative cerebrospinal fluid leakage. The dural and periorbital defects are ideally managed using a vascularized and pedicled pericranial graft that is rotated over the orbit. Alternative solutions include using the temporal fascia or synthetic dura patches. Finally, the remaining dead space left by the tumor removal can be filled with a fat graft.
Bone reconstruction for SOM is often more complex than for other meningiomas due to the extensive bony resection, which sometimes involves the superior and lateral orbital rims. Various options are available to perform cranioplasty and obtain a satisfactory cosmetic result. If the orbital margins are intact, the healthy part of the craniotomy can be replaced using grids that are cut to a suitable shape and serve as anchor points for the reinsertion of the temporal muscle. For larger defects, hydroxyapatite cement can be shaped easily. A custom-made polymethylmethacrylate or polyetheretherketone (PEEK) prosthesis can be ordered before the procedure, especially when the orbital rims are planned to be resected. The design of the prosthesis can also compensate for temporal muscle atrophy by incorporating an increased thickening at the level of the temporal fossa. Trimming of the edges of the prosthesis is often required to perfectly match the craniotomy. The zygomatic osteotomy must be reattached with standard plates before reinserting the temporal muscle and suturing the scalp in layers according to the usual technique.
The first postoperative night is ideally spent in an intensive care unit, so that the patient can be closely monitored, and any respiratory, hemodynamic, or neurological failures can be detected at an early stage, particularly in the event of a surgical site hematoma. Most postoperative complications of SOM are related to the cranial nerves affected by the tumor. In their meta-analysis of retrospective series of operated SOM, Fisher
In most cases, SOM surgery stabilizes or improves visual function. In a large retrospective study of 130 patients, Terrier
Regarding oculomotion, the reporting of results is generally less detailed, but seems to indicate a long-term improvement of the preoperative symptomatology that could reach 96% (although the degree of this improvement was not specified) [12]. Postoperative oculomotor deficits are frequent, varying from 8 to 68% depending on the series, but they recover in the majority of cases and persist in only 0–17% of cases [6, 11, 30, 31].
Proptosis, the most common sign encountered in patients with SOM, may be explained by different, yet interrelated, factors. From a mechanical point of view, the bony involvement of the orbital walls and the intraorbital tumor extension exert a direct mass effect on the eyeball. From a vascular point of view, the meningioma invasion of the SOF is responsible for a decrease in venous drainage and subsequently exacerbates the proptosis by increasing the intraorbital venous engorgement [32, 33]. This multifactorial physiopathology may explain the varied results from retrospective clinical series, which report improvements ranging from 50 to 100% [34, 35, 36, 37, 38, 39]. Thus, if mechanical compression is relieved by surgical opening of the orbit and resection of the intraorbital portion of the tumor, exophthalmos will certainly improve. Nevertheless, it is rare that the proptosis recovers completely, likely due to persistent disturbances of venous drainage and potential trophic disorders of the oculomotor muscles. Removal of the periorbit appears to have a beneficial effect and seems to be a key factor in reducing proptosis [29].
The quality of surgical resection of meningiomas, assessed by Simpson’s grading system, remains an important prognostic factor in the evolution of these tumors, regardless of the histological subtypes considered [40, 41]. Gross total resection, defined as Simpson grade I to III, is achieved in 25–70% of SOM cases depending on the series [34, 42, 43, 44]. Given the complex anatomy of the spheno-orbital region, Simpson grade I or II resections are rarely feasible without risking the induction of cranial nerve deficits, especially at the level of the orbital apex, SOF, and CS [43]. In this context, the current trend is strongly in favor of symptom-oriented surgery rather than radical surgery, targeting optic nerve decompression to improve visual function, and intraorbital tumor resection to reduce proptosis [30, 32].
Histologically, SOMs are commonly World Health Organization (WHO) grade I tumors (77–100%, depending on the series), with the meningothelial subtype being the most frequent [11, 13, 28, 43]. Although much less frequent, WHO grade II (atypical) or III (anaplastic) meningiomas may be encountered, together representing 11% of the cases in the retrospective series presented by Belinsky
The highly variable recurrence rate of SOM in the scientific literature, ranging from 10 to 56%, is likely due to differences in the follow-up duration [34, 47, 48, 49]. Indeed, the risk of recurrence logically increases with the duration of follow-up (6% at 3 years and 46% at 6 years after the intervention) [28].
The role and timing of radiation therapy remain a matter of debate for meningiomas in general and SOM in particular. However, experts (Response Assessment in Neuro-Oncology Committee) agree on the importance of using adjuvant radiotherapy for WHO grade III meningiomas, regardless of the quality of surgical resection [40]. For WHO grade II meningiomas, the European Association of Neuro-Oncology guidelines recommends observation or fractioned radiotherapy in cases of gross total resection and fractioned radiotherapy in cases of subtotal resection [16]. For WHO grade I meningiomas, simple observation is indicated after gross total resection, and stereotactic radiosurgery or fractioned radiotherapy may be proposed after subtotal resection. We suggest radiological monitoring of the tumor residue for subtotal resections of WHO grade I meningiomas initially. Stereotactic radiosurgery is then justified in cases of objective progression. Cases of meningiomas of WHO grade II or III must be discussed in a collegial manner in a multidisciplinary consultation meeting.
Spheno-orbital meningiomas are usually slow-growing skull base tumors revealed by proptosis or visual impairment. They typically present with significant tumoral spheno-orbital hyperostosis and a globoid or
ACP | Anterior clinoid process |
CS | Cavernous sinus |
CT | Computed tomography |
MRI | Magnetic resonance imaging |
OCT | Optical coherence tomography |
ON | Optic nerve |
SOF | Superior orbital fissure |
SOM | Spheno-orbital meningioma |
WHO | World Health Organization |
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\\n\\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
\\n\\nDigital Archiving Policy
\\n\\nIntechOpen is committed to ensuring the long-term preservation and the availability of all scholarly research we publish. We employ a variety of means to enable us to deliver on our commitments to the scientific community. Apart from preservation by the Croatian National Library (for publications prior to April 18, 2018) and the British Library (for publications after April 18, 2018), our entire catalogue is preserved in the CLOCKSS archive.
\\n\\nOpen Science is transparent and accessible knowledge that is shared and developed through collaborative networks.
\\n\\nOpen Science is about increased rigour, accountability, and reproducibility for research. It is based on the principles of inclusion, fairness, equity, and sharing, and ultimately seeks to change the way research is done, who is involved and how it is valued. It aims to make research more open to participation, review/refutation, improvement and (re)use for the world to benefit.
\\n\\nOpen Science refers to doing traditional science with more transparency involved at various stages, for example by openly sharing code and data. It implies a growing set of practices - within different disciplines - aiming at:
\\n\\nWe aim at improving the quality and availability of scholarly communication by promoting and practicing:
\\n\\n\\n"}]'},components:[{type:"htmlEditorComponent",content:'
The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\n\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\n\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
\n\n“By “open access” to [peer-reviewed research literature], we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited” (reference: http://www.budapestopenaccessinitiative.org)
\n\nOAI-PMH
\n\nAs a firm believer in the wider dissemination of knowledge, IntechOpen supports the Open Access Initiative Protocol for Metadata Harvesting (OAI-PMH Version 2.0). Read more
\n\nLicense
\n\nBook chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen upholds a very flexible Copyright Policy. There is no copyright transfer to the publisher and Authors retain exclusive copyright to their work. All Monographs/Compacts are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Read more
\n\nPeer Review Policies
\n\nAll scientific works are Peer Reviewed prior to publishing. Read more
\n\nOA Publishing Fees
\n\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
\n\nDigital Archiving Policy
\n\nIntechOpen is committed to ensuring the long-term preservation and the availability of all scholarly research we publish. We employ a variety of means to enable us to deliver on our commitments to the scientific community. Apart from preservation by the Croatian National Library (for publications prior to April 18, 2018) and the British Library (for publications after April 18, 2018), our entire catalogue is preserved in the CLOCKSS archive.
\n\nOpen Science is transparent and accessible knowledge that is shared and developed through collaborative networks.
\n\nOpen Science is about increased rigour, accountability, and reproducibility for research. It is based on the principles of inclusion, fairness, equity, and sharing, and ultimately seeks to change the way research is done, who is involved and how it is valued. It aims to make research more open to participation, review/refutation, improvement and (re)use for the world to benefit.
\n\nOpen Science refers to doing traditional science with more transparency involved at various stages, for example by openly sharing code and data. It implies a growing set of practices - within different disciplines - aiming at:
\n\nWe aim at improving the quality and availability of scholarly communication by promoting and practicing:
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Many factors contribute to burnout, and it occurs at all stages of medicine: it can begin during medical school, intensify during the years of graduate medical education (GME) or residency training, and persist as residents become staff physicians. It affects both sexes, but may impact female physicians disproportionately. Impact can also vary among specialties. 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He is a full professor of signal processing and pattern recognition and is head of the Signals and Communications Department at ULPGC, teaching from 2001 on subjects on signal processing and learning theory. His research lines are biometrics, biomedical signals and images, data mining, classification system, signal and image processing, machine learning, and environmental intelligence. He has researched in 52 international and Spanish research projects, some of them as head researcher. He is co-author of 4 books, co-editor of 27 proceedings books, guest editor for 8 JCR-ISI international journals, and up to 24 book chapters. He has over 450 papers published in international journals and conferences (81 of them indexed on JCR – ISI - Web of Science). He has published seven patents in the Spanish Patent and Trademark Office. He has been a supervisor on 8 Ph.D. theses (11 more are under supervision), and 130 master theses. He is the founder of The IEEE IWOBI conference series and the president of its Steering Committee, as well as the founder of both the InnoEducaTIC and APPIS conference series. He is an evaluator of project proposals for the European Union (H2020), Medical Research Council (MRC, UK), Spanish Government (ANECA, Spain), Research National Agency (ANR, France), DAAD (Germany), Argentinian Government, and the Colombian Institutions. He has been a reviewer in different indexed international journals (<70) and conferences (<250) since 2001. 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He has (co)authored more than 150 publications in indexed journals, international conferences and book chapters, 1 book (in Greek), 3 edited books, and 5 journal special issues. His publications have more than 2100 citations with h-index 27 (GoogleScholar). His research interests include computer/machine vision, machine learning, pattern recognition, computational intelligence. \nDr. Papakostas served as a reviewer in numerous journals, as a program\ncommittee member in international conferences and he is a member of the IAENG, MIR Labs, EUCogIII, INSTICC and the Technical Chamber of Greece (TEE).",institutionString:null,institution:{name:"International Hellenic University",institutionURL:null,country:{name:"Greece"}}},editorTwo:null,editorThree:null},{id:"25",title:"Evolutionary Computation",coverUrl:"https://cdn.intechopen.com/series_topics/covers/25.jpg",isOpenForSubmission:!0,editor:{id:"136112",title:"Dr.",name:"Sebastian",middleName:null,surname:"Ventura Soto",slug:"sebastian-ventura-soto",fullName:"Sebastian Ventura Soto",profilePictureURL:"https://mts.intechopen.com/storage/users/136112/images/system/136112.png",biography:"Sebastian Ventura is a Spanish researcher, a full professor with the Department of Computer Science and Numerical Analysis, University of Córdoba. 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Saxena",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",institutionURL:null,country:{name:"India"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null}]},subseriesFiltersForPublishedBooks:[{group:"subseries",caption:"Bacterial Infectious Diseases",value:3,count:2},{group:"subseries",caption:"Parasitic Infectious Diseases",value:5,count:4},{group:"subseries",caption:"Viral Infectious Diseases",value:6,count:7}],publicationYearFilters:[{group:"publicationYear",caption:"2022",value:2022,count:2},{group:"publicationYear",caption:"2021",value:2021,count:4},{group:"publicationYear",caption:"2020",value:2020,count:3},{group:"publicationYear",caption:"2019",value:2019,count:3},{group:"publicationYear",caption:"2018",value:2018,count:1}],authors:{paginationCount:189,paginationItems:[{id:"221831",title:"Prof.",name:"Niansheng",middleName:null,surname:"Tang",slug:"niansheng-tang",fullName:"Niansheng Tang",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221831/images/system/221831.jpeg",biography:"Niansheng Tang is a Professor of Statistics and Dean of the School of Mathematics and Statistics, Yunnan University, China. He was elected a Yangtze River Scholars Distinguished Professor in 2013, a member of the International Statistical Institute (ISI) in 2016, a member of the board of the International Chinese Statistical Association (ICSA) in 2018, and a fellow of the Institute of Mathematical Statistics (IMS) in 2021. He received the ICSA Outstanding Service Award in 2018 and the National Science Foundation for Distinguished Young Scholars of China in 2012. He serves as a member of the editorial board of Statistics and Its Interface and Journal of Systems Science and Complexity. He is also a field editor for Communications in Mathematics and Statistics. His research interests include biostatistics, empirical likelihood, missing data analysis, variable selection, high-dimensional data analysis, Bayesian statistics, and data science. He has published more than 190 research papers and authored five books.",institutionString:"Yunnan University",institution:{name:"Yunnan University",country:{name:"China"}}},{id:"1177",title:"Prof.",name:"António",middleName:"J. R.",surname:"José Ribeiro Neves",slug:"antonio-jose-ribeiro-neves",fullName:"António José Ribeiro Neves",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1177/images/system/1177.jpg",biography:"Prof. António J. R. Neves received a Ph.D. in Electrical Engineering from the University of Aveiro, Portugal, in 2007. Since 2002, he has been a researcher at the Institute of Electronics and Informatics Engineering of Aveiro. Since 2007, he has been an assistant professor in the Department of Electronics, Telecommunications, and Informatics, University of Aveiro. He is the director of the undergraduate course on Electrical and Computers Engineering and the vice-director of the master’s degree in Electronics and Telecommunications Engineering. He is an IEEE Senior Member and a member of several other research organizations worldwide. His main research interests are computer vision, intelligent systems, robotics, and image and video processing. He has participated in or coordinated several research projects and received more than thirty-five awards. He has 161 publications to his credit, including books, book chapters, journal articles, and conference papers. He has vast experience as a reviewer of several journals and conferences. As a professor, Dr. Neves has supervised several Ph.D. and master’s students and was involved in more than twenty-five different courses.",institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"11317",title:"Dr.",name:"Francisco",middleName:null,surname:"Javier Gallegos-Funes",slug:"francisco-javier-gallegos-funes",fullName:"Francisco Javier Gallegos-Funes",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/11317/images/system/11317.png",biography:"Francisco J. Gallegos-Funes received his Ph.D. in Communications and Electronics from the Instituto Politécnico Nacional de México (National Polytechnic Institute of Mexico) in 2003. He is currently an associate professor in the Escuela Superior de Ingeniería Mecánica y Eléctrica (Mechanical and Electrical Engineering Higher School) at the same institute. His areas of scientific interest are signal and image processing, filtering, steganography, segmentation, pattern recognition, biomedical signal processing, sensors, and real-time applications.",institutionString:"Instituto Politécnico Nacional",institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"428449",title:"Dr.",name:"Ronaldo",middleName:null,surname:"Ferreira",slug:"ronaldo-ferreira",fullName:"Ronaldo Ferreira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/428449/images/21449_n.png",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:'"Politechnica" University Timişoara',institution:null},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:null,institution:null},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. 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