Values of the recruited evaluation measures.
\r\n\t
",isbn:"978-1-83881-111-2",printIsbn:"978-1-83880-992-8",pdfIsbn:"978-1-83881-112-9",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"acb2875b3bfc189c9881a9b44b6a5184",bookSignature:"Dr. Abdo Abou Jaoudé",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11865.jpg",keywords:"Linear Operators, Normal Operators, Spectral Theorem, Applications, Differential Operators, Integral Operators, Functional Calculus, Complex Variables, Complex Analysis, Theory, Recent Advances, Latest Trends",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 13th 2022",dateEndSecondStepPublish:"June 21st 2022",dateEndThirdStepPublish:"August 20th 2022",dateEndFourthStepPublish:"November 8th 2022",dateEndFifthStepPublish:"January 7th 2023",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"2 months",secondStepPassed:!0,areRegistrationsClosed:!1,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Abdo Abou Jaoudé is a pioneering Associate Professor of Mathematics and Statistics at Notre Dame University-Louaizé. 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The ventricular system comprises four interconnected cavities in the brain and contains a network of ependymal cells forming the choroid plexus which has been believed to be the site of production of the CSF. The ventricular system is continuous with the central canal of the spinal cord (from the fourth ventricle) and allows the CSF to continuously bathe the cranium and the spine. The subarachnoid spaces form openings termed as subarachnoid cisterns which separate the arachnoid and the pia mater, thereby creating an anatomic space between the two meninges. These cisterns are filled with cerebrospinal fluid and form the second compartment where the CSF flows within the cranial cavity.
\nThe anatomy of the fluid compartments of the brain: ventricular and cisternal systems.
Adult CSF volume is estimated to be 150 ml with a distribution of 125 ml within the subarachnoid spaces and 25 ml within the ventricles. This difference in the volume of CSF between the two compartments is important to understand the function of the CSF in a unique perspective.
\nThe CSF secretion varies between individuals, usually ranging between 400 and 600 ml per day in an adult. The constant secretion of CSF contributes to a four to five times turnover per 24-h period. This turnover is of immense importance in exploring the functions of the CSF which have not yet been understood quite well. While the CSF has been considered as a source of nutrition and waste removal and a mechanically buoyant substance, cushioning the brain, the newer insights of the glymphatic pathways have demonstrated a critical role of CSF flow as a physiological buffer for brain functioning.
\nWith a closely regulated composition, the CSF is valuable in analyzing cerebral pathologies. Alterations in the regulation of localized temperatures, malformation of proteins, and impeding clearance of pathologic proteins are the pathophysiological mechanisms for onset and progress of most neurodegenerative disorders as well as secondary brain damage in the setting of trauma. It is, however, interesting to analyze how the impairment of CSF inflow or outflow through the glymphatic system might lead to the cascade of these degenerative and traumatic pathologies.
\nThe amount of CSF within the CSF compartments is a consequence of the net filtration and absorption of water through the selectively permeable capillary walls traversing through the brain tissue. This net effect is governed by the physiological or pathological conditions prevailing within these compartments. The glymphatic system branches along the course of the arteries, arterioles, capillaries, and venules, forming a paravascular cast. This CSF interacts with the end feet of glia and indirectly with neurons to establish an exchange with the brain ISF (Figure 2).
\nArtistic representation that depicts the persistence of the paravascular system through the arteries, arterioles, capillaries, venules, and veins. This indicates that just as there is a vascular cast of the brain, there is a paravascular system cast as well. Courtesy: Cherian and Beltran [
The AQP4 channels mediate the bidirectional transport of water in response to passive osmotic and hydraulic pressure gradients [2, 3], resulting in the CSF-ISF exchange [4]. This makes the glymphatic system extremely pressure dependent. Any increase of pressure in the glymphatic system would produce the passage of fluid toward the interstitial space until the pressure in both compartments is equalized. This exchange drives the removal of exogenous molecules from the interstitial spaces of the brain [5, 6] (Figure 3).
\nThe anatomy of the Virchow Robin spaces forming an extensive network of communication within the glymphatic pathway. Courtesy: Orešković and Klarica [
The dependence of AQP4 to pressure gradients in both senses might be the underlying mechanism leading to the recently described “shift edema” following trauma [8] and also would explain the advantages of cisternostomy over craniectomy for the treatment in the short- and long-term follow-up of the patients [9]. Subsequent to subarachnoid hemorrhage, red blood cells are confined to the subarachnoid space and do not enter the VRS as pial membranes between the PVS and the SAS prevent the exchange of large molecules [10] (Figure 4).
\nSchematic representation of the mechanism of CSF-shift edema following traumatic brain injury. The AQP-4 channels on the lining of VRS allow the shift of CSF from the cisterns into the brain parenchyma leading to brain edema.
The brain can be assumed as a water-cooled system with the CSF as a medium of heat removal and the paranasal sinuses as cooling surfaces. The close contact of the PNS with the suprasellar cisterns helps create a radiation system, and the mechanical process of breathing allows the sinuses to deliver the acquired heat from the brain parenchyma which is dumped by the CSF residing in the cisterns. Evaporation at the sinus surface causes cooling effect that is transmitted to the cisterns, dissipating the heat from the CSF which is acquired from the brain parenchyma [1] (Figure 5).
\nClose communication of the paranasal sinuses with the cisterns creating a brain cooling unit. Courtesy: Cherian and Beltran [
This cooling unit can be hypothesized to be a fundamental thermostat, and any hindrance in CSF flow might explain the cascade of protein misfolding secondary to heat accumulation as seen in neurodegeneration. While brain cooling is a passive process that occurs throughout the day, brain cleaning is more pronounced nocturnally. It is believed that brain cleaning is regulated by AQP4 and exchanges between interstitial fluid and CSF have been demonstrated to be more active during sleep due to an expansion of the extracellular space, being increased by 60% during sleep [11], particularly in the lateral position [12]. The increased glymphatic clearance of the metabolic waste products generated by neural activity in the awake brain occurs during sleep, explaining the need to sleep for restoring alertness and activity.
\nCSF is permanently produced and absorbed in the whole CSF system as a consequence of filtration and reabsorption of water volume through the capillary walls into the surrounding brain tissue. The three- to fourfold turnover rate in CSF production allows for a rigorous cerebral buffering at physiological states which helps maintain brain function. The brain generates tremendous amount of heat throughout the day which needs to be removed essentially to prevent protein misfolding and generation of free radicals. This warrants a system to allow for heat removal in the form of cooling as well as cleaning of metabolic wastes to prevent accumulation of toxic metabolites.
\nAt a physiological state, the difference in arterial and venous hydrostatic and osmotic pressures allows a unidirectional flow of water and other molecules (soluble waste), with water leaving from the arterial end and molecules entering at the venous end. This simultaneous exchange of water and waste at two different ends can thus be regarded as a means of cleaning for the brain [5].
\nA deeper insight to this simultaneous exchange of water and waste in the blood vessels reveals the orientation of the brain vasculature, which, unlike other organs, runs in an opposite fashion, with the primary arteries lying ventral and more medially, whereas the principal veins run in a dorsal and lateral manner. Additionally, the disposition of white matter tracts creates an anisotropic field that facilitates the direction of fluid and molecules toward the main veins, which is further directed by changes in arteriovenous pressure gradients.
\nThe paravascular system therefore maintains a very intricate and evolved system through extensive branching of vessels in the brain along with its paravascular system, thus following the vascular cast of the brain. This intricate system is limited by the selectively permeable capillary walls which is only large enough for a red blood cell to permeate through and may indeed be even more intricate than the vessels, since the limiting dimension of the capillaries is 3 in diameter, which is just large enough for a red blood corpuscle to squeeze through (Figure 6).
\nSchematic representation of the Virchow Robin spaces traveling around the blood vessels from the cisterns into the brain. Courtesy: Cherian and Beltran [
The arteriovenous pressure difference described above can lead to the potential role of breathing on the dynamics of CSF flow within the extensive paravascular system. The close relationship of the paranasal sinuses with the basal cisterns provides an excellent radiation chamber that can help in buffering the thermal environment of the brain through continuous evaporation of the mucosa-lined sinus surfaces in contact with the external atmosphere, hence the hypothesis of breathing playing an important role in the cooling of the brain and possibly the clearance of molecules within the paravascular system.
\nAttributed to the expression and function of the AQP-4 channels, the brain cleaning mechanism is predominant during sleep. Sleep increases the expansion of the extracellular spaces by up to 60% which allows for a maximal exchange of substances to and fro the CSF and the ISF compartments [11]. This phenomenon is particularly observed in the lateral position [12]. Therefore, the restorative properties of sleep may be linked to increased glymphatic clearance of the metabolic waste products that are generated by neural activity in the awake brain. This might underpin the beneficial effects of sleep, in clearance of metabolic byproducts, the phenomenon of jetlag, and the problems with lack of sleep.
\nThe primary CSF delivery mechanism, from the subarachnoid space into the paravascular system and along the paravascular space, appears to be arterial pulsatility [6, 13], coupled with brain compliance [2] (Figure 7). Arterial pulsatility, coupled with a perivascular compliance, generates successive physical brain compression and expansion, allowing the brain to act like a sponge by virtue of the cycle-dependent systolic-diastolic circulatory movement of blood through the brain [14]. This reciprocal movement influences the flow of fluids in the brain parenchyma to initiate a “pumping” effect of CSF around the vessels. These movements are driven by physiological oscillations of arterial and venous blood during craniospinal blood circulation, which are influenced by respiration, body activity, and posture [7].
\nGraphical representation of pulsations in the artery and veins being the driving force to the CSF in the paravascular pathway.
Loss of arterial elasticity may lead to an impairment of this “pumping” effect in the paravascular system. This is classically seen in small vessel disease or as a consequence of low craniospinal compliance that impedes the expansion of the arteries, as can be seen in normal pressure hydrocephalus, gliosis [15], or post-traumatic hypertension. This would result in a decrease of CSF turnover that hinders the clearance of metabolites [16] and generates excess metabolic heat, thereby contributing to the pathogenesis of neurological diseases.
\nAging is a phenomenon that leads to a decline in the exchange efficiency between CSF in the paravascular spaces, and ISF occurs. This can be related to a reduction in the vessel wall pulsatility of intracortical arterioles and the widespread loss of perivascular AQP4 channels [17]. This “hardening” of vessel walls, as a consequence of aging, decreases the drainage of amyloid peptides, which may deposit in the paravascular pathways as cerebral amyloid angiopathy (CAA). These deposits further impede the drainage of ISF along the paravascular spaces, resulting in loss of homeostasis of the neuronal environment that may contribute to neuronal malfunction [15, 18]. The concurrent loss of localized thermal regulation by the paravascular pathway may add to the cascade of damage by modification of proteinaceous components, which are very sensitive to subtle changes in temperature. These structural changes in molecular geometries might disturb solubility and thus the drainage of this metabolic waste, giving rise to a vicious circle.
\nThe functional impairment of the paravascular system appears to be an underlying condition of the aging human brain [19], which has also been related to various CNS disorders, such as neurodegenerative disorders that are brought on by the accumulation of misfolded, prion-like proteins (e.g., Alzheimer’s or amyloid angiopathy) [17, 20, 21], normal pressure hydrocephalus [19, 22, 23], post-traumatic encephalopathy [24, 25], or neuroinflammatory disorders, such as multiple sclerosis. Furthermore, the presence of the paravascular system would explain the advantages of cisternostomy over decompressive craniectomy, in the treatment of acute brain trauma [8, 26].
\nDecreased intracranial compliance leads to increased intraparenchymal pressure, affecting the arterial perfusion of the brain and promoting venous congestion. On the whole, the kinetics of the fluid in the paravascular spaces is impaired. Should there be a loss of AQP4 localization, as seen in reactive astrogliosis and the aging brain, or following trauma or ischemia, or if the CSF outflow is reduced as a consequence of either CSF flow obstruction, cerebral artery pulsatility inefficiency, cerebrospinal venous insufficiency, or lymphatic disorders [27], the localized perivascular CSF recirculation may be impaired.
\nThe corresponding author serendipitously uncovered the fact that opening cisterns in severe head trauma had the effect of abating severe brain swelling while drastically reducing the requirement for decompressive hemicraniectomies [24, 28]. His decade-long work on this led him to believe that CSF was ingressing to the brain through the Virchow Robin spaces, producing a condition which has been recently termed as CSF shift edema. Experimental studies on the glymphatic system by Iliff et al. categorically proved the communication of the CSF with the brain through the Virchow Robin spaces, or paravascular spaces, and that this pathway was critical for clearing the brain of metabolites [5, 6]. Perhaps the biggest clinical implication of this finding is the microsurgical opening of the cisterns: cisternostomy, in cases of moderate to severe head injury in order to reverse CSF shift edema, which is the mainstay of the cascade of the TBI damage. This procedure has been discussed in detail in previous publications and prevents progression to diffuse axonal damage or cortical stretch as otherwise seen in decompressive procedures. The phenomenal prognosis in the patients undergoing cisternostomy led the author to investigate the paravascular system in further depth, as well as CSF shifts, and subsequently the likely functionality of the paravascular system (Figure 8).
\n(a) Raised cisternal pressure due to the traumatic subarachnoid hemorrhage shifts cerebrospinal fluid into the brain, causing raised intracerebral pressure. (b) Opening of the cisterns reverses the cisternal pressure gradient, causing cerebrospinal fluid to flow back into the cisterns, thus decreasing the brain pressure. (c) Decompressive hemicraniectomy allows extracalvarial herniation, leading to further deterioration due to axonal stretch and altered blood flow dynamics. Courtesy: Cherian et al. [
Today, cisternostomy has shown to be efficacious as a primary surgical intervention in moderate to severe traumatic brain injury. While following the principles of reversal of CSF shift edema, cisternostomy has proven to help in the prognosis by decreasing the rates of morbidities and mortalities [22]. It is now being practiced in many neurosurgical centers around the world [25] and has also been accepted as one of the options of surgical intervention in the ongoing Global Neurotrauma Outcomes Study [29].
\nThe paravascular system, its cleaning and cooling properties, and the consequent pathophysiological conditions secondary to the impedance of this system as well as potential treatment measures have not yet been investigated in detail. Reports of an experiment where a bacteriophage is being introduced into the olfactory system of a mouse resulted in the reversal of Alzheimer’s symptoms. This could be due to the clearance of the obstructed paravascular system as the phage traveled into the cisterns through the perineural space of the olfactory. This observation opens doors for a paradigm shift in the management of neurodegenerative diseases and warrants extensive research. Further experimental work in this area will include the injection of paramagnetic nanoparticles into the suprasellar cisterns of mice, porcine, or baboon models, where the movement of these nanoparticles may be observed with a T1 W3T MRI.
\nThe paravascular system is a branching structure that extensively connects the cells and vessels within the brain. The intricacy of the system and the challenges in performing studies have been a hurdle in exploring this system. However, an in-depth analysis of brain fluid dynamics and its relationship to the cardiopulmonary mechanisms can provide a game changing pathway to the preventive and therapeutic measures of various pathophysiological brain disorders.
\nRisk-based security is built around the premise that information obtained from observable aspects of human identity and possession and knowledge acquired about hidden aspects of human capability and intent can be intelligently combined to assess to some great extent of accuracy the threat a given individual poses to a security system, be it an airport or a border crossing point (BCP). Then, in turn, associating the estimated level of threat with a measure of risk by factoring in the cost that the assessed threat can represent to the system that is being secured by taking into account the impact and cost a given threat can have on a security system, a risk-based security approach can be designed and implemented, whereby security checks are tailored to be commensurate to the estimated risk each individual may pose, instead of being uniform irrespectively of the risk posed by each individual, as is the case today. Taking into account that less than 5% of all individuals can be a potential security risk, the savings in terms of time required to go through risk-based security systems with speedier tests for the 95% of low to no risk individuals can be significant, waiting times in security lines can be reduced and thus the level of comfort and customer satisfaction be drastically improved.
The concept of
The concept of risk-based security is indeed promising in terms of improving travelers’ experience by easing off security screening and reducing the overall time required to spend at a security check-point. However, the difficulty in implementing a risk-based security systems lies on: (a) developing and implementing non-intrusive, GDPR1 compliant technology and systems that can estimate the risk level of each traveler without inducing additional and cumulative delays; (b) testing such systems before rolling them out in operational environments; and (c) estimate their performance and efficacy under ideal conditions for obtaining performance bounds, calculating the cost of the required investment for implementing risk-based technologies; and (d) calculate the degradation in performance when moving away from the “ideal” operational conditions into realistic operational conditions.
The European Union (EU) and other international organizations promote this approach through various initiatives. The European Commission (EC) issued the “Smart Borders package” which aims to modernize the Schengen area’s external border management by improving the quality and efficiency of border crossing processes through the establishment of ‘Stronger and Smarter Information Systems for Borders and Security’ [1]. The International Air Transport Association (IATA) proposed a Checkpoint of the Future, designed to enhance security while reducing queues and intrusive searches at airports by using intelligence-driven risk-based measures [2]. Along these lines the EC funded the Research and Innovation project FLYSEC [3] has developed and demonstrated an innovative, integrated, and end-to-end airport security system facilitating risk-based screening with the introduction of novel intelligent technologies.
This chapter
Figure 1 shows a today’s conventional security check point whereby we distinguish two types of checks: (a) the “normal” check where all individuals in the security check area are treated uniformly by applying the same level of security for all; and (b) the “increased” security check point where travelers are channeled if they fail at normal security check point. It should be pointed out that in this security system of check points, currently implemented almost worldwide, the “increase inspection” is usually the outcome of randomized selection of travelers to be subjected to an increased level of inspection and is usually based on the principle of “importance sampling2” methods. These methods try to detect a probabilistic event, such as the existence of a suspect among travelers, with a certain degree of confidence by taking into account the probability of existence of such an event and possibly the range of values the event can assume. These methods are “blind,” that it they draw samples from the distribution indiscriminately and without takin into account any specific attributes of the samples, and thus, they are also GDPR compliant. As it will be pointed out further down in the chapter, risk-based methods need to pay special attention to comply with GDPR as they gather and use information and knowledge about individuals’ private data such as identity, possession, capability, and intent.
Today’s security check-point concept (curtesy of TRESSPASS).
Risk-based security associates the estimated risk for each traveler with a commensurate level of security scrutiny. Using prior information about each traveler and sensory data obtained while the traveler is within the security perimeter of a monitored area, a risk-based security system assigns a risk factor to each traveler and depending on the value of the risk factor, the traveler is mapped to a level of security scrutiny commensurate with the perceived risk. Although different number of levels can be associated with the estimated risk, for practical reasons, it is sufficient to associate the entire range of risk values into three different levels of security, Trusted/Registered (Green), Casual (Yellow) and Enhanced Security (Red), as shown in Figure 2 [5].
Association of three security scrutiny levels, namely “enhanced security,” “casual traveler,” and “trusted/registered” with the estimated level of risk for each traveler. These three levels have been introduced in the FLYSEC project [
In Figure 2,3,4 a number of GDPR-compliant technologies that can be used for and contribute to the risk assessment are shown in and include: mobile app way finding; dynamic travelers flow management; intelligent visual surveillance; Wi-Fi/Bluetooth localization; RFID mobile tracking; and behavioral analysis & risk-based security personnel mobile app.
Figure 3 represents a risk-based security check point that results from combining the three-level risk-based security screening of Figure 2 with the conventional security screening of Figure 1. As it can been seen from Figure 3, the need for assessing each traveler’s risk factor from various observable parameters requires measuring somehow these parameters, of course in a GDPR compliant way, and thus additional processing steps and capabilities that may induce additional delays in screening process. Thus, the fundamental premise of risk-based security as a means of providing the same, at least, level of security as conventional check points without inducing additional delays, seems to be in conflict with the additional delay induced by additional screening tests required for estimating each traveler’ risk index, unless the risk assessment process is done transparently while the travelers move from the entry to exit points in a BCP (Border Crossing Point).
Risk-based security check point: The standard (randomized scrutiny checks) security check point of
Figures 4 and 5 depict two block diagrams implementing the conventional security screening process of Figure 1 and the risk-based security screening process of Figure 3 respectively. From the two diagrams it is clear that additional screening stages are required for assessing the risk for each traveler in risk-based security. Each one of these additional risk assessing stages induce additional delays in the security screening process, that add up to an overall additional time required for risk-based security screening compared to the time required for security screening through a conventional security check point.
Configuration 1 (current BCP implementation).
Configuration 2 (risk-based BCP implementation).
Thus, it appears that risk-based security may require additional processing time for estimating risk that may offset the benefits from faster security screening for those travelers whose estimated risk classifies them in either the “trusted/registered traveler” or “casual travelers” categories for whom security screening is relaxed and thus faster than the time would be required to screen them in today’s conventional check points of Figure 1. Granted that over 90% of travelers fall within these two categories and will experience reduced delays at security screening, it remains to determine if the aggregate benefits from the reduced security screening at check points will trade off positively against the additional delays induced by the additional screening points for determining each traveler’s risk as in Figure 5.
In order to quantify the cost–benefit trade-offs between the efficiency of a risk-based security BCP and the delay induced by additional checks required for assessing risk, the following experiment was conducted using Fraunhofer’s FhG BCP Monte-Carlo agent-based simulator of a BCP configuration (curtesy of Fraunhofer Institute) [4].
For the simulation, we assumed a BCP with 1000 travelers, some exhibiting normal (no risky) behavior, whereas the rest exhibit suspicious behavior, with the following parameters:
Distribution of traveler types: [Normal, Suspicious]: [0.9,0.1]
Alarm threshold for each component: 0.5
Risk calculation: According to the script below:
Effectiveness calculation:
Ran over 10000 iteration with 100 travelers each time for both the configurations.
Using the above script for generating travelers with the above choice of parameters, 10.000 iterations with 100 travelers each time were run for each one of the two configurations of Figures 4 and 5, and the effectiveness (as defined above) of each configuration was calculated. The results regarding the effectiveness (as defined above) of each configuration are qualitatively summarized schematically in the graph of Figure 6.
Effectiveness calculation of a conventional BCP with random security checks determined by importance sampling versus risk-based BCP configuration: Effectiveness increases with the use of risk-based security in a BCP.
Effectiveness calculation of a conventional BCP with random security checks determined by importance sampling versus risk-based BCP configuration taking into consideration the additional delays induced by the additional risk assessment stages in configuration 2: Effectiveness increases with the use of risk-based security in a BCP, while induced delays increase as well.
From Figure 7 it is clear that there is a competing mechanism between effectiveness (another way of stating “comfort”) and delay induced by a risk-based security BCP versus a conventional BCP with randomized tests based on the theory of importance sampling5. The aim of the two EU-funded projects FLYSEC and TRESSPASS, coordinated by the author, is for FLYSEC to: (a) demonstrate that there is technology available or can be developed to implement risk-based security in a GDPR compliant way; (b) provide solid evidence of the risk-based security screening as an effective and non-instructive means of providing security with convenience to travelers; and for TRESSPASS to: (c) provide a comprehensive risk-assessment framework for calculating risk systematically in accordance with the TRESSPASS multi threat, multimodal that includes all
measures undertaken with third countries or service providers;
cooperation with neighboring countries;
border control and counter-smuggling measures;
control measures within the area of free move,
by taking into account estimates and information about.
Multi-modal, multi-tier TRESSPASS risk-assessment model.
Observable and hidden risk factors.
Thus, the aim of the two funded projects, namely FLYSEC and TRESSPASS, is to provide solid evidence and the means for moving the operating point (OP) of a risk-based BCP from the delay induced OP to the no-delay induced OP, or as close to it as possible without inconveniencing travelers and in a GDPR compliant way, as shown in Figure 10.
Moving the operating point of a risk-based BCP to minimizing security check delays is the objective of both FLYSEC and TRESSPASS EU-funded projects.
The greatest challenge in risk-based border management is the estimation of the risk for each individual traveler. In TRESSPASS, a framework for modeling risk and a systematic approach of quantifying risk are proposed as follows:
Risk indicators are accurately estimated from available data collected from background information.
The risk for each traveler is calculated.
Based on risk, the system adjusts the number and types of security checks required for each traveler, in order to maintain a desired security level while optimizing the security system performance in terms of efficiency, traveler satisfaction and operational cost reduction.
Figure 11 summarizes in a comprehensive visual depiction the risk-based framework used in TRESSPASS [4], and previously introduced in FLYSEC [3]. The framework for risk-based security consists of an extensive use of technologies to estimate risk from both Observable and Hidden risk indicators across all four security tiers and heavily tested, both in vivo and in vitro through simulation, in carefully designed pilots across all three BCP modalities: air, land and sea.
TRESSPASS comprehensive risk-based security framework.
Paramount to the design and testing alternative designs of risk-based security concepts, technologies and protocols, in order to achieve the increase in effectiveness of BCPs with the parallel reduction of delays, is the use of simulation. iCrowd is an agent-based simulator that can be used to implement and test different risk-based concepts and technologies in a flexible and realistic simulation environment [6]. Figures 12 and 13 show a photo-realistic virtual reconstruction of an airport used extensively in simulating security scenarios and policies for a variety of projects and pilot use-cases.
Photo-realistic, agent-based simulation using iCrowd.
Queue lanes in a risk-based security checking system: Photo-realistic simulation provided by iCrowd.
The iCrowd Simulator is an agent-based simulation platform capable of handling small-scale to large-scale crowds and calculating the change of the status of each participating component depending on dynamic interactions with other entities or the environment during simulation time [7, 8]. It can be utilized in any bounded area, i.e. building interiors and exteriors, stadiums, or any exterior area e.g. public places like squares, open-air festival etc. Currently, it is being used to simulate crowd movement and crowd interactions in general, with the graphical display being optional. As
iCrowd offers a fully operational flow simulation for travelers and personnel inside an airport, as displayed in Figures 12 and 13. It enables the user to define simulation scenarios, it is implementing a sophisticated crowd engine with collision avoidance6 with multiple, different behaviors that can co-exist inside the same simulation. It also supports distributed simulations, operating as an orchestrator. It has been integrated with the C2 Web Portal OCULUS Air to communicate data, such as displaying the position and the movement of simulated entities in real time, and the Fusion and Ingestion Server to update travelers’ status accordingly depending on their interactions with the airport’s hardware and other security technologies (i.e. Beacons, RFID scanners and RFID tags for carry-on luggage tracking), Figure 14(a)–(d).
(a): Aspect of third-person camera. (b): Path planning example: The green line indicates the path the selected agent (displayed are red) is following (c): Travelers enter the airport. The display of hold and hand luggage is turned on. (d): Travelers go through the check-ins. The display of hold and hand luggage is turned on.
This section of the chapter presents and discusses implementable means for assessing risk without inducing additional delays beyond what passengers experience with today’s screening process, but instead reduce the time it takes to go through the security screening process by adjusting the level scrutiny in accordance to the perceived risk.
If passenger trajectories at an airport, or any BCP by the same token, could be tracked from the moment they enter the airport or the BCP in general, one could conceivably be able to differentiate suspicious looking trajectories from trajectories that would be expected for a passenger and thus classified as normal. Differentiating, however, between normal and abnormal behaviors may be a difficult proposition by itself, let alone that it should be done in accordance with privacy and GDPR regulations.
In the work presented in [9, 10], those two issues were addressed as follows. To develop a privacy and GDPR compliant tracking method, we assumed that passengers are tracked using overhead cameras that identify passengers as point targets from their top-down footprints (silhouettes); the footprints are reduced to a point for each passenger and are tracked across the entire airport area or BCP. In the initial phase of the study in [9, 10], it was assumed that passengers tracking was perfect, i.e. that all passengers’ traces as they moved around the airport or BCP area are (anonymously) identifiable and traceable. i.e. that the tracking system has perfect knowledge of the position of each passenger at any time. Although the assumption of perfect knowledge is idealistic, it allows us to get upper bounds on the performance of the tracking system that can be used to make trade off calculations between cost of investment on cameras infrastructure versus the (theoretically) achievable accuracy of the risk calculation.
The difficulty in risk assessment based on trajectories stems from the difficulty in defining what constitutes an abnormal behavior and how it can analytically be described. In the approach in [9, 10] this has been overcome by defining what constitutes a normal (expected) behavior, training the AI (Artificial Intelligence) system to recognize normal behavior and test it with abnormal behaviors to reflect loitering, jittering, and other deviations from expected “normal” behaviors.
Figure 14(a) through (d) are snap shots from the native visualizer of the iCrowd simulator simulating an anomaly detection mechanism based on travelers’ tracking AI algorithm based on a Recursive Neural Network (RNN) [9, 10]. As discussed above, we assumed that travelers can be tracked anonymously using top-down view cameras in compliance with GDPR and ethics regulations. Based on a model of what constitutes a normal traveler route (trajectory) in an airport (or similarly any other BCP), a convolutional recursive neural network was trained with “normal trajectories” generated by the iCrowd simulator. Once the RNN is trained with “normal trajectories,” travelers with “suspicious behaviors” are generated among travelers with “normal behaviors” and the algorithm is tested if it could detect the “suspicious trajectories.” In Figure 14(b), the traveler with suspicious behavior is color-coded red. The risk assessment algorithm detects and identifies the suspicious traveler in Figure 14(d).
A complete technical description of the anomaly detection algorithm is given in the references [9, 10]. Next, we summarize the results in [9, 10] in order to demonstrate the possibility of implementing a risk-based security system that monitors traveler risk continually without additional delays that can offset the benefits of the risk-based approach.
The evaluation of the risk assessment system of [9, 10] is done using the Precision-Recall (PR) diagram, the Receiver Operating Characteristic (ROC) curve, the Confusion Matrix, the F1-score and the Total Accuracy, as defined next:
Precision = (# of true suspicious behaviors detected)/(# of total labeled suspicious behaviors)
Recall = (# of true suspicious behaviors detected)/(# of total suspicious behaviors)
Receiver Operating Characteristic (ROC) curve = Probability of detection versus false alarm probability diagram
Confusion Matrix = Normal versus abnormal confusion matrix
F1-score = 2*[(Precision * Recall)/[Precision + Recall] which is the harmonic average of Precision and Recall.
Total Accuracy = (# of Total Assessments)/(# of Total Cases)
Figures 15–17 illustrate the PR diagram, the ROC curve and the Confusion Matrix respectively. Eqs. 6 and 7 calculate F1-score and Total Accuracy respectively. It should be reminded that the values of all evaluation metrics are defined within the interval [0, 1]. The closer to 1 a value lies, the better the achieved performance. Table 1 summarizes the values of the recruited evaluation measures. The threshold score derived by the RNN architecture, by maximizing F1-score, is 3.7.
Precision-recall diagram.
ROC curve.
Confusion matrix.
Measure | Value |
---|---|
Average PR score | 0.66 |
ROC AUC (Area Under Curve) | 0.97 |
F1-Score | 0.78 |
Total Accuracy | 0.99 |
Values of the recruited evaluation measures.
Furthermore, the F1 score (i.e. the harmonic average between Precision and Recall, Eq. (1)), along with the Total Accuracy, Eq. (2), the ROC AUC (Area Under Curve), and Average PR score, are calculated in Table 1,
Most of the
Although the conditions the risk assessment algorithm was evaluated under assumed perfect knowledge of the traveler trajectories, relaxation of the assumption of perfect knowledge of the traveler trajectories by injecting noise in the position accuracy and/or assuming missing position data, did not have a considerable negative effect on the detection of abnormal trajectories as discussed next.
In order to assess the performance of the anomaly detection algorithm in realistic conditions we introduce noise in the data to emulate the uncertainty in passengers’ positions reports. The “noisy data” emulate the inaccuracy in the reports of the positions of the people in the space. Under realistic conditions, the tracking and risk assessment system will receive data from inaccurate sources, such as cameras, sensors, etc. used to estimate distances, mobile signal strength, etc.
In stark contrast, the iCrowd emulator produces people and their movements, and periodically reports the exact ones (so without noise) their positions in the risk assessment system. During the preprocessing of this data the possibility of the system to add Gaussian noise, the “volume” of which (parameter σ2 of Gaussian noise) is given by the user. This is obviously not intended to never be used in real application, and exists only for experimentation. For examining the behavior of the system under realistic conditions is required noisily data of different intensity.
Noise can enter the system in 2 cases: during training and during testing or actual application. It is known that when training any neural network, it is good to have variety in the data in which the network is exposed so that it is not over-trained. So, it is expected that training with Noisy data can improve the overall performance of the system. During testing or the actual implementation of the system would definitely be better to have perfect data, but unfortunately this is often impossible. In the context of the internship training and validation data were performed with Gaussian noise with σ2 from 0 to 1.9 with step 0.1, testing data with corresponding noise levels, and for each combination they were trained and evaluation of the neural network, and metrics were calculated for each of them. The metrics used were the Receiver Operating Characteristic curve (ROC curve), the Precision-Recall curve (PR curve), and the corresponding Area Under Curve (AUC) scores. These metrics give similar results, in the sense that they are defined in [0,1] with value range [0,1], so the minimum AUC value is 0 and the maximum is 1. Higher value means better true positive and true negative to false positive and false negative ratio. The two metrics generally return similar results, but in our case more weight is given in metric PR, as it offers a better estimate in cases that interest us more the positive class of results, or the results consist of significantly more elements of one of the two classes. Both features apply in the case of this risk assessment system.
During the experiment, networks emerged that failed to find an acceptable solution to why either they were trapped in a local minimum or they encountered the phenomenon of exploding gradient. These cases appeared to be random and independent of the parameters noise, so the network was initialized differently and the training started from the beginning. The experiments were performed using 3 levels of congestion in space, low, moderate, and high, and for each of them 40 neural networks were created, one for each training/testing noise combination mentioned above. For every desired network, 4 independent trainings were conducted and the averages of metrics of interest were kept. The same test data, corresponding to low-to-medium congestion, were used for testing all tested models. The final results are presented below (Figures 18–20):
Training with low congestions data with different noise levels. Testing with low-to-medium congestion data.
Training with medium congestions data with different noise levels. Testing with low-to-medium congestion data.
Training with high congestions data with different noise levels. Testing with low-to-medium congestion data.
From the ROC AUC score graphs above, it is seen that the models that result in the highest performance correspond to the following noise level in the training data:
For low noise data, the best performing data with AUC = 0.91 corresponds to noise level σ2 = 0.8 in the training data.
For medium noise data, the best performing data with AUC = 0.96 corresponds to noise level σ2 = 1.6 in the training data.
For high noise data, the best performing data with AUC = 0.95 corresponds to noise level σ2 = 1.4 in the training data.
From the above results it is clear that the performance of the networks remains constant when we apply noise to the test data. This implies that, since training completed, the network remains robust and is not affected by data noise, so it can to be used in a real application. Of particular interest are variations that occur when present noise in education data. As mentioned above, training a neuron network usually benefits from the difference in training data, as it helps learn the patterns that appear in the data instead of the data itself. This obviously does not mean that the more noise the better. In every network and for every application there is some optimal noise level that offers the best performance. At cases with low and moderate congestion it seems that the Gaussian noise with σ2 ∼ 0.5–0.8 has the best performance, while for high congestion the training with noise performs better with σ2 ∼ 1.4. The variance has not yet been attributed to any of its specific features network, model, training method, or data.
The evaluation results from the performance of the risk assessment algorithm with the iCrowd simulator demonstrates that risk assessment can be done accurately and without necessarily inducing additional delays in the security screening process since the trajectory classification in normal or suspicious is done by overhead cameras while the travelers go about their normal check-in routine at the airport. To that extent, the proposed risk assessment method based on anomaly detection on traveler trajectories can be used to improve the security screening effectiveness while keeping the delay low (or moving the operating point in Figure 10 from high delay to low.).
Furthermore, the proposed method can be used as a financial investment tool for estimating the cost of acquiring the necessary equipment (in this case overhead cameras) for a certain level (probability of accuracy) before purchasing it, and for performing a trade-off analysis between the cost of acquisition of the necessary equipment and the expected performance improvement in risk assessment. This way, the risk assessment simulator allows to be used as a cost–benefit tool for the analysis of performance of a risk-based security system.
In its current form, the work in [9, 10] uses the time series of the coordinates of the trajectories of airport travelers for deep learning. In the future, additional features could be exploited. Such features are the velocity, acceleration and heading of the traveler. Moreover, alternative deep learning architectures could be tested such as the ones that account for contextual anomalies [11]. Furthermore, experiments on real-world data of human trajectories should be conducted. Such data are expected to contain more subtle and sophisticated anomalies. Finally, procedures that degrade data quality and emulate more realistic operational conditions are being implemented in order to test our system in the artificial presence of missing data, noisy data, data association issues, as is the case with data capturing devices operating under realistic operational condtions. Nevertheless, the present work and framework allow security investment decisions on tracking devices and infrastructure to be made by assessing the effectiveness of such an investment through the proposed risk assessment method that envelops the performance of any such system from above by considering ideal tracking conditions through perfect knowledge of all agents’ location. The proposed method and framework is currently being extended to cover other border security modalities, such as sea, land as well as multimodal crossing points in the context of the EU-funded TRESSPASS project [4].
In conclusion, a deep learning architecture for real-time risk assessment based on the trajectories of airport travelers as proposed in [9, 10] can be used for assessing risk without interrupting or delaying the flow of passengers at an airport or BCP at large. The architecture implements a deep RNN network and is fully automated. Thus, it is expected to be of great use to the human operators monitoring airport surveillance footages, reducing the potential errors and misjudges. The proposed risk assessment system is tested on a realistic, synthetic data set generated with the iCrowd simulator tailored to data sets representing traveler movements at the Luxembourg airport; however, any airport or BCP could have been modeled and used instead. The experimental results are very promising and they indicate that further security improvements at airport control points are achievable through risk assessment without inducing additional delays. This is due to the fact that the suspicious behavior threshold, derived by the deep learning procedure in [9, 10], lies at such a level so as to capture the malicious behavior while, at the same time, reducing false-positive alerts.
In [3] a GDPR compliant, mobile application was developed to allow security personnel on the floor of an airport, or any BCP, report in real time and with full respect to passengers’ anonymity, suspicious behaviors, such as nervousness, unjustifiable sweating, etc., while passengers stand in security check lines. The mobile app works in conjunction with Smart Queue, another enabler of risk-based security [5]. Smart Queue is system that works in conjunction with passengers’ ID documents; the system scans the passengers’ ID document upon their arrival at the airport, or entry in the BCP, and in any subsequent security queue. This way, Smart Queue not only does it count the number of passengers at a queue waiting to go through security screening, but knows in which position in the queue each passenger stands. This way, the security personnel that uses the security mobile app, needs to identify passengers only by their indexing number in the line they stand when reporting to the risk assessment back office system any suspicious behaviors about them. This way, anonymity of passengers and their personal data protection are maintained by the security mobile app. The information sent this way by the security personnel on the floor is then fused along with all other risk assessment reports about each passenger and the risk estimate is updated. The risk is reported to the security screening system and the passenger is classified in one of the three risk categories, namely green, yellow or red, as mentioned earlier.
In FLYSEC [3], a novel system architecture for Security and Safety surveillance systems that aims to identify adverse events or behaviors which may endanger the safety of people or their well-being has been introduced [12]. Through proper adaptations the system is applicable to a variety of monitoring systems for various critical infrastructures, border crossing points, and other places of interest (e.g., malls, mass transport systems). The proposed architecture depicts an Internet of Things (IoT) platform which comprises a sensing tier, a back – end processing and intelligence tier and a front end for visualization and user feedback tier. In further monitor and surveillance is performed mainly on the back – end intelligence component which consists of two modules: (a) the event detection module combined with a data fusion component responsible for the fusion of the sensors inputs along with relevant high level metadata, which are pre-defined features that are correlated with a suspicious event, (b) an adaptive learning module which takes inputs from security personnel about the correctness of the detected events, and uses it in order to properly parameterize the event detection algorithm. Moreover, a statistical and stochastic analysis component is incorporated which is responsible for specifying the appropriate features to be used by the event detection module. Statistical analysis estimates the correlations between the features employed in the study, while stochastic analysis is used for the estimation of dependencies between the features and the achieved system performance.
The system architecture is organized basically in three tiers: Sensing components, back–end components, and front – end devices. The sensing components are responsible for acquiring input which is either high or low level heterogeneous data coming from visual sensors (CCD, IR, etc.), biometric sensors (fingerprints, other), audio sensors (microphones), indoor localization equipment (Wi-Fi, beacons, RFID scanners, etc.), document scanners which provide information about visitors (for example travel documents in an airport, or purchase information recorded on personal discount electronic cards), or human reports via terminal devices (e.g. PDAs, mobile phones, tablets, etc.).
Front–end devices are responsible for visualizing information to end–users and assisting their operations (for example official authorities receiving information about detected incidents of great interest, or visitors getting navigation information inside an infrastructure, etc.). Front–end devices consist of official management terminal tools which manage the information collected and processed by the back–end and sensing components and assist personnel operations by providing alerts and notifications about significant events (Figure 21), visualizations of infrastructure’s layout along with real – time updates about essential points of interest (for example size of queues, sensors viability, crowd distribution, etc.) (Figure 22). Moreover, front – end devices include also mobile user devices which operate as a personal assistant to passengers at an airport or a BCP. These mobile devices may provide online and offline services regarding indoor navigation, recommendation services (for products, point of interests, etc.), notifications and alerts. Finally, via these devices each user may provide a feedback to the system about requests or reports, about incidents that may concern their safety, or public security, or interactions with the system in the context of system automatic personal servicing.
FlySec portal: - intelligent services visualization (upper); − automatic passenger classification (lower).
FlySec portal - layout visualization.
The back–end component contains the intelligence modules which process the input coming from sensing devices and produce high level intelligence and metadata which assist operational personnel, enhance end–users’ experience and content management services. These metadata are used either for further processing by fusion algorithms, or presented to end – devices via visualization methods on each end–device. Such metadata concerns directed paths for navigation services, fused high level visual information, or information regarding recommendations, detected incidents or notifications and alerts. Finally, the content management services enable efficient data storing and retrieving operations in a scalable way. The back – end component comprises a Message-oriented middleware in order to interconnect all the sensing and processing component, provides a REST API to front–end devices, supports web platforms interfaces (web – portal) and orchestrates the accurate functionality of the whole system, Figure 23.
Reference architecture of the FLYSEC security and safety risk-assessment surveillance system.
The core intelligence residing in the “Analytics, Data Fusion and Risk-based Security Server” is presented in Section 3.3. The Data protection, Legal Compliance and Ethics are important aspects that should be taken into consideration in the system architecting process and are analyzed in Section 3.4.
The proposed system is designed with the aim of enabling automated surveillance of large infrastructures such as airport, shopping malls, other. Such tasks incorporate massive monitoring of infrastructure visitors in real – time. Monitoring operation is based on an Internet of Things (IoT) installation architecture consisting of: (a) various types of sensing devices such as CCD surveillance cameras, QR/barcode scanners, localization equipment (NFC tags, WiFi beacons, etc), RFID scanners, etc., (b) processing units, both centralized and/or distributed, and (c) terminal devices such as mobile phones/tablets, computers, screens, electric signs, etc. (Figure 24).
Back-end intelligence system architecture.
Each sensor device may pre-process the acquired raw data (distributed processing) and the results are gathered on a central cloud-computing infrastructure consisting of independent but co-operative intelligent component each one dedicated for processing data and producing a specific intelligent response for the system. Moreover, the output is transferred to terminal devices. This processing procedure consists of the following steps (Figure 25).
Flow of data from sensors to the cloud or terminal devices.
The intelligent services are also responsible for automating the monitoring procedure and enhancing visitors’ experience. Therefore, we propose two types of services: (a)
These services aim at monitoring visitors’ behavior, profile, and interactions and provide information that could facilitate their purpose of visit and indicate services that act as added value to visitors and simultaneously promote each infrastructure expectations. Indicatively two representative use cases are Navigation services and Recommendation engine.
Navigation service corresponds to indoor localization and navigation of infrastructure visitors in order to assist them in reaching their desired points of interest (POI) not only as quickly as possible but also as efficient and desirable as possible by taking into account user requirements (e.g. disabilities, specific demands) and user location. Moreover, the service provide directions to each visitor via their mobile device to various POIs and informs the user in order to assist them reaching their goal of visit (for example provide information about location of various products in a supermarket, or shops in a mall, or provide information about flight departures or gates status in an airport)
Recommendation engine aims at providing suggestion of POIs or services that take place inside the infrastructure. The engine takes into account the user profile (information that each user provides optionally during account registration), user feedback (comments, rates), user location and contextual information (time, season, POI status) and create recommendations that are estimated to be assistive to user visiting experience but also promoting infrastructure and POIs expectations and benefits.
These services aim at monitoring visitors’ position and behavior and automatically detect incidents of significant interest such as malicious behavior, anomalous crowd trajectory flow etc. This solution is expected to enhance surveillance procedure for large-scale circumstances where it is demanded in real time, the accurate surveillance of a massive crowd. Indicatively we suggest two surveillance services: Suspicious unattended luggage incidents detection and suspicious visitor loitering detection.
Unattended luggage incidents detection aims at monitoring in parallel both visitors and the luggage they carry. Such monitoring could be approached either using CCD cameras and approximately detect abandoned luggage for a long period of time, or by tagging luggage (for example using RFID tags) where using RFID scanners in co-operation with visual sensors (CCD cameras) and human reports (official surveillance personnel), estimate potential unattended luggage incidents. Moreover, in order to monitor visitors’ position, we propose the use of indoor localization techniques using mobile devices in order to have an approximation of visitors’ location that willingly allow it, and in addition visual sensors and human reports as well, in order to increase system’s awareness of crowd location. Fusion of such information shall be exploited by machine learning algorithms, which result to a coarse grain estimation of visitors’ luggage abandonment.
Suspicious loitering detection aims at monitoring visitors’ location and in real–time detect anomalous visitors’ trajectories or positions that could be suspicious for malicious purposes. Such components may incorporate visual sensors (CCD cameras), human reports and mobile devices localization techniques (Wi-Fi beacons, NFC tags).
The Data Fusion unit inside the Analytics, Data Fusion and Risk-based Security Server aims to perform Hard and Soft fusion of heterogeneous data [13, 14, 15] available from disparate sources of information such as physical sensors (“hard” data) and human resources (“soft” data). Hard data fusion refers to the combination of raw information from multiple sources so as to achieve more accurate estimations of the desired parameters (position, speed, other). To this end, a variety of theoretical tools, such as Signal processing techniques, Kalman filters, Sequential Monte Carlo methods, etc., can be used. On the other hand, soft data fusion usually applies on textual information (e.g., from humans’ reports, social networks, Internet, other) which has to be further processed using methods such as Information retrieval, Natural Language processing, and Semantic knowledge representation. Moreover, in this unit, Decision level fusion techniques could be applied using Evidence theory [14, 15, 16], Fuzzy Logic [17], 2-tuple Linguistic representation models [18, 19], and reinforcement learning methods [20, 21].
The Risk-based assessment unit is responsible for the classification of events and individuals into security classes according to their risk severity level. The unit exploits behavior and event indicators and their corresponding weights estimated in the ALMS system, intelligence generated in the Back–end Intelligence component, and any useful information from the system’s data sources in order to generate alerts and notifications to the Command-and-Control (C2) center if the risk severity level exceeds predefined thresholds.
A security and safety monitoring system has to detect, evaluate, and classify, in an efficient and timely manner, behaviors and events of interest. To achieve this critical need, the algorithmic parameters used in the “Analytics, Data Fusion and Risk-based Security Server” have to be initialized and adaptively adjusted to handle changes in the monitoring environment. To this end, the use of an Adaptive Learning Management System (ALMS) which will exploit new and accumulated information is essential. An ALMS system can be applied for instance to iteratively adjust the Risk Assessment classification thresholds and the weights of the behavioral and event indicators or to recognize correlations between indicators, events, and behaviors in order to optimize the classification process and improve the efficiency of the system. An example of such an optimization approach could be the selection of a reduced number of indicators for event identification.
For the development of automated procedures able to estimate correlations, optimize selected parameters under certain criteria, and extract reduced dimensional feature vectors for Behavior and event detection the ALMS system demands efficient methodologies and algorithms. These methodologies and techniques can cover a wide area of theoretical tools including Machine Learning, Factor Component Analysis, Statistical methods, Time series analysis, Optimization theory, Sparse clustering, Fuzzy Logic, and other [18, 19, 20, 21].
As shown in Figures 23 and 26, the ALMS unit receives input from i) the system’s database which includes data from system’s data sources, outputs of Data Fusion, Analytics, and Risk assessment unit, and optimization criteria and constraints and ii) the Security personnel Mobile App which is then used for the training of the applied algorithms. The ALMS stores its output in the system database, making it accessible to other units, and creating a continuous feedback loop of information gathering, learning, and adapting to security threats as they evolve.
The adaptive learning management system architecture.
The Factor Component Analysis component performs Factor Analysis on features/indicators denoting individual characteristics which affect the categorization of individuals in security-threat levels. Factor analysis is used to reduce the dimensionality of a correlation matrix that contains features/indicators describing a specific event or behavior. Factor Analysis does that by producing new general variables, called “factors”, incorporating inside them, the initial features/indicators according to a condition of high inter-correlation between the newly emerged general variables (“factors”) and the initially presented specific variables [19, 22].
The system needs to analyze the input feed and result to its outcome, taking into account however, environmental factors regarding system’s efficiency, explicit policies that should by adopted or exceptions that should be applied, that are related to specific locations (e.g., restricted areas) or specific human profiles. Such information usually is returned to the system in the form of a generic asynchronous qualitative feedback (for example insisting user discards of system’s outcomes, or exception to system’s rules) that should be assimilated in real – time.
The system should be able to receive environmental feedback and adapt its operation to the current circumstances and requirements. Therefore, we propose a two-mode adaptation, an offline and an online. The offline adaptation regards a system initialization, responsible for translating human – understandable requirements to algorithms’ parameterization. The online adaptation should track environmental feedback for each action of set of actions (policies) produced by the system and adapt algorithms’ behavior in order to fulfill system’s requirements.
In this case we propose the implementation of reinforcement learning techniques where environmental feedback should be encoded to quantitative measures of rewards, Figure 27.
Online ALMS.
Security and safety management systems and their data fusion and intelligent analytics capabilities require substantial data collection and processing in order to offer the best possible awareness and decision support to C&C operators, field personnel and first responders. Especially in the context of homeland security, privacy and data protection is often seen through the typical trade-off model perspective, requesting the public to give up –in the best case knowingly- on particular rights over the control of their personal data. However, such systems should not be based and developed on exceptions or operate only in extraordinary circumstances, the latter being very inefficient. With the latest guidelines of EU General Data Protection Regulation (GDPR), principles of data minimization and privacy by design will shift from best practices into a much more regulated form.
The proposed system is in line with these principles, following a “by design approach” in terms of data protection and ethics. Data collected are structurally separated from identifiable information, and identification occurs only upon the logged and explicit intervention of a human operator when truly needed. By assessing risks on real time, the system itself has the advantage of performing data minimization through early elimination of lower risk cases. On the front end and field, privacy enhancing technologies and smart sensors are also preferred and selected. E.g. smart visual sensors with on-board processing capabilities can filter out data before sending it over the wire and to the server for processing. Moreover, the system has been designed to include specific safeguards to protect individuals against discrimination, stigmatization and unduly prohibition of access to goods and services. Defined in [23], the system adopts these definitions and extends them to all protected grounds as defined in the Charter and the Treaty of Amsterdam, taking also into account the proposal for the horizontal directive that extends the context of EU non-discrimination law and prohibits discrimination “on grounds of sex, racial or ethnic origin, age, disability, sexual orientation, religion or belief”. In this context, Fairness and bias detection algorithms are applied to the adaptive learning management system while the human operator remains in control of the final enforcement following any automated decision making process. Intelligent behavior analytics can further support the case where security risks are based and calculated on how a person acts on the scene and not any discriminatory background information.
A subject of past and current research, assessing the societal acceptance of surveillance and security solutions comes with its own challenges. Acceptance is based on multiple parameters, individual perceptions and sometimes misconceptions and individual practices which may not be in line with the expressed concerns [24]. The proposed system and the overall risk-based security paradigm, is based on the positive fact that the vast majority of people have no malicious intent. The system focuses on the unknown and high-risk cases, intending to shift the current practices from annoying horizontal and disruptive processes to seamless and unobtrusive security. The combination of privacy and ethics by design along with the ethical and unobtrusive treatment set the parameters for a system with high acceptance, positive public perception and trust.
In this chapter we discussed the concept of risk-based security, the possible trade-off between increased convenience for passengers from risk-based security and the delays induced by additional checks needed for establishing each passenger’s risk. We also presented a number of technologies, systems and applications that can be used for assessing risk at an airport or BCP without inducing additional delay as the discussed approaches estimate risk on-the-fly while passengers either walk around the airport or BCP from entrance to security check points or BCPs, or queue up in a security line awaiting to go through security checks. All methods discussed are GDPR and ethics compliant, thus they can be implemented in accordance to privacy and ethics regulations. Furthermore, the novel system architecture for Security and Safety monitoring systems introduced in [3] has been presented. The proposed system aims to identify adverse events or behaviors which may endanger the safety of people or their well-being having the ability to adapt in the surveillance environment changes. The dynamic adjustment of the algorithmic parameters adopted in various units of the system such as intelligence, and Risk assessment, makes it possible to monitor security threats as they evolve. Thus, the proposed scheme provides the potential of a high-performance system both in terms of the detection interval as well as in terms of the performance accuracy offering the capability of a timely and efficient response to abnormal events and behaviors.
The research described in this paper has been supported by the following research contracts:
“
“
The author would also like to acknowledge the use of some material from the Refs. [5, 6, 7, 8, 9, 10, 12, 14]. He co-authored in collaboration with his colleagues whose names appear in these references.
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Applying FMEA in clinical approaches can lead to a significant reduction of the risk priority number (RPN).",book:{id:"9808",slug:"contemporary-topics-in-patient-safety-volume-1",title:"Contemporary Topics in Patient Safety",fullTitle:"Contemporary Topics in Patient Safety - Volume 1"},signatures:"Hoda Sabati, Amin Mohsenzadeh and Nooshin Khelghati",authors:[{id:"340486",title:"M.Sc.",name:"Hoda",middleName:null,surname:"Sabati",slug:"hoda-sabati",fullName:"Hoda Sabati"},{id:"348872",title:"M.Sc.",name:"Amin",middleName:null,surname:"Mohsenzadeh",slug:"amin-mohsenzadeh",fullName:"Amin Mohsenzadeh"},{id:"348874",title:"MSc.",name:"Nooshin",middleName:null,surname:"Khelghati",slug:"nooshin-khelghati",fullName:"Nooshin Khelghati"}]},{id:"69876",title:"Leadership Styles in Nursing",slug:"leadership-styles-in-nursing",totalDownloads:3157,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Recent developments in the field of management-organization and organizational behavior and new concepts have also led to the emergence of new leadership styles in leadership. Leadership in health services is important for following innovations and adapting to current situations. Nurses working together with other health personnel in hospitals providing health services constitute an important group in leadership. Nursing, which is a key force for patient safety and safe care, is a human-centered profession, and therefore leadership is a key skill for nurses at all levels. The leadership styles of nurse managers are believed to be an important determinant of job satisfaction and persistence of nurses. The need for nurses with leadership skills and the need for nurses to develop their leadership skills are increasing day by day. There are several leadership styles defined in nursing literature. These leadership styles are examined under the titles of relational leadership style, transformational leadership, resonant leadership, emotional intelligence leadership, and participatory leadership. The task-focused leadership style is explored under the headings of transactional and autocratic leadership, laissez-faire leadership, and instrumental leadership.",book:{id:"9047",slug:"nursing-new-perspectives",title:"Nursing",fullTitle:"Nursing - New Perspectives"},signatures:"Serpil Çelik Durmuş and Kamile Kırca",authors:null},{id:"58916",title:"Factors Affecting the Attitudes of Women toward Family Planning",slug:"factors-affecting-the-attitudes-of-women-toward-family-planning",totalDownloads:8548,totalCrossrefCites:9,totalDimensionsCites:18,abstract:"Everyone has the right to decide on the number and timing of children without discrimination, violence and oppression, to have the necessary information and facilities for it, to access sexual and reproductive health services at the highest standard. Deficient or incorrect family planning methods, wrong attitudes and behaviors toward the methods and consequent unplanned pregnancies, increased maternal and infant mortality rates are the main health problems in most countries. Individuals’ learning modern family planning methods and having positive attitude for these methods may increase the usage of these methods and contributes the formation of healthy communities. It is considered important to examine the current attitudes and determinants in order to spread the choice of effective method.",book:{id:"6142",slug:"family-planning",title:"Family Planning",fullTitle:"Family Planning"},signatures:"Nazli Sensoy, Yasemin Korkut, Selcuk Akturan, Mehmet Yilmaz,\nCanan Tuz and Bilge Tuncel",authors:[{id:"216377",title:"Prof.",name:"Nazli",middleName:null,surname:"Sensoy",slug:"nazli-sensoy",fullName:"Nazli Sensoy"},{id:"216589",title:"Dr.",name:"Yasemin",middleName:null,surname:"Korkut",slug:"yasemin-korkut",fullName:"Yasemin Korkut"},{id:"216595",title:"Dr.",name:"Selcuk",middleName:null,surname:"Akturan",slug:"selcuk-akturan",fullName:"Selcuk Akturan"},{id:"216596",title:"Dr.",name:"Canan",middleName:null,surname:"Tuz",slug:"canan-tuz",fullName:"Canan Tuz"},{id:"216598",title:"Dr.",name:"Bilge",middleName:null,surname:"Tuncel",slug:"bilge-tuncel",fullName:"Bilge Tuncel"},{id:"216599",title:"Dr.",name:"Mehmet",middleName:null,surname:"Yilmaz",slug:"mehmet-yilmaz",fullName:"Mehmet Yilmaz"}]},{id:"69631",title:"Cultural Practices and Health Consequences: Health or Habits, the Choice Is Ours",slug:"cultural-practices-and-health-consequences-health-or-habits-the-choice-is-ours",totalDownloads:902,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Human beings are social animals with an innate desire to conform to socially accepted norms and values. Over periods of time, some of these norms become standards that all members of the community are expected to adhere to. Deviance from these standards is seen as absurd, wrong, or frankly abnormal. However, many of these cultural mores have no scientific basis and, some of them actually promote behaviors with negative health consequences. This chapter examines the cultural practices of some communities in Africa and their health consequences and, explores ways to address the challenges.",book:{id:"9138",slug:"public-health-in-developing-countries-challenges-and-opportunities",title:"Public Health in Developing Countries",fullTitle:"Public Health in Developing Countries - Challenges and Opportunities"},signatures:"Radiance Ogundipe",authors:[{id:"302308",title:"Dr.",name:"Radiance",middleName:null,surname:"Ogundipe",slug:"radiance-ogundipe",fullName:"Radiance Ogundipe"}]},{id:"55808",title:"The Role of Legumes in Human Nutrition",slug:"the-role-of-legumes-in-human-nutrition",totalDownloads:5433,totalCrossrefCites:63,totalDimensionsCites:109,abstract:"Legumes are valued worldwide as a sustainable and inexpensive meat alternative and are considered the second most important food source after cereals. Legumes are nutritionally valuable, providing proteins (20–45%) with essential amino acids, complex carbohydrates (±60%) and dietary fibre (5–37%). Legumes also have no cholesterol and are generally low in fat, with ±5% energy from fat, with the exception of peanuts (±45%), chickpeas (±15%) and soybeans (±47%) and provide essential minerals and vitamins. In addition to their nutritional superiority, legumes have also been ascribed economical, cultural, physiological and medicinal roles owing to their possession of beneficial bioactive compounds. Research has shown that most of the bioactive compounds in legumes possess antioxidant properties, which play a role in the prevention of some cancers, heart diseases, osteoporosis and other degenerative diseases. Because of their composition, legumes are attractive to health conscious consumers, celiac and diabetic patients as well as consumers concerned with weight management. The incorporation of legumes in diets, especially in developing countries, could play a major role in eradicating protein-energy malnutrition especially in developing Afro-Asian countries. Legumes could be a base for the development of many functional foods to promote human health.",book:{id:"5963",slug:"functional-food-improve-health-through-adequate-food",title:"Functional Food",fullTitle:"Functional Food - Improve Health through Adequate Food"},signatures:"Yvonne Maphosa and Victoria A. Jideani",authors:[{id:"201151",title:"Ph.D. Student",name:"Yvonne",middleName:null,surname:"Maphosa",slug:"yvonne-maphosa",fullName:"Yvonne Maphosa"}]}],onlineFirstChaptersFilter:{topicId:"200",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"82616",title:"The Quantum Theory of Reproduction – How Unique is an Individual?",slug:"the-quantum-theory-of-reproduction-how-unique-is-an-individual",totalDownloads:12,totalDimensionsCites:0,doi:"10.5772/intechopen.105769",abstract:"Our understanding of nature’s way is founded on quantum mechanics. In its existence of over 80 years, quantum theory has been describing the physical world. The attraction of studying quantum mechanics is the perception of the conceptual structure of nature. This is aided by the mathematical structure that exposes the internal logic of the subject by inventing a notation that embeds the philosophy of the question. To describe how unique each individual is. A calculation method was applied. The uniqueness of an individual is one in two nonillion, octillion, septillion, sextillion, quintillion, quadrillion, trillion, billion, million and thousand. Individuals are indefinitely unique.",book:{id:"11284",title:"Studies in Family Planning",coverURL:"https://cdn.intechopen.com/books/images_new/11284.jpg"},signatures:"Zouhair O. Amarin"},{id:"81930",title:"Smoking and Its Consequences on Male and Female Reproductive Health",slug:"smoking-and-its-consequences-on-male-and-female-reproductive-health",totalDownloads:14,totalDimensionsCites:0,doi:"10.5772/intechopen.104941",abstract:"Smoking contributes to the death of around one in 10 adults worldwide. Specifically, cigarettes are known to contain around 4000 toxins and chemicals that are hazardous in nature. The negative effects of smoking on human health and interest in smoking-related diseases have a long history. Among these concerns are the harmful effects of smoking on reproductive health. Thirteen percent of female infertility is due to smoking. Female smoking can lead to gamete mutagenesis, early loss of reproductive function, and thus advance the time to menopause. It has been also associated with ectopic pregnancy and spontaneous abortion. Even when it comes to assisted reproductive technologies cycles, smokers require more cycles, almost double the number of cycles needed to conceive as non-smokers. Male smoking is shown to be correlated with poorer semen parameters and sperm DNA fragmentation. Not only active smokers but also passive smokers, when excessively exposed to smoking, can have reproductive problems comparable to those seen in smokers. In this book chapter, we will approach the effect of tobacco, especially tobacco smoking, on male and female reproductive health. This aims to take a preventive approach to infertility by discouraging smoking and helping to eliminate exposure to tobacco smoke in both women and men.",book:{id:"11284",title:"Studies in Family Planning",coverURL:"https://cdn.intechopen.com/books/images_new/11284.jpg"},signatures:"Amor Houda, Jankowski Peter Michael, Micu Romeo and Hammadeh Mohamad Eid"},{id:"81468",title:"The Knowledge and Use of Intra-Uterine Device by Women Attending Ante-Natal Clinic at Enugu State Teaching Hospital, Parklane",slug:"the-knowledge-and-use-of-intra-uterine-device-by-women-attending-ante-natal-clinic-at-enugu-state-te",totalDownloads:24,totalDimensionsCites:0,doi:"10.5772/intechopen.104097",abstract:"Intrauterine contraception has been recognized globally as one of the modern long-term reversible contraceptive methods suitable for women of all reproductive ages. It represents the most cost-effective method for preventing unwanted pregnancies, scientifically proven for its safety, efficacy and cost-effectiveness and is known to last longer in preventing pregnancy than other methods. This study assessed the knowledge of mothers attending ESUT teaching hospital, Parklane on intrauterine contraceptive device, the use as well as the common side effects experienced by the users. A descriptive survey research design was used to sample 175 mothers. A structured researcher developed questionnaire was used for data collection. The findings revealed that more than half of the respondents have good knowledge of intrauterine device but only 23 (14%) respondents make use of it. The commonly experienced side effects identified were irregular bleeding (75%) and vaginal discharge (62.5%). Although, the respondents had good knowledge of intrauterine device, their uptake of the method was poor. Therefore, there is a need to improve contraceptive counseling to ensure that women understand the relative effectiveness of IUDS. The study also recommended the need for better education for both clients and providers to improve the accessibility and acceptability of intrauterine device.",book:{id:"11284",title:"Studies in Family Planning",coverURL:"https://cdn.intechopen.com/books/images_new/11284.jpg"},signatures:"Chukwuasokam Caleb Aniechi and Uloma Cynthia Ezuma"},{id:"81003",title:"Perspective Chapter: Modern Birth Control Methods",slug:"perspective-chapter-modern-birth-control-methods",totalDownloads:43,totalDimensionsCites:0,doi:"10.5772/intechopen.103858",abstract:"This chapter focuses on various modern birth control methods, including combined oral contraceptives, progestogen-only pills, progestogen-only injectables, progestogen-only implants, intrauterine devices, barrier contraceptives, and emergency contraceptive pills. Each contraceptive method is covered in detail, including mechanism of action, effectiveness, health benefits, advantages, disadvantages, risks, and side-effects.",book:{id:"11284",title:"Studies in Family Planning",coverURL:"https://cdn.intechopen.com/books/images_new/11284.jpg"},signatures:"Rahma Al Kindi, Asma Al Salmani, Rahma Al Hadhrami, Sanaa Al Sumri and Hana Al Sumri"},{id:"80084",title:"Contraceptive Implants",slug:"contraceptive-implants",totalDownloads:174,totalDimensionsCites:0,doi:"10.5772/intechopen.101999",abstract:"Contraceptive implants or implantable contraceptive are five subdermal implants, rods the size of pencil lead that are embedded just under the skin on the inside of the upper arm. The rods contain etonogestrel, the metabolite of desogestrel, an equivalent progestin. Implants are often used during breastfeeding without an impact on milk production. It was identified that age does not affect the use of contraceptive implants but educational status is significant to its usage; there is an association between the age at first birth and the use of contraceptive implants; the number of liveborn children has a significant impact or influence on the use of implants; etc. This chapter focuses on types of contraceptive implants and its mechanism of action; global statistics on contraceptive implants; side effects; health benefits and positive characteristics of contraceptive implants; those who can and cannot use contraceptive implants; reasons women are not interested in contraceptive implants and factors influencing its usage.",book:{id:"11284",title:"Studies in Family Planning",coverURL:"https://cdn.intechopen.com/books/images_new/11284.jpg"},signatures:"Paul Hassan Ilegbusi"}],onlineFirstChaptersTotal:5},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:108,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:330,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:14,numberOfPublishedChapters:145,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:9,numberOfPublishedChapters:141,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:123,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:112,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:22,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:11,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:"2753-6580",doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}},{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}}]},series:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"August 2nd, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:33,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",slug:"miroslav-blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:4,paginationItems:[{id:"14",title:"Cell and Molecular Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",isOpenForSubmission:!0,editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",slug:"rosa-maria-martinez-espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",biography:"Dr. Rosa María Martínez-Espinosa has been a Spanish Full Professor since 2020 (Biochemistry and Molecular Biology) and is currently Vice-President of International Relations and Cooperation development and leader of the research group 'Applied Biochemistry” (University of Alicante, Spain). Other positions she has held at the university include Vice-Dean of Master Programs, Vice-Dean of the Degree in Biology and Vice-Dean for Mobility and Enterprise and Engagement at the Faculty of Science (University of Alicante). She received her Bachelor in Biology in 1998 (University of Alicante) and her PhD in 2003 (Biochemistry, University of Alicante). She undertook post-doctoral research at the University of East Anglia (Norwich, U.K. 2004-2005; 2007-2008).\nHer multidisciplinary research focuses on investigating archaea and their potential applications in biotechnology. She has an H-index of 21. She has authored one patent and has published more than 70 indexed papers and around 60 book chapters.\nShe has contributed to more than 150 national and international meetings during the last 15 years. Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",isOpenForSubmission:!0,editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. He performed post-doctoral studies at Max-Planck Institute, Germany, and University of Florence, Italy in addition to making several scientific visits abroad. He currently works as a Full Professor of Biochemistry in the Faculty of Pharmacy, Anadolu University, Turkey. Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. Dr. Beydemir is also Rector of Bilecik Şeyh Edebali University, Turkey.",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",slug:"deniz-ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",biography:"Dr. Deniz Ekinci obtained a BSc in Chemistry in 2004, MSc in Biochemistry in 2006, and PhD in Biochemistry in 2009 from Atatürk University, Turkey. He studied at Stetson University, USA, in 2007-2008 and at the Max Planck Institute of Molecular Cell Biology and Genetics, Germany, in 2009-2010. Dr. Ekinci currently works as a Full Professor of Biochemistry in the Faculty of Agriculture and is the Head of the Enzyme and Microbial Biotechnology Division, Ondokuz Mayıs University, Turkey. He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. Dr. Ekinci serves as the Editor in Chief of four international books and is involved in the Editorial Board of several international journals.",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null},{id:"17",title:"Metabolism",coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",isOpenForSubmission:!0,editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",slug:"yannis-karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",biography:"Yannis Karamanos, born in Greece in 1953, completed his pre-graduate studies at the Université Pierre et Marie Curie, Paris, then his Masters and Doctoral degree at the Université de Lille (1983). He was associate professor at the University of Limoges (1987) before becoming full professor of biochemistry at the Université d’Artois (1996). He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. His teaching areas are energy metabolism and regulation, integration and organ specialization and metabolic adaptation.",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null},{id:"18",title:"Proteomics",coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",isOpenForSubmission:!0,editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",slug:"paolo-iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",biography:"Paolo Iadarola graduated with a degree in Chemistry from the University of Pavia (Italy) in July 1972. He then worked as an Assistant Professor at the Faculty of Science of the same University until 1984. In 1985, Prof. Iadarola became Associate Professor at the Department of Biology and Biotechnologies of the University of Pavia and retired in October 2017. Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. In this context, he has developed and validated new methodologies (e.g., Capillary Electrophoresis coupled to Laser-Induced Fluorescence, CE-LIF) whose application enabled him to determine both the amounts of biochemical markers (Desmosines) in urine/serum of patients affected by Chronic Obstructive Pulmonary Disease (COPD) and the activity of proteolytic enzymes (Human Neutrophil Elastase, Cathepsin G, Pseudomonas aeruginosa elastase) in sputa of these patients. More recently, Prof. Iadarola was involved in developing techniques such as two-dimensional electrophoresis coupled to liquid chromatography/mass spectrometry (2DE-LC/MS) for the proteomic analysis of biological fluids aimed at the identification of potential biomarkers of different lung diseases. He is the author of about 150 publications (According to Scopus: H-Index: 23; Total citations: 1568- According to WOS: H-Index: 20; Total Citations: 1296) of peer-reviewed international journals. He is a Consultant Reviewer for several journals, including the Journal of Chromatography A, Journal of Chromatography B, Plos ONE, Proteomes, International Journal of Molecular Science, Biotech, Electrophoresis, and others. He is also Associate Editor of Biotech.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorTwo:{id:"201414",title:"Dr.",name:"Simona",middleName:null,surname:"Viglio",slug:"simona-viglio",fullName:"Simona Viglio",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKDHQA4/Profile_Picture_1630402531487",biography:"Simona Viglio is an Associate Professor of Biochemistry at the Department of Molecular Medicine at the University of Pavia. She has been working since 1995 on the determination of proteolytic enzymes involved in the degradation process of connective tissue matrix and on the identification of biological markers of lung diseases. She gained considerable experience in developing and validating new methodologies whose applications allowed her to determine both the amount of biomarkers (Desmosine and Isodesmosine) in the urine of patients affected by COPD, and the activity of proteolytic enzymes (HNE, Cathepsin G, Pseudomonas aeruginosa elastase) in the sputa of these patients. Simona Viglio was also involved in research dealing with the supplementation of amino acids in patients with brain injury and chronic heart failure. She is presently engaged in the development of 2-DE and LC-MS techniques for the study of proteomics in biological fluids. The aim of this research is the identification of potential biomarkers of lung diseases. 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