Biometrics is the scienceand technology of uniquely identifying a person bythe physical, physiological, genomic, or behavioralcharacteristics. For example, the biometric traitsor signatures for unique characterization of aperson may be obtained from fingerprint, palm print,face, iris, retina, shape of ear, voice, signature,gait, vein in the hand, odor, handwriting, DNAsequences, etc. Some of these traits are evidentlyvisible and are often used in our socialinteractions to identify a person. But many of themmay need use of technology and computationalprocessing for extraction of biometriccharacteristic signatures from them and verifyingthem subsequently. For a unique identification of aperson, the biometric data, also referred to as thebiometric signature, should have the properties ofuniqueness and permanence. The uniqueness is thecharacteristics that uniquely identifies anindividual person and permanence implies that itshould remain unchanged throughout the life of theindividual. However, permanence in absolute sense isseldom true in practice. In view of that, it ispragmatic to use those biometric traits, which areexpected to remain mostly unaltered for asignificant period of time. During this period,there may be some marginal deviations that can belargely tolerated for a practical solution.

17.1 | Biometric system

A biometric system isprimarily designed for managing the identity of aperson. Identity management is required in almostevery sphere of social interaction and activitieslike, border control, access control to certainresources, to avail conditional facilities (food,LPG connection, etc.), financial transactions,admission to examinations, certifying thequalification and competence, etc. There may also bevarious related tasks other than identifying aperson like, determining age and gender of anindividual, establishing kinship between twopersons, etc. There are three main generic tasksthat are involved in such a system of identitymanagement.

Classification is a taskof assigning a known category or class to an object.A class is a wellstudied group of objects that is identified by theircommon properties or characteristics. For example,consider the image in Fig. 7.1, where an instance ofa region in the image is denoted by a rectangularbounding box. Here, the task is to classifydifferent regions in the image by consideringvarious patches, as illustrated by a few boundingboxes, to two classes, “human” or “nonhuman”.Likewise a few other examples of imageclassification problem are, detection of pedestriansin an image patch, recognition of a letter given atwo-dimensional (2-D) image pattern, assigning apixel of an image to its foreground or background,finding whether an image captured indoor or outdoor,etc. We may observe here the diversified nature ofclassification problems and by solving them,different types of tasks are performed. Mostly, theclassification problem falls under the supervisedlearning framework, where training samples withappropriate features and class labels are used tolearn a model that is suitable for predictingclasses of the given data. There are variousapproaches for addressing the classification problemlike probabilistic approach, distance basedapproach, discriminant analysis based approach,artificial neural network (ANN) based approach, etc.This chapter introduces four specific techniquesfrom these approaches, namely, Bayesianclassification technique (particularly, naiveBayesian classifier), 𝐾-nearest neighbor (𝐾-NN)classifier, use of linear discriminant functions,and artificial neutral network, respectively.

Computer vision is the science of facilitating amachine or a computer with the human-like capabilityof seeing and understanding the environment. It is afield of artificial intelligence (AI), which dealswith the theory, algorithmic basis, and computationfor automatic understanding of visual data acquiredfrom an environment. With the rapid advancement ofdigital and computing technology, it is possible tocapture images and videos of a scene and store thedata in the memory of a computer. Computer vision isprimarily concerned with the automatic extraction,analysis and understanding of useful informationfrom a single image, a set of images, or a videowhich is a sequence of images. It has a wide rangeof applications across the society and variousindustries, such as in autonomous vehicles, healthcare, surveillance, augmented reality, robotics,remote sensing, document processing, biometrics, andmore. Some of the key tasks of computer vision areacquisition and processing of images and videos,extracting information, and finally, derivingknowledge and description about the scene. In thisintroductory chapter, we briefly review some of thefundamental aspects of image and video processingwhich may be sufficient to follow the content of therest of the book. However, the readers may beadvised to go through first level image and videoprocessing textbooks to know more details aboutit.

1.1 Image representation

To understand how images are represented in a computer,consider an image shown in Fig 1.1. A small portionof this image, shown by a white rectangle, is zoomedto reveal enlarging details of that portion of theimage. We observe that, within this zoomed portion,although the details are better visible, the edgesappear jagged.

Classification of Large Signal Amplifiers

The amplifiers studied so far are small signal amplifiers, where the magnitude of the input signal is small, and the main aim is to amplify either voltage or current with minimum distortion. However, in many applications like control, communication, and power conversion, a large amount of power, sometimes exceeding tens of kW, is to be handled by transistors and other semiconductor devices. In that case, the employed amplifiers are called power amplifiers or large signal amplifiers, where output signals, voltage and current, are large in magnitude.

Based on the type of circuit configuration like CE, CB, and CC, and the location of the quiescent point on the output characteristics, power amplifiers are classified as class A, class B, class AB, class C, and D, E, and F. Each class has its advantages and limitations, which will be discussed along with their circuits and operation. Class D is used very little, and classes E and F are rarely used, so only A, B, and C types of amplifiers will form part of this study, and their classification criterion is mentioned next.

Class A Amplifier: In class A operation, an amplifier is so biased that its operating point is almost in the middle of the output characteristics. The magnitude of the input signal is such that the amplifier operates over its full linear region of the characteristics, but without any clipping of the input signal. So, the output is the amplified replica of the input signal with minimal distortion. However, class A operation works with poor power conversion efficiency; the theoretical maximum power conversion efficiency from DC input to AC output is from 25–50%.

A comparison of trajectories (i.e., of how things change through time in complexification) is pursued graphically by aligning trajectories in time according to their points of initial regional integration and of maximal differentiation. Some of these patterns of change “rhyme” in time and signal bundles of trajectories in which similar changes can be seen as responses to similar forces.

Key Concepts

• • Decarbonization pyramid and the importance of energy conservation in sustainable development

• • Concept of energy management for optimal utilization of electricity

• • Demand-side management

• • Role of energy-efficient appliances in decarbonization

• • Energy Conservation Act of India

• • Major schemes on energy conservation by the BEE in India

• • Concept and types of energy audit, energy managers, and energy auditors

• • Power factor and energy conservation

• • Importance of awareness campaigns, and participation of stakeholders in energy conservation

Introduction

Decarbonizing the electricity infrastructure is of prime importance for achieving climate protection and SDGs. Switching over to carbon-free generation of electricity, like solar and wind, is a mandatory requirement for it. But this energy shifting is not the sufficient requirement for decarbonization. Conservation of energy, in addition to energy shifting, needs to be pursued and implemented simultaneously. Energy conservation is using less energy by avoiding unnecessary uses of energy. The idea of energy conservation, in fact, is in the true spirit of sustainable development also. As defined earlier, development that meets the needs of the present without compromising the ability of future generations to meet their own needs is sustainable development.

‘One unit saved is equal to two units generated’ has been a famous saying of electrical engineering for a long time.

The objective behind this principle, however, was more on financial savings. But in the changed scenario, this principle needs aggressive reiteration as it involves financial as well as environmental savings. In addition, energy conservation leads to reduction in peak demand and the requirement of new infrastructure.

Concept of Negative Feedback

In a feedback system, a signal that is proportional to the output is fed back to the input. It may happen unintentionally or be done intentionally. When the feedback signal adds to the input signal, it is called positive feedback, and when the input signal gets subtracted from the feedback signal, it becomes negative feedback.

Positive feedback is mostly used for the realization of oscillators, whereas negative feedback is used to stabilize the gain of amplifiers against a variation in transistor parameters, supply voltage, and temperature etc.The study in this chapter is limited to negative feedback only, which is primarily used to improve any one of the four types of amplifiers given in the next section, such that the amplifiers become as close to ideal as possible. However, certain conditions are required that help achieve the objective. For example, a primary amplifier is needed to have a very high gain in the forward direction, minimum reverse transmission, which normally happens as a property of the transistors used. Appropriate negative feedback connection and minimum effect of loading due to the feedback network on the main amplifier circuit are also very important.

The above mentioned term appropriate negative feedback needs a bit of explanation. In the voltage and current amplifiers, variables at the input and output are the same, hence there is no problem as such while feeding a part of the output to input.

In this chapter, the theory and properties of singleview camera geometry are discussed. We consider theprinciple of image formation in optical cameras inthis case and apply it to relate thethree-dimensional (3-D) world with the image pointson a two-dimensional (2-D) plane.

11.1 | Pinhole camera

A mapping of a point in a 3-D coordinate space to apoint on a 2-D plane has been already discussed inthe previous chapter while explaining the canonicalconfiguration of a 2-D projective space. We relatethese concepts with respect to a pinhole camerabased imaging system. Consider a 3-D scene point, 𝑷, as shown in Fig. 11.1. The corresponding imagepoint, 𝒑′, is the point of intersection of theimage plane and the straight line from 𝑷 thatpasses through the center of the lens, 𝑂. In thesame analogy, consider the formation of an image infront of the camera center, where the correspondingimage plane is placed at the same distance as thesensor is placed behind the lens. In this case, theimages obtained on the image plane that is placed infront of the lens are of the same size as on thesensor, and there is a logical transformation ofcoordinates from point 𝒑′ to point 𝒑. Thus we maydirectly relate the scene point 𝑷 with the imagepoint 𝒑. This is a convenient way of handlingcoordinate system of image points by placing it infront of the camera in the same side of the viewingobjects.

12.1 INTRODUCTION [LO1]

There are in general two approaches to solving equilibrium problems in solid mechanics: Eulerian and Lagrangian. The first approach deals with vectors such as force and moments, and considers the static equilibrium and compatibility equations to solve the problems. In the second approach, scalars such as work and energy are used, and here solutions to problems are based on the principle of conservation of energy. There are many situations where the second approach is more advantageous, and here some powerful methods, such as the method of virtual work, based on this approach, are used.

Eulerian and Lagrangian approaches to solving solid mechanics problems are much more involved. However, here we have chosen to describe these in a simplified manner, which is suitable as a prologue to the present discussion on energy methods.

In mechanics, energy is defined as the capacity to do work, and this may exist in different forms. We are concerned here with elastic strain energy, which is a form of potential energy stored in a body on which some work is done by externally applied forces. Here it is assumed that the material remains elastic when work has been done so that all the energy is recoverable and no permanent deformation occurs. This means that strain energy U = work done. If the load is applied gradually in straining, the material load–extension graph is as shown in Figure 12.1, and we may write U = ½ Pδ.

The hatched portion of the load–extension graph represents the strain energy and the unhatched portion ABD represents the complementary energy that is utilized in some advanced energy methods of solution.

List of Experiments

• 1. Determine the energy band gap of N-type Germanium (Ge) semiconductor using the four-probe method.

• 2. Verify Stefan's fourth power law for black body radiation and determine the exponent of temperature.

• 3. Study of thermoelectricity: Determine thermopower of copper-constantan thermocouple.

• 4. Study the variation of magnetic field with distance along the axis of current-carrying coil and then estimate the radius of the coil.

• 5. Study of Carrey Foster bridge: Determine resistance per unit length of the bridge wire and of a given unknown resistance.

• 6. Determine specific charge (charge to mass ratio; e/m) for electron.

• 7. Study of tangent galvanometer: Determine reduction factor and horizontal component of the earth's magnetic field.

• 8. Determine the wavelength of sodium light using Newton's rings method.

• 9. Determine the concentration of sugar solution using half-shade polarimeter.

• 10. Determine the wavelength of spectral lines of mercury (for violet, green, yellow-1, and yellow-2) using plane transmission grating.

• 11. Determine the charge sensitivity and ballistic constant of a ballistic galvanometer.

• 12. Determine the wavelength of spectral lines of hydrogen and hence the value of Rydberg constant.

• 13. Draw the V-I characteristic of light-emitting diode (LED) and determine the value of Planck's constant.

Experiment 1: Band Gap of Semiconductor

Objective: To determine the energy band gap of n-type Ge-semiconductor using four-probe method.

Apparatus Used: The following apparatus are used in this experiment:

• 1. Probe arrangement (shown in Figure 14.1).

• 2. n-type Ge-crystal chip with nonconducting base.

• 3. Oven with temperature up to 200°C.

• 4. A constant current generator power supply.

• 5. Power source for the oven.

• 6. Thermometer.

Introduction

Classification, characteristics, and basic design methods of certain types of networks that perform filtering action on the basis of the frequency of signals are briefly discussed in this chapter. The filters, which used only passive elements, and known as passive filters, were the only kind of filters in earlier days. Passive filters are still in use in many specific cases but have been replaced by active filters (using at least one active device) in a majority of applications. One essential reason for the changeover from the passive filters to the active filters was the inability of the realization of practically feasible inductors in integrated circuit (IC) form over a large frequency range of operation. Hence, structures that replaced (simulated) inductors employing resistance, capacitance, and op-amp were synonymous with the active filters, and these were called active RC filters. The usage of op-amps is still dominant, but other active devices are also used in a big way.

Another important approach to analog filter realization has emerged in the form of switched capacitor (SC) circuits. An important feature of the SC circuits is that it uses only capacitors, op-amps, and electronic switches. Consequently, performance parameters of the circuit depend on capacitor ratios and switching frequency. It is to be noted that very small value capacitances can be used, resulting in consuming less chip area, and better practical results as capacitors in ratio form can be fabricated with much less tolerance.

Rigorous collection, reporting, and analysis of household artifact assemblage data in future research would make it possible to characterize differentiation of all kinds with greater confidence. The lack of regional-scale settlement research in some regions leaves demographic estimates lacking good support. The richness of ethnographic information for some places has undermined the archaeological research needed to say how organization developed before the “ethnographic present.”

Our lived experiences are punctuated by events that are sometimes a result of our purposeful intentions and at other times outcomes that happen by pure chance. Even at an abstract level, it is a very human endeavor to deduce meaning from seemingly random observations an exercise whose primary objective is to derive a causal structure in observed phenomena. In fact, our whole intellectual pursuit that differentiates us from other beings can be understood through our inner urge to discover the very purpose of our existence and the conditions that make this possible. This eternal play between chance episodes and purposeful volition manifests in diverse situations that I have labored to recreate through computer simulations of realistic events. This play has a dual role - first, it binds together the flow of our varied experiences and, second, it offers us a perspective to assimilate our understanding of events happening around us that affect us. In order to appreciate this play of chance and purpose, it is essential that students and readers have a conceptual grounding in the areas of probability, statistics, and stochastic processes. Therefore, several playful computer simulations and projects are interlaced with theoretical foundations and numerical examples - both solved and exercise problems. In this way, the presentation in this book remains true to its spirit of inviting thoughtful readers to the various aspects of this area of study.

Historical remark

The advent of a rigorous framework for studying probability and statistics dates back to the eighth century AD and is documented in the works of Al-Khalil, who was an Arab philologist. This branch of mathematics continues to be under development with major contributions from Soviet mathematician Andrey N. Kolmogorov, who developed the modern foundations of probability and statistical theory from a measure-theoretic standpoint in the twentieth century.

This chapter provides an insight to some of the generalimage transforms that offer an alternativerepresentation of images and videos. Few of theirproperties and applications are also discussed thatare related to image compression and reconstruction.Other forms of representation that depend on data,like principal component analysis and sparserepresentation, are provided as an extension tothese representations. Techniques of computing basisfunctions and dictionary learning are introduced inthis chapter.

2.1 Image transforms

Consider a continuous function, 𝑓(𝑥), inone-dimensional (1-D) space, where, 𝑥 ∈ ℝ. Considera set, B, of 1-D basis functions, whose functionalvalues may either be in real or in complex domain.This is represented as in Eq. 2.1.

NANO

The term “nano” is derived from a Greek word that means “dwarf” (small) and is represented by the symbol “n.” As a unit prefix, it signifies “one billionth,” denoting a factor of 10-9 or 0.000000001. It is primarily used with the metric system, as illustrated in Figures 8.1 and 8.2. For example, one nanometer is equal to 1 × 10-9 m, and one nanosecond is equal to

1 × 10-9 sec. It is frequently encountered in science and electronics, particularly for prefixing units of time and length.

HISTORY OF NANOTECHNOLOGY

The origin of nanotechnology is often attributed to American physicist Richard Feynman's speech, “There's Plenty of Room at the Bottom,” which he gave on December 29, 1959, at an American Physical Society conference at Caltech. A 1959 lecture by Richard Feynman served as the intellectual inspiration for the field of nanotechnology. The term “nanotechnology” was initially used in a conference in 1974 by a Japanese scientist by the name of Norio Taniguchi from Tokyo University of Science to describe semiconductor techniques with characteristic control on the order of a nanometer, such as thin film deposition and ion beam milling. According to his definition, “nanotechnology” is primarily the processing, separation, consolidation, and deformation of materials by a single atom or molecule.