# Neeraj GuptaOakland University · Department of Computer Science and Engineering

Neeraj Gupta

PhD

https://www.adscientificindex.com/scientist.php?id=883408

## About

84

Publications

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1,833

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Introduction

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Education

July 2006 - February 2013

## Publications

Publications (84)

The expected fifth industrial revolution or Industry 5.0 (I-5.0) is human-centered and concerns societal values, and sustainability. I-5.0 focuses on human and machine coworking by augmenting human-collaborative intelligent robots. The current developments in information communications and the increasing market need for high agility and innovative...

The potential for sabotaging Deep Convolutions Neural Networks classifiers by Universal Perturbation Attack (UPA) has proved itself as an effective threat to fool deep learning models in sensitive applications such as autonomous vehicles, clinical diagnosis, face recognition, etc. The prospective application of UPA is for adversarial training of de...

Telecommunications systems with Multi-Input Multi-Output (MIMO) structure using Orthogonal Frequency Division Modulation (OFDM) has a great potential of efficient application to a network of Internet of Things (IoT) of a high data rate. When the IoT network is amongst the underwater sensory devices known as the Internet of Underwater Things (IoUT),...

Electrical energy is critical to a country’s socioeconomic progress. Distribution system expansion planning addresses the services that must be installed for the distribution networks to meet the expected load need, while also meeting different operational and technical limitations. The incorporation of distributed generation sources (DGs) alters t...

This paper focuses on developing a computationally economic lightweight artificial intelligence (AI) technology for smartphones. Until date, no commercial system is available on this technology. Thus the developed breakthrough technology can enhance the capability of users on the field for monitoring the agricultural vehicles (AgV)s health by analy...

This chapter illustrates the role of evolutionary optimization in designing AI end-devices to monitor the efficiency of agriculture vehicles (AgVs) mainly on the field via economic sound-based IoT sensors. Due to the application of AI on end-devices, there is a certain limitation for memory and complexity of the deployed algorithms. In such a condi...

This chapter presents the concept of evolutionary optimally designed machine learning models for end devices monitoring the operational condition of agriculture vehicles (AgVs). The ultimate target is an App usable in normal smartphones as IoT sensory device for monitoring healthy condition of agricultural machinery. Since smartphones use a small i...

Crossover is an important operator in genetic algorithms. Although hundreds of application dependent and independent crossover operators exist in the literature, this chapter provides holistic, but by no means an exhaustive, overview of different crossover techniques used in different variants of genetic algorithms. We will review some of the commo...

Compressive sensing has the ability of reconstruction of signal/image from the compressive measurements which are sensed with a much lower number of samples than a minimum requirement by Nyquist sampling theorem. The random acquisition is widely suggested and used for compressive sensing. In the random ac...

Multi-Input Multi-Output (MIMO) telecommunication systems with Orthogonal Frequency Division Modulation (OFDM) scheme support high rate data exchange which can be efficiently applied to the fast-growing networks of Internet of Things (IoT). In the case of Underwater IoT (UIoT) where the strength of electromagnetic waves rapidly falls off, the MIMO...

Smart monitoring of off-road vehicles are cursed by their complex and expensive IoT sensors technologies. High dependency on the cloud/fog computation, availability of the network and Expert knowledge make it handicap in the rural off-network areas. Use of edge devices such as smartphones attributed by computation capabilities is the solution that...

The hydraulic system is the backbone of industrial, construction, and agricultural machines. Its high-power density and efficiency execution make it the preferred choice for high-energy applications. This manuscript presents the evidence against the statement, Whenever the system runs to its full capacity, hydraulic oil heats up more as compared to...

Optimization plays a fundamental role in understanding stability characteristics of optical systems, for example, lenses, mirrors, and their constrained counterparts. For a dynamical object, the authors address the issue of stability of an image formed under fluctuations of optimization variables. As per this analysis, for a given single lens, mirr...

Generation of renewable energy sources and their interfacing to the main system has turn out to be most fascinating challenge. Renewable energy generation requires stable and reliable incorporation of energy to the low or medium voltage networks. This paper presents the microgrid modelling as an alternative and feasible power supply for Institute o...

Agents are intelligent entities that act flexibly and autonomously to make wise decisions based on their intelligence and experience. A multi-agent system (MAS) contains multiple intelligent interconnected collaborating agents for solving a problem beyond a single-agent ability. A smart grid combines advanced intelligence systems, control technique...

In the era of Internet of things (IoT), network Connection of an enormous number of agriculture machines and service centers is an expectation. However, it will be with a generation of massive volume of data, thus overwhelming the network traffic and storage system especially when manufacturers give maintenance service typically by various data ana...

Boost in solar energy (SE) incorporation into the
power system network creates power quality (PQ) issues in the
supply. This paper presents an assessment of PQ issues related
with the grid interfaced solar photovoltaic (SPV) system under
various operating conditions in the experimental framework by
utilizing Stockwell transform supported algorithm....

This is the MATLAB code for the very recent Evolutionary Optimizer as the article can be found in:
https://www.researchgate.net/publication/343178852_Mendelian_Evolutionary_Theory_Optimization_Algorithm
Also available in Githhub:
https://github.com/ngtaj/Mendelian-Evolutionary-Theory-Optimization
Evolutionary Computation Algorithm: "Mendelian...

This study presented a new multi-species binary coded algorithm, Mendelian Evolutionary Theory Optimization (METO), inspired by the plant genetics. This framework mainly consists of three concepts: First, the “denaturation” of DNA’s of two different species to produce the hybrid “offspring DNA”. Second , the Mendelian evolutionary theory of genetic...

Penetration level of solar photovoltaic (PV) energy in the utility network is steadily increasing. This changes the fault level and causes protection problems. Further, multi-tapped structure of distribution network deployed to integrate solar PV energy to the grid and supplying loads at the same time also raised the protection challenges. Hence, t...

In practical operating conditions, the Solar-Photo Voltaic (SPV) system experiences multifarious irradiation and temperature levels, which generate power with multiple peaks. This is considered as the nonuniform operating condition (NUOC). This requires accurate tracking of global power peaks to achieve maximum power from SPV, which is a challengin...

By the increasing growth of the Internet of Things (IoT) which provides interconnection and communications between electronic devices and corresponding sensors, a large volume of data is exchanged by multi-input multi-output (MIMO) telecommunication systems. In the case of IoT, reducing the data volume by removing the data redundancy results in mor...

div>This study presented a new multi-species binary coded algorithm, Mendelian Evolutionary Theory Optimization (METO), inspired by the plant genetics. This framework mainly consists of three concepts: First, the “denaturation” of DNA’s of two different species to produce the hybrid “offspring DNA”. Second , the Mendelian evolutionary theory of gen...

This study presented a new multi-species binary coded algorithm, Mendelian Evolutionary Theory Optimization (METO), inspired by the plant genetics. This framework mainly consists of three concepts: First, the “denaturation” of DNA’s of two different species to produce the hybrid “offspring DNA”. Second , the Mendelian evolutionary theory of genetic...

A very recent meta-heuristic optimizer is by inspiration from plant biology where the Mendel law of heredity is implemented through multi-species in two generations. Plant biology-inspired optimizer named as Mendelian Evolutionary Optimization Algorithm (METO), which has several advantages outperforming the state-of-the-art optimizers. It is highly...

As a great computational intelligence technique, artificial neural networks (ANNs) have intensively attracted the interest of researchers of artificial intelligence. Due to the easy implementation of ANN, vast types of structures and associated rules, their successful application can be seen in real-life and industrial problems. From a wide variety...

This chapter introduces problem frameworks to determine coordinated operation schedules of microgrid components including controllable generation systems (CGs), energy storage systems (ESSs) and controllable loads (CLs). The aim of this study is to design a profitable and stable operation of microgrids based on optimization theory and methods, and...

This chapter illustrates the characteristics of plant genetics-inspired evolutionary optimization (PGEO). The computation strategy of PGEO is inspired by the theory of Mendelian evolution. Presented PGEO optimizer is a binary-coded algorithm based on mainly three concepts from plant genetics: (i) the “denaturation” of DNA of two different species t...

Artificial neural networks (ANN) have a great impact on research in the field of artificial intelligence. It has great capability besides the easy implementation, and due to that, it has been widely used in a wide area of real-life and industrial applications. Today, we can see a variety of ANNs such as feed-forward ANN, Kohonen self-organizing ANN...

Electrocardiogram (ECG) is the most vital biosignal of the body. It contains a variety of important clinical pieces of information and it is the fastest approach to asses the health condition. However, ECG is highly susceptible to noise and low-frequency interference. The low-frequency interference in ECG appears in the form of baseline drift that...

This chapter analytically compares the efficiency of the recent plant biology-inspired genetic algorithm (PBGA) and the firefly algorithm (FA) optimizer. The comparison is over a range of well-known critical benchmark test functions. Through statistical comparisons over the benchmark functions, the efficiency of PBGA has been evaluated versus FA as...

This book addresses the frontier advances in the theory and application of nature-inspired optimization techniques, including solving the quadratic assignment problem, prediction in nature-inspired dynamic optimization, the lion algorithm and its applications, optimizing the operation scheduling of microgrids, PID controllers for two-legged robots,...

A very recent methodology of data sampling with a sub-Nyquist rate is compressive sensing (CS). CS theory is established based on the higher sparsity of the data containing information. It uses this fact for recovery of the data sampled with much fewer samples than required by the Nyquist sampling theorem. CS addresses two main questions: (i) how t...

Compressive sensing is a recent data sampling technique with a variety of advantages over the classical Shannon–Nyquist based technique. The main theoretical approach to compressive sensing is based on the informative value of data according to sparsity where the higher sparsity indicates the higher information content. Therefore, while data sample...

Compressive sensing is a recent highly applicative approach. It enables efficient data sampling at a much lower rate than the requirements indicated by the Nyquist theorem. Compressive sensing possesses several advantages, such as the much smaller need for sensory devices, much less memory storage, higher data transmission rate, many times less pow...

Compressive sensing is a quite recent signal/image acquisition achievement with the capability of sampling data via a much smaller number of sensory devices. It is even less than the theoretical requirement set by the Shannon–Nyquist sampling theorem. Compressive sensing foundations are established on the sparsity of the data with informative chara...

Agricultural Machinery as an off-road vehicle is the backbone of the World agricultural industry. Its main function is to operate as a prime mover and support the power requirements to function the various type of draft implements. In this regards, the hydraulic system is an important part and is controlled by the propagated oil which is cleaned by...

The wind power generation is a rapidly growing grid integrated renewable energy (RE)
technology with an installed capacity of 539.291 GW. The capability of the wind energy conversion system (WECS) to remain integrated into the utility network in the case of low voltage events is called low voltage ride-through (LVRT) capability. This manuscript off...

In this paper, we introduce the selection and mutation schemes to enhance the computational power of Genetic Algorithm (GA) for global optimization of multi-modal problems. Proposed operators make the GA an efficient optimizer in comparison of other variants of GA with improved precision, consistency and diversity. Due to the presented selection an...

In the context of efficient generation expansion planning (GEP) and transmission expansion planning (TEP), value assessment method (VAM) is the critical topic to discuss. Presently, two well-known VAMs, min-cut max-flow (MCMF) and load curtailment strategy (LCS), are used for GEP and TEP. MCMF does not follow electrical laws and is unable to calcul...

In this paper, a real-life application of bi-level evolutionary optimization is proposed to optimize the electricity industry infrastructure. It offers a coordinated generation and transmission expansion planning (CGTEP) from the perspective of Independent System Operator (ISO). The main objective of the proposed study is to show the effect of opti...

This paper presents a binary coded evolutionary computational method inspired from the evolution in plant genetics. It introduces the concept of artificial DNA which is an abstract idea inspired from inheritance of characteristics in plant genetics through transmitting dominant and recessive genes and Epimutaiton. It involves a rehabilitation proce...

Optimization theory emerges as an integral part of applied mathematics in order to address complex scientific and engineering problems. Optical optimization is formulated mathematically by considering the corresponding focal length of the lens/ mirror as the objective function subject to object distance and lateral magnification. The stability doma...

A Gross morphologic and biometric study was conducted on ovaries of a total 72 female chicks/ growers, 36 each of Kadaknath and White Leghorn (WLH) breeds. The birds were grouped according to age into 6 (I-VI) groups, viz., 1, 4, 8, 12, 16 and 20 weeks old. The gross observations revealed that the left ovary was elongated triangular with base direc...

The image perception by human brain through the eyes is not exactly what the eyes receive. In order to have an enhanced view of the received image and more clarity in detail, the brain naturally modifies the color tones in adjacent neighborhoods of colors. A very famous example of this human sight natural modification to the view is the famous Chev...

Morphological filters (MFs) are composed of two basic operators: dilation and erosion, inspired by natural geometrical dilation and erosion. MFs locally modify geometrical features of the signal/image using a probe resembling a segment of a function/image that is called structuring element. This chapter analytically explains MFs and their inspirati...

The Perceptual Adaptation of the Image (PAI) is introduced by inspiration from Chevreul-Mach Bands (CMB) visual phenomenon. By boosting the CMB assisting illusory effect on boundaries of the regions, PAI adapts the image to the perception of the human visual system (HVS) and thereof increases the quality of the image. PAI is proposed for applicatio...

In this paper, we introduce an optical objective function in order to obtain the optimized image of a dynamical object by an optical instrument having a variable zooming range. To be precise, about a given fixed point of the focal length of a single lens, mirror or an extended optical instrument, the local stability of the image thus formed is char...

A pseudo-spectrum analysis approach for tractor oil pump defect detection through sound records in a simple mobile application is presented. The sound of tractor engine is recorded in different conditions of oil pump is contamination to dust. By analyzing the sound tracks the dust pollution level is determined and chocking of oil pump is efficientl...

This paper aims at achieving global optimal
solution of complex problems, such as traveling salesman problem
(TSP), using extended version of real coded genetic algorithms
(RCGA). Since genetic algorithm (GA) consists of several genetic
operators, namely selection procedure, crossover, and mutation
operators, that offers the choice to be modifi...

Blind Components Processing (BCP), a novel
approach in processing of data (signal,image, etc.) components, is introduced as well some applications to information communications technology (ICT) are proposed. The
newly introduced BCP is with capability of deployment
orientation in a wider range of applications. The fundamental of BCP is based on Bli...

The study was conducted on 18 prepubertal goats divided into early prepubertal (1-3 months), mid prepubertal (3-6 months) and late prepubertal (6-9 months) stages. The tissue samples were collected from body of mammary gland fixed in 10 per cent neutral buffered formalin for histological and histochemical studies. In early prepubertal stage no dist...

This paper presents an integrated approach for composite transmission expansion planning incorporating: (i) computationally efficient linear matrices, (ii) a novel Demand/Energy Not Served (DNS/ENS) and Generation Not Served (GNS) calculation approach, to circumvent the time intensive iterative procedures. A self-tuning mechanism based on stochasti...

This paper presents an integrated approach for composite transmission expansion planning incorporating: (i) computationally efficient linear matrices, (ii) a novel Demand/Energy Not Served (DNS/ENS) and Generation Not Served (GNS) calculation approach, to circumvent the time intensive iterative procedures. A self-tuning mechanism based on stochasti...

This paper addresses the failure of capacitor cells
of high voltage (HV) shunt capacitor banks in Rajasthan Rajya
Vidhyut Prasaran Nigam Ltd. (RRVPNL) power grid, a
transmission network of Rajasthan state of India, due to pole
discrepancy among the three poles of circuit breaker (CB). The
high voltage peaks detected at the time of capacitor switchi...

In this chapter, we apply the methods of state-space geometry to the issue of complex power optimization in a non-steady state regime by incorporating the intrinsic state-space geometry. Considering the power flow between two arbitrary points along the chosen transmission line, we compute the stability domains for a large voltage instability proble...

In this chapter, we extend the techniques of intrinsic geometry and examine the problem of voltage stability in network theory. In order to carry out this investigation, we determine stability domains by first specifying the three-parameter model for the reformulation of the problem. We then consider single-component LCR networks, showing how volta...

In this chapter, we offer a concise account of network power flow and stability criteria arising from real intrinsic Riemannian geometry. We begin by considering a brief review of the flow equations and related concepts, for use in the later chapters.

In this chapter, we focus on the aforementioned techniques of network theory and real intrinsic geometry. In order to carry out this investigation, we first formulate the problem as in the previous chapter. We then describe the details of this innovation for two-parameter single-component networks and show in the sequel that the method works in gen...

In this chapter, we recall the mathematical preliminaries and the flow properties of power networks. The method used here is to eliminate the effect of voltage fluctuation about an equilibrium.

The present research concerns the problem of planning in the power industry.The issues of network reliability and bus voltage stability have been examined from the perspective of engineering applications to planning and operation using intrinsic geometric considerations. Specifically, we have considered an intrinsic geometric model for the limiting...

In this chapter, we describe the intrinsic geometric design of power flow and the parametric stability of power networks by focusing our attention on the admissible values of the parameters \(\{L, C, R\}\) for the real power flow, the imaginary power flow, and their arbitrary linear combinations as the unified description of the network power flow....

In the context of network planning, equipment and load dynamics are of course the driving force behind phase shift voltage instability. In this chapter, for the 2-bus systems in a connected power system, we show that the voltage of all relevant buses (i.e., both bus-1 and bus-2) varies in the same way as the transmitted power. In the sequel, we exa...

Rapid changes in the business environment during the last few decades have heavily affected the social and professional developments in the electricity sector thus the design of the electrical transmission systems become prominent [1] -[129], [136] – [161]. The effect of changing business scenarios of electricity industry has been briefly reviewed...

Transmission expansion planning (TEP) is of prime importance for reducing generation cost,
minimizing consumer cost and improving the quality of power supply. Indeed, previous TEP
procedures have multiple shortcomings: (i) capacity of new alternative transmission lines are
specified a priori, (ii) the followed procedure of reliability calculatio...

This paper presents the intrinsic geometric model for the solution of power system planning and its operation. This problem is large-scale and nonlinear, in general. Thus, we have developed the intrinsic geometric model for the network reliability and voltage stability, and examined it for the two and three parameter systems. The robustness of the...

In this chapter, we analyze the voltage instability pertaining to the maximum deliverable power for a given load. We thus illustrate the role of state-space geometry in complex power flow optimization. In the rapidly growing and competitive power market, optimization is crucial in order to define the loadability limit of the power network, where no...

This book is a short introduction to power system planning and operation using advanced geometrical methods. The approach is based on well-known insights and techniques developed in theoretical physics in the context of Riemannian manifolds.
The proof of principle and robustness of this approach is examined in the context of the IEEE 5 bus system...

This paper proposes a single-stage probabilistic transmission expansion planning (TEP) methodology where apriory specification of candidate transmission lines capacity is not required. The proposed methodology involves: (i) minimization of the sum of the investment, expected demand not served (EDNS), expected generation not served (EGNS) and expect...

This paper proposes a single-stage probabilistic transmission expansion planning (TEP) methodology where a priory specification of candidate transmission lines capacity is not required. The proposed methodology involves: (i) minimization of the sum of the investment, expected demand not served (EDNS), expected generation not served (EGNS) and expec...

A new probabilistic methodology for transmission expansion planning (TEP)
that does not require a priori specification of new/additional transmission
capacities and uses the concept of social welfare has been proposed. Two new
concepts have been introduced in this paper: (i) roulette wheel methodology has
been used to calculate the capacity of new...

Restructuring of the power market introduced demand uncertainty in
transmission expansion planning (TEP), which in turn also requires an accurate
estimation of demand not served (DNS). Unfortunately, the graph theory based
minimum-cut maximum-flow (MCMF) approach does not ensure that electrical laws
are followed. Nor can it be used for calculating...