Madan M Gupta

• B.E. (H), M.E., PhD. D. Sc.
• Chair at University of Saskatchewan

Biological cells and tissues have diversified behaviors, which are supported by active tissues and passive tissues. Inspired by this, an underactuated self-reconfigurable robot was designed with passive joints and active joints. The inclusion of passive joints can offer benefits not only on cost but also on functionality. This paper presents the ar...

Existing self-reconfigurable robots achieve connections and disconnections by a separate drive of the docking system. In this paper, we present a new docking system with which the connections and disconnections are driven by locomotion actuators, without the need for a separate drive, which reduces the weight and the complexity of the modules. This...

This paper reviews recent developments in the emerging field of resilient robots and the related robots that share common concerns with them, such as self-reconfigurable robots. This paper addresses the identity of the resilient robots by distinguishing the concept of resilience from other similar concepts and summarizes the strategies used by robo...

The development of an emotion-based (or affect-based) apparel design system has become an important issue nowadays due to the customer?s increased demand for apparel products not only in the aspect of function but also of aesthetics or affect/emotion. This paper presents a study on developing a mapping from affective words to design parameters. The...

Resilient robotic systems are a kind of robotic system that is able to recover their original function after partial damage of the system. This is achieved by making changes on the partially damaged robot. The general resilient robot, which makes sense by including active joints, passive joints, passive links, and passive adjustable links, was prop...

Human cognitive and perception processes have a great tolerance for imprecision or uncertainty. For this reason, the notions of perception and cognition have great importance in solving many decision making problems in engineering, medicine, science, and social science as there are innumerable uncertainties in real-world phenomena. These uncertaint...

Many qualitative group decisions in professional fields such as law, engineering, economics, psychology, and medicine that appear to be crisp and certain are in reality shrouded in fuzziness as a result of uncertain environments and the nature of human cognition within which the group decisions are made. In this paper, we introduce an innovative ap...

During a presidential forum in the 2008 U.S. presidential campaign, the moderator, Pastor Rick Warren, wanted Senator John McCain and then-Senator Barack Obama to define “rich” with a specific number. Warren wanted to know at what specific income level a person goes from being not rich to rich. The problem with this question is that there is no spe...

A resilient robotic system is capable of recovering the original function after some parts failed. This paper develops a general architecture of resilient robot in terms of physical components and their relationships. This architecture includes active joints and passive joints and adjustable links. The inclusion of passive joints and adjustable lin...

During a presidential forum in the 2008 U.S. presidential campaign, the moderator, Pastor Rick Warren, wanted Senator John McCain and then-Senator Barack Obama to define "rich" with a specific number. Warren wanted to know at what specific income level a person goes from being not rich to rich. The problem with this question is that there is no spe...

In clinical practice, making diagnostically crisp decisions is critical to successful treatment outcomes. However, there is no agreement on the operational methodology that is best suited to convert imprecise symptomatic information into crisp clinical treatment decision making. In this paper, a new computational decision making tool, Delphi-Neural...

Many qualitative group decisions in professional fields such as law, engineering, economics, psychology, and medicine that appear to be crisp and certain are in reality shrouded in fuzziness as a result of uncertain environments and the nature of human cognition within which the group decisions are made. In this paper we introduce an innovative app...

In this paper, we present an innovative approach for stability analysis of nonlinear discrete time-varying systems introducing a new notion of dynamic poles and Extended-Routh's stability approach. The stability analysis is carried out by introducing a new notion of dynamic characteristic equation for the nonlinear discrete time-varying system and...

The theory of fuzzy logic is based on the notion of relative graded membership, as inspired by the processes of human perception and cognition. Lotfi A. Zadeh published his first famous research paper on fuzzy sets in 1965. Fuzzy logic can deal with information arising from computational perception and cognition, that is, uncertain, imprecise, vagu...

In this paper, we proposed a new method to analyze the condition and region of stability of nonlinear time-varying systems by introducing the notions of dynamic poles and dynamic-Routh's stability method. The stability analysis is carried out in a special type of complex plane called g(t)-plane which is similar to the traditional s-plane where both...

Accurate and reliable production forecasting is certainly a significant step for the management and planning of the petroleum reservoirs. This paper presents a new neural approach called higher-order neural network (HONN) to forecast the oil production of a petroleum reservoir. In HONN, the neural input variables are correlated linearly as well as...

In this paper, we present a flocking control algorithm for a group of autonomous underwater vehicles (AUVs) using the leader-follower concept. Leader vehicle have global knowledge of desired trajectory and other AUVs are chosen as followers which are mounted with sensors to estimate the positions of neighbor AUVs. The follower vehicles have no know...

The theory of fuzzy logic is based on the notion of relative graded membership, as inspired by the processes of human perception and cognition. Lotfi A. Zadeh published his first famous research paper on fuzzy sets in 1965. Fuzzy logic can deal with information arising from computational perception and cognition, that is, uncertain, imprecise, vagu...

Neural network (NN) models have gained much attention for river flow forecasting because of their ability to map complex non-linearities. However, the selection of appropriate length of training datasets is crucial and the uncertainty in predictions of the trained NNs with new datasets is a crucial problem. In this study, self-organising maps (SOM)...

Dear Da: It was on Monday, August 1st, 2011, that I received from our friend Prof. Tianrui Li the following heart-breaking E-mail message: ‘Our best friend Prof. Da Ruan (Chair of FLINS and ISKE) suddenly passed away yesterday (Sunday, July, 31st, 2011)’ My young charming friend Da, first I did not believe it - how it can be possible with you becau...

Many qualitative group decisions in professional fields such as law, engineering, economics, psychology, and medicine that appear to be crisp and certain are in reality shrouded in fuzziness as a result of uncertain environments and the nature of human cognition within which the group decisions are made. In this paper we introduce an innovative app...

In this chapter, the authors provide fundamental principles of Higher Order Neural Units (HONUs) and Higher Order Neural Networks (HONNs) for modeling and simulation. An essential core of HONNs can be found in higher order weighted combinations or correlations between the input variables and HONU. Except for the high quality of nonlinear approximat...

This paper describes a novel microfluidic method to prepare monodispersed water-in-oil (W/O) microspheres utilizing a piezoelectric actuator. In the main channel, a dispersed phase stream becomes focused and stabilized. In the side channels, oscillating streams are generated by the piezoelectric actuator and flow to the main channel to pinch off th...

Many qualitative decisions that appear crisp and certain are grounded in fuzziness as a result of the uncertain environment within which the decisions are made. We propose an innovative approach for decision making in such uncertain conditions by using a fuzzy-neural method. The key idea of this proposed approach is to adapt the synaptic neural wei...

This work describes a novel microfluidic method to generate uniform water-in-oil (W/O) microspheres using the phase separation technique. Axiomatic design theory (ADT) was employed for the conceptual design of microchannel systems, and ADT verified that the proposed microfluidic system is a decoupled design. The integration of hydrodynamic flow foc...

In this paper, we propose a novel neural modeling methodology for forecasting daily river discharge that makes use of neural units with higher-order synaptic operations (NU-HSOs). For hydrologic forecasting, conventional rainfall-runoff models based on mechanistic approaches in the literature have shown limitations attributable to their overparamet...

This paper proposes a design methodology for the conceptual design of microchannel systems by applying axiomatic design theory (ADT). The microchannel system concerned in this paper is for the purpose of preparing uniform microspheres based on the phase separation principle and technique. There are two general design goals for this system: controll...

This paper proposes a design methodology for conceptual design of microchannel systems by applying axiomatic design theory (ADT). The microchannel system concerned, as an example, in this paper is for the purpose of preparing uniform microspheres based on the phase separation principle. There are two general design goals for this system: controllab...

In this paper, we provide a new perspective on the issues of mentation and cognition and its mathematical formulation using fuzzy logic approach.

Forums on the Web are increasingly spammed by miscreants in order to attract visitors to their (often malicious) websites. In this paper, we study the prevalence of forum spamming and find that Internet users are at a high risk of encountering forums with spam links posted on them. To mitigate the problem, we examine the characteristics of 286 days...

This book introduces neural networks (NN) as a novel approach towards aiding biocomposite materials analysis and processing. At its core, the book acts as a primer on the use of NN as a tool for advancing the field of biocomposites. Biocomposites and neural networks may seem unrelated areas in two completely separate fields of science and engineeri...

Design of an adaptive controller for complex dynamic systems is a big challenge faced by the researchers. In this paper, we introduce a novel concept of dynamic pole motion (DPM) for the design of an error-based adaptive controller (E-BAC). The purpose of this novel design approach is to make the system response reasonably fast with no overshoot, w...

Design of an adaptive controller for complex dynamic systems is a big challenge faced by the researchers. In this paper, we introduce a novel concept of dynamic pole motion (DPM) for the design of an error-based adaptive controller (E-BAC). The purpose of this novel design approach is to make the system response reasonably fast with no overshoot, w...

We the Guest Editors would like to express their sincere appreciation to the Editorial Board of the Journal of Robotics for their confidence and unwavering support for this special issue on “Cognitive and Neural Aspects in Robotics with Applications.” We acknowledge the efforts of the authors for their valuable research contributions to this specia...

Human cognitive and perception processes have a great tolerance for imprecision or uncertainty. For this reason, the notions of perception and cognition have great importance in solving many decision making problems in engineering, medicine, science, and social science as there are innumerable uncertainties in real-world phenomena. These uncertaint...

This paper presents a motion control strategy for a rigid and constraint consistent formation that can be modeled by a directed graph whose each vertex represents individual agent kinematics and each of directed edges represents distance constraints maintained by an agent, called follower, to its neighbouring agent. A rigid and constraint consisten...

In this chapter, we provide fundamental principles of higher order neural units (HONUs) and higher order neural networks (HONNs). An essential core of HONNs can be found in higher order weighted combinations or correlations between the input variables. By using some typical examples, this chapter describes how and why higher order combinations or c...

Design of an adaptive controller for complex dynamic systems is a big challenge faced by the researchers. In this paper, we propose a novel method for the design of an error- based robust adaptive controller to make the system response reasonably fast with no overshoot. Here the control action is designed by introducing the notion of `error-based a...

The non performance of a microwave communication link located over Kolkata due to heavy rain in the monsoon months of 2006 has been investigated by monitoring the amplitude variation of signal on twenty hour basis. It has been seen that the link did not serve any purpose for 4% during the monsoon period of 2006 while the signal level was less than...

This paper presents a new method to generate uniform microspheres with biodegradable poly(lactic-co-glycolic acid) (PLGA) material using microelectromechanical system technology. The general idea with this method is such that a liquid phase containing the dissolved microsphere matrix material reaches a continuous phase after a silicon membrane with...

The DNS is a cornerstone of the Internet. Unfortunately, no matter how securely an organization provisions and guards its own DNS infrastructure, it is at the mercy of others' provisioning when it comes to resolutions its resolvers perform on behalf of its clients - even one compromised DNS server in the Internet can mislead an organization's clien...

Design of neuro-controller for complex dynamic systems is a big challenge faced by the researchers. In this paper we present a design of a robust neuro-controller for a dynamic system to make the system response fast with no overshoot. Here the control action decided by the controller completely depends on the value of the error at that point of ti...

The Asprox infection weaves a complex chain of dependencies involving bots that perform SQL injections on vulnerable web servers, and visitors whose machines get compromised simply by visiting infected websites. Using real-world data sets, we study Asprox bots, infected web servers, and the malicious infrastructure behind Asprox propagation. We fin...

A recurrent neural network is proposed to deal with the convex optimization problem. By employing a specific nonlinear unit, the proposed neural network is proved to be convergent to the optimal solution in finite time, which increases the computation efficiency dramatically. Compared with most of existing stability conditions, i.e., asymptotical s...

An innovative uniform microsphere formation based on MEMS was developed by numerical simulation as a preliminary study. This simulation study proposes a new technology to cut off a hydrodynamically focused liquid filament into micro-sized spheres applying a novel combination of hydrodynamic flow focusing and an oscillating external flux. A disperse...

PDAs and smart phones are increasingly being used as handheld computers. Today, their network connectivity and their usages for various tasks over the Internet require privacy and authenticity. In this paper, we conduct a comprehensive and comparative study of the performance of the SSL protocol for PDA and laptop clients, both in WEP secured and o...

Several gradient-based approaches such as back-propagation, conjugate gradient and Levenberg Marquardt (LM) methods have been developed for training the neural network (NN) based systems. Still, in some situations, like multimodal cost function, these procedures may lead to some local minima, therefore, the evolutionary algorithms (EAs) based proce...

During a presidential forum in the 2008 U.S. presidential campaign, the moderator, Pastor Rick Warren, wanted Senator John McCain and then-Senator Barack Obama to define "rich" with a specific number. Warren wanted to know at what specific income level a person goes from being not rich to rich. The problem with this question is that there is no spe...

The computational neural-network structures described in the literature are often based on the concept of linear synaptic operations. In biological processes, however, neurons form a set of very complex computing elements and perform much more complex computations than just the linear aggregation. It is well known that the computational efficiency...

The computational neural-network structures described in the literature are often based on the concept of linear synaptic operations. In biological process, however, neurons form a set of very complex computing elements and perform much more complex computations than just the linear aggregation. It is well known that the computational efficiency of...

This article introduces basic types of nonconventional neural units and focuses on their notation and classification. Namely, the notation and classification of higher order nonlinear neural units, time-delay dynamic neural units, and time-delay higher order nonlinear neural units are introduced. Brief introduction into the simplified parallels of...

A mechanical amplifier is an important device, which together with a piezoelectric actuator can achieve motion with high reso-lution and long range. In this paper, a new topology based on a symmetric five-bar structure for displacement amplification is pro-posed, and a compliant mechanism is implemented for the ampli-fier. In short, the new mechani...

K-Edge Subtraction (KES) utilizes the discontinuity in the X-ray absorption across the absorption edge of the selected contrast element and creates an image of the projected density of the contrast element from two images acquired just above and below the K-edge of the contrast element. KES has proved to be powerful in coronary angiography, micro-a...

In this chapter, we aim to describe fundamental principles of artificial higher order neural units (AHO-NUs) and networks (AHONNs). An essential core of AHONNs can be found in higher order weighted combinations or correlations between the input variables. By using some typical examples, this chapter describes how and why higher order combinations o...

In this paper, we propose a new computer aided diagnosis method of pulmonary nodules in X-ray CT images to reduce false positive (FP) rate under high true positive (TP) rate conditions. An essential core of the method is to extract and combine two novel and effective features from the raw CT images: One is orientation features of nodules in a regio...

Thermodynamic, optical texture and frequency dependent dielectric studies of re-synthesized discotic compounds Rufigallol hexa-n-alkoxylates (for n = 6, 7, 8, 9) having wide temperature range hexagonal columnar (colh) mesophase have been carried out. The mesophase and their transition temperatures have been determined by using polarizing microscope...

Temperature-dependent dielectric spectroscopy of resynthesized discotic compounds, rufigallol hexa-n-alkoxylates for n = 6, 7, 8, 9 having wide temperature range (>70°C) hexagonal columnar mesophase has been carried out in the frequency range of 10 Hz to 10 MHz. The mesophase and their transition temperatures have been determined by using polarizin...

K-Edge Subtraction (KES) utilizes the discontinuity in the X-ray absorption across the absorption edge of the selected contrast element and creates an image of the projected density of the contrast element from two images acquired just above and below the K-edge of the contrast element. KES has proved to be powerful in coronary angiography, micro-a...

Saskatoon berry (Amelanchier alnifolia) is a high moisture content fruit crop, harvested at 75-80% moisture content (w.b.) and needs to be dried to lower moisture contents for safe, extended shelf life and for further usage in food applications. Saskatoon berries were dried from an initial moisture content of 75.5% to around 25% (w.b.) using microw...

In this chapter, we aim to describe fundamental principles of artificial higher order neural units (AHONUs) and networks (AHONNs). An essential core of AHONNs can be found in higher order weighted combinations or correlations between the input variables. By using some typical examples, this chapter describes how and why higher order combinations or...

We have developed a new self-organizing network model of concept formation by using neurons with dynamic and spatial changing weights. The proposed network can recognize concepts using incomplete information of concepts at current degree of understanding and develop its synaptic connections of inner informational structure to discover new informati...

The development of an automated bio-micromanipulation system provides high manipulation rates with optimal reproducibility and makes quantitative bio-micromanipulation possible. Visual-servo control is necessary for realizing automated bio-micromanipulation and increasing accuracy of micromanipulator. We have developed a dual-hand bio-micromanipula...

Humans often mimic nature in the development of new machines or systems. The human brain, particularly its faculty for perception and cognition, is the most intriguing model for developing intelligent systems. Human cognitive processes have a great tolerance for imprecision or uncertainty. This is of great value in solving many engineering problems...

The paper introduces basic types of nonconventional artificial neural units and focuses their notation and classification: namely; the notation and classification of dynamic higher-order nonlinear neural units, time-delay dynamic neural units, and time-delay higher-order nonlinear neural units is introduced. Brief introduction into the simplified p...

The Canadian Oil sands industry in Northern Alberta has been operating ultra size haulers to optimize the mining process. The ground on which these heavy haulers run can behave as hard as competent sandstone in winters and as soft as weak clay in summers. This changing behaviour of the ground conditions has large impacts on not only the structural...

Universal approximation capabilities of neural networks and fuzzy basis functions are given in this chapter using the Stone-Weierstrass theorem, Kolmogorov’s theorem and functional analysis methods. This study focuses on few commonly-used neural networks such as multilayered feedforward neural networks (MFNNs) with sigmoidal activation functions, t...

This paper presents an adaptive design approach for controlling a class of unknown nonlinear multivariable plants operating in an uncertain environment. The approach uses a “two-level” control technique, with a feedforward controller on its first-level, and a conditional feedback controller on its second-level. The procedure employs a Liapunov type...

A recurrent neural network for the optimal control of a group of interconnected dynamic systems is presented in this paper. On the basis of decomposition and coordination strategy for interconnected dynamic systems, the proposed neural network has a two-level hierarchical structure: several local optimization subnetworks at the lower level and one...

A recurrent neural network for the optimal control of a group of interconnected dynamic systems is presented in this paper. On the basis of decomposition and coordination strategy for interconnected dynamic systems, the proposed neural network has a two-level hierarchical structure: several local optimization subnetworks at the lower level and one...

In the experimental setup for Diffraction Enhanced Imaging (DEI) and its extension, Multiple-Image Radiography (MIR), it is essential to have the two or three crystals angularly aligned relative to one another around two orthogonal axes; the angle around an axis perpendicular to the diffraction plane (the Bragg angle) and also around a perpendicula...

Without Abstract

Neural units with higher-order synaptic operations have good computational properties in information processing and control applications. This paper presents neural units with higher-order synaptic operations for visual image processing applications. We use the neural units with higher-order synaptic operations for edge detection and employ the Hou...

In this paper, a PD-type on-line learning control (OLC) is proposed for the tracking problem in a class of nonlinear time-varying systems with state uncertainties and measurement disturbances. In this proposed OLC algorithm, we use a combination of PD feedback control and feedforward control that is based on the previous control input profiles in a...

In the autonomous mobile robot industry, the landmark‐based navigation method has been widely used in which landmark recognition plays an important role. The landmark recognition using visual sensors relies heavily on the quality of image segmentation. To localise and navigate the robot using vision information, the camera has to be first calibrate...

The Web has evolved much from when Arlitt and Williamson proposed the ten Web workload invariants more than a decade ago. Many diverse communities now depend on the Web in their day-to-day lives. A current knowledge of the invariants for the Web is useful for performance enhancement and for synthetic Web workload generation. Invariants can also ser...

This paper presents a novel approach to mobile robot environment modeling based on principal component analysis of ultrasonic sensors array data. A principal components space, which has the less dimensionality than the raw data space, is constructed from the principal components of a large number of ultrasonic sensors data sets. Subsequent ultrason...

The paper introduces the concept of continuous-time dynamic neural units with adaptable input and state variable time delays (TmDNU - Time Delay Neural Units). Two types of TmDNUs are proposed as they introduce adaptable time delays either into the neural inputs or both the neural inputs and the neural unit state variable. Robust capabilities of Tm...

In this paper, a new type of six-degrees of freedom (DOF) flexible parallel mechanism (FPM) is presented. This type of parallel mechanism possesses several favorable properties: (1) its number of DOFs is independent of the number of serial chains which make up the mechanism; (2) it has no kinematical singularities; (3) it is designed to move on rai...

In this paper, a new adaptive switching learning control approach, called adaptive switching learning PD control (ASL-PD), is proposed for trajectory tracking of robot manipulators in an iterative operation mode. The ASL-PD control method is a combination of the feedback PD control law with a gain switching technique and the feedforward learning co...

In this paper, we analyze neural spike dynamics of a double feedback neural unit (DFNU). An essential emphasis of the analysis is on use of the DFNU's simple formulations that can provide quantitative analytic results. Comparing dynamics of Hodgkin-Huxley model to that of the DFNU, it is shown that dynamics of the DFNU is also physiologically plaus...

Internet protocol security (IPSec) is a widely deployed mechanism for implementing virtual private networks (VPNs). This paper evaluates the performance overheads associated with IPSec. We use Openswan, an open source implementation of IPSec, and measure the running times of individual security operations and also the speedup gained by replacing va...

The computational neural-network structures described in the literature are often based on the notion of linear neural units (LNUs). The biological neurons consist of complex computing elements, which perform more computations than just linear summation. The computational efficiency of the neural networks depends on their structure and the training...

Attenuation due to clouds in millimeter wave and microwave frequency bands lead to degradation in the performance of radio communication, especially for low noise systems. Frequent presence of cloud causes some amount of link degradation for significant percentage of time over the tropical Indian subcontinent. The cloud morphology particularly in r...

Discrete-Time Two-State Systems Asynchronous Operating Hopfield Neural Network An Alternative Version of the Asynchronous Binary Neural Network Neural Network in Synchronous Mode of Operation Block Sequential Operation of the Hopfield Neural Network Concluding Remarks Problems

General Class of Discrete-Time Dynamic Neural Networks (DT-DNNs) Lyapunov Stability of Discrete-Time Nonlinear Systems Stability Conditions for Discrete-Time DNNs More General Results on Globally Asymptotic Stability Concluding Remarks Problems

Models of Dynamic Neural Units (DNUs) Models and Circuits of Isolated DNUs Neuron with Excitatory and Inhibitory Dynamics Neuron with Multiple Nonlinear Feedback Dynamic Temporal Behavior of DNN Nonlinear Analysis for DNUs Concluding Remarks Problems

Dynamic Neural Network Structures: An Introduction Hopfield Dynamic Neural Network (DNN) and Its Implementation Hopfield Dynamic Neural Network (DNNs) as Gradient-like Systems Modifications of Hopfield Dynamic Neural Networks Other DNN Models Conditions for Equilibrium Points in DNN Concluding Remarks Problems

Hebb's Neural Learning Mechanisms Information Retrieval Process Nonorthogonal Fundamental Memories Other Learning Algorithms for Associative Memory Information Capacity of Binary Hopfield Neural Network Concluding Remarks Problems

Local Asymptotic Stability Global Asymptotic Stability of Dynamic Neural Network Local Exponential Stability of DNNs Global Exponential Stability of DNNs Concluding Remarks Problems