Naveed Sheikh

Asian Institute of Technology (AIT), Mechatronics, Post-Doc

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Dr. Naveed Sheikh received his Ph.D. in Mechatronics Engineering from the Asian Institute of Technology in 2015. After completion of his degree I appointed as a Faculty Fellow in the Department of Applied Mathematics and Computational Sciences at the University of Balochistan, Quetta. Dr. Naveed serving as the visiting faculty of Computer sciences at UoB from 2005. My interests are focused on the Nano technology, Robotics, Artificial intelligence. In particular my laboratory is currently working on understanding the structure and dynamics of Quadcopter.

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Papers by Naveed Sheikh

A Hybrid Approach for Accurate Forecasting of Exchange Rate Prices Using Vmd-Ceemdan-Gru-Atcn Model

Sains Malaysiana, Nov 29, 2023

The foreign exchange (Forex) market has greatly influenced the global financial market. While For... more The foreign exchange (Forex) market has greatly influenced the global financial market. While Forex trading offers investors substantial yield prospects, some risks are also involved. It is challenging to accurately model financial time series due to their nonlinear, non-stationary and noisy properties with an uncertain and hidden relationship. Thus, developing extremely precise forecasting techniques is crucial for investors and decision-makers. This study introduces a novel hybrid forecasting model, VMD-CEEMDAN-GRU-ATCN, designed to improve Forex price prediction accuracy. To begin with, our proposed model utilizes the variational model decomposition (VMD) technique for breaking down raw prices into multiple sub-components and residual terms. The complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) technique is utilized to extract features from the residual terms, which involves further decomposition and analysis of these complex information-containing terms. These sub-components are then predicted by the gated recurrent unit (GRU) model. To enhance the effectiveness of our hybrid model, we include the open, high, low, and close prices and seven Forex market technical indicators. Finally, an attention-based temporal convolutional network (ATCN) model is used to obtain the Forex price forecasts. For both one-step and multi-step ahead forecasting, our proposed VMD-CEEMDAN-GRU-ATCN model has demonstrated superior and consistent performance in predicting USD/PKR exchange rate price series.

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Real-Time Object Identification Through Convolution Neural Network Based on YOLO Algorithm

Annular Axisymmetric Stagnation Flow of a Casson Fluid Through Porous Media in a Moving Cylinder

American Journal of Modern Physics, Dec 13, 2023

Numerical Study of the Boundary Layer Flow Problem over a Flat Plate by Finite Difference Method

Solar drying experimental research and mathematical modelling of wild mint and peach moisture content

Journal of Asian Scientific Research

This research may be seen in the solar drying of several mature plants. Fruits and vegetables suc... more This research may be seen in the solar drying of several mature plants. Fruits and vegetables such as peaches and wild mint are grown in a semi-arid region near Quetta, Pakistan. Our research is confined to determining the volume of moisture removed from the distinct items and employing forced convection using three distinct mass flow rates to regulate the pace of the solar dryer, which enables us to further our study and improve the influence of mass flow rate on the quantity of water extracted from the item. A series of mathematical models for different scientists, based on the mathematical connection used, and by determining the constants for each model, which implies that each mass flow correlates to the constants of the five models, and thus the product ultimately influences them in terms of type, shape, and mass. The findings were upgraded, and analyzed the mathematical models of the scientists with our approach, which was likewise quite accurate. We infer that the mass flow r...

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Flow of a Williamson Fluid over a Stretching Sheet Containing Nanoparticles

International journal of systems engineering, 2021

In this article, an attempt has been made to study the behavior of non-Newtonian viscoelastic mod... more In this article, an attempt has been made to study the behavior of non-Newtonian viscoelastic model of a Williamson fluid flow problem containing nanoparticles and is assumed to be flowing over a stretching sheet stretched along its surface in both directions with the same constant surface stretching velocity. The boundary layer governing equations of the conservation of mass, conservation of linear momentum and the energy are first modeled into a set of nonlinear coupled partial differential equations along with the appropriate boundary conditions. A numerical study of impact of nanofluid flow over a stretching sheet is tabulated. The basic equations of Williamson fluid are modeled with the help of Navier-Stokes equations for momentum and heat transfer. With the assistance of appropriate similarity transformations these pair of PEDs is transformed into up-to-date system of coupled nonlinear ODEs. These transformed systems of equations are evaluated numerically with the assistance of shooting method using forth order. The dominant physical properties for system of equations of the model that is wall shear stress, and the coefficient of skin friction are acquired. The behavior of nondimensional velocity and thermal flow profiles are discussed for the important involved dimensionless parameters like the Williamson fluid parameter and the nanoparticles volume fraction through tables and graphs.

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Extended Forgery Detection Framework for COVID-19 Medical Data Using Convolutional Neural Network

Computers, Materials & Continua, 2021

Medical data tampering has become one of the main challenges in the field of secure-aware medical... more Medical data tampering has become one of the main challenges in the field of secure-aware medical data processing. Forgery of normal patients' medical data to present them as COVID-19 patients is an illegitimate action that has been carried out in different ways recently. Therefore, the integrity of these data can be questionable. Forgery detection is a method of detecting an anomaly in manipulated forged data. An appropriate number of features are needed to identify an anomaly as either forged or non-forged data in order to find distortion or tampering in the original data. Convolutional neural networks (CNNs) have contributed a major breakthrough in this type of detection. There has been much interest from both the clinicians and the AI community in the possibility of widespread usage of artificial neural networks for quick diagnosis using medical data for early COVID-19 patient screening. The purpose of this paper is to detect forgery in COVID-19 medical data by using CNN in the error level analysis (ELA) by verifying the noise pattern in the data. The proposed improved ELA method is evaluated using a type of data splicing forgery and sigmoid and ReLU phenomenon schemes. The proposed method is verified by manipulating COVID-19 data using different types of forgeries and then applying the proposed CNN model to the data to detect the data tampering. The results show that the accuracy of the proposed CNN model on the test COVID-19 data is approximately 92%.

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Mathematical modelling of COVID-19 pandemic in Pakistan with optimal control

Journal of Asian Scientific Research

We propose an innovative mathematical modeling to examine the previous coronavirus disease of 201... more We propose an innovative mathematical modeling to examine the previous coronavirus disease of 2019 pandemic or (COVID-19). This analysis has been performed qualitatively through differential equation stability theory, as well as the basic reproductive value, which indicates a pandemic index, then calculated from the maximum eigenvalue of the subsequent matrix. We establish the global asymptotic stability criteria for such disease-free state. The actual COVID-19 occurrence documents and data from 01 July, 2021 to 14 August, 2022 in Pakistan are analyzed for estimation methods, leading in fitted values for biological parameters. Sensitivity analyzation is used to identify the much more relevant attributes in the developed framework. This scientific research revealed a deterministic computational formula that assesses the impact of various mitigation measures on the propagation of COVID-19 in a worldwide population. The analysis will concentrate on Pakistan, and relevant data gathered ...

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Blood Pressure Estimation Using Artificial Neural Network and Multitaper Model

LINGUISTICA ANTVERPIENSIA, May 15, 2021

Performance Analysis of Commercially Available Piezoelectric Based Energy Harvester

Abstract- In this paper we focused on the performance and analysis of commercially available piez... more Abstract- In this paper we focused on the performance and analysis of commercially available piezo generator, which converts mechanical vibration to electrical power. The relationship between the dynamic response of piezo generator and its power output is realized. The efficient energy transfer of mechanical structure and high electromechanical transformation of piezoelectric material make the piezoelectric generator a extraordinary performance. The piezoelectric generator produces maximum output voltage of 4.3 V which is 0.012 µW per centimeter square. Index Terms: MEMS, Energy harvester, Piezo generator. I.

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Heat Transfer Analysis over the Boundary Layer Stagnation-Point Flow of Couple Stress Fluid over an Exponentially Stretching Sheet

American Journal of Applied Mathematics

Deep transferable learning on heartbeat classification for imbalance dataset

Journal of Intelligent & Fuzzy Systems, 2022

Electrocardiogram (ECG) data recorded by medical devices are hard to analyze manually. Therefore,... more Electrocardiogram (ECG) data recorded by medical devices are hard to analyze manually. Therefore, it is important to analyze and categorize each heartbeat using machine learning. Recently, advancements in machine learning have made classification of complex data easy and fast. However, these machine learning algorithms require sufficient amount of training data and have limited performance in case the data is imbalance. In case of MIT-BIH arrhythmia dataset, the distribution of training instances are quite imbalance. Many machine learning, particularly deep learning, algorithms give high accuracy on these datasets but still the minority classes have zero accuracy. In this paper, we improve the accuracy of minority classes without hurting the overall accuracy of other classes using transfer learning. The accuracy of existing deep learning model is increased from 90.67% to 98.47%, respectively.

Topological Structure of Fuzzy PU-new Ideal in PU-algebra

International Journal of Systems Science and Applied Mathematics

Forecasting Fertility and Child Mortality Rates of Pakistan Using Time Series Model

LINGUISTICA ANTVERPIENSIA, Jun 2, 2021

Simulation of Piezoelectric Actuator and Investigation of Flow Rate using PZT Infusion Pump for Wearable Artificial Kidney

Energy Procedia, 2011

Some Results of Self-Maps in PU-Algebra

Punjab University Journal of Mathematics, 2021

In this manuscript we examine the concept of left and right self-maps in PU-Algebra and explore s... more In this manuscript we examine the concept of left and right self-maps in PU-Algebra and explore some further interesting prperties to PU-Algebra.We prove that R 2 x is idempotent, isotonic and endomorphic. We determine the condition for which the composition of L α and R b is equivalent to R o. We prove that under what condition L n x is an endomorphism. We define the Ker(R 2 x) and show that it is a subalgebra and ideal of PU-Algebra. We also prove that the Fix(R 2 x) is a subalgebra and ideal of PU-Algebra.

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Bombesin as intraluminal releaser of gastrin and PP in the pig

by E. Lezoche and Naveed Sheikh

Regulatory Peptides, 1983

Second Language Readers Capitalize on Some but Not All Sources of Emotional and Sensorimotor Information During Natural Sentence Reading

PsycEXTRA Dataset

In the Moment" Links Between Bilingualism and Executive Control and Their Relation to Enduring Changes in Cognition

PsycEXTRA Dataset

The embodiment of emotional words in a second language: An eye-movement study

Cognition and Emotion, 2015

The hypothesis that word representations are emotionally impoverished in a second language (L2) h... more The hypothesis that word representations are emotionally impoverished in a second language (L2) has variable support. However, this hypothesis has only been tested using tasks that present words in isolation or that require laboratory-specific decisions. Here, we recorded eye movements for 34 bilinguals who read sentences in their L2 with no goal other than comprehension, and compared them to 43 first language readers taken from our prior study. Positive words were read more quickly than neutral words in the L2 across first-pass reading time measures. However, this emotional advantage was absent for negative words for the earliest measures. Moreover, negative words but not positive words were influenced by concreteness, frequency and L2 proficiency in a manner similar to neutral words. Taken together, the findings suggest that only negative words are at risk of emotional disembodiment during L2 reading, perhaps because a positivity bias in L2 experiences ensures that positive words are emotionally grounded.

A Hybrid Approach for Accurate Forecasting of Exchange Rate Prices Using Vmd-Ceemdan-Gru-Atcn Model

Sains Malaysiana, Nov 29, 2023

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Real-Time Object Identification Through Convolution Neural Network Based on YOLO Algorithm

Annular Axisymmetric Stagnation Flow of a Casson Fluid Through Porous Media in a Moving Cylinder

American Journal of Modern Physics, Dec 13, 2023

Numerical Study of the Boundary Layer Flow Problem over a Flat Plate by Finite Difference Method

Solar drying experimental research and mathematical modelling of wild mint and peach moisture content

Journal of Asian Scientific Research

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Flow of a Williamson Fluid over a Stretching Sheet Containing Nanoparticles

International journal of systems engineering, 2021

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Extended Forgery Detection Framework for COVID-19 Medical Data Using Convolutional Neural Network

Computers, Materials & Continua, 2021

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Mathematical modelling of COVID-19 pandemic in Pakistan with optimal control

Journal of Asian Scientific Research

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Blood Pressure Estimation Using Artificial Neural Network and Multitaper Model

LINGUISTICA ANTVERPIENSIA, May 15, 2021

Performance Analysis of Commercially Available Piezoelectric Based Energy Harvester

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Heat Transfer Analysis over the Boundary Layer Stagnation-Point Flow of Couple Stress Fluid over an Exponentially Stretching Sheet

American Journal of Applied Mathematics

Deep transferable learning on heartbeat classification for imbalance dataset

Journal of Intelligent & Fuzzy Systems, 2022

Topological Structure of Fuzzy PU-new Ideal in PU-algebra

International Journal of Systems Science and Applied Mathematics

Forecasting Fertility and Child Mortality Rates of Pakistan Using Time Series Model

LINGUISTICA ANTVERPIENSIA, Jun 2, 2021

Simulation of Piezoelectric Actuator and Investigation of Flow Rate using PZT Infusion Pump for Wearable Artificial Kidney

Energy Procedia, 2011

Some Results of Self-Maps in PU-Algebra

Punjab University Journal of Mathematics, 2021

Download

Bombesin as intraluminal releaser of gastrin and PP in the pig

by E. Lezoche and Naveed Sheikh

Regulatory Peptides, 1983

Second Language Readers Capitalize on Some but Not All Sources of Emotional and Sensorimotor Information During Natural Sentence Reading

PsycEXTRA Dataset

In the Moment" Links Between Bilingualism and Executive Control and Their Relation to Enduring Changes in Cognition

PsycEXTRA Dataset

The embodiment of emotional words in a second language: An eye-movement study

Cognition and Emotion, 2015

Naveed Sheikh

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