About
110
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Introduction
Currently, working as Dean Research, Dean Faculty of Science at Adani University, In past worked in China, Poland, North Macedonia, South Korea and Japan. Research interests in Nano-material Toxicity Modeling, Chemical Sensors, Chemoinformatics, Sensor Array Signal Processing, and Human Body Odor Data Mining.
Additional affiliations
Education
July 2007 - June 2012
July 2006 - June 2007
Udai Pratap Autonomous College, Varanasi, India/VBS Purvanchal University, Jaunpur, India
Field of study
- Education
July 2003 - June 2005
Udai Pratap Autonomous College, Varanasi, India/ VBS Purvanchal University, Jaunpur, India
Field of study
- Physics (Electronics)
Publications
Publications (110)
Secure computational geometry (SCG) is an important type of secure multi-party computation (SMC) problem, which studies how to calculate the relationship of several geometric objects securely. Quantum SCG (QSCG) can achieve higher security than classical SCG protocols, but the achievements of QSCG are still limited at present. In this paper, we def...
The existing soil moisture sensing mechanism of the heat pulse probe (HPP) assumes the ideal condition of the soil while overlooking the physics of the device and the composition of the soil and its properties. In the present study, we propose modifications to the soil moisture sensing model of HPP by considering its physical parameters and their a...
The image emotion classification task aims to use the model to automatically predict the emotional response of people when they see the image. Studies have shown that certain local regions are more likely to inspire an emotional response than the whole image. However, existing methods perform poorly in predicting the details of emotional regions an...
Wind data play a crucial role in the advanced planning, design, and maintenance of wind farms, scheduling, energy production, and accurate distribution. Most of the measured wind dataset comprises missing observations due to several reasons, including the failure of measuring devices, human mistakes, environmental impact, and natural calamities. Co...
The rapid development of the generative adversarial networks (GANs) has made it an unprecedented success in image generation. The emergence of BigGAN, StyleGAN, and other advanced GAN makes the generated images more real and deceptive, which poses potential threats to national security, social stability, and personal privacy. In this paper, we prop...
Breast cancer is one of the most common types of cancer around the world. The early‐stage recognition of breast cancer is favourable for the diagnosis and treatment of the affecting patient. Data mining approaches can ease the diagnosis of breast cancer by analysis of the associated dataset for real‐time decision‐making. The present study proposes...
Chlorpyrifos is a widely used organochlorine pesticide. The unsystematic use of pesticides for the restrain of soil-borne pests and bacterium causes pollution of ecosystems and harming the health of animals and humans. Moreover, due to high persistence, mobility, and higher toxicity in soil environments, it causes severe destruction of species. The...
It is about inventing new technique for automatic identification of COVID 19 through use of Deep Convolutional Neural Network.
The leakage of medical audio data in telemedicine seriously violates the privacy of patients. In order to avoid the leakage of patient information in telemedicine, a two-stage reversible robust audio watermarking algorithm is proposed to protect medical audio data. The scheme decomposes the medical audio into two independent embedding domains, embe...
The key to preventing the COVID-19 is to diagnose patients quickly and accurately. Studies have shown that using Convolutional Neural Networks (CNN) to analyze chest Computed Tomography (CT) images is helpful for timely COVID-19 diagnosis. However, personal privacy issues, public chest CT data sets are relatively few, which has limited CNN's applic...
The motivation of the present study is to evolve virtual creatures in a diverse simulated 3D environment. The proposed scheme is based on the artificial evolution using the Neuro Evolution of Augmenting Topologies (NEAT) algorithm to educe a neural network that controls the muscle forces of the artificial creatures. The morphologies of the creature...
Due to the popularity of JPEG format images in recent years, JPEG images will inevitably involve image editing operation. Thus, some tramped images will leave tracks of Non-aligned double JPEG ( NA-DJPEG ) compression. By detecting the presence of NA-DJPEG compression, one can verify whether a given JPEG image has been tampered with. However, only...
Chlorpyrifos has a substantial risk to human health besides biodiversity. In the present study, a previously isolated bacterial strain Enterobacter sp. SWLC2 has been used to investigate its biodegradation potential in different soil-slurries systems and to optimize culture conditions to achieve enhanced biodegradation of chlorpyrifos. The optimiza...
The study aims identification of discriminating chemical constituents in the banana odor grown in Philippines and Ecuador using GC-MS characterization. Ester is recognized as a major chemical class in selected banana odor. Odors discriminating compounds like, 2-hexenal, ethyl acetate, and hexanoic acid, ethyl ester, etc. have been identified. Besid...
Machine learning approaches have a valuable contribution in improving competency in automated decision systems. Several machine learning approaches have been developed in the past studies in individual disease diagnosis prediction. The present study aims to develop a hybrid machine learning approach for diagnosis predictions of multiple diseases ba...
Joint photographic experts group (JPEG) compression is widely used in image processing and computer vision. Detecting double compressed JPEG images is a common problem in forensics and detecting compressed images with the same quantization matrix remains a challenging task. However, most existing methods were designed for detection in grayscale ima...
Meteorological parameters were crucial and effective factors in past infectious diseases, like influenza and severe acute respiratory syndrome (SARS), etc. The present study targets to explore the association between the coronavirus disease 2019 (COVID-19) transmission rates and meteorological parameters. For this purpose, the meteorological parame...
The toxic impact of chromium on hormonal concentrations of the Urva auropuctatus in a tannery industrial area has been analyzed through exposure to a sub-lethal contaminated environment. Chromium concentration in the body tissues (blood, testes, and ovaries) of the exposed Urva auropunctatus was found significantly higher than the control. Moreover...
The emergence of adversarial examples has had a great impact on the development and application of deep learning. In this paper, a novel convolutional neural network model, the stochastic multifilter statistical network (SmsNet), is proposed for the detection of adversarial examples. A feature statistical layer is constructed to collect statistical...
Ohrid trout (Salamo letnica) is an endemic species of fish found in Lake Ohrid in the Former Yugoslav Republic of Macedonia (FYROM). The growth of Ohrid trout was examined in a controlled environment for a certain period, thereafter released into the lake to grow their natural population. The external features of the fish were measured regularly du...
The cutting simulation of soft tissue is important in virtual surgery. It includes three major challenges in computation: Soft tissue simulation, collision detection, and handling, as well as soft tissue models. In order to address the earlier challenges, we propose a virtual cutting system based on the mass-spring model. In this system, MSM is uti...
Object recognition and location has always been one of the research hotspots in machine vision. It is of great value and significance to the development and application of current service robots, industrial automation, unmanned driving and other fields. In order to realize the real-time recognition and location of indoor scene objects, this article...
Real-time dense reconstruction of indoor scenes is of great research value for the application and development of service robots, augmented reality, cultural relics conservation and other fields. ORB-SLAM2 method is one of the excellent open source algorithms in visual SLAM system, which is often used in indoor scene reconstruction. However, it is...
In the simulation of acupuncture manipulation, it is necessary to accurately capture the information of acupuncture points and particles around them. Therefore, a soft tissue modeling method that can accurately track model particles is needed. In this paper, a soft tissue acupuncture model based on the mass-spring force net is designed. MSM is used...
Health care data mining is noteworthy in disease diagnosis and recognition procedures. There exist several potentials to further improve the performance of machine learning based-classification methods in healthcare data analysis. The selection of a substantial subset of features is one of the feasible approaches to achieve improved recognition res...
Virtual surgery simulation is indispensable for virtual vascular interventional training system, which provides the doctor with visual scene between catheter and vascular. Soft tissue deformation, as the most significant part, determines the success or failure of the virtual surgery simulation. However, most soft tissue deformation model cannot sim...
The binocular stereo vision system is often used to reconstruct 3D point clouds of an object. However, it is challenging to find effective matching points in two object images with similar color or less texture. This will lead to mismatching by using the stereo matching algorithm to calculate the disparity map. In this context, the object can’t be...
A R T I C L E I N F O Keywords: green design practices multi-level motivations dynamic interactions system dynamics model behavioral patterns A B S T R A C T Green building construction is essential to meet severe environmental challenges and achieve sustainability, where designers' practices are crucial to improve the green performance of construc...
With the rapid development of splicing manipulation, more and more negative effects have been brought. Therefore, the demand for image splicing detection algorithms is growing dramatically. In this paper, a new image splicing detection method is proposed which is based on convolutional neural network (CNN) with weight combination strategy. In the p...
Sub-lethal toxic impacts of chromium on hematological, biochemical and histological parameters were analyzed in the female small Indian mongoose (Urva auropuctatus) residing contaminated environment of tannery industry. Chromium bioaccumulation in the blood, liver and kidney tissue of the exposed mongooses was found elevated compared to the control...
Due to the widespread use of the JPEG format, non-aligned double JPEG (NA-DJPEG) compression is very common in image tampering. Therefore, non-aligned double JPEG compression detection has attracted significant attention in digital forensics in recent years. In most of the previous detection algorithms, grayscale images are used directly, or color...
In sensor networks, it is a challenge to ensure the security of data exchange between packet switching nodes holding different private keys. In order to solve this problem, the present study proposes a scheme called multi-conditional proxy broadcast re-encryption (MC-PBRE). The scheme consists of the following roles: the source node, proxy server,...
In the present study, the performance of physicochemical descriptors of metal oxide nanomaterials on the basis of their origins, including descriptors related to element/ion, the metal oxide in bulk, and metal oxide in the media for toxicity modelling has been evaluated. Three published experimental nanomaterial data sets were selected for the stud...
Splicing is a common tampering operation where the splicing area and the original image have different noise levels. In this paper, novel color spliced image localization based on quaternion principal component analysis (QPCA) and quaternion skewness is proposed. Firstly, the proposed algorithm uses QPCA to estimate the block-wise noise level. Then...
Detection of double Joint Photographic Experts Group (JPEG) compression is an important part of image forensics. Although methods in the past studies have been presented for detecting the double JPEG compression with a different quantization matrix, detection of double JPEG compression with the same quantization matrix is still a challenging proble...
This study estimated energy use flow of buffalo farms, energy use indices, production efficiency, energy use targets, impact of energy inputs on energy output, and sensitivity analysis of energy inputs. A well-structured questionnaire was used to collect data of 360 domestic buffalo farms from Punjab Pakistan during May–July 2017. Results revealed...
In recent years, air pollution in China has posed serious threats to human health. In this study, we investigate the relationship between air pollution and residents’ health by nesting the household registration data of the China Migrant Dynamic Survey in 2014 with city characteristic data and pollution data. The results indicated that an increase...
A promising research to evaluate the quality of ripe banana during storage period by analyzing the variability of the volatile chemical components in odor from peels and flesh based on solid-phase microextraction-GC-MS characterization and statistical analysis has been discussed. A rapid increase of ethanol concentration in peels and flesh contribu...
In the paper, we present a method estimating the linear Gaussian filter kernel by means of photo-response non-uniformity (PRNU) noise. In the past decade, a large number of works have proved that PRNU noise is a reliable fingerprint for digital image. Accordingly, PRNU noise has been widely used in such fields as camera identification and image man...
The convolutional neural network is widely popular for solving the problems of color image feature extraction. However, in the general network, the interrelationship of the color image channels is neglected. Therefore, a novel quaternion convolutional neural network (QCNN) is proposed in this paper, which always treats color triples as a whole to a...
The unique characteristics of dental pulp stem cells (DPSCs), like multi-lineage differentiation, have attracted considerable interest among clinicians and researchers for the treatment of various diseases. Platelet-derived concentrates (PRSs) are utilized for wound healing, due to the plethora of growth factors that are released from platelets. In...
Currently, the development of smart systems for recognition and sensing of volatile organic compounds (VOCs) in medical, agricultural, biometric, security and safety, applications is an emerging research area. This review presents an introduction to the field of VOC recognition by analytical methods and sensing by chemical sensors. The role of patt...
Healthcare data analysis is currently a challenging and crucial research issue for the development of a robust disease diagnosis and prediction system. Many specific and a few common methods have been discussed in the literature for healthcare data classification. The present study implements 32 classification methods of six categories (Bayes, func...
The healthcare data analytics is a demanding task at present due to enormous amount and diversity of information. Several algorithms were developed to analyze healthcare data with the objective to develop a non-invasive, unbiased and robust prediction system. The present study proposed a hybrid algorithm for healthcare data mining by using the Deci...
In this paper, a novel forensics scheme for color image is proposed in color quaternion wavelet transform (CQWT) domain. Compared to discrete wavelet transform (DWT), contourlet wavelet transform (CWT) and local binary patterns (LBP), CQWT processes a color image as a unit and so it can provide more forensics information to identify the photograph...
The present study targets short-term wind speed prediction of the wind turbine station at Bogdanci in the Former Yugoslav Republic of Macedonia (FYROM), using artificial neural network (ANN) method. Wind directions and meteorological parameters (temperature, pressure, and humidity) measured at the interval of 10 min in between May 2015 and Septembe...
Soils are often rich in insoluble mineral and organic phosphates solubilized by specific bacterial species. The present study investigates the factors affecting microbial solubilization of phosphate in the sandy clay loam textured soil. Phosphate solubilization was measured using pot soil experiment spiked with rock phosphate and inoculated with ph...
Three-dimensional graphics software has been extensively used to create animations, video games in multimedia applications. However, the graphics software requires user's efficiency and long creation time in order to maintain a perfect animation. In the present report, a novel parallax engine has been proposed with the objective to ease the designe...
Microbial activities are the indicators of soil strength. The present study explores the development of efficient predictive modeling systems for the estimation of specific soil microbial dynamics, phosphate solubilization (PS), bacterial population (BP), and 1-aminocyclopropane-1-carboxylate ACC-deaminase activity. More specifically, fuzzy c-means...
This paper proposes a novel approach for the evolution of artificial creatures which moves in a 3D virtual environment based on the neuroevolution of augmenting topologies (NEAT) algorithm. The NEAT algorithm is used to evolve neural networks that observe the virtual environment and respond to it, by controlling the muscle force of the creature. Th...
The present study is based on the application of a multivariate statistical analysis approach for the selection of optimal descriptors of nanomaterials with the objective of robust qualitative modeling of their toxicity. A novel data mining protocol has been developed for the selection of an optimal subset of descriptors of nanomaterials by using t...
Computational intelligence plays a significant role in the improvement of the learning process. Student profile provides an overview of personality and establishes a connection between the abilities and learning preferences. The objective of the present study is to develop an algorithmic approach to student profiling in the selection of subjects an...
Wireless sensor networks (WSNs) are used for several commercial and military applications, by collecting, processing and distributing a wide range of data. Maximizing the battery life of WSNs is crucial in improving the performance of WSN. In the present study, different variations of genetic algorithm (GA) method have been implemented independentl...
The existence of sunlight, air and other resources on earth must be used in an appropriate way for human welfare while still protecting the environment and its living creatures. The exploitation of sunlight and air as a substantial Renewable Energy (RE) source is an important research and development domain over past few years. The present and futu...
In the present study, body odor samples have been collected according to different sampling protocols and characterized using the gas chromatography (GC)-mass spectrometry (MS) technique with the objective to investigate the existence of different volatile organic compounds (VOCs) belonging to several chemical classes in body odor composition. More...
Cinematography is an animated part of multimedia, where parallax engine can play a significant role in easing out the workflow. Animations are difficult to compose in precise terms while keeping the consistency of the work; the parallax engine is capable of yielding in multimedia proficiency. In this report, the main objective is to explain the pro...
Microbial population and enzyme activities are the significant indicators of soil strength. Soil microbial dynamics characterize microbial population and enzyme activities. The present study explores the development of efficient predictive modeling systems for the estimation of specific soil microbial dynamics, like rock phosphate solubilization, b...
Human body odor is a unique identity feature of individual as well as an established composite of numerous volatile organic compounds (VOCs) belonging to significant chemical classes. Several analytical methods have been used in the characterization of human body odor in order to recognize the chemical composition of VOCs in medical, forensic, and...
Present study deals with the operation of filter based approaches for selection of an optimal subset of peaks of chemical compounds in gas chromatography (GC)-mass spectrometry (MS) spectra with the objective to robust classification modeling of human body odor. Particularly, we have employed four filter based approaches including CFS, Linear-corre...
The focus of the present study is the human body odour recognition by analysis of information about the chemical compounds identified in their gas chromatography–mass spectrometry (GC-MS) chromatogram. The Artificial neural network (ANN) technique implemented in the current study, has been comprehensively used for classification and regression task...
Environmental and medium parameters estimation is an essential step in Bioprocess engineering.In the present study, artificial neural network (ANN) was employed in estimation of biosurfactants yield from bacterial strain Klebseilla sp. FKOD36, surface tension reduction as well emulsification index. The data obtained from experimental design were us...
The present study explores individual identity perception by analyzing the chemical peak information in the gas chromatography-mass spectrometry (GC-MS) spectra of body odor samples with standard data mining approaches. Mainly, the principal component analysis (PCA) method is chosen for the visual discrimination of the body odor samples in feature...
Drug of abuse or illicit drugs have become a serious health issue and global evils during the last few decades. Their detection is a significant area of research, for preventing illegal traffic and toxic effects on human health and society. Numerous analytical methods, based on diverse principles, have been developed for the detection of drugs of a...
In present work, a novel quartz crystal microbalance (QCM) sensor array has been developed for prompt identification of primary aldehydes in human body odor. Molecularly imprinted polymers (MIP) are prepared using the polyacrylic acid (PAA) polymer matrix and three organic acids (propenoic acid, hexanoic acid and octanoic acid) as template molecule...