The higher education sector in developing counties has undergone through dynamic changes in recen... more The higher education sector in developing counties has undergone through dynamic changes in recent era due to highly innovative and competitive environment. The phenomenon of innovation behaviour has gained intensive importance due to its long-lasting impact on performance of industry. The growth of knowledge-based economy is linked with innovative initiatives of employees of higher education sector. The proposed research contributes to the body of knowledge by explaining the relationship between exogenous constructs and innovative behaviour based on the theories of social exchange and social cognition as both theories explains the innovative behaviour of employees. The proposed research intends to bridge the research gap and inconclusive results between constructs to explain the innovative behaviour of academic employees of higher education sector. Moreover, the mediation role of affective commitment is incorporated for deeper insight of innovative behaviour. The data was obtained ...
2021 9th European Workshop on Visual Information Processing (EUVIP), 2021
Human actions that do not conform to usual behavior are considered as anomalous and such actors a... more Human actions that do not conform to usual behavior are considered as anomalous and such actors are called anomalous entities. Detection of anomalous actions using visual data is a challenging problem in computer vision. This paper presents a new approach to detect anomalous actions in complex situations of examination halls. The proposed method uses a cascade of deep convolutional neural network models. In the first stage, we apply a pretrained model of human pose estimation on frames of videos to extract key feature points of body. Patches extracted from each key point are utilized in the second stage to build a densely connected deep convolutional neural network model for detecting anomalous actions. For experiments we collect a video database of students undertaking examination in a hall. Our results show that the proposed method can detect anomalous actions and warrant unusual behavior with high accuracy.
This work studies the time-dependent convective flow of non-Newtonian power-law fluid by vertical... more This work studies the time-dependent convective flow of non-Newtonian power-law fluid by vertical plate. Fluid flow is studied in the presence of thermal radiation. The Buongiorno model is employed to describe the features of nanofluid. Entropy generation and Bejan number are calculated. The flow, temperature and concentration are given by the system of partial differential equations (PDE’s). The system of PDE’s is transformed into dimensionless form by transformation and then solve implementing finite difference technique. Special emphasis is given to the outcomes of Prandtl number, Reynolds number, Eckert number, radiation parameter, thermophoresis, Brownian parameter, and Schmidt number. Velocity, temperature, concentration, skin friction, Sherwood and Nusselt numbers are graphically analyzed. Graphical results show that velocity of fluid enhanced for high Grashof number while shows opposite behavior for Reynold number. For the high estimation of the thermophoresis parameter and ...
Head detection in real-world videos is a classical research problem in computer vision. Head dete... more Head detection in real-world videos is a classical research problem in computer vision. Head detection in videos is challenging than in a single image due to many nuisances that are commonly observed in natural videos, including arbitrary poses, appearances, and scales. Generally, head detection is treated as a particular case of object detection in a single image. However, the performance of object detectors deteriorates in unconstrained videos. In this paper, we propose a temporal consistency model (TCM) to enhance the performance of a generic object detector by integrating spatial-temporal information that exists among subsequent frames of a particular video. Generally, our model takes detection from a generic detector as input and improves mean average precision (mAP) by recovering missed detection and suppressing false positives. We compare and evaluate the proposed framework on four challenging datasets, i.e., HollywoodHeads, Casablanca, BOSS, and PAMELA. Experimental evaluati...
International Journal of Advanced Computer Science and Applications, 2018
Trillions of posts from Facebook, tweets in Twitter, photos on Instagram and e-mails on exchange ... more Trillions of posts from Facebook, tweets in Twitter, photos on Instagram and e-mails on exchange servers are overwhelming the Internet with big data. This necessitates the development of such tools that can detect the frequent updates and select the required information instantly. This research work aims to implement scraper software that is capable of collecting the updated information from the target products hosted in fabulous online e-commerce websites. The software is implemented using Scrapy and Django frameworks. The software is configured and evaluated across different e-commerce websites. Individual website generates a greater amount of data about the products that need to be scraped. The proposed software provides the ability to search a target product in a single consolidated place instead of searching across various websites, such as amazon.com, alibaba.com and daraz.pk. Furthermore, the scheduling mechanism enables the scraper to execute at a required frequency within a specified time frame.
Critical Reviews in Environmental Science and Technology, 2020
The rapid development in nanotechnology and incorporation of engineered nano-particles (ENPs) in ... more The rapid development in nanotechnology and incorporation of engineered nano-particles (ENPs) in a wide range of consumer products releasing the massive quantities of ENPs in different environmental compartments. The released ENPs from nanoenabled products during their life cycle raising environmental health and safety issues. This review addresses the recent state of knowledge regarding the ENPs ecotoxicity to various organisms lying at different trophic levels. Studies show that reactive oxygen species (ROS) mediated oxidative stress is the primary mechanism of nano-toxicity, either through physical damage by direct contact or release of toxic ions after ENPs dissolution process. Moreover, ENPs uptake, transformation and toxicity on physiomorphological, biochemical and molecular levels in primary producers of terrestrial environment (plants) were also reviewed. Additionally, the intrinsic detoxification mechanism in plants in response to ENPs accumulation was also examined. In the end different sustainable approaches such as biogenic synthesis, clay minerals role, biochar application, bioremediation, and legislative measures are proposed for effective handling and treatment of nano-wastes to get the maximum benefits of nanotechnology with minimum negative outcomes.
h i g h l i g h t s g r a p h i c a l a b s t r a c t Photoswitchable catalysis for hydrogen reco... more h i g h l i g h t s g r a p h i c a l a b s t r a c t Photoswitchable catalysis for hydrogen recombination is reported for the first time. The catalyst is rationally designed by studying proton and hydride affinities. Dithienylethene photochrome offer promising application for photoswitchable catalysis. The hydrogen recombination in closed form is much faster than that of the open isomer.
Photoelectrochemical water splitting (PEC) offers a promising path for sustainable generation of ... more Photoelectrochemical water splitting (PEC) offers a promising path for sustainable generation of hydrogen fuel. However, improving solar fuel water splitting efficiency facing tremendous challenges, due to the energy loss related to fast recombination of the photogenerated charge carriers, electrode degradation, as well as limited light harvesting. This review focuses on the brief introduction of basic fundamental of PEC water splitting and the concept of various types of water splitting approaches. Numerous engineering strategies for the investgating of the higher efficiency of the PEC, including charge separation, light harvesting, and co-catalysts doping, have been discussed. Moreover, recent remarkable progress and developments for PEC water splitting with some promising materials are discussed. Recent advanced applications of PEC are also reviewed. Finally, the review concludes with a summary and future outlook of this hot field.
Atmospheric dust, especially air-conditioner dust in urban-industrial environments, can act as a ... more Atmospheric dust, especially air-conditioner dust in urban-industrial environments, can act as a significant sink for both black carbon and nanoparticles posing allied health risks to the air conditioner repairman as well as to local inhabitants. However, the chemical composition of black carbon/nanoparticles in air-conditioner dust and their association with potentially toxic elements remain uncertain. The present study investigate the black carbon and nanoparticles compositions of air-conditioner dust and their associated potentially toxic elements, as an indicator of indoor air-pollution. The black carbon and nanoparticles in air-conditioner dust, were comprehensively characterized using array-based techniques including Inductively Coupled Plasma-Mass Spectrometry, particle size distribution, Scanning Electron Microscopy, Transmission electron microscopy along with Energy-dispersive X-ray spectroscopy and selected area-(electron) diffraction, from metropolitan area of Hefei, China. Geo-accumulation index values of air-conditioner dust reveal Lead, Tin, Arsenic and Cadmium are under Geo-accumulation Classes V-VI level of contamination. The majority of the particles were found to be in the ultrafine nanoparticles range (<100 nm). A strong correlation was found between black carbon and total potential toxic elements content (R 2 ¼ 0.79). The metallic nanoparticles (Iron, Copper and Lead) and black carbon were identified using Scanning Electron Microscopy/Transmission electron microscopy along with Energy-dispersive X-ray spectroscopy/selected area (electron) diffraction mode. Using array-based techniques seems to be a useful tool to study the black carbon and nanoparticles in air-conditioner dust. It is the first demonstration presenting evidence for the concept of air-conditioner dust as a sink for black carbon/nanoparticles bound potentially toxic elements in the urban-industrial environments, as an ultimate source of environmental pollutants.
ABSTRACT In this paper, we propose a fast and robust framework for anomaly detection in crowed sc... more ABSTRACT In this paper, we propose a fast and robust framework for anomaly detection in crowed scenes. In our method, anomaly is adaptively modeled as a deviation from the normal behavior of crowd observed in the scene. For this purpose, we extract motion features by repeatedly initializing a grid of particles over a temporal window. These features are exploited in a real-time anomaly detection system. In order to model the ordinary behavior of the people moving in the crowd, we use the Gaussian mixture model (GMM) technique, which is robust enough to capture the scene dynamics. As opposed to explicitly modeling the values of all the pixels as a mixture of Gaussians, we adopted the GMM to learn the behavior of the motion features extracted from the particles. Based on the persistence and the variance of each Gaussian distribution, we determine which Gaussians can be associated to the normal behavior of the crowd. Particles with motion features that do not fit the distributions representing normal behavior are signaled as anomaly, until there is a Gaussian able to include them with sufficient evidence supporting it. Experiments are extensively conducted on publically available benchmark dataset, and also on a challenging dataset of video sequences we captured. The experimental results revealed that the proposed method performs effectively for anomaly detection.
2013 IEEE International Conference on Image Processing, 2013
ABSTRACT In this paper we present a novel method for motion segmentation in crowded scenes, based... more ABSTRACT In this paper we present a novel method for motion segmentation in crowded scenes, based on statistical modeling for structured prediction using a Conditional Random Field (CRF). As opposed to other conditional Markov models, CRF overcomes the label bias problem, making it suitable for crowd motion analysis. In our method, a grid of particles is initialized on the scene, and advected using optical flow. The particles are exploited to extract motion patterns, used as input priors for CRF training. Furthermore, we exploit min cut/max flow algorithm to remove the residual noise and highlight the main directions of crowd motion. The experimental evaluation is conducted on a set of benchmark video sequences, commonly used for crowd motion analysis, and the obtained results are compared against other state of the art techniques.
ABSTRACT The structural and electronic properties of (0) and (+2) charged oxygen vacancies (Vo0 a... more ABSTRACT The structural and electronic properties of (0) and (+2) charged oxygen vacancies (Vo0 and Vo+2) in KTN are investigated through first-principles density functional calculations. We have tested three exchange–correlation functionals local-density approximation (LDA), the Perdew–Burke–Ernzerhof (PBE) generalized-gradient approximation (GGA), and Wu–Cohen (WC) GGA. WC leads to excellent improvements of geometry predications of KTN (with Vo) over LDA and PBE, although they all underestimate the band gap. We find that Vo0 state is metallic, in good agreement with the conclusion of Vo in KNbO3, and there is a defect peak 0.23 eV below the Fermi level which is related to the infrared absorption. The charged Vo state plays an essential role in the displacements of Ta and O ions. We have shown that Vo+2 state of KTN is the most stable in practice, and Vo0 state may be obtained by introducing extra electrons to Vo+2. The results of our calculations indicate that Vo plays an essential role in the metal–insulator transitions in KTN and hence studying Vo is necessitate and significant for devices design.
ABSTRACT Farmyard manure (FYM) improves various soil parameters and to a large extent, the availa... more ABSTRACT Farmyard manure (FYM) improves various soil parameters and to a large extent, the availability of water and nutrient to crops when it is applied to the soil. This study aims to further investigate the short-term effects of different levels of FYM on maize plants and soil parameters. Maize plants grown in pot culture were treated with no FYM (control), recommended NPK (inorganic fertilizers), and FYM at 2, 4, 6, 8, and 10 t ha−1 along with recommended NPK, and the cultures were analyzed 8 weeks after germination. Soil bulk density and soil pH decreased with the increasing levels of FYM, whereas soil porosity, soil organic matter (SOM), soil water content, plant height, root and shoot yield, and NPK uptake of maize were increased compared with the control or recommended NPK, respectively. The present results indicate that short-term application of higher FYM levels improves soil properties. Furthermore, the application of FYM at only higher rates significantly increases the nutrient uptake of maize plants due to improved soil properties. The supply of different amounts of nutrients increases biomass and nutrient uptake in plants.
The higher education sector in developing counties has undergone through dynamic changes in recen... more The higher education sector in developing counties has undergone through dynamic changes in recent era due to highly innovative and competitive environment. The phenomenon of innovation behaviour has gained intensive importance due to its long-lasting impact on performance of industry. The growth of knowledge-based economy is linked with innovative initiatives of employees of higher education sector. The proposed research contributes to the body of knowledge by explaining the relationship between exogenous constructs and innovative behaviour based on the theories of social exchange and social cognition as both theories explains the innovative behaviour of employees. The proposed research intends to bridge the research gap and inconclusive results between constructs to explain the innovative behaviour of academic employees of higher education sector. Moreover, the mediation role of affective commitment is incorporated for deeper insight of innovative behaviour. The data was obtained ...
2021 9th European Workshop on Visual Information Processing (EUVIP), 2021
Human actions that do not conform to usual behavior are considered as anomalous and such actors a... more Human actions that do not conform to usual behavior are considered as anomalous and such actors are called anomalous entities. Detection of anomalous actions using visual data is a challenging problem in computer vision. This paper presents a new approach to detect anomalous actions in complex situations of examination halls. The proposed method uses a cascade of deep convolutional neural network models. In the first stage, we apply a pretrained model of human pose estimation on frames of videos to extract key feature points of body. Patches extracted from each key point are utilized in the second stage to build a densely connected deep convolutional neural network model for detecting anomalous actions. For experiments we collect a video database of students undertaking examination in a hall. Our results show that the proposed method can detect anomalous actions and warrant unusual behavior with high accuracy.
This work studies the time-dependent convective flow of non-Newtonian power-law fluid by vertical... more This work studies the time-dependent convective flow of non-Newtonian power-law fluid by vertical plate. Fluid flow is studied in the presence of thermal radiation. The Buongiorno model is employed to describe the features of nanofluid. Entropy generation and Bejan number are calculated. The flow, temperature and concentration are given by the system of partial differential equations (PDE’s). The system of PDE’s is transformed into dimensionless form by transformation and then solve implementing finite difference technique. Special emphasis is given to the outcomes of Prandtl number, Reynolds number, Eckert number, radiation parameter, thermophoresis, Brownian parameter, and Schmidt number. Velocity, temperature, concentration, skin friction, Sherwood and Nusselt numbers are graphically analyzed. Graphical results show that velocity of fluid enhanced for high Grashof number while shows opposite behavior for Reynold number. For the high estimation of the thermophoresis parameter and ...
Head detection in real-world videos is a classical research problem in computer vision. Head dete... more Head detection in real-world videos is a classical research problem in computer vision. Head detection in videos is challenging than in a single image due to many nuisances that are commonly observed in natural videos, including arbitrary poses, appearances, and scales. Generally, head detection is treated as a particular case of object detection in a single image. However, the performance of object detectors deteriorates in unconstrained videos. In this paper, we propose a temporal consistency model (TCM) to enhance the performance of a generic object detector by integrating spatial-temporal information that exists among subsequent frames of a particular video. Generally, our model takes detection from a generic detector as input and improves mean average precision (mAP) by recovering missed detection and suppressing false positives. We compare and evaluate the proposed framework on four challenging datasets, i.e., HollywoodHeads, Casablanca, BOSS, and PAMELA. Experimental evaluati...
International Journal of Advanced Computer Science and Applications, 2018
Trillions of posts from Facebook, tweets in Twitter, photos on Instagram and e-mails on exchange ... more Trillions of posts from Facebook, tweets in Twitter, photos on Instagram and e-mails on exchange servers are overwhelming the Internet with big data. This necessitates the development of such tools that can detect the frequent updates and select the required information instantly. This research work aims to implement scraper software that is capable of collecting the updated information from the target products hosted in fabulous online e-commerce websites. The software is implemented using Scrapy and Django frameworks. The software is configured and evaluated across different e-commerce websites. Individual website generates a greater amount of data about the products that need to be scraped. The proposed software provides the ability to search a target product in a single consolidated place instead of searching across various websites, such as amazon.com, alibaba.com and daraz.pk. Furthermore, the scheduling mechanism enables the scraper to execute at a required frequency within a specified time frame.
Critical Reviews in Environmental Science and Technology, 2020
The rapid development in nanotechnology and incorporation of engineered nano-particles (ENPs) in ... more The rapid development in nanotechnology and incorporation of engineered nano-particles (ENPs) in a wide range of consumer products releasing the massive quantities of ENPs in different environmental compartments. The released ENPs from nanoenabled products during their life cycle raising environmental health and safety issues. This review addresses the recent state of knowledge regarding the ENPs ecotoxicity to various organisms lying at different trophic levels. Studies show that reactive oxygen species (ROS) mediated oxidative stress is the primary mechanism of nano-toxicity, either through physical damage by direct contact or release of toxic ions after ENPs dissolution process. Moreover, ENPs uptake, transformation and toxicity on physiomorphological, biochemical and molecular levels in primary producers of terrestrial environment (plants) were also reviewed. Additionally, the intrinsic detoxification mechanism in plants in response to ENPs accumulation was also examined. In the end different sustainable approaches such as biogenic synthesis, clay minerals role, biochar application, bioremediation, and legislative measures are proposed for effective handling and treatment of nano-wastes to get the maximum benefits of nanotechnology with minimum negative outcomes.
h i g h l i g h t s g r a p h i c a l a b s t r a c t Photoswitchable catalysis for hydrogen reco... more h i g h l i g h t s g r a p h i c a l a b s t r a c t Photoswitchable catalysis for hydrogen recombination is reported for the first time. The catalyst is rationally designed by studying proton and hydride affinities. Dithienylethene photochrome offer promising application for photoswitchable catalysis. The hydrogen recombination in closed form is much faster than that of the open isomer.
Photoelectrochemical water splitting (PEC) offers a promising path for sustainable generation of ... more Photoelectrochemical water splitting (PEC) offers a promising path for sustainable generation of hydrogen fuel. However, improving solar fuel water splitting efficiency facing tremendous challenges, due to the energy loss related to fast recombination of the photogenerated charge carriers, electrode degradation, as well as limited light harvesting. This review focuses on the brief introduction of basic fundamental of PEC water splitting and the concept of various types of water splitting approaches. Numerous engineering strategies for the investgating of the higher efficiency of the PEC, including charge separation, light harvesting, and co-catalysts doping, have been discussed. Moreover, recent remarkable progress and developments for PEC water splitting with some promising materials are discussed. Recent advanced applications of PEC are also reviewed. Finally, the review concludes with a summary and future outlook of this hot field.
Atmospheric dust, especially air-conditioner dust in urban-industrial environments, can act as a ... more Atmospheric dust, especially air-conditioner dust in urban-industrial environments, can act as a significant sink for both black carbon and nanoparticles posing allied health risks to the air conditioner repairman as well as to local inhabitants. However, the chemical composition of black carbon/nanoparticles in air-conditioner dust and their association with potentially toxic elements remain uncertain. The present study investigate the black carbon and nanoparticles compositions of air-conditioner dust and their associated potentially toxic elements, as an indicator of indoor air-pollution. The black carbon and nanoparticles in air-conditioner dust, were comprehensively characterized using array-based techniques including Inductively Coupled Plasma-Mass Spectrometry, particle size distribution, Scanning Electron Microscopy, Transmission electron microscopy along with Energy-dispersive X-ray spectroscopy and selected area-(electron) diffraction, from metropolitan area of Hefei, China. Geo-accumulation index values of air-conditioner dust reveal Lead, Tin, Arsenic and Cadmium are under Geo-accumulation Classes V-VI level of contamination. The majority of the particles were found to be in the ultrafine nanoparticles range (<100 nm). A strong correlation was found between black carbon and total potential toxic elements content (R 2 ¼ 0.79). The metallic nanoparticles (Iron, Copper and Lead) and black carbon were identified using Scanning Electron Microscopy/Transmission electron microscopy along with Energy-dispersive X-ray spectroscopy/selected area (electron) diffraction mode. Using array-based techniques seems to be a useful tool to study the black carbon and nanoparticles in air-conditioner dust. It is the first demonstration presenting evidence for the concept of air-conditioner dust as a sink for black carbon/nanoparticles bound potentially toxic elements in the urban-industrial environments, as an ultimate source of environmental pollutants.
ABSTRACT In this paper, we propose a fast and robust framework for anomaly detection in crowed sc... more ABSTRACT In this paper, we propose a fast and robust framework for anomaly detection in crowed scenes. In our method, anomaly is adaptively modeled as a deviation from the normal behavior of crowd observed in the scene. For this purpose, we extract motion features by repeatedly initializing a grid of particles over a temporal window. These features are exploited in a real-time anomaly detection system. In order to model the ordinary behavior of the people moving in the crowd, we use the Gaussian mixture model (GMM) technique, which is robust enough to capture the scene dynamics. As opposed to explicitly modeling the values of all the pixels as a mixture of Gaussians, we adopted the GMM to learn the behavior of the motion features extracted from the particles. Based on the persistence and the variance of each Gaussian distribution, we determine which Gaussians can be associated to the normal behavior of the crowd. Particles with motion features that do not fit the distributions representing normal behavior are signaled as anomaly, until there is a Gaussian able to include them with sufficient evidence supporting it. Experiments are extensively conducted on publically available benchmark dataset, and also on a challenging dataset of video sequences we captured. The experimental results revealed that the proposed method performs effectively for anomaly detection.
2013 IEEE International Conference on Image Processing, 2013
ABSTRACT In this paper we present a novel method for motion segmentation in crowded scenes, based... more ABSTRACT In this paper we present a novel method for motion segmentation in crowded scenes, based on statistical modeling for structured prediction using a Conditional Random Field (CRF). As opposed to other conditional Markov models, CRF overcomes the label bias problem, making it suitable for crowd motion analysis. In our method, a grid of particles is initialized on the scene, and advected using optical flow. The particles are exploited to extract motion patterns, used as input priors for CRF training. Furthermore, we exploit min cut/max flow algorithm to remove the residual noise and highlight the main directions of crowd motion. The experimental evaluation is conducted on a set of benchmark video sequences, commonly used for crowd motion analysis, and the obtained results are compared against other state of the art techniques.
ABSTRACT The structural and electronic properties of (0) and (+2) charged oxygen vacancies (Vo0 a... more ABSTRACT The structural and electronic properties of (0) and (+2) charged oxygen vacancies (Vo0 and Vo+2) in KTN are investigated through first-principles density functional calculations. We have tested three exchange–correlation functionals local-density approximation (LDA), the Perdew–Burke–Ernzerhof (PBE) generalized-gradient approximation (GGA), and Wu–Cohen (WC) GGA. WC leads to excellent improvements of geometry predications of KTN (with Vo) over LDA and PBE, although they all underestimate the band gap. We find that Vo0 state is metallic, in good agreement with the conclusion of Vo in KNbO3, and there is a defect peak 0.23 eV below the Fermi level which is related to the infrared absorption. The charged Vo state plays an essential role in the displacements of Ta and O ions. We have shown that Vo+2 state of KTN is the most stable in practice, and Vo0 state may be obtained by introducing extra electrons to Vo+2. The results of our calculations indicate that Vo plays an essential role in the metal–insulator transitions in KTN and hence studying Vo is necessitate and significant for devices design.
ABSTRACT Farmyard manure (FYM) improves various soil parameters and to a large extent, the availa... more ABSTRACT Farmyard manure (FYM) improves various soil parameters and to a large extent, the availability of water and nutrient to crops when it is applied to the soil. This study aims to further investigate the short-term effects of different levels of FYM on maize plants and soil parameters. Maize plants grown in pot culture were treated with no FYM (control), recommended NPK (inorganic fertilizers), and FYM at 2, 4, 6, 8, and 10 t ha−1 along with recommended NPK, and the cultures were analyzed 8 weeks after germination. Soil bulk density and soil pH decreased with the increasing levels of FYM, whereas soil porosity, soil organic matter (SOM), soil water content, plant height, root and shoot yield, and NPK uptake of maize were increased compared with the control or recommended NPK, respectively. The present results indicate that short-term application of higher FYM levels improves soil properties. Furthermore, the application of FYM at only higher rates significantly increases the nutrient uptake of maize plants due to improved soil properties. The supply of different amounts of nutrients increases biomass and nutrient uptake in plants.
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