Biomedical imaging, archiving, and classification is the recent challenge of computer-aided medic... more Biomedical imaging, archiving, and classification is the recent challenge of computer-aided medical imaging. The popular and influential Deep Learning methods predict and congregate distinct markable features of ambiguity in radiographs precisely and accurately. This study submits a new topology of a deep learning network for chest radiograph classification. In this approach, a hybrid ensemble fusion of neural network topology can better diagnose ambiguities with high precision. The proposed topology also compares statistical findings with three optimizers and the most possible varying essential attributes of dropout probabilities and learning rates. The performance as a function of the AUCROC of this model is measured on the Chest Xpert dataset.
Necessity and exploitation of fossil fuel products are implacable in serving the needs of humanit... more Necessity and exploitation of fossil fuel products are implacable in serving the needs of humanity despite being a finite and limited resource. To meet the thrust of energy, biofuels derived from varieties of renewable resources are imperative in fulfilling the demand of renewable fuels on a large scale without creating environmental concerns. Biofuels are inevitably the result of the carbon fixation process which stores chemical energy, ultimately reducing the total amount of carbon dioxide. Different kinds of biofuels like bioethanol, biomethanol, biogas, and biodiesel are derived depending on varieties of feedstock materials. Among these, production of biodiesel augments the progression of clean and renewable fuel. In this review, we have discussed the production of biodiesel derived from various feedstock and using several processes like pyrolysis, direct blending, micro-emulsion, and trans-esterification, with critical discussion focussing on increasing biodiesel production usi...
International Journal of Bio-resource and Stress Management
The experiment was conducted at the farm of Sher-e-Bangla Agricultural University, Dhaka, Banglad... more The experiment was conducted at the farm of Sher-e-Bangla Agricultural University, Dhaka, Bangladesh during the period from December 2015 to March 2016 to study the effect of zinc and molybdenum on the growth and yield of garden pea. The variety BARI Motorshuti-1 was used as the test crop. Two factors experiment as, Factor A: Levels of zinc (3 levels)- Zn0: 0 kg Zn ha-1, Zn1.5: 1.5 kg Zn ha-1 Zn3.0: 3.0 kg Zn ha-1 and Factors B: Levels of molybdenum (3 levels)- Mo0: 0 kg Mo ha-1, Mo0.3: 0.3 kg Mo ha-1, Mo0.6: 0.6 kg Mo ha-1 was laid out in Randomized Complete Block Design (RCBD) with three replications. In case of different levels of zinc, the tallest plant, maximum number of pods plant-1, the highest green pod yield hectare-1 were recorded from Zn3.0, whereas the shortest plant, the lowest green pod yield hectare-1 were found from Zn0. For different levels of molybdenum, the tallest plant, the highest green pod yield hectare-1, was found from Mo0.6, while the shortest plant, the minimum number of pods plant-1, the lowest green pod yield hectare-1, was recorded from Mo0. Due to the interaction effect of different levels of zinc and molybdenum, the tallest plant, the highest green pod yield hectare-1 were found from Zn3.0Mo0.6 and maximum number of pods plant-1 found from Zn1.5Mo0.6. The shortest plant, the minimum number of pods plant-1, the lowest green pod yield hectare-1 were found from Zn0Mo0.
Bio-nanocomposites were synthesized via grafting polypyrrole/ZnO onto chitosan chain for the phot... more Bio-nanocomposites were synthesized via grafting polypyrrole/ZnO onto chitosan chain for the photodegradation of organic pollutants and biomedical applications.
Visible light-driven Ag 2 S-grafted NiO−ZnO ternary nanocomposites are synthesized using a facile... more Visible light-driven Ag 2 S-grafted NiO−ZnO ternary nanocomposites are synthesized using a facile and cost-effective homogeneous precipitation method. The structural, morphological, and optical properties were extensively studied, confirming the formation of ternary nanocomposites. The surface area of the synthesized nanocomposites was calculated by electrochemical double-layer capacitance (C dl). Ternary Ag 2 S/NiO−ZnO nanocomposites showed excellent visible light photocatalytic property which increases further with the concentration of Ag 2 S. The maximum photocatalytic activity was shown by 8% Ag 2 S/NiO− ZnO with a RhB degradation efficiency of 95%. Hydroxyl and superoxide radicals were found to be dominant species for photodegradation of RhB, confirmed by scavenging experiments. It is noteworthy that the recycling experiments demonstrated high stability and recyclable nature of the photocatalyst. Moreover, the electrochemical results indicated that the prepared nanocomposite exhibits remarkable activity toward detection of acetone. The fabricated nanocomposite sensor showed high sensitivity (4.0764 μA mmol L −1 cm −2) and a lower detection limit (0.06 mmol L −1) for the detection of acetone. The enhanced photocatalytic and the sensing property of Ag 2 S/NiO−ZnO can be attributed to the synergistic effects of strong visible light absorption, excellent charge separation, and remarkable surface properties.
In the present study novel polypyrrole-cellulose-graphene oxide nanocomposite (PCeGONC) was emplo... more In the present study novel polypyrrole-cellulose-graphene oxide nanocomposite (PCeGONC) was employed for the immobilization of ginger peroxidase (GP) via simple adsorption mechanism. Immobilization of enzyme on the obtained support resulted in enhancement of the enzyme activity. The recovery of activity was 128% of the initial activity. Consequently, in 3 h stirred batch treatment, PCeGONC bound GP exhibited higher decolorization efficiency (99%) for Reactive Blue 4 (RB 4) dye as compared to free GP (88%). The immobilized GP exhibited higher operational stability and retained approximately 72% of its initial activity even after ten sequential cycles of dye decolorization in batch process. The kinetic characterization of PCeGONC bound GP revealed slightly lower K and 3.3 times higher V compared to free GP. Degraded products were identified on the basis of GC-MS analysis and degradation pathway was proposed accordingly which confirms enzymatic breakdown of RB 4 into low molecular weig...
Among the various electrically conducting polymers, polyaniline (PANI) has gained attentions due ... more Among the various electrically conducting polymers, polyaniline (PANI) has gained attentions due to its unique properties and doping chemistry. A number of electrically conducting biodegradable polymers has been synthesized by incorporating a biodegradable content of cellulose, chitin, chitosan, etc. in the matrix of PANI. The hybrid materials are also employed as photocatalysts, antibacterial agents, sensors, fuel cells and as materials in biomedical applications. Furthermore, these biodegradable and biocompatible conducting polymers are employed in tissue engineering, dental implants and targeted drug delivery. This review presents state of the art of PANI based biodegradable polymers along with their synthesis routes and unique applications in diverse fields. In future, the synthesis of PANI-grafted biodegradable nanocomposite material is expected to open innovative ways for their outstanding applications.
Novel bio-nanocomposites with enhanced biodegradability and photocatalytic activity were prepared... more Novel bio-nanocomposites with enhanced biodegradability and photocatalytic activity were prepared by chemical in situ polymerization.
Complete removal of reactive orange 16 in a microbial fuel cell coupled aerobic post-treatment pr... more Complete removal of reactive orange 16 in a microbial fuel cell coupled aerobic post-treatment process along with energy recovery.
The variability of the object models is treated as flexible constellations of rigid parts which i... more The variability of the object models is treated as flexible constellations of rigid parts which is represented by a joint probability density function (pdf) on the shape of the constellation and the output of part detectors. Firstly we use method an Affine Invariant Salient Region Detector to identify the distinctive parts in the training set for clustering data. Then we use Markov chain Monte Carlo expectation maximization (MCMC-EM) algorithm to learn the statistical shape model of the object and discover object categories in an unsupervised manner. In the MCMC-EM algorithm, the high-dimensional integrals required in the EM algorithm are estimated using MCMC sampling. The MCMC sampler requires simulation of sample paths from a continuous time Markov process, conditional on the beginning and ending states and the paths of the neighboring sites.
Biomedical imaging, archiving, and classification is the recent challenge of computer-aided medic... more Biomedical imaging, archiving, and classification is the recent challenge of computer-aided medical imaging. The popular and influential Deep Learning methods predict and congregate distinct markable features of ambiguity in radiographs precisely and accurately. This study submits a new topology of a deep learning network for chest radiograph classification. In this approach, a hybrid ensemble fusion of neural network topology can better diagnose ambiguities with high precision. The proposed topology also compares statistical findings with three optimizers and the most possible varying essential attributes of dropout probabilities and learning rates. The performance as a function of the AUCROC of this model is measured on the Chest Xpert dataset.
Necessity and exploitation of fossil fuel products are implacable in serving the needs of humanit... more Necessity and exploitation of fossil fuel products are implacable in serving the needs of humanity despite being a finite and limited resource. To meet the thrust of energy, biofuels derived from varieties of renewable resources are imperative in fulfilling the demand of renewable fuels on a large scale without creating environmental concerns. Biofuels are inevitably the result of the carbon fixation process which stores chemical energy, ultimately reducing the total amount of carbon dioxide. Different kinds of biofuels like bioethanol, biomethanol, biogas, and biodiesel are derived depending on varieties of feedstock materials. Among these, production of biodiesel augments the progression of clean and renewable fuel. In this review, we have discussed the production of biodiesel derived from various feedstock and using several processes like pyrolysis, direct blending, micro-emulsion, and trans-esterification, with critical discussion focussing on increasing biodiesel production usi...
International Journal of Bio-resource and Stress Management
The experiment was conducted at the farm of Sher-e-Bangla Agricultural University, Dhaka, Banglad... more The experiment was conducted at the farm of Sher-e-Bangla Agricultural University, Dhaka, Bangladesh during the period from December 2015 to March 2016 to study the effect of zinc and molybdenum on the growth and yield of garden pea. The variety BARI Motorshuti-1 was used as the test crop. Two factors experiment as, Factor A: Levels of zinc (3 levels)- Zn0: 0 kg Zn ha-1, Zn1.5: 1.5 kg Zn ha-1 Zn3.0: 3.0 kg Zn ha-1 and Factors B: Levels of molybdenum (3 levels)- Mo0: 0 kg Mo ha-1, Mo0.3: 0.3 kg Mo ha-1, Mo0.6: 0.6 kg Mo ha-1 was laid out in Randomized Complete Block Design (RCBD) with three replications. In case of different levels of zinc, the tallest plant, maximum number of pods plant-1, the highest green pod yield hectare-1 were recorded from Zn3.0, whereas the shortest plant, the lowest green pod yield hectare-1 were found from Zn0. For different levels of molybdenum, the tallest plant, the highest green pod yield hectare-1, was found from Mo0.6, while the shortest plant, the minimum number of pods plant-1, the lowest green pod yield hectare-1, was recorded from Mo0. Due to the interaction effect of different levels of zinc and molybdenum, the tallest plant, the highest green pod yield hectare-1 were found from Zn3.0Mo0.6 and maximum number of pods plant-1 found from Zn1.5Mo0.6. The shortest plant, the minimum number of pods plant-1, the lowest green pod yield hectare-1 were found from Zn0Mo0.
Bio-nanocomposites were synthesized via grafting polypyrrole/ZnO onto chitosan chain for the phot... more Bio-nanocomposites were synthesized via grafting polypyrrole/ZnO onto chitosan chain for the photodegradation of organic pollutants and biomedical applications.
Visible light-driven Ag 2 S-grafted NiO−ZnO ternary nanocomposites are synthesized using a facile... more Visible light-driven Ag 2 S-grafted NiO−ZnO ternary nanocomposites are synthesized using a facile and cost-effective homogeneous precipitation method. The structural, morphological, and optical properties were extensively studied, confirming the formation of ternary nanocomposites. The surface area of the synthesized nanocomposites was calculated by electrochemical double-layer capacitance (C dl). Ternary Ag 2 S/NiO−ZnO nanocomposites showed excellent visible light photocatalytic property which increases further with the concentration of Ag 2 S. The maximum photocatalytic activity was shown by 8% Ag 2 S/NiO− ZnO with a RhB degradation efficiency of 95%. Hydroxyl and superoxide radicals were found to be dominant species for photodegradation of RhB, confirmed by scavenging experiments. It is noteworthy that the recycling experiments demonstrated high stability and recyclable nature of the photocatalyst. Moreover, the electrochemical results indicated that the prepared nanocomposite exhibits remarkable activity toward detection of acetone. The fabricated nanocomposite sensor showed high sensitivity (4.0764 μA mmol L −1 cm −2) and a lower detection limit (0.06 mmol L −1) for the detection of acetone. The enhanced photocatalytic and the sensing property of Ag 2 S/NiO−ZnO can be attributed to the synergistic effects of strong visible light absorption, excellent charge separation, and remarkable surface properties.
In the present study novel polypyrrole-cellulose-graphene oxide nanocomposite (PCeGONC) was emplo... more In the present study novel polypyrrole-cellulose-graphene oxide nanocomposite (PCeGONC) was employed for the immobilization of ginger peroxidase (GP) via simple adsorption mechanism. Immobilization of enzyme on the obtained support resulted in enhancement of the enzyme activity. The recovery of activity was 128% of the initial activity. Consequently, in 3 h stirred batch treatment, PCeGONC bound GP exhibited higher decolorization efficiency (99%) for Reactive Blue 4 (RB 4) dye as compared to free GP (88%). The immobilized GP exhibited higher operational stability and retained approximately 72% of its initial activity even after ten sequential cycles of dye decolorization in batch process. The kinetic characterization of PCeGONC bound GP revealed slightly lower K and 3.3 times higher V compared to free GP. Degraded products were identified on the basis of GC-MS analysis and degradation pathway was proposed accordingly which confirms enzymatic breakdown of RB 4 into low molecular weig...
Among the various electrically conducting polymers, polyaniline (PANI) has gained attentions due ... more Among the various electrically conducting polymers, polyaniline (PANI) has gained attentions due to its unique properties and doping chemistry. A number of electrically conducting biodegradable polymers has been synthesized by incorporating a biodegradable content of cellulose, chitin, chitosan, etc. in the matrix of PANI. The hybrid materials are also employed as photocatalysts, antibacterial agents, sensors, fuel cells and as materials in biomedical applications. Furthermore, these biodegradable and biocompatible conducting polymers are employed in tissue engineering, dental implants and targeted drug delivery. This review presents state of the art of PANI based biodegradable polymers along with their synthesis routes and unique applications in diverse fields. In future, the synthesis of PANI-grafted biodegradable nanocomposite material is expected to open innovative ways for their outstanding applications.
Novel bio-nanocomposites with enhanced biodegradability and photocatalytic activity were prepared... more Novel bio-nanocomposites with enhanced biodegradability and photocatalytic activity were prepared by chemical in situ polymerization.
Complete removal of reactive orange 16 in a microbial fuel cell coupled aerobic post-treatment pr... more Complete removal of reactive orange 16 in a microbial fuel cell coupled aerobic post-treatment process along with energy recovery.
The variability of the object models is treated as flexible constellations of rigid parts which i... more The variability of the object models is treated as flexible constellations of rigid parts which is represented by a joint probability density function (pdf) on the shape of the constellation and the output of part detectors. Firstly we use method an Affine Invariant Salient Region Detector to identify the distinctive parts in the training set for clustering data. Then we use Markov chain Monte Carlo expectation maximization (MCMC-EM) algorithm to learn the statistical shape model of the object and discover object categories in an unsupervised manner. In the MCMC-EM algorithm, the high-dimensional integrals required in the EM algorithm are estimated using MCMC sampling. The MCMC sampler requires simulation of sample paths from a continuous time Markov process, conditional on the beginning and ending states and the paths of the neighboring sites.
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Papers by Saima Sultana