In this research work, the thermal conductivity and density of alumina/silica(Al_2O_3/SiO_2) in water hybrid nanofluids at different temperatures and volume concentrations have been modeled using the artificial neural...In this research work, the thermal conductivity and density of alumina/silica(Al_2O_3/SiO_2) in water hybrid nanofluids at different temperatures and volume concentrations have been modeled using the artificial neural networks(ANN). The nanocolloid involved in the study was synthesized by the two-step method and characterized by XRD, TEM, SEM–EDX and zeta potential analysis. The properties of the synthesized nanofluid were measured at various volume concentrations(0.05%, 0.1% and 0.2%) and temperatures(20 to 60 °C). Established on the observational data and ANN, the optimum neural structure was suggested for predicting the thermal conductivity and density of the hybrid nanofluid as a function of temperature and solid volume concentrations. The results indicate that a neural network with 2 hidden layers and 10 neurons have the lowest error and a highest fitting coefficient o thermal conductivity, whereas in the case of density, the structure with 1 hidden layer consisting of 4 neurons proved to be the optimal structure.展开更多
Biodiesel fuel is a potential alternative energy source for diesel engines due to its physiochemical characteristics relatively similar to those of traditional diesel fuel.In this study,the performance,emission,and co...Biodiesel fuel is a potential alternative energy source for diesel engines due to its physiochemical characteristics relatively similar to those of traditional diesel fuel.In this study,the performance,emission,and combustion features of a mono cylinder DI diesel engine are assessed using 20%Pumpkin seed methyl ester(PSOME20)and considering varying injection pressures(200,220,240,and 260 bar).The considered Pumpkin seed oil is converted into pumpkin biodiesel by transesterification and then used as fuel.The findings demonstrate that the Brake Thermal Efficiency(BTE)of PSOME20 can be raised by 1.68%,and the carbon monoxide(CO),hydrocarbon(HC),and smoke emanations can be lowered,while oxides of nitrogen(NOx)emissions are increased at an injection pressure(IP)of 240 bar compared to the standard IP of 200 bar.The cylinder pressure and the Heat Release Rate(HRR)become higher at 240 bar,whereas the ignition delay is shortened with respect to PSOME20 at a normal IP of 200 bar.展开更多
Bioadsorption phenomenon is more or less like a chemical reaction and several parameters are bound to affect the process. The pH, amount of adsorbent and agitation time influence the biosorptive potentiality. Hence, t...Bioadsorption phenomenon is more or less like a chemical reaction and several parameters are bound to affect the process. The pH, amount of adsorbent and agitation time influence the biosorptive potentiality. Hence, the present study on adsorption of Cr(VI) by activated Vetivera roots and Blue green algae Anabaena supports that it is an effective low cost adsorbent for the removal of Cr(VI) from plating effluent. Langmuir and Freundlich adsorption isotherm correlate the equilibrium adsorption data. In batch experiments both Vetiveria and Anabaena species were found to be cost effective biosorbent for the efficient removal of Cr(VI) from the effluent and comparatively Anabaena species was found to adsorb maximum Cr(VI) (88.86%) at a low contact time of 60 min. The data obtained from the experiments and modeling would prove useful in designing and fabricating an efficient treatment plant for Cr(VI) rich effluent.展开更多
Antimicrobial-treated textiles should exhibit efficacy against a broad spectrum of bacterial and fungal species,all while maintaining user safety with a non-toxic profile.Natural antimicrobial compounds play a vital r...Antimicrobial-treated textiles should exhibit efficacy against a broad spectrum of bacterial and fungal species,all while maintaining user safety with a non-toxic profile.Natural antimicrobial compounds play a vital role in textile finishing processes.The proliferation of synthetic antimicrobial agents introduces environmental and consumer safety concerns.Given these potential hazards associated with synthetic agents,the utilization of natural antimicrobial agents is gaining traction,as they tend to have fewer adverse effects on users and are more environmentally sustainable.Numerous natural antimicrobial compounds,sourced from plants such as neem,basil,turmeric,aloe vera,and clove oil,have been developed,showcasing inherent antimicrobial properties.This review article highlights the importance of incorporating bioactive components in the creation of antibacterial textile fabrics.展开更多
At present,the prediction of brain tumors is performed using Machine Learning(ML)and Deep Learning(DL)algorithms.Although various ML and DL algorithms are adapted to predict brain tumors to some range,some concerns st...At present,the prediction of brain tumors is performed using Machine Learning(ML)and Deep Learning(DL)algorithms.Although various ML and DL algorithms are adapted to predict brain tumors to some range,some concerns still need enhancement,particularly accuracy,sensitivity,false positive and false negative,to improve the brain tumor prediction system symmetrically.Therefore,this work proposed an Extended Deep Learning Algorithm(EDLA)to measure performance parameters such as accuracy,sensitivity,and false positive and false negative rates.In addition,these iterated measures were analyzed by comparing the EDLA method with the Convolutional Neural Network(CNN)way further using the SPSS tool,and respective graphical illustrations were shown.The results were that the mean performance measures for the proposed EDLA algorithm were calculated,and those measured were accuracy(97.665%),sensitivity(97.939%),false positive(3.012%),and false negative(3.182%)for ten iterations.Whereas in the case of the CNN,the algorithm means accuracy gained was 94.287%,mean sensitivity 95.612%,mean false positive 5.328%,and mean false negative 4.756%.These results show that the proposed EDLA method has outperformed existing algorithms,including CNN,and ensures symmetrically improved parameters.Thus EDLA algorithm introduces novelty concerning its performance and particular activation function.This proposed method will be utilized effectively in brain tumor detection in a precise and accurate manner.This algorithm would apply to brain tumor diagnosis and be involved in various medical diagnoses aftermodification.If the quantity of dataset records is enormous,then themethod’s computation power has to be updated.展开更多
Antibiotic resistance is one of the major issues in the medical field and a potential threat to human health.However,newly emerging antimicrobial compounds failed to combat antimicrobial resistance developed by bacter...Antibiotic resistance is one of the major issues in the medical field and a potential threat to human health.However,newly emerging antimicrobial compounds failed to combat antimicrobial resistance developed by bacterial pathogens.Recently,a bismuth-based complex has been developed to eradicate antimicrobial-resistant microorganism infections.The complex is known as organobismuth(III)phosphinate,which is said to be a potential broad-spectrum antimicrobial agent.This complex has been incorporated into the nanocellulose suspension to fabricate a biomedical composite for various applications.The composite can be fabricated by two methods namely vacuum filtration and spray coating.In this paper,the surface and topography of the composite are investigated and discussed in terms of SEM micrographs and their antimicrobial potential.This review focuses on the organo-bismuth nanocellulose composite and its biomedical application in the future.展开更多
In this investigation, an approach using Coac-tive Neuro-Fuzzy Inference System (CANFIS) as diagnosis system for breast cancer has been proposed on Wisconsin Breast Cancer Data (WBCD). It is occasionally difficult to ...In this investigation, an approach using Coac-tive Neuro-Fuzzy Inference System (CANFIS) as diagnosis system for breast cancer has been proposed on Wisconsin Breast Cancer Data (WBCD). It is occasionally difficult to attain the ultimate diagnosis even for medical experts due to the complexity and non-linearity of the rela-tionships between the large measured factors, which can be possibly resolved with a human like decision-making process using Artificial Intelligence (AI) algorithms. CANFIS is an AI algorithm which has the advantages of both fuzzy inference system and neural networks and can deal with ambiguous data and learn from the past data by itself. The Multi Layer Percep-tron Neural Network (MLPNN), Probabilistic Neural Network (PNN) Principal Component Analysis (PCA), Support Vector Machine (SVM) and Self Organizing Map (SOM) were also tested and benchmarked for their展开更多
Concrete encased with trapezoidally corrugated web profiled cold-formed steel beams are used worldwide to improve resistance toward fire and corrosion,higher load carrying capacity as well as significant increase in t...Concrete encased with trapezoidally corrugated web profiled cold-formed steel beams are used worldwide to improve resistance toward fire and corrosion,higher load carrying capacity as well as significant increase in the bending stiffness by encasing concrete on the beam portion.The present work gives a detailed description on the experimental,analytical and numerical investigation on the flexural behavior of concrete encased trapezoidally corrugated web profiled cold-formed steel beams which were simply supported at both ends and subjected to two point symmetric loading.The flexural behavior of such structure has been experimentally tested to failure under pure bending.To find the effct of concrete encasement in the web,12 experiments were conducted by two different series.Beams having three different web corrugation angles of 0°,30°,and 45°with two different web depth-thickness(dw/tw)ratios of 60 and 80 were tested.Experimental results such as load-deflection relationship,ultimate capacity,load-strain relationship,moment-curvature curves,ductility and failure mode indices of the specimens are presented.From the static bending tests the concrete encased trapezoidally corugated web beam showed improved moment carrying capacity,ductility bchavior and the resistance to transverse deflections in comparison to concrete encased with plain web beam.Especially for the beams with concrete encased 30°trapezoidally corrugated web having(dw/tw)ratio 60 and 80,the loading capacity was improved about 54%and 67.3%and the ductility also increased about l.6 and 3.6 times,when compared to concrete encased beams with plain web.This research should contribute to the future engineering applications on seismic resistant structures and efficient usage of concrete encased with cold-formed steel beams by exhibiting its super elasto-plastic property.The analytical and numerical results showed good agreement with the experimental results at yield load,which indicates that the proposed analytical equations can be applied in predicting flexural strength accurately for such concrete encased trapezoidally corrugated web profiled cold-formed steel beams.展开更多
文摘In this research work, the thermal conductivity and density of alumina/silica(Al_2O_3/SiO_2) in water hybrid nanofluids at different temperatures and volume concentrations have been modeled using the artificial neural networks(ANN). The nanocolloid involved in the study was synthesized by the two-step method and characterized by XRD, TEM, SEM–EDX and zeta potential analysis. The properties of the synthesized nanofluid were measured at various volume concentrations(0.05%, 0.1% and 0.2%) and temperatures(20 to 60 °C). Established on the observational data and ANN, the optimum neural structure was suggested for predicting the thermal conductivity and density of the hybrid nanofluid as a function of temperature and solid volume concentrations. The results indicate that a neural network with 2 hidden layers and 10 neurons have the lowest error and a highest fitting coefficient o thermal conductivity, whereas in the case of density, the structure with 1 hidden layer consisting of 4 neurons proved to be the optimal structure.
文摘Biodiesel fuel is a potential alternative energy source for diesel engines due to its physiochemical characteristics relatively similar to those of traditional diesel fuel.In this study,the performance,emission,and combustion features of a mono cylinder DI diesel engine are assessed using 20%Pumpkin seed methyl ester(PSOME20)and considering varying injection pressures(200,220,240,and 260 bar).The considered Pumpkin seed oil is converted into pumpkin biodiesel by transesterification and then used as fuel.The findings demonstrate that the Brake Thermal Efficiency(BTE)of PSOME20 can be raised by 1.68%,and the carbon monoxide(CO),hydrocarbon(HC),and smoke emanations can be lowered,while oxides of nitrogen(NOx)emissions are increased at an injection pressure(IP)of 240 bar compared to the standard IP of 200 bar.The cylinder pressure and the Heat Release Rate(HRR)become higher at 240 bar,whereas the ignition delay is shortened with respect to PSOME20 at a normal IP of 200 bar.
文摘Bioadsorption phenomenon is more or less like a chemical reaction and several parameters are bound to affect the process. The pH, amount of adsorbent and agitation time influence the biosorptive potentiality. Hence, the present study on adsorption of Cr(VI) by activated Vetivera roots and Blue green algae Anabaena supports that it is an effective low cost adsorbent for the removal of Cr(VI) from plating effluent. Langmuir and Freundlich adsorption isotherm correlate the equilibrium adsorption data. In batch experiments both Vetiveria and Anabaena species were found to be cost effective biosorbent for the efficient removal of Cr(VI) from the effluent and comparatively Anabaena species was found to adsorb maximum Cr(VI) (88.86%) at a low contact time of 60 min. The data obtained from the experiments and modeling would prove useful in designing and fabricating an efficient treatment plant for Cr(VI) rich effluent.
文摘Antimicrobial-treated textiles should exhibit efficacy against a broad spectrum of bacterial and fungal species,all while maintaining user safety with a non-toxic profile.Natural antimicrobial compounds play a vital role in textile finishing processes.The proliferation of synthetic antimicrobial agents introduces environmental and consumer safety concerns.Given these potential hazards associated with synthetic agents,the utilization of natural antimicrobial agents is gaining traction,as they tend to have fewer adverse effects on users and are more environmentally sustainable.Numerous natural antimicrobial compounds,sourced from plants such as neem,basil,turmeric,aloe vera,and clove oil,have been developed,showcasing inherent antimicrobial properties.This review article highlights the importance of incorporating bioactive components in the creation of antibacterial textile fabrics.
基金supported by Project No.R-2023-23 of the Deanship of Scientific Research at Majmaah University.
文摘At present,the prediction of brain tumors is performed using Machine Learning(ML)and Deep Learning(DL)algorithms.Although various ML and DL algorithms are adapted to predict brain tumors to some range,some concerns still need enhancement,particularly accuracy,sensitivity,false positive and false negative,to improve the brain tumor prediction system symmetrically.Therefore,this work proposed an Extended Deep Learning Algorithm(EDLA)to measure performance parameters such as accuracy,sensitivity,and false positive and false negative rates.In addition,these iterated measures were analyzed by comparing the EDLA method with the Convolutional Neural Network(CNN)way further using the SPSS tool,and respective graphical illustrations were shown.The results were that the mean performance measures for the proposed EDLA algorithm were calculated,and those measured were accuracy(97.665%),sensitivity(97.939%),false positive(3.012%),and false negative(3.182%)for ten iterations.Whereas in the case of the CNN,the algorithm means accuracy gained was 94.287%,mean sensitivity 95.612%,mean false positive 5.328%,and mean false negative 4.756%.These results show that the proposed EDLA method has outperformed existing algorithms,including CNN,and ensures symmetrically improved parameters.Thus EDLA algorithm introduces novelty concerning its performance and particular activation function.This proposed method will be utilized effectively in brain tumor detection in a precise and accurate manner.This algorithm would apply to brain tumor diagnosis and be involved in various medical diagnoses aftermodification.If the quantity of dataset records is enormous,then themethod’s computation power has to be updated.
文摘Antibiotic resistance is one of the major issues in the medical field and a potential threat to human health.However,newly emerging antimicrobial compounds failed to combat antimicrobial resistance developed by bacterial pathogens.Recently,a bismuth-based complex has been developed to eradicate antimicrobial-resistant microorganism infections.The complex is known as organobismuth(III)phosphinate,which is said to be a potential broad-spectrum antimicrobial agent.This complex has been incorporated into the nanocellulose suspension to fabricate a biomedical composite for various applications.The composite can be fabricated by two methods namely vacuum filtration and spray coating.In this paper,the surface and topography of the composite are investigated and discussed in terms of SEM micrographs and their antimicrobial potential.This review focuses on the organo-bismuth nanocellulose composite and its biomedical application in the future.
文摘In this investigation, an approach using Coac-tive Neuro-Fuzzy Inference System (CANFIS) as diagnosis system for breast cancer has been proposed on Wisconsin Breast Cancer Data (WBCD). It is occasionally difficult to attain the ultimate diagnosis even for medical experts due to the complexity and non-linearity of the rela-tionships between the large measured factors, which can be possibly resolved with a human like decision-making process using Artificial Intelligence (AI) algorithms. CANFIS is an AI algorithm which has the advantages of both fuzzy inference system and neural networks and can deal with ambiguous data and learn from the past data by itself. The Multi Layer Percep-tron Neural Network (MLPNN), Probabilistic Neural Network (PNN) Principal Component Analysis (PCA), Support Vector Machine (SVM) and Self Organizing Map (SOM) were also tested and benchmarked for their
文摘Concrete encased with trapezoidally corrugated web profiled cold-formed steel beams are used worldwide to improve resistance toward fire and corrosion,higher load carrying capacity as well as significant increase in the bending stiffness by encasing concrete on the beam portion.The present work gives a detailed description on the experimental,analytical and numerical investigation on the flexural behavior of concrete encased trapezoidally corrugated web profiled cold-formed steel beams which were simply supported at both ends and subjected to two point symmetric loading.The flexural behavior of such structure has been experimentally tested to failure under pure bending.To find the effct of concrete encasement in the web,12 experiments were conducted by two different series.Beams having three different web corrugation angles of 0°,30°,and 45°with two different web depth-thickness(dw/tw)ratios of 60 and 80 were tested.Experimental results such as load-deflection relationship,ultimate capacity,load-strain relationship,moment-curvature curves,ductility and failure mode indices of the specimens are presented.From the static bending tests the concrete encased trapezoidally corugated web beam showed improved moment carrying capacity,ductility bchavior and the resistance to transverse deflections in comparison to concrete encased with plain web beam.Especially for the beams with concrete encased 30°trapezoidally corrugated web having(dw/tw)ratio 60 and 80,the loading capacity was improved about 54%and 67.3%and the ductility also increased about l.6 and 3.6 times,when compared to concrete encased beams with plain web.This research should contribute to the future engineering applications on seismic resistant structures and efficient usage of concrete encased with cold-formed steel beams by exhibiting its super elasto-plastic property.The analytical and numerical results showed good agreement with the experimental results at yield load,which indicates that the proposed analytical equations can be applied in predicting flexural strength accurately for such concrete encased trapezoidally corrugated web profiled cold-formed steel beams.
