The freshness of fruits is considered to be one of the essential characteristics for consumers in determining their quality,flavor and nutritional value.The primary need for identifying rotten fruits is to ensure that...The freshness of fruits is considered to be one of the essential characteristics for consumers in determining their quality,flavor and nutritional value.The primary need for identifying rotten fruits is to ensure that only fresh and high-quality fruits are sold to consumers.The impact of rotten fruits can foster harmful bacteria,molds and other microorganisms that can cause food poisoning and other illnesses to the consumers.The overall purpose of the study is to classify rotten fruits,which can affect the taste,texture,and appearance of other fresh fruits,thereby reducing their shelf life.The agriculture and food industries are increasingly adopting computer vision technology to detect rotten fruits and forecast their shelf life.Hence,this research work mainly focuses on the Convolutional Neural Network’s(CNN)deep learning model,which helps in the classification of rotten fruits.The proposed methodology involves real-time analysis of a dataset of various types of fruits,including apples,bananas,oranges,papayas and guavas.Similarly,machine learningmodels such as GaussianNaïve Bayes(GNB)and random forest are used to predict the fruit’s shelf life.The results obtained from the various pre-trained models for rotten fruit detection are analysed based on an accuracy score to determine the best model.In comparison to other pre-trained models,the visual geometry group16(VGG16)obtained a higher accuracy score of 95%.Likewise,the random forest model delivers a better accuracy score of 88% when compared with GNB in forecasting the fruit’s shelf life.By developing an accurate classification model,only fresh and safe fruits reach consumers,reducing the risks associated with contaminated produce.Thereby,the proposed approach will have a significant impact on the food industry for efficient fruit distribution and also benefit customers to purchase fresh fruits.展开更多
A single-stage plasma-catalytic reactor in which catalytic materials werepacked was used to remove nitrogen oxides. The packing material was scoria being made of variousmetal oxides including Al_2O_3, MgO, TiO_2, etc....A single-stage plasma-catalytic reactor in which catalytic materials werepacked was used to remove nitrogen oxides. The packing material was scoria being made of variousmetal oxides including Al_2O_3, MgO, TiO_2, etc. Scoria was able to act not only as dielectricpellets but also as a catalyst in the presence of reducing agent such as ethylene and ammonia.Without plasma discharge, scoria did not work well as a catalyst in the temperature range of 100 ℃to 200 ℃, showing less than 10% of NOx removal efficiency. When plasma is produced inside thereactor, the NOx removal efficiency could be increased to 60% in this temperature range.展开更多
An electric discharge plasma reactor combined with a catalytic reactor wasstudied for removing nitrogen oxides. To understand the combined process thoroughly, dischargeplasma and catalytic process were separately stud...An electric discharge plasma reactor combined with a catalytic reactor wasstudied for removing nitrogen oxides. To understand the combined process thoroughly, dischargeplasma and catalytic process were separately studied first, and then the two processes were combinedfor the study. The plasma reactor was able to oxidize NO to NO_2 well although the oxidation ratedecreased with temperature. The plasma reactor alone did not reduce the NO_x (NO+NO_2) leveleffectively, but the increase in the ratio of NO_2 to NO as a result of plasma discharge led to theenhancement of NO_x removal efficiency even at lower temperatures over the catalyst surface(V_2O_5-WO_3/TiO_2). At a gas temperature of 100℃, the NO_x removal efficiency obtained using thecombined plasma catalytic process was 88% for an energy input of 36 eV/molecule or 30 J/l.展开更多
A plasma-assisted catalytic reactor was used to remove nitrogen oxides (NOx)from diesel engine exhaust operated under different load conditions. Initial studies were focused onplasma reactor (a dielectric barrier disc...A plasma-assisted catalytic reactor was used to remove nitrogen oxides (NOx)from diesel engine exhaust operated under different load conditions. Initial studies were focused onplasma reactor (a dielectric barrier discharge reactor) treatment of diesel exhaust at varioustemperatures. The nitric oxide (NO) removal efficiency was lowered when high temperature exhaust wastreated using plasma reactor. Also, NO removal efficiency decreased when 45% load exhaust wastreated. Studies were then made with plasma reactor combined with a catalytic reactor consisting ofa selective catalytic reduction (SCR) catalyst, V_2O_5/TiO_2. Ammonia was used as a reducing agentfor SCR process in a ratio of 1:1 to NOx. The studies were focused on temperatures of the SCRcatalytic reactor below 200℃. The plasma-assisted catalytic reactor was operated well to remove NOxunder no-load and load conditions. For an energy input of 96 J/l, the NOx removal efficienciesobtained under no-load and load conditions were 90% and 72% respectively at an exhaust temperatureof 100 ℃.展开更多
Investigations on the recycling plasma pyrolysis technique are presented in 25 kW was employed for the experiments. of oyster shells and bone waste treatment using the this paper. A arc based plasma torch operated at ...Investigations on the recycling plasma pyrolysis technique are presented in 25 kW was employed for the experiments. of oyster shells and bone waste treatment using the this paper. A arc based plasma torch operated at Fresh oyster shells were recycled using the plasma torch to convert them to a useful product such as CaO. Bone waste was treated to remove the infectious organic part and to vitrify the inorganic part. The time required for treatment in both cases was significantly short. Significant reduction in the weight of the samples was observed in both cases.展开更多
A plasma discharge initiation system for the explosive volumetric combustion charge was designed, investigated and developed for practical application. Laboratory scale experiments were carried out before conducting t...A plasma discharge initiation system for the explosive volumetric combustion charge was designed, investigated and developed for practical application. Laboratory scale experiments were carried out before conducting the large scale field tests. The resultant explosions gave rise to less noise, insignificant seismic vibrations and good specific explosive consumption for rock blasting. Importantly, the technique was found to be safe and environmentally friendly.展开更多
In this paper, we employed Na?ve Bayes, Markov blanket and Tabu search to rank web services. The Bayesian Network is demonstrated on a dataset taken from literature. The dataset consists of 364 web services whose qual...In this paper, we employed Na?ve Bayes, Markov blanket and Tabu search to rank web services. The Bayesian Network is demonstrated on a dataset taken from literature. The dataset consists of 364 web services whose quality is described by 9 attributes. Here, the attributes are treated as criteria, to classify web services. From the experiments, we conclude that Na?ve based Bayesian network performs better than other two techniques comparable to the classification done in literature.展开更多
文摘The freshness of fruits is considered to be one of the essential characteristics for consumers in determining their quality,flavor and nutritional value.The primary need for identifying rotten fruits is to ensure that only fresh and high-quality fruits are sold to consumers.The impact of rotten fruits can foster harmful bacteria,molds and other microorganisms that can cause food poisoning and other illnesses to the consumers.The overall purpose of the study is to classify rotten fruits,which can affect the taste,texture,and appearance of other fresh fruits,thereby reducing their shelf life.The agriculture and food industries are increasingly adopting computer vision technology to detect rotten fruits and forecast their shelf life.Hence,this research work mainly focuses on the Convolutional Neural Network’s(CNN)deep learning model,which helps in the classification of rotten fruits.The proposed methodology involves real-time analysis of a dataset of various types of fruits,including apples,bananas,oranges,papayas and guavas.Similarly,machine learningmodels such as GaussianNaïve Bayes(GNB)and random forest are used to predict the fruit’s shelf life.The results obtained from the various pre-trained models for rotten fruit detection are analysed based on an accuracy score to determine the best model.In comparison to other pre-trained models,the visual geometry group16(VGG16)obtained a higher accuracy score of 95%.Likewise,the random forest model delivers a better accuracy score of 88% when compared with GNB in forecasting the fruit’s shelf life.By developing an accurate classification model,only fresh and safe fruits reach consumers,reducing the risks associated with contaminated produce.Thereby,the proposed approach will have a significant impact on the food industry for efficient fruit distribution and also benefit customers to purchase fresh fruits.
基金The project supported by the Basic Research Program of the Korea Science & Engineering Foundation (KOSEF) (No. R05-2001-000-01247-0)
文摘A single-stage plasma-catalytic reactor in which catalytic materials werepacked was used to remove nitrogen oxides. The packing material was scoria being made of variousmetal oxides including Al_2O_3, MgO, TiO_2, etc. Scoria was able to act not only as dielectricpellets but also as a catalyst in the presence of reducing agent such as ethylene and ammonia.Without plasma discharge, scoria did not work well as a catalyst in the temperature range of 100 ℃to 200 ℃, showing less than 10% of NOx removal efficiency. When plasma is produced inside thereactor, the NOx removal efficiency could be increased to 60% in this temperature range.
文摘An electric discharge plasma reactor combined with a catalytic reactor wasstudied for removing nitrogen oxides. To understand the combined process thoroughly, dischargeplasma and catalytic process were separately studied first, and then the two processes were combinedfor the study. The plasma reactor was able to oxidize NO to NO_2 well although the oxidation ratedecreased with temperature. The plasma reactor alone did not reduce the NO_x (NO+NO_2) leveleffectively, but the increase in the ratio of NO_2 to NO as a result of plasma discharge led to theenhancement of NO_x removal efficiency even at lower temperatures over the catalyst surface(V_2O_5-WO_3/TiO_2). At a gas temperature of 100℃, the NO_x removal efficiency obtained using thecombined plasma catalytic process was 88% for an energy input of 36 eV/molecule or 30 J/l.
文摘A plasma-assisted catalytic reactor was used to remove nitrogen oxides (NOx)from diesel engine exhaust operated under different load conditions. Initial studies were focused onplasma reactor (a dielectric barrier discharge reactor) treatment of diesel exhaust at varioustemperatures. The nitric oxide (NO) removal efficiency was lowered when high temperature exhaust wastreated using plasma reactor. Also, NO removal efficiency decreased when 45% load exhaust wastreated. Studies were then made with plasma reactor combined with a catalytic reactor consisting ofa selective catalytic reduction (SCR) catalyst, V_2O_5/TiO_2. Ammonia was used as a reducing agentfor SCR process in a ratio of 1:1 to NOx. The studies were focused on temperatures of the SCRcatalytic reactor below 200℃. The plasma-assisted catalytic reactor was operated well to remove NOxunder no-load and load conditions. For an energy input of 96 J/l, the NOx removal efficienciesobtained under no-load and load conditions were 90% and 72% respectively at an exhaust temperatureof 100 ℃.
文摘Investigations on the recycling plasma pyrolysis technique are presented in 25 kW was employed for the experiments. of oyster shells and bone waste treatment using the this paper. A arc based plasma torch operated at Fresh oyster shells were recycled using the plasma torch to convert them to a useful product such as CaO. Bone waste was treated to remove the infectious organic part and to vitrify the inorganic part. The time required for treatment in both cases was significantly short. Significant reduction in the weight of the samples was observed in both cases.
文摘A plasma discharge initiation system for the explosive volumetric combustion charge was designed, investigated and developed for practical application. Laboratory scale experiments were carried out before conducting the large scale field tests. The resultant explosions gave rise to less noise, insignificant seismic vibrations and good specific explosive consumption for rock blasting. Importantly, the technique was found to be safe and environmentally friendly.
文摘In this paper, we employed Na?ve Bayes, Markov blanket and Tabu search to rank web services. The Bayesian Network is demonstrated on a dataset taken from literature. The dataset consists of 364 web services whose quality is described by 9 attributes. Here, the attributes are treated as criteria, to classify web services. From the experiments, we conclude that Na?ve based Bayesian network performs better than other two techniques comparable to the classification done in literature.
