The color perception is related to color objects, vision system and central nervous system. The methods of evaluation, classification and prediction of the color perception are investigated and analyzed in this paper....The color perception is related to color objects, vision system and central nervous system. The methods of evaluation, classification and prediction of the color perception are investigated and analyzed in this paper. The artificial neural networks are used for color perception, clustering and predicting based on the given data obtained from both objective measurement and subjective evaluation.展开更多
Retinal degenerative diseases may induce the degeneration of outer retina and in turn,blindness.Nevertheless,due to the maintenance of inner retina,the coding and processing of visual neurons responses are still able ...Retinal degenerative diseases may induce the degeneration of outer retina and in turn,blindness.Nevertheless,due to the maintenance of inner retina,the coding and processing of visual neurons responses are still able to be executed naturally.Therefore,an effective retinal prosthesis device may be developed by mimicking the function of outer retina:transferring the visual light into artificial stimulus and delivering the stimulus to the retina aiming to evoke the neural responses.As two main developing directions for current retinal prosthesis,epiretinal(ER)and subretinal(SR)prosthesis are both undergoing experimental stage and possessing advantages and limitations.Further investigations in power supply,biocompatibility,etc.are still required.Additionally,suprachoroidal transretinal stimulation(STS)and neurotransmitter-induced stimulation as some other alternatives in retinal prosthesis are also considered as promising research directions,although they are not mature enough to be applied commercially,either.展开更多
OBJECTIVE:We applied data mining techniques to the study of acupuncture as a treatment for juvenile myopia,with the aim of identifying hidden patterns in the data.METHODS:Fifty patients with juvenile myopia were selec...OBJECTIVE:We applied data mining techniques to the study of acupuncture as a treatment for juvenile myopia,with the aim of identifying hidden patterns in the data.METHODS:Fifty patients with juvenile myopia were selected and treated with acupuncture,and data mining was used to analyze the effects of treatment and the influence of behavioral variables.Clustering analysis was used to divide myopia patients into two classifications before acupuncture treatment.Artificial neural network BP algorithm was adopted to analyze the roles of different factors in changes in diopters.An association algorithm was used to analyze factors associated with the subjective experience of acupuncture and average diopter.RESULTS:The two classification results were fully consistent with the understandings of the ophthalmic circles.The duration of using the Internet and watching TV every day was the main factor that affected vision.Acupuncture feelings and therapeutic effect have a strong correlativity.A good or above experience's score of acupuncture could slow the progression of juvenile myopia.CONCLUSION:Collecting data from patients with juvenile myopia by using data mining can extract hidden potential rules and knowledge from the research evidence.The decision support can be provided to improve the doctor's clinical acupuncture treatment effects.展开更多
The weight of shelled shrimp is an important parameter for grading process.The weight prediction of shelled shrimp by contour area is not accurate enough because of the ignorance of the shrimp thickness.In this paper,...The weight of shelled shrimp is an important parameter for grading process.The weight prediction of shelled shrimp by contour area is not accurate enough because of the ignorance of the shrimp thickness.In this paper,a multivariate prediction model containing area,perimeter,length,and width was established.A new calibration algorithm for extracting length of shelled shrimp was proposed,which contains binary image thinning,branch recognition and elimination,and length reconstruction,while its width was calculated during the process of length extracting.The model was further validated with another set of images from 30 shelled shrimps.For a comparison purpose,artificial neural network(ANN) was used for the shrimp weight predication.The ANN model resulted in a better prediction accuracy(with the average relative error at 2.67%),but took a tenfold increase in calculation time compared with the weight-area-perimeter(WAP) model(with the average relative error at 3.02%).We thus conclude that the WAP model is a better method for the prediction of the weight of shelled red shrimp.展开更多
文摘The color perception is related to color objects, vision system and central nervous system. The methods of evaluation, classification and prediction of the color perception are investigated and analyzed in this paper. The artificial neural networks are used for color perception, clustering and predicting based on the given data obtained from both objective measurement and subjective evaluation.
文摘Retinal degenerative diseases may induce the degeneration of outer retina and in turn,blindness.Nevertheless,due to the maintenance of inner retina,the coding and processing of visual neurons responses are still able to be executed naturally.Therefore,an effective retinal prosthesis device may be developed by mimicking the function of outer retina:transferring the visual light into artificial stimulus and delivering the stimulus to the retina aiming to evoke the neural responses.As two main developing directions for current retinal prosthesis,epiretinal(ER)and subretinal(SR)prosthesis are both undergoing experimental stage and possessing advantages and limitations.Further investigations in power supply,biocompatibility,etc.are still required.Additionally,suprachoroidal transretinal stimulation(STS)and neurotransmitter-induced stimulation as some other alternatives in retinal prosthesis are also considered as promising research directions,although they are not mature enough to be applied commercially,either.
基金Supported by National Natural Science Foundation grant NO.40976108Public Projects of Science and Technology Ministry grant NO.201105033
文摘OBJECTIVE:We applied data mining techniques to the study of acupuncture as a treatment for juvenile myopia,with the aim of identifying hidden patterns in the data.METHODS:Fifty patients with juvenile myopia were selected and treated with acupuncture,and data mining was used to analyze the effects of treatment and the influence of behavioral variables.Clustering analysis was used to divide myopia patients into two classifications before acupuncture treatment.Artificial neural network BP algorithm was adopted to analyze the roles of different factors in changes in diopters.An association algorithm was used to analyze factors associated with the subjective experience of acupuncture and average diopter.RESULTS:The two classification results were fully consistent with the understandings of the ophthalmic circles.The duration of using the Internet and watching TV every day was the main factor that affected vision.Acupuncture feelings and therapeutic effect have a strong correlativity.A good or above experience's score of acupuncture could slow the progression of juvenile myopia.CONCLUSION:Collecting data from patients with juvenile myopia by using data mining can extract hidden potential rules and knowledge from the research evidence.The decision support can be provided to improve the doctor's clinical acupuncture treatment effects.
文摘The weight of shelled shrimp is an important parameter for grading process.The weight prediction of shelled shrimp by contour area is not accurate enough because of the ignorance of the shrimp thickness.In this paper,a multivariate prediction model containing area,perimeter,length,and width was established.A new calibration algorithm for extracting length of shelled shrimp was proposed,which contains binary image thinning,branch recognition and elimination,and length reconstruction,while its width was calculated during the process of length extracting.The model was further validated with another set of images from 30 shelled shrimps.For a comparison purpose,artificial neural network(ANN) was used for the shrimp weight predication.The ANN model resulted in a better prediction accuracy(with the average relative error at 2.67%),but took a tenfold increase in calculation time compared with the weight-area-perimeter(WAP) model(with the average relative error at 3.02%).We thus conclude that the WAP model is a better method for the prediction of the weight of shelled red shrimp.
