The cult of Mazu is a common folk belief in China and Vietnam.Originating from the Song and Yuan Dynasties,particularly during the Ming and Qing Dynasties,the cult of Mazu spread to Vietnam through maritime trade and ...The cult of Mazu is a common folk belief in China and Vietnam.Originating from the Song and Yuan Dynasties,particularly during the Ming and Qing Dynasties,the cult of Mazu spread to Vietnam through maritime trade and migration from coastal regions of China.After centuries of integration and development,it evolved into its own cultural system of Mazu worship,becoming an important component of Vietnamese folk culture.Hainan,China,as a crucial supply station on the Maritime Silk Road,has close connections with the transmission of Mazu culture to Vietnam.This paper adopts field investigations and literature research methods to explore the Mazu worship and culture in Hainan,China,and the Qiongfu Assembly Halls in Vietnam.展开更多
Tuberculosis is a dangerous disease to human life,and we need a lot of attempts to stop and reverse it.Significantly,in theCOVID-19 pandemic,access to medical services for tuberculosis has become very difficult.The la...Tuberculosis is a dangerous disease to human life,and we need a lot of attempts to stop and reverse it.Significantly,in theCOVID-19 pandemic,access to medical services for tuberculosis has become very difficult.The late detection of tuberculosis could lead to danger to patient health,even death.Vietnamis one of the countries heavily affected by the COVID-19 pandemic,andmany residential areas as well as hospitals have to be isolated for a long time.Reality demands a fast and effective tuberculosis diagnosis solution to deal with the difficulty of accessingmedical services,such as an automatic tuberculosis diagnosis system.In our study,aiming to build that system,we were interested in the tuberculosis diagnosis problem from the chest X-ray images of Vietnamese patients.The chest X-ray image is an important data type to diagnose tuberculosis,and it has also received a lot of attention from deep learning researchers.This paper proposed a novel method for tuberculosis diagnosis and visualization using the deeplearning approach with a large Vietnamese X-ray image dataset.In detail,we designed our custom convolutional neural network for the X-ray image classification task and then analyzed the predicted result to provide visualization as a heat-map.To prove the performance of our network model,we conducted several experiments to compare it to another study and also to evaluate it with the dataset of this research.To support the implementation,we built a specific annotation system for tuberculosis under the requirements of radiologists in the Vietnam National Lung Hospital.A large experiment dataset was also from this hospital,and most of this data was for training the convolutional neural network model.The experiment results were evaluated regarding sensitivity,specificity,and accuracy.We achieved high scores with a training accuracy score of 0.99,and the testing specificity and sensitivity scores were over 0.9.Based on the X-ray image classification result,we visualize prediction results as heat-maps and also analyze them in comparison with annotated symptoms of radiologists.展开更多
Deep learning created a sharp rise in the development of autonomous image recognition systems,especially in the case of the medical field.Among lung problems,tuberculosis,caused by a bacterium called Mycobacterium tub...Deep learning created a sharp rise in the development of autonomous image recognition systems,especially in the case of the medical field.Among lung problems,tuberculosis,caused by a bacterium called Mycobacterium tuberculosis,is a dangerous disease because of its infection and damage.When an infected person coughs or sneezes,tiny droplets can bring pathogens to others through inhaling.Tuberculosis mainly damages the lungs,but it also affects any part of the body.Moreover,during the period of the COVID-19(coronavirus disease 2019)pandemic,the access to tuberculosis diagnosis and treatment has become more difficult,so early and simple detection of tuberculosis has been more and more important.In our study,we focused on tuberculosis diagnosis by using the chestX-ray image,the essential input for the radiologist’s profession,and researched the effectiveness of the transfer learning approach in the case study of Vietnamese chest X-ray images.We proposed four strategies to clarify our hypothesis in different ways of applying transfer learning and different training set types.We also prepared a Vietnamese X-ray image dataset with the support of the VRPACS team to provide the basis for training and testing deep learning models.Our experiments were carried out by applying three different architectures,Alexnet,Resnet,and Densenet,on international,Vietnamese,and combined X-ray image datasets.After training,all models were verified on a pure Vietnamese X-rays set.The results show that transfer learning is suitable in the case study of Vietnamese chest X-ray images with high evaluating metrics in terms of AUC(Area under the Receiver Operating Characteristic Curve),sensitivity,specificity,and accuracy.In the best strategy,most of the scores were more than 0.93,and all AUCs were more than 0.98.展开更多
In recent years,speech synthesis systems have allowed for the produc-tion of very high-quality voices.Therefore,research in this domain is now turning to the problem of integrating emotions into speech.However,the met...In recent years,speech synthesis systems have allowed for the produc-tion of very high-quality voices.Therefore,research in this domain is now turning to the problem of integrating emotions into speech.However,the method of con-structing a speech synthesizer for each emotion has some limitations.First,this method often requires an emotional-speech data set with many sentences.Such data sets are very time-intensive and labor-intensive to complete.Second,training each of these models requires computers with large computational capabilities and a lot of effort and time for model tuning.In addition,each model for each emotion failed to take advantage of data sets of other emotions.In this paper,we propose a new method to synthesize emotional speech in which the latent expressions of emotions are learned from a small data set of professional actors through a Flow-tron model.In addition,we provide a new method to build a speech corpus that is scalable and whose quality is easy to control.Next,to produce a high-quality speech synthesis model,we used this data set to train the Tacotron 2 model.We used it as a pre-trained model to train the Flowtron model.We applied this method to synthesize Vietnamese speech with sadness and happiness.Mean opi-nion score(MOS)assessment results show that MOS is 3.61 for sadness and 3.95 for happiness.In conclusion,the proposed method proves to be more effec-tive for a high degree of automation and fast emotional sentence generation,using a small emotional-speech data set.展开更多
Our aim was to evaluate the quality of ejaculated and epididymal frozen-thawed pig sperm of endangered Vietnam native pig breeds. Ejaculated sperm was collected from live boars and epididymal sperm was collected from ...Our aim was to evaluate the quality of ejaculated and epididymal frozen-thawed pig sperm of endangered Vietnam native pig breeds. Ejaculated sperm was collected from live boars and epididymal sperm was collected from slaughtered boars of the MuongTe, Kieng Sat and Co BinhThuan breeds and frozen in 0.25 ml straws using a protocol established earlier for modern pig breeds. We evaluated the sperm quality after thawing in terms of motility and rates of viable and abnormal spermatozoa. Our results revealed that the sperm motility and rates of viable and abnormal frozen-thawed sperm were >30%, >44%, and <14%, respectively. The origin of sperm had an effect on the production of pig embryos in vitro. In the Co BinhThuan breed, ejaculated sperm generated higher cleavage, blastocyst and hatching rates than did the epididymal sperm (60.11% vs 56.02%, 17.23% vs 14.31%, 3.78% vs 2.34%, respectively, P < 0.05). Although no difference in cleavage rate, blastocyst formation rate and the average number of cells/blastocysts, the hatching blastocyst rate was different between the breeds (P > 0.05). In the Co BinhThuan breed, the rate of pregnancy of ejaculated groups was similar to that of the epididymal group. In conclusion, the ejaculated and epididymal sperm of native Vietnamese pigs were successfully frozen. We succeeded in creating embryos in vitro and pregnant pigs after artificial insemination from frozen-thawed semen in three native Vietnamese pig breeds for the first time. The use of the ejaculated sperm improved the production of native pig embryos in vitro efficiency.展开更多
基金sponsored by the 2021 Research Project of Hainan Research Center for Applied Foreign Languages(HNWYJD21-05)by the Scientific Research Project of Hainan Higher Education Institutions(Hnky2023-20).
文摘The cult of Mazu is a common folk belief in China and Vietnam.Originating from the Song and Yuan Dynasties,particularly during the Ming and Qing Dynasties,the cult of Mazu spread to Vietnam through maritime trade and migration from coastal regions of China.After centuries of integration and development,it evolved into its own cultural system of Mazu worship,becoming an important component of Vietnamese folk culture.Hainan,China,as a crucial supply station on the Maritime Silk Road,has close connections with the transmission of Mazu culture to Vietnam.This paper adopts field investigations and literature research methods to explore the Mazu worship and culture in Hainan,China,and the Qiongfu Assembly Halls in Vietnam.
基金funded by the Project KC-4.0.14/19-25“Research on Building a Support System for Diagnosis and Prediction Geo-Spatial Epidemiology of Pulmonary Tuberculosis by Chest X-Ray Images in Vietnam”.
文摘Tuberculosis is a dangerous disease to human life,and we need a lot of attempts to stop and reverse it.Significantly,in theCOVID-19 pandemic,access to medical services for tuberculosis has become very difficult.The late detection of tuberculosis could lead to danger to patient health,even death.Vietnamis one of the countries heavily affected by the COVID-19 pandemic,andmany residential areas as well as hospitals have to be isolated for a long time.Reality demands a fast and effective tuberculosis diagnosis solution to deal with the difficulty of accessingmedical services,such as an automatic tuberculosis diagnosis system.In our study,aiming to build that system,we were interested in the tuberculosis diagnosis problem from the chest X-ray images of Vietnamese patients.The chest X-ray image is an important data type to diagnose tuberculosis,and it has also received a lot of attention from deep learning researchers.This paper proposed a novel method for tuberculosis diagnosis and visualization using the deeplearning approach with a large Vietnamese X-ray image dataset.In detail,we designed our custom convolutional neural network for the X-ray image classification task and then analyzed the predicted result to provide visualization as a heat-map.To prove the performance of our network model,we conducted several experiments to compare it to another study and also to evaluate it with the dataset of this research.To support the implementation,we built a specific annotation system for tuberculosis under the requirements of radiologists in the Vietnam National Lung Hospital.A large experiment dataset was also from this hospital,and most of this data was for training the convolutional neural network model.The experiment results were evaluated regarding sensitivity,specificity,and accuracy.We achieved high scores with a training accuracy score of 0.99,and the testing specificity and sensitivity scores were over 0.9.Based on the X-ray image classification result,we visualize prediction results as heat-maps and also analyze them in comparison with annotated symptoms of radiologists.
基金This research is funded by the project KC-4.0.14/19-25“Research on building a support system for diagnosis and prediction geo-spatial epidemiology of pulmonary tuberculosis by chest X-Ray images in Vietnam”.
文摘Deep learning created a sharp rise in the development of autonomous image recognition systems,especially in the case of the medical field.Among lung problems,tuberculosis,caused by a bacterium called Mycobacterium tuberculosis,is a dangerous disease because of its infection and damage.When an infected person coughs or sneezes,tiny droplets can bring pathogens to others through inhaling.Tuberculosis mainly damages the lungs,but it also affects any part of the body.Moreover,during the period of the COVID-19(coronavirus disease 2019)pandemic,the access to tuberculosis diagnosis and treatment has become more difficult,so early and simple detection of tuberculosis has been more and more important.In our study,we focused on tuberculosis diagnosis by using the chestX-ray image,the essential input for the radiologist’s profession,and researched the effectiveness of the transfer learning approach in the case study of Vietnamese chest X-ray images.We proposed four strategies to clarify our hypothesis in different ways of applying transfer learning and different training set types.We also prepared a Vietnamese X-ray image dataset with the support of the VRPACS team to provide the basis for training and testing deep learning models.Our experiments were carried out by applying three different architectures,Alexnet,Resnet,and Densenet,on international,Vietnamese,and combined X-ray image datasets.After training,all models were verified on a pure Vietnamese X-rays set.The results show that transfer learning is suitable in the case study of Vietnamese chest X-ray images with high evaluating metrics in terms of AUC(Area under the Receiver Operating Characteristic Curve),sensitivity,specificity,and accuracy.In the best strategy,most of the scores were more than 0.93,and all AUCs were more than 0.98.
基金funded by the Hanoi University of Science and Technology(HUST)under grant number T2018-PC-210.
文摘In recent years,speech synthesis systems have allowed for the produc-tion of very high-quality voices.Therefore,research in this domain is now turning to the problem of integrating emotions into speech.However,the method of con-structing a speech synthesizer for each emotion has some limitations.First,this method often requires an emotional-speech data set with many sentences.Such data sets are very time-intensive and labor-intensive to complete.Second,training each of these models requires computers with large computational capabilities and a lot of effort and time for model tuning.In addition,each model for each emotion failed to take advantage of data sets of other emotions.In this paper,we propose a new method to synthesize emotional speech in which the latent expressions of emotions are learned from a small data set of professional actors through a Flow-tron model.In addition,we provide a new method to build a speech corpus that is scalable and whose quality is easy to control.Next,to produce a high-quality speech synthesis model,we used this data set to train the Tacotron 2 model.We used it as a pre-trained model to train the Flowtron model.We applied this method to synthesize Vietnamese speech with sadness and happiness.Mean opi-nion score(MOS)assessment results show that MOS is 3.61 for sadness and 3.95 for happiness.In conclusion,the proposed method proves to be more effec-tive for a high degree of automation and fast emotional sentence generation,using a small emotional-speech data set.
文摘Our aim was to evaluate the quality of ejaculated and epididymal frozen-thawed pig sperm of endangered Vietnam native pig breeds. Ejaculated sperm was collected from live boars and epididymal sperm was collected from slaughtered boars of the MuongTe, Kieng Sat and Co BinhThuan breeds and frozen in 0.25 ml straws using a protocol established earlier for modern pig breeds. We evaluated the sperm quality after thawing in terms of motility and rates of viable and abnormal spermatozoa. Our results revealed that the sperm motility and rates of viable and abnormal frozen-thawed sperm were >30%, >44%, and <14%, respectively. The origin of sperm had an effect on the production of pig embryos in vitro. In the Co BinhThuan breed, ejaculated sperm generated higher cleavage, blastocyst and hatching rates than did the epididymal sperm (60.11% vs 56.02%, 17.23% vs 14.31%, 3.78% vs 2.34%, respectively, P < 0.05). Although no difference in cleavage rate, blastocyst formation rate and the average number of cells/blastocysts, the hatching blastocyst rate was different between the breeds (P > 0.05). In the Co BinhThuan breed, the rate of pregnancy of ejaculated groups was similar to that of the epididymal group. In conclusion, the ejaculated and epididymal sperm of native Vietnamese pigs were successfully frozen. We succeeded in creating embryos in vitro and pregnant pigs after artificial insemination from frozen-thawed semen in three native Vietnamese pig breeds for the first time. The use of the ejaculated sperm improved the production of native pig embryos in vitro efficiency.
