Researchers in several disciplines and fields agree that the image establishing has both perceptual and affecfive evaluations. The paper comparatively analyzes the image of landscapes in ancient water towns held by 16...Researchers in several disciplines and fields agree that the image establishing has both perceptual and affecfive evaluations. The paper comparatively analyzes the image of landscapes in ancient water towns held by 1619 tourists after the investigations of Zbouzhuang and Tongli of Jiangsu Province. Based on the elements of the image of urban landscapes, the perceptual/cognitive image of tourist landscapes in water towns is developed including path, node, landmark, important courtyard, district and edge. Particularly the important courtyard plays the great role on the perceptive image of tourists, however, the perceptual/cognitive images of the district and the edge are obviously weak. Meanwhile, the finding showed that the affective images of tourist landscapes in Zhonzhuang differ with those of Tongli by the method of paired comparison. The main reason is that the affective images are influenced by the impressive scenery spots. Furthermore, the commercialization of streets and pollution of rivers are easy to be functioned negatively.展开更多
Image captioning models typically operate with a fixed vocabulary,but captioning is an open-vocabulary problem.Existing work addresses the image captioning of out-of-vocabulary words by labeling it as unknown in a dic...Image captioning models typically operate with a fixed vocabulary,but captioning is an open-vocabulary problem.Existing work addresses the image captioning of out-of-vocabulary words by labeling it as unknown in a dictionary.In addition,recurrent neural network(RNN)and its variants used in the caption task have become a bottleneck for their generation quality and training time cost.To address these 2 essential problems,a simpler but more effective approach is proposed for generating open-vocabulary caption,long short-term memory(LSTM)unit is replaced with transformer as decoder for better caption quality and less training time.The effectiveness of different word segmentation vocabulary and generation improvement of transformer over LSTM is discussed and it is proved that the improved models achieve state-of-the-art performance for the MSCOCO2014 image captioning tasks over a back-off dictionary baseline model.展开更多
Breast pathology is varied, bringing together tumor and non-tumor lesions. Objective: To study the contribution of the ultrasound-mammography pair in the diagnosis of breast pathologies. Materials and Method: This was...Breast pathology is varied, bringing together tumor and non-tumor lesions. Objective: To study the contribution of the ultrasound-mammography pair in the diagnosis of breast pathologies. Materials and Method: This was a retrospective descriptive study, carried out over a period of 3 years (from January 2018 to December 2020) at the Diagnostic Imaging Center (C.I.D) “TERIYA” in BAMAKO. It concerned all patients who came for a mammogram/ultrasound examination of the breast. All women admitted for mammogram or breast ultrasound who were diagnosed with a breast injury during the study period were included. Incomplete records and radiological checks were not included. The variables analyzed were age, sex, clinical data, and ultrasound and mammography aspects. The devices used are: a Voluson 730 PRO ultrasound machine and a G 600T type mammography machine. Results: At the end of our study, we collected 254 breast pathologies on a number of 382 women, i.e. a frequency of 66.49%. The average age of our patients was 41 years old. The dominant clinical data were mastodynia (41.88%) and mammary nodule (21.70%). On imaging (mammo-ultrasound) the lesions predominated on the left in 36% of cases, bilateral in 28% of cases and in the upper-outer quadrants in 31.5% of cases. Tumor pathologies represented 66.54% of which 45.27% were benign mainly composed of fibro-adenoma (20.88%) and cyst (18.50%), 11.8% of suspected cases and 9.45% of cancers. Non-tumor pathologies represented 33.46%, mainly mastitis (16.14%), galactophoric dilations (11.02%) and abscesses (5.51%). These pathologies were classified in 50.3% in ACR2, 17.75% in ACR3 and 4, and in 14.20% in ACR5. Lymphadenopathy was present in 73.21% of cases.展开更多
基金Under the auspices of the National Natural Science Foundation of China (No. 40371030), Research Project of Ministry of Construction (No. 20031018)
文摘Researchers in several disciplines and fields agree that the image establishing has both perceptual and affecfive evaluations. The paper comparatively analyzes the image of landscapes in ancient water towns held by 1619 tourists after the investigations of Zbouzhuang and Tongli of Jiangsu Province. Based on the elements of the image of urban landscapes, the perceptual/cognitive image of tourist landscapes in water towns is developed including path, node, landmark, important courtyard, district and edge. Particularly the important courtyard plays the great role on the perceptive image of tourists, however, the perceptual/cognitive images of the district and the edge are obviously weak. Meanwhile, the finding showed that the affective images of tourist landscapes in Zhonzhuang differ with those of Tongli by the method of paired comparison. The main reason is that the affective images are influenced by the impressive scenery spots. Furthermore, the commercialization of streets and pollution of rivers are easy to be functioned negatively.
基金the National Natural Science Foundation of China(No.61877002)Beijing Municipal Commission of Education(PXM2019014213000007).
文摘Image captioning models typically operate with a fixed vocabulary,but captioning is an open-vocabulary problem.Existing work addresses the image captioning of out-of-vocabulary words by labeling it as unknown in a dictionary.In addition,recurrent neural network(RNN)and its variants used in the caption task have become a bottleneck for their generation quality and training time cost.To address these 2 essential problems,a simpler but more effective approach is proposed for generating open-vocabulary caption,long short-term memory(LSTM)unit is replaced with transformer as decoder for better caption quality and less training time.The effectiveness of different word segmentation vocabulary and generation improvement of transformer over LSTM is discussed and it is proved that the improved models achieve state-of-the-art performance for the MSCOCO2014 image captioning tasks over a back-off dictionary baseline model.
文摘Breast pathology is varied, bringing together tumor and non-tumor lesions. Objective: To study the contribution of the ultrasound-mammography pair in the diagnosis of breast pathologies. Materials and Method: This was a retrospective descriptive study, carried out over a period of 3 years (from January 2018 to December 2020) at the Diagnostic Imaging Center (C.I.D) “TERIYA” in BAMAKO. It concerned all patients who came for a mammogram/ultrasound examination of the breast. All women admitted for mammogram or breast ultrasound who were diagnosed with a breast injury during the study period were included. Incomplete records and radiological checks were not included. The variables analyzed were age, sex, clinical data, and ultrasound and mammography aspects. The devices used are: a Voluson 730 PRO ultrasound machine and a G 600T type mammography machine. Results: At the end of our study, we collected 254 breast pathologies on a number of 382 women, i.e. a frequency of 66.49%. The average age of our patients was 41 years old. The dominant clinical data were mastodynia (41.88%) and mammary nodule (21.70%). On imaging (mammo-ultrasound) the lesions predominated on the left in 36% of cases, bilateral in 28% of cases and in the upper-outer quadrants in 31.5% of cases. Tumor pathologies represented 66.54% of which 45.27% were benign mainly composed of fibro-adenoma (20.88%) and cyst (18.50%), 11.8% of suspected cases and 9.45% of cancers. Non-tumor pathologies represented 33.46%, mainly mastitis (16.14%), galactophoric dilations (11.02%) and abscesses (5.51%). These pathologies were classified in 50.3% in ACR2, 17.75% in ACR3 and 4, and in 14.20% in ACR5. Lymphadenopathy was present in 73.21% of cases.
