Disambiguation of Chinese Polyphones in an End-to-End Framework with Semantic Features Extracted by Pre-Trained BERT

2019 ◽  
Author(s):  
Dongyang Dai ◽  
Zhiyong Wu ◽  
Shiyin Kang ◽  
Xixin Wu ◽  
Jia Jia ◽  
...  
Keyword(s):  
Semantic Features ◽  
End To End

scholarly journals STRUCTURAL AND SEMANTIC FEATURES OF THE TITLE COMPLEX AND ILLUSTRATIVE MATERIAL OF A. VARLAMOV’S BOOK «ALEXEY TOLSTOY»

2020 ◽  
pp. 111-116
Author(s):  
Людмила Николаевна Скаковская
Keyword(s):  
Title Complex ◽  
Main Theme ◽  
Semantic Features ◽  
Original Title ◽  
Literary Portraits ◽  
End To End ◽  
Relationship Of ◽  
Internal Relationship ◽  
Illustrative Material

Потенциал паратекста книг серии «ЖЗЛ» А.Н. Варламова представляется очень важным не только вследствие репрезентационного расширения и рецепционного углубления этих произведений, но и определения внутренней взаимосвязи конкретных литературных портретов. В случае «Алексея Толстого» паратекст выполняет сквозную функцию, то есть его элементы раскрываются на протяжении всего произведения (исходное заглавие, подписи к фото и др.) и связаны с основной темой. The potential of the paratext of the books in the «LWP» series by A.N. Varlamov is very important not only because of the representational expansion and receptive deepening of these works, but also determines the internal relationship of specific literary portraits. In the case of Alexey Tolstoy, the paratext performs an end-to-end function, i.e. its elements are revealed throughout the work (the original title, photo captions, etc.) and are related to the main theme.

scholarly journals Zero-Shot Image Classification Based on a Learnable Deep Metric

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3241
Author(s):  
Jingyi Liu ◽  
Caijuan Shi ◽  
Dongjing Tu ◽  
Ze Shi ◽  
Yazhi Liu
Keyword(s):  
Image Classification ◽  
Euclidean Distance ◽  
Similarity Score ◽  
Visual Features ◽  
Semantic Features ◽  
Common Space ◽  
Training Samples ◽  
Mapping Process ◽  
The Common ◽  
End To End

The supervised model based on deep learning has made great achievements in the field of image classification after training with a large number of labeled samples. However, there are many categories without or only with a few labeled training samples in practice, and some categories even have no training samples at all. The proposed zero-shot learning greatly reduces the dependence on labeled training samples for image classification models. Nevertheless, there are limitations in learning the similarity of visual features and semantic features with a predefined fixed metric (e.g., as Euclidean distance), as well as the problem of semantic gap in the mapping process. To address these problems, a new zero-shot image classification method based on an end-to-end learnable deep metric is proposed in this paper. First, the common space embedding is adopted to map the visual features and semantic features into a common space. Second, an end-to-end learnable deep metric, that is, the relation network is utilized to learn the similarity of visual features and semantic features. Finally, the invisible images are classified, according to the similarity score. Extensive experiments are carried out on four datasets and the results indicate the effectiveness of the proposed method.

scholarly journals An end-to-end text spotter with text relation networks

Cybersecurity ◽  
2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Jianguo Jiang ◽  
Baole Wei ◽  
Min Yu ◽  
Gang Li ◽  
Boquan Li ◽  
...  
Keyword(s):  
Semantic Information ◽  
Research Topic ◽  
Semantic Features ◽  
Research Attention ◽  
Convolution Operation ◽  
Scene Text ◽  
Significant Research ◽  
Reading Text ◽  
End To End ◽  
Relationship Of

AbstractReading text in images automatically has become an attractive research topic in computer vision. Specifically, end-to-end spotting of scene text has attracted significant research attention, and relatively ideal accuracy has been achieved on several datasets. However, most of the existing works overlooked the semantic connection between the scene text instances, and had limitations in situations such as occlusion, blurring, and unseen characters, which result in some semantic information lost in the text regions. The relevance between texts generally lies in the scene images. From the perspective of cognitive psychology, humans often combine the nearby easy-to-recognize texts to infer the unidentifiable text. In this paper, we propose a novel graph-based method for intermediate semantic features enhancement, called Text Relation Networks. Specifically, we model the co-occurrence relationship of scene texts as a graph. The nodes in the graph represent the text instances in a scene image, and the corresponding semantic features are defined as representations of the nodes. The relative positions between text instances are measured as the weights of edges in the established graph. Then, a convolution operation is performed on the graph to aggregate semantic information and enhance the intermediate features corresponding to text instances. We evaluate the proposed method through comprehensive experiments on several mainstream benchmarks, and get highly competitive results. For example, on the , our method surpasses the previous top works by 2.1% on the word spotting task.

scholarly journals End-to-end automatic differentiation of the coronavirus disease 2019 (COVID-19) from viral pneumonia based on chest CT

2020 ◽  
Vol 47 (11) ◽  
pp. 2516-2524 ◽  
Author(s):  
Jiangdian Song ◽  
Hongmei Wang ◽  
Yuchan Liu ◽  
Wenqing Wu ◽  
Gang Dai ◽  
...  
Keyword(s):  
Real Time ◽  
Automatic Differentiation ◽  
External Validation ◽  
Ct Images ◽  
Chest Ct ◽  
Viral Pneumonia ◽  
Semantic Features ◽  
Rt Pcr ◽  
Linear Classifier ◽  
End To End

Abstract Purpose In the absence of a virus nucleic acid real-time reverse transcriptase-polymerase chain reaction (RT-PCR) test and experienced radiologists, clinical diagnosis is challenging for viral pneumonia with clinical symptoms and CT signs similar to that of coronavirus disease 2019 (COVID-19). We developed an end-to-end automatic differentiation method based on CT images to identify COVID-19 pneumonia patients in real time. Methods From January 18 to February 23, 2020, we conducted a retrospective study and enrolled 201 patients from two hospitals in China who underwent chest CT and RT-PCR tests, of which 98 patients tested positive for COVID-19 (118 males and 83 females, with an average age of 42 years). Patient CT images from one hospital were divided among training, validation and test datasets with an 80%:10%:10% ratio. An end-to-end representation learning method using a large-scale bi-directional generative adversarial network (BigBiGAN) architecture was designed to extract semantic features from the CT images. The semantic feature matrix was input for linear classifier construction. Patients from the other hospital were used for external validation. Differentiation accuracy was evaluated using a receiver operating characteristic curve. Results Based on the 120-dimensional semantic features extracted by BigBiGAN from each image, the linear classifier results indicated that the area under the curve (AUC) in the training, validation and test datasets were 0.979, 0.968 and 0.972, respectively, with an average sensitivity of 92% and specificity of 91%. The AUC for external validation was 0.850, with a sensitivity of 80% and specificity of 75%. Publicly available architecture and computing resources were used throughout the study to ensure reproducibility. Conclusion This study provides an efficient recognition method for coronavirus disease 2019 pneumonia, using an end-to-end design to implement targeted and effective isolation for the containment of this communicable disease.

Surgical management of extracranial carotid artery aneurysms

VASA ◽  
2016 ◽  
Vol 45 (3) ◽  
pp. 223-228 ◽  
Author(s):  
Jan Paweł Skóra ◽  
Jacek Kurcz ◽  
Krzysztof Korta ◽  
Przemysław Szyber ◽  
Tadeusz Andrzej Dorobisz ◽  
...  
Keyword(s):  
Carotid Artery ◽  
Surgical Management ◽  
Minor Stroke ◽  
Stroke Rate ◽  
Extracranial Carotid Artery ◽  
Long Term Follow Up ◽  
End To End ◽  
Dacron Patch ◽  
Major Stroke

Abstract. Background: We present the methods and results of the surgical management of extracranial carotid artery aneurysms (ECCA). Postoperative complications including early and late neurological events were analysed. Correlation between reconstruction techniques and morphology of ECCA was assessed in this retrospective study. Patients and methods: In total, 32 reconstructions of ECCA were performed in 31 symptomatic patients with a mean age of 59.2 (range 33 - 84) years. The causes of ECCA were divided among atherosclerosis (n = 25; 78.1 %), previous carotid endarterectomy with Dacron patch (n = 4; 12.5 %), iatrogenic injury (n = 2; 6.3 %) and infection (n = 1; 3.1 %). In 23 cases, intervention consisted of carotid bypass. Aneurysmectomy with end-to-end suture was performed in 4 cases. Aneurysmal resection with patching was done in 2 cases and aneurysmorrhaphy without patching in another 2 cases. In 1 case, ligature of the internal carotid artery (ICA) was required. Results: Technical success defined as the preservation of ICA patency was achieved in 31 cases (96.9 %). There was one perioperative death due to major stroke (3.1 %). Two cases of minor stroke occurred in the 30-day observation period (6.3 %). Three patients had a transient hypoglossal nerve palsy that subsided spontaneously (9.4 %). At a mean long-term follow-up of 68 months, there were no major or minor ipsilateral strokes or surgery-related deaths reported. In all 30 surviving patients (96.9 %), long-term clinical outcomes were free from ipsilateral neurological symptoms. Conclusions: Open surgery is a relatively safe method in the therapy of ECCA. Surgical repair of ECCAs can be associated with an acceptable major stroke rate and moderate minor stroke rate. Complication-free long-term outcomes can be achieved in as many as 96.9 % of patients. Aneurysmectomy with end-to-end anastomosis or bypass surgery can be implemented during open repair of ECCA.

Reliability of the Mangled Extremity Severity Score in the Management of Peripheral Vascular Injuries in Children: A Retrospective Review

2020 ◽  
Author(s):  
Ahmed Mousa ◽  
Ossama M. Zakaria ◽  
Mai A. Elkalla ◽  
Lotfy A. Abdelsattar ◽  
Hamad Al-Game'a
Keyword(s):  
Severity Score ◽  
Vein Graft ◽  
Bypass Surgery ◽  
Age Groups ◽  
Vascular Injuries ◽  
Peripheral Vascular ◽  
Group Iii ◽  
Mangled Extremity ◽  
Group I ◽  
End To End

AbstractThis study was aimed to evaluate different management modalities for peripheral vascular trauma in children, with the aid of the Mangled Extremity Severity Score (MESS). A single-center retrospective analysis took place between 2010 and 2017 at University Hospitals, having emergencies and critical care centers. Different types of vascular repair were adopted by skillful vascular experts and highly trained pediatric surgeons. Patients were divided into three different age groups. Group I included those children between 5 and 10 years; group II involved pediatrics between 11 and 15 years; while children between 16 and 21 years participated in group III. We recruited 183 children with peripheral vascular injuries. They were 87% males and 13% females, with the mean age of 14.72 ± 04. Arteriorrhaphy was performed in 32%; end-to-end anastomosis and natural vein graft were adopted in 40.5 and 49%, respectively. On the other hand, 10.5% underwent bypass surgery. The age groups I and II are highly susceptible to penetrating trauma (p = 0.001), while patients with an extreme age (i.e., group III) are more susceptible to blunt injury (p = 0.001). The MESS has a significant correlation to both age groups I and II (p = 0.001). Vein patch angioplasty and end-to-end primary repair should be adopted as the main treatment options for the repair of extremity vascular injuries in children. Moreover, other treatment modalities, such as repair with autologous vein graft/bypass surgery, may be adopted whenever possible. They are cost-effective, reliable, and simple techniques with fewer postoperative complication, especially in poor/limited resources.

WS-Security on PRODML

2014 ◽  
Vol 1 (1) ◽  
pp. 9-34
Author(s):  
Bobby Suryajaya
Keyword(s):  
Web Services ◽  
Digital Signature ◽  
Data Transfer ◽  
Web Services Security ◽  
Soap Message ◽  
Simulation Results ◽  
End To End

SKK Migas plans to apply end-to-end security based on Web Services Security (WS-Security) for Sistem Operasi Terpadu (SOT). However, there are no prototype or simulation results that can support the plan that has already been communicated to many parties. This paper proposes an experiment that performs PRODML data transfer using WS-Security by altering the WSDL to include encryption and digital signature. The experiment utilizes SoapUI, and successfully loaded PRODML WSDL that had been altered with WSP-Policy based on X.509 to transfer a SOAP message.

Mit MindSphere die digitale Transformation vorantreiben

Controlling ◽  
2019 ◽  
Vol 31 (6) ◽  
pp. 63-65
Author(s):  
Carsten Speckmann ◽  
Péter Horváth
Keyword(s):  
Digitale Transformation ◽  
Internet Der Dinge ◽  
End To End

MindSphere ist das cloudbasierte, offene IoT-Betriebssystem von Siemens. Es verbindet Produkte, Anlagen, Systeme und Maschinen und ermöglicht es so, die Fülle von Daten aus dem Internet der Dinge (IoT) mit umfangreichen Analysen zu nutzen. Als eine sichere, skalierbare End-to-End-Lösung für die Industrie sorgt MindSphere für die Konnektivität von Anlagen und liefert somit handlungsrelevante Geschäftserkenntnisse, die zur Steigerung der Produktivität und Effizienz im gesamten Unternehmen nutzbar gemacht werden können. MindSphere ist weltweit verfügbar.

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