Research and Realization Based on Content Video Retrieval

2011 ◽  
Vol 55-57 ◽  
pp. 2163-2168
Author(s):  
Li Wei Chen ◽  
Yong Li Gao
Keyword(s):  
Large Scale ◽  
Video Retrieval ◽  
Technological Development ◽  
Rapid Development ◽  
Widespread Application ◽  
Frame Selection ◽  
Video Frequency

Along with the multimedia technological development and the large-scale database widespread application, the content video retrieval technology obtains the rapid development, at the same time, the algorithms were also proposed. This article has carried on the induction summary to these new theory technologies based on the content video retrieval demonstration system. This article first introduced based on the content video retrieval essential technology including regards the lens the boundary examination and the division, the essential frame selection the characteristic withdraws, the similar match and the video frequency gathers the kind and so on. Simultaneously provided video frequency retrieval essential technology some algorithms,and carried on the summary regarding the recent years based on the content.

scholarly journals High-Rate Transition Metal-based Cathode Materials for Battery-Supercapacitor Hybrid Devices

2021 ◽  
Author(s):  
Cong Wang ◽  
Zehao Song ◽  
Pei Shi ◽  
Lin Lv ◽  
Houzhao Wan ◽  
...  
Keyword(s):  
Large Scale ◽  
Rapid Development ◽  
Electronic Devices ◽  
High Rate ◽  
Specific Power ◽  
Energy Storage Devices ◽  
Storage Devices ◽  
Electrochemical Devices ◽  
Hybrid Devices ◽  
Scale Grid

With the rapid development of portable electronic devices, electric vehicles and large-scale grid energy storage devices, it needs to reinforce specific energy and specific power of related electrochemical devices meeting...

scholarly journals High-Throughput Phenotyping Methods for Breeding Drought-Tolerant Crops

2021 ◽  
Vol 22 (15) ◽  
pp. 8266
Author(s):  
Minsu Kim ◽  
Chaewon Lee ◽  
Subin Hong ◽  
Song Lim Kim ◽  
Jeong-Ho Baek ◽  
...  
Keyword(s):  
Drought Stress ◽  
High Throughput ◽  
Large Scale ◽  
Crop Yields ◽  
Plant Traits ◽  
Rapid Development ◽  
Plant Responses ◽  
Phenotypic Data ◽  
Agricultural Technologies ◽  
High Throughput Phenotyping

Drought is a main factor limiting crop yields. Modern agricultural technologies such as irrigation systems, ground mulching, and rainwater storage can prevent drought, but these are only temporary solutions. Understanding the physiological, biochemical, and molecular reactions of plants to drought stress is therefore urgent. The recent rapid development of genomics tools has led to an increasing interest in phenomics, i.e., the study of phenotypic plant traits. Among phenomic strategies, high-throughput phenotyping (HTP) is attracting increasing attention as a way to address the bottlenecks of genomic and phenomic studies. HTP provides researchers a non-destructive and non-invasive method yet accurate in analyzing large-scale phenotypic data. This review describes plant responses to drought stress and introduces HTP methods that can detect changes in plant phenotypes in response to drought.

scholarly journals Cloud-based intelligent self-diagnosis and department recommendation service using Chinese medical BERT

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Junshu Wang ◽  
Guoming Zhang ◽  
Wei Wang ◽  
Ka Zhang ◽  
Yehua Sheng
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Medical Service ◽  
Rapid Development ◽  
Medical Knowledge ◽  
Language Models ◽  
Computing Environment ◽  
Computing Power ◽  
Cloud Computing Environment ◽  
Proposed Model

AbstractWith the rapid development of hospital informatization and Internet medical service in recent years, most hospitals have launched online hospital appointment registration systems to remove patient queues and improve the efficiency of medical services. However, most of the patients lack professional medical knowledge and have no idea of how to choose department when registering. To instruct the patients to seek medical care and register effectively, we proposed CIDRS, an intelligent self-diagnosis and department recommendation framework based on Chinese medical Bidirectional Encoder Representations from Transformers (BERT) in the cloud computing environment. We also established a Chinese BERT model (CHMBERT) trained on a large-scale Chinese medical text corpus. This model was used to optimize self-diagnosis and department recommendation tasks. To solve the limited computing power of terminals, we deployed the proposed framework in a cloud computing environment based on container and micro-service technologies. Real-world medical datasets from hospitals were used in the experiments, and results showed that the proposed model was superior to the traditional deep learning models and other pre-trained language models in terms of performance.

scholarly journals Large-Scale Video Retrieval via Deep Local Convolutional Features

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Chen Zhang ◽  
Bin Hu ◽  
Yucong Suo ◽  
Zhiqiang Zou ◽  
Yimu Ji
Keyword(s):  
Large Scale ◽  
Video Retrieval ◽  
Video Data ◽  
Query Image ◽  
Key Frame Extraction ◽  
Key Frame ◽  
Storage Cost ◽  
Extraction Algorithm ◽  
Feature Aggregation ◽  
And Storage

In this paper, we study the challenge of image-to-video retrieval, which uses the query image to search relevant frames from a large collection of videos. A novel framework based on convolutional neural networks (CNNs) is proposed to perform large-scale video retrieval with low storage cost and high search efficiency. Our framework consists of the key-frame extraction algorithm and the feature aggregation strategy. Specifically, the key-frame extraction algorithm takes advantage of the clustering idea so that redundant information is removed in video data and storage cost is greatly reduced. The feature aggregation strategy adopts average pooling to encode deep local convolutional features followed by coarse-to-fine retrieval, which allows rapid retrieval in the large-scale video database. The results from extensive experiments on two publicly available datasets demonstrate that the proposed method achieves superior efficiency as well as accuracy over other state-of-the-art visual search methods.

Prospects for Cooperation Between Russia and the Republic of Korea in the Fields of Big Data, Network and Artificial Intelligence for the Development of the Digital Economy

2021 ◽  
Vol 65 (8) ◽  
pp. 51-60
Author(s):  
Yujeong Kim
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Large Scale ◽  
Technology Development ◽  
Technological Development ◽  
Digital Economy ◽  
Republic Of Korea ◽  
Data Network ◽  
Leading Position ◽  
The Government

Today, each country has interest in digital economy and has established and implemented policies aimed at digital technology development and digital transformation for the transition to the digital economy. In particular, interest in digital technologies such as big data, 5G, and artificial intelligence, which are recognized as important factors in the digital economy, has been increasing recently, and it is a time when the role of the government for technological development and international cooperation becomes important. In addition to the overall digital economic policy, the Russian and Korean governments are also trying to improve their international competitiveness and take a leading position in the new economic order by establishing related technical and industrial policies. Moreover, Republic of Korea often refers to data, network and artificial intelligence as D∙N∙A, and has established policies in each of these areas in 2019. Russia is also establishing and implementing policies in the same field in 2019. Therefore, it is timely to find ways to expand cooperation between Russia and Republic of Korea. In particular, the years of 2020and 2021marks the 30th anniversary of diplomatic relations between the two countries, and not only large-scale events and exchange programs have prepared, but the relationship is deepening as part of the continued foreign policy of both countries – Russia’s Eastern Policy and New Northern Policy of Republic of Korea. Therefore, this paper compares and analyzes the policies of the two countries in big data, 5G, and artificial intelligence to seek long-term sustainable cooperation in the digital economy.

scholarly journals Differential Regulatory Analysis Based on Coexpression Network in Cancer Research

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Junyi Li ◽  
Yi-Xue Li ◽  
Yuan-Yuan Li
Keyword(s):  
Cancer Research ◽  
Large Scale ◽  
Rapid Development ◽  
Differential Expression Analysis ◽  
Coexpression Network ◽  
Differential Analysis ◽  
Integrative Research ◽  
Research Fields ◽  
System Properties ◽  
Regulatory Analysis

With rapid development of high-throughput techniques and accumulation of big transcriptomic data, plenty of computational methods and algorithms such as differential analysis and network analysis have been proposed to explore genome-wide gene expression characteristics. These efforts are aiming to transform underlying genomic information into valuable knowledges in biological and medical research fields. Recently, tremendous integrative research methods are dedicated to interpret the development and progress of neoplastic diseases, whereas differential regulatory analysis (DRA) based on gene coexpression network (GCN) increasingly plays a robust complement to regular differential expression analysis in revealing regulatory functions of cancer related genes such as evading growth suppressors and resisting cell death. Differential regulatory analysis based on GCN is prospective and shows its essential role in discovering the system properties of carcinogenesis features. Here we briefly review the paradigm of differential regulatory analysis based on GCN. We also focus on the applications of differential regulatory analysis based on GCN in cancer research and point out that DRA is necessary and extraordinary to reveal underlying molecular mechanism in large-scale carcinogenesis studies.

The long-term development of Russian biotech sector

foresight ◽  
2017 ◽  
Vol 19 (5) ◽  
pp. 491-500 ◽  
Author(s):  
Anna Grebenyuk ◽  
Nikolai Ravin
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Technological Development ◽  
Science And Technology ◽  
Plant Biotechnology ◽  
High Tech ◽  
Content Type ◽  
Research Areas ◽  
Research Activities ◽  
The Usa

Purpose To define strategic directions for the Russia’s social, economic, scientific and technological development in 2011-2013, a large-scale foresight study including the deep analysis of prospects of biotechnology development there was undertaken (Russia 2030: Science and Technology Foresight). This paper aims to present results of this research. Design/methodology/approach The study was based on a combination of technology-push and market-pull approaches that aimed not only to identify most promising science and technology (S&T) areas but also to understand how they can be realized in practice. Representatives from federal authorities, science and business were involved in the project to create future visions of technological directions; analyze grand challenges, weak signals and wild cards; and set research and development (R&D) priorities. Findings According to results of the study, Russia has a potential for biotech sector development, although the level of R&D in the majority of areas is lagging behind that in the USA and leading EU countries. However, there are several advanced applied research areas where efforts can be focused. Among them are high-performance genomics and post-genomics research platforms, systems and structural biology, microbial metabolic engineering, plant biotechnology and microbial strains and consortia for development of symbiotic plant–microbial communities. Originality/value Concentration of available resources of government and business on biotechnological sector development can help to find answers for challenges that Russia faces today or will face tomorrow. It will help to pick up on the current level of research activities, improve the quality of personnel training, make this area the engine of the economy and carry out the so-called new industrialization of the country, building a new, high-tech device industry.

scholarly journals SCIENTIFIC AND TECHNOLOGICAL DEVELOPMENT AS A FACTOR OF ACCELERATING ECONOMIC GROWTH IN RUSSIA

2021 ◽  
Vol 230 (4) ◽  
pp. 237-244
Author(s):  
E.B. LENCHUK ◽  
Keyword(s):  
Economic Growth ◽  
World Economy ◽  
Large Scale ◽  
Industrial Revolution ◽  
Technological Development ◽  
Technological Basis ◽  
Fourth Industrial Revolution ◽  
The World ◽  
Sustainable Economic Growth ◽  
Scientific And Technological Development

The article deals with the modern processes of changing the technological basis of the world economy on the basis of large-scale transition to the use of technologies of the fourth industrial revolution, shaping new markets and opens up prospects for sustainable economic growth. It is in the scientific and technological sphere that the competition between countries is shifting. Russia remains nearly invisible player in this field. The author tried to consider the main reasons for such a lag and identify a set of measures of state scientific and technological policy that can give the necessary impetus to the scientific and technological development of Russia.

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