Spoken content retrieval and understanding using deep learning

Impact ◽  
2021 ◽  
Vol 2021 (1) ◽  
pp. 9-11
Author(s):  
Lin-shan Lee
Keyword(s):  
Deep Learning ◽  
Scientific Community ◽  
Online Courses ◽  
The Internet ◽  
Human Voice ◽  
Content Retrieval ◽  
Youtube Videos ◽  
Access Information ◽  
Teaching Machines

Spoken content refers to all content over the Internet which includes human voice, essentially those in multimedia, such As YouTube videos and online courses. Today such content is retrieved via Google primarily based on human-generated text labels, because Google can only retrieve text over the Internet. The goal of this project is to produce technologies to retrieve accurately and efficiently such spoken content directly based on the included audio sounds instead of text labels, because machines today can listen to human voice just as they can read the text. The long term goal is to create a spoken version of Google, which may revolutionize the ways in which humans access information and improve their knowledge. Professor Lin-shan Lee at National Taiwan University is leading this project. He has been a distinguished leader in the global scientific community for the area of teaching machines to speak and listen to human voice for many years.

Social Media, Surgeons, and the Internet: An Era or an Error?

2012 ◽  
Vol 78 (5) ◽  
pp. 555-558 ◽  
Author(s):  
Michelle C. Azu ◽  
Elizabeth J. Lilley ◽  
Aparna H. Kolli
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Care Setting ◽  
Primary Care Setting ◽  
The Internet ◽  
Research Corporation ◽  
Physician Rating ◽  
Access Information ◽  
The Impact

According to the National Research Corporation, 1 in 5 Americans use social media sites to obtain healthcare information. Patients can easily access information on medical conditions and medical professionals; however physicians may not be aware of the nature and impact of this information. All physicians must learn to use the Internet to their advantage and be acutely aware of the disadvantages. Surgeons are in a unique position because, unlike in the primary care setting, less time is spent developing a long-term relationship with the patient. In this literature review, we discuss the impact of the Internet, social networking websites, and physician rating websites and make recommendations for surgeons about managing digital identity and maintaining professionalism.

Cloud Computing in Library

2014 ◽  
Vol 3 ◽  
pp. 94-112
Author(s):  
Angelė Pečeliūnaitė
Keyword(s):  
Cloud Computing ◽  
Scientific Community ◽  
Digital Age ◽  
International Experience ◽  
The Internet ◽  
Library Services ◽  
General Activity ◽  
Computing Services ◽  
Cloud Computing Services

The article analyses the possibility of how Cloud Computing can be used by libraries to organise activities online. In order to achieve a uniform understanding of the essence of technology SaaS, IaaS, and PaaS, the article discusses the Cloud Computing services, which can be used for the relocation of libraries to the Internet. The improvement of the general activity of libraries in the digital age, the analysis of the international experience in the libraries are examples. Also the article discusses the results of a survey of the Lithuanian scientific community that confirms that 90% of the scientific community is in the interest of getting full access to e-publications online. It is concluded that the decrease in funding for libraries, Cloud Computing can be an economically beneficial step, expanding the library services and improving their quality.

Courting the Youth Vote in 2008: The Obama Effect

2009 ◽  
Vol 5 ◽  
Author(s):  
Lindsey C Bohl
Keyword(s):  
Presidential Elections ◽  
Voter Registration ◽  
The Internet ◽  
The Past ◽  
Several Variables ◽  
High Turnout ◽  
Short And Long Term ◽  
Use Of The Internet ◽  
Youth Vote

This paper examines a few of the numerous factors that may have led to increased youth turnout in 2008 Election. First, theories of voter behavior and turnout are related to courting the youth vote. Several variables that are perceived to affect youth turnout such as party polarization, perceived candidate difference, voter registration, effective campaigning and mobilization, and use of the Internet, are examined. Over the past 40 years, presidential elections have failed to engage the majority of young citizens (ages 18-29) to the point that they became inclined to participate. This trend began to reverse starting in 2000 Election and the youth turnout reached its peak in 2008. While both short and long-term factors played a significant role in recent elections, high turnout among youth voters in 2008 can be largely attributed to the Obama candidacy and campaign, which mobilized young citizens in unprecedented ways.

DIGITALIZATION OF LABOR MIGRATION PROCESSES IN UZBEKISTAN. WORLD EXPERIENCE

2020 ◽  
Vol 4 (3) ◽  
pp. 29-39
Author(s):  
Sulkhiya Gazieva ◽  
Keyword(s):  
Labor Market ◽  
Technological Change ◽  
Labor Migration ◽  
Smart Phone ◽  
Logic Circuits ◽  
Digital Logic ◽  
The Internet ◽  
The Future

The future of labor market depends upon several factors, long-term innovation and the demographic developments. However, one of the main drivers of technological change in the future is digitalization and central to this development is the production and use of digital logic circuits and its derived technologies, including the computer,the smart phone and the Internet. Especially, smart automation will perhaps not cause e.g.regarding industries, occupations, skills, tasks and duties

Teacher digital competence: bringing education to the next level

2020 ◽  
Vol 11 (1) ◽  
pp. 22-26
Author(s):  
S.V. Tsymbal ◽  
Keyword(s):  
Deep Learning ◽  
Learning Experiences ◽  
Digital Competence ◽  
Digital Revolution ◽  
Access Information ◽  
Set Up ◽  
Insight Into ◽  
The Way

The digital revolution has transformed the way people access information, communicate and learn. It is teachers' responsibility to set up environments and opportunities for deep learning experiences that can uncover and boost learners’ capacities. Twentyfirst century competences can be seen as necessary to navigate contemporary and future life, shaped by technology that changes workplaces and lifestyles. This study explores the concept of digital competence and provide insight into the European Framework for the Digital Competence of Educators.

Hydrogen Sulfide in Physiological and Pathological Mechanisms in Brain

2018 ◽  
Vol 17 (9) ◽  
pp. 654-670 ◽  
Author(s):  
Mohit Kumar ◽  
Rajat Sandhir
Keyword(s):  
Nitric Oxide ◽  
Traumatic Brain Injury ◽  
Hydrogen Sulfide ◽  
Neurodegenerative Disorders ◽  
Neurological Disorders ◽  
Scientific Community ◽  
Molecular Targets ◽  
Long Term Potentiation ◽  
Term Potentiation

Background & Objective: Hydrogen sulfide [H2S] has been widely known as a toxic gas for more than 300 years in the scientific community. However, the understanding about this small molecule has changed after the discovery of involvement of H2S in physiological and pathological mechanisms in brain. H2S is a third gasotransmitter and neuromodulator after carbon monoxide [CO] and nitric oxide [NO]. H2S plays an important role in memory and cognition by regulating long-term potentiation [LTP] and calcium homeostasis in neuronal cells. The disturbances in endogenous H2S levels and trans-sulfuration pathway have been implicated in neurodegenerative disorders like Alzheimer’s disease, Parkinson disease, stroke and traumatic brain injury. According to the results obtained from various studies, H2S not only behaves as neuromodulator but also is a potent antioxidant, anti-inflammatory and anti-apoptotic molecule suggesting its neuroprotective potential. Conclusion: Recently, there is an increased interest in developing H2S releasing pharmaceuticals to target various neurological disorders. This review covers the information about the involvement of H2S in neurodegenerative diseases, its molecular targets and its role as potential therapeutic molecule.

Update of the last 2 years on the impact of the internet and social networks on the management of type 2 diabetes mellitus: simple review. (Preprint)

2020 ◽  
Author(s):  
Mayli Lañas-Navarro ◽  
Jose Ipanaque-Calderon Sr ◽  
Fiorela E Solano
Keyword(s):  
Social Networks ◽  
Mobile Applications ◽  
Health Personnel ◽  
Online Courses ◽  
The Internet ◽  
Diabetic Patients ◽  
Bibliographic Search ◽  
Use Of The Internet ◽  
And Control ◽  
The Impact

BACKGROUND Research on the use of the Internet in the medical field is experiencing many advances, including mobile applications, social networks, telemedicine. Its implementation in medical care and comprehensive patient management is a much discussed topic at present. OBJECTIVE This narrative review aims to understand the impact of the internet and social networks on the management of diabetes, both for patients and medical staff. METHODS The bibliographic search was carried out in the databases Pubmed, Virtual Health Library (VHL) and Lilacs between 2018 to 2020. RESULTS Multiple mobile applications have been created for the help and control of diabetic patients, as well as the implementation of online courses, improving the knowledge of health personnel applying them in the field of telemedicine. CONCLUSIONS The use of the Internet and social networks brings many benefits for both the diabetic patient and the health personnel, offering advantages for both.

scholarly journals The role and uses of antibodies in COVID-19 infections: a living review

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
D Oliver Scourfield ◽  
Sophie G Reed ◽  
Max Quastel ◽  
Jennifer Alderson ◽  
Valentina M T Bart ◽  
...  
Keyword(s):  
Infection Control ◽  
Specific Antibody ◽  
Scientific Community ◽  
Vaccine Candidates ◽  
Therapeutic Uses ◽  
Humoral Responses

Abstract Coronavirus disease 2019 has generated a rapidly evolving field of research, with the global scientific community striving for solutions to the current pandemic. Characterizing humoral responses towards SARS-CoV-2, as well as closely related strains, will help determine whether antibodies are central to infection control, and aid the design of therapeutics and vaccine candidates. This review outlines the major aspects of SARS-CoV-2-specific antibody research to date, with a focus on the various prophylactic and therapeutic uses of antibodies to alleviate disease in addition to the potential of cross-reactive therapies and the implications of long-term immunity.

scholarly journals Domain randomization-enhanced deep learning models for bird detection

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xin Mao ◽  
Jun Kang Chow ◽  
Pin Siang Tan ◽  
Kuan-fu Liu ◽  
Jimmy Wu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Continuous Monitoring ◽  
Bird Species ◽  
Training Data ◽  
Learning Models ◽  
Fine Grained ◽  
Bird Detection ◽  
Relationship Of ◽  
The Relationship

AbstractAutomatic bird detection in ornithological analyses is limited by the accuracy of existing models, due to the lack of training data and the difficulties in extracting the fine-grained features required to distinguish bird species. Here we apply the domain randomization strategy to enhance the accuracy of the deep learning models in bird detection. Trained with virtual birds of sufficient variations in different environments, the model tends to focus on the fine-grained features of birds and achieves higher accuracies. Based on the 100 terabytes of 2-month continuous monitoring data of egrets, our results cover the findings using conventional manual observations, e.g., vertical stratification of egrets according to body size, and also open up opportunities of long-term bird surveys requiring intensive monitoring that is impractical using conventional methods, e.g., the weather influences on egrets, and the relationship of the migration schedules between the great egrets and little egrets.

scholarly journals Long-Term Data Traffic Forecasting for Network Dimensioning in LTE with Short Time Series

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1151
Author(s):  
Carolina Gijón ◽  
Matías Toril ◽  
Salvador Luna-Ramírez ◽  
María Luisa Marí-Altozano ◽  
José María Ruiz-Avilés
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Time Series Analysis ◽  
Data Traffic ◽  
Medium Term ◽  
Short Term ◽  
Traffic Forecasting ◽  
Series Analysis ◽  
Radio Planning

Network dimensioning is a critical task in current mobile networks, as any failure in this process leads to degraded user experience or unnecessary upgrades of network resources. For this purpose, radio planning tools often predict monthly busy-hour data traffic to detect capacity bottlenecks in advance. Supervised Learning (SL) arises as a promising solution to improve predictions obtained with legacy approaches. Previous works have shown that deep learning outperforms classical time series analysis when predicting data traffic in cellular networks in the short term (seconds/minutes) and medium term (hours/days) from long historical data series. However, long-term forecasting (several months horizon) performed in radio planning tools relies on short and noisy time series, thus requiring a separate analysis. In this work, we present the first study comparing SL and time series analysis approaches to predict monthly busy-hour data traffic on a cell basis in a live LTE network. To this end, an extensive dataset is collected, comprising data traffic per cell for a whole country during 30 months. The considered methods include Random Forest, different Neural Networks, Support Vector Regression, Seasonal Auto Regressive Integrated Moving Average and Additive Holt–Winters. Results show that SL models outperform time series approaches, while reducing data storage capacity requirements. More importantly, unlike in short-term and medium-term traffic forecasting, non-deep SL approaches are competitive with deep learning while being more computationally efficient.

Sign in / Sign up

Export Citation Format

Share Document