Statistical modeling of the Internet traffic dynamics: To which extent do we need long-term correlations?

2017 ◽  
Vol 485 ◽  
pp. 48-60 ◽  
Author(s):  
Oleg Markelov ◽  
Viet Nguyen Duc ◽  
Mikhail Bogachev
Keyword(s):  
Statistical Modeling ◽  
Internet Traffic ◽  
The Internet ◽  
Traffic Dynamics

Universal model for collective access patterns in the Internet traffic dynamics: A superstatistical approach

2016 ◽  
Vol 115 (1) ◽  
pp. 10008 ◽  
Author(s):  
A. Tamazian ◽  
V. D. Nguyen ◽  
O. A. Markelov ◽  
M. I. Bogachev
Keyword(s):  
Internet Traffic ◽  
The Internet ◽  
Universal Model ◽  
Traffic Dynamics ◽  
Access Patterns

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

MODERN LINGUODIDACTICS AND MNEMONICS: FROM THE EXPERIENCE OF TEACHING STUDENTS HOW TO MEMORIZE NEW VOCABULARY

2021 ◽  
pp. 109-119
Author(s):  
Tat’yana A. Markelova ◽  
Keyword(s):  
Foreign Language ◽  
Personal Development ◽  
Practical Experience ◽  
Foreign Languages ◽  
Visual Images ◽  
The Internet ◽  
English Classes ◽  
False Idea ◽  
Mnemonic Techniques

The paper deals with the search and application of effective methods of memorizing foreign language vocabulary, based on integrative and personal development approaches within the framework of modern linguodidactics. The Internet era, which maximally simplifies the process of searching for and translating foreign words, engender among students a false idea that there is no need to form special skills of memorizing foreign language vocabulary. In this regard, the development of new ways how to activate memory for educational purposes is of particular relevance, as well as the study of such mental processes of memory as memorizing, preserving, reproducing and forgetting. The author refers to some aspects of linguodidactics’ and mnemonics’ historical evolution, foreign and Russian experience of using mnemonic techniques in the process of studying and teaching foreign languages. Memorizing based on mnemonic encoding into images (when objects are linked with existing information in the memory) contributes to the process of mastering foreign language vocabulary, it becomes faster and easier, and it results in a long-term memorization of the material. In the paper, the author shares the practical experience of applying and teaching mnemonic techniques at English classes. The latter include phonetic associations, visual images, pictures, kinesthetic representations. In conclusion, the author makes an inference that it is advisable to teach students the technique of mnemonics as one of the effective ways to facilitate the process of memorizing new vocabulary.

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.

From Users’ Intentions to IF-THEN Rules in the Internet of Things

2021 ◽  
Vol 39 (4) ◽  
pp. 1-33
Author(s):  
Fulvio Corno ◽  
Luigi De Russis ◽  
Alberto Monge Roffarello
Keyword(s):  
Internet Of Things ◽  
Smart Devices ◽  
The Internet ◽  
Short Term ◽  
Real World Data ◽  
Original Intention ◽  
Recommendation Accuracy ◽  
High Level ◽  
The Internet Of Things

In the Internet of Things era, users are willing to personalize the joint behavior of their connected entities, i.e., smart devices and online service, by means of trigger-action rules such as “IF the entrance Nest security camera detects a movement, THEN blink the Philips Hue lamp in the kitchen.” Unfortunately, the spread of new supported technologies makes the number of possible combinations between triggers and actions continuously growing, thus motivating the need of assisting users in discovering new rules and functionality, e.g., through recommendation techniques. To this end, we present , a semantic Conversational Search and Recommendation (CSR) system able to suggest pertinent IF-THEN rules that can be easily deployed in different contexts starting from an abstract user’s need. By exploiting a conversational agent, the user can communicate her current personalization intention by specifying a set of functionality at a high level, e.g., to decrease the temperature of a room when she left it. Stemming from this input, implements a semantic recommendation process that takes into account ( a ) the current user’s intention , ( b ) the connected entities owned by the user, and ( c ) the user’s long-term preferences revealed by her profile. If not satisfied with the suggestions, then the user can converse with the system to provide further feedback, i.e., a short-term preference , thus allowing to provide refined recommendations that better align with the original intention. We evaluate by running different offline experiments with simulated users and real-world data. First, we test the recommendation process in different configurations, and we show that recommendation accuracy and similarity with target items increase as the interaction between the algorithm and the user proceeds. Then, we compare with other similar baseline recommender systems. Results are promising and demonstrate the effectiveness of in recommending IF-THEN rules that satisfy the current personalization intention of the user.

PANDORA: Providing Long Term Access to Australia's Online Electronic Publications

1998 ◽  
Vol 10 (1) ◽  
pp. 63-75 ◽  
Author(s):  
Wendy Smith
Keyword(s):  
World Wide Web ◽  
World Wide ◽  
The Internet ◽  
Online Environment ◽  
National Library ◽  
Policies And Procedures ◽  
Electronic Publications ◽  
Set Up ◽  
Printed Materials

The Internet, particularly through the application of World Wide Web (WWW) technology, has proved to be a very attractive medium for publishing. However, the difficulties of finding appropriate information online and then of ensuring its long term accessibility have created problems for libraries. Practices that work for books and other printed materials do not always translate directly to online materials. The National Library of Australia's PANDORA project has been set up to develop policies and procedures for ensuring long term access to significant Australian publications which are accessible only in an online environment, and to establish and maintain a permanent archive ofthat material.

scholarly journals A Statistical Modeling Methodology for Long-Term Wind Generation and Power Ramp Simulations in New Generation Locations

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2442 ◽  
Author(s):  
Jussi Ekström ◽  
Matti Koivisto ◽  
Ilkka Mellin ◽  
Robert Millar ◽  
Matti Lehtonen
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Statistical Modeling ◽  
Renewable Energy Sources ◽  
Measurement Data ◽  
Wind Power Generation ◽  
System Level ◽  
Wind Generation ◽  
The Impact

In future power systems, a large share of the energy will be generated with wind power plants (WPPs) and other renewable energy sources. With the increasing wind power penetration, the variability of the net generation in the system increases. Consequently, it is imperative to be able to assess and model the behavior of the WPP generation in detail. This paper presents an improved methodology for the detailed statistical modeling of wind power generation from multiple new WPPs without measurement data. A vector autoregressive based methodology, which can be applied to long-term Monte Carlo simulations of existing and new WPPs, is proposed. The proposed model improves the performance of the existing methodology and can more accurately analyze the temporal correlation structure of aggregated wind generation at the system level. This enables the model to assess the impact of new WPPs on the wind power ramp rates in a power system. To evaluate the performance of the proposed methodology, it is verified against hourly wind speed measurements from six locations in Finland and the aggregated wind power generation from Finland in 2015. Furthermore, a case study analyzing the impact of the geographical distribution of WPPs on wind power ramps is included.

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