The Identification of Online Strategy Learning Results While Students Learn from Home During the Disruption of the COVID-19 Pandemic in Indonesia

Keyword(s):  
Author(s):  
Sari Lestari Zainal Ridho ◽  
Neneng Miskiyah ◽  
Muhammad Anshari ◽  
Hadi Jauhari

Robotics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 58
Author(s):  
Yusuke Adachi ◽  
Masahide Ito ◽  
Tadashi Naruse

This paper addresses a strategy learning problem in the RoboCupSoccer Small Size League (SSL). We propose a novel method based on action sequences to cluster an opponent’s strategies online. Our proposed method is composed of the following three steps: (1) extracting typical actions from geometric data to make action sequences, (2) calculating the dissimilarity of the sequences, and (3) clustering the sequences by using the dissimilarity. This method can reduce the amount of data used in the clustering process; handling action sequences instead of geometric data as data-set makes it easier to search actions. As a result, the proposed clustering method is online feasible and also is applicable to countering an opponent’s strategy. The effectiveness of the proposed method was validated by experimental results.


2020 ◽  
pp. 102015
Author(s):  
Anna Plotnikova ◽  
Krsto Pandza ◽  
Heraldo Sales-Cavalcante
Keyword(s):  

2017 ◽  
Vol 17 (2) ◽  
pp. 258-280 ◽  
Author(s):  
Alexandra A. Siegel ◽  
Joshua A. Tucker

Abstract How successful is the Islamic State’s online strategy? To what extent does the organization achieve its goals of attracting a global audience, broadcasting its military successes, and marketing the Caliphate? Using Twitter and YouTube search data, collected throughout 2015 and early 2016, we assess how suspected ISIS accounts, sympathizers, and opponents behave across two social media platforms, offering key insights into the successes and limitations of ISIS’s information warfare strategy. Analyzing the tweet content and metadata from 16,364 suspected ISIS accounts, we find that a core network of ISIS Twitter users are producing linguistically diverse narratives, touting battlefield victories and depicting utopian life in the Caliphate. Furthermore, a dataset of over 70 million tweets, as well as analysis YouTube search data, indicates that although pro-ISIS content spreads globally and remains on message, it is far less prolific than anti-ISIS content. However, this anti-ISIS content is not necessarily anti-extremist or aligned with Western policy goals.


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